def parse(filename, show=False, external=True):
"""@TODO
Assumes json file is of the form:
dict with three entries: 'tests', which is a one-element list of dicts,
'parameters', which is a dict of parameters used to generate the data,
and 'data', a dict of relevant statistics regarding the model used to
generate the data.
In the case of real data, 'parameters' and 'data' will be empty dicts.
For 'tests':
The inner dict has experiment names as the keys and dicts with various
performance metrics as values
Args:
external:
flag for whether this function is being called directly from
the command line (ie it is being called by main() below);
set this to False if you want to call it from anywhere else
Returns:
A tuple (names, scores, tests, parameters, data), where:
- names is a list of all experiment names in the file, excluding those in
HIDDEN;
- scores is a list, in the same order of names, of the prediction rates
achieved by the experiments;
- tests, parameters and data are the corresponding fields taken directly
from the json file.
"""
with open(filename, 'r') as f:
data = json.load(f)
names = []
scores = []
for test in data[TEST]:
for key in sorted(test.keys(),
cmp=(lambda x,y: cmp(test[x]['Predicted_Mean'],
test[y]['Predicted_Mean']))):
if key not in HIDDEN:
names.append(str(key))
scores.append(test[key]['Predicted_Mean'])
if external:
util.figure(figsize=(12,7))
util.plot_dist(scores, labels=names)
if data[DATA]:
for datum in data[DATA]:
if datum == 'sig_words' or datum == 'sig_topics':
util.plot(0, label=str(datum) + " "
+ str(data[DATA][datum]))
util.legend(loc='best')
if show:
util.show()
else:
util.savefig(filename + '.pdf')
return names, scores, data[TEST][0], data[PARAMS], data[DATA]
def parse(filename, show):
with open(filename, 'r') as f:
data = json.load(f)
names = []
scores = []
for test in data[TEST]:
for key in test.keys():
names.append(str(key))
scores.append(test[key]['Predicted_Mean'])
util.plot_dist(scores, labels=names)
if show:
util.show()
else:
util.savefig(filename + '.pdf')
return data
def parse(filename, show):
with open(filename, 'r') as f:
data = json.load(f)
names = []
scores = []
for test in data[TEST]:
for key in test.keys():
names.append(str(key))
scores.append(test[key]['Predicted_Mean'])
util.plot_dist(scores, labels=names)
if show:
util.show()
else:
util.savefig(filename + '.pdf')
return data
