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)
