From 36a66ef955fb1516d70a03a9760c2a58781657cb Mon Sep 17 00:00:00 2001 From: Yasset Perez-Riverol Date: Sun, 14 Dec 2025 19:45:30 +0000 Subject: [PATCH 01/26] First iteration of refacotring from GenerativeProteomics to GainPro --- .gitignore | 34150 +--------------- GenerativeProteomics/__init__.py | 71 + GenerativeProteomics/correlation.py | 2 +- GenerativeProteomics/dataset.py | 16 +- .../{gaindannmodel.py => gain_dann_model.py} | 20 +- GenerativeProteomics/gaindann.py | 20 +- GenerativeProteomics/generativeproteomics.py | 52 +- ...Optimization.py => hypers_optimization.py} | 8 +- GenerativeProteomics/imputation_management.py | 8 +- GenerativeProteomics/model.py | 230 +- GenerativeProteomics/models/__init__.py | 17 + GenerativeProteomics/output.py | 6 +- GenerativeProteomics/parameters.json | 19 +- ...{paramsgaindann.py => params_gain_dann.py} | 2 +- GenerativeProteomics/train.py | 26 +- MANIFEST.in | 18 + README.md | 2 +- ...toGain.dataset.rst => GainPro.dataset.rst} | 2 +- ...n.rst => GainPro.generativeproteomics.rst} | 4 +- ...rotoGain.hypers.rst => GainPro.hypers.rst} | 2 +- ...toGain.manager.rst => GainPro.manager.rst} | 6 +- ...{ProtoGain.model.rst => GainPro.model.rst} | 4 +- ...rotoGain.output.rst => GainPro.output.rst} | 6 +- docs/source/{ProtoGain.rst => GainPro.rst} | 14 +- ...{ProtoGain.utils.rst => GainPro.utils.rst} | 2 +- docs/source/Installation.rst | 2 +- docs/source/conf.py | 2 +- docs/source/index.rst | 2 +- pyproject.toml | 137 + requirements.txt | 13 +- test.py | 16 - tests/README.md | 2 +- tests/test_imputation_management.py | 12 +- use-case/2-tests/test_generate_reference.py | 4 +- use-case/2-tests/test_hint_generation.py | 2 +- .../2-tests/test_imputation_with_reference.py | 2 +- use-case/2-tests/test_impute_no_reference.py | 2 +- utils.py | 58 - 38 files changed, 676 insertions(+), 34285 deletions(-) rename GenerativeProteomics/{gaindannmodel.py => gain_dann_model.py} (90%) rename GenerativeProteomics/{HypersOptimization.py => hypers_optimization.py} (95%) create mode 100644 GenerativeProteomics/models/__init__.py rename GenerativeProteomics/{paramsgaindann.py => params_gain_dann.py} (99%) create mode 100644 MANIFEST.in rename docs/source/{ProtoGain.dataset.rst => GainPro.dataset.rst} (97%) rename docs/source/{ProtoGain.protogain.rst => GainPro.generativeproteomics.rst} (94%) rename docs/source/{ProtoGain.hypers.rst => GainPro.hypers.rst} (97%) rename docs/source/{ProtoGain.manager.rst => GainPro.manager.rst} (90%) rename docs/source/{ProtoGain.model.rst => GainPro.model.rst} (97%) rename docs/source/{ProtoGain.output.rst => GainPro.output.rst} (95%) rename docs/source/{ProtoGain.rst => GainPro.rst} (73%) rename docs/source/{ProtoGain.utils.rst => GainPro.utils.rst} (98%) create mode 100644 pyproject.toml delete mode 100644 test.py delete mode 100644 utils.py diff --git a/.gitignore b/.gitignore index 0a20f34..7444eb3 100644 --- a/.gitignore +++ b/.gitignore @@ -1,3 +1,11 @@ +# ============================================================================= +# GenerativeProteomics .gitignore +# ============================================================================= + +# ============================================================================= +# Python +# ============================================================================= + # Byte-compiled / optimized / DLL files __pycache__/ *.py[cod] @@ -27,8 +35,6 @@ share/python-wheels/ MANIFEST # PyInstaller -# Usually these files are written by a python script from a template -# before PyInstaller builds the exe, so as to inject date/other infos into it. *.manifest *.spec @@ -55,19 +61,6 @@ cover/ *.mo *.pot -# Django stuff: -*.log -local_settings.py -db.sqlite3 -db.sqlite3-journal - -# Flask stuff: -instance/ -.webassets-cache - -# Scrapy stuff: -.scrapy - # Sphinx documentation docs/_build/ @@ -76,49 +69,12 @@ docs/_build/ target/ # Jupyter Notebook -.ipynb_checkpoints +.ipynb_checkpoints/ # IPython profile_default/ ipython_config.py -# pyenv -# For a library or package, you might want to ignore these files since the code is -# intended to run in multiple environments; otherwise, check them in: -# .python-version - -# pipenv -# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. -# However, in case of collaboration, if having platform-specific dependencies or dependencies -# having no cross-platform support, pipenv may install dependencies that don't work, or not -# install all needed dependencies. -#Pipfile.lock - -# poetry -# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control. -# This is especially recommended for binary packages to ensure reproducibility, and is more -# commonly ignored for libraries. -# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control -#poetry.lock - -# pdm -# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control. -#pdm.lock -# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it -# in version control. -# https://pdm.fming.dev/#use-with-ide -.pdm.toml - -# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm -__pypackages__/ - -# Celery stuff -celerybeat-schedule -celerybeat.pid - -# SageMath parsed files -*.sage.py - # Environments .env .venv @@ -128,16 +84,6 @@ ENV/ env.bak/ venv.bak/ -# Spyder project settings -.spyderproject -.spyproject - -# Rope project settings -.ropeproject - -# mkdocs documentation -/site - # mypy .mypy_cache/ .dmypy.json @@ -152,33913 +98,171 @@ dmypy.json # Cython debug symbols cython_debug/ -# PyCharm -# JetBrains specific template is maintained in a separate JetBrains.gitignore that can -# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore -# and can be added to the global gitignore or merged into this file. 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-credit/results/total_run_time_20_21600.csv -credit/results/total_run_time_20_24000.csv +# ============================================================================= +# IDEs and Editors +# ============================================================================= + +# PyCharm / JetBrains +.idea/ +*.iml +*.ipr +*.iws + +# VS Code +.vscode/ +*.code-workspace + +# Cursor +.cursor/ + +# Spyder +.spyderproject +.spyproject + +# Rope +.ropeproject/ + +# Vim +*.swp +*.swo +*~ + +# Emacs +*~ +\#*\# +/.emacs.desktop +/.emacs.desktop.lock +*.elc + +# ============================================================================= +# OS Generated Files +# ============================================================================= + +# macOS +.DS_Store +.AppleDouble +.LSOverride +._* +.Spotlight-V100 +.Trashes + +# Windows +Thumbs.db +ehthumbs.db +Desktop.ini +$RECYCLE.BIN/ +*.lnk + +# Linux +*~ + +# ============================================================================= +# Project-Specific: Generated Results & Outputs +# ============================================================================= + +# Results directories (generated during training/testing) +**/results/ +results/ +reports/ + +# Model checkpoints and saved models +checkpoints/ +*.pt +*.pth +*.ckpt +*.h5 +*.hdf5 +*.pkl +*.pickle + +# Profiling results +*.prof +results.prof + +# Generated CSV outputs (imputed data, metrics, etc.) +**/imputed*.csv +**/test_imputed*.csv +**/lossD*.csv +**/lossG*.csv +**/lossMSE*.csv +**/cpu*.csv +**/ram*.csv +**/ram_percentage*.csv +**/run_time*.csv +**/total_run_time*.csv +x_reconstructed.csv +x_domain.csv + +# Generated images +**/imgs/ +*.png +!docs/**/*.png + +# ============================================================================= +# Test-Generated Files +# ============================================================================= + +# Files generated by running tests (dot-prefixed metrics files) +tests/.cpu.csv +tests/.ram.csv +tests/.ram_percentage.csv +tests/.imputed.csv +tests/.test_imputed.csv +tests/.lossD.csv +tests/.lossG.csv +tests/.lossMSE_train.csv +tests/.lossMSE_test.csv + +# Test output files (generated during test runs) +tests/hint_matrix.csv +tests/reference_generated.csv + +# HuggingFace models downloaded during tests +tests/GAIN_DANN_model/ +tests/models--*/ + +# ============================================================================= +# Project-Specific: Downloaded Models & Data +# ============================================================================= + +# HuggingFace downloaded models +GAIN_DANN_model/ + +# Large datasets (keep only sample/test data in repo) +*.parquet +*.h5ad + +# ============================================================================= +# Project-Specific: Legacy/Old Directories +# ============================================================================= + +# Old project directories that may contain generated files +GAIN/ +credit/ +ProtoGain/ + +# ============================================================================= +# Databases +# ============================================================================= + +*.db +*.sqlite +*.sqlite3 + +# ============================================================================= +# Logs +# ============================================================================= + +*.log +logs/ + +# ============================================================================= +# Secrets & Credentials +# ============================================================================= + +.env +.env.* +*.pem +*.key +secrets.json +credentials.json diff --git a/GenerativeProteomics/__init__.py b/GenerativeProteomics/__init__.py index 8b13789..779f342 100644 --- a/GenerativeProteomics/__init__.py +++ b/GenerativeProteomics/__init__.py @@ -1 +1,72 @@ +""" +GenerativeProteomics (GainPro) +============================== +A PyTorch implementation of Generative Adversarial Imputation Networks (GAIN) +for imputing missing values in proteomics datasets. + +Main Classes +------------ +- Data: Handles datasets with missing values, preprocessing, masking, and scaling +- Params: Manages hyperparameters for model training +- Network: Core GAIN model architecture and training logic +- Metrics: Tracks performance metrics during training and evaluation +- ImputationManagement: Factory for managing different imputation strategies + +Example Usage +------------- +>>> from GenerativeProteomics import Data, Params, Network, Metrics +>>> import torch +>>> import pandas as pd +>>> +>>> # Load dataset +>>> dataset_df = pd.read_csv("your_dataset.csv") +>>> dataset = dataset_df.values +>>> +>>> # Configure parameters +>>> params = Params( +... input="your_dataset.csv", +... output="imputed.csv", +... num_iterations=2001, +... ) +>>> +>>> # Set up and train model +>>> data = Data(dataset=dataset, miss_rate=0.2, hint_rate=0.9) +>>> # ... define net_G, net_D ... +>>> network = Network(hypers=params, net_G=net_G, net_D=net_D, metrics=Metrics(params)) +>>> network.train(data=data, missing_header=dataset_df.columns.tolist()) +""" + +__version__ = "0.2.0" +__author__ = "QuantitativeBiology" + +# Core classes +from GenerativeProteomics.dataset import Data +from GenerativeProteomics.hypers import Params +from GenerativeProteomics.model import Network +from GenerativeProteomics.output import Metrics +from GenerativeProteomics.imputation_management import ImputationManagement + +# Utilities +from GenerativeProteomics import utils + +# GAIN-DANN components (optional, for advanced usage) +from GenerativeProteomics.gain_dann_model import GainDann +from GenerativeProteomics.params_gain_dann import ParamsGainDann + +__all__ = [ + # Core classes + "Data", + "Params", + "Network", + "Metrics", + "ImputationManagement", + # Utilities + "utils", + # GAIN-DANN + "GainDann", + "ParamsGainDann", + # Version info + "__version__", + "__author__", +] diff --git a/GenerativeProteomics/correlation.py b/GenerativeProteomics/correlation.py index 596f165..834555e 100644 --- a/GenerativeProteomics/correlation.py +++ b/GenerativeProteomics/correlation.py @@ -7,7 +7,7 @@ import os from datetime import datetime -from dann_utils import inverse_transform_output +from GenerativeProteomics.dann_utils import inverse_transform_output logging.basicConfig(level=logging.INFO) logger = logging.getLogger(__name__) diff --git a/GenerativeProteomics/dataset.py b/GenerativeProteomics/dataset.py index c93962e..f494163 100644 --- a/GenerativeProteomics/dataset.py +++ b/GenerativeProteomics/dataset.py @@ -39,21 +39,21 @@ def __init__(self, dataset, miss_rate, hint_rate, ref=None): print("Number of features:", self.dataset.shape[1]) print("Missing Rate (%):", (1.0 - self.mask.mean().item()) * 100.0, "\n") - def _create_ref(cls, miss_rate, hint_rate): + def _create_ref(self, miss_rate, hint_rate): - cls.ref_mask = cls.mask.detach().clone() - cls.ref_dataset = cls.dataset.detach().clone() - zero_idxs = torch.nonzero(cls.mask == 1) + self.ref_mask = self.mask.detach().clone() + self.ref_dataset = self.dataset.detach().clone() + zero_idxs = torch.nonzero(self.mask == 1) chance = torch.rand(len(zero_idxs)) miss = chance > miss_rate selected_idx = zero_idxs[~miss] for idx in selected_idx: - cls.ref_mask[tuple(idx)] = 0 - cls.ref_dataset[tuple(idx)] = 0 + self.ref_mask[tuple(idx)] = 0 + self.ref_dataset[tuple(idx)] = 0 - cls.ref_hint = generate_hint(cls.ref_mask, hint_rate) - cls.ref_dataset_scaled = torch.from_numpy(cls.scaler.transform(cls.ref_dataset)) + self.ref_hint = generate_hint(self.ref_mask, hint_rate) + self.ref_dataset_scaled = torch.from_numpy(self.scaler.transform(self.ref_dataset)) def generate_hint(mask, hint_rate): diff --git a/GenerativeProteomics/gaindannmodel.py b/GenerativeProteomics/gain_dann_model.py similarity index 90% rename from GenerativeProteomics/gaindannmodel.py rename to GenerativeProteomics/gain_dann_model.py index c58afb9..f5501be 100644 --- a/GenerativeProteomics/gaindannmodel.py +++ b/GenerativeProteomics/gain_dann_model.py @@ -1,23 +1,23 @@ import torch import torch.nn as nn -from encoder import Encoder -from decoder import Decoder -from domain_classifier import DomainClassifier -from grl import GradientReversalLayer -from model import Network -from hypers import Params -from output import Metrics +from GenerativeProteomics.encoder import Encoder +from GenerativeProteomics.decoder import Decoder +from GenerativeProteomics.domain_classifier import DomainClassifier +from GenerativeProteomics.grl import GradientReversalLayer +from GenerativeProteomics.model import Network +from GenerativeProteomics.hypers import Params +from GenerativeProteomics.output import Metrics #-----------------------------------# # DANN GAIN model # #-----------------------------------# -class GAIN_DANN(nn.Module): +class GainDann(nn.Module): def __init__(self, protein_names: list[str], input_dim: int, latent_dim: int, n_class: int, num_hidden_layers: int, dann_params: dict, gain_params: Params, gain_metrics: Metrics): - super(GAIN_DANN, self).__init__() + super(GainDann, self).__init__() self.protein_names = protein_names @@ -62,7 +62,7 @@ def __init__(self, protein_names: list[str], def forward(self, x: torch.tensor): """ - Forward pass of GAIN_DANN. + Forward pass of GainDann. Args: - x (torch.tensor): Dataset to be imputed diff --git a/GenerativeProteomics/gaindann.py b/GenerativeProteomics/gaindann.py index 2512a64..74811d4 100644 --- a/GenerativeProteomics/gaindann.py +++ b/GenerativeProteomics/gaindann.py @@ -9,18 +9,18 @@ import umap.umap_ as umap # model -from gaindannmodel import GAIN_DANN -from hypers import Params -from output import Metrics -from paramsgaindann import ParamsGainDann -from data_utils import Data -from train import GainDannTrain -from dann_utils import inverse_transform_output +from GenerativeProteomics.gain_dann_model import GainDann +from GenerativeProteomics.hypers import Params +from GenerativeProteomics.output import Metrics +from GenerativeProteomics.params_gain_dann import ParamsGainDann +from GenerativeProteomics.data_utils import Data +from GenerativeProteomics.train import GainDannTrain +from GenerativeProteomics.dann_utils import inverse_transform_output # post analysis # from umap_analysis import umap_analysis # from pca_analysis import pca_analysis -from correlation import correlation_measured_predicted +from GenerativeProteomics.correlation import correlation_measured_predicted import logging import argparse @@ -121,7 +121,7 @@ def select_checkpoint_interactively(): "dropout_rate": metadata["params"]["dropout_rate"]} # load model - model = GAIN_DANN(metadata["protein_names"], metadata["input_dim"], latent_dim=metadata["latent_dim"], n_class=metadata["n_class"], num_hidden_layers=metadata["params"]["num_hidden_layers"], + model = GainDann(metadata["protein_names"], metadata["input_dim"], latent_dim=metadata["latent_dim"], n_class=metadata["n_class"], num_hidden_layers=metadata["params"]["num_hidden_layers"], dann_params=dann_params, gain_params=gain_params, gain_metrics=gain_metrics) model_path = f"{checkpoint_dir}/model.pt" if not os.path.isfile(model_path): @@ -208,7 +208,7 @@ def select_checkpoint_interactively(): "dropout_rate": metadata["params"]["dropout_rate"]} # load model - model = GAIN_DANN(metadata["protein_names"], metadata["input_dim"], latent_dim=metadata["latent_dim"], n_class=metadata["n_class"], num_hidden_layers=metadata["params"]["num_hidden_layers"], + model = GainDann(metadata["protein_names"], metadata["input_dim"], latent_dim=metadata["latent_dim"], n_class=metadata["n_class"], num_hidden_layers=metadata["params"]["num_hidden_layers"], dann_params=dann_params, gain_params=gain_params, gain_metrics=gain_metrics) model_path = f"{checkpoint_dir}/model.pt" if not os.path.isfile(model_path): diff --git a/GenerativeProteomics/generativeproteomics.py b/GenerativeProteomics/generativeproteomics.py index 47bd883..4aa06e3 100644 --- a/GenerativeProteomics/generativeproteomics.py +++ b/GenerativeProteomics/generativeproteomics.py @@ -1,9 +1,16 @@ -from hypers import Params -from model import Network -from dataset import Data -from output import Metrics -from imputation_management import Imputation_Management -import utils +""" +GenerativeProteomics - Main entry point for GAIN-based imputation. + +This module provides the command-line interface for running the +Generative Adversarial Imputation Network on proteomics datasets. +""" + +from GenerativeProteomics.hypers import Params +from GenerativeProteomics.model import Network +from GenerativeProteomics.dataset import Data +from GenerativeProteomics.output import Metrics +from GenerativeProteomics.imputation_management import ImputationManagement +from GenerativeProteomics import utils import torch from torch import nn @@ -23,9 +30,13 @@ def init_arg(): - parser = argparse.ArgumentParser() - parser.add_argument("-i", help="path to missing data") - parser.add_argument("-o", default="imputed", help="name of output file") + """Parse command-line arguments for the imputation pipeline.""" + parser = argparse.ArgumentParser( + description="GenerativeProteomics (GainPro) - GAIN-based missing value imputation", + formatter_class=argparse.ArgumentDefaultsHelpFormatter, + ) + parser.add_argument("-i", "--input", dest="i", help="path to missing data file") + parser.add_argument("-o", "--output", dest="o", default="imputed", help="name of output file") parser.add_argument("--ref", help="path to a reference (complete) dataset") parser.add_argument( "--ofolder", default=os.getcwd() + "/results/", help="path to output folder" @@ -46,11 +57,14 @@ def init_arg(): "--override", type=int, default=0, help="override previous files" ) parser.add_argument("--outall", type=int, default=0, help="output all files") - parser.add_argument("--model", type = str, help = "indicates which model from HuggingFace to use") + parser.add_argument( + "--model", type=str, help="indicates which model from HuggingFace to use" + ) return parser.parse_args() -if __name__ == "__main__": +def main(): + """Main entry point for the GenerativeProteomics CLI.""" start_time = time.time() with cProfile.Profile() as profile: @@ -74,7 +88,6 @@ def init_arg(): output_all = args.outall model = args.model - if parameters_file is not None: params = Params.read_hyperparameters(parameters_file) missing_file = params.input @@ -136,12 +149,11 @@ def init_arg(): if args.model is not None: print(args.model) - imputation_management = Imputation_Management(args.model, df_missing, missing_file) + imputation_management = ImputationManagement(args.model, df_missing, missing_file) imputation_management.run_model(args.model) exit(0) else: - dim = missing.shape[1] train_size = missing.shape[0] @@ -167,7 +179,7 @@ def init_arg(): ) metrics = Metrics(params) - model = Network(hypers=params, net_G=net_G, net_D=net_D, metrics=metrics) + network = Network(hypers=params, net_G=net_G, net_D=net_D, metrics=metrics) if ref_file is not None: df_ref = pd.read_csv(ref_file) @@ -186,12 +198,12 @@ def init_arg(): exit(3.2) data = Data(missing, miss_rate, hint_rate, ref) - model.train_ref(data, missing_header) + network.train_ref(data, missing_header) else: data = Data(missing, miss_rate, hint_rate) - model.evaluate(data, missing_header) - model.train(data, missing_header) + network.evaluate(data, missing_header) + network.train(data, missing_header) run_time = [] run_time.append(time.time() - start_time) @@ -215,3 +227,7 @@ def init_arg(): results.sort_stats(pstats.SortKey.TIME) # results.print_stats() results.dump_stats("results.prof") + + +if __name__ == "__main__": + main() diff --git a/GenerativeProteomics/HypersOptimization.py b/GenerativeProteomics/hypers_optimization.py similarity index 95% rename from GenerativeProteomics/HypersOptimization.py rename to GenerativeProteomics/hypers_optimization.py index 09d756b..422212e 100644 --- a/GenerativeProteomics/HypersOptimization.py +++ b/GenerativeProteomics/hypers_optimization.py @@ -5,9 +5,9 @@ import matplotlib.pyplot as plt # from models import plot_folder -from train import GainDannTrain -from paramsgaindann import ParamsGainDann -from data_utils import Data +from GenerativeProteomics.train import GainDannTrain +from GenerativeProteomics.params_gain_dann import ParamsGainDann +from GenerativeProteomics.data_utils import Data class OptunaOptimization: @@ -98,7 +98,7 @@ def sample_params(self, trial): best_hypers.update_hypers(best_trial.params) path = f"{results_folder}/optuna_{study_name}_best_hypers.json" - best_hypers.toJSON(path) + best_hypers.to_json(path) # with open(f"{results_folder}/optuna_{study_name}_best_hypers.json", "w") as f: # json.dump(best_hypers, f, indent=2) diff --git a/GenerativeProteomics/imputation_management.py b/GenerativeProteomics/imputation_management.py index f96f5d7..a819a2c 100644 --- a/GenerativeProteomics/imputation_management.py +++ b/GenerativeProteomics/imputation_management.py @@ -1,9 +1,9 @@ -from models.base_abstract import ImputationModel -from models.gain_dann import GainDannImputationModel -from models.medium import MediumImputationModel +from GenerativeProteomics.models.base_abstract import ImputationModel +from GenerativeProteomics.models.gain_dann import GainDannImputationModel +from GenerativeProteomics.models.medium import MediumImputationModel -class Imputation_Management: +class ImputationManagement: def __init__ (self, model, df_missing, missing_file_path): self.model = model self.df = df_missing diff --git a/GenerativeProteomics/model.py b/GenerativeProteomics/model.py index 2371b53..afce056 100644 --- a/GenerativeProteomics/model.py +++ b/GenerativeProteomics/model.py @@ -1,13 +1,13 @@ -from hypers import Params -from dataset import Data -from output import Metrics +from GenerativeProteomics.hypers import Params +from GenerativeProteomics.dataset import Data +from GenerativeProteomics.output import Metrics +from GenerativeProteomics import utils import torch from torch import nn import numpy as np from tqdm import tqdm -import utils import psutil from torchinfo import summary @@ -46,7 +46,7 @@ def __init__(self, hypers: Params, net_G, net_D, metrics: Metrics): # print(summary(net_G)) - def generate_sample(cls, data, mask): + def generate_sample(self, data, mask): dim = data.shape[1] size = data.shape[0] @@ -54,29 +54,29 @@ def generate_sample(cls, data, mask): missing_data_with_noise = mask * data + (1 - mask) * Z input_G = torch.cat((missing_data_with_noise, mask), 1).float() - return cls.net_G(input_G) + return self.net_G(input_G) - def impute(cls, data: Data): - sample_G = cls.generate_sample(data.dataset_scaled, data.mask) + def impute(self, data: Data): + sample_G = self.generate_sample(data.dataset_scaled, data.mask) data_imputed_scaled = data.dataset_scaled * data.mask + sample_G * ( 1 - data.mask ) - cls.metrics.data_imputed = data.scaler.inverse_transform( + self.metrics.data_imputed = data.scaler.inverse_transform( data_imputed_scaled.detach().numpy() ) utils.create_csv( - cls.metrics.data_imputed, - f"{cls.hypers.output_folder}{cls.hypers.output}", - cls.hypers.header, + self.metrics.data_imputed, + f"{self.hypers.output_folder}{self.hypers.output}", + self.hypers.header, ) - def _evaluate_impute(cls, data: Data): - sample_G = cls.generate_sample(data.ref_dataset_scaled, data.ref_mask) + def _evaluate_impute(self, data: Data): + sample_G = self.generate_sample(data.ref_dataset_scaled, data.ref_mask) data_imputed_scaled = data.ref_dataset_scaled * data.ref_mask + sample_G * ( 1 - data.ref_mask ) - cls.metrics.ref_data_imputed = data.scaler.inverse_transform( + self.metrics.ref_data_imputed = data.scaler.inverse_transform( data_imputed_scaled.detach().numpy() ) @@ -87,7 +87,7 @@ def _evaluate_impute(cls, data: Data): ref_imputed[i] = np.array( [ data.dataset[tuple(id)], - cls.metrics.ref_data_imputed[tuple(id)], + self.metrics.ref_data_imputed[tuple(id)], id[0], id[1], ] @@ -95,22 +95,22 @@ def _evaluate_impute(cls, data: Data): utils.create_csv( ref_imputed, - f"{cls.hypers.output_folder}test_imputed", + f"{self.hypers.output_folder}test_imputed", ["original", "imputed", "sample", "feature"], ) - def _update_G(cls, batch, mask, hint, Z, loss): + def _update_G(self, batch, mask, hint, Z, loss): loss_mse = nn.MSELoss(reduction="none") ones = torch.ones_like(batch) new_X = mask * batch + (1 - mask) * Z input_G = torch.cat((new_X, mask), 1).float() - sample_G = cls.net_G(input_G) + sample_G = self.net_G(input_G) fake_X = new_X * mask + sample_G * (1 - mask) fake_input_D = torch.cat((fake_X, hint), 1).float() - fake_Y = cls.net_D(fake_input_D) + fake_Y = self.net_D(fake_input_D) # print(batch, mask, ones.reshape(fake_Y.shape), fake_Y, loss(fake_Y, ones.reshape(fake_Y.shape).float()) * (1-mask), (loss(fake_Y, ones.reshape(fake_Y.shape).float()) * (1-mask)).mean()) loss_G_entropy = ( @@ -120,37 +120,37 @@ def _update_G(cls, batch, mask, hint, Z, loss): loss_mse((sample_G * mask).float(), (batch * mask).float()) ).mean() - loss_G = loss_G_entropy + cls.hypers.alpha * loss_G_mse + loss_G = loss_G_entropy + self.hypers.alpha * loss_G_mse - cls.optimizer_G.zero_grad() + self.optimizer_G.zero_grad() loss_G.backward() - cls.optimizer_G.step() + self.optimizer_G.step() return loss_G - def _update_D(cls, batch, mask, hint, Z, loss): + def _update_D(self, batch, mask, hint, Z, loss): new_X = mask * batch + (1 - mask) * Z input_G = torch.cat((new_X, mask), 1).float() - sample_G = cls.net_G(input_G) + sample_G = self.net_G(input_G) fake_X = new_X * mask + sample_G * (1 - mask) fake_input_D = torch.cat((fake_X.detach(), hint), 1).float() - fake_Y = cls.net_D(fake_input_D) + fake_Y = self.net_D(fake_input_D) loss_D = (loss(fake_Y.float(), mask.float())).mean() - cls.optimizer_D.zero_grad() + self.optimizer_D.zero_grad() loss_D.backward() - cls.optimizer_D.step() + self.optimizer_D.step() return loss_D - def train_ref(cls, data: Data, missing_header): + def train_ref(self, data: Data, missing_header): dim = data.dataset_scaled.shape[1] train_size = data.dataset_scaled.shape[0] - if train_size < cls.hypers.batch_size: - cls.hypers.batch_size = train_size + if train_size < self.hypers.batch_size: + self.hypers.batch_size = train_size print( "Batch size is larger than the number of samples\nReducing batch size to the number of samples\n" ) @@ -159,68 +159,68 @@ def train_ref(cls, data: Data, missing_header): loss = nn.BCELoss(reduction="none") loss_mse = nn.MSELoss(reduction="none") - pbar = tqdm(range(cls.hypers.num_iterations)) + pbar = tqdm(range(self.hypers.num_iterations)) for it in pbar: - mb_idx = utils.sample_idx(train_size, cls.hypers.batch_size) + mb_idx = utils.sample_idx(train_size, self.hypers.batch_size) batch = data.dataset_scaled[mb_idx].detach().clone() mask_batch = data.mask[mb_idx].detach().clone() hint_batch = data.hint[mb_idx].detach().clone() ref_batch = data.ref_dataset_scaled[mb_idx].detach().clone() - Z = torch.rand((cls.hypers.batch_size, dim)) * 0.01 - cls.metrics.loss_D[it] = cls._update_D( + Z = torch.rand((self.hypers.batch_size, dim)) * 0.01 + self.metrics.loss_D[it] = self._update_D( batch, mask_batch, hint_batch, Z, loss ) - cls.metrics.loss_G[it] = cls._update_G( + self.metrics.loss_G[it] = self._update_G( batch, mask_batch, hint_batch, Z, loss ) - sample_G = cls.generate_sample(batch, mask_batch) + sample_G = self.generate_sample(batch, mask_batch) - cls.metrics.loss_MSE_train[it] = ( + self.metrics.loss_MSE_train[it] = ( loss_mse(mask_batch * batch, mask_batch * sample_G) ).mean() - cls.metrics.loss_MSE_test[it] = ( + self.metrics.loss_MSE_test[it] = ( loss_mse((1 - mask_batch) * ref_batch, (1 - mask_batch) * sample_G) ).mean() / (1 - mask_batch).mean() if it % 100 == 0: - s = f"{it}: loss D={cls.metrics.loss_D[it]: .3f} loss G={cls.metrics.loss_G[it]: .3f} rmse train={np.sqrt(cls.metrics.loss_MSE_train[it]): .4f} rmse test={np.sqrt(cls.metrics.loss_MSE_test[it]): .3f}" + s = f"{it}: loss D={self.metrics.loss_D[it]: .3f} loss G={self.metrics.loss_G[it]: .3f} rmse train={np.sqrt(self.metrics.loss_MSE_train[it]): .4f} rmse test={np.sqrt(self.metrics.loss_MSE_test[it]): .3f}" pbar.clear() pbar.set_description(s) - cls.metrics.cpu[it] = psutil.cpu_percent() - cls.metrics.ram[it] = psutil.virtual_memory()[3] / 1000000000 - cls.metrics.ram_percentage[it] = psutil.virtual_memory()[2] + self.metrics.cpu[it] = psutil.cpu_percent() + self.metrics.ram[it] = psutil.virtual_memory()[3] / 1000000000 + self.metrics.ram_percentage[it] = psutil.virtual_memory()[2] - cls.impute(data) + self.impute(data) - if cls.hypers.output_all == 1: + if self.hypers.output_all == 1: utils.output( - cls.metrics.data_imputed, - cls.hypers.output_folder, - cls.hypers.output, + self.metrics.data_imputed, + self.hypers.output_folder, + self.hypers.output, missing_header, - cls.metrics.loss_D, - cls.metrics.loss_G, - cls.metrics.loss_MSE_train, - cls.metrics.loss_MSE_test, - cls.metrics.cpu, - cls.metrics.ram, - cls.metrics.ram_percentage, - cls.hypers.override, + self.metrics.loss_D, + self.metrics.loss_G, + self.metrics.loss_MSE_train, + self.metrics.loss_MSE_test, + self.metrics.cpu, + self.metrics.ram, + self.metrics.ram_percentage, + self.hypers.override, ) - def evaluate(cls, data: Data, missing_header): + def evaluate(self, data: Data, missing_header): dim = data.ref_dataset_scaled.shape[1] train_size = data.ref_dataset_scaled.shape[0] - if train_size < cls.hypers.batch_size: - cls.hypers.batch_size = train_size + if train_size < self.hypers.batch_size: + self.hypers.batch_size = train_size print( "\nBatch size is larger than the number of samples\nReducing batch size to the number of samples\n" ) @@ -229,29 +229,29 @@ def evaluate(cls, data: Data, missing_header): loss = nn.BCELoss(reduction="none") loss_mse = nn.MSELoss(reduction="none") - pbar = tqdm(range(cls.hypers.num_iterations)) + pbar = tqdm(range(self.hypers.num_iterations)) for it in pbar: - mb_idx = utils.sample_idx(train_size, cls.hypers.batch_size) + mb_idx = utils.sample_idx(train_size, self.hypers.batch_size) train_batch = data.ref_dataset_scaled[mb_idx].detach().clone() train_mask_batch = data.ref_mask[mb_idx].detach().clone() train_hint_batch = data.ref_hint[mb_idx].detach().clone() test_batch = data.dataset_scaled[mb_idx].detach().clone() test_mask_batch = data.mask[mb_idx].detach().clone() - Z = torch.rand((cls.hypers.batch_size, dim)) * 0.01 - cls.metrics.loss_D_evaluate[it] = cls._update_D( + Z = torch.rand((self.hypers.batch_size, dim)) * 0.01 + self.metrics.loss_D_evaluate[it] = self._update_D( train_batch, train_mask_batch, train_hint_batch, Z, loss ) - cls.metrics.loss_G_evaluate[it] = cls._update_G( + self.metrics.loss_G_evaluate[it] = self._update_G( train_batch, train_mask_batch, train_hint_batch, Z, loss ) - sample_G = cls.generate_sample(train_batch, train_mask_batch) + sample_G = self.generate_sample(train_batch, train_mask_batch) - cls.metrics.loss_MSE_train_evaluate[it] = ( + self.metrics.loss_MSE_train_evaluate[it] = ( loss_mse(train_mask_batch * train_batch, train_mask_batch * sample_G) ).mean() - cls.metrics.loss_MSE_test[it] = ( + self.metrics.loss_MSE_test[it] = ( loss_mse( (test_mask_batch - train_mask_batch) * test_batch, (test_mask_batch - train_mask_batch) * sample_G, @@ -259,52 +259,52 @@ def evaluate(cls, data: Data, missing_header): ).mean() / (test_mask_batch - train_mask_batch).mean() if it % 100 == 0: - s = f"{it}: loss D={cls.metrics.loss_D_evaluate[it]: .3f} loss G={cls.metrics.loss_G_evaluate[it]: .3f} rmse train={np.sqrt(cls.metrics.loss_MSE_train_evaluate[it]): .4f} rmse test={np.sqrt(cls.metrics.loss_MSE_test[it]): .3f}" + s = f"{it}: loss D={self.metrics.loss_D_evaluate[it]: .3f} loss G={self.metrics.loss_G_evaluate[it]: .3f} rmse train={np.sqrt(self.metrics.loss_MSE_train_evaluate[it]): .4f} rmse test={np.sqrt(self.metrics.loss_MSE_test[it]): .3f}" pbar.clear() pbar.set_description(s) - cls.metrics.cpu_evaluate[it] = psutil.cpu_percent() - cls.metrics.ram_evaluate[it] = psutil.virtual_memory()[3] / 1000000000 - cls.metrics.ram_percentage_evaluate[it] = psutil.virtual_memory()[2] + self.metrics.cpu_evaluate[it] = psutil.cpu_percent() + self.metrics.ram_evaluate[it] = psutil.virtual_memory()[3] / 1000000000 + self.metrics.ram_percentage_evaluate[it] = psutil.virtual_memory()[2] - cls._evaluate_impute(data) + self._evaluate_impute(data) - if cls.hypers.output_all == 1: + if self.hypers.output_all == 1: utils.output( - cls.metrics.ref_data_imputed, - cls.hypers.output_folder, - cls.hypers.output, + self.metrics.ref_data_imputed, + self.hypers.output_folder, + self.hypers.output, missing_header, - cls.metrics.loss_D_evaluate, - cls.metrics.loss_G_evaluate, - cls.metrics.loss_MSE_train_evaluate, - cls.metrics.loss_MSE_test, - cls.metrics.cpu_evaluate, - cls.metrics.ram_evaluate, - cls.metrics.ram_percentage_evaluate, - cls.hypers.override, + self.metrics.loss_D_evaluate, + self.metrics.loss_G_evaluate, + self.metrics.loss_MSE_train_evaluate, + self.metrics.loss_MSE_test, + self.metrics.cpu_evaluate, + self.metrics.ram_evaluate, + self.metrics.ram_percentage_evaluate, + self.hypers.override, ) - def train(cls, data: Data, missing_header): + def train(self, data: Data, missing_header): - for name, param in cls.net_D.named_parameters(): + for name, param in self.net_D.named_parameters(): if "weight" in name: nn.init.xavier_normal_(param) # nn.init.uniform_(param) - for name, param in cls.net_G.named_parameters(): + for name, param in self.net_G.named_parameters(): if "weight" in name: nn.init.xavier_normal_(param) # nn.init.uniform_(param) - cls.optimizer_D = torch.optim.Adam(cls.net_D.parameters(), lr=cls.hypers.lr_D) - cls.optimizer_G = torch.optim.Adam(cls.net_G.parameters(), lr=cls.hypers.lr_G) + self.optimizer_D = torch.optim.Adam(self.net_D.parameters(), lr=self.hypers.lr_D) + self.optimizer_G = torch.optim.Adam(self.net_G.parameters(), lr=self.hypers.lr_G) dim = data.dataset_scaled.shape[1] train_size = data.dataset_scaled.shape[0] - if train_size < cls.hypers.batch_size: - cls.hypers.batch_size = train_size + if train_size < self.hypers.batch_size: + self.hypers.batch_size = train_size print( "\nBatch size is larger than the number of samples\nReducing batch size to the number of samples\n" ) @@ -313,52 +313,52 @@ def train(cls, data: Data, missing_header): loss = nn.BCELoss(reduction="none") loss_mse = nn.MSELoss(reduction="none") - pbar = tqdm(range(cls.hypers.num_iterations)) + pbar = tqdm(range(self.hypers.num_iterations)) for it in pbar: - mb_idx = utils.sample_idx(train_size, cls.hypers.batch_size) + mb_idx = utils.sample_idx(train_size, self.hypers.batch_size) batch = data.dataset_scaled[mb_idx].detach().clone() mask_batch = data.mask[mb_idx].detach().clone() hint_batch = data.hint[mb_idx].detach().clone() - Z = torch.rand((cls.hypers.batch_size, dim)) * 0.01 - cls.metrics.loss_D[it] = cls._update_D( + Z = torch.rand((self.hypers.batch_size, dim)) * 0.01 + self.metrics.loss_D[it] = self._update_D( batch, mask_batch, hint_batch, Z, loss ) - cls.metrics.loss_G[it] = cls._update_G( + self.metrics.loss_G[it] = self._update_G( batch, mask_batch, hint_batch, Z, loss ) - sample_G = cls.generate_sample(batch, mask_batch) + sample_G = self.generate_sample(batch, mask_batch) - cls.metrics.loss_MSE_train[it] = ( + self.metrics.loss_MSE_train[it] = ( loss_mse(mask_batch * batch, mask_batch * sample_G) ).mean() if it % 100 == 0: - s = f"{it}: loss D={cls.metrics.loss_D[it]: .3f} loss G={cls.metrics.loss_G[it]: .3f} rmse train={np.sqrt(cls.metrics.loss_MSE_train[it]): .4f}" + s = f"{it}: loss D={self.metrics.loss_D[it]: .3f} loss G={self.metrics.loss_G[it]: .3f} rmse train={np.sqrt(self.metrics.loss_MSE_train[it]): .4f}" pbar.clear() pbar.set_description(s) - cls.metrics.cpu[it] = psutil.cpu_percent() - cls.metrics.ram[it] = psutil.virtual_memory()[3] / 1000000000 - cls.metrics.ram_percentage[it] = psutil.virtual_memory()[2] + self.metrics.cpu[it] = psutil.cpu_percent() + self.metrics.ram[it] = psutil.virtual_memory()[3] / 1000000000 + self.metrics.ram_percentage[it] = psutil.virtual_memory()[2] - cls.impute(data) + self.impute(data) - if cls.hypers.output_all == 1: + if self.hypers.output_all == 1: utils.output( - cls.metrics.data_imputed, - cls.hypers.output_folder, - cls.hypers.output, + self.metrics.data_imputed, + self.hypers.output_folder, + self.hypers.output, missing_header, - cls.metrics.loss_D, - cls.metrics.loss_G, - cls.metrics.loss_MSE_train, - cls.metrics.loss_MSE_test, - cls.metrics.cpu, - cls.metrics.ram, - cls.metrics.ram_percentage, - cls.hypers.override, + self.metrics.loss_D, + self.metrics.loss_G, + self.metrics.loss_MSE_train, + self.metrics.loss_MSE_test, + self.metrics.cpu, + self.metrics.ram, + self.metrics.ram_percentage, + self.hypers.override, ) diff --git a/GenerativeProteomics/models/__init__.py b/GenerativeProteomics/models/__init__.py new file mode 100644 index 0000000..1e55c4c --- /dev/null +++ b/GenerativeProteomics/models/__init__.py @@ -0,0 +1,17 @@ +""" +Imputation model implementations. + +This module contains different imputation strategies: +- GainDannImputationModel: GAIN-DANN based imputation using HuggingFace models +- MediumImputationModel: Simple median-based imputation +""" + +from GenerativeProteomics.models.base_abstract import ImputationModel +from GenerativeProteomics.models.gain_dann import GainDannImputationModel +from GenerativeProteomics.models.medium import MediumImputationModel + +__all__ = [ + "ImputationModel", + "GainDannImputationModel", + "MediumImputationModel", +] diff --git a/GenerativeProteomics/output.py b/GenerativeProteomics/output.py index 6a2745b..0f117f3 100644 --- a/GenerativeProteomics/output.py +++ b/GenerativeProteomics/output.py @@ -1,4 +1,4 @@ -from hypers import Params +from GenerativeProteomics.hypers import Params import numpy as np import pandas as pd import os @@ -32,8 +32,8 @@ def __init__(self, hypers: Params): self.data_imputed = None self.ref_data_imputed = None - def create_output(cls, data, name: str): - hypers = cls.hypers # Accessing metrics.hypers + def create_output(self, data, name: str): + hypers = self.hypers # Accessing metrics.hypers if hypers.override == 1: df = pd.DataFrame(data) diff --git a/GenerativeProteomics/parameters.json b/GenerativeProteomics/parameters.json index 566767e..9db2698 100644 --- a/GenerativeProteomics/parameters.json +++ b/GenerativeProteomics/parameters.json @@ -1,16 +1,15 @@ { - "input": "/home/leandrosobral/LeandroSobralThesis/ProtoGain/credit/creditMissing_20.csv", - "output": "creditImputed_20", - "ref": "/home/leandrosobral/LeandroSobralThesis/ProtoGain/credit/credit.csv", - "output_folder": "/home/leandrosobral/LeandroSobralThesis/ProtoGain/credit/results/", - "num_iterations": 3000, + "input": "./breast/breastMissing_20.csv", + "output": "imputed", + "ref": "./breast/breast.csv", + "output_folder": "./results/", + "num_iterations": 2001, "batch_size": 128, "alpha": 10, - "miss_rate": 0.2, + "miss_rate": 0.1, "hint_rate": 0.9, - "train_ratio": 0.8, "lr_D": 0.001, "lr_G": 0.001, - "num_runs": 50 - -} \ No newline at end of file + "override": 1, + "output_all": 0 +} diff --git a/GenerativeProteomics/paramsgaindann.py b/GenerativeProteomics/params_gain_dann.py similarity index 99% rename from GenerativeProteomics/paramsgaindann.py rename to GenerativeProteomics/params_gain_dann.py index 16959e5..460abed 100644 --- a/GenerativeProteomics/paramsgaindann.py +++ b/GenerativeProteomics/params_gain_dann.py @@ -261,7 +261,7 @@ def to_dict(self) -> dict: } return params - def toJSON(self, path: str): + def to_json(self, path: str): with open(path, "w") as f: j = json.dump( self, diff --git a/GenerativeProteomics/train.py b/GenerativeProteomics/train.py index 4516c89..9559ca2 100644 --- a/GenerativeProteomics/train.py +++ b/GenerativeProteomics/train.py @@ -8,17 +8,17 @@ from torch.utils.data import DataLoader, TensorDataset, WeightedRandomSampler # model -from gaindannmodel import GAIN_DANN -from hypers import Params -from dataset import generate_hint -from output import Metrics - -from data_utils import Data -from paramsgaindann import ParamsGainDann -from early_stopping import EarlyStopping -from metrics import MetricsTracker -from evaluation import EvaluationTracker -from dann_utils import save_model, save_metadata +from GenerativeProteomics.gain_dann_model import GainDann +from GenerativeProteomics.hypers import Params +from GenerativeProteomics.dataset import generate_hint +from GenerativeProteomics.output import Metrics + +from GenerativeProteomics.data_utils import Data +from GenerativeProteomics.params_gain_dann import ParamsGainDann +from GenerativeProteomics.early_stopping import EarlyStopping +from GenerativeProteomics.metrics import MetricsTracker +from GenerativeProteomics.evaluation import EvaluationTracker +from GenerativeProteomics.dann_utils import save_model, save_metadata import logging @@ -55,13 +55,13 @@ def init_weights(self, m): nn.init.xavier_uniform_(m.weight) nn.init.constant_(m.bias, 0) - def initialize_model(self) -> GAIN_DANN: + def initialize_model(self) -> GainDann: input_dim = self.data.n_proteins gain_params = Params() gain_metrics = Metrics(gain_params) protein_names = self.data.protein_names - model = GAIN_DANN(protein_names, input_dim, latent_dim=input_dim, n_class=self.data.n_projects, num_hidden_layers=self.hypers["num_hidden_layers"], dann_params=self.hypers, gain_params=gain_params, gain_metrics=gain_metrics) + model = GainDann(protein_names, input_dim, latent_dim=input_dim, n_class=self.data.n_projects, num_hidden_layers=self.hypers["num_hidden_layers"], dann_params=self.hypers, gain_params=gain_params, gain_metrics=gain_metrics) model.encoder.apply(self.init_weights) model.decoder.apply(self.init_weights) model.to(self.device) diff --git a/MANIFEST.in b/MANIFEST.in new file mode 100644 index 0000000..139e5f6 --- /dev/null +++ b/MANIFEST.in @@ -0,0 +1,18 @@ +# Include documentation +include README.md +include LICENSE + +# Include package data +recursive-include GenerativeProteomics/breast *.csv *.json +include GenerativeProteomics/parameters.json + +# Include configs +recursive-include configs *.json + +# Exclude tests and development files +recursive-exclude tests * +recursive-exclude use-case * +recursive-exclude docs * +recursive-exclude .github * +exclude .gitignore +exclude .readthedocs.yaml diff --git a/README.md b/README.md index 64f19a8..d7cd53e 100644 --- a/README.md +++ b/README.md @@ -22,7 +22,7 @@ Here are the main components you'll find in this repository: 1. .github/workflows - contains the code for the automatization of the tests in the repository -2. Datasets +2. datasets - directory with datasets with missing values from PRIDE that can be used for testing 3. GenerativeProteomics: - Contains the core package source code diff --git a/docs/source/ProtoGain.dataset.rst b/docs/source/GainPro.dataset.rst similarity index 97% rename from docs/source/ProtoGain.dataset.rst rename to docs/source/GainPro.dataset.rst index 2164759..fab4c34 100644 --- a/docs/source/ProtoGain.dataset.rst +++ b/docs/source/GainPro.dataset.rst @@ -1,7 +1,7 @@ Data Class ======================== -.. automodule:: ProtoGain.dataset +.. automodule:: GenerativeProteomics.dataset :members: :undoc-members: :show-inheritance: diff --git a/docs/source/ProtoGain.protogain.rst b/docs/source/GainPro.generativeproteomics.rst similarity index 94% rename from docs/source/ProtoGain.protogain.rst rename to docs/source/GainPro.generativeproteomics.rst index b49e5a3..0f635e0 100644 --- a/docs/source/ProtoGain.protogain.rst +++ b/docs/source/GainPro.generativeproteomics.rst @@ -1,7 +1,7 @@ GenerativeProteomics Class ======================== -.. automodule:: ProtoGain.protogain +.. automodule:: GenerativeProteomics.generativeproteomics :members: :undoc-members: :show-inheritance: @@ -26,4 +26,4 @@ Methods - If a reference dataset is provided, it runs training with reference (train_ref). - Otherwise, runs evaluation (evaluate) followed by training (train). 7. Records Execution Time and stores it in run_time.csv. - 8. Performs Profiling with cProfile to measure execution performance. \ No newline at end of file + 8. Performs Profiling with cProfile to measure execution performance. diff --git a/docs/source/ProtoGain.hypers.rst b/docs/source/GainPro.hypers.rst similarity index 97% rename from docs/source/ProtoGain.hypers.rst rename to docs/source/GainPro.hypers.rst index 567bb9f..b623294 100644 --- a/docs/source/ProtoGain.hypers.rst +++ b/docs/source/GainPro.hypers.rst @@ -1,7 +1,7 @@ Params class ================ -.. automodule:: ProtoGain.hypers +.. automodule:: GenerativeProteomics.hypers :members: :undoc-members: :show-inheritance: diff --git a/docs/source/ProtoGain.manager.rst b/docs/source/GainPro.manager.rst similarity index 90% rename from docs/source/ProtoGain.manager.rst rename to docs/source/GainPro.manager.rst index ab6921d..f8bddaa 100644 --- a/docs/source/ProtoGain.manager.rst +++ b/docs/source/GainPro.manager.rst @@ -1,12 +1,12 @@ Imputation Manager Class ======================== -.. automodule:: ProtoGain.manager +.. automodule:: GenerativeProteomics.imputation_management :members: :undoc-members: :show-inheritance: -Here you will find the class `Imputation Manager` and other functions used by it +Here you will find the class `ImputationManagement` and other functions used by it during the process of managing the selection of an imputation method besides GenerativeProteomics. This class works as a wrapper, allowing the user to easily add and use different imputation methods. @@ -21,7 +21,7 @@ Methods -------- - __init__(model, df, missing): - Initializes the `Imputation_Manager` class by setting the model, dataset, + Initializes the `ImputationManagement` class by setting the model, dataset, and missing values file. - add_method(self, model, fn): diff --git a/docs/source/ProtoGain.model.rst b/docs/source/GainPro.model.rst similarity index 97% rename from docs/source/ProtoGain.model.rst rename to docs/source/GainPro.model.rst index 50190d5..8375539 100644 --- a/docs/source/ProtoGain.model.rst +++ b/docs/source/GainPro.model.rst @@ -1,7 +1,7 @@ Network Class ======================== -.. automodule:: ProtoGain.model +.. automodule:: GenerativeProteomics.model :members: :undoc-members: :show-inheritance: @@ -127,4 +127,4 @@ Methods 2. Configures optimizers for both networks. 3. Starts the training process with the imputation dataset. 4. Updates the networks iteratively using _update_G() and _update_D(). - 5. Tracks performance metrics and saves the results. \ No newline at end of file + 5. Tracks performance metrics and saves the results. diff --git a/docs/source/ProtoGain.output.rst b/docs/source/GainPro.output.rst similarity index 95% rename from docs/source/ProtoGain.output.rst rename to docs/source/GainPro.output.rst index 0956e1d..65ed803 100644 --- a/docs/source/ProtoGain.output.rst +++ b/docs/source/GainPro.output.rst @@ -1,7 +1,7 @@ Metrics Class ======================== -.. automodule:: ProtoGain.output +.. automodule:: GenerativeProteomics.output :members: :undoc-members: :show-inheritance: @@ -45,7 +45,7 @@ Methods - CPU and RAM usage metrics. 3. Sets data_imputed and ref_data_imputed to None until values are computed. -- create_output(cls, data, name: str) +- create_output(self, data, name: str) Stores model output (e.g., imputed data) in CSV files. It saves the data to the output_folder, either overwriting existing files or appending new data. @@ -59,4 +59,4 @@ Methods - Reads the existing file. - Appends new data to it. - Ensures column integrity before saving. - - Otherwise, saves data as a new CSV file. \ No newline at end of file + - Otherwise, saves data as a new CSV file. diff --git a/docs/source/ProtoGain.rst b/docs/source/GainPro.rst similarity index 73% rename from docs/source/ProtoGain.rst rename to docs/source/GainPro.rst index 8b67953..ddfadab 100644 --- a/docs/source/ProtoGain.rst +++ b/docs/source/GainPro.rst @@ -8,12 +8,12 @@ responsible for different tasks in the processing and imputation of large proteo .. toctree:: :maxdepth: 20 - ProtoGain.dataset - ProtoGain.hypers - ProtoGain.model - ProtoGain.output - ProtoGain.protogain - ProtoGain.utils - ProtoGain.manager + GainPro.dataset + GainPro.hypers + GainPro.model + GainPro.output + GainPro.generativeproteomics + GainPro.utils + GainPro.manager diff --git a/docs/source/ProtoGain.utils.rst b/docs/source/GainPro.utils.rst similarity index 98% rename from docs/source/ProtoGain.utils.rst rename to docs/source/GainPro.utils.rst index 86b63e5..9faf8d4 100644 --- a/docs/source/ProtoGain.utils.rst +++ b/docs/source/GainPro.utils.rst @@ -1,7 +1,7 @@ Utils Class ======================== -.. automodule:: ProtoGain.utils +.. automodule:: GenerativeProteomics.utils :members: :undoc-members: :show-inheritance: diff --git a/docs/source/Installation.rst b/docs/source/Installation.rst index c28e177..b54336d 100644 --- a/docs/source/Installation.rst +++ b/docs/source/Installation.rst @@ -26,7 +26,7 @@ In order to clone the repository, you should use the following command: .. code-block:: bash - git clone https://github.com/QuantitativeBiology/ProtoGain/ + git clone https://github.com/QuantitativeBiology/GainPro/ After cloning the repository, you should create a Python environment (versions 3.10 and 3.11). If you have Conda installed, you can use the following command: diff --git a/docs/source/conf.py b/docs/source/conf.py index b511e23..0d6caae 100644 --- a/docs/source/conf.py +++ b/docs/source/conf.py @@ -12,7 +12,7 @@ print("Sphynx sys.path", sys.path) -autodoc_mock_imports = ["ProtoGain"] +autodoc_mock_imports = ["GenerativeProteomics"] # -- Project information ----------------------------------------------------- # https://www.sphinx-doc.org/en/master/usage/configuration.html#project-information diff --git a/docs/source/index.rst b/docs/source/index.rst index 477279c..1e7b71a 100644 --- a/docs/source/index.rst +++ b/docs/source/index.rst @@ -21,7 +21,7 @@ GenerativeProteomics is a work that was developed to address the problem of miss Installation How to use Architecture - ProtoGain + GainPro Tests diff --git a/pyproject.toml b/pyproject.toml new file mode 100644 index 0000000..0e31546 --- /dev/null +++ b/pyproject.toml @@ -0,0 +1,137 @@ +[build-system] +requires = ["setuptools>=61.0", "wheel"] +build-backend = "setuptools.build_meta" + +[project] +name = "GenerativeProteomics" +version = "0.2.0" +description = "Generative Adversarial Imputation Networks (GAIN) for imputing missing values in proteomics datasets" +readme = "README.md" +license = {text = "BSD-3-Clause"} +authors = [ + {name = "QuantitativeBiology", email = "yperez@ebi.ac.uk"}, +] +maintainers = [ + {name = "Diogo Ferreira"}, + {name = "Emanuel Gonçalves"}, + {name = "Jorge Ribeiro"}, + {name = "Leandro Sobral"}, + {name = "Rita Gama"}, + {name = "Yasset Perez-Riverol"}, +] +keywords = [ + "proteomics", + "imputation", + "missing-data", + "deep-learning", + "GAIN", + "generative-adversarial-networks", + "bioinformatics", + "mass-spectrometry", +] +classifiers = [ + "Development Status :: 4 - Beta", + "Intended Audience :: Science/Research", + "Intended Audience :: Developers", + "License :: OSI Approved :: BSD License", + "Operating System :: OS Independent", + "Programming Language :: Python :: 3", + "Programming Language :: Python :: 3.9", + "Programming Language :: Python :: 3.10", + "Programming Language :: Python :: 3.11", + "Programming Language :: Python :: 3.12", + "Topic :: Scientific/Engineering :: Bio-Informatics", + "Topic :: Scientific/Engineering :: Artificial Intelligence", +] +requires-python = ">=3.9" +dependencies = [ + "torch>=2.0.0", + "torchinfo", + "numpy<2", + "tqdm", + "pandas", + "scikit-learn", + "optuna", + "psutil", + "anndata", + "polars", + "huggingface_hub", + "transformers", +] + +[project.optional-dependencies] +dev = [ + "pytest>=7.0", + "pytest-cov", + "black", + "isort", + "flake8", + "mypy", +] +visualization = [ + "holoviews", + "datashader", + "umap-learn", + "seaborn", + "matplotlib", +] +docs = [ + "sphinx", + "sphinx-rtd-theme", + "sphinx-autodoc-typehints", +] +all = [ + "GenerativeProteomics[dev,visualization,docs]", +] + +[project.urls] +Homepage = "https://github.com/QuantitativeBiology/GainPro" +Documentation = "https://generativeproteomics.readthedocs.io/en/latest/" +Repository = "https://github.com/QuantitativeBiology/GainPro.git" +Issues = "https://github.com/QuantitativeBiology/GainPro/issues" +Changelog = "https://github.com/QuantitativeBiology/GainPro/releases" + +[project.scripts] +gainpro = "GenerativeProteomics.generativeproteomics:main" + +[tool.setuptools] +packages = ["GenerativeProteomics"] +include-package-data = true + +[tool.setuptools.package-data] +GenerativeProteomics = [ + "breast/*.csv", + "breast/*.json", + "parameters.json", +] + +[tool.black] +line-length = 100 +target-version = ["py39", "py310", "py311", "py312"] +include = '\.pyi?$' +exclude = ''' +/( + \.git + | \.venv + | build + | dist + | \.eggs +)/ +''' + +[tool.isort] +profile = "black" +line_length = 100 +known_first_party = ["GenerativeProteomics"] + +[tool.pytest.ini_options] +testpaths = ["tests"] +python_files = ["test_*.py"] +python_functions = ["test_*"] +addopts = "-v --tb=short" + +[tool.mypy] +python_version = "3.10" +warn_return_any = true +warn_unused_configs = true +ignore_missing_imports = true diff --git a/requirements.txt b/requirements.txt index 23bfd25..ee39172 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,17 +1,22 @@ -torch +# Core dependencies for GenerativeProteomics +# For development installation, use: pip install -e ".[dev]" + +torch>=2.0.0 torchinfo -numpy +numpy<2 tqdm pandas scikit-learn optuna -argparse psutil anndata polars huggingface_hub transformers + +# Visualization (optional) holoviews datashader umap-learn -seaborn \ No newline at end of file +seaborn +matplotlib diff --git a/test.py b/test.py deleted file mode 100644 index a86b757..0000000 --- a/test.py +++ /dev/null @@ -1,16 +0,0 @@ -import pandas as pd -import numpy as np -import utils - -df = pd.read_csv( - "/home/leandrosobral/LeandroSobralThesis/ProtoGain/breast/results/lossD.csv" -) - -print(df) - - -utils.create_output( - df, - "/home/leandrosobral/LeandroSobralThesis/ProtoGain/breast/results/lossD.csv", - 1, -) diff --git a/tests/README.md b/tests/README.md index 182751f..ff6c38a 100644 --- a/tests/README.md +++ b/tests/README.md @@ -9,7 +9,7 @@ In this directory, you can find the tests for the GenerativeProteomics model. - `test_hyper`: tests if the model is correctly reading and updating the parameters used for imputation - `test_hint_generation`: test to infer the process of generating the hint matrix - `test_generate_reference`: test to infer the production of a synthetic reference dataset -- `test_imputation_management`: test to infer if the Imputation_Management class is properly working +- `test_imputation_management`: test to infer if the ImputationManagement class is properly working ## Test Goals diff --git a/tests/test_imputation_management.py b/tests/test_imputation_management.py index c42f899..769a552 100644 --- a/tests/test_imputation_management.py +++ b/tests/test_imputation_management.py @@ -8,7 +8,7 @@ sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))) sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "GenerativeProteomics"))) -from GenerativeProteomics.imputation_management import Imputation_Management +from GenerativeProteomics.imputation_management import ImputationManagement import GenerativeProteomics.utils class TestImputationManagement(unittest.TestCase): @@ -23,27 +23,27 @@ def test_correct_model(self): random.seed(self.seed) df_missing = pd.read_csv("hela_missing_dann.csv") - imputation_management = Imputation_Management("GAIN_DANN_model", df_missing, "hela_missing_dann.csv") + imputation_management = ImputationManagement("GAIN_DANN_model", df_missing, "hela_missing_dann.csv") imputation_management.run_model("GAIN_DANN_model") self.assertTrue(os.path.isdir("GAIN_DANN_model"), "The directory does not exist") def test_incorrect_model(self): """test the class with an incorrect model""" df_missing = pd.read_csv("hela_missing_dann.csv") - imputation_management = Imputation_Management("non_existing", df_missing, "hela_missing_dann.csv") + imputation_management = ImputationManagement("non_existing", df_missing, "hela_missing_dann.csv") with self.assertRaises(SystemExit): imputation_management.run_model("non_existing") def test_add_existing_model(self): """test adding an existing model""" df_missing = pd.read_csv("hela_missing_dann.csv") - imputation_management = Imputation_Management("model_1", df_missing, "hela_missing_dann.csv") + imputation_management = ImputationManagement("model_1", df_missing, "hela_missing_dann.csv") imputation_management.add_method("model_1", "model_1_function") self.assertEqual(imputation_management.dict_imputation_methods["model_1"], "model_1_function") def test_add_exhisting_model(self): """test to try adding model already known""" - imputation_management = Imputation_Management("GAIN_DANN_model", None, "hela_missing_dann.csv") + imputation_management = ImputationManagement("GAIN_DANN_model", None, "hela_missing_dann.csv") with self.assertRaises(SystemExit): imputation_management.add_method("GAIN_DANN_model", "hugging_face_gain_dann") @@ -51,7 +51,7 @@ def test_add_exhisting_model(self): def test_medium_imputation(self): """test the medium imputation method""" df_missing = pd.read_csv("breastMissing_20.csv") - imputation_management = Imputation_Management("medium_imputation", df_missing, "breastMissing_20.csv") + imputation_management = ImputationManagement("medium_imputation", df_missing, "breastMissing_20.csv") result = imputation_management.run_model("medium_imputation") file = pd.read_csv("output_medium.csv") np.testing.assert_allclose(result, file, rtol=1e-8, atol=1e-12, err_msg="There are still missing values after medium imputation") diff --git a/use-case/2-tests/test_generate_reference.py b/use-case/2-tests/test_generate_reference.py index a15a053..279c861 100644 --- a/use-case/2-tests/test_generate_reference.py +++ b/use-case/2-tests/test_generate_reference.py @@ -2,14 +2,12 @@ import os sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))) -sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "ProtoGain"))) +sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "GenerativeProteomics"))) from GenerativeProteomics import Data -#from ProtoGain.dataset import Data import numpy as np import unittest from GenerativeProteomics.utils import create_csv -#from ProtoGain.utils import create_csv import torch import pandas as pd import random diff --git a/use-case/2-tests/test_hint_generation.py b/use-case/2-tests/test_hint_generation.py index 2599128..43ffdb3 100644 --- a/use-case/2-tests/test_hint_generation.py +++ b/use-case/2-tests/test_hint_generation.py @@ -2,7 +2,7 @@ import os sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))) -sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "ProtoGain"))) +sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "GenerativeProteomics"))) from GenerativeProteomics.dataset import Data, generate_hint import numpy as np diff --git a/use-case/2-tests/test_imputation_with_reference.py b/use-case/2-tests/test_imputation_with_reference.py index 4b3fb26..74d7c1e 100644 --- a/use-case/2-tests/test_imputation_with_reference.py +++ b/use-case/2-tests/test_imputation_with_reference.py @@ -2,7 +2,7 @@ import os sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))) -sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "ProtoGain"))) +sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "GenerativeProteomics"))) from GenerativeProteomics.dataset import Data diff --git a/use-case/2-tests/test_impute_no_reference.py b/use-case/2-tests/test_impute_no_reference.py index 1908a1d..4b1efa4 100644 --- a/use-case/2-tests/test_impute_no_reference.py +++ b/use-case/2-tests/test_impute_no_reference.py @@ -2,7 +2,7 @@ import os sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))) -sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "ProtoGain"))) +sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "GenerativeProteomics"))) from GenerativeProteomics.dataset import Data from GenerativeProteomics.model import Network diff --git a/utils.py b/utils.py deleted file mode 100644 index 29fc08b..0000000 --- a/utils.py +++ /dev/null @@ -1,58 +0,0 @@ -import torch -import numpy as np -import pandas as pd -import os - - -def create_csv(data, name: str, header): - df = pd.DataFrame(data) - df.to_csv(name + ".csv", index=False, header=header) - - -def create_dist(size: int, dim: int, name: str): - - X = torch.normal(0.0, 1, (size, dim)) - A = torch.tensor([[1, 2], [-0.1, 0.5]]) - b = torch.tensor([0, 0]) - data = torch.matmul(X, A) + b - - create_csv(data, name) - - -def create_missing(data, miss_rate: float, name: str, header): - - size = data.shape[0] - dim = data.shape[1] - - mask = torch.zeros(data.shape) - - for i in range(dim): - - chance = torch.rand(size) - miss = chance > miss_rate - mask[:, i] = miss - - missing_data = np.where(mask < 1, np.nan, data) - - name = name + "_{}".format(int(miss_rate * 100)) - - create_csv(missing_data, name, header) - - -def create_output(data, path: str, override: bool): - - if override == 1: - print("0") - df = pd.DataFrame(data) - df.to_csv(path, index=False) - - else: - if os.path.exists(path): - df = pd.read_csv(path) - new_df = pd.DataFrame(data) - df = pd.concat([df, new_df], axis=1, join="inner") - df.columns = range(len(df.columns)) - df.to_csv(path, index=False) - else: - df = pd.DataFrame(data) - df.to_csv(path, index=False) From 8416da9af99ca9407fe4db7e592e4ebcbc30328c Mon Sep 17 00:00:00 2001 From: Yasset Perez-Riverol Date: Sun, 14 Dec 2025 19:52:58 +0000 Subject: [PATCH 02/26] major updates inside the package --- .../breast/breast.csv | 0 .../breast/breastMissing_20.csv | 0 .../breast/parameters.json | 9 ++++---- .../breast/parameters_noref.json | 9 +++----- GenerativeProteomics/multiple_runs.sh | 8 ------- MANIFEST.in | 8 ++++--- README.md | 6 ++--- .../params_gain.json | 4 ++-- docs/source/How to use.rst | 2 +- pyproject.toml | 6 +---- scripts/README.md | 22 +++++++++++++++++++ scripts/multiple_runs.sh | 16 ++++++++++++++ 12 files changed, 57 insertions(+), 33 deletions(-) rename {GenerativeProteomics => Datasets}/breast/breast.csv (100%) rename {GenerativeProteomics => Datasets}/breast/breastMissing_20.csv (100%) rename {GenerativeProteomics => Datasets}/breast/parameters.json (63%) rename {GenerativeProteomics => Datasets}/breast/parameters_noref.json (62%) delete mode 100644 GenerativeProteomics/multiple_runs.sh rename GenerativeProteomics/parameters.json => configs/params_gain.json (72%) create mode 100644 scripts/README.md create mode 100644 scripts/multiple_runs.sh diff --git a/GenerativeProteomics/breast/breast.csv b/Datasets/breast/breast.csv similarity index 100% rename from GenerativeProteomics/breast/breast.csv rename to Datasets/breast/breast.csv diff --git a/GenerativeProteomics/breast/breastMissing_20.csv b/Datasets/breast/breastMissing_20.csv similarity index 100% rename from GenerativeProteomics/breast/breastMissing_20.csv rename to Datasets/breast/breastMissing_20.csv diff --git a/GenerativeProteomics/breast/parameters.json b/Datasets/breast/parameters.json similarity index 63% rename from GenerativeProteomics/breast/parameters.json rename to Datasets/breast/parameters.json index f9ef5a7..51c21ae 100644 --- a/GenerativeProteomics/breast/parameters.json +++ b/Datasets/breast/parameters.json @@ -1,8 +1,8 @@ { - "input": "./breast/breastMissing_20.csv", + "input": "./datasets/breast/breastMissing_20.csv", "output": "breastImputed_20", - "ref": "./breast/breast.csv", - "output_folder": "./breast/results/", + "ref": "./datasets/breast/breast.csv", + "output_folder": "./results/", "num_iterations": 2001, "batch_size": 128, "alpha": 10, @@ -12,5 +12,4 @@ "lr_G": 0.001, "override": 1, "output_all": 1 - -} \ No newline at end of file +} diff --git a/GenerativeProteomics/breast/parameters_noref.json b/Datasets/breast/parameters_noref.json similarity index 62% rename from GenerativeProteomics/breast/parameters_noref.json rename to Datasets/breast/parameters_noref.json index 58d7555..9839571 100644 --- a/GenerativeProteomics/breast/parameters_noref.json +++ b/Datasets/breast/parameters_noref.json @@ -1,17 +1,14 @@ { - "input": "./breast/breastMissing_20.csv", + "input": "./datasets/breast/breastMissing_20.csv", "output": "breastImputed_20", "ref": null, - "output_folder": "./breast/results/", + "output_folder": "./results/", "num_iterations": 2000, "batch_size": 128, "alpha": 10, "miss_rate": 0.2, "hint_rate": 0.9, - "train_ratio": 0.8, "lr_D": 0.001, "lr_G": 0.001, - "num_runs": 50, "override": 1 - -} \ No newline at end of file +} diff --git a/GenerativeProteomics/multiple_runs.sh b/GenerativeProteomics/multiple_runs.sh deleted file mode 100644 index 7ac9216..0000000 --- a/GenerativeProteomics/multiple_runs.sh +++ /dev/null @@ -1,8 +0,0 @@ -#!/bin/bash - -for run in {1..50} -do - echo "Running run = $run" - python3 protogain.py --parameters ./Yasset/parameters.json - -done \ No newline at end of file diff --git a/MANIFEST.in b/MANIFEST.in index 139e5f6..80b63e3 100644 --- a/MANIFEST.in +++ b/MANIFEST.in @@ -2,9 +2,11 @@ include README.md include LICENSE -# Include package data -recursive-include GenerativeProteomics/breast *.csv *.json -include GenerativeProteomics/parameters.json +# Include configs +recursive-include configs *.json + +# Include datasets +recursive-include datasets *.csv *.tsv *.json # Include configs recursive-include configs *.json diff --git a/README.md b/README.md index d7cd53e..d38e1c5 100644 --- a/README.md +++ b/README.md @@ -121,7 +121,7 @@ Running in this manner will result in two separate training phases. 2) Imputation run: Then a proper training phase takes place using the entire dataset. An `imputed.csv` file will be created containing the imputed dataset. -However, there are a few arguments which you may want to change. You can do this using a parameters.json file (you may find an example in `GenerativeProteomics/breast/parameters.json`) or you can choose them directly in the command line. +However, there are a few arguments which you may want to change. You can do this using a parameters.json file (you may find an example in `datasets/breast/parameters.json`) or you can choose them directly in the command line. Run with a parameters.json file: `python generativeproteomics.py --parameters /path/to/parameters.json`
Run with command line arguments: `python generativeproteomics.py -i /path/to/file_to_impute.csv -o imputed_name --ofolder ./results/ --it 2001` @@ -157,8 +157,8 @@ In this repository you may find a folder named `breast`, inside it you have a br `breastMissing_20.csv`: the same dataset but with 20% of its values taken out -To simply impute `breastMissing_20.csv` run: `python generativeproteomics.py -i ./breast/breastMissing_20.csv`
-If you want to compare the imputation with the original dataset run: `python generativeproteomics.py -i ./breast/breastMissing_20.csv --ref ./breast/breast.csv` or `python generativeproteomics.py --parameters ./breast/parameters.json` +To simply impute `breastMissing_20.csv` run: `python generativeproteomics.py -i ./datasets/breast/breastMissing_20.csv`
+If you want to compare the imputation with the original dataset run: `python generativeproteomics.py -i ./datasets/breast/breastMissing_20.csv --ref ./datasets/breast/breast.csv` or `python generativeproteomics.py --parameters ./datasets/breast/parameters.json` If you want to go deep in the analysis of every metric you either set `--outall` to `1` or you run the code in an IPython console, this way you can access every variable you want in the `metrics` object, e.g. `metrics.loss_D`. diff --git a/GenerativeProteomics/parameters.json b/configs/params_gain.json similarity index 72% rename from GenerativeProteomics/parameters.json rename to configs/params_gain.json index 9db2698..466b572 100644 --- a/GenerativeProteomics/parameters.json +++ b/configs/params_gain.json @@ -1,7 +1,7 @@ { - "input": "./breast/breastMissing_20.csv", + "input": "./datasets/breast/breastMissing_20.csv", "output": "imputed", - "ref": "./breast/breast.csv", + "ref": "./datasets/breast/breast.csv", "output_folder": "./results/", "num_iterations": 2001, "batch_size": 128, diff --git a/docs/source/How to use.rst b/docs/source/How to use.rst index 2261a58..75ee02b 100644 --- a/docs/source/How to use.rst +++ b/docs/source/How to use.rst @@ -19,7 +19,7 @@ By running it in this manner, it will result in two separate training phases. Afterwards, a proper training phase takes place using the entire dataset. An **imputed.csv** file will be created containing the imputed dataset. However, there might be a few arguments which you may want to change. You can do this using a **parameters.json** file -(you may find an example in ``GenerativeProteomics/breast/parameters.json``) or you can choose them directly in the command line. +(you may find an example in ``datasets/breast/parameters.json``) or you can choose them directly in the command line. Run with a parameters.json file: diff --git a/pyproject.toml b/pyproject.toml index 0e31546..a1a02cf 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -99,11 +99,7 @@ packages = ["GenerativeProteomics"] include-package-data = true [tool.setuptools.package-data] -GenerativeProteomics = [ - "breast/*.csv", - "breast/*.json", - "parameters.json", -] +GenerativeProteomics = [] [tool.black] line-length = 100 diff --git a/scripts/README.md b/scripts/README.md new file mode 100644 index 0000000..01ca112 --- /dev/null +++ b/scripts/README.md @@ -0,0 +1,22 @@ +# Scripts + +This folder contains utility scripts for running and managing GainPro experiments. + +## Available Scripts + +### `multiple_runs.sh` + +Runs the imputation model multiple times for statistical analysis or hyperparameter tuning. + +**Usage:** +```bash +# Default: 50 runs with breast dataset parameters +./scripts/multiple_runs.sh + +# Custom parameters file and number of runs +./scripts/multiple_runs.sh ./path/to/parameters.json 100 +``` + +**Arguments:** +1. `parameters_file` (optional): Path to the JSON parameters file. Default: `./datasets/breast/parameters.json` +2. `num_runs` (optional): Number of runs to execute. Default: `50` diff --git a/scripts/multiple_runs.sh b/scripts/multiple_runs.sh new file mode 100644 index 0000000..f6c9b9b --- /dev/null +++ b/scripts/multiple_runs.sh @@ -0,0 +1,16 @@ +#!/bin/bash +# Script to run multiple imputation training runs +# Usage: ./multiple_runs.sh [parameters_file] [num_runs] + +PARAMS_FILE=${1:-"./datasets/breast/parameters.json"} +NUM_RUNS=${2:-50} + +echo "Running $NUM_RUNS imputation runs with parameters: $PARAMS_FILE" + +for run in $(seq 1 $NUM_RUNS) +do + echo "Running run = $run / $NUM_RUNS" + python -m GenerativeProteomics.generativeproteomics --parameters "$PARAMS_FILE" +done + +echo "Completed all $NUM_RUNS runs" From db43b53780cf671900001552e1edfd4289fdeaa5 Mon Sep 17 00:00:00 2001 From: Yasset Perez-Riverol Date: Sun, 14 Dec 2025 20:49:00 +0000 Subject: [PATCH 03/26] Update GenerativeProteomics/gaindann.py Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> --- GenerativeProteomics/gaindann.py | 1 - 1 file changed, 1 deletion(-) diff --git a/GenerativeProteomics/gaindann.py b/GenerativeProteomics/gaindann.py index 74811d4..afd2ff9 100644 --- a/GenerativeProteomics/gaindann.py +++ b/GenerativeProteomics/gaindann.py @@ -15,7 +15,6 @@ from GenerativeProteomics.params_gain_dann import ParamsGainDann from GenerativeProteomics.data_utils import Data from GenerativeProteomics.train import GainDannTrain -from GenerativeProteomics.dann_utils import inverse_transform_output # post analysis # from umap_analysis import umap_analysis From 3e54455236d2f469fdd75539fd384b9f40dcc09d Mon Sep 17 00:00:00 2001 From: Yasset Perez-Riverol Date: Sun, 14 Dec 2025 20:49:23 +0000 Subject: [PATCH 04/26] Update GenerativeProteomics/train.py Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> --- GenerativeProteomics/train.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/GenerativeProteomics/train.py b/GenerativeProteomics/train.py index 9559ca2..f004849 100644 --- a/GenerativeProteomics/train.py +++ b/GenerativeProteomics/train.py @@ -18,7 +18,7 @@ from GenerativeProteomics.early_stopping import EarlyStopping from GenerativeProteomics.metrics import MetricsTracker from GenerativeProteomics.evaluation import EvaluationTracker -from GenerativeProteomics.dann_utils import save_model, save_metadata +from GenerativeProteomics.dann_utils import save_model import logging From 4dd03e3b0aea6726fd393383bb2db7c057061610 Mon Sep 17 00:00:00 2001 From: Yasset Perez-Riverol Date: Sun, 14 Dec 2025 20:49:32 +0000 Subject: [PATCH 05/26] Update GenerativeProteomics/gaindann.py Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> --- GenerativeProteomics/gaindann.py | 1 - 1 file changed, 1 deletion(-) diff --git a/GenerativeProteomics/gaindann.py b/GenerativeProteomics/gaindann.py index afd2ff9..f45b3d1 100644 --- a/GenerativeProteomics/gaindann.py +++ b/GenerativeProteomics/gaindann.py @@ -19,7 +19,6 @@ # post analysis # from umap_analysis import umap_analysis # from pca_analysis import pca_analysis -from GenerativeProteomics.correlation import correlation_measured_predicted import logging import argparse From 98ce525586131cbd8df2d249ea5484a1b28782f7 Mon Sep 17 00:00:00 2001 From: Yasset Perez-Riverol Date: Sun, 14 Dec 2025 20:49:42 +0000 Subject: [PATCH 06/26] Update GenerativeProteomics/imputation_management.py Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> --- GenerativeProteomics/imputation_management.py | 1 - 1 file changed, 1 deletion(-) diff --git a/GenerativeProteomics/imputation_management.py b/GenerativeProteomics/imputation_management.py index a819a2c..64ea665 100644 --- a/GenerativeProteomics/imputation_management.py +++ b/GenerativeProteomics/imputation_management.py @@ -1,4 +1,3 @@ -from GenerativeProteomics.models.base_abstract import ImputationModel from GenerativeProteomics.models.gain_dann import GainDannImputationModel from GenerativeProteomics.models.medium import MediumImputationModel From 9f9e466eba2e68d61ac125027e3b55e82ec443ba Mon Sep 17 00:00:00 2001 From: Yasset Perez-Riverol Date: Sun, 14 Dec 2025 20:58:31 +0000 Subject: [PATCH 07/26] notebooks organized --- README.md | 12 +- notebooks/plots.ipynb | 987 ++++++++++++++++++++++++++++++++++++++++++ 2 files changed, 997 insertions(+), 2 deletions(-) create mode 100644 notebooks/plots.ipynb diff --git a/README.md b/README.md index d38e1c5..eb95cc6 100644 --- a/README.md +++ b/README.md @@ -9,12 +9,13 @@ In this repository you may find a PyTorch implementation of Generative Adversari ## Table of Contents -- [Repository Strucure](#repository-structure) +- [Repository Structure](#repository-structure) - [Installation](#installation) - [Basic Usage](#basic-usage) - [GitHub](#github) - [Demo](#demo) -- [References](#reference) +- [DANN & GAIN Hybrid](#dann--gain-hybrid) +- [References](#references) ## Repository Structure @@ -164,6 +165,13 @@ If you want to compare the imputation with the original dataset run: `python gen If you want to go deep in the analysis of every metric you either set `--outall` to `1` or you run the code in an IPython console, this way you can access every variable you want in the `metrics` object, e.g. `metrics.loss_D`. +## DANN & GAIN Hybrid + +The repository also includes a hybrid model combining Domain Adversarial Neural Networks (DANN) with GAIN for domain-adaptive imputation. + +To prepare the HeLa dataset for the **DANN & GAIN** hybrid model, run the `hela_dann.ipynb` notebook first and alter the directory of the HeLa dataset in the third cell of the notebook. + + ## References [1] J. Yoon, J. Jordon & M. van der Schaar (2018). GAIN: Missing Data Imputation using Generative Adversarial Nets
diff --git a/notebooks/plots.ipynb b/notebooks/plots.ipynb new file mode 100644 index 0000000..9556517 --- /dev/null +++ b/notebooks/plots.ipynb @@ -0,0 +1,987 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + " {'input': '/home/leandrosobral/LeandroSobralThesis/ProtoGain/breast/breastMissing_20.csv', 'output': 'breastImputed_20', 'ref': '/home/leandrosobral/LeandroSobralThesis/ProtoGain/breast/breast.csv', 'output_folder': '/home/leandrosobral/LeandroSobralThesis/ProtoGain/breast/results/', 'num_iterations': 2001, 'batch_size': 128, 'alpha': 10, 'miss_rate': 0.1, 'hint_rate': 0.9, 'lr_D': 0.001, 'lr_G': 0.001, 'override': 1, 'output_all': 1}\n" + ] + } + ], + "source": [ + "from hypers import Params\n", + "\n", + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "from scipy.stats import ttest_ind\n", + "\n", + "dataset = \"breast\"\n", + "params = Params.read_hyperparameters(\n", + " f\"/home/leandrosobral/LeandroSobralThesis/ProtoGain/{dataset}/parameters.json\"\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [], + "source": [ + "# Load the CSV files for Breast\n", + "\n", + "dataset = \"breast\"\n", + "folder = \"~/LeandroSobralThesis/ProtoGain/\"\n", + "\n", + "loss_D = {}\n", + "loss_G = {}\n", + "loss_MSE_train = {}\n", + "loss_MSE_test = {}\n", + "cpu = {}\n", + "ram_percentage = {}\n", + "ram = {}\n", + "\n", + "MSE_final = {}\n", + "\n", + "run_time = {}\n", + "\n", + "loss_D = pd.read_csv(params.output_folder + \"lossD.csv\").values.T\n", + "loss_G = pd.read_csv(params.output_folder + \"lossG.csv\").values.T\n", + "\n", + "loss_MSE_train = pd.read_csv(params.output_folder + \"lossMSE_train.csv\").values.T\n", + "loss_MSE_test = pd.read_csv(params.output_folder + \"lossMSE_test.csv\").values.T\n", + "\n", + "MSE_final = loss_MSE_test[:, -1]\n", + "\n", + "# cpu = pd.read_csv(params.output_folder + \"cpu.csv\").values.T\n", + "# ram_percentage = pd.read_csv(\n", + "# params.output_folder + \"ram_percentage.csv\"\n", + "# ).values.flatten()\n", + "# ram = pd.read_csv(params.output_folder + \"ram.csv\").values.T\n", + "\n", + "\n", + "run_time = pd.read_csv(params.output_folder + \"run_time.csv\").values.flatten()" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0.0037490644029438 [38.5696249 33.42994547]\n" + ] + } + ], + "source": [ + "# Load the CSV files for Spam\n", + "\n", + "dataset = \"spam\"\n", + "folder = \"~/LeandroSobralThesis/ProtoGain/\" + dataset + \"/\"\n", + "\n", + "loss_D = {}\n", + "loss_G = {}\n", + "loss_MSE_train = {}\n", + "loss_MSE_test = {}\n", + "cpu = {}\n", + "ram_percentage = {}\n", + "ram = {}\n", + "\n", + "MSE_final = {}\n", + "\n", + "run_time = {}\n", + "\n", + "loss_D = pd.read_csv(folder + f\"results/lossD.csv\").values.flatten()\n", + "loss_G = pd.read_csv(folder + f\"results/lossG.csv\").values.flatten()\n", + "\n", + "loss_MSE_train = pd.read_csv(folder + f\"results/lossMSE_train.csv\").values.flatten()\n", + "loss_MSE_test = pd.read_csv(folder + f\"results/lossMSE_test.csv\").values.flatten()\n", + "\n", + "cpu = pd.read_csv(folder + f\"results/cpu.csv\").values.flatten()\n", + "ram_percentage = pd.read_csv(folder + f\"results/ram_percentage.csv\").values.flatten()\n", + "ram = pd.read_csv(folder + f\"results/ram.csv\").values.flatten()\n", + "MSE_final = loss_MSE_test[-1]\n", + "\n", + "run_time = pd.read_csv(folder + f\"results/run_time.csv\").values.flatten()\n", + "\n", + "print(MSE_final, run_time)" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[0.02183125 0.02112623 0.02016055 ... 0.01808863 0.01929819 0.02000422] [[1.20936659 1.12057044 1.12004996 ... 0.25733846 0.28484619 0.26737295]\n", + " [1.52351968 1.46751945 1.45301188 ... 0.25842794 0.24529088 0.26182438]\n", + " [1.20822835 1.14543456 1.16969142 ... 0.25671357 0.2539771 0.23803761]\n", + " ...\n", + " [1.36142477 1.33428932 1.31567314 ... 0.24964616 0.26234183 0.25739478]\n", + " [1.43475016 1.44056278 1.38704627 ... 0.27495386 0.26098384 0.25528386]\n", + " [1.63076071 1.59219757 1.54155536 ... 0.25295851 0.22227823 0.24195301]]\n" + ] + } + ], + "source": [ + "# Load the CSV files for Credit\n", + "\n", + "folder = \"~/LeandroSobralThesis/ProtoGain/\" + dataset + \"/\"\n", + "\n", + "loss_D = {}\n", + "loss_G = {}\n", + "loss_MSE_train = {}\n", + "loss_MSE_test = {}\n", + "cpu = {}\n", + "ram_percentage = {}\n", + "ram = {}\n", + "\n", + "MSE_final = {}\n", + "\n", + "run_time = {}\n", + "\n", + "loss_D = pd.read_csv(params.output_folder + \"lossD.csv\").values.T\n", + "loss_G = pd.read_csv(params.output_folder + \"lossG.csv\").values.T\n", + "\n", + "loss_MSE_train = pd.read_csv(params.output_folder + \"lossMSE_train.csv\").values.T\n", + "loss_MSE_test = pd.read_csv(params.output_folder + \"lossMSE_test.csv\").values.T\n", + "\n", + "MSE_final = loss_MSE_test[:, -1]\n", + "\n", + "cpu = pd.read_csv(params.output_folder + \"cpu.csv\").values.T\n", + "ram_percentage = pd.read_csv(\n", + " params.output_folder + \"ram_percentage.csv\"\n", + ").values.flatten()\n", + "ram = pd.read_csv(params.output_folder + \"ram.csv\").values.T\n", + "\n", + "\n", + "run_time = pd.read_csv(params.output_folder + \"run_time.csv\").values.flatten()\n", + "\n", + "print(loss_D.std(axis=0), loss_G)" + ] + }, + { + "cell_type": "code", + "execution_count": 66, + "metadata": {}, + "outputs": [], + "source": [ + "# Load the CSV files for Yasset\n", + "\n", + "dataset = \"Yasset\"\n", + "folder = \"~/LeandroSobralThesis/ProtoGain/\"\n", + "\n", + "loss_D = pd.read_csv(params.output_folder + \"lossD.csv\").values.T\n", + "loss_G = pd.read_csv(params.output_folder + \"lossG.csv\").values.T\n", + "\n", + "loss_D_evaluate = pd.read_csv(params.output_folder + \"lossD_evaluate.csv\").values.T\n", + "loss_G_evaluate = pd.read_csv(params.output_folder + \"lossG_evaluate.csv\").values.T\n", + "\n", + "loss_MSE_train = pd.read_csv(params.output_folder + \"lossMSE_train.csv\").values.T\n", + "loss_MSE_train_evaluate = pd.read_csv(\n", + " params.output_folder + \"lossMSE_train_evaluate.csv\"\n", + ").values.T\n", + "loss_MSE_test = pd.read_csv(params.output_folder + \"lossMSE_test.csv\").values.T\n", + "\n", + "MSE_final = loss_MSE_test[:, -1]\n", + "\n", + "# cpu = pd.read_csv(params.output_folder + \"cpu.csv\").values.T\n", + "# ram_percentage = pd.read_csv(\n", + "# params.output_folder + \"ram_percentage.csv\"\n", + "# ).values.flatten()\n", + "# ram = pd.read_csv(params.output_folder + \"ram.csv\").values.T\n", + "\n", + "\n", + "run_time = pd.read_csv(params.output_folder + \"run_time.csv\").values.flatten()" + ] + }, + { + "cell_type": "code", + "execution_count": 63, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Plot the D and G losses (Multiple Runs)\n", + "\n", + "xmax = params.num_iterations\n", + "\n", + "fig, axs = plt.subplots()\n", + "\n", + "\n", + "axs.set_xlabel(\"Iteration\")\n", + "axs.set_ylabel(\"Loss\")\n", + "axs.set_xlim(0, xmax)\n", + "axs.set_title(f\"Losses ProtoGain\")\n", + "\n", + "\n", + "axs.fill_between(\n", + " np.arange(1, len(loss_D[0]) + 1, 1),\n", + " loss_D.mean(axis=0) + loss_D.std(axis=0),\n", + " loss_D.mean(axis=0) - loss_D.std(axis=0),\n", + " alpha=0.4,\n", + ")\n", + "axs.plot(loss_D.mean(axis=0), label=\"D loss\")\n", + "\n", + "axs.fill_between(\n", + " np.arange(1, len(loss_G[0]) + 1, 1),\n", + " loss_G.mean(axis=0) + loss_G.std(axis=0),\n", + " loss_G.mean(axis=0) - loss_G.std(axis=0),\n", + " alpha=0.4,\n", + ")\n", + "axs.plot(loss_G.mean(axis=0), label=\"G loss\")\n", + "axs.xaxis.grid(True, which=\"major\")\n", + "axs.yaxis.grid(True, which=\"major\")\n", + "\n", + "\n", + "fig.legend(loc=\"upper right\", bbox_to_anchor=(0.9, 0.85))\n", + "\n", + "# Adjust the spacing between subplots\n", + "plt.subplots_adjust(wspace=0.05, hspace=0.2)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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w3nvvISUlBT179sTEiRNhMBjw9ddfo6ysDB999JEjbcuWLdGnTx906NABVatWxf79+7Fq1SpMmjQJAHD27FncddddePDBB9GyZUsYDAb8/vvvyMrKckxvj4mJwVdffYXHH38ct99+Ox566CHUqFEDqampWLt2LXr06IEvvvhCVllCzJkzB4MGDUK3bt3w5JNPOqahx8bGYvr06R4dx+3bt7spbgDjIGv3xQKYqe1TpkzBlClTULVqVTdr2ZAhQzB37lzcfffdeOSRR3D9+nUsWLAAjRs3xtGjR0VlGDBgAOrVq4cnn3wSr7zyCvR6PZYsWeI4jna6d++OKlWqYMyYMXj++edBURR++OEH3iGYDh06YOXKlZg8eTI6deqEqKgoDBs2jLd+bx5fLXn99dfx888/Y9CgQXj++edRtWpVLFu2DJcuXcLq1auh0zHvxY0aNUJcXBwWLlyI6OhoREZGokuXLmjQoAE+/PBDjBs3DnfccQcefvhhxzT/pKQkvPTSS466evXqhS+++AL/+9//0KRJE0ckbZPJhLNnz+Knn35CSEiIY1i5efPmaNSoEaZMmYJr164hJiYGq1evJv5DhMDEfxPoCATvYZ/6LfSXlpZG0zRNHzx4kB44cCAdFRVFR0RE0H379qV37tzpUtZ7771Hd+7cmY6Li6PDw8Pp5s2b0++//z5tMplomqbpGzdu0M899xzdvHlzOjIyko6NjaW7dOlC//LLL25ybd26lR44cCAdGxtLh4WF0Y0aNaLHjh1L79+/X3FZfGzatInu0aMHHR4eTsfExNDDhg2jT5486SYDNJrm/84777jl6dGjBw2Afuqpp3jLXLx4Md2kSRM6NDSUbt68Of3dd9/xTunmTvOnaZo+cOAA3aVLFzokJISuV68ePXfuXN5p/v/99x/dtWtXOjw8nK5Vqxb96quv0hs2bKAB0Fu3bnWkKywspB955BE6Li6OBuCY8s83zZ+m5R1fe1uys7NdtvPJyYd9mr8U9evXFww/ceHCBfqBBx6g4+Li6LCwMLpz587033//7ZZuzZo1dMuWLWmDweDW3pUrV9Lt27enQ0ND6apVq9KPPvooffXqVd76Dh06RI8ePZquV68eHRISQkdGRtJt2rShX375ZZcp+TRN0ydPnqT79etHR0VF0dWrV6fHjx/vmKrPrl9omv9zzz3Heyy41wqB4CkUTRPPNgKBQCAQCAQ2xAeJQCAQCAQCgQNRkAgEAoFAIBA4EAWJQCAQCAQCgQNRkAgEAoFAIBA4EAWJQCAQCAQCgQNRkAgEAoFAIBA4BF2gSJvNhvT0dERHR2u6OCaBQCAQCATvQdM0CgoKUKtWLUfAU28SdApSenq6yxpbBAKBQCAQKg5paWmoU6eO1+sJOgUpOjoaALNwZdWqVf0sje8wm83YuHEjBgwYAKPR6G9xfAZpN2l3MEDaTdodDOTk5KBBgwaOftzbBJ2CZB9Wi46OdixGGgyYzWZEREQgJiYmqG4o0m7S7mCAtJu0OxiwL/TtK/cY4qRNIBAIBAKBwIEoSAQCgUAgEAgciIJEIBAIBAKBwIEoSAQCgUAgEAgciIJEIBAIBAKBwIEoSAQCgUAgEAgciIJEIBAIBAKBwIEoSAQCgUAgEAgciIJEIBAIBAKBwIEoSAQCgUAgEAgciIJEIBAIBAKBwIEoSAQCgUAgEAgciIJEIBAIBN9hKva3BASCLIiCRCAQCATfcO0AMCsRSH7F35IQCJIErYJ0NY+8xRAIBIJP2TqL+dz7jX/lIBBkELQK0rnMIn+LQCAQCEEG5W8BCATZBK2CdKvM7G8RCAQCgUAgBCgGfwvgLwpLLf4WgUAgEAgVCJvNBpPJ5G8xYDabYTAYUFpaCqvV6m9xNCUkJAQ6XWDYboJWQSooIQoSgUAg+BSq4g6xmUwmXLp0CTabzd+igKZp1KxZE2lpaaAq8DHlQ6fToUGDBggJCfG3KMGrIOWXEQWJQCAQCNLQNI2MjAzo9XrUrVvX7xYOm82GwsJCREVF+V0WLbHZbEhPT0dGRgbq1avnd+UvaBWkghLig0QgEAi+pWJaOywWC4qLi1GrVi1ERET4WxzHUF9YWFjFV5DMJUBJLhAVD+gMqFGjBtLT02GxWGA0Gv0qWtAqSMSCRCAQCAQ52P18AmHYp9KRfZr5tJmBuPqOY2y1Wv2uIFVw1VM9xEmbQCAQfEwF95fx95BPpcZUAiCwjnHQKkj5pWSIjUAgEAgEAj9BqyAVEAsSgUAg+JjAsQ4QxBk7dixGjBjBv9NmBYpvArbK3Y8GrYKUTxQkAoFAIFRixo4dC4qiQFEUjEYjEhIS0L9/fyxZssSzcAW5V4C8VCDnknbCBiABoSAtWLAASUlJCAsLQ5cuXbB3717BtH369HGccPbfkCFDFNVZarbBZPF/PAsCgUAIGnzpX3J2I7B+KmANbneKu+++GxkZGbh8+TLWrVuHvn374oUXXsDQoUNhsag0FJTdYj5NhdoJGoDGRb8rSCtXrsTkyZPxzjvv4ODBg2jbti0GDhyI69ev86b/7bffkJGR4fg7fvw49Ho9Ro4cqbhu4odEIBAIlZTlI4HdXwIHl/lbEr8SGhqKmjVronbt2rj99tvxxhtvYM2aNVi3bh2WLl0qu5yysjI8//zziI+PR1jDrug54gnsO3zCsT83NxePPvooatSogfDwcDRp0gTfffcdACbI5qRJk5CYmIiwsDDUr18fs2fP1rqpmuP3af5z587F+PHjMW7cOADAwoULsXbtWixZsgSvv/66W/qqVau6/F6xYgUiIiLUKUglZlSPClUnOIFAIBAU4gczQX665kXSNI0Ss3+W+Ag36j0u484770Tbtm3x22+/4amnnpKV59VXX8Xq1auxbNky1A8vxkdfLsPAR5/D+QuDUbVqVbz99ts4efIk1q1bh+rVq+P8+fMoKWFmps2fPx9//vknfvnlF9SrVw9paWlIS0vzuB3exq8KkslkwoEDBzB16lTHNp1Oh379+mHXrl2yyli8eDEeeughREZGKq7/FgkWSSAQCJUc7ZWyErMVLadt0LxcOZycORBhBs8Hf5o3b46jR4/KSltUVISvvvoKS5cuxaBBg4D0Q1g05y2kdN2NxYsX45VXXkFqairat2+Pjh07AgCSkpKY4U2aRmpqKpo0aYKePXuCoijUr1/fY/l9gV8VpBs3bsBqtSIhIcFle0JCAk6fPi2Zf+/evTh+/DgWL14smKasrAxlZWWO3/n5+Y7vOYWlMJuDQ0mytzNY2muHtJu0OxioKO3W07TDr0MLWcXabQ8xaLXZYPOwLrPZDJqmYbPZHH/+wmazgaYZpc8ukxA0TQumsdlsoChKMD8777lz52A2m9GtWzfYbDboABiNRnRu1wonT56EzWbDM888g5EjR+LgwYPo378/RgwegB7NqoMOjcHo0aMxcOBANGvWDAMHDsSQIUMwYMAAAE4/H5oG6PJjS9M0zGYz9HpXa5mvr2+/D7F5wuLFi9G6dWt07txZMM3s2bMxY8YM3n2b/tuHwnO0t8QLSFJSUvwtgl8g7Q4uSLsDk85ZWUgs/56cnKxZuXztHl7+ef78eZwu9qwug8GAmjVrorCwECaTCTRNY9fkrh6VqRZzSREspYyCVFBQIJ7WbIbFYnExDNg5ceIE6tSpw7uPm7ewsNBRX35+PuI46fLz89GjRw8cPXoUKSkp2Lp1K/oNHobnxjyIj6e9hMaNG+PQoUPYtGkT/vnnH4waNQp9+vTBsmXLHGVZbVYU5ufDZDKhpKQE//77r5sTeXFxsZxDpBl+VZCqV68OvV6PrKwsl+1ZWVmoWbOmaN6ioiKsWLECM2fOFE03depUTJ482fE7Pz8fdevWBQCsumzAzLH9VUpfsTCbzUhJSUH//v39Hr7dl5B2k3YHAxWl3fpVK4HyCVCDBw/2uDzRdh9iPho3boKGfTyrq7S0FGlpaYiKikJYWBgAINajEj2DpmkUFBQgOjpaNPK00WiEwWBATEyMy/YtW7bg5MmTmDx5sts+vrxt27ZFSEgIjh49ilatWgHFzLHfd/gEXpg8yFFGTEwMnnnmGTzzzDP45tNZeHX6B/h42kuIiYlBTEwMxo4di7Fjx+Khhx7C4MGDXRQgvZ6pq7S0FOHh4ejdu7fjWNu5efOm2kOmCr8qSCEhIejQoQM2b97sCEhls9mwefNmTJo0STTvr7/+irKyMjz22GOi6UJDQxEayu+IXSsuPKAfJt7AaDQGXZsB0u5gg7Q7QGF15lrKKdZuvV4PvYd1Wa1WUBQFnU4XEIvD2ofF7DIJQVEUTCYTrl+/DqvViqysLKxfvx6zZ8/G0KFDMXbsWMH89hA6Op0O0dHRmDBhAl577TVUr14d9cKK8NGXy1BcWoqnnnoKOp0O06ZNQ4cOHXDbbbehrKwMazduQYsmDQAA8+bNQ2JiItq3bw+dTofVq1ejZs2azKSrTMZZmwJAlR9fe9wm7jn19bXt9yG2yZMnY8yYMejYsSM6d+6MefPmoaioyDGrbfTo0ahdu7bblMDFixdjxIgRqFatmuq6STRtAoFA8CFK4yDZrMDVfUBiW8AY7h2ZKjnr169HYmIiDAYDqlSpgrZt22L+/PkYM2aMImXvgw8+gM1mw+OPP46Cgnx0bNMSG35agCpVqgBgDB5Tp07F5cuXER4ejl5dbseKL5l+Ozo6Gh999BHOnTsHvV6PTp06ITk5OSCUTTH8riCNGjUK2dnZmDZtGjIzM9GuXTusX7/e4bidmprqdhDPnDmDHTt2YOPGjR7VnVdsgs1GQ6cLwAhVBAKBEOxsnwtsfQ9o3A94bLW6MgJo8VNfs3TpUkWxjrh52YSFhWH+/PmYP38+kH7ILf1bb72Ft956y7nh5gWgjPFvGj9+PMaPH69KDn/idwUJACZNmiQ4pLZt2za3bc2aNQNNe+5cbaOBQpMFMWEBbJImEAiESoNCZWXv18zn+U2+q5NAKCew7VteJMzINP1WcWBPiyUQCITghSg3BP8RtApSRHk00qz8Uj9LQiAQCEGCP4a7gniIjeAZQasg5ZRbjh5YuAt5xSY/S0MgEAjBAFFWCBWHoFWQjKxQ7f/72d3hjEAgEAiVAaKUEdQRtArS5LsaOb5vP3fDj5IQCARCkKB0uKsyDY/RNJB7BcjP8LckAUrgneugVZCiycw1AoFAqPwEipJlLgZKcoDCTH9LQpBJ0CpIseEBEeGAQCAQggilykqAKDdaoEFoGoJvCVoFKSGaf/kRAoFAIFQmeJSsXV8CJ373vSiECkXQmlFqxpKw9QQCgeBT/OGDxC4idQ/w23gg7wrz+7Z7PS8/0KBtgNUCGEI8Kmbs2LHIy8vDH3/8oY1cFZCgtSBFhwWtbkggEAjByZIBTuWosnL9NHD9BGAqBgBkZmbihRdeQOPGjREWFoaEhAT06NEDX331FYqLi/0sbGAT1FrCN493wNM/HAAAWKw2GPRBqy8SCASCD/CHT1El8mOSg7WM+SzNw8WrmejRowfi4uIwa9YstG7dGqGhoTh27Bi++eYb1K5dG/fcc49/5Q1ggloj6Ns83vH9mXJFiUAgEAiBQpApN1LQNGAukZ184sSJMBgM2L9/Px588EG0aNECDRs2xPDhw7F27VoMGzZMdlllZWV4/vnnER8fj7CGXdFzxBPYd/iEY39ubi4effRR1KhRA+Hh4WjSsS++W7kGAGAymTBp0iQkJiYiLCwM9evXx+zZs10rCMBTHdQWJCPLYrT59HU/SkIgEAhBQGVZaoSmmWn7SjCXOJWbskJ1chVmAiW3QEVWBxAjmvRmTi42btyIWbNmITIykjcNpUCGV199FatXr8ayZctQP7wYH325DAMffQ7nLwxG1apV8fbbb+PkyZNYt24dqsdE4vzBf1BSyizlNX/+fPz555/45ZdfUK9ePaSlpSEtLU123Q4KspTn8YCgVpAA4KMH2uDVVUcBAMUmCyJCgv6QEAgEAkEMczEwq5Z/6h63DlTxTSBCXEE6f/EyaJpGs2bNXLZXr14dpeWKy3PPPYcPP/xQssqioiJ89dVXWLp0KQYNGgSkH8KiOW8hpetuLF68GK+88gpSU1PRvn17dOzYETAVIymqiyN/amoqmjRpgp49e4KiKNSvX195u7NOwPh1N+X5PCCoh9gA4IHb6zgU+aIyq3+FIRAIhEqNPyJpS5SxdgrwVQ/AHBwLl+/duxeHDx/GbbfdhrKyMll5Lly4ALPZjB49eji2GY1GdG7XCqdOnQIATJgwAStWrEC7du3w6tQ3sXPfEUfasWPH4vDhw2jWrBmef/55bNy4Ubngx35VnsdDgt5cotNRiDDqUWSyothkAUDiIxEIBIJfuXEeOP2X8mEsNexbxHye+hNo86C8PMYI4I10ZfWYioGb55jvNVsDlAz7ROYxZto+ACS2BTKOAIYwWdU1btgAFEXhzJkzLtsbNmwIAAgP1zbUzaBBg3DlyhUkJycjZcM63PXQV3huzIP4eNpLuP3223Hp0iWsW7cOmzZtwoMPPoh+/fph1apVrBICzwkp6C1IABARyuiJxIJEIBAIAcBX3YBN04GSXM/LkmuFsisicssMiVT4FwEYw5k/uXns6e15jOGy21OtWlX0798fX3zxBYqKiuS3jYdGjRohJCQE//33n2Ob2WzGvsMn0LJlS8e2GjVqYMyYMfhx6RLMm/4yvvnpN8e+mJgYjBo1CosWLcLKlSuxevVq5OTkCFdK04DNv31y0FuQACAq1IDsgjJculGElrXEx3UJBAKB4GWsJt/X6culQGh4bDDRWaWHx7788kv06NEDHTt2xPTp09GmTRvodDrs27cPp0+fRocOHWTVFRkZiQkTJuCVV15B1apVUS+sCB99uQzFpaV48sknAQDTpk1Dhw4dmKG7wjz8vWk7WjRpAACYO3cuEhMT0b59e+h0Ovz666+oWbMm4uLigEyBuFS/PQ1cPwT876DHQS/VQhQkADlFzM2499JNDGmT6GdpCAQCoZLil4VjA2/oRgtiytJhQw3RNI0aNcKhQ4cwa9YsTJ06FVevXkVoaChatmyJKVOmYOLEibLr++CDD2Cz2fD444+joCAfHdu0xIafFqBKlSoAgJCQEEydOhWXL19GeHg4enVqgxVfMlP5o6Oj8dFHH+HcuXPQ6/Xo1OF2JCcnQ6cTGcTKOAQUpgEZh4G6nWXLqSVEQQLQpUFVbDyZRQJFEggEQmVDtlLmy8VkfVEX0+7ExER8/vnn+PzzzxXlXrp0qcvvsLAwzJ8/H/PnzwfSD7mlf+utt/DWc48DJTlASBRgKnTsGz9+PMaPHw9YSoHrjFM3arV3LcBUCNw4C0TWVSSnNyEaAYDmNaMBAGargjFoAoFAICikclpzQNNASR5gkTcrzCf441CXlPsUsZQjFywSQ6emIuaPF983iChIAEIMzGEgChKBQCBUNnzQsZbmAbmXgOsnvV9XRYY9c0+2z5f/lGqiIMEZUdtk8aWJlUAgEIIMv/ggycQTJ+0yAYuJL6FpwMZ+yRc51qYioPgm870kF8jP8I2Tusv5l1mfH68Z4oMEloJELEgEAoHgRSrJUiOq4FEOrBaAtsiObcQLTTMKT2EmUFYgL8+Ns8ynzgjkXma+h0YDoVHq5ZAF6xjQtPzLYdcCYMdcr0gkBlGQABjtQ2wWoiARCARCcCJh0bBZy31oPFBmuGQdYz7jWwIGlUGKy/KBnIvq8uZccH63WdSVoQSKoyDxYSnhxL+igA1veFUsIcgQG4DQcgvS+hOZfpaEQCAQKjEVeZp//jXQN89ro0hwdQNBx2QZlOYL7AgUyxmYKOIAeK1oHOjCbMYS5su4VAIQBQlAXonTsz49r8SPkhAIBEIF5eQa4Phqf0uhnjXPAds+4N2l1+sBmwUmGwJrphoAzUIGeFN5vXHGfZtA5HKTDYDNAr3ZPlzoP0WJDLEBuFHoVJBm/HUCXz/e0Y/SEAgEQgXDXAL8Mpr53uguIDxOIKGXrRoFWUBENUDP6tqUdPzbZgN9XnfbbDAYEJF9GNmRVWCsWgqdTe+awGwB7JN8SjmL3lotzLR3vdE1jd7g/F1mAnQ8i+WaaTgUhNJSZ/pybKWl0JksbtsBACazuyx2+NKXmQHIXLCXnZ9dh9hEp9JSwFzmTFNSChhplzw2Gsi+VYqI6wdhMAlZxnwHUZAAtEx0Li+SX+KDcVgCgUCoTFhK+b/7kmsHgUV9gbpdgCdlrhbPN4xz7QAQVROIre3YRFEUEk8vwaWYBriij3D3FyrJdTpIF11y3VeYxVid9CHOJVQKQgCdHsjLZn5H2IAQnnXnbmU7LS1Fl5zp7eIXhoEqyeWPOxRuAUJv8bebUw6zjQKMMv2r2Pnt7TWXAkU85bLTWc1AQXmafAOjNLrIQkNXkoN6Z5aCsiuGfhxqIwoSgGFta2HB1vM4d70QkaHkkBAIBIIghdmMI21cPec2dicmtko915hD004Lj80KrHqCWbVeDQe/Zz7T9khUKsGiO5nP6a7KRUjpDTTZ/j+YxmwAajZ3zfPvauDoCub7pP2u+74Y6V7HuA1AZDXnvn4zgAZD3NN9PQYwFzvL5ZRlfmYXjDtWACd+c8/bZyrQ/H6+FvLLNPxLoG4L5jv7vEjln7Sf8YP69k7h9PZ0OZeA9S8zvx/8EYhv4FqWzYqQkuvQ0YFhqCDaAAC9jsKoTnXx3tpT2HQqCzYbDZ0ugBzcCAQCIVD4uDHz+doV51AaLTP+DpvsM8CyYUCvKUCXp4ELW4CTfzB/WiLW0Su0TuhoC8L0NBDGsbRYC5h1wwD3ffbtbEIMTDr7Psrsng8Aiq45rUPs9OXow8JgtOTz1wETf5lCMhn1TPo9XwP/zgHG/AXEt5DOHxYGlF4XkAGu6QyUM52Bv03u+M+CRJy0y8kucDrelZHp/gQCwVeU3gLWTwWuHvC3JMqwx88BXBUkMQsSW3n6ezIz/LTuFea32VsTZDR42XVRpPg6bKV1yOz0ZSlwAmmUOl3ryv2q1r3KDJX9/ZKy/Irx/yw1KYiCVM7j3eo7vpdZrH6UhEAgBBWbpgO7v3QOUQTA9GZZuMS0sfFvF4PmPGd1ng5oqFEUVBxrvvOjVBkRmMEFiwk4+SdQnKNcLjcUykRxHM9t3ugHWceuAlznREEqp06VCOjLh9WIBYlAIPiMbNYU6APLgI8aMI7CgYiQr5GQgrTzc2Dft/z7uB2kjtNBBxJsWYWUG7Xlsdn6PvDL48D3w5nfnky9F7Xk8aDjpFfSTlXKjpZWNO9AFCQWVhtzIo5eFfD8JxAIBM1hdYJ/Pc/MiFr1pP/EEUPI14i93d6hFWQBG98C1r7MzF6SgmvB0AwtfJCk0mk0xHZ0JfOZebQ8mQfKgVLlylQMXNrO2uAFxcRF0ZSdSXs5ZEIUJB7Gf79fOhGBQCBoAW9HFqDDD0KWIj5rg5kVHdoxXCPSaXsaqJD24vCNpA+SJ+UBjuPCjtJN067HUClKLUjLhjJ/jvq9PZISoNc4C6IgEQgEgj/hUwz86Z+R/Aoz1d1ict/nIpeAgpS6Cyi6AcVWFY99kFi4DAV64IOUcYSZXSflO6OVDxLb0rZIYtq8mDwAAIqZALBmEnDxH0XiMeXyyJi2D7j0r/KynIWyvpIhNgKBQCCIwfum70cFae83jA/U2fXu+4Rmq7G3r3gE+EwglpGYIqHUB2nXl9BtnyOwU+bx++8z8f1f9wZ+uBfIvSJeNrtd2TzLarghIB/bMTr9oIxyRKB0wNZZwKEfgO/vUZ6fq5hYzcDifkxoBjXsXeRaZtZxdeX4EKIgEQgEgj/hU5ACYfSBz4IgOMTGEdgtsrOMBinxQbLZgA1Tof/3Q4SbbrjXIdfqsOVdeenyLssv2+5gLYZQGVoshGunLJ8JzKgWroy3roolli4veQpwfpPz998vyhVEZjrtIQoSi3Uv9HJ8tztsEwgEgnepqD5IAhYkx36+doms5q7IguTMq7eVDwVq7SckWDXf8BirXQUZcgrh36ylgpQ8BTi3wXVbzkXBBXnd4LZTrF1y/ZVyLshLFyCQSNosGtWIcnwvLLUgNsLoR2kIBEJQwGtBCgAFidc3SsYsNj7ktEfLWWyyfZBUlMeHYh8kIQVJxmw/T/j6DsayJAfuORWbiVgB/InUQCxILEIMOoQbmZs0v9TLFyqBQCAAAgpSgMZi4w6xld4Cim7Kl1dIkbj8n3scHlE5BJzFnQkk9nuCN2axeVSY/KRylSOA55yK1BOo16uHEAWJQ0w4Y1S7VUIUJAKB4AMCzUlbDK6C9EE9YE5DwOTBdHQAWDpYftpSbpw6mvMJ707z5y3b0zhINJAyTWEZYvJoAFfpEavHmwoSmcUWOMSFhwAAcot5prgSCASC1gTaNH8HEnKxv+ddcU/L62/kYdDGo78wStmOTyUSajzEJlS26iI4CsXFf6Rn1HnKTaX+PzxKnGBSmQrSoR8UyuBfiILEoWYss/pxRl6pnyUhEAhBQUW1ILGxqfBBctsmo82/P8N8bn1PeX0eIbHUiKc+SMU3+NNpSfIUZekVLTXizSG2ILYgLViwAElJSQgLC0OXLl2wd+9e0fR5eXl47rnnkJiYiNDQUDRt2hTJycmayVMrrlxBukUUJAKB4AMC1oLEh4BckkoDzbNNTfUiHTEt9ENjJ2120RYTYClTUQcN3DjPX763UDoMypbJagb+fF4kbeX0QfLrLLaVK1di8uTJWLhwIbp06YJ58+Zh4MCBOHPmDOLj493Sm0wm9O/fH/Hx8Vi1ahVq166NK1euIC4uTjOZokKZQ1Js0nC6JYFAIAgSoNP8pWaxsTvQ/GtyCxUuX3WT/aRg2mzA3OaMgtTxCZY4MuwONA389YJGgshsKzsIpaxiWef60I/ArTR5abXGjy8LflWQ5s6di/Hjx2PcuHEAgIULF2Lt2rVYsmQJXn/9dbf0S5YsQU5ODnbu3AmjkZmCn5SUpKlM9llsJWaFFxOBQCCowRez2ErzgXWvAq0eAJr0E06XfpgtmLhcm6ezvs8Qr1+rITb+wsW3aeKDxBNjyVwMFN9kvhdeZ9UnI1wBbWPy+xKlMZbY56coWyItGWLTFJPJhAMHDqBfP+fNqtPp0K9fP+zatYs3z59//olu3brhueeeQ0JCAlq1aoVZs2bBatVOmQkPsVuQiIJEIBB8gC+G2P75EDjyM/DT/cJpci4C39whIRerIzz1l0SlXhhiE8Wbs9j4LGcCSpisRWL90Ol7YkGSOp7EgqQtN27cgNVqRUJCgsv2hIQEnD59mjfPxYsXsWXLFjz66KNITk7G+fPnMXHiRJjNZrzzzju8ecrKylBWVub4nZ/PxIEwm80wm92n8oeUK//FZfz7Kyr2tlSmNsmBtJu0O9DR0+5vqjRoWBS0Qard+txURx1Caai0Ay4dgsViAc1NazZBbvhcs8XiSGs2mwG9GTqbDXb7io22ubTbYjGLdkhms1mwbrPZDL3N5tJGe1qL1QraZAIoSrbsbmVYLA7ZLBYzc1xY+215aY66aZ3e5dzx1Wk2m6GH87zbbDZJawVf+5l207IsHbTNrMhTiqatjnbobFYI2cXMZjMos/i5E8JcfEvynLCPva+pUJG0bTYb4uPj8c0330Cv16NDhw64du0a5syZI6ggzZ49GzNmuJt/t27dioiICLft57IoAHpcuZaB5GS54+oVh5SUFH+L4BdIu4MLb7Q7rugiSo1xKA2pqmm5HTIyUIezzWwyYZ2KySdC7e6YmYHa5d+FJrXUydmPDqzfBw4cQCZnZnhEWTb6y5Rl69YtGFD+fePGjbAYItH66hU0LN+Wl5sL9pHcufM/9BYpLzk5GUKrnKWkpKD91TTUc9S3AUPKvxuSJyNzxzLsafSyYH6p+g4cOIAu5d/379+HrHMWGCxFjjp0V3Y48lmsNpdjzFfnfzu2o21eHqqU/87OzkYCTzoheeykpKSgXVoa6stoT2H+LUTLSGenrKQEG8rb0TTjHFqIyFWl6JzouRPC+FE9yTR79+xGdxVla4HfFKTq1atDr9cjKyvLZXtWVhZq1qzJmycxMRFGoxF6vVOXbdGiBTIzM2EymRASEuKWZ+rUqZg8ebLjd35+PurWrYu+ffuiWrVqbumtRzOw4uIxRMdVw+DBndQ2L+Awm81ISUlB//79Hf5bwQBpN2m3Jlw/BeOi0Uwdb2o7JVu/5k8g13Wb0WjA4MHygydKtVu/+lcgj/kuVC51JA9ghTPq0LEj6KaDXBPlXgJOypOpb587gBPM9wH9+wPhcdBt2A6Uu7PExcUBLDec7t26AWeFyxs8eDBwiH9f//79EbY+Gchh1XfMub9m/hHR/FL1dejQAShf97Vjh9sZP6PCEpc67BhCQl2PMU+dPXp0h37d747216hRAyiQL48dpt3rHe0WIyoiDCiTTmcnNDTE0Q7d9hNAprBcVNoe0XPnCZ07dwb8tISb3xSkkJAQdOjQAZs3b8aIESMAMBaizZs3Y9KkSbx5evTogeXLlzPmyPKw9GfPnkViYiKvcgQAoaGhCA0NddtuNBp5HyQRoUw5ZhsqZcci1O7KDml3cKF5uzMOuJStKTr3xzBFq6tHsN2Uaxp+XP1IDHoDwE2rl79emlHnrNRo0DNlsZYT0XHGewx68e5I7HgYjUboKE593DQGZd0dO71B75TboNMBKx8RzEdROqesuZf5y9brXfyWdNyDwZeHp/1Go9HRF0pB0cp8kCjQzjpFFhI2Go2KrgulsI+9r/FrHKTJkydj0aJFWLZsGU6dOoUJEyagqKjIMatt9OjRmDp1qiP9hAkTkJOTgxdeeAFnz57F2rVrMWvWLDz33HOayRRiYC7UA1dysWznZc3KJRAIBF4CJVAk3ywnmw3IT3f+1jJ4oJK1vrRAqbOvUNRwKUXDPovtwhbgs7ZChcOrTuW8VSptf4AEigxGJ20AGDVqFLKzszFt2jRkZmaiXbt2WL9+vcNxOzU11UU7rlu3LjZs2ICXXnoJbdq0Qe3atfHCCy/gtdde00ymEJYm/M6fJzCme5JmZRMIhIqKFx/SvNP8/dApcFdrpyhg9ZPAid+Ah5YDzYeol8uejz3bi1uWlm3mK2v3l9qULTUbzH4+DywVTuOXTt+TaN9+nMXmx2n+fnfSnjRpkuCQ2rZt29y2devWDbt37/aaPCEG14cVTdOgvDo1lUCoBJTeApbcDbQYBvR9w9/SeI7NBlhNgJGJrO/VDo03TqSHHQ5NAzfOAdWbMEqJHPlt3NltFKMcAczaZ82HKLQqSNXpxQVl+cre+KbSAp1f2TGLpI6ByHCUswza90qS0n5MSdwkr1qQ/Bel2+9LjQQaXAXJaguAiLYEQqCzbzFw/SQTb6eiQtPA7xOA7XOB7wYBsxKBErv3tI8tSJ7Wt2k6sKATsOVd+XmsnAW6XTrU8u9qh12un3AtB9AwUCRf3RqUZWF5NNvXgAOkj4HP4yDJLEuWXCzK8oEz62WKUDmH2IiCxMGod9WyrQG7JhKBEEBwh2cqIld2AkeWM1Gh03YzD/3zm5l9Xn0OeCFQ5H/zmM/tn8jPY+VYDDa+5Z5GUUfIasOyYTwL2iocYnMoqzI4/bf8tEII+Q/JHWITg+b4IPliGEmOZYvLz6PkpSMWpOAglGNBklqkmkAgAAGxdpin8C394IsXpEB10r7BmrdNeWhBYjZwfJAUSccM4/JX5F7g3y8qLJyHouv82yWdtOUoSCo6loIs6TSieNFVxKv3CbEgBQwhnOmKxIJEIMigMtwnvG3whYLkp8VW1eCJguTmlK1wFlugHBMtLEhQ4YOUe0lZei5K12Jj49elRogFKWAhPkgEghwq+X2itnMuvQUc/QUoE4kC6G8LUvph4NgqiUQaWZDErBiqnbp9PIlGStGQ66StFIuCKI98eKpgiUF8kIKDuEjXYFxFZR5o3QQCQZxDPwKrnwpcHya+hUmVsOoJ4LfxwB8ThdPwTvO3AUdWAptnunYQZYXaj/t/cwcznT9tj3RaJZ0VN+0fE5jYQM4E3Awq66aVy+YJkhYkOb4+KuIgHVzmXtXRFTLq8gGVdJo/UZA4xIQZEW50XuBv/3Hcj9IQCJWcNc8Bx34FDi/3tySQ/SD+5yPBCMlunN/EfJ76UySRwBDb708zTtZXdjLbCjKB2bWBpUPc02vBTZH1HLTwQTr2K5B9Sni/xwqOjzpSKR8kWRYkFQrFzfNumwx/TQqMoUdiQQoeOiZVcXzffFrAUY9AIDjx9CFWmqeJGF6D3b6t7wPf9HFP89cLjMVI6bHgjU/DKqOkfKGtE78zn6k7lVuR5Mhk4F+uSVAuT+vk7hcLrCgBdfhHRgHzBVJDbLJnsSmkrFB5Hl9BfJCCh64N3RexJRAIYgTAW6xXEBhi4045t5iYDv74aiAvVYNqeToF9tDO4Z+UFiidRO++ZqUTLXyQJPbbg1IKpudvg95mhmHti/Ll8hStnLTZ8FiH3BDzY/M3ZIgteBjfq6G/RSAQKhaeWpACYpjAAxnYHYTCRUGlsSsnrHKPr9amaHabxSItazLN31P4z4/SRVg9RhMLks21ObfSpPOYBCxIZfnSeT3Gn7PYiIIUUHCjaRMIBCkCQMHxBvaHs6KHtNJZVRLp7coJ23KhNCqyEOzOPvu0dHpFx0HjpUaE6vb1UlBaLTWitP18cboAoCRPWTnegChIBAKBIEAgWIA8RcwXSLID8EFUZLalRCulgLu8iCD2+pT4ICkcYpMuUNFmr6GFBUlLoa/s0K4sQSSuN2/e/8QHiUAgBDWBsCB0oCt5LsNhGj26lcbW0dQHSeHxFpCV8rWGJKkgybEgIfCvNxf8OMRGfJAIBELFpiI97NUg1T6ehV01g8f/R6mCJNQZy7UgOXyQNJzFpvSa+bqXNuV4iiZrsVWyNay08onjgwyxEQiECk1FddIuKwTOpTCz0Pg6Wtk+SDLkz093fj/6C3B2I/NdrvXMpWPWSAmrSBYk4YI0KkdudVrNYqskLxX5GcC5DV6sgChIPoe6vN3fIhAIBH+z4hHgpweALTM9K0fObLC5LYDM40wYgN/GA8tHKqzDy07a8oRQkFSJ35Z6KF8r15IWJBnKa4UaXoO4vL+M9m7dB9wjiPuKoFWQYCrytwQEgjpoWoOVvbUmwB/45lJgw5vA5f+AHZ8C3/ZjrEeX/mH27/wc+PkhnoweLjXC5cRvQFG28nw2K3Bll/O3v3y2FA2xSShIWsSLYirSqByZaDHEZi2reEqSEFf3erf8tN3eLV8Eg99q9jeVbQyYEDz8Np6JGvzwCqDZIH9LwxDoD/ud84FdXzB/dg79IJ1PyyE2APxDYzKm+e+Yy0TQZm/LTwfCqwLGMBn1Cs0Akym3V3yQtMH3FiQpJ20Zyqu3rS4ETQheCxJRkAgVFfuSCts/8U75BZnA8oeAc5u8Uz4f3raI3Djnvs3TmD5FN5SXRVFQ5T+060vX3zcvMEN2CzorL8sFpcqFlkNs2kDBx89yyWHJAJiRSdCEIFaQfBx9lUCoKCS/ApxdB/x0v4JMFdBJ2xjuWf5l97B+sOX3wiw27vPq+knmM++KZ0XLPu4qLEg+Gvpqke6jNdjsaOKkTagIBO+ZJBYkAoGfggzleQJ9iI2vsw6JlJ+Pr33XT7CSqRxik5OPoqT9XqQQqkfpc9CvS43wU7X4gk/qcSC1UHDuJWDtyxr6WAUCgX5/e4cgVpDET/ifk3oAAKpFylnhmkAgBDR897siC5K3omPT8oYXPVGQRPMq9EFSchyyz8hPW5GQGmLLuQjs+xZIP+QbeQhegyhIAkSHGQEAN4tMKLOQ4ThCMBGAPhRHfwHS9nlQgEoFScpJO3UPMzuOvU7WmueA7LP86d2UIZkKh1VhvCI2h34Qrkep5U9J+k3vKCu7onDZF0t7BBoynwm6yjXvK3gVJIk3MvaCtR+sk7GII4HgcwJIkfF4iE0k/9X9zMy9xf08rIODzigjkcQ0/yUDmJlx2z5wbru8HfhOZHYhW0mSe9w8Ga7KOilWsMxCeKJ5BysF6dJpKh0yr5PYOt4Vw8cEr4IkcaOHshSkpTsve1kYAiGAUDKj7NTfwE8jgaLr3pOHbwaaUngVESUzsiT2Z3Neoopv8KdzU2rlyOChIiz2rNNqwVgCAZC3Dl0FonLZwxQh/mBgW5AC3v+UQPAXKx/VqCARJcATq0VxDnDzPFR37HJvfsURqctZNgxI3SWdzhPEZl0pjoNELEgEESrZEFvlao0CKIkbPUTvalxLOZmF/i0TvCkSgUDgxYM3lHltAFMBEBrLU6yGU9blKkhc65y3lSOAcScQbKsCBTDnInlbDFbknndd5bIgkSE2AbgK0vjv9+NcVoE3JSIQAoQA8m0CPLNamMrv2bJbHsog0UFYlViQFB5fT4NoilmQCjLllXHpX2B+e+DUn57JQqjcVLIYUJWrNUqQeOjqdO4Ppf/OC/kVEAgEXopuyJyizlJAbl5gnJ5L8sp3ectqIadcmqlfykIke4jND8qn2PFb/qCyso6v9kwWQsVErpJOLEiVhNzLirP8fVRFAD0CwVv4a8FSuWQcBeY0ApYOVZbvy27AttnAh/WZ3/70e8m5BMyIA/79SDydzSyvPFXnTCKPlALpaZBJQnCz60sFvmpEQaoU6A8tU5xn/5VcL0hCIPgBm1U6IrCnHCy/x9iLrMrBLeaPF4M0SrFzvryyfG1BYg9lcBUgbruIYzXBEzZMlZ+WWJAIBEKFxmoBPu8ALOrjXadbdse8d5FEPB4vzWITQ8tIz0qsNEqtSHzJ2W/qXOWshPMiR1tBpucTfAKxIBEIhApN7iXmL+MIf8fO7sCXDgXOrFNXD7vs5CnAV93UleMtJU7Jm7EUsmexaVSfiwXJIrwPkJjFRiBoSCWb5k8UJBGevaORv0UgELyAgl768nbg54fUVaPI8iPQgZfkAhYPltnwFVaZPkhawVaCuLPUuMddaBZbfjBGhCZ4FV3lUikqV2s0pn/LeH+LQCB4GT7FRCMzhxZWiw+TgI1vel6Ot/G1D5KlhFU3RwFa95rrb6HzsPldbWQhVH4ubpWXjgyxBQ/x0WH+FoFA0B41a4GpQY3vkFxrkbnEGQYgEPDqEJaEUsW2XpXeAo794rrfJuCDxFayCAQxrh2Ql444aQcPdatGoEZ0qMu2X/enocREps0SAgEtrBEBpiAt6Cwv3UeNmDAApR4GgNQMJUt2aByewVTo/M5nyRI6D2Fx2spBIBALUnBxX/vaLr9fWXUUs9ed8pM0BILG8Fk+tIqvJBbBmUvRDSbsgNz4ZOYi5jPrhGKxvII/naCllESh8xBeRXtZCMENsSAFF0a9+yHaeCLLD5IQCF7AavJeIEElFqRdXwCrn/COHL5AsK1cZVOF8pl+UHx/Wb74fqHzG1tHuSwEghhkFltwoedZcoRAqDTMbQF81Z2zUSsLksIhthO/a1NvIKGFNW7Le+L72RYkPksWLTDNv5K97RMCAGOE52V0meB5GRpBFCQJDERBIlQ22J22qRDIPu2dISKfLHERKPen0PHjyEdR2i8Rw3bS5lNK+SKmXzsI/PWCtnIQCIYQz/I3GQgM+kAbWTSgctnDlELTkg8rA88QG4FQseG55q1mIOcicGApUHRdm2q8EQG76CYQWU37cj1Fdlu9rNDxycH3jFvU17tyEIIUD6/vAFtfMrh7/3MpkkmIBYkQsGj5MLGZgYU9gD1fATfOalOmNxSkpYO1L1MLhCxw3KjWFKW9tY5dHomYTajQBFZ/G9wK0qk1kklCje6HKMCUXEJFwVImf5aWN+G7gK1mBcEOZcKnIC0bBhxZob5M7nBgoN+MfPIdXalxJWyliCxMS6jABNj9HNwKkoyYDVGhwT0KSdCQr3sDn7UF0vb6tt6iG8CCLsB/nwmn0Vo5AvgVpEv/Ar8/42G5gWglkemDBIqZsadp1ay6+fy+aBpksVpCxYAoSG4sWLAASUlJCAsLQ5cuXbB3r3AHsnTpUlAU5fIXFqYy4rWMKYl8ChIF4Jt/L2D98Ux19RKCk+zTzOfRX8TTac2/HzN1p0wr3yBgQRLj0r/AjXPK6vXGEBtTsJfK9QChtvrkjZg5HjXzDkB38g+BJAF4zAgELgFmQfK7eWTlypWYPHkyFi5ciC5dumDevHkYOHAgzpw5g/h4/rXQYmJicObMGcdvSu1BlTHNNSHGXflKv1WKWclMZ3f5gyHq6iYQfIVVxvIdNgkFadkw5nO6gsjV3lKQXDr7AHmgylVAvNEB0DRgNaHLpc+ASzz7r+zQvk4CQYhmg4Ezyf6WQhP8bkGaO3cuxo8fj3HjxqFly5ZYuHAhIiIisGTJEsE8FEWhZs2ajr+EhAR1lcsYYmtTJ1Zd2QSCt0ndBSwdqs1q995YjT4QAlD6DB4FyeqFYUshvDFESiAoxdMXgACzIPlVQTKZTDhw4AD69evn2KbT6dCvXz/s2rVLMF9hYSHq16+PunXrYvjw4ThxQuVyAzIsSKqtUwSCIB4Md6x60vX35e3AsVXKyuC7pn3lg6RNwV4q1wP4LEg7PoUmkbSlKydDaIQAwpNrPLD6W78Osd24cQNWq9XNApSQkIDTp0/z5mnWrBmWLFmCNm3a4NatW/j444/RvXt3nDhxAnXquIfOLysrQ1mZ8w07P98Zlt9qs8Fm9uzN2exhfl9hl7OiyKsVgdRuY/mn6uvOaobxuLsyZM257FYeu906qxV69naL1SGLI31Zids2PrjHkS+PPY3eZhV8A7OnkVOne16TI5/FagHNkol7vtWUrw53BYXe+RkoS4nLNqvNeS60wmKxwGwqk91W8/WzPjwuhGDCarOBom2qLS82GrCazQFzffrdB0kp3bp1Q7du3Ry/u3fvjhYtWuDrr7/Gu+++65Z+9uzZmDFjBm9ZFy9dwslk6bHSDtV1OHCD/5Qny8gfSKSkSMd+qowEQruHl3+mXrmCoyqumy4XPkFNnu1nz53H2UL+8lJSUtAmNRUNyn+fXvoCMuI6YAAn3X/bt6GPDBmS1651sUAN50tT3rbhqTuFy7GnkVEnlw3r12Fo+fedu3YhN/KGW5oDv3+BtmnL/PqgpcoK3LadPHUarTWu59jRI8i4YoDcCFHbt6TgTo1lIBAAIC01DaGWW0hUmT8jMxP7k5NVPRe8gV8VpOrVq0Ov1yMry3Xx16ysLNSsydcVuGM0GtG+fXucP3+ed//UqVMxefJkx+/8/HzUrVsXANCwYSMk3SX9WBlgtaHljE28VuzBgwM0cB0Hs9mMlJQU9O/fH0ZjoOjn3ieg2n2I+ahXrx7qDFJ+3RjfH827vWnTpmjcy7U82/HfcfzwfrQYNR2hm7YAN5ntra/9hOYjXgY4o9I9u3UBzkCSwYMGus7+PMSTZvBgZhFcnn0uaQTySzFwwADgCPO9e7fuoOt0cuyzn+9e595XXrAPaNmyJXBN2zLbNEvCbWVpstP3unMAcPoNbYUgEADUrVcXVFE4oGAuB5vExETm2aDiueAN/KoghYSEoEOHDti8eTNGjBgBALDZbNi8eTMmTZokqwyr1Ypjx44JKiqhoaEIDQ3l3afX6aCX0WkajUDLxBicSHdfNdvvna5CjEZjhZNZCwKp3XKvO9nl6Q2u5VktwJrx6ADAbHoRep2r9dNocL/tDZQ8HxajDswNIZbGaAQg7tPkyblgy28wGCTlCST0eu0fufqUtxQN2xnJ8kmBz+g/gZ8fAszF/pZEEXqdDtCpv750FKALoPvZ70NskydPxpgxY9CxY0d07twZ8+bNQ1FREcaNGwcAGD16NGrXro3Zs2cDAGbOnImuXbuicePGyMvLw5w5c3DlyhU89dRTyitX4ICtJ0uOEDRDRBkpKwBCoz0rnu1wbSpUVr8UVhNgDJdOJ8dpWLVjsfg0/7jiiyrLDRL+ftHfEhAI/ATYZAO/K0ijRo1CdnY2pk2bhszMTLRr1w7r1693OG6npqZCx9JIc3NzMX78eGRmZqJKlSro0KEDdu7cyZiuvYiQgkTTNJnpRtCG7Z8Am2cCDywBWt2vUaEy1/6S+2CSPXXdiwqS2Ow4qxl3nJmurlyfEADPikv/+lsCghy46/gFBURBcmPSpEmCQ2rbtm1z+f3pp5/i008/1abiGPdZb0IILVprtdEw6APgoUeo+GyeyXyu+Z+rgmQxAUsGCudzu/wkHjJ8iknWcTkSMhYkOUhN8f99AjBU5X0spljJCYrpDSg9QHsp7hMhCAksRcFnBJhSGBAKUkVAyEpkC9LrmOABUpYTbkyicxuA9IPqyue9bnnqL5XpVSkVcZtPBj6OLAcubpVXlnvhzq/c9vnLRG+MAEzus9bcINZmacKrAiU5/pbCvwTYUJPPCDAFKbCk8TUaBLKzBeuFTPAeXCVE6erv3PxyOmXZQ2xy4zfJKK8gQ2ZZ3KJZZf/9kmugTH/dj3KtR+R5IY1B5dqalY0AUxZ8gozVLXxJEJ4BFtmnPC7CSkxIBK3hKu6n/pLIwFKAaBpY0MV1H7dT9qSTtlmAgkzpMrypCLDLzjwKrGZHF/fT/Sh3WRUZ0fuDHhmLiAcHFdHaSHlmJQ2w+yO4FaQDSwGTzGmUAs9dYkEi8GIuAX4ZAxxZwbOz/JqxWoAi9yCHHmEqcrHMUBe3Age+k84n15p6ZAXwSTNgRhxgLhUrUF55qhAp21/3o698n9o96pt6CH4mSPuVALOaBZY0/qAk16PstkBcN5Pgf/Z9C5z8A/j9GeE0394FzGkEZMuI0CiX0jyXn4Z1L8vMKPOBvGOu8/v2T0SK85EFyW1fgN+Qnh6XoPBhClLlgA1NV0wDkqeQIbYAw8MHKrEgEXgpvimdJuMw83l8tWd1sTvNkjzp9HzXrJr7IG2PcPmLvLiYhZisga4gedr5B9gbNoHgjgeaXYC9AJC7zcMH6uWbRY7vuUUm0ERhqtxc2Qkc/cWzMuRcIwVZ0mn4kDsbjYua69bAH6EepkIg95I6OWTBI+vZjYw5N9AVpHWvelhAYHUgXqNhX39L4GeCtB8JsBeAwJLGH3gYu+SFFYcBAH8fTUf7d1MwK9lzx29CAPPdIOC38UDGEQ0L5en0TvwuP/uBZcAXnYC8VPcQAbxoZEHSh/Bvl+uwrBY+ZW75SODwT5U/FlGAvWF7BZoG7vvG31L4lyDVj4iTdqAh82FOC1yxqTmMk/e7f58EACza7s03Z0LAkJeqYWEeKix5V4AbZ4H1U/nLUiuDFEIWJG9bcYTKP7u+8k+jD7A3bO9AI2gsZaJU0GPgiRJPfJACDJlxXWpEC3QGAA5cyUFWvp8i+BIqIHI6cRUdvblE/bIiahQLvcA9wXEU154K7KTtMRW001QCTQeHpUwUGkFpRgqwF4DAksYfyIwM/M6w2wT33f/VLt7tJSYrbpXIDaxHqFAIKRS5V5jQEQeWeVa+7ICMHGQpCHyya2hBmt9eeVlKEDr2WcdhWDbYu3X7m2BQHIKhjZUVigK6TGC+Rycqz0+G2AIMmYtvJsSEoX/LBEVFt52xEW1nbERRmdwFPgl+Y9sHwMJeQJmM5SIA8CoU108Bn7VhFARPl0rY9I6KTB68dWrppO11hJTTy6AK0n0riq8JsDds7xHkShJdgYcZ63cDppwHHvpJed4Au74DSxp/IHfxTQAd61dRVLTJyrzNX8wukkhJ8DvbZjNRmffLCKooxOm1zGdhpng6qwW4dkB9PWLIGr3TyknbqDyPFlT6YTQxKkCnqUUnp9CKREdU87xOgnZE1VB3HQhN/PATREGSu/gmgLE9kjCsbS15xbKWICEW4wqEguvBHZlWmCPLvRgnSKUFad9i5Xl0/lKQgtA3w06AvWHz4rGjrfIHprX/+x7W6WXihV00+PHDNV6tibblqblPa7bSVgYPqQB3m5dR4OsRatDjoU515RUbzA/xQKQgA9g6C8j34hCM2nMuJ7ij3PrV+iBZSpTX5zd/gSC+tyrC25YW14XSdiq1Ztbtqiy9p+gDfH25uPpAdY0VJDW0HOFvCVwgCpJCZ9iuDavhrubx0sUSC1JAof/lMeCfD4GfHtSmQK1mggHA3q+Bmxc8k0eJDFop7zs+1aYcpZzf7J96A4IK8DDxdLFZioLidlIK6xy3DrhfhdVULUrvOZ+/YHujPhVlEiftAKNY2WKheh2FxWM74dEu9UTTsZcgoSrCQ62So8ssD+yYdcyLtXjwkDm2yv8yKEVWUEovkDzFP/UGAgp8Jv2GFrFsFFuQFCpIOh3Q+gFleXyKrxUkSnulzBCmbXl+gChIKgP+3SlhRWJbkAgVCE8eEkLDW3lpwMa31Jcrl4tbZcpPrs0Ky9GV/pZAGp0W3YqAglS/B9D7FZ46A3wISylR8b4devBGXfEtgdtHM+esgkIUJNnTul3R68QvKBurr9TkeUEIMBQMsS0fBez8XHl5YmUKFhPMM7yCAFOhvyWQxpsWpHHJQCTPy6mnEwb6v+vlITeZ93HbR4D+M4HaHSroZATWeaMo4J7Pgb5v+E8cDyFdt8p1owwiWk96XgnyS52+TT/sugJz+ZR/mqaRfCwDV26Sqf+VD4EH2vUTMrJqpCDJeRBXyAcvgaECDNcr9SMZNp+zQcIHie8lwFPfFYry7gxBubfckI+BHi94Tw5RyHOBC1GQvOBH0f2DLej10VbH75/2pGLxDmaNtvXHMzHxp4O4Y842zesl+Jnim9qXqdQiJEf5WTtZnSwE/1MRZnwoHe7ia5NoO3mucb46hy9QIoSXj60K5aPtQ9qLIQZ5cXJDlYKUlpaGq1evOn7v3bsXL774Ir75pgKuwKxy9W+l0/j3XWIiK++55GGEZYJiGl5fLz8xTQNnNwJFEs77fOd//xJlgrkWKFCHFyxIaXsUlkkIHCqAgqR4iI2vTfItSDQo/iG2WrcrEEHFzDmvwJKh3wxgpIdLFinCWwpSIBxXdahSkB555BFs3cpYSDIzM9G/f3/s3bsXb775JmbOnKmpgF5H5RCbTaETtrk8vcVGfER8Tetry+UnPrAUWD4SWNjTa/LwIhQ2wBsWJALBmyh1uuRabiiebWx47gmab4hN0bCbty1IKjCGAbeN8F1AVvLscEOVgnT8+HF07twZAPDLL7+gVatW2LlzJ3766ScsXbpUS/m8hrX3a8wXlQqSRaGCZC1XjKxEPwps8sstowUZ/pUDAEATJ22Cd6jR3HtlK14uQqFiwneN8wWKVDzU500fJA+UDwHFzaa1hwx5drih6gibzWaEhjILVW7atAn33HMPAKB58+bIyAiEjkUGdjOw2iE2hQrStdwSpOUUK7Y8EYIFjSxIxNGycqOFlaPFPcAALy7N0WeqBoUoddLmUYaUWJAonXidvoLv/DYfwpt0W/P3NK6cPDu4qFKQbrvtNixcuBDbt29HSkoK7r77bgBAeno6qlWrIIsG2s3AKp20QwzKbqbLN4vR66OtKDL5KbgegYHrH3HiD8bnSDEaP0x43zBV+CARM3klR+ZzJ1xkYe2wGKBJP23E4SOmtrL0Sp20Odc444PEowwp8YWiZA6xjVKxQj0Aj54XQ+fxl+ipxathH9YPLwSKrASoOsIffvghvv76a/Tp0wcPP/ww2rZtCwD4888/HUNvAY89NL3KIbbeTWog3Kh8amlucQWIhFuZsT9UbDZg37fAr2MYnyOl+OJhosqCRKjUyLUg1WwjvM/bl67iKffcNimb5k+BFrAgKRlik+mkrXa9MqHnRUJrHjk4hMWqq1MKtwCOGlwYgebH5SGqwo/26dMHN27cQH5+PqpUcb6pPP3004iIiNBMOK9ityCpHGIz6HX4/snOGLlwl6J8ZgvR0hWTcwkIjQEiNbBO2h/eR34G1r7seXmawTfEZiM+SAR1+HNNK6WdpIcWJAo0v7VI6TGQssh0nQjEylusXFO8pnRwytXi2cH3vIqSXrs0UFFlQSopKUFZWZlDObpy5QrmzZuHM2fOID6+YhwM2n5DqbQgAeqWEymzqK8vKCnIBOa3A+Y01KY8+3m/9I825dnx1KIkNMRGZrERXJDZWYoNL3n7JV8TZ2cRIRvdKa9OJRYkOUNsTQZ4oKzIvC8Vlk9Xb6ZCFoG6vPXsELK6xYmvZxoIqLqShw8fju+//x4AkJeXhy5duuCTTz7BiBEj8NVXX2kqoNfwcIgNUKcgHbl6S3V9QUmmZ4vL6n951HWDJ2/WYg8QbzxcvBUHiVBxkduBiikpWl8i3KU/FCtICi1IdTrwpOepU7EyI5Fep/dM+UvqpT6vAJaHVqjP7A0FSckxf3ITcO83QDWVw5Y+QNXZPnjwIHr1Yk72qlWrkJCQgCtXruD777/H/PncsPEBir2j9CCSdteGFcQhvULjweuuxQTduQ2c4uyXvMJyzaXAl91EEnj6cBGyIBEnbYIKtJyyLrVG2TMca6zSQJFucZBUBG3kffFRUIacpUZi6york8voP4Gp18Qd6IXKFwqdwDfkZ1c4JBeJ5dYl89kxchnQYhjHyVsF0QlA21GAIdSzcryIqruouLgY0dHRAICNGzfivvvug06nQ9euXXHlyhVNBfQa9ptSpQ8SIL1gLSEAcTxIFSoS5zYA2aeE93tjiO3CFuKD5G9qtfe3BK7IVXy09EGStApwFRwvW5D4CIly38YXG0lMBqEqn9gAPPQzULWBesWTphm/19AoThleeKEZvQbo84Z0FG4lFqQGvZ3fG/UFRv0IJLRSL2MFQdXZbty4Mf744w+kpaVhw4YNGDBgAADg+vXriImJ0VRAr6HzfIhNK8xWGywkgiQ/HumgPDe86gect88Pj6wrHyNxkPxJtSZAp/H+loKD3CE2LV/eJMpyswB5GElbTVRrYzgwNhkYuxYY/DEzNT4kUqEMAnXW6wo0Hywgq1xY96XY8REqv9kg5rNKknRVsbWBPq8BUTUkEiq0IL14HJh0QPtZdQFs9VY1i23atGl45JFH8NJLL+HOO+9Et27M0MPGjRvRvn2AvXEJofPcSVsLNpzIxDM/HEC9qhHYNqUPdMQqpR28ygXF+VRbNvem9oaTtopyrWbP5CC4UlGnLYsOc2ndIXGOkb9m0CWVDyklqVkmSK5SpsH14KIgySzvns+Bet0ZRW0eNzSAWjmUzGKjgDg/zODzM6pepx944AGkpqZi//792LDB6eNx11134dNPP9VMOK9id9L2YIjNUwpKzXjmhwMAgNScYhSb3WVZdeAqXlt1lFiY1MCndKjt8IQUGIsJKCvw3luQUgvS3y96RYygxRDmbwlckXv9Kl1mwxO4FhFvLtnhLeT4INnTsWncH3jlonQ+9vNBVHkVOL9hsUDXZ4GomtJ1ycZHs9gkCVwLkuoruWbNmmjfvj3S09Nx9SqzflXnzp3RvLkX1/jREg8jaWvBwn8uuPy2Wt0vlCm/HsHK/WlYe6yCLOGiOZ68sYnceFpZBj5rA8yuA5gKPSxIQNYANj8HBS2G+VsCDhrMYlNzT3FnqrkUxyrvoeXaxEHyOTIdwymK8e+xo9PLjM8mc4hNTv1c+k33vCyKIv6LPKg6UzabDTNnzkRsbCzq16+P+vXrIy4uDu+++y5sFWW1eocPkv8UpAVbXRUkk4iVKKeIicD9acpZPL54D8yV3aJkLgX2fAPkyHg7E0LshleqeJz+m3+7fVHbjCPKypMrTzA+tHy1erkktEJH3wBCtBNWeO1Ldp6sjrZGc3mz2G67lz+/vT5fI3epEYDx71EK+/ip8UFyJnDf1PMl5fLwyuGDF0o+eJ99gaA0q/RBevPNN7F48WJ88MEH6NGDGffdsWMHpk+fjtLSUrz/vhcXQtQKQ/m0SXOpf+VgIaYgAcDhtDx8tvkcACDlZBYGt070hVj+Ycdc4J8PPSvD0xvv0I9A+8eY78dXu++3spRrT4dizqwT2BGEFqSAsCgEEDG1gfxrzHfZQ2wiSooqq6SCzlOOheTOt4ETv/Pn9wsyh9j48snBZYhNq/Z6Wo6SITa5damRSWAyjR/dX+yosiAtW7YM3377LSZMmIA2bdqgTZs2mDhxIhYtWoSlS5dqLKKXMJRPCzUXe1TM64Oaw6Cj8HBnzx3YTBZxBWnEgv8c3yf+dNDj+gKay/9Jp5FC7K1XzkNq41tihQOWEudPg0CcErnkXODfHowWJIIrnVkz6WQHihRJ500fIbW+PP4mtg68a7WQO8SmcMagJyhy0ubBm8P//lwqh4WqOyUnJ4fX16h58+bIycnxWChfQIeEM19MRR6V8+wdjXDq3bvRvq5Y8C95fLT+NLILygAwU/+HsxQivqjdpTxO3ZUHLW4+gTLObgTy02Vkl4iczbY+emtYiPgg+Z/aPJGbfUXDvuoUGtGlRmR0srHsZSAo8evQ02n+/hxOeew3YMB7TNBDvuPS+Rnx/HIVFlorHyRn3hJjVfXlMIVxfvvpWcM7mYZz/ZY7p9MRUqELtEXVmWrbti2++OILt+1ffPEF2rQRWUU6kDCWK0geWpAAwKjXgRa4uEZ2qCO7nHXHM/Hc8oO4VWzGlZvFOJKW59j3895Ut/RXcz2XPWDRQjHgK6MwE1g+UuZabBIyWHwwPBuUFqRAsS6Uy3H/t/4TofN4qDoeYm/gUh30/YuB8Vs4G+UOv6gYiuGLg+QrGt8FdP+fexyk+j2AKeeAQVLD/BorSFIKF0UBr16C+YWTsOo9jEDtqQVJM4VKRry6xLbA/w7C8tRWjeqUhyofpI8++ghDhgzBpk2bHDGQdu3ahbS0NCQnJ2sqoNcwRDCfllImFpKHJj2h/rxpQrSicvZeykHbmRtROy7cZfuFbHdLV5nFBpqmkV9qQWx4BXUmFcRLCpKWsJVrrykyxILkP8qPvacdkUci0Ori5oh2whIKUusHOOkpZh2xU38KlKdCoaHUKFVexmVWl07jVegFFCQ1TY+oChi1iHfGVZDEkvr4HPFdo9UaATdv+lQMVRakO+64A2fPnsW9996LvLw85OXl4b777sOJEyfwww8/aC2jdzCynGrNJcLpZFKLo9DYsanspK/lSct0OqMAb685jrYzNmL7uWxV9VRuvKxcHGEtFOktBUmDa5PgIX71h6DVdU6hIisaqBniuWc+0FfIJ0+NgsRWEgJEQWI/q+WeczVDbKLWPR8eC7e6lD4vPZBVKhp39/+pL1tDVA+G1qpVC++//z5Wr16N1atX47333kNubi4WL5ZY2DBQYE/fLb7hcXG9mlTHi/3cVyX2Zhf98q9H8ONuZujto/VnvFiTH+BTLANq4VYaKL3l+tsb/Pywd8r1Nr4MVOhtAqktcjvQ8Dhh3yk1ClJ4FeCOV6RloijIuhcCMZgke9aU5udcwILU1o/3N9eKp/h5qfKZV6czMHE3qxiecnpPAZ7iDvP6ngC8Sn0E2wnsl9GeF0dRmNS3sdt2X/nYHrt2C0ev5jl+5xWb8NW2C0jPK8GuCzcx4+9TKKtQPt18CpLSWRYeWnWkzl1MLVZaL53ovCveKdfbaB0Mz5/4szOnabi8qcu9zigdME4gdITm7eGcLzkhL8SGDRWe//PxgxSlF4S97JScWE5KEJrm3+VZoOnd2tbFptskIK6ewE5PfZBU0naU67OTD50eqOPHyRF2MfwtAAAsWLAASUlJCAsLQ5cuXbB3715Z+VasWAGKojBixAjllbJvUE+D/JVj0Lsezs8eaifovO0N7vnCOett6m/H8OH60xj1zS48vGg3ftyThk3XAuJ0q2fP1wozaHTs+Tql0luu24PSmVqEQLQQdJukLL39/Pp7yjH7WMq9zigdYBDwnfJEAa3RQrq8iKpAjxclChJz0paPrU5nnKj1kOr8LrhYkDQeYhOyIOn0jH+Xtxj4PvDCUf59iobYNAgvYacpV6GVY3H0z0uT359iK1euxOTJk/HOO+/g4MGDaNu2LQYOHIjr16+L5rt8+TKmTJmCXr1UXlxePuDbX+2L4e1q+22W9o7zzLBhWo7Th+VG4MTElIbvwG2YqrAMjZQWvnLWvQqcT9G+rsqC1m/gWtCgt7p8/h5ic3lWybUgeTCLzT2D8+tTKcCgOcL77d87Py1enhrHcz6qJGn3LHexIMk9RnJ9kEQiaXu78xcs309xkGJrKy/HTx2pojv/vvvuE92fl5enWIC5c+di/PjxGDduHABg4cKFWLt2LZYsWYLXX3+dN4/VasWjjz6KGTNmYPv27arq9RZrnuuBnGIT6lZlZsnRPCf2yZ4NsHjHJa/JQNM0LDzrugXayIU4Mm6I4hwgbS/QuB+g57mUPb2pzEXAvx8Lm8DT9rDqCnIFacp54GPWELOWVpe6XYG03dLppFBr1fKrskeL/hTEk1lsYoRGA12eBtax/ZF4hBKyXmkhAxstO06bF30Q5C41opbYesCtVKBqI/l53Kb5+0AJ8ffLhkIUnanY2FjRv/r162P0aPn+PCaTCQcOHEC/fv2cAul06NevH3bt2iWYb+bMmYiPj8eTTz6pRHyf0LZuHPo2c04P5YnviMhQ714kb/x+DCU8QSQrln4k42ZddCfw8yhgz1fu+yxlwO8SQd6ksFmALe8CC3tIpw32gI4RnAU7+TqBIXNlFsa5Uh9ZqUok92JV3gHsh3pMbeDuDzyXpetEeem4Pki9X5aXTzSSthcXk7WnjawukU5GNOnG/Zjj7SsF1ZtLW4jGQdLgyTxmDdDpKeDx3xRkUjDExqvwejEOEhc/vd0r6qm/++47TSu/ceMGrFYrEhISXLYnJCTg9OnTvHl27NiBxYsX4/Dhw7LqKCsrQ1lZmeN3fn4+AMBsdo0jwf2tFQ+0T8QXW8+7LCMSYfTeyTabzfh5bxrvvv03dDh5LQ8ta8ehqMzidUXNE/S0jVd7t/0xCdbBnwCUDsZcxgpnO/EHrJ2edUmn2/8d9Je3+0BSBovFpC6oWCXBbDGDHYmL1undHr8WyiDrGLFVAjq+JSzQQ4soXxarTdE5okHDYjYDNO2o3zLsc9B1u8K4nt+6LVuWxgNh2P2la33Vm4G64Tob1WK1grLRsKsI5k4TgKS+MC4Sdy2w0oDNbOY9bmL7AOez0NFmixU05/lo5KS3/zZbLEB5Wn2zodCdcV/kmaYoWCwWVvlml/PiOO4P/gzQNhg+aQiqfMUDrmy2cquP0PNbqo1sKLPzHrbZbLCK9AmO+mnAKnIs7TjaBEAPyvFsM5vN0NlszvMrsx+yp3Okj64LDPjAvlNQXjYWm/N+oEEDNM2rqtFVG8HS7123ctly27HabLCJ1E+DchwHOwZWvdz2O88zcz681U8LUaGe6QUFBXj88cexaNEiVK8u8YZSzuzZszFjxgy37Vu3bgV7gqU3A1zO7gC8vMd5qKvmnERihB4ZxdorSpMXrQPcLlsnwxfuxUMNrVhxUY9RDa3onhCYlo/eeXngW7xFd/gH7MmPx/XYthhevi0vNxfbOeevWcZuuC+G4z327N4NGXamSkty8jrH+QCAMpMF3LlMR48ew+0yyrLarI4HU35+Af5dvx7DNJBx79596K4gfVFRETaXX1f2tu3Zswc3T+ThHg9l2bVnL7gqTkFhIbjRiw4dPIgQSwHalv9OXrfORR4hjh0/gSuZybzpLly8jFOl/PsA57PQvv/AwYPIvOj6rGLnTU7Zhl6RjaG3mbBtxxGAOgYA6JSZCd65SjSNlE2bMdhe/oED6MLaXVhYhC2s+3mwxeroKLmyZWRkAElASgrLH5BF2G2fou/ptxBidQ20y/e8r5W7H53Kv2dlZWKvSJ/gqD8zE/uThY+lHVNZGdaXl5cQ0gNdsRfX4jphf3IyGl4/hdYicokh1G4hedkcO3Yc7cu/FxUVATSNKE6aG1HN8V/9N4CdJwCccNnX6uplcAf0rly+jGM8bbDXb6NptzbeVVTkqJe7z57v+vUs7ElORnGxb1eP8KuCVL16dej1emRlZblsz8rKQs2aNd3SX7hwAZcvX8awYc7Hpc3GWGYMBgPOnDmDRo1cT9nUqVMxefJkx+/8/HzUrVsXffv2BVgva4MHD4Y3eXnPRsf3e4cNRpuuRbh7vgYLsnL4K1XaHL3iIpNm5UU93hs3QHMZtECf+SkgcC90at0EdKvBwCHmd1yVKm7nT7f9JJDpZSFZdOnUETjvu/oCjcFDhgCHnb9Dw8KBwlsuadq0bQe4r5jjhl5vAGwmAEBMdBTuvnsQoMFE086dOwMCawLzERkZ6byuyq+1Lp06gU7q5dJWISxj18OwlN9/rVu37sA5123RUZEAZyJFu0GPQ3fpX+Aq85srjxCtWrfBbe0H86Zr1KgxGvTl38dXR4cOHUA34zwfWXkHDxkC0IMB0BjMGj7Sr/oFKL8ErO3HQH9oGfODotB/wEDgWHn5t98OsFwyIxt2drmfDSeNQFkpr2yJ5f1E//79YTTy23H0v20DTq3hbyML6qQJuMx8T4ivId4n2OtPTGTSSZyPkBAjq7zBMOc/gfjoBAymdNDtuwpcE5aLD7PZjJSUFNF288nLpnWbto77MTIyErDZAJNrmqpVqwrKpNu4A+DEJ66f1AB1B/KkL69fp9O7lWe4/I6jXre6yvPFx8dj8ODBuOnjSNp+VZBCQkLQoUMHbN682TFV32azYfPmzZg0yX1KbvPmzXHs2DGXbW+99RYKCgrw2WefoW7dum55QkNDERrqPn7KvahkXWQaYTQaERoSGEuD+LLdLtjH5IXGlkWMawa9HmDJraN00HHbwee07UUM+grl4aUtkfFu1xHF47RuMMi71ijWyacoSrNr1GBQdk1QcK/boKcAY4h05naPwZDUTVgWnjIotp/KkE+AWu1hTGgOpO10bJZ7LAwGg8s9wkZvMEBvNAK9pgDbP3bb795mvWBZojLpWMrS8PlAuYJEgYIxxNl+l/AoobHQDf2Ucz8793Pr0ukox3Y5cojK3HIo8Ht5Fopyf6bwFs3z7OGBomnXOquxYhOxnlVKr3XRdkvAvh+Ye859NEFXrZFw+3iOq16nY64tASjwtdFZr9u+iOpA8Q3oWgyFzoO2qsXv0/wnT56MRYsWYdmyZTh16hQmTJiAoqIix6y20aNHY+pUZnp3WFgYWrVq5fIXFxeH6OhotGrVCiEhMh5cAYI+AKeUpd4sxgfrTuN6gZfjAdA0sGQgMK8NsPEt4NY15fldN7jPQPH18Q3MkUrfcM/nzGdd1kCJpcw9nepz4sG5vJ8V2V9x/TwnVWeQWY7EBcHrpMzKE1uXFQlbuj5rv3dlyMSp+663gdcuy8+nKQKhCx5bDURyHf5FitFycoSRtVyU7HJVxEEKGEQioI9NBto/BvSfqXGVPMerX7kLTKen3Pc9twd4dBXQ3vNgzmrwu4I0atQofPzxx5g2bRratWuHw4cPY/369Q7H7dTUVGacuYJz922MKbhTEuNZo+dYHBrWiHT5XT3K3er1+cPt3bZ5SuYtpzL04Ne7sPCfC3j+Zwl7sacUZDJT5G+lAjs/B1Y84p5G9AHF2Xd1H/B5B9dO2deBCoN5mr99lle9rs5tVj4FSeScCC254EkHGFuXWXi17cNA+8eZKepq6f480GQAE9RPC+WbrwyXwKOs77Wk73tblwncCkTqZp2HcD5PP40QnUnHDn5JA09uAu79BqjbiS+xSCWBG0NHvgw+eJlrMpD5rMM6vtzzUyXJ+T2pBzB8ARP0UwjeNqk41reNAF65AAx2t2YisjrQpD+vtcoXBIST9qRJk3iH1ABg27ZtonmXLl2qvUBeYM7INrijWQ2HosS1IG15uQ+SXl/r+M23yO3t9augVmwY0m9pZ+FZsPU8Lt4oRESIAZn5TLl7L+VoVr4LuVeAXV8At93ruj3jME9ikRuN78bMvQRkHneGpycKku+wX8vsY85rQRI5JyO+Ao78LF6+csGYj3sXMp/XDqosB8AABRYaNgLDWJIWJDa12gGj1zAKnwhFITUQaRJYtLphXyD9EFCaxyh6StDa8kdxA0WCUYx4lSMAYTGM3FrQ8yWghRyXf4mOvvVI4NivQI/n5dXrbyXtwWXAtQPMffmjPZ4h5/yMWAhsfJNZ/sRrCFwTUmEh/ITfLUjBQnSYEQ93rocqkcwwIJ9CHGJwbjRbbWhY3dWqZNRR+PwROfOA5PPD7iv47/xNpJx0OsrzxW7ShB/vB/Z+A3wvNecD0haklGnum9kmcqIgKefOt9XlcyhI7AkCPOdPqKPlDltpNTzKLcYfw9rdnuPfzrsYs8g11LAPUE08CODuRpNF9+PFo8DEPUBtbZ8hqnC5PyUeOKN+YpY4eYhHgZaleLDS9JsuvIivknLvWwS8nibLuseUJ3JufXFdGsOBpJ6uAVy59cbWBkYudbUEi8J3jCTaEoCuJWIQBclPsC1I97RlJsP+PN55YVptNFY83RX3tXeGZTfodehQ34smcRaXbxRJJ1LKzfJpO1aTeDoAkhak/z5z32714xBbQPoYyKB+T+f3Tk8xD36l2I81+y0wvqVwOuUVqMznR9o8KJFA6npRfj0Vh9Rw/uB2RBQFhMUC8WqCX6g8/mJLXLD3SSkjiW2A53YDzb0709gVKR8yirFsaVWePwjE9RIDDHKE/ISBZUKa3L8pALgoP1YbjfiYMDzatb5jm9GHM6XWHffhHHk+RJ8nAjstJuZhu3cRY072JZXBgkRRQFSCdDr3jMxHh3FAyxHMcNlDy4FmQ/jTKcKTjsXNhKQsuxplEWCUw4Z9lOcT8kGSiY1ieUyYvPCCoxk0xwfJg3vHW0NXWpcrVl4Fs6o4USN3xWorUZD8BM168IcZ3WMXWcvHudhruRn1vjtdBl0AX8hCDxtrGXB6LZA8BTihJOS+FjJVVAWJfSwpdQ9re2dnDGN8Hdo9AlRtAAz7jD+d4vJVXouhnDd8peXU6Si8b+Bs4X3soTChOnn9Wz3slNnHt8DPLzhSeGq9qNECAGBr9YAGwvChteIVKBYkLZ/rgdIm70EUJD/BXuajWpQzPMHobozFaMrAZgBc/YF8qbS8n3wKX24rj3xo9vK0f15U3HzLhgHbNFgnSw0VVkFiQVFQ9QCVq3hovUK6FN25Ez80vH+6ia2lxvanUvKI1bDDkeNn4zdUKuJsxm8Gnt0Buukg6bRqFE9fWpD8ZVXx9BzYZ8YZwsXTaVmnjwluBYm96KSPZxkY9Tocers/Dk/r72IZmj7sNmyafAee6d2wXCynXHofW3U+Wn8GSNsHvJ/A7xTtTZRM82eTdUx4nzfJPiOdRg59pmpTjio8tCC5befxg1EKd7FWudni6gNtRnlev8cI1cnnpE2L75eBedJhZnizucrhzXLLDAAgsnzRbdlOu1xk1qnm2RsSCdRs7cVzqrWCFCgvUByLMe93mTS+Cxi3HnjpuKdCBSzBrSC1Y8Xf4ZuW7GWqRIYgLsI1uKVOR6FxfBSo8hufbUGiRB4G4TzDdFpAp5TPbOJzivYqYk7agfKwYbFNZMhFCU35l6bwGi6rjHs5kKNca4oGnZ6tYV+ecjTuTN18rOzV+NGCFFuHUY7c2i6z7CfWO7+/dBx47Yp4LBwxZJ9Hb7+cBoAFSUwGf1lVPK2XooD63RRO0ScWpIqDjhW23GbxnxwitExk/CjY1/LiMR3RsX4VvDnY+bb30/gu3KyaYLZYpRMBwI5Pgb9e0O7B4u+4If5C5x1FVxaqfYSE8slVULwwNZjv+tG6IxrxJTDgfZ4dMhQk3mn+XrzmKRnXVVgcEB7n/G0Idf3tKe0eZT7veM11e0De60EwxKY0HpYWkCG2CgS7M6JlKgI+JjbCiP1v9cOx6QMd2+5qkYBVE7qjdhXn2G/7unH4bpxAoDUPOHI1z/H9nTXH8cOuy/wJN00HDiz1fPaYzQqU5ounCcgHqkbI6cg0hWNyV3NsBdfT4w6xqfFBEpCnTmcmDo1OaG0mFTFalBIex+PnBJkWJIk4SFpf43KOvebTvjnHe9h84Nn/gN5TOOm8fD8Hgg9S/e7C+/ylNCjxHZKLZFsqloIUEJG0/Qa7M+Ku5RVA8C07AgAW1vgbRVFeceJml7hs1xUAwOPdkoQzeDq9eOkQIHWXRKJKrCD52oKkZoitSgMmcrkjn5eHzvjy2ePQhEYDJV6K/K4FitrsTQuSDDm83VHrDUDNVu7bK/MLjx32moBuVNAhtiCAWJDsBKJfiwRhBtfTZ+CE535vBM/DSCGUwoe22aryYXdpO3D1gAzlCJX7gaqRBcna6xWZKYWcNkVoeAdng1wfJC88kB/5RX5an3UIMixI9kCa7LXQqjdlJagEFqSK3AFr+Yzp/SoQrSa+mJfxx/mpYJdEcCtI7GnNAWxBEuLO5vEY3Lom3hjMRMc1cAJJWqy+V/q+/Oe8uozLhgLf3ikzcSVWkDRalNHW+zWcTZCz5hQLbz8wteyA63Yu/+wE9HnDvSreDs4fHYJAm0OjgKnXgJfPAE//A7R7DLjvG9/L4ZrIe/WLEoj3sw9lqsiKpGIqVluDW0ECnFakAPVBEsOg1+HLRzvg6d5MYLowg6v1waLBomqCFiSbjfE34sRI2n3RB8Mdld2CNEGGFU0GtJyHEc21IMk5tjJnSKmdRSaV7K53eJUi6XJ99HB2qUekztAoxhG6VjtgxAIgppaPZBJK46fuIBCt91o+YwJJAarMz04vQBQk+5BGBbQgcWmeGO3y28a6Gfo1r8FN7hl7vwEW3QmseMRls9IhOQIHnR5IaAnE1JZOK4Hic6H5tGy1TtoS9JoMhERIJPKnBYk9xKayTl86aXcrdzQfyDcjz6NK5SXzdqftMnQpFw1lkmxfAClQ3qJma+az1f3+lUMhwe2kDTAdkhUV0oLExajX4fiMgZi0/CDuaFoDJWZnm756tD2avL1Ru8r2fs18XtisXZlyqcxvQXaF3RNlojeP/1GDO4BL//AkVuGD5FaEzPPhrTdpueUa+Cc7aA6lgYKkNWLX04D3gJ6TgchqvpPHl/SeAtjMQHMFQ86+fMYEyjWiCQJtGf0ncH4z0GKob8XxEGJBqkQWJACICjVg6bjOGNejgduQmxoEb13WA9emwVCeMiqxgmQf8vXkocnn6G1/g+PCncUmp2NwSyNziE2N0qe2o+LLV6U+UFtkfbXKjNixpyjvKEduzvxCePl+DolklMB6SmLF+XKIrTIpSAJEVAXajASMXggt4EWIgmR/cCwdWuksEw91rosuDaq6BJQUYkjrRNnlWqw2lwfultPXVclH4MGh3Ag8NGu1B6o2lCiDJ6/gta1FJG2ZeGsttoTb5Kcd7wuLp4D8HZ8EarYBhn4qoww/zGLTmraPACOXAi9KLP8TiM9dLWUKxPYRZEEUpLJbzGdBOlBW4F9ZNCYixICVz3TD+N4SHSqA+Bjn8ENibJjjO58fS7O31+NmsdPiNunng27paZpGWk4xaJsNOLtRu7XKAGDdq9qVFWjYZ7GJKStefeBqGVTPy0t92Gk2mAlC+My/3ilfivsXAw37SqeLrgk8ux3o+IT3ZeLiDwVJpwNuuxeIqyeRMBAVCDLERiAKkiv+msXhY3Sw4TbqMnRwzh4pszi/x4QJRSdmsNpoXC80OX63o53Kj/1WX7zjEnp9tBUrf/4OWD4SWNBZG+ErO1IWJJqG9MNbwQPXq8tbaOGkLUM+igI6jAES2yovfvot5Xm4tH4AGP2H07LX+gH+dEqOtT8iafuLQLSwVNZZbLJnnBIAoiC5EojTTTVkeH0rGlSLwJuGn7A29A28ZfjRsa+U5dAdE8723ee/oWysS2eF4R23/e+tPQUAuHlqm2dCBxtyfJCkHt68eWUMsalGYydtsXSdxssrQ1YHx1NPaIy88vl4Zjvz5481rqQIZAWpsluQAnkWW+9ya/ygD/0nQwATyHeN76kEM9nEuLMWjY0v9sSThnUAgCcMzpW7q0WGOL5PurOJ47vQrWuTeVPLisVDcCIZSVuOBUmAto+4b7OqWaRZ7TR/udeCSDq+pSq0pFoj9XlDo4DENiLt9KMiEMgWgspgQbprmvq6/Hlu7nwTeCMDaCQ3SG9wQRQkNrbKbUHio0qEEUvHdcKkvk0wuHVNfPN4B9zRVDpmklXg0qFA49hVDYYtghWptdhoWkY/a3/gshLSNDBsHjB2LdDEufAxrCa4INUxPLqaXyY5aGLF0DpWE4vQWOV5vIYC+SfslE5DLEgKUShTr5eByaf59wX6LDbJmGLBSyDfNb6nkg+x8XHw7f7o0ywesRFGfPloBwy4raasfLTIpTPsix2sdAH85hqISPkgcS1II5fxlFH+4aK40EwcoKSegMFpLYS1TJl8TfopeLvmphNok5LhxEC2hEihqQ8S6zjImcUXiApS3a7Mp5L4RL5CjVUrRmAmcCBZyCK8HOuqIt+fPATgXeNHKvkQGx+UwAX9ysBm4vkgT5n096OBDo2WThRIyFmLjf3AjayuohLWObeaVeSXiVdii2nwAG42mPns/LTnZfkLpR1RICpI49YBb6QH5kKulXUWW2JbZjjwvm99V2cFhkTSZhOEFiQhJvZphKu5JaAO8z8oQiCv8/O7BUkfIp2mwsGOXcTX8Ukcc3Ye7hCbHNRGrtbCSVuL5VDuXwyk7gKSenHKllm0arTsdP2tIMldt08EnY4J4hiIqLX63L8YOL0WOPGbc1ugWVV6vexvCSoMAfha4UcqSTRtj0g/DGSfAUVRmHHPbYLreRnB79zrnt7PD4eKqvQKPVRpcKJf89zCUoEi2fvdFCQNI2nLjZor2hl54XoKiQAa3+U61MhXldYo6nQDfJr/4DnMZ8/J2pYbMKg8/q0fAEZ+pzBTgClQBAdEQWITDENspSIO1EU3gW/ucMQsCjEIXx4h8OLQjJYE0vi/VrQdxXwmtpMx640H9kK4cofY4m9jprDzIbSMiRsKOoJGdzGf3GEwuW/jlfG8s1FsldC4E+48Hnj5jGeztwKR/jMBnREYOk+7MivyUK5cek4GohOBni/5WxJNIUNsbCqqtUEm9W7+A+Mno4UT5F91fqdpgKIEH6tGSs70cBqNqHQlInqBitpRijhp93kDqNMJqN8DyLkoMy/rONzxGlCQAbQeCax8zDWZ0Eyuge8xU9i5Zb2eBsj18xLq1PkWkX34ZyDrBKMEuhYiry41550CUK87kH5IeV5fE50I3EqTn94bPkjR8iZ0VCh6vAB0fQ7Qa9U1UtJ+goE2BKeGfu8wynJlaAsLYkFiB56r5NP826culp+4/A08Ppp/BfR9tuaSRUzS/4Gh+t3y6/QGAa/0qpjZZQgBmg8BwuMAHc+DXOohFRYDPLAEaDYIsHEU3dq3A90muecRssiEeRBYEQBi6gCPcUMHUIzSVPt2d6d1bz+A73wL6P8u8L+D0mkVo6Gy/sgvjDI3dq289IHopB2oaKYcQd71WlmUisrSDhbkrhnysfOtuZIPsdkgI8aO4zujWMRH8zs5X6fjeLfbb5Em1FVMMf6qUEIvQNtg0QWgo3ZsXWDKOeDRVcrycRUVvdiyMGqsKBQw8H3pelXB8wCdfAKo19WzMrQkJALo8bxnASO1QOp4J7QEnljHhG2QQyXsvCoElX2ot5JDFCTA+cYQ8NYGz7Do+a1BvNiPhcD9rRPYYXfS/i7kIyWieQ8a2NnoNX9L4U79HkBUvLxp/S5wjruOT0GScNJWgyb3hkwZxGYeVmQfJH/KFFHVf3UTJCDKa6BCFCTA6ega6LPYrBZg6VBg/VR12XUSCtJ/nzm/S1jTdBJxkBJxU65YXobGrYgk31aZIGM5DEdHL/RwFNje7TnX37yRt2nOpwZooSBJlXH/YiC6FvDQjyKJZC5xU108jlfQMPxLJu5Tlwn+liRICUBFnSAb4qQNODuZQLcgXdwGXN7O/N09W3F2SQWJHbtD4lgITf+3o6cC5MFA22DTGWGr0wW6q3v8LY07ciwiU84B4VWAnEtA9Sau+0SH2LSE5v2qrAiJ+6v1A8yfGBLHyzJ2PS6s+xINu0yQGlD2A364J9o/yvwRApc6nfwtAUEAYkECnA6Mge6DpHRZCA42SoE+LNGZCQ2x3aPfiQZUhhKxtCG2Hv/28nbQdTr6UBg52NcDkXELRsUzilCNpu4KAp+TNi8BMMRmkBkXyQPo2h1xutYD/DPjKhKBOERI8A5xdYHnDwGvXvK3JAQOREECWENsAW5BUsu5FOj/mgS9rVR+Hsdwo/NBPbFPIwyqa0XrarTgENt9+h3YGuqHSK1V6vNvt3c0gdbhSA2xyfW14fNB4murv3yQxiYzn3e+pY3SUpGdjQPtGiQEDlUbEj+xAIQMsQHOh26gD7GpfcD+9AB0ABQF9Xc4aTvrfLV7LLD7cQDActypThYvkV5gRi3ePXYFKdDOrd2CpNAHiYvIlGRNVQm1xy+pBzC9PDhpjhZvyBVYQSL+KARChYJYkACWD1KAD7H5Ej5l7Np+x1cpHyRfcy07h3+Ho2MPLHmdeNjhV6QhNi3OgVctSIGkfAXq9UogBA9EQQKcQ2wBZ2Xg4sOHJu0+xMZGLzGLzdc0o67y76BpFJoReMMbjhE2LwyxeeM6cTl+AXYsCQQCwQsQBQlwOsr6e5r/rWvMVP49XwNHVrjvZ3dSB7/3riy0DdjyPnD9JGujs9N+0PCPd+tXSD4ieLdToPHmfgOsVh+eW1nKmAInbTHELEgugT8DwYKkhYUmkKw8ClFyDgJNoScQghDigwQExhDb5R3A0iHM0gv2NdHaPiSc/s//AbeLrKvmKemHgX85wR4D2EHWSutE+85bIQmo4TNplHRung6x8SlY9jI16mQpHdD4Ludv1Z13oA+xeRui9BAIFQliQQICY4ht/xLmM19gqAiAVx+wBZmc3/5eZFYZQmEH7Nxs4UVlkouc64jicdKu3YGdwBMBPMjLYfgC4I0MJg6Tp2hRRkW2IBEIhAoFUZAA50wgi8l/Mmg5Nbs4B9j+CZCnYLXvTTNcf5cV8CQK3M6JkghMadWHIqf5w27bv7IM86xiY6S7H5AiRZt1TId/qU6GqdeAF49LJFKrNFGAMYyzSeV1EF4FGP0nEJWgUhYP6vYn9bozn20fUZCJWJsIBH9DFCSA6eQAwFzkXzm4cBUkuQrTn/8DNs8Evhskvy5ToetvXgUpcJFa+uT73alYfzzTbftHllGeVUzp3DttRT5IrLzhcazdChSB0Cggopr89J7iiX9MwzuANp4c8wqoII39mwkCGN9cfp6KHuiSQKgEEAUJYFbwBgBTsX/lcIPbEcnsmC5sYT5vKbAgcSkrlE4TQEgNsa3cf413Ow0dMuNuBwAUhqqwbOh0cOu0lQyxueQV+i4DtkIV6A6+d7wGdBgLPP6H8rwV0YKk08sPAtjnDaDRXUDzod6VieBdBs5iPocv8K8cBI8gTtoAYCxXkMw+UJD2fA0c/AF4/DdmCQkHKobYbDZXJ938DCC6JtS9ZXPq2vOVe5IA7pykFCQxBmQ+i766wygwRWBJyMfKMlN6HguSnCE2HguSR8fXPa/LFk0dqz1UwEKjgGGfSafjgwq8FdY0pc9r/paAoAXdngPaPw6ExfhbEoIHBIQFacGCBUhKSkJYWBi6dOmCvXv3Cqb97bff0LFjR8TFxSEyMhLt2rXDDz/84JkAIeVDbCYfDLGtexXIOgZs+0BGYokhNpvF+f3wcmBuc6Z8JR2tWcHyIwE8vCE1xCZGPqKwxtYTxXD62tBy28o91i2HK/NBojywGonJAeBaXGfWL5VKTXSiunxac/toILEd0MiLEdwD+AWAUAEhylGFx+8K0sqVKzF58mS88847OHjwINq2bYuBAwfi+vXrvOmrVq2KN998E7t27cLRo0cxbtw4jBs3Dhs2bFAvhC8tSHYsLMWkIJOZ5s9F0oLEUpBSpjGfe7+Boo52z0Im/lMFX4fOEwXJDk07j5uNcwzpsFjePAWlFldlauQyyFJG+DpjF2uSdBGczKzvTP25UU2cm/Qhyop7eCWzfpo3FRIl3PM58Mw/gEFhOwgEAkElfleQ5s6di/Hjx2PcuHFo2bIlFi5ciIiICCxZsoQ3fZ8+fXDvvfeiRYsWaNSoEV544QW0adMGO3bwKBhysc/SsSixpngIW/n5pBlQlM2Thtvpi1iQ1A6h5F8DvugEnFkrnTaA37C1kMzlCLKO52/Wnvi87jzePCarDTb2sacoZU7akttkInBurHdNB6o3Zfx+lNDsbqD3KwF9zgkEAsGb+FVBMplMOHDgAPr16+fYptPp0K9fP+zatUsyP03T2Lx5M86cOYPevXurF0RfPmPEn9P8eVEwxMZGSaeWcwnIuaBMrABE3tIn4seFbQlif6dAY+4xBbOK+IbYuENVUhYkxfDntXWdBEzax/F3I/BiVLScM4FAqOT41Un7xo0bsFqtSEhwnT2UkJCA06dPC+a7desWateujbKyMuj1enz55Zfo378/b9qysjKUlZU5fufn5wMAzGYzzGYzAEBHGaAHYCsrhLV8m7ewR8yx2ayOuvhW02JkNIF9iiir1eWEmU2lgJEpwwDX+MmUowyzYPkAYDMVydaSbSfW+N/kKIAWi+cKlSBWNuVytJnjbbBZ3dQV8zM7gdxLMC5mhqysNhtsZjNgsTjOj9liAcqvCQPteg4lsTnLsVptjjxSednXhqx6AOhtVsd1IDePr5DbbjbUA99Dv/VdWEZ87Tj+FQ017a4MkHYHZ7t9RYWcxRYdHY3Dhw+jsLAQmzdvxuTJk9GwYUP06dPHLe3s2bMxY8YMt+1bt25FRATje9Q46xJuA6A78hP2FsQjK7a912QfXv559dpVHEpOdtnGZcP6DbDqnZaL2rmH0ZG1f8umjSg1MtGJ7zaVwZ7Swup09/wyFz1F5Mm7kQWZE5ChO/KTzJS+RxMfJAErjJRdx2qzwT63Kjk5GQNLS8AJrYjkzdtB08CI8t9XrqTiWHIyYosvo0/5to0pm2AxMFaMO/LzEccqU1p4m+M6Onv2LM7mpwAAUlJSRLOxrz1Z9QC4/eo11FWYx9dItduNem8DB68CEItkH/gobnclgbQ7OCgu9m0oHr8qSNWrV4der0dWVpbL9qysLNSsWVMwn06nQ+PGjQEA7dq1w6lTpzB79mxeBWnq1KmYPHmy43d+fj7q1q2Lvn37olo1Jriebt9VIH0lAKDrxU9hfvOGp00T5hDzUad2HSQOHuyyjcvAgf2BkCjHb+pEKXDZuf/OPncAsXUAAIYzIUD5iJvBaATKl5XreW6WqDhVosKBQAv/pAJPpvnbERtiE0Ov1zuO/eDBg2E4+7Ljt53BgwfjjT9OOBSk+klJqDtwMJBxBDjDbBswYCAQFoMNJ7JguBIFlDjzSgtvAw4zX5s2bYr6XfojJSUF/fv3h9EoYkNkXXuy6gGg//NvIFdZHl9hNpvltbuSQdpN2h0M3Lx506f1+VVBCgkJQYcOHbB582aMGDECAGCz2bB582ZMmjRJdjk2m81lGI1NaGgoQkPd/UeMRqPzwgoJd9vnbXSludBlHADqdhFMY9TrAbYsetcYMEYdXPeXo8SThaIF/JgqGFoMsbFhlyamfFGs/0D5tcPjg2Q0GvHrgWuYU25a0uv00BuNgMHgkubyLRMmrTiCP0OK0UbHKlNSYKeMep3OkcflOpdA9nVPOQdaA/XhrKTdlQnS7uAi2Nrt67b6fYht8uTJGDNmDDp27IjOnTtj3rx5KCoqwrhx4wAAo0ePRu3atTF79mwAzJBZx44d0ahRI5SVlSE5ORk//PADvvqKJ7ChXFjDWG7ranmLcxuZv0d+EUkk5aRtFcinQEWqJIH3ChCOMHg2Pi0c+8j1uNtoCjqKM3PNJbmSaf6u5VzLK5HOK1oegUAgELTA7wrSqFGjkJ2djWnTpiEzMxPt2rXD+vXrHY7bqamp0LGiRRcVFWHixIm4evUqwsPD0bx5c/z4448YNcqD9Z3Y6x4pjRfjKWfXC++zd7RlhUDabsDGUQC0mMVGBarbtTLCo6sChfkelSF3iO0A3QSdqLOO3yaLDXYb5JfbzuMZlk+SaH00DbPVBucVR7mGDNAQk4WxaoUYtDjfAb6UCYFAIGiA3xUkAJg0aZLgkNq2bdtcfr/33nt47733tBXAyBpi0/vaXCmmzJR3RCseAS7942rpAgBLCfDj/UCdThyrhRIFSX7SQCaqai2g8DLvvuaxNpy+Ja0YuHb7FM83hhO2JHTSMQqSFTr8bu6MRwxbcNyWhI/Wn8FjoSbESB5XCi+uPIzLx3Zjjf2SoyjYaLss/AVM/e0Y1h/PwKLRHdExSci93rUlVhuNbrM3g6KAPW/0g17n4UmvJEo1gUAgiEGedABQg7XKtq+HKsQ6G7vSc+kf5tPK8bM6uQY4vwnYNptTpiIvJAVp/UDVhtJp4uoD98wX3H1fA3kz3IRnsbkqHMfpBo7vNugw0/I4XjBNxGOmqbzp2RTRjJL7U05zrDmcDovNVbGVsiD9vDcVucVmPLBwF2Yln8Ks5FOguXk4v28WleFmkQk3Ck3IL9FgmqyvrawEAoHgBwLCguR3qjg7PJTk+rZuMWVGarillD2kVFmHPWQocC8eFd0t9y1gUOtE4Kz7dgMnhICVdpZoA4VShGKNzRlMQSzkQI+y+WhIZeDgsRruOynKXdkR4Zt/LwIAhrZJRJs6cc4dtJBvGvDOnyeQEBOKN4e0lF2PGwZuEAMCgUCofBALEgCwfJzY0+r9j0RnaRWK/K3EKhTgipUGFr0omaOm8dHsxWqdhHCcv9nrtHHXbAPEZ73lIRoH6aYCeynHknh8JVis/IpXQSnHF43jvM/Wuf48ko5F2y+h1MxVohQcZ4OCqOIEAoFQQSEKkp365RaA20b4uGIPLEhWgeGSYgVxnKyVY5q/GOEy7aTVop0dP3u4zcgJakSDbUFyv4W4CtJk07PYcU7GOaHEh9gW/sO/JIxbHk6YATOPYuWWR4kiShQkAoEQBBAFyU6jvsynrx1QRTsmCQWJO6tNDYJWqEDBuz5SG1/qjY8eaIPz7w9C1Qj+jt9IuSpILhYk2l0+ijXE9re1C36z9cb3uy5LykIDcLokuZf74+5U3nwWG438Uta1wFGQLFb368hq4ypIzHVfWGbBR+tP4/i1W8KCEgWJQCAEAcQHyY5dMeJbaNQX9fIhaUHSQLkxB3gYbSWWjWf/A86uA7a4z3Lc8HwPGNb/DnB0jKYJ0WiaEA0AiIt0Oh+7WpCY4ajrdBziqTzstjn9d/gsSBTPr40ns9zScVN3nb0Fg9rWc6vf7pdU4jYsxvDKr0dxo7AMl+0jhLQV3+28gg3ndEj++TCGtq3tlsfGuczNsQ2waNt5rDmUjjNZBfhy2wVc/mAIv8jc2ZQEAoFQCSEKkh27osLtOfyJlLLGHmJTGz+nIENdPp+hQEGq2Yr541GQGtaIhLFGlJuCxKZOXDjvdvsQW6+yeQhHGfIQ7dhn5R1iU3cNZRdZsHTnZbftDaYmo0H1SNwSmIF2o9B1dqPFYsGsLWcA6IAb17Hh5HW3PFb79fLUFmDHXDx2cRD2rD8jT9AIuav3EQgEQsWFDLHZ0ZWH9vO1BUlUsVHpg1SZ8GHYBZ1AfCC7gvTWiNtdlCOAPzSAnhVlW1ptlZf20o0iyZLsmCzCs9jsWGw2FJSa8couA3Z0+Ax78qvILh+tHwSaDgIGaByPjEAgEAIIYkGy468hNrH6fDHERnDCOt7hoUbAxFhmjLCgSoQRj3WpB5PFhnf/PulIxzeLLZuORQ2K8eEpoeUPR7GVrcO2RmivO6+4CQCw54K7xYiLzQZ8mnIOvx64il8PKFzB3hACPLJClWwEAoFQUSAKkh2HgiT99q0pogqZlJM223mYlTY0FigTcbKtUPgnkCW71joxBhx8uT8oisKTPRsg3KgH1jH7+IbYxpheQ3LoGwCAOZYHVdU6xzIKeXQU1tk6K5b96s1CyTRWmsbFG9LpCAQCIVghCpIdyl9DbCIKmZJp/uzYN75W8ryJh0NslvsWA5dUZr7jdeCfD2AcNtdFjs4NnMNRNI+CdJJOQlLpcpmV8LevGGH4zHq/InHtiMVhsmO10ig2VaLrhEAgEDSG+CDZsXeAATXEJiHLtf3O7yaWNcBWmTo+zxQkusVwJald6+07FZh6DWh2t0uqxvFsJ23P5MultQ9MKsdJvPecrdh7KUdWebeKzYoifCvh37PZmLfpLGzcsAMEAoHgZ4gFyY5jFlsFGmJTVWYFw9dr43EJFVdg+Kb5KyEd1fGK+Wnk0xEelcNGjgVJLtvOXMfY7/YBAE6/ezfOZhWgWc1ohBr0bmnzS824mF2EBtUi8eOeK+jVpLrrEig8jF6yFwDQvGY07m6VqJncBAKB4ClEQbLjmMXm4zdZT5y01ZRZ4fCTgiRTMaNBoV3dOBxOy1Nd1a/WPqrz8qGntDn/NE1jVvIpx+/mb68HAHRpUBUT+zZGr8bVXWb+3fnxPy4hB37afQU7p97lUuYPu69gw/FMfP14B0SGOh8/2YVkwgGBQAgsyBCbHX/NYjv0o/C+tZOBf+YoL7NSKUg+hOYMsYnRbRIAoOSOaVg6rhNSXuqNNwe3wKG3+7slHdomEasndEe/FvEaCiuM2jhMXDaf4p8Nt+dSDsYs2YsXVx7G9D9PoKA8ijc3HlP6rVKk5TCBSG02GuuOZeDtP45jx/kbWLLjksuwWlSou0XKFxy4kovx3+/HlZvywygQCITggFiQ7PhrFpsYF7Ywf0oJpDZ4ip9H2AQZ+D7QZyq6lQ/BxUWEoEl5RO4nejTAkv8Yz/CX+zfF/+5qAgAID/HsdhvUqiZqx4Xj2x3iXudaKUgXbxS6L0nC4s8j6QCAfZdz3JQjO70+2op5o9oh+ViGSzTxm0Uml0V2w43+eRTd/9VOAMC13BIkv9DLLzIQCITAhFiQ7PhrFltF59HVXq7AixpSRDXPqhXwTzLqnZkn3dnYuV0gEGX7enEyKgN6NamBt4a2RMPqkaLp+HyQ1FivZiWfxoVsacvKifR8ZOXzK0gA8OLKw25LrSzdeRkD5v3j+P3P2WwM/mw7Tqbn43pBqWJZPeUysSARCAQOREGyY7cgnd8E3FIYOC+YiRRRMsRocQ8QFiedzltO2k0GAGP+4mzUxv9Mz1KEKJb8LWvF8KZ/qFNdWeUayss1WZ1K/KS+jd3S8VmQdP52dueBrVT9vDcVJzPyMXj+dnR+fzN+2Z+G1QeuIiufUZZuFZtx6UYRHv5mN7afy9ZcFpuvfQ8JBELAQ4bY7LAXjV39FPDEev/JUpEQs8KIUaM58MB3wLtS+Xk69qgEoFBo8VexolhlPfqr+36XPlK9QtG/ZQK+3HYB1ViL3wLAmO5JKCi1oHfTGvhlXxpW7k8DAMSGG2WVa3eIblUrFldzSwAAiXFhbun0PAoSW6mqCLy66igAoEZ0KD64rzWeXOYMabHr4k1smnwHCkrNaF+vCrLyS/H30QzEhRsxpJU6Py8SZYBAIHAhCpKd/GvO76m7tC3bamH8ggyVcBX0SJWOxzYLoJdx+fFZPu58G/hzknTe5kMVCsXqJT2wuLSvVwVrn++J2pzFb416HV7q3xQA8NOeK47tfZvHo0+zGrhRWIbj1/IFy40qn/X17ohWqBEdioc718PB1Fy3dIdt7lal4rKK6ZeWXVDmohzZ6TeXGZ7bPfUu9Jv7DwrLGH+mgpLmqAIgp8iEq7cK0aG+vDXmvBXniUAgVFzIEJud0jzvlGsxAXMaAe/FA5tmqCuD8s8MH1kY3S0YsnBZJkUMHkVFrfLS7lHmM7GduvwKuK1WLOIiQoQTsFeGMeixdFxn/DWpJx7tUg+v3t2MN0v/lgkAGKvKuyNaoWWtGJeO/a6yOZhuHo0rTce45a1oFiS5XLpR5FCOAGD9Ccay+PzKI7j/q53YeCJTVjliFqQFW8/jhRWHAi6Y5bGrt7D74k1/i0EgVFqIgmTHworDIsc3Rg5n1gPv1XAqXzvmqisnrp428niLISra5ZEzvEoFqU5H4KWTwFObvFeHTF7q3xTVIkPwUr+mzhopCu/f2xoT+7hbgLa/2tfFt8kOu8u+QNfGUuvdsFJG9GtewyXdrHtbIzIkgBVtlWw65TrUuvtSLiw2YM8lxrK2pnymHU3TmPjTAUz59QjMPMqimA/SnA1nsOZwOrafv6FItjd/P4a3/jimKI8Shn2xAw99sxvZBcIO8gQCQT1EQbLTnTVk0+hObcpc+Zg25ci2tviJjk8AMXVct/WZKp5HbsRyT5yL+SxFsbUBvYDPj0sn6V1rQd2qEdj/Vj+80K+JaLrPHmqHf1/pi7pVlUXanvNAa5ffLWvF4MDb/fFUzwaKZQ1kFvOEPPjqlFMRNOgobDmdhbNZhUg+lolVB66iyZvrsGDreRfrG00DTy7dh/fXnhSs68L1Qmw7cx2rDghP4ig2WZB8LANpOcX4aU8qftydilvFZt60JosNNwXCI0jBtmZdyysRTCcWpoFAIIhDfJDsxNQChs4D/n4RsHj4Rma1MEqNViED1CpIt48BDi7TRgY7XZ8Ddi9w3UaVr1u25jnntvaPMe3/50P+cmS1iYKbJadaE2ml6dn/gPMpQNeJ6vUcH/ikUCLt+HZ0RxxPv4V72tYSTSckZlSo+60dZtTDGgS+NufzncdrzeF0rDmc7mZ9m7PhDE5nFrhs23z6OjafBt4c0hIAcDarANdZM+1m/u1UntrUiUXThGhwefP34/j90DWX0A0Wm+tzICu/FKk5xXjz92M4m1WIf1/pi3rVlCnAFpbiw2cRA4CZf53E6oNXseHF3qgZq3IonEAIYogFiY2x3Kn2zFqgWN5Cnrws6AzMrq1dwEYr/xuoJC3vAe75QhsZAKBed6DvG/z7uMqgzgB0GAfoBRzT45tL10fpgJ4vOn9HJwITd8NFaYqr756vZiug50sV2im+X8sEvNivqahyBIg7F7ep6t5xsi0KKS/1dtknFV+pIsNnSfmrfPiNi9lqw4srDmHAp//iscV7eNNcvuEeN8lqo/H7IWayx6HUPOd2zjnqOnszRi7chbNZzALT609kyGoDty47Jgu/grTkv0u4VWLGN/9eVFx+IGG22rD1zHUXXzMCwRcQBYlNOGvGy7UD6svJuaDtsJhNpYJE6Vzb5Cmt7gMMAm+i3I46JAqISQTeuOaett904Pax0vVROqDFMOdvYwQz8y2xrXPbkynS5cjGd0NsWsE3gmJXqfomMh1nIst6wO5Ym3AsINEyww0AQO+mNaQTVVBaTluPPw7zK092ikyu9zdN02g7YyNvWrOVOeaHUnNxMj3f7VZR4z/PtkpdzS0WTasmxtOtYjO2nr4OSwA4989NOYtx3+3DeJ7ZjASCNyEKEpuGfZzfTYV+E8MNq0pli9Ixlhyt0IeIDG9xFaRyawSfv0/Pl2RO8edenuV1JLQExq4F/ncQiE6QLkcu7JhOFUM/EhWzYQyQ/L/uSJl8h2ObWGfZSiCQJQA83tVpqasVG4Zl4zrJDnBZ0bArNGIUcsImlFlsghYOs8WGglIz7v1yJwbP3+62n3tOdl64gaeW7Ue6TN+i11Yfw77L7uEe7KgJYTDqm10Yt3Qflu26Ipru+LVbWLD1vKAVSwt+3psKgIl/RSD4EqIgsTGEMhGWAaAsgBQks8plECidPEVEDjVaAK1HQvbsLi0iN3PLYD/ok3oC1Rp5Xgcbl/IqhoYk1fk1iY9y8UeyiHT+A26r6bYtqVoEhrZJxMzhtzm2zRjeChRFoXG8+1IrrwxshssfDMHeN+7CEz0ql0M4m7f/OI4fdjPKw/WCUpSZhRWEm0UmLN+TKrjfruz8d/4Gen64BY8s2oNNp7Lw2uqjKDVbMfiz7Zj+5wmXPFwl7tsdlx3ft525jk7vO2dqqrmS7f5Zfx8Vt6QN/XwH5mw4gzkbTquoRTm3is3YdeFmpY5bVWKy4khaXqVuY0WBKEhcQsof+oFkQRJDJzIsQunE9wtRJcn1d0wd4LndQEiEsOLjjZvZzYLkA1o/yHz2fMn3daugSwOn1WtkB2Ym4USe5UfsiDlpt64d67Zty8t98MUjt4OiKIxoVwtN4qPQq0l1AMCQNolu6cf3aggAiI8Jw7RhLXH5gyHyGlIBefuP47iYXYjO729G25n8w2sAMGn5QcxeJ6xA2IexHv12jyNCOgCk55Vg3fEMnMzIx9Kdl13ycH2qSi1Oi9bY7/a5TP0/mJqLW8VmnEi/5Zg1J7fztSvXP+6+gp4fbsHFbP7n4qLtl7Bg63kAwJrD15D0+los/U98UWUxzmYV4O55/2L98QyXV7LhC3bg4UW78dtBnqH7SsLji/dg+IL/8Ot+suSVvyEKEhf7AqRqLUi+1vp1IrFtKL3yIbb4loCR66wrp02sNHW7uO5qPVKZDHaEhti8yYivmFlwFURBal0nFr9N7I69b9yFjx5og2PTB6Bd3TjB9H2bMZHPo3lmuVWNDMHuqXehZaJzqE3Hmv0176H22PhSb4QZmWsuMTYcR6cPcOwf0a4WQgzB9Uj5fMt5yTQZt8QX350vUgbXUlRUZsHyPalIOekaAHPnhRy8sMvAOyR2/Fo++n36D4bM34EO723Cir2puOeL//DsD9J+lpEhzHXy1h/HcTW3BDP/PgmrjUbGLffhvzkbzqDYZMELKw4DAKb/dRKfppwtb4fNobT9czYbh1JzYbXRePib3byxop7/+RBOZxbg2R8PIpcVJuHyTcbf6i8ByxZN0xXe8rL/CjNc+vM+YasjwTeQaf5cjOXTbS3C4/+i+PzmFBnKonTiChQfz/4HfOM6u8mlTYIWJNYQwxMbXPcN+ww4xrP2mRRsB21foTcws+AqELfXczriR4eJWwyHtklETLgRLRIZB+1WtWNw/Fq+wxpUMzaMN0SAHe6suhhWfUIhd8KMOpSKDEHZ+eKR9pi0/JBkukDCPmvNG1AU5RJD6dOUs7h0owh/Csy+A4D3ks/wbmdblF7/jVFIjl27BauNhl5HwWajMWXVETSJj8aEPs6h5ohQ1+dHQakF//v5IJKPZWL5U5wXIcDtPH+2+Rxe6t8UIxb8hxPp+Vj+VBeMWbIXANCrSXXsungTuy7exJhuSYgNNyI+hplQkF8iPjEllye2FE3TGLlwFygK+OWZbpIzQHOKTNh+LhsDb6vpUPq1orDMAh0FRISo72IDb3lp9VhtNIpNFsnnU6BBFCQudqditbGQtIp9JIeuE4EDInGO1ChIOp38pU1q3e78LqZEhciYPt7mISaEwN8vAhe2MNsGfyxPDoJsKIrCHawZaN+N7Yz1xzMwon1txza1sZKEHMB/eaYbPlp/BkPaJGLqb05rQZ0q4biaW4L7bq+NaUNbIi4iRLaCFB1qQEElmvbNF4bg/PVCvJ98yvH7s83nNK+3sNSC2Agjdl646Ri2eqqX03fsbFYBvt3uDBNw4IrTGfyrfy64lSc06+1EOrPG4CPfOsMmbD/njEze/9N/AQBHpw/AmkPXkC5hdTuSlgebjXYEzHxrzQlk5psc1pe8YjOqRIos9QPgkUW7cTqzAON7NUDThGiczizAW0Na8CpWNhuN4+m30LxmjKSVtMxiRat3NsCgo3D2vUEuVlgl6LTw4wwQ7v9qJw6n5WH31LsqVEwuoiBxscftURt7yFcKUscngLtnAwd/EE5D6YSjRoshd2irx/PKy+byzHbg2n4mZhJFAb1edipIoRwn4ApuOg9EakSH4vFuSS7bnuvbCE8s3Y/h7WopKkvo9LSpE4cfn+qCk+nOhXj3vdkPNaJDUWq2qnp791Q5alg9Ei1qxWDtUeUxiLzB4TThWWjeJL/UjNgII3KLnUst3WJZb45fyxdcQPlclrsbAlsBYtchl7YzNsq+zUd+vQu3ik0YXhNYeczVktfhvRS8dndz3FYrFmFGHTomVXXsu55fig0ns1iO6BnIuMX4S/VsUt0xDM1mwdbz+CTlLO5tXxufjmoHgJltWGaxuaW/Vu5HZrHRMNtsCJX5knr0ah6qRTljt1Ui/QiH0/IAABtOZGJM9yS/yqIEoiBxsQcXtFYACxIg7shMUcp8kOy+Qtwy5Tyx1CoviW2YPweV6KlQQbmzeQL2vHEXakQpC7QpFW9Hx7qs7C/VXOUoIkSPYpN7gNXE2DAXX54hbRI9Um5eH9QcpzIKsBaBoSDd/9Uuv9SbcjILvZvWQBlrmn6ewNIoXDLz3a0856+7K01tpgs7sHNR8hixW7M+yXZ/xtlouDjGX5w12GHJeXzxXpzJKnDLAwDZ+fzP/U/Kfal+P3QNn45qB7PVhkcWMcrgkWkDEBvhfBFlWwP52nMxuxC1q4Qj1KB32XbPF/+5pKMC8FlI07Tk0KUYco1pF7ILsfX0dTzWtb7mw59KIAoSF325WZa9eK0SfKUg2QM2il2sOr38WWyj1wAN7nDmc0Ghk7Yn+GPmGsGNhBjlZnCpzo09ZMC38C4A7HnjLuQWmdF7zlaX7dyH5NtDWooqSEnVIhwOvUIEm0M5H+zlU+z0m/uPHyTxLiarDddzy/D0D/vdlKOCUotLOi4HrrivqlDIylNosrgqSKwbgb0kTKnZiscX78G+y7no3bQGvn+is2Pf8XQeK50KPSS3yIRJPx9ETJgRD3euJzug660SMw6n5aFHo2ow6Pnvi9wiE4Z+vgND2iTijcEtAABpOcU4du0WBrWq6VCcCkrNmPHXSQxrW8tlOB+A7OHGuz5hrsH8Ugsm928qkdp7kCcEF7uCpNSCVJwDbHkPuHFWe5nsRLGCIjoUJDELkoI4SKExTmWL64Mk57Wu1QOAIRxoPpR//9hkoGoj4PE/xMsRfTshQ2yBjJQFiX1mhd5Co8OMvOuSsdc2q18tQtKPIeXFnrzbPx3VFmO7J6FPs3iEchSkMKP7vfTq3c1E6yFUDIrKLOg9Z6vb+nsAXAJ88gW8ZPtK2WEPG9psNCxWGxZsPY9DqbkuscYsVptjrbzPt5xzBPT892y2S3l8dwN3m9VG48CVXJRZhJewWvjPBfx3/ibWHc/E6CV7YbPROJNZgFSelwUry4froW92Y8ySvfjuv8uCZX+38zKu5ZW4LF3T66OtmPjTQXy0wTk54PMt57HqwFWHMz4bpX5V+y55sOSXBhAFiYvBriAptCD9/RLw7xzgmzuk06rlSZap2j7bTuyCUxJJm12Omun1kdWA11OBUT/y70/qATx/EGjUV0oQ900RTNwdNJTKS/AnUgvHsy8xIQuSnZSXemNCn0ZY+XRXPHNHQ7wzzBmo0j70Z4/H9HDnum7lA0CjGu6TA4a0roXp99yGEIPOxYL0+cPtseeNfm7pIwVmIZ2cORCn373bJcyBnWY8i9hyeVmjt+K6VcM1Kaey89IvR2Sl41v4l21hAphhpkGfOSOil1ms+HlvKuZsOIN7v9yJa6wI6O1mpqDJm+uw/ngGDl7JE6yX7zFOUYwSY1eIFv5zAfd/tROvrToqWE6J2VV5Ss0pxsB5/7pZZEtMVjR6IxkN30jGd/9dwqkMxoL1x2H3WZmH0/Lw4frTojMLv9p2AT/svoJTGfm86xTaUeqvTvv5pZgMsXGxO2krHWJL3e1ZvU0GAuc2iKdhW3aMMixIgPwhNnY5aseYDeKzRmRRszUACohxzqrC09uA038D7R/3vHyC5jSsEYmL2UUY1tY9cCQbttVI6kHZJCEar93NLGjcpWE1l312S9Wi0R2RcasUDapH4vW7W+DbHRdd4hL98VwPpOYUY8j8HQCApglRLkoR24KUGBuGWJ616ISG4ezTt/n8I9a90AurDlzFq6uFO7L2rNAMnvDVox0w9PMdmpRVmeFabIQoMlnx55F09GxcHVXLZ8EVcJzMswvKXPzkdl64ibOsYbtneOJLPfvjQbdt7689iT2XcpiQBDwvhnnFZgz7fAdOZuTj2PQBWFQ+m/CPw+mYc79rKBK7RSs8xPV67PPxNsf3Pw5dQ9XIELSrF4ed551WsRl/OYdZKYpxSL9yswgf3t+GCRC7wNU3Soi3/zjOu93GenNiPwOW70nFifRbeHd4K+h0FPKKTVi0/SLuu72OMy/N5M8rMTvOhy8hChIX1U7aHmq693wOfCLxVslWYozlb453fwCsflJAJFp8FltINGCy39isG5TrgyQ0dOKNWWUhEcAb6a5yx9UFuk7Qvi6CJvzxXA+cyypwicfEB7sLUDOFuWlCFM5mFeKetszsujCjHg2qM1ai2AgjRndLwo+7r6B1DHPvRocZcVstZ3TwXk1c/SHqVXUO5VUXcEhvyrIG1Y4Ld7EOCKHTUXiwU118vvUc0nL400tZ0OTSiif6OUE988tDKXRKqoJfn+0OAG7nsPOszS6/p61xXQZGLou2MzPn1h7NQESIu6LNHg5sPX0jGtWI5HWgN1ttuH1mCiw2WtTn6MWVhx3f+V4GAOa+nFM+XHbf7XUEXxCOXb2FhjwWWj7Yfl3s+/6N35mQH52SqiIy1IBf96dh48ksLN7hjMBO0zT+t+IQ1h7NwKpnu6GBtHFWU4iCxMXeMSud5u+psiBnKihbQYoun4LdcoSwggRavNyarYHUne5lq4qkrSEh7j4ohMAlJsyIDvWrSqZjvz2qMVL++mx3HL2ah+6NqvPurxEdil2v9cGG9etcthv1FMxWGj2buObrlFQVE/s0QtXIECSVK1r9WsRj06nrjjQd6lfBp6Paon61SEz6yd0KwCU6zPlI5fqzTOzTCP9v797joqrz/4G/ZoYZYLgN95tcRUUEuQphKl5IRLe07Cua64X1krfKpdRod9VqC8oy2zJt28wubtrulu7PjFYRNI28Y3lNEcSKi2KAiMow8/n9McxhzlyYgYYZBt7Px8OHM+f6+cyZOefN5/ruwSvY+FhCp6saiGUdq/gVUzd9iwhvZ1w2ML2KuXxUUoFsE+YtrNboxbnj+E9ovgO8e7Acowb5cI3BTS0pazAyECegapdkyINvm15qqVltueVQOeKDZejv3T6Ei2bgBvAHG21pVXKdMf5+8AryJll2fkcKkLQJuxgg/dYgwpTeW0IRMPkdoOo0MHBC234d3GmZ0shcbQbaHU3IUzU2r2sbmI7GHyJmoDlCd1dKkNwcxTqlQNr0lcwcWjUWl2qacH8Ev6pOKBRgZVs1ntq6R2MR/+JeAOBKpx6OVxX5G/sVuDrY4eDK9nZyd7SGK5iWFITl6QMhsRPiqEbj08Wj+2NTcRmc7e14DYYB4MKLE5D/1QWdudgAIDNad3Jhff61KBUNzXJEB7ph2T9PcoMpko6duPorb2DM7nL6pwadIEGf2xrfpz/vOgfV4/sSNhZfMbhPZ33/U4PZjqWmOV3OuapGjHv9gMlzNJ7WSM/l601cI3dLoQBJm7pRs7KTA9FZqgQpfqbqn+Yyg2lSdtxI2z8OuNpWv6z5wHIPAZ44Dqx1a3+vNz30ZzAxnbeLPfIeiYGDWAixga7E3cHX1cHkYQs0R1/WntPL2E98yZgIyKTt+zdqNe61Ewm4KgvNn87KjEGYNyIMjmIRvi2rw3sHr+BoxU08PiocDmIR7gv31BsgGes1qBbm5cRVIWYM8aMAqZfRbpjdkzTeleMXE6qlTXHl+m0s/MSyUxFRLzZt6m7xSkuXIHWyio1b1kGQolQaboPkPRhI0Gj0rO/Y8/aquu0/+oHxtBFighnJwVyJTE8XFeDKe2+oR82+nFFY82AU5o/gF//baZVm2WmMlKk95IGXsz2c7O3wQJQvPluUih/Wjkdu21gzmveW//2xfZ5E7fhosEyJRaPCINEKPjVL637LKMbH/6zby6+nGDvItPF+iGUNXfs/vZ0IQp/90gqp6TwKkLSpq6Sqf+hcT7bfWoJkShVbZ0tsmFK1zyrdGb6RPF8rKNNz7KBkYPo2wMOy9b6EWNOeJ0di7vBQ/HVKDG+5oZ94hI8Lsu8P0xlg74PsYbz3mtV//rKOu+drTuqpWUWh2XZDe1gFFzHw9AMD8ONLmdimMZGsSOO+YajRbZiXE96cHsdblvdIDB6I8sVHf0hGRf4kXkN27arMZzP5VZWW9resocY3IqSTKEDSplkl9c9pljuvnVYvmpFP625j6iSyagFxqv8dZfrXdzj2ESF9U1SAK9Y+NESnW3Fn/wQaOcAb+3LaS3zEovbfW6DMEe/PScK/F6UaPY5mI1d+YMJPkWbApNlLSaj1056Tqltl/vG8ZIyJ5M8pNiM5GO/NTtLbM0q719WitP7cuFTWYK813MKYTpQoJYca72BA+qYe8VTcuHEjQkND4eDggJSUFBw9qjsCp9p7772HkSNHwt3dHe7u7khPT+9w+07TrJK6UmR4Ox2duH1O/1R3mU4bJH0jh3XycnU4Ua2Afw5qT0RIh7TbJJmio+lVxg325U2iaojmyMz89PDfax5dczwc7fP+aVIUPl8ynHs/f0QY+rlL4aLRiH5GcnCHadJscK/2YXYyTq/WHTjTmEVp/XlpnWJgkmQHsRCbZibgv8vuN3pMzYFFjdnx+H0I9zKtyzrpW6weIO3YsQM5OTlYs2YNTp48idjYWGRkZKC2tlbv9sXFxZgxYwaKiopQUlKCoKAgjB8/Hj//rDsCaJdoN2pWmtgArjM3T68ujqJrzlIegVCrBIkCJEI6MrVtALu4IJnJ+2gGJ10d+ygzxg9+rg54OD6Qt1x9x1mRMQjezhJkBrWXNLlrNBbX7jEosRPyxqwa2pYfgUCASTH+CHBzwJ8nDUZHnPQESEKhgDcnmaboQNe2dOmu1wxO3KVibJgej7xH+NWb785KxIUXM5EZ449AI9WTk+MCEOrl1GHJUEqYBxaOCsf/WzYCAoGgx00p09PS01dZPUBav349FixYgOzsbERFRWHz5s2QSqXYsmWL3u23bduGJUuWIC4uDpGRkfjHP/4BpVKJwsJCvdt3mk6AZGpvtk4ESKYGIwuKAEeNwfdM6elmgGJ8Pn+BTr4oQCKkIznjB+LdWYn4UGOSUWM0q+m62nPPxUGMw8+OxRtZcbzl6l5sS8dE4PDKNHhqdNTzcJLglakxePXRoQZnQ3/7sXhk3x+K38W0j4C+cWYCvlk1Vm8ApMlJz8CGau/NToKrgx3en5PELUsb6I0tc5OwNydNJ/iKCnBFblsbptenqfI4IzkYPi7tzQ4yhrQPaaA9WrSaun2VeviDjTMTMNdAo3QXBzs8N3EwYvqpeuoamyZH7zGMfEbaYjoxqKdmGzRzUQepxHRW7ebf0tKCEydOIDc3l1smFAqRnp6OkpISk47R3NwMuVwODw/9fy3cu3cP9+61j4rd2Kiac0Yul0Mu19NTjQmg+dWU32sGmPEbmx1jJocY8tZWaH/95XI5b5lCyaD0iYFgyt9h9+n/te2nAJhumtX7KSasg6hgBe+Y3Ou4OZD+79n247c0Q6lQcPvKFUpA3+ehh3qfVoUCzMR9rEX9Gei91r0Y5dv8+RYCGDvQs1PHdxABny1MVvVoUyogN7VEWg/tXV3t7bh0tLa26qTrkTj/DtOaMdgbGYO9oVC0QqF1bGPJdNSY2NddKuadY/QADxx/bgxvYNB+MgeM7K+6R8+5LwhZiQG40dSCn+vvYJCPFIN8gjE9KQBSSXueNNtsaR5fpFVaP3+QAnK5HPuWj8DFmltIG+AJuVwOmYMQM5MD9Q+RoGS8Yyq0PwATdLZ7faueed4MkdqZ/w/WmABXnPm50ezH7c2sGiDduHEDCoUCvr6+vOW+vr64cOGCScdYtWoVAgICkJ6uvwtqXl4enn/+eZ3lRUVFkEp1R2x2ulsFzSP9r+ArtNoZr5+eqBXgdOTAgQO8cxyOWIUbe/Zgssayy5cv4ULzHng3noG6tcCegq/1VrOp9ys9X4ZEjeV79uzRux0A/Hj2e/z0ixMeaHtfVFyMOxLTGlmqj3Pq5Cn8Um7+v3S6w969e62dBKugfPcc10ybL9WouQMEOFQjRJL4GvbsucZb1/35Vj0yGn6tg7oC4snIOzr3GrUnooBLjQI4VJ3Gnj36P4A95/WfaVo/4O9NIjwUotQ5/qNhAtxpBcb3UwVLmvn+qn06PlQ3t6f54VAFvqhQlT7V1tbwjtmiADztRQh2ZjhVZ/wP4sWDFdh0vnMl+vUNjTC1pP7CD6UAOj6+hz3DzXumB1Iut67qPeaUEAV2XjUtL7MHKPDRpc7l21XM0Ci3zRoKmx4oMj8/H9u3b0dxcTEcHPQPBJebm4ucnBzufWNjI4KCgjBmzBh4enrq7nDzCqDxgx0/bgzgZDxwsDsrAkwcFSAtLQ2s3B2CO7+CObghOaut1EdjDKyIAQMQnjYRgitSoEy1bOLESfqr59r2i02+H/Lxj0H05R+hTHsWE8PbR/WVy+W84w8MD0FE3BigbZ7CMWPH8SeI7UjbceIT4hE3eKJp+1iJXC7H3r178cADD0Asto1gzhwo37033/p+cZbK91Ml/wMAeHt745MlQyFXMnh24ySiixnjlUSpqT8DY/luVSjx76oSuDqI8eq8ZHzxF1X6fX19MXFiPG/bhyYxCIUCnKysR3XDXThKRPj4u0osHxeBqe8eAaAqOds6NwkJwTJEna3BE9s7jnq/WHQfHt6smrJD4uiEAS4CXKo1PNu92rBhSXjvoupG6+Jgh38vTEFewUUsGR2O/Reuo67pHuprfsLen00PPJ55bAIGnq7CM/9RTSq7fFwEUsLckRTiDu+vf8R7hyqMHiM5MQEfXWrPc5inFOV1zdz7idG+2HOmhrePr7szGjvIs4eTGDdv98ySbqsGSF5eXhCJRKip4X+gNTU18PPreBj91157Dfn5+di3bx+GDjU8Boa9vT3s7XUnohSLxfpvJFrtBMStTYC441nKVUz/oorFYmDul0DRyxCMeU5vOkRCEURiMWDXfonEEgM3opj/A2rOwW5Qhmq4gIX7jTYuEynvqY7PpUkCdPLGaicUdnofazF4vXs5ynffYql8CwRCeLr2nDkTDeVbLAYKlqdBKFA1QvdwkuDm7Rb0c5ca/JxS+rcPETA+OoA3p95H81IwrK3x94Nx/XDrnpKbdFXbNyvHIEhjQuS7rQp8vmQkdpb+ghd3n+swPyKRCAdXjEF53W2khntCYifE1j+oxrZKDveGXC7H4s0/cdtPGuqPK9dvQwDVdB5qAW4OcHUU49VHh0IikeDRYSGYmhSsE3Q+nRHJBUjL0wdgw75LetPlaM//zD5ZcB/uz9/Pvc+I9seCUf3x8DvfcsucjbSnchTbAdAfIP11SjT+vPNMh/t3J6s20pZIJEhMTOQ1sFY3uE5NNTw+yKuvvooXX3wRBQUFSEpKMrhdl2j3Rvvvk6bu2Lnz+A5RDcLoa6Q7qikNuqf+A1h8WHcspY603oPWeL6m70sI6ZMc2toeWXPMo84SCQVcQPD8Q0MwMyUYf3zA9J7Emr0Pte+S04cFYVykD4b2022ArRkcAUBziwKezvaYNyIMb2TFcsu1eycCqsdQsKcUaQO9DQ7uqfmo2vhYAnY/MQK7nxiBd2YmcMunJvZDwfJRGNpP1p4HPc8UB7EIkX4uEAqAP2iNCK95PO3G7IEyR+x+YgT3vuleK+KD3eHlrPpjPiFYZnTIiGGh7ph1n/7prH5vYLmlWL2KLScnB3PmzEFSUhKSk5OxYcMG3L59G9nZ2QCA2bNnIzAwEHl5eQCAV155BatXr8Y///lPhIaGorq6GgDg7OwMZ2dng+cxmWcE/33lt/q302buCV25L7GJgYsJgdQ19+EI+rUtPwMndH2gSL8Y1Ujj/ccY35YQ0mvsf3o0jpbfxO+GmlKq3vM8GBuAB2P1j7NkiOboDNq3WaFQgPfnqkZMNzR9xv0Rnjh8uY4bJgIAb5iFN7Li8MUp/jA1zg7GH83ajxx1IDdRo1fiAF8Xo8dR2/3ECLQolJBK+OfOjPbDs5mRiAuS6R1iIVqjd971W6oOUZ89noqPSq5iUVp/+LraI8RDisEBrjh65Sbmf3Sc237x6P5YNKo/3KRixAfLkPOZqvrunZkJCPdWtf19ctwA/K1Qf4lWd7N6gJSVlYXr169j9erVqK6uRlxcHAoKCriG25WVlRBqDAW7adMmtLS04NFHH+UdZ82aNVi7du1vT5BQCPz+P8AnUzu5o7lnvDd/ic7JkMfh9/vNEN+5DgQmAo2/aJyuE+dbeEBVAiXpOUXshJDuFyBzxBQ9JR69Gb/ExbT75Ja57TUbm36fiG8v38DoQe0jlYd4OuGf81Pg0VbS8uNfM1F2vQnHK27icm0TUsKMDyDaUZ+4L5YMx8nKet4QDsbYiYQ60+UAqvxrDub5zcoxeKXgAi8Qiw5U9ZCb0DbEQri3M9Y+1F47khKuau+rOaq7t4s9Vk1on6JGoVE8pXnsnAcGIueBgVaZv83qARIALFu2DMuWLdO7rri4mPe+oqKi+xMU0YVJGeXNxrfpCmNVcJ0hEACuAYBnSPt7bl0nSpCEIgqOCCF9Toin8fvevBFhGBvZ3jPb1UGMCdG6gcrwiPZqSomdEIP9XTHY3/SxiqLdGYqrAJmewTfjg90Rr1FK1VX3R+h2ZArykOLtxxJ4y/6zeDjqmloQYGQQTx+X9s5U2qOxm7sSxhx6RIDUZ0g9gZbbgGsnZjN38gKeOg1IzFB92CFqg0QIIfp8s3IMmlsUvAl7DVF0ZdTJLhjgxvD5ohSE+1h/AEh7O5HR4AhQVcfFBclQeq0eb83g9yLUbrOlbf/TadhXegWPb/gtKe0cCpAsKecCwJSAXSe7xbqHdktyeCE7TTVCCCF6GXt4a7o/wnIN2GMC3bq112J3lOrsXKp/Lr37wj3w4pRoDPTRXxgQ7u2MqQmBeNz8STKIAqSuYqw9qDB1dFxjgVHoSKDim9+Wrq6iAIkQQrrsu9xxuFhzC6NsqIefMZas9hIIBAZ7s1mL1edi6/EkenoBVJ8BXo8Ejr2ven9ks/59RZ3odg8As//b/toiAYtmCRJ9FQghpKv83ByQNtBbbzd6W8XM3vnIttBT0ZAJbZO7BsTprvs6F2iqBr7MASoOAV8/p/8Y/rH6lxui2cTf4m2Ces+PmhBCSNc9mxkJF3s7Xk+0voiq2Axxa2tIrTAyf8j1i4bXBSYAPx01X5q6Uy/6q4cQQkjXLUrrjwUjw3mDZPZFVIJkiLCt4ZtCawj0ujKg/GD7+1/LDR9jzJ/Mny5z6on9KgkhhFhdXw+OAAqQDBO1Fa4ptQKk3cv57799y/Ax7E0fxdT66MdACCGEqFGAZIi6BKn6B+DNOKClbSDIuw2mH+O3VFsFDev6viajEiRCCCFEHwqQDBFpdMn/tRwo3aZ6bWq1lLiLI00/cRKY/inQf2zX9u8Me40BxkSdHJuJEEII6cWokbYhIq3Bt/Y8oxoF29QAadrHqv9HrQAOrjP9vJ79Vf8swVEGzNihqk7s7OCVhBBCSC9GAZIhQj0fzb41gI+J3R7Vc5UJROZLU3cYNMHaKSCEEEJ6HKpiM8RglZOJJUiso7mWCSGEENKTUYBkiHYVm5qpVWzStuHmaXwhQgghxOZQgGSIvio2wLSSoYmvAT6R5k0PIYQQQiyGAiRDDFWx3ehg5Gy1YfM13lAJEiGEEGJrKEAyxDWg6/tStRohhBBi0yhAMoSCHEIIIaTPogCpu3lFWDsFhBBCCOkkGgepI4nZwIkPftsxoh4G0q8BQSnmSRMhhBBCuh0FSB2Z9DogcQJK3u76MYRCYMRysyWJEEIIId2Pqtg6IhQBfkOtnQpCCCGEWBgFSMYYGjCSEEIIIb0WBUjG2NlbOwWEEEIIsTAKkIwxOCcbIYQQQnorCpCMoSo2QgghpM+hAMkYTxrHiBBCCOlrKEAyxq2ftVNACCGEEAujAMlchjxs7RQQQgghxEwoQDJF+JiO1zv7AuGjLZIUQgghhHQ/CpBMMX0bkLmOvyznfPtrBxkQ+TvV66D7LJYsQgghhHQPCpBMIXECUhbyl7kGAG7BqteRkwAnL+C5KiD7K8unjxBCCCFmRQFSZ2R9wn8/fx/w8LvA6GdV7yVS1dxrhBBCCLFpNFltZwzIAIJSAO9I1XsXXyB2unXTRAghhBCzowCpM+wkwLz/WTsVhBBCCOlmVB9ECCGEEKKFAiRCCCGEEC0UIBFCCCGEaKEAiRBCCCFECwVIhBBCCCFaKEAihBBCCNFCARIhhBBCiBYKkAghhBBCtFCARAghhBCihQIkQgghhBAtVg+QNm7ciNDQUDg4OCAlJQVHjx41uO3Zs2cxdepUhIaGQiAQYMOGDZZLKCGEEEL6DKsGSDt27EBOTg7WrFmDkydPIjY2FhkZGaitrdW7fXNzM8LDw5Gfnw8/Pz8Lp5YQQgghfYVVA6T169djwYIFyM7ORlRUFDZv3gypVIotW7bo3X7YsGFYt24dpk+fDnt7ewunlhBCCCF9hZ21TtzS0oITJ04gNzeXWyYUCpGeno6SkhKznefevXu4d+8e976xsREAIJfLIZfLzXaenk6d176UZ4DyTfnuGyjflO++wNL5tVqAdOPGDSgUCvj6+vKW+/r64sKFC2Y7T15eHp5//nmd5V9++SWkUqnZzmMrdu3aZe0kWAXlu2+hfPctlO++obm5GQDAGLPI+awWIFlKbm4ucnJyuPfl5eWIi4vD/PnzrZgqQgghhHRFXV0d3Nzcuv08VguQvLy8IBKJUFNTw1teU1Nj1gbY9vb2vPZKISEhAIDKykqLfMA9RWNjI4KCgnDt2jW4urpaOzkWQ/mmfPcFlG/Kd1/Q0NCA4OBgeHh4WOR8VguQJBIJEhMTUVhYiClTpgAAlEolCgsLsWzZsm47r1Coapfu5ubWp75Yaq6urpTvPoTy3bdQvvuWvppv9XO8u1m1ii0nJwdz5sxBUlISkpOTsWHDBty+fRvZ2dkAgNmzZyMwMBB5eXkAVA27z507x73++eefUVpaCmdnZ0RERFgtH4QQQgjpXawaIGVlZeH69etYvXo1qqurERcXh4KCAq7hdmVlJS9S/OWXXxAfH8+9f+211/Daa68hLS0NxcXFlk4+IYQQQnopqzfSXrZsmcEqNe2gJzQ09De3Xre3t8eaNWv63DhKlG/Kd19A+aZ89wWUb8vkW8As1V+OEEIIIcRGWH0uNkIIIYSQnoYCJEIIIYQQLRQgEUIIIYRooQCJEEIIIURLnwuQNm7ciNDQUDg4OCAlJQVHjx61dpK6LC8vD8OGDYOLiwt8fHwwZcoUXLx4kbfN6NGjIRAIeP8WLVrE26ayshKTJk2CVCqFj48PVqxYgdbWVktmpVPWrl2rk6fIyEhu/d27d7F06VJ4enrC2dkZU6dO1Rmx3dbyDKh6cWrnWyAQYOnSpQB6z7U+ePAgHnzwQQQEBEAgEGDnzp289YwxrF69Gv7+/nB0dER6ejouXbrE2+bmzZuYOXMmXF1dIZPJMG/ePDQ1NfG2+f777zFy5Eg4ODggKCgIr776andnrUMd5Vsul2PVqlWIiYmBk5MTAgICMHv2bPzyyy+8Y+j7juTn5/O2saV8A8DcuXN18jRhwgTeNr3tegPQ+1sXCARYt24dt40tXm9TnlvmuocXFxcjISEB9vb2iIiIwNatWzuXWNaHbN++nUkkErZlyxZ29uxZtmDBAiaTyVhNTY21k9YlGRkZ7IMPPmBnzpxhpaWlbOLEiSw4OJg1NTVx26SlpbEFCxawqqoq7l9DQwO3vrW1lUVHR7P09HR26tQptmfPHubl5cVyc3OtkSWTrFmzhg0ZMoSXp+vXr3PrFy1axIKCglhhYSE7fvw4u++++9jw4cO59baYZ8YYq62t5eV57969DAArKipijPWea71nzx72pz/9iX3++ecMAPviiy946/Pz85mbmxvbuXMnO336NHvooYdYWFgYu3PnDrfNhAkTWGxsLPvuu+/YN998wyIiItiMGTO49Q0NDczX15fNnDmTnTlzhn366afM0dGRvfvuu5bKpo6O8l1fX8/S09PZjh072IULF1hJSQlLTk5miYmJvGOEhISwF154gfcd0Lwf2Fq+GWNszpw5bMKECbw83bx5k7dNb7vejDFefquqqtiWLVuYQCBgZWVl3Da2eL1NeW6Z4x5+5coVJpVKWU5ODjt37hx76623mEgkYgUFBSantU8FSMnJyWzp0qXce4VCwQICAlheXp4VU2U+tbW1DAA7cOAAtywtLY099dRTBvfZs2cPEwqFrLq6mlu2adMm5urqyu7du9edye2yNWvWsNjYWL3r6uvrmVgsZv/617+4ZefPn2cAWElJCWPMNvOsz1NPPcX69+/PlEolY6x3XmvtB4dSqWR+fn5s3bp13LL6+npmb2/PPv30U8YYY+fOnWMA2LFjx7htvvrqKyYQCNjPP//MGGPsnXfeYe7u7rx8r1q1ig0aNKibc2QafQ9MbUePHmUA2NWrV7llISEh7I033jC4jy3me86cOWzy5MkG9+kr13vy5Mls7NixvGW2fr0Z031umesevnLlSjZkyBDeubKyslhGRobJaeszVWwtLS04ceIE0tPTuWVCoRDp6ekoKSmxYsrMp6GhAQB0JvLbtm0bvLy8EB0djdzcXDQ3N3PrSkpKEBMTw41eDgAZGRlobGzE2bNnLZPwLrh06RICAgIQHh6OmTNnorKyEgBw4sQJyOVy3nWOjIxEcHAwd51tNc+aWlpa8Mknn+APf/gDBAIBt7w3XmtN5eXlqK6u5l1fNzc3pKSk8K6vTCZDUlISt016ejqEQiGOHDnCbTNq1ChIJBJum4yMDFy8eBG//vqrhXLz2zQ0NEAgEEAmk/GW5+fnw9PTE/Hx8Vi3bh2v2sFW811cXAwfHx8MGjQIixcvRl1dHbeuL1zvmpoafPnll5g3b57OOlu/3trPLXPdw0tKSnjHUG/Tmee91UfStpQbN25AoVDwPlAA8PX1xYULF6yUKvNRKpVYvnw57r//fkRHR3PLH3vsMYSEhCAgIADff/89Vq1ahYsXL+Lzzz8HAFRXV+v9TNTreqKUlBRs3boVgwYNQlVVFZ5//nmMHDkSZ86cQXV1NSQSic5Dw9fXl8uPLeZZ286dO1FfX4+5c+dyy3rjtdamTqe+fGheXx8fH956Ozs7eHh48LYJCwvTOYZ6nbu7e7ek31zu3r2LVatWYcaMGbzJSp988kkkJCTAw8MD3377LXJzc1FVVYX169cDsM18T5gwAY888gjCwsJQVlaG5557DpmZmSgpKYFIJOoT1/vDDz+Ei4sLHnnkEd5yW7/e+p5b5rqHG9qmsbERd+7cgaOjo9H09ZkAqbdbunQpzpw5g0OHDvGWL1y4kHsdExMDf39/jBs3DmVlZejfv7+lk2kWmZmZ3OuhQ4ciJSUFISEh+Oyzz0z60vcG77//PjIzMxEQEMAt643XmuiSy+WYNm0aGGPYtGkTb11OTg73eujQoZBIJHj88ceRl5dns9NSTJ8+nXsdExODoUOHon///iguLsa4ceOsmDLL2bJlC2bOnAkHBwfeclu/3oaeWz1Fn6li8/Lygkgk0mkJX1NTAz8/PyulyjyWLVuG3bt3o6ioCP369etw25SUFADA5cuXAQB+fn56PxP1Olsgk8kwcOBAXL58GX5+fmhpaUF9fT1vG83rbOt5vnr1Kvbt24f58+d3uF1vvNbqdHb0O/bz80NtbS1vfWtrK27evGnz3wF1cHT16lXs3buXV3qkT0pKClpbW1FRUQHAdvOtKTw8HF5eXrzvdW+93gDwzTff4OLFi0Z/74BtXW9Dzy1z3cMNbePq6mryH9J9JkCSSCRITExEYWEht0ypVKKwsBCpqalWTFnXMcawbNkyfPHFF9i/f79OUao+paWlAAB/f38AQGpqKn744QfeDUZ9442KiuqWdJtbU1MTysrK4O/vj8TERIjFYt51vnjxIiorK7nrbOt5/uCDD+Dj44NJkyZ1uF1vvNZhYWHw8/PjXd/GxkYcOXKEd33r6+tx4sQJbpv9+/dDqVRyQWNqaioOHjwIuVzObbN3714MGjTI6tUOhqiDo0uXLmHfvn3w9PQ0uk9paSmEQiFXBWWL+db2008/oa6ujve97o3XW+39999HYmIiYmNjjW5rC9fb2HPLXPfw1NRU3jHU23Tqed+1due2afv27cze3p5t3bqVnTt3ji1cuJDJZDJeS3hbsnjxYubm5saKi4t53Tybm5sZY4xdvnyZvfDCC+z48eOsvLyc7dq1i4WHh7NRo0Zxx1B3lxw/fjwrLS1lBQUFzNvbu8d1/db09NNPs+LiYlZeXs4OHz7M0tPTmZeXF6utrWWMqbqIBgcHs/3797Pjx4+z1NRUlpqayu1vi3lWUygULDg4mK1atYq3vDdd61u3brFTp06xU6dOMQBs/fr17NSpU1xvrfz8fCaTydiuXbvY999/zyZPnqy3m398fDw7cuQIO3ToEBswYACv23d9fT3z9fVls2bNYmfOnGHbt29nUqnUqt2fO8p3S0sLe+ihh1i/fv1YaWkp7/eu7rXz7bffsjfeeIOVlpaysrIy9sknnzBvb282e/Zs7hy2lu9bt26xZ555hpWUlLDy8nK2b98+lpCQwAYMGMDu3r3LHaO3XW+1hoYGJpVK2aZNm3T2t9Xrbey5xZh57uHqbv4rVqxg58+fZxs3bqRu/sa89dZbLDg4mEkkEpacnMy+++47ayepywDo/ffBBx8wxhirrKxko0aNYh4eHsze3p5FRESwFStW8MbGYYyxiooKlpmZyRwdHZmXlxd7+umnmVwut0KOTJOVlcX8/f2ZRCJhgYGBLCsri12+fJlbf+fOHbZkyRLm7u7OpFIpe/jhh1lVVRXvGLaWZ7Wvv/6aAWAXL17kLe9N17qoqEjv93rOnDmMMVVX/7/85S/M19eX2dvbs3Hjxul8HnV1dWzGjBnM2dmZubq6suzsbHbr1i3eNqdPn2YjRoxg9vb2LDAwkOXn51sqi3p1lO/y8nKDv3f1OFgnTpxgKSkpzM3NjTk4OLDBgwezl19+mRdIMGZb+W5ubmbjx49n3t7eTCwWs5CQELZgwQKdP2p72/VWe/fdd5mjoyOrr6/X2d9Wr7ex5xZj5ruHFxUVsbi4OCaRSFh4eDjvHKYQtCWYEEIIIYS06TNtkAghhBBCTEUBEiGEEEKIFgqQCCGEEEK0UIBECCGEEKKFAiRCCCGEEC0UIBFCCCGEaKEAiRBCCCFECwVIhJA+JzQ0FBs2bLB2MgghPRgFSISQbjV37lxMmTIFADB69GgsX77cYufeunUrZDKZzvJjx45h4cKFFksHIcT22Fk7AYQQ0lktLS2QSCRd3t/b29uMqSGE9EZUgkQIsYi5c+fiwIEDePPNNyEQCCAQCFBRUQEAOHPmDDIzM+Hs7AxfX1/MmjULN27c4PYdPXo0li1bhuXLl8PLywsZGRkAgPXr1yMmJgZOTk4ICgrCkiVL0NTUBAAoLi5GdnY2GhoauPOtXbsWgG4VW2VlJSZPngxnZ2e4urpi2rRpqKmp4davXbsWcXFx+PjjjxEaGgo3NzdMnz4dt27d6t4PjRBiNRQgEUIs4s0330RqaioWLFiAqqoqVFVVISgoCPX19Rg7dizi4+Nx/PhxFBQUoKamBtOmTePt/+GHH0IikeDw4cPYvHkzAEAoFOJvf/sbzp49iw8//BD79+/HypUrAQDDhw/Hhg0b4Orqyp3vmWee0UmXUqnE5MmTcfPmTRw4cAB79+7FlStXkJWVxduurKwMO3fuxO7du7F7924cOHAA+fn53fRpEUKsjarYCCEW4ebmBolEAqlUCj8/P27522+/jfj4eLz88svcsi1btiAoKAg//vgjBg4cCAAYMGAAXn31Vd4xNdszhYaG4q9//SsWLVqEd955BxKJBG5ubhAIBLzzaSssLMQPP/yA8vJyBAUFAQA++ugjDBkyBMeOHcOwYcMAqAKprVu3wsXFBQAwa9YsFBYW4qWXXvptHwwhpEeiEiRCiFWdPn0aRUVFcHZ25v5FRkYCUJXaqCUmJursu2/fPowbNw6BgYFwcXHBrFmzUFdXh+bmZpPPf/78eQQFBXHBEQBERUVBJpPh/Pnz3LLQ0FAuOAIAf39/1NbWdiqvhBDbQSVIhBCrampqwoMPPohXXnlFZ52/vz/32snJibeuoqICv/vd77B48WK89NJL8PDwwKFDhzBv3jy0tLRAKpWaNZ1isZj3XiAQQKlUmvUchJCegwIkQojFSCQSKBQK3rKEhAT85z//QWhoKOzsTL8lnThxAkqlEq+//jqEQlVh+GeffWb0fNoGDx6Ma9eu4dq1a1wp0rlz51BfX4+oqCiT00MI6V2oio0QYjGhoaE4cuQIKioqcOPGDSiVSixduhQ3b97EjBkzcOzYMZSVleHrr79GdnZ2h8FNREQE5HI53nrrLVy5cgUff/wx13hb83xNTU0oLCzEjRs39Fa9paenIyYmBjNnzsTJkydx9OhRzJ49G2lpaUhKSjL7Z0AIsQ0UIBFCLOaZZ56BSCRCVFQUvL29UVlZiYCAABw+fBgKhQLjx49HTEwMli9fDplMxpUM6RMbG4v169fjlVdeQXR0NLZt24a8vDzeNsOHD8eiRYuQlZUFb29vnUbegKqqbNeuXXB3d8eoUaOQnp6O8PBw7Nixw+z5J4TYDgFjjFk7EYQQQgghPQmVIBFCCCGEaKEAiRBCCCFECwVIhBBCCCFaKEAihBBCCNFCARIhhBBCiBYKkAghhBBCtFCARAghhBCihQIkQgghhBAtFCARQgghhGihAIkQQgghRAsFSIQQQgghWihAIoQQQgjR8v8B5gM1OH4QBAkAAAAASUVORK5CYII=", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Plot the D and G losses (Evaluation)\n", + "\n", + "xmax = params.num_iterations\n", + "\n", + "fig, axs = plt.subplots()\n", + "\n", + "\n", + "axs.set_xlabel(\"Iteration\")\n", + "axs.set_ylabel(\"Loss\")\n", + "axs.set_xlim(0, xmax)\n", + "axs.set_title(f\"Losses of Evaluation ProtoGain\")\n", + "\n", + "\n", + "axs.fill_between(\n", + " np.arange(1, len(loss_D_evaluate[0]) + 1, 1),\n", + " loss_D_evaluate.mean(axis=0) + loss_D_evaluate.std(axis=0),\n", + " loss_D_evaluate.mean(axis=0) - loss_D_evaluate.std(axis=0),\n", + " alpha=0.4,\n", + ")\n", + "axs.plot(loss_D_evaluate.mean(axis=0), label=\"D loss\")\n", + "\n", + "axs.fill_between(\n", + " np.arange(1, len(loss_G_evaluate[0]) + 1, 1),\n", + " loss_G_evaluate.mean(axis=0) + loss_G_evaluate.std(axis=0),\n", + " loss_G_evaluate.mean(axis=0) - loss_G_evaluate.std(axis=0),\n", + " alpha=0.4,\n", + ")\n", + "axs.plot(loss_G_evaluate.mean(axis=0), label=\"G loss\")\n", + "axs.xaxis.grid(True, which=\"major\")\n", + "axs.yaxis.grid(True, which=\"major\")\n", + "\n", + "\n", + "fig.legend(loc=\"upper right\", bbox_to_anchor=(0.9, 0.85))\n", + "\n", + "# Adjust the spacing between subplots\n", + "plt.subplots_adjust(wspace=0.05, hspace=0.2)" + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Plot the MSE (Multiple runs)\n", + "\n", + "xmax = params.num_iterations\n", + "\n", + "fig, axs = plt.subplots()\n", + "\n", + "\n", + "axs.set_xlabel(\"Iteration\")\n", + "axs.set_ylabel(\"MSE\")\n", + "axs.set_xlim(0, xmax)\n", + "axs.set_title(f\"MSE ProtoGain\")\n", + "\n", + "axs.fill_between(\n", + " np.arange(1, len(loss_MSE_train[0]) + 1, 1),\n", + " loss_MSE_train.mean(axis=0) + loss_MSE_train.std(axis=0),\n", + " loss_MSE_train.mean(axis=0) - loss_MSE_train.std(axis=0),\n", + " alpha=0.4,\n", + ")\n", + "axs.plot(loss_MSE_train.mean(axis=0), label=\"MSE of the NOT missing values\")\n", + "\n", + "axs.fill_between(\n", + " np.arange(1, len(loss_MSE_test[0]) + 1, 1),\n", + " loss_MSE_test.mean(axis=0) + loss_MSE_test.std(axis=0),\n", + " loss_MSE_test.mean(axis=0) - loss_MSE_test.std(axis=0),\n", + " alpha=0.4,\n", + ")\n", + "axs.plot(loss_MSE_test.mean(axis=0), label=\"MSE of the missing values\")\n", + "\n", + "\n", + "axs.xaxis.grid(True, which=\"major\")\n", + "axs.yaxis.grid(True, which=\"major\")\n", + "fig.legend(loc=\"upper right\", bbox_to_anchor=(0.9, 0.85))\n", + "\n", + "# Adjust the spacing between subplots\n", + "plt.subplots_adjust(wspace=0.05, hspace=0.2)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Plot the MSE (Evaluation)\n", + "\n", + "xmax = params.num_iterations\n", + "\n", + "fig, axs = plt.subplots()\n", + "\n", + "\n", + "axs.set_xlabel(\"Iteration\")\n", + "axs.set_ylabel(\"MSE\")\n", + "axs.set_xlim(0, xmax)\n", + "axs.set_title(f\"MSE ProtoGain\")\n", + "\n", + "axs.fill_between(\n", + " np.arange(1, len(loss_MSE_train_evaluate[0]) + 1, 1),\n", + " loss_MSE_train_evaluate.mean(axis=0) + loss_MSE_train_evaluate.std(axis=0),\n", + " loss_MSE_train_evaluate.mean(axis=0) - loss_MSE_train_evaluate.std(axis=0),\n", + " alpha=0.4,\n", + ")\n", + "axs.plot(loss_MSE_train_evaluate.mean(axis=0), label=\"MSE of the NOT missing values\")\n", + "\n", + "axs.fill_between(\n", + " np.arange(1, len(loss_MSE_test[0]) + 1, 1),\n", + " loss_MSE_test.mean(axis=0) + loss_MSE_test.std(axis=0),\n", + " loss_MSE_test.mean(axis=0) - loss_MSE_test.std(axis=0),\n", + " alpha=0.4,\n", + ")\n", + "axs.plot(loss_MSE_test.mean(axis=0), label=\"MSE of the missing values\")\n", + "\n", + "\n", + "axs.xaxis.grid(True, which=\"major\")\n", + "axs.yaxis.grid(True, which=\"major\")\n", + "fig.legend(loc=\"upper right\", bbox_to_anchor=(0.9, 0.85))\n", + "\n", + "# Adjust the spacing between subplots\n", + "plt.subplots_adjust(wspace=0.05, hspace=0.2)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Final MSE\n", + "\n", + "space = 0.15\n", + "fig, ax = plt.subplots(figsize=(12, 8))\n", + "\n", + "box_param = dict(\n", + " whis=(5, 95),\n", + " widths=0.2,\n", + " patch_artist=True,\n", + " flierprops=dict(marker=\".\", markeredgecolor=\"black\", fillstyle=None),\n", + " notch=True,\n", + " medianprops=dict(color=\"black\"),\n", + ")\n", + "\n", + "\n", + "bp1 = ax.boxplot(\n", + " MSE_final,\n", + " boxprops=dict(facecolor=\"tab:blue\"),\n", + " **box_param,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "metadata": {}, + "outputs": [ + { + "ename": "ValueError", + "evalue": "Invalid file path or buffer object type: ", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[47], line 10\u001b[0m\n\u001b[1;32m 6\u001b[0m x \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39mlinspace(\u001b[38;5;241m-\u001b[39mxlim, xlim, \u001b[38;5;241m100\u001b[39m)\n\u001b[1;32m 7\u001b[0m y \u001b[38;5;241m=\u001b[39m x\n\u001b[0;32m---> 10\u001b[0m df_data \u001b[38;5;241m=\u001b[39m \u001b[43mpd\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mread_csv\u001b[49m\u001b[43m(\u001b[49m\u001b[43mparams\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mref\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241m.\u001b[39mvalues\n\u001b[1;32m 12\u001b[0m df_missing \u001b[38;5;241m=\u001b[39m pd\u001b[38;5;241m.\u001b[39mread_csv(params\u001b[38;5;241m.\u001b[39minput)\u001b[38;5;241m.\u001b[39mvalues\n\u001b[1;32m 14\u001b[0m df_imputed \u001b[38;5;241m=\u001b[39m pd\u001b[38;5;241m.\u001b[39mread_csv(params\u001b[38;5;241m.\u001b[39moutput_folder \u001b[38;5;241m+\u001b[39m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mparams\u001b[38;5;241m.\u001b[39moutput\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m.csv\u001b[39m\u001b[38;5;124m\"\u001b[39m)\u001b[38;5;241m.\u001b[39mvalues\n", + "File \u001b[0;32m~/miniconda3/envs/proto/lib/python3.12/site-packages/pandas/io/parsers/readers.py:1026\u001b[0m, in \u001b[0;36mread_csv\u001b[0;34m(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, skipfooter, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, date_format, dayfirst, cache_dates, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, doublequote, escapechar, comment, encoding, encoding_errors, dialect, on_bad_lines, delim_whitespace, low_memory, memory_map, float_precision, storage_options, dtype_backend)\u001b[0m\n\u001b[1;32m 1013\u001b[0m kwds_defaults \u001b[38;5;241m=\u001b[39m _refine_defaults_read(\n\u001b[1;32m 1014\u001b[0m dialect,\n\u001b[1;32m 1015\u001b[0m delimiter,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 1022\u001b[0m dtype_backend\u001b[38;5;241m=\u001b[39mdtype_backend,\n\u001b[1;32m 1023\u001b[0m )\n\u001b[1;32m 1024\u001b[0m kwds\u001b[38;5;241m.\u001b[39mupdate(kwds_defaults)\n\u001b[0;32m-> 1026\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_read\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfilepath_or_buffer\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkwds\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/miniconda3/envs/proto/lib/python3.12/site-packages/pandas/io/parsers/readers.py:620\u001b[0m, in \u001b[0;36m_read\u001b[0;34m(filepath_or_buffer, kwds)\u001b[0m\n\u001b[1;32m 617\u001b[0m _validate_names(kwds\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnames\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;28;01mNone\u001b[39;00m))\n\u001b[1;32m 619\u001b[0m \u001b[38;5;66;03m# Create the parser.\u001b[39;00m\n\u001b[0;32m--> 620\u001b[0m parser \u001b[38;5;241m=\u001b[39m \u001b[43mTextFileReader\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfilepath_or_buffer\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwds\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 622\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m chunksize \u001b[38;5;129;01mor\u001b[39;00m iterator:\n\u001b[1;32m 623\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m parser\n", + "File \u001b[0;32m~/miniconda3/envs/proto/lib/python3.12/site-packages/pandas/io/parsers/readers.py:1620\u001b[0m, in \u001b[0;36mTextFileReader.__init__\u001b[0;34m(self, f, engine, **kwds)\u001b[0m\n\u001b[1;32m 1617\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39moptions[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhas_index_names\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m kwds[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhas_index_names\u001b[39m\u001b[38;5;124m\"\u001b[39m]\n\u001b[1;32m 1619\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhandles: IOHandles \u001b[38;5;241m|\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[0;32m-> 1620\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_engine \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_make_engine\u001b[49m\u001b[43m(\u001b[49m\u001b[43mf\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mengine\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/miniconda3/envs/proto/lib/python3.12/site-packages/pandas/io/parsers/readers.py:1880\u001b[0m, in \u001b[0;36mTextFileReader._make_engine\u001b[0;34m(self, f, engine)\u001b[0m\n\u001b[1;32m 1878\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mb\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m mode:\n\u001b[1;32m 1879\u001b[0m mode \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mb\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m-> 1880\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhandles \u001b[38;5;241m=\u001b[39m \u001b[43mget_handle\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 1881\u001b[0m \u001b[43m \u001b[49m\u001b[43mf\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1882\u001b[0m \u001b[43m \u001b[49m\u001b[43mmode\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1883\u001b[0m \u001b[43m \u001b[49m\u001b[43mencoding\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mencoding\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1884\u001b[0m \u001b[43m \u001b[49m\u001b[43mcompression\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mcompression\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1885\u001b[0m \u001b[43m \u001b[49m\u001b[43mmemory_map\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mmemory_map\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1886\u001b[0m \u001b[43m \u001b[49m\u001b[43mis_text\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mis_text\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1887\u001b[0m \u001b[43m \u001b[49m\u001b[43merrors\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mencoding_errors\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mstrict\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1888\u001b[0m \u001b[43m \u001b[49m\u001b[43mstorage_options\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mstorage_options\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1889\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1890\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhandles \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m 1891\u001b[0m f \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhandles\u001b[38;5;241m.\u001b[39mhandle\n", + "File \u001b[0;32m~/miniconda3/envs/proto/lib/python3.12/site-packages/pandas/io/common.py:728\u001b[0m, in \u001b[0;36mget_handle\u001b[0;34m(path_or_buf, mode, encoding, compression, memory_map, is_text, errors, storage_options)\u001b[0m\n\u001b[1;32m 725\u001b[0m codecs\u001b[38;5;241m.\u001b[39mlookup_error(errors)\n\u001b[1;32m 727\u001b[0m \u001b[38;5;66;03m# open URLs\u001b[39;00m\n\u001b[0;32m--> 728\u001b[0m ioargs \u001b[38;5;241m=\u001b[39m \u001b[43m_get_filepath_or_buffer\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 729\u001b[0m \u001b[43m \u001b[49m\u001b[43mpath_or_buf\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 730\u001b[0m \u001b[43m \u001b[49m\u001b[43mencoding\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mencoding\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 731\u001b[0m \u001b[43m \u001b[49m\u001b[43mcompression\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcompression\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 732\u001b[0m \u001b[43m \u001b[49m\u001b[43mmode\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmode\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 733\u001b[0m \u001b[43m \u001b[49m\u001b[43mstorage_options\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstorage_options\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 734\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 736\u001b[0m handle \u001b[38;5;241m=\u001b[39m ioargs\u001b[38;5;241m.\u001b[39mfilepath_or_buffer\n\u001b[1;32m 737\u001b[0m handles: \u001b[38;5;28mlist\u001b[39m[BaseBuffer]\n", + "File \u001b[0;32m~/miniconda3/envs/proto/lib/python3.12/site-packages/pandas/io/common.py:472\u001b[0m, in \u001b[0;36m_get_filepath_or_buffer\u001b[0;34m(filepath_or_buffer, encoding, compression, mode, storage_options)\u001b[0m\n\u001b[1;32m 468\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m (\n\u001b[1;32m 469\u001b[0m \u001b[38;5;28mhasattr\u001b[39m(filepath_or_buffer, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mread\u001b[39m\u001b[38;5;124m\"\u001b[39m) \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mhasattr\u001b[39m(filepath_or_buffer, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mwrite\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 470\u001b[0m ):\n\u001b[1;32m 471\u001b[0m msg \u001b[38;5;241m=\u001b[39m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mInvalid file path or buffer object type: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mtype\u001b[39m(filepath_or_buffer)\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m--> 472\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(msg)\n\u001b[1;32m 474\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m IOArgs(\n\u001b[1;32m 475\u001b[0m filepath_or_buffer\u001b[38;5;241m=\u001b[39mfilepath_or_buffer,\n\u001b[1;32m 476\u001b[0m encoding\u001b[38;5;241m=\u001b[39mencoding,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 479\u001b[0m mode\u001b[38;5;241m=\u001b[39mmode,\n\u001b[1;32m 480\u001b[0m )\n", + "\u001b[0;31mValueError\u001b[0m: Invalid file path or buffer object type: " + ] + } + ], + "source": [ + "# Original VS Imputed\n", + "\n", + "xlim = 1000000\n", + "\n", + "\n", + "x = np.linspace(-xlim, xlim, 100)\n", + "y = x\n", + "\n", + "\n", + "df_data = pd.read_csv(params.ref).values\n", + "\n", + "df_missing = pd.read_csv(params.input).values\n", + "\n", + "df_imputed = pd.read_csv(params.output_folder + f\"{params.output}.csv\").values\n", + "\n", + "\n", + "zeros = np.where(np.isnan(df_missing))\n", + "\n", + "features = np.arange(len(df_data[0]))\n", + "# features = np.array([0, 1])\n", + "\n", + "corr = np.empty(len(df_data[0]))\n", + "\n", + "fig, axs = plt.subplots(len(features), figsize=(8, len(df_data[0]) * 6))\n", + "\n", + "for feature in features:\n", + "\n", + " xmin = df_data[:, feature].min()\n", + " xmax = df_data[:, feature].max()\n", + "\n", + " ymin = df_imputed[:, feature].min()\n", + " ymax = df_imputed[:, feature].max()\n", + "\n", + " zeros_0 = []\n", + " for i in range(len(zeros[0])):\n", + " if zeros[1][i] == feature:\n", + " zeros_0.append(zeros[0][i])\n", + "\n", + " corr[feature] = np.corrcoef(\n", + " df_data[zeros_0, feature], df_imputed[zeros_0, feature]\n", + " )[0, 1]\n", + "\n", + " axs[feature].plot(x, y, color=\"red\", linestyle=\"--\")\n", + " axs[feature].scatter(\n", + " df_data[zeros_0, feature], df_imputed[zeros_0, feature], label=corr[feature]\n", + " )\n", + " axs[feature].set_xlabel(\"Original\")\n", + " axs[feature].set_ylabel(\"Imputed\")\n", + " axs[feature].set_xlim(xmin * 0.9, xmax * 1.1)\n", + " axs[feature].legend() # Add this line to show the label on the graph\n", + " axs[feature].set_ylim(ymin * 0.9, ymax * 1.1)\n", + " axs[feature].set_title(f\"ProtoGain - Original vs Imputed (Feature {feature})\")\n", + " axs[feature].xaxis.grid(True, which=\"major\")\n", + " axs[feature].yaxis.grid(True, which=\"major\")" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Histogram: [4 1 3 1 3 2 2 2 6 6]\n", + "Bins: [0.5373835 0.57425734 0.61113118 0.64800502 0.68487886 0.7217527\n", + " 0.75862654 0.79550038 0.83237422 0.86924806 0.9061219 ]\n" + ] + }, + { + "data": { + "text/plain": [ + "Text(0.5, 1.0, 'Histogram of the Pearson Correlation between original and imputed values')" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import numpy as np\n", + "\n", + "# Define the number of bins\n", + "num_bins = 10\n", + "\n", + "# Create the bins using numpy.histogram\n", + "hist, bins = np.histogram(corr, bins=num_bins)\n", + "\n", + "# Print the histogram and bins\n", + "print(\"Histogram:\", hist)\n", + "print(\"Bins:\", bins)\n", + "\n", + "fig, ax = plt.subplots(figsize=(10, 6))\n", + "\n", + "plt.xticks(bins)\n", + "\n", + "plt.hist(corr, alpha=0.5, bins=num_bins, histtype=\"bar\", ec=\"black\")\n", + "plt.xlabel(\"Correlation\")\n", + "plt.ylabel(\"Frequency\")\n", + "plt.title(\"Histogram of the Pearson Correlation between original and imputed values\")\n", + "\n", + "# plt.figure()\n", + "# plt.plot(corr, marker=\"o\", linestyle=\"-\")\n", + "# plt.ylim(0, 1)" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Boxplot of each run duration\n", + "\n", + "space = 0.15\n", + "fig, ax = plt.subplots(figsize=(12, 8))\n", + "\n", + "box_param = dict(\n", + " whis=(5, 95),\n", + " widths=0.2,\n", + " patch_artist=True,\n", + " flierprops=dict(marker=\".\", markeredgecolor=\"black\", fillstyle=None),\n", + " notch=True,\n", + " medianprops=dict(color=\"black\"),\n", + ")\n", + "\n", + "\n", + "bp1 = ax.boxplot(\n", + " run_time,\n", + " boxprops=dict(facecolor=\"tab:blue\"),\n", + " **box_param,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 69, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'train_samples' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[69], line 29\u001b[0m\n\u001b[1;32m 25\u001b[0m x_ticks \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mrange\u001b[39m(\u001b[38;5;241m0\u001b[39m, xmax, \u001b[38;5;241m100\u001b[39m)\n\u001b[1;32m 28\u001b[0m \u001b[38;5;66;03m# Create a color gradient based on the loop index\u001b[39;00m\n\u001b[0;32m---> 29\u001b[0m colors \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39mlinspace(\u001b[38;5;241m0\u001b[39m, \u001b[38;5;241m1\u001b[39m, \u001b[38;5;28mlen\u001b[39m(\u001b[43mtrain_samples\u001b[49m))\n\u001b[1;32m 31\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i, samples \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28menumerate\u001b[39m(train_samples):\n\u001b[1;32m 32\u001b[0m runs_cpu \u001b[38;5;241m=\u001b[39m {run: data \u001b[38;5;28;01mfor\u001b[39;00m (s, run), data \u001b[38;5;129;01min\u001b[39;00m my_cpu\u001b[38;5;241m.\u001b[39mitems() \u001b[38;5;28;01mif\u001b[39;00m s \u001b[38;5;241m==\u001b[39m samples}\n", + "\u001b[0;31mNameError\u001b[0m: name 'train_samples' is not defined" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# CPU and RAM\n", + "\n", + "xmax = params.num_iterations\n", + "\n", + "fig, axs = plt.subplots(2, 2, figsize=(12, 12), sharex=True, sharey=\"row\")\n", + "\n", + "# Set the labels and limits for Loss D\n", + "axs[0, 0].set_xlabel(\"Iteration\")\n", + "axs[0, 0].set_ylabel(\"CPU (%)\")\n", + "axs[0, 0].set_xlim(0, xmax)\n", + "axs[0, 0].set_title(f\"CPU usage ProtoGain\")\n", + "\n", + "# Set the labels and limits for Loss G\n", + "axs[0, 1].set_xlabel(\"Iteration\")\n", + "axs[0, 1].set_title(f\"CPU usage GAIN\")\n", + "\n", + "\n", + "axs[1, 0].set_xlabel(\"Iteration\")\n", + "axs[1, 0].set_ylabel(\"RAM (GB)\")\n", + "axs[1, 0].set_title(f\"RAM usage ProtoGain\")\n", + "axs[1, 1].set_xlabel(\"Iteration\")\n", + "axs[1, 1].set_title(f\"RAM usage GAIN\")\n", + "\n", + "\n", + "x_ticks = range(0, xmax, 100)\n", + "\n", + "\n", + "# Create a color gradient based on the loop index\n", + "colors = np.linspace(0, 1, len(train_samples))\n", + "\n", + "for i, samples in enumerate(train_samples):\n", + " runs_cpu = {run: data for (s, run), data in my_cpu.items() if s == samples}\n", + " runs_cpu_array = np.array(list(runs_cpu.values()))\n", + " mean_runs_cpu = np.mean(runs_cpu_array, axis=0)\n", + " std_runs_cpu = np.std(runs_cpu_array, axis=0)\n", + "\n", + " # Use the color gradient for the plot\n", + " axs[0, 0].plot(\n", + " x_ticks, mean_runs_cpu, label=f\"{samples} samples\", c=plt.cm.viridis(colors[i])\n", + " )\n", + " axs[0, 0].fill_between(\n", + " np.arange(1, len(mean_runs_cpu) + 1, 1),\n", + " mean_runs_cpu[:, 0] + std_runs_cpu[:, 0],\n", + " mean_runs_cpu[:, 0] - std_runs_cpu[:, 0],\n", + " alpha=0.4,\n", + " color=plt.cm.viridis(colors[i]),\n", + " )\n", + " axs[0, 0].xaxis.grid(True, which=\"major\")\n", + " axs[0, 0].yaxis.grid(True, which=\"major\")\n", + "\n", + " runs_cpu = {run: data for (s, run), data in gain_cpu.items() if s == samples}\n", + " runs_cpu_array = np.array(list(runs_cpu.values()))\n", + " mean_runs_cpu = np.mean(runs_cpu_array, axis=0)\n", + " std_runs_cpu = np.std(runs_cpu_array, axis=0)\n", + "\n", + " # Use the color gradient for the plot\n", + "\n", + " axs[0, 1].plot(x_ticks, mean_runs_cpu, c=plt.cm.viridis(colors[i]))\n", + " axs[0, 1].fill_between(\n", + " np.arange(1, len(mean_runs_cpu) + 1, 1),\n", + " mean_runs_cpu[:, 0] + std_runs_cpu[:, 0],\n", + " mean_runs_cpu[:, 0] - std_runs_cpu[:, 0],\n", + " alpha=0.4,\n", + " color=plt.cm.viridis(colors[i]),\n", + " )\n", + " axs[0, 1].xaxis.grid(True, which=\"major\")\n", + " axs[0, 1].yaxis.grid(True, which=\"major\")\n", + "\n", + " runs_ram = {run: data for (s, run), data in my_ram.items() if s == samples}\n", + " runs_ram_array = np.array(list(runs_ram.values()))\n", + " mean_runs_ram = np.mean(runs_ram_array, axis=0)\n", + " std_runs_ram = np.std(runs_ram_array, axis=0)\n", + "\n", + " axs[1, 0].plot(x_ticks, mean_runs_ram, c=plt.cm.viridis(colors[i]))\n", + " axs[1, 0].fill_between(\n", + " np.arange(1, len(mean_runs_ram) + 1, 1),\n", + " mean_runs_ram[:, 0] + std_runs_ram[:, 0],\n", + " mean_runs_ram[:, 0] - std_runs_ram[:, 0],\n", + " alpha=0.4,\n", + " color=plt.cm.viridis(colors[i]),\n", + " )\n", + " axs[1, 0].xaxis.grid(True, which=\"major\")\n", + " axs[1, 0].yaxis.grid(True, which=\"major\")\n", + "\n", + " runs_ram = {run: data for (s, run), data in gain_ram.items() if s == samples}\n", + " runs_ram_array = np.array(list(runs_ram.values()))\n", + " mean_runs_ram = np.mean(runs_ram_array, axis=0)\n", + " std_runs_ram = np.std(runs_ram_array, axis=0)\n", + "\n", + " axs[1, 1].plot(x_ticks, mean_runs_ram, c=plt.cm.viridis(colors[i]))\n", + " axs[1, 1].fill_between(\n", + " np.arange(1, len(mean_runs_ram) + 1, 1),\n", + " mean_runs_ram[:, 0] + std_runs_ram[:, 0],\n", + " mean_runs_ram[:, 0] - std_runs_ram[:, 0],\n", + " alpha=0.4,\n", + " color=plt.cm.viridis(colors[i]),\n", + " )\n", + " axs[1, 1].xaxis.grid(True, which=\"major\")\n", + " axs[1, 1].yaxis.grid(True, which=\"major\")\n", + "\n", + "\n", + "fig.legend(loc=\"center right\", bbox_to_anchor=(1.05, 0.5))\n", + "\n", + "# Adjust the spacing between subplots\n", + "plt.subplots_adjust(wspace=0.05, hspace=0.2)\n", + "\n", + "# Show the plot\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0.0 2499.0\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Original vs Imputed by feature (Added Missing Values)\n", + "\n", + "xlim = 1000000\n", + "# c=plt.cm.viridis(colors[df_test[:,3].astype(int)]), label=f\"{df_test[:,3]}\",\n", + "\n", + "x = np.linspace(-xlim, xlim, 100)\n", + "y = x\n", + "\n", + "\n", + "df_test = pd.read_csv(f\"{params.output_folder}test_imputed.csv\").values\n", + "print(df_test.min(), df_test.max())\n", + "features = [int(feature) for feature in np.unique(df_test[:, 3])]\n", + "corr = np.empty(len(features))\n", + "fig, axs = plt.subplots(len(features), figsize=(7, len(features) * 6))\n", + "colors = np.linspace(0, 1, len(features))\n", + "\n", + "for feature in features:\n", + "\n", + " filtered_array = df_test[df_test[:, 3] == feature]\n", + "\n", + " xmin = filtered_array[:, 0].min()\n", + " xmax = filtered_array[:, 0].max()\n", + "\n", + " ymin = filtered_array[:, 1].min()\n", + " ymax = filtered_array[:, 1].max()\n", + "\n", + " corr[feature] = np.corrcoef(filtered_array[:, 0], filtered_array[:, 1])[0, 1]\n", + "\n", + " axs[feature].plot(x, y, color=\"red\", linestyle=\"--\")\n", + " axs[feature].scatter(\n", + " filtered_array[:, 0],\n", + " filtered_array[:, 1],\n", + " label=f\"Correlation: {round(corr[feature],3)}\",\n", + " )\n", + " axs[feature].set_xlabel(\"Original\")\n", + " axs[feature].set_ylabel(\"Imputed\")\n", + " axs[feature].set_xlim(xmin * 0.9, xmax * 1.1)\n", + " axs[feature].legend(markerscale=0)\n", + " axs[feature].set_ylim(ymin * 0.9, ymax * 1.1)\n", + " axs[feature].set_title(f\"ribaq - Original vs Imputed (Sample {feature})\")\n", + " axs[feature].xaxis.grid(True, which=\"major\")\n", + " axs[feature].yaxis.grid(True, which=\"major\")" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Histogram: [1 0 2 4 2 3 1 4 6 7]\n", + "Bins: [0.39959863 0.44779994 0.49600124 0.54420255 0.59240385 0.64060516\n", + " 0.68880646 0.73700777 0.78520907 0.83341038 0.88161168]\n" + ] + }, + { + "data": { + "text/plain": [ + "Text(0.5, 1.0, 'Histogram of the Pearson Correlation between original and imputed values')" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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Vh/bBwcFm4MCB6dZ8+fJlEx4ebipXrmz+/fdf+/Tvv//eSDKvvfaafVpkZKSRZF5//XWHeVSrVs3UqFHjhn2T2tcLFy68YbtUgwcPNpLMihUr7NPi4uJMiRIlTPHixU1ycrIx5v9e25IlS6bpr9R6X3rpJYfpK1asMJLMzJkzHab//PPPaaY3bNjQNGzY0P74ypUrDmPImKvjPn/+/ObRRx+1Tztz5kya7TFV6jaVKiPbQ7FixdJso6dPnzY+Pj7mueeeS7Osa6WOTz8/P/PXX3/Zp69du9ZIMs8++6x9WpMmTcxdd91lLl26ZJ+WkpJi7rvvPlOmTBn7tHnz5hlJZtmyZQ7LOn36tJFkPvroI2OMMRcuXDAeHh6mc+fOJn/+/PZ2gwYNMqGhofZtYcaMGcbDw8PhdTfGmI8//thIMn/88YcxxpjDhw8bT09PM3r0aId227ZtM7ly5XKY3rBhwzTbTGJioilQoIB56KGHbthnmXltfv755zTzuf694umnnzY2m81s2rTJPu3s2bMmNDTUSDKHDh1yqP/aMejq/swY5/uQsWPHGpvNZo4cOWKfdv2YTI+r83N1X5H6vvfWW2/Zp125csXUr1/fSDLR0dE3rCe1L64df6mv91dffWWftnv3biPJeHh4mDVr1tinL1q0KM1yUvuibdu2DssaMGCAkWS2bNlijPm/7clZjddv+2+//Xaa19UY18dx6n66atWqDq/5p59+aiQ5jA9n9uzZYySZ999/P8065c6d2+F1vf41vnz5sqlcubK5//77HaZfP6bTG0Op70+p6x4XF2dCQkJMv379HNqdPHnSBAcH26efP3/eSDJvv/32DdcNWY/T4Szsww8/1OLFi9P8u9G3uKlCQkK0Y8cO7du3L8PL/fHHH+Xp6Wn/hjTVc889J2OMfvrpJ0nSzz//LOnqt/7Xevrpp9Od9xNPPJFmmp+fn/3/L126pH/++Uf33nuvJKU5VUq6+m1oKk9PT9WsWVPGGPXt29c+PSQkROXKldPBgwfTrUW6uq6SNGTIEIfpzz33nCSlOeUpq/Tp08fh/Pr69etLkr3ezZs3a9++fXr44Yd19uxZ/fPPP/rnn3908eJFNWnSRL///rtSUlJuupwRI0YoLCxMBQoUUKNGjXTgwAGNGzdOHTt2zNAyrn2NkpKSdPbsWZUuXVohISFOX6N+/fqlOcoSEhKitWvX6u+//3Za64YNG3T69GkNGDDA4dz61q1bq3z58k5fi+vHU/369W/6msfGxkpSmm9b0/Pjjz+qVq1a9tM3patH9vr376/Dhw9r586dDu0jIyMd+uta1x+hmjdvnoKDg9WsWTN7///zzz+qUaOGcufO7XBq2/U8PT3tYyglJUXnzp3TlStXVLNmTaeviavrKrm+PVSsWNE+dqWr3yi7st2lat++vQoXLmx/XKtWLdWuXdtex7lz5/Trr7+qS5cuiouLs/fP2bNn1bx5c+3bty/NqZLXCwsLU/ny5fX7779Lkv744w95enrq+eef16lTp+z7yBUrVqhevXr2I8/z5s1ThQoVVL58eYfXJvWU0tTXZsGCBUpJSVGXLl0c2hUoUEBlypRJ8xrmzp3b4To9b29v1apVK8v3VSVKlFDz5s1vOE/p6n68Tp06DjdKCQ0NtZ+u6Yqb7c8kx33IxYsX9c8//+i+++6TMUabNm1yeVmZnd/N9hU//vijcuXK5bCNenp63vD9zBW5c+d2OLpRrlw5hYSEqEKFCqpdu7Z9eur/OxsHAwcOdHicWlPqmMgKro7j1P30E0884fCap55GeDNly5ZV1apVNWfOHPu05ORkzZ8/X23atHF4Xa/9//PnzysmJkb169fP9P7teosXL9aFCxfUvXt3h3X29PRU7dq17eucei3w8uXLb3qaMrIWp8NZWK1atVSzZs000/PkyeP0NLlrvf7662rXrp3Kli2rypUrq0WLFurZs6dLAerIkSMqVKhQmg+JqaeYHDlyxP5fDw8PlShRwqFd6dKl05339W2lqx90oqKiNHv2bJ0+fdrhuZiYmDTtixYt6vA4ODhYvr6+9kP7106//rqi66Wuw/U1FyhQQCEhIfZ1zWrXr0OePHkkyb6DTf1gdqNTMWJiYux/l57+/furc+fO8vDwUEhIiCpVqmQ/zSUjy0i9jiY6OlrHjx93uL7C2Wvk7HV+6623FBkZqYiICNWoUUOtWrVSr169VLJkSUn/N66cnbZTvnx5rVy50mGar6+v/TSOVHny5Lnpm1RQUJCkq9coueLIkSMOH1ZSXbs9XHvLemfrLl29CUHq9VGp9u3bp5iYGIWHhzv9m+u3h+tNmzZN48eP1+7dux1Ok02vhpvJ6PZw/TiWXHsNUpUpUybNtLJly2ru3LmSrp5uZ4zRq6++qldffdXpPE6fPu0QpJypX7++/QPjihUrVLNmTdWsWVOhoaFasWKF8ufPry1btujhhx+2/82+ffu0a9euNGPs2uWmtjPGOF0XSWlOZyxSpEiaU3zz5MmjrVu33nAdMvrauDoGjhw5ojp16qSZfqP9+PVutj+TpKNHj+q1117Td999l2Z8ONuH3ExG5ufKvuLIkSMqWLBgmlOX0zuN0FXOXu/g4OA0p42lBghn2871Y6tUqVLy8PDI0utRXB3HqePs+nZeXl72ffnNdO3aVS+//LKOHz+uwoULa/ny5Tp9+rS6du3q0O7777/XG2+8oc2bN6e5RjcrpL4Hpn6xcb3U9wofHx+NGzdOzz33nPLnz697771XDz74oHr16uVwSh+yHiEImdKgQQMdOHBA3377rX755Rd9/vnnmjBhgj7++GOHIym3m7NvyLt06aJVq1bp+eefV9WqVZU7d26lpKSoRYsWTo92OLuOI71rO679sH4jt/vH+W5Wb+p6v/322+neyvr6N2tnypQpo6ZNmzp9LiPLePrppxUdHa3BgwerTp06Cg4Ols1mU7du3Zy+Rum9zvXr19fChQv1yy+/6O2339a4ceO0YMGCm14L4Ywr1/M4U758eUnStm3b1L59+0zN40bSOwrk4+OT5i5xKSkpCg8P18yZM53+TXofwKWrFzD37t1b7du31/PPP6/w8HB5enpq7Nix9mu/MsvV7eFWt7ubSR1bQ4cOTfeohisf1uvVq6fPPvtMBw8e1IoVK1S/fn3ZbDbVq1dPK1asUKFChZSSkuJwVCslJUV33XWX3n33XafzTP0Qm5KSIpvNpp9++slpf1y/nd6ufVV64zA73GydkpOT1axZM507d04vvviiypcvr4CAAB0/fly9e/d26aj2tTI6v8zuK7JCesu+lXFw/RhIb0zc7CYx18roOL4VXbt21bBhwzRv3jwNHjxYc+fOVXBwsFq0aGFvs2LFCrVt21YNGjTQRx99pIIFC8rLy0vR0dH66quvbjh/V/sjdZzMmDHDaZi59s6ZgwcPVps2bfTNN99o0aJFevXVVzV27Fj9+uuvqlatmsvrjowhBCHTQkND1adPH/Xp00fx8fFq0KCBRo4caQ9B6e0oihUrpiVLliguLs7haNDu3bvtz6f+NyUlRYcOHXL4VsjZXc7Sc/78eS1dulRRUVF67bXX7NMzcxpfZqSuw759++zf7EtXL4a/cOGCfV0z6lZDValSpSRd/SYqvRBzqzKyjPnz5ysyMtLhjnuXLl3K8A/uFSxYUAMGDNCAAQN0+vRpVa9eXaNHj1bLli3tfb1nz54038zt2bMn06/F9erVq6c8efJo1qxZevnll2/6AalYsWLas2dPmunXbw+ZUapUKS1ZskR169bN8IfW+fPnq2TJklqwYIHDeBsxYoRDu4yMxezaHtLjbDvfu3ev/ULj1G+Wvby8bjpGb7SeqeFm8eLFWr9+vf23kRo0aKDJkyerUKFCCggIUI0aNex/U6pUKW3ZskVNmjS54bxLlSolY4xKlCihsmXL3rDGW5Fdr02xYsWc7rMzsh+/mW3btmnv3r2aNm2aevXqZZ+eerdSd89PutoPS5cuVXx8vMMHfmfb/u22b98+hyN7+/fvV0pKin07ST3ydv3+2NmZDOmNZVfHceo427dvn8N+OikpSYcOHVKVKlVuuj4lSpRQrVq1NGfOHD311FNasGCB2rdv73Azjq+//lq+vr5atGiRw/To6Oibzv/a/rj2piTX90fqe2B4eLhL77OlSpXSc889p+eee0779u1T1apVNX78eH355Zc3/VtkDtcEIVOuPw0sd+7cKl26tMMh5dTfKLl+x5n645offPCBw/QJEybIZrPZv7VP/Wb2o48+cmj3/vvvu1xn6gfQ67/9mjhxosvzuBWtWrVyurzUb38zeweagICATJ3ikapGjRoqVaqU3nnnHcXHx6d5/syZM5med2aW4enpmeY1ev/9913+pjE5OTlNf4SHh6tQoUL2MVmzZk2Fh4fr448/dhinP/30k3bt2pVldwPy9/fXiy++qF27dunFF190+s3rl19+qXXr1km6OkbWrVun1atX25+/ePGiPv30UxUvXlwVK1bMdC1dunRRcnKyRo0alea5K1eu3DBkOtt21q5d61CnJPtd6FwJrNm1PaTnm2++cbimZ926dVq7dq19HxMeHq5GjRrpk08+0YkTJ9L8/bVjNL39mXT1Q1fhwoU1YcIEJSUlqW7dupKuhqMDBw5o/vz5uvfeex2++e3SpYuOHz+uzz77LM38/v33X/tdDzt27ChPT09FRUWlGUvGmJuekuuq7HptmjdvrtWrV2vz5s32aefOnUv36GRmOBurxhhNmjQpR8xPutq/V65ccbhFenJycobez7JL6s9ZpEqtKXU7CQoKUr58+ezXvaW6/r1ZSn87cXUc16xZU2FhYfr44491+fJle5upU6dm6Euxrl27as2aNfriiy/0zz//pDkVztPTUzabzeE95vDhww53ZUxPari5tj8uXryoadOmObRr3ry5goKCNGbMGKd33U3dvyQkJDjckjx1GYGBgU5vl4+sw5EgZErFihXVqFEj1ahRQ6GhodqwYYP99sSpUr/1HDRokJo3by5PT09169ZNbdq0UePGjTV8+HAdPnxYVapU0S+//KJvv/1WgwcPtu9gatSooYceekgTJ07U2bNn7bfI3rt3ryTXvoEOCgpSgwYN9NZbbykpKUmFCxfWL7/84vA7NtmpSpUqioyM1KeffqoLFy6oYcOGWrdunaZNm6b27ds7/T0DV9SoUUNz5szRkCFDdM899yh37txq06aNy3/v4eGhzz//XC1btlSlSpXUp08fFS5cWMePH9eyZcsUFBSk//3vf5mqLTPLePDBBzVjxgwFBwerYsWKWr16tZYsWWK/1fbNxMXFqUiRIurUqZOqVKmi3Llza8mSJVq/fr396JKXl5fGjRunPn36qGHDhurevbv9FtnFixfXs88+e0vre63nn39eO3bs0Pjx47Vs2TJ16tRJBQoU0MmTJ/XNN99o3bp1WrVqlSTppZde0qxZs9SyZUsNGjRIoaGhmjZtmg4dOqSvv/7a6Q+huqphw4Z6/PHHNXbsWG3evFkPPPCAvLy8tG/fPs2bN0+TJk1y+N2Maz344INasGCBOnTooNatW+vQoUP6+OOPVbFiRYdQ6+fnp4oVK2rOnDkqW7asQkNDVblyZYfrmFJl1/aQntKlS6tevXp68sknlZiYqIkTJypv3rx64YUX7G0+/PBD1atXT3fddZf69eunkiVL6tSpU1q9erX++usvbdmyRZJUtWpVeXp6aty4cYqJiZGPj4/uv/9++/VW9evX1+zZs3XXXXfZvymuXr26AgICtHfvXofrgaSrvxU1d+5cPfHEE1q2bJnq1q2r5ORk7d69W3PnzrX/Bk+pUqX0xhtvaNiwYTp8+LDat2+vwMBAHTp0SAsXLlT//v01dOjQW+6r7HptXnjhBX355Zdq1qyZnn76afstsosWLapz585lyanC5cuXV6lSpTR06FAdP35cQUFB+vrrrzN9kXlWz0+S2rRpo7p16+qll17S4cOHVbFiRS1YsOCWvszKKocOHVLbtm3VokULrV69Wl9++aUefvhhh6Mujz32mN5880099thjqlmzpn7//Xf7e/G1Ut/3hw8frm7dusnLy0tt2rRxeRx7eXnpjTfe0OOPP677779fXbt21aFDhxQdHe3yNUHS1S8Zhg4dqqFDhyo0NDTNkZjWrVvr3XffVYsWLfTwww/r9OnT+vDDD1W6dOmbXj/3wAMPqGjRourbt6+ef/55eXp66osvvlBYWJiOHj1qbxcUFKTJkyerZ8+eql69urp162Zv88MPP6hu3br64IMPtHfvXjVp0kRdunRRxYoVlStXLi1cuFCnTp1yuOkFssHtuQkdcpLU2ziuX7/e6fMNGza86S2y33jjDVOrVi0TEhJi/Pz8TPny5c3o0aPN5cuX7W2uXLlinn76aRMWFmZsNpvDLSXj4uLMs88+awoVKmS8vLxMmTJlzNtvv+1wK2VjjLl48aIZOHCgCQ0NNblz5zbt27e33wLz2ltWp96y8syZM2nW56+//jIdOnQwISEhJjg42HTu3Nn8/fff6d5m+/p5pHframf95ExSUpKJiooyJUqUMF5eXiYiIsIMGzbM4Za8N1qOM/Hx8ebhhx82ISEhRpL9dtmpt1GdN2+eQ/v0bnG6adMm07FjR5M3b17j4+NjihUrZrp06WKWLl16w+Wnzs+VW3q6sozz58+bPn36mHz58pncuXOb5s2bm927d6cZd+mN3cTERPP888+bKlWqmMDAQBMQEGCqVKliv23xtebMmWOqVatmfHx8TGhoqOnRo4fDbZSNSf+1cPX2uqnmz59vHnjgARMaGmpy5cplChYsaLp27WqWL1/u0O7AgQOmU6dOJiQkxPj6+ppatWqZ77//3qFNeq/tjepN9emnn5oaNWoYPz8/ExgYaO666y7zwgsvmL///tve5vrbE6ekpJgxY8aYYsWKGR8fH1OtWjXz/fffm8jIyDS3Z1+1apWpUaOG8fb2dtiunPWXq9tDsWLFnN6G//o6nbl2fI4fP95EREQYHx8fU79+ffttf6914MAB06tXL1OgQAHj5eVlChcubB588EEzf/58h3afffaZKVmypPH09Exzu+IPP/zQSDJPPvmkw980bdrUSHK6TV2+fNmMGzfOVKpUyfj4+Jg8efKYGjVqmKioKBMTE+PQ9uuvvzb16tUzAQEBJiAgwJQvX94MHDjQ7Nmzx6FvnO2TnL1mztzqa5P63PU/HbBp0yZTv3594+PjY4oUKWLGjh1r3nvvPSPJnDx50qF+Z7fIdmV/tnPnTtO0aVOTO3duky9fPtOvXz+zZcuWdG8LfTOuzi8j+4qzZ8+anj17mqCgIBMcHGx69uxpNm3adEu3yHb2eqf3+khy+BmB1Bp37txpOnXqZAIDA02ePHnMU0895fAzAsZcvZ103759TXBwsAkMDDRdunSx3x7++tvjjxo1yhQuXNh4eHikuV22K+PYGGM++ugjU6JECePj42Nq1qxpfv/9d5e2/WvVrVvX6W3fU02ZMsWUKVPG+Pj4mPLly5vo6Ginr5uzMb1x40ZTu3Zt4+3tbYoWLWrefffdNLfITrVs2TLTvHlzExwcbHx9fU2pUqVM7969zYYNG4wxxvzzzz9m4MCBpnz58iYgIMAEBweb2rVrm7lz57q8rsgcmzFZdIUpcJts3rxZ1apV05dffpmh26wCAHKGwYMH65NPPlF8fLxbbyxgZSNHjlRUVJTOnDmT5u6ngBVwTRBytH///TfNtIkTJ8rDw8P+y+sAgJzr+v342bNnNWPGDNWrV48ABMBtuCYIOdpbb72ljRs3qnHjxsqVK5d++ukn/fTTT+rfv3+a30EAAOQ8derUUaNGjVShQgWdOnVKU6ZMUWxsbLq/zQQAtwMhCDnafffdp8WLF2vUqFGKj49X0aJFNXLkSA0fPtzdpQEAXNCqVSvNnz9fn376qWw2m6pXr64pU6ZwNB+AW3FNEAAAAABL4ZogAAAAAJZCCAIAAABgKf/pa4JSUlL0999/KzAwMEt+cA0AAADAf5MxRnFxcSpUqNBNf2z8Px2C/v77b+4QBgAAAMDu2LFjKlKkyA3b/KdDUGBgoKSrKxoUFOTmagAAAAC4S2xsrCIiIuwZ4Ub+0yEo9RS4oKAgQhAAAAAAly6T4cYIAAAAACyFEAQAAADAUghBAAAAACyFEAQAAADAUghBAAAAACyFEAQAAADAUghBAAAAACyFEAQAAADAUghBAAAAACyFEAQAAADAUghBAAAAACyFEAQAAADAUghBAAAAACyFEAQAAADAUghBAAAAACzFrSGoePHistlsaf4NHDjQnWUBAAAAuIPlcufC169fr+TkZPvj7du3q1mzZurcubMbqwIAAABwJ3NrCAoLC3N4/Oabb6pUqVJq2LChmyoCAAAAcKdzawi61uXLl/Xll19qyJAhstlsTtskJiYqMTHR/jg2NvZ2lQcAAAALi4mJUUJCgrvLyJH8/f0VHBzs7jIyJMeEoG+++UYXLlxQ7969020zduxYRUVF3b6iAAAAYHkxMTEa/dYEnY0jBDmTN9Bfw1949j8VhHJMCJoyZYpatmypQoUKpdtm2LBhGjJkiP1xbGysIiIibkd5AAAAsKiEhASdjUtQaKV6yh0c6u5ycpT4mHM6u2OlEhISCEEZdeTIES1ZskQLFiy4YTsfHx/5+PjcpqoAAACA/5M7OFRBecPdXUaOc87dBWRCjvidoOjoaIWHh6t169buLgUAAADAHc7tISglJUXR0dGKjIxUrlw54sAUAAAAgDuY20PQkiVLdPToUT366KPuLgUAAACABbj90MsDDzwgY4y7ywAAAABgEW4/EgQAAAAAtxMhCAAAAIClEIIAAAAAWAohCAAAAIClEIIAAAAAWAohCAAAAIClEIIAAAAAWAohCAAAAIClEIIAAAAAWAohCAAAAIClEIIAAAAAWAohCAAAAIClEIIAAAAAWAohCAAAAIClEIIAAAAAWAohCAAAAIClEIIAAAAAWAohCAAAAIClEIIAAAAAWAohCAAAAIClEIIAAAAAWAohCAAAAIClEIIAAAAAWAohCAAAAIClEIIAAAAAWAohCAAAAIClEIIAAAAAWAohCAAAAIClEIIAAAAAWAohCAAAAIClEIIAAAAAWAohCAAAAIClEIIAAAAAWAohCAAAAIClEIIAAAAAWAohCAAAAIClEIIAAAAAWAohCAAAAIClEIIAAAAAWAohCAAAAIClEIIAAAAAWAohCAAAAIClEIIAAAAAWAohCAAAAIClEIIAAAAAWAohCAAAAIClEIIAAAAAWAohCAAAAIClEIIAAAAAWAohCAAAAIClEIIAAAAAWAohCAAAAICluD0EHT9+XI888ojy5s0rPz8/3XXXXdqwYYO7ywIAAABwh8rlzoWfP39edevWVePGjfXTTz8pLCxM+/btU548edxZFgAAAIA7mFtD0Lhx4xQREaHo6Gj7tBIlSrixIgAAAAB3OreGoO+++07NmzdX586d9dtvv6lw4cIaMGCA+vXr57R9YmKiEhMT7Y9jY2NvV6kAAACWEBMTo4SEBHeXkaOcOnVKSUmX3V0GspBbQ9DBgwc1efJkDRkyRC+//LLWr1+vQYMGydvbW5GRkWnajx07VlFRUW6oFAAA4M4XExOj0W9N0Nk4QtC1Ei7Ga9fe/SpSJ/HmjfGf4NYQlJKSopo1a2rMmDGSpGrVqmn79u36+OOPnYagYcOGaciQIfbHsbGxioiIuG31AgAA3MkSEhJ0Ni5BoZXqKXdwqLvLyTFOHt2vxB27dSXpirtLQRZxawgqWLCgKlas6DCtQoUK+vrrr5229/HxkY+Pz+0oDQAAwLJyB4cqKG+4u8vIMeLO/+PuEpDF3HqL7Lp162rPnj0O0/bu3atixYq5qSIAAAAAdzq3hqBnn31Wa9as0ZgxY7R//3599dVX+vTTTzVw4EB3lgUAAADgDubWEHTPPfdo4cKFmjVrlipXrqxRo0Zp4sSJ6tGjhzvLAgAAAHAHc+s1QZL04IMP6sEHH3R3GQAAAAAswq1HggAAAADgdiMEAQAAALAUQhAAAAAASyEEAQAAALAUQhAAAAAASyEEAQAAALAUQhAAAAAASyEEAQAAALAUQhAAAAAASyEEAQAAALAUQhAAAAAASyEEAQAAALAUQhAAAAAASyEEAQAAALAUQhAAAAAASyEEAQAAALAUQhAAAAAASyEEAQAAALAUQhAAAAAASyEEAQAAALAUQhAAAAAASyEEAQAAALAUQhAAAAAASyEEAQAAALAUQhAAAAAASyEEAQAAALAUQhAAAAAASyEEAQAAALAUQhAAAAAASyEEAQAAALAUQhAAAAAASyEEAQAAALAUQhAAAAAASyEEAQAAALAUQhAAAAAASyEEAQAAALAUQhAAAAAASyEEAQAAALAUQhAAAAAASyEEAQAAALAUQhAAAAAASyEEAQAAALAUQhAAAAAASyEEAQAAALAUQhAAAAAASyEEAQAAALAUQhAAAAAASyEEAQAAALAUQhAAAAAASyEEAQAAALAUQhAAAAAASyEEAQAAALAUt4agkSNHymazOfwrX768O0sCAAAAcIfL5e4CKlWqpCVLltgf58rl9pIAAAAA3MHcnjhy5cqlAgUKuNQ2MTFRiYmJ9sexsbHZVRYAAACAO5Tbrwnat2+fChUqpJIlS6pHjx46evRoum3Hjh2r4OBg+7+IiIjbWCkAAACAO4FbQ1Dt2rU1depU/fzzz5o8ebIOHTqk+vXrKy4uzmn7YcOGKSYmxv7v2LFjt7liAAAAAP91bj0drmXLlvb/v/vuu1W7dm0VK1ZMc+fOVd++fdO09/HxkY+Pz+0sEQAAAMAdxu2nw10rJCREZcuW1f79+91dCgAAAIA7VI4KQfHx8Tpw4IAKFizo7lIAAAAA3KHcGoKGDh2q3377TYcPH9aqVavUoUMHeXp6qnv37u4sCwAAAMAdzK3XBP3111/q3r27zp49q7CwMNWrV09r1qxRWFiYO8sCAAAAcAdzawiaPXu2OxcPAAAAwIJy1DVBAAAAAJDdCEEAAAAALIUQBAAAAMBSCEEAAAAALIUQBAAAAMBSCEEAAAAALIUQBAAAAMBSCEEAAAAALIUQBAAAAMBSCEEAAAAALIUQBAAAAMBSCEEAAAAALIUQBAAAAMBSCEEAAAAALIUQBAAAAMBSCEEAAAAALIUQBAAAAMBSCEEAAAAALIUQBAAAAMBSCEEAAAAALIUQBAAAAMBSCEEAAAAALIUQBAAAAMBSCEEAAAAALIUQBAAAAMBSCEEAAAAALIUQBAAAAMBSCEEAAAAALIUQBAAAAMBSCEEAAAAALIUQBAAAAMBSCEEAAAAALIUQBAAAAMBSCEEAAAAALIUQBAAAAMBSCEEAAAAALIUQBAAAAMBSCEEAAAAALIUQBAAAAMBSCEEAAAAALIUQBAAAAMBSCEEAAAAALIUQBAAAAMBSMhWCDh48mNV1AAAAAMBtkakQVLp0aTVu3FhffvmlLl26lNU1AQAAAEC2yVQI+vPPP3X33XdryJAhKlCggB5//HGtW7cuq2sDAAAAgCyXqRBUtWpVTZo0SX///be++OILnThxQvXq1VPlypX17rvv6syZM1ldJwAAAABkiVu6MUKuXLnUsWNHzZs3T+PGjdP+/fs1dOhQRUREqFevXjpx4kRW1QkAAAAAWeKWQtCGDRs0YMAAFSxYUO+++66GDh2qAwcOaPHixfr777/Vrl27rKoTAAAAALJErsz80bvvvqvo6Gjt2bNHrVq10vTp09WqVSt5eFzNVCVKlNDUqVNVvHjxrKwVAAAAAG5ZpkLQ5MmT9eijj6p3794qWLCg0zbh4eGaMmXKLRUHAAAAAFktU6fD7du3T8OGDUs3AEmSt7e3IiMjXZ7nm2++KZvNpsGDB2emJAAAAABwSaZCUHR0tObNm5dm+rx58zRt2rQMz2/9+vX65JNPdPfdd2emHAAAAABwWaZC0NixY5UvX74008PDwzVmzJgMzSs+Pl49evTQZ599pjx58mSmHAAAAABwWaauCTp69KhKlCiRZnqxYsV09OjRDM1r4MCBat26tZo2bao33njjhm0TExOVmJhofxwbG5uhZQH474iJiVFCQoK7y8hx/P39FRwc7O4ygDsC+5m0Tp06paSky+4uA8h2mQpB4eHh2rp1a5q7v23ZskV58+Z1eT6zZ8/Wn3/+qfXr17vUfuzYsYqKispIqQD+g2JiYjT6rQk6G8eHk+vlDfTX8BeeJQgBt4j9jHMJF+O1a+9+FamTePPGwH9YpkJQ9+7dNWjQIAUGBqpBgwaSpN9++03PPPOMunXr5tI8jh07pmeeeUaLFy+Wr6+vS38zbNgwDRkyxP44NjZWERERGV8BADlaQkKCzsYlKLRSPeUODnV3OTlGfMw5nd2xUgkJCYQg4Baxn3Hu5NH9StyxW1eSrri7FCBbZSoEjRo1SocPH1aTJk2UK9fVWaSkpKhXr14uXxO0ceNGnT59WtWrV7dPS05O1u+//64PPvhAiYmJ8vT0dPgbHx8f+fj4ZKZkAP9BuYNDFZQ33N1l5Cjn3F0AcIdhP+Mo7vw/7i4BuC0yFYK8vb01Z84cjRo1Slu2bJGfn5/uuusuFStWzOV5NGnSRNu2bXOY1qdPH5UvX14vvvhimgAEAAAAAFkhUyEoVdmyZVW2bNlM/W1gYKAqV67sMC0gIEB58+ZNMx0AAAAAskqmQlBycrKmTp2qpUuX6vTp00pJSXF4/tdff82S4gAAAAAgq2UqBD3zzDOaOnWqWrdurcqVK8tms2VJMcuXL8+S+QAAAABAejIVgmbPnq25c+eqVatWWV0PAAAAAGQrj8z8kbe3t0qXLp3VtQAAAABAtstUCHruuec0adIkGWOyuh4AAAAAyFaZOh1u5cqVWrZsmX766SdVqlRJXl5eDs8vWLAgS4oDAAAAgKyWqRAUEhKiDh06ZHUtAAAAAJDtMhWCoqOjs7oOAAAAALgtMnVNkCRduXJFS5Ys0SeffKK4uDhJ0t9//634+PgsKw4AAAAAslqmjgQdOXJELVq00NGjR5WYmKhmzZopMDBQ48aNU2Jioj7++OOsrhMAAAAAskSmjgQ988wzqlmzps6fPy8/Pz/79A4dOmjp0qVZVhwAAAAAZLVMHQlasWKFVq1aJW9vb4fpxYsX1/Hjx7OkMAAAAADIDpk6EpSSkqLk5OQ00//66y8FBgbeclEAAAAAkF0yFYIeeOABTZw40f7YZrMpPj5eI0aMUKtWrbKqNgAAAADIcpk6HW78+PFq3ry5KlasqEuXLunhhx/Wvn37lC9fPs2aNSurawQAAACALJOpEFSkSBFt2bJFs2fP1tatWxUfH6++ffuqR48eDjdKAAAAAICcJlMhSJJy5cqlRx55JCtrAQAAAIBsl6kQNH369Bs+36tXr0wVAwAAAADZLVMh6JlnnnF4nJSUpISEBHl7e8vf358QBAAAACDHytTd4c6fP+/wLz4+Xnv27FG9evW4MQIAAACAHC1TIciZMmXK6M0330xzlAgAAAAAcpIsC0HS1Zsl/P3331k5SwAAAADIUpm6Jui7775zeGyM0YkTJ/TBBx+obt26WVIYAAAAAGSHTIWg9u3bOzy22WwKCwvT/fffr/Hjx2dFXQAAAACQLTIVglJSUrK6DgAAAAC4LbL0miAAAAAAyOkydSRoyJAhLrd99913M7MIAAAAAMgWmQpBmzZt0qZNm5SUlKRy5cpJkvbu3StPT09Vr17d3s5ms2VNlQAAAACQRTIVgtq0aaPAwEBNmzZNefLkkXT1B1T79Omj+vXr67nnnsvSIgEAAAAgq2TqmqDx48dr7Nix9gAkSXny5NEbb7zB3eEAAAAA5GiZCkGxsbE6c+ZMmulnzpxRXFzcLRcFAAAAANklUyGoQ4cO6tOnjxYsWKC//vpLf/31l77++mv17dtXHTt2zOoaAQAAACDLZOqaoI8//lhDhw7Vww8/rKSkpKszypVLffv21dtvv52lBQIAAABAVspUCPL399dHH32kt99+WwcOHJAklSpVSgEBAVlaHAAAAABktVv6sdQTJ07oxIkTKlOmjAICAmSMyaq6AAAAACBbZCoEnT17Vk2aNFHZsmXVqlUrnThxQpLUt29fbo8NAAAAIEfLVAh69tln5eXlpaNHj8rf398+vWvXrvr555+zrDgAAAAAyGqZuibol19+0aJFi1SkSBGH6WXKlNGRI0eypDAAAAAAyA6ZOhJ08eJFhyNAqc6dOycfH59bLgoAAAAAskumQlD9+vU1ffp0+2ObzaaUlBS99dZbaty4cZYVBwAAAABZLVOnw7311ltq0qSJNmzYoMuXL+uFF17Qjh07dO7cOf3xxx9ZXSMAAAAAZJlMHQmqXLmy9u7dq3r16qldu3a6ePGiOnbsqE2bNqlUqVJZXSMAAAAAZJkMHwlKSkpSixYt9PHHH2v48OHZURMAAAAAZJsMHwny8vLS1q1bs6MWAAAAAMh2mTod7pFHHtGUKVOyuhYAAAAAyHaZujHClStX9MUXX2jJkiWqUaOGAgICHJ5/9913s6Q4AAAAAMhqGQpBBw8eVPHixbV9+3ZVr15dkrR3716HNjabLeuqAwAAAIAslqEQVKZMGZ04cULLli2TJHXt2lXvvfee8ufPny3FAQAAAEBWy9A1QcYYh8c//fSTLl68mKUFAQAAAEB2ytSNEVJdH4oAAAAAIKfLUAiy2WxprvnhGiAAAAAA/yUZuibIGKPevXvLx8dHknTp0iU98cQTae4Ot2DBgqyrEAAAAACyUIZCUGRkpMPjRx55JEuLAQAAAIDslqEQFB0dnV11AAAAAMBtcUs3RrhVkydP1t13362goCAFBQWpTp06+umnn9xZEgAAAIA7nFtDUJEiRfTmm29q48aN2rBhg+6//361a9dOO3bscGdZAAAAAO5gGTodLqu1adPG4fHo0aM1efJkrVmzRpUqVXJTVQAAAADuZG4NQddKTk7WvHnzdPHiRdWpU8dpm8TERCUmJtofx8bG3q7yAAA5XExMjBISEtxdRo7j7++v4OBgd5cBADmK20PQtm3bVKdOHV26dEm5c+fWwoULVbFiRadtx44dq6ioqNtcIQAgp4uJidHotybobBwh6Hp5A/01/IVnCUIAcA23h6By5cpp8+bNiomJ0fz58xUZGanffvvNaRAaNmyYhgwZYn8cGxuriIiI21kuACAHSkhI0Nm4BIVWqqfcwaHuLifHiI85p7M7ViohIYEQBADXcHsI8vb2VunSpSVJNWrU0Pr16zVp0iR98sknadr6+PjYf6gVAIDr5Q4OVVDecHeXkaOcc3cBAJADufXucM6kpKQ4XPcDAAAAAFnJrUeChg0bppYtW6po0aKKi4vTV199peXLl2vRokXuLAsAAADAHcytIej06dPq1auXTpw4oeDgYN19991atGiRmjVr5s6yAAAAANzB3BqCpkyZ4s7FAwAAALCgHHdNEAAAAABkJ0IQAAAAAEshBAEAAACwFEIQAAAAAEshBAEAAACwFEIQAAAAAEshBAEAAACwFEIQAAAAAEshBAEAAACwFEIQAAAAAEshBAEAAACwFEIQAAAAAEshBAEAAACwFEIQAAAAAEshBAEAAACwFEIQAAAAAEshBAEAAACwFEIQAAAAAEshBAEAAACwFEIQAAAAAEshBAEAAACwFEIQAAAAAEshBAEAAACwFEIQAAAAAEshBAEAAACwFEIQAAAAAEshBAEAAACwFEIQAAAAAEshBAEAAACwFEIQAAAAAEshBAEAAACwFEIQAAAAAEshBAEAAACwFEIQAAAAAEshBAEAAACwFEIQAAAAAEshBAEAAACwFEIQAAAAAEshBAEAAACwFEIQAAAAAEshBAEAAACwFEIQAAAAAEshBAEAAACwFEIQAAAAAEshBAEAAACwFEIQAAAAAEshBAEAAACwFEIQAAAAAEshBAEAAACwFEIQAAAAAEshBAEAAACwFEIQAAAAAEtxawgaO3as7rnnHgUGBio8PFzt27fXnj173FkSAAAAgDucW0PQb7/9poEDB2rNmjVavHixkpKS9MADD+jixYvuLAsAAADAHSyXOxf+888/OzyeOnWqwsPDtXHjRjVo0MBNVQEAAAC4k7k1BF0vJiZGkhQaGur0+cTERCUmJtofx8bG3pa6gOwSExOjhIQEd5eR45w6dUpJSZfdXUaOdDkxUadOnXJ3GTkOYwYAkBE5JgSlpKRo8ODBqlu3ripXruy0zdixYxUVFXWbKwOyR0xMjEa/NUFn4whB10u4GK9de/erSJ3Emze2kEsJ8dq6bave+nCK/Pz83F1OjsKYAQBkRI4JQQMHDtT27du1cuXKdNsMGzZMQ4YMsT+OjY1VRETE7SgPyHIJCQk6G5eg0Er1lDvY+dFPqzp5dL8Sd+zWlaQr7i4lR0lKvKTLKTblqVhX4QWLuLucHIUxAwDIiBwRgp566il9//33+v3331WkSPpv7D4+PvLx8bmNlQHZL3dwqILyhru7jBwl7vw/7i4hRwsIysOYuQ5jBgCQEW4NQcYYPf3001q4cKGWL1+uEiVKuLMcAAAAABbg1hA0cOBAffXVV/r2228VGBiokydPSpKCg4M53x0AAABAtnDr7wRNnjxZMTExatSokQoWLGj/N2fOHHeWBQAAAOAO5vbT4QAAAADgdnLrkSAAAAAAuN0IQQAAAAAshRAEAAAAwFIIQQAAAAAshRAEAAAAwFIIQQAAAAAshRAEAAAAwFIIQQAAAAAshRAEAAAAwFIIQQAAAAAshRAEAAAAwFIIQQAAAAAshRAEAAAAwFIIQQAAAAAshRAEAAAAwFIIQQAAAAAshRAEAAAAwFIIQQAAAAAshRAEAAAAwFIIQQAAAAAshRAEAAAAwFIIQQAAAAAshRAEAAAAwFIIQQAAAAAshRAEAAAAwFIIQQAAAAAshRAEAAAAwFIIQQAAAAAshRAEAAAAwFIIQQAAAAAshRAEAAAAwFIIQQAAAAAshRAEAAAAwFIIQQAAAAAshRAEAAAAwFIIQQAAAAAshRAEAAAAwFIIQQAAAAAshRAEAAAAwFIIQQAAAAAshRAEAAAAwFIIQQAAAAAshRAEAAAAwFIIQQAAAAAshRAEAAAAwFIIQQAAAAAshRAEAAAAwFIIQQAAAAAshRAEAAAAwFIIQQAAAAAshRAEAAAAwFIIQQAAAAAsxa0h6Pfff1ebNm1UqFAh2Ww2ffPNN+4sBwAAAIAFuDUEXbx4UVWqVNGHH37ozjIAAAAAWEgudy68ZcuWatmypTtLAAAAAGAxbg1BGZWYmKjExET749jYWDdWk1ZMTIwSEhLcXUaO5O/vr+DgYHeXAQCWczkxUadOnXJ3GTnOqVOnlJR02d1lAHCT/1QIGjt2rKKiotxdhlMxMTEa/dYEnY0jBDmTN9Bfw194liAEALfRpYR4bd22VW99OEV+fn7uLidHSbgYr11796tIncSbNwZwx/lPhaBhw4ZpyJAh9sexsbGKiIhwY0X/JyEhQWfjEhRaqZ5yB4e6u5wcJT7mnM7uWKmEhARCEADcRkmJl3Q5xaY8FesqvGARd5eTo5w8ul+JO3brStIVd5cCwA3+UyHIx8dHPj4+7i7jhnIHhyoob7i7y8hxzrm7AACwsICgPLw3XSfu/D/uLgGAG/E7QQAAAAAsxa1HguLj47V//37740OHDmnz5s0KDQ1V0aJF3VgZAAAAgDuVW0PQhg0b1LhxY/vj1Ot9IiMjNXXqVDdVBQAAAOBO5tYQ1KhRIxlj3FkCAAAAAIvhmiAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGApOSIEffjhhypevLh8fX1Vu3ZtrVu3zt0lAQAAALhDuT0EzZkzR0OGDNGIESP0559/qkqVKmrevLlOnz7t7tIAAAAA3IHcHoLeffdd9evXT3369FHFihX18ccfy9/fX1988YW7SwMAAABwB8rlzoVfvnxZGzdu1LBhw+zTPDw81LRpU61evTpN+8TERCUmJtofx8TESJJiY2Ozv9ibiIuL0+XLiTp78i9dSrjo7nJylIux53UxPk4HDhxQXFycu8vJMU6fPq2EhHjGjBPnz5xQ8pUrOn/6uDxt7q4m56Bf0kffOEe/pI++cY5+cY5+Sd/F2PO6fDlRcXFxCggIcGstqZnAGHPTtjbjSqts8vfff6tw4cJatWqV6tSpY5/+wgsv6LffftPatWsd2o8cOVJRUVG3u0wAAAAA/xHHjh1TkSJFbtjGrUeCMmrYsGEaMmSI/XFKSorOnTunvHnzymZzbyyPjY1VRESEjh07pqCgILfWktPQN87RL+mjb5yjX9JH3zhHv6SPvnGOfnGOfklfTuobY4zi4uJUqFChm7Z1awjKly+fPD09derUKYfpp06dUoECBdK09/HxkY+Pj8O0kJCQ7Cwxw4KCgtw+AHIq+sY5+iV99I1z9Ev66Bvn6Jf00TfO0S/O0S/pyyl9Exwc7FI7t94YwdvbWzVq1NDSpUvt01JSUrR06VKH0+MAAAAAIKu4/XS4IUOGKDIyUjVr1lStWrU0ceJEXbx4UX369HF3aQAAAADuQG4PQV27dtWZM2f02muv6eTJk6patap+/vln5c+f392lZYiPj49GjBiR5nQ90DfpoV/SR984R7+kj75xjn5JH33jHP3iHP2Svv9q37j17nAAAAAAcLu5/cdSAQAAAOB2IgQBAAAAsBRCEAAAAABLIQQBAAAAsBTLhqAPP/xQxYsXl6+vr2rXrq1169al23bBggWqWbOmQkJCFBAQoKpVq2rGjBkObU6dOqXevXurUKFC8vf3V4sWLbRv3z6HNgcOHFCHDh0UFhamoKAgdenSJc0PxUrSDz/8oNq1a8vPz0958uRR+/bts2SdXZWRvrnW7NmzZbPZbljvE088IZvNpokTJ9qnLV++XDabzem/9evX29stWrRI9957rwIDAxUWFqaHHnpIhw8fzuRaZlxW94srY0aSVq9erfvvv18BAQEKCgpSgwYN9O+//9qfP3funHr06KGgoCCFhISob9++io+Pv6V1zaiM9M3UqVPTvM6+vr7ptnc2Zq6VmJioqlWrymazafPmzfbpy5cvV7t27VSwYEH7djtz5szMrmKmZHW/3GzMnDt3Tk8//bTKlSsnPz8/FS1aVIMGDVJMTIzTZZ49e1ZFihSRzWbThQsXsmSdXZHRbenChQsaOHCgChYsKB8fH5UtW1Y//vij07ZvvvmmbDabBg8e7DD90qVLGjhwoPLmzavcuXProYcecrr/nTp1qu6++275+voqPDxcAwcOzPR6ZkZW901ycrJeffVVlShRQn5+fipVqpRGjRqla++JFB8fr6eeekpFihSRn5+fKlasqI8//thhOSdPnlTPnj1VoEABBQQEqHr16vr666+zduVvICP90qhRI6fvJ61bt7a3GTlypMqXL6+AgADlyZNHTZs21dq1a+3Pu/q+tHXrVtWvX1++vr6KiIjQW2+9lT0dcANZ3TeujAdn83niiSfsz2/ZskXdu3dXRESE/Pz8VKFCBU2aNCnrV/4GMrotTZw40b7vjIiI0LPPPqtLly7Zn588ebLuvvtu+w+C1qlTRz/99JPDPB5//HGVKlVKfn5+CgsLU7t27bR7926ny/uv7H9v1i+u7GMWLFigBx54QHnz5k3zXn2tm33eyXLGgmbPnm28vb3NF198YXbs2GH69etnQkJCzKlTp5y2X7ZsmVmwYIHZuXOn2b9/v5k4caLx9PQ0P//8szHGmJSUFHPvvfea+vXrm3Xr1pndu3eb/v37m6JFi5r4+HhjjDHx8fGmZMmSpkOHDmbr1q1m69atpl27duaee+4xycnJ9mXNnz/f5MmTx0yePNns2bPH7Nixw8yZMyf7O+X/y2jfpDp06JApXLiwqV+/vmnXrp3TNgsWLDBVqlQxhQoVMhMmTLBPT0xMNCdOnHD499hjj5kSJUqYlJQUY4wxBw8eND4+PmbYsGFm//79ZuPGjaZBgwamWrVqWbXqN5TV/eLKmDHGmFWrVpmgoCAzduxYs337drN7924zZ84cc+nSJXubFi1amCpVqpg1a9aYFStWmNKlS5vu3btneR+kJ6N9Ex0dbYKCghxe75MnTzptm96YudagQYNMy5YtjSSzadMm+/TRo0ebV155xfzxxx/27dbDw8P873//u9VVdklW94srY2bbtm2mY8eO5rvvvjP79+83S5cuNWXKlDEPPfSQ02W2a9fO3nfnz5/P8j5wJqP9kpiYaGrWrGlatWplVq5caQ4dOmSWL19uNm/enKbtunXrTPHixc3dd99tnnnmGYfnnnjiCRMREWGWLl1qNmzYYO69915z3333ObQZP368KVSokJk5c6bZv3+/2bJli/n222+zbN1vJjv6ZvTo0SZv3rzm+++/N4cOHTLz5s0zuXPnNpMmTbK36devnylVqpRZtmyZOXTokPnkk0+Mp6enw7o3a9bM3HPPPWbt2rXmwIEDZtSoUcbDw8P8+eef2dch/19G++Xs2bMO29H27duNp6eniY6OtreZOXOmWbx4sTlw4IDZvn276du3rwkKCjKnT582xrj2vhQTE2Py589vevToYbZv325mzZpl/Pz8zCeffJLtfZIqO/rGlfHQsGFD069fP4d5xcTE2J+fMmWKGTRokFm+fLk5cOCAmTFjhvHz8zPvv/9+tvXFtTLaLzNnzjQ+Pj5m5syZ5tChQ2bRokWmYMGC5tlnn7W3+e6778wPP/xg9u7da/bs2WNefvll4+XlZbZv325v88knn5jffvvNHDp0yGzcuNG0adPGREREmCtXrqRZ5n9h/+tKv7iyj5k+fbqJiooyn332WZr36lSufN7JapYMQbVq1TIDBw60P05OTjaFChUyY8eOdXke1apVM6+88ooxxpg9e/YYSQ4bQnJysgkLCzOfffaZMcaYRYsWGQ8PD4edxIULF4zNZjOLFy82xhiTlJRkChcubD7//PNbWr9bkZm+uXLlirnvvvvM559/biIjI52GoL/++ssULlzYbN++3RQrVizdD7TGGHP58mUTFhZmXn/9dfu0efPmmVy5cjkExu+++87YbDZz+fLljK1kJmR1v7gyZowxpnbt2vZx5szOnTuNJLN+/Xr7tJ9++snYbDZz/PjxjK5mpmS0b6Kjo01wcPBN5+vKmPnxxx9N+fLlzY4dO9LdsV6rVatWpk+fPjdddlbI6n5xdcxcb+7cucbb29skJSU5TP/oo49Mw4YNzdKlS2/rm3BG+2Xy5MmmZMmSN93O4+LiTJkyZczixYtNw4YNHULQhQsXjJeXl5k3b5592q5du4wks3r1amOMMefOnTN+fn5myZIlt7B2tyY7+qZ169bm0UcfdZjWsWNH06NHD/vjSpUqOexvjTGmevXqZvjw4fbHAQEBZvr06Q5tQkNDbzj2ssqtvmdPmDDBBAYGOnzBdL2YmBgjKd3X39n70kcffWTy5MljEhMT7dNefPFFU65cOZfqygrZ0TeujIfrtzFXDBgwwDRu3DhDf5NZGe2XgQMHmvvvv99h2pAhQ0zdunVvuJw8efLc8DPbli1bjCSzf/9+h+n/lf2vK/3iyj4m1aFDh9J9r77Z553sYLnT4S5fvqyNGzeqadOm9mkeHh5q2rSpVq9efdO/N8Zo6dKl2rNnjxo0aCDp6uk4khxOXfHw8JCPj49Wrlxpb2Oz2Rx+SMrX11ceHh72Nn/++aeOHz8uDw8PVatWTQULFlTLli21ffv2W19xF2S2b15//XWFh4erb9++Tp9PSUlRz5499fzzz6tSpUo3reO7777T2bNn1adPH/u0GjVqyMPDQ9HR0UpOTlZMTIxmzJihpk2bysvLKwNrmXHZ0S+ujJnTp09r7dq1Cg8P13333af8+fOrYcOG9uelq4eOQ0JCVLNmTfu0pk2bysPDw+HUjuyS2b6Jj49XsWLFFBERoXbt2mnHjh0Oz7syZk6dOqV+/fppxowZ8vf3d6nemJgYhYaGutT2VmRHv7gyZpyJiYlRUFCQcuX6v9/G3rlzp15//XVNnz5dHh63720gM/3y3XffqU6dOho4cKDy58+vypUra8yYMUpOTnZoN3DgQLVu3dph3qk2btyopKQkh+fKly+vokWL2pe7ePFipaSk6Pjx46pQoYKKFCmiLl266NixY1mx6jeVXX1z3333aenSpdq7d6+kq6cprVy5Ui1btnRo89133+n48eMyxmjZsmXau3evHnjgAYc2c+bM0blz55SSkqLZs2fr0qVLatSoURb3hKNbfc+WpClTpqhbt24KCAhIdxmffvqpgoODVaVKFadtnL0vrV69Wg0aNJC3t7d9WvPmzbVnzx6dP3/epdpuRXb1jSvjQZJmzpypfPnyqXLlyho2bJgSEhJuuKycvP+97777tHHjRvupYQcPHtSPP/6oVq1aOW2fnJys2bNn6+LFi6pTp47TNhcvXlR0dLRKlCihiIgI+/T/0v7XlX5xZR9zM6583skWtzVy5QDHjx83ksyqVascpj///POmVq1a6f7dhQsXTEBAgMmVK5fx8fExU6ZMsT93+fJlU7RoUdO5c2dz7tw5k5iYaN58800jyTzwwAPGGGNOnz5tgoKCzDPPPGMuXrxo4uPjzVNPPWUkmf79+xtjjJk1a5aRZIoWLWrmz59vNmzYYLp3727y5s1rzp49mw294SgzfbNixQpTuHBhc+bMGWOMcXokaMyYMaZZs2b2UwhudiSoZcuWpmXLlmmmL1++3ISHhxtPT08jydSpU+e2fHuSHf3iyphZvXq1kWRCQ0PNF198Yf78808zePBg4+3tbfbu3WuMuXoYumzZsmmWHxYWZj766KOsWP0bykzfrFq1ykybNs1s2rTJLF++3Dz44IMmKCjIHDt2zN7mZmMmJSXFtGjRwowaNcoYc+Nvl1LNmTPHeHt7OxxJyS7Z0S+ujJnrnTlzxhQtWtS8/PLL9mmXLl0yd999t5kxY4Yx5urpvrpN30Rmpl/KlStnfHx8zKOPPmo2bNhgZs+ebUJDQ83IkSPtbWbNmmUqV65s/v33X2NM2m+pZ86caby9vdPM+5577jEvvPCCMcaYsWPHGi8vL1OuXDnz888/m9WrV5smTZqYcuXKOXzTn12yq2+Sk5PNiy++aGw2m8mVK5ex2WxmzJgxDvO5dOmS6dWrl5FkcuXKZby9vc20adMc2pw/f9488MAD9jZBQUFm0aJFWbT26cvse3aqtWvXGklm7dq1aZ773//+ZwICAozNZjOFChUy69atS3c+zt6XmjVrZn//TpV6VHrnzp03re1WZVffuDIePvnkE/Pzzz+brVu3mi+//NIULlzYdOjQId1l/fHHHyZXrlw5esxMmjTJeHl5mVy5chlJ5oknnkjTZuvWrSYgIMB4enqa4OBg88MPP6Rp8+GHH5qAgAAjyZQrV87hKNB/bf9rzM37xZV9TKr03qtd+byTHSx3JCizAgMDtXnzZq1fv16jR4/WkCFDtHz5ckmSl5eXFixYoL179yo0NFT+/v5atmyZWrZsaU/5YWFhmjdvnv73v/8pd+7cCg4O1oULF1S9enV7m5SUFEnS8OHD9dBDD6lGjRqKjo6WzWbTvHnz3LLeNxIXF6eePXvqs88+U758+Zy22bhxoyZNmmS/6Ptm/vrrLy1atCjN0ZOTJ0+qX79+ioyM1Pr16/Xbb7/J29tbnTp1crj4LidwpV9cGTOp4+Hxxx9Xnz59VK1aNU2YMEHlypXTF198cdvWJ6vVqVNHvXr1UtWqVdWwYUMtWLBAYWFh+uSTTyS5Nmbef/99xcXFadiwYS4tc9myZerTp48+++wzl45GusPN+sWVMXOt2NhYtW7dWhUrVtTIkSPt04cNG6YKFSrokUceuV2rdktSUlIUHh6uTz/9VDVq1FDXrl01fPhw+4Xax44d0zPPPKOZM2fe8AYbriwnKSlJ7733npo3b657771Xs2bN0r59+7Rs2bKsWp0sdbO+kaS5c+dq5syZ+uqrr/Tnn39q2rRpeueddzRt2jR7m/fff19r1qzRd999p40bN2r8+PEaOHCglixZYm/z6quv6sKFC1qyZIk2bNigIUOGqEuXLtq2bdttXeeMmjJliu666y7VqlUrzXONGzfW5s2btWrVKrVo0UJdunTR6dOn07RL733pvy69vnFlPPTv31/NmzfXXXfdpR49emj69OlauHChDhw4kGY527dvV7t27TRixIg0R5NyiuXLl2vMmDH66KOP9Oeff2rBggX64YcfNGrUKId25cqV0+bNm7V27Vo9+eSTioyM1M6dOx3a9OjRQ5s2bdJvv/2msmXLqkuXLvYbCfzX9r+u9Isr+5ibcdvnnWyLVzlUYmKi8fT0NAsXLnSY3qtXL9O2bVuX59O3b1+n375euHDBfmFlrVq1zIABA9K0OXPmjD3158+f37z11lvGGGN+/fVXI8msWLHCoX2tWrUcvsnNLhntm02bNhlJxtPT0/7PZrMZm81mPD09zf79+82ECRPsj1P/STIeHh6mWLFiaeb5+uuvm7CwsDTnuL/yyiumZs2aDtOOHTvmcE5/dsmOfrlWemPm4MGDRpL9G6NUXbp0MQ8//LAx5urFpyEhIQ7PJyUlGU9PT7NgwYJbWm9XZNX21KlTJ9OtWzdjjHFpzLRr1854eHikaePp6Wl69erlMO/ly5ebgICA23qxcnb0y7Vutp+JjY01derUMU2aNLEfHUlVpUoVh77z8PCw991rr73mcm2ZkZl+adCggWnSpInDtB9//NFIMomJiWbhwoVptjdJ9jF05cqVdM+7L1q0qHn33XeNMcZ88cUXRpLDEUljjAkPDzeffvrpra24C7Kjb4wxpkiRIuaDDz5waDNq1Cj7dSsJCQnGy8vLfP/99w5t+vbta5o3b26MMWb//v1prkczxpgmTZqYxx9/PGMrmkG3si3Fx8eboKAgM3HiRJeWVbp0aaffYKf3vtSzZ880Zz6kvo+fO3fOpWXeiuzoG1fGQ3rzk2S/YVSqHTt2mPDw8NvyGSZVZvqlXr16ZujQoQ7TUm/mcO21yNdr0qRJmqOB19fi7+9vvvrqK2PMf2//60q/3Gwfc630jgS58nknO1juSJC3t7dq1KihpUuX2qelpKRo6dKl6Z7X6UxKSor9HP1rBQcHKywsTPv27dOGDRvUrl27NG3y5cunkJAQ/frrrzp9+rTatm0r6ep1Lz4+PtqzZ4+9bVJSkg4fPqxixYplZDUzJaN9U758eW3btk2bN2+2/2vbtq3927WIiAj17NlTW7dudWhTqFAhPf/881q0aJHD/Iwxio6OVq9evdJc55OQkJDm225PT097jdkpO/rlWumNmeLFi6tQoUIO40GS9u7dax8PderU0YULF7Rx40b787/++qtSUlJUu3btLOuD9GTF9pScnKxt27apYMGCkuTSmHnvvfe0ZcsW+/OptwSeM2eORo8ebZ/38uXL1bp1a40bN079+/fPqtW+qezol2vdaD8TGxurBx54QN7e3vruu+/SHB35+uuvHfru888/lyStWLEi228HnZl+qVu3rvbv3++wne/du1cFCxaUt7e3mjRpkmZ7q1mzpnr06KHNmzfL09NTNWrUkJeXl8Ny9+zZo6NHj9qXW7duXfv0VOfOndM///yTI/e/0s37Rkp/35n6N0lJSUpKSrphm9RrPW7UJrvcyrY0b948JSYmuvytu7P39Ru9L9WpU0e///67kpKS7NMWL16scuXKKU+ePC4t81ZkR9+4Mh6cSb3l8bX7qx07dqhx48aKjIx02C9nt8z0y40+Y5gbnG2S3mfBVObqDcjsbf5r+19X+uVm+xhXuPJ5J1tkW7zKwWbPnm18fHzM1KlTzc6dO03//v1NSEiI/Xa0PXv2NC+99JK9/ZgxY8wvv/xiDhw4YHbu3GneeecdkytXLoe74sydO9csW7bMHDhwwHzzzTemWLFipmPHjg7L/eKLL8zq1avN/v37zYwZM0xoaKgZMmSIQ5tnnnnGFC5c2CxatMjs3r3b9O3b14SHh9+Wb5WMyXjfXC+9u8NdK71rgpYsWWIkmV27dqV5bunSpcZms5moqCizd+9es3HjRtO8eXNTrFgxk5CQkKF1zIzs6BdXxsyECRNMUFCQmTdvntm3b5955ZVXjK+vr8PRpBYtWphq1aqZtWvXmpUrV5oyZcrc9ltkZ6RvoqKizKJFi8yBAwfMxo0bTbdu3Yyvr6/ZsWNHusu42XVkzr5d+vXXX42/v78ZNmyYw21cb8f1dcZkT7/cbMzExMSY2rVrm7vuusvs37/fYb2d3aLVmNt7TroxGe+Xo0ePmsDAQPPUU0+ZPXv2mO+//96Eh4ebN954I91lOLtz1RNPPGGKFi1qfv31V7NhwwZTp04dU6dOHYc27dq1M5UqVTJ//PGH2bZtm3nwwQdNxYoVb8sdKI3Jnr6JjIw0hQsXtt++dsGCBSZfvnz2a6GMudpflSpVMsuWLTMHDx400dHRxtfX135d4eXLl03p0qVN/fr1zdq1a83+/fvNO++8Y2w2m9NrItzdL6nq1atnunbtmmZ6fHy8GTZsmFm9erU5fPiw2bBhg+nTp4/x8fFJc7TrRu9LFy5cMPnz5zc9e/Y027dvN7Nnzzb+/v63/RbZWdk3xtx8POzfv9+8/vrrZsOGDebQoUPm22+/NSVLljQNGjSwz2Pbtm0mLCzMPPLIIw77odQj2Nkto/0yYsQIExgYaGbNmmUOHjxofvnlF1OqVCnTpUsXe5uXXnrJfvvrrVu3mpdeesnYbDbzyy+/GGOMOXDggBkzZozZsGGDOXLkiPnjjz9MmzZtTGho6A1/giUn739d6RdX9jFnz541mzZtMj/88IORZGbPnm02bdpkTpw4YW/jyuedrGbJEGSMMe+//74pWrSo8fb2NrVq1TJr1qyxP9ewYUMTGRlpfzx8+HBTunRp4+vra/LkyWPq1KljZs+e7TC/SZMmmSJFihgvLy9TtGhR88orr6S5mPbFF180+fPnN15eXqZMmTJm/Pjx9gu/U12+fNk899xzJjw83AQGBpqmTZvelgu5r5WRvrnerYSg7t27p/ndjmvNmjXLVKtWzQQEBJiwsDDTtm1bp29M2SWr+8WVMWPM1Qu2ixQpYvz9/U2dOnXSnC559uxZ0717d5M7d24TFBRk+vTpY+Li4m5pXTMqI30zePBge9v8+fObVq1a3fS3RjITgiIjI42kNP8aNmyYybXMuKzul5uNmdQ3VGf/Dh065LTG2/0mbEzGt6VVq1aZ2rVrGx8fH1OyZEkzevTodENd6jyuD0H//vuvGTBggMmTJ4/x9/c3HTp0cHgDNuZqiHz00UdNSEiICQ0NNR06dDBHjx695fXNiKzum9jYWPPMM8+YokWLGl9fX1OyZEkzfPhwh3Fz4sQJ07t3b1OoUCHj6+trypUrl+b9ae/evaZjx44mPDzc+Pv7m7vvvjvNLbOzU0b7Zffu3UaS/QPqtf7991/ToUMHU6hQIePt7W0KFixo2rZt6/TGCDd7X9qyZYupV6+e8fHxMYULFzZvvvlm5lcyk7Kyb4y5+Xg4evSoadCggQkNDTU+Pj6mdOnS5vnnn3f4CZARI0Y43Q85Ow0+u2SkX5KSkszIkSNNqVKljK+vr4mIiDADBgxw2C8++uijplixYsbb29uEhYWZJk2aOPTh8ePHTcuWLU14eLjx8vIyRYoUMQ8//LDZvXt3ujXm9P2vK/3iyj4mOjra6XgYMWKEQ203+7yT1WzG5LCrygEAAAAgG1numiAAAAAA1kYIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAAAAAlkIIAgAAAGAphCAAwB3BZrPpm2++yTHzAQDkXIQgAECmnDx5Uk8//bRKliwpHx8fRUREqE2bNlq6dKm7S3PJyJEjVbVq1TTTT5w4oZYtW97+ggAAt00udxcAAPjvOXz4sOrWrauQkBC9/fbbuuuuu5SUlKRFixZp4MCB2r17d4bnefnyZXl7e6eZnpSUJC8vr6wo2yUFChS4bcsCALgHR4IAABk2YMAA2Ww2rVu3Tg899JDKli2rSpUqaciQIVqzZo0k6ejRo2rXrp1y586toKAgdenSRadOnbLPI/VIzOeff64SJUrI19dX0tXT0SZPnqy2bdsqICBAo0ePliR9++23ql69unx9fVWyZElFRUXpypUr6db44osvqmzZsvL391fJkiX16quvKikpSZI0depURUVFacuWLbLZbLLZbJo6dap9+deeDrdt2zbdf//98vPzU968edW/f3/Fx8fbn+/du7fat2+vd955RwULFlTevHk1cOBA+7IAADkPR4IAABly7tw5/fzzzxo9erQCAgLSPB8SEqKUlBR7APrtt9905coVDRw4UF27dtXy5cvtbffv36+vv/5aCxYskKenp336yJEj9eabb2rixInKlSuXVqxYoV69eum9995T/fr1deDAAfXv31+SNGLECKd1BgYGaurUqSpUqJC2bdumfv36KTAwUC+88IK6du2q7du36+eff9aSJUskScHBwWnmcfHiRTVv3lx16tTR+vXrdfr0aT322GN66qmn7KFJkpYtW6aCBQtq2bJl2r9/v7p27aqqVauqX79+meliAEA2IwQBADJk//79MsaofPny6bZZunSptm3bpkOHDikiIkKSNH36dFWqVEnr16/XPffcI+nqKXDTp09XWFiYw98//PDD6tOnj/3xo48+qpdeekmRkZGSpJIlS2rUqFF64YUX0g1Br7zyiv3/ixcvrqFDh2r27Nl64YUX5Ofnp9y5cytXrlw3PP3tq6++0qVLlzR9+nR74Pvggw/Upk0bjRs3Tvnz55ck5cmTRx988IE8PT1Vvnx5tW7dWkuXLiUEAUAORQgCAGSIMeambXbt2qWIiAh7AJKkihUrKiQkRLt27bKHoGLFiqUJQJJUs2ZNh8dbtmzRH3/8YT81TpKSk5N16dIlJSQkyN/fP8085syZo/fee08HDhxQfHy8rly5oqCgIJfXM3U9qlSp4nDEq27dukpJSdGePXvsIahSpUoOR7IKFiyobdu2ZWhZAIDbhxAEAMiQMmXKyGazZermB9dzdjqds+nx8fGKiopSx44d07RNvZboWqtXr1aPHj0UFRWl5s2bKzg4WLNnz9b48eNvuWZnrr9xg81mU0pKSrYsCwBw6whBAIAMCQ0NVfPmzfXhhx9q0KBBaQLLhQsXVKFCBR07dkzHjh2zHw3auXOnLly4oIoVK2Z4mdWrV9eePXtUunRpl9qvWrVKxYoV0/Dhw+3Tjhw54tDG29tbycnJN5xPhQoVNHXqVF28eNG+nn/88Yc8PDxUrly5DK4FACCn4O5wAIAM+/DDD5WcnKxatWrp66+/1r59+7Rr1y699957qlOnjpo2baq77rpLPXr00J9//ql169apV69eatiwYZpT3Vzx2muvafr06YqKitKOHTu0a9cuzZ492+G6n2uVKVNGR48e1ezZs3XgwAG99957WrhwoUOb4sWL69ChQ9q8ebP++ecfJSYmpplPjx495Ovrq8jISG3fvl3Lli3T008/rZ49e9pPhQMA/PcQggAAGVayZEn9+eefaty4sZ577jlVrlxZzZo109KlSzV58mTZbDZ9++23ypMnjxo0aKCmTZuqZMmSmjNnTqaW17x5c33//ff65ZdfdM899+jee+/VhAkTVKxYMaft27Ztq2effVZPPfWUqlatqlWrVunVV191aPPQQw+pRYsWaty4scLCwjRr1qw08/H399eiRYt07tw53XPPPerUqZOaNGmiDz74IFPrAQDIGWzGlStcAQAAAOAOwZEgAAAAAJZCCAIAAABgKYQgAAAAAJZCCAIAAABgKYQgAAAAAJZCCAIAAABgKYQgAAAAAJZCCAIAAABgKYQgAAAAAJZCCAIAAABgKYQgAAAAAJby/wDjruhkCEyhbwAAAABJRU5ErkJggg==", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Correlation Histogram\n", + "\n", + "# Define the number of bins\n", + "num_bins = 10\n", + "\n", + "# Create the bins using numpy.histogram\n", + "hist, bins = np.histogram(corr, bins=num_bins)\n", + "\n", + "# Print the histogram and bins\n", + "print(\"Histogram:\", hist)\n", + "print(\"Bins:\", bins)\n", + "\n", + "fig, ax = plt.subplots(figsize=(10, 6))\n", + "\n", + "plt.xticks(bins)\n", + "\n", + "plt.hist(corr, alpha=0.5, bins=num_bins, histtype=\"bar\", ec=\"black\")\n", + "plt.xlabel(\"Correlation\")\n", + "plt.ylabel(\"Frequency\")\n", + "plt.title(\"Histogram of the Pearson Correlation between original and imputed values\")\n", + "\n", + "# plt.figure()\n", + "# plt.plot(corr, marker=\"o\", linestyle=\"-\")\n", + "# plt.ylim(0, 1)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Original vs Imputed all features (Added Missing Values)\n", + "\n", + "xlim = 1000000\n", + "# c=plt.cm.viridis(colors[df_test[:,3].astype(int)]), label=f\"{df_test[:,3]}\",\n", + "\n", + "x = np.linspace(-xlim, xlim, 100)\n", + "y = x\n", + "\n", + "\n", + "df_test = pd.read_csv(f\"{params.output_folder}test_imputed.csv\").values\n", + "\n", + "features = [int(feature) for feature in np.unique(df_test[:, 3])]\n", + "corr = np.corrcoef(df_test[:, 0], df_test[:, 1])\n", + "\n", + "\n", + "xmin = df_test[:, 0].min()\n", + "xmax = df_test[:, 0].max()\n", + "\n", + "ymin = df_test[:, 1].min()\n", + "ymax = df_test[:, 1].max()\n", + "\n", + "plt.scatter(df_test[:, 0], df_test[:, 1], label=corr[0, 1])\n", + "plt.legend()\n", + "plt.plot(x, y, color=\"red\", linestyle=\"--\")\n", + "\n", + "plt.xlim(xmin * 0.9, xmax * 1.1)\n", + "plt.ylim(ymin * 0.9, ymax * 1.1)\n", + "plt.xlabel(\"Original\")\n", + "plt.ylabel(\"Imputed\")\n", + "plt.grid(True)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "d2l", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.18" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} From 11110db544614dd9f39460a386bf5f15dc3f5644 Mon Sep 17 00:00:00 2001 From: Yasset Perez-Riverol Date: Sun, 14 Dec 2025 20:59:19 +0000 Subject: [PATCH 08/26] organize notebooks --- GenerativeProteomics/README.md | 7 - GenerativeProteomics/plots.ipynb | 987 ------------------------------- 2 files changed, 994 deletions(-) delete mode 100644 GenerativeProteomics/README.md delete mode 100644 GenerativeProteomics/plots.ipynb diff --git a/GenerativeProteomics/README.md b/GenerativeProteomics/README.md deleted file mode 100644 index 56caec1..0000000 --- a/GenerativeProteomics/README.md +++ /dev/null @@ -1,7 +0,0 @@ -# DANN & GAIN Hybrid - -How to use? - -To prepare the HeLa for the **DANN&GAIN** hybrid it is needed to run the `hela_dann.ipynb` notebook first and just alter the directory of the HeLa dataset on the third cell of the notebook. - -test to see CI diff --git a/GenerativeProteomics/plots.ipynb b/GenerativeProteomics/plots.ipynb deleted file mode 100644 index 9556517..0000000 --- a/GenerativeProteomics/plots.ipynb +++ /dev/null @@ -1,987 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - " {'input': '/home/leandrosobral/LeandroSobralThesis/ProtoGain/breast/breastMissing_20.csv', 'output': 'breastImputed_20', 'ref': '/home/leandrosobral/LeandroSobralThesis/ProtoGain/breast/breast.csv', 'output_folder': '/home/leandrosobral/LeandroSobralThesis/ProtoGain/breast/results/', 'num_iterations': 2001, 'batch_size': 128, 'alpha': 10, 'miss_rate': 0.1, 'hint_rate': 0.9, 'lr_D': 0.001, 'lr_G': 0.001, 'override': 1, 'output_all': 1}\n" - ] - } - ], - "source": [ - "from hypers import Params\n", - "\n", - "import pandas as pd\n", - "import matplotlib.pyplot as plt\n", - "import numpy as np\n", - "from scipy.stats import ttest_ind\n", - "\n", - "dataset = \"breast\"\n", - "params = Params.read_hyperparameters(\n", - " f\"/home/leandrosobral/LeandroSobralThesis/ProtoGain/{dataset}/parameters.json\"\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "metadata": {}, - "outputs": [], - "source": [ - "# Load the CSV files for Breast\n", - "\n", - "dataset = \"breast\"\n", - "folder = \"~/LeandroSobralThesis/ProtoGain/\"\n", - "\n", - "loss_D = {}\n", - "loss_G = {}\n", - "loss_MSE_train = {}\n", - "loss_MSE_test = {}\n", - "cpu = {}\n", - "ram_percentage = {}\n", - "ram = {}\n", - "\n", - "MSE_final = {}\n", - "\n", - "run_time = {}\n", - "\n", - "loss_D = pd.read_csv(params.output_folder + \"lossD.csv\").values.T\n", - "loss_G = pd.read_csv(params.output_folder + \"lossG.csv\").values.T\n", - "\n", - "loss_MSE_train = pd.read_csv(params.output_folder + \"lossMSE_train.csv\").values.T\n", - "loss_MSE_test = pd.read_csv(params.output_folder + \"lossMSE_test.csv\").values.T\n", - "\n", - "MSE_final = loss_MSE_test[:, -1]\n", - "\n", - "# cpu = pd.read_csv(params.output_folder + \"cpu.csv\").values.T\n", - "# ram_percentage = pd.read_csv(\n", - "# params.output_folder + \"ram_percentage.csv\"\n", - "# ).values.flatten()\n", - "# ram = pd.read_csv(params.output_folder + \"ram.csv\").values.T\n", - "\n", - "\n", - "run_time = pd.read_csv(params.output_folder + \"run_time.csv\").values.flatten()" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "0.0037490644029438 [38.5696249 33.42994547]\n" - ] - } - ], - "source": [ - "# Load the CSV files for Spam\n", - "\n", - "dataset = \"spam\"\n", - "folder = \"~/LeandroSobralThesis/ProtoGain/\" + dataset + \"/\"\n", - "\n", - "loss_D = {}\n", - "loss_G = {}\n", - "loss_MSE_train = {}\n", - "loss_MSE_test = {}\n", - "cpu = {}\n", - "ram_percentage = {}\n", - "ram = {}\n", - "\n", - "MSE_final = {}\n", - "\n", - "run_time = {}\n", - "\n", - "loss_D = pd.read_csv(folder + f\"results/lossD.csv\").values.flatten()\n", - "loss_G = pd.read_csv(folder + f\"results/lossG.csv\").values.flatten()\n", - "\n", - "loss_MSE_train = pd.read_csv(folder + f\"results/lossMSE_train.csv\").values.flatten()\n", - "loss_MSE_test = pd.read_csv(folder + f\"results/lossMSE_test.csv\").values.flatten()\n", - "\n", - "cpu = pd.read_csv(folder + f\"results/cpu.csv\").values.flatten()\n", - "ram_percentage = pd.read_csv(folder + f\"results/ram_percentage.csv\").values.flatten()\n", - "ram = pd.read_csv(folder + f\"results/ram.csv\").values.flatten()\n", - "MSE_final = loss_MSE_test[-1]\n", - "\n", - "run_time = pd.read_csv(folder + f\"results/run_time.csv\").values.flatten()\n", - "\n", - "print(MSE_final, run_time)" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[0.02183125 0.02112623 0.02016055 ... 0.01808863 0.01929819 0.02000422] [[1.20936659 1.12057044 1.12004996 ... 0.25733846 0.28484619 0.26737295]\n", - " [1.52351968 1.46751945 1.45301188 ... 0.25842794 0.24529088 0.26182438]\n", - " [1.20822835 1.14543456 1.16969142 ... 0.25671357 0.2539771 0.23803761]\n", - " ...\n", - " [1.36142477 1.33428932 1.31567314 ... 0.24964616 0.26234183 0.25739478]\n", - " [1.43475016 1.44056278 1.38704627 ... 0.27495386 0.26098384 0.25528386]\n", - " [1.63076071 1.59219757 1.54155536 ... 0.25295851 0.22227823 0.24195301]]\n" - ] - } - ], - "source": [ - "# Load the CSV files for Credit\n", - "\n", - "folder = \"~/LeandroSobralThesis/ProtoGain/\" + dataset + \"/\"\n", - "\n", - "loss_D = {}\n", - "loss_G = {}\n", - "loss_MSE_train = {}\n", - "loss_MSE_test = {}\n", - "cpu = {}\n", - "ram_percentage = {}\n", - "ram = {}\n", - "\n", - "MSE_final = {}\n", - "\n", - "run_time = {}\n", - "\n", - "loss_D = pd.read_csv(params.output_folder + \"lossD.csv\").values.T\n", - "loss_G = pd.read_csv(params.output_folder + \"lossG.csv\").values.T\n", - "\n", - "loss_MSE_train = pd.read_csv(params.output_folder + \"lossMSE_train.csv\").values.T\n", - "loss_MSE_test = pd.read_csv(params.output_folder + \"lossMSE_test.csv\").values.T\n", - "\n", - "MSE_final = loss_MSE_test[:, -1]\n", - "\n", - "cpu = pd.read_csv(params.output_folder + \"cpu.csv\").values.T\n", - "ram_percentage = pd.read_csv(\n", - " params.output_folder + \"ram_percentage.csv\"\n", - ").values.flatten()\n", - "ram = pd.read_csv(params.output_folder + \"ram.csv\").values.T\n", - "\n", - "\n", - "run_time = pd.read_csv(params.output_folder + \"run_time.csv\").values.flatten()\n", - "\n", - "print(loss_D.std(axis=0), loss_G)" - ] - }, - { - "cell_type": "code", - "execution_count": 66, - "metadata": {}, - "outputs": [], - "source": [ - "# Load the CSV files for Yasset\n", - "\n", - "dataset = \"Yasset\"\n", - "folder = \"~/LeandroSobralThesis/ProtoGain/\"\n", - "\n", - "loss_D = pd.read_csv(params.output_folder + \"lossD.csv\").values.T\n", - "loss_G = pd.read_csv(params.output_folder + \"lossG.csv\").values.T\n", - "\n", - "loss_D_evaluate = pd.read_csv(params.output_folder + \"lossD_evaluate.csv\").values.T\n", - "loss_G_evaluate = pd.read_csv(params.output_folder + \"lossG_evaluate.csv\").values.T\n", - "\n", - "loss_MSE_train = pd.read_csv(params.output_folder + \"lossMSE_train.csv\").values.T\n", - "loss_MSE_train_evaluate = pd.read_csv(\n", - " params.output_folder + \"lossMSE_train_evaluate.csv\"\n", - ").values.T\n", - "loss_MSE_test = pd.read_csv(params.output_folder + \"lossMSE_test.csv\").values.T\n", - "\n", - "MSE_final = loss_MSE_test[:, -1]\n", - "\n", - "# cpu = pd.read_csv(params.output_folder + \"cpu.csv\").values.T\n", - "# ram_percentage = pd.read_csv(\n", - "# params.output_folder + \"ram_percentage.csv\"\n", - "# ).values.flatten()\n", - "# ram = pd.read_csv(params.output_folder + \"ram.csv\").values.T\n", - "\n", - "\n", - "run_time = pd.read_csv(params.output_folder + \"run_time.csv\").values.flatten()" - ] - }, - { - "cell_type": "code", - "execution_count": 63, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Plot the D and G losses (Multiple Runs)\n", - "\n", - "xmax = params.num_iterations\n", - "\n", - "fig, axs = plt.subplots()\n", - "\n", - "\n", - "axs.set_xlabel(\"Iteration\")\n", - "axs.set_ylabel(\"Loss\")\n", - "axs.set_xlim(0, xmax)\n", - "axs.set_title(f\"Losses ProtoGain\")\n", - "\n", - "\n", - "axs.fill_between(\n", - " np.arange(1, len(loss_D[0]) + 1, 1),\n", - " loss_D.mean(axis=0) + loss_D.std(axis=0),\n", - " loss_D.mean(axis=0) - loss_D.std(axis=0),\n", - " alpha=0.4,\n", - ")\n", - "axs.plot(loss_D.mean(axis=0), label=\"D loss\")\n", - "\n", - "axs.fill_between(\n", - " np.arange(1, len(loss_G[0]) + 1, 1),\n", - " loss_G.mean(axis=0) + loss_G.std(axis=0),\n", - " loss_G.mean(axis=0) - loss_G.std(axis=0),\n", - " alpha=0.4,\n", - ")\n", - "axs.plot(loss_G.mean(axis=0), label=\"G loss\")\n", - "axs.xaxis.grid(True, which=\"major\")\n", - "axs.yaxis.grid(True, which=\"major\")\n", - "\n", - "\n", - "fig.legend(loc=\"upper right\", bbox_to_anchor=(0.9, 0.85))\n", - "\n", - "# Adjust the spacing between subplots\n", - "plt.subplots_adjust(wspace=0.05, hspace=0.2)" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Plot the D and G losses (Evaluation)\n", - "\n", - "xmax = params.num_iterations\n", - "\n", - "fig, axs = plt.subplots()\n", - "\n", - "\n", - "axs.set_xlabel(\"Iteration\")\n", - "axs.set_ylabel(\"Loss\")\n", - "axs.set_xlim(0, xmax)\n", - "axs.set_title(f\"Losses of Evaluation ProtoGain\")\n", - "\n", - "\n", - "axs.fill_between(\n", - " np.arange(1, len(loss_D_evaluate[0]) + 1, 1),\n", - " loss_D_evaluate.mean(axis=0) + loss_D_evaluate.std(axis=0),\n", - " loss_D_evaluate.mean(axis=0) - loss_D_evaluate.std(axis=0),\n", - " alpha=0.4,\n", - ")\n", - "axs.plot(loss_D_evaluate.mean(axis=0), label=\"D loss\")\n", - "\n", - "axs.fill_between(\n", - " np.arange(1, len(loss_G_evaluate[0]) + 1, 1),\n", - " loss_G_evaluate.mean(axis=0) + loss_G_evaluate.std(axis=0),\n", - " loss_G_evaluate.mean(axis=0) - loss_G_evaluate.std(axis=0),\n", - " alpha=0.4,\n", - ")\n", - "axs.plot(loss_G_evaluate.mean(axis=0), label=\"G loss\")\n", - "axs.xaxis.grid(True, which=\"major\")\n", - "axs.yaxis.grid(True, which=\"major\")\n", - "\n", - "\n", - "fig.legend(loc=\"upper right\", bbox_to_anchor=(0.9, 0.85))\n", - "\n", - "# Adjust the spacing between subplots\n", - "plt.subplots_adjust(wspace=0.05, hspace=0.2)" - ] - }, - { - "cell_type": "code", - "execution_count": 64, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Plot the MSE (Multiple runs)\n", - "\n", - "xmax = params.num_iterations\n", - "\n", - "fig, axs = plt.subplots()\n", - "\n", - "\n", - "axs.set_xlabel(\"Iteration\")\n", - "axs.set_ylabel(\"MSE\")\n", - "axs.set_xlim(0, xmax)\n", - "axs.set_title(f\"MSE ProtoGain\")\n", - "\n", - "axs.fill_between(\n", - " np.arange(1, len(loss_MSE_train[0]) + 1, 1),\n", - " loss_MSE_train.mean(axis=0) + loss_MSE_train.std(axis=0),\n", - " loss_MSE_train.mean(axis=0) - loss_MSE_train.std(axis=0),\n", - " alpha=0.4,\n", - ")\n", - "axs.plot(loss_MSE_train.mean(axis=0), label=\"MSE of the NOT missing values\")\n", - "\n", - "axs.fill_between(\n", - " np.arange(1, len(loss_MSE_test[0]) + 1, 1),\n", - " loss_MSE_test.mean(axis=0) + loss_MSE_test.std(axis=0),\n", - " loss_MSE_test.mean(axis=0) - loss_MSE_test.std(axis=0),\n", - " alpha=0.4,\n", - ")\n", - "axs.plot(loss_MSE_test.mean(axis=0), label=\"MSE of the missing values\")\n", - "\n", - "\n", - "axs.xaxis.grid(True, which=\"major\")\n", - "axs.yaxis.grid(True, which=\"major\")\n", - "fig.legend(loc=\"upper right\", bbox_to_anchor=(0.9, 0.85))\n", - "\n", - "# Adjust the spacing between subplots\n", - "plt.subplots_adjust(wspace=0.05, hspace=0.2)" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Plot the MSE (Evaluation)\n", - "\n", - "xmax = params.num_iterations\n", - "\n", - "fig, axs = plt.subplots()\n", - "\n", - "\n", - "axs.set_xlabel(\"Iteration\")\n", - "axs.set_ylabel(\"MSE\")\n", - "axs.set_xlim(0, xmax)\n", - "axs.set_title(f\"MSE ProtoGain\")\n", - "\n", - "axs.fill_between(\n", - " np.arange(1, len(loss_MSE_train_evaluate[0]) + 1, 1),\n", - " loss_MSE_train_evaluate.mean(axis=0) + loss_MSE_train_evaluate.std(axis=0),\n", - " loss_MSE_train_evaluate.mean(axis=0) - loss_MSE_train_evaluate.std(axis=0),\n", - " alpha=0.4,\n", - ")\n", - "axs.plot(loss_MSE_train_evaluate.mean(axis=0), label=\"MSE of the NOT missing values\")\n", - "\n", - "axs.fill_between(\n", - " np.arange(1, len(loss_MSE_test[0]) + 1, 1),\n", - " loss_MSE_test.mean(axis=0) + loss_MSE_test.std(axis=0),\n", - " loss_MSE_test.mean(axis=0) - loss_MSE_test.std(axis=0),\n", - " alpha=0.4,\n", - ")\n", - "axs.plot(loss_MSE_test.mean(axis=0), label=\"MSE of the missing values\")\n", - "\n", - "\n", - "axs.xaxis.grid(True, which=\"major\")\n", - "axs.yaxis.grid(True, which=\"major\")\n", - "fig.legend(loc=\"upper right\", bbox_to_anchor=(0.9, 0.85))\n", - "\n", - "# Adjust the spacing between subplots\n", - "plt.subplots_adjust(wspace=0.05, hspace=0.2)" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Final MSE\n", - "\n", - "space = 0.15\n", - "fig, ax = plt.subplots(figsize=(12, 8))\n", - "\n", - "box_param = dict(\n", - " whis=(5, 95),\n", - " widths=0.2,\n", - " patch_artist=True,\n", - " flierprops=dict(marker=\".\", markeredgecolor=\"black\", fillstyle=None),\n", - " notch=True,\n", - " medianprops=dict(color=\"black\"),\n", - ")\n", - "\n", - "\n", - "bp1 = ax.boxplot(\n", - " MSE_final,\n", - " boxprops=dict(facecolor=\"tab:blue\"),\n", - " **box_param,\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 47, - "metadata": {}, - "outputs": [ - { - "ename": "ValueError", - "evalue": "Invalid file path or buffer object type: ", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[47], line 10\u001b[0m\n\u001b[1;32m 6\u001b[0m x \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39mlinspace(\u001b[38;5;241m-\u001b[39mxlim, xlim, \u001b[38;5;241m100\u001b[39m)\n\u001b[1;32m 7\u001b[0m y \u001b[38;5;241m=\u001b[39m x\n\u001b[0;32m---> 10\u001b[0m df_data \u001b[38;5;241m=\u001b[39m \u001b[43mpd\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mread_csv\u001b[49m\u001b[43m(\u001b[49m\u001b[43mparams\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mref\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241m.\u001b[39mvalues\n\u001b[1;32m 12\u001b[0m df_missing \u001b[38;5;241m=\u001b[39m pd\u001b[38;5;241m.\u001b[39mread_csv(params\u001b[38;5;241m.\u001b[39minput)\u001b[38;5;241m.\u001b[39mvalues\n\u001b[1;32m 14\u001b[0m df_imputed \u001b[38;5;241m=\u001b[39m pd\u001b[38;5;241m.\u001b[39mread_csv(params\u001b[38;5;241m.\u001b[39moutput_folder \u001b[38;5;241m+\u001b[39m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mparams\u001b[38;5;241m.\u001b[39moutput\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m.csv\u001b[39m\u001b[38;5;124m\"\u001b[39m)\u001b[38;5;241m.\u001b[39mvalues\n", - "File \u001b[0;32m~/miniconda3/envs/proto/lib/python3.12/site-packages/pandas/io/parsers/readers.py:1026\u001b[0m, in \u001b[0;36mread_csv\u001b[0;34m(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, skipfooter, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, date_format, dayfirst, cache_dates, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, doublequote, escapechar, comment, encoding, encoding_errors, dialect, on_bad_lines, delim_whitespace, low_memory, memory_map, float_precision, storage_options, dtype_backend)\u001b[0m\n\u001b[1;32m 1013\u001b[0m kwds_defaults \u001b[38;5;241m=\u001b[39m _refine_defaults_read(\n\u001b[1;32m 1014\u001b[0m dialect,\n\u001b[1;32m 1015\u001b[0m delimiter,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 1022\u001b[0m dtype_backend\u001b[38;5;241m=\u001b[39mdtype_backend,\n\u001b[1;32m 1023\u001b[0m )\n\u001b[1;32m 1024\u001b[0m kwds\u001b[38;5;241m.\u001b[39mupdate(kwds_defaults)\n\u001b[0;32m-> 1026\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_read\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfilepath_or_buffer\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkwds\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m~/miniconda3/envs/proto/lib/python3.12/site-packages/pandas/io/parsers/readers.py:620\u001b[0m, in \u001b[0;36m_read\u001b[0;34m(filepath_or_buffer, kwds)\u001b[0m\n\u001b[1;32m 617\u001b[0m _validate_names(kwds\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnames\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;28;01mNone\u001b[39;00m))\n\u001b[1;32m 619\u001b[0m \u001b[38;5;66;03m# Create the parser.\u001b[39;00m\n\u001b[0;32m--> 620\u001b[0m parser \u001b[38;5;241m=\u001b[39m \u001b[43mTextFileReader\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfilepath_or_buffer\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwds\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 622\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m chunksize \u001b[38;5;129;01mor\u001b[39;00m iterator:\n\u001b[1;32m 623\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m parser\n", - "File \u001b[0;32m~/miniconda3/envs/proto/lib/python3.12/site-packages/pandas/io/parsers/readers.py:1620\u001b[0m, in \u001b[0;36mTextFileReader.__init__\u001b[0;34m(self, f, engine, **kwds)\u001b[0m\n\u001b[1;32m 1617\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39moptions[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhas_index_names\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m kwds[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhas_index_names\u001b[39m\u001b[38;5;124m\"\u001b[39m]\n\u001b[1;32m 1619\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhandles: IOHandles \u001b[38;5;241m|\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[0;32m-> 1620\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_engine \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_make_engine\u001b[49m\u001b[43m(\u001b[49m\u001b[43mf\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mengine\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m~/miniconda3/envs/proto/lib/python3.12/site-packages/pandas/io/parsers/readers.py:1880\u001b[0m, in \u001b[0;36mTextFileReader._make_engine\u001b[0;34m(self, f, engine)\u001b[0m\n\u001b[1;32m 1878\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mb\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m mode:\n\u001b[1;32m 1879\u001b[0m mode \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mb\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m-> 1880\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhandles \u001b[38;5;241m=\u001b[39m \u001b[43mget_handle\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 1881\u001b[0m \u001b[43m \u001b[49m\u001b[43mf\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1882\u001b[0m \u001b[43m \u001b[49m\u001b[43mmode\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1883\u001b[0m \u001b[43m \u001b[49m\u001b[43mencoding\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mencoding\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1884\u001b[0m \u001b[43m \u001b[49m\u001b[43mcompression\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mcompression\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1885\u001b[0m \u001b[43m \u001b[49m\u001b[43mmemory_map\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mmemory_map\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1886\u001b[0m \u001b[43m \u001b[49m\u001b[43mis_text\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mis_text\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1887\u001b[0m \u001b[43m \u001b[49m\u001b[43merrors\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mencoding_errors\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mstrict\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1888\u001b[0m \u001b[43m \u001b[49m\u001b[43mstorage_options\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43moptions\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mstorage_options\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1889\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1890\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhandles \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m 1891\u001b[0m f \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhandles\u001b[38;5;241m.\u001b[39mhandle\n", - "File \u001b[0;32m~/miniconda3/envs/proto/lib/python3.12/site-packages/pandas/io/common.py:728\u001b[0m, in \u001b[0;36mget_handle\u001b[0;34m(path_or_buf, mode, encoding, compression, memory_map, is_text, errors, storage_options)\u001b[0m\n\u001b[1;32m 725\u001b[0m codecs\u001b[38;5;241m.\u001b[39mlookup_error(errors)\n\u001b[1;32m 727\u001b[0m \u001b[38;5;66;03m# open URLs\u001b[39;00m\n\u001b[0;32m--> 728\u001b[0m ioargs \u001b[38;5;241m=\u001b[39m \u001b[43m_get_filepath_or_buffer\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 729\u001b[0m \u001b[43m \u001b[49m\u001b[43mpath_or_buf\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 730\u001b[0m \u001b[43m \u001b[49m\u001b[43mencoding\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mencoding\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 731\u001b[0m \u001b[43m \u001b[49m\u001b[43mcompression\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcompression\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 732\u001b[0m \u001b[43m \u001b[49m\u001b[43mmode\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmode\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 733\u001b[0m \u001b[43m \u001b[49m\u001b[43mstorage_options\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstorage_options\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 734\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 736\u001b[0m handle \u001b[38;5;241m=\u001b[39m ioargs\u001b[38;5;241m.\u001b[39mfilepath_or_buffer\n\u001b[1;32m 737\u001b[0m handles: \u001b[38;5;28mlist\u001b[39m[BaseBuffer]\n", - "File \u001b[0;32m~/miniconda3/envs/proto/lib/python3.12/site-packages/pandas/io/common.py:472\u001b[0m, in \u001b[0;36m_get_filepath_or_buffer\u001b[0;34m(filepath_or_buffer, encoding, compression, mode, storage_options)\u001b[0m\n\u001b[1;32m 468\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m (\n\u001b[1;32m 469\u001b[0m \u001b[38;5;28mhasattr\u001b[39m(filepath_or_buffer, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mread\u001b[39m\u001b[38;5;124m\"\u001b[39m) \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mhasattr\u001b[39m(filepath_or_buffer, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mwrite\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 470\u001b[0m ):\n\u001b[1;32m 471\u001b[0m msg \u001b[38;5;241m=\u001b[39m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mInvalid file path or buffer object type: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mtype\u001b[39m(filepath_or_buffer)\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m--> 472\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(msg)\n\u001b[1;32m 474\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m IOArgs(\n\u001b[1;32m 475\u001b[0m filepath_or_buffer\u001b[38;5;241m=\u001b[39mfilepath_or_buffer,\n\u001b[1;32m 476\u001b[0m encoding\u001b[38;5;241m=\u001b[39mencoding,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 479\u001b[0m mode\u001b[38;5;241m=\u001b[39mmode,\n\u001b[1;32m 480\u001b[0m )\n", - "\u001b[0;31mValueError\u001b[0m: Invalid file path or buffer object type: " - ] - } - ], - "source": [ - "# Original VS Imputed\n", - "\n", - "xlim = 1000000\n", - "\n", - "\n", - "x = np.linspace(-xlim, xlim, 100)\n", - "y = x\n", - "\n", - "\n", - "df_data = pd.read_csv(params.ref).values\n", - "\n", - "df_missing = pd.read_csv(params.input).values\n", - "\n", - "df_imputed = pd.read_csv(params.output_folder + f\"{params.output}.csv\").values\n", - "\n", - "\n", - "zeros = np.where(np.isnan(df_missing))\n", - "\n", - "features = np.arange(len(df_data[0]))\n", - "# features = np.array([0, 1])\n", - "\n", - "corr = np.empty(len(df_data[0]))\n", - "\n", - "fig, axs = plt.subplots(len(features), figsize=(8, len(df_data[0]) * 6))\n", - "\n", - "for feature in features:\n", - "\n", - " xmin = df_data[:, feature].min()\n", - " xmax = df_data[:, feature].max()\n", - "\n", - " ymin = df_imputed[:, feature].min()\n", - " ymax = df_imputed[:, feature].max()\n", - "\n", - " zeros_0 = []\n", - " for i in range(len(zeros[0])):\n", - " if zeros[1][i] == feature:\n", - " zeros_0.append(zeros[0][i])\n", - "\n", - " corr[feature] = np.corrcoef(\n", - " df_data[zeros_0, feature], df_imputed[zeros_0, feature]\n", - " )[0, 1]\n", - "\n", - " axs[feature].plot(x, y, color=\"red\", linestyle=\"--\")\n", - " axs[feature].scatter(\n", - " df_data[zeros_0, feature], df_imputed[zeros_0, feature], label=corr[feature]\n", - " )\n", - " axs[feature].set_xlabel(\"Original\")\n", - " axs[feature].set_ylabel(\"Imputed\")\n", - " axs[feature].set_xlim(xmin * 0.9, xmax * 1.1)\n", - " axs[feature].legend() # Add this line to show the label on the graph\n", - " axs[feature].set_ylim(ymin * 0.9, ymax * 1.1)\n", - " axs[feature].set_title(f\"ProtoGain - Original vs Imputed (Feature {feature})\")\n", - " axs[feature].xaxis.grid(True, which=\"major\")\n", - " axs[feature].yaxis.grid(True, which=\"major\")" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Histogram: [4 1 3 1 3 2 2 2 6 6]\n", - "Bins: [0.5373835 0.57425734 0.61113118 0.64800502 0.68487886 0.7217527\n", - " 0.75862654 0.79550038 0.83237422 0.86924806 0.9061219 ]\n" - ] - }, - { - "data": { - "text/plain": [ - "Text(0.5, 1.0, 'Histogram of the Pearson Correlation between original and imputed values')" - ] - }, - "execution_count": 23, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import numpy as np\n", - "\n", - "# Define the number of bins\n", - "num_bins = 10\n", - "\n", - "# Create the bins using numpy.histogram\n", - "hist, bins = np.histogram(corr, bins=num_bins)\n", - "\n", - "# Print the histogram and bins\n", - "print(\"Histogram:\", hist)\n", - "print(\"Bins:\", bins)\n", - "\n", - "fig, ax = plt.subplots(figsize=(10, 6))\n", - "\n", - "plt.xticks(bins)\n", - "\n", - "plt.hist(corr, alpha=0.5, bins=num_bins, histtype=\"bar\", ec=\"black\")\n", - "plt.xlabel(\"Correlation\")\n", - "plt.ylabel(\"Frequency\")\n", - "plt.title(\"Histogram of the Pearson Correlation between original and imputed values\")\n", - "\n", - "# plt.figure()\n", - "# plt.plot(corr, marker=\"o\", linestyle=\"-\")\n", - "# plt.ylim(0, 1)" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Boxplot of each run duration\n", - "\n", - "space = 0.15\n", - "fig, ax = plt.subplots(figsize=(12, 8))\n", - "\n", - "box_param = dict(\n", - " whis=(5, 95),\n", - " widths=0.2,\n", - " patch_artist=True,\n", - " flierprops=dict(marker=\".\", markeredgecolor=\"black\", fillstyle=None),\n", - " notch=True,\n", - " medianprops=dict(color=\"black\"),\n", - ")\n", - "\n", - "\n", - "bp1 = ax.boxplot(\n", - " run_time,\n", - " boxprops=dict(facecolor=\"tab:blue\"),\n", - " **box_param,\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 69, - "metadata": {}, - "outputs": [ - { - "ename": "NameError", - "evalue": "name 'train_samples' is not defined", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[69], line 29\u001b[0m\n\u001b[1;32m 25\u001b[0m x_ticks \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mrange\u001b[39m(\u001b[38;5;241m0\u001b[39m, xmax, \u001b[38;5;241m100\u001b[39m)\n\u001b[1;32m 28\u001b[0m \u001b[38;5;66;03m# Create a color gradient based on the loop index\u001b[39;00m\n\u001b[0;32m---> 29\u001b[0m colors \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39mlinspace(\u001b[38;5;241m0\u001b[39m, \u001b[38;5;241m1\u001b[39m, \u001b[38;5;28mlen\u001b[39m(\u001b[43mtrain_samples\u001b[49m))\n\u001b[1;32m 31\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i, samples \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28menumerate\u001b[39m(train_samples):\n\u001b[1;32m 32\u001b[0m runs_cpu \u001b[38;5;241m=\u001b[39m {run: data \u001b[38;5;28;01mfor\u001b[39;00m (s, run), data \u001b[38;5;129;01min\u001b[39;00m my_cpu\u001b[38;5;241m.\u001b[39mitems() \u001b[38;5;28;01mif\u001b[39;00m s \u001b[38;5;241m==\u001b[39m samples}\n", - "\u001b[0;31mNameError\u001b[0m: name 'train_samples' is not defined" - ] - }, - { - "data": { - "image/png": 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joYceqvGuxqJFi9Z4bN9Vhw4dYrfddou77rorlixZkml/7bXX4qmnnorDDjss07Yy8H+9X0Rk+nzzr/GjRo2KiMgs5dtoo43il7/8Zbz22mtx4YUX1nhH/ZttK+/Gf729rKxslYsjADY8rh2q11df1w5bbrllnHzyyfHEE0/ETTfdVGOfbx7TymX7v/jFL+KYY46p9jrttNNi2223jfvuu2+N+63JeeedF61atYrLL7+81mOhobmjz/dC586d4/77748BAwbEjjvuGAMHDowuXbrEihUrYvr06fHAAw/E4MGDa73d008/Pe6444740Y9+FCeffHJ069YtPvzww5g4cWK89tprcffdd1d70FpNevfuHVtuuWWccsop8Ytf/CKaNGkSd9xxR7Rt2zbmzZuX6XfXXXfFzTffHEcddVR07tw5li5dGrfeemvk5eVlwuzhhx8eo0aNikMOOSSOP/74WLhwYYwZMya22Wab+Pvf/57ZVvfu3ePoo4+O0aNHx4cffpj5iZy33norIqrfHb/qqqvi2WefjZ49e8Zpp50WO+20U3z00Ucxa9asePrpp+Ojjz6q9XmrjWuvvTYOPfTQ6NWrV5xyyimZn9fLz8+v9pu93bt3j4iIiy66KI499tho1qxZ9O3bN7p27RqDBg2KcePGxZIlS2K//faLl156Ke66667o379/HHDAAZltXHjhhfHGG2/EtddeG0899VQcffTRscUWW8THH38cs2bNigceeCDatWuXWVLZu3fvaN68efTt2zd+8pOfxCeffBK33nprtGvXLj744IP1el4AWL9cOzTctcPo0aPj3XffjXPOOScmTJgQffv2jXbt2sXixYvjxRdfjMceeyzz/J6Kiop46KGH4uCDD17tVx769esXN9xwQyxcuDDatWu3xn1/XX5+fpx77rkeyseGqWEe9g8N46233kpOO+20pKioKGnevHmyySabJHvttVdy4403Jp999lmm35p++uabPv7442To0KHJ1ltvnTRr1izJy8tLDjjggOSJJ55Y67pmzpyZ9OzZM2nevHmy5ZZbJqNGjVrlJ3JmzZqVHHfcccmWW26Z5OTkJO3atUuOOOKI5JVXXqm2rdtvvz3Zdtttk5ycnGSHHXZIxo8fX+PP8Cxbtiw5++yzk0033TRp2bJl0r9//+TNN99MIiK56qqrqvUtLS1Nzj777KSwsDBp1qxZ0r59++Sggw5Kxo0b963Htjbn8tt+tubpp59O9tprr6RFixZJXl5e0rdv3+Sf//znKv1+/etfJx07dkyys7OrnbvPP/88ueyyyzL/RoWFhcmwYcOq/Zt/3SOPPJIcdthhSdu2bZOmTZsmrVq1Svbee+/k2muvTZYsWVKt75/+9Kdk1113TXJzc5OioqLk6quvTu64445VfupvdT+v98ADD9R4Lr7tp5UAqB+uHb5SX9cOSfLlz9uOHz8+OfDAA5NNN900adq0adKmTZvkoIMOSsaOHZssX748SZIkeeihh5KISG6//fbVbuu5555LIiK54YYbkiT59p/X+7qPP/44yc/P9/N6bHCyksQTn4AvzZ49O7p16xb33nvvWn8vDgD4/nLtAI2T7+jD91RNT/wdPXp0ZGdnx7777tsAFQEAjZlrB9hw+I4+fE9dc801MXPmzDjggAOiadOm8cQTT8QTTzwRp59+ehQWFjZ0eQBAI+PaATYclu7D99TUqVPjsssui3/+85/xySefxJZbbhknnXRSXHTRRdG0qb8BAgDVuXaADUeDBv3nn38+rr322pg5c2Z88MEH8cgjj0T//v3XOOa5556LkpKSeP3116OwsDAuvvjidXriKQAAAKRRg35Hf9myZdG1a9cYM2bMWvV/99134/DDD48DDjggZs+eHeedd16ceuqp8eSTT67nSgEAAGDD0GiW7mdlZX3rHf0LLrggJk2aFK+99lqm7dhjj40lS5bElClT6qFKAAAAaNw2qC/TzJgxI4qLi6u19enTJ84777zVjqmoqIiKiorM+6qqqvjoo49is802i6ysrPVVKgCstSRJYunSpbH55ptHdrYfxFkX5nsAGrP6nus3qKC/YMGCKCgoqNZWUFAQ5eXlsXz58mjRosUqY0aOHBmXXXZZfZUIAOts/vz5scUWWzR0GRsk8z0AG4L6mus3qKC/LoYNGxYlJSWZ92VlZbHlllvG/PnzIy8vrwErA4AvlZeXR2FhYWyyySYNXcoGy3wPQGNW33P9BhX027dvH6WlpdXaSktLIy8vr8a7+REROTk5kZOTs0p7Xl6eiR+ARsUS83VnvgdgQ1Bfc/0G9UXAXr16xbRp06q1TZ06NXr16tVAFQEAAEDj0qBB/5NPPonZs2fH7NmzI+LLn8+bPXt2zJs3LyK+XIY3cODATP8zzjgj3nnnnfjlL38Z//rXv+Lmm2+OP/zhDzF06NCGKB8AAAAanQYN+q+88kp069YtunXrFhERJSUl0a1btxg+fHhERHzwwQeZ0B8RsfXWW8ekSZNi6tSp0bVr17juuuvitttuiz59+jRI/QAAANDYZCVJkjR0EfWpvLw88vPzo6yszHf2AGgUzE11zzkFoDGp73lpg/qOPgAAALBmgj4AAACkiKAPAAAAKSLoAwAAQIoI+gAAAJAigj4AAACkiKAPAAAAKSLoAwAAQIoI+gAAAJAigj4AAACkiKAPAAAAKSLoAwAAQIoI+gAAAJAigj4AAACkiKAPAAAAKSLoAwAAQIoI+gAAAJAigj4AAACkiKAPAAAAKSLoAwAAQIoI+gAAAJAigj4AAACkiKAPAAAAKSLoAwAAQIoI+gAAAJAigj4AAACkiKAPAAAAKSLoAwAAQIoI+gAAAJAigj4AAACkiKAPAAAAKSLoAwAAQIoI+gAAAJAigj4AAACkiKAPAAAAKSLoAwAAQIoI+gAAAJAigj4AAACkiKAPAAAAKSLoAwAAQIoI+gAAAJAigj4AAACkiKAPAAAAKSLoAwAAQIoI+gAAAJAigj4AAACkiKAPAAAAKSLoAwAAQIoI+gAAAJAigj4AAACkiKAPAAAAKSLoAwAAQIoI+gAAAJAigj4AAACkiKAPAAAAKSLoAwAAQIoI+gAAAJAigj4AAACkiKAPAAAAKSLoAwAAQIoI+gAAAJAigj4AAACkiKAPAAAAKSLoAwAAQIoI+gAAAJAigj4AAACkiKAPAAAAKSLoAwAAQIoI+gAAAJAigj4AAACkiKAPAAAAKSLoAwAAQIoI+gAAAJAiDR70x4wZE0VFRZGbmxs9e/aMl156aY39R48eHdtvv320aNEiCgsLY+jQofHZZ5/VU7UAAADQuDVo0J84cWKUlJTEiBEjYtasWdG1a9fo06dPLFy4sMb+999/f1x44YUxYsSIeOONN+L222+PiRMnxq9+9at6rhwAAAAapwYN+qNGjYrTTjsthgwZEjvttFOMHTs2Ntpoo7jjjjtq7D99+vTYa6+94vjjj4+ioqLo3bt3HHfccd+6CgAAAAC+Lxos6K9YsSJmzpwZxcXFXxWTnR3FxcUxY8aMGsfsueeeMXPmzEywf+edd2Ly5Mlx2GGHrXY/FRUVUV5eXu0FAKSL+R4AvtJgQX/x4sVRWVkZBQUF1doLCgpiwYIFNY45/vjj4/LLL4+99947mjVrFp07d479999/jUv3R44cGfn5+ZlXYWFhnR4HANDwzPcA8JUGfxhfbTz33HNx5ZVXxs033xyzZs2Khx9+OCZNmhS//vWvVztm2LBhUVZWlnnNnz+/HisGAOqD+R4AvtK0oXbcpk2baNKkSZSWllZrLy0tjfbt29c45pJLLomTTjopTj311IiI2GWXXWLZsmVx+umnx0UXXRTZ2av+3SInJydycnLq/gAAgEbDfA8AX2mwO/rNmzeP7t27x7Rp0zJtVVVVMW3atOjVq1eNYz799NNVwnyTJk0iIiJJkvVXLAAAAGwgGuyOfkRESUlJDBo0KHr06BG77757jB49OpYtWxZDhgyJiIiBAwdGx44dY+TIkRER0bdv3xg1alR069YtevbsGXPmzIlLLrkk+vbtmwn8AAAA8H3WoEF/wIABsWjRohg+fHgsWLAgdtttt5gyZUrmAX3z5s2rdgf/4osvjqysrLj44ovj/fffj7Zt20bfvn3jiiuuaKhDAAAAgEYlK/merXkvLy+P/Pz8KCsri7y8vIYuBwDMTeuBcwpAY1Lf89IG9dR9AAAAYM0EfQAAAEgRQR8AAABSRNAHAACAFBH0AQAAIEUEfQAAAEgRQR8AAABSRNAHAACAFBH0AQAAIEUEfQAAAEgRQR8AAABSRNAHAACAFBH0AQAAIEUEfQAAAEgRQR8AAABSRNAHAACAFBH0AQAAIEUEfQAAAEgRQR8AAABSRNAHAACAFBH0AQAAIEUEfQAAAEgRQR8AAABSRNAHAACAFBH0AQAAIEUEfQAAAEgRQR8AAABSRNAHAACAFBH0AQAAIEUEfQAAAEgRQR8AAABSRNAHAACAFBH0AQAAIEUEfQAAAEgRQR8AAABSRNAHAACAFBH0AQAAIEUEfQAAAEgRQR8AAABSRNAHAACAFBH0AQAAIEUEfQAAAEgRQR8AAABSRNAHAACAFBH0AQAAIEUEfQAAAEgRQR8AAABSRNAHAACAFBH0AQAAIEUEfQAAAEgRQR8AAABSRNAHAACAFBH0AQAAIEUEfQAAAEgRQR8AAABSRNAHAACAFBH0AQAAIEUEfQAAAEgRQR8AAABSRNAHAACAFBH0AQAAIEUEfQAAAEgRQR8AAABSRNAHAACAFBH0AQAAIEUEfQAAAEgRQR8AAABSRNAHAACAFBH0AQAAIEUEfQAAAEgRQR8AAABSRNAHAACAFBH0AQAAIEUaPOiPGTMmioqKIjc3N3r27BkvvfTSGvsvWbIkzj777OjQoUPk5OTEdtttF5MnT66nagEAAKBxa9qQO584cWKUlJTE2LFjo2fPnjF69Ojo06dPvPnmm9GuXbtV+q9YsSIOPvjgaNeuXTz44IPRsWPHeO+996JVq1b1XzwAAAA0Qg0a9EeNGhWnnXZaDBkyJCIixo4dG5MmTYo77rgjLrzwwlX633HHHfHRRx/F9OnTo1mzZhERUVRUVJ8lAwAAQKPWYEv3V6xYETNnzozi4uKvisnOjuLi4pgxY0aNY/70pz9Fr1694uyzz46CgoLo0qVLXHnllVFZWbna/VRUVER5eXm1FwCQLuZ7APhKgwX9xYsXR2VlZRQUFFRrLygoiAULFtQ45p133okHH3wwKisrY/LkyXHJJZfEddddF7/5zW9Wu5+RI0dGfn5+5lVYWFinxwEANDzzPQB8pcEfxlcbVVVV0a5duxg3blx07949BgwYEBdddFGMHTt2tWOGDRsWZWVlmdf8+fPrsWIAoD6Y7wHgKw32Hf02bdpEkyZNorS0tFp7aWlptG/fvsYxHTp0iGbNmkWTJk0ybTvuuGMsWLAgVqxYEc2bN19lTE5OTuTk5NRt8QBAo2K+B4CvNNgd/ebNm0f37t1j2rRpmbaqqqqYNm1a9OrVq8Yxe+21V8yZMyeqqqoybW+99VZ06NChxpAPAAAA3zcNunS/pKQkbr311rjrrrvijTfeiDPPPDOWLVuWeQr/wIEDY9iwYZn+Z555Znz00Udx7rnnxltvvRWTJk2KK6+8Ms4+++yGOgQAAABoVBr05/UGDBgQixYtiuHDh8eCBQtit912iylTpmQe0Ddv3rzIzv7qbxGFhYXx5JNPxtChQ2PXXXeNjh07xrnnnhsXXHBBQx0CAAAANCpZSZIkDV1EfSovL4/8/PwoKyuLvLy8hi4HAMxN64FzCkBjUt/z0gb11H0AAABgzQR9AAAASBFBHwAAAFJE0AcAAIAUEfQBAAAgRQR9AAAASBFBHwAAAFJE0AcAAIAUEfQBAAAgRZquy6CKior429/+Fu+99158+umn0bZt2+jWrVtsvfXWdV0fAAAAUAu1Cvovvvhi3HDDDfHYY4/F559/Hvn5+dGiRYv46KOPoqKiIjp16hSnn356nHHGGbHJJpusr5oBAACA1Vjrpfv9+vWLAQMGRFFRUTz11FOxdOnS+PDDD+M///lPfPrpp/Hvf/87Lr744pg2bVpst912MXXq1PVZNwAAAFCDtb6jf/jhh8dDDz0UzZo1q/HzTp06RadOnWLQoEHxz3/+Mz744IM6KxIAAABYO2sd9H/yk5+s9UZ32mmn2GmnndapIAAAAGDdrdPD+L7utddeiz//+c9RWVkZe+21V3Tv3r0u6gIAAADWwXf6eb0xY8bEQQcdFH/+85/j2WefjQMPPDCuuOKKuqoNAAAAqKVa3dGfP39+FBYWZt7fdNNN8frrr0ebNm0iImLGjBnRr1+/uOiii+q2SgAAAGCt1OqOfnFxcdxwww2RJElERGy22WYxZcqUqKioiKVLl8bTTz8dbdu2XS+FAgAAAN+uVkH/5ZdfjjfffDN69uwZs2fPjnHjxsX1118fLVq0iFatWsXEiRPjrrvuWl+1AgAAAN+iVkv38/Ly4uabb47p06fH4MGD48ADD4y//OUvUVlZGZWVldGqVav1VCYAAACwNtbpYXx77rlnvPLKK9G6devo1q1bPP/880I+AAAANAK1uqP/xRdfxLhx4+KNN96Irl27xq9+9asYMGBAnHHGGXHnnXfGTTfdFAUFBeurVgAAAOBb1OqO/imnnBI33XRTbLzxxjF+/PgYOnRobLfddvHMM8/EIYccEr169YpbbrllfdUKAAAAfItaBf0//vGP8dBDD8VVV10VU6dOjUmTJmU+O+WUU+Kvf/1r/OUvf6nzIgEAAIC1U6ugX1BQEE899VSsWLEinnnmmdhss82qfd6uXbu4//7767RAAAAAYO3V6jv6N910U5xwwglRUlISHTp0iD/84Q/rqy4AAABgHdQq6B988MFRWloaixcvjrZt266vmgAAAIB1VOuf18vKyhLyAQAAoJFa66B/yCGHxF//+tdv7bd06dK4+uqrY8yYMd+pMAAAAKD21nrp/o9+9KM4+uijIz8/P/r27Rs9evSIzTffPHJzc+Pjjz+Of/7zn/HCCy/E5MmT4/DDD49rr712fdYNAAAA1GCtg/4pp5wSJ554YjzwwAMxceLEGDduXJSVlUXEl8v5d9ppp+jTp0+8/PLLseOOO663ggEAAIDVq9XD+HJycuLEE0+ME088MSIiysrKYvny5bHZZptFs2bN1kuBAAAAwNqrVdD/pvz8/MjPz6+rWgAAAIDvqNZP3QcAAAAaL0EfAAAAUkTQBwAAgBQR9AEAACBFavUwvvLy8hrbN95442jSpEmdFAQAAACsu1rd0W/VqlW0bt16lVeLFi1i++23j1tvvXV91QkAAACshVrd0X/22WdrbF+yZEnMnDkzfvGLX0TTpk1jyJAhdVIcAAAAUDu1Cvr77bffaj878sgjo6ioKG688UZBHwAAABpInT6Mb7/99os5c+bU5SYBAACAWqjToF9WVhb5+fl1uUkAAACgFuos6H/++edx7bXXRs+ePetqkwAAAEAt1eo7+j/84Q9rbC8rK4vXX389srKy4i9/+UudFAYAAADUXq2C/uqW5RcWFsbRRx8dJ5xwgqX7AAAA0IBqFfTHjx+/vuoAAAAA6kCtgn5ExF//+td47LHHYsWKFXHQQQfFIYccsj7qAgAAANZBrYL+gw8+GAMGDIgWLVpEs2bNYtSoUXH11VfH+eefv77qAwAAAGqhVk/dHzlyZJx22mlRVlYWH3/8cfzmN7+JK6+8cn3VBgAAANRSrYL+m2++Geeff340adIkIiJ+/vOfx9KlS2PhwoXrpTgAAACgdmoV9D/99NPIy8vLvG/evHnk5ubGJ598UueFAQAAALVX64fx3XbbbdGyZcvM+y+++CLuvPPOaNOmTabtZz/7Wd1UBwAAANRKVpIkydp2LioqiqysrDVvMCsr3nnnne9c2PpSXl4e+fn5UVZWVm11AgA0FHNT3XNOAWhM6nteqtUd/blz566nMgAAAIC6UKvv6AMAAACNW62C/jPPPBM77bRTlJeXr/JZWVlZ7LzzzvH888/XWXEAAABA7dQq6I8ePTpOO+20Gr9TkJ+fHz/5yU/i+uuvr7PiAAAAgNqpVdB/9dVX45BDDlnt5717946ZM2d+56IAAACAdVOroF9aWhrNmjVb7edNmzaNRYsWfeeiAAAAgHVTq6DfsWPHeO2111b7+d///vfo0KHDdy4KAAAAWDe1CvqHHXZYXHLJJfHZZ5+t8tny5ctjxIgRccQRR9RZcQAAAEDtNK1N54svvjgefvjh2G677eKnP/1pbL/99hER8a9//SvGjBkTlZWVcdFFF62XQgEAAIBvV6ugX1BQENOnT48zzzwzhg0bFkmSREREVlZW9OnTJ8aMGRMFBQXrpVAAAADg29Uq6EdEbLXVVjF58uT4+OOPY86cOZEkSWy77bbRunXr9VEfAAAAUAu1DvortW7dOn7wgx/UZS0AAADAd1Srh/EBAAAAjZugDwAAACki6AMAAECKCPoAAACQIoI+AAAApIigDwAAACki6AMAAECKNIqgP2bMmCgqKorc3Nzo2bNnvPTSS2s1bsKECZGVlRX9+/dfvwUCAADABqLBg/7EiROjpKQkRowYEbNmzYquXbtGnz59YuHChWscN3fu3Dj//PNjn332qadKAQAAoPFr8KA/atSoOO2002LIkCGx0047xdixY2OjjTaKO+64Y7VjKisr44QTTojLLrssOnXqVI/VAgAAQOPWoEF/xYoVMXPmzCguLs60ZWdnR3FxccyYMWO14y6//PJo165dnHLKKd+6j4qKiigvL6/2AgDSxXwPAF9p0KC/ePHiqKysjIKCgmrtBQUFsWDBghrHvPDCC3H77bfHrbfeulb7GDlyZOTn52dehYWF37luAKBxMd8DwFcafOl+bSxdujROOumkuPXWW6NNmzZrNWbYsGFRVlaWec2fP389VwkA1DfzPQB8pWlD7rxNmzbRpEmTKC0trdZeWloa7du3X6X/22+/HXPnzo2+fftm2qqqqiIiomnTpvHmm29G586dq43JycmJnJyc9VA9ANBYmO8B4CsNeke/efPm0b1795g2bVqmraqqKqZNmxa9evVapf8OO+wQ//jHP2L27NmZV79+/eKAAw6I2bNnW6YHAADA916D3tGPiCgpKYlBgwZFjx49Yvfdd4/Ro0fHsmXLYsiQIRERMXDgwOjYsWOMHDkycnNzo0uXLtXGt2rVKiJilXYAAAD4PmrwoD9gwIBYtGhRDB8+PBYsWBC77bZbTJkyJfOAvnnz5kV29gb1KAEAAABoMFlJkiQNXUR9Ki8vj/z8/CgrK4u8vLyGLgcAzE3rgXMKQGNS3/OSW+UAAACQIoI+AAAApIigDwAAACki6AMAAECKCPoAAACQIoI+AAAApIigDwAAACki6AMAAECKCPoAAACQIoI+AAAApIigDwAAACki6AMAAECKCPoAAACQIoI+AAAApIigDwAAACki6AMAAECKCPoAAACQIoI+AAAApIigDwAAACki6AMAAECKCPoAAACQIoI+AAAApIigDwAAACki6AMAAECKCPoAAACQIoI+AAAApIigDwAAACki6AMAAECKCPoAAACQIoI+AAAApIigDwAAACki6AMAAECKCPoAAACQIoI+AAAApIigDwAAACki6AMAAECKCPoAAACQIoI+AAAApIigDwAAACki6AMAAECKCPoAAACQIoI+AAAApIigDwAAACki6AMAAECKCPoAAACQIoI+AAAApIigDwAAACki6AMAAECKCPoAAACQIoI+AAAApIigDwAAACki6AMAAECKCPoAAACQIoI+AAAApIigDwAAACki6AMAAECKCPoAAACQIoI+AAAApIigDwAAACki6AMAAECKCPoAAACQIoI+AAAApIigDwAAACki6AMAAECKCPoAAACQIoI+AAAApIigDwAAACki6AMAAECKCPoAAACQIoI+AAAApIigDwAAACki6AMAAECKCPoAAACQIo0i6I8ZMyaKiooiNzc3evbsGS+99NJq+956662xzz77ROvWraN169ZRXFy8xv4AAADwfdLgQX/ixIlRUlISI0aMiFmzZkXXrl2jT58+sXDhwhr7P/fcc3HcccfFs88+GzNmzIjCwsLo3bt3vP/++/VcOQAAADQ+WUmSJA1ZQM+ePeMHP/hB3HTTTRERUVVVFYWFhXHOOefEhRde+K3jKysro3Xr1nHTTTfFwIEDv7V/eXl55OfnR1lZWeTl5X3n+gHguzI31T3nFIDGpL7npabrfQ9rsGLFipg5c2YMGzYs05adnR3FxcUxY8aMtdrGp59+Gp9//nlsuummNX5eUVERFRUVmffl5eXfrWgAoNEx3wPAVxp06f7ixYujsrIyCgoKqrUXFBTEggUL1mobF1xwQWy++eZRXFxc4+cjR46M/Pz8zKuwsPA71w0ANC7mewD4SoN/R/+7uOqqq2LChAnxyCOPRG5ubo19hg0bFmVlZZnX/Pnz67lKAGB9M98DwFcadOl+mzZtokmTJlFaWlqtvbS0NNq3b7/Gsb/97W/jqquuiqeffjp23XXX1fbLycmJnJycOqkXAGiczPcA8JUGvaPfvHnz6N69e0ybNi3TVlVVFdOmTYtevXqtdtw111wTv/71r2PKlCnRo0eP+igVAAAANggNekc/IqKkpCQGDRoUPXr0iN133z1Gjx4dy5YtiyFDhkRExMCBA6Njx44xcuTIiIi4+uqrY/jw4XH//fdHUVFR5rv8LVu2jJYtWzbYcQAAAEBj0OBBf8CAAbFo0aIYPnx4LFiwIHbbbbeYMmVK5gF98+bNi+zsrxYe3HLLLbFixYo45phjqm1nxIgRcemll9Zn6QAAANDoZCVJkjR0EfXJ7+oC0NiYm+qecwpAY1Lf89IG/dR9AAAAoDpBHwAAAFJE0AcAAIAUEfQBAAAgRQR9AAAASBFBHwAAAFJE0AcAAIAUEfQBAAAgRQR9AAAASBFBHwAAAFJE0AcAAIAUEfQBAAAgRQR9AAAASBFBHwAAAFJE0AcAAIAUEfQBAAAgRQR9AAAASBFBHwAAAFJE0AcAAIAUEfQBAAAgRQR9AAAASBFBHwAAAFJE0AcAAIAUEfQBAAAgRQR9AAAASBFBHwAAAFJE0AcAAIAUEfQBAAAgRQR9AAAASBFBHwAAAFJE0AcAAIAUEfQBAAAgRQR9AAAASBFBHwAAAFJE0AcAAIAUEfQBAAAgRQR9AAAASBFBHwAAAFJE0AcAAIAUEfQBAAAgRQR9AAAASBFBHwAAAFJE0AcAAIAUEfQBAAAgRQR9AAAASBFBHwAAAFJE0AcAAIAUEfQBAAAgRQR9AAAASBFBHwAAAFJE0AcAAIAUEfQBAAAgRQR9AAAASBFBHwAAAFJE0AcAAIAUEfQBAAAgRQR9AAAASBFBHwAAAFJE0AcAAIAUEfQBAAAgRQR9AAAASBFBHwAAAFJE0AcAAIAUEfQBAAAgRQR9AAAASBFBHwAAAFJE0AcAAIAUEfQBAAAgRQR9AAAASBFBHwAAAFJE0AcAAIAUEfQBAAAgRQR9AAAASJFGEfTHjBkTRUVFkZubGz179oyXXnppjf0feOCB2GGHHSI3Nzd22WWXmDx5cj1VCgAAAI1bgwf9iRMnRklJSYwYMSJmzZoVXbt2jT59+sTChQtr7D99+vQ47rjj4pRTTon/+7//i/79+0f//v3jtddeq+fKAQAAoPHJSpIkacgCevbsGT/4wQ/ipptuioiIqqqqKCwsjHPOOScuvPDCVfoPGDAgli1bFo8//nimbY899ojddtstxo4d+637Ky8vj/z8/CgrK4u8vLy6OxAAWEfmprrnnALQmNT3vNR0ve9hDVasWBEzZ86MYcOGZdqys7OjuLg4ZsyYUeOYGTNmRElJSbW2Pn36xKOPPlpj/4qKiqioqMi8Lysri4gvTzQANAYr56QG/tv7Bs18D0BjVt9zfYMG/cWLF0dlZWUUFBRUay8oKIh//etfNY5ZsGBBjf0XLFhQY/+RI0fGZZddtkp7YWHhOlYNAOvHhx9+GPn5+Q1dxgbJfA/AhqC+5voGDfr1YdiwYdVWACxZsiS22mqrmDdvXmoupsrLy6OwsDDmz5+fmuWJjmnDkLZjStvxRDimDUVZWVlsueWWsemmmzZ0KRustM/3afzv3jFtGBzThiFtx5S244mo/7m+QYN+mzZtokmTJlFaWlqtvbS0NNq3b1/jmPbt29eqf05OTuTk5KzSnp+fn5r/aFbKy8tzTBsAx9T4pe14IhzThiI7u8GfkbvB+r7M92n8794xbRgc04YhbceUtuOJqL+5vkGvKJo3bx7du3ePadOmZdqqqqpi2rRp0atXrxrH9OrVq1r/iIipU6eutj8AAAB8nzT40v2SkpIYNGhQ9OjRI3bfffcYPXp0LFu2LIYMGRIREQMHDoyOHTvGyJEjIyLi3HPPjf322y+uu+66OPzww2PChAnxyiuvxLhx4xryMAAAAKBRaPCgP2DAgFi0aFEMHz48FixYELvttltMmTIl88C9efPmVVvesOeee8b9998fF198cfzqV7+KbbfdNh599NHo0qXLWu0vJycnRowYUePyvg2VY9owOKbGL23HE+GYNhRpPKaGlrZzmrbjiXBMGwrHtGFI2zGl7Xgi6v+YshK/5QMAAACp4ak/AAAAkCKCPgAAAKSIoA8AAAApIugDAABAigj6wHpXVFQUo0ePbugyAID1xFwPjYugDykzePDg6N+/f0RE7L///nHeeefV277vvPPOaNWq1SrtL7/8cpx++un1VgcApJm5Hvg2TRu6AKDxW7FiRTRv3nydx7dt27YOqwEA6pq5HtLFHX1IqcGDB8ef//znuOGGGyIrKyuysrJi7ty5ERHx2muvxaGHHhotW7aMgoKCOOmkk2Lx4sWZsfvvv3/89Kc/jfPOOy/atGkTffr0iYiIUaNGxS677BIbb7xxFBYWxllnnRWffPJJREQ899xzMWTIkCgrK8vs79JLL42IVZfzzZs3L4488sho2bJl5OXlxY9//OMoLS3NfH7ppZfGbrvtFvfcc08UFRVFfn5+HHvssbF06dL1e9IAYANirgdWR9CHlLrhhhuiV69ecdppp8UHH3wQH3zwQRQWFsaSJUviwAMPjG7dusUrr7wSU6ZMidLS0vjxj39cbfxdd90VzZs3jxdffDHGjh0bERHZ2dnxv//7v/H666/HXXfdFc8880z88pe/jIiIPffcM0aPHh15eXmZ/Z1//vmr1FVVVRVHHnlkfPTRR/HnP/85pk6dGu+8804MGDCgWr+33347Hn300Xj88cfj8ccfjz//+c9x1VVXraezBQAbHnM9sDqW7kNK5efnR/PmzWOjjTaK9u3bZ9pvuumm6NatW1x55ZWZtjvuuCMKCwvjrbfeiu222y4iIrbddtu45pprqm3z698BLCoqit/85jdxxhlnxM033xzNmzeP/Pz8yMrKqra/b5o2bVr84x//iHfffTcKCwsjIuLuu++OnXfeOV5++eX4wQ9+EBFfXiTceeedsckmm0RExEknnRTTpk2LK6644rudGABICXM9sDru6MP3zKuvvhrPPvtstGzZMvPaYYcdIuLLv6yv1L1791XGPv3003HQQQdFx44dY5NNNomTTjopPvzww/j000/Xev9vvPFGFBYWZib+iIiddtopWrVqFW+88UamraioKDPxR0R06NAhFi5cWKtjBYDvI3M94I4+fM988skn0bdv37j66qtX+axDhw6Z/3vjjTeu9tncuXPjiCOOiDPPPDOuuOKK2HTTTeOFF16IU045JVasWBEbbbRRndbZrFmzau+zsrKiqqqqTvcBAGlkrgcEfUix5s2bR2VlZbW2//mf/4mHHnooioqKomnTtf+fgJkzZ0ZVVVVcd911kZ395WKgP/zhD9+6v2/acccdY/78+TF//vzMX/r/+c9/xpIlS2KnnXZa63oAAHM9UDNL9yHFioqK4m9/+1vMnTs3Fi9eHFVVVXH22WfHRx99FMcdd1y8/PLL8fbbb8eTTz4ZQ4YMWePEvc0228Tnn38eN954Y7zzzjtxzz33ZB7c8/X9ffLJJzFt2rRYvHhxjcv8iouLY5dddokTTjghZs2aFS+99FIMHDgw9ttvv+jRo0ednwMASDNzPVATQR9S7Pzzz48mTZrETjvtFG3bto158+bF5ptvHi+++GJUVlZG7969Y5dddonzzjsvWrVqlfnrfU26du0ao0aNiquvvjq6dOkS9913X4wcObJanz333DPOOOOMGDBgQLRt23aVB/xEfLks749//GO0bt069t133yguLo5OnTrFxIkT6/z4ASDtzPVATbKSJEkauggAAACgbrijDwAAACki6AMAAECKCPoAAACQIoI+AAAApIigDwAAACki6AMAAECKCPoAAACQIoI+AAAApIigDwAAACki6AMAAECKCPoAAACQIoI+AAAApIigDwAAACki6AMAAECKCPoAAACQIoI+AAAApIigDwAAACki6AMAAECKCPoAAACQIoI+AAAApIigDwAAACki6AMAAECKCPoAAACQIoI+AAAApIigDwAAACki6AMAAECKCPoAAACQIoI+AAAApIigDwAAACki6AMAAECKCPoAAACQIoI+AAAApIigDwAAACki6AMAAECKCPoAAACQIoI+AAAApIigDwAAACki6AMAAECKCPoAAACQIoI+QD0pKiqKwYMHN3QZAACknKBPqt15552RlZWVeTVt2jQ6duwYgwcPjvfff3+1426++ebIysqKnj17rrbPym2eeuqpNX5+0UUXZfosXrz4Ox/Lhuzr/wbZ2dmx+eabR+/eveO5556r0/1Mnjw5Lr300u+8naqqqrj77rvj4IMPjjZt2kSzZs2iXbt20bt37xg3blxUVFR892IBaJRcOzQeFRUVceONN8bee+8drVu3jubNm8fmm28e/fr1i9///vdRWVlZ47g33ngjsrKyIjc3N5YsWVJjn/333z+6dOlSra2oqCiysrLinHPOWaX/c889F1lZWfHggw9+5+OC+iDo871w+eWXxz333BNjx46NQw89NO69997Yb7/94rPPPqux/3333RdFRUXx0ksvxZw5c1a73dzc3HjooYdixYoVq3z2+9//PnJzc+vsGDZ0Bx98cNxzzz1x1113xRlnnBF///vf48ADD4wnnniizvYxefLkuOyyy77TNpYvXx6HHXZYDBo0KD799NM4//zzY9y4cXHBBRdEbm5unHXWWXHWWWet07bffPPNuPXWW79TfQDUD9cODWvRokWx1157xc9+9rNo2bJlXHzxxfG73/0uzjnnnFi2bFkcf/zxceWVV9Y49t5774327dtHRKxTML/11lvjv//973eqHxpcAik2fvz4JCKSl19+uVr7BRdckEREMnHixFXGvPPOO0lEJA8//HDStm3b5NJLL61x2xGR9O/fP8nOzk4effTRap+9+OKLSUQkRx99dBIRyaJFi+ruoDZAEZGcffbZ1dr+/ve/JxGR9O7de7Xjli9fnlRWVq71fs4+++zku/7P2k9+8pMkIpLRo0fX+Plbb72VjBkz5jvtA4DGy7VD49CnT58kOzs7eeihh2r8/OWXX07uvffeVdqrqqqSoqKipKSkJDnqqKOS/fffv8bx++23X7LzzjtXa9tqq62SnXfeOWnatGlyzjnnVPvs2WefTSIieeCBB9bxiKB+uaPP99I+++wTERFvv/32Kp/dd9990bp16zj88MPjmGOOifvuu2+12+nYsWPsu+++cf/996+yjV122WWVJWGrM3jw4CgqKlql/dJLL42srKxqbVOnTo299947WrVqFS1btoztt98+fvWrX2U+X7FiRQwfPjy6d+8e+fn5sfHGG8c+++wTzz777Crb//DDD+Okk06KvLy8aNWqVQwaNCheffXVyMrKijvvvLNa33/9619xzDHHxKabbhq5ubnRo0eP+NOf/rRWx1eTXXbZJdq0aRPvvvtuRHy1JG7ChAlx8cUXR8eOHWOjjTaK8vLyiIh44IEHonv37tGiRYto06ZNnHjiidWWUA4ePDjGjBkTEdW/KrDSsmXL4uc//3kUFhZGTk5ObL/99vHb3/42kiTJ9Jk/f37cdtttccghh8S5555bY93bbrvtKnf0f/vb38aee+4Zm222WbRo0SK6d+9e4x2Eb35Hf+Xy0BdffDFKSkqibdu2sfHGG8dRRx0VixYtquUZBWB9cu3wpfq4dpgxY0Y8+eSTcfrpp8cPf/jDGvv06NEjTjjhhFXaX3zxxZg7d24ce+yxceyxx8bzzz8f//nPf751nysVFRXFwIED3dVngyfo8700d+7ciIho3br1Kp/dd9998cMf/jCaN28exx13XPz73/+Ol19+ebXbOv744+Oxxx6LTz75JCIivvjii3jggQfi+OOPr/O6X3/99TjiiCOioqIiLr/88rjuuuuiX79+8eKLL2b6lJeXx2233Rb7779/XH311XHppZfGokWLok+fPjF79uxMv6qqqujbt2/8/ve/j0GDBsUVV1wRH3zwQQwaNKjG/e6xxx7xxhtvxIUXXhjXXXddbLzxxtG/f/945JFH1ulYPv744/j4449js802q9b+61//OiZNmhTnn39+XHnlldG8efO4884748c//nE0adIkRo4cGaeddlo8/PDDsffee2e+e/eTn/wkDj744IiIuOeeezKviIgkSaJfv35x/fXXxyGHHBKjRo2K7bffPn7xi19ESUlJZt9PPPFEVFZWxoknnlirY7nhhhuiW7ducfnll8eVV14ZTZs2jR/96EcxadKktRp/zjnnxKuvvhojRoyIM888Mx577LH46U9/WqsaAFi/XDvU37XDY489FhFR6/k44st/i86dO8cPfvCD6Nu3b2y00Ubx+9//vlbbuOiii+KLL76Iq666qtb7h0ajoZcUwPq0cvnd008/nSxatCiZP39+8uCDDyZt27ZNcnJykvnz51fr/8orryQRkUydOjVJki+Xf22xxRbJueeeu8q24/8vR//oo4+S5s2bJ/fcc0+SJEkyadKkJCsrK5k7d24yYsSItVp+N2jQoGSrrbZapX3l+JWuv/76b93eF198kVRUVFRr+/jjj5OCgoLk5JNPzrQ99NBDqyxRr6ysTA488MAkIpLx48dn2g866KBkl112ST777LNMW1VVVbLnnnsm22677RqPLUm+PFennHJKsmjRomThwoXJ3/72t+Sggw5KIiK57rrrkiT5aklcp06dkk8//TQzdsWKFUm7du2SLl26JMuXL8+0P/7440lEJMOHD8+0rW7p/qOPPppERPKb3/ymWvsxxxyTZGVlJXPmzEmSJEmGDh2aREQye/bsav0qKiqSRYsWZV6LFy+u9vnX611Zc5cuXZIDDzywWvtWW22VDBo0KPN+5X+fxcXFSVVVVaZ96NChSZMmTZIlS5asejIBWK9cO3ypIa8djjrqqCQiVpkHly9fXm0+/vjjj6t9vmLFimSzzTZLLrrookzb8ccfn3Tt2nWVfaxu6f7hhx+eJEmSDBkyJMnNzU3++9//Jkli6T4bHnf0+V4oLi6Otm3bRmFhYRxzzDGx8cYbx5/+9KfYYostqvW77777oqCgIA444ICI+HIJ+IABA2LChAmrfbJr69at45BDDsn8tfj++++PPffcM7baaqs6P45WrVpFRMQf//jHqKqqqrFPkyZNonnz5hHx5V/eP/roo/jiiy+iR48eMWvWrEy/KVOmRLNmzeK0007LtGVnZ8fZZ59dbXsfffRRPPPMM/HjH/84li5dGosXL47FixfHhx9+GH369Il///vfa3wK8Uq33357tG3bNtq1axc9e/bMLFc/77zzqvUbNGhQtGjRIvP+lVdeiYULF8ZZZ51V7QFFhx9+eOywww5rddd88uTJ0aRJk/jZz35Wrf3nP/95JEmSeSDgyq8JtGzZcpXxbdu2zby++W/79Xo//vjjKCsri3322afa+V6T008/vdoyy3322ScqKyvjvffeW6vxANQ91w4Nd+2wuvl47Nix1ebjvffeu9rnTzzxRHz44Ydx3HHHZdqOO+64ePXVV+P1119f7f5qcvHFF7urzwZN0Od7YcyYMTF16tR48MEH47DDDovFixdHTk5OtT6VlZUxYcKEOOCAA+Ldd9+NOXPmxJw5c6Jnz55RWloa06ZNW+32jz/++Jg6dWrMmzcvHn300fWy9C4iYsCAAbHXXnvFqaeeGgUFBXHsscfGH/7wh1Um7rvuuit23XXXyM3Njc022yzatm0bkyZNirKyskyf9957Lzp06BAbbbRRtbHbbLNNtfdz5syJJEnikksuqTa5tm3bNkaMGBEREQsXLvzW2o888siYOnVqPP300/G3v/0tFi9eHNddd11kZ1f/n6Gtt9662vuVYXf77bdfZZs77LDDWoXh9957LzbffPPYZJNNqrXvuOOO1fax8vOVSylX2muvvWLq1KkxderU6N279yrbf/zxx2OPPfaI3Nzc2HTTTaNt27Zxyy23VDvfa7LllltWe79yWejHH3+8VuMBqHuuHRru2mF18/HRRx+dmY933XXXVcbde++9sfXWW0dOTk7m36Jz586x0UYbrfG5CTXp1KlTnHTSSTFu3Lj44IMPajUWGoOmDV0A1Ifdd989evToERER/fv3j7333juOP/74ePPNNzN/LX7mmWfigw8+iAkTJsSECRNW2cZ9991XY8iLiOjXr1/k5OTEoEGDoqKiIn784x/Xqr5vPjRnpW/eCWjRokU8//zz8eyzz8akSZNiypQpMXHixDjwwAPjqaeeiiZNmsS9994bgwcPjv79+8cvfvGLaNeuXea77TU9QOjbrLwQOP/886NPnz419vnmBF+TLbbYIoqLi7+139fvjte3HXbYISIiXnvttejatWumvW3btpna77333mpj/vKXv0S/fv1i3333jZtvvjk6dOgQzZo1i/Hjx6/yoKXVadKkSY3tydceFAhA/XLt0HDXDl+fj/faa69Me2FhYRQWFkbEl38UX7x4ceaz8vLyeOyxx+Kzzz6LbbfddpVt3n///XHFFVes9rzV5KKLLop77rknrr766ujfv/9aj4PGQNDne2flxHXAAQfETTfdFBdeeGFEfDkZt2vXLvPk9q97+OGH45FHHomxY8fWGERbtGgR/fv3j3vvvTcOPfTQaNOmTa1qat26deahcl9X093q7OzsOOigg+Kggw6KUaNGxZVXXhkXXXRRPPvss1FcXBwPPvhgdOrUKR5++OFqk9nKv6CvtNVWW8Wzzz4bn376abW/zH/zt387deoUERHNmjVbq6Be11YuY3zzzTfjwAMPrPbZm2++WW2Z4+om76222iqefvrpWLp0abW7+v/617+q7ePQQw+NJk2axH333Vfjk3xr8tBDD0Vubm48+eST1e70jB8/fq3GA9D4uXb4Un1dOxxxxBFx1VVXxX333Vct6K/Jww8/HJ999lnccsstq5zLN998My6++OJ48cUXV1nuvyadO3eOE088MX73u99Fz549a3UM0NAs3ed7af/994/dd989Ro8eHZ999lksX748Hn744TjiiCPimGOOWeX105/+NJYuXbrGn4Q5//zzY8SIEXHJJZfUup7OnTtHWVlZ/P3vf8+0ffDBB6s8lfajjz5aZexuu+0WEREVFRUR8dXd4a/fDf7b3/4WM2bMqDauT58+8fnnn8ett96aaauqqlrlYqVdu3ax//77x+9+97sal66t75+B69GjR7Rr1y7Gjh2bOcaIL7+H98Ybb8Thhx+eadt4440jIla58DnssMOisrIybrrppmrt119/fWRlZcWhhx4aEV8uoT/55JPjiSeeWKXvSt+8y96kSZPIysqqdgdl7ty58eijj9b6WAFovFw71N+1w1577RUHH3xwjBs3Lv74xz/W2Oeb8/G9994bnTp1ijPOOGOVf4vzzz8/WrZsWevl+xFfflf/888/j2uuuabWY6EhuaPP99YvfvGL+NGPfhR33nlntG7dOpYuXRr9+vWrse8ee+wRbdu2jfvuuy8GDBhQY5+uXbtWW+5dG8cee2xccMEFcdRRR8XPfvaz+PTTT+OWW26J7bbbrtpDcC6//PJ4/vnn4/DDD4+tttoqFi5cGDfffHNsscUWmb9QH3HEEfHwww/HUUcdFYcffni8++67MXbs2Nhpp52qfdetf//+sfvuu8fPf/7zmDNnTuywww7xpz/9KXNB8PW/6I8ZMyb23nvv2GWXXeK0006LTp06RWlpacyYMSP+85//xKuvvrpOx702mjVrFldffXUMGTIk9ttvvzjuuOOitLQ0brjhhigqKoqhQ4dm+nbv3j0iIn72s59Fnz59okmTJnHsscdG375944ADDoiLLroo5s6dG127do2nnnoq/vjHP8Z5550XnTt3zmxj9OjR8e6778Y555wTEyZMiL59+0a7du1i8eLF8eKLL8Zjjz1W7XkBhx9+eIwaNSoOOeSQOP7442PhwoUxZsyY2GabbapdfAGw4XPtUH/XDvfee28ccsgh0b9//zj00EOjuLg4WrduHQsWLIinn346nn/++cwf6v/73//Gs88+u8pDd1fKycmJPn36xAMPPBD/+7//G82aNVvr87zyrv5dd9211mOgUWi4B/7D+rfyJ3JefvnlVT6rrKxMOnfunHTu3Dk54ogjktzc3GTZsmWr3dbgwYOTZs2aZX5aLf7/T+Ssydr+RE6SJMlTTz2VdOnSJWnevHmy/fbbJ/fee+8qP5Ezbdq05Mgjj0w233zzpHnz5snmm2+eHHfccclbb72V6VNVVZVceeWVyVZbbZXk5OQk3bp1Sx5//PEaf4Zn0aJFyfHHH59ssskmSX5+fjJ48ODkxRdfTCIimTBhQrW+b7/9djJw4MCkffv2SbNmzZKOHTsmRxxxRPLggw9+67Gtzbn6tp+tmThxYtKtW7ckJycn2XTTTZMTTjgh+c9//lOtzxdffJGcc845Sdu2bZOsrKxq527p0qXJ0KFDk8033zxp1qxZsu222ybXXntttZ+1+/p2xo8fnxx44IHJpptumjRt2jRp06ZNctBBByVjx46t9jN/SZIkt99+e7LtttsmOTk5yQ477JCMHz9+lX+7JFn9z+t987/Plefi2WefXeM5A6DuuXZoHNcOSfLlz+mNHj066dWrV5KXl5c0bdo0ad++fXLEEUck9913X/LFF18kSZIk1113XRIRybRp01a7rTvvvDOJiOSPf/xjkiTf/vN6X/fvf/87adKkiZ/XY4OSlSSe9gR85dFHH42jjjoqXnjhhbX+XhwA8P3l2gEaH0EfvseWL19e7QFBlZWV0bt373jllVdiwYIFDfoEfACg8XHtABsG39GH77Fzzjknli9fHr169YqKiop4+OGHY/r06XHllVeaqAGAVbh2gA2DO/rwPXb//ffHddddF3PmzInPPvssttlmmzjzzDPjpz/9aUOXBgA0Qq4dYMPQoEH/+eefj2uvvTZmzpyZ+TmQ/v37r3HMc889FyUlJfH6669HYWFhXHzxxTF48OB6qRcAAAAau+yG3PmyZcuia9euq/z25uq8++67cfjhh8cBBxwQs2fPjvPOOy9OPfXUePLJJ9dzpQAAALBhaDRL97Oysr71jv4FF1wQkyZNitdeey3Tduyxx8aSJUtiypQp9VAlAAAANG4b1MP4ZsyYEcXFxdXa+vTpE+edd95qx1RUVERFRUXmfVVVVXz00Uex2WabRVZW1voqFQDWWpIksXTp0th8880jO7tBF9ttsMz3ADRm9T3Xb1BBf8GCBVFQUFCtraCgIMrLy1f5qY+VRo4cGZdddll9lQgA62z+/PmxxRZbNHQZGyTzPQAbgvqa6zeooL8uhg0bFiUlJZn3ZWVlseWWW8b8+fMjLy+vASsDgC+Vl5dHYWFhbLLJJg1dygbLfA9AY1bfc/0GFfTbt28fpaWl1dpKS0sjLy9vtb/bmZOTEzk5Oau05+XlmfgBaFQsMV935nsANgT1NddvUF8E7NWrV0ybNq1a29SpU6NXr14NVBEAAAA0Lg0a9D/55JOYPXt2zJ49OyK+/Pm82bNnx7x58yLiy2V4AwcOzPQ/44wz4p133olf/vKX8a9//Stuvvnm+MMf/hBDhw5tiPIBAACg0WnQoP/KK69Et27dolu3bhERUVJSEt26dYvhw4dHRMQHH3yQCf0REVtvvXVMmjQppk6dGl27do3rrrsubrvttujTp0+D1A8AAACNTVaSJElDF1GfysvLIz8/P8rKynxnD4BGwdxU95xTABqT+p6XNqjv6AMAAABrJugDAABAigj6AAAAkCKCPgAAAKSIoA8AAAApIugDAABAigj6AAAAkCKCPgAAAKSIoA8AAAApIugDAABAigj6AAAAkCKCPgAAAKSIoA8AAAApIugDAABAigj6AAAAkCKCPgAAAKSIoA8AAAApIugDAABAigj6AAAAkCKCPgAAAKSIoA8AAAApIugDAABAigj6AAAAkCKCPgAAAKSIoA8AAAApIugDAABAigj6AAAAkCKCPgAAAKSIoA8AAAApIugDAABAigj6AAAAkCKCPgAAAKSIoA8AAAApIugDAABAigj6AAAAkCKCPgAAAKSIoA8AAAApIugDAABAigj6AAAAkCKCPgAAAKSIoA8AAAApIugDAABAigj6AAAAkCKCPgAAAKSIoA8AAAApIugDAABAigj6AAAAkCKCPgAAAKSIoA8AAAApIugDAABAigj6AAAAkCKCPgAAAKSIoA8AAAApIugDAABAigj6AAAAkCKCPgAAAKSIoA8AAAApIugDAABAigj6AAAAkCKCPgAAAKSIoA8AAAApIugDAABAigj6AAAAkCKCPgAAAKSIoA8AAAApIugDAABAigj6AAAAkCKCPgAAAKSIoA8AAAApIugDAABAigj6AAAAkCKCPgAAAKSIoA8AAAAp0uBBf8yYMVFUVBS5ubnRs2fPeOmll9bYf/To0bH99ttHixYtorCwMIYOHRqfffZZPVULAAAAjVuDBv2JEydGSUlJjBgxImbNmhVdu3aNPn36xMKFC2vsf//998eFF14YI0aMiDfeeCNuv/32mDhxYvzqV7+q58oBAACgcWrQoD9q1Kg47bTTYsiQIbHTTjvF2LFjY6ONNoo77rijxv7Tp0+PvfbaK44//vgoKiqK3r17x3HHHfetqwAAAADg+6LBgv6KFSti5syZUVxc/FUx2dlRXFwcM2bMqHHMnnvuGTNnzswE+3feeScmT54chx122Gr3U1FREeXl5dVeAEC6mO8B4CsNFvQXL14clZWVUVBQUK29oKAgFixYUOOY448/Pi6//PLYe++9o1mzZtG5c+fYf//917h0f+TIkZGfn595FRYW1ulxAAANz3wPAF9p8Ifx1cZzzz0XV155Zdx8880xa9asePjhh2PSpEnx61//erVjhg0bFmVlZZnX/Pnz67FiAKA+mO8B4CtNG2rHbdq0iSZNmkRpaWm19tLS0mjfvn2NYy655JI46aST4tRTT42IiF122SWWLVsWp59+elx00UWRnb3q3y1ycnIiJyen7g8AAGg0zPcA8JUGu6PfvHnz6N69e0ybNi3TVlVVFdOmTYtevXrVOObTTz9dJcw3adIkIiKSJFl/xQIAAMAGosHu6EdElJSUxKBBg6JHjx6x++67x+jRo2PZsmUxZMiQiIgYOHBgdOzYMUaOHBkREX379o1Ro0ZFt27domfPnjFnzpy45JJLom/fvpnADwAAAN9nDRr0BwwYEIsWLYrhw4fHggULYrfddospU6ZkHtA3b968anfwL7744sjKyoqLL7443n///Wjbtm307ds3rrjiioY6BAAAAGhUspLv2Zr38vLyyM/Pj7KyssjLy2vocgDA3LQeOKcANCb1PS9tUE/dBwAAANZM0AcAAIAUEfQBAAAgRQR9AAAASBFBHwAAAFJE0AcAAIAUEfQBAAAgRQR9AAAASBFBHwAAAFJE0AcAAIAUEfQBAAAgRQR9AAAASBFBHwAAAFJE0AcAAIAUEfQBAAAgRQR9AAAASBFBHwAAAFJE0AcAAIAUEfQBAAAgRQR9AAAASBFBHwAAAFJE0AcAAIAUEfQBAAAgRQR9AAAASBFBHwAAAFJE0AcAAIAUEfQBAAAgRQR9AAAASBFBHwAAAFJE0AcAAIAUEfQBAAAgRQR9AAAASBFBHwAAAFJE0AcAAIAUEfQBAAAgRQR9AAAASBFBHwAAAFJE0AcAAIAUEfQBAAAgRQR9AAAASBFBHwAAAFJE0AcAAIAUEfQBAAAgRQR9AAAASBFBHwAAAFJE0AcAAIAUEfQBAAAgRQR9AAAASBFBHwAAAFJE0AcAAIAUEfQBAAAgRQR9AAAASBFBHwAAAFJE0AcAAIAUEfQBAAAgRQR9AAAASBFBHwAAAFJE0AcAAIAUEfQBAAAgRQR9AAAASBFBHwAAAFJE0AcAAIAUEfQBAAAgRQR9AAAASBFBHwAAAFJE0AcAAIAUEfQBAAAgRQR9AAAASBFBHwAAAFJE0AcAAIAUEfQBAAAgRQR9AAAASBFBHwAAAFKkwYP+mDFjoqioKHJzc6Nnz57x0ksvrbH/kiVL4uyzz44OHTpETk5ObLfddjF58uR6qhYAAAAat6YNufOJEydGSUlJjB07Nnr27BmjR4+OPn36xJtvvhnt2rVbpf+KFSvi4IMPjnbt2sWDDz4YHTt2jPfeey9atWpV/8UDAABAI9SgQX/UqFFx2mmnxZAhQyIiYuzYsTFp0qS444474sILL1yl/x133BEfffRRTJ8+PZo1axYREUVFRfVZMgAAADRqDbZ0f8WKFTFz5swoLi7+qpjs7CguLo4ZM2bUOOZPf/pT9OrVK84+++woKCiILl26xJVXXhmVlZWr3U9FRUWUl5dXewEA6WK+B4CvNFjQX7x4cVRWVkZBQUG19oKCgliwYEGNY95555148MEHo7KyMiZPnhyXXHJJXHfddfGb3/xmtfsZOXJk5OfnZ16FhYV1ehwAQMMz3wPAVxr8YXy1UVVVFe3atYtx48ZF9+7dY8CAAXHRRRfF2LFjVztm2LBhUVZWlnnNnz+/HisGAOqD+R4AvtJg39Fv06ZNNGnSJEpLS6u1l5aWRvv27Wsc06FDh2jWrFk0adIk07bjjjvGggULYsWKFdG8efNVxuTk5EROTk7dFg8ANCrmewD4SoPd0W/evHl07949pk2blmmrqqqKadOmRa9evWocs9dee8WcOXOiqqoq0/bWW29Fhw4dagz5AAAA8H3ToEv3S0pK4tZbb4277ror3njjjTjzzDNj2bJlmafwDxw4MIYNG5bpf+aZZ8ZHH30U5557brz11lsxadKkuPLKK+Pss89uqEMAAACARqVBf15vwIABsWjRohg+fHgsWLAgdtttt5gyZUrmAX3z5s2L7Oyv/hZRWFgYTz75ZAwdOjR23XXX6NixY5x77rlxwQUXNNQhAAAAQKOSlSRJ0tBF1Kfy8vLIz8+PsrKyyMvLa+hyAMDctB44pwA0JvU9L21QT90HAAAA1kzQBwAAgBQR9AEAACBFvnPQr6ioqIs6AAAAgDpQ66D/xBNPxKBBg6JTp07RrFmz2GijjSIvLy/222+/uOKKK+K///3v+qgTAAAAWAtrHfQfeeSR2G677eLkk0+Opk2bxgUXXBAPP/xwPPnkk3HbbbfFfvvtF08//XR06tQpzjjjjFi0aNH6rBsAAACoQdO17XjNNdfE9ddfH4ceemi137Zf6cc//nFERLz//vtx4403xr333htDhw6tu0oBAACAb7XWQX/GjBlr1a9jx45x1VVXrXNBAAAAwLrz1H0AAABIkVoH/X//+9/x0EMPxbvvvhsREZMmTYp99903fvCDH8QVV1wRSZLUeZEAAADA2lnrpfsRXz6Q78c//nFkZ2dHVlZWjBs3Ln7yk5/E/vvvH3l5eXHppZdmHtQHAAAA1L9a3dG/4oor4pe//GV89tlnccstt8QZZ5wRI0eOjCeeeCIef/zxGDNmTNx5553rqVQAAADg29Qq6L/55ptx8sknR1ZWVgwaNChWrFgRxcXFmc979+4d7733Xp0XCQAAAKydWgX9ZcuWxSabbPLlwOzsaNGiRWy00UaZz1u0aBEVFRV1WyEAAACw1moV9LOysiIrK2u17wEAAICGVauH8SVJEtttt10m3H/yySfRrVu3yM7OznwOAAAANJxaBf3x48evrzoAAACAOlCroD9o0KD1VQcAAABQB2oV9L9p6dKl1ZbrZ2dnR8uWLb9zUQAAAMC6qdXD+GbPnh2HHXZY5v3mm28erVu3zrxatWoVL7/8cp0XCQAAAKydWt3Rv/HGG2Pvvfeu1nbPPfdEx44dI0mSuOOOO+J///d/45577qnTIgEAAIC1U6ugP3369PjpT39arW2PPfaITp06RUREixYt4sc//nHdVQcAAADUSq2W7r/33nvRtm3bzPvLL7882rRpk3nfoUOHKC0trbvqAAAAgFqpVdDPzc2N9957L/N+6NChkZeXl3k/f/782GijjequOgAAAKBWahX0u3XrFo8++uhqP3/44YejW7du37UmAAAAYB3V6jv6Z511Vhx77LFRVFQUZ555ZmRnf/l3gsrKyrj55pvjxhtvjPvvv3+9FAoAAAB8u1oF/aOPPjpKSkrinHPOiV/96leZh/C988478cknn0RJSUkcc8wx66VQAAAA4NvVKuhHRFx99dVx1FFHxe9///v497//HRER++67bxx33HGxxx571HmBAAAAwNqrddCP+PIn9YR6AAAAaHzW+mF88+bNq9WG33///VoXAwAAAHw3ax30f/CDH8RPfvKTePnll1fbp6ysLG699dbo0qVLPPTQQ3VSIAAAALD21nrp/j//+c+44oor4uCDD47c3Nzo3r17bL755pGbmxsff/xx/POf/4zXX389/ud//ieuueaaOOyww9Zn3QAAAEANspIkSWozYPny5TFp0qR44YUX4r333ovly5dHmzZtolu3btGnT5/o0qXL+qq1TpSXl0d+fn6UlZVFXl5eQ5cDAOam9cA5BaAxqe95qdYP42vRokUcc8wxfkYPAAAAGqG1/o4+AAAA0PgJ+gAAAJAigj4AAACkiKAPAAAAKSLoAwAAQIrU6qn7zz///Fr123fffdepGAAAAOC7qVXQ33///SMrKysiIpIkqbFPVlZWVFZWfvfKAAAAgFqrVdBv3bp1bLLJJjF48OA46aSTok2bNuurLgAAAGAd1Oo7+h988EFcffXVMWPGjNhll13ilFNOienTp0deXl7k5+dnXgAAAEDDqFXQb968eQwYMCCefPLJ+Ne//hW77rpr/PSnP43CwsK46KKL4osvvlhfdQIAAABrYZ2fur/lllvG8OHD4+mnn47tttsurrrqqigvL6/L2gAAAIBaWqegX1FREffff38UFxdHly5dok2bNjFp0qTYdNNN67o+AAAAoBZq9TC+l156KcaPHx8TJkyIoqKiGDJkSPzhD38Q8AEAAKCRqFXQ32OPPWLLLbeMn/3sZ9G9e/eIiHjhhRdW6devX7+6qQ4AAAColVoF/YiIefPmxa9//evVfp6VlRWVlZXfqSgAAABg3dQq6FdVVa2vOgAAAIA6sM5P3a9JVVVVPP7443W5SQAAAKAWar10vyZz5syJO+64I+68885YtGhRfP7553WxWQAAAKCW1vmO/vLly+Puu++OfffdN7bffvuYPn16DB8+PP7zn//UZX0AAABALdT6jv7LL78ct912W0yYMCE6d+4cJ5xwQkyfPj1uvvnm2GmnndZHjQAAAMBaqlXQ33XXXaO8vDyOP/74mD59euy8884REXHhhReul+IAAACA2qnV0v0333wz9t133zjggAPcvQcAAIBGqFZB/5133ontt98+zjzzzNhiiy3i/PPPj//7v/+LrKys9VUfAAAAUAu1CvodO3aMiy66KObMmRP33HNPLFiwIPbaa6/44osv4s4774y33nprfdUJAAAArIV1fur+gQceGPfee2988MEHcdNNN8UzzzwTO+ywQ+y66651WR8AAABQC+sc9FfKz8+Ps846K1555ZWYNWtW9OrVqy7qAgAAANbBdw76K1VUVMQzzzwTf/zjH+tqkwAAAEAt1SroV1RUxLBhw6JHjx6x5557xqOPPhoREePHj4+tt946rr/++hg6dOj6qBMAAABYC01r03n48OHxu9/9LoqLi2P69Onxox/9KIYMGRJ//etfY9SoUfGjH/0omjRpsr5qBQAAAL5FrYL+Aw88EHfffXf069cvXnvttdh1113jiy++iFdffdVP7AEAAEAjUKul+//5z3+ie/fuERHRpUuXyMnJiaFDhwr5AAAA0EjUKuhXVlZG8+bNM++bNm0aLVu2rPOiAAAAgHVTq6X7SZLE4MGDIycnJyIiPvvsszjjjDNi4403rtbv4YcfrrsKAQAAgLVWq6A/aNCgau9PPPHEOi0GAAAA+G5qFfTHjx+/vuoAAAAA6kCtvqMPAAAANG6CPgAAAKSIoA8AAAApIugDAABAijSKoD9mzJgoKiqK3Nzc6NmzZ7z00ktrNW7ChAmRlZUV/fv3X78FAgAAwAaiwYP+xIkTo6SkJEaMGBGzZs2Krl27Rp8+fWLhwoVrHDd37tw4//zzY5999qmnSgEAAKDxa/CgP2rUqDjttNNiyJAhsdNOO8XYsWNjo402ijvuuGO1YyorK+OEE06Iyy67LDp16lSP1QIAAEDj1qBBf8WKFTFz5swoLi7OtGVnZ0dxcXHMmDFjteMuv/zyaNeuXZxyyinfuo+KioooLy+v9gIA0sV8DwBfadCgv3jx4qisrIyCgoJq7QUFBbFgwYIax7zwwgtx++23x6233rpW+xg5cmTk5+dnXoWFhd+5bgCgcTHfA8BXGnzpfm0sXbo0TjrppLj11lujTZs2azVm2LBhUVZWlnnNnz9/PVcJANQ38z0AfKVpQ+68TZs20aRJkygtLa3WXlpaGu3bt1+l/9tvvx1z586Nvn37ZtqqqqoiIqJp06bx5ptvRufOnauNycnJiZycnPVQPQDQWJjvAeArDXpHv3nz5tG9e/eYNm1apq2qqiqmTZsWvXr1WqX/DjvsEP/4xz9i9uzZmVe/fv3igAMOiNmzZ1umBwAAwPdeg97Rj4goKSmJQYMGRY8ePWL33XeP0aNHx7Jly2LIkCERETFw4MDo2LFjjBw5MnJzc6NLly7Vxrdq1SoiYpV2AAAA+D5q8KA/YMCAWLRoUQwfPjwWLFgQu+22W0yZMiXzgL558+ZFdvYG9SgBAAAAaDBZSZIkDV1EfSovL4/8/PwoKyuLvLy8hi4HAMxN64FzCkBjUt/zklvlAAAAkCKCPgAAAKSIoA8AAAApIugDAABAigj6AAAAkCKCPgAAAKSIoA8AAAApIugDAABAigj6AAAAkCKCPgAAAKSIoA8AAAApIugDAABAigj6AAAAkCKCPgAAAKSIoA8AAAApIugDAABAigj6AAAAkCKCPgAAAKSIoA8AAAApIugDAABAigj6AAAAkCKCPgAAAKSIoA8AAAApIugDAABAigj6AAAAkCKCPgAAAKSIoA8AAAApIugDAABAigj6AAAAkCKCPgAAAKSIoA8AAAApIugDAABAigj6AAAAkCKCPgAAAKSIoA8AAAApIugDAABAigj6AAAAkCKCPgAAAKSIoA8AAAApIugDAABAigj6AAAAkCKCPgAAAKSIoA8AAAApIugDAABAigj6AAAAkCKCPgAAAKSIoA8AAAApIugDAABAigj6AAAAkCKCPgAAAKSIoA8AAAApIugDAABAigj6AAAAkCKCPgAAAKSIoA8AAAApIugDAABAigj6AAAAkCKCPgAAAKSIoA8AAAApIugDAABAigj6AAAAkCKCPgAAAKSIoA8AAAApIugDAABAigj6AAAAkCKCPgAAAKSIoA8AAAApIugDAABAigj6AAAAkCKCPgAAAKSIoA8AAAApIugDAABAigj6AAAAkCKNIuiPGTMmioqKIjc3N3r27BkvvfTSavveeuutsc8++0Tr1q2jdevWUVxcvMb+AAAA8H3S4EF/4sSJUVJSEiNGjIhZs2ZF165do0+fPrFw4cIa+z/33HNx3HHHxbPPPhszZsyIwsLC6N27d7z//vv1XDkAAAA0PllJkiQNWUDPnj3jBz/4Qdx0000REVFVVRWFhYVxzjnnxIUXXvit4ysrK6N169Zx0003xcCBA7+1f3l5eeTn50dZWVnk5eV95/oB4LsyN9U95xSAxqS+56Wm630Pa7BixYqYOXNmDBs2LNOWnZ0dxcXFMWPGjLXaxqeffhqff/55bLrppjV+XlFRERUVFZn35eXl361oAKDRMd8DwFcadOn+4sWLo7KyMgoKCqq1FxQUxIIFC9ZqGxdccEFsvvnmUVxcXOPnI0eOjPz8/MyrsLDwO9cNADQu5nsA+EqDf0f/u7jqqqtiwoQJ8cgjj0Rubm6NfYYNGxZlZWWZ1/z58+u5SgBgfTPfA8BXGnTpfps2baJJkyZRWlparb20tDTat2+/xrG//e1v46qrroqnn346dt1119X2y8nJiZycnDqpFwBonMz3APCVBr2j37x58+jevXtMmzYt01ZVVRXTpk2LXr16rXbcNddcE7/+9a9jypQp0aNHj/ooFQAAADYIDXpHPyKipKQkBg0aFD169Ijdd989Ro8eHcuWLYshQ4ZERMTAgQOjY8eOMXLkyIiIuPrqq2P48OFx//33R1FRUea7/C1btoyWLVs22HEAAABAY9DgQX/AgAGxaNGiGD58eCxYsCB22223mDJlSuYBffPmzYvs7K8WHtxyyy2xYsWKOOaYY6ptZ8SIEXHppZfWZ+kAAADQ6GQlSZI0dBH1ye/qAtDYmJvqnnMKQGNS3/PSBv3UfQAAAKA6QR8AAABSRNAHAACAFBH0AQAAIEUEfQAAAEgRQR8AAABSRNAHAACAFBH0AQAAIEUEfQAAAEgRQR8AAABSRNAHAACAFBH0AQAAIEUEfQAAAEgRQR8AAABSRNAHAACAFBH0AQAAIEUEfQAAAEgRQR8AAABSRNAHAACAFBH0AQAAIEUEfQAAAEgRQR8AAABSRNAHAACAFBH0AQAAIEUEfQAAAEgRQR8AAABSRNAHAACAFBH0AQAAIEUEfQAAAEgRQR8AAABSRNAHAACAFBH0AQAAIEUEfQAAAEgRQR8AAABSRNAHAACAFBH0AQAAIEUEfQAAAEgRQR8AAABSRNAHAACAFBH0AQAAIEUEfQAAAEgRQR8AAABSRNAHAACAFBH0AQAAIEUEfQAAAEgRQR8AAABSRNAHAACAFBH0AQAAIEUEfQAAAEgRQR8AAABSRNAHAACAFBH0AQAAIEUEfQAAAEgRQR8AAABSRNAHAACAFBH0AQAAIEUEfQAAAEgRQR8AAABSRNAHAACAFBH0AQAAIEUEfQAAAEgRQR8AAABSRNAHAACAFBH0AQAAIEUEfQAAAEgRQR8AAABSRNAHAACAFBH0AQAAIEUEfQAAAEgRQR8AAABSRNAHAACAFBH0AQAAIEUEfQAAAEiRRhH0x4wZE0VFRZGbmxs9e/aMl156aY39H3jggdhhhx0iNzc3dtlll5g8eXI9VQoAAACNW4MH/YkTJ0ZJSUmMGDEiZs2aFV27do0+ffrEwoULa+w/ffr0OO644+KUU06J//u//4v+/ftH//7947XXXqvnygH4f+3dfVBU1/kH8O+C7gri7orAAmYBUaNR8A2VYBt14o5IbUKazkgs41utVoOtjtFQ0jaaTBNInBhTk5h0JopN0ph0muCMtWYQwUSzUaGiwReqCGJbXgJ0F4kvIPv8/uDH/XllDTY/YHcv388MM8u55+49zz6759mzXPYSERERkffRiYh4cgCJiYmYNm0aXn/9dQCAy+WC1WrFL37xC/zqV7/q0j8tLQ3ffPMN9u3bp7Q9+OCDmDRpEt56661uj9fc3AyTyQSn0wmj0dhzgRAREX1HrE09j48pERF5k76uSwN6/QjforW1FSUlJcjKylLa/Pz8YLPZYLfb3e5jt9uxfv16VVtycjLy8vLc9r958yZu3ryp/O50OgF0PNBERETeoLMmefizd5/Gek9ERN6sr2u9Rxf6DQ0NaG9vh8ViUbVbLBacP3/e7T61tbVu+9fW1rrtn52djeeee65Lu9Vq/Y6jJiIi6h2NjY0wmUyeHoZPYr0nIiJf0Fe13qML/b6QlZWlOgPA4XAgOjoa1dXVmnkz1dzcDKvViitXrmjm9ETG5Bu0FpPW4gEYk69wOp2IiopCcHCwp4fis7Re77X4vGdMvoEx+QatxaS1eIC+r/UeXeiHhITA398fdXV1qva6ujqEh4e73Sc8PPy/6m8wGGAwGLq0m0wmzTxpOhmNRsbkAxiT99NaPABj8hV+fh7/jlyf1V/qvRaf94zJNzAm36C1mLQWD9B3td6j7yj0ej0SEhJQUFCgtLlcLhQUFCApKcntPklJSar+AJCfn3/X/kRERERERET9icdP3V+/fj2WLFmCqVOnYvr06di2bRu++eYbLFu2DACwePFiDB8+HNnZ2QCAtWvXYtasWXjllVcwf/587NmzB8XFxfjDH/7gyTCIiIiIiIiIvILHF/ppaWn4+uuv8eyzz6K2thaTJk3CgQMHlC/cq66uVp3eMGPGDPzpT3/Cb37zGzzzzDMYPXo08vLyEBcXd0/HMxgM2LRpk9vT+3wVY/INjMn7aS0egDH5Ci3G5Glae0y1Fg/AmHwFY/INWotJa/EAfR+TTngtHyIiIiIiIiLN4Lf+EBEREREREWkIF/pEREREREREGsKFPhEREREREZGGcKFPREREREREpCH9bqH/xhtvICYmBoMGDUJiYiKOHz/u6SG5lZ2djWnTpmHIkCEICwvDY489hvLyclWf2bNnQ6fTqX5WrVql6lNdXY358+cjMDAQYWFh2LhxI27dutWXoSg2b97cZbxjx45Vtt+4cQMZGRkYNmwYgoKC8OMf/xh1dXWq+/CmeAAgJiamS0w6nQ4ZGRkAfCNHn332GR555BFERkZCp9MhLy9PtV1E8OyzzyIiIgIBAQGw2Wy4cOGCqk9TUxPS09NhNBphNpuxfPlytLS0qPqcPn0aDz30EAYNGgSr1YqXX365z+Npa2tDZmYm4uPjMXjwYERGRmLx4sX497//rboPd3nNycnxSDzdxQQAS5cu7TLeefPmqfp4U47uJSZ3ryudToctW7YofbwtT/cyb/fUPFdUVIQpU6bAYDBg1KhRyM3N7bW4fBFrPWt9T2Kt7+BLdYT13jvyxFrv4Vov/ciePXtEr9fLzp075cyZM7JixQoxm81SV1fn6aF1kZycLLt27ZKysjIpLS2VH/zgBxIVFSUtLS1Kn1mzZsmKFSukpqZG+XE6ncr2W7duSVxcnNhsNjl58qTs379fQkJCJCsryxMhyaZNm2T8+PGq8X799dfK9lWrVonVapWCggIpLi6WBx98UGbMmKFs97Z4RETq6+tV8eTn5wsAKSwsFBHfyNH+/fvl17/+tXz88ccCQD755BPV9pycHDGZTJKXlyenTp2SRx99VEaMGCHXr19X+sybN08mTpwoX375pXz++ecyatQoWbhwobLd6XSKxWKR9PR0KSsrkw8++EACAgLk7bff7tN4HA6H2Gw2+fDDD+X8+fNit9tl+vTpkpCQoLqP6Ohoef7551V5u/2115fxdBeTiMiSJUtk3rx5qvE2NTWp+nhTju4lpttjqampkZ07d4pOp5OKigqlj7fl6V7m7Z6Y5y5duiSBgYGyfv16OXv2rGzfvl38/f3lwIEDvRKXr2GtZ63vaaz1HXypjrDee0eeWOs9W+v71UJ/+vTpkpGRofze3t4ukZGRkp2d7cFR3Zv6+noBIIcPH1baZs2aJWvXrr3rPvv37xc/Pz+pra1V2nbs2CFGo1Fu3rzZm8N1a9OmTTJx4kS32xwOhwwcOFD+/Oc/K23nzp0TAGK320XE++JxZ+3atTJy5EhxuVwi4ns5unMSdrlcEh4eLlu2bFHaHA6HGAwG+eCDD0RE5OzZswJATpw4ofT529/+JjqdTv71r3+JiMibb74pQ4cOVcWUmZkpY8aM6dN43Dl+/LgAkMuXLytt0dHR8uqrr951H0/FI+I+piVLlkhqaupd9/HmHIncW55SU1Pl4YcfVrV5c55Eus7bPTXPPf300zJ+/HjVsdLS0iQ5Obm3Q/IJrPWs9b2Ntb6Dr9UR1nvvf0/GWt+ztb7fnLrf2tqKkpIS2Gw2pc3Pzw82mw12u92DI7s3TqcTABAcHKxqf//99xESEoK4uDhkZWXh2rVryja73Y74+HhYLBalLTk5Gc3NzThz5kzfDPwOFy5cQGRkJGJjY5Geno7q6moAQElJCdra2lT5GTt2LKKiopT8eGM8t2ttbcV7772Hn/70p9DpdEq7r+XodpWVlaitrVXlxWQyITExUZUXs9mMqVOnKn1sNhv8/Pxw7Ngxpc/MmTOh1+uVPsnJySgvL8d//vOfPorGPafTCZ1OB7PZrGrPycnBsGHDMHnyZGzZskV1OpU3xlNUVISwsDCMGTMGq1evRmNjo7LN13NUV1eHv/71r1i+fHmXbd6cpzvn7Z6a5+x2u+o+Ovv4Qi3rbaz1HTxdR1jrvT9Ht+sPtR5gvff2PLHW93ytH/DdQvI9DQ0NaG9vVz2gAGCxWHD+/HkPjereuFwurFu3Dt/73vcQFxentP/kJz9BdHQ0IiMjcfr0aWRmZqK8vBwff/wxAKC2ttZtvJ3b+lpiYiJyc3MxZswY1NTU4LnnnsNDDz2EsrIy1NbWQq/Xd5l8LRaLMlZvi+dOeXl5cDgcWLp0qdLmazm6U+cY3I3x9ryEhYWptg8YMADBwcGqPiNGjOhyH53bhg4d2ivj786NGzeQmZmJhQsXwmg0Ku2//OUvMWXKFAQHB+OLL75AVlYWampqsHXrVmXM3hTPvHnz8Pjjj2PEiBGoqKjAM888g5SUFNjtdvj7+/t0jgBg9+7dGDJkCB5//HFVuzfnyd283VPz3N36NDc34/r16wgICOiNkHwCa30H1vrew1r/f3ypjrDee3+eWOt7vtb3m4W+L8vIyEBZWRmOHDmial+5cqVyOz4+HhEREZgzZw4qKiowcuTIvh5mt1JSUpTbEyZMQGJiIqKjo/HRRx9p4o3pO++8g5SUFERGRiptvpaj/qStrQ0LFiyAiGDHjh2qbevXr1duT5gwAXq9Hj//+c+RnZ0Ng8HQ10Pt1hNPPKHcjo+Px4QJEzBy5EgUFRVhzpw5HhxZz9i5cyfS09MxaNAgVbs35+lu8zbR3bDW+wbWet/Deu8bWOt7Xr85dT8kJAT+/v5dvvGwrq4O4eHhHhpV99asWYN9+/ahsLAQ991337f2TUxMBABcvHgRABAeHu423s5tnmY2m3H//ffj4sWLCA8PR2trKxwOh6rP7fnx5nguX76MgwcP4mc/+9m39vO1HHWO4dteN+Hh4aivr1dtv3XrFpqamrw2d51F//Lly8jPz1d9uu9OYmIibt26haqqKgDeF8+dYmNjERISonqe+VqOOn3++ecoLy/v9rUFeE+e7jZv99Q8d7c+RqNREwup/w/W+g7e8NrtxFrv3THdPgat1XqA9R7wjTyx1vdOre83C329Xo+EhAQUFBQobS6XCwUFBUhKSvLgyNwTEaxZswaffPIJDh061OWUFHdKS0sBABEREQCApKQkfPXVV6oXfOckN27cuF4Z93+jpaUFFRUViIiIQEJCAgYOHKjKT3l5Oaqrq5X8eHM8u3btQlhYGObPn/+t/XwtRyNGjEB4eLgqL83NzTh27JgqLw6HAyUlJUqfQ4cOweVyKW92kpKS8Nlnn6GtrU3pk5+fjzFjxvT5KWKdRf/ChQs4ePAghg0b1u0+paWl8PPzU06H86Z43PnnP/+JxsZG1fPMl3J0u3feeQcJCQmYOHFit309nafu5u2emueSkpJU99HZxxtrWV9jre/gTXWEtd67YwK0WesB1vtO3p4ngLW+c8w9Xuu/w5cL+qw9e/aIwWCQ3NxcOXv2rKxcuVLMZrPqGw+9xerVq8VkMklRUZHqchLXrl0TEZGLFy/K888/L8XFxVJZWSl79+6V2NhYmTlzpnIfnZdumDt3rpSWlsqBAwckNDTUY5eoeeqpp6SoqEgqKyvl6NGjYrPZJCQkROrr60Wk41IUUVFRcujQISkuLpakpCRJSkry2ng6tbe3S1RUlGRmZqrafSVHV69elZMnT8rJkycFgGzdulVOnjypfCttTk6OmM1m2bt3r5w+fVpSU1PdXnJn8uTJcuzYMTly5IiMHj1adSkXh8MhFotFFi1aJGVlZbJnzx4JDAzslUuffFs8ra2t8uijj8p9990npaWlqtdW57ecfvHFF/Lqq69KaWmpVFRUyHvvvSehoaGyePFij8TTXUxXr16VDRs2iN1ul8rKSjl48KBMmTJFRo8eLTdu3FDuw5ty1F1MnZxOpwQGBsqOHTu67O+Neepu3hbpmXmu85I7GzdulHPnzskbb7zBy+vdhrWetb43sNb7Vh1hvfeOPLHWe7bW96uFvojI9u3bJSoqSvR6vUyfPl2+/PJLTw/JLQBuf3bt2iUiItXV1TJz5kwJDg4Wg8Ego0aNko0bN6qu2yoiUlVVJSkpKRIQECAhISHy1FNPSVtbmwci6rgkREREhOj1ehk+fLikpaXJxYsXle3Xr1+XJ598UoYOHSqBgYHyox/9SGpqalT34U3xdPr0008FgJSXl6vafSVHhYWFbp9rS5YsEZGOy+789re/FYvFIgaDQebMmdMl1sbGRlm4cKEEBQWJ0WiUZcuWydWrV1V9Tp06Jd///vfFYDDI8OHDJScnp8/jqaysvOtrq/N6yCUlJZKYmCgmk0kGDRokDzzwgLz44ouqItqX8XQX07Vr12Tu3LkSGhoqAwcOlOjoaFmxYkWXRY035ai7mDq9/fbbEhAQIA6Ho8v+3pin7uZtkZ6b5woLC2XSpEmi1+slNjZWdQxirWet73ms9b5VR1jvvSNPrPWerfW6/x0wEREREREREWlAv/kffSIiIiIiIqL+gAt9IiIiIiIiIg3hQp+IiIiIiIhIQ7jQJyIiIiIiItIQLvSJiIiIiIiINIQLfSIiIiIiIiIN4UKfiIiIiIiISEO40CciIiIiIiLSEC70iajXxcTEYNu2bZ4eBhEREfUS1noi78KFPpHGLF26FI899hgAYPbs2Vi3bl2fHTs3Nxdms7lL+4kTJ7By5co+GwcREZGWsdYTUXcGeHoAROT9Wltbodfrv/P+oaGhPTgaIiIi6mms9UTawr/oE2nU0qVLcfjwYbz22mvQ6XTQ6XSoqqoCAJSVlSElJQVBQUGwWCxYtGgRGhoalH1nz56NNWvWYN26dQgJCUFycjIAYOvWrYiPj8fgwYNhtVrx5JNPoqWlBQBQVFSEZcuWwel0KsfbvHkzgK6n81VXVyM1NRVBQUEwGo1YsGAB6urqlO2bN2/GpEmT8O677yImJgYmkwlPPPEErl692rsPGhERkQ9hrSeiu+FCn0ijXnvtNSQlJWHFihWoqalBTU0NrFYrHA4HHn74YUyePBnFxcU4cOAA6urqsGDBAtX+u3fvhl6vx9GjR/HWW28BAPz8/PD73/8eZ86cwe7du3Ho0CE8/fTTAIAZM2Zg27ZtMBqNyvE2bNjQZVwulwupqaloamrC4cOHkZ+fj0uXLiEtLU3Vr6KiAnl5edi3bx/27duHw4cPIycnp5ceLSIiIt/DWk9Ed8NT94k0ymQyQa/XIzAwEOHh4Ur766+/jsmTJ+PFF19U2nbu3Amr1Yp//OMfuP/++wEAo0ePxssvv6y6z9v/BzAmJga/+93vsGrVKrz55pvQ6/UwmUzQ6XSq492poKAAX331FSorK2G1WgEAf/zjHzF+/HicOHEC06ZNA9DxJiE3NxdDhgwBACxatAgFBQV44YUX/n8PDBERkUaw1hPR3fAv+kT9zKlTp1BYWIigoCDlZ+zYsQA6PlnvlJCQ0GXfgwcPYs6cORg+fDiGDBmCRYsWobGxEdeuXbvn4587dw5Wq1Up/AAwbtw4mM1mnDt3TmmLiYlRCj8AREREoL6+/r+KlYiIqD9irSci/kWfqJ9paWnBI488gpdeeqnLtoiICOX24MGDVduqqqrwwx/+EKtXr8YLL7yA4OBgHDlyBMuXL0draysCAwN7dJwDBw5U/a7T6eByuXr0GERERFrEWk9EXOgTaZher0d7e7uqbcqUKfjLX/6CmJgYDBhw71NASUkJXC4XXnnlFfj5dZwM9NFHH3V7vDs98MADuHLlCq5cuaJ80n/27Fk4HA6MGzfunsdDRERErPVE5B5P3SfSsJiYGBw7dgxVVVVoaGiAy+VCRkYGmpqasHDhQpw4cQIVFRX49NNPsWzZsm8t3KNGjUJbWxu2b9+OS5cu4d1331W+uOf247W0tKCgoAANDQ1uT/Oz2WyIj49Heno6/v73v+P48eNYvHgxZs2ahalTp/b4Y0BERKRlrPVE5A4X+kQatmHDBvj7+2PcuHEIDQ1FdXU1IiMjcfToUbS3t2Pu3LmIj4/HunXrYDablU/v3Zk4cSK2bt2Kl156CXFxcXj//feRnZ2t6jNjxgysWrUKaWlpCA0N7fIFP0DHaXl79+7F0KFDMXPmTNhsNsTGxuLDDz/s8fiJiIi0jrWeiNzRiYh4ehBERERERERE1DP4F30iIiIiIiIiDeFCn4iIiIiIiEhDuNAnIiIiIiIi0hAu9ImIiIiIiIg0hAt9IiIiIiIiIg3hQp+IiIiIiIhIQ7jQJyIiIiIiItIQLvSJiIiIiIiINIQLfSIiIiIiIiIN4UKfiIiIiIiISEO40CciIiIiIiLSkP8B1HRDz7DTBS4AAAAASUVORK5CYII=", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# CPU and RAM\n", - "\n", - "xmax = params.num_iterations\n", - "\n", - "fig, axs = plt.subplots(2, 2, figsize=(12, 12), sharex=True, sharey=\"row\")\n", - "\n", - "# Set the labels and limits for Loss D\n", - "axs[0, 0].set_xlabel(\"Iteration\")\n", - "axs[0, 0].set_ylabel(\"CPU (%)\")\n", - "axs[0, 0].set_xlim(0, xmax)\n", - "axs[0, 0].set_title(f\"CPU usage ProtoGain\")\n", - "\n", - "# Set the labels and limits for Loss G\n", - "axs[0, 1].set_xlabel(\"Iteration\")\n", - "axs[0, 1].set_title(f\"CPU usage GAIN\")\n", - "\n", - "\n", - "axs[1, 0].set_xlabel(\"Iteration\")\n", - "axs[1, 0].set_ylabel(\"RAM (GB)\")\n", - "axs[1, 0].set_title(f\"RAM usage ProtoGain\")\n", - "axs[1, 1].set_xlabel(\"Iteration\")\n", - "axs[1, 1].set_title(f\"RAM usage GAIN\")\n", - "\n", - "\n", - "x_ticks = range(0, xmax, 100)\n", - "\n", - "\n", - "# Create a color gradient based on the loop index\n", - "colors = np.linspace(0, 1, len(train_samples))\n", - "\n", - "for i, samples in enumerate(train_samples):\n", - " runs_cpu = {run: data for (s, run), data in my_cpu.items() if s == samples}\n", - " runs_cpu_array = np.array(list(runs_cpu.values()))\n", - " mean_runs_cpu = np.mean(runs_cpu_array, axis=0)\n", - " std_runs_cpu = np.std(runs_cpu_array, axis=0)\n", - "\n", - " # Use the color gradient for the plot\n", - " axs[0, 0].plot(\n", - " x_ticks, mean_runs_cpu, label=f\"{samples} samples\", c=plt.cm.viridis(colors[i])\n", - " )\n", - " axs[0, 0].fill_between(\n", - " np.arange(1, len(mean_runs_cpu) + 1, 1),\n", - " mean_runs_cpu[:, 0] + std_runs_cpu[:, 0],\n", - " mean_runs_cpu[:, 0] - std_runs_cpu[:, 0],\n", - " alpha=0.4,\n", - " color=plt.cm.viridis(colors[i]),\n", - " )\n", - " axs[0, 0].xaxis.grid(True, which=\"major\")\n", - " axs[0, 0].yaxis.grid(True, which=\"major\")\n", - "\n", - " runs_cpu = {run: data for (s, run), data in gain_cpu.items() if s == samples}\n", - " runs_cpu_array = np.array(list(runs_cpu.values()))\n", - " mean_runs_cpu = np.mean(runs_cpu_array, axis=0)\n", - " std_runs_cpu = np.std(runs_cpu_array, axis=0)\n", - "\n", - " # Use the color gradient for the plot\n", - "\n", - " axs[0, 1].plot(x_ticks, mean_runs_cpu, c=plt.cm.viridis(colors[i]))\n", - " axs[0, 1].fill_between(\n", - " np.arange(1, len(mean_runs_cpu) + 1, 1),\n", - " mean_runs_cpu[:, 0] + std_runs_cpu[:, 0],\n", - " mean_runs_cpu[:, 0] - std_runs_cpu[:, 0],\n", - " alpha=0.4,\n", - " color=plt.cm.viridis(colors[i]),\n", - " )\n", - " axs[0, 1].xaxis.grid(True, which=\"major\")\n", - " axs[0, 1].yaxis.grid(True, which=\"major\")\n", - "\n", - " runs_ram = {run: data for (s, run), data in my_ram.items() if s == samples}\n", - " runs_ram_array = np.array(list(runs_ram.values()))\n", - " mean_runs_ram = np.mean(runs_ram_array, axis=0)\n", - " std_runs_ram = np.std(runs_ram_array, axis=0)\n", - "\n", - " axs[1, 0].plot(x_ticks, mean_runs_ram, c=plt.cm.viridis(colors[i]))\n", - " axs[1, 0].fill_between(\n", - " np.arange(1, len(mean_runs_ram) + 1, 1),\n", - " mean_runs_ram[:, 0] + std_runs_ram[:, 0],\n", - " mean_runs_ram[:, 0] - std_runs_ram[:, 0],\n", - " alpha=0.4,\n", - " color=plt.cm.viridis(colors[i]),\n", - " )\n", - " axs[1, 0].xaxis.grid(True, which=\"major\")\n", - " axs[1, 0].yaxis.grid(True, which=\"major\")\n", - "\n", - " runs_ram = {run: data for (s, run), data in gain_ram.items() if s == samples}\n", - " runs_ram_array = np.array(list(runs_ram.values()))\n", - " mean_runs_ram = np.mean(runs_ram_array, axis=0)\n", - " std_runs_ram = np.std(runs_ram_array, axis=0)\n", - "\n", - " axs[1, 1].plot(x_ticks, mean_runs_ram, c=plt.cm.viridis(colors[i]))\n", - " axs[1, 1].fill_between(\n", - " np.arange(1, len(mean_runs_ram) + 1, 1),\n", - " mean_runs_ram[:, 0] + std_runs_ram[:, 0],\n", - " mean_runs_ram[:, 0] - std_runs_ram[:, 0],\n", - " alpha=0.4,\n", - " color=plt.cm.viridis(colors[i]),\n", - " )\n", - " axs[1, 1].xaxis.grid(True, which=\"major\")\n", - " axs[1, 1].yaxis.grid(True, which=\"major\")\n", - "\n", - "\n", - "fig.legend(loc=\"center right\", bbox_to_anchor=(1.05, 0.5))\n", - "\n", - "# Adjust the spacing between subplots\n", - "plt.subplots_adjust(wspace=0.05, hspace=0.2)\n", - "\n", - "# Show the plot\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "0.0 2499.0\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Original vs Imputed by feature (Added Missing Values)\n", - "\n", - "xlim = 1000000\n", - "# c=plt.cm.viridis(colors[df_test[:,3].astype(int)]), label=f\"{df_test[:,3]}\",\n", - "\n", - "x = np.linspace(-xlim, xlim, 100)\n", - "y = x\n", - "\n", - "\n", - "df_test = pd.read_csv(f\"{params.output_folder}test_imputed.csv\").values\n", - "print(df_test.min(), df_test.max())\n", - "features = [int(feature) for feature in np.unique(df_test[:, 3])]\n", - "corr = np.empty(len(features))\n", - "fig, axs = plt.subplots(len(features), figsize=(7, len(features) * 6))\n", - "colors = np.linspace(0, 1, len(features))\n", - "\n", - "for feature in features:\n", - "\n", - " filtered_array = df_test[df_test[:, 3] == feature]\n", - "\n", - " xmin = filtered_array[:, 0].min()\n", - " xmax = filtered_array[:, 0].max()\n", - "\n", - " ymin = filtered_array[:, 1].min()\n", - " ymax = filtered_array[:, 1].max()\n", - "\n", - " corr[feature] = np.corrcoef(filtered_array[:, 0], filtered_array[:, 1])[0, 1]\n", - "\n", - " axs[feature].plot(x, y, color=\"red\", linestyle=\"--\")\n", - " axs[feature].scatter(\n", - " filtered_array[:, 0],\n", - " filtered_array[:, 1],\n", - " label=f\"Correlation: {round(corr[feature],3)}\",\n", - " )\n", - " axs[feature].set_xlabel(\"Original\")\n", - " axs[feature].set_ylabel(\"Imputed\")\n", - " axs[feature].set_xlim(xmin * 0.9, xmax * 1.1)\n", - " axs[feature].legend(markerscale=0)\n", - " axs[feature].set_ylim(ymin * 0.9, ymax * 1.1)\n", - " axs[feature].set_title(f\"ribaq - Original vs Imputed (Sample {feature})\")\n", - " axs[feature].xaxis.grid(True, which=\"major\")\n", - " axs[feature].yaxis.grid(True, which=\"major\")" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Histogram: [1 0 2 4 2 3 1 4 6 7]\n", - "Bins: [0.39959863 0.44779994 0.49600124 0.54420255 0.59240385 0.64060516\n", - " 0.68880646 0.73700777 0.78520907 0.83341038 0.88161168]\n" - ] - }, - { - "data": { - "text/plain": [ - "Text(0.5, 1.0, 'Histogram of the Pearson Correlation between original and imputed values')" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Correlation Histogram\n", - "\n", - "# Define the number of bins\n", - "num_bins = 10\n", - "\n", - "# Create the bins using numpy.histogram\n", - "hist, bins = np.histogram(corr, bins=num_bins)\n", - "\n", - "# Print the histogram and bins\n", - "print(\"Histogram:\", hist)\n", - "print(\"Bins:\", bins)\n", - "\n", - "fig, ax = plt.subplots(figsize=(10, 6))\n", - "\n", - "plt.xticks(bins)\n", - "\n", - "plt.hist(corr, alpha=0.5, bins=num_bins, histtype=\"bar\", ec=\"black\")\n", - "plt.xlabel(\"Correlation\")\n", - "plt.ylabel(\"Frequency\")\n", - "plt.title(\"Histogram of the Pearson Correlation between original and imputed values\")\n", - "\n", - "# plt.figure()\n", - "# plt.plot(corr, marker=\"o\", linestyle=\"-\")\n", - "# plt.ylim(0, 1)" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Original vs Imputed all features (Added Missing Values)\n", - "\n", - "xlim = 1000000\n", - "# c=plt.cm.viridis(colors[df_test[:,3].astype(int)]), label=f\"{df_test[:,3]}\",\n", - "\n", - "x = np.linspace(-xlim, xlim, 100)\n", - "y = x\n", - "\n", - "\n", - "df_test = pd.read_csv(f\"{params.output_folder}test_imputed.csv\").values\n", - "\n", - "features = [int(feature) for feature in np.unique(df_test[:, 3])]\n", - "corr = np.corrcoef(df_test[:, 0], df_test[:, 1])\n", - "\n", - "\n", - "xmin = df_test[:, 0].min()\n", - "xmax = df_test[:, 0].max()\n", - "\n", - "ymin = df_test[:, 1].min()\n", - "ymax = df_test[:, 1].max()\n", - "\n", - "plt.scatter(df_test[:, 0], df_test[:, 1], label=corr[0, 1])\n", - "plt.legend()\n", - "plt.plot(x, y, color=\"red\", linestyle=\"--\")\n", - "\n", - "plt.xlim(xmin * 0.9, xmax * 1.1)\n", - "plt.ylim(ymin * 0.9, ymax * 1.1)\n", - "plt.xlabel(\"Original\")\n", - "plt.ylabel(\"Imputed\")\n", - "plt.grid(True)" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "d2l", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.9.18" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} From dbbe64ef40c4250289d9aa52a4ce75fe8658bda9 Mon Sep 17 00:00:00 2001 From: Yasset Perez-Riverol Date: Mon, 15 Dec 2025 06:23:46 +0000 Subject: [PATCH 09/26] Update README.md Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index eb95cc6..16abf74 100644 --- a/README.md +++ b/README.md @@ -169,7 +169,7 @@ If you want to go deep in the analysis of every metric you either set `--outall` The repository also includes a hybrid model combining Domain Adversarial Neural Networks (DANN) with GAIN for domain-adaptive imputation. -To prepare the HeLa dataset for the **DANN & GAIN** hybrid model, run the `hela_dann.ipynb` notebook first and alter the directory of the HeLa dataset in the third cell of the notebook. +To prepare the HeLa dataset for the **DANN & GAIN** hybrid model, run the `hela_dann.ipynb` notebook first and update the dataset path for the HeLa dataset in the third cell of the notebook. ## References From 1a11b8e5607d44df1b7844684ce8ebdc7de863db Mon Sep 17 00:00:00 2001 From: Yasset Perez-Riverol Date: Mon, 15 Dec 2025 06:29:20 +0000 Subject: [PATCH 10/26] update CI/CD --- .../workflows/run_continuous_integration.yml | 42 ++++++++++++++--- .github/workflows/run_tests.yml | 45 +++++++++++++------ 2 files changed, 67 insertions(+), 20 deletions(-) diff --git a/.github/workflows/run_continuous_integration.yml b/.github/workflows/run_continuous_integration.yml index 76314b3..1567960 100644 --- a/.github/workflows/run_continuous_integration.yml +++ b/.github/workflows/run_continuous_integration.yml @@ -1,29 +1,57 @@ -name: Run tests on GenerativeProteomics and tests +name: CI - Run Tests on: push: + branches: [main, master, develop] paths: - 'GenerativeProteomics/**' - 'tests/**' + - 'requirements.txt' + - 'pyproject.toml' + pull_request: + branches: [main, master, develop] + paths: + - 'GenerativeProteomics/**' + - 'tests/**' + - 'requirements.txt' + - 'pyproject.toml' jobs: - run-tests: + test: runs-on: ubuntu-latest + strategy: + matrix: + python-version: ['3.10', '3.11'] steps: - - name: Checkout repo + - name: Checkout repository uses: actions/checkout@v4 - - name: Set up Python + - name: Set up Python ${{ matrix.python-version }} uses: actions/setup-python@v5 with: - python-version: '3.11' + python-version: ${{ matrix.python-version }} + + - name: Cache pip dependencies + uses: actions/cache@v4 + with: + path: ~/.cache/pip + key: ${{ runner.os }}-pip-${{ hashFiles('requirements.txt') }} + restore-keys: | + ${{ runner.os }}-pip- - name: Install dependencies run: | + python -m pip install --upgrade pip pip install -r requirements.txt + # Ensure numpy < 2 for PyTorch compatibility + pip install "numpy<2" - name: Run tests run: | - python -m unittest discover - working-directory: ./tests + python -m unittest discover -v + working-directory: ./tests + + - name: Test package import + run: | + python -c "from GenerativeProteomics import Data, Params, Network, Metrics; print('Package imports successful!')" diff --git a/.github/workflows/run_tests.yml b/.github/workflows/run_tests.yml index 019300f..acb1bae 100644 --- a/.github/workflows/run_tests.yml +++ b/.github/workflows/run_tests.yml @@ -1,29 +1,48 @@ -name: Run Tests on Schedule - +name: Scheduled Tests on: schedule: - - cron: '0 0 */1 * *' - workflow_dispatch: + # Run daily at midnight UTC + - cron: '0 0 * * *' + workflow_dispatch: + # Allow manual triggering jobs: test: - runs-on: ubuntu-latest + runs-on: ubuntu-latest + strategy: + matrix: + python-version: ['3.10', '3.11'] steps: - - name: Checkout the code from the repository - uses: actions/checkout@v2 + - name: Checkout repository + uses: actions/checkout@v4 + + - name: Set up Python ${{ matrix.python-version }} + uses: actions/setup-python@v5 + with: + python-version: ${{ matrix.python-version }} - - name: Set up Python - uses: actions/setup-python@v2 + - name: Cache pip dependencies + uses: actions/cache@v4 with: - python-version: '3.11' + path: ~/.cache/pip + key: ${{ runner.os }}-pip-${{ hashFiles('requirements.txt') }} + restore-keys: | + ${{ runner.os }}-pip- - name: Install dependencies run: | - pip install -r requirements.txt + python -m pip install --upgrade pip + pip install -r requirements.txt + # Ensure numpy < 2 for PyTorch compatibility + pip install "numpy<2" - name: Run tests run: | - python -m unittest discover - working-directory: ./tests + python -m unittest discover -v + working-directory: ./tests + + - name: Test package import + run: | + python -c "from GenerativeProteomics import Data, Params, Network, Metrics; print('Package imports successful!')" From e0f8ccc6b2c76909bfee24003b79f247704a791d Mon Sep 17 00:00:00 2001 From: Yasset Perez-Riverol Date: Mon, 15 Dec 2025 09:06:28 +0000 Subject: [PATCH 11/26] consolidate more about gainpro --- GenerativeProteomics/gaindann.py | 288 ------- GenerativeProteomics/gainpro.py | 796 ++++++++++++++++++ GenerativeProteomics/generativeproteomics.py | 233 ----- GenerativeProteomics/imputation_management.py | 25 +- GenerativeProteomics/models/__init__.py | 17 - GenerativeProteomics/models/base_abstract.py | 10 - GenerativeProteomics/models/gain_dann.py | 72 -- GenerativeProteomics/models/medium.py | 19 - README.md | 285 +++++-- docs/source/Architecture.rst | 5 +- docs/source/GainPro.generativeproteomics.rst | 2 +- pyproject.toml | 4 +- requirements.txt | 4 + tests/test_imputation_management.py | 33 +- 14 files changed, 1047 insertions(+), 746 deletions(-) delete mode 100644 GenerativeProteomics/gaindann.py create mode 100644 GenerativeProteomics/gainpro.py delete mode 100644 GenerativeProteomics/generativeproteomics.py delete mode 100644 GenerativeProteomics/models/__init__.py delete mode 100644 GenerativeProteomics/models/base_abstract.py delete mode 100644 GenerativeProteomics/models/gain_dann.py delete mode 100644 GenerativeProteomics/models/medium.py diff --git a/GenerativeProteomics/gaindann.py b/GenerativeProteomics/gaindann.py deleted file mode 100644 index f45b3d1..0000000 --- a/GenerativeProteomics/gaindann.py +++ /dev/null @@ -1,288 +0,0 @@ -import json -import torch -import pandas as pd -import numpy as np -from datetime import datetime - -import seaborn as sns -import matplotlib.pyplot as plt -import umap.umap_ as umap - -# model -from GenerativeProteomics.gain_dann_model import GainDann -from GenerativeProteomics.hypers import Params -from GenerativeProteomics.output import Metrics -from GenerativeProteomics.params_gain_dann import ParamsGainDann -from GenerativeProteomics.data_utils import Data -from GenerativeProteomics.train import GainDannTrain - -# post analysis -# from umap_analysis import umap_analysis -# from pca_analysis import pca_analysis - -import logging -import argparse -import inquirer -import os - -logging.basicConfig(level=logging.INFO) -logger = logging.getLogger(__name__) - - -def list_checkpoints(): - checkpoint_root="checkpoints" - return sorted([d for d in os.listdir(checkpoint_root) - if os.path.isdir(os.path.join(checkpoint_root, d))]) - -def select_checkpoint_interactively(): - checkpoints = list_checkpoints() - if not checkpoints: - raise FileNotFoundError("No checkpoints found.") - - question = [ - inquirer.List("timestamp", - message="Select a checkpoint to load", - choices=checkpoints) - ] - answer = inquirer.prompt(question) - return answer["timestamp"] - - -if __name__ == "__main__": - parser = argparse.ArgumentParser() - parser.add_argument("--train", action="store_true", help="Train the model") - parser.add_argument("--impute", action="store_true", help="Impute the dataset") - parser.add_argument("--debug", action="store_true", help="Enable debug logging") - parser.add_argument("--save", action="store_true", help="Save trained model") - parser.add_argument("--umap", action="store_true", help="UMAP analysis with the trained model") - parser.add_argument("--pca", action="store_true", help="PCA analysis with the trained model") - parser.add_argument("--corr", action="store_true", help="Correlation analysis with the trained model") - parser.add_argument("--latent", action="store_true") #todo delete depois - args = parser.parse_args() - - if args.debug: - logger.setLevel(logging.DEBUG) - else: - logger.setLevel(logging.INFO) - - params_gain_dann = ParamsGainDann.read_hyperparameters("../configs/params_gain_dann.json") - params = params_gain_dann.to_dict() - logger.debug(params_gain_dann) - - if params_gain_dann["path_trained_model"] is not None: - checkpoint_dir = params_gain_dann["path_trained_model"] - logger.info(f"Loading model from {checkpoint_dir}") - try: - json_path = f"{checkpoint_dir}/metadata.json" - with open(json_path, "r") as f: - metadata = json.load(f) - except FileNotFoundError: - logger.error(f"JSON file not found: {json_path}") - raise - except json.JSONDecodeError as e: - logger.error(f"Error decoding JSON: {e}") - raise - else: #todo não sei se preciso realmente deste else - timestamp = datetime.now().strftime('%d-%m_%H:%M') - save_dir = f"../../imgs/train/{timestamp}" - - - if args.train: - # === Read dataset === - # ⚠️ todo delete o start_col na versão oficial - if params_gain_dann.path_dataset_missing != "": - print(f"Missing pd {params_gain_dann.path_dataset_missing}") - dataset_missing = pd.read_csv(params_gain_dann.path_dataset_missing, index_col=0) # dataset with induced missingness for benchmarking - dataset_missing = dataset_missing.iloc[:, 8500:] - data = Data(dataset_path=params_gain_dann.path_dataset, dataset_missing=dataset_missing, start_col=8500) - else: - data = Data(dataset_path=params_gain_dann.path_dataset, miss_rate=params["miss_rate"], start_col=8500) - protein_names = data.protein_names - input_dim = data.n_proteins - gain_params = Params() - gain_metrics = Metrics(gain_params) - logger.debug(data) - - # === Train Model === - print("Early stop patience: ", params_gain_dann["early_stop_patience"]) - train = GainDannTrain(data, params, early_stop_patience=params_gain_dann["early_stop_patience"], save_model=args.save) - train.train() - #todo test if the output of the model returns the missing values imputed and the other values as in the original - - if args.latent: - - logger.info("\nLoading model...\n") - gain_params = Params() - gain_metrics = Metrics(gain_params) - - dann_params = {"hidden_dim": metadata["params"]["hidden_dim"], - "dropout_rate": metadata["params"]["dropout_rate"]} - - # load model - model = GainDann(metadata["protein_names"], metadata["input_dim"], latent_dim=metadata["latent_dim"], n_class=metadata["n_class"], num_hidden_layers=metadata["params"]["num_hidden_layers"], - dann_params=dann_params, gain_params=gain_params, gain_metrics=gain_metrics) - model_path = f"{checkpoint_dir}/model.pt" - if not os.path.isfile(model_path): - logger.error(f"Model in {model_path} not found.") - raise FileNotFoundError - model.load_state_dict(torch.load(model_path, map_location=torch.device('cpu'))) - logger.info("\nModel loaded.\n") - - # read dataset - df = pd.read_csv(params_gain_dann["path_dataset"], index_col=0) - print("df", df.shape) - df = df.iloc[:, 8000:] - projects = df["Domain"] - - # reduce to only common proteins - common_proteins = set(model.protein_names) & set(df.columns) - df = df.loc[:, list(common_proteins)] - df["Domain"] = projects - print("df: ", df.shape) # 4820 x 2013 - data = Data(df, miss_rate=0) - print("data: ", data.dataset_normalized.shape) # 64 x 1568 - - # pad with nans - padded_data = data.dataset_normalized.reindex(columns=model.protein_names) # trick `reindex` - print("padded: ", padded_data.shape) # 64 x 2013 - - # transform to tensor - model_input = torch.tensor(padded_data.values, dtype=torch.float32) - print("model input: ", model_input.shape) - - # impute do modelo até o encoder - logger.info("Encoder...") - model.encoder.eval() - - device = torch.device("cuda" if torch.cuda.is_available() else "cpu") - - x = torch.tensor(padded_data.values, dtype=torch.float32) - - x = x.to(device) - x_filled = x.clone() - x_filled[torch.isnan(x_filled)] = 0 - - with torch.no_grad(): - x_encoded = model.encoder(x_filled) - print("X encoded", x_encoded) - - seed = 42 - - projects = data.domain_labels - print(projects) - - all_projects = projects.unique() - palette = sns.color_palette("colorblind", n_colors=len(all_projects)) - project_colors = dict(zip(all_projects, palette)) - - reducer = umap.UMAP(random_state=seed) - # embedding = reducer.fit_transform(hela) - embedding = reducer.fit_transform(x_encoded) - print(f"UMAP embedding shape: {embedding.shape}") - - plt.figure(figsize=(11,8)) - # sns.scatterplot(x=embedding[:, 0], y=embedding[:, 1], hue=hela_projects["Domain"], palette=project_colors, alpha=0.7, s=70) - sns.scatterplot(x=embedding[:, 0], y=embedding[:, 1], hue=projects, palette=project_colors, alpha=0.7, s=70) - plt.title("UMAP projection of the latent space", fontsize=12, loc="left") - ax = plt.gca() - ax.spines['top'].set_visible(False) - ax.spines['right'].set_visible(False) - plt.legend(bbox_to_anchor=(1, 1), title="Domain", frameon=False, title_fontsize="large") - plt.tight_layout() - plt.savefig("../../imgs/umap-latent-space.png") - plt.show() - - - - - - - if args.impute: - logger.info("\nLoading model...\n") - gain_params = Params() - gain_metrics = Metrics(gain_params) - - dann_params = {"hidden_dim": metadata["params"]["hidden_dim"], - "dropout_rate": metadata["params"]["dropout_rate"]} - - # load model - model = GainDann(metadata["protein_names"], metadata["input_dim"], latent_dim=metadata["latent_dim"], n_class=metadata["n_class"], num_hidden_layers=metadata["params"]["num_hidden_layers"], - dann_params=dann_params, gain_params=gain_params, gain_metrics=gain_metrics) - model_path = f"{checkpoint_dir}/model.pt" - if not os.path.isfile(model_path): - logger.error(f"Model in {model_path} not found.") - raise FileNotFoundError - model.load_state_dict(torch.load(model_path, map_location=torch.device('cpu'))) - logger.info("\nModel loaded.\n") - - # dataset_missing = torch.tensor(data.dataset_missing.values, dtype=torch.float32) - # dataset_imputed, _ = model(dataset_missing) - # dataset_hat = inverse_transform_output(dataset_imputed, data.scaler) - - # if args.umap: - # # perform umap analysis - # umap_analysis(dataset_missing, dataset_hat, data.domain_labels, params["seed"], checkpoint_dir) - - # if args.pca: - # # perform pca analysis - # n_components = 2 - # pca_analysis(dataset_hat, n_components, params["seed"], checkpoint_dir) - - # if args.corr: - # correlation_measured_predicted(dataset_missing, dataset_hat, data.samples_names, data.sample_to_project, checkpoint_dir) - - # imputation - #todo verificar a ordem das colunas, isso vai ser importante para o nosso modelo! - - # read dataset - df = pd.read_csv(params_gain_dann["path_dataset"], index_col=0) - - # reduce to only common proteins - common_proteins = set(model.protein_names) & set(df.columns) - df = df.loc[:, list(common_proteins)] - print("df: ", df.shape) # 64 x 1569 - - # print(common_proteins) - # print(len(common_proteins)) - - # create data (that will be scaled) - # mask alguns elementos - data = Data(df, miss_rate=0.1, start_col=0) - print("data: ", data.dataset_normalized.shape) # 64 x 1568 - - # use normalized dataset - # usar dataset with induced missingness - incomplete_data = data.dataset_missing - # incomplete_data = data.dataset_normalized - - # pad with nans - padded_data = incomplete_data.reindex(columns=model.protein_names) # trick `reindex` - print("padded: ", padded_data.shape) # 64 x 2013 - - # transform to tensor - model_input = torch.tensor(padded_data.values, dtype=torch.float32) - print("model input: ", model_input.shape) - - # impute to model - imputed_data, _ = model(model_input) - - # retrieve only original proteins - imputed_data = pd.DataFrame(imputed_data, index=incomplete_data.index, columns=model.protein_names) - imputed_data = imputed_data.loc[:, list(common_proteins)] - print("imputed data: ", imputed_data.shape) # 64 x 1568 - - # comparar imputation com o dataset without induced missingness - ground_truth = torch.tensor(data.dataset_normalized.values, dtype=torch.float32) - mask = (~torch.isnan(ground_truth)).float() - ground_truth[torch.isnan(ground_truth)] = 0 - imputed_data_tensor = torch.tensor(imputed_data.values, dtype=torch.float32) - squared_error = (ground_truth - imputed_data_tensor) ** 2 - rmse = torch.sqrt((squared_error * mask).sum() / mask.sum()) # RMSE error - print(f"rmse: {rmse}") - - # scale back to real space - imputed_data_real_values = data.scaler.inverse_transform(imputed_data.values) # in real space - imputed_data_real = pd.DataFrame(imputed_data_real_values, index=imputed_data.index, columns=imputed_data.columns) - - print("imputed data real df: ", imputed_data_real.shape) # 64 x 1568 - print(imputed_data_real) \ No newline at end of file diff --git a/GenerativeProteomics/gainpro.py b/GenerativeProteomics/gainpro.py new file mode 100644 index 0000000..55ce342 --- /dev/null +++ b/GenerativeProteomics/gainpro.py @@ -0,0 +1,796 @@ +""" +GainPro - Unified command-line interface for GAIN-based imputation methods. + +This module provides a consolidated CLI for: +- Basic GAIN imputation (simple Generator + Discriminator) +- Training GAIN-DANN models (with domain adaptation) +- Imputing with trained models +- Downloading and using pre-trained HuggingFace models +- Using simple imputation methods (median, etc.) +""" + +import json +import torch +import torch.nn as nn +import pandas as pd +import numpy as np +from datetime import datetime +from pathlib import Path +import time +import cProfile +import pstats + +import seaborn as sns +import matplotlib.pyplot as plt +import umap.umap_ as umap + +# Model imports +from GenerativeProteomics.gain_dann_model import GainDann +from GenerativeProteomics.model import Network +from GenerativeProteomics.hypers import Params +from GenerativeProteomics.output import Metrics +from GenerativeProteomics.params_gain_dann import ParamsGainDann +from GenerativeProteomics.data_utils import Data as DataDANN +from GenerativeProteomics.dataset import Data +from GenerativeProteomics.train import GainDannTrain +from GenerativeProteomics import utils +from GenerativeProteomics.imputation_management import ImputationManagement +from huggingface_hub import hf_hub_download +from sklearn.preprocessing import LabelEncoder +import sys + +import logging +import click +import os + +try: + import inquirer + INQUIRER_AVAILABLE = True +except ImportError: + INQUIRER_AVAILABLE = False + +logging.basicConfig(level=logging.INFO) +logger = logging.getLogger(__name__) + + +def setup_logging(debug: bool): + """Configure logging level.""" + logger.setLevel(logging.DEBUG if debug else logging.INFO) + + +def load_model_metadata(checkpoint_dir: str): + """Load model metadata from checkpoint directory.""" + json_path = os.path.join(checkpoint_dir, "metadata.json") + if not os.path.exists(json_path): + raise click.ClickException(f"Metadata file not found: {json_path}") + + try: + with open(json_path, "r") as f: + return json.load(f) + except json.JSONDecodeError as e: + raise click.ClickException(f"Error decoding JSON: {e}") + + +def load_trained_model(checkpoint_dir: str, metadata: dict): + """Load a trained GAIN-DANN model from checkpoint.""" + gain_params = Params() + gain_metrics = Metrics(gain_params) + + dann_params = { + "hidden_dim": metadata["params"]["hidden_dim"], + "dropout_rate": metadata["params"]["dropout_rate"] + } + + model = GainDann( + metadata["protein_names"], + metadata["input_dim"], + latent_dim=metadata["latent_dim"], + n_class=metadata["n_class"], + num_hidden_layers=metadata["params"]["num_hidden_layers"], + dann_params=dann_params, + gain_params=gain_params, + gain_metrics=gain_metrics + ) + + model_path = os.path.join(checkpoint_dir, "model.pt") + if not os.path.isfile(model_path): + raise click.ClickException(f"Model file not found: {model_path}") + + model.load_state_dict(torch.load(model_path, map_location=torch.device('cpu'))) + return model + + +# Click group for main command +@click.group(context_settings={"help_option_names": ["-h", "--help"]}) +@click.option( + "--debug", + is_flag=True, + help="Enable debug logging", +) +@click.pass_context +def cli(ctx, debug): + """ + GainPro - Unified GAIN-based imputation tools for proteomics data. + + This tool provides various imputation methods: + - Basic GAIN (Generator + Discriminator) + - GAIN-DANN (Domain-adaptive with Encoder/Decoder) + - Pre-trained HuggingFace models + - Simple statistical methods (median) + """ + ctx.ensure_object(dict) + ctx.obj['debug'] = debug + setup_logging(debug) + + +@cli.command() +@click.option( + "--config", + "config_file", + type=click.Path(exists=True), + default="configs/params_gain_dann.json", + help="Path to GAIN-DANN configuration file", + show_default=True, +) +@click.option( + "--save/--no-save", + default=False, + help="Save trained model checkpoint", +) +def train(config_file, save): + """ + Train a GAIN-DANN model on your dataset. + + Example: + + gainpro train --config configs/params_gain_dann.json --save + """ + logger.info("Starting GAIN-DANN training...") + + params_gain_dann = ParamsGainDann.read_hyperparameters(config_file) + params = params_gain_dann.to_dict() + + # Read dataset + if params_gain_dann.path_dataset_missing: + logger.info(f"Loading dataset with missing values: {params_gain_dann.path_dataset_missing}") + dataset_missing = pd.read_csv(params_gain_dann.path_dataset_missing, index_col=0) + dataset_missing = dataset_missing.iloc[:, 8500:] # TODO: Remove start_col hardcoding + data = Data( + dataset_path=params_gain_dann.path_dataset, + dataset_missing=dataset_missing, + start_col=8500 + ) + else: + data = Data( + dataset_path=params_gain_dann.path_dataset, + miss_rate=params["miss_rate"], + start_col=8500 + ) + + logger.info(f"Early stop patience: {params_gain_dann['early_stop_patience']}") + train_obj = GainDannTrain( + data, + params, + early_stop_patience=params_gain_dann["early_stop_patience"], + save_model=save + ) + train_obj.train() + + click.echo("Training completed successfully!") + + +@cli.command() +@click.option( + "--checkpoint", + "checkpoint_dir", + type=click.Path(exists=True, file_okay=False, dir_okay=True), + required=True, + help="Path to model checkpoint directory", +) +@click.option( + "--input", + "input_file", + type=click.Path(exists=True), + required=True, + help="Path to input CSV file with missing values", +) +@click.option( + "--output", + "output_file", + type=click.Path(), + default="imputed.csv", + help="Path to output CSV file", + show_default=True, +) +@click.option( + "--miss-rate", + type=float, + default=0.1, + help="Missing rate for evaluation (only used if no missing values in input)", + show_default=True, +) +def impute(checkpoint_dir, input_file, output_file, miss_rate): + """ + Impute missing values using a trained GAIN-DANN model. + + Example: + + gainpro impute --checkpoint checkpoints/2024-01-01_12:00 --input data.csv --output imputed.csv + """ + logger.info("Loading trained model...") + + metadata = load_model_metadata(checkpoint_dir) + model = load_trained_model(checkpoint_dir, metadata) + model.eval() + + # Read dataset + df = pd.read_csv(input_file, index_col=0) + + # Reduce to common proteins + common_proteins = set(model.protein_names) & set(df.columns) + df = df.loc[:, list(common_proteins)] + logger.info(f"Using {len(common_proteins)} common proteins") + + # Create data object + data = Data(df, miss_rate=miss_rate, start_col=0) + incomplete_data = data.dataset_missing + + # Pad with NaNs for model compatibility + padded_data = incomplete_data.reindex(columns=model.protein_names) + + # Transform to tensor + model_input = torch.tensor(padded_data.values, dtype=torch.float32) + + # Impute + logger.info("Running imputation...") + with torch.no_grad(): + imputed_data, _ = model(model_input) + + # Retrieve only original proteins + imputed_data = pd.DataFrame(imputed_data.numpy(), index=incomplete_data.index, columns=model.protein_names) + imputed_data = imputed_data.loc[:, list(common_proteins)] + + # Scale back to real space + imputed_data_real_values = data.scaler.inverse_transform(imputed_data.values) + imputed_data_real = pd.DataFrame( + imputed_data_real_values, + index=imputed_data.index, + columns=imputed_data.columns + ) + + # Save output + imputed_data_real.to_csv(output_file) + click.echo(f"Imputation completed! Results saved to {output_file}") + + +@cli.command() +@click.option( + "--input", + "input_file", + type=click.Path(exists=True), + required=True, + help="Path to input CSV file with missing values", +) +@click.option( + "--output", + "output_file", + type=click.Path(), + default="imputed.csv", + help="Path to output CSV file", + show_default=True, +) +@click.option( + "--model-id", + default="QuantitativeBiology/GAIN_DANN_model", + help="HuggingFace model repository ID", + show_default=True, +) +def download(input_file, output_file, model_id): + """ + Download a pre-trained model from HuggingFace and perform imputation. + + Example: + + gainpro download --input data.csv --output imputed.csv + """ + logger.info(f"Downloading model from HuggingFace: {model_id}") + + save_dir = "./GAIN_DANN_model" + os.makedirs(save_dir, exist_ok=True) + + # Download files from HuggingFace + logger.info("Downloading model files...") + config_path = hf_hub_download( + repo_id=model_id, + filename="config.json", + cache_dir=save_dir + ) + weights_path = hf_hub_download( + repo_id=model_id, + filename="pytorch_model.bin", + cache_dir=save_dir + ) + model_path = hf_hub_download( + repo_id=model_id, + filename="modeling_gain_dann.py", + cache_dir=save_dir + ) + + # Add directory to Python path to import the model + directory = os.path.dirname(model_path) + if directory not in sys.path: + sys.path.append(directory) + + # Import model classes + from modeling_gain_dann import GainDANNConfig, GainDANN + + logger.info("Loading model configuration...") + + # Load config + with open(config_path) as f: + cfg = json.load(f) + + # Read input data + df = pd.read_csv(input_file) + + # Extract data (assuming first column might be index/ID, skip it) + if df.shape[1] > 1: + data_df = df.iloc[:, 1:] if 'Project' in df.columns else df + else: + data_df = df + + input_dim = data_df.shape[1] + logger.info(f"Input dimension: {input_dim}") + + cfg['input_dim'] = input_dim + config = GainDANNConfig(**cfg) + model = GainDANN(config) + + # Load model weights + logger.info("Loading model weights...") + state_dict = torch.load(weights_path, map_location="cpu") + + # Add "model." prefix to keys for HuggingFace compatibility + renamed_state_dict = {f"model.{k}": v for k, v in state_dict.items()} + model.load_state_dict(renamed_state_dict) + model.eval() + + # Prepare data + if 'Project' in data_df.columns: + label_encoder = LabelEncoder() + data_df['Project'] = label_encoder.fit_transform(data_df['Project']) + + x = torch.tensor(data_df.values, dtype=torch.float32) + + # Perform imputation + logger.info("Running imputation...") + with torch.no_grad(): + x_reconstructed, x_domain = model(x) + + # Convert to DataFrame and save + result_df = pd.DataFrame(x_reconstructed.numpy(), columns=data_df.columns if hasattr(data_df, 'columns') else None) + + # If original DataFrame had index, preserve it + if df.index.name is not None or len(df.index) != len(result_df): + result_df.index = df.index + + result_df.to_csv(output_file, index=True) + + # Optionally save domain predictions + domain_file = output_file.replace(".csv", "_domain.csv") + pd.DataFrame(x_domain.numpy()).to_csv(domain_file, index=False) + + click.echo(f"Imputation completed! Results saved to {output_file}") + click.echo(f"Domain predictions saved to {domain_file}") + + +@cli.command() +@click.option( + "--input", + "input_file", + type=click.Path(exists=True), + required=True, + help="Path to input CSV file with missing values", +) +@click.option( + "--output", + "output_file", + type=click.Path(), + default="imputed.csv", + help="Path to output CSV file", + show_default=True, +) +def median(input_file, output_file): + """ + Perform median imputation on the dataset. + + Replaces missing values with the median of each column. + + Example: + + gainpro median --input data.csv --output imputed.csv + """ + logger.info("Performing median imputation...") + + try: + df = pd.read_csv(input_file) + df_imputed = df.copy() + + # Select numeric columns only + num_cols = df_imputed.select_dtypes(include=[np.number]).columns + + # Replace 0 with NaN (common representation of missing values) + df_imputed[num_cols] = df_imputed[num_cols].astype(float).replace(0, np.nan) + + # Calculate column medians + col_medians = df_imputed[num_cols].median().fillna(0.0) + + # Fill missing values with medians + df_imputed[num_cols] = df_imputed[num_cols].fillna(col_medians) + + # Save output + df_imputed.to_csv(output_file, index=False) + click.echo(f"Median imputation completed! Results saved to {output_file}") + except Exception as e: + logger.error(f"Error during median imputation: {e}") + raise click.ClickException(f"Imputation failed: {e}") + + +@cli.command() +@click.option( + "-i", + "--input", + "missing_file", + type=click.Path(exists=True), + required=True, + help="Path to missing data file", +) +@click.option( + "-o", + "--output", + "output_file", + default="imputed", + help="Name of output file", + show_default=True, +) +@click.option( + "--ref", + "ref_file", + type=click.Path(exists=True), + help="Path to a reference (complete) dataset", +) +@click.option( + "--ofolder", + "output_folder", + default=lambda: os.path.join(os.getcwd(), "results"), + help="Path to output folder", + show_default=True, +) +@click.option( + "--it", + "num_iterations", + type=int, + default=2001, + help="Number of iterations", + show_default=True, +) +@click.option( + "--batchsize", + "batch_size", + type=int, + default=128, + help="Batch size", + show_default=True, +) +@click.option( + "--alpha", + type=float, + default=10.0, + help="Alpha parameter", + show_default=True, +) +@click.option( + "--miss", + "miss_rate", + type=float, + default=0.1, + help="Missing rate", + show_default=True, +) +@click.option( + "--hint", + "hint_rate", + type=float, + default=0.9, + help="Hint rate", + show_default=True, +) +@click.option( + "--lrd", + "lr_D", + type=float, + default=0.001, + help="Learning rate for the discriminator", + show_default=True, +) +@click.option( + "--lrg", + "lr_G", + type=float, + default=0.001, + help="Learning rate for the generator", + show_default=True, +) +@click.option( + "--parameters", + "parameters_file", + type=click.Path(exists=True), + help="Load a parameters.json file", +) +@click.option( + "--override", + type=int, + default=0, + help="Override previous files (1 to override, 0 otherwise)", + show_default=True, +) +@click.option( + "--outall", + "output_all", + type=int, + default=0, + help="Output all files (1 to output all, 0 otherwise)", + show_default=True, +) +@click.option( + "--model", + type=str, + help="Custom imputation model name (must be registered via ImputationManagement)", +) +def gain( + missing_file, + output_file, + ref_file, + output_folder, + num_iterations, + batch_size, + alpha, + miss_rate, + hint_rate, + lr_D, + lr_G, + parameters_file, + override, + output_all, + model, +): + """ + Perform basic GAIN (Generative Adversarial Imputation Network) imputation. + + This command uses a simple Generator + Discriminator architecture for + general-purpose missing value imputation. For domain-adaptive imputation, + use 'gainpro train' and 'gainpro impute' commands. + + Examples: + + gainpro gain -i data.csv + gainpro gain -i data.csv --ref reference.csv --it 3000 + gainpro gain --parameters configs/params_gain.json + """ + start_time = time.time() + + with cProfile.Profile() as profile: + # Load parameters from file if provided + if parameters_file is not None: + params = Params.read_hyperparameters(parameters_file) + missing_file = params.input + output_file = params.output + ref_file = params.ref + output_folder = params.output_folder + num_iterations = params.num_iterations + batch_size = params.batch_size + alpha = params.alpha + miss_rate = params.miss_rate + hint_rate = params.hint_rate + lr_D = params.lr_D + lr_G = params.lr_G + override = params.override + output_all = params.output_all + else: + params = Params( + missing_file, + output_file, + ref_file, + output_folder, + None, + num_iterations, + batch_size, + alpha, + miss_rate, + hint_rate, + lr_D, + lr_G, + override, + output_all, + ) + + # Create output folder + if not os.path.exists(output_folder): + os.makedirs(output_folder) + + # Handle custom model via ImputationManagement + if model is not None: + df_missing = pd.read_csv(missing_file) + imputation_management = ImputationManagement(model, df_missing, missing_file) + imputation_management.run_model(model) + click.echo("Imputation completed using custom model.") + return + + # Load and process input data + if missing_file.endswith(".csv"): + df_missing = pd.read_csv(missing_file) + missing = df_missing.values + missing_header = df_missing.columns.tolist() + params.update_hypers(header=missing_header) + elif missing_file.endswith(".tsv"): + df_missing = utils.build_protein_matrix(missing_file) + missing = df_missing.values + missing_header = df_missing.columns.tolist() + params.update_hypers(header=missing_header) + elif missing_file.endswith(".parquet"): + df_missing = utils.handle_parquet(missing_file) + missing = df_missing.to_numpy() + missing_header = df_missing.columns + params.update_hypers(header=missing_header) + else: + raise click.ClickException("Unsupported file format. Supported: .csv, .tsv, .parquet") + + # Build model architecture + dim = missing.shape[1] + train_size = missing.shape[0] + h_dim1 = dim + h_dim2 = dim + + net_G = nn.Sequential( + nn.Linear(dim * 2, h_dim1), + nn.ReLU(), + nn.Linear(h_dim1, h_dim2), + nn.ReLU(), + nn.Linear(h_dim2, dim), + nn.Sigmoid(), + ) + + net_D = nn.Sequential( + nn.Linear(dim * 2, h_dim1), + nn.ReLU(), + nn.Linear(h_dim1, h_dim2), + nn.ReLU(), + nn.Linear(h_dim2, dim), + nn.Sigmoid(), + ) + + # Initialize network and metrics + metrics = Metrics(params) + network = Network(hypers=params, net_G=net_G, net_D=net_D, metrics=metrics) + + # Train with or without reference + if ref_file is not None: + logger.info("Training with reference dataset...") + df_ref = pd.read_csv(ref_file) + ref = df_ref.values + ref_header = df_ref.columns.tolist() + + if dim != ref.shape[1]: + raise click.ClickException( + f"Mismatch in number of features: input has {dim}, reference has {ref.shape[1]}" + ) + elif train_size != ref.shape[0]: + raise click.ClickException( + f"Mismatch in number of samples: input has {train_size}, reference has {ref.shape[0]}" + ) + + data = Data(missing, miss_rate, hint_rate, ref) + network.train_ref(data, missing_header) + else: + logger.info("Training without reference (evaluation + training mode)...") + data = Data(missing, miss_rate, hint_rate) + network.evaluate(data, missing_header) + network.train(data, missing_header) + + # Save execution time + run_time = time.time() - start_time + file_path = os.path.join(output_folder, "run_time.csv") + + if override == 1: + pd.DataFrame([run_time]).to_csv(file_path, index=False) + else: + if os.path.exists(file_path): + with open(file_path, "a") as f: + f.write(str(run_time) + "\n") + else: + pd.DataFrame([run_time]).to_csv(file_path, index=False) + + click.echo(f"\n--- Execution time: {run_time:.2f} seconds ---\n") + + # Save profiling results + results = pstats.Stats(profile) + results.sort_stats(pstats.SortKey.TIME) + results.dump_stats(os.path.join(output_folder, "results.prof")) + + +# Legacy function for backward compatibility +def list_checkpoints(): + """List available checkpoint directories.""" + checkpoint_root = "checkpoints" + if not os.path.exists(checkpoint_root): + return [] + return sorted([ + d for d in os.listdir(checkpoint_root) + if os.path.isdir(os.path.join(checkpoint_root, d)) + ]) + + +def select_checkpoint_interactively(): + """Interactively select a checkpoint.""" + checkpoints = list_checkpoints() + if not checkpoints: + raise FileNotFoundError("No checkpoints found.") + + if not INQUIRER_AVAILABLE: + click.echo("Available checkpoints:") + for i, cp in enumerate(checkpoints, 1): + click.echo(f" {i}. {cp}") + raise click.ClickException( + "Please specify checkpoint with --checkpoint flag. " + "Install 'inquirer' for interactive selection." + ) + + question = [ + inquirer.List("timestamp", message="Select a checkpoint to load", choices=checkpoints) + ] + answer = inquirer.prompt(question) + return answer["timestamp"] + + +# Main entry point +def main(): + """Main entry point for the gainpro CLI.""" + cli() + + +# Backward compatibility wrapper for 'gain' command +def gain_main(): + """ + Backward compatibility entry point for the deprecated 'gain' command. + + This wrapper invokes 'gainpro gain' subcommand to maintain backward compatibility. + """ + import sys + + # Show deprecation warning + click.echo( + "⚠️ WARNING: The 'gain' command is deprecated. " + "Please use 'gainpro gain' instead.\n", + err=True + ) + + # Modify sys.argv to route to the 'gain' subcommand + # When called as 'gain', sys.argv[0] is the entry point script + # We need to insert 'gain' as the subcommand argument + original_argv = sys.argv[:] + # Insert 'gain' as the first argument (subcommand) if not already present + if len(sys.argv) > 1 and sys.argv[1] != 'gain': + sys.argv = [sys.argv[0], 'gain'] + sys.argv[1:] + elif len(sys.argv) == 1: + # Just 'gain' was called, show help + sys.argv = [sys.argv[0], 'gain', '--help'] + # If sys.argv[1] is already 'gain', keep it as is + + try: + cli() + finally: + sys.argv = original_argv + + +if __name__ == "__main__": + main() diff --git a/GenerativeProteomics/generativeproteomics.py b/GenerativeProteomics/generativeproteomics.py deleted file mode 100644 index 4aa06e3..0000000 --- a/GenerativeProteomics/generativeproteomics.py +++ /dev/null @@ -1,233 +0,0 @@ -""" -GenerativeProteomics - Main entry point for GAIN-based imputation. - -This module provides the command-line interface for running the -Generative Adversarial Imputation Network on proteomics datasets. -""" - -from GenerativeProteomics.hypers import Params -from GenerativeProteomics.model import Network -from GenerativeProteomics.dataset import Data -from GenerativeProteomics.output import Metrics -from GenerativeProteomics.imputation_management import ImputationManagement -from GenerativeProteomics import utils - -import torch -from torch import nn -import numpy as np -from tqdm import tqdm -import pandas as pd -from sklearn.preprocessing import MinMaxScaler - -import optuna - -import time -import cProfile -import pstats -import argparse -import os -import psutil - - -def init_arg(): - """Parse command-line arguments for the imputation pipeline.""" - parser = argparse.ArgumentParser( - description="GenerativeProteomics (GainPro) - GAIN-based missing value imputation", - formatter_class=argparse.ArgumentDefaultsHelpFormatter, - ) - parser.add_argument("-i", "--input", dest="i", help="path to missing data file") - parser.add_argument("-o", "--output", dest="o", default="imputed", help="name of output file") - parser.add_argument("--ref", help="path to a reference (complete) dataset") - parser.add_argument( - "--ofolder", default=os.getcwd() + "/results/", help="path to output folder" - ) - parser.add_argument("--it", type=int, default=2001, help="number of iterations") - parser.add_argument("--batchsize", type=int, default=128, help="batch size") - parser.add_argument("--alpha", type=float, default=10, help="alpha") - parser.add_argument("--miss", type=float, default=0.1, help="missing rate") - parser.add_argument("--hint", type=float, default=0.9, help="hint rate") - parser.add_argument( - "--lrd", type=float, default=0.001, help="learning rate for the discriminator" - ) - parser.add_argument( - "--lrg", type=float, default=0.001, help="learning rate for the generator" - ) - parser.add_argument("--parameters", help="load a parameters.json file") - parser.add_argument( - "--override", type=int, default=0, help="override previous files" - ) - parser.add_argument("--outall", type=int, default=0, help="output all files") - parser.add_argument( - "--model", type=str, help="indicates which model from HuggingFace to use" - ) - return parser.parse_args() - - -def main(): - """Main entry point for the GenerativeProteomics CLI.""" - start_time = time.time() - with cProfile.Profile() as profile: - - folder = os.getcwd() - - args = init_arg() - - missing_file = args.i - output_file = args.o - ref_file = args.ref - output_folder = args.ofolder - num_iterations = args.it - batch_size = args.batchsize - alpha = args.alpha - miss_rate = args.miss - hint_rate = args.hint - lr_D = args.lrd - lr_G = args.lrg - parameters_file = args.parameters - override = args.override - output_all = args.outall - model = args.model - - if parameters_file is not None: - params = Params.read_hyperparameters(parameters_file) - missing_file = params.input - output_file = params.output - ref_file = params.ref - output_folder = params.output_folder - num_iterations = params.num_iterations - batch_size = params.batch_size - alpha = params.alpha - miss_rate = params.miss_rate - hint_rate = params.hint_rate - lr_D = params.lr_D - lr_G = params.lr_G - override = params.override - output_all = params.output_all - - else: - params = Params( - missing_file, - output_file, - ref_file, - output_folder, - None, - num_iterations, - batch_size, - alpha, - miss_rate, - hint_rate, - lr_D, - lr_G, - override, - output_all, - ) - - if not os.path.exists(output_folder): - os.makedirs(output_folder) - - if missing_file is None: - print("Input file not provided") - exit(1) - if missing_file.endswith(".csv"): - df_missing = pd.read_csv(missing_file) - missing = df_missing.values - missing_header = df_missing.columns.tolist() - params.update_hypers(header=missing_header) - elif missing_file.endswith(".tsv"): - df_missing = utils.build_protein_matrix(missing_file) - missing = df_missing.values - missing_header = df_missing.columns.tolist() - params.update_hypers(header=missing_header) - elif missing_file.endswith(".parquet"): - df_missing = utils.handle_parquet(missing_file) - missing = df_missing.to_numpy() - missing_header = df_missing.columns - params.update_hypers(header=missing_header) - else: - print("Invalid file format") - exit(2) - - if args.model is not None: - print(args.model) - imputation_management = ImputationManagement(args.model, df_missing, missing_file) - imputation_management.run_model(args.model) - exit(0) - - else: - dim = missing.shape[1] - train_size = missing.shape[0] - - h_dim1 = dim - h_dim2 = dim - - net_G = nn.Sequential( - nn.Linear(dim * 2, h_dim1), - nn.ReLU(), - nn.Linear(h_dim1, h_dim2), - nn.ReLU(), - nn.Linear(h_dim2, dim), - nn.Sigmoid(), - ) - - net_D = nn.Sequential( - nn.Linear(dim * 2, h_dim1), - nn.ReLU(), - nn.Linear(h_dim1, h_dim2), - nn.ReLU(), - nn.Linear(h_dim2, dim), - nn.Sigmoid(), - ) - - metrics = Metrics(params) - network = Network(hypers=params, net_G=net_G, net_D=net_D, metrics=metrics) - - if ref_file is not None: - df_ref = pd.read_csv(ref_file) - ref = df_ref.values - ref_header = df_ref.columns.tolist() - - if dim != ref.shape[1]: - print( - "\n\nThe reference and data files provided don't have the same number of features\n" - ) - exit(3.1) - elif train_size != ref.shape[0]: - print( - "\n\nThe reference and data files provided don't have the same number of samples\n" - ) - exit(3.2) - - data = Data(missing, miss_rate, hint_rate, ref) - network.train_ref(data, missing_header) - - else: - data = Data(missing, miss_rate, hint_rate) - network.evaluate(data, missing_header) - network.train(data, missing_header) - - run_time = [] - run_time.append(time.time() - start_time) - file_path = output_folder + "run_time.csv" - - if override == 1: - df_run_time = pd.DataFrame(run_time) - df_run_time.to_csv(file_path, index=False) - - else: - if os.path.exists(file_path): - with open(file_path, "a") as myfile: - myfile.write(str(run_time[0]) + "\n") - - else: - df_run_time = pd.DataFrame(run_time) - df_run_time.to_csv(file_path, index=False) - - print("\n--- %s seconds ---\n\n" % (run_time[0])) - results = pstats.Stats(profile) - results.sort_stats(pstats.SortKey.TIME) - # results.print_stats() - results.dump_stats("results.prof") - - -if __name__ == "__main__": - main() diff --git a/GenerativeProteomics/imputation_management.py b/GenerativeProteomics/imputation_management.py index 64ea665..1078891 100644 --- a/GenerativeProteomics/imputation_management.py +++ b/GenerativeProteomics/imputation_management.py @@ -1,13 +1,17 @@ -from GenerativeProteomics.models.gain_dann import GainDannImputationModel -from GenerativeProteomics.models.medium import MediumImputationModel - - class ImputationManagement: + """ + Factory class for managing custom imputation methods. + + This class allows users to register and use custom imputation functions. + For built-in methods, use the 'gainpro' command-line tool instead: + - gainpro median: for median imputation + - gainpro download: for HuggingFace models + """ def __init__ (self, model, df_missing, missing_file_path): self.model = model self.df = df_missing self.missing = missing_file_path - self.dict_imputation_methods = {"GAIN_DANN_model" : GainDannImputationModel(), "medium_imputation" : MediumImputationModel()} + self.dict_imputation_methods = {} def add_method(self, model, fn): @@ -21,7 +25,16 @@ def run_model(self, model): if model not in self.dict_imputation_methods: raise SystemExit (f"Unknown model called {model}, Models available are: {','.join(self.dict_imputation_methods)}") else: - return self.dict_imputation_methods[model].run(self.df) + method = self.dict_imputation_methods[model] + # Handle both callable functions and objects with .run() method + if callable(method) and not hasattr(method, 'run'): + # It's a plain function, call it directly + return method(self.df) + elif hasattr(method, 'run'): + # It's an object with a .run() method + return method.run(self.df) + else: + raise SystemExit(f"Invalid imputation method: {model} must be callable or have a .run() method") diff --git a/GenerativeProteomics/models/__init__.py b/GenerativeProteomics/models/__init__.py deleted file mode 100644 index 1e55c4c..0000000 --- a/GenerativeProteomics/models/__init__.py +++ /dev/null @@ -1,17 +0,0 @@ -""" -Imputation model implementations. - -This module contains different imputation strategies: -- GainDannImputationModel: GAIN-DANN based imputation using HuggingFace models -- MediumImputationModel: Simple median-based imputation -""" - -from GenerativeProteomics.models.base_abstract import ImputationModel -from GenerativeProteomics.models.gain_dann import GainDannImputationModel -from GenerativeProteomics.models.medium import MediumImputationModel - -__all__ = [ - "ImputationModel", - "GainDannImputationModel", - "MediumImputationModel", -] diff --git a/GenerativeProteomics/models/base_abstract.py b/GenerativeProteomics/models/base_abstract.py deleted file mode 100644 index 5cc6b94..0000000 --- a/GenerativeProteomics/models/base_abstract.py +++ /dev/null @@ -1,10 +0,0 @@ -from abc import ABC, abstractmethod - -class ImputationModel(ABC): - '''Abstract base class for imputation models.''' - - @abstractmethod - def run(self, df): - '''Run the imputation model on the provided DataFrame.''' - pass - diff --git a/GenerativeProteomics/models/gain_dann.py b/GenerativeProteomics/models/gain_dann.py deleted file mode 100644 index 640fc8a..0000000 --- a/GenerativeProteomics/models/gain_dann.py +++ /dev/null @@ -1,72 +0,0 @@ -from .base_abstract import ImputationModel -from sklearn.preprocessing import LabelEncoder -from huggingface_hub import hf_hub_download -import torch -import os -import json -import pandas as pd -import argparse -import numpy as np - -class GainDannImputationModel(ImputationModel): - '''Imputation model using GAIN_DANN from Hugging Face.''' - - def run(self, df): - """ Function to import and use the GAIN_DANN model from Hugging Face. """ - - save_dir = "./GAIN_DANN_model" - os.makedirs(save_dir, exist_ok=True) - - # Download files manually - config_path = hf_hub_download(repo_id = "QuantitativeBiology/GAIN_DANN_model", filename="config.json", cache_dir = save_dir) - weights_path = hf_hub_download(repo_id =f"QuantitativeBiology/GAIN_DANN_model", filename="pytorch_model.bin", cache_dir = save_dir) - model_path = hf_hub_download(repo_id = f"QuantitativeBiology/GAIN_DANN_model", filename="modeling_gain_dann.py", cache_dir = save_dir) - - directory = os.path.dirname(model_path) - - # Add the directory containing 'modeling_gain_dann.py' to the Python path - import sys - sys.path.append(directory) - - # Import the functions or classes inside the file - from modeling_gain_dann import GainDANNConfig, GainDANN - - print("import successfully done") - - # Load config - with open(config_path) as f: - cfg = json.load(f) - - hela = df.iloc[:, 1:] - input_dim = hela.shape[1] - - print(input_dim) - cfg['input_dim'] = input_dim - - config = GainDANNConfig(**cfg) - model = GainDANN(config) - - # Load raw state_dict - state_dict = torch.load(weights_path, map_location="cpu") - - # Add "model." prefix to every key(because state_dict has the weights of GAIN_DANN but I added the Gain_DANN for the huggingFace accordance) - renamed_state_dict = {f"model.{k}": v for k, v in state_dict.items()} - - # Load with corrected keys - model.load_state_dict(renamed_state_dict) - - model.eval() - - label_encoder = LabelEncoder() - hela['Project'] = label_encoder.fit_transform(hela['Project']) - - x = torch.tensor(hela.values, dtype=torch.float32) - - with torch.no_grad(): - x_reconstructed, x_domain = model(x) - - print("x_reconstructed:", x_reconstructed) - print("x_domain:", x_domain) - - pd.DataFrame(x_reconstructed.numpy()).to_csv("x_reconstructed.csv", index=False) - pd.DataFrame(x_domain.numpy()).to_csv("x_domain.csv", index=False) \ No newline at end of file diff --git a/GenerativeProteomics/models/medium.py b/GenerativeProteomics/models/medium.py deleted file mode 100644 index 051b6df..0000000 --- a/GenerativeProteomics/models/medium.py +++ /dev/null @@ -1,19 +0,0 @@ -from .base_abstract import ImputationModel -import numpy as np - -class MediumImputationModel(ImputationModel): - '''Imputation model using medium value for imputation.''' - - def run(self, df): - '''Function that calculates the medium value of each column and imputes missing values with - that value ''' - df_2 = df.copy() - num_cols = df_2.select_dtypes(include=[np.number]).columns - - df_2[num_cols] = df_2[num_cols].astype(float).replace(0, np.nan) - - col_means = df_2[num_cols].mean().fillna(0.0) - - df_2[num_cols] = df_2[num_cols].fillna(col_means) - print(df_2) - return df_2 \ No newline at end of file diff --git a/README.md b/README.md index 16abf74..a8b4879 100644 --- a/README.md +++ b/README.md @@ -1,54 +1,177 @@ -# Generative Proteomics +# GainPro [![PyPi Version](https://img.shields.io/pypi/v/GenerativeProteomics?label=PyPi&color=blue&style=flat&logo=pypi)](https://pypi.org/project/GenerativeProteomics/) [![Colab](https://img.shields.io/badge/Google_Colab-0061F2?style=flat&logo=googlecolab&color=blue&label=Colab&colorB=grey)](https://colab.research.google.com/drive/1ihtmsv_UvEz74YrLHZvATu1y2qH4X9-r?usp=sharing) [![Documentation](https://img.shields.io/badge/docs-read%20the%20docs-blue)](https://generativeproteomics.readthedocs.io/en/latest/) [![HuggingFace](https://img.shields.io/badge/Hugging_Face-grey?style=flat&logo=huggingface&color=grey)](https://huggingface.co/QuantitativeBiology) -In this repository you may find a PyTorch implementation of Generative Adversarial Imputation Networks (GAIN) [[1]](#1) for imputing missing iBAQ values in proteomics datasets. +**GainPro** is a PyTorch implementation of Generative Adversarial Imputation Networks (GAIN) [[1]](#1) for imputing missing iBAQ values in proteomics datasets. The package provides a unified command-line interface with multiple imputation methods including basic GAIN, GAIN-DANN (domain-adaptive), and pre-trained HuggingFace models. ## Table of Contents -- [Repository Structure](#repository-structure) +- [Features](#features) - [Installation](#installation) -- [Basic Usage](#basic-usage) -- [GitHub](#github) -- [Demo](#demo) +- [Quick Start](#quick-start) +- [Command-Line Usage](#command-line-usage) +- [Python API](#python-api) +- [Repository Structure](#repository-structure) - [DANN & GAIN Hybrid](#dann--gain-hybrid) - [References](#references) -## Repository Structure +## Features -Here are the main components you'll find in this repository: - -1. .github/workflows - - contains the code for the automatization of the tests in the repository -2. datasets - - directory with datasets with missing values from PRIDE that can be used for testing -3. GenerativeProteomics: - - Contains the core package source code -4. docs/source - - contains the information used for the documentation of our work (ReadtheDocs) -5. tests: - - batery of unittests to assess the model's functionality -6. use-case - - set of clear examples on how to use our model's functionalities - - includes examples on how to install the package and use it, how to run the tests, and how to download and use a pre-trained model from HuggingFace +- **Basic GAIN**: Simple Generator + Discriminator architecture for general-purpose imputation +- **GAIN-DANN**: Domain-adaptive imputation with Encoder/Decoder architecture +- **Pre-trained Models**: Easy access to HuggingFace pre-trained models +- **Median Imputation**: Simple baseline method +- **Flexible CLI**: Unified `gainpro` command with intuitive subcommands +- **Python API**: Full programmatic access to all functionality ## Installation -### Pip install +### From PyPI (Recommended) -We have submitted a package to the Python Package Index (PyPI) for easy installation. You can install the package using the following command: +The package is available on PyPI. Install it using: ```bash pip install GenerativeProteomics ``` -This way, you can install the package and its dependencies in one go. +### From Source + +1. Clone the repository: + ```bash + git clone https://github.com/QuantitativeBiology/GainPro.git + cd GainPro + ``` + +2. Create a Python environment (recommended): + ```bash + conda create -n gainpro python=3.10 + conda activate gainpro + ``` + +3. Install dependencies: + ```bash + pip install -r requirements.txt + ``` + +4. Install the package in development mode: + ```bash + pip install -e . + ``` + +## Quick Start + +After installation, you can use the `gainpro` command-line interface: + +```bash +# Basic GAIN imputation +gainpro gain -i data.csv + +# With reference dataset for evaluation +gainpro gain -i data.csv --ref reference.csv + +# Using a configuration file +gainpro gain --parameters configs/params_gain.json +``` + +## Command-Line Usage + +GainPro provides a unified CLI with the following subcommands: + + +### `gainpro gain` - Basic GAIN Imputation + +The basic GAIN command performs imputation using a Generator + Discriminator architecture. + +**Basic usage:** +```bash +gainpro gain -i data.csv +``` + +**With options:** +```bash +gainpro gain -i data.csv -o imputed.csv --ofolder ./results/ --it 3000 +``` + +**Using a configuration file:** +```bash +gainpro gain --parameters configs/params_gain.json +``` + +**With reference dataset for evaluation:** +```bash +gainpro gain -i data.csv --ref reference.csv +``` + +**Note:** When run without a reference, the command performs two phases: +1. **Evaluation run**: Conceals a percentage of values (10% by default) during training, calculates RMSE, and creates `test_imputed.csv` for accuracy estimation +2. **Imputation run**: Trains on the entire dataset and creates `imputed.csv` + +**Common options:** +- `-i, --input`: Path to input file (CSV, TSV, or Parquet) +- `-o, --output`: Name of output file (default: `imputed`) +- `--ref`: Path to reference (complete) dataset for evaluation +- `--ofolder`: Output folder path (default: `./results`) +- `--it`: Number of training iterations (default: 2001) +- `--batchsize`: Batch size (default: 128) +- `--miss`: Missing rate for evaluation (0-1, default: 0.1) +- `--hint`: Hint rate (0-1, default: 0.9) +- `--lrd`: Learning rate for discriminator (default: 0.001) +- `--lrg`: Learning rate for generator (default: 0.001) +- `--parameters`: Path to JSON configuration file +- `--override`: Override previous output files (1) or append (0, default) +- `--outall`: Output all metrics (1) or minimal output (0, default) + +### `gainpro train` - Train GAIN-DANN Model + +Train a domain-adaptive GAIN-DANN model: + +```bash +gainpro train --config configs/params_gain_dann.json --save +``` + +### `gainpro impute` - Impute with Trained Model + +Use a trained GAIN-DANN checkpoint for imputation: -#### Basic Usage +```bash +gainpro impute --checkpoint checkpoints/your_model --input data.csv --output imputed.csv +``` + +### `gainpro download` - HuggingFace Pre-trained Models + +Download and use pre-trained models from HuggingFace: + +```bash +gainpro download --input data.csv --output imputed.csv +``` + +### `gainpro median` - Median Imputation + +Simple median imputation baseline: + +```bash +gainpro median --input data.csv --output imputed.csv +``` + +### Getting Help + +For detailed help on any command: +```bash +gainpro --help +gainpro gain --help +gainpro train --help +``` + +**Legacy command:** The `gain` command is still available but deprecated. Use `gainpro gain` instead. + + +## Python API + +GainPro can also be used programmatically through its Python API: ```python from GenerativeProteomics import utils, Network, Params, Metrics, Data @@ -57,8 +180,8 @@ import pandas as pd # Load your dataset dataset_path = "your_dataset.tsv" -dataset_df = utils.build_protein_matrix(dataset_path) # use this function if dataset is a tsv -#dataset_df = pd.read_csv(dataset_path) # if your dataset is a csv +dataset_df = utils.build_protein_matrix(dataset_path) # For TSV files +# dataset_df = pd.read_csv(dataset_path) # For CSV files dataset = dataset_df.values missing_header = dataset_df.columns.tolist() @@ -84,10 +207,18 @@ input_dim = dataset.shape[1] h_dim = input_dim net_G = torch.nn.Sequential( torch.nn.Linear(input_dim * 2, h_dim), + torch.nn.ReLU(), + torch.nn.Linear(h_dim, h_dim), + torch.nn.ReLU(), + torch.nn.Linear(h_dim, input_dim), torch.nn.Sigmoid() ) net_D = torch.nn.Sequential( torch.nn.Linear(input_dim * 2, h_dim), + torch.nn.ReLU(), + torch.nn.Linear(h_dim, h_dim), + torch.nn.ReLU(), + torch.nn.Linear(h_dim, input_dim), torch.nn.Sigmoid() ) @@ -99,77 +230,71 @@ data = Data(dataset=dataset, miss_rate=0.2, hint_rate=0.9, ref=None) # Run evaluation and training network.evaluate(data=data, missing_header=missing_header) network.train(data=data, missing_header=missing_header) -print("Final Matrix:\n", metrics.data_imputed) +print("Final Matrix:\n", metrics.data_imputed) ``` -For a more detailed explanation on how to use the model and all the functionalities we have to offer, you can open the `use-case` directory. - -### GitHub - -If you prefer to use the code of the GenerativeProteomics model directly, you can access it in our GitHub repository and follow the next sequence of commands. -1. Clone this repository: `git clone https://github.com/QuantitativeBiology/GenerativeProteomics/` -2. Create a Python environment: `conda create -n proto python=3.10` if you have conda installed -3. Activate the previously created environment: `conda activate proto` -4. Install the necessary packages: `pip install -r libraries.txt` +For more examples, see the `use-case` directory. +## Repository Structure -#### How to Use GenerativeProteomics - -If you just want to impute a general dataset, the most straightforward and simplest way to run GenerativeProteomics is to run: `python generativeproteomics.py -i /path/to/file_to_impute.csv` -Running in this manner will result in two separate training phases. - -1) Evaluation run: In this run a percentage of the values (10% by default) are concealed during the training phase and then the dataset is imputed. The RMSE is calculated with those hidden values as targets and at the end of the training phase a `test_imputed.csv` file will be created containing the original hidden values and the resulting imputation, this way you can have an estimation of the imputation accuracy. - -2) Imputation run: Then a proper training phase takes place using the entire dataset. An `imputed.csv` file will be created containing the imputed dataset. - -However, there are a few arguments which you may want to change. You can do this using a parameters.json file (you may find an example in `datasets/breast/parameters.json`) or you can choose them directly in the command line. - -Run with a parameters.json file: `python generativeproteomics.py --parameters /path/to/parameters.json`
-Run with command line arguments: `python generativeproteomics.py -i /path/to/file_to_impute.csv -o imputed_name --ofolder ./results/ --it 2001` - -#### How to import and use a pre-trained model - -Instead of running our trained model GenerativeProteomics, you can always use other inference forms. To do so, all you need to do is use the --model flag. - -Run the following command in order to use an alternative imputation form: `python generativeproteomics.py -i /path/to/file_to_impute.csv --model ` - -#### Arguments: - -`-i`: Path to file to impute
-`-o`: Name of imputed file
-`--ofolder`: Path to the output folder
-`--it`: Number of iterations to train the model
-`--miss`: The percentage of values to be concealed during the evaluation run (from `0` to `1`)
-`--outall`: Set this argument to `1` if you want to output every metric
-`--override`: Set this argument to `1` if you want to delete the previously created files when writing the new output
-`--model`: Contains the name of the imputation form to run. Default value is the GenerativeProteomics model. +Main components of the repository: +- **`.github/workflows`**: CI/CD workflows for automated testing +- **`datasets/`**: Sample datasets with missing values from PRIDE for testing +- **`GenerativeProteomics/`**: Core package source code + - `gainpro.py`: Main CLI interface (unified command with subcommands) + - `model.py`: Basic GAIN model implementation + - `gain_dann_model.py`: GAIN-DANN model implementation + - Other core modules (dataset, hypers, output, etc.) +- **`configs/`**: Configuration files for different models +- **`docs/source/`**: Documentation source files for ReadTheDocs +- **`tests/`**: Unit tests to assess model functionality +- **`use-case/`**: Examples demonstrating package usage + - Installation examples + - Test execution examples + - HuggingFace model usage examples -If you want to test the efficacy of the code you may give a reference file containing a complete version of the dataset (without missing values): `python generativeproteomics.py -i /path/to/file_to_impute.csv --ref /path/to/complete_dataset.csv` +## Demo -Running this way will calculate the RMSE of the imputation in relation to the complete dataset. +The repository includes a breast cancer diagnostic dataset [[2]](#2) in `datasets/breast/`: +- `breast.csv`: Complete dataset +- `breastMissing_20.csv`: Same dataset with 20% missing values +- `parameters.json`: Example configuration file -#### Demo +**Quick demo commands:** -In this repository you may find a folder named `breast`, inside it you have a breast cancer diagnostic dataset [[2]](#2) which you may use to try out the code. +```bash +# Simple imputation +gainpro gain -i ./datasets/breast/breastMissing_20.csv -`breast.csv`: complete dataset
-`breastMissing_20.csv`: the same dataset but with 20% of its values taken out +# With reference for evaluation +gainpro gain -i ./datasets/breast/breastMissing_20.csv --ref ./datasets/breast/breast.csv +# Using configuration file +gainpro gain --parameters ./datasets/breast/parameters.json +``` -To simply impute `breastMissing_20.csv` run: `python generativeproteomics.py -i ./datasets/breast/breastMissing_20.csv`
-If you want to compare the imputation with the original dataset run: `python generativeproteomics.py -i ./datasets/breast/breastMissing_20.csv --ref ./datasets/breast/breast.csv` or `python generativeproteomics.py --parameters ./datasets/breast/parameters.json` +For detailed metric analysis, either: +- Set `--outall 1` to output all metrics +- Use the Python API in an IPython console to access the `metrics` object (e.g., `metrics.loss_D`, `metrics.loss_G`, `metrics.rmse_train`) -If you want to go deep in the analysis of every metric you either set `--outall` to `1` or you run the code in an IPython console, this way you can access every variable you want in the `metrics` object, e.g. `metrics.loss_D`. +## DANN & GAIN Hybrid +The repository includes a hybrid model combining Domain Adversarial Neural Networks (DANN) with GAIN for domain-adaptive imputation. This is particularly useful when you have multiple datasets from different domains and want to learn domain-invariant representations. -## DANN & GAIN Hybrid +**Training a GAIN-DANN model:** +```bash +gainpro train --config configs/params_gain_dann.json --save +``` -The repository also includes a hybrid model combining Domain Adversarial Neural Networks (DANN) with GAIN for domain-adaptive imputation. +**Using a trained model:** +```bash +gainpro impute --checkpoint checkpoints/your_model --input data.csv --output imputed.csv +``` -To prepare the HeLa dataset for the **DANN & GAIN** hybrid model, run the `hela_dann.ipynb` notebook first and update the dataset path for the HeLa dataset in the third cell of the notebook. +For detailed information about the GAIN-DANN architecture and training procedure, see the documentation. ## References diff --git a/docs/source/Architecture.rst b/docs/source/Architecture.rst index 376b6c7..d8816b9 100644 --- a/docs/source/Architecture.rst +++ b/docs/source/Architecture.rst @@ -25,9 +25,7 @@ This diagram illustrates the overall architecture of GenerativeProteomics, showi - **Params**: Stores hyperparameters and passes them to the network. - **Metrics**: Computes key metrics such as loss values for both the Discriminator and Generator. - **Utils**: Provides auxiliary functions like indexing, output generation, and CSV creation. -- **ImputationManager**: Manages the selection and execution of different imputation methods. -- **ImputationModel**: Provides a common API to the difference pre-trained models that can be used, ensuring their consistency and compatibility with the rest of the codebase. -- **GainDannImputationModel**: Contains the logic of the GAIN-DANN imputation method. +- **ImputationManager**: Factory class for managing custom imputation methods (for extensibility). Execution Flow -------------- @@ -40,6 +38,7 @@ Execution Flow 6. The model outputs files such as `impute.csv`, `test_imputed.csv`, and performance metrics like `loss_G` and `loss_D`. 7. The `ImputationManager` class allows users to select and run different imputation methods. 8. The `ImputationModel` class serves as a base for various imputation models, ensuring a consistent interface. +9. Pre-trained HuggingFace models can be downloaded and used via the `gainpro download` command. This structure ensures **modularity, maintainability, and scalability**, making it easier to extend GenerativeProteomics. diff --git a/docs/source/GainPro.generativeproteomics.rst b/docs/source/GainPro.generativeproteomics.rst index 0f635e0..08384ca 100644 --- a/docs/source/GainPro.generativeproteomics.rst +++ b/docs/source/GainPro.generativeproteomics.rst @@ -17,7 +17,7 @@ Methods **Steps:** - 1. Parses Command-Line Arguments using argparse to obtain user-defined settings. + 1. Parses Command-Line Arguments using Click to obtain user-defined settings. 2. Loads Hyperparameters either from command-line arguments or a JSON configuration file. 3. Reads the Dataset (CSV/TSV format) and preprocesses it. 4. Initializes the Generator (G) and Discriminator (D) Networks with a specific architecture. diff --git a/pyproject.toml b/pyproject.toml index a1a02cf..136214f 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -57,6 +57,7 @@ dependencies = [ "polars", "huggingface_hub", "transformers", + "click>=8.0", ] [project.optional-dependencies] @@ -92,7 +93,8 @@ Issues = "https://github.com/QuantitativeBiology/GainPro/issues" Changelog = "https://github.com/QuantitativeBiology/GainPro/releases" [project.scripts] -gainpro = "GenerativeProteomics.generativeproteomics:main" +gainpro = "GenerativeProteomics.gainpro:main" +gain = "GenerativeProteomics.gainpro:gain_main" # Backward compatibility wrapper: use 'gainpro gain' instead [tool.setuptools] packages = ["GenerativeProteomics"] diff --git a/requirements.txt b/requirements.txt index ee39172..7d8f016 100644 --- a/requirements.txt +++ b/requirements.txt @@ -13,6 +13,10 @@ anndata polars huggingface_hub transformers +click>=8.0 + +# Interactive CLI (optional, for checkpoint selection) +inquirer # Visualization (optional) holoviews diff --git a/tests/test_imputation_management.py b/tests/test_imputation_management.py index 769a552..7633acf 100644 --- a/tests/test_imputation_management.py +++ b/tests/test_imputation_management.py @@ -15,17 +15,25 @@ class TestImputationManagement(unittest.TestCase): def test_correct_model(self): - """test running a correct model""" + """test running a custom model after adding it""" self.seed = 42 np.random.seed(self.seed) torch.manual_seed(self.seed) random.seed(self.seed) - df_missing = pd.read_csv("hela_missing_dann.csv") - imputation_management = ImputationManagement("GAIN_DANN_model", df_missing, "hela_missing_dann.csv") - imputation_management.run_model("GAIN_DANN_model") - self.assertTrue(os.path.isdir("GAIN_DANN_model"), "The directory does not exist") + # Define a simple custom imputation function + def custom_imputation(df): + df_copy = df.copy() + numeric_cols = df_copy.select_dtypes(include=[np.number]).columns + df_copy[numeric_cols] = df_copy[numeric_cols].fillna(0) + return df_copy + + df_missing = pd.read_csv("breastMissing_20.csv") + imputation_management = ImputationManagement("custom_model", df_missing, "breastMissing_20.csv") + imputation_management.add_method("custom_model", custom_imputation) + result = imputation_management.run_model("custom_model") + self.assertIsNotNone(result, "Custom imputation should return a result") def test_incorrect_model(self): """test the class with an incorrect model""" @@ -43,18 +51,11 @@ def test_add_existing_model(self): def test_add_exhisting_model(self): """test to try adding model already known""" - imputation_management = ImputationManagement("GAIN_DANN_model", None, "hela_missing_dann.csv") - with self.assertRaises(SystemExit): - imputation_management.add_method("GAIN_DANN_model", "hugging_face_gain_dann") - - - def test_medium_imputation(self): - """test the medium imputation method""" df_missing = pd.read_csv("breastMissing_20.csv") - imputation_management = ImputationManagement("medium_imputation", df_missing, "breastMissing_20.csv") - result = imputation_management.run_model("medium_imputation") - file = pd.read_csv("output_medium.csv") - np.testing.assert_allclose(result, file, rtol=1e-8, atol=1e-12, err_msg="There are still missing values after medium imputation") + imputation_management = ImputationManagement("test_model", df_missing, "breastMissing_20.csv") + imputation_management.add_method("test_model", lambda x: x) + with self.assertRaises(SystemExit): + imputation_management.add_method("test_model", "some_function") if __name__ == '__main__': unittest.main() \ No newline at end of file From 71afc9dd80986dc33e84622361652de1b3cde66f Mon Sep 17 00:00:00 2001 From: Yasset Perez-Riverol Date: Mon, 15 Dec 2025 09:16:20 +0000 Subject: [PATCH 12/26] Update GenerativeProteomics/gainpro.py Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> --- GenerativeProteomics/gainpro.py | 1 - 1 file changed, 1 deletion(-) diff --git a/GenerativeProteomics/gainpro.py b/GenerativeProteomics/gainpro.py index 55ce342..5cbec5f 100644 --- a/GenerativeProteomics/gainpro.py +++ b/GenerativeProteomics/gainpro.py @@ -20,7 +20,6 @@ import cProfile import pstats -import seaborn as sns import matplotlib.pyplot as plt import umap.umap_ as umap From 3a809758fe4ddc7f65cab182bbc56a2a0c22307a Mon Sep 17 00:00:00 2001 From: Yasset Perez-Riverol Date: Mon, 15 Dec 2025 12:07:44 +0000 Subject: [PATCH 13/26] Major change to GainPro package --- README.md | 8 +-- docs/source/Architecture.rst | 10 ++-- docs/source/GainPro.dataset.rst | 2 +- docs/source/GainPro.generativeproteomics.rst | 8 +-- docs/source/GainPro.hypers.rst | 2 +- docs/source/GainPro.manager.rst | 4 +- docs/source/GainPro.model.rst | 2 +- docs/source/GainPro.output.rst | 2 +- docs/source/GainPro.rst | 6 +-- docs/source/GainPro.utils.rst | 2 +- docs/source/How to use.rst | 6 +-- docs/source/Installation.rst | 6 +-- docs/source/Introduction.rst | 6 +-- docs/source/conf.py | 4 +- docs/source/index.rst | 6 +-- {GenerativeProteomics => gainpro}/__init__.py | 22 ++++---- .../correlation.py | 2 +- .../dann_utils.py | 0 .../data_utils.py | 0 {GenerativeProteomics => gainpro}/dataset.py | 0 {GenerativeProteomics => gainpro}/decoder.py | 0 .../domain_classifier.py | 0 .../early_stopping.py | 0 {GenerativeProteomics => gainpro}/encoder.py | 0 .../evaluation.py | 0 .../gain_dann_model.py | 14 ++--- {GenerativeProteomics => gainpro}/gainpro.py | 51 +++++++++++++------ {GenerativeProteomics => gainpro}/grl.py | 0 {GenerativeProteomics => gainpro}/hypers.py | 0 .../hypers_optimization.py | 6 +-- .../imputation_management.py | 0 {GenerativeProteomics => gainpro}/metrics.py | 0 {GenerativeProteomics => gainpro}/model.py | 8 +-- {GenerativeProteomics => gainpro}/output.py | 2 +- .../params_gain_dann.py | 0 {GenerativeProteomics => gainpro}/train.py | 22 ++++---- {GenerativeProteomics => gainpro}/utils.py | 0 pyproject.toml | 14 ++--- requirements.txt | 2 +- scripts/multiple_runs.sh | 2 +- tests/README.md | 4 +- tests/test_generate_reference.py | 7 +-- tests/test_hint_generation.py | 5 +- tests/test_hyper.py | 2 +- tests/test_imputation_management.py | 6 +-- tests/test_imputation_with_reference.py | 10 ++-- tests/test_impute_no_reference.py | 10 ++-- use-case/1-pip_install/README.md | 12 ++--- use-case/1-pip_install/test.py | 4 +- use-case/2-tests/README.md | 2 +- use-case/2-tests/test_generate_reference.py | 6 +-- use-case/2-tests/test_hint_generation.py | 6 +-- use-case/2-tests/test_hyper.py | 2 +- .../2-tests/test_imputation_with_reference.py | 10 ++-- use-case/2-tests/test_impute_no_reference.py | 10 ++-- use-case/3-HuggingFace/hugging.py | 2 +- use-case/README.md | 4 +- 57 files changed, 169 insertions(+), 152 deletions(-) rename {GenerativeProteomics => gainpro}/__init__.py (73%) rename {GenerativeProteomics => gainpro}/correlation.py (98%) rename {GenerativeProteomics => gainpro}/dann_utils.py (100%) rename {GenerativeProteomics => gainpro}/data_utils.py (100%) rename {GenerativeProteomics => gainpro}/dataset.py (100%) rename {GenerativeProteomics => gainpro}/decoder.py (100%) rename {GenerativeProteomics => gainpro}/domain_classifier.py (100%) rename {GenerativeProteomics => gainpro}/early_stopping.py (100%) rename {GenerativeProteomics => gainpro}/encoder.py (100%) rename {GenerativeProteomics => gainpro}/evaluation.py (100%) rename {GenerativeProteomics => gainpro}/gain_dann_model.py (92%) rename {GenerativeProteomics => gainpro}/gainpro.py (94%) rename {GenerativeProteomics => gainpro}/grl.py (100%) rename {GenerativeProteomics => gainpro}/hypers.py (100%) rename {GenerativeProteomics => gainpro}/hypers_optimization.py (96%) rename {GenerativeProteomics => gainpro}/imputation_management.py (100%) rename {GenerativeProteomics => gainpro}/metrics.py (100%) rename {GenerativeProteomics => gainpro}/model.py (98%) rename {GenerativeProteomics => gainpro}/output.py (97%) rename {GenerativeProteomics => gainpro}/params_gain_dann.py (100%) rename {GenerativeProteomics => gainpro}/train.py (96%) rename {GenerativeProteomics => gainpro}/utils.py (100%) diff --git a/README.md b/README.md index a8b4879..7d5b2d9 100644 --- a/README.md +++ b/README.md @@ -1,6 +1,6 @@ # GainPro -[![PyPi Version](https://img.shields.io/pypi/v/GenerativeProteomics?label=PyPi&color=blue&style=flat&logo=pypi)](https://pypi.org/project/GenerativeProteomics/) +[![PyPi Version](https://img.shields.io/pypi/v/gainpro?label=PyPi&color=blue&style=flat&logo=pypi)](https://pypi.org/project/gainpro/) [![Colab](https://img.shields.io/badge/Google_Colab-0061F2?style=flat&logo=googlecolab&color=blue&label=Colab&colorB=grey)](https://colab.research.google.com/drive/1ihtmsv_UvEz74YrLHZvATu1y2qH4X9-r?usp=sharing) [![Documentation](https://img.shields.io/badge/docs-read%20the%20docs-blue)](https://generativeproteomics.readthedocs.io/en/latest/) [![HuggingFace](https://img.shields.io/badge/Hugging_Face-grey?style=flat&logo=huggingface&color=grey)](https://huggingface.co/QuantitativeBiology) @@ -35,7 +35,7 @@ The package is available on PyPI. Install it using: ```bash -pip install GenerativeProteomics +pip install gainpro ``` ### From Source @@ -174,7 +174,7 @@ gainpro train --help GainPro can also be used programmatically through its Python API: ```python -from GenerativeProteomics import utils, Network, Params, Metrics, Data +from gainpro import utils, Network, Params, Metrics, Data import torch import pandas as pd @@ -241,7 +241,7 @@ Main components of the repository: - **`.github/workflows`**: CI/CD workflows for automated testing - **`datasets/`**: Sample datasets with missing values from PRIDE for testing -- **`GenerativeProteomics/`**: Core package source code +- **`gainpro/`**: Core package source code - `gainpro.py`: Main CLI interface (unified command with subcommands) - `model.py`: Basic GAIN model implementation - `gain_dann_model.py`: GAIN-DANN model implementation diff --git a/docs/source/Architecture.rst b/docs/source/Architecture.rst index d8816b9..bb0d985 100644 --- a/docs/source/Architecture.rst +++ b/docs/source/Architecture.rst @@ -3,7 +3,7 @@ Architecture =============== -GenerativeProteomics follows a modular architecture that promotes flexibility and scalability. +gainpro follows a modular architecture that promotes flexibility and scalability. It is composed of seven main classes responsible for different tasks in the processing and imputation of large proteomics datasets. Among those tasks, we can highlight the data processing, the imputation of missing values, the generation of synthetic data and the metrics calculation. @@ -17,9 +17,9 @@ Bellow, you can find a class diagram that showcases how these modules are connec Overview -------- -This diagram illustrates the overall architecture of GenerativeProteomics, showing how the different components interact during the imputation process. +This diagram illustrates the overall architecture of gainpro, showing how the different components interact during the imputation process. -- **GenerativeProteomics**: The main entry point that initializes all classes. +- **gainpro**: The main entry point that initializes all classes. - **Data**: Handles dataset loading and preparation, as well as the creation of the hint matrix, the mask matrix and the synthetic reference dataset. - **Network**: Trains the model using the attributes from the `Data` class. - **Params**: Stores hyperparameters and passes them to the network. @@ -30,7 +30,7 @@ This diagram illustrates the overall architecture of GenerativeProteomics, showi Execution Flow -------------- -1. The `GenerativeProteomics` module orchestrates the imputation process. +1. The `gainpro` module orchestrates the imputation process. 2. The `Data` module loads the dataset, which is used by the `Network`. 3. The `Network` requires hyperparameters from the `Params` class. 4. The `Metrics` class contains evaluation metrics from the training process. @@ -41,4 +41,4 @@ Execution Flow 9. Pre-trained HuggingFace models can be downloaded and used via the `gainpro download` command. -This structure ensures **modularity, maintainability, and scalability**, making it easier to extend GenerativeProteomics. +This structure ensures **modularity, maintainability, and scalability**, making it easier to extend gainpro. diff --git a/docs/source/GainPro.dataset.rst b/docs/source/GainPro.dataset.rst index fab4c34..79f6255 100644 --- a/docs/source/GainPro.dataset.rst +++ b/docs/source/GainPro.dataset.rst @@ -1,7 +1,7 @@ Data Class ======================== -.. automodule:: GenerativeProteomics.dataset +.. automodule:: gainpro.dataset :members: :undoc-members: :show-inheritance: diff --git a/docs/source/GainPro.generativeproteomics.rst b/docs/source/GainPro.generativeproteomics.rst index 08384ca..59f535f 100644 --- a/docs/source/GainPro.generativeproteomics.rst +++ b/docs/source/GainPro.generativeproteomics.rst @@ -1,13 +1,13 @@ -GenerativeProteomics Class +gainpro Class ======================== -.. automodule:: GenerativeProteomics.generativeproteomics +.. automodule:: gainpro.generativeproteomics :members: :undoc-members: :show-inheritance: -Here you will find the class `GenerativeProteomics` used during the training and evaluation of the model. -The `GenerativeProteomics` class is responsible for setting up, initializing, and running the GenerativeProteomics imputation process. +Here you will find the class `gainpro` used during the training and evaluation of the model. +The `gainpro` class is responsible for setting up, initializing, and running the gainpro imputation process. It reads input arguments, configures the model, trains it, and saves the results. Methods diff --git a/docs/source/GainPro.hypers.rst b/docs/source/GainPro.hypers.rst index b623294..a4e959f 100644 --- a/docs/source/GainPro.hypers.rst +++ b/docs/source/GainPro.hypers.rst @@ -1,7 +1,7 @@ Params class ================ -.. automodule:: GenerativeProteomics.hypers +.. automodule:: gainpro.hypers :members: :undoc-members: :show-inheritance: diff --git a/docs/source/GainPro.manager.rst b/docs/source/GainPro.manager.rst index f8bddaa..86ea109 100644 --- a/docs/source/GainPro.manager.rst +++ b/docs/source/GainPro.manager.rst @@ -1,13 +1,13 @@ Imputation Manager Class ======================== -.. automodule:: GenerativeProteomics.imputation_management +.. automodule:: gainpro.imputation_management :members: :undoc-members: :show-inheritance: Here you will find the class `ImputationManagement` and other functions used by it -during the process of managing the selection of an imputation method besides GenerativeProteomics. +during the process of managing the selection of an imputation method besides gainpro. This class works as a wrapper, allowing the user to easily add and use different imputation methods. Attributes diff --git a/docs/source/GainPro.model.rst b/docs/source/GainPro.model.rst index 8375539..6c98416 100644 --- a/docs/source/GainPro.model.rst +++ b/docs/source/GainPro.model.rst @@ -1,7 +1,7 @@ Network Class ======================== -.. automodule:: GenerativeProteomics.model +.. automodule:: gainpro.model :members: :undoc-members: :show-inheritance: diff --git a/docs/source/GainPro.output.rst b/docs/source/GainPro.output.rst index 65ed803..8181bac 100644 --- a/docs/source/GainPro.output.rst +++ b/docs/source/GainPro.output.rst @@ -1,7 +1,7 @@ Metrics Class ======================== -.. automodule:: GenerativeProteomics.output +.. automodule:: gainpro.output :members: :undoc-members: :show-inheritance: diff --git a/docs/source/GainPro.rst b/docs/source/GainPro.rst index ddfadab..751f0ae 100644 --- a/docs/source/GainPro.rst +++ b/docs/source/GainPro.rst @@ -1,8 +1,8 @@ -GenerativeProteomics Code +gainpro Code ========================== -In this section, we will provide a more detailed explanation of the classes used in GenerativeProteomics. -As mentioned before in the :ref:`Architecture` section, GenerativeProteomics is composed of six main classes +In this section, we will provide a more detailed explanation of the classes used in gainpro. +As mentioned before in the :ref:`Architecture` section, gainpro is composed of six main classes responsible for different tasks in the processing and imputation of large proteomics datasets. .. toctree:: diff --git a/docs/source/GainPro.utils.rst b/docs/source/GainPro.utils.rst index 9faf8d4..49c79c1 100644 --- a/docs/source/GainPro.utils.rst +++ b/docs/source/GainPro.utils.rst @@ -1,7 +1,7 @@ Utils Class ======================== -.. automodule:: GenerativeProteomics.utils +.. automodule:: gainpro.utils :members: :undoc-members: :show-inheritance: diff --git a/docs/source/How to use.rst b/docs/source/How to use.rst index 75ee02b..5ab1942 100644 --- a/docs/source/How to use.rst +++ b/docs/source/How to use.rst @@ -1,7 +1,7 @@ -How to use GenerativeProteomics +How to use gainpro ================================= -If your main goal is simply to just impute a general dataset, the most straightforward and simplest way to use GenerativeProteomics is to run: +If your main goal is simply to just impute a general dataset, the most straightforward and simplest way to use gainpro is to run: .. code-block:: bash @@ -42,7 +42,7 @@ Arguments: - **--miss**: The percentage of values to be concealed during the evaluation run (from 0 to 1) - **--outall**: Set this argument to 1 if you want to output every metric - **--override**: Set this argument to 1 if you want to delete the previously created files when writing the new output -- **--model**: Choose the model to use (None if GenerativeProteomics, otherwise provide name of the pre-trained model) +- **--model**: Choose the model to use (None if gainpro, otherwise provide name of the pre-trained model) If you want to assess the efficiency of the code you may provide a reference file containing a complete version of the dataset (without missing values): diff --git a/docs/source/Installation.rst b/docs/source/Installation.rst index b54336d..f9ae12e 100644 --- a/docs/source/Installation.rst +++ b/docs/source/Installation.rst @@ -9,7 +9,7 @@ You can install the package using the following command: .. code-block:: bash - pip install GenerativeProteomics + pip install gainpro This way, you can install the package and its dependencies in one go. @@ -18,9 +18,9 @@ After that, you can import all the functions and classes from the package of the GitHub ------------------- -If you prefer to use the code of the GenerativeProteomics model directly, you can access it in our GitHub repository. +If you prefer to use the code of the gainpro model directly, you can access it in our GitHub repository. -https://github.com/QuantitativeBiology/GenerativeProteomics +https://github.com/QuantitativeBiology/gainpro In order to clone the repository, you should use the following command: diff --git a/docs/source/Introduction.rst b/docs/source/Introduction.rst index c0c7e7e..a966b25 100644 --- a/docs/source/Introduction.rst +++ b/docs/source/Introduction.rst @@ -3,9 +3,9 @@ Introduction -What is GenerativeProteomics? +What is gainpro? ------------------------------ -GenerativeProteomics is a framework designed for missing data imputation and augmentation in the field of proteomics, by +gainpro is a framework designed for missing data imputation and augmentation in the field of proteomics, by using advanced generative models, like GAIN. @@ -20,7 +20,7 @@ Advanced models have also been developed, but they each have limitations and can All of these factors highlight the need to develop models and methods that can address this problem in an efficient and accurate way. -It was with the goal of addressing the recurrent and complex problem of missing data in proteomics that GenerativeProteomics was created. +It was with the goal of addressing the recurrent and complex problem of missing data in proteomics that gainpro was created. diff --git a/docs/source/conf.py b/docs/source/conf.py index 0d6caae..624ee3b 100644 --- a/docs/source/conf.py +++ b/docs/source/conf.py @@ -12,12 +12,12 @@ print("Sphynx sys.path", sys.path) -autodoc_mock_imports = ["GenerativeProteomics"] +autodoc_mock_imports = ["gainpro"] # -- Project information ----------------------------------------------------- # https://www.sphinx-doc.org/en/master/usage/configuration.html#project-information -project = 'GenerativeProteomics' +project = 'GainPro' copyright = '2025, Diogo Ferreira, Emanuel Gonçalves, Jorge Ribeiro, Leandro Sobral, Rita Gama' author = 'Diogo Ferreira, Emanuel Gonçalves, Jorge Ribeiro, Leandro Sobral, Rita Gama' release = '0.1' diff --git a/docs/source/index.rst b/docs/source/index.rst index 1e7b71a..7ed86c8 100644 --- a/docs/source/index.rst +++ b/docs/source/index.rst @@ -1,16 +1,16 @@ -.. GenerativeProteomics documentation master file, created by +.. gainpro documentation master file, created by sphinx-quickstart on Fri Feb 28 16:10:00 2025. You can adapt this file completely to your liking, but it should at least contain the root `toctree` directive. -GenerativeProteomics documentation +gainpro documentation ================================== .. Add your content using ``reStructuredText`` syntax. See the .. `reStructuredText `_ .. documentation for details. -GenerativeProteomics is a work that was developed to address the problem of missing data in the field of proteomics. +gainpro is a work that was developed to address the problem of missing data in the field of proteomics. .. toctree:: diff --git a/GenerativeProteomics/__init__.py b/gainpro/__init__.py similarity index 73% rename from GenerativeProteomics/__init__.py rename to gainpro/__init__.py index 779f342..41eea08 100644 --- a/GenerativeProteomics/__init__.py +++ b/gainpro/__init__.py @@ -1,6 +1,6 @@ """ -GenerativeProteomics (GainPro) -============================== +GainPro +======= A PyTorch implementation of Generative Adversarial Imputation Networks (GAIN) for imputing missing values in proteomics datasets. @@ -15,7 +15,7 @@ Example Usage ------------- ->>> from GenerativeProteomics import Data, Params, Network, Metrics +>>> from gainpro import Data, Params, Network, Metrics >>> import torch >>> import pandas as pd >>> @@ -41,18 +41,18 @@ __author__ = "QuantitativeBiology" # Core classes -from GenerativeProteomics.dataset import Data -from GenerativeProteomics.hypers import Params -from GenerativeProteomics.model import Network -from GenerativeProteomics.output import Metrics -from GenerativeProteomics.imputation_management import ImputationManagement +from .dataset import Data +from .hypers import Params +from .model import Network +from .output import Metrics +from .imputation_management import ImputationManagement # Utilities -from GenerativeProteomics import utils +from . import utils # GAIN-DANN components (optional, for advanced usage) -from GenerativeProteomics.gain_dann_model import GainDann -from GenerativeProteomics.params_gain_dann import ParamsGainDann +from .gain_dann_model import GainDann +from .params_gain_dann import ParamsGainDann __all__ = [ # Core classes diff --git a/GenerativeProteomics/correlation.py b/gainpro/correlation.py similarity index 98% rename from GenerativeProteomics/correlation.py rename to gainpro/correlation.py index 834555e..de34db2 100644 --- a/GenerativeProteomics/correlation.py +++ b/gainpro/correlation.py @@ -7,7 +7,7 @@ import os from datetime import datetime -from GenerativeProteomics.dann_utils import inverse_transform_output +from gainpro.dann_utils import inverse_transform_output logging.basicConfig(level=logging.INFO) logger = logging.getLogger(__name__) diff --git a/GenerativeProteomics/dann_utils.py b/gainpro/dann_utils.py similarity index 100% rename from GenerativeProteomics/dann_utils.py rename to gainpro/dann_utils.py diff --git a/GenerativeProteomics/data_utils.py b/gainpro/data_utils.py similarity index 100% rename from GenerativeProteomics/data_utils.py rename to gainpro/data_utils.py diff --git a/GenerativeProteomics/dataset.py b/gainpro/dataset.py similarity index 100% rename from GenerativeProteomics/dataset.py rename to gainpro/dataset.py diff --git a/GenerativeProteomics/decoder.py b/gainpro/decoder.py similarity index 100% rename from GenerativeProteomics/decoder.py rename to gainpro/decoder.py diff --git a/GenerativeProteomics/domain_classifier.py b/gainpro/domain_classifier.py similarity index 100% rename from GenerativeProteomics/domain_classifier.py rename to gainpro/domain_classifier.py diff --git a/GenerativeProteomics/early_stopping.py b/gainpro/early_stopping.py similarity index 100% rename from GenerativeProteomics/early_stopping.py rename to gainpro/early_stopping.py diff --git a/GenerativeProteomics/encoder.py b/gainpro/encoder.py similarity index 100% rename from GenerativeProteomics/encoder.py rename to gainpro/encoder.py diff --git a/GenerativeProteomics/evaluation.py b/gainpro/evaluation.py similarity index 100% rename from GenerativeProteomics/evaluation.py rename to gainpro/evaluation.py diff --git a/GenerativeProteomics/gain_dann_model.py b/gainpro/gain_dann_model.py similarity index 92% rename from GenerativeProteomics/gain_dann_model.py rename to gainpro/gain_dann_model.py index f5501be..bee4b43 100644 --- a/GenerativeProteomics/gain_dann_model.py +++ b/gainpro/gain_dann_model.py @@ -1,13 +1,13 @@ import torch import torch.nn as nn -from GenerativeProteomics.encoder import Encoder -from GenerativeProteomics.decoder import Decoder -from GenerativeProteomics.domain_classifier import DomainClassifier -from GenerativeProteomics.grl import GradientReversalLayer -from GenerativeProteomics.model import Network -from GenerativeProteomics.hypers import Params -from GenerativeProteomics.output import Metrics +from gainpro.encoder import Encoder +from gainpro.decoder import Decoder +from gainpro.domain_classifier import DomainClassifier +from gainpro.grl import GradientReversalLayer +from gainpro.model import Network +from gainpro.hypers import Params +from gainpro.output import Metrics #-----------------------------------# diff --git a/GenerativeProteomics/gainpro.py b/gainpro/gainpro.py similarity index 94% rename from GenerativeProteomics/gainpro.py rename to gainpro/gainpro.py index 55ce342..e533846 100644 --- a/GenerativeProteomics/gainpro.py +++ b/gainpro/gainpro.py @@ -20,21 +20,42 @@ import cProfile import pstats -import seaborn as sns -import matplotlib.pyplot as plt -import umap.umap_ as umap - -# Model imports -from GenerativeProteomics.gain_dann_model import GainDann -from GenerativeProteomics.model import Network -from GenerativeProteomics.hypers import Params -from GenerativeProteomics.output import Metrics -from GenerativeProteomics.params_gain_dann import ParamsGainDann -from GenerativeProteomics.data_utils import Data as DataDANN -from GenerativeProteomics.dataset import Data -from GenerativeProteomics.train import GainDannTrain -from GenerativeProteomics import utils -from GenerativeProteomics.imputation_management import ImputationManagement +# Optional visualization imports (only needed for certain features) +try: + import seaborn as sns + import matplotlib.pyplot as plt + import umap.umap_ as umap +except ImportError: + # These are optional dependencies for visualization features + sns = None + plt = None + umap = None + +# Model imports - use try/except to handle both relative and absolute imports +try: + # Try relative imports first (when run as package module) + from .gain_dann_model import GainDann + from .model import Network + from .hypers import Params + from .output import Metrics + from .params_gain_dann import ParamsGainDann + from .data_utils import Data as DataDANN + from .dataset import Data + from .train import GainDannTrain + from . import utils + from .imputation_management import ImputationManagement +except ImportError: + # Fall back to absolute imports (when run as script or in test environment) + from gainpro.gain_dann_model import GainDann + from gainpro.model import Network + from gainpro.hypers import Params + from gainpro.output import Metrics + from gainpro.params_gain_dann import ParamsGainDann + from gainpro.data_utils import Data as DataDANN + from gainpro.dataset import Data + from gainpro.train import GainDannTrain + from gainpro import utils + from gainpro.imputation_management import ImputationManagement from huggingface_hub import hf_hub_download from sklearn.preprocessing import LabelEncoder import sys diff --git a/GenerativeProteomics/grl.py b/gainpro/grl.py similarity index 100% rename from GenerativeProteomics/grl.py rename to gainpro/grl.py diff --git a/GenerativeProteomics/hypers.py b/gainpro/hypers.py similarity index 100% rename from GenerativeProteomics/hypers.py rename to gainpro/hypers.py diff --git a/GenerativeProteomics/hypers_optimization.py b/gainpro/hypers_optimization.py similarity index 96% rename from GenerativeProteomics/hypers_optimization.py rename to gainpro/hypers_optimization.py index 422212e..c4642aa 100644 --- a/GenerativeProteomics/hypers_optimization.py +++ b/gainpro/hypers_optimization.py @@ -5,9 +5,9 @@ import matplotlib.pyplot as plt # from models import plot_folder -from GenerativeProteomics.train import GainDannTrain -from GenerativeProteomics.params_gain_dann import ParamsGainDann -from GenerativeProteomics.data_utils import Data +from gainpro.train import GainDannTrain +from gainpro.params_gain_dann import ParamsGainDann +from gainpro.data_utils import Data class OptunaOptimization: diff --git a/GenerativeProteomics/imputation_management.py b/gainpro/imputation_management.py similarity index 100% rename from GenerativeProteomics/imputation_management.py rename to gainpro/imputation_management.py diff --git a/GenerativeProteomics/metrics.py b/gainpro/metrics.py similarity index 100% rename from GenerativeProteomics/metrics.py rename to gainpro/metrics.py diff --git a/GenerativeProteomics/model.py b/gainpro/model.py similarity index 98% rename from GenerativeProteomics/model.py rename to gainpro/model.py index afce056..3760d6c 100644 --- a/GenerativeProteomics/model.py +++ b/gainpro/model.py @@ -1,7 +1,7 @@ -from GenerativeProteomics.hypers import Params -from GenerativeProteomics.dataset import Data -from GenerativeProteomics.output import Metrics -from GenerativeProteomics import utils +from gainpro.hypers import Params +from gainpro.dataset import Data +from gainpro.output import Metrics +from gainpro import utils import torch from torch import nn diff --git a/GenerativeProteomics/output.py b/gainpro/output.py similarity index 97% rename from GenerativeProteomics/output.py rename to gainpro/output.py index 0f117f3..71cd850 100644 --- a/GenerativeProteomics/output.py +++ b/gainpro/output.py @@ -1,4 +1,4 @@ -from GenerativeProteomics.hypers import Params +from gainpro.hypers import Params import numpy as np import pandas as pd import os diff --git a/GenerativeProteomics/params_gain_dann.py b/gainpro/params_gain_dann.py similarity index 100% rename from GenerativeProteomics/params_gain_dann.py rename to gainpro/params_gain_dann.py diff --git a/GenerativeProteomics/train.py b/gainpro/train.py similarity index 96% rename from GenerativeProteomics/train.py rename to gainpro/train.py index f004849..24f072d 100644 --- a/GenerativeProteomics/train.py +++ b/gainpro/train.py @@ -8,17 +8,17 @@ from torch.utils.data import DataLoader, TensorDataset, WeightedRandomSampler # model -from GenerativeProteomics.gain_dann_model import GainDann -from GenerativeProteomics.hypers import Params -from GenerativeProteomics.dataset import generate_hint -from GenerativeProteomics.output import Metrics - -from GenerativeProteomics.data_utils import Data -from GenerativeProteomics.params_gain_dann import ParamsGainDann -from GenerativeProteomics.early_stopping import EarlyStopping -from GenerativeProteomics.metrics import MetricsTracker -from GenerativeProteomics.evaluation import EvaluationTracker -from GenerativeProteomics.dann_utils import save_model +from gainpro.gain_dann_model import GainDann +from gainpro.hypers import Params +from gainpro.dataset import generate_hint +from gainpro.output import Metrics + +from gainpro.data_utils import Data +from gainpro.params_gain_dann import ParamsGainDann +from gainpro.early_stopping import EarlyStopping +from gainpro.metrics import MetricsTracker +from gainpro.evaluation import EvaluationTracker +from gainpro.dann_utils import save_model import logging diff --git a/GenerativeProteomics/utils.py b/gainpro/utils.py similarity index 100% rename from GenerativeProteomics/utils.py rename to gainpro/utils.py diff --git a/pyproject.toml b/pyproject.toml index 136214f..ca2c2d4 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -3,7 +3,7 @@ requires = ["setuptools>=61.0", "wheel"] build-backend = "setuptools.build_meta" [project] -name = "GenerativeProteomics" +name = "gainpro" version = "0.2.0" description = "Generative Adversarial Imputation Networks (GAIN) for imputing missing values in proteomics datasets" readme = "README.md" @@ -82,7 +82,7 @@ docs = [ "sphinx-autodoc-typehints", ] all = [ - "GenerativeProteomics[dev,visualization,docs]", + "gainpro[dev,visualization,docs]", ] [project.urls] @@ -93,15 +93,15 @@ Issues = "https://github.com/QuantitativeBiology/GainPro/issues" Changelog = "https://github.com/QuantitativeBiology/GainPro/releases" [project.scripts] -gainpro = "GenerativeProteomics.gainpro:main" -gain = "GenerativeProteomics.gainpro:gain_main" # Backward compatibility wrapper: use 'gainpro gain' instead +gainpro = "gainpro.gainpro:main" +gain = "gainpro.gainpro:gain_main" # Backward compatibility wrapper: use 'gainpro gain' instead [tool.setuptools] -packages = ["GenerativeProteomics"] +packages = ["gainpro"] include-package-data = true [tool.setuptools.package-data] -GenerativeProteomics = [] +gainpro = [] [tool.black] line-length = 100 @@ -120,7 +120,7 @@ exclude = ''' [tool.isort] profile = "black" line_length = 100 -known_first_party = ["GenerativeProteomics"] +known_first_party = ["gainpro"] [tool.pytest.ini_options] testpaths = ["tests"] diff --git a/requirements.txt b/requirements.txt index 7d8f016..d795b21 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,4 +1,4 @@ -# Core dependencies for GenerativeProteomics +# Core dependencies for GainPro # For development installation, use: pip install -e ".[dev]" torch>=2.0.0 diff --git a/scripts/multiple_runs.sh b/scripts/multiple_runs.sh index f6c9b9b..361ab63 100644 --- a/scripts/multiple_runs.sh +++ b/scripts/multiple_runs.sh @@ -10,7 +10,7 @@ echo "Running $NUM_RUNS imputation runs with parameters: $PARAMS_FILE" for run in $(seq 1 $NUM_RUNS) do echo "Running run = $run / $NUM_RUNS" - python -m GenerativeProteomics.generativeproteomics --parameters "$PARAMS_FILE" + gainpro gain --parameters "$PARAMS_FILE" done echo "Completed all $NUM_RUNS runs" diff --git a/tests/README.md b/tests/README.md index ff6c38a..c249c3d 100644 --- a/tests/README.md +++ b/tests/README.md @@ -1,6 +1,6 @@ -# Generative Proteomics Tests +# GainPro Tests -In this directory, you can find the tests for the GenerativeProteomics model. +In this directory, you can find the tests for the GainPro model. ## Tests diff --git a/tests/test_generate_reference.py b/tests/test_generate_reference.py index ee2fca1..be41d79 100644 --- a/tests/test_generate_reference.py +++ b/tests/test_generate_reference.py @@ -2,13 +2,10 @@ import os sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))) -sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "GenerativeProteomics"))) - - -from GenerativeProteomics.dataset import Data +from gainpro.dataset import Data import numpy as np import unittest -from GenerativeProteomics.utils import create_csv +from gainpro.utils import create_csv import torch import pandas as pd import random diff --git a/tests/test_hint_generation.py b/tests/test_hint_generation.py index 35cd56e..bbc7273 100644 --- a/tests/test_hint_generation.py +++ b/tests/test_hint_generation.py @@ -2,12 +2,11 @@ import os sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))) -sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "GenerativeProteomics"))) -from GenerativeProteomics.dataset import Data, generate_hint +from gainpro.dataset import Data, generate_hint import numpy as np import unittest -from GenerativeProteomics.utils import create_csv +from gainpro.utils import create_csv import torch import pandas as pd import random diff --git a/tests/test_hyper.py b/tests/test_hyper.py index 9d4192e..6f4d853 100644 --- a/tests/test_hyper.py +++ b/tests/test_hyper.py @@ -5,7 +5,7 @@ import sys sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))) -from GenerativeProteomics.hypers import Params +from gainpro.hypers import Params class TestParams(unittest.TestCase): diff --git a/tests/test_imputation_management.py b/tests/test_imputation_management.py index 7633acf..94becfe 100644 --- a/tests/test_imputation_management.py +++ b/tests/test_imputation_management.py @@ -6,10 +6,10 @@ import sys import pandas as pd sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))) -sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "GenerativeProteomics"))) +sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "gainpro"))) -from GenerativeProteomics.imputation_management import ImputationManagement -import GenerativeProteomics.utils +from gainpro.imputation_management import ImputationManagement +import gainpro.utils class TestImputationManagement(unittest.TestCase): diff --git a/tests/test_imputation_with_reference.py b/tests/test_imputation_with_reference.py index f3b6b68..47a5b82 100644 --- a/tests/test_imputation_with_reference.py +++ b/tests/test_imputation_with_reference.py @@ -2,13 +2,13 @@ import os sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))) -sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "GenerativeProteomics"))) +sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "gainpro"))) -from GenerativeProteomics.dataset import Data -from GenerativeProteomics.model import Network -from GenerativeProteomics.hypers import Params -from GenerativeProteomics.output import Metrics +from gainpro.dataset import Data +from gainpro.model import Network +from gainpro.hypers import Params +from gainpro.output import Metrics import numpy as np import unittest import torch diff --git a/tests/test_impute_no_reference.py b/tests/test_impute_no_reference.py index 7a8bee0..f35545a 100644 --- a/tests/test_impute_no_reference.py +++ b/tests/test_impute_no_reference.py @@ -2,12 +2,12 @@ import os sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))) -sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "GenerativeProteomics"))) +sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "gainpro"))) -from GenerativeProteomics.dataset import Data -from GenerativeProteomics.model import Network -from GenerativeProteomics.hypers import Params -from GenerativeProteomics.output import Metrics +from gainpro.dataset import Data +from gainpro.model import Network +from gainpro.hypers import Params +from gainpro.output import Metrics import numpy as np import unittest import torch diff --git a/use-case/1-pip_install/README.md b/use-case/1-pip_install/README.md index b2f7e6d..39ba972 100644 --- a/use-case/1-pip_install/README.md +++ b/use-case/1-pip_install/README.md @@ -1,20 +1,20 @@ -# GenerativeProteomics +# gainpro -In this first part, we will show in a simple and clear way how to install and use `GenerativeProteomics` +In this first part, we will show in a simple and clear way how to install and use `gainpro` to perform imputation of missing values of proteomics' datasets. ## Installation -`GenerativeProteomics` is a Python package for imputation of missing values in the field of proteomics. +`gainpro` is a Python package for imputation of missing values in the field of proteomics. It is currently based on the `Generative Adversarial Imputation Network (GAIN)` architecture. To use the package, you need to have `Python 3.10` or `Python 3.11` on your system. To do that, you can create a conda environment, for example. -The package is available on `PyPI` and can be installed using a `pip` command (GenerativeProteomics 0.2.1). +The package is available on `PyPI` and can be installed using a `pip` command (gainpro 0.2.1). ```bash - pip install GenerativeProteomics + pip install gainpro ``` @@ -105,7 +105,7 @@ role in the imputation process : ## Example -In this use-case, you can find a file that showcases how to import and use the functions and classes of GenerativeProteomics. +In this use-case, you can find a file that showcases how to import and use the functions and classes of gainpro. This file is called `test.py` and it performs the imputation of missing values on a dataset of proteins from PRIDE. The dataset in question is called `PXD004452.tsv` and it is also accessible in this directory. This dataset has a missing rate of 17.442532054984405%, 8657 samples and 4 features. diff --git a/use-case/1-pip_install/test.py b/use-case/1-pip_install/test.py index cca06bb..f7b2407 100644 --- a/use-case/1-pip_install/test.py +++ b/use-case/1-pip_install/test.py @@ -1,11 +1,11 @@ -from GenerativeProteomics import utils, Network, Params, Metrics, Data +from gainpro import utils, Network, Params, Metrics, Data import torch import argparse import os def test_network(): - """ Test to showcase how to import and use the classes and functions of the GenerativeProteomics package. """ + """ Test to showcase how to import and use the classes and functions of the gainpro package. """ parser = argparse.ArgumentParser() parser.add_argument("--model", type = str, help = "indicates the model to use") diff --git a/use-case/2-tests/README.md b/use-case/2-tests/README.md index 097d6ae..f1a1480 100644 --- a/use-case/2-tests/README.md +++ b/use-case/2-tests/README.md @@ -1,6 +1,6 @@ # Generative Proteomics Tests -In this directory, you can find the tests for the GenerativeProteomics model. +In this directory, you can find the tests for the gainpro model. ## Tests diff --git a/use-case/2-tests/test_generate_reference.py b/use-case/2-tests/test_generate_reference.py index 279c861..db03f24 100644 --- a/use-case/2-tests/test_generate_reference.py +++ b/use-case/2-tests/test_generate_reference.py @@ -2,12 +2,12 @@ import os sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))) -sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "GenerativeProteomics"))) +sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "gainpro"))) -from GenerativeProteomics import Data +from gainpro import Data import numpy as np import unittest -from GenerativeProteomics.utils import create_csv +from gainpro.utils import create_csv import torch import pandas as pd import random diff --git a/use-case/2-tests/test_hint_generation.py b/use-case/2-tests/test_hint_generation.py index 43ffdb3..082cfc3 100644 --- a/use-case/2-tests/test_hint_generation.py +++ b/use-case/2-tests/test_hint_generation.py @@ -2,12 +2,12 @@ import os sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))) -sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "GenerativeProteomics"))) +sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "gainpro"))) -from GenerativeProteomics.dataset import Data, generate_hint +from gainpro.dataset import Data, generate_hint import numpy as np import unittest -from GenerativeProteomics.utils import create_csv +from gainpro.utils import create_csv import torch import pandas as pd import random diff --git a/use-case/2-tests/test_hyper.py b/use-case/2-tests/test_hyper.py index 6696225..c88e1d6 100644 --- a/use-case/2-tests/test_hyper.py +++ b/use-case/2-tests/test_hyper.py @@ -5,7 +5,7 @@ import sys sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))) -from GenerativeProteomics.hypers import Params +from gainpro.hypers import Params class TestParams(unittest.TestCase): diff --git a/use-case/2-tests/test_imputation_with_reference.py b/use-case/2-tests/test_imputation_with_reference.py index 74d7c1e..ccd6617 100644 --- a/use-case/2-tests/test_imputation_with_reference.py +++ b/use-case/2-tests/test_imputation_with_reference.py @@ -2,13 +2,13 @@ import os sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))) -sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "GenerativeProteomics"))) +sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "gainpro"))) -from GenerativeProteomics.dataset import Data -from GenerativeProteomics.model import Network -from GenerativeProteomics.hypers import Params -from GenerativeProteomics.output import Metrics +from gainpro.dataset import Data +from gainpro.model import Network +from gainpro.hypers import Params +from gainpro.output import Metrics import numpy as np import unittest import torch diff --git a/use-case/2-tests/test_impute_no_reference.py b/use-case/2-tests/test_impute_no_reference.py index 4b1efa4..524c622 100644 --- a/use-case/2-tests/test_impute_no_reference.py +++ b/use-case/2-tests/test_impute_no_reference.py @@ -2,12 +2,12 @@ import os sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))) -sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "GenerativeProteomics"))) +sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "gainpro"))) -from GenerativeProteomics.dataset import Data -from GenerativeProteomics.model import Network -from GenerativeProteomics.hypers import Params -from GenerativeProteomics.output import Metrics +from gainpro.dataset import Data +from gainpro.model import Network +from gainpro.hypers import Params +from gainpro.output import Metrics import numpy as np import unittest import torch diff --git a/use-case/3-HuggingFace/hugging.py b/use-case/3-HuggingFace/hugging.py index 4a175a5..6d7a9a7 100644 --- a/use-case/3-HuggingFace/hugging.py +++ b/use-case/3-HuggingFace/hugging.py @@ -8,7 +8,7 @@ def test_network(): - """ Test to showcase how to import and use the classes and functions of the GenerativeProteomics package. """ + """ Test to showcase how to import and use the classes and functions of the gainpro package. """ parser = argparse.ArgumentParser() parser.add_argument("--model", type = str, help = "indicates the model to use") diff --git a/use-case/README.md b/use-case/README.md index 5976bca..3a40c41 100644 --- a/use-case/README.md +++ b/use-case/README.md @@ -1,6 +1,6 @@ # Generative Proteomics -GenerativeProteomics is a Python package for missing value imputation in proteomics datasets. +gainpro is a Python package for missing value imputation in proteomics datasets. It leverages generative models to accurately estimate missing values, improving downstream analysis and data quality. @@ -27,7 +27,7 @@ https://colab.research.google.com/drive/1ihtmsv_UvEz74YrLHZvATu1y2qH4X9-r?usp=sh If you want to take a closer look at the code, you can visit our GitHub repository: -https://github.com/QuantitativeBiology/GenerativeProteomics +https://github.com/QuantitativeBiology/gainpro If you want to learn more about our work, you can read its documentation in the following link: From 8d28bb8c0155de4a4d7bf66eea3d989c5f7a1f12 Mon Sep 17 00:00:00 2001 From: Yasset Perez-Riverol Date: Mon, 15 Dec 2025 14:03:20 +0000 Subject: [PATCH 14/26] improve the docs --- docs/source/GainPro.rst | 16 ++++++++-------- docs/source/{How to use.rst => how_to_use.rst} | 0 docs/source/index.rst | 12 ++++++------ 3 files changed, 14 insertions(+), 14 deletions(-) rename docs/source/{How to use.rst => how_to_use.rst} (100%) diff --git a/docs/source/GainPro.rst b/docs/source/GainPro.rst index 751f0ae..a149b0b 100644 --- a/docs/source/GainPro.rst +++ b/docs/source/GainPro.rst @@ -2,18 +2,18 @@ gainpro Code ========================== In this section, we will provide a more detailed explanation of the classes used in gainpro. -As mentioned before in the :ref:`Architecture` section, gainpro is composed of six main classes +As mentioned before in the :ref:`architecture` section, gainpro is composed of six main classes responsible for different tasks in the processing and imputation of large proteomics datasets. .. toctree:: :maxdepth: 20 - GainPro.dataset - GainPro.hypers - GainPro.model - GainPro.output - GainPro.generativeproteomics - GainPro.utils - GainPro.manager + gainpro.dataset + gainpro.hypers + gainpro.model + gainpro.output + gainpro.generativeproteomics + gainpro.utils + gainpro.manager diff --git a/docs/source/How to use.rst b/docs/source/how_to_use.rst similarity index 100% rename from docs/source/How to use.rst rename to docs/source/how_to_use.rst diff --git a/docs/source/index.rst b/docs/source/index.rst index 7ed86c8..6d6b431 100644 --- a/docs/source/index.rst +++ b/docs/source/index.rst @@ -17,12 +17,12 @@ gainpro is a work that was developed to address the problem of missing data in t :maxdepth: 14 :caption: Contents: - Introduction - Installation - How to use - Architecture - GainPro - Tests + introduction + installation + how_to_use + architecture + gainpro + tests From 2d505c28d65bc2fa493ff02df0acb9cebf5ccc23 Mon Sep 17 00:00:00 2001 From: Yasset Perez-Riverol Date: Mon, 15 Dec 2025 14:17:52 +0000 Subject: [PATCH 15/26] minor changes github actions --- .github/workflows/run_continuous_integration.yml | 8 +++++--- .github/workflows/run_tests.yml | 4 +++- 2 files changed, 8 insertions(+), 4 deletions(-) diff --git a/.github/workflows/run_continuous_integration.yml b/.github/workflows/run_continuous_integration.yml index 1567960..17bf062 100644 --- a/.github/workflows/run_continuous_integration.yml +++ b/.github/workflows/run_continuous_integration.yml @@ -4,14 +4,14 @@ on: push: branches: [main, master, develop] paths: - - 'GenerativeProteomics/**' + - 'gainpro/**' - 'tests/**' - 'requirements.txt' - 'pyproject.toml' pull_request: branches: [main, master, develop] paths: - - 'GenerativeProteomics/**' + - 'gainpro/**' - 'tests/**' - 'requirements.txt' - 'pyproject.toml' @@ -46,6 +46,8 @@ jobs: pip install -r requirements.txt # Ensure numpy < 2 for PyTorch compatibility pip install "numpy<2" + # Install package in editable mode for import tests + pip install -e . - name: Run tests run: | @@ -54,4 +56,4 @@ jobs: - name: Test package import run: | - python -c "from GenerativeProteomics import Data, Params, Network, Metrics; print('Package imports successful!')" + python -c "from gainpro import Data, Params, Network, Metrics; print('Package imports successful!')" diff --git a/.github/workflows/run_tests.yml b/.github/workflows/run_tests.yml index acb1bae..34cff75 100644 --- a/.github/workflows/run_tests.yml +++ b/.github/workflows/run_tests.yml @@ -37,6 +37,8 @@ jobs: pip install -r requirements.txt # Ensure numpy < 2 for PyTorch compatibility pip install "numpy<2" + # Install package in editable mode for import tests + pip install -e . - name: Run tests run: | @@ -45,4 +47,4 @@ jobs: - name: Test package import run: | - python -c "from GenerativeProteomics import Data, Params, Network, Metrics; print('Package imports successful!')" + python -c "from gainpro import Data, Params, Network, Metrics; print('Package imports successful!')" From e84a10a3ff9568fa152cec04bc7fb1df4531ef2d Mon Sep 17 00:00:00 2001 From: Yasset Perez-Riverol Date: Mon, 15 Dec 2025 14:18:28 +0000 Subject: [PATCH 16/26] Update docs/source/GainPro.manager.rst Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> --- docs/source/GainPro.manager.rst | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/source/GainPro.manager.rst b/docs/source/GainPro.manager.rst index 86ea109..bd5d148 100644 --- a/docs/source/GainPro.manager.rst +++ b/docs/source/GainPro.manager.rst @@ -7,7 +7,7 @@ Imputation Manager Class :show-inheritance: Here you will find the class `ImputationManagement` and other functions used by it -during the process of managing the selection of an imputation method besides gainpro. +during the process of managing the selection of an imputation method besides GainPro. This class works as a wrapper, allowing the user to easily add and use different imputation methods. Attributes From d0eea52ad0e39b87480eba3c19960c4215767859 Mon Sep 17 00:00:00 2001 From: Yasset Perez-Riverol Date: Mon, 15 Dec 2025 14:21:56 +0000 Subject: [PATCH 17/26] Update docs/source/GainPro.rst Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> --- docs/source/GainPro.rst | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/source/GainPro.rst b/docs/source/GainPro.rst index a149b0b..255380e 100644 --- a/docs/source/GainPro.rst +++ b/docs/source/GainPro.rst @@ -1,4 +1,4 @@ -gainpro Code +GainPro Code ========================== In this section, we will provide a more detailed explanation of the classes used in gainpro. From c2b19f28ecdb60e12e4fce8083e4845b20d12257 Mon Sep 17 00:00:00 2001 From: Yasset Perez-Riverol Date: Mon, 5 Jan 2026 13:47:04 +0000 Subject: [PATCH 18/26] first comment Diogo --- README.md | 15 ++++++--- gainpro/gainpro.py | 78 ++++++++++++++++++++++++++++++++-------------- 2 files changed, 66 insertions(+), 27 deletions(-) diff --git a/README.md b/README.md index 7d5b2d9..43287d8 100644 --- a/README.md +++ b/README.md @@ -5,7 +5,7 @@ [![Documentation](https://img.shields.io/badge/docs-read%20the%20docs-blue)](https://generativeproteomics.readthedocs.io/en/latest/) [![HuggingFace](https://img.shields.io/badge/Hugging_Face-grey?style=flat&logo=huggingface&color=grey)](https://huggingface.co/QuantitativeBiology) -**GainPro** is a PyTorch implementation of Generative Adversarial Imputation Networks (GAIN) [[1]](#1) for imputing missing iBAQ values in proteomics datasets. The package provides a unified command-line interface with multiple imputation methods including basic GAIN, GAIN-DANN (domain-adaptive), and pre-trained HuggingFace models. +**GainPro** is a PyTorch implementation of Generative Adversarial Imputation Networks (GAIN) [[1]](#1) for imputing missing iBAQ values in proteomics datasets. The package provides a unified command-line interface with multiple imputation methods including basic GAIN, GAIN-DANN (domain-adaptive), and pre-trained GAIN-DANN models from HuggingFace. ## Table of Contents @@ -22,7 +22,7 @@ - **Basic GAIN**: Simple Generator + Discriminator architecture for general-purpose imputation - **GAIN-DANN**: Domain-adaptive imputation with Encoder/Decoder architecture -- **Pre-trained Models**: Easy access to HuggingFace pre-trained models +- **Pre-trained Models**: Easy access to HuggingFace pre-trained GAIN-DANN models - **Median Imputation**: Simple baseline method - **Flexible CLI**: Unified `gainpro` command with intuitive subcommands - **Python API**: Full programmatic access to all functionality @@ -141,14 +141,21 @@ Use a trained GAIN-DANN checkpoint for imputation: gainpro impute --checkpoint checkpoints/your_model --input data.csv --output imputed.csv ``` -### `gainpro download` - HuggingFace Pre-trained Models +### `gainpro download` - HuggingFace Pre-trained GAIN-DANN Models -Download and use pre-trained models from HuggingFace: +Download and use pre-trained GAIN-DANN models from HuggingFace: ```bash gainpro download --input data.csv --output imputed.csv ``` +**Note:** This command is specifically designed for GAIN-DANN models. It requires the HuggingFace repository to contain: +- `config.json` - Model configuration +- `pytorch_model.bin` - Model weights +- `modeling_gain_dann.py` - Model architecture file with `GainDANN` class + +The model must follow the GAIN-DANN interface (returning `(x_reconstructed, x_domain)` from forward pass). Other model types are not currently supported. + ### `gainpro median` - Median Imputation Simple median imputation baseline: diff --git a/gainpro/gainpro.py b/gainpro/gainpro.py index e533846..91145a4 100644 --- a/gainpro/gainpro.py +++ b/gainpro/gainpro.py @@ -303,47 +303,73 @@ def impute(checkpoint_dir, input_file, output_file, miss_rate): @click.option( "--model-id", default="QuantitativeBiology/GAIN_DANN_model", - help="HuggingFace model repository ID", + help="HuggingFace model repository ID (must be a GAIN-DANN model with modeling_gain_dann.py file)", show_default=True, ) def download(input_file, output_file, model_id): """ - Download a pre-trained model from HuggingFace and perform imputation. + Download a pre-trained GAIN-DANN model from HuggingFace and perform imputation. + + NOTE: This command is specifically designed for GAIN-DANN models. It expects: + - A config.json file with model configuration + - A pytorch_model.bin file with model weights + - A modeling_gain_dann.py file with the model architecture class + + The model must implement the GainDANN interface with forward() returning + (x_reconstructed, x_domain) tuples. Other model types are not supported. Example: gainpro download --input data.csv --output imputed.csv """ - logger.info(f"Downloading model from HuggingFace: {model_id}") + logger.info(f"Downloading GAIN-DANN model from HuggingFace: {model_id}") + logger.warning( + "NOTE: This command only works with GAIN-DANN models that include " + "modeling_gain_dann.py. Other model types are not supported." + ) save_dir = "./GAIN_DANN_model" os.makedirs(save_dir, exist_ok=True) # Download files from HuggingFace + # NOTE: This is specific to GAIN-DANN model structure logger.info("Downloading model files...") - config_path = hf_hub_download( - repo_id=model_id, - filename="config.json", - cache_dir=save_dir - ) - weights_path = hf_hub_download( - repo_id=model_id, - filename="pytorch_model.bin", - cache_dir=save_dir - ) - model_path = hf_hub_download( - repo_id=model_id, - filename="modeling_gain_dann.py", - cache_dir=save_dir - ) + try: + config_path = hf_hub_download( + repo_id=model_id, + filename="config.json", + cache_dir=save_dir + ) + weights_path = hf_hub_download( + repo_id=model_id, + filename="pytorch_model.bin", + cache_dir=save_dir + ) + model_path = hf_hub_download( + repo_id=model_id, + filename="modeling_gain_dann.py", + cache_dir=save_dir + ) + except Exception as e: + raise click.ClickException( + f"Failed to download GAIN-DANN model files from {model_id}. " + f"Ensure the repository contains config.json, pytorch_model.bin, " + f"and modeling_gain_dann.py files. Error: {e}" + ) # Add directory to Python path to import the model directory = os.path.dirname(model_path) if directory not in sys.path: sys.path.append(directory) - # Import model classes - from modeling_gain_dann import GainDANNConfig, GainDANN + # Import model classes (GAIN-DANN specific) + try: + from modeling_gain_dann import GainDANNConfig, GainDANN + except ImportError as e: + raise click.ClickException( + f"Failed to import GAIN-DANN model classes from modeling_gain_dann.py. " + f"This command only works with GAIN-DANN models. Error: {e}" + ) logger.info("Loading model configuration...") @@ -383,10 +409,16 @@ def download(input_file, output_file, model_id): x = torch.tensor(data_df.values, dtype=torch.float32) - # Perform imputation + # Perform imputation (GAIN-DANN specific: returns reconstructed data and domain predictions) logger.info("Running imputation...") with torch.no_grad(): - x_reconstructed, x_domain = model(x) + try: + x_reconstructed, x_domain = model(x) + except (ValueError, TypeError) as e: + raise click.ClickException( + f"Model output format not recognized. This command expects GAIN-DANN models " + f"that return (x_reconstructed, x_domain) tuples. Error: {e}" + ) # Convert to DataFrame and save result_df = pd.DataFrame(x_reconstructed.numpy(), columns=data_df.columns if hasattr(data_df, 'columns') else None) @@ -397,7 +429,7 @@ def download(input_file, output_file, model_id): result_df.to_csv(output_file, index=True) - # Optionally save domain predictions + # Save domain predictions (GAIN-DANN specific feature) domain_file = output_file.replace(".csv", "_domain.csv") pd.DataFrame(x_domain.numpy()).to_csv(domain_file, index=False) From b35781ac370a36f1c480b6507e0ae10f9c9cea0d Mon Sep 17 00:00:00 2001 From: Yasset Perez-Riverol Date: Mon, 5 Jan 2026 14:11:59 +0000 Subject: [PATCH 19/26] Second comment from Diogo --- gainpro/gainpro.py | 10 +++++----- use-case/1-pip_install/README.md | 2 +- 2 files changed, 6 insertions(+), 6 deletions(-) diff --git a/gainpro/gainpro.py b/gainpro/gainpro.py index 91145a4..4a675a1 100644 --- a/gainpro/gainpro.py +++ b/gainpro/gainpro.py @@ -171,18 +171,18 @@ def train(config_file, save): params_gain_dann = ParamsGainDann.read_hyperparameters(config_file) params = params_gain_dann.to_dict() - # Read dataset + # Read dataset - use DataDANN for GAIN-DANN models if params_gain_dann.path_dataset_missing: logger.info(f"Loading dataset with missing values: {params_gain_dann.path_dataset_missing}") dataset_missing = pd.read_csv(params_gain_dann.path_dataset_missing, index_col=0) dataset_missing = dataset_missing.iloc[:, 8500:] # TODO: Remove start_col hardcoding - data = Data( + data = DataDANN( dataset_path=params_gain_dann.path_dataset, dataset_missing=dataset_missing, start_col=8500 ) else: - data = Data( + data = DataDANN( dataset_path=params_gain_dann.path_dataset, miss_rate=params["miss_rate"], start_col=8500 @@ -252,8 +252,8 @@ def impute(checkpoint_dir, input_file, output_file, miss_rate): df = df.loc[:, list(common_proteins)] logger.info(f"Using {len(common_proteins)} common proteins") - # Create data object - data = Data(df, miss_rate=miss_rate, start_col=0) + # Create data object - use DataDANN for GAIN-DANN models + data = DataDANN(dataset=df, miss_rate=miss_rate, start_col=0) incomplete_data = data.dataset_missing # Pad with NaNs for model compatibility diff --git a/use-case/1-pip_install/README.md b/use-case/1-pip_install/README.md index 39ba972..36f3c85 100644 --- a/use-case/1-pip_install/README.md +++ b/use-case/1-pip_install/README.md @@ -11,7 +11,7 @@ to perform imputation of missing values of proteomics' datasets. It is currently based on the `Generative Adversarial Imputation Network (GAIN)` architecture. To use the package, you need to have `Python 3.10` or `Python 3.11` on your system. To do that, you can create a conda environment, for example. -The package is available on `PyPI` and can be installed using a `pip` command (gainpro 0.2.1). +The package is available on `PyPI` and can be installed using a `pip` command (gainpro 0.2.0). ```bash pip install gainpro From 9374735f3a2da874c8258a7eda5b2bb3b1fb84e4 Mon Sep 17 00:00:00 2001 From: Yasset Perez-Riverol Date: Mon, 5 Jan 2026 14:18:46 +0000 Subject: [PATCH 20/26] minor changes --- gainpro/gainpro.py | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) diff --git a/gainpro/gainpro.py b/gainpro/gainpro.py index 4a675a1..66baed5 100644 --- a/gainpro/gainpro.py +++ b/gainpro/gainpro.py @@ -822,8 +822,11 @@ def gain_main(): # Show deprecation warning click.echo( - "⚠️ WARNING: The 'gain' command is deprecated. " - "Please use 'gainpro gain' instead.\n", + "⚠️ WARNING: The standalone 'gain' command is deprecated and will be " + "removed in version 0.3.0.\n" + " Please migrate to 'gainpro gain' instead. The functionality is identical.\n" + " For documentation and examples, see: " + "https://github.com/bigbio/GainPro/blob/main/README.md\n", err=True ) From bf475e0e67ffbb539ce4db1638fab4e104494648 Mon Sep 17 00:00:00 2001 From: Yasset Perez-Riverol Date: Mon, 5 Jan 2026 14:25:24 +0000 Subject: [PATCH 21/26] minor change --- .gitignore | 4 ---- 1 file changed, 4 deletions(-) diff --git a/.gitignore b/.gitignore index aca0442..7444eb3 100644 --- a/.gitignore +++ b/.gitignore @@ -266,7 +266,3 @@ logs/ *.key secrets.json credentials.json - - -#Ignore cursor AI rules -.cursor/rules/codacy.mdc From ca47cf476832131b3f0e6190dbbd80c1203fea13 Mon Sep 17 00:00:00 2001 From: Yasset Perez-Riverol Date: Mon, 5 Jan 2026 14:43:08 +0000 Subject: [PATCH 22/26] mor comments from Copilot tackled --- tests/test_imputation_management.py | 5 ----- tests/test_impute_no_reference.py | 18 +++++++----------- 2 files changed, 7 insertions(+), 16 deletions(-) diff --git a/tests/test_imputation_management.py b/tests/test_imputation_management.py index 94becfe..0628bd6 100644 --- a/tests/test_imputation_management.py +++ b/tests/test_imputation_management.py @@ -2,14 +2,9 @@ import numpy as np import torch import random -import os -import sys import pandas as pd -sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))) -sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "gainpro"))) from gainpro.imputation_management import ImputationManagement -import gainpro.utils class TestImputationManagement(unittest.TestCase): diff --git a/tests/test_impute_no_reference.py b/tests/test_impute_no_reference.py index f35545a..fbb0c36 100644 --- a/tests/test_impute_no_reference.py +++ b/tests/test_impute_no_reference.py @@ -1,18 +1,15 @@ -import sys +import unittest import os -sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))) - -sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "gainpro"))) +import random +import numpy as np +import pandas as pd +import torch from gainpro.dataset import Data from gainpro.model import Network from gainpro.hypers import Params from gainpro.output import Metrics -import numpy as np -import unittest -import torch -import pandas as pd -import random + class TestImputation(unittest.TestCase): def setUp(self): """Set up reusable test data and parameters.""" @@ -103,8 +100,7 @@ def test_imputation(self): except Exception as e: self.fail(f"Imputation failed with exception: {e}") - - "test the metrics class produced during imputation" + # Test the metrics class produced during imputation self.assertEqual(metrics.loss_D.size, self.params.num_iterations) self.assertEqual(metrics.loss_G.size, self.params.num_iterations) self.assertEqual(metrics.ram.size, self.params.num_iterations) From ac9b65f06edcb189ce3e2874385e34e954aa9d73 Mon Sep 17 00:00:00 2001 From: Yasset Perez-Riverol Date: Mon, 5 Jan 2026 14:56:14 +0000 Subject: [PATCH 23/26] minor changes --- gainpro/gainpro.py | 21 ++++++++++++++------- scripts/multiple_runs.sh | 21 +++++++++++++++++++-- 2 files changed, 33 insertions(+), 9 deletions(-) diff --git a/gainpro/gainpro.py b/gainpro/gainpro.py index 66baed5..1d4218f 100644 --- a/gainpro/gainpro.py +++ b/gainpro/gainpro.py @@ -637,18 +637,12 @@ def gain( if parameters_file is not None: params = Params.read_hyperparameters(parameters_file) missing_file = params.input - output_file = params.output ref_file = params.ref output_folder = params.output_folder - num_iterations = params.num_iterations - batch_size = params.batch_size - alpha = params.alpha + # Extract only variables that are used directly (not through params) miss_rate = params.miss_rate hint_rate = params.hint_rate - lr_D = params.lr_D - lr_G = params.lr_G override = params.override - output_all = params.output_all else: params = Params( missing_file, @@ -666,6 +660,19 @@ def gain( override, output_all, ) + + # Log training parameters + logger.info(f"Training parameters:") + logger.info(f" - Input file: {missing_file}") + logger.info(f" - Output file: {params.output}") + logger.info(f" - Iterations: {params.num_iterations}") + logger.info(f" - Batch size: {params.batch_size}") + logger.info(f" - Alpha: {params.alpha}") + logger.info(f" - Missing rate: {params.miss_rate}") + logger.info(f" - Hint rate: {params.hint_rate}") + logger.info(f" - Learning rate (D): {params.lr_D}") + logger.info(f" - Learning rate (G): {params.lr_G}") + logger.info(f" - Output folder: {output_folder}") # Create output folder if not os.path.exists(output_folder): diff --git a/scripts/multiple_runs.sh b/scripts/multiple_runs.sh index 361ab63..158eac0 100644 --- a/scripts/multiple_runs.sh +++ b/scripts/multiple_runs.sh @@ -2,12 +2,29 @@ # Script to run multiple imputation training runs # Usage: ./multiple_runs.sh [parameters_file] [num_runs] +set -euo pipefail # Exit on error, undefined vars, pipe failures + PARAMS_FILE=${1:-"./datasets/breast/parameters.json"} -NUM_RUNS=${2:-50} +NUM_RUNS_INPUT=${2:-50} + +# Validate NUM_RUNS is a positive integer +if ! [[ "$NUM_RUNS_INPUT" =~ ^[1-9][0-9]*$ ]]; then + echo "Error: num_runs must be a positive integer (got: $NUM_RUNS_INPUT)" >&2 + exit 1 +fi + +# Validate PARAMS_FILE exists +if [[ ! -f "$PARAMS_FILE" ]]; then + echo "Error: Parameters file not found: $PARAMS_FILE" >&2 + exit 1 +fi + +NUM_RUNS=$NUM_RUNS_INPUT echo "Running $NUM_RUNS imputation runs with parameters: $PARAMS_FILE" -for run in $(seq 1 $NUM_RUNS) +# Use C-style for loop to avoid command injection (safer than $(seq ...)) +for ((run=1; run<=NUM_RUNS; run++)) do echo "Running run = $run / $NUM_RUNS" gainpro gain --parameters "$PARAMS_FILE" From 9db437ea5eab7e8b8ea549480f5ce407bcb096b1 Mon Sep 17 00:00:00 2001 From: Yasset Perez-Riverol Date: Mon, 5 Jan 2026 15:09:41 +0000 Subject: [PATCH 24/26] Update MANIFEST.in Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> --- MANIFEST.in | 3 --- 1 file changed, 3 deletions(-) diff --git a/MANIFEST.in b/MANIFEST.in index 80b63e3..735d752 100644 --- a/MANIFEST.in +++ b/MANIFEST.in @@ -8,9 +8,6 @@ recursive-include configs *.json # Include datasets recursive-include datasets *.csv *.tsv *.json -# Include configs -recursive-include configs *.json - # Exclude tests and development files recursive-exclude tests * recursive-exclude use-case * From b2e3a31a703a125fe76fb2386cfd9536febc6c47 Mon Sep 17 00:00:00 2001 From: Yasset Perez-Riverol Date: Mon, 5 Jan 2026 15:13:35 +0000 Subject: [PATCH 25/26] another small change --- gainpro/gainpro.py | 1 - 1 file changed, 1 deletion(-) diff --git a/gainpro/gainpro.py b/gainpro/gainpro.py index 1d4218f..40d7fbf 100644 --- a/gainpro/gainpro.py +++ b/gainpro/gainpro.py @@ -738,7 +738,6 @@ def gain( logger.info("Training with reference dataset...") df_ref = pd.read_csv(ref_file) ref = df_ref.values - ref_header = df_ref.columns.tolist() if dim != ref.shape[1]: raise click.ClickException( From a014d8f6c31cbfd33eb42267872607d4c7638a6a Mon Sep 17 00:00:00 2001 From: Yasset Perez-Riverol Date: Mon, 5 Jan 2026 15:17:32 +0000 Subject: [PATCH 26/26] minor changes also. --- docs/source/GainPro.manager.rst | 2 +- tests/test_imputation_management.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/source/GainPro.manager.rst b/docs/source/GainPro.manager.rst index bd5d148..91f36d0 100644 --- a/docs/source/GainPro.manager.rst +++ b/docs/source/GainPro.manager.rst @@ -58,7 +58,7 @@ Methods 3. Saves the model locally. 4. Calls the model to perform imputation on the dataset located at dataset_path. -- medium_imputation(dataset): +- median_imputation(dataset): Performs median imputation on the dataset. diff --git a/tests/test_imputation_management.py b/tests/test_imputation_management.py index 0628bd6..616ec22 100644 --- a/tests/test_imputation_management.py +++ b/tests/test_imputation_management.py @@ -44,7 +44,7 @@ def test_add_existing_model(self): imputation_management.add_method("model_1", "model_1_function") self.assertEqual(imputation_management.dict_imputation_methods["model_1"], "model_1_function") - def test_add_exhisting_model(self): + def test_add_duplicate_model(self): """test to try adding model already known""" df_missing = pd.read_csv("breastMissing_20.csv") imputation_management = ImputationManagement("test_model", df_missing, "breastMissing_20.csv")