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Created with Raphaël 2.2.018Oct15141312118765427Sep241413987632131Aug30272625242322212019181716141312119643227Jul26232221201918161587542130Jun2928232221181728May27262522212019181764329Apr282721201918161514131211109876131Mar302926252322181716151211109854326Feb252423Merge branch 'issue333_feat_sample-uncertainty-rename-feature-importance-bootstrap' into 'issue333_feat_test-set-sample-uncertainty'include first draft of PlotSampleUncertaintyFromBootstrapupdated parameter names in run scriptsinclude first draft of PlotSampleUncertaintyFromBootstraptest updatetest for defaults updatedrenamed feature importance bootstrap variables and methodsadded parameter to set number of boots for uncertainty estimationinclude create_n_bootstrap_realizations in estimate_sample_uncertainty, added left-over todosMerge branch 'issue333A-test-set-sample-uncertainty-in-postprocessing-2' into 'issue333_feat_test-set-sample-uncertainty'draft uncertainiy bootsdraft uncertainiy bootsblock_length and evaluate_competitors can be set from outsidecan calculate block mseMerge branch 'lukas_issue332_feat_report-error-metrics-for-all-competitors' into 'issue333_feat_test-set-sample-uncertainty'add helpersremove does not work properly stillfix issue with remove items if length is of 0fixed another problem with missing station forecastasmake_predict_function() changed to non-private version in training:102, abstract_model_class:134+ disabled __compare_keras_optimizers and rewrite empty lists with Noneadded weighted skill score mean to tablesanother adjustment for cases that no observation but a competitor is availablechange naming of skill score reportssmall fix if no model_list is availalso store competitive skill scoresobs dim is now derived from class attributerecent develop branch changes put in data_handler_single_station manually. May has overwritten something. Certainly {self.target_dim: helpers.to_list(self.target_var)}) # ToDo: is it right to expand this dim??experiment_setup.py: if no experiment_name is given (None), only the experiment_date is chosen as a nameerrors of external competitors are now added tooreports now errors for all competitors tootf_upgrade_tf2 run on whole directory. Only training.py and abstract_model_class.py directly affected by the script. Other problems were mostly import keras related and solved with import tensorflow.keras as keras. Not possible for advanced_paddings.py. For details see: https://gitlab.jsc.fz-juelich.de/esde/machine-learning/mlair/-/issues/331Merge branch 'lukas_issue330_bug_calculate-bootstraps' into 'develop'manually loaded CUDA/10.1.105 added to mlt_modules_juwels.shmanually loaded CUDA/11.0.2 added to mlt_modules_juwels.shmax_number_multiprocessing=7 added, np.linalg.det(first_param) < 1e-5 in legendre_reduction addedlazy preprocessed data only saved when not foundcalculate_legendre_reduction loops correctly over all split intervals nowpre_processing.py when station raised an error no _res_file is returned in f_proc, but None. This is catched within validate_station before it is read there againcalculate_legendre_reduction removed old dask codecalculate_legendre_reduction refactored to a splitted dask computation using client.submit and client.gather functionality