Tôi theo liên kết này cách nối nhiều tệp numpy vào một tệp numpy trong Python để đặt tất cả các tệp numpy của tôi trong một tệp. Bây giờ, tôi cần vẽ tệp của mình có chứa nhiều mảng, mỗi mảng chứa một số số float: đây là mã cuối cùng của tôi để nối các mảng trong một mảng lớn:
import matplotlib.pyplot as plt
import numpy as np
import glob
import os, sys
fpath ="/home/user/Desktop/OutFileTraces.npy"
npyfilespath="/home/user/Desktop/test"
os.chdir[npyfilespath]
npfiles= glob.glob["*.npy"]
npfiles.sort[]
all_arrays = []
with open[fpath,'ab'] as f_handle:
for npfile in npfiles:
#Find the path of the file and Load file
all_arrays.append[np.load[os.path.join[npyfilespath, npfile]]]
np.save[f_handle, all_arrays]
data = np.load[fpath]
print data
Mã này cho tôi kết quả như thế này:
[[[[-0.00824758 -0.0081808 -0.00811402 ..., -0.0077236 -0.00765425
-0.00762086]]]
[[[-0.00141527 -0.00160791 -0.00176716 ..., -0.00821419 -0.00822446
-0.0082296 ]]]
[[[ 0.01028957 0.01005326 0.0098298 ..., -0.01043341 -0.01050019
-0.01059523]]]
...,
[[[ 0.00614908 0.00581004 0.00549154 ..., -0.00814741 -0.00813457
-0.00809347]]]
[[[-0.00291786 -0.00309509 -0.00329287 ..., -0.00809861 -0.00797789
-0.00784175]]]
[[[-0.00379887 -0.00410453 -0.00438963 ..., -0.03497837 -0.0353842
-0.03575151]]]]
Tôi cần vẽ sơ đồ cốt truyện tệp cuối cùng OutfileTraces.npy chứa mảng lớn. Vì vậy, tôi sử dụng mã này:
import matplotlib.pyplot as plt
import numpy as np
dataArray1= np.load[r'/home/user/Desktop/OutFileTraces.npy']
print[dataArray1]
plt.plot[dataArray1.T ]
plt.show[]
Nó cho tôi lỗi này:
Tăng giá trị HERROR ["X và Y có thể không lớn hơn 2-D"] ValueError: X và Y có thể không lớn hơn 2-D
Tất cả các giá trị đó đại diện cho y_axe, tuy nhiên x-trục của tôi đại diện cho các điểm từ 1 đến 8000. Vì vậy, theo tôi hiểu, để vẽ sơ đồ mảng lớn cuối cùng của tôi, nó phải trông như thế này [sự khác biệt là trên []
]:
[[-0.00824758 -0.0081808 -0.00811402 ..., -0.0077236 -0.00765425
-0.00762086]
[-0.00141527 -0.00160791 -0.00176716 ..., -0.00821419 -0.00822446
-0.0082296 ]
[ 0.01028957 0.01005326 0.0098298 ..., -0.01043341 -0.01050019
-0.01059523]
...,
[0.00614908 0.00581004 0.00549154 ..., -0.00814741 -0.00813457
-0.00809347]
[-0.00291786 -0.00309509 -0.00329287 ..., -0.00809861 -0.00797789
-0.00784175]
[-0.00379887 -0.00410453 -0.00438963 ..., -0.03497837 -0.0353842
-0.03575151]]
Tôi có thể dễ dàng vẽ tệp này.
Vì vậy, tôi thực sự không thể hiểu được vấn đề.
Tôi sẽ rất biết ơn nếu bạn có thể giúp tôi.
Xem thảo luận
Cải thiện bài viết
Lưu bài viết
Xem thảo luận
Cải thiện bài viết
Lưu bài viết
Đọcpyplot[], which is used to plot two-dimensional data.
Bàn luận
- Để vẽ đồ thị trong Python, chúng tôi sẽ sử dụng thư viện matplotlib. Matplotlib được sử dụng cùng với dữ liệu numpy để vẽ bất kỳ loại đồ thị nào. Từ matplotlib, chúng tôi sử dụng hàm cụ thể, tức là pyplot [], được sử dụng để vẽ dữ liệu hai chiều.This function returns equally spaced values from the interval [start, end].
- Các chức năng khác nhau được sử dụng được giải thích dưới đây:It is used to give a title to the graph. Title is passed as the parameter to this function.
- np.arange [bắt đầu, kết thúc]: hàm này trả về các giá trị cách đều nhau từ khoảng [bắt đầu, kết thúc].It sets the label name at X-axis. Name of X-axis is passed as argument to this function.
- plt.title []: Nó được sử dụng để đưa ra một tiêu đề cho biểu đồ. Tiêu đề được truyền làm tham số cho hàm này.It sets the label name at Y-axis. Name of Y-axis is passed as argument to this function.
- plt.xlabel []: Nó đặt tên nhãn tại trục x. Tên của trục x được truyền làm đối số cho hàm này.It plots the values of parameters passed to it together.
- plt.ylabel []: Nó đặt tên nhãn tại trục y. Tên của trục y được truyền như là đối số cho hàm này.It shows all the graph to the console.
plt.plot []: Nó biểu thị các giá trị của các tham số được truyền cho nó cùng nhau.
Python3
plt.show []: Nó hiển thị tất cả các biểu đồ cho bảng điều khiển.
Ví dụ 1 :
import
numpy as np
import
matplotlib.pyplot as plt
import matplotlib.pyplot as plt
import numpy as np
dataArray1= np.load[r'/home/user/Desktop/OutFileTraces.npy']
print[dataArray1]
plt.plot[dataArray1.T ]
plt.show[]
1import matplotlib.pyplot as plt
import numpy as np
dataArray1= np.load[r'/home/user/Desktop/OutFileTraces.npy']
print[dataArray1]
plt.plot[dataArray1.T ]
plt.show[]
2[[[[-0.00824758 -0.0081808 -0.00811402 ..., -0.0077236 -0.00765425
-0.00762086]]]
[[[-0.00141527 -0.00160791 -0.00176716 ..., -0.00821419 -0.00822446
-0.0082296 ]]]
[[[ 0.01028957 0.01005326 0.0098298 ..., -0.01043341 -0.01050019
-0.01059523]]]
...,
[[[ 0.00614908 0.00581004 0.00549154 ..., -0.00814741 -0.00813457
-0.00809347]]]
[[[-0.00291786 -0.00309509 -0.00329287 ..., -0.00809861 -0.00797789
-0.00784175]]]
[[[-0.00379887 -0.00410453 -0.00438963 ..., -0.03497837 -0.0353842
-0.03575151]]]]
5import matplotlib.pyplot as plt
import numpy as np
dataArray1= np.load[r'/home/user/Desktop/OutFileTraces.npy']
print[dataArray1]
plt.plot[dataArray1.T ]
plt.show[]
4import matplotlib.pyplot as plt
import numpy as np
dataArray1= np.load[r'/home/user/Desktop/OutFileTraces.npy']
print[dataArray1]
plt.plot[dataArray1.T ]
plt.show[]
5[[[[-0.00824758 -0.0081808 -0.00811402 ..., -0.0077236 -0.00765425
-0.00762086]]]
[[[-0.00141527 -0.00160791 -0.00176716 ..., -0.00821419 -0.00822446
-0.0082296 ]]]
[[[ 0.01028957 0.01005326 0.0098298 ..., -0.01043341 -0.01050019
-0.01059523]]]
...,
[[[ 0.00614908 0.00581004 0.00549154 ..., -0.00814741 -0.00813457
-0.00809347]]]
[[[-0.00291786 -0.00309509 -0.00329287 ..., -0.00809861 -0.00797789
-0.00784175]]]
[[[-0.00379887 -0.00410453 -0.00438963 ..., -0.03497837 -0.0353842
-0.03575151]]]]
5import matplotlib.pyplot as plt
import numpy as np
dataArray1= np.load[r'/home/user/Desktop/OutFileTraces.npy']
print[dataArray1]
plt.plot[dataArray1.T ]
plt.show[]
7import matplotlib.pyplot as plt
import numpy as np
dataArray1= np.load[r'/home/user/Desktop/OutFileTraces.npy']
print[dataArray1]
plt.plot[dataArray1.T ]
plt.show[]
8[[[[-0.00824758 -0.0081808 -0.00811402 ..., -0.0077236 -0.00765425
-0.00762086]]]
[[[-0.00141527 -0.00160791 -0.00176716 ..., -0.00821419 -0.00822446
-0.0082296 ]]]
[[[ 0.01028957 0.01005326 0.0098298 ..., -0.01043341 -0.01050019
-0.01059523]]]
...,
[[[ 0.00614908 0.00581004 0.00549154 ..., -0.00814741 -0.00813457
-0.00809347]]]
[[[-0.00291786 -0.00309509 -0.00329287 ..., -0.00809861 -0.00797789
-0.00784175]]]
[[[-0.00379887 -0.00410453 -0.00438963 ..., -0.03497837 -0.0353842
-0.03575151]]]]
5[[-0.00824758 -0.0081808 -0.00811402 ..., -0.0077236 -0.00765425
-0.00762086]
[-0.00141527 -0.00160791 -0.00176716 ..., -0.00821419 -0.00822446
-0.0082296 ]
[ 0.01028957 0.01005326 0.0098298 ..., -0.01043341 -0.01050019
-0.01059523]
...,
[0.00614908 0.00581004 0.00549154 ..., -0.00814741 -0.00813457
-0.00809347]
[-0.00291786 -0.00309509 -0.00329287 ..., -0.00809861 -0.00797789
-0.00784175]
[-0.00379887 -0.00410453 -0.00438963 ..., -0.03497837 -0.0353842
-0.03575151]]
0[[[[-0.00824758 -0.0081808 -0.00811402 ..., -0.0077236 -0.00765425
-0.00762086]]]
[[[-0.00141527 -0.00160791 -0.00176716 ..., -0.00821419 -0.00822446
-0.0082296 ]]]
[[[ 0.01028957 0.01005326 0.0098298 ..., -0.01043341 -0.01050019
-0.01059523]]]
...,
[[[ 0.00614908 0.00581004 0.00549154 ..., -0.00814741 -0.00813457
-0.00809347]]]
[[[-0.00291786 -0.00309509 -0.00329287 ..., -0.00809861 -0.00797789
-0.00784175]]]
[[[-0.00379887 -0.00410453 -0.00438963 ..., -0.03497837 -0.0353842
-0.03575151]]]]
0[[-0.00824758 -0.0081808 -0.00811402 ..., -0.0077236 -0.00765425
-0.00762086]
[-0.00141527 -0.00160791 -0.00176716 ..., -0.00821419 -0.00822446
-0.0082296 ]
[ 0.01028957 0.01005326 0.0098298 ..., -0.01043341 -0.01050019
-0.01059523]
...,
[0.00614908 0.00581004 0.00549154 ..., -0.00814741 -0.00813457
-0.00809347]
[-0.00291786 -0.00309509 -0.00329287 ..., -0.00809861 -0.00797789
-0.00784175]
[-0.00379887 -0.00410453 -0.00438963 ..., -0.03497837 -0.0353842
-0.03575151]]
2[[[[-0.00824758 -0.0081808 -0.00811402 ..., -0.0077236 -0.00765425
-0.00762086]]]
[[[-0.00141527 -0.00160791 -0.00176716 ..., -0.00821419 -0.00822446
-0.0082296 ]]]
[[[ 0.01028957 0.01005326 0.0098298 ..., -0.01043341 -0.01050019
-0.01059523]]]
...,
[[[ 0.00614908 0.00581004 0.00549154 ..., -0.00814741 -0.00813457
-0.00809347]]]
[[[-0.00291786 -0.00309509 -0.00329287 ..., -0.00809861 -0.00797789
-0.00784175]]]
[[[-0.00379887 -0.00410453 -0.00438963 ..., -0.03497837 -0.0353842
-0.03575151]]]]
5[[-0.00824758 -0.0081808 -0.00811402 ..., -0.0077236 -0.00765425
-0.00762086]
[-0.00141527 -0.00160791 -0.00176716 ..., -0.00821419 -0.00822446
-0.0082296 ]
[ 0.01028957 0.01005326 0.0098298 ..., -0.01043341 -0.01050019
-0.01059523]
...,
[0.00614908 0.00581004 0.00549154 ..., -0.00814741 -0.00813457
-0.00809347]
[-0.00291786 -0.00309509 -0.00329287 ..., -0.00809861 -0.00797789
-0.00784175]
[-0.00379887 -0.00410453 -0.00438963 ..., -0.03497837 -0.0353842
-0.03575151]]
4x
____10
[[[[-0.00824758 -0.0081808 -0.00811402 ..., -0.0077236 -0.00765425
-0.00762086]]]
[[[-0.00141527 -0.00160791 -0.00176716 ..., -0.00821419 -0.00822446
-0.0082296 ]]]
[[[ 0.01028957 0.01005326 0.0098298 ..., -0.01043341 -0.01050019
-0.01059523]]]
...,
[[[ 0.00614908 0.00581004 0.00549154 ..., -0.00814741 -0.00813457
-0.00809347]]]
[[[-0.00291786 -0.00309509 -0.00329287 ..., -0.00809861 -0.00797789
-0.00784175]]]
[[[-0.00379887 -0.00410453 -0.00438963 ..., -0.03497837 -0.0353842
-0.03575151]]]]
1[[[[-0.00824758 -0.0081808 -0.00811402 ..., -0.0077236 -0.00765425
-0.00762086]]]
[[[-0.00141527 -0.00160791 -0.00176716 ..., -0.00821419 -0.00822446
-0.0082296 ]]]
[[[ 0.01028957 0.01005326 0.0098298 ..., -0.01043341 -0.01050019
-0.01059523]]]
...,
[[[ 0.00614908 0.00581004 0.00549154 ..., -0.00814741 -0.00813457
-0.00809347]]]
[[[-0.00291786 -0.00309509 -0.00329287 ..., -0.00809861 -0.00797789
-0.00784175]]]
[[[-0.00379887 -0.00410453 -0.00438963 ..., -0.03497837 -0.0353842
-0.03575151]]]]
2[[[[-0.00824758 -0.0081808 -0.00811402 ..., -0.0077236 -0.00765425
-0.00762086]]]
[[[-0.00141527 -0.00160791 -0.00176716 ..., -0.00821419 -0.00822446
-0.0082296 ]]]
[[[ 0.01028957 0.01005326 0.0098298 ..., -0.01043341 -0.01050019
-0.01059523]]]
...,
[[[ 0.00614908 0.00581004 0.00549154 ..., -0.00814741 -0.00813457
-0.00809347]]]
[[[-0.00291786 -0.00309509 -0.00329287 ..., -0.00809861 -0.00797789
-0.00784175]]]
[[[-0.00379887 -0.00410453 -0.00438963 ..., -0.03497837 -0.0353842
-0.03575151]]]]
3[[[[-0.00824758 -0.0081808 -0.00811402 ..., -0.0077236 -0.00765425
-0.00762086]]]
[[[-0.00141527 -0.00160791 -0.00176716 ..., -0.00821419 -0.00822446
-0.0082296 ]]]
[[[ 0.01028957 0.01005326 0.0098298 ..., -0.01043341 -0.01050019
-0.01059523]]]
...,
[[[ 0.00614908 0.00581004 0.00549154 ..., -0.00814741 -0.00813457
-0.00809347]]]
[[[-0.00291786 -0.00309509 -0.00329287 ..., -0.00809861 -0.00797789
-0.00784175]]]
[[[-0.00379887 -0.00410453 -0.00438963 ..., -0.03497837 -0.0353842
-0.03575151]]]]
4[[[[-0.00824758 -0.0081808 -0.00811402 ..., -0.0077236 -0.00765425
-0.00762086]]]
[[[-0.00141527 -0.00160791 -0.00176716 ..., -0.00821419 -0.00822446
-0.0082296 ]]]
[[[ 0.01028957 0.01005326 0.0098298 ..., -0.01043341 -0.01050019
-0.01059523]]]
...,
[[[ 0.00614908 0.00581004 0.00549154 ..., -0.00814741 -0.00813457
-0.00809347]]]
[[[-0.00291786 -0.00309509 -0.00329287 ..., -0.00809861 -0.00797789
-0.00784175]]]
[[[-0.00379887 -0.00410453 -0.00438963 ..., -0.03497837 -0.0353842
-0.03575151]]]]
5Output :
6[[[[-0.00824758 -0.0081808 -0.00811402 ..., -0.0077236 -0.00765425
-0.00762086]]]
[[[-0.00141527 -0.00160791 -0.00176716 ..., -0.00821419 -0.00822446
-0.0082296 ]]]
[[[ 0.01028957 0.01005326 0.0098298 ..., -0.01043341 -0.01050019
-0.01059523]]]
...,
[[[ 0.00614908 0.00581004 0.00549154 ..., -0.00814741 -0.00813457
-0.00809347]]]
[[[-0.00291786 -0.00309509 -0.00329287 ..., -0.00809861 -0.00797789
-0.00784175]]]
[[[-0.00379887 -0.00410453 -0.00438963 ..., -0.03497837 -0.0353842
-0.03575151]]]]
0 [[[[-0.00824758 -0.0081808 -0.00811402 ..., -0.0077236 -0.00765425
-0.00762086]]]
[[[-0.00141527 -0.00160791 -0.00176716 ..., -0.00821419 -0.00822446
-0.0082296 ]]]
[[[ 0.01028957 0.01005326 0.0098298 ..., -0.01043341 -0.01050019
-0.01059523]]]
...,
[[[ 0.00614908 0.00581004 0.00549154 ..., -0.00814741 -0.00813457
-0.00809347]]]
[[[-0.00291786 -0.00309509 -0.00329287 ..., -0.00809861 -0.00797789
-0.00784175]]]
[[[-0.00379887 -0.00410453 -0.00438963 ..., -0.03497837 -0.0353842
-0.03575151]]]]
x
9 [[[[-0.00824758 -0.0081808 -0.00811402 ..., -0.0077236 -0.00765425
-0.00762086]]]
[[[-0.00141527 -0.00160791 -0.00176716 ..., -0.00821419 -0.00822446
-0.0082296 ]]]
[[[ 0.01028957 0.01005326 0.0098298 ..., -0.01043341 -0.01050019
-0.01059523]]]
...,
[[[ 0.00614908 0.00581004 0.00549154 ..., -0.00814741 -0.00813457
-0.00809347]]]
[[[-0.00291786 -0.00309509 -0.00329287 ..., -0.00809861 -0.00797789
-0.00784175]]]
[[[-0.00379887 -0.00410453 -0.00438963 ..., -0.03497837 -0.0353842
-0.03575151]]]]
0import matplotlib.pyplot as plt
import numpy as np
dataArray1= np.load[r'/home/user/Desktop/OutFileTraces.npy']
print[dataArray1]
plt.plot[dataArray1.T ]
plt.show[]
Python3
plt.show []: Nó hiển thị tất cả các biểu đồ cho bảng điều khiển.
Ví dụ 1 :
import
numpy as np
import
matplotlib.pyplot as plt
import matplotlib.pyplot as plt
import numpy as np
dataArray1= np.load[r'/home/user/Desktop/OutFileTraces.npy']
print[dataArray1]
plt.plot[dataArray1.T ]
plt.show[]
1import matplotlib.pyplot as plt
import numpy as np
dataArray1= np.load[r'/home/user/Desktop/OutFileTraces.npy']
print[dataArray1]
plt.plot[dataArray1.T ]
plt.show[]
2[[[[-0.00824758 -0.0081808 -0.00811402 ..., -0.0077236 -0.00765425
-0.00762086]]]
[[[-0.00141527 -0.00160791 -0.00176716 ..., -0.00821419 -0.00822446
-0.0082296 ]]]
[[[ 0.01028957 0.01005326 0.0098298 ..., -0.01043341 -0.01050019
-0.01059523]]]
...,
[[[ 0.00614908 0.00581004 0.00549154 ..., -0.00814741 -0.00813457
-0.00809347]]]
[[[-0.00291786 -0.00309509 -0.00329287 ..., -0.00809861 -0.00797789
-0.00784175]]]
[[[-0.00379887 -0.00410453 -0.00438963 ..., -0.03497837 -0.0353842
-0.03575151]]]]
5import matplotlib.pyplot as plt
import numpy as np
dataArray1= np.load[r'/home/user/Desktop/OutFileTraces.npy']
print[dataArray1]
plt.plot[dataArray1.T ]
plt.show[]
4import matplotlib.pyplot as plt
import numpy as np
dataArray1= np.load[r'/home/user/Desktop/OutFileTraces.npy']
print[dataArray1]
plt.plot[dataArray1.T ]
plt.show[]
5[[[[-0.00824758 -0.0081808 -0.00811402 ..., -0.0077236 -0.00765425
-0.00762086]]]
[[[-0.00141527 -0.00160791 -0.00176716 ..., -0.00821419 -0.00822446
-0.0082296 ]]]
[[[ 0.01028957 0.01005326 0.0098298 ..., -0.01043341 -0.01050019
-0.01059523]]]
...,
[[[ 0.00614908 0.00581004 0.00549154 ..., -0.00814741 -0.00813457
-0.00809347]]]
[[[-0.00291786 -0.00309509 -0.00329287 ..., -0.00809861 -0.00797789
-0.00784175]]]
[[[-0.00379887 -0.00410453 -0.00438963 ..., -0.03497837 -0.0353842
-0.03575151]]]]
5import matplotlib.pyplot as plt
import numpy as np
dataArray1= np.load[r'/home/user/Desktop/OutFileTraces.npy']
print[dataArray1]
plt.plot[dataArray1.T ]
plt.show[]
7import matplotlib.pyplot as plt
import numpy as np
dataArray1= np.load[r'/home/user/Desktop/OutFileTraces.npy']
print[dataArray1]
plt.plot[dataArray1.T ]
plt.show[]
8[[[[-0.00824758 -0.0081808 -0.00811402 ..., -0.0077236 -0.00765425
-0.00762086]]]
[[[-0.00141527 -0.00160791 -0.00176716 ..., -0.00821419 -0.00822446
-0.0082296 ]]]
[[[ 0.01028957 0.01005326 0.0098298 ..., -0.01043341 -0.01050019
-0.01059523]]]
...,
[[[ 0.00614908 0.00581004 0.00549154 ..., -0.00814741 -0.00813457
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[[[-0.00291786 -0.00309509 -0.00329287 ..., -0.00809861 -0.00797789
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[[[-0.00379887 -0.00410453 -0.00438963 ..., -0.03497837 -0.0353842
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5[[-0.00824758 -0.0081808 -0.00811402 ..., -0.0077236 -0.00765425
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[-0.00141527 -0.00160791 -0.00176716 ..., -0.00821419 -0.00822446
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[ 0.01028957 0.01005326 0.0098298 ..., -0.01043341 -0.01050019
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...,
[0.00614908 0.00581004 0.00549154 ..., -0.00814741 -0.00813457
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[-0.00291786 -0.00309509 -0.00329287 ..., -0.00809861 -0.00797789
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[-0.00379887 -0.00410453 -0.00438963 ..., -0.03497837 -0.0353842
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0[[[[-0.00824758 -0.0081808 -0.00811402 ..., -0.0077236 -0.00765425
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[[[-0.00141527 -0.00160791 -0.00176716 ..., -0.00821419 -0.00822446
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[[[ 0.01028957 0.01005326 0.0098298 ..., -0.01043341 -0.01050019
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...,
[[[ 0.00614908 0.00581004 0.00549154 ..., -0.00814741 -0.00813457
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[[[-0.00291786 -0.00309509 -0.00329287 ..., -0.00809861 -0.00797789
-0.00784175]]]
[[[-0.00379887 -0.00410453 -0.00438963 ..., -0.03497837 -0.0353842
-0.03575151]]]]
0matplotlib.pyplot as plt
0[[[[-0.00824758 -0.0081808 -0.00811402 ..., -0.0077236 -0.00765425
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[[[-0.00141527 -0.00160791 -0.00176716 ..., -0.00821419 -0.00822446
-0.0082296 ]]]
[[[ 0.01028957 0.01005326 0.0098298 ..., -0.01043341 -0.01050019
-0.01059523]]]
...,
[[[ 0.00614908 0.00581004 0.00549154 ..., -0.00814741 -0.00813457
-0.00809347]]]
[[[-0.00291786 -0.00309509 -0.00329287 ..., -0.00809861 -0.00797789
-0.00784175]]]
[[[-0.00379887 -0.00410453 -0.00438963 ..., -0.03497837 -0.0353842
-0.03575151]]]]
5[[-0.00824758 -0.0081808 -0.00811402 ..., -0.0077236 -0.00765425
-0.00762086]
[-0.00141527 -0.00160791 -0.00176716 ..., -0.00821419 -0.00822446
-0.0082296 ]
[ 0.01028957 0.01005326 0.0098298 ..., -0.01043341 -0.01050019
-0.01059523]
...,
[0.00614908 0.00581004 0.00549154 ..., -0.00814741 -0.00813457
-0.00809347]
[-0.00291786 -0.00309509 -0.00329287 ..., -0.00809861 -0.00797789
-0.00784175]
[-0.00379887 -0.00410453 -0.00438963 ..., -0.03497837 -0.0353842
-0.03575151]]
4x
____10
[[[[-0.00824758 -0.0081808 -0.00811402 ..., -0.0077236 -0.00765425
-0.00762086]]]
[[[-0.00141527 -0.00160791 -0.00176716 ..., -0.00821419 -0.00822446
-0.0082296 ]]]
[[[ 0.01028957 0.01005326 0.0098298 ..., -0.01043341 -0.01050019
-0.01059523]]]
...,
[[[ 0.00614908 0.00581004 0.00549154 ..., -0.00814741 -0.00813457
-0.00809347]]]
[[[-0.00291786 -0.00309509 -0.00329287 ..., -0.00809861 -0.00797789
-0.00784175]]]
[[[-0.00379887 -0.00410453 -0.00438963 ..., -0.03497837 -0.0353842
-0.03575151]]]]
1[[[[-0.00824758 -0.0081808 -0.00811402 ..., -0.0077236 -0.00765425
-0.00762086]]]
[[[-0.00141527 -0.00160791 -0.00176716 ..., -0.00821419 -0.00822446
-0.0082296 ]]]
[[[ 0.01028957 0.01005326 0.0098298 ..., -0.01043341 -0.01050019
-0.01059523]]]
...,
[[[ 0.00614908 0.00581004 0.00549154 ..., -0.00814741 -0.00813457
-0.00809347]]]
[[[-0.00291786 -0.00309509 -0.00329287 ..., -0.00809861 -0.00797789
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[[[-0.00379887 -0.00410453 -0.00438963 ..., -0.03497837 -0.0353842
-0.03575151]]]]
2[[[[-0.00824758 -0.0081808 -0.00811402 ..., -0.0077236 -0.00765425
-0.00762086]]]
[[[-0.00141527 -0.00160791 -0.00176716 ..., -0.00821419 -0.00822446
-0.0082296 ]]]
[[[ 0.01028957 0.01005326 0.0098298 ..., -0.01043341 -0.01050019
-0.01059523]]]
...,
[[[ 0.00614908 0.00581004 0.00549154 ..., -0.00814741 -0.00813457
-0.00809347]]]
[[[-0.00291786 -0.00309509 -0.00329287 ..., -0.00809861 -0.00797789
-0.00784175]]]
[[[-0.00379887 -0.00410453 -0.00438963 ..., -0.03497837 -0.0353842
-0.03575151]]]]
3[[[[-0.00824758 -0.0081808 -0.00811402 ..., -0.0077236 -0.00765425
-0.00762086]]]
[[[-0.00141527 -0.00160791 -0.00176716 ..., -0.00821419 -0.00822446
-0.0082296 ]]]
[[[ 0.01028957 0.01005326 0.0098298 ..., -0.01043341 -0.01050019
-0.01059523]]]
...,
[[[ 0.00614908 0.00581004 0.00549154 ..., -0.00814741 -0.00813457
-0.00809347]]]
[[[-0.00291786 -0.00309509 -0.00329287 ..., -0.00809861 -0.00797789
-0.00784175]]]
[[[-0.00379887 -0.00410453 -0.00438963 ..., -0.03497837 -0.0353842
-0.03575151]]]]
4[[[[-0.00824758 -0.0081808 -0.00811402 ..., -0.0077236 -0.00765425
-0.00762086]]]
[[[-0.00141527 -0.00160791 -0.00176716 ..., -0.00821419 -0.00822446
-0.0082296 ]]]
[[[ 0.01028957 0.01005326 0.0098298 ..., -0.01043341 -0.01050019
-0.01059523]]]
...,
[[[ 0.00614908 0.00581004 0.00549154 ..., -0.00814741 -0.00813457
-0.00809347]]]
[[[-0.00291786 -0.00309509 -0.00329287 ..., -0.00809861 -0.00797789
-0.00784175]]]
[[[-0.00379887 -0.00410453 -0.00438963 ..., -0.03497837 -0.0353842
-0.03575151]]]]
5Output :