ValueError: Cannot copy sequence to array axis in Python for MatplotLib Animation
ValueError: Cannot copy sequence to array axis in Python for MatplotLib Animation
我正在读取一个不断更新的 data.txt 文件，并且正在计算传入数据流的滚动标准偏差。我将其存储在 std 中。我的滚动标准差 window 大小为 100。
我收到一个错误：
ValueError: cannot copy sequence with size 78 to array axis with dimension 1
其中大小对应于 std 数组中的项目数。 （所以这个，当然，每次我点击 运行 时都会增加）。
我想知道为什么我会收到此 ValueError，并且正在寻找任何修复它的建议！当我刚刚评分 ax1.plot(xar, yar) 时，动画效果很好。但是一旦我尝试绘制 ax1.plot(xar, std) 图表，问题就出现了。
data.txt中的数据如下所示：
[0.0, 0.0078125, 0.015625][0.0, 0.0078125, 0.015625][0.0, 0.0078125, 0.015625][0.0, 0.0078125, 0.015625][0.0, 0.0078125, 0.015625][0.0, 0.0078125, 0.015625][0.0244140625, 0.0322265625, 0.9609375][0.0244140625, 0.0322265625, 0.9609375][0.0244140625, 0.0322265625, 0.9609375][0.0244140625, 0.0322265625, 0.9609375][0.0244140625, 0.0322265625, 0.9609375][0.0244140625, 0.0322265625, 0.9609375][0.0244140625, 0.0322265625, 0.9609375][0.0244140625, 0.0322265625, 0.9609375][0.0244140625, 0.0322265625, 0.9609375][0.0263671875, 0.0341796875, 1.0341796875][0.0263671875, 0.0341796875, 1.0341796875][0.0263671875, 0.0341796875, 1.0341796875][0.0263671875, 0.0341796875, 1.0341796875][0.0263671875, 0.0341796875, 1.0341796875][0.0263671875, 0.0341796875, 1.0341796875][0.0263671875, 0.0341796875, 1.0341796875][0.0263671875, 0.0341796875, 1.0341796875][0.0244140625, 0.0341796875, 1.0048828125][0.0244140625, 0.0341796875, 1.0048828125][0.0244140625, 0.0341796875, 1.0048828125][0.0244140625, 0.0341796875, 1.0048828125][0.0244140625, 0.0341796875, 1.0048828125][0.0244140625, 0.0341796875, 1.0048828125][0.0244140625, 0.0341796875, 1.0048828125][0.0244140625, 0.0341796875, 1.0048828125][0.0244140625, 0.0341796875, 1.0048828125][0.025390625, 0.0341796875, 1.0107421875][0.025390625, 0.0341796875, 1.0107421875][0.025390625, 0.0341796875, 1.0107421875][0.025390625, 0.0341796875, 1.0107421875][0.025390625, 0.0341796875, 1.0107421875][0.025390625, 0.0341796875, 1.0107421875][0.025390625, 0.0341796875, 1.0107421875][0.025390625, 0.0341796875, 1.0107421875][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.033203125, 1.009765625][0.025390625, 0.033203125, 1.009765625][0.025390625, 0.033203125, 1.009765625][0.025390625, 0.033203125, 1.009765625][0.025390625, 0.033203125, 1.009765625][0.025390625, 0.033203125, 1.009765625][0.025390625, 0.033203125, 1.009765625][0.025390625, 0.033203125, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.0263671875, 0.0341796875, 1.009765625][0.0263671875, 0.0341796875, 1.009765625][0.0263671875, 0.0341796875, 1.009765625][0.0263671875, 0.0341796875, 1.009765625][0.0263671875, 0.0341796875, 1.009765625][0.0263671875, 0.0341796875, 1.009765625][0.0263671875, 0.0341796875, 1.009765625][0.0263671875, 0.0341796875, 1.009765625][0.0263671875, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.0107421875][0.025390625, 0.0341796875, 1.0107421875][0.025390625, 0.0341796875, 1.0107421875][0.025390625, 0.0341796875, 1.0107421875][0.025390625, 0.0341796875, 1.0107421875][0.025390625, 0.0341796875, 1.0107421875][0.025390625, 0.0341796875, 1.0107421875][0.025390625, 0.0341796875, 1.0107421875][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625]
我目前的代码如下：
fig = plt.figure()
ax1 = fig.add_subplot(1,1,1)
def animate(i):
data = pd.read_csv("C:\Users\Desktop\data.txt", sep="\[|\]\[|\]",engine = 'python', header = None)
data = data.iloc[0]
data = data.astype(str).apply(lambda x: x.split(',')[-1]).astype(float)
data.pop(0)
xar = []
yar = []
std = []
for j in range(len(data)):
xar.append(j)
for k in range(len(data)):
yar.append(data.iloc[k])
yar = pd.DataFrame(yar)
std.append(pd.rolling_std(yar, 100))
ax1.clear()
ax1.plot(xar,std)
ani = animation.FuncAnimation(fig, animate, interval=.01)
plt.show()
你的错误原因是你std变成了一个数据框的列表（一个元素）。 pd.rolling_std() 已经为您提供了一个数据框，然后您将其附加到您的列表中。如果直接赋值，效果会更好：
std = pd.rolling_std(yar, 100)
但是，当 运行 pd.rolling_std() 时会给出弃用警告。因此，该行应该是：
std = yar.rolling(window=100,center=False).std()
此外，对于如何生成 xar 和 yar，可以进行一些更多的简化。 xar 只是一个范围，yar 包含 data 的所有元素，您可以这样写：
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.animation as animation
def animate(i):
data = pd.read_csv("C:\Users\Desktop\data.txt", sep="\[|\]\[|\]",engine = 'python', header = None)
data = data.iloc[0]
data = data.astype(str).apply(lambda x: x.split(',')[-1]).astype(float)
data.pop(0)
xar = range(len(data))
yar = pd.DataFrame(data)
std = yar.rolling(window=100,center=False).std()
ax1.clear()
ax1.plot(xar,std)
fig = plt.figure()
ax1 = fig.add_subplot(1,1,1)
ani = animation.FuncAnimation(fig, animate, interval=.01)
plt.show()
其中 animate() 有所简化。
我正在读取一个不断更新的 data.txt 文件，并且正在计算传入数据流的滚动标准偏差。我将其存储在 std 中。我的滚动标准差 window 大小为 100。
我收到一个错误：
ValueError: cannot copy sequence with size 78 to array axis with dimension 1
其中大小对应于 std 数组中的项目数。 （所以这个，当然，每次我点击 运行 时都会增加）。
我想知道为什么我会收到此 ValueError，并且正在寻找任何修复它的建议！当我刚刚评分 ax1.plot(xar, yar) 时，动画效果很好。但是一旦我尝试绘制 ax1.plot(xar, std) 图表，问题就出现了。
data.txt中的数据如下所示：
[0.0, 0.0078125, 0.015625][0.0, 0.0078125, 0.015625][0.0, 0.0078125, 0.015625][0.0, 0.0078125, 0.015625][0.0, 0.0078125, 0.015625][0.0, 0.0078125, 0.015625][0.0244140625, 0.0322265625, 0.9609375][0.0244140625, 0.0322265625, 0.9609375][0.0244140625, 0.0322265625, 0.9609375][0.0244140625, 0.0322265625, 0.9609375][0.0244140625, 0.0322265625, 0.9609375][0.0244140625, 0.0322265625, 0.9609375][0.0244140625, 0.0322265625, 0.9609375][0.0244140625, 0.0322265625, 0.9609375][0.0244140625, 0.0322265625, 0.9609375][0.0263671875, 0.0341796875, 1.0341796875][0.0263671875, 0.0341796875, 1.0341796875][0.0263671875, 0.0341796875, 1.0341796875][0.0263671875, 0.0341796875, 1.0341796875][0.0263671875, 0.0341796875, 1.0341796875][0.0263671875, 0.0341796875, 1.0341796875][0.0263671875, 0.0341796875, 1.0341796875][0.0263671875, 0.0341796875, 1.0341796875][0.0244140625, 0.0341796875, 1.0048828125][0.0244140625, 0.0341796875, 1.0048828125][0.0244140625, 0.0341796875, 1.0048828125][0.0244140625, 0.0341796875, 1.0048828125][0.0244140625, 0.0341796875, 1.0048828125][0.0244140625, 0.0341796875, 1.0048828125][0.0244140625, 0.0341796875, 1.0048828125][0.0244140625, 0.0341796875, 1.0048828125][0.0244140625, 0.0341796875, 1.0048828125][0.025390625, 0.0341796875, 1.0107421875][0.025390625, 0.0341796875, 1.0107421875][0.025390625, 0.0341796875, 1.0107421875][0.025390625, 0.0341796875, 1.0107421875][0.025390625, 0.0341796875, 1.0107421875][0.025390625, 0.0341796875, 1.0107421875][0.025390625, 0.0341796875, 1.0107421875][0.025390625, 0.0341796875, 1.0107421875][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.033203125, 1.009765625][0.025390625, 0.033203125, 1.009765625][0.025390625, 0.033203125, 1.009765625][0.025390625, 0.033203125, 1.009765625][0.025390625, 0.033203125, 1.009765625][0.025390625, 0.033203125, 1.009765625][0.025390625, 0.033203125, 1.009765625][0.025390625, 0.033203125, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.0263671875, 0.0341796875, 1.009765625][0.0263671875, 0.0341796875, 1.009765625][0.0263671875, 0.0341796875, 1.009765625][0.0263671875, 0.0341796875, 1.009765625][0.0263671875, 0.0341796875, 1.009765625][0.0263671875, 0.0341796875, 1.009765625][0.0263671875, 0.0341796875, 1.009765625][0.0263671875, 0.0341796875, 1.009765625][0.0263671875, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.0107421875][0.025390625, 0.0341796875, 1.0107421875][0.025390625, 0.0341796875, 1.0107421875][0.025390625, 0.0341796875, 1.0107421875][0.025390625, 0.0341796875, 1.0107421875][0.025390625, 0.0341796875, 1.0107421875][0.025390625, 0.0341796875, 1.0107421875][0.025390625, 0.0341796875, 1.0107421875][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625][0.025390625, 0.0341796875, 1.009765625]
我目前的代码如下：
fig = plt.figure()
ax1 = fig.add_subplot(1,1,1)
def animate(i):
data = pd.read_csv("C:\Users\Desktop\data.txt", sep="\[|\]\[|\]",engine = 'python', header = None)
data = data.iloc[0]
data = data.astype(str).apply(lambda x: x.split(',')[-1]).astype(float)
data.pop(0)
xar = []
yar = []
std = []
for j in range(len(data)):
xar.append(j)
for k in range(len(data)):
yar.append(data.iloc[k])
yar = pd.DataFrame(yar)
std.append(pd.rolling_std(yar, 100))
ax1.clear()
ax1.plot(xar,std)
ani = animation.FuncAnimation(fig, animate, interval=.01)
plt.show()
你的错误原因是你std变成了一个数据框的列表（一个元素）。 pd.rolling_std() 已经为您提供了一个数据框，然后您将其附加到您的列表中。如果直接赋值，效果会更好：
std = pd.rolling_std(yar, 100)
但是，当 运行 pd.rolling_std() 时会给出弃用警告。因此，该行应该是：
std = yar.rolling(window=100,center=False).std()
此外，对于如何生成 xar 和 yar，可以进行一些更多的简化。 xar 只是一个范围，yar 包含 data 的所有元素，您可以这样写：
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.animation as animation
def animate(i):
data = pd.read_csv("C:\Users\Desktop\data.txt", sep="\[|\]\[|\]",engine = 'python', header = None)
data = data.iloc[0]
data = data.astype(str).apply(lambda x: x.split(',')[-1]).astype(float)
data.pop(0)
xar = range(len(data))
yar = pd.DataFrame(data)
std = yar.rolling(window=100,center=False).std()
ax1.clear()
ax1.plot(xar,std)
fig = plt.figure()
ax1 = fig.add_subplot(1,1,1)
ani = animation.FuncAnimation(fig, animate, interval=.01)
plt.show()
其中 animate() 有所简化。