Calculate RGB value for a range of values to create heat map

I am trying to create a heat map with python. For this I have to assign an RGB value to every value in the range of possible values. I thought of changing the color from blue (minimal value) over green to red (maximal value).

The picture example below explains how I thought of the color composition: We have a range from 1 (pure blue) to 3 (pure red), 2 is in between resembled by green.

I read about linear interpolation and wrote a function that (more or less) handles the calculation for a certain value in the range between a minimum and a maximum and returns an RGB tuple. It uses if and elif conditions (which does not make me completely happy):

def convert_to_rgb(minimum, maximum, value):
    minimum, maximum = float(minimum), float(maximum)    
    halfmax = (minimum + maximum) / 2
    if minimum <= value <= halfmax:
        r = 0
        g = int( 255./(halfmax - minimum) * (value - minimum))
        b = int( 255. + -255./(halfmax - minimum)  * (value - minimum))
        return (r,g,b)    
    elif halfmax < value <= maximum:
        r = int( 255./(maximum - halfmax) * (value - halfmax))
        g = int( 255. + -255./(maximum - halfmax)  * (value - halfmax))
        b = 0
        return (r,g,b)

However I wonder if one could write a function for each color value without using if conditions. Does anybody have an idea? Thank you a lot!

Solution 1:

def rgb(minimum, maximum, value):
    minimum, maximum = float(minimum), float(maximum)
    ratio = 2 * (value-minimum) / (maximum - minimum)
    b = int(max(0, 255*(1 - ratio)))
    r = int(max(0, 255*(ratio - 1)))
    g = 255 - b - r
    return r, g, b

Solution 2:

Here's another way to do it that, while not as absolutely short as possible, is much more general since it hasn't been hardcoded for your specific set of colors. This means it can also be used to linearly interpolate a specified range of values over a variably-sized palette of arbitrary colors.

Also note that colors could have been interpolated in other colorspaces giving results that may be more pleasing than in others. This is illustrated in the different results obtained from the two separate answers I submitted to a related question titled Range values to pseudocolor.

import sys
EPSILON = sys.float_info.epsilon  # Smallest possible difference.

def convert_to_rgb(minval, maxval, val, colors):
    # `colors` is a series of RGB colors delineating a series of
    # adjacent linear color gradients between each pair.

    # Determine where the given value falls proportionality within
    # the range from minval->maxval and scale that fractional value
    # by the total number in the `colors` palette.
    i_f = float(val-minval) / float(maxval-minval) * (len(colors)-1)

    # Determine the lower index of the pair of color indices this
    # value corresponds and its fractional distance between the lower
    # and the upper colors.
    i, f = int(i_f // 1), i_f % 1  # Split into whole & fractional parts.

    # Does it fall exactly on one of the color points?
    if f < EPSILON:
        return colors[i]
    else: # Return a color linearly interpolated in the range between it and 
          # the following one.
        (r1, g1, b1), (r2, g2, b2) = colors[i], colors[i+1]
        return int(r1 + f*(r2-r1)), int(g1 + f*(g2-g1)), int(b1 + f*(b2-b1))

if __name__ == '__main__':
    minval, maxval = 1, 3
    steps = 10
    delta = float(maxval-minval) / steps
    colors = [(0, 0, 255), (0, 255, 0), (255, 0, 0)]  # [BLUE, GREEN, RED]
    print('  Val       R    G    B')
    for i in range(steps+1):
        val = minval + i*delta
        r, g, b = convert_to_rgb(minval, maxval, val, colors)
        print('{:.3f} -> ({:3d}, {:3d}, {:3d})'.format(val, r, g, b))

Numeric output:

  Val       R    G    B
1.000 -> (  0,   0, 255)
1.200 -> (  0,  50, 204)
1.400 -> (  0, 101, 153)
1.600 -> (  0, 153, 101)
1.800 -> (  0, 204,  50)
2.000 -> (  0, 255,   0)
2.200 -> ( 51, 203,   0)
2.400 -> (102, 152,   0)
2.600 -> (153, 101,   0)
2.800 -> (203,  51,   0)
3.000 -> (255,   0,   0)

Here's the output visualized as a horizontal gradient: