我试图将一个范围的数字转换为另一个,保持比率。数学不是我的强项。
I have an image file where point values may range from -16000.00 to 16000.00 though the typical range may be much less. What I want to do is compress these values into the integer range 0-100, where 0 is the value of the smallest point, and 100 is the value of the largest. All points in between should keep a relative ratio even though some precision is being lost I'd like to do this in python but even a general algorithm should suffice. I'd prefer an algorithm where the min/max or either range can be adjusted (ie, the second range could be -50 to 800 instead of 0 to 100).
我个人使用支持泛型的helper类(Swift 3,4)。x兼容)
struct Rescale<Type : BinaryFloatingPoint> {
typealias RescaleDomain = (lowerBound: Type, upperBound: Type)
var fromDomain: RescaleDomain
var toDomain: RescaleDomain
init(from: RescaleDomain, to: RescaleDomain) {
self.fromDomain = from
self.toDomain = to
}
func interpolate(_ x: Type ) -> Type {
return self.toDomain.lowerBound * (1 - x) + self.toDomain.upperBound * x;
}
func uninterpolate(_ x: Type) -> Type {
let b = (self.fromDomain.upperBound - self.fromDomain.lowerBound) != 0 ? self.fromDomain.upperBound - self.fromDomain.lowerBound : 1 / self.fromDomain.upperBound;
return (x - self.fromDomain.lowerBound) / b
}
func rescale(_ x: Type ) -> Type {
return interpolate( uninterpolate(x) )
}
}
Ex:
let rescaler = Rescale<Float>(from: (-1, 1), to: (0, 100))
print(rescaler.rescale(0)) // OUTPUT: 50
我写了一个函数用R来做这个,方法和上面一样,但是我需要在R中做很多次,所以我想分享一下,以防它对任何人有帮助。
convertRange <- function(
oldValue,
oldRange = c(-16000.00, 16000.00),
newRange = c(0, 100),
returnInt = TRUE # the poster asked for an integer, so this is an option
){
oldMin <- oldRange[1]
oldMax <- oldRange[2]
newMin <- newRange[1]
newMax <- newRange[2]
newValue = (((oldValue - oldMin)* (newMax - newMin)) / (oldMax - oldMin)) + newMin
if(returnInt){
return(round(newValue))
} else {
return(newValue)
}
}
我没有为此挖掘BNF,但Arduino文档有一个很好的函数示例,它是分解的。我可以在Python中通过简单地添加一个def重命名到remap(因为map是内置的)并删除类型强制转换和花括号(即删除所有的'long')来使用它。
原始
long map(long x, long in_min, long in_max, long out_min, long out_max)
{
return (x - in_min) * (out_max - out_min) / (in_max - in_min) + out_min;
}
Python
def remap(x, in_min, in_max, out_min, out_max):
return (x - in_min) * (out_max - out_min) / (in_max - in_min) + out_min
https://www.arduino.cc/en/reference/map