def testAvgAll(modelOutputs, mixRatio, data, outputFolder):
# finalOutput = mixRatio * modelOutputs[0] + \
# (1 - mixRatio) * modelOutputs[1]
finalOutput = np.zeros(modelOutputs[0].shape)
for output in modelOutputs:
shape0 = min(finalOutput.shape[0], output.shape[0])
shape1 = min(finalOutput.shape[1], output.shape[1])
finalOutput[:shape0, :shape1] += output[:shape0, :shape1] / float(len(modelOutputs))
testAnswerFile = it.getAnswerFilename(outputFolder, resultsFolder)
testTruthFile = it.getTruthFilename(outputFolder, resultsFolder)
resultsRank, \
resultsCategory, \
resultsWups = it.runAllMetrics(
data['testData'][0],
finalOutput,
data['testData'][1],
data['ansIdict'],
data['questionTypeArray'],
testAnswerFile,
testTruthFile)
it.writeMetricsToFile(
outputFolder,
resultsRank,
resultsCategory,
resultsWups,
resultsFolder)
def testEnsemblePrior(
ensembleId,
models,
dataFolder,
classDataFolders,
resultsFolder):
data = it.loadDataset(dataFolder)
inputTest = data['testData'][0]
targetTest = data['testData'][1]
ensembleOutputTest = runEnsemblePrior(
inputTest,
models,
dataFolder,
classDataFolders,
data['questionTypeArray'])
ensembleAnswerFile = it.getAnswerFilename(ensembleId, resultsFolder)
ensembleTruthFile = it.getTruthFilename(ensembleId, resultsFolder)
rate, correct, total = nn.calcRate(
model, ensembleOutputTest, data['testData'][1])
print 'rate: %.4f' % rate
resultsRank, \
resultsCategory, \
resultsWups = it.runAllMetrics(
inputTest,
ensembleOutputTest,
targetTest,
data['ansIdict'],
data['questionTypeArray'],
ensembleAnswerFile,
ensembleTruthFile)
it.writeMetricsToFile(
ensembleId,
rate,
resultsRank,
resultsCategory,
resultsWups,
resultsFolder)
return ensembleOutputTest