"""Pure helper functions (no torch / gradio imports, so they are easy to test)."""

from __future__ import annotations

DEFAULT_FRAME_RATE = 24.0

# Resolution presets: (width, height). All values are multiples of 64, which the
# two-stage pipeline (half-res stage 1 -> x2 upscale -> stage 2) requires.
RESOLUTIONS = {
    "high": {"16:9": (1536, 1024), "9:16": (1024, 1536), "1:1": (1024, 1024)},
    "low": {"16:9": (768, 512), "9:16": (512, 768), "1:1": (768, 768)},
}

RESOLUTION_MULTIPLE = 64
MIN_SIDE = 256
MAX_SIDE = 2048


def snap_dimension(value, multiple: int = RESOLUTION_MULTIPLE, lo: int = MIN_SIDE, hi: int = MAX_SIDE) -> int:
    """Round ``value`` to the nearest multiple of ``multiple`` inside [lo, hi].

    The UI exposes free-form Width/Height boxes; an arbitrary value such as 1000
    would crash the pipeline, so we always snap before generating.
    """
    try:
        v = float(value)
    except (TypeError, ValueError):
        v = float(lo)
    snapped = int(round(v / multiple)) * multiple
    return max(lo, min(hi, snapped))


def compute_num_frames(duration: float, frame_rate: float = DEFAULT_FRAME_RATE) -> int:
    """Number of frames for ``duration`` seconds, in the 8k+1 form LTX expects."""
    frames = int(float(duration) * frame_rate) + 1
    return ((frames - 1 + 7) // 8) * 8 + 1


def detect_aspect_ratio(image) -> str:
    """Closest of '16:9', '9:16', '1:1' for a PIL image / numpy array (default 16:9)."""
    if image is None:
        return "16:9"
    size = getattr(image, "size", None)
    if isinstance(size, tuple) and len(size) == 2:  # PIL.Image -> (w, h)
        w, h = size
    elif hasattr(image, "shape"):  # numpy array -> (h, w, ...); its .size is an int
        h, w = image.shape[:2]
    else:
        return "16:9"
    if not w or not h:
        return "16:9"
    ratio = w / h
    candidates = {"16:9": 16 / 9, "9:16": 9 / 16, "1:1": 1.0}
    return min(candidates, key=lambda k: abs(ratio - candidates[k]))


def pick_resolution(image, high_res: bool) -> tuple[int, int]:
    """(width, height) preset matching the image's aspect ratio and the quality tier."""
    tier = "high" if high_res else "low"
    return RESOLUTIONS[tier][detect_aspect_ratio(image)]