recursive_art.py

""" TODO: Put your header comment here """

import random
import math 
from PIL import Image


def build_random_function(min_depth, max_depth):
    """ Builds a random function of depth at least min_depth and depth
        at most max_depth (see assignment writeup for definition of depth
        in this context)
        
        depth is how nested the functions is 

        min_depth: the minimum depth of the random function
        max_depth: the maximum depth of the random function
        returns: the randomly generated function represented as a nested list
                 (see assignment writeup for details on the representation of
                 these functions)
    """
    random_function = ["prod","avg","cos_pi","sin_pi","x","y","squares","sin_pi_sqr","something"]

    my_func = random.choice(random_function) #assigning random func for each recurse

    if max_depth == 0:
        return random.choice(["x","y"]) 
    else:
        if my_func == "prod" or "avg":
            return [my_func, build_random_function(min_depth, max_depth-1), build_random_function(min_depth, max_depth-1)]
        else:   
            return [my_func, build_random_function(min_depth, max_depth-1)]


def evaluate_random_function(f, x, y):
    """ Evaluate the random function f with inputs x,y
        Representation of the function f is defined in the assignment writeup

        f: the function to evaluate
        x: the value of x to be used to evaluate the function
        y: the value of y to be used to evaluate the function
        returns: the function value

        >>> evaluate_random_function(["x"],-0.5, 0.75)
        -0.5
        >>> evaluate_random_function(["y"],0.1,0.02)
        0.02
    """
    function = f[0] # now function is a string 

    if function == "x": # base case (look at diagram)
        return x 
    elif function == "y": # another base case (look at diagram)
        return y 
    elif function == "prod": 
        return evaluate_random_function(f[1],x,y) * evaluate_random_function(f[2],x,y)
    elif function == "avg": 
        return 0.5 * (evaluate_random_function(f[1],x,y) + evaluate_random_function(f[2],x,y))
    elif function == "cos_pi": 
        return math.cos(math.pi*evaluate_random_function(f[1],x,y))
    elif function == "sin_pi":
        return math.sin(math.pi*evaluate_random_function(f[1],x,y))
    elif function == "squares":
        return evaluate_random_function(f[1],x,y)**2 + evaluate_random_function(f[1],x,y)**3
    elif function == "sin_pi_sqr":
        return math.sin(math.pi*evaluate_random_function(f[1],x,y)**2) + evaluate_random_function(f[1],x,y)
    elif function == "something":
        return evaluate_random_function(f[1],x,y) * math.sin(evaluate_random_function(f[1],x,y))


def remap_interval(val,
                   input_interval_start,
                   input_interval_end,
                   output_interval_start,
                   output_interval_end):
    """ Given an input value in the interval [input_interval_start,
        input_interval_end], return an output value scaled to fall within
        the output interval [output_interval_start, output_interval_end].

        val: the value to remap
        input_interval_start: the start of the interval that contains all
                              possible values for val
        input_interval_end: the end of the interval that contains all possible
                            values for val
        output_interval_start: the start of the interval that contains all
                               possible output values
        output_inteval_end: the end of the interval that contains all possible
                            output values
        returns: the value remapped from the input to the output interval

        >>> remap_interval(0.5, 0, 1, 0, 10)
        5.0
        >>> remap_interval(5, 4, 6, 0, 2)
        1.0
        >>> remap_interval(5, 4, 6, 1, 2)
        1.5
    """
    # Here is some math to remap the old (input) value to the new (output) interval
    # It looks for the proportion of the value and then maps that on to the new interval

    numerator = input_interval_end - float(val)
    denominator = input_interval_end - input_interval_start
    proportion = numerator / denominator 

    interval_range = output_interval_end - output_interval_start
    result = (interval_range * proportion) + output_interval_start # remapped val

    return result


def color_map(val):
    """ Maps input value between -1 and 1 to an integer 0-255, suitable for
        use as an RGB color code.

        val: value to remap, must be a float in the interval [-1, 1]
        returns: integer in the interval [0,255]

        >>> color_map(-1.0)
        0
        >>> color_map(1.0)
        255
        >>> color_map(0.0)
        127
        >>> color_map(0.5)
        191
    """
    # NOTE: This relies on remap_interval, which you must provide
    color_code = remap_interval(val, -1, 1, 0, 255)
    return int(color_code)


def test_image(filename, x_size=350, y_size=350):
    """ Generate test image with random pixels and save as an image file.

        filename: string filename for image (should be .png)
        x_size, y_size: optional args to set image dimensions (default: 350)
    """
    # Create image and loop over all pixels
    im = Image.new("RGB", (x_size, y_size))
    pixels = im.load()
    for i in range(x_size):
        for j in range(y_size):
            x = remap_interval(i, 0, x_size, -1, 1)
            y = remap_interval(j, 0, y_size, -1, 1)
            pixels[i, j] = (random.randint(0, 255),  # Red channel
                            random.randint(0, 255),  # Green channel
                            random.randint(0, 255))  # Blue channel

    im.save(filename)


def generate_art(filename, x_size=350, y_size=350):
    """ Generate computational art and save as an image file.

        filename: string filename for image (should be .png)
        x_size, y_size: optional args to set image dimensions (default: 350)
    """
    # Functions for red, green, and blue channels - where the magic happens!
    red_function = build_random_function(1,1)
    green_function = build_random_function(1,9)
    blue_function = build_random_function(1,7)

    # Create image and loop over all pixels
    im = Image.new("RGB", (x_size, y_size))
    pixels = im.load()
    for i in range(x_size):
        for j in range(y_size):
            x = remap_interval(i, 0, x_size, -1, 1)
            y = remap_interval(j, 0, y_size, -1, 1)
            pixels[i, j] = (
                    color_map(evaluate_random_function(red_function, x, y)),
                    color_map(evaluate_random_function(green_function, x, y)),
                    color_map(evaluate_random_function(blue_function, x, y))
                    )

    im.save(filename)


if __name__ == '__main__':
    # import doctest
    # doctest.testmod()
    # doctest.run_docstring_examples(remap_interval, globals(),verbose = True)

    # Create some computational art!
    # TODO: Un-comment the generate_art function call after you
    #       implement remap_interval and evaluate_random_function
    generate_art("myart19.png")

    # Test that PIL is installed correctly
    # TODO: Comment or remove this function call after testing PIL install
    # test_image("noise.png")