.gitignore

@@ -1,3 +1,10 @@
+# Ignore feature_* directory (usually used as git worktree)
+feature_*/
+
+# Ignore extensions directory
+extensions/*
+!extensions/__init__.py
+
 # Ignore some symbolic links
 install
 
@@ -7,5 +14,17 @@ install
 .vscode/
 *.pyc
 __pycache__/
-sbmy_control.egg-info/
+pysbmy.egg-info/
 *.h5
+*.rng
+*.gadget1
+*.gadget2
+*.gadget3
+log.txt
+testpdf.txt
+tests/
+params/
+results/
+slurm_logs/
+slurm_scripts/
+work/

ICs.py

@@ -3,9 +3,9 @@ def main_ICs(parsed_args):
     """
     Main function for the initial conditions generator.
     """
-    from .args_main import parse_arguments_main
+    from args_main import parse_arguments_main
-    from .parameters_card import parse_arguments_card_for_ICs
+    from parameters_card import parse_arguments_card_for_ICs
-    from .low_level import print_starting_module, print_message, print_ending_module
+    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 low_level import print_message
-    from .parameters_monofonic import parse_arguments_monofonic
+    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 args_main import register_arguments_main
-    from .parameters_card import register_arguments_card_for_ICs
+    from parameters_card import register_arguments_card_for_ICs
-    from .cosmo_params import register_arguments_cosmo
+    from cosmo_params import register_arguments_cosmo
-    from .parameters_monofonic import register_arguments_monofonic
+    from parameters_monofonic import register_arguments_monofonic
-    from .slurm_submission import register_arguments_slurm
+    from slurm_submission import register_arguments_slurm
 
     parser = ArgumentParser(description="Generate initial conditions for a Simbelmyne simulation.")
     # TODO: reduce the volume of arguments

analysis/power_spectrum.py

@@ -1,29 +1,10 @@
 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
@@ -34,10 +15,10 @@ def get_power_spectrum(field, kmin=kmin, kmax=kmax, Nk=Nk, G=None):
             field.L0,
             field.L1,
             field.L2,
-            int(field.N0),
+            field.N0,
-            int(field.N1),
+            field.N1,
-            int(field.N2),
+            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(
+            k_modes=np.concat([PowerSpectrum(field.L0,field.L1,field.L2,field.N0,field.N1,field.N2,).FourierGrid.k_modes[:10],np.logspace(
                 np.log10(kmin),
                 np.log10(kmax),
                 Nk,
@@ -62,10 +43,10 @@ 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,
-            int(field_A.N0),
+            field_A.N0,
-            int(field_A.N1),
+            field_A.N1,
-            int(field_A.N2),
+            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(
+            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(
                 np.log10(kmin),
                 np.log10(kmax),
                 Nk,
@@ -110,8 +91,7 @@ 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 
@@ -130,7 +110,6 @@ 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,
@@ -149,7 +128,7 @@ 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=-0)
+    ax.set_xlabel(r'$k$ [$h/\mathrm{Mpc}$]', labelpad=-10)
 
     if Pk_ref is not None:
         ax.set_ylabel(r'$P(k)/P_\mathrm{ref}(k)$')
@@ -184,9 +163,7 @@ 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 
@@ -204,11 +181,9 @@ 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,
@@ -227,7 +202,7 @@ 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=-0)
+    ax.set_xlabel(r'$k$ [$h/\mathrm{Mpc}$]', labelpad=-10)
     ax.set_ylabel('$R(k)$')
     
     if bound1 is not None:
@@ -263,15 +238,13 @@ 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, default='./', help='Directory containing the fields files.')
+    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.')
@@ -282,7 +255,6 @@ def console_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()
 
@@ -290,15 +262,9 @@ def console_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
-        F_ref = read_field(args.directory+args.reference)
+        G, _, Pk_ref = get_power_spectrum(read_field(args.directory+args.reference), kmin=kmin, kmax=kmax, Nk=Nk)
-        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
@@ -313,7 +279,6 @@ def console_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,
@@ -329,9 +294,7 @@ def console_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,
@@ -348,9 +311,7 @@ def console_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")
@@ -373,9 +334,7 @@ def console_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)
@@ -394,9 +353,7 @@ def console_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)
@@ -407,6 +364,3 @@ def console_main():
         fig.savefig(args.directory+'power_spectrum.png')
     
 
-if __name__ == "__main__":
-    console_main()
-    

analysis/slices.py

@@ -0,0 +1,176 @@
+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')

low_level.py

@@ -225,8 +225,6 @@ 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
 
 
@@ -239,6 +237,7 @@ 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

main.py

@@ -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 simbelmyne import main_simbelmyne
-            from .parameters_card import parse_arguments_card
+            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 scola import main_pre_scola
-            from .parameters_card import parse_arguments_card
+            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 scola import main_post_scola
-            from .parameters_card import parse_arguments_card
+            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 scola import main_scola
-            from .parameters_card import parse_arguments_card
+            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 parameters_card import parse_arguments_card, main_parameter_card
-            from .timestepping import main_timestepping
+            from timestepping import main_timestepping
-            from .ICs import main_ICs
+            from ICs import main_ICs
-            from .simbelmyne import main_simbelmyne
+            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'}")
@@ -133,17 +133,10 @@ 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)
 
@@ -153,7 +146,7 @@ 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'}")
@@ -186,7 +179,7 @@ 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)
@@ -227,15 +220,15 @@ def check_consistency(card_dict, mode):
             raise ValueError(f"ModulePMCOLA is not 1: ModulePMCOLA={card_dict["ModulePMCOLA"]}")
 
 
-def console_main():
+if __name__ == "__main__":
     from argparse import ArgumentParser
-    from .args_main import register_arguments_main
+    from args_main import register_arguments_main
-    from .timestepping import register_arguments_timestepping, main_timestepping
+    from timestepping import register_arguments_timestepping, main_timestepping
-    from .parameters_card import register_arguments_card, main_parameter_card
+    from parameters_card import register_arguments_card, main_parameter_card
-    from .cosmo_params import register_arguments_cosmo
+    from cosmo_params import register_arguments_cosmo
-    from .parameters_monofonic import register_arguments_monofonic
+    from parameters_monofonic import register_arguments_monofonic
-    from .slurm_submission import register_arguments_slurm
+    from slurm_submission import register_arguments_slurm
-    from .low_level import wait_until_file_exists
+    from low_level import wait_until_file_exists
 
     parser = ArgumentParser(description="Run sCOLA.")
     register_arguments_main(parser)
@@ -246,8 +239,3 @@ def console_main():
     register_arguments_cosmo(parser)
     parsed_args = parser.parse_args()
     main(parsed_args)
-
-
-if __name__ == "__main__":
-    console_main()
-    

monofonic.py

@@ -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 parameters_monofonic import main_parameters_monofonic
-    from .low_level import print_starting_module, print_message, print_ending_module
+    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 slurm_submission import create_slurm_script, parse_arguments_slurm
-        from .args_main import parse_arguments_main
+        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 parameters_monofonic import register_arguments_monofonic
-    from .args_main import register_arguments_main
+    from args_main import register_arguments_main
-    from .parameters_card import register_arguments_card_for_ICs
+    from parameters_card import register_arguments_card_for_ICs
-    from .cosmo_params import register_arguments_cosmo
+    from cosmo_params import register_arguments_cosmo
-    from .slurm_submission import register_arguments_slurm
+    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 

parameters_card.py

@@ -47,7 +47,6 @@ 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.")
@@ -57,12 +56,6 @@ 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):
@@ -89,8 +82,8 @@ def parse_arguments_card(parsed_args):
     """
     Parse the arguments for the parameter card.
     """
-    from .args_main import parse_arguments_main
+    from args_main import parse_arguments_main
-    from .cosmo_params import parse_arguments_cosmo
+    from cosmo_params import parse_arguments_cosmo
 
     cosmo_dict=parse_arguments_cosmo(parsed_args)
     card_dict=dict(
@@ -128,10 +121,6 @@ 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,
@@ -233,7 +222,6 @@ 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"]
@@ -245,12 +233,6 @@ 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
 
@@ -260,7 +242,7 @@ 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(
@@ -300,7 +282,7 @@ 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(
@@ -369,7 +351,6 @@ 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',
@@ -379,13 +360,6 @@ 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,
@@ -441,10 +415,6 @@ 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,
@@ -482,7 +452,7 @@ 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()
@@ -501,7 +471,7 @@ 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)
@@ -517,8 +487,8 @@ def main_parameter_card(parsed_args):
     return card_dict
 
 if __name__ == "__main__":
-    from .args_main import register_arguments_main
+    from args_main import register_arguments_main
-    from .cosmo_params import register_arguments_cosmo
+    from cosmo_params import register_arguments_cosmo
 
     parser = ArgumentParser(description="Create sbmy parameter card.")
     register_arguments_main(parser)

parameters_monofonic.py

@@ -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 args_main import parse_arguments_main
-    from .parameters_card import parse_arguments_card_for_ICs
+    from parameters_card import parse_arguments_card_for_ICs
-    from .cosmo_params import parse_arguments_cosmo
+    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": 99.0,
+        "zstart": 999.0,
         "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 args_main import register_arguments_main
-    from .parameters_card import register_arguments_card_for_ICs
+    from parameters_card import register_arguments_card_for_ICs
-    from .cosmo_params import register_arguments_cosmo
+    from cosmo_params import register_arguments_cosmo
 
     parser = ArgumentParser(description="Create monofonIC configuration file.")
     register_arguments_main(parser)

progress_bar.py

@@ -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.")

sbmy_control/analysis/colormaps.py

@@ -1,36 +0,0 @@
-
-
-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

sbmy_control/analysis/slices.py

@@ -1,228 +0,0 @@
-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()

sbmy_control/scripts/convert_snapshot_to_density.py

@@ -1,82 +0,0 @@
-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()

sbmy_control/scripts/field_to_field.py

@@ -1,134 +0,0 @@
-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()

sbmy_control/scripts/gather_tiles.py

@@ -1,128 +0,0 @@
-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()

sbmy_control/scripts/scola_submit.py

@@ -1,502 +0,0 @@
-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()
-
-
-
-            

scola.py

@@ -1,8 +1,6 @@
-
-
 def main_scola(parsed_args):
-    from .args_main import parse_arguments_main
+    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 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
     
@@ -21,7 +19,7 @@ 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)
@@ -52,16 +50,14 @@ 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, limit_slurm_arrays
+        from slurm_submission import create_slurm_script, parse_arguments_slurm
-        from .args_main import parse_arguments_main
+        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) and card_dict["N_tiles"]**3 < limit_slurm_arrays :
+        if have_no_tiles(parsed_args) or parsed_args.force:
             ## Submit all boxes
             print_message("Submitting all boxes.", 2, "scola", verbose=parsed_args.verbose)
             slurm_script = slurm_dict["scripts"]+"scola_"+main_dict["simname"]+".sh"
@@ -97,7 +93,6 @@ 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)
 
@@ -132,7 +127,6 @@ 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)
 
@@ -148,15 +142,15 @@ 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 low_level import print_starting_module, print_message, print_ending_module
-    from .parameters_card import parse_arguments_card
+    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.")
@@ -172,8 +166,8 @@ 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 low_level import print_starting_module, print_message, print_ending_module
-    from .parameters_card import parse_arguments_card
+    from parameters_card import parse_arguments_card
     print_starting_module("post-scola", verbose=parsed_args.verbose)
     card_dict = parse_arguments_card(parsed_args)
 
@@ -186,7 +180,7 @@ 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)
@@ -203,7 +197,7 @@ 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)
@@ -216,7 +210,7 @@ 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)
@@ -229,24 +223,17 @@ 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
@@ -260,13 +247,13 @@ def get_missing_tiles_arrays(parsed_args):
 
 if __name__ == "__main__":
     from argparse import ArgumentParser
-    from .args_main import register_arguments_main
+    from args_main import register_arguments_main
-    from .timestepping import register_arguments_timestepping, main_timestepping
+    from timestepping import register_arguments_timestepping, main_timestepping
-    from .parameters_card import register_arguments_card, main_parameter_card
+    from parameters_card import register_arguments_card, main_parameter_card
-    from .cosmo_params import register_arguments_cosmo
+    from cosmo_params import register_arguments_cosmo
-    from .parameters_monofonic import register_arguments_monofonic
+    from parameters_monofonic import register_arguments_monofonic
-    from .slurm_submission import register_arguments_slurm
+    from slurm_submission import register_arguments_slurm
-    from .low_level import wait_until_file_exists
+    from low_level import wait_until_file_exists
 
     parser = ArgumentParser(description="Run sCOLA.")
     register_arguments_main(parser)

setup.py

@@ -1,42 +0,0 @@
-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',
-        ],
-    },
-)

simbelmyne.py

@@ -1,6 +1,6 @@
 def main_simbelmyne(parsed_args):
-    from .args_main import parse_arguments_main
+    from args_main import parse_arguments_main
-    from .low_level import print_starting_module, print_message, print_ending_module, progress_bar_from_logfile
+    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 slurm_submission import create_slurm_script, parse_arguments_slurm
-        from .args_main import parse_arguments_main
+        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 args_main import register_arguments_main
-    from .timestepping import register_arguments_timestepping, main_timestepping
+    from timestepping import register_arguments_timestepping, main_timestepping
-    from .parameters_card import register_arguments_card, main_parameter_card
+    from parameters_card import register_arguments_card, main_parameter_card
-    from .cosmo_params import register_arguments_cosmo
+    from cosmo_params import register_arguments_cosmo
-    from .parameters_simbelmyne import register_arguments_simbelmyne
+    from parameters_simbelmyne import register_arguments_simbelmyne
-    from .slurm_submission import register_arguments_slurm
+    from slurm_submission import register_arguments_slurm
 
     parser = ArgumentParser(description="Run Simbelmyne.")
     register_arguments_main(parser)

slurm_submission.py

@@ -1,8 +1,7 @@
 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):
     """
@@ -134,15 +133,11 @@ 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):
@@ -160,7 +155,7 @@ 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} "+f"-b $(({index_sub*limit_slurm_arrays} + $SLURM_ARRAY_TASK_ID))"
+            command_line = f"{job} {job_config_file} {job_log} "+"-b ${SLURM_ARRAY_TASK_ID}"
         case _:
             raise ValueError(f"Job type {job} not recognized.")
     
@@ -168,7 +163,7 @@ 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={index_sub if index_sub!=0 else ''}{job_name}\n"
+                line = f"#SBATCH --job-name={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):

timestepping.py

@@ -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 parameters_card import parse_arguments_card_for_timestepping
-    from .cosmo_params import parse_arguments_cosmo, z2a
+    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 args_main import register_arguments_main
-    from .parameters_card import register_arguments_card_for_timestepping
+    from parameters_card import register_arguments_card_for_timestepping
-    from .cosmo_params import register_arguments_cosmo
+    from cosmo_params import register_arguments_cosmo
 
     parser = ArgumentParser(description="Create timestepping file.")
     # TODO: reduce the volume of arguments