"""Binary payload serialization for sweep/result collections."""

from __future__ import annotations

import struct
from numbers import Integral

import numpy as np

from python_app.models.dataset_model import ResultCollection, SweepCollection

RAW_MAGIC = 0x32574152
PREPROC_MAGIC = 0x32525050
RESULT_MAGIC = 0x324C5352  # RSL2: adds processing_duration_ns after monotonic_ns


def _write_interleaved_complex(buffer: bytearray, values: np.ndarray) -> None:
    """Append complex64 array as interleaved float32 real/imag pairs."""
    interleaved = np.empty(values.size * 2, dtype="<f4")
    interleaved[0::2] = values.real.astype("<f4", copy=False)
    interleaved[1::2] = values.imag.astype("<f4", copy=False)
    buffer.extend(interleaved.tobytes())


def validate_trace_collection(collection: SweepCollection, *, require_finite: bool = False) -> None:
    """Reject ambiguous combinations and malformed traces before saving any files."""
    for field in ("collection_id", "monotonic_ns", "capture_start_ns", "capture_end_ns"):
        _validate_u64(getattr(collection, field), field)
    if require_finite and not collection.traces:
        raise ValueError("Preprocess set must contain at least one trace")
    seen: set[tuple[int, int]] = set()
    for trace in collection.traces:
        _validate_u64(trace.capture_start_ns, "trace.capture_start_ns")
        _validate_u64(trace.capture_end_ns, "trace.capture_end_ns")
        if any(
            isinstance(value, bool) or not isinstance(value, Integral) or not 0 <= value <= 0xFFFFFFFF
            for value in (trace.combo.input, trace.combo.output)
        ):
            raise ValueError("Trace input/output positions must be unsigned 32-bit integers")
        combo = (int(trace.combo.input), int(trace.combo.output))
        if combo in seen:
            raise ValueError(f"Invalid or duplicate trace combination: {combo}")
        seen.add(combo)
        arrays = (
            np.asarray(trace.frequency_hz, dtype=np.float32),
            np.asarray(trace.s11, dtype=np.complex64),
            np.asarray(trace.s21, dtype=np.complex64),
        )
        if any(array.ndim != 1 for array in arrays) or len({array.shape for array in arrays}) != 1:
            raise ValueError(f"Trace {combo} frequency, S11 and S21 must be equally sized 1D arrays")
        if require_finite and (not arrays[0].size or any(not np.isfinite(array).all() for array in arrays)):
            raise ValueError(f"Preprocess trace {combo} must contain finite, nonempty arrays")


def _validate_u64(value: int, field: str) -> None:
    if isinstance(value, bool) or not isinstance(value, Integral) or not 0 <= value < 1 << 64:
        raise ValueError(f"{field} must be an unsigned 64-bit integer")


def serialize_trace_collection(collection: SweepCollection, magic: int) -> bytes:
    """Serialize one raw/preprocessed trace collection into ring-compatible binary format.

    The trailer is appended after the trace blocks so older readers, which stop at
    the last block, still decode the traces: first the collection capture window,
    then a per-trace window table (one ``(start_ns, end_ns)`` pair per trace, in
    trace order). See :func:`python_app.orchestration.shm.decoder.decode_trace_collection`
    and ``read_trace_collection`` in ``common_cpp/ipc/src/shared_types.cpp``.
    """
    validate_trace_collection(collection)
    buffer = bytearray()
    buffer.extend(struct.pack("<IQQI", magic, collection.collection_id, collection.monotonic_ns, len(collection.traces)))

    for trace in collection.traces:
        freq = np.asarray(trace.frequency_hz, dtype=np.float32)
        s11 = np.asarray(trace.s11, dtype=np.complex64)
        s21 = np.asarray(trace.s21, dtype=np.complex64)
        buffer.extend(struct.pack("<III", trace.combo.input, trace.combo.output, int(freq.size)))
        buffer.extend(freq.astype("<f4", copy=False).tobytes())

        _write_interleaved_complex(buffer, s11)
        _write_interleaved_complex(buffer, s21)

    buffer.extend(
        struct.pack(
            "<QQ",
            int(collection.capture_start_ns),
            int(collection.capture_end_ns),
        )
    )
    buffer.extend(struct.pack("<I", len(collection.traces)))
    for trace in collection.traces:
        buffer.extend(
            struct.pack("<QQ", int(trace.capture_start_ns), int(trace.capture_end_ns))
        )
    return bytes(buffer)


def serialize_result_collection(collection: ResultCollection) -> bytes:
    """Serialize one processed collection with result blocks/payloads."""

    def serialize_payload(buffer: bytearray, payload) -> None:
        """Append one payload in ring-compatible result format."""
        name_bytes = payload.processing_name.encode("utf-8")
        if len(name_bytes) > 0xFFFF:
            raise ValueError("processing_name is too long")

        buffer.extend(struct.pack("<BH", payload.kind, len(name_bytes)))
        buffer.extend(name_bytes)

        if payload.kind == 1:
            freq = np.asarray(payload.frequency_hz, dtype=np.float32)
            trace = np.asarray(payload.trace, dtype=np.complex64)
            if freq.ndim != 1 or trace.ndim != 1 or freq.shape != trace.shape:
                raise ValueError("Result trace frequency and values must be equally sized 1D arrays")

            buffer.extend(struct.pack("<I", int(freq.size)))
            buffer.extend(freq.astype("<f4", copy=False).tobytes())

            _write_interleaved_complex(buffer, trace)
            return

        if payload.kind == 2:
            buffer.extend(struct.pack("<f", float(payload.scalar_value)))
            return

        if payload.kind == 3:
            image_x_axis = np.asarray(payload.image_x_axis, dtype=np.float32)
            image_y_axis = np.asarray(payload.image_y_axis, dtype=np.float32)
            image = np.asarray(payload.image, dtype=np.float32)
            if image_x_axis.ndim != 1 or image_y_axis.ndim != 1 or image.shape != (image_y_axis.size, image_x_axis.size):
                raise ValueError("Result image axis sizes must match image matrix shape")
            buffer.extend(struct.pack("<II", int(image_x_axis.size), int(image_y_axis.size)))
            buffer.extend(image_x_axis.astype("<f4", copy=False).tobytes())
            buffer.extend(image_y_axis.astype("<f4", copy=False).tobytes())
            buffer.extend(image.astype("<f4", copy=False).ravel(order="C").tobytes())
            return

        if payload.kind == 4:
            table = np.asarray(payload.table, dtype=np.float32)
            if table.ndim != 2:
                raise ValueError("Result table payload must be a 2D matrix")
            if table.shape[0] and not table.shape[1]:
                raise ValueError("Result table with rows must have at least one column")
            buffer.extend(struct.pack("<II", int(table.shape[1]), int(table.shape[0])))
            buffer.extend(table.astype("<f4", copy=False).ravel(order="C").tobytes())
            return

        raise ValueError(f"Unsupported payload kind: {payload.kind}")

    for field in ("collection_id", "monotonic_ns", "processing_duration_ns"):
        _validate_u64(getattr(collection, field), field)
    buffer = bytearray()
    buffer.extend(
        struct.pack(
            "<IQQQII",
            RESULT_MAGIC,
            collection.collection_id,
            collection.monotonic_ns,
            int(collection.processing_duration_ns),
            len(collection.collection_payloads),
            len(collection.blocks),
        )
    )

    for payload in collection.collection_payloads:
        serialize_payload(buffer, payload)

    for block in collection.blocks:
        buffer.extend(struct.pack("<II", block.combo.input, block.combo.output))
        buffer.extend(struct.pack("<I", len(block.payloads)))

        for payload in block.payloads:
            serialize_payload(buffer, payload)

    return bytes(buffer)