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_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()