#!/usr/bin/env python from joblib import Parallel, delayed import numpy as np import os import tempfile import tsh.obsolete as tsh; logger = tsh.create_logger(__name__) from utils import read_argsfile, read_listfile, write_listfile, clean_args method_table = {} def get_pregenerated_features(sample, feature_names=None, **kwargs): assert feature_names is not None return np.array([ sample[f] for f in feature_names ], dtype=np.float64) def prepare_pregenerated_features(data, features=None, **kwargs): return {} method_table['pregenerated'] = { 'function': get_pregenerated_features, 'prepare': prepare_pregenerated_features } try: from features_chaincode import get_chaincode_features,\ prepare_chaincode_features method_table['chaincode'] = { 'function': get_chaincode_features,
#!/usr/bin/env python import matplotlib matplotlib.use('Agg') import matplotlib.pyplot as plt import numpy as np import tempfile import os import tsh.obsolete as tsh logger = tsh.create_logger(__name__) from utils import read_propagatorfile if __name__ == '__main__': import argparse parser = argparse.ArgumentParser( description='Plot cross-validation results for a given model.') parser.add_argument('-c', '--config', dest='config', required=False, action='store', default=None, help='Path to the config file') parser.add_argument('-m', '--model', dest='model', required=True, action='store', default=None, help='Propagator file.')
#!/usr/bin/env python import matplotlib; matplotlib.use('Agg') import numpy as np import heapq import os import tempfile from jinja2 import Environment, FileSystemLoader import tsh.obsolete as tsh; logger = tsh.create_logger(__name__) from utils import read_listfile, read_truthfile, read_weightsfile def get_samples_data(listname, dissimname, predname, propname, truthname, only_errors, k=5): meta, data = read_listfile(listname) dissim_meta, dissim_ids, dissim = read_weightsfile(dissimname) assert (data['id'] == dissim_ids).all() if 'truth' in meta: truth_name = meta['truth'] labels = meta[truth_name + '_labels'] if predname != None: pred_meta, pred = read_listfile(predname) assert (data['id'] == pred['id']).all() if propname != None: prop_meta, prop = read_listfile(propname) assert (data['id'] == prop['id']).all() if truthname != None: truth_meta, truth_ids, truth = read_truthfile(truthname) truth_name = truth_meta['truth'] labels = truth_meta[truth_name + '_labels'] samples = []