ch13 利用pca进行图像压缩出现以下错误，请问有出现相同错误的同学吗？

[gaoya-J]

Traceback (most recent call last):
File "F:/C-Practice/PCA-MNIST.py", line 36, in
instances.append(x[y==i][0])
IndexError: index 0 is out of bounds for axis 0 with size 0

[Yimeng-Zhang]

看上去是输入数据为空导致的呢，能在之前步骤看下是否成功读取了图像数据吗

[gaoya-J]

这是写得代码:
`import numpy as np
import matplotlib
import matplotlib.pyplot as plt
#from sklearn.datasets import fetch_mldata
#sklearn 没有fetch_mldata了，在网上查到可以导入fetch_openml
from sklearn.datasets import fetch_openml
from sklearn.decomposition import PCA

mnist=fetch_openml('mnist_784')
x=mnist["data"]
y=mnist["target"]

pca=PCA()
pca.fit(x)

'''cumsum=np.cumsum(pca.explained_variance_ratio_)
d=np.argmax(cumsum>=0.9)+1

plt.plot(cumsum)
plt.ylim(0,1.1)
plt.xlabel('no.of principals',fontsize=16)
plt.ylabel('explained variance ratio',fontsize=16)
plt.show()'''

Xr=[]
for n in [5,15,35,85]:
pca=PCA(n_components=n)
X_reduced=pca.fit_transform(x)
X_recovered=pca.inverse_transform(X_reduced)
Xr.append(X_recovered)

instances=[]
for i in range(10):
instances.append(x[y==i][0])
for j in range(1,5):
instances.append(Xr[j-1][y==i][0])

def plot_digits(instances):
images = [instance.reshape(28,28)
for instance in instances]
row_images=[]
for row in range(5):
rimages=images[row*5:(row+1)*5]
row_images.append(np.concatenate(rimages,axis=1))
image=np.concatenate(row_images,axis=0)
plt.imshow(image,cmap=matplotlib.cm.binary)
plt.axis("off")

plt.figure(figsize=(7,4))
plt.subplot(121)
plot_digits(instances[:25])
plt.subplot(122)
plot_digits(instances[25:])
plt.show()
`

[gaoya-J]

使用fetch_openml读取的mnist数据集截图：

[gaoya-J]

请问是要怎么改才能解决这个错误啊？
Traceback (most recent call last):
File "F:\C-Practice\test.py", line 51, in
instances.append(x[y==i][0])
IndexError: index 0 is out of bounds for axis 0 with size 0

[Yimeng-Zhang]

我明天测试下回复你

[gaoya-J]

我明天测试下回复你
你好，请问你那边测试有出现和我一样的问题吗？

[chaosjeyli]

我明天测试下回复你

作者您好，我也遇到了一样的问题，不知道有没有有没有解决了