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python 三维坐标图

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内容图文

绘制3D柱状图，其数据格式为，二维数组或三维数组。

from numpy import *

file=open(‘C:\\Users\\jyjh\\Desktop\\count.txt‘,‘r‘)

arr=[]

for i in file.readlines():

temp=[]

for j in i.strip().split(‘\t‘):

temp.append(float(j))

arr.append(temp)

import random

import numpy as np

import matplotlib as mpl

import matplotlib.pyplot as plt

from mpl_toolkits.mplot3d import Axes3D

mpl.rcParams[‘font.size‘]=10

fig=plt.figure()

ax=fig.add_subplot(111,projection=‘3d‘)

xs=range(len(arr))

ys=range(len(arr[0]))

for z in range(len(arr)):

xs=range(len(arr))

ys=arr[z]

color=plt.cm.Set2(random.choice(range(plt.cm.Set2.N)))

ax.bar(xs,ys,zs=z,zdir=‘y‘,color=color,alpha=0.5)

ax.xaxis.set_major_locator(mpl.ticker.FixedLocator(xs))

ax.yaxis.set_major_locator(mpl.ticker.FixedLocator(ys))

ax.set_xlabel(‘x‘)

ax.set_ylabel(‘y‘)

ax.set_zlabel(‘copies‘)

plt.show()

通过设置xs，ys，z可以设定绘制不同维度的数据。
绘制热图：

import numpy as np

from matplotlib import pyplot as plt

from matplotlib import cm

from matplotlib import axes

def draw_heatmap(data,xlabels,ylabels):

#cmap = cm.get_cmap(‘rainbow‘,1000)

cmap=cm.gray

figure=plt.figure(facecolor=‘w‘)

ax=figure.add_subplot(2,1,1,position=[1,1,1,1])

ax.set_yticks(range(len(ylabels)))

ax.set_yticklabels(ylabels)

ax.set_xticks(range(len(xlabels)))

ax.set_xticklabels(xlabels)

vmax=data[0][0]

vmin=data[0][0]

for i in data:

for j in i:

if j>vmax:

vmax=j

if j<vmin:

vmin=j

map=ax.imshow(data,interpolation=‘nearest‘,cmap=cmap,aspect=‘auto‘,vmin=vmin,vmax=vmax)

cb=plt.colorbar(mappable=map,cax=None,ax=None,shrink=0.8)

plt.show()

xl=range(16)

yl=range(16)

draw_heatmap(arr,xl,yl)
绘制曲面图

from matplotlib import pyplot as plt

import numpy as np

from mpl_toolkits.mplot3d import Axes3D

figure = plt.figure()

ax = Axes3D(figure)

X = np.arange(-10, 10, 0.25)

Y = np.arange(-10, 10, 0.25)

#网格化数据

X, Y = np.meshgrid(X, Y)

R = np.sqrt(X**2 + Y**2)

Z = np.cos(R)

ax.plot_surface(X, Y, Z, rstride=1, cstride=1, cmap=‘rainbow‘)

plt.show()
绘制曲线图

from mpl_toolkits.mplot3d import Axes3D

import numpy as np

import matplotlib.pyplot as plt

#生成画布

figure=plt.figure()

ax=figure.add_subplot(111,projection=‘3d‘)

#生成向量

z=np.linspace(0,6,1000)

r=1

x=r*np.sin(np.pi*2*z)

y=r*np.cos(np.pi*2*z)

ax.plot(x,y,z)

plt.show()