def search_fractals(height, width, quality, out_dir='/Volumes/internal/Datasets/flames', num=1000): max_iter = width * height * quality for i in range(num): n = randint(4, 10) pixels = np.zeros((height, width, 4), dtype=np.uint8) counts = np.zeros((height, width), dtype=np.uint32) colors = generate_palette(n) maps = generate_transformations(n) write_parameters(os.path.join(out_dir, '{0}.txt'.format(i)), colors, maps) pixels = render_fractal(pixels, counts, maps, colors, height, width, max_iter) pixels = composite_black_background(pixels) writer = png.Writer(width=width, height=height, alpha=True) writer.write(open(os.path.join(out_dir, '{0}.png'.format(i)), 'w'), pixels.reshape(-1, width * 4))
def generate_fractal(number, height=3000, width=3000, quality=30, out_dir='/Volumes/internal/Datasets/flames'): parameters = read_parameters(os.path.join(out_dir, '{0}.txt'.format(number))) colors = parameters['colors'] maps = parameters['maps'] max_iter = width * height * quality pixels = np.zeros((height, width, 4), dtype=np.uint8) counts = np.zeros((height, width), dtype=np.uint32) pixels = render_fractal(pixels, counts, maps, colors, height, width, max_iter) pixels = composite_black_background(pixels) writer = png.Writer(width=width, height=height, alpha=True) writer.write(open('{0}_high_quality.png'.format(number), 'w'), pixels.reshape(-1, width * 4))
def generate_fractal(number, height=3000, width=3000, quality=30, out_dir='/Volumes/internal/Datasets/flames'): parameters = read_parameters( os.path.join(out_dir, '{0}.txt'.format(number))) colors = parameters['colors'] maps = parameters['maps'] max_iter = width * height * quality pixels = np.zeros((height, width, 4), dtype=np.uint8) counts = np.zeros((height, width), dtype=np.uint32) pixels = render_fractal(pixels, counts, maps, colors, height, width, max_iter) pixels = composite_black_background(pixels) writer = png.Writer(width=width, height=height, alpha=True) writer.write(open('{0}_high_quality.png'.format(number), 'w'), pixels.reshape(-1, width * 4))