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).


当前回答

在由PenguinTD提供的清单中,我不明白为什么范围是颠倒的,它不需要颠倒范围就能工作。线性范围转换基于线性方程Y=Xm+n,其中m和n是从给定的范围推导出来的。与其将范围称为min和max,不如将它们称为1和2。所以公式是:

Y = (((X - x1) * (y2 - y1)) / (x2 - x1)) + y1

当X=x1时Y=y1,当X=x2时Y=y2。X1, x2, y1和y2可以取任意正值或负值。在宏中定义表达式使其更有用,它可以与任何参数名称一起使用。

#define RangeConv(X, x1, x2, y1, y2) (((float)((X - x1) * (y2 - y1)) / (x2 - x1)) + y1)

在所有实参都是整数值的情况下,浮点强制转换将确保浮点除法。 根据应用程序的不同,可能不需要检查x1=x2和y1==y2的范围。

其他回答

Java版本

不管你喂它什么,它都能工作!

我把所有内容都展开了,这样便于学习。当然,最后舍入是可选的。

    private long remap(long p, long Amin, long Amax, long Bmin, long Bmax ) {

    double deltaA = Amax - Amin;
    double deltaB = Bmax - Bmin;
    double scale  = deltaB / deltaA;
    double negA   = -1 * Amin;
    double offset = (negA * scale) + Bmin;
    double q      = (p * scale) + offset;
    return Math.round(q);

}

列出理解一行的解决方案

color_array_new = [int((((x - min(node_sizes)) * 99) / (max(node_sizes) - min(node_sizes))) + 1) for x in node_sizes]

完整版

def colour_specter(waste_amount):
color_array = []
OldRange = max(waste_amount) - min(waste_amount)
NewRange = 99
for number_value in waste_amount:
    NewValue = int((((number_value - min(waste_amount)) * NewRange) / OldRange) + 1)
    color_array.append(NewValue)
print(color_array)
return color_array

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)
  }
}
NewValue = (((OldValue - OldMin) * (NewMax - NewMin)) / (OldMax - OldMin)) + NewMin

或者更容易读懂:

OldRange = (OldMax - OldMin)  
NewRange = (NewMax - NewMin)  
NewValue = (((OldValue - OldMin) * NewRange) / OldRange) + NewMin

或者如果你想保护旧范围为0的情况(OldMin = OldMax):

OldRange = (OldMax - OldMin)
if (OldRange == 0)
    NewValue = NewMin
else
{
    NewRange = (NewMax - NewMin)  
    NewValue = (((OldValue - OldMin) * NewRange) / OldRange) + NewMin
}

注意,在这种情况下,我们被迫任意选择一个可能的新范围值。根据上下文,明智的选择可能是:NewMin(见示例),NewMax或(NewMin + NewMax) / 2

C++变体

我发现PenguinTD的解决方案很有用,所以我把它移植到c++,如果有人需要它:

float remap(float x, float oMin, float oMax, float nMin, float nMax ){ //range check if( oMin == oMax) { //std::cout<< "Warning: Zero input range"; return -1; } if( nMin == nMax){ //std::cout<<"Warning: Zero output range"; return -1; } //check reversed input range bool reverseInput = false; float oldMin = min( oMin, oMax ); float oldMax = max( oMin, oMax ); if (oldMin == oMin) reverseInput = true; //check reversed output range bool reverseOutput = false; float newMin = min( nMin, nMax ); float newMax = max( nMin, nMax ); if (newMin == nMin) reverseOutput = true; float portion = (x-oldMin)*(newMax-newMin)/(oldMax-oldMin); if (reverseInput) portion = (oldMax-x)*(newMax-newMin)/(oldMax-oldMin); float result = portion + newMin; if (reverseOutput) result = newMax - portion; return result; }