matplotlib科研绘图

2023-07-31 04:57| 来源: 网络整理| 查看: 265

matplotlib科研绘图—Times New Roman字体设置一、法一 plt.figure(figsize=[15,8]) plt.scatter(X, Y, label = 'RealValue') plt.plot(X, func(X, a, b), 'red', label = 'CurveLine') plt.title(station, fontdict={'family' : 'Times New Roman', 'size' : 16}) plt.ylabel('Clocks($\mu S$)', fontdict={'family' : 'Times New Roman', 'size' : 16}) plt.xlabel('Time', fontdict={'family' : 'Times New Roman', 'size' : 16}) plt.yticks(fontproperties = 'Times New Roman', size = 14) plt.xticks(fontproperties = 'Times New Roman', size = 14) plt.legend(prop={'family' : 'Times New Roman', 'size' : 16}) plt.savefig('./stationClocks/' + station + '.ps', dpi = 200) plt.show() 二、法二

解决字体不一致的方法将全局字体改为Times New Roman

import matplotlib.pyplot as plt plt.rc('font',family='Times New Roman')

解决Times New Roman加粗的问题

del matplotlib.font_manager.weight_dict['roman'] matplotlib.font_manager._rebuild() 三、一些参数

matplotlib说明框中字体粗细用默认的字体时，'weight’的变化是可以改变字体粗细的，以下是代码

一旦把字体设定为’Times New Roman’，'weight’就没办法调节说明框中字体的粗细

import matplotlib.pyplot as plt styles=['normal','italic','oblique'] weights=['ultralight', 'light', 'normal', 'regular', 'book', 'medium', 'roman', 'semibold', 'demibold', 'demi', 'bold', 'heavy', 'extra bold', 'black'] plt.figure(figsize=(15,3)) for i in range(len(styles)): for j in range(len(weights)): font={'family' : 'Times New Roman','style':styles[i],'weight':weights[j]} plt.subplot(len(styles),len(weights),i*len(weights)+j+1) plt.plot([1, 2, 3, 4], [1, 4, 9, 16], 'b', label='VGG-16') plt.legend(loc='upper right', prop=font) plt.savefig('style.png') 四、Matplotlib画各种论文图 # coding=utf-8 import numpy as np import matplotlib.pyplot as plt plt.rcParams['font.sans-serif'] = ['Arial'] # 如果要显示中文字体,则在此处设为：SimHei plt.rcParams['axes.unicode_minus'] = False # 显示负号 x = np.array([1, 2, 3, 4, 5, 6]) VGG_supervised = np.array([2.9749694, 3.9357018, 4.7440844, 6.482254, 8.720203, 13.687582]) VGG_unsupervised = np.array([2.1044724, 2.9757383, 3.7754183, 5.686206, 8.367847, 14.144531]) ourNetwork = np.array([2.0205495, 2.6509762, 3.1876223, 4.380781, 6.004548, 9.9298]) # label在图示(legend)中显示。若为数学公式,则最好在字符串前后添加"$"符号 # color：b:blue、g:green、r:red、c:cyan、m:magenta、y:yellow、k:black、w:white、、、 # 线型：- -- -. : , # marker：. , o v < * + 1 plt.figure(figsize=(10, 5)) plt.grid(linestyle="--") # 设置背景网格线为虚线 ax = plt.gca() ax.spines['top'].set_visible(False) # 去掉上边框 ax.spines['right'].set_visible(False) # 去掉右边框 plt.plot(x, VGG_supervised, marker='o', color="blue", label="VGG-style Supervised Network", linewidth=1.5) plt.plot(x, VGG_unsupervised, marker='o', color="green", label="VGG-style Unsupervised Network", linewidth=1.5) plt.plot(x, ourNetwork, marker='o', color="red", label="ShuffleNet-style Network", linewidth=1.5) group_labels = ['Top 0-5%', 'Top 5-10%', 'Top 10-20%', 'Top 20-50%', 'Top 50-70%', ' Top 70-100%'] # x轴刻度的标识 plt.xticks(x, group_labels, fontsize=12, fontweight='bold') # 默认字体大小为10 plt.yticks(fontsize=12, fontweight='bold') # plt.title("example", fontsize=12, fontweight='bold') # 默认字体大小为12 plt.xlabel("Performance Percentile", fontsize=13, fontweight='bold') plt.ylabel("4pt-Homography RMSE", fontsize=13, fontweight='bold') plt.xlim(0.9, 6.1) # 设置x轴的范围 plt.ylim(1.5, 16) # plt.legend() #显示各曲线的图例 plt.legend(loc=0, numpoints=1) leg = plt.gca().get_legend() ltext = leg.get_texts() plt.setp(ltext, fontsize=12, fontweight='bold') # 设置图例字体的大小和粗细 plt.savefig('./filename.svg', format='svg') # 建议保存为svg格式,再用inkscape转为矢量图emf后插入word中 plt.show()

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