diff --git a/PyPI/setup.cfg b/PyPI/setup.cfg index 58ab677..c616c23 100644 --- a/PyPI/setup.cfg +++ b/PyPI/setup.cfg @@ -1,7 +1,7 @@ [metadata] # replace with your username: name = guan -version = 0.1.74 +version = 0.1.75 author = guanjihuan author_email = guanjihuan@163.com description = An open source python package diff --git a/PyPI/src/guan.egg-info/PKG-INFO b/PyPI/src/guan.egg-info/PKG-INFO index 3c202b2..5f42383 100644 --- a/PyPI/src/guan.egg-info/PKG-INFO +++ b/PyPI/src/guan.egg-info/PKG-INFO @@ -1,6 +1,6 @@ Metadata-Version: 2.1 Name: guan -Version: 0.1.74 +Version: 0.1.75 Summary: An open source python package Home-page: https://py.guanjihuan.com Author: guanjihuan diff --git a/PyPI/src/guan.egg-info/SOURCES.txt b/PyPI/src/guan.egg-info/SOURCES.txt index 3f3f35a..188ccab 100644 --- a/PyPI/src/guan.egg-info/SOURCES.txt +++ b/PyPI/src/guan.egg-info/SOURCES.txt @@ -9,7 +9,10 @@ src/guan/__init__.py src/guan/band_structures_and_wave_functions.py src/guan/basic_functions.py src/guan/data_processing.py +src/guan/decorator.py src/guan/density_of_states.py +src/guan/figure_plotting.py +src/guan/file_reading_and_writing.py src/guan/machine_learning.py src/guan/others.py src/guan/quantum_transport.py diff --git a/PyPI/src/guan/__init__.py b/PyPI/src/guan/__init__.py index d90b52f..cb84d55 100644 --- a/PyPI/src/guan/__init__.py +++ b/PyPI/src/guan/__init__.py @@ -1,47 +1,6 @@ # Guan is an open-source python package developed and maintained by https://www.guanjihuan.com/about (Ji-Huan Guan, 关济寰). The primary location of this package is on website https://py.guanjihuan.com. The GitHub location of this package is on https://github.com/guanjihuan/py.guanjihuan.com. -# 函数的装饰器，用于获取计算时间（秒） -def timer_decorator(func): - import time - def wrapper(*args, **kwargs): - start = time.time() - result = func(*args, **kwargs) - end = time.time() - print(f"Running time of {func.__name__}: {end - start} seconds") - return result - return wrapper - -# 函数的装饰器，用于获取计算时间（分） -def timer_decorator_minutes(func): - import time - def wrapper(*args, **kwargs): - start = time.time() - result = func(*args, **kwargs) - end = time.time() - print(f"Running time of {func.__name__}: {(end - start)/60} minutes") - return result - return wrapper - -# 函数的装饰器，用于获取计算时间（时） -def timer_decorator_hours(func): - import time - def wrapper(*args, **kwargs): - start = time.time() - result = func(*args, **kwargs) - end = time.time() - print(f"Running time of {func.__name__}: {(end - start)/3600} hours") - return result - return wrapper - -# 函数的装饰器，用于GUAN软件包的统计 -def statistics_decorator(func): - def wrapper(*args, **kwargs): - result = func(*args, **kwargs) - import guan - guan.statistics_of_guan_package(func.__name__) - return result - return wrapper - +from .decorator import * from .basic_functions import * from .Fourier_transform import * from .Hamiltonian_of_examples import * @@ -51,5 +10,7 @@ from .density_of_states import * from .quantum_transport import * from .topological_invariant import * from .machine_learning import * +from .file_reading_and_writing import * +from .figure_plotting import * from .data_processing import * from .others import * \ No newline at end of file diff --git a/PyPI/src/guan/data_processing.py b/PyPI/src/guan/data_processing.py index 2ef7dda..5a07732 100644 --- a/PyPI/src/guan/data_processing.py +++ b/PyPI/src/guan/data_processing.py @@ -1,713 +1,6 @@ -# Module: data_processing (including figure-plotting and file-reading/writing) +# Module: data_processing import guan -# 导入plt, fig, ax -@guan.statistics_decorator -def import_plt_and_start_fig_ax(adjust_bottom=0.2, adjust_left=0.2, labelsize=20): - import matplotlib.pyplot as plt - fig, ax = plt.subplots() - plt.subplots_adjust(bottom=adjust_bottom, left=adjust_left) - ax.grid() - ax.tick_params(labelsize=labelsize) - labels = ax.get_xticklabels() + ax.get_yticklabels() - [label.set_fontname('Times New Roman') for label in labels] - return plt, fig, ax - -# 基于plt, fig, ax画图 -@guan.statistics_decorator -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): - if color==None: - ax.plot(x_array, y_array, style, linewidth=linewidth, markersize=markersize) - else: - ax.plot(x_array, y_array, style, linewidth=linewidth, markersize=markersize, color=color) - ax.set_title(title, fontsize=fontsize, fontfamily='Times New Roman') - ax.set_xlabel(xlabel, fontsize=fontsize, fontfamily='Times New Roman') - ax.set_ylabel(ylabel, fontsize=fontsize, fontfamily='Times New Roman') - if y_min!=None or y_max!=None: - if y_min==None: - y_min=min(y_array) - if y_max==None: - y_max=max(y_array) - ax.set_ylim(y_min, y_max) - -# 画图 -@guan.statistics_decorator -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): - import guan - plt, fig, ax = guan.import_plt_and_start_fig_ax(adjust_bottom=adjust_bottom, adjust_left=adjust_left, labelsize=labelsize) - ax.plot(x_array, y_array, style, linewidth=linewidth, markersize=markersize) - ax.set_title(title, fontsize=fontsize, fontfamily='Times New Roman') - ax.set_xlabel(xlabel, fontsize=fontsize, fontfamily='Times New Roman') - ax.set_ylabel(ylabel, fontsize=fontsize, fontfamily='Times New Roman') - if y_min!=None or y_max!=None: - if y_min==None: - y_min=min(y_array) - if y_max==None: - y_max=max(y_array) - ax.set_ylim(y_min, y_max) - if save == 1: - plt.savefig(filename+file_format, dpi=dpi) - if show == 1: - plt.show() - plt.close('all') - -# 一组横坐标数据，两组纵坐标数据画图 -@guan.statistics_decorator -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): - import guan - plt, fig, ax = guan.import_plt_and_start_fig_ax(adjust_bottom=adjust_bottom, adjust_left=adjust_left, labelsize=labelsize) - ax.plot(x_array, y1_array, style_1, linewidth=linewidth_1, markersize=markersize_1) - ax.plot(x_array, y2_array, style_2, linewidth=linewidth_2, markersize=markersize_2) - ax.set_title(title, fontsize=fontsize, fontfamily='Times New Roman') - ax.set_xlabel(xlabel, fontsize=fontsize, fontfamily='Times New Roman') - ax.set_ylabel(ylabel, fontsize=fontsize, fontfamily='Times New Roman') - if y_min!=None or y_max!=None: - if y_min==None: - y1_min=min(y1_array) - y2_min=min(y2_array) - y_min=min([y1_min, y2_min]) - if y_max==None: - y1_max=max(y1_array) - y2_max=max(y2_array) - y_max=max([y1_max, y2_max]) - ax.set_ylim(y_min, y_max) - if save == 1: - plt.savefig(filename+file_format, dpi=dpi) - if show == 1: - plt.show() - plt.close('all') - -# 两组横坐标数据，两组纵坐标数据画图 -@guan.statistics_decorator -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): - import guan - plt, fig, ax = guan.import_plt_and_start_fig_ax(adjust_bottom=adjust_bottom, adjust_left=adjust_left, labelsize=labelsize) - ax.plot(x1_array, y1_array, style_1, linewidth=linewidth_1, markersize=markersize_1) - ax.plot(x2_array, y2_array, style_2, linewidth=linewidth_2, markersize=markersize_2) - ax.set_title(title, fontsize=fontsize, fontfamily='Times New Roman') - ax.set_xlabel(xlabel, fontsize=fontsize, fontfamily='Times New Roman') - ax.set_ylabel(ylabel, fontsize=fontsize, fontfamily='Times New Roman') - if y_min!=None or y_max!=None: - if y_min==None: - y1_min=min(y1_array) - y2_min=min(y2_array) - y_min=min([y1_min, y2_min]) - if y_max==None: - y1_max=max(y1_array) - y2_max=max(y2_array) - y_max=max([y1_max, y2_max]) - ax.set_ylim(y_min, y_max) - if save == 1: - plt.savefig(filename+file_format, dpi=dpi) - if show == 1: - plt.show() - plt.close('all') - -# 一组横坐标数据，三组纵坐标数据画图 -@guan.statistics_decorator -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): - import guan - plt, fig, ax = guan.import_plt_and_start_fig_ax(adjust_bottom=adjust_bottom, adjust_left=adjust_left, labelsize=labelsize) - ax.plot(x_array, y1_array, style_1, linewidth=linewidth_1, markersize=markersize_1) - ax.plot(x_array, y2_array, style_2, linewidth=linewidth_2, markersize=markersize_2) - ax.plot(x_array, y3_array, style_3, linewidth=linewidth_3, markersize=markersize_3) - ax.set_title(title, fontsize=fontsize, fontfamily='Times New Roman') - ax.set_xlabel(xlabel, fontsize=fontsize, fontfamily='Times New Roman') - ax.set_ylabel(ylabel, fontsize=fontsize, fontfamily='Times New Roman') - if y_min!=None or y_max!=None: - if y_min==None: - y1_min=min(y1_array) - y2_min=min(y2_array) - y3_min=min(y3_array) - y_min=min([y1_min, y2_min, y3_min]) - if y_max==None: - y1_max=max(y1_array) - y2_max=max(y2_array) - y3_max=max(y3_array) - y_max=max([y1_max, y2_max, y3_max]) - ax.set_ylim(y_min, y_max) - if save == 1: - plt.savefig(filename+file_format, dpi=dpi) - if show == 1: - plt.show() - plt.close('all') - -# 三组横坐标数据，三组纵坐标数据画图 -@guan.statistics_decorator -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): - import guan - plt, fig, ax = guan.import_plt_and_start_fig_ax(adjust_bottom=adjust_bottom, adjust_left=adjust_left, labelsize=labelsize) - ax.plot(x1_array, y1_array, style_1, linewidth=linewidth_1, markersize=markersize_1) - ax.plot(x2_array, y2_array, style_2, linewidth=linewidth_2, markersize=markersize_2) - ax.plot(x3_array, y3_array, style_3, linewidth=linewidth_3, markersize=markersize_3) - ax.set_title(title, fontsize=fontsize, fontfamily='Times New Roman') - ax.set_xlabel(xlabel, fontsize=fontsize, fontfamily='Times New Roman') - ax.set_ylabel(ylabel, fontsize=fontsize, fontfamily='Times New Roman') - if y_min!=None or y_max!=None: - if y_min==None: - y1_min=min(y1_array) - y2_min=min(y2_array) - y3_min=min(y3_array) - y_min=min([y1_min, y2_min, y3_min]) - if y_max==None: - y1_max=max(y1_array) - y2_max=max(y2_array) - y3_max=max(y3_array) - y_max=max([y1_max, y2_max, y3_max]) - ax.set_ylim(y_min, y_max) - if save == 1: - plt.savefig(filename+file_format, dpi=dpi) - if show == 1: - plt.show() - plt.close('all') - -# 画三维图 -@guan.statistics_decorator -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): - import numpy as np - import matplotlib.pyplot as plt - from matplotlib import cm - from matplotlib.ticker import LinearLocator - matrix = np.array(matrix) - fig, ax = plt.subplots(subplot_kw={"projection": "3d"}) - plt.subplots_adjust(bottom=0.1, right=0.65) - x_array, y_array = np.meshgrid(x_array, y_array) - if len(matrix.shape) == 2: - surf = ax.plot_surface(x_array, y_array, matrix, rcount=rcount, ccount=ccount, cmap=cm.coolwarm, linewidth=0, antialiased=False) - elif len(matrix.shape) == 3: - for i0 in range(matrix.shape[2]): - surf = ax.plot_surface(x_array, y_array, matrix[:,:,i0], rcount=rcount, ccount=ccount, cmap=cm.coolwarm, linewidth=0, antialiased=False) - ax.set_title(title, fontsize=fontsize, fontfamily='Times New Roman') - ax.set_xlabel(xlabel, fontsize=fontsize, fontfamily='Times New Roman') - ax.set_ylabel(ylabel, fontsize=fontsize, fontfamily='Times New Roman') - ax.set_zlabel(zlabel, fontsize=fontsize, fontfamily='Times New Roman') - ax.zaxis.set_major_locator(LinearLocator(5)) - ax.zaxis.set_major_formatter('{x:.2f}') - if z_min!=None or z_max!=None: - if z_min==None: - z_min=matrix.min() - if z_max==None: - z_max=matrix.max() - ax.set_zlim(z_min, z_max) - ax.tick_params(labelsize=labelsize) - labels = ax.get_xticklabels() + ax.get_yticklabels() + ax.get_zticklabels() - [label.set_fontname('Times New Roman') for label in labels] - cax = plt.axes([0.8, 0.1, 0.05, 0.8]) - cbar = fig.colorbar(surf, cax=cax) - cbar.ax.tick_params(labelsize=labelsize) - for l in cbar.ax.yaxis.get_ticklabels(): - l.set_family('Times New Roman') - if save == 1: - plt.savefig(filename+file_format, dpi=dpi) - if show == 1: - plt.show() - plt.close('all') - -# 画Contour图 -@guan.statistics_decorator -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): - import numpy as np - import matplotlib.pyplot as plt - fig, ax = plt.subplots() - plt.subplots_adjust(bottom=0.2, right=0.75, left=0.2) - x_array, y_array = np.meshgrid(x_array, y_array) - contour = ax.contourf(x_array,y_array,matrix,cmap=cmap, levels=levels) - ax.set_title(title, fontsize=fontsize, fontfamily='Times New Roman') - ax.set_xlabel(xlabel, fontsize=fontsize, fontfamily='Times New Roman') - ax.set_ylabel(ylabel, fontsize=fontsize, fontfamily='Times New Roman') - ax.tick_params(labelsize=labelsize) - labels = ax.get_xticklabels() + ax.get_yticklabels() - [label.set_fontname('Times New Roman') for label in labels] - cax = plt.axes([0.8, 0.2, 0.05, 0.68]) - cbar = fig.colorbar(contour, cax=cax) - cbar.ax.tick_params(labelsize=labelsize) - for l in cbar.ax.yaxis.get_ticklabels(): - l.set_family('Times New Roman') - if save == 1: - plt.savefig(filename+file_format, dpi=dpi) - if show == 1: - plt.show() - plt.close('all') - -# 画棋盘图/伪彩色图 -@guan.statistics_decorator -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): - import numpy as np - import matplotlib.pyplot as plt - fig, ax = plt.subplots() - plt.subplots_adjust(bottom=0.2, right=0.75, left=0.2) - x_array, y_array = np.meshgrid(x_array, y_array) - contour = ax.pcolor(x_array,y_array,matrix, cmap=cmap) - ax.set_title(title, fontsize=fontsize, fontfamily='Times New Roman') - ax.set_xlabel(xlabel, fontsize=fontsize, fontfamily='Times New Roman') - ax.set_ylabel(ylabel, fontsize=fontsize, fontfamily='Times New Roman') - ax.tick_params(labelsize=labelsize) - labels = ax.get_xticklabels() + ax.get_yticklabels() - [label.set_fontname('Times New Roman') for label in labels] - cax = plt.axes([0.8, 0.2, 0.05, 0.68]) - cbar = fig.colorbar(contour, cax=cax) - cbar.ax.tick_params(labelsize=labelsize) - for l in cbar.ax.yaxis.get_ticklabels(): - l.set_family('Times New Roman') - if save == 1: - plt.savefig(filename+file_format, dpi=dpi) - if show == 1: - plt.show() - plt.close('all') - -# 通过坐标画点和线 -@guan.statistics_decorator -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): - import numpy as np - import matplotlib.pyplot as plt - coordinate_array = np.array(coordinate_array) - print(coordinate_array.shape) - x_range = max(coordinate_array[:, 0])-min(coordinate_array[:, 0]) - y_range = max(coordinate_array[:, 1])-min(coordinate_array[:, 1]) - fig, ax = plt.subplots(figsize=(6*x_range/y_range,6)) - plt.subplots_adjust(left=0, bottom=0, right=1, top=1) - plt.axis('off') - if draw_lines==1: - for i1 in range(coordinate_array.shape[0]): - for i2 in range(coordinate_array.shape[0]): - if np.sqrt((coordinate_array[i1, 0] - coordinate_array[i2, 0])**2+(coordinate_array[i1, 1] - coordinate_array[i2, 1])**2) < max_distance: - ax.plot([coordinate_array[i1, 0], coordinate_array[i2, 0]], [coordinate_array[i1, 1], coordinate_array[i2, 1]], line_style, linewidth=linewidth) - if draw_dots==1: - for i in range(coordinate_array.shape[0]): - ax.plot(coordinate_array[i, 0], coordinate_array[i, 1], dot_style, markersize=markersize) - if show==1: - plt.show() - if save==1: - if file_format=='.eps': - plt.savefig(filename+file_format) - else: - plt.savefig(filename+file_format, dpi=dpi) - -# 合并两个图片 -@guan.statistics_decorator -def combine_two_images(image_path_array, figsize=(16,8), 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 != 2: - print('Error: The number of images should be two!') - 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(121) - ax2 = fig.add_subplot(122) - image_1 = mpimg.imread(image_path_array[0]) - image_2 = mpimg.imread(image_path_array[1]) - ax1.imshow(image_1) - ax2.imshow(image_2) - ax1.axis('off') - ax2.axis('off') - if show == 1: - plt.show() - if save == 1: - plt.savefig(filename+file_format, dpi=dpi) - plt.close('all') - -# 合并三个图片 -@guan.statistics_decorator -def combine_three_images(image_path_array, figsize=(16,5), 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 != 3: - print('Error: The number of images should be three!') - 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(131) - ax2 = fig.add_subplot(132) - ax3 = fig.add_subplot(133) - 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.statistics_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.statistics_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.statistics_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.statistics_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 - -# 如果不存在文件夹，则新建文件夹 -@guan.statistics_decorator -def make_directory(directory='./test'): - import os - if not os.path.exists(directory): - os.makedirs(directory) - -# 如果不存在文件，则新建空文件 -@guan.statistics_decorator -def make_file(file_path='./a.txt'): - import os - if not os.path.exists(file_path): - with open(file_path, 'w') as f: - pass - -# 读取文本文件内容，如果不存在，则新建空文件 -@guan.statistics_decorator -def read_text_file(file_path='./a.txt'): - import os - if not os.path.exists(file_path): - with open(file_path, 'w') as f: - pass - return '' - else: - with open(file_path, 'r') as f: - content = f.read() - return content - -# 将变量存到文件 -@guan.statistics_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.statistics_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.statistics_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.statistics_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.statistics_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.statistics_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.statistics_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.statistics_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.statistics_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.statistics_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.statistics_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.statistics_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.statistics_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.statistics_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.statistics_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.statistics_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 - -# 获取目录中的所有文件名（不包括子目录） -@guan.statistics_decorator -def get_all_filenames_in_directory_without_subdirectory(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]) - break - return file_list - -# 获取文件夹中某种文本类型的文件路径以及读取内容 -@guan.statistics_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.statistics_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.statistics_decorator def preprocess_for_parallel_calculations(parameter_array_all, cpus=1, task_index=0): @@ -745,6 +38,24 @@ def generate_random_int_number_for_a_specific_seed(seed=0, x_min=0, x_max=10): rand_num = np.random.randint(x_min, x_max) # 左闭右开[x_min, x_max) return rand_num +# 以显示编号的样式，打印数组 +@guan.statistics_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) + # 使用jieba软件包进行分词 @guan.statistics_decorator def divide_text_into_words(text): @@ -752,18 +63,79 @@ def divide_text_into_words(text): words = jieba.lcut(text) return words -# 拼接两个PDF文件 +# 根据一定的字符长度来分割文本 @guan.statistics_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) \ No newline at end of file +def split_text(text, wrap_width=3000): + import textwrap + split_text_list = textwrap.wrap(text, wrap_width) + return split_text_list + +# 判断某个字符是中文还是英文或其他 +@guan.statistics_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.statistics_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.statistics_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.statistics_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.statistics_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.statistics_decorator +def encryption_SHA_256(password, salt=''): + import hashlib + password = salt+password + hashed_password = hashlib.sha256(password.encode()).hexdigest() + return hashed_password \ No newline at end of file diff --git a/PyPI/src/guan/decorator.py b/PyPI/src/guan/decorator.py new file mode 100644 index 0000000..e53e8f1 --- /dev/null +++ b/PyPI/src/guan/decorator.py @@ -0,0 +1,41 @@ +# 函数的装饰器，用于获取计算时间（秒） +def timer_decorator(func): + import time + def wrapper(*args, **kwargs): + start = time.time() + result = func(*args, **kwargs) + end = time.time() + print(f"Running time of {func.__name__}: {end - start} seconds") + return result + return wrapper + +# 函数的装饰器，用于获取计算时间（分） +def timer_decorator_minutes(func): + import time + def wrapper(*args, **kwargs): + start = time.time() + result = func(*args, **kwargs) + end = time.time() + print(f"Running time of {func.__name__}: {(end - start)/60} minutes") + return result + return wrapper + +# 函数的装饰器，用于获取计算时间（时） +def timer_decorator_hours(func): + import time + def wrapper(*args, **kwargs): + start = time.time() + result = func(*args, **kwargs) + end = time.time() + print(f"Running time of {func.__name__}: {(end - start)/3600} hours") + return result + return wrapper + +# 函数的装饰器，用于GUAN软件包的统计 +def statistics_decorator(func): + def wrapper(*args, **kwargs): + result = func(*args, **kwargs) + import guan + guan.statistics_of_guan_package(func.__name__) + return result + return wrapper \ No newline at end of file diff --git a/PyPI/src/guan/figure_plotting.py b/PyPI/src/guan/figure_plotting.py new file mode 100644 index 0000000..81c92b7 --- /dev/null +++ b/PyPI/src/guan/figure_plotting.py @@ -0,0 +1,403 @@ +# Module: figure_plotting +import guan + +# 导入plt, fig, ax +@guan.statistics_decorator +def import_plt_and_start_fig_ax(adjust_bottom=0.2, adjust_left=0.2, labelsize=20): + import matplotlib.pyplot as plt + fig, ax = plt.subplots() + plt.subplots_adjust(bottom=adjust_bottom, left=adjust_left) + ax.grid() + ax.tick_params(labelsize=labelsize) + labels = ax.get_xticklabels() + ax.get_yticklabels() + [label.set_fontname('Times New Roman') for label in labels] + return plt, fig, ax + +# 基于plt, fig, ax画图 +@guan.statistics_decorator +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): + if color==None: + ax.plot(x_array, y_array, style, linewidth=linewidth, markersize=markersize) + else: + ax.plot(x_array, y_array, style, linewidth=linewidth, markersize=markersize, color=color) + ax.set_title(title, fontsize=fontsize, fontfamily='Times New Roman') + ax.set_xlabel(xlabel, fontsize=fontsize, fontfamily='Times New Roman') + ax.set_ylabel(ylabel, fontsize=fontsize, fontfamily='Times New Roman') + if y_min!=None or y_max!=None: + if y_min==None: + y_min=min(y_array) + if y_max==None: + y_max=max(y_array) + ax.set_ylim(y_min, y_max) + +# 画图 +@guan.statistics_decorator +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): + import guan + plt, fig, ax = guan.import_plt_and_start_fig_ax(adjust_bottom=adjust_bottom, adjust_left=adjust_left, labelsize=labelsize) + ax.plot(x_array, y_array, style, linewidth=linewidth, markersize=markersize) + ax.set_title(title, fontsize=fontsize, fontfamily='Times New Roman') + ax.set_xlabel(xlabel, fontsize=fontsize, fontfamily='Times New Roman') + ax.set_ylabel(ylabel, fontsize=fontsize, fontfamily='Times New Roman') + if y_min!=None or y_max!=None: + if y_min==None: + y_min=min(y_array) + if y_max==None: + y_max=max(y_array) + ax.set_ylim(y_min, y_max) + if save == 1: + plt.savefig(filename+file_format, dpi=dpi) + if show == 1: + plt.show() + plt.close('all') + +# 一组横坐标数据，两组纵坐标数据画图 +@guan.statistics_decorator +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): + import guan + plt, fig, ax = guan.import_plt_and_start_fig_ax(adjust_bottom=adjust_bottom, adjust_left=adjust_left, labelsize=labelsize) + ax.plot(x_array, y1_array, style_1, linewidth=linewidth_1, markersize=markersize_1) + ax.plot(x_array, y2_array, style_2, linewidth=linewidth_2, markersize=markersize_2) + ax.set_title(title, fontsize=fontsize, fontfamily='Times New Roman') + ax.set_xlabel(xlabel, fontsize=fontsize, fontfamily='Times New Roman') + ax.set_ylabel(ylabel, fontsize=fontsize, fontfamily='Times New Roman') + if y_min!=None or y_max!=None: + if y_min==None: + y1_min=min(y1_array) + y2_min=min(y2_array) + y_min=min([y1_min, y2_min]) + if y_max==None: + y1_max=max(y1_array) + y2_max=max(y2_array) + y_max=max([y1_max, y2_max]) + ax.set_ylim(y_min, y_max) + if save == 1: + plt.savefig(filename+file_format, dpi=dpi) + if show == 1: + plt.show() + plt.close('all') + +# 两组横坐标数据，两组纵坐标数据画图 +@guan.statistics_decorator +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): + import guan + plt, fig, ax = guan.import_plt_and_start_fig_ax(adjust_bottom=adjust_bottom, adjust_left=adjust_left, labelsize=labelsize) + ax.plot(x1_array, y1_array, style_1, linewidth=linewidth_1, markersize=markersize_1) + ax.plot(x2_array, y2_array, style_2, linewidth=linewidth_2, markersize=markersize_2) + ax.set_title(title, fontsize=fontsize, fontfamily='Times New Roman') + ax.set_xlabel(xlabel, fontsize=fontsize, fontfamily='Times New Roman') + ax.set_ylabel(ylabel, fontsize=fontsize, fontfamily='Times New Roman') + if y_min!=None or y_max!=None: + if y_min==None: + y1_min=min(y1_array) + y2_min=min(y2_array) + y_min=min([y1_min, y2_min]) + if y_max==None: + y1_max=max(y1_array) + y2_max=max(y2_array) + y_max=max([y1_max, y2_max]) + ax.set_ylim(y_min, y_max) + if save == 1: + plt.savefig(filename+file_format, dpi=dpi) + if show == 1: + plt.show() + plt.close('all') + +# 一组横坐标数据，三组纵坐标数据画图 +@guan.statistics_decorator +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): + import guan + plt, fig, ax = guan.import_plt_and_start_fig_ax(adjust_bottom=adjust_bottom, adjust_left=adjust_left, labelsize=labelsize) + ax.plot(x_array, y1_array, style_1, linewidth=linewidth_1, markersize=markersize_1) + ax.plot(x_array, y2_array, style_2, linewidth=linewidth_2, markersize=markersize_2) + ax.plot(x_array, y3_array, style_3, linewidth=linewidth_3, markersize=markersize_3) + ax.set_title(title, fontsize=fontsize, fontfamily='Times New Roman') + ax.set_xlabel(xlabel, fontsize=fontsize, fontfamily='Times New Roman') + ax.set_ylabel(ylabel, fontsize=fontsize, fontfamily='Times New Roman') + if y_min!=None or y_max!=None: + if y_min==None: + y1_min=min(y1_array) + y2_min=min(y2_array) + y3_min=min(y3_array) + y_min=min([y1_min, y2_min, y3_min]) + if y_max==None: + y1_max=max(y1_array) + y2_max=max(y2_array) + y3_max=max(y3_array) + y_max=max([y1_max, y2_max, y3_max]) + ax.set_ylim(y_min, y_max) + if save == 1: + plt.savefig(filename+file_format, dpi=dpi) + if show == 1: + plt.show() + plt.close('all') + +# 三组横坐标数据，三组纵坐标数据画图 +@guan.statistics_decorator +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): + import guan + plt, fig, ax = guan.import_plt_and_start_fig_ax(adjust_bottom=adjust_bottom, adjust_left=adjust_left, labelsize=labelsize) + ax.plot(x1_array, y1_array, style_1, linewidth=linewidth_1, markersize=markersize_1) + ax.plot(x2_array, y2_array, style_2, linewidth=linewidth_2, markersize=markersize_2) + ax.plot(x3_array, y3_array, style_3, linewidth=linewidth_3, markersize=markersize_3) + ax.set_title(title, fontsize=fontsize, fontfamily='Times New Roman') + ax.set_xlabel(xlabel, fontsize=fontsize, fontfamily='Times New Roman') + ax.set_ylabel(ylabel, fontsize=fontsize, fontfamily='Times New Roman') + if y_min!=None or y_max!=None: + if y_min==None: + y1_min=min(y1_array) + y2_min=min(y2_array) + y3_min=min(y3_array) + y_min=min([y1_min, y2_min, y3_min]) + if y_max==None: + y1_max=max(y1_array) + y2_max=max(y2_array) + y3_max=max(y3_array) + y_max=max([y1_max, y2_max, y3_max]) + ax.set_ylim(y_min, y_max) + if save == 1: + plt.savefig(filename+file_format, dpi=dpi) + if show == 1: + plt.show() + plt.close('all') + +# 画三维图 +@guan.statistics_decorator +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): + import numpy as np + import matplotlib.pyplot as plt + from matplotlib import cm + from matplotlib.ticker import LinearLocator + matrix = np.array(matrix) + fig, ax = plt.subplots(subplot_kw={"projection": "3d"}) + plt.subplots_adjust(bottom=0.1, right=0.65) + x_array, y_array = np.meshgrid(x_array, y_array) + if len(matrix.shape) == 2: + surf = ax.plot_surface(x_array, y_array, matrix, rcount=rcount, ccount=ccount, cmap=cm.coolwarm, linewidth=0, antialiased=False) + elif len(matrix.shape) == 3: + for i0 in range(matrix.shape[2]): + surf = ax.plot_surface(x_array, y_array, matrix[:,:,i0], rcount=rcount, ccount=ccount, cmap=cm.coolwarm, linewidth=0, antialiased=False) + ax.set_title(title, fontsize=fontsize, fontfamily='Times New Roman') + ax.set_xlabel(xlabel, fontsize=fontsize, fontfamily='Times New Roman') + ax.set_ylabel(ylabel, fontsize=fontsize, fontfamily='Times New Roman') + ax.set_zlabel(zlabel, fontsize=fontsize, fontfamily='Times New Roman') + ax.zaxis.set_major_locator(LinearLocator(5)) + ax.zaxis.set_major_formatter('{x:.2f}') + if z_min!=None or z_max!=None: + if z_min==None: + z_min=matrix.min() + if z_max==None: + z_max=matrix.max() + ax.set_zlim(z_min, z_max) + ax.tick_params(labelsize=labelsize) + labels = ax.get_xticklabels() + ax.get_yticklabels() + ax.get_zticklabels() + [label.set_fontname('Times New Roman') for label in labels] + cax = plt.axes([0.8, 0.1, 0.05, 0.8]) + cbar = fig.colorbar(surf, cax=cax) + cbar.ax.tick_params(labelsize=labelsize) + for l in cbar.ax.yaxis.get_ticklabels(): + l.set_family('Times New Roman') + if save == 1: + plt.savefig(filename+file_format, dpi=dpi) + if show == 1: + plt.show() + plt.close('all') + +# 画Contour图 +@guan.statistics_decorator +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): + import numpy as np + import matplotlib.pyplot as plt + fig, ax = plt.subplots() + plt.subplots_adjust(bottom=0.2, right=0.75, left=0.2) + x_array, y_array = np.meshgrid(x_array, y_array) + contour = ax.contourf(x_array,y_array,matrix,cmap=cmap, levels=levels) + ax.set_title(title, fontsize=fontsize, fontfamily='Times New Roman') + ax.set_xlabel(xlabel, fontsize=fontsize, fontfamily='Times New Roman') + ax.set_ylabel(ylabel, fontsize=fontsize, fontfamily='Times New Roman') + ax.tick_params(labelsize=labelsize) + labels = ax.get_xticklabels() + ax.get_yticklabels() + [label.set_fontname('Times New Roman') for label in labels] + cax = plt.axes([0.8, 0.2, 0.05, 0.68]) + cbar = fig.colorbar(contour, cax=cax) + cbar.ax.tick_params(labelsize=labelsize) + for l in cbar.ax.yaxis.get_ticklabels(): + l.set_family('Times New Roman') + if save == 1: + plt.savefig(filename+file_format, dpi=dpi) + if show == 1: + plt.show() + plt.close('all') + +# 画棋盘图/伪彩色图 +@guan.statistics_decorator +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): + import numpy as np + import matplotlib.pyplot as plt + fig, ax = plt.subplots() + plt.subplots_adjust(bottom=0.2, right=0.75, left=0.2) + x_array, y_array = np.meshgrid(x_array, y_array) + contour = ax.pcolor(x_array,y_array,matrix, cmap=cmap) + ax.set_title(title, fontsize=fontsize, fontfamily='Times New Roman') + ax.set_xlabel(xlabel, fontsize=fontsize, fontfamily='Times New Roman') + ax.set_ylabel(ylabel, fontsize=fontsize, fontfamily='Times New Roman') + ax.tick_params(labelsize=labelsize) + labels = ax.get_xticklabels() + ax.get_yticklabels() + [label.set_fontname('Times New Roman') for label in labels] + cax = plt.axes([0.8, 0.2, 0.05, 0.68]) + cbar = fig.colorbar(contour, cax=cax) + cbar.ax.tick_params(labelsize=labelsize) + for l in cbar.ax.yaxis.get_ticklabels(): + l.set_family('Times New Roman') + if save == 1: + plt.savefig(filename+file_format, dpi=dpi) + if show == 1: + plt.show() + plt.close('all') + +# 通过坐标画点和线 +@guan.statistics_decorator +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): + import numpy as np + import matplotlib.pyplot as plt + coordinate_array = np.array(coordinate_array) + print(coordinate_array.shape) + x_range = max(coordinate_array[:, 0])-min(coordinate_array[:, 0]) + y_range = max(coordinate_array[:, 1])-min(coordinate_array[:, 1]) + fig, ax = plt.subplots(figsize=(6*x_range/y_range,6)) + plt.subplots_adjust(left=0, bottom=0, right=1, top=1) + plt.axis('off') + if draw_lines==1: + for i1 in range(coordinate_array.shape[0]): + for i2 in range(coordinate_array.shape[0]): + if np.sqrt((coordinate_array[i1, 0] - coordinate_array[i2, 0])**2+(coordinate_array[i1, 1] - coordinate_array[i2, 1])**2) < max_distance: + ax.plot([coordinate_array[i1, 0], coordinate_array[i2, 0]], [coordinate_array[i1, 1], coordinate_array[i2, 1]], line_style, linewidth=linewidth) + if draw_dots==1: + for i in range(coordinate_array.shape[0]): + ax.plot(coordinate_array[i, 0], coordinate_array[i, 1], dot_style, markersize=markersize) + if show==1: + plt.show() + if save==1: + if file_format=='.eps': + plt.savefig(filename+file_format) + else: + plt.savefig(filename+file_format, dpi=dpi) + +# 合并两个图片 +@guan.statistics_decorator +def combine_two_images(image_path_array, figsize=(16,8), 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 != 2: + print('Error: The number of images should be two!') + 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(121) + ax2 = fig.add_subplot(122) + image_1 = mpimg.imread(image_path_array[0]) + image_2 = mpimg.imread(image_path_array[1]) + ax1.imshow(image_1) + ax2.imshow(image_2) + ax1.axis('off') + ax2.axis('off') + if show == 1: + plt.show() + if save == 1: + plt.savefig(filename+file_format, dpi=dpi) + plt.close('all') + +# 合并三个图片 +@guan.statistics_decorator +def combine_three_images(image_path_array, figsize=(16,5), 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 != 3: + print('Error: The number of images should be three!') + 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(131) + ax2 = fig.add_subplot(132) + ax3 = fig.add_subplot(133) + 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.statistics_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.statistics_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.statistics_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.statistics_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 \ No newline at end of file diff --git a/PyPI/src/guan/file_reading_and_writing.py b/PyPI/src/guan/file_reading_and_writing.py new file mode 100644 index 0000000..0e76941 --- /dev/null +++ b/PyPI/src/guan/file_reading_and_writing.py @@ -0,0 +1,337 @@ +# Module: file_reading_and_writing +import guan + +# 使用pickle将变量保存到文件（支持几乎所有对象类型） +@guan.statistics_decorator +def dump_data(data, filename, file_format='.txt'): + import pickle + with open(filename+file_format, 'wb') as f: + pickle.dump(data, f) + +# 使用pickle从文件中恢复数据到变量（支持几乎所有对象类型） +@guan.statistics_decorator +def load_data(filename, file_format='.txt'): + import pickle + with open(filename+file_format, 'rb') as f: + data = pickle.load(f) + return data + +# 使用NumPy保存数组变量到npy文件（二进制文件） +@guan.statistics_decorator +def save_npy_data(data, filename): + import numpy as np + np.save(filename+'.npy', data) + +# 使用NumPy从npy文件恢复数据到数组变量（二进制文件） +@guan.statistics_decorator +def load_npy_data(filename): + import numpy as np + data = np.load(filename+'.npy') + return data + +# 使用NumPy保存数组变量到TXT文件（文本文件） +@guan.statistics_decorator +def save_txt_data(data, filename): + import numpy as np + np.savetxt(filename+'.txt', data) + +# 使用NumPy从TXT文件恢复数据到数组变量（文本文件） +@guan.statistics_decorator +def load_txt_data(filename): + import numpy as np + data = np.loadtxt(filename+'.txt') + return data + +# 读取文件中的一维数据（一行一组x和y） +@guan.statistics_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.statistics_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.statistics_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.statistics_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.statistics_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.statistics_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.statistics_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.statistics_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.statistics_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.statistics_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.statistics_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.statistics_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') + +# 如果不存在文件夹，则新建文件夹 +@guan.statistics_decorator +def make_directory(directory='./test'): + import os + if not os.path.exists(directory): + os.makedirs(directory) + +# 如果不存在文件，则新建空文件 +@guan.statistics_decorator +def make_file(file_path='./a.txt'): + import os + if not os.path.exists(file_path): + with open(file_path, 'w') as f: + pass + +# 读取文本文件内容，如果不存在，则新建空文件 +@guan.statistics_decorator +def read_text_file(file_path='./a.txt'): + import os + if not os.path.exists(file_path): + with open(file_path, 'w') as f: + pass + return '' + else: + with open(file_path, 'r') as f: + content = f.read() + return content + +# 获取目录中的所有文件名 +@guan.statistics_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 + +# 获取目录中的所有文件名（不包括子目录） +@guan.statistics_decorator +def get_all_filenames_in_directory_without_subdirectory(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]) + break + return file_list + +# 获取文件夹中某种文本类型的文件路径以及读取内容 +@guan.statistics_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.statistics_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 + +# 复制一份文件 +@guan.statistics_decorator +def copy_file(file1='./a.txt', file2='./b.txt'): + import shutil + shutil.copy(file1, file2) + +# 拼接两个PDF文件 +@guan.statistics_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) \ No newline at end of file diff --git a/PyPI/src/guan/machine_learning.py b/PyPI/src/guan/machine_learning.py index 722d5fa..8f77803 100644 --- a/PyPI/src/guan/machine_learning.py +++ b/PyPI/src/guan/machine_learning.py @@ -165,9 +165,9 @@ def batch_train_model(model, train_loader, optimizer='Adam', learning_rate=0.001 loss.backward() optimizer.step() losses.append(loss.item()) - if print_show == 1: - if (epoch + 1) % 100 == 0: - print(epoch, loss.item()) + if print_show == 1: + if (epoch + 1) % 100 == 0: + print(epoch, loss.item()) return model, losses # 保存模型参数到文件 diff --git a/PyPI/src/guan/others.py b/PyPI/src/guan/others.py index 6fec614..6577c74 100644 --- a/PyPI/src/guan/others.py +++ b/PyPI/src/guan/others.py @@ -19,76 +19,6 @@ def get_time(colon=True): datetime_time = datetime_time.replace(':', '') return datetime_time -# 判断某个字符是中文还是英文或其他 -@guan.statistics_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.statistics_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.statistics_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.statistics_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.statistics_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.statistics_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.statistics_decorator def run_programs_sequentially(program_files=['./a.py', './b.py'], execute='python ', show_time=0): @@ -109,12 +39,6 @@ def run_programs_sequentially(program_files=['./a.py', './b.py'], execute='pytho end = time.time() print('Total running time = '+str((end-start)/60)+' min') -# 复制一份文件 -@guan.statistics_decorator -def copy_file(file1='./a.txt', file2='./b.txt'): - import shutil - shutil.copy(file1, file2) - # 获取CPU使用率 @guan.statistics_decorator def get_cpu_usage(interval=1): @@ -197,13 +121,6 @@ def count_number_of_import_statements(filename, file_format='.py', num=1000): import_statement_counter = Counter(import_array).most_common(num) return import_statement_counter -# 根据一定的字符长度来分割文本 -@guan.statistics_decorator -def split_text(text, wrap_width=3000): - import textwrap - split_text_list = textwrap.wrap(text, wrap_width) - return split_text_list - # 获取本月的所有日期 @guan.statistics_decorator def get_days_of_the_current_month(str_or_datetime='str'): diff --git a/README.md b/README.md index 51ea570..962136c 100755 --- a/README.md +++ b/README.md @@ -1,6 +1,6 @@ ## Guan package -Guan is an open-source python package developed and maintained by https://www.guanjihuan.com/about (Ji-Huan Guan, 关济寰). With this package, you can calculate band structures, density of states, quantum transport and topological invariant of tight-binding models by invoking the functions you need. Other frequently used functions are also integrated, such as machine learning, figure plotting and file reading/writing. +Guan is an open-source python package developed and maintained by https://www.guanjihuan.com/about (Ji-Huan Guan, 关济寰). With this package, you can calculate band structures, density of states, quantum transport and topological invariant of tight-binding models by invoking the functions you need. Other frequently used functions are also integrated, such as machine learning, figure plotting, file reading and writing, and data processing. The primary location of this package is on https://py.guanjihuan.com. @@ -14,6 +14,7 @@ import guan ## Summary of API Reference ++ decorator + basic functions + Fourier transform + Hamiltonian of examples @@ -23,6 +24,8 @@ import guan + quantum transport + topological invariant + machine learning ++ file reading and writing ++ figure plotting + data processing + others