def objectFeatureValues(dataSet, column, row, plate, exemplars, probes):
objects = allObjects(dataSet, column, row, plate, exemplars, probes)
cols = data.features(dataSet)
pool = Pool()
results = pool.imap(forObjectFeatureValues, [(dataSet, col, objects) for col in cols])
pool.close()
pool.join()
mrg = pd.DataFrame(index=objects, columns=cols)
for c, vals in results:
mrg[c] = vals
return mrg
def featureMetrics(dataSet):
print "Computing image feature metrics for " + dataSet
return {feature: ftrMet(dataSet, feature) for feature in data.features(dataSet)}
