使用python代替MATLAB进行绘图（二）使用python进行绘图（二）

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我是靠谱客的博主阔达书本，最近开发中收集的这篇文章主要介绍使用python代替MATLAB进行绘图（二）使用python进行绘图（二），觉得挺不错的，现在分享给大家，希望可以做个参考。

概述

使用python进行绘图（二）

条形图：

#!  conda env
# -*- coding:utf-8 -*-
# Time:2020/4/9 10:57 上午
# Author : nishizzma
# File : barEx.py

import numpy as np
import matplotlib.pyplot as plt

n = 12
X = np.arange(n)
"""
numpy.random.uniform(low,high,size)
从一个均匀分布[low,high)中随机采样，注意定义域是左闭右开，即包含low，不包含high.
"""
Y1 = (1-X/float(n)) * np.random.uniform(0.5,1.0,n)
Y2 = (1-X/float(n)) * np.random.uniform(0.5,1.0,n)

plt.axes([0.025,0.025,0.95,0.95])
"""
bar(x, height, width=0.8, bottom=None, ***, align='center', data=None, **kwargs)
"""
plt.bar(X,+Y1,facecolor='#9999FF',edgecolor='white')
plt.bar(X,-Y2,facecolor='#ff9999',edgecolor='white')

#对数轴进行一个数字表示
for x,y in zip(X,Y1):
    plt.text(x+0.4, y+0.05, '%.2f' % y, ha='center', va= 'bottom')

for x,y in zip(X,Y2):
    plt.text(x+0.4, -y-0.05, '%.2f' % y, ha='center', va= 'top')

plt.xlim(-.5,n), plt.xticks([])
plt.ylim(-1.25,+1.25), plt.yticks([])


plt.show()

等高线图：

#!  conda env
# -*- coding:utf-8 -*-
# Time:2020/4/9 11:19 上午
# Author : nishizzma
# File : contourEx.py


import numpy as np
import matplotlib.pyplot as plt

def f(x,y):
    return (1-x/2+x**5+y**3)*np.exp(-x**2-y**2)

n = 256
x = np.linspace(-3,3,n)
y = np.linspace(-3,3,n)
X,Y = np.meshgrid(x,y)

plt.axes([0.025,0.025,0.95,0.95])

#cmap:可选参数，可以转换为热力图
plt.contourf(X, Y, f(X,Y), 8, alpha=.75, cmap=plt.cm.hot)
C = plt.contour(X, Y, f(X,Y), 8, colors='black', linewidth=.5)
plt.clabel(C, inline=1, fontsize=10)

plt.xticks([]), plt.yticks([])
plt.show()

灰度图：

#!  conda env
# -*- coding:utf-8 -*-
# Time:2020/4/9 11:40 上午
# Author : nishizzma
# File : imshowEx.py

import numpy as np
import matplotlib.pyplot as plt

def f(x,y):
    return (1-x/2+x**5+y**3)*np.exp(-x**2-y**2)

n = 10
x = np.linspace(-3,3,3.5*n)
y = np.linspace(-3,3,3.0*n)
X,Y = np.meshgrid(x,y)
Z = f(X,Y)

plt.axes([0.025,0.025,0.95,0.95])
plt.imshow(Z,interpolation='bicubic', cmap='bone', origin='lower')
plt.colorbar(shrink=.92)

plt.xticks([]), plt.yticks([])

plt.show()

饼状图：

#!  conda env
# -*- coding:utf-8 -*-
# Time:2020/4/9 11:48 上午
# Author : nishizzma
# File : pieEx.py


import numpy as np
import matplotlib.pyplot as plt

n = 20
Z = np.ones(n)
Z[-1] *= 2

plt.axes([0.025, 0.025, 0.95, 0.95])

plt.pie(Z, explode=Z*.05, colors=['%f' % (i/float(n)) for i in range(n)],
        wedgeprops={"linewidth": 1, "edgecolor": "black"})

plt.gca().set_aspect('equal')
plt.xticks([]), plt.yticks([])

plt.show()

极坐标图：

#!  conda env
# -*- coding:utf-8 -*-
# Time:2020/4/9 11:58 上午
# Author : nishizzma
# File : polarEx.py


import numpy as np
import matplotlib.pyplot as plt

ax = plt.axes([0.025,0.025,0.95,0.95], polar=True)

N = 20
theta = np.arange(0.0, 2*np.pi, 2*np.pi/N)
radii = 10*np.random.rand(N)
width = np.pi/4*np.random.rand(N)
bars = plt.bar(theta, radii, width=width, bottom=0.0)

for r,bar in zip(radii, bars):
    bar.set_facecolor( plt.cm.jet(r/10.))
    bar.set_alpha(0.5)

ax.set_xticklabels([])
ax.set_yticklabels([])

plt.show()

散点图：

#!  conda env
# -*- coding:utf-8 -*-
# Time:2020/4/9 10:40 上午
# Author : nishizzma
# File : scatterDiagram.py

import numpy as np
import matplotlib.pyplot as plt

n = 1024
X = np.random.normal(0,1,n)
Y = np.random.normal(0,1,n)
T = np.arctan2(Y,X)

plt.axes([0.025,0.025,0.95,0.95])
#这里的c是控制颜色的，也应该与X，Y格式相同
plt.scatter(X,Y, s=75, c=T, alpha=.5)

plt.xlim(-1.5,1.5), plt.xticks([])
plt.ylim(-1.5,1.5), plt.yticks([])
# savefig('../figures/scatter_ex.png',dpi=48)

plt.show()

随机生成文字图：

#!  conda env
# -*- coding:utf-8 -*-
# Time:2020/4/9 11:49 上午
# Author : nishizzma
# File : testEx.py

import numpy as np
import matplotlib.pyplot as plt

#首先将公式存入列表中
eqs = []
eqs.append((r"$W^{3beta}_{delta_1 rho_1 sigma_2} = U^{3beta}_{delta_1 rho_1} + frac{1}{8 pi 2} int^{alpha_2}_{alpha_2} d alpha^prime_2 left[frac{ U^{2beta}_{delta_1 rho_1} - alpha^prime_2U^{1beta}_{rho_1 sigma_2} }{U^{0beta}_{rho_1 sigma_2}}right]$"))
eqs.append((r"$frac{drho}{d t} + rho vec{v}cdotnablavec{v} = -nabla p + munabla^2 vec{v} + rho vec{g}$"))
eqs.append((r"$int_{-infty}^infty e^{-x^2}dx=sqrt{pi}$"))
eqs.append((r"$E = mc^2 = sqrt{{m_0}^2c^4 + p^2c^2}$"))
eqs.append((r"$F_G = Gfrac{m_1m_2}{r^2}$"))


plt.axes([0.025,0.025,0.95,0.95])

#采用循环进行多次打印
for i in range(24):
    index = np.random.randint(0,len(eqs))
    eq = eqs[index]
    size = np.random.uniform(12,32)
    x,y = np.random.uniform(0,1,2)
    alpha = np.random.uniform(0.25,.75)
    plt.text(x, y, eq, ha='center', va='center', color="#11557c", alpha=alpha,
             transform=plt.gca().transAxes, fontsize=size, clip_on=True)

plt.xticks([]), plt.yticks([])

plt.show()
"""
如果对于循环的变量进行一定的设置，然后在写入一些限制条件，就可以多样化的输出文字
"""

三维立体图：

#!  conda env
# -*- coding:utf-8 -*-
# Time:2020/4/9 11:57 上午
# Author : nishizzma
# File : threeD.py


import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D

fig = plt.figure()
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)
Z = np.sin(R)

ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=plt.cm.hot)
ax.contourf(X, Y, Z, zdir='z', offset=-2, cmap=plt.cm.hot)
ax.set_zlim(-2,2)

plt.show()