"""Commodore VIC-20 monochrome / tinted-mono mode.

176x184 hi-res matched by luminance: a single global background (black) and one
foreground colour (white, or a tinted base) used by every cell, so the picture is
carried entirely by the custom character shapes + dithering -- a clean two-tone
image with no per-cell colour budget to spend.  Reuses the hires char clustering,
data layout and viewer.
"""

from __future__ import annotations

import numpy as np

from ... import palette as c64pal
from ...convert import base
from .. import palette as vpal
from . import hires

WIDTH, HEIGHT, PIXEL_ASPECT = hires.WIDTH, hires.HEIGHT, hires.PIXEL_ASPECT


def convert(img_rgb, palette_name="vic", dither_mode="floyd",
            intensive=False, base_color=None):
    plab = vpal.palette_lab()
    prgb = vpal.get_palette().astype(np.uint8)

    bg = 0                                      # black background
    fg = base_color if base_color in range(1, 8) else 1    # white (or tinted)
    ramp = sorted([bg, fg], key=lambda i: plab[i, 0])

    idx, sets, rows, cols, err = base.mono_render(
        img_rgb, plab, ramp, hires.WIDTH, hires.HEIGHT,
        hires.CELL_W, hires.CELL_H, dither_mode, n_free=2)

    # cell bitmaps (1 = foreground) reduced to the 256-char dictionary by a
    # frequency codebook -- keeps the dithered detail (k-means centroids would
    # invent near-solid 'average' chars -> block artefacts).
    bitmaps = np.zeros((hires.N_CELLS, 64), np.uint8)
    for cr in range(rows):
        for cc in range(cols):
            ci = cr * cols + cc
            block = idx[cr * 8:cr * 8 + 8, cc * 8:cc * 8 + 8]
            bitmaps[ci] = (block == fg).astype(np.uint8).reshape(-1)
    chars, labels = base.mono_codebook(bitmaps, hires.N_CHARS)

    img_mono = np.zeros((hires.HEIGHT, hires.WIDTH, 3))
    img_mono[..., 0] = c64pal.srgb_to_lab(img_rgb)[..., 0]
    plab_mono = np.zeros_like(plab)
    plab_mono[:, 0] = plab[:, 0]

    prev_idx = np.empty((hires.HEIGHT, hires.WIDTH), np.uint8)
    screen = np.zeros(hires.N_CELLS, np.uint8)
    color = np.zeros(hires.N_CELLS, np.uint8)
    for ci in range(hires.N_CELLS):
        cr, cc = divmod(ci, cols)
        ch = chars[labels[ci]].reshape(8, 8)
        prev_idx[cr * 8:cr * 8 + 8, cc * 8:cc * 8 + 8] = np.where(ch == 1, fg, bg)
        screen[ci] = labels[ci] & 0xFF
        color[ci] = fg & 0x07
    chardata = np.zeros(hires.N_CHARS * 8, np.uint8)
    for t in range(hires.N_CHARS):
        rb = chars[t].reshape(8, 8)
        for r in range(8):
            byte = 0
            for x in range(8):
                byte = (byte << 1) | int(rb[r, x])
            chardata[t * 8 + r] = byte

    data = {"chardata": chardata, "screen": screen, "color": color,
            "bg": int(bg), "border": 0, "aux": 0}

    preview = prgb[prev_idx]
    disp_w = int(round(hires.WIDTH * hires.PIXEL_ASPECT))
    xs = (np.arange(disp_w) * hires.WIDTH) // disp_w
    preview = preview[:, xs]

    return base.Conversion(
        mode="mono", width=hires.WIDTH, height=hires.HEIGHT,
        pixel_aspect=hires.PIXEL_ASPECT, index_image=prev_idx.astype(np.uint16),
        data=data, data_addr=0, viewer="hires", preview_rgb=preview,
        error=base.perceptual_error(prev_idx, img_mono, plab_mono),
        meta={"palette": "vic", "dither": dither_mode, "base_color": base_color},
    )