Python matplotlib模块，是扩展的MATLAB的一个绘图工具库，它可以绘制各种图形
建议安装 Anaconda后使用 ，集成了很多第三库，基本满足大家的需求，下载地址，对应选择python 2.7 或是 3.5 的就可以了： https://www.continuum.io/downloads#windows
脚本默认执行方式： 1.获取当前文件夹下的1.log文件 2.将数据格式化为矩阵 3.以矩阵的列索引为x坐标，行索引为y坐标，值为z坐标 4.绘制曲面图 测试数据 测试所用数据： r_gain= 79.000000f, 89.000000f, 104.000000f, 120.000000f, 135.000000f, 149.000000f, 160.000000f, 172.000000f, 176.000000f, 172.000000f, 164.000000f, 159.000000f, 143.000000f, 128.000000f, 113.000000f, 97.000000f, 81.000000f, r_gain= 84.000000f, 100.000000f, 120.000000f, 136.000000f, 156.000000f, 176.000000f, 192.000000f, 204.000000f, 208.000000f, 204.000000f, 196.000000f, 180.000000f, 164.000000f, 144.000000f, 124.000000f, 108.000000f, 92.000000f, r_gain= 91.000000f, 112.000000f, 132.000000f, 156.000000f, 176.000000f, 200.000000f, 224.000000f, 240.000000f, 248.000000f, 244.000000f, 228.000000f, 208.000000f, 188.000000f, 164.000000f, 140.000000f, 120.000000f, 99.000000f, r_gain= 99.000000f, 120.000000f, 144.000000f, 172.000000f, 200.000000f, 228.000000f, 256.000000f, 276.000000f, 284.000000f, 280.000000f, 264.000000f, 240.000000f, 208.000000f, 180.000000f, 156.000000f, 132.000000f, 105.000000f, r_gain=107.000000f, 128.000000f, 156.000000f, 184.000000f, 216.000000f, 256.000000f, 288.000000f, 308.000000f, 320.000000f, 316.000000f, 296.000000f, 264.000000f, 228.000000f, 196.000000f, 164.000000f, 140.000000f, 113.000000f, r_gain=111.000000f, 132.000000f, 160.000000f, 192.000000f, 232.000000f, 272.000000f, 304.000000f, 332.000000f, 340.000000f, 336.000000f, 316.000000f, 284.000000f, 244.000000f, 204.000000f, 172.000000f, 144.000000f, 117.000000f, r_gain=109.000000f, 136.000000f, 164.000000f, 196.000000f, 232.000000f, 276.000000f, 312.000000f, 336.000000f, 348.000000f, 344.000000f, 320.000000f, 288.000000f, 248.000000f, 208.000000f, 172.000000f, 144.000000f, 117.000000f, r_gain=111.000000f, 132.000000f, 160.000000f, 192.000000f, 228.000000f, 268.000000f, 304.000000f, 328.000000f, 340.000000f, 332.000000f, 312.000000f, 280.000000f, 240.000000f, 200.000000f, 168.000000f, 140.000000f, 119.000000f, r_gain=101.000000f, 128.000000f, 152.000000f, 180.000000f, 212.000000f, 248.000000f, 280.000000f, 304.000000f, 312.000000f, 308.000000f, 288.000000f, 260.000000f, 224.000000f, 192.000000f, 160.000000f, 136.000000f, 109.000000f, r_gain= 95.000000f, 116.000000f, 140.000000f, 164.000000f, 192.000000f, 224.000000f, 248.000000f, 272.000000f, 280.000000f, 272.000000f, 256.000000f, 232.000000f, 200.000000f, 176.000000f, 152.000000f, 128.000000f, 101.000000f, r_gain= 87.000000f, 108.000000f, 128.000000f, 148.000000f, 172.000000f, 192.000000f, 216.000000f, 232.000000f, 236.000000f, 232.000000f, 220.000000f, 200.000000f, 180.000000f, 156.000000f, 136.000000f, 116.000000f, 95.000000f, r_gain= 80.000000f, 96.000000f, 112.000000f, 132.000000f, 148.000000f, 168.000000f, 180.000000f, 192.000000f, 196.000000f, 196.000000f, 184.000000f, 172.000000f, 156.000000f, 136.000000f, 120.000000f, 104.000000f, 88.000000f, r_gain= 69.000000f, 85.000000f, 96.000000f, 111.000000f, 127.000000f, 141.000000f, 153.000000f, 160.000000f, 164.000000f, 159.000000f, 157.000000f, 145.000000f, 135.000000f, 120.000000f, 104.000000f, 88.000000f, 77.000000f,曲面图脚本 # -*- coding: utf-8 -*- from matplotlib import pyplot as plt from mpl_toolkits.mplot3d import Axes3D from pandas import DataFrame def draw(x, y, z): ''' 采用matplolib绘制曲面图 :param x: x轴坐标数组 :param y: y轴坐标数组 :param z: z轴坐标数组 :return: ''' X = x Y = y Z = z fig = plt.figure() ax = fig.add_subplot( 111 , projection = '3d' ) ax.plot_trisurf(X, Y, Z) plt.show() if __name__ = = '__main__' : ''' 默认执行方式： 1.获取当前文件夹下的1.log文件 2.将数据格式化为矩阵 3.以矩阵的列索引为x坐标，行索引为y坐标，值为z坐标 4.绘制曲面图 ''' data = {} index_origin = 0 f = open ( "1.log" ) line = f.readline() while line: data[index_origin] = line.split( '=' )[ - 1 ].replace( ' ' , ' ').split(' f,')[ 0 : - 1 ] index_origin = index_origin + 1 line = f.readline() f.close() df = DataFrame(data) df = df.T x = [] for i in range ( len (df.index)): x = x + list (df.columns) print (x) y = [] for i in range ( len (df.index)): for m in range ( 17 ): y.append(i) print (y) z = [] for i in range ( len (df.index)): z = z + df[i:i + 1 ].values.tolist()[ 0 ] z = map ( float , z) print (z) draw(x, y, z)
