将一个数字范围转换为另一个范围，保持比率

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

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)
  }
}

2020-08-21 17:19:52

其他回答

捷径/简化方案

 NewRange/OldRange = Handy multiplicand or HM
 Convert OldValue in OldRange to NewValue in NewRange = 
 (OldValue - OldMin x HM) + NewMin

韦恩

2015-04-08 04:30:54

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; }

2014-11-25 22:11:12

这是一个简单的线性变换。

new_value = ( (old_value - old_min) / (old_max - old_min) ) * (new_max - new_min) + new_min

因此，将10000在-16000到16000的范围内转换为0到100的新范围会得到:

old_value = 10000
old_min = -16000
old_max = 16000
new_min = 0
new_max = 100

new_value = ( ( 10000 - -16000 ) / (16000 - -16000) ) * (100 - 0) + 0
          = 81.25

2009-05-30 05:50:45

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

2019-08-20 10:32:21

下面是一些简单的Python函数，便于复制和粘贴，包括一个扩展整个列表的函数。

def scale_number(unscaled, to_min, to_max, from_min, from_max):
    return (to_max-to_min)*(unscaled-from_min)/(from_max-from_min)+to_min

def scale_list(l, to_min, to_max):
    return [scale_number(i, to_min, to_max, min(l), max(l)) for i in l]

可以这样使用:

scale_list([1,3,4,5], 0, 100)

[0.0, 50.0, 75.0, 100.0]

在我的例子中，我想缩放一条对数曲线，像这样:

scale_list([math.log(i+1) for i in range(5)], 0, 50)

[0.0, 21.533827903669653, 34.130309724299266, 43.06765580733931, 50.0]

2017-02-07 16:32:06

将一个数字范围转换为另一个范围，保持比率

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