[python] plt绘图前准备

import matplotlib.pyplot as plt
# ======================== plot
def set_figure(font_size=10., tick_size=8., ms=7., lw=1.2, fig_w=8.):
    # print(plt.rcParams.keys())  # 很有用，查看所需属性
    # exit()
    cm_to_inc = 1 / 2.54  # 厘米和英寸的转换 1inc = 2.54cm
    w = fig_w * cm_to_inc  # cm ==> inch
    h = w * 3 / 4
    plt.rcParams['figure.figsize'] = (w, h)  # 单位 inc
    plt.rcParams['figure.dpi'] = 300
    # plt.rcParams['figure.figsize'] = (14 * cm_to_inc, 6 * cm_to_inc)

    # 1. Times New Roman or Arial:
    plt.rc('font', family='Arial', weight= 'normal', size=float(font_size))
    # 2. Helvetica:
    # font = {'family': 'sans-serif', 'sans-serif': 'Helvetica',
    #         'weight': 'normal', 'size': float(font_size)}
    # plt.rc('font', **font)  # pass in the font dict as kwargs

    plt.rcParams['axes.linewidth'] = lw  # 图框宽度

    # plt.rcParams['lines.markeredgecolor'] = 'k'
    plt.rcParams['lines.markeredgewidth'] = lw
    plt.rcParams['lines.markersize'] = ms

    # 刻度在内
    plt.rcParams['xtick.direction'] = 'in'
    plt.rcParams['xtick.labelsize'] = tick_size
    plt.rcParams['xtick.major.width'] = lw
    plt.rcParams['xtick.major.size'] = 2.5  # 刻度长度

    plt.rcParams['ytick.direction'] = 'in'
    plt.rcParams['ytick.labelsize'] = tick_size
    plt.rcParams['ytick.major.width'] = lw
    plt.rcParams['ytick.major.size'] = 2.5

    plt.rcParams["legend.frameon"] = True  # 图框
    plt.rcParams["legend.framealpha"] = 0.8  # 不透明度
    plt.rcParams["legend.fancybox"] = False  # 圆形边缘
    plt.rcParams['legend.edgecolor'] = 'k'
    plt.rcParams["legend.columnspacing"] = 1  # /font unit 以字体大小为单位
    plt.rcParams['legend.labelspacing'] = 0.2
    plt.rcParams["legend.borderaxespad"] = 0.5
    plt.rcParams["legend.borderpad"] = 0.3


marker_style = ['o', '^', 'v', 's', 'd', '>', '<', 'h']
marker_color = [
    [0.00, 0.45, 0.74],  # 蓝色
    [0.93, 0.69, 0.13],  # 黄色
    [0.85, 0.33, 0.10],  # 橘红色
    [0.49, 0.18, 0.56],  # 紫色
    [0.47, 0.67, 0.19],  # 绿色
    [0.30, 0.75, 0.93],  # 青色
    [0.64, 0.08, 0.18],  # 棕色
]
line_style = ['-', '--', '-.', ':']


def plot_acc(data, x_lim, y_lim, legend_list, save_path):
    lw = 1.2
    ms = 7
    set_figure(lw=lw, ms=ms, font_size=10, tick_size=10)
    plt.figure(1)
    x = [1, 2, 3, 4]
    x_name = ['10', '30', '50', '100']

    for i in range(len(data)):
        plt.plot(x, data[i], lw=lw, color='k', marker=marker_style[i],
                 markerfacecolor=marker_color[i], markeredgecolor='k')
    # adjust
    plt.ylim(y_lim)
    plt.xlim(x_lim)
    plt.ylabel('Accuracy (%)')
    plt.xlabel('Sample size')
    plt.xticks(x, x_name)
    # plt.yticks([0, 20, 40, 60, 80, 95])
    # plt.legend(legend_list, ncol=2, loc="lower center",
    #            labelspacing=0.2).get_frame().set_linewidth(lw)
    plt.legend(legend_list, ncol=2, loc="lower center").get_frame().set_linewidth(lw)

    # save
    order = input('Save fig' + save_path[-4:] + '? Y/N\n')
    if order == 'y' or order == 'Y':
        # plt.savefig(save_path, dpi=300, format='svg', bbox_inches='tight')
        plt.savefig(save_path + '.svg', dpi=600, format='svg', bbox_inches='tight', pad_inches=0.01)
        plt.savefig(save_path + '.png', dpi=600, format='png', bbox_inches='tight', pad_inches=0.01)
        # 保留0.01白边，防止切掉线框.注意剪裁之后，图像尺寸会变小。

    # show
    plt.show()


def plot_box_acc(data, legend_list, save_path):
    lw = 1.2
    ms = 7
    # set_figure(font_size=10, tick_size=8, lw=lw, ms=ms, fig_w=8.5)
    set_figure(font_size=10, tick_size=10, lw=lw, ms=ms, fig_w=8)
    plt.figure(1)

    plt.boxplot(data, showmeans=True, showfliers=False,
                labels=legend_list,
                meanprops=dict(markersize=6), whiskerprops=dict(linewidth=lw),
                boxprops=dict(linewidth=lw),
                capprops=dict(linewidth=lw),  # 首尾横线属性
                medianprops=dict(linewidth=lw),  # 中位线属性
                )
    # plt.violinplot(data, showmeans=True, showmedians=True)
    plt.ylabel('Accuracy (%)')
    # plt.xlabel('Models')
    # save
    order = input('Save fig' + save_path[-4:] + '? Y/N\n')
    if order == 'y' or order == 'Y':
        plt.savefig(save_path + '.svg', dpi=600, format='svg', bbox_inches='tight', pad_inches=0.01)
        plt.savefig(save_path + '.png', dpi=600, format='png', bbox_inches='tight', pad_inches=0.01)
        # 保留0.01白边，防止切掉线框.注意剪裁之后，图像尺寸会变小。

    plt.show()


def plot_acc_ablation(data, x_lim, y_lim, legend_list, save_path):
    lw = 1.2
    ms = 7
    set_figure(lw=lw, ms=ms, font_size=10, tick_size=10)
    plt.figure(1)
    x = [1, 2, 3, 4]
    x_name = ['10', '30', '50', '100']

    for i in range(2):
        plt.plot(x, data[i], lw=lw, color='k', marker=marker_style[i],
                 markerfacecolor=marker_color[i], markeredgecolor='k')

    plt.plot(x, data[2], lw=lw, color='k', marker=marker_style[5],
             markerfacecolor=marker_color[5], markeredgecolor='k')  # DASMN
    plt.plot(x, data[3], '--', lw=lw, color='k', marker=marker_style[0],
             markerfacecolor=marker_color[3], markeredgecolor='k')  # CNN
    plt.plot(x, data[4], '--', lw=lw, color='k', marker=marker_style[1],
             markerfacecolor=marker_color[4], markeredgecolor='k')  # ProtoNets
    # adjust
    plt.ylim(y_lim)
    plt.xlim(x_lim)
    plt.ylabel('Accuracy (%)')
    plt.xlabel('Sample size')
    plt.xticks(x, x_name)
    # plt.yticks([0, 20, 40, 60, 80, 95])
    plt.legend(legend_list, ncol=2, loc="lower center",
               labelspacing=0.2).get_frame().set_linewidth(lw)

    # save
    order = input('Save fig' + save_path[-4:] + '? Y/N\n')
    if order == 'y' or order == 'Y':
        # plt.savefig(save_path, dpi=300, format='svg', bbox_inches='tight')
        plt.savefig(save_path + '.svg', dpi=600, format='svg', bbox_inches='tight', pad_inches=0.01)
        plt.savefig(save_path + '.png', dpi=600, format='png', bbox_inches='tight', pad_inches=0.01)
        # 保留0.01白边，防止切掉线框.注意剪裁之后，图像尺寸会变小。

    # show
    plt.show()


if __name__ == '__main__':
    pass