Python绘制三维图
Python的绘图功能强大，与matlab有得一比，当然不是专业的绘图软件，所以稍微逊色一点。对于一般绘图matlibplot足够了。mpl_toolkits.mplot3d可以用于3D图的绘制。
操作方法
- 01
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。
- 02
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)
- 03
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()
- 04
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()