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author | Daniel Baumann <daniel.baumann@progress-linux.org> | 2024-04-07 16:40:16 +0000 |
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committer | Daniel Baumann <daniel.baumann@progress-linux.org> | 2024-04-07 16:40:16 +0000 |
commit | 3f25952c13d5847d510c0cae22a8ba876638d570 (patch) | |
tree | 02f505f016ed5a1029277dcae520d5e2a75906fb /tools/generate_gradients.py | |
parent | Initial commit. (diff) | |
download | powerline-upstream.tar.xz powerline-upstream.zip |
Adding upstream version 2.8.3.upstream/2.8.3upstream
Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>
Diffstat (limited to 'tools/generate_gradients.py')
-rwxr-xr-x | tools/generate_gradients.py | 217 |
1 files changed, 217 insertions, 0 deletions
diff --git a/tools/generate_gradients.py b/tools/generate_gradients.py new file mode 100755 index 0000000..290e75e --- /dev/null +++ b/tools/generate_gradients.py @@ -0,0 +1,217 @@ +#!/usr/bin/env python +# vim:fileencoding=utf-8:noet + +'''Gradients generator +''' + +from __future__ import (unicode_literals, division, absolute_import, print_function) + +import sys +import json +import argparse + +from itertools import groupby + +from colormath.color_objects import sRGBColor, LabColor +from colormath.color_conversions import convert_color +from colormath.color_diff import delta_e_cie2000 + +from powerline.colorscheme import cterm_to_hex + + +def num2(s): + try: + return (True, [int(v) for v in s.partition(' ')[::2]]) + except TypeError: + return (False, [float(v) for v in s.partition(' ')[::2]]) + + +def rgbint_to_lab(rgbint): + rgb = sRGBColor( + (rgbint >> 16) & 0xFF, (rgbint >> 8) & 0xFF, rgbint & 0xFF, + is_upscaled=True + ) + return convert_color(rgb, LabColor) + + +cterm_to_lab = tuple((rgbint_to_lab(v) for v in cterm_to_hex)) + + +def color(s): + if len(s) <= 3: + return cterm_to_lab[int(s)] + else: + return rgbint_to_lab(int(s, 16)) + + +def nums(s): + return [int(i) for i in s.split()] + + +def linear_gradient(start_value, stop_value, start_offset, stop_offset, offset): + return start_value + ((offset - start_offset) * (stop_value - start_value) / (stop_offset - start_offset)) + + +def lab_gradient(slab, elab, soff, eoff, off): + svals = slab.get_value_tuple() + evals = elab.get_value_tuple() + return LabColor(*[ + linear_gradient(start_value, end_value, soff, eoff, off) + for start_value, end_value in zip(svals, evals) + ]) + + +def generate_gradient_function(DATA): + def gradient_function(y): + initial_offset = 0 + for offset, start, end in DATA: + if y <= offset: + return lab_gradient(start, end, initial_offset, offset, y) + initial_offset = offset + return gradient_function + + +def get_upscaled_values(rgb): + return [min(max(0, i), 255) for i in rgb.get_upscaled_value_tuple()] + + +def get_rgb(lab): + rgb = convert_color(lab, sRGBColor) + rgb = sRGBColor(*get_upscaled_values(rgb), is_upscaled=True) + return rgb.get_rgb_hex()[1:] + + +def find_color(ulab, colors, ctrans): + cur_distance = float('inf') + cur_color = None + i = 0 + for clab in colors: + dist = delta_e_cie2000(ulab, clab) + if dist < cur_distance: + cur_distance = dist + cur_color = (ctrans(i), clab) + i += 1 + return cur_color + + +def print_color(color): + if type(color) is int: + colstr = '5;' + str(color) + else: + rgb = convert_color(color, sRGBColor) + colstr = '2;' + ';'.join((str(i) for i in get_upscaled_values(rgb))) + sys.stdout.write('\033[48;' + colstr + 'm ') + + +def print_colors(colors, num): + for i in range(num): + color = colors[int(round(i * (len(colors) - 1) / num))] + print_color(color) + sys.stdout.write('\033[0m\n') + + +def dec_scale_generator(num): + j = 0 + r = '' + while num: + r += '\033[{0}m'.format(j % 2) + for i in range(10): + r += str(i) + num -= 1 + if not num: + break + j += 1 + r += '\033[0m\n' + return r + + +def compute_steps(gradient, weights): + maxweight = len(gradient) - 1 + if weights: + weight_sum = sum(weights) + norm_weights = [100.0 * weight / weight_sum for weight in weights] + steps = [0] + for weight in norm_weights: + steps.append(steps[-1] + weight) + steps.pop(0) + steps.pop(0) + else: + step = m / maxweight + steps = [i * step for i in range(1, maxweight + 1)] + return steps + + +palettes = { + '16': (cterm_to_lab[:16], lambda c: c), + '256': (cterm_to_lab, lambda c: c), + None: (cterm_to_lab[16:], lambda c: c + 16), +} + + +def show_scale(rng, num_output): + if not rng and num_output >= 32 and (num_output - 1) // 10 >= 4 and (num_output - 1) % 10 == 0: + sys.stdout.write('0') + sys.stdout.write(''.join(('%*u' % (num_output // 10, i) for i in range(10, 101, 10)))) + sys.stdout.write('\n') + else: + if rng: + vmin, vmax = rng[1] + isint = rng[0] + else: + isint = True + vmin = 0 + vmax = 100 + s = '' + lasts = ' ' + str(vmax) + while len(s) + len(lasts) < num_output: + curpc = len(s) + 1 if s else 0 + curval = vmin + curpc * (vmax - vmin) / num_output + if isint: + curval = int(round(curval)) + s += str(curval) + ' ' + sys.stdout.write(s[:-1] + lasts + '\n') + sys.stdout.write(dec_scale_generator(num_output) + '\n') + + +if __name__ == '__main__': + p = argparse.ArgumentParser(description=__doc__) + p.add_argument('gradient', nargs='*', metavar='COLOR', type=color, help='List of colors (either indexes from 8-bit palette or 24-bit RGB in hexadecimal notation)') + p.add_argument('-n', '--num_items', metavar='INT', type=int, help='Number of items in resulting list', default=101) + p.add_argument('-N', '--num_output', metavar='INT', type=int, help='Number of characters in sample', default=101) + p.add_argument('-r', '--range', metavar='V1 V2', type=num2, help='Use this range when outputting scale') + p.add_argument('-s', '--show', action='store_true', help='If present output gradient sample') + p.add_argument('-p', '--palette', choices=('16', '256'), help='Use this palette. Defaults to 240-color palette (256 colors without first 16)') + p.add_argument('-w', '--weights', metavar='INT INT ...', type=nums, help='Adjust weights of colors. Number of weights must be equal to number of colors') + p.add_argument('-C', '--omit-terminal', action='store_true', help='If present do not compute values for terminal') + + args = p.parse_args() + + m = args.num_items + + steps = compute_steps(args.gradient, args.weights) + + data = [ + (weight, args.gradient[i - 1], args.gradient[i]) + for weight, i in zip(steps, range(1, len(args.gradient))) + ] + gr_func = generate_gradient_function(data) + gradient = [gr_func(y) for y in range(0, m)] + + r = [get_rgb(lab) for lab in gradient] + if not args.omit_terminal: + r2 = [find_color(lab, *palettes[args.palette])[0] for lab in gradient] + r3 = [i[0] for i in groupby(r2)] + + if not args.omit_terminal: + print(json.dumps(r3) + ',') + print(json.dumps(r2) + ',') + print(json.dumps(r)) + + if args.show: + print_colors(args.gradient, args.num_output) + if not args.omit_terminal: + print_colors(r3, args.num_output) + print_colors(r2, args.num_output) + print_colors(gradient, args.num_output) + + show_scale(args.range, args.num_output) |