Python ValueError: 绘图时 x 和 y 必须具有相同的第一维
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ValueError: x and y must have same first dimension when plotting
提问by baconwichsand
I am trying to plot an array of x and y values and keep getting this error.
我正在尝试绘制 x 和 y 值数组并不断收到此错误。
ValueError: x and y must have same first dimension
ValueError：x 和 y 必须具有相同的第一维
This is my code:
这是我的代码：
import numpy as np
import pylab as plt
from matplotlib import rc
def analyze(targt_data, targt_data_name, trang_data, trang_data_name, matches):
"""Analyze a set of samples on target data"""
_timefrm = [40, 80, 120]
_scorefilter = 0.8
index = 0
matches = matches[np.where(matches[:, 3] > _scorefilter)]
# PLOTS
rc('text', usetex=True)
fig = plt.figure()
plt1 = fig.add_subplot(321)
plt1.hold(True)
plt2 = fig.add_subplot(322)
plt3 = fig.add_subplot(323)
plt4 = fig.add_subplot(324)
plt5 = fig.add_subplot(325)
plt6 = fig.add_subplot(326)
matches = matches[np.where(matches[:, 2] == index)]
avg_score = np.mean(matches[:, 3])
# PLOT SAMPLE
plt1.plot(trang_data[index])
rwresults = [targt_data[y-1:y+np.max(_timefrm)] for y in matches[:,1]]
pctresults = [np.log(np.divide(y[1:], y[0])) for y in rwresults]
for res in pctresults:
plt1.plot(np.arange(len(trang_data[index]),
len(trang_data[index])+np.max(_timefrm)),
np.dot(trang_data[index][-1], np.add(res, 1)))
plt.show()
results_name = raw_input('Load matching scores: ')
# #### LOAD MATCHING SCORES FROM DB
results, training_data_name, target_data_name = Results(DB).load_matching_scores(results_name)
# #### LOAD TARGET DATA AND TRAINING DATA
target_data = TargetData(DB).load(target_data_name)
training_data = TrainingData(DB).load(training_data_name)
# #### RUN ANALYSIS
analyze(target_data, target_data_name, training_data, training_data_name, results)
Also, here are the values printed out:
此外，这里是打印出来的值：
(Pdb) len(np.dot(trang_data[ns.index][-1], np.add(pctresults[0], 1)))
120
(Pdb) len(np.arange(len(trang_data[ns.index]), len(trang_data[ns.index])+np.max(_timefrm)))
120
(Pdb) np.dot(trang_data[ns.index][-1], np.add(pctresults[0], 1)).shape
(120,)
(Pdb) np.arange(len(trang_data[ns.index]), len(trang_data[ns.index])+np.max(_timefrm)).shape
(120,)
采纳答案by baconwichsand
It turns out one of the subarrays was too short:
事实证明，其中一个子数组太短了：
(Pdb) len(pctresults[71])
100
The value error "x and y must have same first dimension" is raised by the plot(x, y)method when x and y are not of the same length.
plot(x, y)当 x 和 y 的长度不同时，该方法会引发值错误“x 和 y 必须具有相同的第一维” 。
