python绘图——坐标轴

1. 2D坐标轴

1.1 绘制简单的曲线

import matplotlib.pyplot as pltimport numpy as npx=np.linspace(-1,1,50)#-1到1中画50个点y=x**2plt.plot(x,y,color='green')plt.tick_params(axis='x',colors='blue')plt.tick_params(axis='y',colors='red')plt.show()

作图：

1.2 坐标轴的刻度线向内

import matplotlib.pyplot as pltimport numpy as npx=np.linspace(-1,1,50)#-1到1中画50个点y=x**2# 下面两行代码要放在plt.plot的前面plt.rcParams['xtick.direction'] = 'in'#将x轴的刻度线方向设置向内plt.rcParams['ytick.direction'] = 'in'#将y轴的刻度线方向设置向内plt.plot(x,y,color='green')plt.tick_params(axis='x',colors='blue')plt.tick_params(axis='y',colors='red')plt.show()

1.3 将坐标刻度从整0开始

plt.margins(x=0)plt.margins(y=0)#设置坐标轴范围#plt.ylim([0,0.8])#plt.xlim([0,0.75])

1.4 设置刻度栅格

简单的刻度：

plt.grid()

主刻度和次刻度

import matplotlib.pyplot as pltimport numpy as npplt.figure(figsize=(17,3))ax = plt.gca()ax.xaxis.set_major_locator(plt.MultipleLocator(0.2))    #设置x轴主刻度ax.xaxis.set_minor_locator(plt.MultipleLocator(0.04))   #设置x轴次刻度ax.yaxis.set_major_locator(plt.MultipleLocator(0.5))    #设置x轴次刻度ax.yaxis.set_minor_locator(plt.MultipleLocator(0.1))    #设置x轴次刻度ax.grid(which='major',axis="both",linewidth=0.75,linestyle='-',color='r')ax.grid(which='minor',axis="both",linewidth=0.25,linestyle='-',color='r')x=np.linspace(0,3*np.pi,50)#-1到1中画50个点y=2*np.sin(x)plt.plot(x,y)plt.margins(x=0)plt.margins(y=0)plt.show()

下面的图形类似于心电图纸绘制，关于心电图相关的绘制，具体在使用python绘制心电图中体现：

1.5 不显示坐标

只是坐标刻度不可见，两种方式的效果一样

# plt.xticks([])plt.yticks([])# 或者下面的# frame.axes.get_xaxis().set_visible(False) # x 轴不可见frame.axes.get_yaxis().set_visible(False) # y 轴不可见

关闭两者坐标轴，只有曲线图形

plt.axis('off')

1.6 坐标值

为坐标设置刻度值, 并且将刻度值旋转45度

import matplotlib.pyplot as pltimport numpy as npx=np.linspace(0,2,50)#-1到1中画50个点y=x**2plt.rcParams['xtick.direction'] = 'in'#将x轴的刻度线方向设置向内plt.rcParams['ytick.direction'] = 'in'#将y轴的刻度线方向设置向内ax = plt.gca()xlabel=[str(val)+'_1' for val in range(100,110)]ax.set_xticklabels(xlabel)plt.xticks(rotation = 45)plt.plot(x,y,color='green')plt.tick_params(axis='x',colors='blue')plt.tick_params(axis='y',colors='red')plt.margins(x=0)plt.margins(y=0)plt.show()

1.7 绘制横线和竖线

plt.axvline(1)plt.axhline(1.5)

1.8 设置坐标点的颜色

下图中设置y轴第3个坐标值的颜色为黄色，x轴第6个坐标值颜色为绿色。

import matplotlib.pyplot as pltimport numpy as npx=np.linspace(0,2,50)#-1到1中画50个点y=x**2plt.rcParams['xtick.direction'] = 'in'#将x轴的刻度线方向设置向内plt.rcParams['ytick.direction'] = 'in'#将y轴的刻度线方向设置向内ax = plt.gca()plt.plot(x,y,color='green')plt.tick_params(axis='x',colors='blue')plt.tick_params(axis='y',colors='red')ax.get_yticklabels()[3].set_color("y")ax.get_xticklabels()[6].set_color("g")plt.show()

1.9 双坐标

代码如下：

import numpy as npimport matplotlib.pyplot as pltt = np.arange(0.01, 10.0, 0.01)data1 = np.exp(t)data2 = np.sin(2 * np.pi * t)fig, ax1 = plt.subplots()color = 'tab:red'ax1.set_xlabel('time (s)')ax1.set_ylabel('exp', color=color)ax1.plot(t, data1, color=color)ax1.tick_params(axis='y', labelcolor=color)ax2 = ax1.twinx()  # instantiate a second axes that shares the same x-axiscolor = 'tab:blue'ax2.set_ylabel('sin', color=color)  # we already handled the x-label with ax1ax2.plot(t, data2, color=color)ax2.tick_params(axis='y', labelcolor=color)fig.tight_layout()  # otherwise the right y-label is slightly clippedplt.show()

1.10 坐标设置汉字

plt.rcParams['font.sans-serif']=['SimHei'] #用来正常显示中文标签plt.rcParams['axes.unicode_minus']=False #用来正常显示负号

2. 3D坐标轴

2.1 绘制3D散点图

关键代码ax.scatter(xs, ys, zs, c=c, marker=m),输入数据xs,ys,zs是相同长度的一维数据。c是颜色，marker是散点类型。

from mpl_toolkits.mplot3d import Axes3Dimport matplotlib.pyplot as pltimport numpy as npdef randrange(n, vmin, vmax):    return (vmax - vmin)*np.random.rand(n) + vminfig = plt.figure()ax = fig.add_subplot(111, projection='3d') n = 100for c, m, zlow, zhigh in [('r', '*', -10, 20), ('b', 'o', -30, -10)]:    xs = randrange(n, 23, 32)    ys = randrange(n, 0, 100)    zs = randrange(n, zlow, zhigh)    ax.scatter(xs, ys, zs, c=c, marker=m)ax.set_xlabel('X Label')ax.set_ylabel('Y Label')ax.set_zlabel('Z Label')plt.show()

2.2 绘制3D曲面图

import numpy as npimport matplotlib.pyplot as pltfrom mpl_toolkits.mplot3d import Axes3Dfig=plt.figure(num=1,figsize=(8,6))ax = Axes3D(fig)X = np.arange(-4, 4, 0.25)Y = np.arange(-4, 4, 0.25)X, Y = np.meshgrid(X, Y)R = np.sqrt(X ** 2 + Y ** 2)# height valueZ = np.cos(R)ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=plt.get_cmap('rainbow'),edgecolors='white')ax.contourf(X, Y, Z, zdir='z', offset=-2, cmap=plt.get_cmap('rainbow'))#投影等高线,改变zdir='x', offset=-4实现投影到不同坐标轴     ax.set_zlim(-2, 2)ax.tick_params(axis='x',colors='g')ax.tick_params(axis='y',colors='g')ax.tick_params(axis='z',colors='g')plt.show()

2.3 绘制3D柱形图

import numpy as npimport matplotlib.pyplot as pltfrom mpl_toolkits.mplot3d import Axes3Dfrom matplotlib import cmX=np.arange(0, 9, step=1)#X轴的坐标Y=np.arange(0, 10, step=1)#Y轴的坐标arr = [[np.random.randint(1,50) for i in range(9)] for i in range(10)]Z = np.array(arr)xx, yy=np.meshgrid(X, Y)#网格化坐标X, Y=xx.ravel(), yy.ravel()#矩阵扁平化bottom=np.zeros_like(X)#设置柱状图的底端位值Z=Z.ravel()#扁平化矩阵width=height=0.8#每一个柱子的长和宽#绘图设置fig=plt.figure()ax=fig.gca(projection='3d')#三维坐标轴ax.bar3d(X, Y, bottom, width, height, Z, shade=True,color='lightgreen')##坐标轴设置ax.set_xlabel('X')ax.set_ylabel('Y')ax.set_zlabel('Z')plt.show()

引用

[1]Matplotlib 文档
[2]python绘制三维图
[3]python-绘制3D柱形图
[4]Python + matplotlib更改纵横坐标刻度颜色
[5]Python绘图总结(Matplotlib篇)之坐标轴及刻度