matplotlib 画图笔记

matplotlib的官方网址：http://matplotlib.org/

问题 Python Matplotlib画图，在坐标轴、标题显示这五个字符 ⊥ + - ⊺ ⨁，并且保存后也能显示   http://q.cnblogs.com/q/68725/

matplotlib可以嵌入tex代码，画出的图形添加文字更加的漂亮。

 

import matplotlib.pyplot as pltimport numpy as npx = np.arange(-4, 4, 0.1)f1 = np.power(10, x)f2 = np.power(np.e, x)f3 = np.power(2, x)plt.plot(x, f1, 'r', x, f2, 'b', x, f3, 'g', linewidth = 2)plt.axis([-4, 4, -0.5, 8])plt.text(1, 7.5, r'$10^x$', fontsize = 16)plt.text(2.2, 7.5, r'$e^x$', fontsize = 16)plt.text(3.2, 7.5, r'$2^x$', fontsize = 16)plt.title('A simple example', fontsize = 16)plt.savefig('power.png', dpi = 75)plt.show()

 可参考

 http://matplotlib.org/examples/pylab_examples/mathtext_demo.html

 

import numpy as npfrom matplotlib.pyplot import figure, showfig = figure()fig.subplots_adjust(bottom=0.2)ax = fig.add_subplot(111, axisbg='y')ax.plot([1,2,3], 'r')x = np.arange(0.0, 3.0, 0.1)ax.grid(True)ax.set_xlabel(r'$\Delta_i^j$', fontsize=20)ax.set_ylabel(r'$\Delta_{i+1}^j$', fontsize=20)tex = r'$\mathcal{R}\prod_{i=\alpha_{i+1}}^\infty a_i\sin(2 \pi f x_i)$'ax.text(1, 1.6, tex, fontsize=20, va='bottom')ax.legend([r"$\sqrt{x^2}$"])ax.set_title(r'$\Delta_i^j \hspace{0.4} \mathrm{versus} \hspace{0.4} \Delta_{i+1}^j$', fontsize=20)show()

 

比如数据格式是

 

最后一列表示的是归属的类别， 读入Python的数据returnMat

 

画出如下效果的图示

 

 

代码如下：

import matplotlib.pyplot as pltcolors = ['red', 'green', 'blue']for i in range(3):        x = returnMat[returnMat[:, 3] == (i + 1)][:, 1]    y = returnMat[returnMat[:, 3] == (i + 1)][:, 2]    scale = 30.0*(i + 1)    color = colors[i]    plt.scatter(x, y,  c = color, s = scale, label = color, alpha=0.3, edgecolors='none')plt.legend(("Don't like", "Ordianry", "Very good"), loc = "best")plt.ylabel('Video')plt.xlabel('Fly')plt.title('Test')plt.show()

 

 

 

演示MatPlotLib中如何设置坐标轴主刻度标签和次刻度标签

#!/usr/bin/env python 2 #-*- coding: utf-8 -*-  3 #--------------------------------------------------- 4 #演示MatPlotLib中设置坐标轴主刻度标签和次刻度标签. 5  6 #对于次刻度显示,如果要使用默认设置只要matplotlib.pyplot.minorticks_on() 7  8 #--------------------------------------------------- 9 10 from pylab import *11 from matplotlib.ticker import MultipleLocator, FormatStrFormatter12 13 #---------------------------------------------------14 15 xmajorLocator   = MultipleLocator(20) #将x主刻度标签设置为20的倍数16 xmajorFormatter = FormatStrFormatter('%5.1f') #设置x轴标签文本的格式17 xminorLocator   = MultipleLocator(5) #将x轴次刻度标签设置为5的倍数18 19 20 ymajorLocator   = MultipleLocator(0.5) #将y轴主刻度标签设置为0.5的倍数21 ymajorFormatter = FormatStrFormatter('%1.1f') #设置y轴标签文本的格式22 yminorLocator   = MultipleLocator(0.1) #将此y轴次刻度标签设置为0.1的倍数23 24  25 26 t = arange(0.0, 100.0, 1)27 s = sin(0.1*pi*t)*exp(-t*0.01)28 29 ax = subplot(111) #注意:一般都在ax中设置,不再plot中设置30 plot(t,s,'--r*')31 32  33 34 #设置主刻度标签的位置,标签文本的格式35 ax.xaxis.set_major_locator(xmajorLocator)36 ax.xaxis.set_major_formatter(xmajorFormatter)37 38 ax.yaxis.set_major_locator(ymajorLocator)39 ax.yaxis.set_major_formatter(ymajorFormatter)40 41 #显示次刻度标签的位置,没有标签文本42 ax.xaxis.set_minor_locator(xminorLocator)43 ax.yaxis.set_minor_locator(yminorLocator)44 45 ax.xaxis.grid(True, which='major') #x坐标轴的网格使用主刻度46 ax.yaxis.grid(True, which='minor') #y坐标轴的网格使用次刻度47 48 show()49 50 ##########################################################

 

 

python中matplotlib绘图中文显示问题

 

matplotlib是支持unicode编码的，出现图1的问题主要是没有找到合适的中文字体，解决方法有两个：
1.直接修改配置文件matplotlibrc
这种方法我没有试过，因为我安装的是python（x，y)，配置文件放的地方不一定一致，所以就选择了下面的方法
2.在代码中动态设置（推荐方式）
这种方式不需要修改配置文件，比较方便，推荐该方法，下面是具体步骤：
首先要再python脚本中的开头加上后面的内容：#-*- coding: utf-8 -*-，即用utf8编码
然后在代码中动态设置字体，下面是主要的几行代码
from matplotlib.font_manager import FontProperties
import matplotlib.pyplot as plt
font = FontProperties(fname=r"c:\windows\fonts\simsun.ttc", size=14) 

plt.xlabel(u"电压差(V)", fontproperties=font)
plt.ylabel(u"介质损耗角差(度)", fontproperties=font)
plt.title(u"介质损耗角和荷电状态SOC关系图",fontproperties=font)

下面举个具体的例子，因为我在网上看了很多例子，都解决不了这个问题，为了方便大家，下面贴出代码，需要的话可以直接贴过去运行：

#-*- coding: utf-8 -*-
from matplotlib.font_manager import FontProperties
import matplotlib.pyplot as plt
font = FontProperties(fname=r"c:\windows\fonts\simsun.ttc", size=14) 
plt.figure(figsize=(6,6))


x = [1,2,3,4,5,6,7,8]
y = []
for i in x:
    y.append(-(i*i)+i+3)


plt.plot(x, y)
plt.title(u'测试程序', fontproperties=font)
plt.xlabel(u'x轴', fontproperties=font)
plt.ylabel(u'y轴', fontproperties=font)
plt.grid(True)
plt.show()

下面是程序的输出

 演示如何实现Matplotlib绘图并保存图像但不显示图形的方法

使用Python的Matplotlib的时候,很多任务是批处理的,

中间需要画图,并保存图像,可是不希望每次都把图形显示出来,

可以试一下下面的脚本testplot.py:

import numpy as np

import matplotlib
matplotlib.use('Agg')

from matplotlib.pyplot import plot,savefig

x=np.linspace(-4,4,30)
y=np.sin(x);

plot(x,y,'--*b')

savefig('D:/MyFig.jpg')

 

运行一下,发现没有,图形并没有在屏幕上显示,但是已保存到文件,关键是要设置'Agg'的属性!

 

Python 画文氏图

 https://pypi.python.org/pypi/matplotlib-venn

from matplotlib import pyplot as pltimport numpy as npfrom matplotlib_venn import venn3, venn3_circlesplt.figure(figsize=(4,4))v = venn3(subsets=(1, 1, 1, 1, 1, 1, 1), set_labels = ('A', 'B', 'C'))v.get_patch_by_id('100').set_alpha(1.0)v.get_patch_by_id('100').set_color('white')v.get_label_by_id('100').set_text('Unknown')v.get_label_by_id('A').set_text('Set "A"')c = venn3_circles(subsets=(1, 1, 1, 1, 1, 1, 1), linestyle='dashed')c[0].set_lw(1.0)c[0].set_ls('dotted')plt.title("Sample Venn diagram")plt.annotate('Unknown set', xy=v.get_label_by_id('100').get_position() - np.array([0, 0.05]), xytext=(-70,-70),             ha='center', textcoords='offset points', bbox=dict(boxstyle='round,pad=0.5', fc='gray', alpha=0.1),             arrowprops=dict(arrowstyle='->', connectionstyle='arc3,rad=0.5',color='gray'))plt.show()

 

 

用Python画左右双坐标轴

http://matplotlib.org/examples/subplots_axes_and_figures/fahrenheit_celsius_scales.html

"""Demo of how to display two scales on the left and right y axis.This example uses the Fahrenheit and Celsius scales."""import matplotlib.pyplot as pltimport numpy as npdef fahrenheit2celsius(temp):    """    Returns temperature in Celsius.    """    return (5. / 9.) * (temp - 32)def convert_ax_c_to_celsius(ax_f):    """    Update second axis according with first axis.    """    y1, y2 = ax_f.get_ylim()    ax_c.set_ylim(fahrenheit2celsius(y1), fahrenheit2celsius(y2))    ax_c.figure.canvas.draw()fig, ax_f = plt.subplots()ax_c = ax_f.twinx()# automatically update ylim of ax2 when ylim of ax1 changes.ax_f.callbacks.connect("ylim_changed", convert_ax_c_to_celsius)ax_f.plot(np.linspace(-40, 120, 100))ax_f.set_xlim(0, 100)ax_f.set_title('Two scales: Fahrenheit and Celsius')ax_f.set_ylabel('Fahrenheit')ax_c.set_ylabel('Celsius')plt.show()

Python 设置标签文字的位置

http://matplotlib.org/examples/pylab_examples/fonts_demo.html

from matplotlib.font_manager import FontPropertiesimport numpy as npimport matplotlib.pylab as pltfont = FontProperties()font.set_size('large')x = np.linspace(-np.pi, np.pi, 201)plt.plot(x, np.sin(x))plt.ylabel('sin(x)')plt.title('hello world')plt.text( 2.5, -1.2, '2015-07-07', fontproperties=font)plt.axis('tight')

 内容来自 http://reverland.org/python/2012/09/07/matplotlib-tutorial/

from pylab import *X = np.linspace(-np.pi, np.pi, 256,endpoint=True)C,S = np.cos(X), np.sin(X)figure(figsize=(10,6), dpi=80)plot(X, C, color="blue", linewidth=2.5, linestyle="-")plot(X, S, color="red",  linewidth=2.5, linestyle="-")#设置边界xlim(X.min()*1.1, X.max()*1.1)ylim(C.min()*1.1, C.max()*1.1)#设置刻度xticks( [-np.pi, -np.pi/2, 0, np.pi/2, np.pi])yticks([-1, 0, +1])#设置刻度标签xticks([-np.pi, -np.pi/2, 0, np.pi/2, np.pi],[r'$-\pi$', r'$-\pi/2$', r'$0$', r'$+\pi/2$', r'$+\pi$'])yticks([-1, 0, +1],[r'$-1$', r'$0$', r'$+1$'])#移动轴线ax = gca()ax.spines['right'].set_color('none')ax.spines['top'].set_color('none')ax.xaxis.set_ticks_position('bottom')ax.spines['bottom'].set_position(('data',0))ax.yaxis.set_ticks_position('left')ax.spines['left'].set_position(('data',0))#添加图例plot(X, C, color="blue", linewidth=2.5, linestyle="-", label="cosine")plot(X, S, color="red",  linewidth=2.5, linestyle="-", label="sine")legend(loc='upper left')#注解某些点t = 2*np.pi/3plot([t,t],[0,np.cos(t)], color ='blue', linewidth=2.5, linestyle="--")scatter([t,],[np.cos(t),], 50, color ='blue')annotate(r'$sin(\frac{2\pi}{3})=\frac{\sqrt{3}}{2}$',         xy=(t, np.sin(t)), xycoords='data',         xytext=(+10, +30), textcoords='offset points', fontsize=16,         arrowprops=dict(arrowstyle="->", connectionstyle="arc3,rad=.2"))plot([t,t],[0,np.sin(t)], color ='red', linewidth=2.5, linestyle="--")scatter([t,],[np.sin(t),], 50, color ='red')annotate(r'$cos(\frac{2\pi}{3})=-\frac{1}{2}$',         xy=(t, np.cos(t)), xycoords='data',         xytext=(-90, -50), textcoords='offset points', fontsize=16,         arrowprops=dict(arrowstyle="->", connectionstyle="arc3,rad=.2"))         #魔鬼在于细节for label in ax.get_xticklabels() + ax.get_yticklabels():    label.set_fontsize(16)    label.set_bbox(dict(facecolor='white', edgecolor='None', alpha=0.65 ))