diff --git a/code/piston/gcl_constant_solution/fom.py b/code/piston/gcl_constant_solution/fom.py new file mode 100644 index 0000000..9f657d8 --- /dev/null +++ b/code/piston/gcl_constant_solution/fom.py @@ -0,0 +1,323 @@ +from pprint import pprint + +import fenics +import matplotlib.pyplot as plt +import numpy as np +import ujson +from romtime.conventions import ( + BDF, + FIG_KWARGS, + Domain, + MassConservation, + PistonParameters, +) +from romtime.fom import OneDimensionalBurgers +from romtime.parameters import get_uniform_dist +from romtime.problems.gcl import define_constant_solution +from sklearn.model_selection import ParameterSampler +from tqdm import tqdm + +fenics.set_log_level(100) + +plt.set_cmap("viridis") + + +def plot_mass_conservation(ts, mass_change, outflow, title, save): + + fig, (ax_mass, ax_error) = plt.subplots( + nrows=2, ncols=1, sharex=True, gridspec_kw={"hspace": 0.35} + ) + + ax_mass.plot( + ts, + mass_change, + label="$\\frac{d}{dt} \\int \\rho dx$", + ) + ax_mass.plot( + ts, + outflow, + linestyle="--", + label="Outflow $(\\rho(0,t)u(0,t))$", + ) + ax_mass.legend(ncol=2, loc="center", bbox_to_anchor=(0.5, -0.175)) + ax_mass.grid(True) + ax_mass.set_title(title) + ax_mass.set_ylabel("Flow") + + #  ------------------------------------------------------------------------- + #  Mass error + mc = mass_change - outflow + mc = np.log10(np.abs(mc)) + + ax_error.plot( + ts, + mc, + color="black", + ) + + mc_mean = np.mean(mc) + ax_error.axhline(mc_mean, 0.1, 0.9, linestyle="dashdot", color="red", alpha=0.5) + + ax_error.grid(True) + ax_error.set_xlabel("t (s)") + ax_error.set_ylabel("Error (log10)") + + plt.savefig(save + ".png", **FIG_KWARGS) + plt.close() + + +def plot_probes(probes, save=None): + + locations = probes.columns + + fig, axes = plt.subplots( + nrows=len(locations), + ncols=1, + sharex=True, + sharey=True, + gridspec_kw={"hspace": 0.20}, + ) + + axes = axes.flatten() + ts = probes.index + + for idx_probe, loc in enumerate(locations): + values = probes[loc] + + ax = axes[idx_probe] + ax.plot(ts, values) + ax.grid(True) + # ax.set_title(label) + ax.set_ylabel(f"$u({loc}, t)$") + + plt.xlabel("u (m/s)") + plt.xlabel("t (s)") + + if save is None: + plt.show() + else: + plt.savefig(save + ".png", **FIG_KWARGS) + + plt.close() + + +def build_sampling_space(grid, num, rnd=None): + """Build sampling space according to filling linearity slope. + + Parameters + ---------- + num : int + rnd : [type], optional + [description], by default None + + Returns + ------- + [type] + [description] + """ + + print("Building linearity sampling space ...") + + piston_mach_space = compute_piston_mach_number_space(grid=grid, num=num) + + sampler = ParameterSampler( + param_distributions=grid, n_iter=int(1e4), random_state=rnd + ) + + samples = [] + domains = [ + (start, end) for start, end in zip(piston_mach_space, piston_mach_space[1:]) + ] + for sample in tqdm(sampler): + + piston_mach = compute_piston_mach(sample) + + remove = None + for domain in domains: + start, end = domain + + is_ge = piston_mach >= start + is_le = piston_mach <= end + inside = is_ge & is_le + + if inside: + + sample[PistonParameters.MACH_PISTON] = piston_mach + samples.append(sample) + + remove = domain + break + + if remove is not None: + domains.remove(remove) + print(len(domains)) + + if len(domains) == 0: + break + + # Add sorting so the idx makes sense + samples = sorted(samples, key=lambda x: x[PistonParameters.MACH_PISTON]) + + return samples + + +def compute_piston_mach(sample): + + A0 = PistonParameters.A0 + OMEGA = PistonParameters.OMEGA + DELTA = PistonParameters.DELTA + + mach = sample[DELTA] * sample[OMEGA] / sample[A0] + + return mach + + +def compute_piston_mach_number_space(grid, num): + + A0 = PistonParameters.A0 + OMEGA = PistonParameters.OMEGA + DELTA = PistonParameters.DELTA + + params = [A0, OMEGA, DELTA] + support = {} + for var in params: + _support = grid[var].support() + support[var] = {"min": min(_support), "max": max(_support)} + + # Less input into the system, maximum linearity + # mach_min = support[DELTA]["min"] * support[OMEGA]["min"] / support[A0]["max"] + mach_min = 0.35 + + # Maximum input into the system, minimum linearity + # forcing_max = support[DELTA]["max"] * support[OMEGA]["max"] / support[A0]["min"] + mach_max = 0.4 + + print(f"forcing : (min, max) = {mach_min}, {mach_max}") + + space = np.linspace(start=mach_min, stop=mach_max, num=num + 1) + + return space + + +def create_solver(L, nx, nt, tf, grid_base, which=None): + """Solve burgers equation problem. + + Parameters + ---------- + L : fenics.Constant + nx : int + nt : int + ft : float + parameters : tuple + + Returns + ------- + solver : romtime.OneDimensionalHeatEquationSolver + """ + + ( + domain, + boundary_conditions, + forcing_term, + u0, + Lt, + dLt_dt, + ) = define_constant_solution(L, nx, tf, nt, which) + + solver = OneDimensionalBurgers( + domain=domain, + dirichlet=boundary_conditions, + parameters=grid_base, + forcing_term=forcing_term, + degrees=1, + u0=u0, + exact_solution=None, + Lt=Lt, + dLt_dt=dLt_dt, + ) + + solver.setup() + + return solver + + +# ----------------------------------------------------------------------------- +# Parametrization +grid_params = { + PistonParameters.A0: { + "min": 18.0, + "max": 25.0, + }, + PistonParameters.OMEGA: { + "min": 15.0, + "max": 30.0, + }, + PistonParameters.DELTA: { + "min": 0.15, + "max": 0.3, + }, +} + +with open("grid_params.json", mode="w") as fp: + ujson.dump(grid_params, fp) + +# ----------------------------------------------------------------------------- +# Space-Time Domain +NX = 5e1 +NT = 5e2 + +# Create data structures +domain = { + Domain.L0: 1.0, + Domain.NX: int(NX), + Domain.NT: int(NT), + Domain.T: 0.75, +} + +which = "moving" + +solver = create_solver( + L=domain[Domain.L0], + nt=domain[Domain.NT], + nx=domain[Domain.NX], + tf=domain[Domain.T], + grid_base=grid_params, + which=which, +) + +grid = { + "a0": get_uniform_dist(**grid_params["a0"]), + "omega": get_uniform_dist(**grid_params["omega"]), + "delta": get_uniform_dist(**grid_params["delta"]), +} + + +N_SAMPLES = 1 + +mu = build_sampling_space(grid=grid, num=N_SAMPLES, rnd=42) +mu = mu[0] + +pprint(mu) + +with open(f"mu.json", mode="w") as fp: + ujson.dump(mu, fp) + + +NXs = [5e1, 1e2, 2e2, 3e2, 5e2, 1e3] +for nx in NXs: + + nx = int(nx) + + solver.domain[Domain.NX] = nx + solver.setup() + solver.update_parametrization(mu) + solver.BDF_SCHEME = BDF.ONE + solver.solve() + + name_probes = f"probes_FOM_nx_{nx}_{which}" + name_solutions = f"solutions_FOM_nx_{nx}_{which}" + + solver.dump_solutions(name_solutions) + probes = solver.save_probes(name=name_probes + ".csv") + + plot_probes(probes, save=name_probes) \ No newline at end of file diff --git a/code/piston/gcl_constant_solution/postprocess_fom.py b/code/piston/gcl_constant_solution/postprocess_fom.py new file mode 100644 index 0000000..d0163b2 --- /dev/null +++ b/code/piston/gcl_constant_solution/postprocess_fom.py @@ -0,0 +1,85 @@ +import matplotlib.pyplot as plt +import pandas as pd +import numpy as np +import seaborn as sns +import pickle + +from romtime.conventions import FIG_KWARGS + +from pathlib import Path + +sns.set_theme(context="paper") + +fixed_paths = Path(".").glob(pattern="*fixed.pkl") +moving_paths = Path(".").glob(pattern="*moving.pkl") + +func = lambda x: x.stem.split("_")[-1] +fixed_paths = sorted(fixed_paths, key=func) +moving_paths = sorted(moving_paths, key=func) + +COLS = ["fixed", "moving"] +FIXED = COLS[0] +MOVING = COLS[1] + +ts = np.linspace(0, 0.75, int(5e2)) +results_fixed = pd.DataFrame(index=ts) +results_moving = pd.DataFrame(index=ts) +NXs = [5e1, 1e2, 2e2, 3e2, 5e2, 1e3] +# NXs = [5e1, 1e2, 2e2] +for fixed, moving, nx in zip(fixed_paths, moving_paths, NXs): + + with open(fixed, mode="rb") as fp: + fom_fixed = pickle.load(fp) + with open(moving, mode="rb") as fp: + fom_moving = pickle.load(fp) + + mean_fixed = np.mean(fom_fixed.fom, axis=0) + mean_moving = np.mean(fom_moving.fom, axis=0) + + results_fixed[nx] = np.abs(mean_fixed) + results_moving[nx] = np.abs(mean_moving) + +results_moving = results_moving.clip(lower=0.1, upper=10) + +fig, (top, middle, bottom) = plt.subplots( + nrows=3, sharex=True, sharey=False, gridspec_kw={"hspace": 0.35} +) + +for nx in NXs: + nx = int(nx) + top.semilogy( + results_fixed.index, results_fixed[nx], label=f"$N_x$ = {nx}", linestyle="--" + ) + +for nx in NXs[:3]: + nx = int(nx) + middle.semilogy(results_moving.index, results_moving[nx], label=f"$N_x$ = {nx}") + +for nx in NXs: + nx = int(nx) + bottom.semilogy( + results_moving.index, results_moving[nx], label=f"$N_x$ = {nx}", alpha=0.65 + ) + +top.set_ylim(top=1.01) + +top.set_ylabel("Mean (FE Vector)") +bottom.set_xlabel("t (s)") + +top.grid(True) +bottom.grid(True) + +top.set_title("Fixed Domain") +middle.set_title("Moving Domain (First $N_x$)") +bottom.set_title("Moving Domain") + +bottom.legend(ncol=3) +middle.legend() +top.legend(ncol=3) + +# plt.show() +plt.savefig("mean_fe_comparison_constant_solution.png", **FIG_KWARGS) +plt.close() + +results_fixed.to_csv("results_fixed.csv") +results_moving.to_csv("results_moving.csv") diff --git a/code/piston/rb_certification/errors_estimator_rom_15_srom_16.pkl b/code/piston/rb_certification/errors_estimator_rom_15_srom_16.pkl index 5520d08..7404be6 100644 Binary files a/code/piston/rb_certification/errors_estimator_rom_15_srom_16.pkl and b/code/piston/rb_certification/errors_estimator_rom_15_srom_16.pkl differ diff --git a/code/piston/rb_certification/halfway_probes_comparison_rom_15_srom_16_online_0.csv b/code/piston/rb_certification/halfway_probes_comparison_rom_15_srom_16_online_0.csv index dbc1312..ff21dcf 100644 --- a/code/piston/rb_certification/halfway_probes_comparison_rom_15_srom_16_online_0.csv +++ b/code/piston/rb_certification/halfway_probes_comparison_rom_15_srom_16_online_0.csv @@ -1,49 +1,49 @@ ,fom,rom,srom,piston 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list(product(N_ROM, N_SROM)) combinations = sorted(combinations, key=lambda x: x[0] + x[1], reverse=True) diff --git a/code/piston/rb_certification/mass_conservation_rom_15_srom_16_online_rom_0.csv b/code/piston/rb_certification/mass_conservation_rom_15_srom_16_online_rom_0.csv index 93978bb..1f83952 100644 --- a/code/piston/rb_certification/mass_conservation_rom_15_srom_16_online_rom_0.csv +++ b/code/piston/rb_certification/mass_conservation_rom_15_srom_16_online_rom_0.csv @@ -1,501 +1,501 @@ ,which,timesteps,mass,mass_change,outflow -0,rom,0.002,1.0004009886744678,0.09070819362509042,5.717464092135269e-07 -1,rom,0.004,1.0005362144080283,0.04451753993539587,8.353311217144772e-06 -2,rom,0.006,1.0005790588342094,0.012318895677543296,4.458351331486911e-05 -3,rom,0.008,1.0005854899907385,-0.00041619366025758,6.700381450407273e-05 -4,rom,0.01,1.0005773940595684,-0.006027432254085419,0.00023613601978924358 -5,rom,0.012,1.0005613802617221,-0.00993056601200637,0.00038915993736102515 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a/code/piston/rb_certification/mass_conservation_rom_10_srom_15_online_rom_0.csv b/code/piston/rb_certification/tol_gmres_10/mass_conservation_rom_10_srom_15_online_rom_0.csv similarity index 100% rename from code/piston/rb_certification/mass_conservation_rom_10_srom_15_online_rom_0.csv rename to code/piston/rb_certification/tol_gmres_10/mass_conservation_rom_10_srom_15_online_rom_0.csv diff --git a/code/piston/rb_certification/mass_conservation_rom_10_srom_15_online_rom_0.png b/code/piston/rb_certification/tol_gmres_10/mass_conservation_rom_10_srom_15_online_rom_0.png similarity index 100% rename from code/piston/rb_certification/mass_conservation_rom_10_srom_15_online_rom_0.png rename to code/piston/rb_certification/tol_gmres_10/mass_conservation_rom_10_srom_15_online_rom_0.png diff --git a/code/piston/rb_certification/mass_conservation_rom_10_srom_20_online_rom_0.csv b/code/piston/rb_certification/tol_gmres_10/mass_conservation_rom_10_srom_20_online_rom_0.csv similarity index 100% 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