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<title>selfisys package &mdash; SelfiSys /Users/hoellinger/Library/CloudStorage/Dropbox/travail/these/science/code/SELFI/selfisys/src/ documentation</title>
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SelfiSys
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<p class="caption" role="heading"><span class="caption-text">API Documentation</span></p>
<ul>
<li class="toctree-l1"><a class="reference internal" href="selfisys.hiddenbox.html">hiddenbox</a><ul>
<li class="toctree-l2"><a class="reference internal" href="selfisys.hiddenbox.html#selfisys.hiddenbox.HiddenBox"><code class="docutils literal notranslate"><span class="pre">HiddenBox</span></code></a><ul>
<li class="toctree-l3"><a class="reference internal" href="selfisys.hiddenbox.html#selfisys.hiddenbox.HiddenBox.Npop"><code class="docutils literal notranslate"><span class="pre">HiddenBox.Npop</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.hiddenbox.html#selfisys.hiddenbox.HiddenBox.Ntimesteps"><code class="docutils literal notranslate"><span class="pre">HiddenBox.Ntimesteps</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.hiddenbox.html#selfisys.hiddenbox.HiddenBox.Psingle"><code class="docutils literal notranslate"><span class="pre">HiddenBox.Psingle</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.hiddenbox.html#selfisys.hiddenbox.HiddenBox.compute_pool"><code class="docutils literal notranslate"><span class="pre">HiddenBox.compute_pool()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.hiddenbox.html#selfisys.hiddenbox.HiddenBox.evaluate"><code class="docutils literal notranslate"><span class="pre">HiddenBox.evaluate()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.hiddenbox.html#selfisys.hiddenbox.HiddenBox.force_neglect_lightcone"><code class="docutils literal notranslate"><span class="pre">HiddenBox.force_neglect_lightcone</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.hiddenbox.html#selfisys.hiddenbox.HiddenBox.force_recompute_mocks"><code class="docutils literal notranslate"><span class="pre">HiddenBox.force_recompute_mocks</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.hiddenbox.html#selfisys.hiddenbox.HiddenBox.gravity_on"><code class="docutils literal notranslate"><span class="pre">HiddenBox.gravity_on</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.hiddenbox.html#selfisys.hiddenbox.HiddenBox.load_pool"><code class="docutils literal notranslate"><span class="pre">HiddenBox.load_pool()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.hiddenbox.html#selfisys.hiddenbox.HiddenBox.make_data"><code class="docutils literal notranslate"><span class="pre">HiddenBox.make_data()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.hiddenbox.html#selfisys.hiddenbox.HiddenBox.modified_selfi"><code class="docutils literal notranslate"><span class="pre">HiddenBox.modified_selfi</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.hiddenbox.html#selfisys.hiddenbox.HiddenBox.prefix_mocks"><code class="docutils literal notranslate"><span class="pre">HiddenBox.prefix_mocks</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.hiddenbox.html#selfisys.hiddenbox.HiddenBox.reset_survey"><code class="docutils literal notranslate"><span class="pre">HiddenBox.reset_survey()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.hiddenbox.html#selfisys.hiddenbox.HiddenBox.setup_only"><code class="docutils literal notranslate"><span class="pre">HiddenBox.setup_only</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.hiddenbox.html#selfisys.hiddenbox.HiddenBox.switch_recompute_pool"><code class="docutils literal notranslate"><span class="pre">HiddenBox.switch_recompute_pool()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.hiddenbox.html#selfisys.hiddenbox.HiddenBox.switch_setup"><code class="docutils literal notranslate"><span class="pre">HiddenBox.switch_setup()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.hiddenbox.html#selfisys.hiddenbox.HiddenBox.update"><code class="docutils literal notranslate"><span class="pre">HiddenBox.update()</span></code></a></li>
</ul>
</li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="selfisys.normalise_hb.html">normalise_hb</a><ul>
<li class="toctree-l2"><a class="reference internal" href="selfisys.normalise_hb.html#selfisys.normalise_hb.define_normalisation"><code class="docutils literal notranslate"><span class="pre">define_normalisation()</span></code></a></li>
<li class="toctree-l2"><a class="reference internal" href="selfisys.normalise_hb.html#selfisys.normalise_hb.worker_normalisation"><code class="docutils literal notranslate"><span class="pre">worker_normalisation()</span></code></a></li>
<li class="toctree-l2"><a class="reference internal" href="selfisys.normalise_hb.html#selfisys.normalise_hb.worker_normalisation_public"><code class="docutils literal notranslate"><span class="pre">worker_normalisation_public()</span></code></a></li>
<li class="toctree-l2"><a class="reference internal" href="selfisys.normalise_hb.html#selfisys.normalise_hb.worker_normalisation_wrapper"><code class="docutils literal notranslate"><span class="pre">worker_normalisation_wrapper()</span></code></a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="selfisys.prior.html">prior</a><ul>
<li class="toctree-l2"><a class="reference internal" href="selfisys.prior.html#selfisys.prior.get_summary"><code class="docutils literal notranslate"><span class="pre">get_summary()</span></code></a></li>
<li class="toctree-l2"><a class="reference internal" href="selfisys.prior.html#selfisys.prior.logposterior_hyperparameters_parallel"><code class="docutils literal notranslate"><span class="pre">logposterior_hyperparameters_parallel()</span></code></a></li>
<li class="toctree-l2"><a class="reference internal" href="selfisys.prior.html#selfisys.prior.perform_prior_optimisation_and_plot"><code class="docutils literal notranslate"><span class="pre">perform_prior_optimisation_and_plot()</span></code></a></li>
<li class="toctree-l2"><a class="reference internal" href="selfisys.prior.html#selfisys.prior.planck_prior"><code class="docutils literal notranslate"><span class="pre">planck_prior</span></code></a><ul>
<li class="toctree-l3"><a class="reference internal" href="selfisys.prior.html#selfisys.prior.planck_prior.mean"><code class="docutils literal notranslate"><span class="pre">planck_prior.mean</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.prior.html#selfisys.prior.planck_prior.covariance"><code class="docutils literal notranslate"><span class="pre">planck_prior.covariance</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.prior.html#selfisys.prior.planck_prior.inv_covariance"><code class="docutils literal notranslate"><span class="pre">planck_prior.inv_covariance</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.prior.html#selfisys.prior.planck_prior.Nbin_max"><code class="docutils literal notranslate"><span class="pre">planck_prior.Nbin_max</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.prior.html#selfisys.prior.planck_prior.Nbin_min"><code class="docutils literal notranslate"><span class="pre">planck_prior.Nbin_min</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.prior.html#selfisys.prior.planck_prior.compute"><code class="docutils literal notranslate"><span class="pre">planck_prior.compute()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.prior.html#selfisys.prior.planck_prior.load"><code class="docutils literal notranslate"><span class="pre">planck_prior.load()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.prior.html#selfisys.prior.planck_prior.logpdf"><code class="docutils literal notranslate"><span class="pre">planck_prior.logpdf()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.prior.html#selfisys.prior.planck_prior.sample"><code class="docutils literal notranslate"><span class="pre">planck_prior.sample()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.prior.html#selfisys.prior.planck_prior.save"><code class="docutils literal notranslate"><span class="pre">planck_prior.save()</span></code></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="selfisys.prior.html#selfisys.prior.worker_class"><code class="docutils literal notranslate"><span class="pre">worker_class()</span></code></a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="selfisys.selection_functions.html">selection_functions</a><ul>
<li class="toctree-l2"><a class="reference internal" href="selfisys.selection_functions.html#selfisys.selection_functions.LognormalSelection"><code class="docutils literal notranslate"><span class="pre">LognormalSelection</span></code></a><ul>
<li class="toctree-l3"><a class="reference internal" href="selfisys.selection_functions.html#selfisys.selection_functions.LognormalSelection.init_selection"><code class="docutils literal notranslate"><span class="pre">LognormalSelection.init_selection()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.selection_functions.html#selfisys.selection_functions.LognormalSelection.lognormals_z_to_x"><code class="docutils literal notranslate"><span class="pre">LognormalSelection.lognormals_z_to_x()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.selection_functions.html#selfisys.selection_functions.LognormalSelection.multiple_lognormal"><code class="docutils literal notranslate"><span class="pre">LognormalSelection.multiple_lognormal()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.selection_functions.html#selfisys.selection_functions.LognormalSelection.multiple_lognormal_z"><code class="docutils literal notranslate"><span class="pre">LognormalSelection.multiple_lognormal_z()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.selection_functions.html#selfisys.selection_functions.LognormalSelection.one_lognormal"><code class="docutils literal notranslate"><span class="pre">LognormalSelection.one_lognormal()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.selection_functions.html#selfisys.selection_functions.LognormalSelection.one_lognormal_z"><code class="docutils literal notranslate"><span class="pre">LognormalSelection.one_lognormal_z()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.selection_functions.html#selfisys.selection_functions.LognormalSelection.r_grid"><code class="docutils literal notranslate"><span class="pre">LognormalSelection.r_grid()</span></code></a></li>
</ul>
</li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="selfisys.selfi_interface.html">selfi_interface</a><ul>
<li class="toctree-l2"><a class="reference internal" href="selfisys.selfi_interface.html#selfisys.selfi_interface.PrintMessage"><code class="docutils literal notranslate"><span class="pre">PrintMessage()</span></code></a></li>
<li class="toctree-l2"><a class="reference internal" href="selfisys.selfi_interface.html#selfisys.selfi_interface.indent"><code class="docutils literal notranslate"><span class="pre">indent()</span></code></a></li>
<li class="toctree-l2"><a class="reference internal" href="selfisys.selfi_interface.html#selfisys.selfi_interface.unindent"><code class="docutils literal notranslate"><span class="pre">unindent()</span></code></a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="selfisys.sbmy_interface.html">sbmy_interface</a><ul>
<li class="toctree-l2"><a class="reference internal" href="selfisys.sbmy_interface.html#selfisys.sbmy_interface.compute_Phi"><code class="docutils literal notranslate"><span class="pre">compute_Phi()</span></code></a></li>
<li class="toctree-l2"><a class="reference internal" href="selfisys.sbmy_interface.html#selfisys.sbmy_interface.generate_white_noise_Field"><code class="docutils literal notranslate"><span class="pre">generate_white_noise_Field()</span></code></a></li>
<li class="toctree-l2"><a class="reference internal" href="selfisys.sbmy_interface.html#selfisys.sbmy_interface.get_power_spectrum_from_cosmo"><code class="docutils literal notranslate"><span class="pre">get_power_spectrum_from_cosmo()</span></code></a></li>
<li class="toctree-l2"><a class="reference internal" href="selfisys.sbmy_interface.html#selfisys.sbmy_interface.handle_time_stepping"><code class="docutils literal notranslate"><span class="pre">handle_time_stepping()</span></code></a></li>
<li class="toctree-l2"><a class="reference internal" href="selfisys.sbmy_interface.html#selfisys.sbmy_interface.setup_sbmy_parfiles"><code class="docutils literal notranslate"><span class="pre">setup_sbmy_parfiles()</span></code></a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="selfisys.grf.html">grf</a><ul>
<li class="toctree-l2"><a class="reference internal" href="selfisys.grf.html#selfisys.grf.primordial_grf"><code class="docutils literal notranslate"><span class="pre">primordial_grf()</span></code></a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="selfisys.utils.html">selfisys.utils package</a><ul>
<li class="toctree-l2"><a class="reference internal" href="selfisys.utils.html#submodules">Submodules</a></li>
<li class="toctree-l2"><a class="reference internal" href="selfisys.utils.html#module-selfisys.utils.examples_utils">selfisys.utils.examples_utils module</a><ul>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.examples_utils.clear_large_plot"><code class="docutils literal notranslate"><span class="pre">clear_large_plot()</span></code></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="selfisys.utils.html#module-selfisys.utils.logger">selfisys.utils.logger module</a><ul>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.logger.CustomLogger"><code class="docutils literal notranslate"><span class="pre">CustomLogger</span></code></a><ul>
<li class="toctree-l4"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.logger.CustomLogger.diagnostic"><code class="docutils literal notranslate"><span class="pre">CustomLogger.diagnostic()</span></code></a></li>
</ul>
</li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.logger.CustomLoggerHandler"><code class="docutils literal notranslate"><span class="pre">CustomLoggerHandler</span></code></a><ul>
<li class="toctree-l4"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.logger.CustomLoggerHandler.emit"><code class="docutils literal notranslate"><span class="pre">CustomLoggerHandler.emit()</span></code></a></li>
</ul>
</li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.logger.INDENT"><code class="docutils literal notranslate"><span class="pre">INDENT()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.logger.PrintDiagnostic"><code class="docutils literal notranslate"><span class="pre">PrintDiagnostic()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.logger.PrintError"><code class="docutils literal notranslate"><span class="pre">PrintError()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.logger.PrintInfo"><code class="docutils literal notranslate"><span class="pre">PrintInfo()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.logger.PrintLeftType"><code class="docutils literal notranslate"><span class="pre">PrintLeftType()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.logger.PrintWarning"><code class="docutils literal notranslate"><span class="pre">PrintWarning()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.logger.UNINDENT"><code class="docutils literal notranslate"><span class="pre">UNINDENT()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.logger.getCustomLogger"><code class="docutils literal notranslate"><span class="pre">getCustomLogger()</span></code></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="selfisys.utils.html#module-selfisys.utils.low_level">selfisys.utils.low_level module</a><ul>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.low_level.stderr_redirector"><code class="docutils literal notranslate"><span class="pre">stderr_redirector()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.low_level.stdout_redirector"><code class="docutils literal notranslate"><span class="pre">stdout_redirector()</span></code></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="selfisys.utils.html#module-selfisys.utils.parser">selfisys.utils.parser module</a><ul>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.parser.bool_sh"><code class="docutils literal notranslate"><span class="pre">bool_sh()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.parser.check_files_exist"><code class="docutils literal notranslate"><span class="pre">check_files_exist()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.parser.intNone"><code class="docutils literal notranslate"><span class="pre">intNone()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.parser.joinstrs"><code class="docutils literal notranslate"><span class="pre">joinstrs()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.parser.joinstrs_only"><code class="docutils literal notranslate"><span class="pre">joinstrs_only()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.parser.none_or_bool_or_str"><code class="docutils literal notranslate"><span class="pre">none_or_bool_or_str()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.parser.safe_npload"><code class="docutils literal notranslate"><span class="pre">safe_npload()</span></code></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="selfisys.utils.html#module-selfisys.utils.path_utils">selfisys.utils.path_utils module</a><ul>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.path_utils.file_names_evaluate"><code class="docutils literal notranslate"><span class="pre">file_names_evaluate()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.path_utils.get_file_names"><code class="docutils literal notranslate"><span class="pre">get_file_names()</span></code></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="selfisys.utils.html#module-selfisys.utils.plot_examples">selfisys.utils.plot_examples module</a><ul>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_examples.plot_comoving_distance_redshift"><code class="docutils literal notranslate"><span class="pre">plot_comoving_distance_redshift()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_examples.plot_galaxy_field_slice"><code class="docutils literal notranslate"><span class="pre">plot_galaxy_field_slice()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_examples.plot_power_spectrum"><code class="docutils literal notranslate"><span class="pre">plot_power_spectrum()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_examples.plot_selection_functions_def_in_z"><code class="docutils literal notranslate"><span class="pre">plot_selection_functions_def_in_z()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_examples.redshift_distance_conversion"><code class="docutils literal notranslate"><span class="pre">redshift_distance_conversion()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_examples.relative_error_analysis"><code class="docutils literal notranslate"><span class="pre">relative_error_analysis()</span></code></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="selfisys.utils.html#module-selfisys.utils.plot_params">selfisys.utils.plot_params module</a><ul>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_params.ScalarFormatterForceFormat_11"><code class="docutils literal notranslate"><span class="pre">ScalarFormatterForceFormat_11</span></code></a><ul>
<li class="toctree-l4"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_params.ScalarFormatterForceFormat_11.get_offset"><code class="docutils literal notranslate"><span class="pre">ScalarFormatterForceFormat_11.get_offset()</span></code></a></li>
<li class="toctree-l4"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_params.ScalarFormatterForceFormat_11.set_scientific"><code class="docutils literal notranslate"><span class="pre">ScalarFormatterForceFormat_11.set_scientific()</span></code></a></li>
<li class="toctree-l4"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_params.ScalarFormatterForceFormat_11.set_useOffset"><code class="docutils literal notranslate"><span class="pre">ScalarFormatterForceFormat_11.set_useOffset()</span></code></a></li>
</ul>
</li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_params.create_all_colormaps"><code class="docutils literal notranslate"><span class="pre">create_all_colormaps()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_params.create_colormap"><code class="docutils literal notranslate"><span class="pre">create_colormap()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_params.dynamic_text_scaling"><code class="docutils literal notranslate"><span class="pre">dynamic_text_scaling()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_params.get_contours"><code class="docutils literal notranslate"><span class="pre">get_contours()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_params.reset_plotting"><code class="docutils literal notranslate"><span class="pre">reset_plotting()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_params.setup_plotting"><code class="docutils literal notranslate"><span class="pre">setup_plotting()</span></code></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="selfisys.utils.html#module-selfisys.utils.plot_utils">selfisys.utils.plot_utils module</a><ul>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_utils.plot_C"><code class="docutils literal notranslate"><span class="pre">plot_C()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_utils.plot_fisher"><code class="docutils literal notranslate"><span class="pre">plot_fisher()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_utils.plot_gradients"><code class="docutils literal notranslate"><span class="pre">plot_gradients()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_utils.plot_histogram"><code class="docutils literal notranslate"><span class="pre">plot_histogram()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_utils.plot_mocks"><code class="docutils literal notranslate"><span class="pre">plot_mocks()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_utils.plot_mocks_compact"><code class="docutils literal notranslate"><span class="pre">plot_mocks_compact()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_utils.plot_observations"><code class="docutils literal notranslate"><span class="pre">plot_observations()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_utils.plot_prior_and_posterior_covariances"><code class="docutils literal notranslate"><span class="pre">plot_prior_and_posterior_covariances()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_utils.plot_reconstruction"><code class="docutils literal notranslate"><span class="pre">plot_reconstruction()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_utils.plot_selection_functions"><code class="docutils literal notranslate"><span class="pre">plot_selection_functions()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_utils.plotly_3d"><code class="docutils literal notranslate"><span class="pre">plotly_3d()</span></code></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="selfisys.utils.html#module-selfisys.utils.timestepping">selfisys.utils.timestepping module</a><ul>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.timestepping.merge_nTS"><code class="docutils literal notranslate"><span class="pre">merge_nTS()</span></code></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="selfisys.utils.html#module-selfisys.utils.tools">selfisys.utils.tools module</a><ul>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.tools.cosmo_vector_to_Simbelmyne_dict"><code class="docutils literal notranslate"><span class="pre">cosmo_vector_to_Simbelmyne_dict()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.tools.cosmo_vector_to_class_dict"><code class="docutils literal notranslate"><span class="pre">cosmo_vector_to_class_dict()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.tools.custom_stat"><code class="docutils literal notranslate"><span class="pre">custom_stat()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.tools.fisher_rao"><code class="docutils literal notranslate"><span class="pre">fisher_rao()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.tools.get_k_max"><code class="docutils literal notranslate"><span class="pre">get_k_max()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.tools.get_summary"><code class="docutils literal notranslate"><span class="pre">get_summary()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.tools.none_or_bool_or_str"><code class="docutils literal notranslate"><span class="pre">none_or_bool_or_str()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.tools.params_ids_to_Simbelmyne_dict"><code class="docutils literal notranslate"><span class="pre">params_ids_to_Simbelmyne_dict()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.tools.sample_omega_from_prior"><code class="docutils literal notranslate"><span class="pre">sample_omega_from_prior()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.tools.summary_to_score"><code class="docutils literal notranslate"><span class="pre">summary_to_score()</span></code></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="selfisys.utils.html#module-selfisys.utils.workers">selfisys.utils.workers module</a><ul>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.workers.Simbelmyne_worker"><code class="docutils literal notranslate"><span class="pre">Simbelmyne_worker()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.workers.evaluate_gradient_of_Symbelmyne"><code class="docutils literal notranslate"><span class="pre">evaluate_gradient_of_Symbelmyne()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.workers.worker_gradient_Symbelmyne"><code class="docutils literal notranslate"><span class="pre">worker_gradient_Symbelmyne()</span></code></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="selfisys.utils.html#module-selfisys.utils">Module contents</a></li>
</ul>
</li>
</ul>
<p class="caption" role="heading"><span class="caption-text">Contribute</span></p>
<ul>
<li class="toctree-l1"><a class="reference internal" href="CONTRIBUTING.html">Contributing to SelfiSys</a><ul>
<li class="toctree-l2"><a class="reference internal" href="CONTRIBUTING.html#reporting-issues">Reporting Issues</a></li>
<li class="toctree-l2"><a class="reference internal" href="CONTRIBUTING.html#submitting-contributions">Submitting Contributions</a></li>
<li class="toctree-l2"><a class="reference internal" href="CONTRIBUTING.html#style-guidelines">Style Guidelines</a><ul>
<li class="toctree-l3"><a class="reference internal" href="CONTRIBUTING.html#python-code">Python code</a></li>
<li class="toctree-l3"><a class="reference internal" href="CONTRIBUTING.html#jupyter-notebooks">Jupyter Notebooks</a></li>
</ul>
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<li class="toctree-l2"><a class="reference internal" href="CONTRIBUTING.html#questions">Questions?</a></li>
</ul>
</li>
</ul>
<p class="caption" role="heading"><span class="caption-text">References</span></p>
<ul>
<li class="toctree-l1"><a class="reference internal" href="REFERENCES.html">References</a></li>
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<section id="selfisys-package">
<h1>selfisys package<a class="headerlink" href="#selfisys-package" title="Link to this heading"></a></h1>
<section id="subpackages">
<h2>Subpackages<a class="headerlink" href="#subpackages" title="Link to this heading"></a></h2>
<div class="toctree-wrapper compound">
<ul>
<li class="toctree-l1"><a class="reference internal" href="selfisys.utils.html">selfisys.utils package</a><ul>
<li class="toctree-l2"><a class="reference internal" href="selfisys.utils.html#submodules">Submodules</a></li>
<li class="toctree-l2"><a class="reference internal" href="selfisys.utils.html#module-selfisys.utils.examples_utils">selfisys.utils.examples_utils module</a><ul>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.examples_utils.clear_large_plot"><code class="docutils literal notranslate"><span class="pre">clear_large_plot()</span></code></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="selfisys.utils.html#module-selfisys.utils.logger">selfisys.utils.logger module</a><ul>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.logger.CustomLogger"><code class="docutils literal notranslate"><span class="pre">CustomLogger</span></code></a><ul>
<li class="toctree-l4"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.logger.CustomLogger.diagnostic"><code class="docutils literal notranslate"><span class="pre">CustomLogger.diagnostic()</span></code></a></li>
</ul>
</li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.logger.CustomLoggerHandler"><code class="docutils literal notranslate"><span class="pre">CustomLoggerHandler</span></code></a><ul>
<li class="toctree-l4"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.logger.CustomLoggerHandler.emit"><code class="docutils literal notranslate"><span class="pre">CustomLoggerHandler.emit()</span></code></a></li>
</ul>
</li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.logger.INDENT"><code class="docutils literal notranslate"><span class="pre">INDENT()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.logger.PrintDiagnostic"><code class="docutils literal notranslate"><span class="pre">PrintDiagnostic()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.logger.PrintError"><code class="docutils literal notranslate"><span class="pre">PrintError()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.logger.PrintInfo"><code class="docutils literal notranslate"><span class="pre">PrintInfo()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.logger.PrintLeftType"><code class="docutils literal notranslate"><span class="pre">PrintLeftType()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.logger.PrintWarning"><code class="docutils literal notranslate"><span class="pre">PrintWarning()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.logger.UNINDENT"><code class="docutils literal notranslate"><span class="pre">UNINDENT()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.logger.getCustomLogger"><code class="docutils literal notranslate"><span class="pre">getCustomLogger()</span></code></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="selfisys.utils.html#module-selfisys.utils.low_level">selfisys.utils.low_level module</a><ul>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.low_level.stderr_redirector"><code class="docutils literal notranslate"><span class="pre">stderr_redirector()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.low_level.stdout_redirector"><code class="docutils literal notranslate"><span class="pre">stdout_redirector()</span></code></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="selfisys.utils.html#module-selfisys.utils.parser">selfisys.utils.parser module</a><ul>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.parser.bool_sh"><code class="docutils literal notranslate"><span class="pre">bool_sh()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.parser.check_files_exist"><code class="docutils literal notranslate"><span class="pre">check_files_exist()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.parser.intNone"><code class="docutils literal notranslate"><span class="pre">intNone()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.parser.joinstrs"><code class="docutils literal notranslate"><span class="pre">joinstrs()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.parser.joinstrs_only"><code class="docutils literal notranslate"><span class="pre">joinstrs_only()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.parser.none_or_bool_or_str"><code class="docutils literal notranslate"><span class="pre">none_or_bool_or_str()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.parser.safe_npload"><code class="docutils literal notranslate"><span class="pre">safe_npload()</span></code></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="selfisys.utils.html#module-selfisys.utils.path_utils">selfisys.utils.path_utils module</a><ul>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.path_utils.file_names_evaluate"><code class="docutils literal notranslate"><span class="pre">file_names_evaluate()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.path_utils.get_file_names"><code class="docutils literal notranslate"><span class="pre">get_file_names()</span></code></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="selfisys.utils.html#module-selfisys.utils.plot_examples">selfisys.utils.plot_examples module</a><ul>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_examples.plot_comoving_distance_redshift"><code class="docutils literal notranslate"><span class="pre">plot_comoving_distance_redshift()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_examples.plot_galaxy_field_slice"><code class="docutils literal notranslate"><span class="pre">plot_galaxy_field_slice()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_examples.plot_power_spectrum"><code class="docutils literal notranslate"><span class="pre">plot_power_spectrum()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_examples.plot_selection_functions_def_in_z"><code class="docutils literal notranslate"><span class="pre">plot_selection_functions_def_in_z()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_examples.redshift_distance_conversion"><code class="docutils literal notranslate"><span class="pre">redshift_distance_conversion()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_examples.relative_error_analysis"><code class="docutils literal notranslate"><span class="pre">relative_error_analysis()</span></code></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="selfisys.utils.html#module-selfisys.utils.plot_params">selfisys.utils.plot_params module</a><ul>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_params.ScalarFormatterForceFormat_11"><code class="docutils literal notranslate"><span class="pre">ScalarFormatterForceFormat_11</span></code></a><ul>
<li class="toctree-l4"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_params.ScalarFormatterForceFormat_11.get_offset"><code class="docutils literal notranslate"><span class="pre">ScalarFormatterForceFormat_11.get_offset()</span></code></a></li>
<li class="toctree-l4"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_params.ScalarFormatterForceFormat_11.set_scientific"><code class="docutils literal notranslate"><span class="pre">ScalarFormatterForceFormat_11.set_scientific()</span></code></a></li>
<li class="toctree-l4"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_params.ScalarFormatterForceFormat_11.set_useOffset"><code class="docutils literal notranslate"><span class="pre">ScalarFormatterForceFormat_11.set_useOffset()</span></code></a></li>
</ul>
</li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_params.create_all_colormaps"><code class="docutils literal notranslate"><span class="pre">create_all_colormaps()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_params.create_colormap"><code class="docutils literal notranslate"><span class="pre">create_colormap()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_params.dynamic_text_scaling"><code class="docutils literal notranslate"><span class="pre">dynamic_text_scaling()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_params.get_contours"><code class="docutils literal notranslate"><span class="pre">get_contours()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_params.reset_plotting"><code class="docutils literal notranslate"><span class="pre">reset_plotting()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_params.setup_plotting"><code class="docutils literal notranslate"><span class="pre">setup_plotting()</span></code></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="selfisys.utils.html#module-selfisys.utils.plot_utils">selfisys.utils.plot_utils module</a><ul>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_utils.plot_C"><code class="docutils literal notranslate"><span class="pre">plot_C()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_utils.plot_fisher"><code class="docutils literal notranslate"><span class="pre">plot_fisher()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_utils.plot_gradients"><code class="docutils literal notranslate"><span class="pre">plot_gradients()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_utils.plot_histogram"><code class="docutils literal notranslate"><span class="pre">plot_histogram()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_utils.plot_mocks"><code class="docutils literal notranslate"><span class="pre">plot_mocks()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_utils.plot_mocks_compact"><code class="docutils literal notranslate"><span class="pre">plot_mocks_compact()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_utils.plot_observations"><code class="docutils literal notranslate"><span class="pre">plot_observations()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_utils.plot_prior_and_posterior_covariances"><code class="docutils literal notranslate"><span class="pre">plot_prior_and_posterior_covariances()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_utils.plot_reconstruction"><code class="docutils literal notranslate"><span class="pre">plot_reconstruction()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_utils.plot_selection_functions"><code class="docutils literal notranslate"><span class="pre">plot_selection_functions()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.plot_utils.plotly_3d"><code class="docutils literal notranslate"><span class="pre">plotly_3d()</span></code></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="selfisys.utils.html#module-selfisys.utils.timestepping">selfisys.utils.timestepping module</a><ul>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.timestepping.merge_nTS"><code class="docutils literal notranslate"><span class="pre">merge_nTS()</span></code></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="selfisys.utils.html#module-selfisys.utils.tools">selfisys.utils.tools module</a><ul>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.tools.cosmo_vector_to_Simbelmyne_dict"><code class="docutils literal notranslate"><span class="pre">cosmo_vector_to_Simbelmyne_dict()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.tools.cosmo_vector_to_class_dict"><code class="docutils literal notranslate"><span class="pre">cosmo_vector_to_class_dict()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.tools.custom_stat"><code class="docutils literal notranslate"><span class="pre">custom_stat()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.tools.fisher_rao"><code class="docutils literal notranslate"><span class="pre">fisher_rao()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.tools.get_k_max"><code class="docutils literal notranslate"><span class="pre">get_k_max()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.tools.get_summary"><code class="docutils literal notranslate"><span class="pre">get_summary()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.tools.none_or_bool_or_str"><code class="docutils literal notranslate"><span class="pre">none_or_bool_or_str()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.tools.params_ids_to_Simbelmyne_dict"><code class="docutils literal notranslate"><span class="pre">params_ids_to_Simbelmyne_dict()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.tools.sample_omega_from_prior"><code class="docutils literal notranslate"><span class="pre">sample_omega_from_prior()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.tools.summary_to_score"><code class="docutils literal notranslate"><span class="pre">summary_to_score()</span></code></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="selfisys.utils.html#module-selfisys.utils.workers">selfisys.utils.workers module</a><ul>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.workers.Simbelmyne_worker"><code class="docutils literal notranslate"><span class="pre">Simbelmyne_worker()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.workers.evaluate_gradient_of_Symbelmyne"><code class="docutils literal notranslate"><span class="pre">evaluate_gradient_of_Symbelmyne()</span></code></a></li>
<li class="toctree-l3"><a class="reference internal" href="selfisys.utils.html#selfisys.utils.workers.worker_gradient_Symbelmyne"><code class="docutils literal notranslate"><span class="pre">worker_gradient_Symbelmyne()</span></code></a></li>
</ul>
</li>
<li class="toctree-l2"><a class="reference internal" href="selfisys.utils.html#module-selfisys.utils">Module contents</a></li>
</ul>
</li>
</ul>
</div>
</section>
<section id="submodules">
<h2>Submodules<a class="headerlink" href="#submodules" title="Link to this heading"></a></h2>
</section>
<section id="module-selfisys.global_parameters">
<span id="selfisys-global-parameters-module"></span><h2>selfisys.global_parameters module<a class="headerlink" href="#module-selfisys.global_parameters" title="Link to this heading"></a></h2>
</section>
<section id="module-selfisys.grf">
<span id="selfisys-grf-module"></span><h2>selfisys.grf module<a class="headerlink" href="#module-selfisys.grf" title="Link to this heading"></a></h2>
<dl class="py function">
<dt class="sig sig-object py" id="selfisys.grf.primordial_grf">
<span class="sig-prename descclassname"><span class="pre">selfisys.grf.</span></span><span class="sig-name descname"><span class="pre">primordial_grf</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">L</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">N</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seedphases</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fname_powerspectrum</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fname_outputinitialdensity</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">force_sim</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_g</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbose</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/selfisys/grf.html#primordial_grf"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#selfisys.grf.primordial_grf" title="Link to this definition"></a></dt>
<dd><p>Generate a Gaussian random field from a specified input power
spectrum.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>L</strong> (<em>float</em>) – Side length of the simulation box in Mpc/h.</p></li>
<li><p><strong>N</strong> (<em>int</em>) – Grid resolution (number of cells per dimension).</p></li>
<li><p><strong>seedphases</strong> (<em>int</em>) – Seed for random phase generation (for reproducibility).</p></li>
<li><p><strong>fname_powerspectrum</strong> (<em>str</em>) – File path to the input power spectrum.</p></li>
<li><p><strong>fname_outputinitialdensity</strong> (<em>str</em>) – File path to store the generated initial density field.</p></li>
<li><p><strong>force_sim</strong> (<em>bool</em><em>, </em><em>optional</em>) – If True, regenerate the GRF even if the output file exists.
Default is False.</p></li>
<li><p><strong>return_g</strong> (<em>bool</em><em>, </em><em>optional</em>) – If True, return the GRF as a numpy array. Default is False.</p></li>
<li><p><strong>verbose</strong> (<em>int</em><em>, </em><em>optional</em>) – Verbosity level (0 = silent, 1 = progress, 2 = detailed).
Default is 0.</p></li>
</ul>
</dd>
<dt class="field-even">Raises<span class="colon">:</span></dt>
<dd class="field-even"><ul class="simple">
<li><p><strong>OSError</strong> – If the power spectrum file cannot be read.</p></li>
<li><p><strong>RuntimeError</strong> – If an unexpected error occurs during power spectrum reading.</p></li>
</ul>
</dd>
<dt class="field-odd">Returns<span class="colon">:</span></dt>
<dd class="field-odd"><p>The GRF data if <cite>return_g</cite> is True, otherwise None.</p>
</dd>
<dt class="field-even">Return type<span class="colon">:</span></dt>
<dd class="field-even"><p>numpy.ndarray or None</p>
</dd>
</dl>
</dd></dl>
</section>
<section id="module-selfisys.hiddenbox">
<span id="selfisys-hiddenbox-module"></span><h2>selfisys.hiddenbox module<a class="headerlink" href="#module-selfisys.hiddenbox" title="Link to this heading"></a></h2>
<dl class="py class">
<dt class="sig sig-object py" id="selfisys.hiddenbox.HiddenBox">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">selfisys.hiddenbox.</span></span><span class="sig-name descname"><span class="pre">HiddenBox</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">k_s</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Any</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">P_ss_path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">Pbins_bnd</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Any</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">theta2P</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Callable</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">P</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">L</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">G_sim_path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">G_ss_path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">Np0</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">Npm0</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fsimdir</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">noise_std</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">radial_selection</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">selection_params</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">Any</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">observed_density</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">linear_bias</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">norm_csts</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">survey_mask_path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">local_mask_prefix</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sim_params</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">eff_redshifts</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">TimeSteps</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">TimeStepDistribution</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seedphase</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seednoise</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fixnoise</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seednorm</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">save_frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">reset</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbosity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/selfisys/hiddenbox.html#HiddenBox"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#selfisys.hiddenbox.HiddenBox" title="Link to this definition"></a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
<p>This class represents custom forward data model of large-scale
spectroscopic galaxy surveys.</p>
<dl class="py property">
<dt class="sig sig-object py" id="selfisys.hiddenbox.HiddenBox.Npop">
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">Npop</span></span><a class="headerlink" href="#selfisys.hiddenbox.HiddenBox.Npop" title="Link to this definition"></a></dt>
<dd><p>Number of populations.</p>
</dd></dl>
<dl class="py property">
<dt class="sig sig-object py" id="selfisys.hiddenbox.HiddenBox.Ntimesteps">
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">Ntimesteps</span></span><a class="headerlink" href="#selfisys.hiddenbox.HiddenBox.Ntimesteps" title="Link to this definition"></a></dt>
<dd><p>Number of time steps.</p>
</dd></dl>
<dl class="py property">
<dt class="sig sig-object py" id="selfisys.hiddenbox.HiddenBox.Psingle">
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">Psingle</span></span><a class="headerlink" href="#selfisys.hiddenbox.HiddenBox.Psingle" title="Link to this definition"></a></dt>
<dd><p>Number of summary statistics for each population.</p>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="selfisys.hiddenbox.HiddenBox.compute_pool">
<span class="sig-name descname"><span class="pre">compute_pool</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">theta</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">d</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">pool_fname</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">N</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">index</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">force_powerspectrum</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">force_parfiles</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">force_sim</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">remove_sbmy</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">theta_is_p</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">simspath</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bar</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/selfisys/hiddenbox.html#HiddenBox.compute_pool"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#selfisys.hiddenbox.HiddenBox.compute_pool" title="Link to this definition"></a></dt>
<dd><p>Compute a pool of realisations of the hidden box compatible
with <cite>pySELFI</cite>.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>theta</strong> (<em>ndarray</em>) – Power spectrum values at the support wavenumbers.</p></li>
<li><p><strong>d</strong> (<em>int</em>) – Direction in parameter space, from 0 to S.</p></li>
<li><p><strong>pool_fname</strong> (<em>str</em>) – Filename for the pool.</p></li>
<li><p><strong>N</strong> (<em>int</em>) – Number of realisations required at the given direction.</p></li>
<li><p><strong>index</strong> (<em>int</em><em>, </em><em>optional</em>) – Index of a single simulation to run. Default is <cite>None</cite>.</p></li>
<li><p><strong>force_powerspectrum</strong> (<em>bool</em><em>, </em><em>optional</em>) – If True, force recomputation of the power spectrum. Default
is <cite>False</cite>.</p></li>
<li><p><strong>force_parfiles</strong> (<em>bool</em><em>, </em><em>optional</em>) – If True, overwrite existing parameter files. Default is
<cite>False</cite>.</p></li>
<li><p><strong>force_sim</strong> (<em>bool</em><em>, </em><em>optional</em>) – If True, rerun the simulation even if the output density
already exists. Default is <cite>False</cite>.</p></li>
<li><p><strong>remove_sbmy</strong> (<em>bool</em><em>, </em><em>optional</em>) – If True, remove Simbelmynë output files from disk. Default
is <cite>False</cite>.</p></li>
<li><p><strong>theta_is_p</strong> (<em>bool</em><em>, </em><em>optional</em>) – Set to True when <cite>theta</cite> is already an unnormalised power
spectrum. Default is <cite>False</cite>.</p></li>
<li><p><strong>simspath</strong> (<em>str</em><em>, </em><em>optional</em>) – Path indicating where to store the simulations. Default is
<cite>None</cite>.</p></li>
<li><p><strong>bar</strong> (<em>bool</em><em>, </em><em>optional</em>) – If True, display a progress bar. Default is <cite>False</cite>.</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p><strong>p</strong> – Simulation pool object.</p>
</dd>
<dt class="field-odd">Return type<span class="colon">:</span></dt>
<dd class="field-odd"><p>Pool</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="selfisys.hiddenbox.HiddenBox.evaluate">
<span class="sig-name descname"><span class="pre">evaluate</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">theta</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">d</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seedphase</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seednoise</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">i</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">N</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">force_powerspectrum</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">force_parfiles</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">force_sim</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">remove_sbmy</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">theta_is_p</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">simspath</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">check_output</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">RSDs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">abc</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cosmo_vect</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/selfisys/hiddenbox.html#HiddenBox.evaluate"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#selfisys.hiddenbox.HiddenBox.evaluate" title="Link to this definition"></a></dt>
<dd><p>Evaluate the hidden box for a given input power spectrum.</p>
<p>The result is deterministic (the phase is fixed), except as it
is modified by nuisance parameters if any.</p>
<p>This routine is used by <cite>pySELFI</cite> to compute the gradient of the
hidden box with respect to the power spectrum, and by ABC-PMC to
evaluate the forward model.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>theta</strong> (<em>ndarray</em>) – Power spectrum values at the support wavenumbers.</p></li>
<li><p><strong>d</strong> (<em>int</em>) – Direction in parameter space, from <cite>0</cite> to <cite>S</cite>.</p></li>
<li><p><strong>seedphase</strong> (<em>int</em><em> or </em><em>list</em><em> of </em><em>int</em>) – Seed to generate the initial white noise in Fourier space.</p></li>
<li><p><strong>seednoise</strong> (<em>int</em><em> or </em><em>list</em><em> of </em><em>int</em>) – Seed to generate the noise realisation.</p></li>
<li><p><strong>i</strong> (<em>int</em><em>, </em><em>optional</em>) – Current evaluation index of the hidden box. Default is <cite>0</cite>.</p></li>
<li><p><strong>N</strong> (<em>int</em><em>, </em><em>optional</em>) – Total number of evaluations of the hidden box. Default is
<cite>0</cite>.</p></li>
<li><p><strong>force_powerspectrum</strong> (<em>bool</em><em>, </em><em>optional</em>) – If <cite>True</cite>, force recomputation of the power spectrum at the
values of the Fourier grid. Default is <cite>False</cite>.</p></li>
<li><p><strong>force_parfiles</strong> (<em>bool</em><em>, </em><em>optional</em>) – If <cite>True</cite>, overwrite existing parameter files. Default is
<cite>False</cite>.</p></li>
<li><p><strong>force_sim</strong> (<em>bool</em><em>, </em><em>optional</em>) – If <cite>True</cite>, rerun the simulation even if the output density
already exists. Default is <cite>False</cite>.</p></li>
<li><p><strong>remove_sbmy</strong> (<em>bool</em><em>, </em><em>optional</em>) – If <cite>True</cite>, remove Simbelmynë output files from disk. Default
is <cite>False</cite>.</p></li>
<li><p><strong>theta_is_p</strong> (<em>bool</em><em>, </em><em>optional</em>) – Set to <cite>True</cite> if <cite>theta</cite> is already an unnormalised power
spectrum. Default is <cite>False</cite>.</p></li>
<li><p><strong>simspath</strong> (<em>str</em><em>, </em><em>optional</em>) – Path to the simulations directory. Default is <cite>None</cite>.</p></li>
<li><p><strong>check_output</strong> (<em>bool</em><em>, </em><em>optional</em>) – If <cite>True</cite>, check the integrity of the output file and
recompute if corrupted. Default is <cite>False</cite>.</p></li>
<li><p><strong>RSDs</strong> (<em>bool</em><em>, </em><em>optional</em>) – Whether to compute redshift-space distortions. Default is
<cite>True</cite>.</p></li>
<li><p><strong>abc</strong> (<em>bool</em><em> or </em><em>str</em><em>, </em><em>optional</em>) – If not False, remove most output files after evaluation.
Default is <cite>False</cite>.</p></li>
<li><p><strong>cosmo_vect</strong> (<em>ndarray</em><em>, </em><em>optional</em>) – Cosmological parameters. Required if <cite>abc</cite> is <cite>True</cite>.</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p><strong>Phi</strong> – Vector of summary statistics.</p>
</dd>
<dt class="field-odd">Return type<span class="colon">:</span></dt>
<dd class="field-odd"><p>ndarray</p>
</dd>
</dl>
</dd></dl>
<dl class="py property">
<dt class="sig sig-object py" id="selfisys.hiddenbox.HiddenBox.force_neglect_lightcone">
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">force_neglect_lightcone</span></span><a class="headerlink" href="#selfisys.hiddenbox.HiddenBox.force_neglect_lightcone" title="Link to this definition"></a></dt>
<dd><p>Whether to force neglecting the lightcone.</p>
</dd></dl>
<dl class="py property">
<dt class="sig sig-object py" id="selfisys.hiddenbox.HiddenBox.force_recompute_mocks">
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">force_recompute_mocks</span></span><a class="headerlink" href="#selfisys.hiddenbox.HiddenBox.force_recompute_mocks" title="Link to this definition"></a></dt>
<dd><p>Whether to force recomputation of mocks.</p>
</dd></dl>
<dl class="py property">
<dt class="sig sig-object py" id="selfisys.hiddenbox.HiddenBox.gravity_on">
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">gravity_on</span></span><a class="headerlink" href="#selfisys.hiddenbox.HiddenBox.gravity_on" title="Link to this definition"></a></dt>
<dd><p>Whether gravity is enabled.</p>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="selfisys.hiddenbox.HiddenBox.load_pool">
<span class="sig-name descname"><span class="pre">load_pool</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">pool_fname</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">N</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/selfisys/hiddenbox.html#HiddenBox.load_pool"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#selfisys.hiddenbox.HiddenBox.load_pool" title="Link to this definition"></a></dt>
<dd><p>Load a pool of realisations of the hidden box.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>pool_fname</strong> (<em>str</em>) – Filename of the pool to load.</p></li>
<li><p><strong>N</strong> (<em>int</em>) – Number of realisations in the pool.</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p><strong>p</strong> – Simulation pool object.</p>
</dd>
<dt class="field-odd">Return type<span class="colon">:</span></dt>
<dd class="field-odd"><p>Pool</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="selfisys.hiddenbox.HiddenBox.make_data">
<span class="sig-name descname"><span class="pre">make_data</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">cosmo</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">id</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seedphase</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seednoise</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">force_powerspectrum</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">force_parfiles</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">force_sim</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">force_cosmo</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">force_phase</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">d</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">-1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">remove_sbmy</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbosity</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_g</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">RSDs</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">prefix_mocks</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/selfisys/hiddenbox.html#HiddenBox.make_data"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#selfisys.hiddenbox.HiddenBox.make_data" title="Link to this definition"></a></dt>
<dd><p>Generate simulated data based on the given cosmological
parameters.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>cosmo</strong> (<em>dict</em>) – Cosmological and infrastructure parameters.</p></li>
<li><p><strong>id</strong> (<em>int</em><em> or </em><em>str</em><em>, </em><em>optional</em>) – Identifier used as a suffix in the file names. Default is
<cite>0</cite>.</p></li>
<li><p><strong>seedphase</strong> (<em>int</em><em> or </em><em>list</em><em> of </em><em>int</em>) – Seed to generate the initial white noise in Fourier space.</p></li>
<li><p><strong>seednoise</strong> (<em>int</em><em> or </em><em>list</em><em> of </em><em>int</em>) – Seed to generate the noise realisation.</p></li>
<li><p><strong>force_powerspectrum</strong> (<em>bool</em><em>, </em><em>optional</em>) – Force recomputing the input spectrum. Default is <cite>False</cite>.</p></li>
<li><p><strong>force_parfiles</strong> (<em>bool</em><em>, </em><em>optional</em>) – Force recomputing the parameter files. Default is <cite>False</cite>.</p></li>
<li><p><strong>force_sim</strong> (<em>bool</em><em>, </em><em>optional</em>) – Force recomputing the simulation. Default is <cite>False</cite>.</p></li>
<li><p><strong>force_cosmo</strong> (<em>bool</em><em>, </em><em>optional</em>) – Force recomputing the cosmological parameters. Default is
<cite>False</cite>.</p></li>
<li><p><strong>force_phase</strong> (<em>bool</em><em>, </em><em>optional</em>) – Force recomputing the initial phase. Default is <cite>False</cite>.</p></li>
<li><p><strong>d</strong> (<em>int</em><em>, </em><em>optional</em>) – Direction in the parameter space. Default is <cite>-1</cite>.</p></li>
<li><p><strong>remove_sbmy</strong> (<em>bool</em><em>, </em><em>optional</em>) – Whether to remove most Simbelmynë output files after use for
disk space management. Default is <cite>True</cite>.</p></li>
<li><p><strong>verbosity</strong> (<em>int</em><em>, </em><em>optional</em>) – Verbosity level. If <cite>None</cite>, use self.verbosity. Default is
<cite>None</cite>.</p></li>
<li><p><strong>return_g</strong> (<em>bool</em><em>, </em><em>optional</em>) – Whether to return the full field alongside the summary.
Default is <cite>False</cite>.</p></li>
<li><p><strong>RSDs</strong> (<em>bool</em><em>, </em><em>optional</em>) – Whether to compute the redshift-space distortions. Default
is <cite>True</cite>.</p></li>
<li><p><strong>prefix_mocks</strong> (<em>str</em><em>, </em><em>optional</em>) – Prefix for the mock data. If None, use self.prefix_mocks.
Default is <cite>None</cite>.</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p><ul class="simple">
<li><p><strong>Phi</strong> (<em>ndarray</em>) – Vector of summary statistics.</p></li>
<li><p><strong>g</strong> (<em>ndarray or list of ndarray or None</em>) – Observed field(s) if return_g is <cite>True</cite>; otherwise <cite>None</cite>.</p></li>
</ul>
</p>
</dd>
</dl>
</dd></dl>
<dl class="py property">
<dt class="sig sig-object py" id="selfisys.hiddenbox.HiddenBox.modified_selfi">
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">modified_selfi</span></span><a class="headerlink" href="#selfisys.hiddenbox.HiddenBox.modified_selfi" title="Link to this definition"></a></dt>
<dd><p>Whether to use the modified selfi.</p>
</dd></dl>
<dl class="py property">
<dt class="sig sig-object py" id="selfisys.hiddenbox.HiddenBox.prefix_mocks">
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">prefix_mocks</span></span><a class="headerlink" href="#selfisys.hiddenbox.HiddenBox.prefix_mocks" title="Link to this definition"></a></dt>
<dd><p>Prefix for the mocks.</p>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="selfisys.hiddenbox.HiddenBox.reset_survey">
<span class="sig-name descname"><span class="pre">reset_survey</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/selfisys/hiddenbox.html#HiddenBox.reset_survey"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#selfisys.hiddenbox.HiddenBox.reset_survey" title="Link to this definition"></a></dt>
<dd><p>Re-initialise the survey mask C(n) and radial selection
function R(r).</p>
</dd></dl>
<dl class="py property">
<dt class="sig sig-object py" id="selfisys.hiddenbox.HiddenBox.setup_only">
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">setup_only</span></span><a class="headerlink" href="#selfisys.hiddenbox.HiddenBox.setup_only" title="Link to this definition"></a></dt>
<dd><p>Whether to only set up the hidden box.</p>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="selfisys.hiddenbox.HiddenBox.switch_recompute_pool">
<span class="sig-name descname"><span class="pre">switch_recompute_pool</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">prefix_mocks</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/selfisys/hiddenbox.html#HiddenBox.switch_recompute_pool"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#selfisys.hiddenbox.HiddenBox.switch_recompute_pool" title="Link to this definition"></a></dt>
<dd><p>Toggle recomputation of the pool for future <cite>compute_pool</cite>
calls.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><p><strong>prefix_mocks</strong> (<em>str</em><em>, </em><em>optional</em>) – Prefix for the future simulation files. Default is <cite>None</cite>.</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="selfisys.hiddenbox.HiddenBox.switch_setup">
<span class="sig-name descname"><span class="pre">switch_setup</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/selfisys/hiddenbox.html#HiddenBox.switch_setup"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#selfisys.hiddenbox.HiddenBox.switch_setup" title="Link to this definition"></a></dt>
<dd><p>Toggle the setup-only mode.</p>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="selfisys.hiddenbox.HiddenBox.update">
<span class="sig-name descname"><span class="pre">update</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/selfisys/hiddenbox.html#HiddenBox.update"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#selfisys.hiddenbox.HiddenBox.update" title="Link to this definition"></a></dt>
<dd><p>Updates the given parameter(s) of the hidden box with the
given value(s).</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><p><strong>**kwargs</strong> (<em>dict</em>) – dictionary of parameters to update</p>
</dd>
</dl>
</dd></dl>
</dd></dl>
</section>
<section id="module-selfisys.normalise_hb">
<span id="selfisys-normalise-hb-module"></span><h2>selfisys.normalise_hb module<a class="headerlink" href="#module-selfisys.normalise_hb" title="Link to this heading"></a></h2>
<dl class="py function">
<dt class="sig sig-object py" id="selfisys.normalise_hb.define_normalisation">
<span class="sig-prename descclassname"><span class="pre">selfisys.normalise_hb.</span></span><span class="sig-name descname"><span class="pre">define_normalisation</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">hidden_box</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="selfisys.hiddenbox.html#selfisys.hiddenbox.HiddenBox" title="selfisys.hiddenbox.HiddenBox"><span class="pre">HiddenBox</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">Pbins</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ndarray</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cosmo</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Any</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">N</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">min_k_norma</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.04</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">npar</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">force</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">ndarray</span></span></span><a class="reference internal" href="_modules/selfisys/normalise_hb.html#define_normalisation"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#selfisys.normalise_hb.define_normalisation" title="Link to this definition"></a></dt>
<dd><p>Define the normalisation constants for the HiddenBox instance.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>hidden_box</strong> (<a class="reference internal" href="selfisys.hiddenbox.html#selfisys.hiddenbox.HiddenBox" title="selfisys.hiddenbox.HiddenBox"><em>HiddenBox</em></a>) – Instance of the HiddenBox class.</p></li>
<li><p><strong>Pbins</strong> (<em>ndarray</em>) – Array of P bin values.</p></li>
<li><p><strong>cosmo</strong> (<em>dict</em>) – Cosmological and infrastructure parameters.</p></li>
<li><p><strong>N</strong> (<em>int</em>) – Number of realisations required.</p></li>
<li><p><strong>min_k_norma</strong> (<em>float</em><em>, </em><em>optional</em>) – Minimum k value to compute the normalisation constants.</p></li>
<li><p><strong>npar</strong> (<em>int</em><em>, </em><em>optional</em>) – Number of parallel processes to use. Default is 1.</p></li>
<li><p><strong>force</strong> (<em>bool</em><em>, </em><em>optional</em>) – If True, force recomputation. Default is False.</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p><strong>norm_csts</strong> – Normalisation constants for the HiddenBox instance.</p>
</dd>
<dt class="field-odd">Return type<span class="colon">:</span></dt>
<dd class="field-odd"><p>ndarray</p>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="selfisys.normalise_hb.worker_normalisation">
<span class="sig-prename descclassname"><span class="pre">selfisys.normalise_hb.</span></span><span class="sig-name descname"><span class="pre">worker_normalisation</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">hidden_box</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="selfisys.hiddenbox.html#selfisys.hiddenbox.HiddenBox" title="selfisys.hiddenbox.HiddenBox"><span class="pre">HiddenBox</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">params</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">Dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Any</span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">list</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">list</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">bool</span><span class="p"><span class="pre">]</span></span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">ndarray</span></span></span><a class="reference internal" href="_modules/selfisys/normalise_hb.html#worker_normalisation"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#selfisys.normalise_hb.worker_normalisation" title="Link to this definition"></a></dt>
<dd><p>Worker function to compute the normalisation constants,
compatible with Python multiprocessing.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>hidden_box</strong> (<a class="reference internal" href="selfisys.hiddenbox.html#selfisys.hiddenbox.HiddenBox" title="selfisys.hiddenbox.HiddenBox"><em>HiddenBox</em></a>) – Instance of the HiddenBox class.</p></li>
<li><p><strong>params</strong> (<em>tuple</em>) – A tuple containing (cosmo, seedphase, seednoise, force).</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p><strong>phi</strong> – Computed summary statistics.</p>
</dd>
<dt class="field-odd">Return type<span class="colon">:</span></dt>
<dd class="field-odd"><p>ndarray</p>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="selfisys.normalise_hb.worker_normalisation_public">
<span class="sig-prename descclassname"><span class="pre">selfisys.normalise_hb.</span></span><span class="sig-name descname"><span class="pre">worker_normalisation_public</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">hidden_box</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cosmo</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Dict</span><span class="p"><span class="pre">[</span></span><span class="pre">str</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">Any</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">N</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">i</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/selfisys/normalise_hb.html#worker_normalisation_public"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#selfisys.normalise_hb.worker_normalisation_public" title="Link to this definition"></a></dt>
<dd><p>Run the i-th simulation required to compute the normalisation
constants.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>hidden_box</strong> (<a class="reference internal" href="selfisys.hiddenbox.html#selfisys.hiddenbox.HiddenBox" title="selfisys.hiddenbox.HiddenBox"><em>HiddenBox</em></a>) – Instance of the HiddenBox class.</p></li>
<li><p><strong>cosmo</strong> (<em>dict</em>) – Cosmological and some infrastructure parameters.</p></li>
<li><p><strong>N</strong> (<em>int</em>) – Total number of realisations required.</p></li>
<li><p><strong>i</strong> (<em>int</em>) – Index of the simulation to be computed.</p></li>
</ul>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="selfisys.normalise_hb.worker_normalisation_wrapper">
<span class="sig-prename descclassname"><span class="pre">selfisys.normalise_hb.</span></span><span class="sig-name descname"><span class="pre">worker_normalisation_wrapper</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">args</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/selfisys/normalise_hb.html#worker_normalisation_wrapper"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#selfisys.normalise_hb.worker_normalisation_wrapper" title="Link to this definition"></a></dt>
<dd><p>Wrapper function for the worker_normalisation function.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><p><strong>args</strong> (<em>tuple</em>) – A tuple containing (hidden_box, params).</p>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p><strong>phi</strong> – Computed summary statistics.</p>
</dd>
<dt class="field-odd">Return type<span class="colon">:</span></dt>
<dd class="field-odd"><p>ndarray</p>
</dd>
</dl>
</dd></dl>
</section>
<section id="module-selfisys.prior">
<span id="selfisys-prior-module"></span><h2>selfisys.prior module<a class="headerlink" href="#module-selfisys.prior" title="Link to this heading"></a></h2>
<dl class="py function">
<dt class="sig sig-object py" id="selfisys.prior.get_summary">
<span class="sig-prename descclassname"><span class="pre">selfisys.prior.</span></span><span class="sig-name descname"><span class="pre">get_summary</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bins</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">normalisation</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">kmax</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1.4</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/selfisys/prior.html#get_summary"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#selfisys.prior.get_summary" title="Link to this definition"></a></dt>
<dd><p>Compute a power-spectrum summary for given cosmological parameters.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>x</strong> (<em>array-like</em>) – Cosmological parameters [h, Omega_b, Omega_m, n_s, sigma_8].</p></li>
<li><p><strong>bins</strong> (<em>array-like</em>) – Wavenumber bins.</p></li>
<li><p><strong>normalisation</strong> (<em>float</em><em> or </em><em>None</em><em>, </em><em>optional</em>) – Normalisation constant to scale the resulting spectrum.</p></li>
<li><p><strong>kmax</strong> (<em>float</em><em>, </em><em>optional</em>) – Maximum wavenumber for get_Pk.</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p><strong>theta</strong> – The computed power-spectrum values, optionally normalised.</p>
</dd>
<dt class="field-odd">Return type<span class="colon">:</span></dt>
<dd class="field-odd"><p>ndarray</p>
</dd>
<dt class="field-even">Raises<span class="colon">:</span></dt>
<dd class="field-even"><p><strong>RuntimeError</strong> – If the power-spectrum computation fails unexpectedly.</p>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="selfisys.prior.logposterior_hyperparameters_parallel">
<span class="sig-prename descclassname"><span class="pre">selfisys.prior.</span></span><span class="sig-name descname"><span class="pre">logposterior_hyperparameters_parallel</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">selfi</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">theta_fiducial</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">Nbin_min</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">Nbin_max</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">theta_norm</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k_corr</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">alpha_cv</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/selfisys/prior.html#logposterior_hyperparameters_parallel"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#selfisys.prior.logposterior_hyperparameters_parallel" title="Link to this definition"></a></dt>
<dd><p>Compute the log-posterior for the hyperparameters of the prior from
[leclercq2019primordial], for use within the SelfiSys pipeline.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>selfi</strong> (<em>object</em>) – The selfi object.</p></li>
<li><p><strong>theta_fiducial</strong> (<em>ndarray</em>) – Fiducial spectrum.</p></li>
<li><p><strong>Nbin_min</strong> (<em>int</em>) – Minimum bin index for the wavenumber range.</p></li>
<li><p><strong>Nbin_max</strong> (<em>int</em>) – Maximum bin index for the wavenumber range.</p></li>
<li><p><strong>theta_norm</strong> (<em>float</em>) – Hyperparameter controlling the overall uncertainty.</p></li>
<li><p><strong>k_corr</strong> (<em>float</em>) – Hyperparameter controlling correlation scale.</p></li>
<li><p><strong>alpha_cv</strong> (<em>float</em>) – Cosmic variance strength.</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p>The log-posterior value for the given hyperparameters.</p>
</dd>
<dt class="field-odd">Return type<span class="colon">:</span></dt>
<dd class="field-odd"><p>float</p>
</dd>
<dt class="field-even">Raises<span class="colon">:</span></dt>
<dd class="field-even"><p><strong>RuntimeError</strong> – If the log-posterior computation fails unexpectedly.</p>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="selfisys.prior.perform_prior_optimisation_and_plot">
<span class="sig-prename descclassname"><span class="pre">selfisys.prior.</span></span><span class="sig-name descname"><span class="pre">perform_prior_optimisation_and_plot</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">selfi</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">theta_fiducial</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">theta_norm_mean</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">theta_norm_std</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.3</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k_corr_mean</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.02</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k_corr_std</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.015</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k_opt_min</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k_opt_max</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1.4</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">theta_norm_min</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.04</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">theta_norm_max</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.12</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k_corr_min</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.012</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k_corr_max</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.02</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">meshsize</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">30</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">Nbin_min</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">Nbin_max</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">100</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">theta_norm</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.05</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k_corr</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.015</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">alpha_cv</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.00065</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">plot</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">savepath</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/selfisys/prior.html#perform_prior_optimisation_and_plot"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#selfisys.prior.perform_prior_optimisation_and_plot" title="Link to this definition"></a></dt>
<dd><p>Optimise the hyperparameters for the selfi2019 prior (from
[leclercq2019primordial]).</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>selfi</strong> (<em>object</em>) – The selfi object.</p></li>
<li><p><strong>theta_fiducial</strong> (<em>ndarray</em>) – Fiducial spectrum.</p></li>
<li><p><strong>theta_norm_mean</strong> (<em>float</em><em>, </em><em>optional</em>) – Mean of the Gaussian hyperprior on theta_norm. Default 0.1.</p></li>
<li><p><strong>theta_norm_std</strong> (<em>float</em><em>, </em><em>optional</em>) – Standard deviation of the hyperprior on theta_norm. Default 0.3.</p></li>
<li><p><strong>k_corr_mean</strong> (<em>float</em><em>, </em><em>optional</em>) – Mean of the Gaussian hyperprior on k_corr. Default 0.020.</p></li>
<li><p><strong>k_corr_std</strong> (<em>float</em><em>, </em><em>optional</em>) – Standard deviation of the hyperprior on k_corr. Default 0.015.</p></li>
<li><p><strong>k_opt_min</strong> (<em>float</em><em>, </em><em>optional</em>) – Minimum wavenumber for the prior optimisation. Default 0.0.</p></li>
<li><p><strong>k_opt_max</strong> (<em>float</em><em>, </em><em>optional</em>) – Maximum wavenumber for the prior optimisation. Default 1.4.</p></li>
<li><p><strong>theta_norm_min</strong> (<em>float</em><em>, </em><em>optional</em>) – Lower bound for theta_norm in the mesh. Default 0.04.</p></li>
<li><p><strong>theta_norm_max</strong> (<em>float</em><em>, </em><em>optional</em>) – Upper bound for theta_norm in the mesh. Default 0.12.</p></li>
<li><p><strong>k_corr_min</strong> (<em>float</em><em>, </em><em>optional</em>) – Lower bound for k_corr in the mesh. Default 0.012.</p></li>
<li><p><strong>k_corr_max</strong> (<em>float</em><em>, </em><em>optional</em>) – Upper bound for k_corr in the mesh. Default 0.02.</p></li>
<li><p><strong>meshsize</strong> (<em>int</em><em>, </em><em>optional</em>) – Number of points in each dimension of the plot mesh. Default 30.</p></li>
<li><p><strong>Nbin_min</strong> (<em>int</em><em>, </em><em>optional</em>) – Minimum bin index for restricting the prior. Default 0.</p></li>
<li><p><strong>Nbin_max</strong> (<em>int</em><em>, </em><em>optional</em>) – Maximum bin index for restricting the prior. Default 100.</p></li>
<li><p><strong>theta_norm</strong> (<em>float</em><em>, </em><em>optional</em>) – Initial or default guess of theta_norm. Default 0.05.</p></li>
<li><p><strong>k_corr</strong> (<em>float</em><em>, </em><em>optional</em>) – Initial or default guess of k_corr. Default 0.015.</p></li>
<li><p><strong>alpha_cv</strong> (<em>float</em><em>, </em><em>optional</em>) – Cosmic variance term or similar. Default 0.00065.</p></li>
<li><p><strong>plot</strong> (<em>bool</em><em>, </em><em>optional</em>) – If True, generate and show/save a 2D contour plot. Default True.</p></li>
<li><p><strong>savepath</strong> (<em>str</em><em>, </em><em>optional</em>) – File path to save the plot. If None, the plot is displayed.</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p>(theta_norm, k_corr) after optimisation.</p>
</dd>
<dt class="field-odd">Return type<span class="colon">:</span></dt>
<dd class="field-odd"><p>tuple</p>
</dd>
<dt class="field-even">Raises<span class="colon">:</span></dt>
<dd class="field-even"><ul class="simple">
<li><p><strong>OSError</strong> – If file operations fail during saving the prior or posterior.</p></li>
<li><p><strong>RuntimeError</strong> – If the optimisation fails unexpectedly.</p></li>
</ul>
</dd>
</dl>
</dd></dl>
<dl class="py class">
<dt class="sig sig-object py" id="selfisys.prior.planck_prior">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">selfisys.prior.</span></span><span class="sig-name descname"><span class="pre">planck_prior</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">Omega_mean</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">Omega_cov</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">bins</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">normalisation</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">kmax</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nsamples</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">10000</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">nthreads</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">-1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">EPS_K</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1e-07</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">EPS_residual</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.001</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">filename</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/selfisys/prior.html#planck_prior"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#selfisys.prior.planck_prior" title="Link to this definition"></a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
<p>Custom prior for the SelfiSys pipeline. This is the prior used in
[hoellinger2024diagnosing], based on the Planck 2018 cosmological
parameters.</p>
<p>This class provides methods to compute a power-spectrum prior from a
prior distribution of cosmological parameters, using a Gaussian fit.
See equation (7) in [hoellinger2024diagnosing].</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>Omega_mean</strong> (<em>array-like</em>) – Mean of the prior distribution on cosmological parameters.</p></li>
<li><p><strong>Omega_cov</strong> (<em>array-like</em>) – Covariance matrix of the prior distribution on cosmological
parameters.</p></li>
<li><p><strong>bins</strong> (<em>array-like</em>) – Wavenumbers where the power spectrum is evaluated.</p></li>
<li><p><strong>normalisation</strong> (<em>float</em><em> or </em><em>None</em>) – If not None, divide the power spectra by the normalisation.</p></li>
<li><p><strong>kmax</strong> (<em>float</em>) – Maximum wavenumber for computations.</p></li>
<li><p><strong>nsamples</strong> (<em>int</em><em>, </em><em>optional</em>) – Number of samples drawn from the prior on the cosmological
parameters. Default is 10,000.</p></li>
<li><p><strong>nthreads</strong> (<em>int</em><em>, </em><em>optional</em>) – Number of CPU threads for parallel tasks. Default is -1, that
is, auto-detect the number of available threads.</p></li>
<li><p><strong>EPS_K</strong> (<em>float</em><em>, </em><em>optional</em>) – Regularisation parameter for covariance inversion. Default 1e-7.</p></li>
<li><p><strong>EPS_residual</strong> (<em>float</em><em>, </em><em>optional</em>) – Additional cutoff for matrix inversion. Default 1e-3.</p></li>
<li><p><strong>filename</strong> (<em>str</em><em> or </em><em>None</em><em>, </em><em>optional</em>) – Path to a .npy file to store or load precomputed power spectra.</p></li>
</ul>
</dd>
</dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="selfisys.prior.planck_prior.mean">
<span class="sig-name descname"><span class="pre">mean</span></span><a class="headerlink" href="#selfisys.prior.planck_prior.mean" title="Link to this definition"></a></dt>
<dd><p>Mean of the computed power spectra.</p>
<dl class="field-list simple">
<dt class="field-odd">Type<span class="colon">:</span></dt>
<dd class="field-odd"><p>ndarray</p>
</dd>
</dl>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="selfisys.prior.planck_prior.covariance">
<span class="sig-name descname"><span class="pre">covariance</span></span><a class="headerlink" href="#selfisys.prior.planck_prior.covariance" title="Link to this definition"></a></dt>
<dd><p>Covariance matrix of the computed power spectra.</p>
<dl class="field-list simple">
<dt class="field-odd">Type<span class="colon">:</span></dt>
<dd class="field-odd"><p>ndarray</p>
</dd>
</dl>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="selfisys.prior.planck_prior.inv_covariance">
<span class="sig-name descname"><span class="pre">inv_covariance</span></span><a class="headerlink" href="#selfisys.prior.planck_prior.inv_covariance" title="Link to this definition"></a></dt>
<dd><p>Inverse of the covariance matrix.</p>
<dl class="field-list simple">
<dt class="field-odd">Type<span class="colon">:</span></dt>
<dd class="field-odd"><p>ndarray</p>
</dd>
</dl>
</dd></dl>
<dl class="field-list simple">
<dt class="field-odd">Raises<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>OSError</strong> – If file reading or writing fails.</p></li>
<li><p><strong>RuntimeError</strong> – For unexpected HPC or multi-processing errors.</p></li>
</ul>
</dd>
</dl>
<dl class="py property">
<dt class="sig sig-object py" id="selfisys.prior.planck_prior.Nbin_max">
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">Nbin_max</span></span><a class="headerlink" href="#selfisys.prior.planck_prior.Nbin_max" title="Link to this definition"></a></dt>
<dd><p>Index of the maximal wavenumber given self.kmax.</p>
</dd></dl>
<dl class="py property">
<dt class="sig sig-object py" id="selfisys.prior.planck_prior.Nbin_min">
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">Nbin_min</span></span><a class="headerlink" href="#selfisys.prior.planck_prior.Nbin_min" title="Link to this definition"></a></dt>
<dd><p>Index of the minimal wavenumber given k_min.</p>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="selfisys.prior.planck_prior.compute">
<span class="sig-name descname"><span class="pre">compute</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/selfisys/prior.html#planck_prior.compute"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#selfisys.prior.planck_prior.compute" title="Link to this definition"></a></dt>
<dd><p>Compute the prior (mean, covariance, and inverse covariance).</p>
<p>If <cite>self.filename</cite> exists, tries to load the prior. Otherwise,
samples from the prior distribution on cosmological parameters
and evaluates the power spectra in parallel.</p>
<dl class="field-list simple">
<dt class="field-odd">Raises<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>OSError</strong> – If self.filename is not writable/accessible.</p></li>
<li><p><strong>RuntimeError</strong> – If multi-processing or power-spectra computations fail.</p></li>
</ul>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="selfisys.prior.planck_prior.load">
<em class="property"><span class="pre">classmethod</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">load</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">fname</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/selfisys/prior.html#planck_prior.load"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#selfisys.prior.planck_prior.load" title="Link to this definition"></a></dt>
<dd><p>Load the prior from input file.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><p><strong>fname</strong> (<em>str</em>) – Input HDF5 filename.</p>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p>The prior object.</p>
</dd>
<dt class="field-odd">Return type<span class="colon">:</span></dt>
<dd class="field-odd"><p>prior</p>
</dd>
<dt class="field-even">Raises<span class="colon">:</span></dt>
<dd class="field-even"><p><strong>OSError</strong> – If the file cannot be read or is invalid.</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="selfisys.prior.planck_prior.logpdf">
<span class="sig-name descname"><span class="pre">logpdf</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">theta</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">theta_mean</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">theta_covariance</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">theta_icov</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/selfisys/prior.html#planck_prior.logpdf"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#selfisys.prior.planck_prior.logpdf" title="Link to this definition"></a></dt>
<dd><p>Return the log prior probability at a given point in parameter
space.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>theta</strong> (<em>ndarray</em>) – Evaluation point in parameter space.</p></li>
<li><p><strong>theta_mean</strong> (<em>ndarray</em>) – Prior mean vector.</p></li>
<li><p><strong>theta_covariance</strong> (<em>ndarray</em>) – Prior covariance matrix.</p></li>
<li><p><strong>theta_icov</strong> (<em>ndarray</em>) – Inverse of the prior covariance matrix.</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p>Log prior probability value.</p>
</dd>
<dt class="field-odd">Return type<span class="colon">:</span></dt>
<dd class="field-odd"><p>float</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="selfisys.prior.planck_prior.sample">
<span class="sig-name descname"><span class="pre">sample</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">seedsample</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/selfisys/prior.html#planck_prior.sample"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#selfisys.prior.planck_prior.sample" title="Link to this definition"></a></dt>
<dd><p>Draw a random sample from the prior distribution.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><p><strong>seedsample</strong> (<em>int</em><em>, </em><em>optional</em>) – Seed for the random number generator.</p>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p>A single sample from the prior distribution.</p>
</dd>
<dt class="field-odd">Return type<span class="colon">:</span></dt>
<dd class="field-odd"><p>ndarray</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="selfisys.prior.planck_prior.save">
<span class="sig-name descname"><span class="pre">save</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">fname</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/selfisys/prior.html#planck_prior.save"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#selfisys.prior.planck_prior.save" title="Link to this definition"></a></dt>
<dd><p>Save the prior to an output file.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><p><strong>fname</strong> (<em>str</em>) – Output HDF5 filename to store the prior data.</p>
</dd>
<dt class="field-even">Raises<span class="colon">:</span></dt>
<dd class="field-even"><p><strong>OSError</strong> – If the file cannot be accessed or written.</p>
</dd>
</dl>
</dd></dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="selfisys.prior.worker_class">
<span class="sig-prename descclassname"><span class="pre">selfisys.prior.</span></span><span class="sig-name descname"><span class="pre">worker_class</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">params</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/selfisys/prior.html#worker_class"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#selfisys.prior.worker_class" title="Link to this definition"></a></dt>
<dd><p>Worker function to compute power spectra with CLASS, compatible with
Python multiprocessing.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><p><strong>params</strong> (<em>tuple</em>) – (x, bins, normalisation, kmax) where x is an array-like of
cosmological parameters, bins is the wavenumber array,
normalisation is a float or None, and kmax is a float.</p>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p><strong>theta</strong> – Power-spectrum summary from <cite>get_summary</cite>.</p>
</dd>
<dt class="field-odd">Return type<span class="colon">:</span></dt>
<dd class="field-odd"><p>ndarray</p>
</dd>
</dl>
</dd></dl>
</section>
<section id="module-selfisys.sbmy_interface">
<span id="selfisys-sbmy-interface-module"></span><h2>selfisys.sbmy_interface module<a class="headerlink" href="#module-selfisys.sbmy_interface" title="Link to this heading"></a></h2>
<dl class="py function">
<dt class="sig sig-object py" id="selfisys.sbmy_interface.compute_Phi">
<span class="sig-prename descclassname"><span class="pre">selfisys.sbmy_interface.</span></span><span class="sig-name descname"><span class="pre">compute_Phi</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">G_ss_path</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">P_ss_path</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">g_obj</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">norm</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">AliasingCorr</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbosity</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/selfisys/sbmy_interface.html#compute_Phi"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#selfisys.sbmy_interface.compute_Phi" title="Link to this definition"></a></dt>
<dd><p>Compute the summary statistics from a field object, based on a
provided summary-statistics Fourier grid and baseline spectrum.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>G_ss_path</strong> (<em>str</em>) – Path to the FourierGrid file used for summary-statistics.</p></li>
<li><p><strong>P_ss_path</strong> (<em>str</em>) – Path to the baseline power spectrum file for normalisation.</p></li>
<li><p><strong>g_obj</strong> (<em>Field</em>) – Input field object from which to compute summary statistics.</p></li>
<li><p><strong>norm</strong> (<em>ndarray</em>) – Normalisation constants for the summary statistics.</p></li>
<li><p><strong>AliasingCorr</strong> (<em>bool</em><em>, </em><em>optional</em>) – Whether to apply aliasing correction. Default is True.</p></li>
<li><p><strong>verbosity</strong> (<em>int</em><em>, </em><em>optional</em>) – Verbosity level (0=quiet, 1=normal, 2=debug). Default 1.</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p><strong>Phi</strong> – Vector of summary statistics.</p>
</dd>
<dt class="field-odd">Return type<span class="colon">:</span></dt>
<dd class="field-odd"><p>ndarray</p>
</dd>
<dt class="field-even">Raises<span class="colon">:</span></dt>
<dd class="field-even"><ul class="simple">
<li><p><strong>OSError</strong> – If file reading fails at G_ss_path or P_ss_path.</p></li>
<li><p><strong>RuntimeError</strong> – If unexpected issues occur during computation.</p></li>
</ul>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="selfisys.sbmy_interface.generate_white_noise_Field">
<span class="sig-prename descclassname"><span class="pre">selfisys.sbmy_interface.</span></span><span class="sig-name descname"><span class="pre">generate_white_noise_Field</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">L</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">size</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seedphase</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fname_whitenoise</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seedname_whitenoise</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">force_phase</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/selfisys/sbmy_interface.html#generate_white_noise_Field"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#selfisys.sbmy_interface.generate_white_noise_Field" title="Link to this definition"></a></dt>
<dd><p>Generate a white noise realisation in physical space and write it to
disk.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>L</strong> (<em>float</em>) – Size of the simulation box (in Mpc/h).</p></li>
<li><p><strong>size</strong> (<em>int</em>) – Number of grid points along each axis.</p></li>
<li><p><strong>seedphase</strong> (<em>int</em><em> or </em><em>list</em><em> of </em><em>int</em>) – User-provided seed to generate the initial white noise.</p></li>
<li><p><strong>fname_whitenoise</strong> (<em>str</em>) – File path to write the white noise realisation.</p></li>
<li><p><strong>seedname_whitenoise</strong> (<em>str</em>) – File path to write the seed state of the RNG.</p></li>
<li><p><strong>force_phase</strong> (<em>bool</em><em>, </em><em>optional</em>) – If True, forces regeneration of the random phases. Default is
False.</p></li>
</ul>
</dd>
<dt class="field-even">Raises<span class="colon">:</span></dt>
<dd class="field-even"><ul class="simple">
<li><p><strong>OSError</strong> – If file writing fails or directory paths are invalid.</p></li>
<li><p><strong>RuntimeError</strong> – For unexpected issues.</p></li>
</ul>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="selfisys.sbmy_interface.get_power_spectrum_from_cosmo">
<span class="sig-prename descclassname"><span class="pre">selfisys.sbmy_interface.</span></span><span class="sig-name descname"><span class="pre">get_power_spectrum_from_cosmo</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">L</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">size</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cosmo</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fname_power_spectrum</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">force</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/selfisys/sbmy_interface.html#get_power_spectrum_from_cosmo"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#selfisys.sbmy_interface.get_power_spectrum_from_cosmo" title="Link to this definition"></a></dt>
<dd><p>Compute a power spectrum from cosmological parameters and save it to
disk.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>L</strong> (<em>float</em>) – Size of the simulation box (in Mpc/h).</p></li>
<li><p><strong>size</strong> (<em>int</em>) – Number of grid points along each axis.</p></li>
<li><p><strong>cosmo</strong> (<em>dict</em>) – Cosmological parameters (and infrastructure parameters).</p></li>
<li><p><strong>fname_power_spectrum</strong> (<em>str</em>) – Name (including path) of the power spectrum file to read/write.</p></li>
<li><p><strong>force</strong> (<em>bool</em><em>, </em><em>optional</em>) – If True, forces recomputation even if the file exists. Default
is False.</p></li>
</ul>
</dd>
<dt class="field-even">Raises<span class="colon">:</span></dt>
<dd class="field-even"><ul class="simple">
<li><p><strong>OSError</strong> – If file writing fails or the directory path is invalid.</p></li>
<li><p><strong>RuntimeError</strong> – For unexpected issues during power spectrum computation.</p></li>
</ul>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="selfisys.sbmy_interface.handle_time_stepping">
<span class="sig-prename descclassname"><span class="pre">selfisys.sbmy_interface.</span></span><span class="sig-name descname"><span class="pre">handle_time_stepping</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">aa</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">float</span><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="n"><span class="pre">total_steps</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">modeldir</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">figuresdir</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sim_params</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">force</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">Tuple</span><span class="p"><span class="pre">[</span></span><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">int</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span><span class="p"><span class="pre">]</span></span></span></span><a class="reference internal" href="_modules/selfisys/sbmy_interface.html#handle_time_stepping"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#selfisys.sbmy_interface.handle_time_stepping" title="Link to this definition"></a></dt>
<dd><p>Create and merge individual time-stepping objects.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>aa</strong> (<em>list</em><em> of </em><em>float</em>) – List of scale factors in ascending order.</p></li>
<li><p><strong>total_steps</strong> (<em>int</em>) – Total number of time steps to distribute among the provided
scale factors.</p></li>
<li><p><strong>modeldir</strong> (<em>str</em>) – Directory path to store generated time-stepping files.</p></li>
<li><p><strong>figuresdir</strong> (<em>str</em>) – Directory path to store time-stepping plots.</p></li>
<li><p><strong>sim_params</strong> (<em>str</em>) – Simulation parameter string (e.g., “custom”, “std”, “nograv”).</p></li>
<li><p><strong>force</strong> (<em>bool</em><em>, </em><em>optional</em>) – Whether to force recompute the time-stepping files. Default is
False.</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p><ul class="simple">
<li><p><strong>merged_path</strong> (<em>str</em>) – Path to the merged time-stepping file.</p></li>
<li><p><strong>indices_steps_cumul</strong> (<em>list of int or None</em>) – Cumulative indices for the distributed steps. Returns None if
using splitLPT or if <cite>sim_params</cite> indicates an alternative
strategy.</p></li>
<li><p><strong>eff_redshifts</strong> (<em>float or None</em>) – Effective redshift derived from the final scale factor in
‘custom’ or ‘nograv’ mode. None otherwise.</p></li>
</ul>
</p>
</dd>
<dt class="field-odd">Raises<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>NotImplementedError</strong> – If a unsupported time-stepping strategy is used.</p></li>
<li><p><strong>OSError</strong> – If file or directory operations fail.</p></li>
<li><p><strong>RuntimeError</strong> – If unexpected issues occur during time-stepping setup.</p></li>
</ul>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="selfisys.sbmy_interface.setup_sbmy_parfiles">
<span class="sig-prename descclassname"><span class="pre">selfisys.sbmy_interface.</span></span><span class="sig-name descname"><span class="pre">setup_sbmy_parfiles</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">d</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cosmology</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">file_names</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">hiddenbox_params</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">force</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/selfisys/sbmy_interface.html#setup_sbmy_parfiles"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#selfisys.sbmy_interface.setup_sbmy_parfiles" title="Link to this definition"></a></dt>
<dd><p>Set up Simbelmynë parameter file (please refer to the Simbelmynë
documentation for more details).</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>d</strong> (<em>int</em>) – Index (from 1 to S) specifying a direction in parameter space, 0
for the expansion point, or -1 for mock data.</p></li>
<li><p><strong>cosmology</strong> (<em>array</em><em>, </em><em>double</em><em>, </em><em>dimension=5</em>) – Cosmological parameters.</p></li>
<li><p><strong>file_names</strong> (<em>dict</em>) – Dictionary containing the names of the input/output files for
the simulation.</p></li>
<li><p><strong>hiddenbox_params</strong> (<em>dict</em>) – See the <cite>HiddenBox</cite> class for more details.</p></li>
<li><p><strong>force</strong> (<em>bool</em><em>, </em><em>optional</em><em>, </em><em>default=False</em>) – If True, forces recompute the simulation parameter files.</p></li>
</ul>
</dd>
</dl>
</dd></dl>
</section>
<section id="module-selfisys.selection_functions">
<span id="selfisys-selection-functions-module"></span><h2>selfisys.selection_functions module<a class="headerlink" href="#module-selfisys.selection_functions" title="Link to this heading"></a></h2>
<dl class="py class">
<dt class="sig sig-object py" id="selfisys.selection_functions.LognormalSelection">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">selfisys.selection_functions.</span></span><span class="sig-name descname"><span class="pre">LognormalSelection</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">L</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">selection_params</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">survey_mask_path</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">local_select_path</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">size</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/selfisys/selection_functions.html#LognormalSelection"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#selfisys.selection_functions.LognormalSelection" title="Link to this definition"></a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></p>
<p>Class to generate radial selection functions.</p>
<dl class="py method">
<dt class="sig sig-object py" id="selfisys.selection_functions.LognormalSelection.init_selection">
<span class="sig-name descname"><span class="pre">init_selection</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">reset</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/selfisys/selection_functions.html#LognormalSelection.init_selection"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#selfisys.selection_functions.LognormalSelection.init_selection" title="Link to this definition"></a></dt>
<dd><p>Initialise the radial selection functions.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><p><strong>reset</strong> (<em>bool</em><em>, </em><em>optional</em>) – Whether to reset the selection function.</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="selfisys.selection_functions.LognormalSelection.lognormals_z_to_x">
<span class="sig-name descname"><span class="pre">lognormals_z_to_x</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">xx</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mask</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">params</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">spline</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/selfisys/selection_functions.html#LognormalSelection.lognormals_z_to_x"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#selfisys.selection_functions.LognormalSelection.lognormals_z_to_x" title="Link to this definition"></a></dt>
<dd><p>Convert log-normal distributions from redshift to distance.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>xx</strong> (<em>array-like</em>) – Comoving distances at which to evaluate the distributions.</p></li>
<li><p><strong>mask</strong> (<em>ndarray</em><em> or </em><em>None</em>) – Survey mask C(n).</p></li>
<li><p><strong>params</strong> (<em>tuple</em><em> of </em><em>arrays</em>) – Parameters for the distributions (ss, mm, rr).</p></li>
<li><p><strong>spline</strong> (<em>UnivariateSpline</em>) – Linear interpolator for the distance-redshift relation.</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p>Tuple containing redshifts and list of distributions.</p>
</dd>
<dt class="field-odd">Return type<span class="colon">:</span></dt>
<dd class="field-odd"><p>tuple</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="selfisys.selection_functions.LognormalSelection.multiple_lognormal">
<span class="sig-name descname"><span class="pre">multiple_lognormal</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mask</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ss</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ll</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rr</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/selfisys/selection_functions.html#LognormalSelection.multiple_lognormal"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#selfisys.selection_functions.LognormalSelection.multiple_lognormal" title="Link to this definition"></a></dt>
<dd><p>Compute multiple log-normal distributions.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>x</strong> (<em>ndarray</em>) – Input array.</p></li>
<li><p><strong>mask</strong> (<em>ndarray</em><em> or </em><em>None</em>) – Survey mask C(n).</p></li>
<li><p><strong>ss</strong> (<em>array_like</em>) – Standard deviations for each distribution.</p></li>
<li><p><strong>ll</strong> (<em>array_like</em>) – Means for each distribution.</p></li>
<li><p><strong>rr</strong> (<em>array_like</em>) – Rescaling factors for each distribution.</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p>List of log-normal distributions.</p>
</dd>
<dt class="field-odd">Return type<span class="colon">:</span></dt>
<dd class="field-odd"><p>list of ndarray</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="selfisys.selection_functions.LognormalSelection.multiple_lognormal_z">
<span class="sig-name descname"><span class="pre">multiple_lognormal_z</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mask</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ss</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mm</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rr</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/selfisys/selection_functions.html#LognormalSelection.multiple_lognormal_z"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#selfisys.selection_functions.LognormalSelection.multiple_lognormal_z" title="Link to this definition"></a></dt>
<dd><p>Compute multiple rescaled lognormal distributions as functions
of redshift.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>x</strong> (<em>ndarray</em>) – Input array (redshifts).</p></li>
<li><p><strong>mask</strong> (<em>ndarray</em><em> or </em><em>None</em>) – Survey mask C(n).</p></li>
<li><p><strong>ss</strong> (<em>array_like</em>) – Standard deviations of the lognormal distributions.</p></li>
<li><p><strong>mm</strong> (<em>array_like</em>) – Means of the lognormal distributions.</p></li>
<li><p><strong>rr</strong> (<em>array_like</em>) – Rescaling factors for each distribution.</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p>List of log-normal distributions.</p>
</dd>
<dt class="field-odd">Return type<span class="colon">:</span></dt>
<dd class="field-odd"><p>list of ndarray</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="selfisys.selection_functions.LognormalSelection.one_lognormal">
<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">one_lognormal</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">std</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mean</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rescale</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/selfisys/selection_functions.html#LognormalSelection.one_lognormal"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#selfisys.selection_functions.LognormalSelection.one_lognormal" title="Link to this definition"></a></dt>
<dd><p>Rescaled log-normal distribution.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>x</strong> (<em>ndarray</em>) – Input array.</p></li>
<li><p><strong>std</strong> (<em>float</em>) – Standard deviation of the distribution.</p></li>
<li><p><strong>mean</strong> (<em>float</em>) – Mean of the distribution.</p></li>
<li><p><strong>rescale</strong> (<em>float</em><em>, </em><em>optional</em>) – Rescaling factor. If None, the distribution is normalised
such that its maximum value is 1.</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p>Log-normal distribution evaluated at x.</p>
</dd>
<dt class="field-odd">Return type<span class="colon">:</span></dt>
<dd class="field-odd"><p>ndarray</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="selfisys.selection_functions.LognormalSelection.one_lognormal_z">
<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">one_lognormal_z</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sig2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mu</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">rescale</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/selfisys/selection_functions.html#LognormalSelection.one_lognormal_z"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#selfisys.selection_functions.LognormalSelection.one_lognormal_z" title="Link to this definition"></a></dt>
<dd><p>Compute a log-normal distribution in redshift.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>x</strong> (<em>ndarray</em>) – Input array.</p></li>
<li><p><strong>sig2</strong> (<em>float</em>) – Variance of the distribution.</p></li>
<li><p><strong>mu</strong> (<em>float</em>) – Mean of the distribution.</p></li>
<li><p><strong>rescale</strong> (<em>float</em><em>, </em><em>optional</em>) – Rescaling factor.</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p>Log-normal distribution evaluated at x.</p>
</dd>
<dt class="field-odd">Return type<span class="colon">:</span></dt>
<dd class="field-odd"><p>ndarray</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="selfisys.selection_functions.LognormalSelection.r_grid">
<span class="sig-name descname"><span class="pre">r_grid</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/selfisys/selection_functions.html#LognormalSelection.r_grid"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#selfisys.selection_functions.LognormalSelection.r_grid" title="Link to this definition"></a></dt>
<dd><p>Compute the grid of radial distances in the simulation box.</p>
<dl class="field-list simple">
<dt class="field-odd">Returns<span class="colon">:</span></dt>
<dd class="field-odd"><p>3D array of radial distances from the origin.</p>
</dd>
<dt class="field-even">Return type<span class="colon">:</span></dt>
<dd class="field-even"><p>ndarray</p>
</dd>
<dt class="field-odd">Raises<span class="colon">:</span></dt>
<dd class="field-odd"><p><strong>AttributeError</strong> – If the ‘size’ attribute is not defined.</p>
</dd>
</dl>
</dd></dl>
</dd></dl>
</section>
<section id="module-selfisys.selfi_interface">
<span id="selfisys-selfi-interface-module"></span><h2>selfisys.selfi_interface module<a class="headerlink" href="#module-selfisys.selfi_interface" title="Link to this heading"></a></h2>
<dl class="py function">
<dt class="sig sig-object py" id="selfisys.selfi_interface.PrintMessage">
<span class="sig-prename descclassname"><span class="pre">selfisys.selfi_interface.</span></span><span class="sig-name descname"><span class="pre">PrintMessage</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">required_verbosity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">message</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbosity</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">None</span></span></span><a class="reference internal" href="_modules/selfisys/selfi_interface.html#PrintMessage"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#selfisys.selfi_interface.PrintMessage" title="Link to this definition"></a></dt>
<dd><p>Print a message to standard output using pyselfi.utils.PrintMessage.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>required_verbosity</strong> (<em>int</em>) – The verbosity level required to display the message.</p></li>
<li><p><strong>message</strong> (<em>str</em>) – The actual message to display.</p></li>
<li><p><strong>verbosity</strong> (<em>int</em>) – The current verbosity level (0=quiet, 1=normal, 2=debug).</p></li>
</ul>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="selfisys.selfi_interface.indent">
<span class="sig-prename descclassname"><span class="pre">selfisys.selfi_interface.</span></span><span class="sig-name descname"><span class="pre">indent</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">None</span></span></span><a class="reference internal" href="_modules/selfisys/selfi_interface.html#indent"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#selfisys.selfi_interface.indent" title="Link to this definition"></a></dt>
<dd><p>Indent the standard output using pyselfi.utils.</p>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="selfisys.selfi_interface.unindent">
<span class="sig-prename descclassname"><span class="pre">selfisys.selfi_interface.</span></span><span class="sig-name descname"><span class="pre">unindent</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">None</span></span></span><a class="reference internal" href="_modules/selfisys/selfi_interface.html#unindent"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#selfisys.selfi_interface.unindent" title="Link to this definition"></a></dt>
<dd><p>Unindent the standard output using pyselfi.utils.</p>
</dd></dl>
</section>
<section id="module-selfisys.setup_model">
<span id="selfisys-setup-model-module"></span><h2>selfisys.setup_model module<a class="headerlink" href="#module-selfisys.setup_model" title="Link to this heading"></a></h2>
<dl class="py class">
<dt class="sig sig-object py" id="selfisys.setup_model.ModelSetup">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">selfisys.setup_model.</span></span><span class="sig-name descname"><span class="pre">ModelSetup</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">size</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">L</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">P</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">S</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">G_sim_path</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">G_ss_path</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">Pbins_bnd</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">Pbins</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k_s</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">P_ss_obj_path</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">P_0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">planck_Pk</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/selfisys/setup_model.html#ModelSetup"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#selfisys.setup_model.ModelSetup" title="Link to this definition"></a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal notranslate"><span class="pre">NamedTuple</span></code></p>
<dl class="py attribute">
<dt class="sig sig-object py" id="selfisys.setup_model.ModelSetup.G_sim_path">
<span class="sig-name descname"><span class="pre">G_sim_path</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">str</span></em><a class="headerlink" href="#selfisys.setup_model.ModelSetup.G_sim_path" title="Link to this definition"></a></dt>
<dd><p>Alias for field number 4</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="selfisys.setup_model.ModelSetup.G_ss_path">
<span class="sig-name descname"><span class="pre">G_ss_path</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">str</span></em><a class="headerlink" href="#selfisys.setup_model.ModelSetup.G_ss_path" title="Link to this definition"></a></dt>
<dd><p>Alias for field number 5</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="selfisys.setup_model.ModelSetup.L">
<span class="sig-name descname"><span class="pre">L</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">float</span></em><a class="headerlink" href="#selfisys.setup_model.ModelSetup.L" title="Link to this definition"></a></dt>
<dd><p>Alias for field number 1</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="selfisys.setup_model.ModelSetup.P">
<span class="sig-name descname"><span class="pre">P</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">int</span></em><a class="headerlink" href="#selfisys.setup_model.ModelSetup.P" title="Link to this definition"></a></dt>
<dd><p>Alias for field number 2</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="selfisys.setup_model.ModelSetup.P_0">
<span class="sig-name descname"><span class="pre">P_0</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">ndarray</span></em><a class="headerlink" href="#selfisys.setup_model.ModelSetup.P_0" title="Link to this definition"></a></dt>
<dd><p>Alias for field number 10</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="selfisys.setup_model.ModelSetup.P_ss_obj_path">
<span class="sig-name descname"><span class="pre">P_ss_obj_path</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">str</span></em><a class="headerlink" href="#selfisys.setup_model.ModelSetup.P_ss_obj_path" title="Link to this definition"></a></dt>
<dd><p>Alias for field number 9</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="selfisys.setup_model.ModelSetup.Pbins">
<span class="sig-name descname"><span class="pre">Pbins</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">ndarray</span></em><a class="headerlink" href="#selfisys.setup_model.ModelSetup.Pbins" title="Link to this definition"></a></dt>
<dd><p>Alias for field number 7</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="selfisys.setup_model.ModelSetup.Pbins_bnd">
<span class="sig-name descname"><span class="pre">Pbins_bnd</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">ndarray</span></em><a class="headerlink" href="#selfisys.setup_model.ModelSetup.Pbins_bnd" title="Link to this definition"></a></dt>
<dd><p>Alias for field number 6</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="selfisys.setup_model.ModelSetup.S">
<span class="sig-name descname"><span class="pre">S</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">int</span></em><a class="headerlink" href="#selfisys.setup_model.ModelSetup.S" title="Link to this definition"></a></dt>
<dd><p>Alias for field number 3</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="selfisys.setup_model.ModelSetup.k_s">
<span class="sig-name descname"><span class="pre">k_s</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">ndarray</span></em><a class="headerlink" href="#selfisys.setup_model.ModelSetup.k_s" title="Link to this definition"></a></dt>
<dd><p>Alias for field number 8</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="selfisys.setup_model.ModelSetup.planck_Pk">
<span class="sig-name descname"><span class="pre">planck_Pk</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">ndarray</span></em><a class="headerlink" href="#selfisys.setup_model.ModelSetup.planck_Pk" title="Link to this definition"></a></dt>
<dd><p>Alias for field number 11</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="selfisys.setup_model.ModelSetup.size">
<span class="sig-name descname"><span class="pre">size</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">int</span></em><a class="headerlink" href="#selfisys.setup_model.ModelSetup.size" title="Link to this definition"></a></dt>
<dd><p>Alias for field number 0</p>
</dd></dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="selfisys.setup_model.compute_alpha_cv">
<span class="sig-prename descclassname"><span class="pre">selfisys.setup_model.</span></span><span class="sig-name descname"><span class="pre">compute_alpha_cv</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">workdir</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k_s</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">ndarray</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">L</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window_fct_path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">force</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">None</span></span></span><a class="reference internal" href="_modules/selfisys/setup_model.html#compute_alpha_cv"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#selfisys.setup_model.compute_alpha_cv" title="Link to this definition"></a></dt>
<dd><p>Compute the cosmic variance parameter alpha_cv.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>workdir</strong> (<em>str</em>) – Directory where the results will be stored.</p></li>
<li><p><strong>k_s</strong> (<em>np.ndarray</em>) – Support wavenumbers.</p></li>
<li><p><strong>size</strong> (<em>int</em>) – Number of elements in each direction of the box.</p></li>
<li><p><strong>L</strong> (<em>float</em>) – Comoving length of the box in Mpc/h.</p></li>
<li><p><strong>window_fct_path</strong> (<em>str</em><em>, </em><em>optional</em>) – Path to the window function file.</p></li>
<li><p><strong>force</strong> (<em>bool</em>) – If True, forces recomputation of the inputs.</p></li>
</ul>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="selfisys.setup_model.setup_model">
<span class="sig-prename descclassname"><span class="pre">selfisys.setup_model.</span></span><span class="sig-name descname"><span class="pre">setup_model</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">workdir</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">str</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">params_planck</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">params_P0</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">dict</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">256</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">L</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">3600.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">S</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">100</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">N_exact</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">8</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">Pinit</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">50</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">trim_threshold</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">100</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">minval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">maxval</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">float</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">None</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">force</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><a class="reference internal" href="selfisys.setup_model.html#selfisys.setup_model.ModelSetup" title="selfisys.setup_model.ModelSetup"><span class="pre">ModelSetup</span></a></span></span><a class="reference internal" href="_modules/selfisys/setup_model.html#setup_model"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#selfisys.setup_model.setup_model" title="Link to this definition"></a></dt>
<dd><p>Set up the model by computing or loading necessary grids and
parameters.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>workdir</strong> (<em>str</em>) – Directory where the results will be stored.</p></li>
<li><p><strong>params_planck</strong> (<em>dict</em>) – Parameters for the Planck 2018 cosmology.</p></li>
<li><p><strong>params_P0</strong> (<em>dict</em>) – Parameters for the normalisation power spectrum.</p></li>
<li><p><strong>size</strong> (<em>int</em>) – Number of elements in each direction of the box.</p></li>
<li><p><strong>L</strong> (<em>float</em>) – Comoving length of the box in Mpc/h.</p></li>
<li><p><strong>S</strong> (<em>int</em>) – Number of support wavenumbers for the input power spectra.</p></li>
<li><p><strong>N_exact</strong> (<em>int</em>) – Number of support wavenumbers matching the Fourier grid.</p></li>
<li><p><strong>Pinit</strong> (<em>int</em>) – Maximum number of bins for the summaries.</p></li>
<li><p><strong>trim_threshold</strong> (<em>int</em>) – Minimum number of modes required per bin.</p></li>
<li><p><strong>minval</strong> (<em>float</em><em>, </em><em>optional</em>) – Minimum k value for the summaries.</p></li>
<li><p><strong>maxval</strong> (<em>float</em><em>, </em><em>optional</em>) – Maximum k value for the summaries.</p></li>
<li><p><strong>force</strong> (<em>bool</em>) – If True, forces recomputation of the inputs.</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p>A named tuple containing:
- size (int): Number of elements in each direction of the box.
- L (float): Comoving length of the box in Mpc/h.
- P (int): Number of bins for the summaries.
- S (int): Number of support wavenumbers for input powerspectra.
- G_sim_path (str): Path to the full Fourier grid file.
- G_ss_path (str): Path to the Fourier grid for summaries file.
- Pbins_bnd (np.ndarray): Boundaries of summary bins.
- Pbins (np.ndarray): Centres of the bins for the summaries.
- k_s (np.ndarray): Support wavenumbers for input power spectra.
- P_ss_obj_path (str): Path to the summary power spectrum file.
- P_0 (np.ndarray): Normalisation power spectrum values.
- planck_Pk (np.ndarray): Planck 2018 power spectrum values.</p>
</dd>
<dt class="field-odd">Return type<span class="colon">:</span></dt>
<dd class="field-odd"><p><a class="reference internal" href="selfisys.setup_model.html#selfisys.setup_model.ModelSetup" title="selfisys.setup_model.ModelSetup">ModelSetup</a></p>
</dd>
</dl>
</dd></dl>
</section>
<section id="module-selfisys">
<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-selfisys" title="Link to this heading"></a></h2>
</section>
</section>
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