Make plotting compatible with notebook demo

src/climatebenchpress/compressor/plotting/plot_metrics.py

@@ -26,22 +26,27 @@
     "zfp-round": "ZFP-ROUND",
     "sz3": "SZ3",
     "bitround-pco-conservative-rel": "BitRound + PCO",
-    "bitround-conservative-rel": "BitRound + Zlib",
-    "stochround": "StochRound + Zlib",
+    "bitround-conservative-rel": "BitRound + Zstd",
+    "stochround": "StochRound + Zstd",
     "stochround-pco": "StochRound + PCO",
     "tthresh": "TTHRESH",
 }
 
 
 def plot_metrics(
-    basepath: Path = Path(), bound_names: list[str] = ["low", "mid", "high"]
+    basepath: Path = Path(),
+    data_loader_base_path: None | Path = None,
+    bound_names: list[str] = ["low", "mid", "high"],
 ):
     metrics_path = basepath / "metrics"
     plots_path = basepath / "plots"
+    datasets = (data_loader_base_path or basepath) / "datasets"
+    compressed_datasets = basepath / "compressed-datasets"
 
     df = pd.read_csv(metrics_path / "all_results.csv")
     plot_per_variable_metrics(
-        basepath=basepath,
+        datasets=datasets,
+        compressed_datasets=compressed_datasets,
         plots_path=plots_path,
         all_results=df,
     )
@@ -56,9 +61,9 @@ def plot_metrics(
     for metric in ["Relative MAE", "Relative DSSIM", "Relative MaxAbsError"]:
         plot_aggregated_rd_curve(
             normalized_df,
-            plots_path / f"rd_curve_{metric.lower().replace(' ', '_')}.pdf",
             compression_metric="Relative CR",
             distortion_metric=metric,
+            outfile=plots_path / f"rd_curve_{metric.lower().replace(' ', '_')}.pdf",
             agg="median",
             bound_names=bound_names,
         )
@@ -138,7 +143,10 @@ def get_normalizer(row):
 
 
 def plot_per_variable_metrics(
-    basepath: Path, plots_path: Path, all_results: pd.DataFrame
+    datasets: Path,
+    compressed_datasets: Path,
+    plots_path: Path,
+    all_results: pd.DataFrame,
 ):
     """Creates all the plots which only depend on a single variable."""
     for dataset in all_results["Dataset"].unique():
@@ -155,8 +163,9 @@ def plot_per_variable_metrics(
                     continue
                 plot_variable_rd_curve(
                     df[df["Variable"] == var],
-                    dataset_plots_path / f"{var}_compression_ratio_{metric_name}.pdf",
                     distortion_metric=dist_metric,
+                    outfile=dataset_plots_path
+                    / f"{var}_compression_ratio_{metric_name}.pdf",
                 )
 
             error_bounds = df[df["Variable"] == var]["Error Bound"].unique()
@@ -170,51 +179,49 @@ def plot_per_variable_metrics(
                 for comp in compressors:
                     print(f"Plotting {var} error for {comp}...")
                     plot_variable_error(
-                        basepath,
+                        datasets,
+                        compressed_datasets,
                         dataset,
                         err_bound,
                         comp,
                         var,
-                        err_bound_path / f"{var}_{comp}.png",
+                        outfile=err_bound_path / f"{var}_{comp}.png",
                     )
 
 
-def plot_variable_error(basepath, dataset_name, error_bound, compressor, var, outfile):
-    if outfile.exists():
+def plot_variable_error(
+    datasets: Path,
+    compressed_datasets: Path,
+    dataset_name: str,
+    error_bound: str,
+    compressor: str,
+    var: str,
+    outfile: None | Path = None,
+):
+    if outfile is not None and outfile.exists():
         # These plots can be quite expensive to generate, so we skip if they already exist.
         return
 
     compressed = (
-        basepath
-        / ".."
-        / "compressor"
-        / "compressed-datasets"
+        compressed_datasets
         / dataset_name
         / error_bound
         / compressor
         / "decompressed.zarr"
     )
-    input = (
-        basepath
-        / ".."
-        / "data-loader"
-        / "datasets"
-        / dataset_name
-        / "standardized.zarr"
-    )
+    input = datasets / dataset_name / "standardized.zarr"
 
     ds = xr.open_dataset(input, chunks=dict(), engine="zarr").compute()
     ds_new = xr.open_dataset(compressed, chunks=dict(), engine="zarr").compute()
-    ds, ds_new = ds[var], ds_new[var]
 
     plotter = PLOTTERS.get(dataset_name, None)
     if plotter:
-        plotter().plot(ds, ds_new, dataset_name, compressor, var, outfile)
+        plotter().plot(ds[var], ds_new[var], dataset_name, compressor, var, outfile)
     else:
         print(f"No plotter found for dataset {dataset_name}")
 
 
-def plot_variable_rd_curve(df, outfile, distortion_metric):
+def plot_variable_rd_curve(df, distortion_metric, outfile: None | Path = None):
     plt.figure(figsize=(8, 6))
     compressors = df["Compressor"].unique()
     for comp in compressors:
@@ -268,15 +275,17 @@ def plot_variable_rd_curve(df, outfile, distortion_metric):
     )
 
     plt.tight_layout()
-    plt.savefig(outfile, dpi=300)
+    if outfile is not None:
+        with outfile.open("wb") as f:
+            plt.savefig(f, dpi=300)
     plt.close()
 
 
 def plot_aggregated_rd_curve(
     normalized_df,
-    outfile,
     compression_metric,
     distortion_metric,
+    outfile: None | Path = None,
     agg="median",
     bound_names=["low", "mid", "high"],
 ):
@@ -367,11 +376,13 @@ def plot_aggregated_rd_curve(
         )
 
     plt.tight_layout()
-    plt.savefig(outfile, dpi=300)
+    if outfile is not None:
+        with outfile.open("wb") as f:
+            plt.savefig(f, dpi=300)
     plt.close()
 
 
-def plot_bound_violations(df, bound_names, outfile):
+def plot_bound_violations(df, bound_names, outfile: None | Path = None):
     fig, axs = plt.subplots(1, 3, figsize=(len(bound_names) * 6, 6), sharey=True)
 
     for i, bound_name in enumerate(bound_names):
@@ -401,7 +412,9 @@ def plot_bound_violations(df, bound_names, outfile):
             axs[i].set_ylabel("")
 
     fig.tight_layout()
-    fig.savefig(outfile, dpi=300)
+    if outfile is not None:
+        with outfile.open("wb") as f:
+            fig.savefig(f, dpi=300)
     plt.close()
 
 

src/climatebenchpress/compressor/plotting/variable_plotters.py

@@ -1,4 +1,5 @@
 from abc import ABC, abstractmethod
+from pathlib import Path
 
 import cartopy.crs as ccrs
 import matplotlib.colors as mcolors
@@ -16,7 +17,9 @@ def __init__(self):
     def plot_fields(self, fig, ax, ds, ds_new, dataset_name, var):
         pass
 
-    def plot(self, ds, ds_new, dataset_name, compressor, var, outfile):
+    def plot(
+        self, ds, ds_new, dataset_name, compressor, var, outfile: None | Path = None
+    ):
         fig, ax = plt.subplots(
             nrows=1,
             ncols=3,
@@ -32,7 +35,9 @@ def plot(self, ds, ds_new, dataset_name, compressor, var, outfile):
         ax[2].set_title("Error")
         fig.suptitle(f"{var} Error for {dataset_name} ({compressor})")
         fig.tight_layout()
-        fig.savefig(outfile, dpi=300)
+        if outfile is not None:
+            with outfile.open("wb") as f:
+                fig.savefig(f, dpi=300)
         plt.close()