Python matplotib 画图

Posted

tags:

篇首语:本文由小常识网(cha138.com)小编为大家整理,主要介绍了Python matplotib 画图相关的知识,希望对你有一定的参考价值。

使用Python 程序来生成可视化图像,具有明确的表达性。

demo1:曲线图和直线图

技术分享
#!/usr/bin/env python
# -*- coding: utf-8 -*-

import numpy as np
import matplotlib.pyplot as plt

t = np.arange(0.0, 1.01, 0.01)
s = np.sin(2*2*np.pi*t)

plt.fill(t, s*np.exp(-5*t), r)
plt.grid(True)

#保存为PDF格式,也可保存为PNG等图形格式
plt.savefig(test.png)
plt.show()
View Code

 技术分享

技术分享
import numpy as np
import matplotlib.pyplot as plt
x=np.linspace(0,10,1000)
y=np.sin(x)
z=np.cos(x**2)

plt.figure(figsize=(8,4))


plt.plot(x,y,label=$sin(x)$,color=red,linewidth=2)

plt.plot(x,z,g--,label=$cos(x^2)$,lw=3)

plt.xlabel(Time(s))
plt.ylabel(volt)
plt.title(First python firgure)
plt.ylim(-1.2,1.2)
plt.legend()
plt.savefig("test.png")
plt.show()
View Code

技术分享

 

技术分享
import numpy as np
import matplotlib.pyplot as plt


# A class that will downsample the data and recompute when zoomed.
class DataDisplayDownsampler(object):
    def __init__(self, xdata, ydata):
        self.origYData = ydata
        self.origXData = xdata
        self.ratio = 5
        self.delta = xdata[-1] - xdata[0]

    def downsample(self, xstart, xend):
        # Very simple downsampling that takes the points within the range
        # and picks every Nth point
        mask = (self.origXData > xstart) & (self.origXData < xend)
        xdata = self.origXData[mask]
        xdata = xdata[::self.ratio]

        ydata = self.origYData[mask]
        ydata = ydata[::self.ratio]

        return xdata, ydata

    def update(self, ax):
        # Update the line
        lims = ax.viewLim
        if np.abs(lims.width - self.delta) > 1e-8:
            self.delta = lims.width
            xstart, xend = lims.intervalx
            self.line.set_data(*self.downsample(xstart, xend))
            ax.figure.canvas.draw_idle()

# Create a signal
xdata = np.linspace(16, 365, 365-16)
ydata = np.sin(2*np.pi*xdata/153) + np.cos(2*np.pi*xdata/127)

d = DataDisplayDownsampler(xdata, ydata)

fig, ax = plt.subplots()

# Hook up the line
d.line, = ax.plot(xdata, ydata, o-)
ax.set_autoscale_on(False)  # Otherwise, infinite loop

# Connect for changing the view limits
ax.callbacks.connect(xlim_changed, d.update)
plt.savefig("test.png")
plt.show()
View Code

 

技术分享

技术分享
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import numpy as np
import matplotlib.pyplot as plt
plt.figure(1) # 创建图表1
plt.figure(2) # 创建图表2
ax1 = plt.subplot(211) # 在图表2中创建子图1
ax2 = plt.subplot(212) # 在图表2中创建子图2
x = np.linspace(0, 3, 100)
for i in xrange(5):
    plt.figure(1)  #? # 选择图表1
    plt.plot(x, np.exp(i*x/3))
    plt.sca(ax1)   #? # 选择图表2的子图1
    plt.plot(x, np.sin(i*x))
    plt.sca(ax2)  # 选择图表2的子图2
    plt.plot(x, np.cos(i*x))
plt.savefig("test.png")
plt.show()
View Code

技术分享

技术分享
import matplotlib.pyplot as plt
X1 = range(0, 50)
Y1 = [num**2 for num in X1] # y = x^2
X2 = [0, 1]
Y2 = [0, 1]  # y = x
Fig = plt.figure(figsize=(8,4))                      # Create a `figure‘ instance
Ax = Fig.add_subplot(111)               # Create a `axes‘ instance in the figure
Ax.plot(X1, Y1, X2, Y2)                 # Create a Line2D instance in the axes
Fig.show()
Fig.savefig("test.png"
View Code

技术分享

技术分享
import numpy as np
import pylab as pl
x = [1, 2, 3, 4, 5]# Make an array of x values
y = [1, 4, 9, 16, 25]# Make an array of y values for each x value
pl.plot(x, y)# use pylab to plot x and y
pl.show()# show the plot on the screen
View Code

技术分享

技术分享
#!/usr/bin/env python
import matplotlib.pyplot as plt

plt.plot([10, 20, 30])
plt.xlabel(times)
plt.ylabel(numbers)
plt.savefig("test.png")
plt.show()
View Code

技术分享

技术分享
import matplotlib.pyplot as plt
import matplotlib.pylab as pylab
import scipy.io
import numpy as np
# params={
    # ‘axes.labelsize‘: ‘35‘,
    # ‘xtick.labelsize‘:‘27‘,
    # ‘ytick.labelsize‘:‘27‘,
    # ‘lines.linewidth‘:2 ,
    # ‘legend.fontsize‘: ‘27‘,
    # ‘figure.figsize‘   : ‘12, 9‘    # set figure size
# }
# pylab.rcParams.update(params)            #set figure parameter
line_styles=[ro-,b^-,gs-,ro--,b^--,gs--]  #set line style

#We give the coordinate date directly to give an example.
x1 = [-20,-15,-10,-5,0,0,5,10,15,20]
y1 = [0,0.04,0.1,0.21,0.39,0.74,0.78,0.80,0.82,0.85]
y2 = [0,0.014,0.03,0.16,0.37,0.78,0.81,0.83,0.86,0.92]
y3 = [0,0.001,0.02,0.14,0.34,0.77,0.82,0.85,0.90,0.96]
y4 = [0,0,0.02,0.12,0.32,0.77,0.83,0.87,0.93,0.98]
y5 = [0,0,0.02,0.11,0.32,0.77,0.82,0.90,0.95,1]


plt.plot(x1,y1,bo-,label=m=2, p=10%,markersize=20) # in ‘bo-‘, b is blue, o is O marker, - is solid line and so on
plt.plot(x1,y2,gv-,label=m=4, p=10%,markersize=20)
plt.plot(x1,y3,ys-,label=m=6, p=10%,markersize=20)
plt.plot(x1,y4,ch-,label=m=8, p=10%,markersize=20)
plt.plot(x1,y5,mD-,label=m=10, p=10%,markersize=20)



fig1 = plt.figure(1)
axes = plt.subplot(111)
#axes = plt.gca()
axes.set_yticks([0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,1.0])
axes.grid(True)  # add grid

plt.legend(loc="lower right")  #set legend location
plt.ylabel(Percentage)   # set ystick label
plt.xlabel(Difference)  # set xstck label

plt.savefig(test.png,dpi = 1000,bbox_inches=tight)
plt.show()
View Code

技术分享

demo2:饼图

技术分享
#!/usr/bin/env python
# -*- coding: utf-8 -*-

from pylab import *

# make a square figure and axes
figure(1, figsize=(6,6))
ax = axes([0.1, 0.1, 0.8, 0.8])

labels = Frogs, Hogs, Dogs, Logs
fracs = [15,30,45, 10]

explode=(0, 0.05, 0, 0)
pie(fracs, explode=explode, labels=labels, autopct=%1.1f%%, shadow=True)
title(Raining Hogs and Dogs, bbox={facecolor:0.8, pad:5})
savefig(pie.png)
show()
View Code

技术分享

技术分享
import matplotlib.pyplot as plt
for idx,color in enumerate(rgbyck):
    plt.subplot(321+idx,axisbg=color)
plt.savefig("test.png")
plt.show()
View Code

技术分享

 

demo3:柱状图

技术分享
import scipy.io
import numpy as np
import matplotlib.pylab as pylab
import matplotlib.pyplot as plt
import matplotlib.ticker as mtick
# params={
    # ‘axes.labelsize‘: ‘35‘,
    # ‘xtick.labelsize‘:‘27‘,
    # ‘ytick.labelsize‘:‘27‘,
    # ‘lines.linewidth‘:2 ,
    # ‘legend.fontsize‘: ‘27‘,
    # ‘figure.figsize‘   : ‘24, 9‘
# }
# pylab.rcParams.update(params)


y1 = [9.79,7.25,7.24,4.78,4.20]
y2 = [5.88,4.55,4.25,3.78,3.92]
y3 = [4.69,4.04,3.84,3.85,4.0]
y4 = [4.45,3.96,3.82,3.80,3.79]
y5 = [3.82,3.89,3.89,3.78,3.77]



ind = np.arange(5)                # the x locations for the groups
width = 0.15
plt.bar(ind,y1,width,color = blue,label = m=2)
plt.bar(ind+width,y2,width,color = g,label = m=4) # ind+width adjusts the left start location of the bar.
plt.bar(ind+2*width,y3,width,color = c,label = m=6)
plt.bar(ind+3*width,y4,width,color = r,label = m=8)
plt.bar(ind+4*width,y5,width,color = m,label = m=10)
plt.xticks(np.arange(5) + 2.5*width, (10%,15%,20%,25%,30%))

plt.xlabel(Sample percentage)
plt.ylabel(Error rate)

fmt = %.0f%% # Format you want the ticks, e.g. ‘40%‘
xticks = mtick.FormatStrFormatter(fmt)
# Set the formatter
axes = plt.gca()   # get current axes
axes.yaxis.set_major_formatter(xticks) # set % format to ystick.
axes.grid(True)
plt.legend(loc="upper right")
plt.savefig(test.png, format=png,dpi = 1000,bbox_inches=tight)

plt.show()
View Code

 

技术分享

demo4:网状图

技术分享
import networkx as nx
import pylab as plt
g = nx.Graph()
g.add_edge(1,2,weight = 4)
g.add_edge(1,3,weight = 7)
g.add_edge(1,4,weight = 8)
g.add_edge(1,5,weight = 3)
g.add_edge(1,9,weight = 3)
 
g.add_edge(1,6,weight = 6)
g.add_edge(6,7,weight = 7)
g.add_edge(6,8,weight = 7) 
 
g.add_edge(6,9,weight = 6)
g.add_edge(9,10,weight = 7)
g.add_edge(9,11,weight = 6)
 
 
 
fixed_pos = {1:(1,1),2:(0.7,2.2),3:(0,1.8),4:(1.6,2.3),5:(2,0.8),6:(-0.6,-0.6),7:(-1.3,0.8), 8:(-1.5,-1), 9:(0.5,-1.5), 10:(1.7,-0.8), 11:(1.5,-2.3)} #set fixed layout location
 
 
 
#pos=nx.spring_layout(g) # or you can use other layout set in the module
nx.draw_networkx_nodes(g,pos = fixed_pos,nodelist=[1,2,3,4,5],
node_color = g,node_size = 600)
nx.draw_networkx_edges(g,pos = fixed_pos,edgelist=[(1,2),(1,3),(1,4),(1,5),(1,9)],edge_color=g,width = [4.0,4.0,4.0,4.0,4.0],label = [1,2,3,4,5],node_size = 600)
 
 
nx.draw_networkx_nodes(g,pos = fixed_pos,nodelist=[6,7,8],
node_color = r,node_size = 600)
nx.draw_networkx_edges(g,pos = fixed_pos,edgelist=[(6,7),(6,8),(1,6)],width = [4.0,4.0,4.0],edge_color=r,node_size = 600)
 
nx.draw_networkx_nodes(g,pos = fixed_pos,nodelist=[9,10,11],
node_color = b,node_size = 600)
nx.draw_networkx_edges(g,pos = fixed_pos,edgelist=[(6,9),(9,10),(9,11)],width = [4.0,4.0,4.0],edge_color=b,node_size = 600)
 
plt.text(fixed_pos[1][0],fixed_pos[1][1]+0.2, s = 1,fontsize = 40)
plt.text(fixed_pos[2][0],fixed_pos[2][1]+0.2, s = 2,fontsize = 40)
plt.text(fixed_pos[3][0],fixed_pos[3][1]+0.2, s = 3,fontsize = 40)
plt.text(fixed_pos[4][0],fixed_pos[4][1]+0.2, s = 4,fontsize = 40)
plt.text(fixed_pos[5][0],fixed_pos[5][1]+0.2, s = 5,fontsize = 40)
plt.text(fixed_pos[6][0],fixed_pos[6][1]+0.2, s = 6,fontsize = 40)
plt.text(fixed_pos[7][0],fixed_pos[7][1]+0.2, s = 7,fontsize = 40)
plt.text(fixed_pos[8][0],fixed_pos[8][1]+0.2, s = 8,fontsize = 40)
plt.text(fixed_pos[9][0],fixed_pos[9][1]+0.2, s = 9,fontsize = 40)
plt.text(fixed_pos[10][0],fixed_pos[10][1]+0.2, s = 10,fontsize = 40)
plt.text(fixed_pos[11][0],fixed_pos[11][1]+0.2, s = 11,fontsize = 40)
 
plt.show()
View Code

技术分享

 

以上是关于Python matplotib 画图的主要内容,如果未能解决你的问题,请参考以下文章

怎么用python画图

python可以画图吗

Python语言画图

python海龟画图怎么把背景变成黑色

python画图的问题~

python画图无法显示中文 python画图显示中文乱码