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