From e25c08532d7296c22772e68beab1a9d00087d5a8 Mon Sep 17 00:00:00 2001 From: guanjihuan <34735497+guanjihuan@users.noreply.github.com> Date: Mon, 30 Aug 2021 17:41:42 +0800 Subject: [PATCH] update --- .../create_GIF_with_python.py | 20 +- .../plot_with_2D_data.py | 58 +- .../write_2D_data_into_txt_file.py | 60 +- .../get_eigenvalues_and_plot_1D_bands.py | 68 +- .../get_eigenvalues_and_plot_2D_bands.py | 92 +-- ...nvalues_and_write_1D_data_into_txt_file.py | 60 +- ...nvalues_and_write_2D_data_into_txt_file.py | 82 +-- .../python_structure.py | 12 +- .../read_txt_file/1D_data.txt | 6 +- .../read_txt_file/2D_data.txt | 6 +- .../read_txt_file/read_1D_data.py | 92 +-- .../read_txt_file/read_2D_data.py | 136 ++-- ...running_and_write_2D_data_into_txt_file.py | 34 +- .../plot_2D_scatter.py | 62 +- .../plot_3D_scatter.py | 74 +- .../plot_3D_surface.py | 86 +-- .../plot_contour.py | 82 +-- .../plot_line.py | 58 +- .../python_code_for_data_processing.py | 642 +++++++++--------- 19 files changed, 865 insertions(+), 865 deletions(-) rename {academic_codes => language_learning}/2019.12.03_create_GIF_with_python/create_GIF_with_python.py (96%) mode change 100755 => 100644 rename {academic_codes => language_learning}/2020.08.29_several_python_functions/2D_data_plot_and_write/plot_with_2D_data.py (96%) mode change 100755 => 100644 rename {academic_codes => language_learning}/2020.08.29_several_python_functions/2D_data_plot_and_write/write_2D_data_into_txt_file.py (96%) mode change 100755 => 100644 rename {academic_codes => language_learning}/2020.08.29_several_python_functions/get_eigenvalues_plot_and_write/get_eigenvalues_and_plot_1D_bands.py (95%) mode change 100755 => 100644 rename {academic_codes => language_learning}/2020.08.29_several_python_functions/get_eigenvalues_plot_and_write/get_eigenvalues_and_plot_2D_bands.py (96%) mode change 100755 => 100644 rename {academic_codes => language_learning}/2020.08.29_several_python_functions/get_eigenvalues_plot_and_write/get_eigenvalues_and_write_1D_data_into_txt_file.py (95%) mode change 100755 => 100644 rename {academic_codes => language_learning}/2020.08.29_several_python_functions/get_eigenvalues_plot_and_write/get_eigenvalues_and_write_2D_data_into_txt_file.py (96%) mode change 100755 => 100644 rename {academic_codes => language_learning}/2020.08.29_several_python_functions/python_structure.py (98%) mode change 100755 => 100644 rename {academic_codes => language_learning}/2020.08.29_several_python_functions/read_txt_file/1D_data.txt (94%) mode change 100755 => 100644 rename {academic_codes => language_learning}/2020.08.29_several_python_functions/read_txt_file/2D_data.txt (97%) mode change 100755 => 100644 rename {academic_codes => language_learning}/2020.08.29_several_python_functions/read_txt_file/read_1D_data.py (96%) mode change 100755 => 100644 rename {academic_codes => language_learning}/2020.08.29_several_python_functions/read_txt_file/read_2D_data.py (96%) mode change 100755 => 100644 rename {academic_codes => language_learning}/2020.08.29_several_python_functions/running_and_write_2D_data_into_txt_file.py (96%) mode change 100755 => 100644 rename {academic_codes => language_learning}/2020.12.23_plot_with_matplotlib/plot_2D_scatter.py (97%) mode change 100755 => 100644 rename {academic_codes => language_learning}/2020.12.23_plot_with_matplotlib/plot_3D_scatter.py (97%) mode change 100755 => 100644 rename {academic_codes => language_learning}/2020.12.23_plot_with_matplotlib/plot_3D_surface.py (97%) mode change 100755 => 100644 rename {academic_codes => language_learning}/2020.12.23_plot_with_matplotlib/plot_contour.py (97%) mode change 100755 => 100644 rename {academic_codes => language_learning}/2020.12.23_plot_with_matplotlib/plot_line.py (97%) mode change 100755 => 100644 rename {academic_codes => language_learning}/2021.01.13_python_code_for_data_processing/python_code_for_data_processing.py (97%) mode change 100755 => 100644 diff --git a/academic_codes/2019.12.03_create_GIF_with_python/create_GIF_with_python.py b/language_learning/2019.12.03_create_GIF_with_python/create_GIF_with_python.py old mode 100755 new mode 100644 similarity index 96% rename from academic_codes/2019.12.03_create_GIF_with_python/create_GIF_with_python.py rename to language_learning/2019.12.03_create_GIF_with_python/create_GIF_with_python.py index cf4e55e..02c79fb --- a/academic_codes/2019.12.03_create_GIF_with_python/create_GIF_with_python.py +++ b/language_learning/2019.12.03_create_GIF_with_python/create_GIF_with_python.py @@ -1,11 +1,11 @@ -import imageio -import numpy as np -import os -os.chdir('D:/data') # 设置文件读取和保存位置 - -images = [] -for i in range(1000): - image = str(i)+'.jpg' - im = imageio.imread(image) - images.append(im) +import imageio +import numpy as np +import os +os.chdir('D:/data') # 设置文件读取和保存位置 + +images = [] +for i in range(1000): + image = str(i)+'.jpg' + im = imageio.imread(image) + images.append(im) imageio.mimsave("a.gif", images, 'GIF', duration=0.1) # durantion是延迟时间 \ No newline at end of file diff --git a/academic_codes/2020.08.29_several_python_functions/2D_data_plot_and_write/plot_with_2D_data.py b/language_learning/2020.08.29_several_python_functions/2D_data_plot_and_write/plot_with_2D_data.py old mode 100755 new mode 100644 similarity index 96% rename from academic_codes/2020.08.29_several_python_functions/2D_data_plot_and_write/plot_with_2D_data.py rename to language_learning/2020.08.29_several_python_functions/2D_data_plot_and_write/plot_with_2D_data.py index 2ebd053..957a940 --- a/academic_codes/2020.08.29_several_python_functions/2D_data_plot_and_write/plot_with_2D_data.py +++ b/language_learning/2020.08.29_several_python_functions/2D_data_plot_and_write/plot_with_2D_data.py @@ -1,30 +1,30 @@ -import numpy as np -from math import * -# import os -# os.chdir('D:/data') # 设置路径 - - -def main(): - k1 = np.arange(-pi, pi, 0.05) - k2 = np.arange(-pi, pi, 0.05) - value = np.ones((k2.shape[0], k1.shape[0])) - plot_matrix(k1, k2, value) - - -def plot_matrix(k1, k2, matrix): - import matplotlib.pyplot as plt - from mpl_toolkits.mplot3d import Axes3D - from matplotlib import cm - from matplotlib.ticker import LinearLocator, FormatStrFormatter - fig = plt.figure() - ax = fig.gca(projection='3d') - k1, k2 = np.meshgrid(k1, k2) - ax.plot_surface(k1, k2, matrix, cmap=cm.coolwarm, linewidth=0, antialiased=False) - plt.xlabel('k1') - plt.ylabel('k2') - ax.set_zlabel('Z') - plt.show() - - -if __name__ == '__main__': +import numpy as np +from math import * +# import os +# os.chdir('D:/data') # 设置路径 + + +def main(): + k1 = np.arange(-pi, pi, 0.05) + k2 = np.arange(-pi, pi, 0.05) + value = np.ones((k2.shape[0], k1.shape[0])) + plot_matrix(k1, k2, value) + + +def plot_matrix(k1, k2, matrix): + import matplotlib.pyplot as plt + from mpl_toolkits.mplot3d import Axes3D + from matplotlib import cm + from matplotlib.ticker import LinearLocator, FormatStrFormatter + fig = plt.figure() + ax = fig.gca(projection='3d') + k1, k2 = np.meshgrid(k1, k2) + ax.plot_surface(k1, k2, matrix, cmap=cm.coolwarm, linewidth=0, antialiased=False) + plt.xlabel('k1') + plt.ylabel('k2') + ax.set_zlabel('Z') + plt.show() + + +if __name__ == '__main__': main() \ No newline at end of file diff --git a/academic_codes/2020.08.29_several_python_functions/2D_data_plot_and_write/write_2D_data_into_txt_file.py b/language_learning/2020.08.29_several_python_functions/2D_data_plot_and_write/write_2D_data_into_txt_file.py old mode 100755 new mode 100644 similarity index 96% rename from academic_codes/2020.08.29_several_python_functions/2D_data_plot_and_write/write_2D_data_into_txt_file.py rename to language_learning/2020.08.29_several_python_functions/2D_data_plot_and_write/write_2D_data_into_txt_file.py index bb0fd48..64c009c --- a/academic_codes/2020.08.29_several_python_functions/2D_data_plot_and_write/write_2D_data_into_txt_file.py +++ b/language_learning/2020.08.29_several_python_functions/2D_data_plot_and_write/write_2D_data_into_txt_file.py @@ -1,31 +1,31 @@ -import numpy as np -from math import * -# import os -# os.chdir('D:/data') # 设置路径 - - -def main(): - k1 = np.arange(-pi, pi, 0.05) - k2 = np.arange(-pi, pi, 0.05) - value = np.ones((k2.shape[0], k1.shape[0])) - write_matrix(k1, k2, value) - - -def write_matrix(k1, k2, matrix): - with open('a.txt', 'w') as f: - # np.set_printoptions(suppress=True) # 取消输出科学记数法 - f.write('0 ') - for k10 in k1: - f.write(str(k10)+' ') - f.write('\n') - i0 = 0 - for k20 in k2: - f.write(str(k20)) - for j0 in range(k1.shape[0]): - f.write(' '+str(matrix[i0, j0])+' ') - f.write('\n') - i0 += 1 - - -if __name__ == '__main__': +import numpy as np +from math import * +# import os +# os.chdir('D:/data') # 设置路径 + + +def main(): + k1 = np.arange(-pi, pi, 0.05) + k2 = np.arange(-pi, pi, 0.05) + value = np.ones((k2.shape[0], k1.shape[0])) + write_matrix(k1, k2, value) + + +def write_matrix(k1, k2, matrix): + with open('a.txt', 'w') as f: + # np.set_printoptions(suppress=True) # 取消输出科学记数法 + f.write('0 ') + for k10 in k1: + f.write(str(k10)+' ') + f.write('\n') + i0 = 0 + for k20 in k2: + f.write(str(k20)) + for j0 in range(k1.shape[0]): + f.write(' '+str(matrix[i0, j0])+' ') + f.write('\n') + i0 += 1 + + +if __name__ == '__main__': main() \ No newline at end of file diff --git a/academic_codes/2020.08.29_several_python_functions/get_eigenvalues_plot_and_write/get_eigenvalues_and_plot_1D_bands.py b/language_learning/2020.08.29_several_python_functions/get_eigenvalues_plot_and_write/get_eigenvalues_and_plot_1D_bands.py old mode 100755 new mode 100644 similarity index 95% rename from academic_codes/2020.08.29_several_python_functions/get_eigenvalues_plot_and_write/get_eigenvalues_and_plot_1D_bands.py rename to language_learning/2020.08.29_several_python_functions/get_eigenvalues_plot_and_write/get_eigenvalues_and_plot_1D_bands.py index 448dbf4..4c8ba79 --- a/academic_codes/2020.08.29_several_python_functions/get_eigenvalues_plot_and_write/get_eigenvalues_and_plot_1D_bands.py +++ b/language_learning/2020.08.29_several_python_functions/get_eigenvalues_plot_and_write/get_eigenvalues_and_plot_1D_bands.py @@ -1,35 +1,35 @@ -import numpy as np -from math import * -# import os -# os.chdir('D:/data') # 设置路径 - - -def hamiltonian(k): - pass - - -def main(): - k = np.arange(-pi, pi, 0.05) - plot_bands_one_dimension(k, hamiltonian) - - -def plot_bands_one_dimension(k, hamiltonian): - import matplotlib.pyplot as plt - dim = hamiltonian(0).shape[0] - dim_k = k.shape[0] - eigenvalue_k = np.zeros((dim_k, dim)) - i0 = 0 - for k0 in k: - matrix0 = hamiltonian(k0) - eigenvalue, eigenvector = np.linalg.eig(matrix0) - eigenvalue_k[i0, :] = np.sort(np.real(eigenvalue[:])) - i0 += 1 - for dim0 in range(dim): - plt.plot(k, eigenvalue_k[:, dim0], '-k') - plt.xlabel('k') - plt.ylabel('E') - plt.show() - - -if __name__ == '__main__': +import numpy as np +from math import * +# import os +# os.chdir('D:/data') # 设置路径 + + +def hamiltonian(k): + pass + + +def main(): + k = np.arange(-pi, pi, 0.05) + plot_bands_one_dimension(k, hamiltonian) + + +def plot_bands_one_dimension(k, hamiltonian): + import matplotlib.pyplot as plt + dim = hamiltonian(0).shape[0] + dim_k = k.shape[0] + eigenvalue_k = np.zeros((dim_k, dim)) + i0 = 0 + for k0 in k: + matrix0 = hamiltonian(k0) + eigenvalue, eigenvector = np.linalg.eig(matrix0) + eigenvalue_k[i0, :] = np.sort(np.real(eigenvalue[:])) + i0 += 1 + for dim0 in range(dim): + plt.plot(k, eigenvalue_k[:, dim0], '-k') + plt.xlabel('k') + plt.ylabel('E') + plt.show() + + +if __name__ == '__main__': main() \ No newline at end of file diff --git a/academic_codes/2020.08.29_several_python_functions/get_eigenvalues_plot_and_write/get_eigenvalues_and_plot_2D_bands.py b/language_learning/2020.08.29_several_python_functions/get_eigenvalues_plot_and_write/get_eigenvalues_and_plot_2D_bands.py old mode 100755 new mode 100644 similarity index 96% rename from academic_codes/2020.08.29_several_python_functions/get_eigenvalues_plot_and_write/get_eigenvalues_and_plot_2D_bands.py rename to language_learning/2020.08.29_several_python_functions/get_eigenvalues_plot_and_write/get_eigenvalues_and_plot_2D_bands.py index 0aab40a..b9971fb --- a/academic_codes/2020.08.29_several_python_functions/get_eigenvalues_plot_and_write/get_eigenvalues_and_plot_2D_bands.py +++ b/language_learning/2020.08.29_several_python_functions/get_eigenvalues_plot_and_write/get_eigenvalues_and_plot_2D_bands.py @@ -1,47 +1,47 @@ -import numpy as np -from math import * -# import os -# os.chdir('D:/data') # 设置路径 - - -def hamiltonian(k1, k2): - pass - - -def main(): - k1 = np.arange(-pi, pi, 0.05) - k2 = np.arange(-pi, pi, 0.05) - plot_bands_two_dimension(k1, k2, hamiltonian) - - -def plot_bands_two_dimension(k1, k2, hamiltonian): - import matplotlib.pyplot as plt - from mpl_toolkits.mplot3d import Axes3D - from matplotlib import cm - from matplotlib.ticker import LinearLocator, FormatStrFormatter - dim = hamiltonian(0, 0).shape[0] - dim1 = k1.shape[0] - dim2 = k2.shape[0] - eigenvalue_k = np.zeros((dim2, dim1, dim)) - i0 = 0 - for k20 in k2: - j0 = 0 - for k10 in k1: - matrix0 = hamiltonian(k10, k20) - eigenvalue, eigenvector = np.linalg.eig(matrix0) - eigenvalue_k[i0, j0, :] = np.sort(np.real(eigenvalue[:])) - j0 += 1 - i0 += 1 - fig = plt.figure() - ax = fig.gca(projection='3d') - k1, k2 = np.meshgrid(k1, k2) - for dim0 in range(dim): - ax.plot_surface(k1, k2, eigenvalue_k[:, :, dim0], cmap=cm.coolwarm, linewidth=0, antialiased=False) - plt.xlabel('k1') - plt.ylabel('k2') - ax.set_zlabel('E') - plt.show() - - -if __name__ == '__main__': +import numpy as np +from math import * +# import os +# os.chdir('D:/data') # 设置路径 + + +def hamiltonian(k1, k2): + pass + + +def main(): + k1 = np.arange(-pi, pi, 0.05) + k2 = np.arange(-pi, pi, 0.05) + plot_bands_two_dimension(k1, k2, hamiltonian) + + +def plot_bands_two_dimension(k1, k2, hamiltonian): + import matplotlib.pyplot as plt + from mpl_toolkits.mplot3d import Axes3D + from matplotlib import cm + from matplotlib.ticker import LinearLocator, FormatStrFormatter + dim = hamiltonian(0, 0).shape[0] + dim1 = k1.shape[0] + dim2 = k2.shape[0] + eigenvalue_k = np.zeros((dim2, dim1, dim)) + i0 = 0 + for k20 in k2: + j0 = 0 + for k10 in k1: + matrix0 = hamiltonian(k10, k20) + eigenvalue, eigenvector = np.linalg.eig(matrix0) + eigenvalue_k[i0, j0, :] = np.sort(np.real(eigenvalue[:])) + j0 += 1 + i0 += 1 + fig = plt.figure() + ax = fig.gca(projection='3d') + k1, k2 = np.meshgrid(k1, k2) + for dim0 in range(dim): + ax.plot_surface(k1, k2, eigenvalue_k[:, :, dim0], cmap=cm.coolwarm, linewidth=0, antialiased=False) + plt.xlabel('k1') + plt.ylabel('k2') + ax.set_zlabel('E') + plt.show() + + +if __name__ == '__main__': main() \ No newline at end of file diff --git a/academic_codes/2020.08.29_several_python_functions/get_eigenvalues_plot_and_write/get_eigenvalues_and_write_1D_data_into_txt_file.py b/language_learning/2020.08.29_several_python_functions/get_eigenvalues_plot_and_write/get_eigenvalues_and_write_1D_data_into_txt_file.py old mode 100755 new mode 100644 similarity index 95% rename from academic_codes/2020.08.29_several_python_functions/get_eigenvalues_plot_and_write/get_eigenvalues_and_write_1D_data_into_txt_file.py rename to language_learning/2020.08.29_several_python_functions/get_eigenvalues_plot_and_write/get_eigenvalues_and_write_1D_data_into_txt_file.py index 46a0198..7e39e87 --- a/academic_codes/2020.08.29_several_python_functions/get_eigenvalues_plot_and_write/get_eigenvalues_and_write_1D_data_into_txt_file.py +++ b/language_learning/2020.08.29_several_python_functions/get_eigenvalues_plot_and_write/get_eigenvalues_and_write_1D_data_into_txt_file.py @@ -1,31 +1,31 @@ -import numpy as np -from math import * -# import os -# os.chdir('D:/data') # 设置路径 - - -def hamiltonian(k): - pass - - -def main(): - k = np.arange(-pi, pi, 0.05) - write_bands_one_dimension(k, hamiltonian) - - -def write_bands_one_dimension(k, hamiltonian): - dim = hamiltonian(0).shape[0] - f = open('a.txt','w') - for k0 in k: - f.write(str(k0)+' ') - matrix0 = hamiltonian(k0) - eigenvalue, eigenvector = np.linalg.eig(matrix0) - eigenvalue = np.sort(np.real(eigenvalue)) - for dim0 in range(dim): - f.write(str(eigenvalue[dim0])+' ') - f.write('\n') - f.close() - - -if __name__ == '__main__': +import numpy as np +from math import * +# import os +# os.chdir('D:/data') # 设置路径 + + +def hamiltonian(k): + pass + + +def main(): + k = np.arange(-pi, pi, 0.05) + write_bands_one_dimension(k, hamiltonian) + + +def write_bands_one_dimension(k, hamiltonian): + dim = hamiltonian(0).shape[0] + f = open('a.txt','w') + for k0 in k: + f.write(str(k0)+' ') + matrix0 = hamiltonian(k0) + eigenvalue, eigenvector = np.linalg.eig(matrix0) + eigenvalue = np.sort(np.real(eigenvalue)) + for dim0 in range(dim): + f.write(str(eigenvalue[dim0])+' ') + f.write('\n') + f.close() + + +if __name__ == '__main__': main() \ No newline at end of file diff --git a/academic_codes/2020.08.29_several_python_functions/get_eigenvalues_plot_and_write/get_eigenvalues_and_write_2D_data_into_txt_file.py b/language_learning/2020.08.29_several_python_functions/get_eigenvalues_plot_and_write/get_eigenvalues_and_write_2D_data_into_txt_file.py old mode 100755 new mode 100644 similarity index 96% rename from academic_codes/2020.08.29_several_python_functions/get_eigenvalues_plot_and_write/get_eigenvalues_and_write_2D_data_into_txt_file.py rename to language_learning/2020.08.29_several_python_functions/get_eigenvalues_plot_and_write/get_eigenvalues_and_write_2D_data_into_txt_file.py index 761d0a4..6281f0b --- a/academic_codes/2020.08.29_several_python_functions/get_eigenvalues_plot_and_write/get_eigenvalues_and_write_2D_data_into_txt_file.py +++ b/language_learning/2020.08.29_several_python_functions/get_eigenvalues_plot_and_write/get_eigenvalues_and_write_2D_data_into_txt_file.py @@ -1,42 +1,42 @@ -import numpy as np -from math import * -# import os -# os.chdir('D:/data') # 设置路径 - - -def hamiltonian(k1, k2): - pass - - -def main(): - k1 = np.arange(-pi, pi, 0.05) - k2 = np.arange(-pi, pi, 0.05) - write_bands_two_dimension(k1, k2, hamiltonian) - - -def write_bands_two_dimension(k1, k2, hamiltonian): - f1 = open('a1.txt', 'w') - f2 = open('a2.txt', 'w') - f1.write('0 ') - f2.write('0 ') - for k10 in k1: - f1.write(str(k10)+' ') - f2.write(str(k10)+' ') - f1.write('\n') - f2.write('\n') - for k20 in k2: - f1.write(str(k20)+' ') - f2.write(str(k20)+' ') - for k10 in k1: - matrix0 = hamiltonian(k10, k20) - eigenvalue, eigenvector = np.linalg.eig(matrix0) - eigenvalue = np.sort(np.real(eigenvalue)) - f1.write(str(eigenvalue[0])+' ') - f2.write(str(eigenvalue[1])+' ') - f1.write('\n') - f2.write('\n') - f1.close() - f2.close() - -if __name__ == '__main__': +import numpy as np +from math import * +# import os +# os.chdir('D:/data') # 设置路径 + + +def hamiltonian(k1, k2): + pass + + +def main(): + k1 = np.arange(-pi, pi, 0.05) + k2 = np.arange(-pi, pi, 0.05) + write_bands_two_dimension(k1, k2, hamiltonian) + + +def write_bands_two_dimension(k1, k2, hamiltonian): + f1 = open('a1.txt', 'w') + f2 = open('a2.txt', 'w') + f1.write('0 ') + f2.write('0 ') + for k10 in k1: + f1.write(str(k10)+' ') + f2.write(str(k10)+' ') + f1.write('\n') + f2.write('\n') + for k20 in k2: + f1.write(str(k20)+' ') + f2.write(str(k20)+' ') + for k10 in k1: + matrix0 = hamiltonian(k10, k20) + eigenvalue, eigenvector = np.linalg.eig(matrix0) + eigenvalue = np.sort(np.real(eigenvalue)) + f1.write(str(eigenvalue[0])+' ') + f2.write(str(eigenvalue[1])+' ') + f1.write('\n') + f2.write('\n') + f1.close() + f2.close() + +if __name__ == '__main__': main() \ No newline at end of file diff --git a/academic_codes/2020.08.29_several_python_functions/python_structure.py b/language_learning/2020.08.29_several_python_functions/python_structure.py old mode 100755 new mode 100644 similarity index 98% rename from academic_codes/2020.08.29_several_python_functions/python_structure.py rename to language_learning/2020.08.29_several_python_functions/python_structure.py index 476ea8c..1a0688a --- a/academic_codes/2020.08.29_several_python_functions/python_structure.py +++ b/language_learning/2020.08.29_several_python_functions/python_structure.py @@ -1,7 +1,7 @@ -import numpy as np # 导入numpy库，用来存储和处理大型矩阵，比python自带的嵌套列表更高效。numpy库还包含了许多数学函数库。python+numpy等同于matlab。 - -def main(): # 主函数的内容放在这里。 - pass - -if __name__ == '__main__': # 如果是当前文件直接运行，执行main()函数中的内容；如果是import当前文件，则不执行。同时将main()语句放在最后运行，可以避免书写的函数出现未定义的情况。 +import numpy as np # 导入numpy库，用来存储和处理大型矩阵，比python自带的嵌套列表更高效。numpy库还包含了许多数学函数库。python+numpy等同于matlab。 + +def main(): # 主函数的内容放在这里。 + pass + +if __name__ == '__main__': # 如果是当前文件直接运行，执行main()函数中的内容；如果是import当前文件，则不执行。同时将main()语句放在最后运行，可以避免书写的函数出现未定义的情况。 main() \ No newline at end of file diff --git a/academic_codes/2020.08.29_several_python_functions/read_txt_file/1D_data.txt b/language_learning/2020.08.29_several_python_functions/read_txt_file/1D_data.txt old mode 100755 new mode 100644 similarity index 94% rename from academic_codes/2020.08.29_several_python_functions/read_txt_file/1D_data.txt rename to language_learning/2020.08.29_several_python_functions/read_txt_file/1D_data.txt index 3d1cc66..6718b0b --- a/academic_codes/2020.08.29_several_python_functions/read_txt_file/1D_data.txt +++ b/language_learning/2020.08.29_several_python_functions/read_txt_file/1D_data.txt @@ -1,4 +1,4 @@ -1 1.2 2.4 -2 5.5 3.2 -3 6.7 7.1 +1 1.2 2.4 +2 5.5 3.2 +3 6.7 7.1 4 3.6 4.9 \ No newline at end of file diff --git a/academic_codes/2020.08.29_several_python_functions/read_txt_file/2D_data.txt b/language_learning/2020.08.29_several_python_functions/read_txt_file/2D_data.txt old mode 100755 new mode 100644 similarity index 97% rename from academic_codes/2020.08.29_several_python_functions/read_txt_file/2D_data.txt rename to language_learning/2020.08.29_several_python_functions/read_txt_file/2D_data.txt index 7d30da5..3172531 --- a/academic_codes/2020.08.29_several_python_functions/read_txt_file/2D_data.txt +++ b/language_learning/2020.08.29_several_python_functions/read_txt_file/2D_data.txt @@ -1,4 +1,4 @@ -0 1 2 3 4 -1 1.3 2.7 6.7 8.3 -2 4.3 2.9 5.4 7.4 +0 1 2 3 4 +1 1.3 2.7 6.7 8.3 +2 4.3 2.9 5.4 7.4 3 9.1 8.2 2.6 3.1 \ No newline at end of file diff --git a/academic_codes/2020.08.29_several_python_functions/read_txt_file/read_1D_data.py b/language_learning/2020.08.29_several_python_functions/read_txt_file/read_1D_data.py old mode 100755 new mode 100644 similarity index 96% rename from academic_codes/2020.08.29_several_python_functions/read_txt_file/read_1D_data.py rename to language_learning/2020.08.29_several_python_functions/read_txt_file/read_1D_data.py index ea0dafc..1fc391b --- a/academic_codes/2020.08.29_several_python_functions/read_txt_file/read_1D_data.py +++ b/language_learning/2020.08.29_several_python_functions/read_txt_file/read_1D_data.py @@ -1,47 +1,47 @@ -import numpy as np -import matplotlib.pyplot as plt -# import os -# os.chdir('D:/data') # 设置路径 - - -def main(): - x, y = read_one_dimension('1D_data.txt') - for dim0 in range(y.shape[1]): - plt.plot(x, y[:, dim0], '-k') - plt.show() - - -def read_one_dimension(file_name): - f = open(file_name, 'r') - text = f.read() - f.close() - row_list = np.array(text.split('\n')) # 根据“回车”分割成每一行 - # print('文本格式：') - # print(text) - # print('row_list:') - # print(row_list) - # print('column:') - dim_column = np.array(row_list[0].split()).shape[0] # 列数 - x = np.array([]) - y = np.array([]) - for row in row_list: - column = np.array(row.split()) # 每一行根据“空格”继续分割 - # print(column) - if column.shape[0] != 0: # 解决最后一行空白的问题 - x = np.append(x, [float(column[0])], axis=0) # 第一列为x数据 - y_row = np.zeros(dim_column-1) - for dim0 in range(dim_column-1): - y_row[dim0] = float(column[dim0+1]) - if np.array(y).shape[0] == 0: - y = [y_row] - else: - y = np.append(y, [y_row], axis=0) - # print('x:') - # print(x) - # print('y:') - # print(y) - return x, y - - -if __name__ == '__main__': +import numpy as np +import matplotlib.pyplot as plt +# import os +# os.chdir('D:/data') # 设置路径 + + +def main(): + x, y = read_one_dimension('1D_data.txt') + for dim0 in range(y.shape[1]): + plt.plot(x, y[:, dim0], '-k') + plt.show() + + +def read_one_dimension(file_name): + f = open(file_name, 'r') + text = f.read() + f.close() + row_list = np.array(text.split('\n')) # 根据“回车”分割成每一行 + # print('文本格式：') + # print(text) + # print('row_list:') + # print(row_list) + # print('column:') + dim_column = np.array(row_list[0].split()).shape[0] # 列数 + x = np.array([]) + y = np.array([]) + for row in row_list: + column = np.array(row.split()) # 每一行根据“空格”继续分割 + # print(column) + if column.shape[0] != 0: # 解决最后一行空白的问题 + x = np.append(x, [float(column[0])], axis=0) # 第一列为x数据 + y_row = np.zeros(dim_column-1) + for dim0 in range(dim_column-1): + y_row[dim0] = float(column[dim0+1]) + if np.array(y).shape[0] == 0: + y = [y_row] + else: + y = np.append(y, [y_row], axis=0) + # print('x:') + # print(x) + # print('y:') + # print(y) + return x, y + + +if __name__ == '__main__': main() \ No newline at end of file diff --git a/academic_codes/2020.08.29_several_python_functions/read_txt_file/read_2D_data.py b/language_learning/2020.08.29_several_python_functions/read_txt_file/read_2D_data.py old mode 100755 new mode 100644 similarity index 96% rename from academic_codes/2020.08.29_several_python_functions/read_txt_file/read_2D_data.py rename to language_learning/2020.08.29_several_python_functions/read_txt_file/read_2D_data.py index b9d1d79..3d8153a --- a/academic_codes/2020.08.29_several_python_functions/read_txt_file/read_2D_data.py +++ b/language_learning/2020.08.29_several_python_functions/read_txt_file/read_2D_data.py @@ -1,69 +1,69 @@ -import numpy as np -# import os -# os.chdir('D:/data') # 设置路径 - - -def main(): - x1, x2, matrix = read_two_dimension('2D_data.txt') - plot_matrix(x1, x2, matrix) - - -def read_two_dimension(file_name): - f = open(file_name, 'r') - text = f.read() - f.close() - row_list = np.array(text.split('\n')) # 根据“回车”分割成每一行 - # print('文本格式：') - # print(text) - # print('row_list:') - # print(row_list) - # print('column:') - dim_column = np.array(row_list[0].split()).shape[0] # 列数 - x1 = np.array([]) - x2 = np.array([]) - matrix = np.array([]) - for i0 in range(row_list.shape[0]): - column = np.array(row_list[i0].split()) # 每一行根据“空格”继续分割 - # print(column) - if i0 == 0: - x1_str = column[1::] # x1坐标（去除第一个在角落的值） - x1 = np.zeros(x1_str.shape[0]) - for i00 in range(x1_str.shape[0]): - x1[i00] = float(x1_str[i00]) # 字符串转浮点 - elif column.shape[0] != 0: # 解决最后一行空白的问题 - x2 = np.append(x2, [float(column[0])], axis=0) # 第一列为x数据 - matrix_row = np.zeros(dim_column-1) - for dim0 in range(dim_column-1): - matrix_row[dim0] = float(column[dim0+1]) - if np.array(matrix).shape[0] == 0: - matrix = [matrix_row] - else: - matrix = np.append(matrix, [matrix_row], axis=0) - # print('x1:') - # print(x1) - # print('x2:') - # print(x2) - # print('matrix:') - # print(matrix) - return x1, x2, matrix - - - -def plot_matrix(x1, x2, matrix): - import matplotlib.pyplot as plt - from mpl_toolkits.mplot3d import Axes3D - from matplotlib import cm - from matplotlib.ticker import LinearLocator, FormatStrFormatter - fig = plt.figure() - ax = fig.gca(projection='3d') - x1, x2 = np.meshgrid(x1, x2) - ax.plot_surface(x1, x2, matrix, cmap=cm.coolwarm, linewidth=0, antialiased=False) - plt.xlabel('x1') - plt.ylabel('x2') - ax.set_zlabel('z') - plt.show() - - - -if __name__ == '__main__': +import numpy as np +# import os +# os.chdir('D:/data') # 设置路径 + + +def main(): + x1, x2, matrix = read_two_dimension('2D_data.txt') + plot_matrix(x1, x2, matrix) + + +def read_two_dimension(file_name): + f = open(file_name, 'r') + text = f.read() + f.close() + row_list = np.array(text.split('\n')) # 根据“回车”分割成每一行 + # print('文本格式：') + # print(text) + # print('row_list:') + # print(row_list) + # print('column:') + dim_column = np.array(row_list[0].split()).shape[0] # 列数 + x1 = np.array([]) + x2 = np.array([]) + matrix = np.array([]) + for i0 in range(row_list.shape[0]): + column = np.array(row_list[i0].split()) # 每一行根据“空格”继续分割 + # print(column) + if i0 == 0: + x1_str = column[1::] # x1坐标（去除第一个在角落的值） + x1 = np.zeros(x1_str.shape[0]) + for i00 in range(x1_str.shape[0]): + x1[i00] = float(x1_str[i00]) # 字符串转浮点 + elif column.shape[0] != 0: # 解决最后一行空白的问题 + x2 = np.append(x2, [float(column[0])], axis=0) # 第一列为x数据 + matrix_row = np.zeros(dim_column-1) + for dim0 in range(dim_column-1): + matrix_row[dim0] = float(column[dim0+1]) + if np.array(matrix).shape[0] == 0: + matrix = [matrix_row] + else: + matrix = np.append(matrix, [matrix_row], axis=0) + # print('x1:') + # print(x1) + # print('x2:') + # print(x2) + # print('matrix:') + # print(matrix) + return x1, x2, matrix + + + +def plot_matrix(x1, x2, matrix): + import matplotlib.pyplot as plt + from mpl_toolkits.mplot3d import Axes3D + from matplotlib import cm + from matplotlib.ticker import LinearLocator, FormatStrFormatter + fig = plt.figure() + ax = fig.gca(projection='3d') + x1, x2 = np.meshgrid(x1, x2) + ax.plot_surface(x1, x2, matrix, cmap=cm.coolwarm, linewidth=0, antialiased=False) + plt.xlabel('x1') + plt.ylabel('x2') + ax.set_zlabel('z') + plt.show() + + + +if __name__ == '__main__': main() \ No newline at end of file diff --git a/academic_codes/2020.08.29_several_python_functions/running_and_write_2D_data_into_txt_file.py b/language_learning/2020.08.29_several_python_functions/running_and_write_2D_data_into_txt_file.py old mode 100755 new mode 100644 similarity index 96% rename from academic_codes/2020.08.29_several_python_functions/running_and_write_2D_data_into_txt_file.py rename to language_learning/2020.08.29_several_python_functions/running_and_write_2D_data_into_txt_file.py index 5944a73..60fc178 --- a/academic_codes/2020.08.29_several_python_functions/running_and_write_2D_data_into_txt_file.py +++ b/language_learning/2020.08.29_several_python_functions/running_and_write_2D_data_into_txt_file.py @@ -1,18 +1,18 @@ -import numpy as np -from math import * -# import os -# os.chdir('D:/data') # 设置路径 - - -f = open('a.txt', 'w') -f.write('0 ') -for k1 in np.arange(-pi, pi, 0.05): - f.write(str(k1)+' ') -f.write('\n') -for k2 in np.arange(-pi, pi, 0.05): - f.write(str(k2)+' ') - for k1 in np.arange(-pi, pi, 0.05): - data = 1000 # 运算数据 - f.write(str(data)+' ') - f.write('\n') +import numpy as np +from math import * +# import os +# os.chdir('D:/data') # 设置路径 + + +f = open('a.txt', 'w') +f.write('0 ') +for k1 in np.arange(-pi, pi, 0.05): + f.write(str(k1)+' ') +f.write('\n') +for k2 in np.arange(-pi, pi, 0.05): + f.write(str(k2)+' ') + for k1 in np.arange(-pi, pi, 0.05): + data = 1000 # 运算数据 + f.write(str(data)+' ') + f.write('\n') f.close() \ No newline at end of file diff --git a/academic_codes/2020.12.23_plot_with_matplotlib/plot_2D_scatter.py b/language_learning/2020.12.23_plot_with_matplotlib/plot_2D_scatter.py old mode 100755 new mode 100644 similarity index 97% rename from academic_codes/2020.12.23_plot_with_matplotlib/plot_2D_scatter.py rename to language_learning/2020.12.23_plot_with_matplotlib/plot_2D_scatter.py index 2f82590..0855492 --- a/academic_codes/2020.12.23_plot_with_matplotlib/plot_2D_scatter.py +++ b/language_learning/2020.12.23_plot_with_matplotlib/plot_2D_scatter.py @@ -1,32 +1,32 @@ -import numpy as np -# import os -# os.chdir('D:/data') # 设置文件保存的位置 - - -def main(): - x = [4, 3, 5, 7] - y = [6, 1, 3, 2] - value = [3, 1, 10, 2] - Plot_2D_Scatter(x, y, value, title='Plot 2D Scatter') - - -def Plot_2D_Scatter(x, y, value, xlabel='x', ylabel='y', title='title', filename='a'): - import matplotlib.pyplot as plt - fig = plt.figure() - ax = fig.add_subplot(111) - plt.subplots_adjust(bottom=0.2, right=0.8, left=0.2) - for i in range(np.array(x).shape[0]): - ax.scatter(x[i], y[i], marker='o', s=100*value[i], c=[(1,0,0)]) - ax.set_title(title, fontsize=20, fontfamily='Times New Roman') - ax.set_xlabel(xlabel, fontsize=20, fontfamily='Times New Roman') - ax.set_ylabel(ylabel, fontsize=20, fontfamily='Times New Roman') - ax.tick_params(labelsize=15) # 设置刻度值字体大小 - labels = ax.get_xticklabels() + ax.get_yticklabels() - [label.set_fontname('Times New Roman') for label in labels] # 设置刻度值字体 - # plt.savefig(filename+'.jpg', dpi=300) - plt.show() - plt.close('all') - - -if __name__ == '__main__': +import numpy as np +# import os +# os.chdir('D:/data') # 设置文件保存的位置 + + +def main(): + x = [4, 3, 5, 7] + y = [6, 1, 3, 2] + value = [3, 1, 10, 2] + Plot_2D_Scatter(x, y, value, title='Plot 2D Scatter') + + +def Plot_2D_Scatter(x, y, value, xlabel='x', ylabel='y', title='title', filename='a'): + import matplotlib.pyplot as plt + fig = plt.figure() + ax = fig.add_subplot(111) + plt.subplots_adjust(bottom=0.2, right=0.8, left=0.2) + for i in range(np.array(x).shape[0]): + ax.scatter(x[i], y[i], marker='o', s=100*value[i], c=[(1,0,0)]) + ax.set_title(title, fontsize=20, fontfamily='Times New Roman') + ax.set_xlabel(xlabel, fontsize=20, fontfamily='Times New Roman') + ax.set_ylabel(ylabel, fontsize=20, fontfamily='Times New Roman') + ax.tick_params(labelsize=15) # 设置刻度值字体大小 + labels = ax.get_xticklabels() + ax.get_yticklabels() + [label.set_fontname('Times New Roman') for label in labels] # 设置刻度值字体 + # plt.savefig(filename+'.jpg', dpi=300) + plt.show() + plt.close('all') + + +if __name__ == '__main__': main() \ No newline at end of file diff --git a/academic_codes/2020.12.23_plot_with_matplotlib/plot_3D_scatter.py b/language_learning/2020.12.23_plot_with_matplotlib/plot_3D_scatter.py old mode 100755 new mode 100644 similarity index 97% rename from academic_codes/2020.12.23_plot_with_matplotlib/plot_3D_scatter.py rename to language_learning/2020.12.23_plot_with_matplotlib/plot_3D_scatter.py index c2d3b5d..b57e012 --- a/academic_codes/2020.12.23_plot_with_matplotlib/plot_3D_scatter.py +++ b/language_learning/2020.12.23_plot_with_matplotlib/plot_3D_scatter.py @@ -1,38 +1,38 @@ -import numpy as np -# import os -# os.chdir('D:/data') # 设置文件保存的位置 - - -def main(): - x = [1, 3, 5, 7] - y = [2, 4, 6, 8] - z = [2, 8, 6, 1] - value = [3, 1, 10, 2] - Plot_3D_Scatter(x, y, z, value, title='Plot 3D Scatter') - - -def Plot_3D_Scatter(x, y, z, value, xlabel='x', ylabel='y', zlabel='z', title='title', filename='a'): - import matplotlib.pyplot as plt - from matplotlib.ticker import LinearLocator - fig = plt.figure() - ax = fig.add_subplot(111, projection='3d') - plt.subplots_adjust(bottom=0.1, right=0.8) - for i in range(np.array(x).shape[0]): - ax.scatter(x[i], y[i], z[i], marker='o', s=int(100*value[i]), c=[(1,0,0)]) - ax.set_title(title, fontsize=20, fontfamily='Times New Roman') - ax.set_xlabel(xlabel, fontsize=20, fontfamily='Times New Roman') - ax.set_ylabel(ylabel, fontsize=20, fontfamily='Times New Roman') - ax.set_zlabel(zlabel, fontsize=20, fontfamily='Times New Roman') - # ax.set_zlim(0, 20) - # ax.zaxis.set_major_locator(LinearLocator(6)) # 设置z轴主刻度的个数 - # ax.zaxis.set_major_formatter('{x:.0f}') # 设置z轴主刻度的格式 - ax.tick_params(labelsize=15) # 设置刻度值字体大小 - labels = ax.get_xticklabels() + ax.get_yticklabels() + ax.get_zticklabels() - [label.set_fontname('Times New Roman') for label in labels] # 设置刻度值字体 - # plt.savefig(filename+'.jpg', dpi=300) - plt.show() - plt.close('all') - - -if __name__ == '__main__': +import numpy as np +# import os +# os.chdir('D:/data') # 设置文件保存的位置 + + +def main(): + x = [1, 3, 5, 7] + y = [2, 4, 6, 8] + z = [2, 8, 6, 1] + value = [3, 1, 10, 2] + Plot_3D_Scatter(x, y, z, value, title='Plot 3D Scatter') + + +def Plot_3D_Scatter(x, y, z, value, xlabel='x', ylabel='y', zlabel='z', title='title', filename='a'): + import matplotlib.pyplot as plt + from matplotlib.ticker import LinearLocator + fig = plt.figure() + ax = fig.add_subplot(111, projection='3d') + plt.subplots_adjust(bottom=0.1, right=0.8) + for i in range(np.array(x).shape[0]): + ax.scatter(x[i], y[i], z[i], marker='o', s=int(100*value[i]), c=[(1,0,0)]) + ax.set_title(title, fontsize=20, fontfamily='Times New Roman') + ax.set_xlabel(xlabel, fontsize=20, fontfamily='Times New Roman') + ax.set_ylabel(ylabel, fontsize=20, fontfamily='Times New Roman') + ax.set_zlabel(zlabel, fontsize=20, fontfamily='Times New Roman') + # ax.set_zlim(0, 20) + # ax.zaxis.set_major_locator(LinearLocator(6)) # 设置z轴主刻度的个数 + # ax.zaxis.set_major_formatter('{x:.0f}') # 设置z轴主刻度的格式 + ax.tick_params(labelsize=15) # 设置刻度值字体大小 + labels = ax.get_xticklabels() + ax.get_yticklabels() + ax.get_zticklabels() + [label.set_fontname('Times New Roman') for label in labels] # 设置刻度值字体 + # plt.savefig(filename+'.jpg', dpi=300) + plt.show() + plt.close('all') + + +if __name__ == '__main__': main() \ No newline at end of file diff --git a/academic_codes/2020.12.23_plot_with_matplotlib/plot_3D_surface.py b/language_learning/2020.12.23_plot_with_matplotlib/plot_3D_surface.py old mode 100755 new mode 100644 similarity index 97% rename from academic_codes/2020.12.23_plot_with_matplotlib/plot_3D_surface.py rename to language_learning/2020.12.23_plot_with_matplotlib/plot_3D_surface.py index dd926f0..79da877 --- a/academic_codes/2020.12.23_plot_with_matplotlib/plot_3D_surface.py +++ b/language_learning/2020.12.23_plot_with_matplotlib/plot_3D_surface.py @@ -1,44 +1,44 @@ -import numpy as np -# import os -# os.chdir('D:/data') # 设置文件保存的位置 - - -def main(): - x = np.arange(-5, 5, 0.25) - y = np.arange(-5, 5, 0.25) - X, Y = np.meshgrid(x, y) - R = np.sqrt(X**2 + Y**2) - Z = np.sin(R) - Plot_3D_Surface(x,y,Z) - - -def Plot_3D_Surface(x,y,matrix,filename='a.jpg', titlename='Plot 3D Surface'): - import matplotlib.pyplot as plt - from matplotlib import cm - from matplotlib.ticker import LinearLocator - fig, ax = plt.subplots(subplot_kw={"projection": "3d"}) - plt.subplots_adjust(bottom=0.1, right=0.65) # 调整位置 - x, y = np.meshgrid(x, y) - surf = ax.plot_surface(x, y, matrix, cmap=cm.coolwarm, linewidth=0, antialiased=False) # Plot the surface. - ax.set_title(titlename, fontsize=20, fontfamily='Times New Roman') - ax.set_xlabel('x', fontsize=30, fontfamily='Times New Roman') # 坐标标签 - ax.set_ylabel('y', fontsize=30, fontfamily='Times New Roman') # 坐标标签 - ax.set_zlabel('z', fontsize=30, fontfamily='Times New Roman') # 坐标标签 - # ax.set_zlim(-1, 1) # 设置z轴的范围 - ax.zaxis.set_major_locator(LinearLocator(5)) # 设置z轴主刻度的个数 - ax.zaxis.set_major_formatter('{x:.2f}') # 设置z轴主刻度的格式 - ax.tick_params(labelsize=15) # 设置刻度值字体大小 - labels = ax.get_xticklabels() + ax.get_yticklabels() + ax.get_zticklabels() - [label.set_fontname('Times New Roman') for label in labels] # 设置刻度值字体 - cax = plt.axes([0.75, 0.15, 0.05, 0.75]) # color bar的位置 [左，下，宽度， 高度] - cbar = fig.colorbar(surf, cax=cax) # color bar - cbar.ax.tick_params(labelsize=15) # 设置color bar刻度的字体大小 - for l in cbar.ax.yaxis.get_ticklabels(): # 设置color bar刻度的字体 - l.set_family('Times New Roman') - # plt.savefig(filename, dpi=800) # 保存图片文件 - plt.show() - plt.close('all') # 关闭所有plt，防止循环画图时占用内存 - - -if __name__ == '__main__': +import numpy as np +# import os +# os.chdir('D:/data') # 设置文件保存的位置 + + +def main(): + x = np.arange(-5, 5, 0.25) + y = np.arange(-5, 5, 0.25) + X, Y = np.meshgrid(x, y) + R = np.sqrt(X**2 + Y**2) + Z = np.sin(R) + Plot_3D_Surface(x,y,Z) + + +def Plot_3D_Surface(x,y,matrix,filename='a.jpg', titlename='Plot 3D Surface'): + import matplotlib.pyplot as plt + from matplotlib import cm + from matplotlib.ticker import LinearLocator + fig, ax = plt.subplots(subplot_kw={"projection": "3d"}) + plt.subplots_adjust(bottom=0.1, right=0.65) # 调整位置 + x, y = np.meshgrid(x, y) + surf = ax.plot_surface(x, y, matrix, cmap=cm.coolwarm, linewidth=0, antialiased=False) # Plot the surface. + ax.set_title(titlename, fontsize=20, fontfamily='Times New Roman') + ax.set_xlabel('x', fontsize=30, fontfamily='Times New Roman') # 坐标标签 + ax.set_ylabel('y', fontsize=30, fontfamily='Times New Roman') # 坐标标签 + ax.set_zlabel('z', fontsize=30, fontfamily='Times New Roman') # 坐标标签 + # ax.set_zlim(-1, 1) # 设置z轴的范围 + ax.zaxis.set_major_locator(LinearLocator(5)) # 设置z轴主刻度的个数 + ax.zaxis.set_major_formatter('{x:.2f}') # 设置z轴主刻度的格式 + ax.tick_params(labelsize=15) # 设置刻度值字体大小 + labels = ax.get_xticklabels() + ax.get_yticklabels() + ax.get_zticklabels() + [label.set_fontname('Times New Roman') for label in labels] # 设置刻度值字体 + cax = plt.axes([0.75, 0.15, 0.05, 0.75]) # color bar的位置 [左，下，宽度， 高度] + cbar = fig.colorbar(surf, cax=cax) # color bar + cbar.ax.tick_params(labelsize=15) # 设置color bar刻度的字体大小 + for l in cbar.ax.yaxis.get_ticklabels(): # 设置color bar刻度的字体 + l.set_family('Times New Roman') + # plt.savefig(filename, dpi=800) # 保存图片文件 + plt.show() + plt.close('all') # 关闭所有plt，防止循环画图时占用内存 + + +if __name__ == '__main__': main() \ No newline at end of file diff --git a/academic_codes/2020.12.23_plot_with_matplotlib/plot_contour.py b/language_learning/2020.12.23_plot_with_matplotlib/plot_contour.py old mode 100755 new mode 100644 similarity index 97% rename from academic_codes/2020.12.23_plot_with_matplotlib/plot_contour.py rename to language_learning/2020.12.23_plot_with_matplotlib/plot_contour.py index a638b18..a5cc63d --- a/academic_codes/2020.12.23_plot_with_matplotlib/plot_contour.py +++ b/language_learning/2020.12.23_plot_with_matplotlib/plot_contour.py @@ -1,42 +1,42 @@ -import numpy as np -# import os -# os.chdir('D:/data') # 设置文件保存的位置 - - -def main(): - x = np.arange(-5, 5, 0.25) - y = np.arange(-5, 5, 0.25) - X, Y = np.meshgrid(x, y) - R = np.sqrt(X**2 + Y**2) - Z = np.sin(R) - Plot_Contour(x,y,Z) - - -def Plot_Contour(x,y,matrix,filename='a.jpg', titlename='Plot Contour'): - import matplotlib.pyplot as plt - from matplotlib import cm - from matplotlib.ticker import LinearLocator - fig, ax = plt.subplots() - plt.subplots_adjust(bottom=0.15, right=0.7) # 调整位置 - x, y = np.meshgrid(x, y) - contour = ax.contourf(x,y,matrix,cmap='jet') - ax.set_title(titlename, fontsize=20, fontfamily='Times New Roman') - ax.set_xlabel('x', fontsize=30, fontfamily='Times New Roman') # 坐标标签 - ax.set_ylabel('y', fontsize=30, fontfamily='Times New Roman') # 坐标标签 - # plt.xlabel('x') - # plt.ylabel('y') - ax.tick_params(labelsize=15) # 设置刻度值字体大小 - labels = ax.get_xticklabels() + ax.get_yticklabels() - [label.set_fontname('Times New Roman') for label in labels] # 设置刻度值字体 - cax = plt.axes([0.75, 0.15, 0.08, 0.73]) # color bar的位置 [左，下，宽度， 高度] - cbar = fig.colorbar(contour, cax=cax) # color bar - cbar.ax.tick_params(labelsize=15) # 设置color bar刻度的字体大小 - for l in cbar.ax.yaxis.get_ticklabels(): # 设置color bar刻度的字体 - l.set_family('Times New Roman') - # plt.savefig(filename, dpi=800) # 保存图片文件 - plt.show() - plt.close('all') # 关闭所有plt，防止循环画图时占用内存 - - -if __name__ == '__main__': +import numpy as np +# import os +# os.chdir('D:/data') # 设置文件保存的位置 + + +def main(): + x = np.arange(-5, 5, 0.25) + y = np.arange(-5, 5, 0.25) + X, Y = np.meshgrid(x, y) + R = np.sqrt(X**2 + Y**2) + Z = np.sin(R) + Plot_Contour(x,y,Z) + + +def Plot_Contour(x,y,matrix,filename='a.jpg', titlename='Plot Contour'): + import matplotlib.pyplot as plt + from matplotlib import cm + from matplotlib.ticker import LinearLocator + fig, ax = plt.subplots() + plt.subplots_adjust(bottom=0.15, right=0.7) # 调整位置 + x, y = np.meshgrid(x, y) + contour = ax.contourf(x,y,matrix,cmap='jet') + ax.set_title(titlename, fontsize=20, fontfamily='Times New Roman') + ax.set_xlabel('x', fontsize=30, fontfamily='Times New Roman') # 坐标标签 + ax.set_ylabel('y', fontsize=30, fontfamily='Times New Roman') # 坐标标签 + # plt.xlabel('x') + # plt.ylabel('y') + ax.tick_params(labelsize=15) # 设置刻度值字体大小 + labels = ax.get_xticklabels() + ax.get_yticklabels() + [label.set_fontname('Times New Roman') for label in labels] # 设置刻度值字体 + cax = plt.axes([0.75, 0.15, 0.08, 0.73]) # color bar的位置 [左，下，宽度， 高度] + cbar = fig.colorbar(contour, cax=cax) # color bar + cbar.ax.tick_params(labelsize=15) # 设置color bar刻度的字体大小 + for l in cbar.ax.yaxis.get_ticklabels(): # 设置color bar刻度的字体 + l.set_family('Times New Roman') + # plt.savefig(filename, dpi=800) # 保存图片文件 + plt.show() + plt.close('all') # 关闭所有plt，防止循环画图时占用内存 + + +if __name__ == '__main__': main() \ No newline at end of file diff --git a/academic_codes/2020.12.23_plot_with_matplotlib/plot_line.py b/language_learning/2020.12.23_plot_with_matplotlib/plot_line.py old mode 100755 new mode 100644 similarity index 97% rename from academic_codes/2020.12.23_plot_with_matplotlib/plot_line.py rename to language_learning/2020.12.23_plot_with_matplotlib/plot_line.py index b28db22..010d5fe --- a/academic_codes/2020.12.23_plot_with_matplotlib/plot_line.py +++ b/language_learning/2020.12.23_plot_with_matplotlib/plot_line.py @@ -1,30 +1,30 @@ -import numpy as np -# import os -# os.chdir('D:/data') # 设置文件保存的位置 - - -def main(): - x = np.arange(0.0, 2.0, 0.01) - y = 1 + np.sin(2 * np.pi * x) - Plot_Line(x,y) - - -def Plot_Line(x,y,filename='a.jpg', titlename='Plot Line'): - import matplotlib.pyplot as plt - fig, ax = plt.subplots() - plt.subplots_adjust(bottom=0.20, left=0.16) - ax.plot(x, y, '-o') - ax.grid() - ax.set_title(titlename, fontsize=20, fontfamily='Times New Roman') - ax.set_xlabel('x', fontsize=30, fontfamily='Times New Roman') # 坐标标签 - ax.set_ylabel('y', fontsize=30, fontfamily='Times New Roman') # 坐标标签 - ax.tick_params(labelsize=20) # 设置刻度值字体大小 - labels = ax.get_xticklabels() + ax.get_yticklabels() - [label.set_fontname('Times New Roman') for label in labels] # 设置刻度值字体 - # plt.savefig(filename, dpi=800) # 保存图片文件 - plt.show() - plt.close('all') # 关闭所有plt，防止循环画图时占用内存 - - -if __name__ == '__main__': +import numpy as np +# import os +# os.chdir('D:/data') # 设置文件保存的位置 + + +def main(): + x = np.arange(0.0, 2.0, 0.01) + y = 1 + np.sin(2 * np.pi * x) + Plot_Line(x,y) + + +def Plot_Line(x,y,filename='a.jpg', titlename='Plot Line'): + import matplotlib.pyplot as plt + fig, ax = plt.subplots() + plt.subplots_adjust(bottom=0.20, left=0.16) + ax.plot(x, y, '-o') + ax.grid() + ax.set_title(titlename, fontsize=20, fontfamily='Times New Roman') + ax.set_xlabel('x', fontsize=30, fontfamily='Times New Roman') # 坐标标签 + ax.set_ylabel('y', fontsize=30, fontfamily='Times New Roman') # 坐标标签 + ax.tick_params(labelsize=20) # 设置刻度值字体大小 + labels = ax.get_xticklabels() + ax.get_yticklabels() + [label.set_fontname('Times New Roman') for label in labels] # 设置刻度值字体 + # plt.savefig(filename, dpi=800) # 保存图片文件 + plt.show() + plt.close('all') # 关闭所有plt，防止循环画图时占用内存 + + +if __name__ == '__main__': main() \ No newline at end of file diff --git a/academic_codes/2021.01.13_python_code_for_data_processing/python_code_for_data_processing.py b/language_learning/2021.01.13_python_code_for_data_processing/python_code_for_data_processing.py old mode 100755 new mode 100644 similarity index 97% rename from academic_codes/2021.01.13_python_code_for_data_processing/python_code_for_data_processing.py rename to language_learning/2021.01.13_python_code_for_data_processing/python_code_for_data_processing.py index 284c77f..e8f5568 --- a/academic_codes/2021.01.13_python_code_for_data_processing/python_code_for_data_processing.py +++ b/language_learning/2021.01.13_python_code_for_data_processing/python_code_for_data_processing.py @@ -1,322 +1,322 @@ -""" -This code is supported by the website: https://www.guanjihuan.com -The newest version of this code is on the web page: https://www.guanjihuan.com/archives/8734 - -函数调用目录： -1. x, y = read_one_dimensional_data(filename='a') -2. x, y, matrix = read_two_dimensional_data(filename='a') -3. write_one_dimensional_data(x, y, filename='a') -4. write_two_dimensional_data(x, y, matrix, filename='a') -5. plot(x, y, xlabel='x', ylabel='y', title='', filename='a') -6. plot_3d_surface(x, y, matrix, xlabel='x', ylabel='y', zlabel='z', title='', filename='a') -7. plot_contour(x, y, matrix, xlabel='x', ylabel='y', title='', filename='a') -8. plot_2d_scatter(x, y, value, xlabel='x', ylabel='y', title='', filename='a') -9. plot_3d_surface(x, y, z, value, xlabel='x', ylabel='y', zlabel='z', title='', filename='a') -10. creat_animation(image_names, duration_time=0.5, filename='a') -11. eigenvalue_array = calculate_eigenvalue_with_one_paramete(x, matrix) -12. eigenvalue_array = calculate_eigenvalue_with_two_parameters(x, y, matrix) - -函数对应的功能： -1. 读取filename.txt文件中的一维数据y(x) -2. 读取filename.txt文件中的二维数据matrix(x,y) -3. 把一维数据y(x)写入filename.txt文件 -4. 把二维数据matrix(x,y)写入filename.txt文件 -5. 画y(x)图，并保存到filename.jpg文件。具体画图格式可在函数中修改！ -6. 画3d_surface图，并保存到filename.jpg文件。具体画图格式可在函数中修改！ -7. 画contour图，并保存到filename.jpg文件。具体画图格式可在函数中修改！ -8. 画2d_scatter图，并保存到filename.jpg文件。具体画图格式可在函数中修改！ -9. 画3d_scatter图，并保存到filename.jpg文件。具体画图格式可在函数中修改！ -10. 制作动画 -11. 在参数x下，计算matrix函数的本征值eigenvalue_array[:, index] -12. 在参数(x,y)下，计算matrix函数的本征值eigenvalue_array[:, :, index] -""" - - -import numpy as np -# import os -# os.chdir('D:/data') - - -def main(): - pass # 读取数据 + 数据处理 + 保存新数据 - - -# 1. 读取filename.txt文件中的一维数据y(x) -def read_one_dimensional_data(filename='a'): - f = open(filename+'.txt', 'r') - text = f.read() - f.close() - row_list = np.array(text.split('\n')) - dim_column = np.array(row_list[0].split()).shape[0] - x = np.array([]) - y = np.array([]) - for row in row_list: - column = np.array(row.split()) - if column.shape[0] != 0: - x = np.append(x, [float(column[0])], axis=0) - y_row = np.zeros(dim_column-1) - for dim0 in range(dim_column-1): - y_row[dim0] = float(column[dim0+1]) - if np.array(y).shape[0] == 0: - y = [y_row] - else: - y = np.append(y, [y_row], axis=0) - return x, y - - -# 2. 读取filename.txt文件中的二维数据matrix(x,y) -def read_two_dimensional_data(filename='a'): - f = open(filename+'.txt', 'r') - text = f.read() - f.close() - row_list = np.array(text.split('\n')) - dim_column = np.array(row_list[0].split()).shape[0] - x = np.array([]) - y = np.array([]) - matrix = np.array([]) - for i0 in range(row_list.shape[0]): - column = np.array(row_list[i0].split()) - if i0 == 0: - x_str = column[1::] - x = np.zeros(x_str.shape[0]) - for i00 in range(x_str.shape[0]): - x[i00] = float(x_str[i00]) - elif column.shape[0] != 0: - y = np.append(y, [float(column[0])], axis=0) - matrix_row = np.zeros(dim_column-1) - for dim0 in range(dim_column-1): - matrix_row[dim0] = float(column[dim0+1]) - if np.array(matrix).shape[0] == 0: - matrix = [matrix_row] - else: - matrix = np.append(matrix, [matrix_row], axis=0) - return x, y, matrix - - -# 3. 把一维数据y(x)写入filename.txt文件 -def write_one_dimensional_data(x, y, filename='a'): - with open(filename+'.txt', 'w') as f: - i0 = 0 - for x0 in x: - f.write(str(x0)+' ') - if len(y.shape) == 1: - f.write(str(y[i0])+'\n') - elif len(y.shape) == 2: - for j0 in range(y.shape[1]): - f.write(str(y[i0, j0])+' ') - f.write('\n') - i0 += 1 - - -# 4. 把二维数据matrix(x,y)写入filename.txt文件 -def write_two_dimensional_data(x, y, matrix, filename='a'): - with open(filename+'.txt', 'w') as f: - f.write('0 ') - for x0 in x: - f.write(str(x0)+' ') - f.write('\n') - i0 = 0 - for y0 in y: - f.write(str(y0)) - j0 = 0 - for x0 in x: - f.write(' '+str(matrix[i0, j0])+' ') - j0 += 1 - f.write('\n') - i0 += 1 - - -# 5. 画y(x)图，并保存到filename.jpg文件。具体画图格式可在函数中修改。 -def plot(x, y, xlabel='x', ylabel='y', title='', filename='a', show=1, save=0): - import matplotlib.pyplot as plt - fig, ax = plt.subplots() - plt.subplots_adjust(bottom=0.20, left=0.18) - ax.plot(x, y, '-o') - ax.grid() - ax.set_title(title, fontsize=20, fontfamily='Times New Roman') - ax.set_xlabel(xlabel, fontsize=20, fontfamily='Times New Roman') - ax.set_ylabel(ylabel, fontsize=20, fontfamily='Times New Roman') - ax.tick_params(labelsize=20) - labels = ax.get_xticklabels() + ax.get_yticklabels() - [label.set_fontname('Times New Roman') for label in labels] - if save == 1: - plt.savefig(filename+'.jpg', dpi=300) - if show == 1: - plt.show() - plt.close('all') - - - -# 6. 画3d_surface图，并保存到filename.jpg文件。具体画图格式可在函数中修改。 -def plot_3d_surface(x, y, matrix, xlabel='x', ylabel='y', zlabel='z', title='', filename='a', show=1, save=0): - import matplotlib.pyplot as plt - from matplotlib import cm - from matplotlib.ticker import LinearLocator - fig, ax = plt.subplots(subplot_kw={"projection": "3d"}) - plt.subplots_adjust(bottom=0.1, right=0.65) - x, y = np.meshgrid(x, y) - if len(matrix.shape) == 2: - surf = ax.plot_surface(x, y, matrix, cmap=cm.coolwarm, linewidth=0, antialiased=False) - elif len(matrix.shape) == 3: - for i0 in range(matrix.shape[2]): - surf = ax.plot_surface(x, y, matrix[:,:,i0], cmap=cm.coolwarm, linewidth=0, antialiased=False) - ax.set_title(title, fontsize=20, fontfamily='Times New Roman') - ax.set_xlabel(xlabel, fontsize=20, fontfamily='Times New Roman') - ax.set_ylabel(ylabel, fontsize=20, fontfamily='Times New Roman') - ax.set_zlabel(zlabel, fontsize=20, fontfamily='Times New Roman') - ax.zaxis.set_major_locator(LinearLocator(5)) - ax.zaxis.set_major_formatter('{x:.2f}') - ax.tick_params(labelsize=15) - labels = ax.get_xticklabels() + ax.get_yticklabels() + ax.get_zticklabels() - [label.set_fontname('Times New Roman') for label in labels] - cax = plt.axes([0.80, 0.15, 0.05, 0.75]) - cbar = fig.colorbar(surf, cax=cax) - cbar.ax.tick_params(labelsize=15) - for l in cbar.ax.yaxis.get_ticklabels(): - l.set_family('Times New Roman') - if save == 1: - plt.savefig(filename+'.jpg', dpi=300) - if show == 1: - plt.show() - plt.close('all') - - - -# 7. 画plot_contour图，并保存到filename.jpg文件。具体画图格式可在函数中修改。 -def plot_contour(x, y, matrix, xlabel='x', ylabel='y', title='', filename='a', show=1, save=0): - import matplotlib.pyplot as plt - from matplotlib import cm - from matplotlib.ticker import LinearLocator - fig, ax = plt.subplots() - plt.subplots_adjust(bottom=0.2, right=0.75, left = 0.16) - x, y = np.meshgrid(x, y) - contour = ax.contourf(x,y,matrix,cmap='jet') - ax.set_title(title, fontsize=20, fontfamily='Times New Roman') - ax.set_xlabel(xlabel, fontsize=20, fontfamily='Times New Roman') - ax.set_ylabel(ylabel, fontsize=20, fontfamily='Times New Roman') - ax.tick_params(labelsize=15) - labels = ax.get_xticklabels() + ax.get_yticklabels() - [label.set_fontname('Times New Roman') for label in labels] - cax = plt.axes([0.78, 0.17, 0.08, 0.71]) - cbar = fig.colorbar(contour, cax=cax) - cbar.ax.tick_params(labelsize=15) - for l in cbar.ax.yaxis.get_ticklabels(): - l.set_family('Times New Roman') - if save == 1: - plt.savefig(filename+'.jpg', dpi=300) - if show == 1: - plt.show() - plt.close('all') - - -# 8. 画2d_scatter图，并保存到filename.jpg文件。具体画图格式可在函数中修改！ -def plot_2d_scatter(x, y, value, xlabel='x', ylabel='y', title='', filename='a', show=1, save=0): - import matplotlib.pyplot as plt - from matplotlib.axes._axes import _log as matplotlib_axes_logger - matplotlib_axes_logger.setLevel('ERROR') - fig = plt.figure() - ax = fig.add_subplot(111) - plt.subplots_adjust(bottom=0.2, right=0.8, left=0.2) - for i in range(np.array(x).shape[0]): - ax.scatter(x[i], y[i], marker='o', s=100*value[i], c=(1,0,0)) - ax.set_title(title, fontsize=20, fontfamily='Times New Roman') - ax.set_xlabel(xlabel, fontsize=20, fontfamily='Times New Roman') - ax.set_ylabel(ylabel, fontsize=20, fontfamily='Times New Roman') - ax.tick_params(labelsize=15) - labels = ax.get_xticklabels() + ax.get_yticklabels() - [label.set_fontname('Times New Roman') for label in labels] - if save == 1: - plt.savefig(filename+'.jpg', dpi=300) - if show == 1: - plt.show() - plt.close('all') - - -# 9. 画3d_scatter图，并保存到filename.jpg文件。具体画图格式可在函数中修改！ -def plot_3d_scatter(x, y, z, value, xlabel='x', ylabel='y', zlabel='z', title='', filename='a', show=1, save=0): - import matplotlib.pyplot as plt - from matplotlib.ticker import LinearLocator - from matplotlib.axes._axes import _log as matplotlib_axes_logger - matplotlib_axes_logger.setLevel('ERROR') - fig = plt.figure() - ax = fig.add_subplot(111, projection='3d') - plt.subplots_adjust(bottom=0.1, right=0.8) - for i in range(np.array(x).shape[0]): - ax.scatter(x[i], y[i], z[i], marker='o', s=int(100*value[i]), c=(1,0,0)) - ax.set_title(title, fontsize=20, fontfamily='Times New Roman') - ax.set_xlabel(xlabel, fontsize=20, fontfamily='Times New Roman') - ax.set_ylabel(ylabel, fontsize=20, fontfamily='Times New Roman') - ax.set_zlabel(zlabel, fontsize=20, fontfamily='Times New Roman') - ax.tick_params(labelsize=15) - labels = ax.get_xticklabels() + ax.get_yticklabels() + ax.get_zticklabels() - [label.set_fontname('Times New Roman') for label in labels] - if save == 1: - plt.savefig(filename+'.jpg', dpi=300) - if show == 1: - plt.show() - plt.close('all') - - -# 10. 制作动画 -def creat_animation(image_names, duration_time=0.5, filename='a'): - import imageio - images = [] - for name in image_names: - image = name+'.jpg' - im = imageio.imread(image) - images.append(im) - imageio.mimsave(filename+'.gif', images, 'GIF', duration=duration_time) # durantion是延迟时间 - - -# 11. 在参数x下，计算matrix函数的本征值eigenvalue_array[:, index] -def calculate_eigenvalue_with_one_parameter(x, matrix): - dim_x = np.array(x).shape[0] - i0 = 0 - if np.array(matrix(0)).shape==(): - eigenvalue_array = np.zeros((dim_x, 1)) - for x0 in x: - matrix0 = matrix(x0) - eigenvalue_array[i0, 0] = np.real(matrix0) - i0 += 1 - else: - dim = np.array(matrix(0)).shape[0] - eigenvalue_array = np.zeros((dim_x, dim)) - for x0 in x: - matrix0 = matrix(x0) - eigenvalue, eigenvector = np.linalg.eig(matrix0) - eigenvalue_array[i0, :] = np.sort(np.real(eigenvalue[:])) - i0 += 1 - return eigenvalue_array - - -# 12. 在参数(x,y)下，计算matrix函数的本征值eigenvalue_array[:, :, index] -def calculate_eigenvalue_with_two_parameters(x, y, matrix): - dim_x = np.array(x).shape[0] - dim_y = np.array(y).shape[0] - if np.array(matrix(0,0)).shape==(): - eigenvalue_array = np.zeros((dim_y, dim_x, 1)) - i0 = 0 - for y0 in y: - j0 = 0 - for x0 in x: - matrix0 = matrix(x0, y0) - eigenvalue_array[i0, j0, 0] = np.real(matrix0) - j0 += 1 - i0 += 1 - else: - dim = np.array(matrix(0, 0)).shape[0] - eigenvalue_array = np.zeros((dim_y, dim_x, dim)) - i0 = 0 - for y0 in y: - j0 = 0 - for x0 in x: - matrix0 = matrix(x0, y0) - eigenvalue, eigenvector = np.linalg.eig(matrix0) - eigenvalue_array[i0, j0, :] = np.sort(np.real(eigenvalue[:])) - j0 += 1 - i0 += 1 - return eigenvalue_array - - -if __name__ == "__main__": +""" +This code is supported by the website: https://www.guanjihuan.com +The newest version of this code is on the web page: https://www.guanjihuan.com/archives/8734 + +函数调用目录： +1. x, y = read_one_dimensional_data(filename='a') +2. x, y, matrix = read_two_dimensional_data(filename='a') +3. write_one_dimensional_data(x, y, filename='a') +4. write_two_dimensional_data(x, y, matrix, filename='a') +5. plot(x, y, xlabel='x', ylabel='y', title='', filename='a') +6. plot_3d_surface(x, y, matrix, xlabel='x', ylabel='y', zlabel='z', title='', filename='a') +7. plot_contour(x, y, matrix, xlabel='x', ylabel='y', title='', filename='a') +8. plot_2d_scatter(x, y, value, xlabel='x', ylabel='y', title='', filename='a') +9. plot_3d_surface(x, y, z, value, xlabel='x', ylabel='y', zlabel='z', title='', filename='a') +10. creat_animation(image_names, duration_time=0.5, filename='a') +11. eigenvalue_array = calculate_eigenvalue_with_one_paramete(x, matrix) +12. eigenvalue_array = calculate_eigenvalue_with_two_parameters(x, y, matrix) + +函数对应的功能： +1. 读取filename.txt文件中的一维数据y(x) +2. 读取filename.txt文件中的二维数据matrix(x,y) +3. 把一维数据y(x)写入filename.txt文件 +4. 把二维数据matrix(x,y)写入filename.txt文件 +5. 画y(x)图，并保存到filename.jpg文件。具体画图格式可在函数中修改！ +6. 画3d_surface图，并保存到filename.jpg文件。具体画图格式可在函数中修改！ +7. 画contour图，并保存到filename.jpg文件。具体画图格式可在函数中修改！ +8. 画2d_scatter图，并保存到filename.jpg文件。具体画图格式可在函数中修改！ +9. 画3d_scatter图，并保存到filename.jpg文件。具体画图格式可在函数中修改！ +10. 制作动画 +11. 在参数x下，计算matrix函数的本征值eigenvalue_array[:, index] +12. 在参数(x,y)下，计算matrix函数的本征值eigenvalue_array[:, :, index] +""" + + +import numpy as np +# import os +# os.chdir('D:/data') + + +def main(): + pass # 读取数据 + 数据处理 + 保存新数据 + + +# 1. 读取filename.txt文件中的一维数据y(x) +def read_one_dimensional_data(filename='a'): + f = open(filename+'.txt', 'r') + text = f.read() + f.close() + row_list = np.array(text.split('\n')) + dim_column = np.array(row_list[0].split()).shape[0] + x = np.array([]) + y = np.array([]) + for row in row_list: + column = np.array(row.split()) + if column.shape[0] != 0: + x = np.append(x, [float(column[0])], axis=0) + y_row = np.zeros(dim_column-1) + for dim0 in range(dim_column-1): + y_row[dim0] = float(column[dim0+1]) + if np.array(y).shape[0] == 0: + y = [y_row] + else: + y = np.append(y, [y_row], axis=0) + return x, y + + +# 2. 读取filename.txt文件中的二维数据matrix(x,y) +def read_two_dimensional_data(filename='a'): + f = open(filename+'.txt', 'r') + text = f.read() + f.close() + row_list = np.array(text.split('\n')) + dim_column = np.array(row_list[0].split()).shape[0] + x = np.array([]) + y = np.array([]) + matrix = np.array([]) + for i0 in range(row_list.shape[0]): + column = np.array(row_list[i0].split()) + if i0 == 0: + x_str = column[1::] + x = np.zeros(x_str.shape[0]) + for i00 in range(x_str.shape[0]): + x[i00] = float(x_str[i00]) + elif column.shape[0] != 0: + y = np.append(y, [float(column[0])], axis=0) + matrix_row = np.zeros(dim_column-1) + for dim0 in range(dim_column-1): + matrix_row[dim0] = float(column[dim0+1]) + if np.array(matrix).shape[0] == 0: + matrix = [matrix_row] + else: + matrix = np.append(matrix, [matrix_row], axis=0) + return x, y, matrix + + +# 3. 把一维数据y(x)写入filename.txt文件 +def write_one_dimensional_data(x, y, filename='a'): + with open(filename+'.txt', 'w') as f: + i0 = 0 + for x0 in x: + f.write(str(x0)+' ') + if len(y.shape) == 1: + f.write(str(y[i0])+'\n') + elif len(y.shape) == 2: + for j0 in range(y.shape[1]): + f.write(str(y[i0, j0])+' ') + f.write('\n') + i0 += 1 + + +# 4. 把二维数据matrix(x,y)写入filename.txt文件 +def write_two_dimensional_data(x, y, matrix, filename='a'): + with open(filename+'.txt', 'w') as f: + f.write('0 ') + for x0 in x: + f.write(str(x0)+' ') + f.write('\n') + i0 = 0 + for y0 in y: + f.write(str(y0)) + j0 = 0 + for x0 in x: + f.write(' '+str(matrix[i0, j0])+' ') + j0 += 1 + f.write('\n') + i0 += 1 + + +# 5. 画y(x)图，并保存到filename.jpg文件。具体画图格式可在函数中修改。 +def plot(x, y, xlabel='x', ylabel='y', title='', filename='a', show=1, save=0): + import matplotlib.pyplot as plt + fig, ax = plt.subplots() + plt.subplots_adjust(bottom=0.20, left=0.18) + ax.plot(x, y, '-o') + ax.grid() + ax.set_title(title, fontsize=20, fontfamily='Times New Roman') + ax.set_xlabel(xlabel, fontsize=20, fontfamily='Times New Roman') + ax.set_ylabel(ylabel, fontsize=20, fontfamily='Times New Roman') + ax.tick_params(labelsize=20) + labels = ax.get_xticklabels() + ax.get_yticklabels() + [label.set_fontname('Times New Roman') for label in labels] + if save == 1: + plt.savefig(filename+'.jpg', dpi=300) + if show == 1: + plt.show() + plt.close('all') + + + +# 6. 画3d_surface图，并保存到filename.jpg文件。具体画图格式可在函数中修改。 +def plot_3d_surface(x, y, matrix, xlabel='x', ylabel='y', zlabel='z', title='', filename='a', show=1, save=0): + import matplotlib.pyplot as plt + from matplotlib import cm + from matplotlib.ticker import LinearLocator + fig, ax = plt.subplots(subplot_kw={"projection": "3d"}) + plt.subplots_adjust(bottom=0.1, right=0.65) + x, y = np.meshgrid(x, y) + if len(matrix.shape) == 2: + surf = ax.plot_surface(x, y, matrix, cmap=cm.coolwarm, linewidth=0, antialiased=False) + elif len(matrix.shape) == 3: + for i0 in range(matrix.shape[2]): + surf = ax.plot_surface(x, y, matrix[:,:,i0], cmap=cm.coolwarm, linewidth=0, antialiased=False) + ax.set_title(title, fontsize=20, fontfamily='Times New Roman') + ax.set_xlabel(xlabel, fontsize=20, fontfamily='Times New Roman') + ax.set_ylabel(ylabel, fontsize=20, fontfamily='Times New Roman') + ax.set_zlabel(zlabel, fontsize=20, fontfamily='Times New Roman') + ax.zaxis.set_major_locator(LinearLocator(5)) + ax.zaxis.set_major_formatter('{x:.2f}') + ax.tick_params(labelsize=15) + labels = ax.get_xticklabels() + ax.get_yticklabels() + ax.get_zticklabels() + [label.set_fontname('Times New Roman') for label in labels] + cax = plt.axes([0.80, 0.15, 0.05, 0.75]) + cbar = fig.colorbar(surf, cax=cax) + cbar.ax.tick_params(labelsize=15) + for l in cbar.ax.yaxis.get_ticklabels(): + l.set_family('Times New Roman') + if save == 1: + plt.savefig(filename+'.jpg', dpi=300) + if show == 1: + plt.show() + plt.close('all') + + + +# 7. 画plot_contour图，并保存到filename.jpg文件。具体画图格式可在函数中修改。 +def plot_contour(x, y, matrix, xlabel='x', ylabel='y', title='', filename='a', show=1, save=0): + import matplotlib.pyplot as plt + from matplotlib import cm + from matplotlib.ticker import LinearLocator + fig, ax = plt.subplots() + plt.subplots_adjust(bottom=0.2, right=0.75, left = 0.16) + x, y = np.meshgrid(x, y) + contour = ax.contourf(x,y,matrix,cmap='jet') + ax.set_title(title, fontsize=20, fontfamily='Times New Roman') + ax.set_xlabel(xlabel, fontsize=20, fontfamily='Times New Roman') + ax.set_ylabel(ylabel, fontsize=20, fontfamily='Times New Roman') + ax.tick_params(labelsize=15) + labels = ax.get_xticklabels() + ax.get_yticklabels() + [label.set_fontname('Times New Roman') for label in labels] + cax = plt.axes([0.78, 0.17, 0.08, 0.71]) + cbar = fig.colorbar(contour, cax=cax) + cbar.ax.tick_params(labelsize=15) + for l in cbar.ax.yaxis.get_ticklabels(): + l.set_family('Times New Roman') + if save == 1: + plt.savefig(filename+'.jpg', dpi=300) + if show == 1: + plt.show() + plt.close('all') + + +# 8. 画2d_scatter图，并保存到filename.jpg文件。具体画图格式可在函数中修改！ +def plot_2d_scatter(x, y, value, xlabel='x', ylabel='y', title='', filename='a', show=1, save=0): + import matplotlib.pyplot as plt + from matplotlib.axes._axes import _log as matplotlib_axes_logger + matplotlib_axes_logger.setLevel('ERROR') + fig = plt.figure() + ax = fig.add_subplot(111) + plt.subplots_adjust(bottom=0.2, right=0.8, left=0.2) + for i in range(np.array(x).shape[0]): + ax.scatter(x[i], y[i], marker='o', s=100*value[i], c=(1,0,0)) + ax.set_title(title, fontsize=20, fontfamily='Times New Roman') + ax.set_xlabel(xlabel, fontsize=20, fontfamily='Times New Roman') + ax.set_ylabel(ylabel, fontsize=20, fontfamily='Times New Roman') + ax.tick_params(labelsize=15) + labels = ax.get_xticklabels() + ax.get_yticklabels() + [label.set_fontname('Times New Roman') for label in labels] + if save == 1: + plt.savefig(filename+'.jpg', dpi=300) + if show == 1: + plt.show() + plt.close('all') + + +# 9. 画3d_scatter图，并保存到filename.jpg文件。具体画图格式可在函数中修改！ +def plot_3d_scatter(x, y, z, value, xlabel='x', ylabel='y', zlabel='z', title='', filename='a', show=1, save=0): + import matplotlib.pyplot as plt + from matplotlib.ticker import LinearLocator + from matplotlib.axes._axes import _log as matplotlib_axes_logger + matplotlib_axes_logger.setLevel('ERROR') + fig = plt.figure() + ax = fig.add_subplot(111, projection='3d') + plt.subplots_adjust(bottom=0.1, right=0.8) + for i in range(np.array(x).shape[0]): + ax.scatter(x[i], y[i], z[i], marker='o', s=int(100*value[i]), c=(1,0,0)) + ax.set_title(title, fontsize=20, fontfamily='Times New Roman') + ax.set_xlabel(xlabel, fontsize=20, fontfamily='Times New Roman') + ax.set_ylabel(ylabel, fontsize=20, fontfamily='Times New Roman') + ax.set_zlabel(zlabel, fontsize=20, fontfamily='Times New Roman') + ax.tick_params(labelsize=15) + labels = ax.get_xticklabels() + ax.get_yticklabels() + ax.get_zticklabels() + [label.set_fontname('Times New Roman') for label in labels] + if save == 1: + plt.savefig(filename+'.jpg', dpi=300) + if show == 1: + plt.show() + plt.close('all') + + +# 10. 制作动画 +def creat_animation(image_names, duration_time=0.5, filename='a'): + import imageio + images = [] + for name in image_names: + image = name+'.jpg' + im = imageio.imread(image) + images.append(im) + imageio.mimsave(filename+'.gif', images, 'GIF', duration=duration_time) # durantion是延迟时间 + + +# 11. 在参数x下，计算matrix函数的本征值eigenvalue_array[:, index] +def calculate_eigenvalue_with_one_parameter(x, matrix): + dim_x = np.array(x).shape[0] + i0 = 0 + if np.array(matrix(0)).shape==(): + eigenvalue_array = np.zeros((dim_x, 1)) + for x0 in x: + matrix0 = matrix(x0) + eigenvalue_array[i0, 0] = np.real(matrix0) + i0 += 1 + else: + dim = np.array(matrix(0)).shape[0] + eigenvalue_array = np.zeros((dim_x, dim)) + for x0 in x: + matrix0 = matrix(x0) + eigenvalue, eigenvector = np.linalg.eig(matrix0) + eigenvalue_array[i0, :] = np.sort(np.real(eigenvalue[:])) + i0 += 1 + return eigenvalue_array + + +# 12. 在参数(x,y)下，计算matrix函数的本征值eigenvalue_array[:, :, index] +def calculate_eigenvalue_with_two_parameters(x, y, matrix): + dim_x = np.array(x).shape[0] + dim_y = np.array(y).shape[0] + if np.array(matrix(0,0)).shape==(): + eigenvalue_array = np.zeros((dim_y, dim_x, 1)) + i0 = 0 + for y0 in y: + j0 = 0 + for x0 in x: + matrix0 = matrix(x0, y0) + eigenvalue_array[i0, j0, 0] = np.real(matrix0) + j0 += 1 + i0 += 1 + else: + dim = np.array(matrix(0, 0)).shape[0] + eigenvalue_array = np.zeros((dim_y, dim_x, dim)) + i0 = 0 + for y0 in y: + j0 = 0 + for x0 in x: + matrix0 = matrix(x0, y0) + eigenvalue, eigenvector = np.linalg.eig(matrix0) + eigenvalue_array[i0, j0, :] = np.sort(np.real(eigenvalue[:])) + j0 += 1 + i0 += 1 + return eigenvalue_array + + +if __name__ == "__main__": main() \ No newline at end of file