在我的应用程序中,数据是在扭曲网格上采样的,我想将其重新采样到非扭曲网格上。为了测试这一点,我编写了这个程序,其中包括了扭曲的示例和一个简单函数作为数据:
from __future__ import division
import numpy as np
import scipy.interpolate as intp
import pylab as plt
# Defining some variables:
quadratic = -3/128
linear = 1/16
pn = np.poly1d([quadratic, linear,0])
pixels_x = 50
pixels_y = 30
frame = np.zeros((pixels_x,pixels_y))
x_width= np.concatenate((np.linspace(8,7.8,57) , np.linspace(7.8,8,pixels_y-57)))
def data(x,y):
z = y*(np.exp(-(x-5)**2/3) + np.exp(-(x)**2/5) + np.exp(-(x+5)**2))
return(z)
# Generating grid coordinates
yt = np.arange(380,380+pixels_y*4,4)
xt = np.linspace(-7.8,7.8,pixels_x)
X, Y = np.meshgrid(xt,yt)
Y=Y.T
X=X.T
Y_m = np.zeros((pixels_x,pixels_y))
X_m = np.zeros((pixels_x,pixels_y))
# generating distorted grid coordinates:
for i in range(pixels_y):
Y_m[:,i] = Y[:,i] - pn(xt)
X_m[:,i] = np.linspace(-x_width[i],x_width[i],pixels_x)
# Sample data:
for i in range(pixels_y):
for j in range(pixels_x):
frame[j,i] = data(X_m[j,i],Y_m[j,i])
Y_m = Y_m.flatten()
X_m = X_m.flatten()
frame = frame.flatten()
##
Y = Y.flatten()
X = X.flatten()
ipf = intp.interp2d(X_m,Y_m,frame)
interpolated_frame = ipf(xt,yt)
在这个时候,我有两个问题:
- 代码可以运行,但是出现以下警告:
警告:由于B样条系数的数量已经超过了数据点m的数量,无法再添加更多的结点。可能的原因是s或者m太小。(fp>s) kx,ky=1,1 nx,ny=54,31 m=1500 fp=0.000006 s=0.000000
- 对于我的实际应用,帧需要大约500 * 100,但是当这样做时,我得到一个MemoryError - 除了将帧拆分成几个部分之外,还有其他方法可以帮助解决这个问题吗?