pandora package
Submodules
- pandora.bootstrap module
- pandora.converter module
- pandora.custom_errors module
- pandora.custom_types module
- pandora.dataset module
EigenDatasetEigenDataset.bootstrap()EigenDataset.check_files()EigenDataset.files_exist()EigenDataset.fst_population_distance()EigenDataset.get_population_info()EigenDataset.get_projected_samples()EigenDataset.get_sample_info()EigenDataset.get_sequence_length()EigenDataset.get_windows()EigenDataset.remove_input_files()EigenDataset.run_mds()EigenDataset.run_pca()
NumpyDatasetnumpy_dataset_from_eigenfiles()
- pandora.distance_metrics module
- pandora.embedding module
- pandora.embedding_comparison module
- pandora.imputation module
- pandora.logger module
- pandora.main module
- pandora.pandora module
PandoraPandoraConfigPandoraConfig.analysis_modePandoraConfig.bootstrap_convergence_checkPandoraConfig.bootstrap_convergence_tolerancePandoraConfig.bootstrap_result_dirPandoraConfig.configfilePandoraConfig.convertfPandoraConfig.convertf_result_dirPandoraConfig.dataset_prefixPandoraConfig.embedding_algorithmPandoraConfig.embedding_populationsPandoraConfig.file_formatPandoraConfig.get_configuration()PandoraConfig.keep_replicatesPandoraConfig.kmeans_kPandoraConfig.log_results_files()PandoraConfig.loglevelPandoraConfig.model_configPandoraConfig.n_componentsPandoraConfig.n_replicatesPandoraConfig.pairwise_stability_result_filePandoraConfig.pandora_logfilePandoraConfig.plot_dim_xPandoraConfig.plot_dim_yPandoraConfig.plot_dirPandoraConfig.plot_resultsPandoraConfig.projected_sample_support_values_csvPandoraConfig.redoPandoraConfig.result_decimalsPandoraConfig.result_dirPandoraConfig.result_filePandoraConfig.sample_support_values_csvPandoraConfig.save_config()PandoraConfig.seedPandoraConfig.sliding_window_result_dirPandoraConfig.smartpcaPandoraConfig.smartpca_optional_settingsPandoraConfig.support_value_rogue_cutoffPandoraConfig.threadsPandoraConfig.verbosity
convert_to_eigenstrat_format()pandora_config_from_configfile()
- pandora.plotting module
- pandora.sliding_window module
Module contents
Numpy uses OMP and BLAS for its linear algebra under the hood.
Per default, both libraries use all cores on the machine. Since we are doing a pairwise comparison of all bootstrap/window replicates, for a substantial amount of time Pandora would require all cores on the machine, which is not an option when working on shared servers/clusters. Therefore, we set the OMP and BLAS threads manually to 1 to prevent this. Setting these variables needs to happen before the first import of numpy.