draw.py

draw.py

import ImageDraw
import Image


def draw_circle(draw, x, y, r, color=(0, 0, 0), bg=(255, 255, 255), d=2):
        draw.ellipse((x - r, y - r, x + r, y + r), fill=color)
        r -= d
        draw.ellipse((x - r, y - r, x + r, y + r), fill=bg)


def draw_net(filename, size=35, circle_k=0.8, students=24, lessons=6, border=2, supersampling_k=2):
    """
    Generates the net table blank by given data

    :param filename: path to output image file
    :param size: size of the table cell
    :param circle_k: circle diameter / cell size
    :param students: number of students
    :param lessons: number of lessons
    :param border: border in pixels
    :param supersampling_k: upscale number
    """
    size *= supersampling_k  # upscaling the cell size

    # COLOR CONSTANTS
    WHITE = (255, 255, 255)
    BLACK = (0,   0,   0)

    # Calculating the width and height
    width = int((2 + students) * size)
    height = int((2 + lessons) * size)
    image_size = (width, height)  # packing to the tuple

    # Creating new image and initializing draw object
    im = Image.new('RGB', image_size)
    draw = ImageDraw.Draw(im)

    # filling with white color
    draw.rectangle((0, 0, width, height), WHITE)                  # fill

    # drawing markets
    draw.rectangle((0, 0, size, size), BLACK)                           # TL
    draw.rectangle((width-size, 0, width, size), BLACK)                 # TR
    draw.rectangle((width-size, height - size, width, height), BLACK)   # BR
    draw.rectangle((0, height - size, size, height), BLACK)             # BL

    # drawing circles
    circle_r = (size/2) * circle_k
    for student in range(0, students):
        for lesson in range(0, lessons):
            x = size * (1.5 + student)    # size + 0.5*size + size*student
            y = size * (1.5 + lesson)     # size + 0.5*size + size*lesson
            draw_circle(draw, x, y, circle_r, BLACK, WHITE, border)
    # text_pos = (10, 10)
    # draw.text(text_pos, 'Test', (255, 0, 0))
    # downscaling
    im.thumbnail((int(width/supersampling_k), int(height/supersampling_k)), Image.ANTIALIAS)
    im.save(filename)


# print devices
if __name__ == '__main__':
    import argparse

    parser = argparse.ArgumentParser(description='CyWarden blank generator')
    parser.add_argument('output', help='Output image file')
    parser.add_argument('-students', default=24, help='Number of students (default=24)', type=int)
    parser.add_argument('-lessons', default=6, help='Number of lessons (default=6)', type=int)
    parser.add_argument('-size', default=30, help='Cell size (default=30)', type=int)
    parser.add_argument('-border', default=2, help='Border in pixels (default=2)', type=int)
    parser.add_argument('-sampling', default=2.0, help='Supersampling k (default=2)', type=float)
    parser.add_argument('-ratio', default=0.8, help='circle_diameter/cell_size (default=0.8)', type=float)
    parser.add_argument('--o', help='Optimize by optipng', action='store_true', default=False)
    parser.add_argument('--silent', help='Silent mode', action='store_true', default=False)
    
    args = parser.parse_args()
    verbose = not args.silent
    # if args.o:
    #     print 'Optimized'
    if verbose:
        print 'Generation starded'
    draw_net(args.output, args.size, args.ratio, args.students, args.lessons, args.border, args.sampling)
    if verbose:
        print 'Blank generated'
    if args.o:
        import subprocess
        s = subprocess.Popen(['optipng', args.output],
                             stderr=subprocess.STDOUT, stdout=subprocess.PIPE).communicate()[0]
        if verbose:
            print s