def test_exponential():
fp = StringIO.StringIO()
fp.write("dpc1,mean\n")
fp.write("0,1\n")
fp.seek(0)
output = StringIO.StringIO()
FeaturesInterpreter.init_from_feature_file(SplineModel(), fp, ',', (0, 100)).write(output, ',')
print output.getvalue()
fp.close()
output.close()
def test_non_gaussian():
fp = StringIO.StringIO()
fp.write("dpc1,mean,.025,.975\n")
fp.write("0,0,-1,2\n")
fp.seek(0)
output = StringIO.StringIO()
FeaturesInterpreter.init_from_feature_file(SplineModel(), fp, ',', ('-inf', 'inf')).write(output, ',')
print output.getvalue()
fp.close()
output.close()
def test_exponential():
fp = StringIO.StringIO()
fp.write("dpc1,mean\n")
fp.write("0,1\n")
fp.seek(0)
output = StringIO.StringIO()
FeaturesInterpreter.init_from_feature_file(SplineModel(), fp, ',',
(0, 100)).write(output, ',')
print output.getvalue()
fp.close()
output.close()
def test_gtc(modelfile, distfile):
with open(modelfile, "r") as modelfp:
model = SplineModel()
FeaturesInterpreter.init_from_feature_file(model, modelfp, ',', (SplineModel.neginf, SplineModel.posinf))
with open(distfile, "r") as distfp:
dist = DistributionModel()
dist.init_from(distfp, ',')
output = StringIO.StringIO()
dist.apply_as_distribution(model).write(output, ',')
print output.getvalue()
output.close()
def test_non_gaussian():
fp = StringIO.StringIO()
fp.write("dpc1,mean,.025,.975\n")
fp.write("0,0,-1,2\n")
fp.seek(0)
output = StringIO.StringIO()
FeaturesInterpreter.init_from_feature_file(SplineModel(), fp, ',',
('-inf', 'inf')).write(
output, ',')
print output.getvalue()
fp.close()
output.close()