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Created with Raphaël 2.2.012Aug119643227Jul26232221201918161587542130Jun2928232221181728May27262522212019181764329Apr282721201918161514131211109876131Mar302926252322181716151211109854326Feb2524232219181716151211108432129Jan272120191818Dec1716151110987321update run_wrf.py and run_wrf_dh_sector.py in order to use toarstatsmove _force_dask_comp to absract dh and include input_output_sampling4toarstatsinclude first impl of toarstatisticsfurther testing if any np.nan is in first_param and det() calculation using da.map_blocks(np.linalg.det,...)fixed tuple dask problem caused by dask_array direct assignment of guess_mat = da.full(...) -> guess_mat = np.full(...)merged origin/master into branchdask_delayed.compute()[0], because get_legendre_fit evaluation now results in a tuple returndask_delayed.compute()[0], because get_legendre_fit evaluation now results in a tuple returndask_delayed.compute[0](), because get_legendre_fit evaluation now results in a tuple returnchanged np. to da. in get_legendre_fit()print experiment configReverting the changesvincent_issue31…vincent_issue318-workaround-to-get-resultsReverting the changesBefore making new branchupdate MyLuongAttentionLSTMModelresorted dealing with self.variables, so self.history only contains input vars. Minor tweaks to legendre transformation. New switches for transformation (standardization, normalization if not Legendre)Updated run-scripts for hdfmlAdded bias and titles to PlotOversamplingContingencyMerge branch 'felix_issue287_tech-wrf-datahandler-should-inherit-from-singlestationdatahandler' of ssh://gitlab.version.fz-juelich.de:10022/esde/machine-learning/mlair into felix_issue287_tech-wrf-datahandler-should-inherit-from-singlestationdatahandlerupdate MyLSTMModelAdd new model class MyLuongAttentionLSTMModel based on https://levelup.gitconnected.com/building-seq2seq-lstm-with-luong-attention-in-keras-for-time-series-forecasting-1ee00958decbGives ValueError if window_lead_time of competitors and model dont matchMade PlotOversamplingContingency get min and max_thresholdtransformation is called when do_legendre_transformation=False, also shape of a_guess return if singular matrix is a np.nan xarray of a_guess shapecheck for det(first_param)==0 in get_legendre_fit(...) for invertibilityMerge branch 'felix_issue287_tech-wrf-datahandler-should-inherit-from-singlestationdatahandler' of ssh://gitlab.version.fz-juelich.de:10022/esde/machine-learning/mlair into felix_issue287_tech-wrf-datahandler-should-inherit-from-singlestationdatahandlerreset data pathmupdate setctorial test modelsremoved 3D REA6 vars in run_mtfalco()removed 3D REA6 vars in run_mtfalco()removed 3D REA6 vars in run_mtfalco()more clear missing variables from DB message handling - aborting only when all are missingdebug available variablesall REA6 variables as inputMerge branch 'develop' into felix_issue287_tech-wrf-datahandler-should-inherit-from-singlestationdatahandlerMade PlotOversamplingContingency plot competitorsepochs=300 and plot_list defaultcomputation_mode='juwels'added n_legendre_polynomials as a parameter into DefaultWorkflow()Merge branch 'release_v1.4.0' into 'master'v1.4.0v1.4.0