from collections import OrderedDict from pypospack.pyposmat.data.pipeline import PyposmatPipeline pipeline_configuration = OrderedDict() # define first segment (plotting) pipeline_configuration[0] = OrderedDict() pipeline_configuration[0]['segment_type'] = 'plot' pipeline_configuration[0]['function_calls'] = OrderedDict() pipeline_configuration[0]['function_calls'][0]= OrderedDict() pipeline_configuration[0]['function_calls'][0]['function'] = 'plot_by_cluster' pipeline_configuration[0]['function_calls'][0]['args'] = OrderedDict() pipeline_configuration[0]['function_calls'][0]['args']['x_axis'] = 'pca_1' pipeline_configuration[0]['function_calls'][0]['args']['y_axis'] = 'pca_2' pipeline_configuration[0]['function_calls'][0]['args']['filename'] = 'param_clusters_in_qoi_pca_space.png' if __name__ == "__main__": pipeline = PyposmatPipeline() fn = __file__.replace('.py', '.in') pipeline.write_configuration(filename=fn, d=pipeline_configuration)
pypospack_root_dir = pypospack.utils.get_pypospack_root_directory() configuration_dir = 'examples/Ni__eam__born_exp_fs_postprocessing/Reduced_Isomap_qoi_in_param/configuration/' config_fn_0 = os.path.join(pypospack_root_dir, configuration_dir, 'configure_qoi_clustering.in') config_fn_1 = os.path.join(pypospack_root_dir, configuration_dir, 'configure_param_isomap.in') config_fn_2 = os.path.join(pypospack_root_dir, configuration_dir, 'configure_final_plot.in') pyposmat_data_fn = os.path.join( pypospack_root_dir, 'data/Ni__eam__born_exp_fs__3.5NN/pyposmat.kde.20.out') if __name__ == "__main__": # normalize, pca transform, and cluster qoi space pipeline_0 = PyposmatPipeline(configuration_fn=config_fn_0, data_fn=pyposmat_data_fn) pipeline_0.read_configuration(config_fn_0) pipeline_0.read_data(pyposmat_data_fn) pipeline_0.run() # normalize and pca transform param space pipeline_1 = PyposmatPipeline(configuration_fn=config_fn_1, data_fn=pyposmat_data_fn) pipeline_1.read_configuration(config_fn_1) pipeline_1.read_data(pyposmat_data_fn) pipeline_1.run() pipeline_1.df['cluster_id'] = pipeline_0.df[ 'cluster_id'] # transfer cluster labels # plot qoi clusters in parameter space