Step by Step solution about How to resolve the algorithm Color wheel step by step in the Python programming language

Detailed Explanation of Python Code to Draw a Rainbow Circle:

1. Image Creation:

• The code begins by creating a new RGB image of size (300, 300) using the Image.new method.

2. Constants and Image Properties:

• radius is set to half the minimum dimension of the image.
• cx and cy are the center coordinates of the image.
• pix is the image pixel data, which can be accessed and modified.

3. Iterating Over Image Pixels:

• The code enters a double loop that iterates over every pixel in the image.

4. Calculating Pixel Position:

• For each pixel, rx and ry are calculated as the horizontal and vertical distances from the pixel to the center of the image.

5. Calculating Saturation (s):

• s is calculated as the square root of the sum of the squared distances, i.e., the distance from the center divided by the radius.

6. Check if Pixel is Within the Circle:

• If s is less than or equal to 1.0, indicating that the pixel is within the circle, the following steps are performed.

7. Calculating Hue (h):

• h is calculated as the angle between the pixel position and the positive x-axis, normalized to the range [0.0, 1.0].

8. Converting to RGB:

• The hue (h), saturation (s), and value (1.0) are converted to RGB colors using the colorsys.hsv_to_rgb function.

9. Setting Pixel Color:

• The RGB color tuple is converted to integers and assigned to the pixel at the current (x, y) coordinates.

10. Image Display:

• After all pixels are processed, the image is displayed using the im.show() method.

Overall Effect:

The code creates a circular gradient of colors, resulting in a rainbow-like effect within the circle drawn on the image. The outer pixels are pure white (s = 0), while the inner pixels transition through the colors of the spectrum based on their distance from the center.

from PIL import Image
import colorsys
import math

if __name__ == "__main__":

    im = Image.new("RGB", (300,300))
    radius = min(im.size)/2.0
    cx, cy = im.size[0]/2, im.size[1]/2
    pix = im.load()
 
    for x in range(im.width):
        for y in range(im.height):
            rx = x - cx
            ry = y - cy
            s = (rx ** 2.0 + ry ** 2.0) ** 0.5 / radius
            if s <= 1.0:
                h = ((math.atan2(ry, rx) / math.pi) + 1.0) / 2.0
                rgb = colorsys.hsv_to_rgb(h, s, 1.0)
                pix[x,y] = tuple([int(round(c*255.0)) for c in rgb])

    im.show()