c = row["$c$"] fig7_spectra( paths_sim[short_name], fig, ax, Fr, c, t_start=tmin, run_nb=run_nb, n_colors=len(df), ) if __name__ == "__main__": sns.set_palette("cubehelix", 3) matplotlib_rc(11) path_fig = exit_if_figure_exists(__file__) set_figsize(7, 3) fig, ax = pl.subplots(1, 2, sharex=True, sharey=True) df_w = load_df("df_w") df_3840 = df_w[df_w["$n$"] == 3840] df_7680 = df_w[df_w["$n$"] == 7680] sns.set_palette("cubehelix", 5) plot_df(df_3840, fig, ax[0]) sns.set_palette("cubehelix", 3) plot_df(df_7680, fig, ax[1]) for ax1 in ax: ax1.set_ylim(1e-2, 1e2)
fig, ax_b, tmin=tmin, run_nb=run_nb, key_var=("uy", "ux"), cache=test_mode, ax_inset=ax_inset, n_colors=len(df), ) if test_mode: break # fig12_atm(fig, ax_b) if __name__ == "__main__": matplotlib_rc(fontsize=fontsize) path_fig = exit_if_figure_exists(__file__) set_figsize(5, 4) fig, ax = pl.subplots(2, 2, sharey=False, sharex=False) df_w = load_df("df_w") df_3840 = df_w[df_w["$n$"] == 3840] df_7680 = df_w[df_w["$n$"] == 7680] ax_inset3 = None # _ax_inset(fig, '$r/L_f$', 0.325, 0.362) ax_inset7 = None # _ax_inset(fig, '$r:/L_f$', 0.775, 0.362) sns.set_palette("cubehelix", 5) plot_df(df_3840, fig, ax[:, 0], ax_inset3) sns.set_palette("cubehelix", 3) plot_df(df_7680, fig, ax[:, 1], ax_inset7)
#!/usr/bin/env python import os import getpass from pathlib import Path import matplotlib.pyplot as plt from fluidsim.util.console import profile as pf from fluiddyn.util import modification_date from base import matplotlib_rc, titles, curdir save = True force_make = False # ; force_make = True matplotlib_rc() if save else matplotlib_rc(dpi=150) textprops = dict(fontsize=10, family="monospace") figx = 5 # 9 # 20 / 2.54 figy = 2.1 # 2 # 6 / 2.54 root = Path("/tmp") / getpass.getuser() / "fluidsim-bench-results" / "profiles" if not os.path.exists(str(root)): raise FileNotFoundError("Run sync.py") patterns2d = [ (root / "beskow_1024x1024/").glob("*np=1_*fftw2d*"), (root / "beskow_1024x1024/").glob("*np=8*fftwmpi2d*"), ] patterns3d = [ (root / "beskow_128x128x128/").glob("*np=1_*fftw3d*"), (root / "beskow_128x128x128/").glob("*np=8*fftwmpi3d*"),
import matplotlib.pyplot as plt from base import matplotlib_rc from paths import load_df, exit_if_figure_exists from base_fig_energy import plot_energy matplotlib_rc(fontsize=10) path_fig = exit_if_figure_exists(__file__) df_w = load_df("df_lap") fig, ax = plt.subplots(1, 2, figsize=(6.5, 3)) plot_energy(df_w, fig, ax, N=[960, 1920, 2880, 3840, 7680], C=[10, 20, 40, 100, 200]) fig.tight_layout() fig.savefig(path_fig) fig.savefig(path_fig.replace(".png", ".pdf"))
#!/usr/bin/env python from pathlib import Path import matplotlib.pyplot as plt import numpy as np import bench_analysis as ba from base import matplotlib_rc from sync import path_fluidsim_bench_results matplotlib_rc() save = True root = Path(path_fluidsim_bench_results) / 'benchmarks' # pattern2d = root.glob('beskow_1024x1024') pattern2d = sorted(root.glob('beskow_?0??x????')) pattern3d = sorted(root.glob('beskow_*x*x*'))[::-1] def increase_lims(ax, fac=2): fac = np.array([1 / fac, fac]) xlim = np.array(ax.get_xlim()) * fac ylim = np.array(ax.get_ylim()) * fac ax.set_xlim(*xlim) ax.set_ylim(*ylim) def plot_fig(pattern, solver, output_file=None, exclude=[]): fig, axes = plt.subplots(1, 2) ax0, ax1 = axes.ravel() markers = ("x", ".") for ipath, path_dir in enumerate(pattern):
paths_sim[run], fig, ax, eps, Fr, tmin=tmin, run_nb=run_nb, n_colors=len(df), **kwargs, ) if "test" in kwargs and kwargs["test"] and run_nb == 1: break if __name__ == "__main__": matplotlib_rc(fontsize=9) path_fig = exit_if_figure_exists(__file__) fig, ax = plt.subplots(3, 2, figsize=(5, 6), sharex=True, sharey=False) # ax[0,0].set_title('$n=3840$') # ax[0,1].set_title('$n=7680$') for row in range(3): set_share_axes(ax[row, :], sharey=True) set_share_axes(ax, sharex=True) df_w = load_df("df_w") df_3840 = df_w[df_w["$n$"] == 3840] df_7680 = df_w[df_w["$n$"] == 7680] sns.set_palette("cubehelix", 5) plot_df(df_3840, fig, ax[:, 0]) sns.set_palette("cubehelix", 3)