使用Matplotlib繪制不同顏色的帶箭頭的線實例

更新時間：2020年04月17日 10:27:58 作者：月落烏啼silence

這篇文章主要介紹了使用Matplotlib繪制不同顏色的帶箭頭的線實例，具有很好的參考價值，希望對大家有所幫助。一起跟隨小編過來看看吧

周五的時候計算出來一條線路，但是計算出來的只是類似與

0->10->19->2->..0

這樣的線路只有寫代碼的人才能看的懂無法直觀的表達出來，讓其它同事看的不清晰，所以考慮怎樣直觀的把線路圖畫出來。

&esp; 當(dāng)然是考慮用matplotlib了，

導(dǎo)入相關(guān)的庫

import matplotlib.pyplot as plt
import numpy
import matplotlib.colors as colors
import matplotlib.cm as cmx

后面兩個主要是用于處理顏色的。

準備數(shù)據(jù)

 _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)
  ]

畫圖

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可以理解為顏色庫，cNorm設(shè)置顏色的范圍，有幾條線路就設(shè)置幾種顏色，scalarMap顏色生成完畢。最后在繪圖的時候，根據(jù)索引獲得相應(yīng)的顏色就可以了。

結(jié)果如下：

補充知識：Python包matplotlib繪圖--如何標(biāo)注某點--附代碼

# -*- 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'] #解決中文顯示
plt.rcParams['axes.unicode_minus'] = False #解決符號無法顯示

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='時間/秒')
ax.set(xlabel='目標(biāo)函數(shù)個數(shù)', ylabel='程序運行時間',title='多目標(biāo)收斂速度')

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()

以上這篇使用Matplotlib繪制不同顏色的帶箭頭的線實例就是小編分享給大家的全部內(nèi)容了，希望能給大家一個參考，也希望大家多多支持腳本之家。

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