使用Matplotlib绘制不同颜色的带箭头的线实例
2020-04-18 07:11
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周五的时候计算出来一条线路,但是计算出来的只是类似与
0->10->19->2->..0
这样的线路只有写代码的人才能看的懂无法直观的表达出来,让其它同事看的不清晰,所以考虑怎样直观的把线路图画出来。
&esp; 当然是考虑用matplotlib了,
导入相关的库
import matplotlib.pyplot as plt import numpy import matplotlib.colors as colors import matplotlib.cm as cmx
后面两个主要是用于处理颜色的。
准备数据
_locations = [ (4, 4), # depot (4, 4), # unload depot_prime (4, 4), # unload depot_second (4, 4), # unload depot_fourth (4, 4), # unload depot_fourth (4, 4), # unload depot_fifth (2, 0), (8, 0), # locations to visit (0, 1), (1, 1), (5, 2), (7, 2), (3, 3), (6, 3), (5, 5), (8, 5), (1, 6), (2, 6), (3, 7), (6, 7), (0, 8), (7, 8) ]
画图
plt.figure(figsize=(10, 10)) p1 = [l[0] for l in _locations] p2 = [l[1] for l in _locations] plt.plot(p1[:6], p2[:6], 'g*', ms=20, label='depot') plt.plot(p1[6:], p2[6:], 'ro', ms=15, label='customer') plt.grid(True) plt.legend(loc='lower left') way = [[0, 12, 18, 17, 16, 4, 14, 10, 11, 13, 5], [0, 6, 9, 8, 20, 3], [0, 19, 21, 15, 7, 2]] # cmap = plt.cm.jet cNorm = colors.Normalize(vmin=0, vmax=len(way)) scalarMap = cmx.ScalarMappable(norm=cNorm,cmap=cmap) for k in range(0, len(way)): way0 = way[k] colorVal = scalarMap.to_rgba(k) for i in range(0, len(way0)-1): start = _locations[way0[i]] end = _locations[way0[i+1]] # plt.arrow(start[0], start[1], end[0]-start[0], end[1]-start[1], length_includes_head=True, # head_width=0.2, head_length=0.3, fc='k', ec='k', lw=2, ls=lineStyle[k], color='red') plt.arrow(start[0], start[1], end[0]-start[0], end[1]-start[1], length_includes_head=True, head_width=0.2, lw=2, color=colorVal) plt.show()
cmap = plt.cm.jet cNorm = colors.Normalize(vmin=0, vmax=len(way)) scalarMap = cmx.ScalarMappable(norm=cNorm,cmap=cmap)
cmap可以理解为颜色库,cNorm设置颜色的范围,有几条线路就设置几种颜色,scalarMap颜色生成完毕。最后在绘图的时候,根据索引获得相应的颜色就可以了。
结果如下:
补充知识:Python包matplotlib绘图--如何标注某点--附代码
# -*- coding: utf-8 -*- import matplotlib as mpl import matplotlib.pyplot as plt import numpy as np plt.style.use('classic') plt.rcParams['font.sans-serif'] = ['SimHei'] #解决中文显示 plt.rcParams['axes.unicode_minus'] = False #解决符号无法显示 x=np.array([1,2,3,4,5,6,7,8]) y1=np.array([3,5,35,300,800,600,1200,4000]) y2=np.array([8,14,94,703,1300,1660,2801,12768]) fig1 = plt.figure() ax = plt.axes() ax.plot(x, y2,label='时间/秒') ax.set(xlabel='目标函数个数', ylabel='程序运行时间',title='多目标收敛速度') plt.hlines(703, 0, 4, colors='r', linestyle="--") plt.text(0, 703, "703") plt.hlines(1300, 0, 5, colors='g', linestyle="--") plt.text(0, 1300, "1300") # annotate plt.annotate("703秒", (4,703), xycoords='data', xytext=(4.2, 2000), arrowprops=dict(arrowstyle='->')) plt.annotate("94秒", (3,94), xycoords='data', xytext=(3.5, 2000), arrowprops=dict(arrowstyle='->')) plt.annotate("14秒", (2,14), xycoords='data', xytext=(2.5, 2000), arrowprops=dict(arrowstyle='->')) plt.annotate("8秒", (1,8), xycoords='data', xytext=(1.5, 2000), arrowprops=dict(arrowstyle='->')) plt.legend() plt.show() fig1.savefig('my_figure1.png')
import numpy as np from matplotlib import pyplot as plt from matplotlib.path import Path from matplotlib.patches import PathPatch # Use seaborn to change the default graphics to something nicer import seaborn as sns # And set a nice color palette sns.set_color_codes('deep') # Create the plot object fig, ax = plt.subplots(figsize=(5, 4)) x = np.linspace(0, 1000) # Add finishing constraint: x2 <= 100/2 - x1/2 plt.plot(x, 50/4 - 3*x/4, linewidth=3, label='First constraint') plt.fill_between(x, 0, 100/2 - x/2, alpha=0.1) # Add carpentry constraint: x2 <= 80 - x1 plt.plot(x, 30 - 2*x, linewidth=3, label='Second constraint') plt.fill_between(x, 0, 100 - 2*x, alpha=0.1) # Add non-negativity constraints plt.plot(np.zeros_like(x), x, linewidth=3, label='$x$ Sign restriction') plt.plot(x, np.zeros_like(x), linewidth=3, label='$y$ Sign restriction') #==================================================== # This part is different from giapetto_feasible.py # Plot the possible (x1, x2) pairs pairs = [(x, y) for x in np.arange(101) for y in np.arange(101) if (300*x + 400*y) <= 5000 and (200*x + 100*y) <= 3000] # Split these into our variables chairs, tables = np.hsplit(np.array(pairs), 2) # Caculate the objective function at each pair z =8*chairs + 9*tables # Plot the results plt.scatter(chairs, tables, c=z, cmap='jet', edgecolor='gray', alpha=0.5, label='Profit at each point', zorder=3) # Colorbar cb = plt.colorbar() cb.set_label('Profit Colormap ($)') #==================================================== # Labels and stuff plt.xlabel('Package A') plt.ylabel('Package B') plt.xlim(-0.5, 20) plt.ylim(-0.5, 20) plt.legend() fig01 = plt.figure() plt.show()
以上这篇使用Matplotlib绘制不同颜色的带箭头的线实例就是小编分享给大家的全部内容了,希望能给大家一个参考
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