Tôi có một danh sách raws
các mảng mà tôi muốn vẽ trong máy tính xách tay ipython. Đây là mã tôi đang cố gắng để làm việc:
fig, axes = subplots[len[raws],1, sharex=True, tight_layout=True, figsize=[12, 6], dpi=72]
for r in range[len[raws]]:
axes[r].plot[raws]
Tôi đã bị mất hàng giờ nếu không phải là ngày cố gắng tìm ra cách lập chỉ mục danh sách raws
, sao cho tôi có thể vẽ từng mảng MXN trên trục riêng của nó trong đó n là số điểm thời gian, tức là, trục x và m là Số lượng hàm chuỗi thời gian được lấy mẫu tại mỗi điểm.
Khi tôi viết mã:
for r in range[len[raws]]:
axes[r].plot[raws[r]]
Tôi nhận được một giá trịerror: Đặt một phần tử mảng với một chuỗi.
Cho thông tin của bạn:
len[raws] = 2
type[raws] = 'list'
np.shape[raws[0][0]] = [306, 10001]
raws =
[[array[[[ -4.13211217e-12, -4.13287303e-12, -4.01705259e-12, ...,
1.36386023e-12, 1.65182851e-12, 2.00368966e-12],
[ 1.08914129e-12, 1.47828466e-12, 1.82257607e-12, ...,
-2.70151520e-12, -2.48631967e-12, -2.28625548e-12],
[ -7.80962369e-14, -1.27119591e-13, -1.73610315e-13, ...,
-1.13219629e-13, -1.15031720e-13, -1.12106621e-13],
...,
[ 2.52774254e-12, 2.32293195e-12, 2.02644002e-12, ...,
4.20064191e-12, 3.94858906e-12, 3.69495394e-12],
[ -4.38122146e-12, -4.96229676e-12, -5.47782145e-12, ...,
3.93820033e-12, 4.18850823e-12, 4.34950629e-12],
[ -1.07284424e-13, -9.23447993e-14, -7.89852400e-14, ...,
7.92079631e-14, 5.60172215e-14, 3.04448868e-14]]], array[[ 60. , 60.001, 60.002, ..., 69.998, 69.999, 70. ]]], [array[[[ -6.71363108e-12, -5.80501003e-12, -4.95944514e-12, ...,
-3.25087343e-12, -2.68982494e-12, -2.13637448e-12],
[ -5.04818633e-12, -4.65757005e-12, -4.16084140e-12, ...,
-4.26120531e-13, 2.20744290e-13, 7.81245614e-13],
[ 1.97329506e-13, 1.64543867e-13, 1.32679812e-13, ...,
2.11645494e-13, 1.94795729e-13, 1.75781773e-13],
...,
[ 3.04245661e-12, 2.28376461e-12, 1.54118900e-12, ...,
-1.14020908e-14, -8.04647589e-13, -1.52676489e-12],
[ -1.83485962e-13, -5.22949893e-13, -8.60038852e-13, ...,
7.70312553e-12, 7.20825156e-12, 6.58362857e-12],
[ -7.26357906e-14, -7.11700989e-14, -6.88759767e-14, ...,
-1.04171843e-13, -1.03084861e-13, -9.68462427e-14]]], array[[ 60. , 60.001, 60.002, ..., 69.998, 69.999, 70. ]]]]
Cải thiện bài viết
Lưu bài viết
Cải thiện bài viết
Lưu bài viết
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.pyplot[], which is used to plot two-dimensional data.
Các chức năng khác nhau được sử dụng được giải thích dưới đây:
- np.arange [bắt đầu, kết thúc]: hàm này trả về các giá trị cách đều nhau từ khoảng [bắt đầu, kết thúc].This function returns equally spaced values from the interval [start, end].
- 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 is used to give a title to the graph. Title is passed as the parameter 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 sets the label name at X-axis. Name of X-axis is passed as argument to this function.
- plt.ylabel []: Nó đặt tên nhãn tại trục y. Tên của trục y được truyền như là đối số cho hàm này.It sets the label name at Y-axis. Name of Y-axis is passed as argument to this function.
- plt.plot []: Nó biểu thị các giá trị của các tham số được truyền cho nó cùng nhau.It plots the values of parameters passed to it together.
- plt.show []: Nó hiển thị tất cả các biểu đồ cho bảng điều khiển.It shows all the graph to the console.
Ví dụ 1 :
Python3
import
numpy as np
import
matplotlib.pyplot as plt
x
____10
for r in range[len[raws]]:
axes[r].plot[raws[r]]
1for r in range[len[raws]]:
axes[r].plot[raws[r]]
2for r in range[len[raws]]:
axes[r].plot[raws[r]]
3for r in range[len[raws]]:
axes[r].plot[raws[r]]
4for r in range[len[raws]]:
axes[r].plot[raws[r]]
5for r in range[len[raws]]:
axes[r].plot[raws[r]]
6for r in range[len[raws]]:
axes[r].plot[raws[r]]
0 x
for r in range[len[raws]]:
axes[r].plot[raws[r]]
9 len[raws] = 2
type[raws] = 'list'
np.shape[raws[0][0]] = [306, 10001]
raws =
[[array[[[ -4.13211217e-12, -4.13287303e-12, -4.01705259e-12, ...,
1.36386023e-12, 1.65182851e-12, 2.00368966e-12],
[ 1.08914129e-12, 1.47828466e-12, 1.82257607e-12, ...,
-2.70151520e-12, -2.48631967e-12, -2.28625548e-12],
[ -7.80962369e-14, -1.27119591e-13, -1.73610315e-13, ...,
-1.13219629e-13, -1.15031720e-13, -1.12106621e-13],
...,
[ 2.52774254e-12, 2.32293195e-12, 2.02644002e-12, ...,
4.20064191e-12, 3.94858906e-12, 3.69495394e-12],
[ -4.38122146e-12, -4.96229676e-12, -5.47782145e-12, ...,
3.93820033e-12, 4.18850823e-12, 4.34950629e-12],
[ -1.07284424e-13, -9.23447993e-14, -7.89852400e-14, ...,
7.92079631e-14, 5.60172215e-14, 3.04448868e-14]]], array[[ 60. , 60.001, 60.002, ..., 69.998, 69.999, 70. ]]], [array[[[ -6.71363108e-12, -5.80501003e-12, -4.95944514e-12, ...,
-3.25087343e-12, -2.68982494e-12, -2.13637448e-12],
[ -5.04818633e-12, -4.65757005e-12, -4.16084140e-12, ...,
-4.26120531e-13, 2.20744290e-13, 7.81245614e-13],
[ 1.97329506e-13, 1.64543867e-13, 1.32679812e-13, ...,
2.11645494e-13, 1.94795729e-13, 1.75781773e-13],
...,
[ 3.04245661e-12, 2.28376461e-12, 1.54118900e-12, ...,
-1.14020908e-14, -8.04647589e-13, -1.52676489e-12],
[ -1.83485962e-13, -5.22949893e-13, -8.60038852e-13, ...,
7.70312553e-12, 7.20825156e-12, 6.58362857e-12],
[ -7.26357906e-14, -7.11700989e-14, -6.88759767e-14, ...,
-1.04171843e-13, -1.03084861e-13, -9.68462427e-14]]], array[[ 60. , 60.001, 60.002, ..., 69.998, 69.999, 70. ]]]]
0 len[raws] = 2
type[raws] = 'list'
np.shape[raws[0][0]] = [306, 10001]
raws =
[[array[[[ -4.13211217e-12, -4.13287303e-12, -4.01705259e-12, ...,
1.36386023e-12, 1.65182851e-12, 2.00368966e-12],
[ 1.08914129e-12, 1.47828466e-12, 1.82257607e-12, ...,
-2.70151520e-12, -2.48631967e-12, -2.28625548e-12],
[ -7.80962369e-14, -1.27119591e-13, -1.73610315e-13, ...,
-1.13219629e-13, -1.15031720e-13, -1.12106621e-13],
...,
[ 2.52774254e-12, 2.32293195e-12, 2.02644002e-12, ...,
4.20064191e-12, 3.94858906e-12, 3.69495394e-12],
[ -4.38122146e-12, -4.96229676e-12, -5.47782145e-12, ...,
3.93820033e-12, 4.18850823e-12, 4.34950629e-12],
[ -1.07284424e-13, -9.23447993e-14, -7.89852400e-14, ...,
7.92079631e-14, 5.60172215e-14, 3.04448868e-14]]], array[[ 60. , 60.001, 60.002, ..., 69.998, 69.999, 70. ]]], [array[[[ -6.71363108e-12, -5.80501003e-12, -4.95944514e-12, ...,
-3.25087343e-12, -2.68982494e-12, -2.13637448e-12],
[ -5.04818633e-12, -4.65757005e-12, -4.16084140e-12, ...,
-4.26120531e-13, 2.20744290e-13, 7.81245614e-13],
[ 1.97329506e-13, 1.64543867e-13, 1.32679812e-13, ...,
2.11645494e-13, 1.94795729e-13, 1.75781773e-13],
...,
[ 3.04245661e-12, 2.28376461e-12, 1.54118900e-12, ...,
-1.14020908e-14, -8.04647589e-13, -1.52676489e-12],
[ -1.83485962e-13, -5.22949893e-13, -8.60038852e-13, ...,
7.70312553e-12, 7.20825156e-12, 6.58362857e-12],
[ -7.26357906e-14, -7.11700989e-14, -6.88759767e-14, ...,
-1.04171843e-13, -1.03084861e-13, -9.68462427e-14]]], array[[ 60. , 60.001, 60.002, ..., 69.998, 69.999, 70. ]]]]
1 len[raws] = 2
type[raws] = 'list'
np.shape[raws[0][0]] = [306, 10001]
raws =
[[array[[[ -4.13211217e-12, -4.13287303e-12, -4.01705259e-12, ...,
1.36386023e-12, 1.65182851e-12, 2.00368966e-12],
[ 1.08914129e-12, 1.47828466e-12, 1.82257607e-12, ...,
-2.70151520e-12, -2.48631967e-12, -2.28625548e-12],
[ -7.80962369e-14, -1.27119591e-13, -1.73610315e-13, ...,
-1.13219629e-13, -1.15031720e-13, -1.12106621e-13],
...,
[ 2.52774254e-12, 2.32293195e-12, 2.02644002e-12, ...,
4.20064191e-12, 3.94858906e-12, 3.69495394e-12],
[ -4.38122146e-12, -4.96229676e-12, -5.47782145e-12, ...,
3.93820033e-12, 4.18850823e-12, 4.34950629e-12],
[ -1.07284424e-13, -9.23447993e-14, -7.89852400e-14, ...,
7.92079631e-14, 5.60172215e-14, 3.04448868e-14]]], array[[ 60. , 60.001, 60.002, ..., 69.998, 69.999, 70. ]]], [array[[[ -6.71363108e-12, -5.80501003e-12, -4.95944514e-12, ...,
-3.25087343e-12, -2.68982494e-12, -2.13637448e-12],
[ -5.04818633e-12, -4.65757005e-12, -4.16084140e-12, ...,
-4.26120531e-13, 2.20744290e-13, 7.81245614e-13],
[ 1.97329506e-13, 1.64543867e-13, 1.32679812e-13, ...,
2.11645494e-13, 1.94795729e-13, 1.75781773e-13],
...,
[ 3.04245661e-12, 2.28376461e-12, 1.54118900e-12, ...,
-1.14020908e-14, -8.04647589e-13, -1.52676489e-12],
[ -1.83485962e-13, -5.22949893e-13, -8.60038852e-13, ...,
7.70312553e-12, 7.20825156e-12, 6.58362857e-12],
[ -7.26357906e-14, -7.11700989e-14, -6.88759767e-14, ...,
-1.04171843e-13, -1.03084861e-13, -9.68462427e-14]]], array[[ 60. , 60.001, 60.002, ..., 69.998, 69.999, 70. ]]]]
2for r in range[len[raws]]:
axes[r].plot[raws[r]]
5 len[raws] = 2
type[raws] = 'list'
np.shape[raws[0][0]] = [306, 10001]
raws =
[[array[[[ -4.13211217e-12, -4.13287303e-12, -4.01705259e-12, ...,
1.36386023e-12, 1.65182851e-12, 2.00368966e-12],
[ 1.08914129e-12, 1.47828466e-12, 1.82257607e-12, ...,
-2.70151520e-12, -2.48631967e-12, -2.28625548e-12],
[ -7.80962369e-14, -1.27119591e-13, -1.73610315e-13, ...,
-1.13219629e-13, -1.15031720e-13, -1.12106621e-13],
...,
[ 2.52774254e-12, 2.32293195e-12, 2.02644002e-12, ...,
4.20064191e-12, 3.94858906e-12, 3.69495394e-12],
[ -4.38122146e-12, -4.96229676e-12, -5.47782145e-12, ...,
3.93820033e-12, 4.18850823e-12, 4.34950629e-12],
[ -1.07284424e-13, -9.23447993e-14, -7.89852400e-14, ...,
7.92079631e-14, 5.60172215e-14, 3.04448868e-14]]], array[[ 60. , 60.001, 60.002, ..., 69.998, 69.999, 70. ]]], [array[[[ -6.71363108e-12, -5.80501003e-12, -4.95944514e-12, ...,
-3.25087343e-12, -2.68982494e-12, -2.13637448e-12],
[ -5.04818633e-12, -4.65757005e-12, -4.16084140e-12, ...,
-4.26120531e-13, 2.20744290e-13, 7.81245614e-13],
[ 1.97329506e-13, 1.64543867e-13, 1.32679812e-13, ...,
2.11645494e-13, 1.94795729e-13, 1.75781773e-13],
...,
[ 3.04245661e-12, 2.28376461e-12, 1.54118900e-12, ...,
-1.14020908e-14, -8.04647589e-13, -1.52676489e-12],
[ -1.83485962e-13, -5.22949893e-13, -8.60038852e-13, ...,
7.70312553e-12, 7.20825156e-12, 6.58362857e-12],
[ -7.26357906e-14, -7.11700989e-14, -6.88759767e-14, ...,
-1.04171843e-13, -1.03084861e-13, -9.68462427e-14]]], array[[ 60. , 60.001, 60.002, ..., 69.998, 69.999, 70. ]]]]
4 len[raws] = 2
type[raws] = 'list'
np.shape[raws[0][0]] = [306, 10001]
raws =
[[array[[[ -4.13211217e-12, -4.13287303e-12, -4.01705259e-12, ...,
1.36386023e-12, 1.65182851e-12, 2.00368966e-12],
[ 1.08914129e-12, 1.47828466e-12, 1.82257607e-12, ...,
-2.70151520e-12, -2.48631967e-12, -2.28625548e-12],
[ -7.80962369e-14, -1.27119591e-13, -1.73610315e-13, ...,
-1.13219629e-13, -1.15031720e-13, -1.12106621e-13],
...,
[ 2.52774254e-12, 2.32293195e-12, 2.02644002e-12, ...,
4.20064191e-12, 3.94858906e-12, 3.69495394e-12],
[ -4.38122146e-12, -4.96229676e-12, -5.47782145e-12, ...,
3.93820033e-12, 4.18850823e-12, 4.34950629e-12],
[ -1.07284424e-13, -9.23447993e-14, -7.89852400e-14, ...,
7.92079631e-14, 5.60172215e-14, 3.04448868e-14]]], array[[ 60. , 60.001, 60.002, ..., 69.998, 69.999, 70. ]]], [array[[[ -6.71363108e-12, -5.80501003e-12, -4.95944514e-12, ...,
-3.25087343e-12, -2.68982494e-12, -2.13637448e-12],
[ -5.04818633e-12, -4.65757005e-12, -4.16084140e-12, ...,
-4.26120531e-13, 2.20744290e-13, 7.81245614e-13],
[ 1.97329506e-13, 1.64543867e-13, 1.32679812e-13, ...,
2.11645494e-13, 1.94795729e-13, 1.75781773e-13],
...,
[ 3.04245661e-12, 2.28376461e-12, 1.54118900e-12, ...,
-1.14020908e-14, -8.04647589e-13, -1.52676489e-12],
[ -1.83485962e-13, -5.22949893e-13, -8.60038852e-13, ...,
7.70312553e-12, 7.20825156e-12, 6.58362857e-12],
[ -7.26357906e-14, -7.11700989e-14, -6.88759767e-14, ...,
-1.04171843e-13, -1.03084861e-13, -9.68462427e-14]]], array[[ 60. , 60.001, 60.002, ..., 69.998, 69.999, 70. ]]]]
5for r in range[len[raws]]:
axes[r].plot[raws[r]]
5 len[raws] = 2
type[raws] = 'list'
np.shape[raws[0][0]] = [306, 10001]
raws =
[[array[[[ -4.13211217e-12, -4.13287303e-12, -4.01705259e-12, ...,
1.36386023e-12, 1.65182851e-12, 2.00368966e-12],
[ 1.08914129e-12, 1.47828466e-12, 1.82257607e-12, ...,
-2.70151520e-12, -2.48631967e-12, -2.28625548e-12],
[ -7.80962369e-14, -1.27119591e-13, -1.73610315e-13, ...,
-1.13219629e-13, -1.15031720e-13, -1.12106621e-13],
...,
[ 2.52774254e-12, 2.32293195e-12, 2.02644002e-12, ...,
4.20064191e-12, 3.94858906e-12, 3.69495394e-12],
[ -4.38122146e-12, -4.96229676e-12, -5.47782145e-12, ...,
3.93820033e-12, 4.18850823e-12, 4.34950629e-12],
[ -1.07284424e-13, -9.23447993e-14, -7.89852400e-14, ...,
7.92079631e-14, 5.60172215e-14, 3.04448868e-14]]], array[[ 60. , 60.001, 60.002, ..., 69.998, 69.999, 70. ]]], [array[[[ -6.71363108e-12, -5.80501003e-12, -4.95944514e-12, ...,
-3.25087343e-12, -2.68982494e-12, -2.13637448e-12],
[ -5.04818633e-12, -4.65757005e-12, -4.16084140e-12, ...,
-4.26120531e-13, 2.20744290e-13, 7.81245614e-13],
[ 1.97329506e-13, 1.64543867e-13, 1.32679812e-13, ...,
2.11645494e-13, 1.94795729e-13, 1.75781773e-13],
...,
[ 3.04245661e-12, 2.28376461e-12, 1.54118900e-12, ...,
-1.14020908e-14, -8.04647589e-13, -1.52676489e-12],
[ -1.83485962e-13, -5.22949893e-13, -8.60038852e-13, ...,
7.70312553e-12, 7.20825156e-12, 6.58362857e-12],
[ -7.26357906e-14, -7.11700989e-14, -6.88759767e-14, ...,
-1.04171843e-13, -1.03084861e-13, -9.68462427e-14]]], array[[ 60. , 60.001, 60.002, ..., 69.998, 69.999, 70. ]]]]
7 len[raws] = 2
type[raws] = 'list'
np.shape[raws[0][0]] = [306, 10001]
raws =
[[array[[[ -4.13211217e-12, -4.13287303e-12, -4.01705259e-12, ...,
1.36386023e-12, 1.65182851e-12, 2.00368966e-12],
[ 1.08914129e-12, 1.47828466e-12, 1.82257607e-12, ...,
-2.70151520e-12, -2.48631967e-12, -2.28625548e-12],
[ -7.80962369e-14, -1.27119591e-13, -1.73610315e-13, ...,
-1.13219629e-13, -1.15031720e-13, -1.12106621e-13],
...,
[ 2.52774254e-12, 2.32293195e-12, 2.02644002e-12, ...,
4.20064191e-12, 3.94858906e-12, 3.69495394e-12],
[ -4.38122146e-12, -4.96229676e-12, -5.47782145e-12, ...,
3.93820033e-12, 4.18850823e-12, 4.34950629e-12],
[ -1.07284424e-13, -9.23447993e-14, -7.89852400e-14, ...,
7.92079631e-14, 5.60172215e-14, 3.04448868e-14]]], array[[ 60. , 60.001, 60.002, ..., 69.998, 69.999, 70. ]]], [array[[[ -6.71363108e-12, -5.80501003e-12, -4.95944514e-12, ...,
-3.25087343e-12, -2.68982494e-12, -2.13637448e-12],
[ -5.04818633e-12, -4.65757005e-12, -4.16084140e-12, ...,
-4.26120531e-13, 2.20744290e-13, 7.81245614e-13],
[ 1.97329506e-13, 1.64543867e-13, 1.32679812e-13, ...,
2.11645494e-13, 1.94795729e-13, 1.75781773e-13],
...,
[ 3.04245661e-12, 2.28376461e-12, 1.54118900e-12, ...,
-1.14020908e-14, -8.04647589e-13, -1.52676489e-12],
[ -1.83485962e-13, -5.22949893e-13, -8.60038852e-13, ...,
7.70312553e-12, 7.20825156e-12, 6.58362857e-12],
[ -7.26357906e-14, -7.11700989e-14, -6.88759767e-14, ...,
-1.04171843e-13, -1.03084861e-13, -9.68462427e-14]]], array[[ 60. , 60.001, 60.002, ..., 69.998, 69.999, 70. ]]]]
8for r in range[len[raws]]:
axes[r].plot[raws[r]]
5raws
0
for r in range[len[raws]]:
axes[r].plot[raws[r]]
0raws
2for r in range[len[raws]]:
axes[r].plot[raws[r]]
5raws
4
& nbsp; đầu ra: & nbsp;
Output :
Ví dụ 2:
Python3
import
numpy as np
import
matplotlib.pyplot as plt
x
____10
for r in range[len[raws]]:
axes[r].plot[raws[r]]
1for r in range[len[raws]]:
axes[r].plot[raws[r]]
2for r in range[len[raws]]:
axes[r].plot[raws[r]]
3for r in range[len[raws]]:
axes[r].plot[raws[r]]
4for r in range[len[raws]]:
axes[r].plot[raws[r]]
5for r in range[len[raws]]:
axes[r].plot[raws[r]]
6for r in range[len[raws]]:
axes[r].plot[raws[r]]
0 x
for r in range[len[raws]]:
axes[r].plot[raws[r]]
9 len[raws] = 2
type[raws] = 'list'
np.shape[raws[0][0]] = [306, 10001]
raws =
[[array[[[ -4.13211217e-12, -4.13287303e-12, -4.01705259e-12, ...,
1.36386023e-12, 1.65182851e-12, 2.00368966e-12],
[ 1.08914129e-12, 1.47828466e-12, 1.82257607e-12, ...,
-2.70151520e-12, -2.48631967e-12, -2.28625548e-12],
[ -7.80962369e-14, -1.27119591e-13, -1.73610315e-13, ...,
-1.13219629e-13, -1.15031720e-13, -1.12106621e-13],
...,
[ 2.52774254e-12, 2.32293195e-12, 2.02644002e-12, ...,
4.20064191e-12, 3.94858906e-12, 3.69495394e-12],
[ -4.38122146e-12, -4.96229676e-12, -5.47782145e-12, ...,
3.93820033e-12, 4.18850823e-12, 4.34950629e-12],
[ -1.07284424e-13, -9.23447993e-14, -7.89852400e-14, ...,
7.92079631e-14, 5.60172215e-14, 3.04448868e-14]]], array[[ 60. , 60.001, 60.002, ..., 69.998, 69.999, 70. ]]], [array[[[ -6.71363108e-12, -5.80501003e-12, -4.95944514e-12, ...,
-3.25087343e-12, -2.68982494e-12, -2.13637448e-12],
[ -5.04818633e-12, -4.65757005e-12, -4.16084140e-12, ...,
-4.26120531e-13, 2.20744290e-13, 7.81245614e-13],
[ 1.97329506e-13, 1.64543867e-13, 1.32679812e-13, ...,
2.11645494e-13, 1.94795729e-13, 1.75781773e-13],
...,
[ 3.04245661e-12, 2.28376461e-12, 1.54118900e-12, ...,
-1.14020908e-14, -8.04647589e-13, -1.52676489e-12],
[ -1.83485962e-13, -5.22949893e-13, -8.60038852e-13, ...,
7.70312553e-12, 7.20825156e-12, 6.58362857e-12],
[ -7.26357906e-14, -7.11700989e-14, -6.88759767e-14, ...,
-1.04171843e-13, -1.03084861e-13, -9.68462427e-14]]], array[[ 60. , 60.001, 60.002, ..., 69.998, 69.999, 70. ]]]]
0 len[raws] = 2
type[raws] = 'list'
np.shape[raws[0][0]] = [306, 10001]
raws =
[[array[[[ -4.13211217e-12, -4.13287303e-12, -4.01705259e-12, ...,
1.36386023e-12, 1.65182851e-12, 2.00368966e-12],
[ 1.08914129e-12, 1.47828466e-12, 1.82257607e-12, ...,
-2.70151520e-12, -2.48631967e-12, -2.28625548e-12],
[ -7.80962369e-14, -1.27119591e-13, -1.73610315e-13, ...,
-1.13219629e-13, -1.15031720e-13, -1.12106621e-13],
...,
[ 2.52774254e-12, 2.32293195e-12, 2.02644002e-12, ...,
4.20064191e-12, 3.94858906e-12, 3.69495394e-12],
[ -4.38122146e-12, -4.96229676e-12, -5.47782145e-12, ...,
3.93820033e-12, 4.18850823e-12, 4.34950629e-12],
[ -1.07284424e-13, -9.23447993e-14, -7.89852400e-14, ...,
7.92079631e-14, 5.60172215e-14, 3.04448868e-14]]], array[[ 60. , 60.001, 60.002, ..., 69.998, 69.999, 70. ]]], [array[[[ -6.71363108e-12, -5.80501003e-12, -4.95944514e-12, ...,
-3.25087343e-12, -2.68982494e-12, -2.13637448e-12],
[ -5.04818633e-12, -4.65757005e-12, -4.16084140e-12, ...,
-4.26120531e-13, 2.20744290e-13, 7.81245614e-13],
[ 1.97329506e-13, 1.64543867e-13, 1.32679812e-13, ...,
2.11645494e-13, 1.94795729e-13, 1.75781773e-13],
...,
[ 3.04245661e-12, 2.28376461e-12, 1.54118900e-12, ...,
-1.14020908e-14, -8.04647589e-13, -1.52676489e-12],
[ -1.83485962e-13, -5.22949893e-13, -8.60038852e-13, ...,
7.70312553e-12, 7.20825156e-12, 6.58362857e-12],
[ -7.26357906e-14, -7.11700989e-14, -6.88759767e-14, ...,
-1.04171843e-13, -1.03084861e-13, -9.68462427e-14]]], array[[ 60. , 60.001, 60.002, ..., 69.998, 69.999, 70. ]]]]
1 len[raws] = 2
type[raws] = 'list'
np.shape[raws[0][0]] = [306, 10001]
raws =
[[array[[[ -4.13211217e-12, -4.13287303e-12, -4.01705259e-12, ...,
1.36386023e-12, 1.65182851e-12, 2.00368966e-12],
[ 1.08914129e-12, 1.47828466e-12, 1.82257607e-12, ...,
-2.70151520e-12, -2.48631967e-12, -2.28625548e-12],
[ -7.80962369e-14, -1.27119591e-13, -1.73610315e-13, ...,
-1.13219629e-13, -1.15031720e-13, -1.12106621e-13],
...,
[ 2.52774254e-12, 2.32293195e-12, 2.02644002e-12, ...,
4.20064191e-12, 3.94858906e-12, 3.69495394e-12],
[ -4.38122146e-12, -4.96229676e-12, -5.47782145e-12, ...,
3.93820033e-12, 4.18850823e-12, 4.34950629e-12],
[ -1.07284424e-13, -9.23447993e-14, -7.89852400e-14, ...,
7.92079631e-14, 5.60172215e-14, 3.04448868e-14]]], array[[ 60. , 60.001, 60.002, ..., 69.998, 69.999, 70. ]]], [array[[[ -6.71363108e-12, -5.80501003e-12, -4.95944514e-12, ...,
-3.25087343e-12, -2.68982494e-12, -2.13637448e-12],
[ -5.04818633e-12, -4.65757005e-12, -4.16084140e-12, ...,
-4.26120531e-13, 2.20744290e-13, 7.81245614e-13],
[ 1.97329506e-13, 1.64543867e-13, 1.32679812e-13, ...,
2.11645494e-13, 1.94795729e-13, 1.75781773e-13],
...,
[ 3.04245661e-12, 2.28376461e-12, 1.54118900e-12, ...,
-1.14020908e-14, -8.04647589e-13, -1.52676489e-12],
[ -1.83485962e-13, -5.22949893e-13, -8.60038852e-13, ...,
7.70312553e-12, 7.20825156e-12, 6.58362857e-12],
[ -7.26357906e-14, -7.11700989e-14, -6.88759767e-14, ...,
-1.04171843e-13, -1.03084861e-13, -9.68462427e-14]]], array[[ 60. , 60.001, 60.002, ..., 69.998, 69.999, 70. ]]]]
2for r in range[len[raws]]:
axes[r].plot[raws[r]]
5 len[raws] = 2
type[raws] = 'list'
np.shape[raws[0][0]] = [306, 10001]
raws =
[[array[[[ -4.13211217e-12, -4.13287303e-12, -4.01705259e-12, ...,
1.36386023e-12, 1.65182851e-12, 2.00368966e-12],
[ 1.08914129e-12, 1.47828466e-12, 1.82257607e-12, ...,
-2.70151520e-12, -2.48631967e-12, -2.28625548e-12],
[ -7.80962369e-14, -1.27119591e-13, -1.73610315e-13, ...,
-1.13219629e-13, -1.15031720e-13, -1.12106621e-13],
...,
[ 2.52774254e-12, 2.32293195e-12, 2.02644002e-12, ...,
4.20064191e-12, 3.94858906e-12, 3.69495394e-12],
[ -4.38122146e-12, -4.96229676e-12, -5.47782145e-12, ...,
3.93820033e-12, 4.18850823e-12, 4.34950629e-12],
[ -1.07284424e-13, -9.23447993e-14, -7.89852400e-14, ...,
7.92079631e-14, 5.60172215e-14, 3.04448868e-14]]], array[[ 60. , 60.001, 60.002, ..., 69.998, 69.999, 70. ]]], [array[[[ -6.71363108e-12, -5.80501003e-12, -4.95944514e-12, ...,
-3.25087343e-12, -2.68982494e-12, -2.13637448e-12],
[ -5.04818633e-12, -4.65757005e-12, -4.16084140e-12, ...,
-4.26120531e-13, 2.20744290e-13, 7.81245614e-13],
[ 1.97329506e-13, 1.64543867e-13, 1.32679812e-13, ...,
2.11645494e-13, 1.94795729e-13, 1.75781773e-13],
...,
[ 3.04245661e-12, 2.28376461e-12, 1.54118900e-12, ...,
-1.14020908e-14, -8.04647589e-13, -1.52676489e-12],
[ -1.83485962e-13, -5.22949893e-13, -8.60038852e-13, ...,
7.70312553e-12, 7.20825156e-12, 6.58362857e-12],
[ -7.26357906e-14, -7.11700989e-14, -6.88759767e-14, ...,
-1.04171843e-13, -1.03084861e-13, -9.68462427e-14]]], array[[ 60. , 60.001, 60.002, ..., 69.998, 69.999, 70. ]]]]
4 len[raws] = 2
type[raws] = 'list'
np.shape[raws[0][0]] = [306, 10001]
raws =
[[array[[[ -4.13211217e-12, -4.13287303e-12, -4.01705259e-12, ...,
1.36386023e-12, 1.65182851e-12, 2.00368966e-12],
[ 1.08914129e-12, 1.47828466e-12, 1.82257607e-12, ...,
-2.70151520e-12, -2.48631967e-12, -2.28625548e-12],
[ -7.80962369e-14, -1.27119591e-13, -1.73610315e-13, ...,
-1.13219629e-13, -1.15031720e-13, -1.12106621e-13],
...,
[ 2.52774254e-12, 2.32293195e-12, 2.02644002e-12, ...,
4.20064191e-12, 3.94858906e-12, 3.69495394e-12],
[ -4.38122146e-12, -4.96229676e-12, -5.47782145e-12, ...,
3.93820033e-12, 4.18850823e-12, 4.34950629e-12],
[ -1.07284424e-13, -9.23447993e-14, -7.89852400e-14, ...,
7.92079631e-14, 5.60172215e-14, 3.04448868e-14]]], array[[ 60. , 60.001, 60.002, ..., 69.998, 69.999, 70. ]]], [array[[[ -6.71363108e-12, -5.80501003e-12, -4.95944514e-12, ...,
-3.25087343e-12, -2.68982494e-12, -2.13637448e-12],
[ -5.04818633e-12, -4.65757005e-12, -4.16084140e-12, ...,
-4.26120531e-13, 2.20744290e-13, 7.81245614e-13],
[ 1.97329506e-13, 1.64543867e-13, 1.32679812e-13, ...,
2.11645494e-13, 1.94795729e-13, 1.75781773e-13],
...,
[ 3.04245661e-12, 2.28376461e-12, 1.54118900e-12, ...,
-1.14020908e-14, -8.04647589e-13, -1.52676489e-12],
[ -1.83485962e-13, -5.22949893e-13, -8.60038852e-13, ...,
7.70312553e-12, 7.20825156e-12, 6.58362857e-12],
[ -7.26357906e-14, -7.11700989e-14, -6.88759767e-14, ...,
-1.04171843e-13, -1.03084861e-13, -9.68462427e-14]]], array[[ 60. , 60.001, 60.002, ..., 69.998, 69.999, 70. ]]]]
5for r in range[len[raws]]:
axes[r].plot[raws[r]]
5 len[raws] = 2
type[raws] = 'list'
np.shape[raws[0][0]] = [306, 10001]
raws =
[[array[[[ -4.13211217e-12, -4.13287303e-12, -4.01705259e-12, ...,
1.36386023e-12, 1.65182851e-12, 2.00368966e-12],
[ 1.08914129e-12, 1.47828466e-12, 1.82257607e-12, ...,
-2.70151520e-12, -2.48631967e-12, -2.28625548e-12],
[ -7.80962369e-14, -1.27119591e-13, -1.73610315e-13, ...,
-1.13219629e-13, -1.15031720e-13, -1.12106621e-13],
...,
[ 2.52774254e-12, 2.32293195e-12, 2.02644002e-12, ...,
4.20064191e-12, 3.94858906e-12, 3.69495394e-12],
[ -4.38122146e-12, -4.96229676e-12, -5.47782145e-12, ...,
3.93820033e-12, 4.18850823e-12, 4.34950629e-12],
[ -1.07284424e-13, -9.23447993e-14, -7.89852400e-14, ...,
7.92079631e-14, 5.60172215e-14, 3.04448868e-14]]], array[[ 60. , 60.001, 60.002, ..., 69.998, 69.999, 70. ]]], [array[[[ -6.71363108e-12, -5.80501003e-12, -4.95944514e-12, ...,
-3.25087343e-12, -2.68982494e-12, -2.13637448e-12],
[ -5.04818633e-12, -4.65757005e-12, -4.16084140e-12, ...,
-4.26120531e-13, 2.20744290e-13, 7.81245614e-13],
[ 1.97329506e-13, 1.64543867e-13, 1.32679812e-13, ...,
2.11645494e-13, 1.94795729e-13, 1.75781773e-13],
...,
[ 3.04245661e-12, 2.28376461e-12, 1.54118900e-12, ...,
-1.14020908e-14, -8.04647589e-13, -1.52676489e-12],
[ -1.83485962e-13, -5.22949893e-13, -8.60038852e-13, ...,
7.70312553e-12, 7.20825156e-12, 6.58362857e-12],
[ -7.26357906e-14, -7.11700989e-14, -6.88759767e-14, ...,
-1.04171843e-13, -1.03084861e-13, -9.68462427e-14]]], array[[ 60. , 60.001, 60.002, ..., 69.998, 69.999, 70. ]]]]
7 len[raws] = 2
type[raws] = 'list'
np.shape[raws[0][0]] = [306, 10001]
raws =
[[array[[[ -4.13211217e-12, -4.13287303e-12, -4.01705259e-12, ...,
1.36386023e-12, 1.65182851e-12, 2.00368966e-12],
[ 1.08914129e-12, 1.47828466e-12, 1.82257607e-12, ...,
-2.70151520e-12, -2.48631967e-12, -2.28625548e-12],
[ -7.80962369e-14, -1.27119591e-13, -1.73610315e-13, ...,
-1.13219629e-13, -1.15031720e-13, -1.12106621e-13],
...,
[ 2.52774254e-12, 2.32293195e-12, 2.02644002e-12, ...,
4.20064191e-12, 3.94858906e-12, 3.69495394e-12],
[ -4.38122146e-12, -4.96229676e-12, -5.47782145e-12, ...,
3.93820033e-12, 4.18850823e-12, 4.34950629e-12],
[ -1.07284424e-13, -9.23447993e-14, -7.89852400e-14, ...,
7.92079631e-14, 5.60172215e-14, 3.04448868e-14]]], array[[ 60. , 60.001, 60.002, ..., 69.998, 69.999, 70. ]]], [array[[[ -6.71363108e-12, -5.80501003e-12, -4.95944514e-12, ...,
-3.25087343e-12, -2.68982494e-12, -2.13637448e-12],
[ -5.04818633e-12, -4.65757005e-12, -4.16084140e-12, ...,
-4.26120531e-13, 2.20744290e-13, 7.81245614e-13],
[ 1.97329506e-13, 1.64543867e-13, 1.32679812e-13, ...,
2.11645494e-13, 1.94795729e-13, 1.75781773e-13],
...,
[ 3.04245661e-12, 2.28376461e-12, 1.54118900e-12, ...,
-1.14020908e-14, -8.04647589e-13, -1.52676489e-12],
[ -1.83485962e-13, -5.22949893e-13, -8.60038852e-13, ...,
7.70312553e-12, 7.20825156e-12, 6.58362857e-12],
[ -7.26357906e-14, -7.11700989e-14, -6.88759767e-14, ...,
-1.04171843e-13, -1.03084861e-13, -9.68462427e-14]]], array[[ 60. , 60.001, 60.002, ..., 69.998, 69.999, 70. ]]]]
8for r in range[len[raws]]:
axes[r].plot[raws[r]]
5raws
0
for r in range[len[raws]]:
axes[r].plot[raws[r]]
0matplotlib.pyplot as plt
0for r in range[len[raws]]:
axes[r].plot[raws[r]]
5raws
4
& nbsp; đầu ra: & nbsp;
Output :