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Merge branch 'main' into tests/GravPotOutput

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Mayeul Aubin 2025-06-02 18:17:19 +02:00
commit d6222df77d
27 changed files with 1406 additions and 342 deletions
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21
.gitignore vendored
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@ -1,10 +1,3 @@
# Ignore feature_* directory (usually used as git worktree)
feature_*/
# Ignore extensions directory
extensions/*
!extensions/__init__.py
# Ignore some symbolic links
install
@ -14,17 +7,5 @@ install
.vscode/
*.pyc
__pycache__/
pysbmy.egg-info/
sbmy_control.egg-info/
*.h5
*.rng
*.gadget1
*.gadget2
*.gadget3
log.txt
testpdf.txt
tests/
params/
results/
slurm_logs/
slurm_scripts/
work/

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__init__.py
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176
analysis/slices.py
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@ -1,176 +0,0 @@
import numpy as np
import sys
sys.path.append('/home/aubin/Simbelmyne/sbmy_control/')
from cosmo_params import register_arguments_cosmo, parse_arguments_cosmo
fs = 18
fs_titles = fs -4
def plot_imshow_with_reference( data_list,
reference=None,
titles=None,
vmin=None,
vmax=None,
L=None,
cmap='viridis'):
"""
Plot the imshow of a list of 2D arrays with two rows: one for the data itself,
one for the data compared to a reference. Each row will have a common colorbar.
Parameters:
- data_list: list of 2D arrays to be plotted
- reference: 2D array to be used as reference for comparison
- titles: list of titles for each subplot
- cmap: colormap to be used for plotting
"""
import matplotlib.pyplot as plt
if titles is None:
titles = [None for f in data_list]
if L is None:
L = [len(data) for data in data_list]
elif isinstance(L, int) or isinstance(L, float):
L = [L for data in data_list]
sep = 10 if L[0] < 50 else 20 if L[0] < 200 else 100
ticks = [np.arange(0, l+1, sep)*len(dat)/l for l, dat in zip(L,data_list)]
tick_labels = [np.arange(0, l+1, sep) for l in L]
def score(data, reference):
return np.linalg.norm(data-reference)/np.linalg.norm(reference)
n = len(data_list)
fig, axes = plt.subplots(1 if reference is None else 2, n, figsize=(5 * n, 5 if reference is None else 5*2), dpi=max(500, data_list[0].shape[0]//2))
if vmin is None or vmax is None:
vmin = min(np.quantile(data,0.01) for data in data_list)
vmax = max(np.quantile(data,0.99) for data in data_list)
if reference is not None:
vmin_diff = min(np.quantile((data-reference),0.01) for data in data_list)
vmax_diff = max(np.quantile((data-reference),0.99) for data in data_list)
else:
vmin_diff = vmin
vmax_diff = vmax
if reference is not None:
# Plot the data itself
for i, data in enumerate(data_list):
im = axes[0, i].imshow(data, cmap=cmap, origin='lower', vmin=vmin, vmax=vmax)
axes[0, i].set_title(titles[i], fontsize=fs_titles)
axes[0, i].set_xticks(ticks[i])
axes[0, i].set_yticks(ticks[i])
axes[0, i].set_xticklabels(tick_labels[i])
axes[0, i].set_yticklabels(tick_labels[i])
axes[0, i].set_xlabel('Mpc/h')
fig.colorbar(im, ax=axes[0, :], orientation='vertical')
# Plot the data compared to the reference
for i, data in enumerate(data_list):
im = axes[1, i].imshow(data - reference, cmap=cmap, origin='lower', vmin=vmin_diff, vmax=vmax_diff)
axes[1, i].set_title(f'{titles[i]} - Reference', fontsize=fs_titles)
axes[1, i].set_xticks(ticks[i])
axes[1, i].set_yticks(ticks[i])
axes[1, i].set_xticklabels(tick_labels[i])
axes[1, i].set_yticklabels(tick_labels[i])
axes[1, i].set_xlabel('Mpc/h')
fig.colorbar(im, ax=axes[1, :], orientation='vertical')
# Add the score on the plots
for i, data in enumerate(data_list):
axes[1, i].text(0.5, 0.9, f"Score: {score(data, reference):.2e}", fontsize=10, transform=axes[1, i].transAxes, color='white')
# plt.tight_layout()
else:
if len(data_list) == 1:
data_list = data_list[0]
im = axes.imshow(data_list, cmap=cmap, origin='lower', vmin=vmin, vmax=vmax)
axes.set_title(titles[0], fontsize=fs_titles)
axes.set_xticks(ticks[0])
axes.set_yticks(ticks[0])
axes.set_xticklabels(tick_labels[0])
axes.set_yticklabels(tick_labels[0])
axes.set_xlabel('Mpc/h')
fig.colorbar(im, ax=axes, orientation='vertical')
else:
for i, data in enumerate(data_list):
im = axes[i].imshow(data, cmap=cmap, origin='lower', vmin=vmin, vmax=vmax)
axes[i].set_title(titles[i], fontsize=fs_titles)
axes[i].set_xticks(ticks[i])
axes[i].set_yticks(ticks[i])
axes[i].set_xticklabels(tick_labels[i])
axes[i].set_yticklabels(tick_labels[i])
axes[i].set_xlabel('Mpc/h')
fig.colorbar(im, ax=axes[:], orientation='vertical')
return fig, axes
if __name__ == "__main__":
from argparse import ArgumentParser
parser = ArgumentParser(description='Comparisons of fields slices.')
parser.add_argument('-a','--axis', type=int, default=0, help='Axis along which the slices will be taken.')
parser.add_argument('-i','--index', type=int, default=None, help='Index of the slice along the axis.')
parser.add_argument('-d', '--directory', type=str, required=True, help='Directory containing the fields files.')
parser.add_argument('-ref', '--reference', type=str, default=None, help='Reference field file.')
parser.add_argument('-f', '--filenames', type=str, nargs='+', required=True, help='Field files to be plotted.')
parser.add_argument('-o', '--output', type=str, default=None, help='Output plot file name.')
parser.add_argument('-l', '--labels', type=str, nargs='+', default=None, help='Labels for each field.')
parser.add_argument('-c', '--cmap', type=str, default='viridis', help='Colormap to be used for plotting.')
parser.add_argument('-vmin', type=float, default=None, help='Minimum value for the colorbar.')
parser.add_argument('-vmax', type=float, default=None, help='Maximum value for the colorbar.')
parser.add_argument('-t', '--title', type=str, default=None, help='Title for the plot.')
parser.add_argument('-log','--log_scale', action='store_true', help='Use log scale for the data.')
register_arguments_cosmo(parser)
args = parser.parse_args()
from pysbmy.field import read_field
from pysbmy.cosmology import d_plus
ref_field = read_field(args.directory+args.reference) if args.reference is not None else None
fields = [read_field(args.directory+f) for f in args.filenames]
if args.index is None:
index = fields[0].N0//2
else:
index=args.index
# args.labels=[f"a={f.time:.2f}" for f in fields]
L = [f.L0 for f in fields]
match args.axis:
case 0 | 'x':
reference = ref_field.data[index,:,:] if ref_field is not None else None
fields = [f.data[index,:,:] for f in fields]
# reference = ref_field.data[index,:,:]/d_plus(1e-3,ref_field.time,parse_arguments_cosmo(args))
# fields = [f.data[index,:,:]/d_plus(1e-3,f.time,parse_arguments_cosmo(args)) for f in fields]
# reference = ref_field.data[index,:,:]/d_plus(1e-3,0.05,parse_arguments_cosmo(args))
# fields = [f.data[index,:,:]/d_plus(1e-3,time,parse_arguments_cosmo(args)) for f,time in zip(fields,[0.05, 1.0])]
case 1 | 'y':
reference = ref_field.data[:,index,:] if ref_field is not None else None
fields = [f.data[:,index,:] for f in fields]
case 2 | 'z':
reference = ref_field.data[:,:,index] if ref_field is not None else None
fields = [f.data[:,:,index] for f in fields]
case _:
raise ValueError(f"Wrong axis provided : {args.axis}")
if args.log_scale:
reference = np.log10(2.+reference) if ref_field is not None else None
fields = [np.log10(2.+f) for f in fields]
fig, axes = plot_imshow_with_reference(fields,reference,args.labels, vmin=args.vmin, vmax=args.vmax,cmap=args.cmap, L=L)
fig.suptitle(args.title)
if args.output is not None:
fig.savefig(args.output)
else:
fig.savefig(args.directory+'slices.png')

34
ICs.py → sbmy_control/ICs.py
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@ -3,9 +3,9 @@ def main_ICs(parsed_args):
"""
Main function for the initial conditions generator.
"""
from args_main import parse_arguments_main
from parameters_card import parse_arguments_card_for_ICs
from low_level import print_starting_module, print_message, print_ending_module
from .args_main import parse_arguments_main
from .parameters_card import parse_arguments_card_for_ICs
from .low_level import print_starting_module, print_message, print_ending_module
from os.path import isfile
main_dict = parse_arguments_main(parsed_args)
@ -52,10 +52,10 @@ def main_ICs(parsed_args):
def ICs_monofonic(parsed_args):
from monofonic import main_monofonic
from .monofonic import main_monofonic
from os.path import isfile
from low_level import print_message
from parameters_monofonic import parse_arguments_monofonic
from .low_level import print_message
from .parameters_monofonic import parse_arguments_monofonic
monofonic_dict = parse_arguments_monofonic(parsed_args)
@ -67,9 +67,9 @@ def ICs_monofonic(parsed_args):
def ICs_sbmy(parsed_args):
from low_level import print_starting_module, print_message
from .low_level import print_starting_module, print_message
from os.path import isfile
from parameters_card import parse_arguments_card_for_ICs
from .parameters_card import parse_arguments_card_for_ICs
print_starting_module("sbmy IC", verbose=parsed_args.verbose)
@ -99,14 +99,14 @@ def ICs_sbmy(parsed_args):
def create_sbmy_power_spectrum_file(parsed_args, card_dict, power_spectrum_file):
from cosmo_params import parse_arguments_cosmo
from .cosmo_params import parse_arguments_cosmo
from pysbmy.power import PowerSpectrum
cosmo_dict = parse_arguments_cosmo(parsed_args)
if parsed_args.verbose < 2:
from io import BytesIO
from low_level import stdout_redirector, stderr_redirector
from .low_level import stdout_redirector, stderr_redirector
f = BytesIO()
g = BytesIO()
with stdout_redirector(f):
@ -138,7 +138,7 @@ def create_sbmy_power_spectrum_file(parsed_args, card_dict, power_spectrum_file)
def create_sbmy_white_noise_field(parsed_args, card_dict, white_noise_field_file):
import numpy as np
from gc import collect
from low_level import print_message
from .low_level import print_message
from pysbmy.field import BaseField
print_message(f"Seed: {parsed_args.seed}", 3, "sbmy IC", verbose=parsed_args.verbose)
@ -161,7 +161,7 @@ def create_sbmy_white_noise_field(parsed_args, card_dict, white_noise_field_file
if parsed_args.verbose < 2:
from io import BytesIO
from low_level import stdout_redirector, stderr_redirector
from .low_level import stdout_redirector, stderr_redirector
f = BytesIO()
g = BytesIO()
with stdout_redirector(f):
@ -175,11 +175,11 @@ def create_sbmy_white_noise_field(parsed_args, card_dict, white_noise_field_file
if __name__ == "__main__":
from argparse import ArgumentParser
from args_main import register_arguments_main
from parameters_card import register_arguments_card_for_ICs
from cosmo_params import register_arguments_cosmo
from parameters_monofonic import register_arguments_monofonic
from slurm_submission import register_arguments_slurm
from .args_main import register_arguments_main
from .parameters_card import register_arguments_card_for_ICs
from .cosmo_params import register_arguments_cosmo
from .parameters_monofonic import register_arguments_monofonic
from .slurm_submission import register_arguments_slurm
parser = ArgumentParser(description="Generate initial conditions for a Simbelmyne simulation.")
# TODO: reduce the volume of arguments

0
analysis/__init__.py → sbmy_control/__init__.py
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0
sbmy_control/analysis/__init__.py Normal file
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36
sbmy_control/analysis/colormaps.py Normal file
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@ -0,0 +1,36 @@
def register_colormaps(colormaps):
# Register cmasher
try:
import cmasher as cma
for name, cmap in cma.cm.cmap_d.items():
try:
colormaps.register(name=name, cmap=cmap)
except ValueError:
pass
except ImportError:
pass
# Register cmocean
try:
import cmocean as cmo
for name, cmap in cmo.cm.cmap_d.items():
try:
colormaps.register(name=name, cmap=cmap)
except ValueError:
pass
except ImportError:
pass
# Register cmcrameri
try:
import cmcrameri as cmc
for name, cmap in cmc.cm.cmaps.items():
try:
colormaps.register(name=name, cmap=cmap)
except ValueError:
pass
except ImportError:
pass

84
analysis/power_spectrum.py → sbmy_control/analysis/power_spectrum.py
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@ -1,10 +1,29 @@
import numpy as np
import os
kmin = 1e-1
kmax = 2e0
Nk = 50
AliasingCorr=False
def crop_field(field, Ncrop):
if Ncrop is None or Ncrop == 0:
return
elif Ncrop > 0:
field.data = field.data[Ncrop:-Ncrop, Ncrop:-Ncrop, Ncrop:-Ncrop]
d0 = field.L0/field.N0
d1 = field.L1/field.N1
d2 = field.L2/field.N2
field.N0 -= 2*Ncrop
field.N1 -= 2*Ncrop
field.N2 -= 2*Ncrop
field.L0 = field.N0*d0
field.L1 = field.N1*d1
field.L2 = field.N2*d2
def get_power_spectrum(field, kmin=kmin, kmax=kmax, Nk=Nk, G=None):
from pysbmy.power import PowerSpectrum
from pysbmy.fft import FourierGrid
@ -15,10 +34,10 @@ def get_power_spectrum(field, kmin=kmin, kmax=kmax, Nk=Nk, G=None):
field.L0,
field.L1,
field.L2,
field.N0,
field.N1,
field.N2,
k_modes=np.concat([PowerSpectrum(field.L0,field.L1,field.L2,field.N0,field.N1,field.N2,).FourierGrid.k_modes[:10],np.logspace(
int(field.N0),
int(field.N1),
int(field.N2),
k_modes=np.concat([PowerSpectrum(field.L0,field.L1,field.L2,int(field.N0),int(field.N1),int(field.N2),).FourierGrid.k_modes[:10],np.logspace(
np.log10(kmin),
np.log10(kmax),
Nk,
@ -43,10 +62,10 @@ def get_cross_correlations(field_A, field_B, kmin=kmin, kmax=kmax, Nk=Nk, G=None
field_A.L0,
field_A.L1,
field_A.L2,
field_A.N0,
field_A.N1,
field_A.N2,
k_modes=np.concat([PowerSpectrum(field_A.L0,field_A.L1,field_A.L2,field_A.N0,field_A.N1,field_A.N2,).FourierGrid.k_modes[:10],np.logspace(
int(field_A.N0),
int(field_A.N1),
int(field_A.N2),
k_modes=np.concat([PowerSpectrum(field_A.L0,field_A.L1,field_A.L2,int(field_A.N0),int(field_A.N1),int(field_A.N2),).FourierGrid.k_modes[:10],np.logspace(
np.log10(kmin),
np.log10(kmax),
Nk,
@ -91,7 +110,8 @@ def plot_power_spectra(filenames,
figsize=(8,4),
dpi=300,
ax=None,
fig=None,):
fig=None,
Ncrop=None,):
import matplotlib.pyplot as plt
from pysbmy.field import read_field
@ -110,6 +130,7 @@ def plot_power_spectra(filenames,
for i, filename in enumerate(filenames):
field = read_field(filename)
crop_field(field, Ncrop)
_, G, k, _ = add_power_spectrum_to_plot(ax=ax,
field=field,
Pk_ref=Pk_ref,
@ -128,7 +149,7 @@ def plot_power_spectra(filenames,
ax.set_ylim(ylims)
if yticks is not None:
ax.set_yticks(yticks)
ax.set_xlabel(r'$k$ [$h/\mathrm{Mpc}$]', labelpad=-10)
ax.set_xlabel(r'$k$ [$h/\mathrm{Mpc}$]', labelpad=-0)
if Pk_ref is not None:
ax.set_ylabel(r'$P(k)/P_\mathrm{ref}(k)$')
@ -163,7 +184,9 @@ def plot_cross_correlations(filenames_A,
figsize=(8,4),
dpi=300,
ax=None,
fig=None,):
fig=None,
Ncrop=None,
):
import matplotlib.pyplot as plt
from pysbmy.field import read_field
@ -181,9 +204,11 @@ def plot_cross_correlations(filenames_A,
markers = [None for f in filenames_A]
field_B = read_field(filename_B)
crop_field(field_B, Ncrop)
for i, filename_A in enumerate(filenames_A):
field_A = read_field(filename_A)
crop_field(field_A, Ncrop)
_, G, k, _ = add_cross_correlations_to_plot(ax=ax,
field_A=field_A,
field_B=field_B,
@ -202,7 +227,7 @@ def plot_cross_correlations(filenames_A,
ax.set_ylim(ylims)
if yticks is not None:
ax.set_yticks(yticks)
ax.set_xlabel(r'$k$ [$h/\mathrm{Mpc}$]', labelpad=-10)
ax.set_xlabel(r'$k$ [$h/\mathrm{Mpc}$]', labelpad=-0)
ax.set_ylabel('$R(k)$')
if bound1 is not None:
@ -238,13 +263,15 @@ def get_ylims_and_yticks(ylims):
return ylims, yticks
if __name__ == "__main__":
def console_main():
from argparse import ArgumentParser
parser = ArgumentParser(description='Plot power spectra of fields')
parser.add_argument('-ps', '--power_spectrum', action='store_true', help='Plot power spectra.')
parser.add_argument('-cc', '--cross_correlation', action='store_true', help='Plot cross correlations.')
parser.add_argument('-d', '--directory', type=str, required=True, help='Directory containing the fields files.')
parser.add_argument('-d', '--directory', type=str, default='./', help='Directory containing the fields files.')
parser.add_argument('-ref', '--reference', type=str, default=None, help='Reference field file.')
parser.add_argument('-f', '--filenames', type=str, nargs='+', required=True, help='Field files to be plotted.')
parser.add_argument('-o', '--output', type=str, default=None, help='Output plot file name.')
@ -255,6 +282,7 @@ if __name__ == "__main__":
parser.add_argument('-t','--title', type=str, default=None, help='Title of the plot.')
parser.add_argument('-yrp', '--ylim_power', type=float, nargs=2, default=[0.9,1.1], help='Y-axis limits.')
parser.add_argument('-yrc', '--ylim_corr', type=float, nargs=2, default=[0.99,1.001], help='Y-axis limits.')
parser.add_argument('--crop', type=int, default=None, help='Remove the outter N pixels of the fields.')
args = parser.parse_args()
@ -262,9 +290,15 @@ if __name__ == "__main__":
print('You must choose between power_spectrum and cross_correlation.')
exit()
for _k,f in enumerate(args.filenames):
if not os.path.exists(args.directory+f):
raise FileNotFoundError(f"File {args.directory+f} does not exist.")
if args.reference is not None:
from pysbmy.field import read_field
G, _, Pk_ref = get_power_spectrum(read_field(args.directory+args.reference), kmin=kmin, kmax=kmax, Nk=Nk)
F_ref = read_field(args.directory+args.reference)
crop_field(F_ref, args.crop)
G, _, Pk_ref = get_power_spectrum(F_ref, kmin=kmin, kmax=kmax, Nk=Nk)
else:
Pk_ref = None
G = None
@ -279,6 +313,7 @@ if __name__ == "__main__":
if args.power_spectrum and args.cross_correlation:
import matplotlib.pyplot as plt
fig, axes = plt.subplots(2, 1, figsize=(8,8))
fig.subplots_adjust(hspace=0.3)
plot_power_spectra(filenames=filenames,
labels=args.labels,
colors=args.colors,
@ -294,7 +329,9 @@ if __name__ == "__main__":
kmax=kmax,
Nk=Nk,
ax=axes[0],
fig=fig)
fig=fig,
Ncrop=args.crop,
)
plot_cross_correlations(filenames_A=filenames,
filename_B=args.directory+args.reference,
@ -311,7 +348,9 @@ if __name__ == "__main__":
kmax=kmax,
Nk=Nk,
ax=axes[1],
fig=fig)
fig=fig,
Ncrop=args.crop,
)
axes[1].legend(loc='lower left')
axes[0].set_title("Power Spectrum")
@ -334,7 +373,9 @@ if __name__ == "__main__":
bound2=0.02,
kmin=kmin,
kmax=kmax,
Nk=Nk)
Nk=Nk,
Ncrop=args.crop,
)
ax.legend()
if args.title is not None:
ax.set_title(args.title)
@ -353,7 +394,9 @@ if __name__ == "__main__":
bound2=0.002,
kmin=kmin,
kmax=kmax,
Nk=Nk)
Nk=Nk,
Ncrop=args.crop,
)
ax.legend(loc='lower left')
if args.title is not None:
ax.set_title(args.title)
@ -364,3 +407,6 @@ if __name__ == "__main__":
fig.savefig(args.directory+'power_spectrum.png')
if __name__ == "__main__":
console_main()

228
sbmy_control/analysis/slices.py Executable file
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@ -0,0 +1,228 @@
import numpy as np
import sys
import os
fs = 18
fs_titles = fs - 4
def add_ax_ticks(ax, ticks, tick_labels):
from matplotlib import ticker
ax.set_xticks(ticks)
ax.set_yticks(ticks)
ax.set_xticklabels([int(t) for t in tick_labels])
ax.set_yticklabels([int(t) for t in tick_labels])
ax.set_xlabel('Mpc/h')
# ax.xaxis.set_major_formatter(ticker.FormatStrFormatter('%d')) # Does not work
# ax.yaxis.set_major_formatter(ticker.FormatStrFormatter('%d'))
def plot_imshow_with_reference( data_list,
reference=None,
titles=None,
vmin=None,
vmax=None,
L=None,
cmap='viridis',
cmap_diff='PuOr',
ref_label="Reference"):
"""
Plot the imshow of a list of 2D arrays with two rows: one for the data itself,
one for the data compared to a reference. Each row will have a common colorbar.
Parameters:
- data_list: list of 2D arrays to be plotted
- reference: 2D array to be used as reference for comparison
- titles: list of titles for each subplot
- cmap: colormap to be used for plotting
"""
import matplotlib.pyplot as plt
from sbmy_control.analysis.colormaps import register_colormaps
register_colormaps(plt.colormaps)
if titles is None:
titles = [None for f in data_list]
if L is None:
L = [len(data) for data in data_list]
elif isinstance(L, int) or isinstance(L, float):
L = [L for data in data_list]
sep = 10 if L[0] < 50 else 20 if L[0] < 100 else 50 if L[0]<250 else 100 if L[0] < 500 else 200 if L[0] < 1000 else 500 if L[0] < 2500 else 1000
ticks = [np.arange(0, l+1, sep)*len(dat)/l for l, dat in zip(L,data_list)]
tick_labels = [np.arange(0, l+1, sep) for l in L]
def score(data, reference):
return np.linalg.norm(data-reference)/np.linalg.norm(reference)
n = len(data_list)
fig, axes = plt.subplots(1 if reference is None else 2, n, figsize=(5 * n, 5 if reference is None else 5*2), dpi=max(500, data_list[0].shape[0]//2), squeeze = False)
if vmin is None or vmax is None:
vmin = min(np.quantile(data,0.01) for data in data_list)
vmax = max(np.quantile(data,0.99) for data in data_list)
if reference is not None:
vmin_diff = min(np.quantile((data-reference),0.01) for data in data_list)
vmax_diff = max(np.quantile((data-reference),0.99) for data in data_list)
vmin_diff = min(vmin_diff, -vmax_diff)
vmax_diff = -vmin_diff
else:
vmin_diff = vmin
vmax_diff = vmax
# Plot the data itself
for i, data in enumerate(data_list):
im = axes[0, i].imshow(data, cmap=cmap, origin='lower', vmin=vmin, vmax=vmax)
axes[0, i].set_title(titles[i], fontsize=fs_titles)
add_ax_ticks(axes[0, i], ticks[i], tick_labels[i])
fig.colorbar(im, ax=axes[0, :], orientation='vertical')
if reference is not None:
# Plot the data compared to the reference
for i, data in enumerate(data_list):
im = axes[1, i].imshow(data - reference, cmap=cmap_diff, origin='lower', vmin=vmin_diff, vmax=vmax_diff)
axes[1, i].set_title(f'{titles[i]} - {ref_label}', fontsize=fs_titles)
add_ax_ticks(axes[1, i], ticks[i], tick_labels[i])
fig.colorbar(im, ax=axes[1, :], orientation='vertical')
# Add the score on the plots
for i, data in enumerate(data_list):
axes[1, i].text(0.5, 0.9, f"RMS: {score(data, reference):.2e}", fontsize=10, transform=axes[1, i].transAxes, color='black')
# plt.tight_layout()
return fig, axes
def plot_imshow_diff(data_list,
reference,
titles,
vmin=None,
vmax=None,
L=None,
cmap='viridis',
ref_label="Reference"):
import matplotlib.pyplot as plt
from sbmy_control.analysis.colormapss import register_colormaps
register_colormaps(plt.colormaps)
if reference is None:
raise ValueError("Reference field is None")
if titles is None:
titles = [None for f in data_list]
if L is None:
L = [len(data) for data in data_list]
elif isinstance(L, int) or isinstance(L, float):
L = [L for data in data_list]
sep = 10 if L[0] < 50 else 20 if L[0] < 100 else 50 if L[0]<250 else 100 if L[0] < 500 else 200 if L[0] < 1000 else 500 if L[0] < 2500 else 1000
ticks = [np.arange(0, l+1, sep)*len(dat)/l for l, dat in zip(L,data_list)]
tick_labels = [np.arange(0, l+1, sep) for l in L]
def score(data, reference):
return np.linalg.norm(data-reference)/np.linalg.norm(reference)
n = len(data_list)
fig, axes = plt.subplots(1, n, figsize=(5 * n, 5), dpi=max(500, data_list[0].shape[0]//2), squeeze = False)
if vmin is None or vmax is None:
vmin = min(np.quantile(data-reference,0.01) for data in data_list)
vmax = max(np.quantile(data-reference,0.99) for data in data_list)
vmin = min(vmin, -vmax)
vmax = -vmin
# Plot the data compared to the reference
for i, data in enumerate(data_list):
im = axes[0, i].imshow(data - reference, cmap=cmap, origin='lower', vmin=vmin, vmax=vmax)
axes[0, i].set_title(f'{titles[i]} - {ref_label}', fontsize=fs_titles)
add_ax_ticks(axes[0, i], ticks[i], tick_labels[i])
fig.colorbar(im, ax=axes[0, :], orientation='vertical')
return fig, axes
def console_main():
from argparse import ArgumentParser
parser = ArgumentParser(description='Comparisons of fields slices.')
parser.add_argument('-a','--axis', type=int, default=0, help='Axis along which the slices will be taken.')
parser.add_argument('-i','--index', type=int, default=None, help='Index of the slice along the axis.')
parser.add_argument('-d', '--directory', type=str, default='./', help='Directory containing the fields files.')
parser.add_argument('-ref', '--reference', type=str, default=None, help='Reference field file.')
parser.add_argument('-f', '--filenames', type=str, nargs='+', required=True, help='Field files to be plotted.')
parser.add_argument('-o', '--output', type=str, default=None, help='Output plot file name.')
parser.add_argument('-l', '--labels', type=str, nargs='+', default=None, help='Labels for each field.')
parser.add_argument('-c', '--cmap', type=str, default='viridis', help='Colormap to be used for plotting.')
parser.add_argument('-vmin', type=float, default=None, help='Minimum value for the colorbar.')
parser.add_argument('-vmax', type=float, default=None, help='Maximum value for the colorbar.')
parser.add_argument('-t', '--title', type=str, default=None, help='Title for the plot.')
parser.add_argument('-log','--log_scale', action='store_true', help='Use log scale for the data.')
parser.add_argument('--diff', action='store_true', help='Plot only the difference with the reference field.')
parser.add_argument('--ref_label', type=str, default='Reference', help='Label for the reference field.')
parser.add_argument('--cmap_diff', type=str, default='PuOr', help='Colormap to be used for the difference plot.')
args = parser.parse_args()
from pysbmy.field import read_field
ref_label = args.ref_label
ref_field = read_field(args.directory+args.reference) if args.reference is not None else None
fields = []
for k,f in enumerate(args.filenames):
if not os.path.exists(args.directory+f):
raise FileNotFoundError(f"File {args.directory+f} does not exist.")
if args.reference is not None and f == args.reference:
fields.append(ref_field) # Simply copy the reference field instead of reading it again
if args.labels is not None:
ref_label = args.labels[k] # Use the label of the field as the reference label
else:
fields.append(read_field(args.directory+f))
if args.index is None:
index = fields[0].N0//2
else:
index=args.index
# args.labels=[f"a={f.time:.2f}" for f in fields]
L = [f.L0 for f in fields]
match args.axis:
case 0 | 'x':
reference = ref_field.data[index,:,:] if ref_field is not None else None
fields = [f.data[index,:,:] for f in fields]
case 1 | 'y':
reference = ref_field.data[:,index,:] if ref_field is not None else None
fields = [f.data[:,index,:] for f in fields]
case 2 | 'z':
reference = ref_field.data[:,:,index] if ref_field is not None else None
fields = [f.data[:,:,index] for f in fields]
case _:
raise ValueError(f"Wrong axis provided : {args.axis}")
if args.log_scale:
reference = np.log10(2.+reference) if ref_field is not None else None
fields = [np.log10(2.+f) for f in fields]
if args.diff:
fig, axes = plot_imshow_diff(fields,reference,args.labels, vmin=args.vmin, vmax=args.vmax,cmap=args.cmap_diff, L=L, ref_label=ref_label)
else:
fig, axes = plot_imshow_with_reference(fields,reference,args.labels, vmin=args.vmin, vmax=args.vmax,cmap=args.cmap, L=L, ref_label=ref_label, cmap_diff=args.cmap_diff)
fig.suptitle(args.title)
if args.output is not None:
fig.savefig(args.output,bbox_inches='tight')
else:
fig.savefig(args.directory+'slices.jpg',bbox_inches='tight')
if __name__ == "__main__":
console_main()

0
args_main.py → sbmy_control/args_main.py
View file

0
cosmo_params.py → sbmy_control/cosmo_params.py
View file

3
low_level.py → sbmy_control/low_level.py
View file

@ -225,6 +225,8 @@ def get_progress_from_logfile(filename):
pass
elif "Fatal" in line or "Error" in line:
return -1, -1
elif "Everything done successfully, exiting." in line:
current_operation = total_operations
return current_operation, total_operations
@ -237,7 +239,6 @@ def progress_bar_from_logfile(filename:str, desc:str="", verbose:int=1, **kwargs
k=0
limit=600
update_interval=0.2
sleep(2) # Wait for the process to be launched, and for the previous log file to be overwritten if necessary.
wait_until_file_exists(filename, verbose=verbose, limit=limit)
current_operation, total_operations = get_progress_from_logfile(filename)
previous_operation = 0

68
main.py → sbmy_control/main.py
View file

@ -1,9 +1,9 @@
def main(parsed_args):
from low_level import print_starting_module, print_message, print_ending_module, wait_until_file_exists
from .low_level import print_starting_module, print_message, print_ending_module, wait_until_file_exists
from os.path import isfile
from args_main import parse_arguments_main
from .args_main import parse_arguments_main
print_starting_module("control", verbose=parsed_args.verbose)
main_dict = parse_arguments_main(parsed_args)
@ -12,22 +12,22 @@ def main(parsed_args):
case "ICs" | "InitialConditions" | "InitialConditionsGenerator" | "ICsGenerator" | "ICsGen" | "ini":
print_message("Running initial conditions generator.", 1, "control", verbose=parsed_args.verbose)
from ICs import main_ICs
from .ICs import main_ICs
main_ICs(parsed_args)
print_message("Initial conditions generator finished.", 1, "control", verbose=parsed_args.verbose)
case "TS" | "timestepping":
print_message("Running timestepping generator.", 1, "control", verbose=parsed_args.verbose)
from timestepping import main_timestepping
from .timestepping import main_timestepping
main_timestepping(parsed_args)
print_message("Timestepping generator finished.", 1, "control", verbose=parsed_args.verbose)
case "PM" | "LPT" | "tCOLA" | "simbelmyne" | "sbmy":
print_message(f"Running Simbelmyne in mode {main_dict["mode"]}.", 1, "control", verbose=parsed_args.verbose)
from simbelmyne import main_simbelmyne
from parameters_card import parse_arguments_card
from .simbelmyne import main_simbelmyne
from .parameters_card import parse_arguments_card
from os.path import isfile
card_dict = parse_arguments_card(parsed_args)
@ -47,8 +47,8 @@ def main(parsed_args):
case "pre_sCOLA":
print_message("Running pre-sCOLA.", 1, "control", verbose=parsed_args.verbose)
from scola import main_pre_scola
from parameters_card import parse_arguments_card
from .scola import main_pre_scola
from .parameters_card import parse_arguments_card
card_dict = parse_arguments_card(parsed_args)
@ -60,8 +60,8 @@ def main(parsed_args):
case "post_sCOLA":
print_message("Running post-sCOLA.", 1, "control", verbose=parsed_args.verbose)
from scola import main_post_scola
from parameters_card import parse_arguments_card
from .scola import main_post_scola
from .parameters_card import parse_arguments_card
card_dict = parse_arguments_card(parsed_args)
@ -73,8 +73,8 @@ def main(parsed_args):
case "sCOLA":
print_message("Running sCOLA.", 1, "control", verbose=parsed_args.verbose)
from scola import main_scola
from parameters_card import parse_arguments_card
from .scola import main_scola
from .parameters_card import parse_arguments_card
card_dict = parse_arguments_card(parsed_args)
@ -86,12 +86,12 @@ def main(parsed_args):
case "alltCOLA" | "allPM":
print_message(f"Running ICs and Simbelmyne in mode {main_dict["mode"]}.", 1, "control", verbose=parsed_args.verbose)
from parameters_card import parse_arguments_card, main_parameter_card
from timestepping import main_timestepping
from ICs import main_ICs
from simbelmyne import main_simbelmyne
from .parameters_card import parse_arguments_card, main_parameter_card
from .timestepping import main_timestepping
from .ICs import main_ICs
from .simbelmyne import main_simbelmyne
from os.path import isfile
from low_level import wait_until_file_exists
from .low_level import wait_until_file_exists
card_dict = main_parameter_card(parsed_args)
@ -101,7 +101,7 @@ def main(parsed_args):
## Check consistency of ICs_gen and ICs
if main_dict["ICs_gen"] == "monofonic":
from parameters_monofonic import parse_arguments_monofonic
from .parameters_monofonic import parse_arguments_monofonic
monofonic_dict = parse_arguments_monofonic(parsed_args)
if monofonic_dict["output"]+"DM_delta.h5" != card_dict["ICs"]:
raise ValueError(f"ICs {card_dict['ICs']} does not match monofonic output {monofonic_dict['output']+'DM_delta.h5'}")
@ -133,10 +133,17 @@ def main(parsed_args):
case "allsCOLA":
print_message(f"Running ICs, pre_sCOLA, sCOLA and post_sCOLA.", 1, "control", verbose=parsed_args.verbose)
<<<<<<< HEAD:main.py
from parameters_card import parse_arguments_card, main_parameter_card
from timestepping import main_timestepping
from ICs import main_ICs
from scola import main_scola, main_pre_scola, main_post_scola, have_all_tiles
=======
from .parameters_card import parse_arguments_card, main_parameter_card
from .timestepping import main_timestepping
from .ICs import main_ICs
from .scola import main_scola, main_pre_scola, main_post_scola, have_all_tiles
>>>>>>> main:sbmy_control/main.py
card_dict = main_parameter_card(parsed_args)
@ -146,7 +153,7 @@ def main(parsed_args):
## Check consistency of ICs_gen and OutputLPTPotential
if main_dict["ICs_gen"] == "monofonic":
from parameters_monofonic import parse_arguments_monofonic
from .parameters_monofonic import parse_arguments_monofonic
monofonic_dict = parse_arguments_monofonic(parsed_args)
if monofonic_dict["output"]+"DM_phi.h5" != card_dict["OutputLPTPotential1"]:
raise ValueError(f"OutputLPTPotential1 {card_dict['OutputLPTPotential1']} does not match monofonic output {monofonic_dict['output']+'DM_phi.h5'}")
@ -179,7 +186,7 @@ def main(parsed_args):
main_scola(parsed_args)
if parsed_args.execution == "slurm" and not have_all_tiles(parsed_args):
from tqdm import tqdm
from low_level import progress_bar_from_logfile
from .low_level import progress_bar_from_logfile
for b in tqdm(range(1,parsed_args.N_tiles**3+1), desc="sCOLA", unit="box", disable=(parsed_args.verbose==0)):
progress_bar_from_logfile(main_dict["logdir"]+main_dict["simname"]+".log_"+str(b), desc=f"Box {b}/{parsed_args.N_tiles**3}", verbose=parsed_args.verbose, leave=False)
print_message("sCOLA finished.", 1, "control", verbose=parsed_args.verbose)
@ -220,15 +227,15 @@ def check_consistency(card_dict, mode):
raise ValueError(f"ModulePMCOLA is not 1: ModulePMCOLA={card_dict["ModulePMCOLA"]}")
if __name__ == "__main__":
def console_main():
from argparse import ArgumentParser
from args_main import register_arguments_main
from timestepping import register_arguments_timestepping, main_timestepping
from parameters_card import register_arguments_card, main_parameter_card
from cosmo_params import register_arguments_cosmo
from parameters_monofonic import register_arguments_monofonic
from slurm_submission import register_arguments_slurm
from low_level import wait_until_file_exists
from .args_main import register_arguments_main
from .timestepping import register_arguments_timestepping, main_timestepping
from .parameters_card import register_arguments_card, main_parameter_card
from .cosmo_params import register_arguments_cosmo
from .parameters_monofonic import register_arguments_monofonic
from .slurm_submission import register_arguments_slurm
from .low_level import wait_until_file_exists
parser = ArgumentParser(description="Run sCOLA.")
register_arguments_main(parser)
@ -239,3 +246,8 @@ if __name__ == "__main__":
register_arguments_cosmo(parser)
parsed_args = parser.parse_args()
main(parsed_args)
if __name__ == "__main__":
console_main()

18
monofonic.py → sbmy_control/monofonic.py
View file

@ -2,8 +2,8 @@
path_to_monofonic_binary = "/home/aubin/monofonic/build/monofonIC"
def main_monofonic(parsed_args):
from parameters_monofonic import main_parameters_monofonic
from low_level import print_starting_module, print_message, print_ending_module
from .parameters_monofonic import main_parameters_monofonic
from .low_level import print_starting_module, print_message, print_ending_module
from os.path import isfile
import subprocess
@ -27,8 +27,8 @@ def main_monofonic(parsed_args):
print_message("Monofonic finished.", 1, "monofonic", verbose=parsed_args.verbose)
elif parsed_args.execution == "slurm":
from slurm_submission import create_slurm_script, parse_arguments_slurm
from args_main import parse_arguments_main
from .slurm_submission import create_slurm_script, parse_arguments_slurm
from .args_main import parse_arguments_main
print_message("Running monofonic in slurm mode.", 1, "monofonic", verbose=parsed_args.verbose)
slurm_dict=parse_arguments_slurm(parsed_args)
main_dict=parse_arguments_main(parsed_args)
@ -67,11 +67,11 @@ def main_monofonic(parsed_args):
if __name__ == "__main__":
from argparse import ArgumentParser
from parameters_monofonic import register_arguments_monofonic
from args_main import register_arguments_main
from parameters_card import register_arguments_card_for_ICs
from cosmo_params import register_arguments_cosmo
from slurm_submission import register_arguments_slurm
from .parameters_monofonic import register_arguments_monofonic
from .args_main import register_arguments_main
from .parameters_card import register_arguments_card_for_ICs
from .cosmo_params import register_arguments_cosmo
from .slurm_submission import register_arguments_slurm
parser = ArgumentParser(description="Run monofonIC initial conditions generator for a Simbelmyne simulation.")
# TODO: reduce the volume of arguments

46
parameters_card.py → sbmy_control/parameters_card.py
View file

@ -47,6 +47,7 @@ def register_arguments_card(parser:ArgumentParser):
parser.add_argument("--OutputFCsDensity", type=str, default=None, help="Output FCs density file.")
parser.add_argument("--OutputFCsSnapshot", type=str, default=None, help="Output FCs snapshot file.")
parser.add_argument("--OutputRngStateLPT", type=str, default=None, help="Output RNG state file.")
<<<<<<< HEAD:parameters_card.py
## Tests with phiBCs and density
parser.add_argument("--WriteGravPot", type=bool, default=False, help="Write gravitational potential.")
parser.add_argument("--OutputGravitationalPotentialBase", type=str, default=None, help="Output gravitational potential base.")
@ -56,6 +57,12 @@ def register_arguments_card(parser:ArgumentParser):
parser.add_argument("--MeshDensity", type=int, default=None, help="Mesh for density.")
parser.add_argument("--LoadPhiBCs", type=bool, default=False, help="Load phiBCs.")
parser.add_argument("--InputPhiBCsBase", type=str, default=None, help="Input phiBCs file base.")
=======
parser.add_argument("--WriteReferenceFrame", type=bool, default=False, help="Write reference frame (COCA).")
parser.add_argument("--OutputMomentaBase", type=str, default=None, help="Output momenta base (COCA).")
parser.add_argument("--ReadReferenceFrame", type=bool, default=False, help="Read reference frame (COCA).")
parser.add_argument("--InputMomentaBase", type=str, default=None, help="Read momenta base (COCA).")
>>>>>>> main:sbmy_control/parameters_card.py
def register_arguments_card_for_ICs(parser:ArgumentParser):
@ -82,8 +89,8 @@ def parse_arguments_card(parsed_args):
"""
Parse the arguments for the parameter card.
"""
from args_main import parse_arguments_main
from cosmo_params import parse_arguments_cosmo
from .args_main import parse_arguments_main
from .cosmo_params import parse_arguments_cosmo
cosmo_dict=parse_arguments_cosmo(parsed_args)
card_dict=dict(
@ -121,6 +128,10 @@ def parse_arguments_card(parsed_args):
GenerateLightcone=parsed_args.GenerateLightcone,
OutputAlsoFCs=parsed_args.OutputAlsoFCs,
Observer=parsed_args.Observer,
WriteReferenceFrame=parsed_args.WriteReferenceFrame,
OutputMomentaBase=parsed_args.OutputMomentaBase,
ReadReferenceFrame=parsed_args.ReadReferenceFrame,
InputMomentaBase=parsed_args.InputMomentaBase,
N_tiles=parsed_args.N_tiles,
Np_buffer=parsed_args.Np_buffer,
Np_lpt_buffer=parsed_args.Np_lpt_buffer,
@ -222,6 +233,7 @@ def parse_arguments_card(parsed_args):
card_dict["OutputFCsSnapshot"] = main_dict["resultdir"]+"final_particles_"+main_dict["simname"]+".gadget3"
if card_dict["OutputRngStateLPT"] is None:
card_dict["OutputRngStateLPT"] = main_dict["workdir"]+"rng_state.h5"
<<<<<<< HEAD:parameters_card.py
## Tests with phiBCs and density
if card_dict["OutputGravitationalPotentialBase"] is None:
card_dict["OutputGravitationalPotentialBase"] = main_dict["workdir"]+"gravpot_"+main_dict["simname"]
@ -233,6 +245,12 @@ def parse_arguments_card(parsed_args):
card_dict["MeshDensity"] = card_dict["N_PM_mesh"]
if card_dict["InputPhiBCsBase"] is None:
card_dict["InputPhiBCsBase"] = main_dict["workdir"]+"gravpot_tCOLA"
=======
if card_dict["OutputMomentaBase"] is None:
card_dict["OutputMomentaBase"] = main_dict["workdir"]+"momenta_"+main_dict["simname"]+"_"
if card_dict["InputMomentaBase"] is None:
card_dict["InputMomentaBase"] = main_dict["workdir"]+"momenta_"+main_dict["simname"]+"_"
>>>>>>> main:sbmy_control/parameters_card.py
return card_dict
@ -242,7 +260,7 @@ def parse_arguments_card_for_ICs(parsed_args):
"""
Parse the arguments for the parameter card for ICs.
"""
from args_main import parse_arguments_main
from .args_main import parse_arguments_main
main_dict = parse_arguments_main(parsed_args)
card_dict = dict(
@ -282,7 +300,7 @@ def parse_arguments_card_for_timestepping(parsed_args):
"""
Parse the arguments for the parameter card for timestepping.
"""
from args_main import parse_arguments_main
from .args_main import parse_arguments_main
main_dict = parse_arguments_main(parsed_args)
card_dict = dict(
@ -351,6 +369,7 @@ def create_parameter_card_dict(
OutputFCsDensity:str = 'fcs_density.h5',
OutputFCsSnapshot:str = 'fcs_particles.gadget3',
<<<<<<< HEAD:parameters_card.py
## Tests with phiBCs and density
WriteGravPot:bool = True,
OutputGravitationalPotentialBase:str = 'gravitational_potential.h5',
@ -360,6 +379,13 @@ def create_parameter_card_dict(
MeshDensity:int = 128,
LoadPhiBCs:bool = False,
InputPhiBCsBase:str = 'gravitational_potential.h5',
=======
## COCA parameters
WriteReferenceFrame:bool = False,
OutputMomentaBase:str = 'momenta_',
ReadReferenceFrame:bool = False,
InputMomentaBase:str = 'momenta_',
>>>>>>> main:sbmy_control/parameters_card.py
## Cosmological parameters
h:float = 0.6732,
@ -415,6 +441,10 @@ def create_parameter_card_dict(
Observer2=Observer[2],
OutputFCsDensity=OutputFCsDensity,
OutputFCsSnapshot=OutputFCsSnapshot,
WriteReferenceFrame=int(WriteReferenceFrame),
OutputMomentaBase=OutputMomentaBase,
ReadReferenceFrame=int(ReadReferenceFrame),
InputMomentaBase=InputMomentaBase,
NumberOfTilesPerDimension=N_tiles,
NumberOfParticlesInBuffer=Np_buffer,
NumberOfParticlesInLPTBuffer=Np_lpt_buffer,
@ -452,7 +482,7 @@ def write_parameter_card(parameter_card_dict:dict, filename:str, verbose:int = 1
if verbose < 2:
from io import BytesIO
from low_level import stdout_redirector, stderr_redirector
from .low_level import stdout_redirector, stderr_redirector
f = BytesIO()
g = BytesIO()
@ -471,7 +501,7 @@ def main_parameter_card(parsed_args):
"""
Main function for the parameter card.
"""
from low_level import print_message, print_starting_module, print_ending_module
from .low_level import print_message, print_starting_module, print_ending_module
print_starting_module("card", verbose=parsed_args.verbose)
print_message("Parsing arguments for the parameter card.", 1, "card", verbose=parsed_args.verbose)
card_dict = parse_arguments_card(parsed_args)
@ -487,8 +517,8 @@ def main_parameter_card(parsed_args):
return card_dict
if __name__ == "__main__":
from args_main import register_arguments_main
from cosmo_params import register_arguments_cosmo
from .args_main import register_arguments_main
from .cosmo_params import register_arguments_cosmo
parser = ArgumentParser(description="Create sbmy parameter card.")
register_arguments_main(parser)

16
parameters_monofonic.py → sbmy_control/parameters_monofonic.py
View file

@ -16,9 +16,9 @@ def parse_arguments_monofonic(parsed_args):
"""
Parse the arguments for the monofonIC parameters.
"""
from args_main import parse_arguments_main
from parameters_card import parse_arguments_card_for_ICs
from cosmo_params import parse_arguments_cosmo
from .args_main import parse_arguments_main
from .parameters_card import parse_arguments_card_for_ICs
from .cosmo_params import parse_arguments_cosmo
main_dict = parse_arguments_main(parsed_args)
card_dict = parse_arguments_card_for_ICs(parsed_args)
@ -71,7 +71,7 @@ def get_config_from_dict(monofonic_dict):
config["setup"] = {
"GridRes": monofonic_dict["gridres"],
"BoxLength": monofonic_dict["boxlength"],
"zstart": 999.0,
"zstart": 99.0,
"LPTorder": 2,
"DoBaryons": False,
"DoBaryonVrel": False,
@ -131,7 +131,7 @@ def get_config_from_dict(monofonic_dict):
def main_parameters_monofonic(parsed_args):
from low_level import print_message
from .low_level import print_message
print_message("Parsing arguments for the config file.", 1, "monofonic", verbose=parsed_args.verbose)
monofonic_dict = parse_arguments_monofonic(parsed_args)
@ -144,9 +144,9 @@ def main_parameters_monofonic(parsed_args):
if __name__ == "__main__":
from args_main import register_arguments_main
from parameters_card import register_arguments_card_for_ICs
from cosmo_params import register_arguments_cosmo
from .args_main import register_arguments_main
from .parameters_card import register_arguments_card_for_ICs
from .cosmo_params import register_arguments_cosmo
parser = ArgumentParser(description="Create monofonIC configuration file.")
register_arguments_main(parser)

2
progress_bar.py → sbmy_control/progress_bar.py
View file

@ -1,7 +1,7 @@
if __name__ == "__main__":
from argparse import ArgumentParser
from tqdm import tqdm
from low_level import progress_bar_from_logfile
from .low_level import progress_bar_from_logfile
parser = ArgumentParser(description="Progress bar from log files.")
parser.add_argument("-l","--logdir", type=str, help="Log directory.")

57
scola.py → sbmy_control/scola.py
View file

@ -1,6 +1,8 @@
def main_scola(parsed_args):
from args_main import parse_arguments_main
from low_level import print_starting_module, print_message, print_ending_module, progress_bar_from_logfile, wait_until_file_exists
from .args_main import parse_arguments_main
from .low_level import print_starting_module, print_message, print_ending_module, progress_bar_from_logfile, wait_until_file_exists
from os.path import isfile
import subprocess
@ -19,7 +21,7 @@ def main_scola(parsed_args):
return
if parsed_args.execution == "local":
from parameters_card import parse_arguments_card
from .parameters_card import parse_arguments_card
from tqdm import tqdm
card_dict = parse_arguments_card(parsed_args)
print_message("Running sCOLA in local mode.", 1, "scola", verbose=parsed_args.verbose)
@ -50,14 +52,16 @@ def main_scola(parsed_args):
print_message("sCOLA finished.", 1, "scola", verbose=parsed_args.verbose)
elif parsed_args.execution == "slurm":
from slurm_submission import create_slurm_script, parse_arguments_slurm
from args_main import parse_arguments_main
from .slurm_submission import create_slurm_script, parse_arguments_slurm, limit_slurm_arrays
from .args_main import parse_arguments_main
from .parameters_card import parse_arguments_card
import os
print_message("Running scola in slurm mode.", 1, "scola", verbose=parsed_args.verbose)
slurm_dict=parse_arguments_slurm(parsed_args)
main_dict=parse_arguments_main(parsed_args)
card_dict=parse_arguments_card(parsed_args)
if have_no_tiles(parsed_args) or parsed_args.force:
if (have_no_tiles(parsed_args) or parsed_args.force) and card_dict["N_tiles"]**3 < limit_slurm_arrays :
## Submit all boxes
print_message("Submitting all boxes.", 2, "scola", verbose=parsed_args.verbose)
slurm_script = slurm_dict["scripts"]+"scola_"+main_dict["simname"]+".sh"
@ -93,6 +97,7 @@ def main_scola(parsed_args):
else:
## Submit missing boxes
from time import sleep
missing_tiles_arrays = get_missing_tiles_arrays(parsed_args)
print_message(f"Submitting missing boxes: {missing_tiles_arrays}.", 2, "scola", verbose=parsed_args.verbose)
@ -127,6 +132,7 @@ def main_scola(parsed_args):
subprocess.run(command_args)
print_message("sCOLA job submitted.", 2, "scola", verbose=parsed_args.verbose)
sleep((missing_tiles[1]-missing_tiles[0])*1.0) # Sleep for a bit to avoid overloading the scheduler
os.remove(slurm_script) # Remove the script after submission (because it is specific to the missing tiles)
@ -142,15 +148,15 @@ def main_pre_scola(parsed_args):
If they already exist, it does nothing. If all tiles exist, raises error.
"""
from os.path import isfile
from low_level import print_starting_module, print_message, print_ending_module
from parameters_card import parse_arguments_card
from .low_level import print_starting_module, print_message, print_ending_module
from .parameters_card import parse_arguments_card
print_starting_module("pre-scola", verbose=parsed_args.verbose)
card_dict = parse_arguments_card(parsed_args)
if not isfile(card_dict["OutputLPTPotential1"]) or not isfile(card_dict["OutputLPTPotential2"]) or parsed_args.force:
if not have_all_tiles(parsed_args):
print_message("Running pre-scola.", 1, "pre-scola", verbose=parsed_args.verbose)
from simbelmyne import main_simbelmyne
from .simbelmyne import main_simbelmyne
main_simbelmyne(parsed_args)
else:
raise NotImplementedError("All tiles exists, so calling simbelmyne would generate the final output instead of the LPT potentials.")
@ -166,8 +172,8 @@ def main_post_scola(parsed_args):
If the output already exists, it does nothing. If tiles are missing, print the missing tiles.
"""
from os.path import isfile
from low_level import print_starting_module, print_message, print_ending_module
from parameters_card import parse_arguments_card
from .low_level import print_starting_module, print_message, print_ending_module
from .parameters_card import parse_arguments_card
print_starting_module("post-scola", verbose=parsed_args.verbose)
card_dict = parse_arguments_card(parsed_args)
@ -180,7 +186,7 @@ def main_post_scola(parsed_args):
if (card_dict["WriteFinalDensity"] and not isfile(card_dict["OutputFinalDensity"])) or (card_dict["WriteFinalSnapshot"] and not isfile(card_dict["OutputFinalSnapshot"])) or parsed_args.force:
if have_all_tiles(parsed_args):
print_message("Running post-scola.", 1, "post-scola", verbose=parsed_args.verbose)
from simbelmyne import main_simbelmyne
from .simbelmyne import main_simbelmyne
main_simbelmyne(parsed_args)
else:
missing_tiles_arrays = get_missing_tiles_arrays(parsed_args)
@ -197,7 +203,7 @@ def main_post_scola(parsed_args):
def have_all_tiles(parsed_args):
from os.path import isfile
from parameters_card import parse_arguments_card
from .parameters_card import parse_arguments_card
card_dict = parse_arguments_card(parsed_args)
nboxes_tot = int(parsed_args.N_tiles**3)
@ -210,7 +216,7 @@ def have_all_tiles(parsed_args):
def have_no_tiles(parsed_args):
from os.path import isfile
from parameters_card import parse_arguments_card
from .parameters_card import parse_arguments_card
card_dict = parse_arguments_card(parsed_args)
nboxes_tot = int(parsed_args.N_tiles**3)
@ -223,17 +229,24 @@ def have_no_tiles(parsed_args):
def get_missing_tiles_arrays(parsed_args):
from os.path import isfile
from parameters_card import parse_arguments_card
from .parameters_card import parse_arguments_card
from .slurm_submission import limit_slurm_arrays
card_dict = parse_arguments_card(parsed_args)
nboxes_tot = int(parsed_args.N_tiles**3)
missing_tiles_arrays = []
in_sequence_of_missing = False
len_sequence_of_missing = 0
for b in range(1,nboxes_tot+1):
if not isfile(card_dict["OutputTilesBase"]+str(b)+".h5"):
len_sequence_of_missing += 1
if not in_sequence_of_missing:
missing_tiles_arrays.append([b])
in_sequence_of_missing = True
len_sequence_of_missing = 1
if b%limit_slurm_arrays==limit_slurm_arrays-1:
missing_tiles_arrays[-1].append(b)
in_sequence_of_missing = False
elif in_sequence_of_missing:
missing_tiles_arrays[-1].append(b-1)
in_sequence_of_missing = False
@ -247,13 +260,13 @@ def get_missing_tiles_arrays(parsed_args):
if __name__ == "__main__":
from argparse import ArgumentParser
from args_main import register_arguments_main
from timestepping import register_arguments_timestepping, main_timestepping
from parameters_card import register_arguments_card, main_parameter_card
from cosmo_params import register_arguments_cosmo
from parameters_monofonic import register_arguments_monofonic
from slurm_submission import register_arguments_slurm
from low_level import wait_until_file_exists
from .args_main import register_arguments_main
from .timestepping import register_arguments_timestepping, main_timestepping
from .parameters_card import register_arguments_card, main_parameter_card
from .cosmo_params import register_arguments_cosmo
from .parameters_monofonic import register_arguments_monofonic
from .slurm_submission import register_arguments_slurm
from .low_level import wait_until_file_exists
parser = ArgumentParser(description="Run sCOLA.")
register_arguments_main(parser)

0
sbmy_control/scripts/__init__.py Normal file
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82
sbmy_control/scripts/convert_snapshot_to_density.py Normal file
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@ -0,0 +1,82 @@
from pysbmy.density import get_density_pm_snapshot
from pysbmy.snapshot import read_snapshot
import argparse
def convert_snapshot_to_density(snapshot_path, output_path, N=None, corner=(0.0, 0.0, 0.0)):
"""
Convert a snapshot to a density field.
Parameters
----------
snapshot_path : str
Path to the snapshot file.
output_path : str
Path to the output density file.
N : int
Size of the density field grid (N x N x N).
corner : tuple of float
Corner of the box (x, y, z).
"""
# Read the snapshot
print("Reading snapshot...")
snap = read_snapshot(snapshot_path)
if N is None:
N = snap.Np0
# Calculate density
print("Calculating density...")
F = get_density_pm_snapshot(snap, N, N, N, corner[0], corner[1], corner[2])
# Write density to file
print("Writing density...")
F.write(output_path)
print("Density written to", output_path)
print("Done.")
def console_main():
parser = argparse.ArgumentParser(description="Convert snapshot to density.")
parser.add_argument(
"-S",
"--snapshot",
type=str,
required=True,
help="Path to the snapshot file.",
)
parser.add_argument(
"-o",
"--output",
type=str,
required=True,
help="Path to the output density file.",
)
parser.add_argument(
"-N",
"--N",
type=int,
default=None,
help="Size of the density field grid (N x N x N).",
)
parser.add_argument(
"-c",
"--corner",
type=float,
nargs=3,
default=[0.0, 0.0, 0.0],
help="Corner of the box (x, y, z).",
)
args = parser.parse_args()
convert_snapshot_to_density(
snapshot_path=args.snapshot,
output_path=args.output,
N=args.N,
corner=args.corner,
)
if __name__ == "__main__":
console_main()

134
sbmy_control/scripts/field_to_field.py Normal file
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@ -0,0 +1,134 @@
from pysbmy.density import mesh_to_mesh
from pysbmy.field import Field, read_field
import numpy as np
import os
def field_to_field(
input_file:str,
output_file:str,
output_size:int|tuple[int,int,int]|list[int],
output_L:float|tuple[float,float,float]|list[float],
output_dpm:float|tuple[float,float,float]|list[float],
output_corner:tuple[float,float,float]|list[float],
boundary_conditions:int,
):
### Make sure all inputs are valid
if output_L is not None and output_dpm is not None:
raise ValueError("Either output_L or output_dpm can be specified, not both.")
if isinstance(output_size, int):
output_size = (output_size, output_size, output_size) # N0, N1, N2
elif len(output_size) == 1:
output_size = (output_size[0], output_size[0], output_size[0])
if output_L is not None:
if isinstance(output_L, float):
output_L = (output_L, output_L, output_L)
elif len(output_L) == 1:
output_L = (output_L[0], output_L[0], output_L[0])
if output_dpm is None:
if output_L is None:
output_dpm = (-1, -1, -1)
else:
output_dpm = (output_L[0] / output_size[0], output_L[1] / output_size[1], output_L[2] / output_size[2])
elif isinstance(output_dpm, float):
output_dpm = (output_dpm, output_dpm, output_dpm) # d0, d1, d2
elif len(output_dpm) == 1:
output_dpm = (output_dpm[0], output_dpm[0], output_dpm[0])
if not os.path.exists(input_file):
raise FileNotFoundError(f"Input file {input_file} does not exist.")
# Read the input field
print(f"Reading input field from {input_file}")
input_field = read_field(input_file)
if input_field.rank != 1 or input_field.data.ndim != 3:
raise NotImplementedError("Only 3D scalar fields are supported for now.")
L0 = input_field.L0
L1 = input_field.L1
L2 = input_field.L2
N0 = input_field.N0
N1 = input_field.N1
N2 = input_field.N2
corner0 = input_field.corner0
corner1 = input_field.corner1
corner2 = input_field.corner2
d0_in = L0 / N0
d1_in = L1 / N1
d2_in = L2 / N2
d0_out = output_dpm[0] if output_dpm[0] > 0 else d0_in
d1_out = output_dpm[1] if output_dpm[1] > 0 else d1_in
d2_out = output_dpm[2] if output_dpm[2] > 0 else d2_in
offset_out_x = (output_corner[0] - corner0)
offset_out_y = (output_corner[1] - corner1)
offset_out_z = (output_corner[2] - corner2)
print("-----------------------------------------")
print(f"Input field size: {N0} x {N1} x {N2}")
print(f"Output field size: {output_size[0]} x {output_size[1]} x {output_size[2]}")
print(f"Input field dpm: {d0_in:.3f} x {d1_in:.3f} x {d2_in:.3f}")
print(f"Output field dpm: {d0_out:.3f} x {d1_out:.3f} x {d2_out:.3f}")
print(f"Input field corner: ({corner0:.1f}, {corner1:.1f}, {corner2:.1f})")
print(f"Output field corner: ({output_corner[0]:.1f}, {output_corner[1]:.1f}, {output_corner[2]:.1f})")
print(f"Boundary conditions: {'periodic' if boundary_conditions == 1 else 'non-periodic'}")
print("-----------------------------------------")
input_grid = input_field.data
output_grid = np.zeros(output_size, dtype=input_grid.dtype)
# Mesh to mesh interpolation
print("Interpolating field...")
mesh_to_mesh(input_grid, output_grid, d0_in, d1_in, d2_in, d0_out, d1_out, d2_out, offset_out_x, offset_out_y, offset_out_z, boundary_conditions)
# Create the output field
output_field = Field(
L0=output_size[0] * d0_out,
L1=output_size[1] * d1_out,
L2=output_size[2] * d2_out,
corner0=output_corner[0],
corner1=output_corner[1],
corner2=output_corner[2],
rank=input_field.rank,
N0=output_size[0],
N1=output_size[1],
N2=output_size[2],
time=input_field.time,
data=output_grid
)
# Write the output field
print(f"Writing output field to {output_file}")
output_field.write(output_file)
print("Done.")
def console_main():
import argparse
parser = argparse.ArgumentParser(description="Convert a field from one size to another.")
parser.add_argument("-i","--input_file", type=str, help="Input field file")
parser.add_argument("-o","--output_file", type=str, help="Output field file")
parser.add_argument("-N","--output_size", type=int, nargs="+", help="Output field size (N0, N1, N2)")
parser.add_argument("-L","--output_L", type=float, nargs="+", default=None, help="Output field size (L0, L1, L2)")
parser.add_argument("-dpm","--output_dpm", type=float, nargs="+", default=None, help="Output field dpm (d0, d1, d2)")
parser.add_argument("-corner","--output_corner", type=float, nargs=3, default=(0.,0.,0.), help="Output field corner (corner0, corner1, corner2)")
parser.add_argument("-BC","--boundary_conditions", type=int, default=1, help="Boundary conditions (1: periodic, 3: non-periodic)")
args = parser.parse_args()
field_to_field(args.input_file, args.output_file, args.output_size, args.output_L, args.output_dpm, args.output_corner, args.boundary_conditions)
if __name__ == "__main__":
console_main()

128
sbmy_control/scripts/gather_tiles.py Normal file
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@ -0,0 +1,128 @@
import numpy as np
from pysbmy.snapshot import read_tile
from pysbmy.field import Field
from pysbmy.density import get_density_pm, density_to_delta
from pysbmy import c_float_t
import tqdm
import argparse
def get_indices(tile, N_TILES0, N_TILES1, N_TILES2):
"""Get the indices of the tile in a 3D grid."""
i = (tile // (N_TILES1 * N_TILES2))%N_TILES0
j = ((tile - N_TILES1 * N_TILES2 * i) // N_TILES2)%N_TILES1
k = (tile - N_TILES2 * j - N_TILES1 * N_TILES2 * i)%N_TILES2
return i, j, k
def tile_to_density_with_buffer(T, N, d, buffer):
"""
Convert a tile to density with a buffer.
"""
# Create a buffer for the density
A = np.zeros((N+2*buffer, N+2*buffer, N+2*buffer), dtype=np.float32)
# Get the density of the tile
A = get_density_pm(T.pos-T.corner_position.astype(c_float_t)+d*buffer, A, d)
return A
def add_density_tile(A,A_tile,corner_indices):
N = A.shape[0]
Np = A_tile.shape[0]
i0, j0, k0 = corner_indices
# Create index arrays for the tile
i_idx = (np.arange(Np) + i0) % N
j_idx = (np.arange(Np) + j0) % N
k_idx = (np.arange(Np) + k0) % N
# Use np.ix_ to get all combinations of indices
A[np.ix_(i_idx, j_idx, k_idx)] += A_tile
def gather_density(A, folder, tile_base, Np_tile, dpm, buffer, N_TILES):
"""
Gather the density from the tiles.
"""
for tile in tqdm.tqdm(range(N_TILES**3), desc="Density of tiles", unit="tiles"):
T=read_tile(folder+tile_base+str(tile+1)+".h5", int(Np_tile**3))
# Get the corner position of the tile
corner_position = T.corner_position
# Get the corner indices of the tile
i,j,k = get_indices(tile, N_TILES, N_TILES, N_TILES)
corner_grid_indices = (i*Np_tile-buffer, j*Np_tile-buffer, k*Np_tile-buffer)
# Get the density of the tile with a buffer
A_tile = tile_to_density_with_buffer(T, Np_tile, dpm, buffer)
# Add the density of the tile to the grid
add_density_tile(A, A_tile, corner_grid_indices)
def gather_tiles(folder, tile_base, L, Np, N_TILES, buffer):
"""
Gather sCOLA tiles into a single density field.
Parameters
----------
folder : str
Folder containing the tiles.
tile_base : str
Base name of the tiles.
L : float
Size of the box in Mpc/h.
Np : int
Number of cells per dimension for the full box.
N_TILES : int
Number of tiles per dimension.
buffer : int
Buffer size for the density field of tiles.
"""
Np_tile = Np//N_TILES
dpm = L/Np_tile
print("Memory allocation for the grid...")
A=np.zeros((Np,Np,Np), dtype=np.float32)
print("Starting to read the tiles...")
gather_density(A, folder, tile_base, Np_tile, dpm, buffer, N_TILES)
print("Finished reading the tiles.")
A=density_to_delta(A,-1)
print("Converting to field...")
F=Field(L,L,L, 0.,0.,0., 1, Np,Np,Np, 1., A)
print("Saving field...")
F.write(folder+"../results/final_density_sCOLA.h5")
print("Density field saved to", folder+"../results/final_density_sCOLA.h5")
print("Done.")
def console_main():
parser = argparse.ArgumentParser(description="Gather density from tiles.")
parser.add_argument("-d","--folder", type=str, default="./", help="Folder containing the tiles")
parser.add_argument("--tile_base", type=str, default="sCOLA_tile", help="Base name of the tiles")
parser.add_argument("-L","--L", type=int, default=1920, help="Size of the box in Mpc/h")
parser.add_argument("-Np","--Np", type=int, default=80, help="Number of cells per dimension for the full box")
parser.add_argument("-Nt","--N_tiles", type=int, default=4, help="Number of tiles per dimension.")
parser.add_argument("--buffer", type=int, default=40, help="Buffer size for the density field of tiles")
args = parser.parse_args()
L = args.L
Np = args.Np
N_TILES = args.N_tiles
buffer = args.buffer
folder = args.folder
tile_base = args.tile_base
Np_tile = Np//N_TILES
dpm = L/Np_tile
gather_tiles(folder, tile_base, L, Np, N_TILES, buffer)
if __name__ == "__main__":
console_main()

502
sbmy_control/scripts/scola_submit.py Normal file
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@ -0,0 +1,502 @@
import tqdm
import argparse
import numpy as np
import os
import subprocess
import time
def create_scola_slurm_script(slurmfile, box):
"""
Create a slurm script for sCOLA.
Parameters
----------
slurmfile : str
Path to the slurm script file.
box : str
Box number to be replaced in the slurm script.
"""
# Read the slurm file
with open(slurmfile, "r") as f:
slurm_script = f.read()
# Replace the placeholders in the slurm script
slurm_script = slurm_script.replace("BOX", box)
# Write the modified slurm script to a new file
with open(slurmfile+f".{box}", "w") as f:
f.write(slurm_script)
def submit_slurm_job(slurmfile):
"""
Submit a slurm job using the sbatch command.
Parameters
----------
slurmfile : str
Path to the slurm script file.
Returns
-------
str
Job ID of the submitted job. None if the submission failed.
"""
# Submit the job
result = subprocess.run(["sbatch", slurmfile], capture_output=True, text=True)
# Check if the submission was successful
if result.returncode != 0:
print(f"Error submitting job: {result.stderr}")
return None
# Get the job ID from the output
job_id = result.stdout.split()[-1]
return job_id
def convert_time_to_seconds(time_str):
"""
Convert a time string of the format D-HH:MM:SS or HH:MM:SS or MM:SS to seconds.
"""
time_parts = time_str.split("-")
if len(time_parts) == 2:
days = int(time_parts[0])
time_str = time_parts[1]
else:
days = 0
time_parts = time_str.split(":")
if len(time_parts) == 3:
hours, minutes, seconds = map(int, time_parts)
elif len(time_parts) == 2:
hours, minutes = map(int, time_parts)
seconds = 0
else:
raise ValueError("Invalid time format")
total_seconds = days * 86400 + hours * 3600 + minutes * 60 + seconds
return total_seconds
def convert_seconds_to_time(seconds):
"""
Convert seconds to a time string of the format D-HH:MM:SS.
"""
seconds = int(seconds)
if seconds < 0:
return "N/A"
days = seconds // 86400
seconds %= 86400
hours = seconds // 3600
seconds %= 3600
minutes = seconds // 60
seconds %= 60
if days > 0:
return f"{days}-{hours:02}:{minutes:02}:{seconds:02}"
if hours > 0:
return f"{hours:02}:{minutes:02}:{seconds:02}"
return f"{minutes:02}:{seconds:02}"
def check_job_status(job_id):
"""
Check the status of a job using the squeue command.
Returns the job status and running time.
Parameters
----------
job_id : str
Job ID of the job to check.
Returns
-------
str
Job status. Possible values are 'R' (running), 'PD' (pending), 'X' (failed), 'CP' (completed).
int
Running time in seconds. -1 if the job is not found.
"""
# Check the job status
result = subprocess.run(["squeue", "-j", str(job_id)], capture_output=True, text=True)
# Check if the job is still running
if result.returncode == 1:
return "X", -1
if len(result.stdout.split("\n")[1].split()) == 0:
return "X", -1
status = result.stdout.split("\n")[1].split()[4]
job_time = convert_time_to_seconds(result.stdout.split("\n")[1].split()[5])
return status, job_time
def get_job_id(jobname):
"""
Get the job ID from the job name using the squeue command.
"""
# Check the job status
result = subprocess.run(["squeue", "-n", jobname], capture_output=True, text=True)
# Check if the job is still running
if result.returncode == 1:
return None
if len(result.stdout.split("\n")[1].split()) == 0:
return None
# Get the job ID
job_id = result.stdout.split("\n")[1].split()[0]
return job_id
def resubmit_job(slurmdir,slurmfile,job_ids_array,box,resubmit_count,error_count,MAX_RESUBMIT=10,MAX_ERRORS=10):
"""
Resubmit a job if it has failed.
Parameters
----------
slurmdir : str
Directory where the slurm scripts are saved.
slurmfile : str
Slurm script file.
job_ids_array : array
Array of job IDs for all previously submitted jobs. Indexed by box-1 number.
box : int
Box number of the job to resubmit.
resubmit_count : int
Number of resubmissions so far.
error_count : int
Number of errors so far.
MAX_RESUBMIT : int
Maximum number of resubmissions allowed.
MAX_ERRORS : int
Maximum number of errors allowed.
Returns
-------
int
Updated resubmit count.
int
Updated error count.
"""
# Resubmit the job
job_id = submit_slurm_job(slurmdir+slurmfile+"."+str(box))
# Check if the job was submitted successfully
if job_id is None:
print(f"Error resubmitting job for box {box}")
error_count+=1
# Check if the error count exceeds the maximum
if error_count >= MAX_ERRORS:
raise RuntimeError(f"Error count exceeded {MAX_ERRORS}. Stopping job submission.")
else:
job_ids_array[box-1] = int(job_id)
resubmit_count += 1
# Check if the resubmit count exceeds the maximum
if resubmit_count >= MAX_RESUBMIT:
raise RuntimeError(f"Resubmit count exceeded {MAX_RESUBMIT}. Stopping job submission.")
return resubmit_count, error_count
def check_previous_jobs(workdir,slurmdir,slurmfile,tilefile,sleeptime,job_ids_array,box,resubmit_count,error_count,MAX_RESUBMIT=10,MAX_ERRORS=10):
"""
Get the status of all previously submitted jobs.
For each job, check if it is running, completed, or failed.
If the job is failed, resubmit it.
Parameters
----------
workdir : str
Directory where the tiles are saved.
slurmdir : str
Directory where the slurm scripts are saved.
slurmfile : str
Slurm script file.
tilefile : str
Tile file name.
sleeptime : float
Sleep time between each job submission (in s).
job_ids_array : array
Array of job IDs for all previously submitted jobs. Indexed by box-1 number.
box : int
Up to which box the job status is checked.
resubmit_count : int
Number of resubmissions so far.
error_count : int
Number of errors so far.
MAX_RESUBMIT : int
Maximum number of resubmissions allowed.
MAX_ERRORS : int
Maximum number of errors allowed.
Returns
-------
dict
Dictionary with the job status categories and their corresponding box numbers.
int
Updated resubmit count.
int
Updated error count.
"""
job_status_categories = {'R':[],'CP':[],'PD':[],'X':[]}
# Check the status of every previously submitted job
for prev_box in tqdm.tqdm(range(1,box), desc="Checking jobs", unit="boxes", leave=False, position=1):
# Check the job status
status, job_time = check_job_status(job_ids_array[prev_box-1])
# Add the job status to the dictionary
if status not in job_status_categories:
job_status_categories[status] = []
# If the status is 'X', check if the tile file was created
if status == 'X':
# Check if the tile file was created
if os.path.exists(workdir+f"{tilefile}{prev_box}.h5"):
job_status_categories['CP'].append(prev_box) # Classify as completed
else:
resubmit_count, error_count = resubmit_job(slurmdir,slurmfile,job_ids_array,prev_box,resubmit_count,error_count,MAX_RESUBMIT,MAX_ERRORS)
job_status_categories[status].append(prev_box) # Classify as failed
# Sleep for a while before resubmitting the next job
time.sleep(sleeptime)
# If the status is not 'X', record the job status
else:
job_status_categories[status].append(prev_box)
return job_status_categories, resubmit_count, error_count
def cap_number_of_jobs(job_status_categories,job_ids_array, max_jobs, sleep_time):
"""
Cap the number of jobs to a maximum number.
Parameters
----------
job_status_categories : dict
Dictionary with the job status categories and their corresponding box numbers.
job_ids_array : array
Array of job IDs for all previously submitted jobs. Indexed by box-1 number.
max_jobs : int
Maximum number of jobs allowed.
sleep_time : float
Sleep time between each job submission (in s).
Returns
-------
dict
Updated dictionary with the job status categories and their corresponding box numbers.
"""
discard_categories = ['CP', 'X'] # Completed and Failed
# Check the number of running /pending jobs
job_num = 0
for status in job_status_categories.keys():
if status not in discard_categories:
job_num += len(job_status_categories[status])
# We wait until the number of jobs is below the maximum
while job_num > max_jobs:
print(f"Number of open jobs: {job_num} > {max_jobs}. Waiting...")
for status in job_status_categories.keys():
if status not in discard_categories:
for box in job_status_categories[status]:
# Check the new job status
new_status, job_time = check_job_status(job_ids_array[box-1])
time.sleep(sleep_time)
if new_status in discard_categories:
job_num -= 1
job_status_categories[new_status].append(box) # WARNING: We do not reclassify 'X' jobs as 'CP'
job_status_categories[status].remove(box)
return job_status_categories
def print_summary_job_status(job_status_categories, box, resubmit_count, error_count):
print("---------------------------------------------------")
# Print summary of job statuses
print(f"Job statuses after box {box}:")
# Print a table with columns for each status and below the % of jobs in that status
row0 = f"{'Status':<14}"
for status in job_status_categories.keys():
row0 += f"{status:>9} "
print(row0)
row1 = f"{'Percentage':<14}"
for status in job_status_categories.keys():
row1 += f"{len(job_status_categories[status])/box*100:>9.1f}%"
print(row1)
# Print the rate of resubmissions
print(f"Resubmission rate: {resubmit_count/box*100:.2f}%")
print(f"Error count: {error_count}")
def scola_submit(directory,
slurmdir=None,
workdir=None,
slurmfile="scola_sCOLA.sh",
tilefile="scola_tile",
jobname="sCOLA_",
N_tiles=4,
sleep=1.5,
force=False,
MAX_ERRORS=10,
MAX_RESUBMIT=10,
MAX_JOBS_AT_ONCE=48,
CHECK_EVERY=100):
if slurmdir is None:
slurmdir = directory + "slurm_scripts/"
if workdir is None:
workdir = directory + "work/"
# Check that the slurm file exists
if not os.path.exists(slurmdir+slurmfile):
raise FileNotFoundError(f"Slurm file {slurmdir+slurmfile} does not exist.")
# Check that the work directory exists
if not os.path.exists(workdir):
raise FileNotFoundError(f"Work directory {workdir} does not exist.")
# If force, remove all pre-existing tile files
if force:
count_removed = 0
for box in range(1,N_tiles**3+1):
if os.path.exists(workdir+f"{tilefile}{box}.h5"):
os.remove(workdir+f"{tilefile}{box}.h5")
count_removed += 1
print(f"Removed {count_removed} ({100*count_removed/N_tiles**3:.1f}%) pre-existing tile files.")
# MAX_ERRORS = 10
if MAX_RESUBMIT is None:
MAX_RESUBMIT = int(0.1*N_tiles**3) # 10% of the total number of jobs
# MAX_JOBS_AT_ONCE = int(3*128/8) # 3 nodes with 128 cores each, 8 jobs per core
# CHECK_EVERY = 100
error_count = 0
resubmit_count = 0
counter_for_checks = 0
job_ids_array = np.zeros((N_tiles**3,), dtype=int)
print("---------------------------------------------------")
print("Starting job submission for sCOLA tiles with the following parameters:")
print(f"Directory: {directory}")
print(f"Slurm file: {slurmdir}{slurmfile}")
print(f"Work directory: {workdir}")
print(f"Number of tiles: {N_tiles**3} tiles")
print(f"Sleep time: {sleep} s")
print(f"Max errors: {MAX_ERRORS} errors")
print(f"Max resubmits: {MAX_RESUBMIT} resubmits")
print(f"Max jobs at once: {MAX_JOBS_AT_ONCE} jobs")
print(f"Check every: {CHECK_EVERY} jobs")
print("---------------------------------------------------")
print(f"ETA: {convert_seconds_to_time(N_tiles**3*sleep*1.2)}")
print("Starting job submission...")
for box in tqdm.tqdm(range(1,N_tiles**3+1), desc="Submitting jobs", unit="boxes"):
# Check if the tile file already exists
if os.path.exists(workdir+f"{tilefile}{box}.h5"):
continue
# Check if the slurm job is already running
job_id = get_job_id(f"{jobname}{box}")
if job_id is not None:
job_ids_array[box-1] = int(job_id)
time.sleep(sleep)
continue
# Create the slurm script for the box
create_scola_slurm_script(slurmdir+slurmfile, str(box))
# Submit the job
job_id = submit_slurm_job(slurmdir+slurmfile+"."+str(box))
# Check if the job was submitted successfully
if job_id is None:
print(f"Error submitting job for box {box}")
error_count+=1
else:
job_ids_array[box-1] = int(job_id)
# Sleep for a while before submitting the next job
time.sleep(sleep)
counter_for_checks += 1
# Check if the error count exceeds the maximum
if error_count >= MAX_ERRORS:
raise RuntimeError(f"Error count exceeded {MAX_ERRORS}. Stopping job submission.")
# Check the job status every CHECK_EVERY jobs
if counter_for_checks >= CHECK_EVERY:
counter_for_checks = 0
job_status_categories, resubmit_count, error_count = check_previous_jobs(workdir,slurmdir,slurmfile,tilefile,sleep,job_ids_array,box,resubmit_count,error_count,MAX_RESUBMIT,MAX_ERRORS)
print_summary_job_status(job_status_categories, box, resubmit_count, error_count)
job_status_categories = cap_number_of_jobs(job_status_categories,job_ids_array,MAX_JOBS_AT_ONCE,sleep)
print("All jobs submitted. Now checking the status of the jobs.")
job_status_categories, resubmit_count, error_count = check_previous_jobs(workdir,slurmdir,slurmfile,tilefile,sleep,job_ids_array,N_tiles**3+1,resubmit_count,error_count,MAX_RESUBMIT,MAX_ERRORS)
print_summary_job_status(job_status_categories, box, resubmit_count, error_count)
# Now wait for all jobs to finish
while len(job_status_categories['CP'])<N_tiles**3:
time.sleep(10*sleep)
job_status_categories, resubmit_count, error_count = check_previous_jobs(workdir,slurmdir,slurmfile,tilefile,sleep,job_ids_array,N_tiles**3+1,resubmit_count,error_count,MAX_RESUBMIT,MAX_ERRORS)
print_summary_job_status(job_status_categories, N_tiles**3, resubmit_count, error_count)
job_status_categories = cap_number_of_jobs(job_status_categories,job_ids_array,MAX_JOBS_AT_ONCE,sleep)
print("All jobs finished.")
# Remove the slurm scripts
for box in range(1,N_tiles**3+1):
if os.path.exists(slurmdir+slurmfile+"."+str(box)):
os.remove(slurmdir+slurmfile+"."+str(box))
def console_main():
parser = argparse.ArgumentParser(description="Submit slurm jobs for sCOLA tiles.")
parser.add_argument("-d", "--directory", type=str, default="./", help="Main directory where the output will be saved (if other dir and filenames are not specified).")
parser.add_argument("-sd", "--slurmdir", type=str, default=None, help="Directory where the slurm scripts are saved (default is -d/slurm_scripts).")
parser.add_argument("-wd", "--workdir", type=str, default=None, help="Directory where the tiles are saved (default is -d/work).")
parser.add_argument("-sf","--slurmfile", type=str, default="scola_sCOLA.sh", help="Slurm script file (located in slurmdir, default is scola_sCOLA.sh).")
parser.add_argument("-tf","--tilefile", type=str, default="scola_tile", help="Tile file name (located in workdir, default is scola_tile).")
parser.add_argument("--jobname", type=str, default="sCOLA_", help="Job name for the slurm jobs (default is sCOLA_).")
parser.add_argument("-Nt","--N_tiles", type=int, default=4, help="Number of tiles per dimension.")
parser.add_argument("--sleep", type=float, default=1.5, help="Sleep time between each job submission (in s).")
parser.add_argument("-F","--force", action="store_true", help="Force to resimulate all tiles, even if they already exist.")
args=parser.parse_args()
scola_submit(args.directory,
slurmdir=args.slurmdir,
workdir=args.workdir,
slurmfile=args.slurmfile,
tilefile=args.tilefile,
jobname=args.jobname,
N_tiles=args.N_tiles,
sleep=args.sleep,
force=args.force)
if __name__ == "__main__":
console_main()

20
simbelmyne.py → sbmy_control/simbelmyne.py
View file

@ -1,6 +1,6 @@
def main_simbelmyne(parsed_args):
from args_main import parse_arguments_main
from low_level import print_starting_module, print_message, print_ending_module, progress_bar_from_logfile
from .args_main import parse_arguments_main
from .low_level import print_starting_module, print_message, print_ending_module, progress_bar_from_logfile
from os.path import isfile
import subprocess
@ -30,8 +30,8 @@ def main_simbelmyne(parsed_args):
print_message("Simbelyne finished.", 1, "simbelmyne", verbose=parsed_args.verbose)
elif parsed_args.execution == "slurm":
from slurm_submission import create_slurm_script, parse_arguments_slurm
from args_main import parse_arguments_main
from .slurm_submission import create_slurm_script, parse_arguments_slurm
from .args_main import parse_arguments_main
print_message("Running simbelmyne in slurm mode.", 1, "simbelmyne", verbose=parsed_args.verbose)
slurm_dict=parse_arguments_slurm(parsed_args)
main_dict=parse_arguments_main(parsed_args)
@ -76,12 +76,12 @@ def main_simbelmyne(parsed_args):
if __name__ == "__main__":
from argparse import ArgumentParser
from args_main import register_arguments_main
from timestepping import register_arguments_timestepping, main_timestepping
from parameters_card import register_arguments_card, main_parameter_card
from cosmo_params import register_arguments_cosmo
from parameters_simbelmyne import register_arguments_simbelmyne
from slurm_submission import register_arguments_slurm
from .args_main import register_arguments_main
from .timestepping import register_arguments_timestepping, main_timestepping
from .parameters_card import register_arguments_card, main_parameter_card
from .cosmo_params import register_arguments_cosmo
from .parameters_simbelmyne import register_arguments_simbelmyne
from .slurm_submission import register_arguments_slurm
parser = ArgumentParser(description="Run Simbelmyne.")
register_arguments_main(parser)

11
slurm_submission.py → sbmy_control/slurm_submission.py
View file

@ -1,7 +1,8 @@
from argparse import ArgumentParser
from args_main import parse_arguments_main
from .args_main import parse_arguments_main
path_to_monofonic_binary = "/home/aubin/monofonic/build/monofonIC"
limit_slurm_arrays=799
def register_arguments_slurm(parser:ArgumentParser):
"""
@ -133,11 +134,15 @@ def create_slurm_script(slurm_template:str,
- simbelmyne
- scola
"""
index_sub=0
if array is not None and job != "scola":
raise ValueError(f"Array job range provided for job type {job}.")
if array is None and job == "scola":
raise ValueError(f"Array job range not provided for job type {job}.")
elif job == "scola":
index_sub=array[0]//limit_slurm_arrays
array=(array[0]%limit_slurm_arrays, array[1]%limit_slurm_arrays)
from os.path import isfile
if not isfile(slurm_template):
@ -155,7 +160,7 @@ def create_slurm_script(slurm_template:str,
case "simbelmyne":
command_line = f"{job} {job_config_file} {job_log}"
case "scola":
command_line = f"{job} {job_config_file} {job_log} "+"-b ${SLURM_ARRAY_TASK_ID}"
command_line = f"{job} {job_config_file} {job_log} "+f"-b $(({index_sub*limit_slurm_arrays} + $SLURM_ARRAY_TASK_ID))"
case _:
raise ValueError(f"Job type {job} not recognized.")
@ -163,7 +168,7 @@ def create_slurm_script(slurm_template:str,
with open(slurm_script, "w") as f:
for line in template:
if job_name is not None and "--job-name" in line:
line = f"#SBATCH --job-name={job_name}\n"
line = f"#SBATCH --job-name={index_sub if index_sub!=0 else ''}{job_name}\n"
if array is not None and "--array" in line:
line = f"#SBATCH --array={array[0]}-{array[1]}\n"
if array is not None and ("--output" in line or "--error" in line):

14
timestepping.py → sbmy_control/timestepping.py
View file

@ -18,8 +18,8 @@ def parse_arguments_timestepping(parsed_args):
"""
Parse the arguments for the timestepping.
"""
from parameters_card import parse_arguments_card_for_timestepping
from cosmo_params import parse_arguments_cosmo, z2a
from .parameters_card import parse_arguments_card_for_timestepping
from .cosmo_params import parse_arguments_cosmo, z2a
card_dict = parse_arguments_card_for_timestepping(parsed_args)
cosmo_dict = parse_arguments_cosmo(parsed_args)
@ -79,7 +79,7 @@ def create_timestepping(timestepping_dict, ts_filename:str, verbose:int=1):
TS = StandardTimeStepping(**timestepping_dict)
if verbose < 2:
from io import BytesIO
from low_level import stdout_redirector, stderr_redirector
from .low_level import stdout_redirector, stderr_redirector
f = BytesIO()
g = BytesIO()
with stdout_redirector(f):
@ -95,7 +95,7 @@ def main_timestepping(parsed_args):
"""
Main function for the timestepping.
"""
from low_level import print_message, print_ending_module, print_starting_module
from .low_level import print_message, print_ending_module, print_starting_module
print_starting_module("timestepping", verbose=parsed_args.verbose)
print_message("Parsing arguments for the timestepping file.", 1, "timestepping", verbose=parsed_args.verbose)
@ -110,9 +110,9 @@ def main_timestepping(parsed_args):
return timestepping_dict
if __name__ == "__main__":
from args_main import register_arguments_main
from parameters_card import register_arguments_card_for_timestepping
from cosmo_params import register_arguments_cosmo
from .args_main import register_arguments_main
from .parameters_card import register_arguments_card_for_timestepping
from .cosmo_params import register_arguments_cosmo
parser = ArgumentParser(description="Create timestepping file.")
# TODO: reduce the volume of arguments

42
setup.py Normal file
View file

@ -0,0 +1,42 @@
from setuptools import setup, find_packages
setup(
name='sbmy_control',
version='0.1.0',
author='Mayeul Aubin',
author_email='mayeul.aubin@iap.fr',
description='Simbelmyne control package',
long_description='This package provides control functionalities for Simbelmyne. It allows to create automatically all the required files and scripts to run a N-body simulation with Simbelmyne, using monofonIC for initial conditions. The subpackage `analysis` provides tools to analyze the results of the simulation (slices and power spectra), while the subpackage `scripts` includes tools to handle snapshots, tiles and density fields.',
long_description_content_type='text/markdown',
url='https://git.aquila-consortium.org/maubin/sbmy_control',
packages=find_packages(),
install_requires=[
'pysbmy',
'numpy',
'matplotlib',
'h5py',
'tqdm',
],
license='GPL-3.0',
classifiers=[
'Development Status :: 3 - Alpha',
'Intended Audience :: Science/Research',
'License :: OSI Approved :: GNU General Public License v3 (GPLv3)',
'Programming Language :: Python :: 3',
'Programming Language :: Python :: 3.8',
'Programming Language :: Python :: 3.9',
'Programming Language :: Python :: 3.10',
'Programming Language :: Python :: 3.11',
],
python_requires='>=3.8',
entry_points={
'console_scripts': [
'sbmy_control=sbmy_control.main:console_main',
'slices=sbmy_control.analysis.slices:console_main',
'power_spectrum=sbmy_control.analysis.power_spectrum:console_main',
'field_to_field=sbmy_control.scripts.field_to_field:console_main',
'gather_tiles=sbmy_control.scripts.gather_tiles:console_main',
'convert_snapshot_to_density=sbmy_control.scripts.convert_snapshot_to_density:console_main',
'scola_submit=sbmy_control.scripts.scola_submit:console_main',
],
},
)