#!/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 = []
