快捷導(dǎo)航

python通過文本在一個圖中畫多條線的實例

更新時間：2020年02月21日 17:03:28 作者：MR小飛俠

今天小編就為大家分享一篇python通過文本在一個圖中畫多條線的實例，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

廢話不多說，直接上代碼吧！

import matplotlib.pyplot as plt
import numpy as np
 
data1 = np.loadtxt('/data_1/SSD/caffe/tools/extra/DSOD300_VOC0712_DSOD300_300x300.log.test')
data2 = np.loadtxt('/data_1/SSD/caffe/tools/extra/DSOD300_VOC0712_DSOD300_300x300.log.train')
 
plt.title('Result Analysis')
 
plt.plot(data1[:,0], data1[:,2], color='skyblue', label='y1')
plt.plot(data2[:,0], data2[:,3], color='blue', label='y2')
plt.legend()
 
plt.xlabel('x')
plt.ylabel('y')
plt.show()

結(jié)果：

加一些不同形式的線

import matplotlib.pyplot as plt
import numpy as np
 
data1 = np.loadtxt('/data_1/project_test/teest1.txt')
data2 = np.loadtxt('/data_1/project_test/teest2.txt')
data3 = np.loadtxt('/data_1/project_test/teest3.txt')
 
plt.title('Result Analysis')
 
plt.plot(data1[:,0], data1[:,1], color='skyblue', label='y1',ls='-.')#ls或linestyle
plt.plot(data2[:,0], data2[:,1], color='green', label='y2',ls=':')
plt.plot(data3[:,0], data3[:,1], color='red', label='y3',ls='steps')
plt.legend()
 
plt.xlabel('x')
plt.ylabel('y')
plt.show()

加標(biāo)記

import matplotlib.pyplot as plt
import numpy as np
 
data1 = np.loadtxt('/data_1/project_test/teest1.txt')
data2 = np.loadtxt('/data_1/project_test/teest2.txt')
data3 = np.loadtxt('/data_1/project_test/teest3.txt')
 
plt.title('Result Analysis')
 
plt.plot(data1[:,0], data1[:,1], color='skyblue', label='y1',ls='-.',marker='*')
plt.plot(data2[:,0], data2[:,1], color='green', label='y2',ls=':',marker='+')
plt.plot(data3[:,0], data3[:,1], color='red', label='y3',ls='steps',marker='D')
plt.legend()
 
plt.xlabel('x')
plt.ylabel('y')
plt.show()

總結(jié)：

linestyle or ls：實線'-' ，破折線'--' , 點劃線'-.' ，虛線':'

plt.plot()參數(shù)設(shè)置
Property Value Type
alpha 控制透明度，0為完全透明，1為不透明
animated [True False]
antialiased or aa [True False]
clip_box a matplotlib.transform.Bbox instance
clip_on [True False]
clip_path a Path instance and a Transform instance, a Patch
color or c 顏色設(shè)置
contains the hit testing function
dash_capstyle [‘butt' ‘round' ‘projecting']
dash_joinstyle [‘miter' ‘round' ‘bevel']
dashes sequence of on/off ink in points
data 數(shù)據(jù)(np.array xdata, np.array ydata)
figure 畫板對象a matplotlib.figure.Figure instance
label 圖示
linestyle or ls 線型風(fēng)格[‘-' ‘–' ‘-.' ‘:' ‘steps' …]
linewidth or lw 寬度float value in points
lod [True False]
marker 數(shù)據(jù)點的設(shè)置[‘+' ‘,' ‘.' ‘1' ‘2' ‘3' ‘4']
markeredgecolor or mec any matplotlib color
markeredgewidth or mew float value in points
markerfacecolor or mfc any matplotlib color
markersize or ms float
markevery [ None integer (startind, stride) ]
picker used in interactive line selection
pickradius the line pick selection radius
solid_capstyle [‘butt' ‘round' ‘projecting']
solid_joinstyle [‘miter' ‘round' ‘bevel']
transform a matplotlib.transforms.Transform instance
visible [True False]
xdata np.array
ydata np.array

zorder any number

補充拓展：python 畫直線和平面實例

畫直線

from mpl_toolkits.axisartist.axislines import SubplotZero
import matplotlib.pyplot as plt
import numpy as np
 
fig = plt.figure(1)
ax = SubplotZero(fig, 111)
fig.add_subplot(ax)
 
for direction in ["xzero", "yzero"]:
  # adds arrows at the ends of each axis
  ax.axis[direction].set_axisline_style("-|>")
 
  # adds X and Y-axis from the origin
  ax.axis[direction].set_visible(True)
 
for direction in ["left", "right", "bottom", "top"]:
  # hides borders
  ax.axis[direction].set_visible(False)
  
plt.text(-2, 2, r"y=kx+b",
     horizontalalignment='center', fontsize=20)  
  
x = np.linspace(-2,2,100)  
   
k=-1
b=0  
  
y = k*x + b
 
ax.plot(x, y)
plt.show()

畫平面

import matplotlib.pyplot as plt
from matplotlib import cm
import numpy as np
 
fig = plt.figure()
ax = fig.gca(projection='3d')
 
# Make data.
X = np.arange(-5, 5, 0.25)
Y = np.arange(-5, 5, 0.25)
X, Y = np.meshgrid(X, Y)
a1 = 2
a2 = 1
Z = a1*X+a2*Y
 
# Plot the surface.
surf = ax.plot_surface(X, Y, Z, cmap=cm.Blues,
            linewidth=0, antialiased=False)
 
ax.set_xlabel(r'$x_1$',fontsize = 20, color = 'blue')
ax.set_ylabel(r'$x_2$',fontsize = 20, color = 'blue')
ax.set_zlabel(r'$x_3$',fontsize = 20, color = 'blue')