def fn(indexes): for index in indexes: if assessment: scores = gd.assessmentScores(index) else: scores = gd.trainingScores(index) pp.plot(scores, linestyle=':', marker='x', label=legendLabel)
def fn(indexes): scores = [] for index in indexes: if assessment: scores += [gd.assessmentScores(index)] else: scores += [gd.trainingScores(index)] scores = np.array(scores) averages = np.mean(scores, 0) pp.plot(averages, linestyle=':', marker='x', label=legendLabel)
def fn(indexes): scores = [] for index in indexes: if assessment: scores += [gd.assessmentScores(index)] else: scores += [gd.trainingScores(index)] scores = np.array(scores) meanScores = np.mean(scores, 0) highErrors = np.max(scores, 0) - meanScores lowErrors = meanScores - np.min(scores, 0) pp.errorbar(x=[i for i in range(0, len(meanScores))], y=meanScores, yerr=[lowErrors, highErrors], label=legendLabel)