''' Provide an intro to image manipulation
'''

from PIL import Image

# UVA official colors
blue   = (   0,  47, 108 )                              # UVA BLUE
orange = ( 229, 114,   0 )                              # UVA ORANGE

def wahoo( original ) :
    ''' wahoo-fy a picture -- for each pixel in the original there is a 50% chance
            it will be the same in the copy, 25% chance it will be UVA blue, and a
            25% chance it will be UVA orange
    '''

    # get dimensions of original
    ow, oh = original.size

    # set dimensions of new image
    nw, nh = ow, oh
    
    # get a new appropriately sized image
    new_image = Image.new( 'RGB', ( nw, nh ) )
    
    # fill in every pixel of the new image
    for nx in range( 0, nw ) :                          # consider all possible x values
        for ny in range( 0, nh ) :                      # consider all possible y values

            # set the spot to be filled in the new image
            nspot = ( nx, ny )
    
            # determine the corresponding spot of interest in original
            ospot = ( nx, ny )
    
            # get the pixel at the ospot
            opixel = original.getpixel( ospot )
    
            # determine the pixel for the new image 
            npixel = ...
    
            # set the nspot in the new image
            new_image.putpixel( nspot, npixel )
    
    # return the filled in new image
    return new_image

if ( __name__ == '__main__' ) :
    import url                                   # get web image support

    id =  input( "Enter email id: " )            # get id of interest

    person = url.get_selfie( id )                # get their class photo

    wahooed = wahoo( person )                    # wahoo-them

    wahooed.show()                               # go wahoos