我正在尝试使用 scipy.ndimage.filters.generic_filter 来计算邻域的加权和。邻域在某些时候会发生变化,但目前我正在努力实现 3x3。 到目前为止,这就是我所在的位置:
def Func(a):
a = np.reshape((3,3))
weights = np.array([[0.5,.05,0.5],[0.5,1,0.5],[0.5,0.5,0.5]])
a = np.multiply(a,weights)
a = np.sum(a)
return a
ndimage.filters.generic_filter(Array,Func,
footprint=np.ones((3,3)),mode='constant',cval=0.0,origin=0.0)
我从 ndimage 收到一个错误,提示“TypeError: a float is required”,但我不知道它指的是什么参数,它看起来与我见过的其他示例基本相同。
这对我有用。 代码有几个小问题:
import scipy.ndimage.filters
import numpy as np
Array = rand( 100,100 )
def Func(a):
a = a.reshape((3,3))
weights = np.array([[0.5,.05,0.5],[0.5,1,0.5],[0.5,0.5,0.5]])
a = np.multiply(a,weights)
a = np.sum(a)
return a
out = scipy.ndimage.filters.generic_filter(Array,Func,footprint=np.ones((3,3)),mode='constant',cval=0.0,origin=0.0)
您的
a = np.reshape( (3,3) )
是不正确的。这就是你想要的吗?
[更新]
根据我们的讨论对此进行一些清理:
import scipy.ndimage.filters
import numpy as np
Array = rand( 100,100 )
def Func(a):
return np.sum( a * r_[0.5,.05,0.5, 0.5,1,0.5, 0.5,0.5,0.5] )
out = scipy.ndimage.filters.generic_filter(Array,Func,footprint=np.ones((3,3)),mode='constant',cval=0.0,origin=0.0)