pythonpandas & matplotlib 数据处理 绘制曲面图

Posted 2020-08-23

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)