Python matplotlib实现条形统计图_python_

import matplotlib.pyplot as plt import numpy as np from matplotlib.pyplot import MultipleLocator def plot_bar(experiment_name, bar_name, bar_value, error_value=None,):     """     Args:         experiment_name: x_labels         bar_name: legend name         bar_value: list(len(experiment_name), each element contains a np.array(),                    which contains bar value in each group         error_value: list(len(experiment_name), each element contains a np.array(),                    which contains error value in each group     Returns:     """     # 用于正常显示中文标签     # plt.rcParams["font.sans-serif"]=['SimHei']     colors = ['lightsteelblue', 'cornflowerblue', 'royalblue', 'blue', 'mediumblue', 'darkblue', 'navy', 'midnightblue',               'lavender', ]     assert len(bar_value[0]) <= len(colors)  # if not try to add color to 'colors'     plt.rcParams['axes.unicode_minus'] = False     plt.style.use('seaborn')     font = {'weight': 'normal', 'size': 20, }     font_title = {'weight': 'normal', 'size': 28, }     # bar width     width = 0.2     # groups of data     x_bar = np.arange(len(experiment_name))     # create figure     plt.figure(figsize=(10, 9))     ax = plt.subplot(111)  # 假如设置为221，则表示创建两行两列也就是4个子画板,ax为第一个子画板     # plot bar     bar_groups = []     value = []     for i in range(len(bar_value[0])):         for j in range(len(experiment_name)):             value.append(bar_value[j][i])         group = ax.bar(x_bar - (len(experiment_name)-3-i)*width, copy.deepcopy(value), width=width, color=colors[i], label=bar_name[i])         bar_groups.append(group)         value.clear()     # add height to each bar     i = j = 0     for bars in bar_groups:         j = 0         for rect in bars:             x = rect.get_x()             height = rect.get_height()             # ax.text(x + 0.1, 1.02 * height, str(height), fontdict=font)             # error bar             if error_value:                 ax.errorbar(x + width / 2, height, yerr=error_value[j][i], fmt="-", ecolor="black",                             elinewidth=1.2, capsize=2,                             capthick=1.2)             j += 1         i += 1     # 设置刻度字体大小     plt.xticks(fontsize=15)     plt.yticks(fontsize=18)     # 设置x轴的刻度     ax.set_xticks(x_bar)     ax.set_xticklabels(experiment_name, fontdict=font)     # 设置y轴的刻标注     ax.set_ylabel("Episode Cost", fontdict=font_title)     ax.set_xlabel('Experiment', fontdict=font_title)     # 是否显示网格     ax.grid(False)     # 拉伸y轴     ax.set_ylim(0, 7.5)     # 把轴的刻度间隔设置为1，并存在变量里     y_major_locator = MultipleLocator(2.5)     ax.yaxis.set_major_locator(y_major_locator)     # 设置标题     plt.suptitle("Cost Comparison", fontsize=30, horizontalalignment='center')     plt.subplots_adjust(left=0.11, bottom=0.1, right=0.95, top=0.93, wspace=0.1, hspace=0.2)     # 设置边框线宽为2.0     ax.spines['bottom'].set_linewidth('2.0')     # 添加图例     ax.legend(loc='upper left', frameon=True, fontsize=19.5)     # plt.savefig("test.png")     plt.show()     plt.legend() if __name__ == "__main__":     test_experiment_name = ["Test 1", "Test 2", "Test 3", "Test 4"]     test_bar_name = ['A', "B", "C"]     test_bar_value = [         np.array([1, 2, 3]),         np.array([4, 5, 6]),         np.array([3, 2, 4]),         np.array([5, 2, 2])     ]     test_error_value = [         np.array([1, 1, 2]),         np.array([0.2, 0.6, 1]),         np.array([0, 0, 0]),         np.array([0.5, 0.2, 0.2])     ]     plot_bar(test_experiment_name, test_bar_name, test_bar_value, test_error_value)