利用ICESat角点数据通过最小二乘精化DEM

# -*- coding:utf-8 -*-
import numpy as np
from scipy.optimize import leastsq
import xlrd
data = xlrd.open_workbook('icesat.xls')
table = data.sheets()[0]
nrows = table.nrows
ncols = table.ncols
usedata = []
for i in range(nrows):
    #删除0值点
    if table.cell(i, 4).value != 0:
        usedata.append(table.row_values(i))
#删除名字
usedata.pop(0)
#每n个点采样（n=3）
usedata = usedata[ ::3 ]
usedata = np.array(usedata)
usedata_T = np.transpose(usedata)
h_icesat = usedata_T[3]
def_topo = usedata_T[4]
h_2000 = 1000
g_X = usedata_T[5]
g_Y = usedata_T[6]
funY = h_icesat-h_2000-(h_2000*def_topo)
def func(p,x,y):
    a,b,c,d,e,f = p
    return a+b*x+c*y+d*x*y+e*x**2+f*y**2
def error(p,x,y,Z,s):
    print( s )
    return func(p, x, y)-Z
Z0 = np.zeros(6)
s = "Test the number of iteration"
Para = leastsq(error, Z0, args=(g_X, g_Y, funY, s))
a, b, c, d, e, f = Para[0]
print(a, b, c, d, e, f)
err = []
for j in range(len(usedata)):
    err.append((func(Para[0], g_X[j], g_Y[j])-funY[j]))
print (err)
f = open('result.txt', 'w+')
for m in Para[0]:
    f.write(str(m))
    f.write('\n')
f1 = open('error.txt', 'w+')
for n in err:
    f1.write(str(n))
    f1.write('\n')