我有以下简单的
Python函数：
def get_lerp_factor( a,x,b ):
if x <= a: return 0.
if x >= b: return 1.
return (x - a) / (b - a)
许多numpy函数,如numpy.sin(x)可以处理浮点数或数组.
那么如何以相同的方式扩展它,以便它还可以处理x的numpy数组？
def get_lerp_factor( a,x_maybe_array,b ):
out = (x_maybe_array - a) / (b - a) # this should work...
# but now I have to clamp each element of out between 0 and 1
我是否必须专门检查x的类型,并相应地进行分支？
怎么样：
def get_lerp_factor( a,x_anything,b ):
x = np.array( x_anything )
out = ...(x)
# now typecast out back into the same type as x... will this work?
？
解决方法
你需要
numpy.asarray.这是第一个参数：
Input data,in any form that can be converted to an array. This includes lists,lists of tuples,tuples,tuples of tuples,tuples of lists and ndarrays.
它返回：
Array interpretation of
a. No copy is performed if the input is already an ndarray.
所以你可以像这样实现你的功能：
import numpy as np
def get_lerp_factor(a,b):
a,b = np.asarray(a),np.asarray(x),np.asarray(b)
return ((x - a) / (b - a)).clip(0,1)
这适用于标量：
>>> get_lerp_factor(0,9,16) 0.5625
以及迭代：
>>> get_lerp_factor(2,range(8),6) array([ 0.,0.,0.25,0.5,0.75,1.,1. ])
