823 lines
33 KiB
Python
823 lines
33 KiB
Python
# Module: data_processing (including figure-plotting and file-reading/writing)
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import guan
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# 导入plt, fig, ax
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@guan.function_decorator
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def import_plt_and_start_fig_ax(adjust_bottom=0.2, adjust_left=0.2, labelsize=20):
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import matplotlib.pyplot as plt
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fig, ax = plt.subplots()
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plt.subplots_adjust(bottom=adjust_bottom, left=adjust_left)
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ax.grid()
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ax.tick_params(labelsize=labelsize)
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labels = ax.get_xticklabels() + ax.get_yticklabels()
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[label.set_fontname('Times New Roman') for label in labels]
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return plt, fig, ax
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# 基于plt, fig, ax画图
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@guan.function_decorator
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def plot_without_starting_fig(plt, fig, ax, x_array, y_array, xlabel='x', ylabel='y', title='', fontsize=20, style='', y_min=None, y_max=None, linewidth=None, markersize=None, color=None):
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if color==None:
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ax.plot(x_array, y_array, style, linewidth=linewidth, markersize=markersize)
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else:
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ax.plot(x_array, y_array, style, linewidth=linewidth, markersize=markersize, color=color)
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ax.set_title(title, fontsize=fontsize, fontfamily='Times New Roman')
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ax.set_xlabel(xlabel, fontsize=fontsize, fontfamily='Times New Roman')
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ax.set_ylabel(ylabel, fontsize=fontsize, fontfamily='Times New Roman')
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if y_min!=None or y_max!=None:
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if y_min==None:
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y_min=min(y_array)
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if y_max==None:
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y_max=max(y_array)
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ax.set_ylim(y_min, y_max)
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# 画图
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@guan.function_decorator
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def plot(x_array, y_array, xlabel='x', ylabel='y', title='', fontsize=20, labelsize=20, show=1, save=0, filename='a', file_format='.jpg', dpi=300, style='', y_min=None, y_max=None, linewidth=None, markersize=None, adjust_bottom=0.2, adjust_left=0.2):
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import guan
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plt, fig, ax = guan.import_plt_and_start_fig_ax(adjust_bottom=adjust_bottom, adjust_left=adjust_left, labelsize=labelsize)
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ax.plot(x_array, y_array, style, linewidth=linewidth, markersize=markersize)
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ax.set_title(title, fontsize=fontsize, fontfamily='Times New Roman')
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ax.set_xlabel(xlabel, fontsize=fontsize, fontfamily='Times New Roman')
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ax.set_ylabel(ylabel, fontsize=fontsize, fontfamily='Times New Roman')
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if y_min!=None or y_max!=None:
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if y_min==None:
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y_min=min(y_array)
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if y_max==None:
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y_max=max(y_array)
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ax.set_ylim(y_min, y_max)
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if save == 1:
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plt.savefig(filename+file_format, dpi=dpi)
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if show == 1:
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plt.show()
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plt.close('all')
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# 一组横坐标数据，两组纵坐标数据画图
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@guan.function_decorator
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def plot_two_array(x_array, y1_array, y2_array, xlabel='x', ylabel='y', title='', fontsize=20, labelsize=20, show=1, save=0, filename='a', file_format='.jpg', dpi=300, style_1='', style_2='', y_min=None, y_max=None, linewidth_1=None, linewidth_2=None, markersize_1=None, markersize_2=None, adjust_bottom=0.2, adjust_left=0.2):
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import guan
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plt, fig, ax = guan.import_plt_and_start_fig_ax(adjust_bottom=adjust_bottom, adjust_left=adjust_left, labelsize=labelsize)
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ax.plot(x_array, y1_array, style_1, linewidth=linewidth_1, markersize=markersize_1)
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ax.plot(x_array, y2_array, style_2, linewidth=linewidth_2, markersize=markersize_2)
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ax.set_title(title, fontsize=fontsize, fontfamily='Times New Roman')
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ax.set_xlabel(xlabel, fontsize=fontsize, fontfamily='Times New Roman')
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ax.set_ylabel(ylabel, fontsize=fontsize, fontfamily='Times New Roman')
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if y_min!=None or y_max!=None:
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if y_min==None:
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y1_min=min(y1_array)
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y2_min=min(y2_array)
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y_min=min([y1_min, y2_min])
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if y_max==None:
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y1_max=max(y1_array)
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y2_max=max(y2_array)
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y_max=max([y1_max, y2_max])
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ax.set_ylim(y_min, y_max)
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if save == 1:
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plt.savefig(filename+file_format, dpi=dpi)
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if show == 1:
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plt.show()
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plt.close('all')
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# 两组横坐标数据，两组纵坐标数据画图
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@guan.function_decorator
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def plot_two_array_with_two_horizontal_array(x1_array, x2_array, y1_array, y2_array, xlabel='x', ylabel='y', title='', fontsize=20, labelsize=20, show=1, save=0, filename='a', file_format='.jpg', dpi=300, style_1='', style_2='', y_min=None, y_max=None, linewidth_1=None, linewidth_2=None, markersize_1=None, markersize_2=None, adjust_bottom=0.2, adjust_left=0.2):
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import guan
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plt, fig, ax = guan.import_plt_and_start_fig_ax(adjust_bottom=adjust_bottom, adjust_left=adjust_left, labelsize=labelsize)
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ax.plot(x1_array, y1_array, style_1, linewidth=linewidth_1, markersize=markersize_1)
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ax.plot(x2_array, y2_array, style_2, linewidth=linewidth_2, markersize=markersize_2)
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ax.set_title(title, fontsize=fontsize, fontfamily='Times New Roman')
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ax.set_xlabel(xlabel, fontsize=fontsize, fontfamily='Times New Roman')
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ax.set_ylabel(ylabel, fontsize=fontsize, fontfamily='Times New Roman')
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if y_min!=None or y_max!=None:
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if y_min==None:
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y1_min=min(y1_array)
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y2_min=min(y2_array)
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y_min=min([y1_min, y2_min])
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if y_max==None:
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y1_max=max(y1_array)
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y2_max=max(y2_array)
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y_max=max([y1_max, y2_max])
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ax.set_ylim(y_min, y_max)
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if save == 1:
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plt.savefig(filename+file_format, dpi=dpi)
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if show == 1:
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plt.show()
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plt.close('all')
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# 一组横坐标数据，三组纵坐标数据画图
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@guan.function_decorator
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def plot_three_array(x_array, y1_array, y2_array, y3_array, xlabel='x', ylabel='y', title='', fontsize=20, labelsize=20, show=1, save=0, filename='a', file_format='.jpg', dpi=300, style_1='', style_2='', style_3='', y_min=None, y_max=None, linewidth_1=None, linewidth_2=None, linewidth_3=None,markersize_1=None, markersize_2=None, markersize_3=None, adjust_bottom=0.2, adjust_left=0.2):
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import guan
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plt, fig, ax = guan.import_plt_and_start_fig_ax(adjust_bottom=adjust_bottom, adjust_left=adjust_left, labelsize=labelsize)
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ax.plot(x_array, y1_array, style_1, linewidth=linewidth_1, markersize=markersize_1)
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ax.plot(x_array, y2_array, style_2, linewidth=linewidth_2, markersize=markersize_2)
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ax.plot(x_array, y3_array, style_3, linewidth=linewidth_3, markersize=markersize_3)
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ax.set_title(title, fontsize=fontsize, fontfamily='Times New Roman')
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ax.set_xlabel(xlabel, fontsize=fontsize, fontfamily='Times New Roman')
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ax.set_ylabel(ylabel, fontsize=fontsize, fontfamily='Times New Roman')
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if y_min!=None or y_max!=None:
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if y_min==None:
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y1_min=min(y1_array)
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y2_min=min(y2_array)
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y3_min=min(y3_array)
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y_min=min([y1_min, y2_min, y3_min])
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if y_max==None:
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y1_max=max(y1_array)
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y2_max=max(y2_array)
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y3_max=max(y3_array)
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y_max=max([y1_max, y2_max, y3_max])
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ax.set_ylim(y_min, y_max)
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if save == 1:
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plt.savefig(filename+file_format, dpi=dpi)
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if show == 1:
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plt.show()
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plt.close('all')
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# 三组横坐标数据，三组纵坐标数据画图
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@guan.function_decorator
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def plot_three_array_with_three_horizontal_array(x1_array, x2_array, x3_array, y1_array, y2_array, y3_array, xlabel='x', ylabel='y', title='', fontsize=20, labelsize=20, show=1, save=0, filename='a', file_format='.jpg', dpi=300, style_1='', style_2='', style_3='', y_min=None, y_max=None, linewidth_1=None, linewidth_2=None, linewidth_3=None,markersize_1=None, markersize_2=None, markersize_3=None, adjust_bottom=0.2, adjust_left=0.2):
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import guan
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plt, fig, ax = guan.import_plt_and_start_fig_ax(adjust_bottom=adjust_bottom, adjust_left=adjust_left, labelsize=labelsize)
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ax.plot(x1_array, y1_array, style_1, linewidth=linewidth_1, markersize=markersize_1)
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ax.plot(x2_array, y2_array, style_2, linewidth=linewidth_2, markersize=markersize_2)
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ax.plot(x3_array, y3_array, style_3, linewidth=linewidth_3, markersize=markersize_3)
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ax.set_title(title, fontsize=fontsize, fontfamily='Times New Roman')
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ax.set_xlabel(xlabel, fontsize=fontsize, fontfamily='Times New Roman')
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ax.set_ylabel(ylabel, fontsize=fontsize, fontfamily='Times New Roman')
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if y_min!=None or y_max!=None:
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if y_min==None:
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y1_min=min(y1_array)
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y2_min=min(y2_array)
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y3_min=min(y3_array)
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y_min=min([y1_min, y2_min, y3_min])
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if y_max==None:
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y1_max=max(y1_array)
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y2_max=max(y2_array)
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y3_max=max(y3_array)
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y_max=max([y1_max, y2_max, y3_max])
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ax.set_ylim(y_min, y_max)
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if save == 1:
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plt.savefig(filename+file_format, dpi=dpi)
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if show == 1:
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plt.show()
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plt.close('all')
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# 画三维图
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@guan.function_decorator
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def plot_3d_surface(x_array, y_array, matrix, xlabel='x', ylabel='y', zlabel='z', title='', fontsize=20, labelsize=15, show=1, save=0, filename='a', file_format='.jpg', dpi=300, z_min=None, z_max=None, rcount=100, ccount=100):
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import numpy as np
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import matplotlib.pyplot as plt
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from matplotlib import cm
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from matplotlib.ticker import LinearLocator
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matrix = np.array(matrix)
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fig, ax = plt.subplots(subplot_kw={"projection": "3d"})
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plt.subplots_adjust(bottom=0.1, right=0.65)
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x_array, y_array = np.meshgrid(x_array, y_array)
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if len(matrix.shape) == 2:
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surf = ax.plot_surface(x_array, y_array, matrix, rcount=rcount, ccount=ccount, cmap=cm.coolwarm, linewidth=0, antialiased=False)
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elif len(matrix.shape) == 3:
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for i0 in range(matrix.shape[2]):
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surf = ax.plot_surface(x_array, y_array, matrix[:,:,i0], rcount=rcount, ccount=ccount, cmap=cm.coolwarm, linewidth=0, antialiased=False)
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ax.set_title(title, fontsize=fontsize, fontfamily='Times New Roman')
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ax.set_xlabel(xlabel, fontsize=fontsize, fontfamily='Times New Roman')
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ax.set_ylabel(ylabel, fontsize=fontsize, fontfamily='Times New Roman')
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ax.set_zlabel(zlabel, fontsize=fontsize, fontfamily='Times New Roman')
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ax.zaxis.set_major_locator(LinearLocator(5))
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ax.zaxis.set_major_formatter('{x:.2f}')
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if z_min!=None or z_max!=None:
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if z_min==None:
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z_min=matrix.min()
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if z_max==None:
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z_max=matrix.max()
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ax.set_zlim(z_min, z_max)
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ax.tick_params(labelsize=labelsize)
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labels = ax.get_xticklabels() + ax.get_yticklabels() + ax.get_zticklabels()
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[label.set_fontname('Times New Roman') for label in labels]
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cax = plt.axes([0.8, 0.1, 0.05, 0.8])
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cbar = fig.colorbar(surf, cax=cax)
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cbar.ax.tick_params(labelsize=labelsize)
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for l in cbar.ax.yaxis.get_ticklabels():
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l.set_family('Times New Roman')
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if save == 1:
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plt.savefig(filename+file_format, dpi=dpi)
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if show == 1:
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plt.show()
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plt.close('all')
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# 画Contour图
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@guan.function_decorator
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def plot_contour(x_array, y_array, matrix, xlabel='x', ylabel='y', title='', fontsize=20, labelsize=15, cmap='jet', levels=None, show=1, save=0, filename='a', file_format='.jpg', dpi=300):
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import numpy as np
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import matplotlib.pyplot as plt
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fig, ax = plt.subplots()
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plt.subplots_adjust(bottom=0.2, right=0.75, left=0.2)
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x_array, y_array = np.meshgrid(x_array, y_array)
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contour = ax.contourf(x_array,y_array,matrix,cmap=cmap, levels=levels)
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ax.set_title(title, fontsize=fontsize, fontfamily='Times New Roman')
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ax.set_xlabel(xlabel, fontsize=fontsize, fontfamily='Times New Roman')
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ax.set_ylabel(ylabel, fontsize=fontsize, fontfamily='Times New Roman')
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ax.tick_params(labelsize=labelsize)
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labels = ax.get_xticklabels() + ax.get_yticklabels()
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[label.set_fontname('Times New Roman') for label in labels]
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cax = plt.axes([0.8, 0.2, 0.05, 0.68])
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cbar = fig.colorbar(contour, cax=cax)
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cbar.ax.tick_params(labelsize=labelsize)
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for l in cbar.ax.yaxis.get_ticklabels():
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l.set_family('Times New Roman')
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if save == 1:
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plt.savefig(filename+file_format, dpi=dpi)
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if show == 1:
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plt.show()
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plt.close('all')
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# 画棋盘图/伪彩色图
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@guan.function_decorator
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def plot_pcolor(x_array, y_array, matrix, xlabel='x', ylabel='y', title='', fontsize=20, labelsize=15, cmap='jet', levels=None, show=1, save=0, filename='a', file_format='.jpg', dpi=300):
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import numpy as np
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import matplotlib.pyplot as plt
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fig, ax = plt.subplots()
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plt.subplots_adjust(bottom=0.2, right=0.75, left=0.2)
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x_array, y_array = np.meshgrid(x_array, y_array)
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contour = ax.pcolor(x_array,y_array,matrix, cmap=cmap)
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ax.set_title(title, fontsize=fontsize, fontfamily='Times New Roman')
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ax.set_xlabel(xlabel, fontsize=fontsize, fontfamily='Times New Roman')
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ax.set_ylabel(ylabel, fontsize=fontsize, fontfamily='Times New Roman')
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ax.tick_params(labelsize=labelsize)
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labels = ax.get_xticklabels() + ax.get_yticklabels()
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[label.set_fontname('Times New Roman') for label in labels]
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cax = plt.axes([0.8, 0.2, 0.05, 0.68])
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cbar = fig.colorbar(contour, cax=cax)
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cbar.ax.tick_params(labelsize=labelsize)
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for l in cbar.ax.yaxis.get_ticklabels():
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l.set_family('Times New Roman')
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if save == 1:
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plt.savefig(filename+file_format, dpi=dpi)
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if show == 1:
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plt.show()
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plt.close('all')
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# 通过坐标画点和线
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@guan.function_decorator
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def draw_dots_and_lines(coordinate_array, draw_dots=1, draw_lines=1, max_distance=1.1, line_style='-k', linewidth=1, dot_style='ro', markersize=3, show=1, save=0, filename='a', file_format='.eps', dpi=300):
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import numpy as np
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import matplotlib.pyplot as plt
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coordinate_array = np.array(coordinate_array)
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print(coordinate_array.shape)
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x_range = max(coordinate_array[:, 0])-min(coordinate_array[:, 0])
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y_range = max(coordinate_array[:, 1])-min(coordinate_array[:, 1])
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fig, ax = plt.subplots(figsize=(6*x_range/y_range,6))
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plt.subplots_adjust(left=0, bottom=0, right=1, top=1)
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plt.axis('off')
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if draw_lines==1:
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for i1 in range(coordinate_array.shape[0]):
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for i2 in range(coordinate_array.shape[0]):
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if np.sqrt((coordinate_array[i1, 0] - coordinate_array[i2, 0])**2+(coordinate_array[i1, 1] - coordinate_array[i2, 1])**2) < max_distance:
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ax.plot([coordinate_array[i1, 0], coordinate_array[i2, 0]], [coordinate_array[i1, 1], coordinate_array[i2, 1]], line_style, linewidth=linewidth)
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if draw_dots==1:
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for i in range(coordinate_array.shape[0]):
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ax.plot(coordinate_array[i, 0], coordinate_array[i, 1], dot_style, markersize=markersize)
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if show==1:
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plt.show()
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if save==1:
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if file_format=='.eps':
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plt.savefig(filename+file_format)
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else:
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plt.savefig(filename+file_format, dpi=dpi)
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# 合并两个图片
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@guan.function_decorator
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def combine_two_images(image_path_array, figsize=(16,8), show=0, save=1, filename='a', file_format='.jpg', dpi=300):
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import numpy as np
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num = np.array(image_path_array).shape[0]
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if num != 2:
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print('Error: The number of images should be two!')
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else:
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import matplotlib.pyplot as plt
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import matplotlib.image as mpimg
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fig = plt.figure(figsize=figsize)
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plt.subplots_adjust(left=0, right=1, bottom=0, top=1, wspace=0, hspace=0)
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ax1 = fig.add_subplot(121)
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ax2 = fig.add_subplot(122)
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image_1 = mpimg.imread(image_path_array[0])
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image_2 = mpimg.imread(image_path_array[1])
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ax1.imshow(image_1)
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ax2.imshow(image_2)
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ax1.axis('off')
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ax2.axis('off')
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if show == 1:
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plt.show()
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if save == 1:
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plt.savefig(filename+file_format, dpi=dpi)
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plt.close('all')
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# 合并三个图片
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@guan.function_decorator
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def combine_three_images(image_path_array, figsize=(16,5), show=0, save=1, filename='a', file_format='.jpg', dpi=300):
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import numpy as np
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num = np.array(image_path_array).shape[0]
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if num != 3:
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print('Error: The number of images should be three!')
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else:
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import matplotlib.pyplot as plt
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import matplotlib.image as mpimg
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fig = plt.figure(figsize=figsize)
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plt.subplots_adjust(left=0, right=1, bottom=0, top=1, wspace=0, hspace=0)
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ax1 = fig.add_subplot(131)
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ax2 = fig.add_subplot(132)
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ax3 = fig.add_subplot(133)
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image_1 = mpimg.imread(image_path_array[0])
|
||
image_2 = mpimg.imread(image_path_array[1])
|
||
image_3 = mpimg.imread(image_path_array[2])
|
||
ax1.imshow(image_1)
|
||
ax2.imshow(image_2)
|
||
ax3.imshow(image_3)
|
||
ax1.axis('off')
|
||
ax2.axis('off')
|
||
ax3.axis('off')
|
||
if show == 1:
|
||
plt.show()
|
||
if save == 1:
|
||
plt.savefig(filename+file_format, dpi=dpi)
|
||
plt.close('all')
|
||
|
||
# 合并四个图片
|
||
@guan.function_decorator
|
||
def combine_four_images(image_path_array, figsize=(16,16), show=0, save=1, filename='a', file_format='.jpg', dpi=300):
|
||
import numpy as np
|
||
num = np.array(image_path_array).shape[0]
|
||
if num != 4:
|
||
print('Error: The number of images should be four!')
|
||
else:
|
||
import matplotlib.pyplot as plt
|
||
import matplotlib.image as mpimg
|
||
fig = plt.figure(figsize=figsize)
|
||
plt.subplots_adjust(left=0, right=1, bottom=0, top=1, wspace=0, hspace=0)
|
||
ax1 = fig.add_subplot(221)
|
||
ax2 = fig.add_subplot(222)
|
||
ax3 = fig.add_subplot(223)
|
||
ax4 = fig.add_subplot(224)
|
||
image_1 = mpimg.imread(image_path_array[0])
|
||
image_2 = mpimg.imread(image_path_array[1])
|
||
image_3 = mpimg.imread(image_path_array[2])
|
||
image_4 = mpimg.imread(image_path_array[3])
|
||
ax1.imshow(image_1)
|
||
ax2.imshow(image_2)
|
||
ax3.imshow(image_3)
|
||
ax4.imshow(image_4)
|
||
ax1.axis('off')
|
||
ax2.axis('off')
|
||
ax3.axis('off')
|
||
ax4.axis('off')
|
||
if show == 1:
|
||
plt.show()
|
||
if save == 1:
|
||
plt.savefig(filename+file_format, dpi=dpi)
|
||
plt.close('all')
|
||
|
||
# 对某个目录中的txt文件批量读取和画图
|
||
@guan.function_decorator
|
||
def batch_reading_and_plotting(directory, xlabel='x', ylabel='y'):
|
||
import re
|
||
import os
|
||
import guan
|
||
for root, dirs, files in os.walk(directory):
|
||
for file in files:
|
||
if re.search('^txt.', file[::-1]):
|
||
filename = file[:-4]
|
||
x_array, y_array = guan.read_one_dimensional_data(filename=filename)
|
||
guan.plot(x_array, y_array, xlabel=xlabel, ylabel=ylabel, title=filename, show=0, save=1, filename=filename)
|
||
|
||
# 将图片制作GIF动画
|
||
@guan.function_decorator
|
||
def make_gif(image_path_array, filename='a', duration=0.1):
|
||
import imageio
|
||
images = []
|
||
for image_path in image_path_array:
|
||
im = imageio.imread(image_path)
|
||
images.append(im)
|
||
imageio.mimsave(filename+'.gif', images, 'GIF', duration=duration)
|
||
|
||
# 选取Matplotlib颜色
|
||
@guan.function_decorator
|
||
def color_matplotlib():
|
||
color_array = ['tab:blue', 'tab:orange', 'tab:green', 'tab:red', 'tab:purple', 'tab:brown', 'tab:pink', 'tab:gray', 'tab:olive', 'tab:cyan']
|
||
return color_array
|
||
|
||
# 将变量存到文件
|
||
@guan.function_decorator
|
||
def dump_data(data, filename, file_format='.txt'):
|
||
import pickle
|
||
with open(filename+file_format, 'wb') as f:
|
||
pickle.dump(data, f)
|
||
|
||
# 从文件中恢复数据到变量
|
||
@guan.function_decorator
|
||
def load_data(filename, file_format='.txt'):
|
||
import pickle
|
||
with open(filename+file_format, 'rb') as f:
|
||
data = pickle.load(f)
|
||
return data
|
||
|
||
# 读取文件中的一维数据（一行一组x和y）
|
||
@guan.function_decorator
|
||
def read_one_dimensional_data(filename='a', file_format='.txt'):
|
||
import numpy as np
|
||
f = open(filename+file_format, 'r')
|
||
text = f.read()
|
||
f.close()
|
||
row_list = np.array(text.split('\n'))
|
||
dim_column = np.array(row_list[0].split()).shape[0]
|
||
x_array = np.array([])
|
||
y_array = np.array([])
|
||
for row in row_list:
|
||
column = np.array(row.split())
|
||
if column.shape[0] != 0:
|
||
x_array = np.append(x_array, [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_array).shape[0] == 0:
|
||
y_array = [y_row]
|
||
else:
|
||
y_array = np.append(y_array, [y_row], axis=0)
|
||
return x_array, y_array
|
||
|
||
# 读取文件中的一维数据（一行一组x和y）（支持复数形式）
|
||
@guan.function_decorator
|
||
def read_one_dimensional_complex_data(filename='a', file_format='.txt'):
|
||
import numpy as np
|
||
f = open(filename+file_format, 'r')
|
||
text = f.read()
|
||
f.close()
|
||
row_list = np.array(text.split('\n'))
|
||
dim_column = np.array(row_list[0].split()).shape[0]
|
||
x_array = np.array([])
|
||
y_array = np.array([])
|
||
for row in row_list:
|
||
column = np.array(row.split())
|
||
if column.shape[0] != 0:
|
||
x_array = np.append(x_array, [complex(column[0])], axis=0)
|
||
y_row = np.zeros(dim_column-1, dtype=complex)
|
||
for dim0 in range(dim_column-1):
|
||
y_row[dim0] = complex(column[dim0+1])
|
||
if np.array(y_array).shape[0] == 0:
|
||
y_array = [y_row]
|
||
else:
|
||
y_array = np.append(y_array, [y_row], axis=0)
|
||
return x_array, y_array
|
||
|
||
# 读取文件中的二维数据（第一行和第一列分别为横纵坐标）
|
||
@guan.function_decorator
|
||
def read_two_dimensional_data(filename='a', file_format='.txt'):
|
||
import numpy as np
|
||
f = open(filename+file_format, 'r')
|
||
text = f.read()
|
||
f.close()
|
||
row_list = np.array(text.split('\n'))
|
||
dim_column = np.array(row_list[0].split()).shape[0]
|
||
x_array = np.array([])
|
||
y_array = 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_array = np.zeros(x_str.shape[0])
|
||
for i00 in range(x_str.shape[0]):
|
||
x_array[i00] = float(x_str[i00])
|
||
elif column.shape[0] != 0:
|
||
y_array = np.append(y_array, [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_array, y_array, matrix
|
||
|
||
# 读取文件中的二维数据（第一行和第一列分别为横纵坐标）（支持复数形式）
|
||
@guan.function_decorator
|
||
def read_two_dimensional_complex_data(filename='a', file_format='.txt'):
|
||
import numpy as np
|
||
f = open(filename+file_format, 'r')
|
||
text = f.read()
|
||
f.close()
|
||
row_list = np.array(text.split('\n'))
|
||
dim_column = np.array(row_list[0].split()).shape[0]
|
||
x_array = np.array([])
|
||
y_array = 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_array = np.zeros(x_str.shape[0], dtype=complex)
|
||
for i00 in range(x_str.shape[0]):
|
||
x_array[i00] = complex(x_str[i00])
|
||
elif column.shape[0] != 0:
|
||
y_array = np.append(y_array, [complex(column[0])], axis=0)
|
||
matrix_row = np.zeros(dim_column-1, dtype=complex)
|
||
for dim0 in range(dim_column-1):
|
||
matrix_row[dim0] = complex(column[dim0+1])
|
||
if np.array(matrix).shape[0] == 0:
|
||
matrix = [matrix_row]
|
||
else:
|
||
matrix = np.append(matrix, [matrix_row], axis=0)
|
||
return x_array, y_array, matrix
|
||
|
||
# 读取文件中的二维数据（不包括x和y）
|
||
@guan.function_decorator
|
||
def read_two_dimensional_data_without_xy_array(filename='a', file_format='.txt'):
|
||
import numpy as np
|
||
matrix = np.loadtxt(filename+file_format)
|
||
return matrix
|
||
|
||
# 打开文件用于新增内容
|
||
@guan.function_decorator
|
||
def open_file(filename='a', file_format='.txt'):
|
||
f = open(filename+file_format, 'a', encoding='UTF-8')
|
||
return f
|
||
|
||
# 在文件中写入一维数据（一行一组x和y）
|
||
@guan.function_decorator
|
||
def write_one_dimensional_data(x_array, y_array, filename='a', file_format='.txt'):
|
||
import guan
|
||
with open(filename+file_format, 'w', encoding='UTF-8') as f:
|
||
guan.write_one_dimensional_data_without_opening_file(x_array, y_array, f)
|
||
|
||
# 在文件中写入一维数据（一行一组x和y）（需要输入已打开的文件）
|
||
@guan.function_decorator
|
||
def write_one_dimensional_data_without_opening_file(x_array, y_array, f):
|
||
import numpy as np
|
||
x_array = np.array(x_array)
|
||
y_array = np.array(y_array)
|
||
i0 = 0
|
||
for x0 in x_array:
|
||
f.write(str(x0)+' ')
|
||
if len(y_array.shape) == 1:
|
||
f.write(str(y_array[i0])+'\n')
|
||
elif len(y_array.shape) == 2:
|
||
for j0 in range(y_array.shape[1]):
|
||
f.write(str(y_array[i0, j0])+' ')
|
||
f.write('\n')
|
||
i0 += 1
|
||
|
||
# 在文件中写入二维数据（第一行和第一列分别为横纵坐标）
|
||
@guan.function_decorator
|
||
def write_two_dimensional_data(x_array, y_array, matrix, filename='a', file_format='.txt'):
|
||
import guan
|
||
with open(filename+file_format, 'w', encoding='UTF-8') as f:
|
||
guan.write_two_dimensional_data_without_opening_file(x_array, y_array, matrix, f)
|
||
|
||
# 在文件中写入二维数据（第一行和第一列分别为横纵坐标）（需要输入已打开的文件）
|
||
@guan.function_decorator
|
||
def write_two_dimensional_data_without_opening_file(x_array, y_array, matrix, f):
|
||
import numpy as np
|
||
x_array = np.array(x_array)
|
||
y_array = np.array(y_array)
|
||
matrix = np.array(matrix)
|
||
f.write('0 ')
|
||
for x0 in x_array:
|
||
f.write(str(x0)+' ')
|
||
f.write('\n')
|
||
i0 = 0
|
||
for y0 in y_array:
|
||
f.write(str(y0))
|
||
j0 = 0
|
||
for x0 in x_array:
|
||
f.write(' '+str(matrix[i0, j0])+' ')
|
||
j0 += 1
|
||
f.write('\n')
|
||
i0 += 1
|
||
|
||
# 在文件中写入二维数据（不包括x和y）
|
||
@guan.function_decorator
|
||
def write_two_dimensional_data_without_xy_array(matrix, filename='a', file_format='.txt'):
|
||
import guan
|
||
with open(filename+file_format, 'w', encoding='UTF-8') as f:
|
||
guan.write_two_dimensional_data_without_xy_array_and_without_opening_file(matrix, f)
|
||
|
||
# 在文件中写入二维数据（不包括x和y）（需要输入已打开的文件）
|
||
@guan.function_decorator
|
||
def write_two_dimensional_data_without_xy_array_and_without_opening_file(matrix, f):
|
||
for row in matrix:
|
||
for element in row:
|
||
f.write(str(element)+' ')
|
||
f.write('\n')
|
||
import guan
|
||
|
||
# 以显示编号的样式，打印数组
|
||
@guan.function_decorator
|
||
def print_array_with_index(array, show_index=1, index_type=0):
|
||
if show_index==0:
|
||
for i0 in array:
|
||
print(i0)
|
||
else:
|
||
if index_type==0:
|
||
index = 0
|
||
for i0 in array:
|
||
print(index, i0)
|
||
index += 1
|
||
else:
|
||
index = 0
|
||
for i0 in array:
|
||
index += 1
|
||
print(index, i0)
|
||
|
||
# 获取目录中的所有文件名
|
||
@guan.function_decorator
|
||
def get_all_filenames_in_directory(directory='./', file_format=None):
|
||
import os
|
||
file_list = []
|
||
for root, dirs, files in os.walk(directory):
|
||
for i0 in range(len(files)):
|
||
if file_format == None:
|
||
file_list.append(files[i0])
|
||
else:
|
||
if file_format in files[i0]:
|
||
file_list.append(files[i0])
|
||
return file_list
|
||
|
||
# 读取文件夹中某种文本类型的文件路径和内容
|
||
@guan.function_decorator
|
||
def read_text_files_in_directory(directory='./', file_format='.md'):
|
||
import os
|
||
file_list = []
|
||
for root, dirs, files in os.walk(directory):
|
||
for i0 in range(len(files)):
|
||
if file_format in files[i0]:
|
||
file_list.append(root+'/'+files[i0])
|
||
content_array = []
|
||
for file in file_list:
|
||
with open(file, 'r') as f:
|
||
content_array.append(f.read())
|
||
return file_list, content_array
|
||
|
||
# 在多个文本文件中查找关键词
|
||
@guan.function_decorator
|
||
def find_words_in_multiple_files(words, directory='./', file_format='.md'):
|
||
import guan
|
||
file_list, content_array = guan.read_text_files_in_directory(directory=directory, file_format=file_format)
|
||
num_files = len(file_list)
|
||
file_list_with_words = []
|
||
for i0 in range(num_files):
|
||
if words in content_array[i0]:
|
||
file_list_with_words.append(file_list[i0])
|
||
return file_list_with_words
|
||
|
||
# 并行计算前的预处理，把参数分成多份
|
||
@guan.function_decorator
|
||
def preprocess_for_parallel_calculations(parameter_array_all, cpus=1, task_index=0):
|
||
import numpy as np
|
||
num_all = np.array(parameter_array_all).shape[0]
|
||
if num_all%cpus == 0:
|
||
num_parameter = int(num_all/cpus)
|
||
parameter_array = parameter_array_all[task_index*num_parameter:(task_index+1)*num_parameter]
|
||
else:
|
||
num_parameter = int(num_all/(cpus-1))
|
||
if task_index != cpus-1:
|
||
parameter_array = parameter_array_all[task_index*num_parameter:(task_index+1)*num_parameter]
|
||
else:
|
||
parameter_array = parameter_array_all[task_index*num_parameter:num_all]
|
||
return parameter_array
|
||
|
||
# 随机获得一个整数，左闭右闭
|
||
@guan.function_decorator
|
||
def get_random_number(start=0, end=1):
|
||
import random
|
||
rand_number = random.randint(start, end) # 左闭右闭 [start, end]
|
||
return rand_number
|
||
|
||
# 选取一个种子生成固定的随机整数
|
||
@guan.function_decorator
|
||
def generate_random_int_number_for_a_specific_seed(seed=0, x_min=0, x_max=10):
|
||
import numpy as np
|
||
np.random.seed(seed)
|
||
rand_num = np.random.randint(x_min, x_max) # 左闭右开[x_min, x_max)
|
||
return rand_num
|
||
|
||
# 使用jieba软件包进行分词
|
||
@guan.function_decorator
|
||
def divide_text_into_words(text):
|
||
import jieba
|
||
words = jieba.lcut(text)
|
||
return words
|
||
|
||
# 判断某个字符是中文还是英文或其他
|
||
@guan.function_decorator
|
||
def check_Chinese_or_English(a):
|
||
if '\u4e00' <= a <= '\u9fff' :
|
||
word_type = 'Chinese'
|
||
elif '\x00' <= a <= '\xff':
|
||
word_type = 'English'
|
||
else:
|
||
word_type = 'Others'
|
||
return word_type
|
||
|
||
# 统计中英文文本的字数，默认不包括空格
|
||
@guan.function_decorator
|
||
def count_words(text, include_space=0, show_words=0):
|
||
import jieba
|
||
import guan
|
||
words = jieba.lcut(text)
|
||
new_words = []
|
||
if include_space == 0:
|
||
for word in words:
|
||
if word != ' ':
|
||
new_words.append(word)
|
||
else:
|
||
new_words = words
|
||
num_words = 0
|
||
new_words_2 = []
|
||
for word in new_words:
|
||
word_type = guan.check_Chinese_or_English(word[0])
|
||
if word_type == 'Chinese':
|
||
num_words += len(word)
|
||
for one_word in word:
|
||
new_words_2.append(one_word)
|
||
elif word_type == 'English' or 'Others':
|
||
num_words += 1
|
||
new_words_2.append(word)
|
||
if show_words == 1:
|
||
print(new_words_2)
|
||
return num_words
|
||
|
||
# 将RGB转成HEX
|
||
@guan.function_decorator
|
||
def rgb_to_hex(rgb, pound=1):
|
||
if pound==0:
|
||
return '%02x%02x%02x' % rgb
|
||
else:
|
||
return '#%02x%02x%02x' % rgb
|
||
|
||
# 将HEX转成RGB
|
||
@guan.function_decorator
|
||
def hex_to_rgb(hex):
|
||
hex = hex.lstrip('#')
|
||
length = len(hex)
|
||
return tuple(int(hex[i:i+length//3], 16) for i in range(0, length, length//3))
|
||
|
||
# 使用MD5进行散列加密
|
||
@guan.function_decorator
|
||
def encryption_MD5(password, salt=''):
|
||
import hashlib
|
||
password = salt+password
|
||
hashed_password = hashlib.md5(password.encode()).hexdigest()
|
||
return hashed_password
|
||
|
||
# 使用SHA-256进行散列加密
|
||
@guan.function_decorator
|
||
def encryption_SHA_256(password, salt=''):
|
||
import hashlib
|
||
password = salt+password
|
||
hashed_password = hashlib.sha256(password.encode()).hexdigest()
|
||
return hashed_password
|
||
|
||
# 自动先后运行程序
|
||
@guan.function_decorator
|
||
def run_programs_sequentially(program_files=['./a.py', './b.py'], execute='python ', show_time=0):
|
||
import os
|
||
import time
|
||
if show_time == 1:
|
||
start = time.time()
|
||
i0 = 0
|
||
for program_file in program_files:
|
||
i0 += 1
|
||
if show_time == 1:
|
||
start_0 = time.time()
|
||
os.system(execute+program_file)
|
||
if show_time == 1:
|
||
end_0 = time.time()
|
||
print('Running time of program_'+str(i0)+' = '+str((end_0-start_0)/60)+' min')
|
||
if show_time == 1:
|
||
end = time.time()
|
||
print('Total running time = '+str((end-start)/60)+' min')
|
||
|
||
# 如果不存在文件夹，则新建文件夹
|
||
@guan.function_decorator
|
||
def make_directory(directory='./test'):
|
||
import os
|
||
if not os.path.exists(directory):
|
||
os.makedirs(directory)
|
||
|
||
# 复制一份文件
|
||
@guan.function_decorator
|
||
def copy_file(file1='./a.txt', file2='./b.txt'):
|
||
import shutil
|
||
shutil.copy(file1, file2)
|
||
|
||
# 拼接两个PDF文件
|
||
@guan.function_decorator
|
||
def combine_two_pdf_files(input_file_1='a.pdf', input_file_2='b.pdf', output_file='combined_file.pdf'):
|
||
import PyPDF2
|
||
output_pdf = PyPDF2.PdfWriter()
|
||
with open(input_file_1, 'rb') as file1:
|
||
pdf1 = PyPDF2.PdfReader(file1)
|
||
for page in range(len(pdf1.pages)):
|
||
output_pdf.add_page(pdf1.pages[page])
|
||
with open(input_file_2, 'rb') as file2:
|
||
pdf2 = PyPDF2.PdfReader(file2)
|
||
for page in range(len(pdf2.pages)):
|
||
output_pdf.add_page(pdf2.pages[page])
|
||
with open(output_file, 'wb') as combined_file:
|
||
output_pdf.write(combined_file) |