diff --git a/analysis/colormaps.py b/analysis/colormaps.py new file mode 100644 index 0000000..54ddf3a --- /dev/null +++ b/analysis/colormaps.py @@ -0,0 +1,36 @@ + + +def register_colormaps(colormaps): + + # Register cmasher + try: + import cmasher as cma + for name, cmap in cma.cm.cmap_d.items(): + try: + colormaps.register(name=name, cmap=cmap) + except ValueError: + pass + except ImportError: + pass + + # Register cmocean + try: + import cmocean as cmo + for name, cmap in cmo.cm.cmap_d.items(): + try: + colormaps.register(name=name, cmap=cmap) + except ValueError: + pass + except ImportError: + pass + + # Register cmcrameri + try: + import cmcrameri as cmc + for name, cmap in cmc.cm.cmaps.items(): + try: + colormaps.register(name=name, cmap=cmap) + except ValueError: + pass + except ImportError: + pass diff --git a/analysis/power_spectrum.py b/analysis/power_spectrum.py index 93bb8ee..9d44005 100644 --- a/analysis/power_spectrum.py +++ b/analysis/power_spectrum.py @@ -5,6 +5,24 @@ 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 @@ -91,7 +109,8 @@ def plot_power_spectra(filenames, figsize=(8,4), dpi=300, ax=None, - fig=None,): + fig=None, + Ncrop=None,): import matplotlib.pyplot as plt from pysbmy.field import read_field @@ -110,6 +129,7 @@ def plot_power_spectra(filenames, for i, filename in enumerate(filenames): field = read_field(filename) + crop_field(field, Ncrop) _, G, k, _ = add_power_spectrum_to_plot(ax=ax, field=field, Pk_ref=Pk_ref, @@ -128,7 +148,7 @@ def plot_power_spectra(filenames, ax.set_ylim(ylims) if yticks is not None: ax.set_yticks(yticks) - ax.set_xlabel(r'$k$ [$h/\mathrm{Mpc}$]', labelpad=-10) + ax.set_xlabel(r'$k$ [$h/\mathrm{Mpc}$]', labelpad=-0) if Pk_ref is not None: ax.set_ylabel(r'$P(k)/P_\mathrm{ref}(k)$') @@ -163,7 +183,9 @@ def plot_cross_correlations(filenames_A, figsize=(8,4), dpi=300, ax=None, - fig=None,): + fig=None, + Ncrop=None, + ): import matplotlib.pyplot as plt from pysbmy.field import read_field @@ -181,9 +203,11 @@ def plot_cross_correlations(filenames_A, markers = [None for f in filenames_A] field_B = read_field(filename_B) + crop_field(field_B, Ncrop) for i, filename_A in enumerate(filenames_A): field_A = read_field(filename_A) + crop_field(field_A, Ncrop) _, G, k, _ = add_cross_correlations_to_plot(ax=ax, field_A=field_A, field_B=field_B, @@ -202,7 +226,7 @@ def plot_cross_correlations(filenames_A, ax.set_ylim(ylims) if yticks is not None: ax.set_yticks(yticks) - ax.set_xlabel(r'$k$ [$h/\mathrm{Mpc}$]', labelpad=-10) + ax.set_xlabel(r'$k$ [$h/\mathrm{Mpc}$]', labelpad=-0) ax.set_ylabel('$R(k)$') if bound1 is not None: @@ -255,6 +279,7 @@ if __name__ == "__main__": parser.add_argument('-t','--title', type=str, default=None, help='Title of the plot.') parser.add_argument('-yrp', '--ylim_power', type=float, nargs=2, default=[0.9,1.1], help='Y-axis limits.') parser.add_argument('-yrc', '--ylim_corr', type=float, nargs=2, default=[0.99,1.001], help='Y-axis limits.') + parser.add_argument('--crop', type=int, default=None, help='Remove the outter N pixels of the fields.') args = parser.parse_args() @@ -264,7 +289,9 @@ if __name__ == "__main__": if args.reference is not None: from pysbmy.field import read_field - G, _, Pk_ref = get_power_spectrum(read_field(args.directory+args.reference), kmin=kmin, kmax=kmax, Nk=Nk) + F_ref = read_field(args.directory+args.reference) + crop_field(F_ref, args.crop) + G, _, Pk_ref = get_power_spectrum(F_ref, kmin=kmin, kmax=kmax, Nk=Nk) else: Pk_ref = None G = None @@ -279,6 +306,7 @@ if __name__ == "__main__": if args.power_spectrum and args.cross_correlation: import matplotlib.pyplot as plt fig, axes = plt.subplots(2, 1, figsize=(8,8)) + fig.subplots_adjust(hspace=0.3) plot_power_spectra(filenames=filenames, labels=args.labels, colors=args.colors, @@ -294,7 +322,9 @@ if __name__ == "__main__": kmax=kmax, Nk=Nk, ax=axes[0], - fig=fig) + fig=fig, + Ncrop=args.crop, + ) plot_cross_correlations(filenames_A=filenames, filename_B=args.directory+args.reference, @@ -311,7 +341,9 @@ if __name__ == "__main__": kmax=kmax, Nk=Nk, ax=axes[1], - fig=fig) + fig=fig, + Ncrop=args.crop, + ) axes[1].legend(loc='lower left') axes[0].set_title("Power Spectrum") @@ -334,7 +366,9 @@ if __name__ == "__main__": bound2=0.02, kmin=kmin, kmax=kmax, - Nk=Nk) + Nk=Nk, + Ncrop=args.crop, + ) ax.legend() if args.title is not None: ax.set_title(args.title) @@ -353,7 +387,9 @@ if __name__ == "__main__": bound2=0.002, kmin=kmin, kmax=kmax, - Nk=Nk) + Nk=Nk, + Ncrop=args.crop, + ) ax.legend(loc='lower left') if args.title is not None: ax.set_title(args.title) diff --git a/analysis/slices.py b/analysis/slices.py index 4f01418..2febe16 100644 --- a/analysis/slices.py +++ b/analysis/slices.py @@ -2,10 +2,21 @@ 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 +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(tick_labels) + ax.set_yticklabels(tick_labels) + ax.set_xlabel('Mpc/h') + ax.xaxis.set_major_formatter(ticker.FormatStrFormatter('%d')) + ax.yaxis.set_major_formatter(ticker.FormatStrFormatter('%d')) + + def plot_imshow_with_reference( data_list, reference=None, @@ -13,7 +24,9 @@ def plot_imshow_with_reference( data_list, vmin=None, vmax=None, L=None, - cmap='viridis'): + 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. @@ -25,7 +38,9 @@ def plot_imshow_with_reference( data_list, - cmap: colormap to be used for plotting """ import matplotlib.pyplot as plt - from matplotlib import ticker + + from colormaps import register_colormaps + register_colormaps(plt.colormaps) if titles is None: titles = [None for f in data_list] @@ -43,7 +58,7 @@ def plot_imshow_with_reference( data_list, 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)) + 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) @@ -52,72 +67,88 @@ def plot_imshow_with_reference( 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 - 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') - axes[0, i].xaxis.set_major_formatter(ticker.FormatStrFormatter('%d')) - axes[0, i].yaxis.set_major_formatter(ticker.FormatStrFormatter('%d')) - fig.colorbar(im, ax=axes[0, :], orientation='vertical') + # 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, 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') - axes[1, i].xaxis.set_major_formatter(ticker.FormatStrFormatter('%d')) - axes[1, i].yaxis.set_major_formatter(ticker.FormatStrFormatter('%d')) + 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='white') + 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() - 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') - axes.xaxis.set_major_formatter(ticker.FormatStrFormatter('%d')) - axes.yaxis.set_major_formatter(ticker.FormatStrFormatter('%d')) - 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') - axes[i].xaxis.set_major_formatter(ticker.FormatStrFormatter('%d')) - axes[i].yaxis.set_major_formatter(ticker.FormatStrFormatter('%d')) - fig.colorbar(im, ax=axes[:], orientation='vertical') 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 colormaps 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 + + + if __name__ == "__main__": from argparse import ArgumentParser parser = ArgumentParser(description='Comparisons of fields slices.') @@ -134,16 +165,24 @@ if __name__ == "__main__": 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) + 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 - # from pysbmy.cosmology import d_plus + ref_label = args.ref_label 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] + fields = [] + for k,f in enumerate(args.filenames): + 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 @@ -157,10 +196,6 @@ if __name__ == "__main__": 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] @@ -175,8 +210,10 @@ if __name__ == "__main__": 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) + 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: