"""Tests for ChordDataset in src/dataset.py."""

from pathlib import Path

import torch
import pytest

from src.dataset import ChordDataset
from src.tokenizer import TOKEN_TO_ID, parse_chord_file, tokenize_period

FIXTURES = Path(__file__).parent / "fixtures"
_PAD_ID = TOKEN_TO_ID["<PAD>"]


# ---------------------------------------------------------------------------
# Helpers
# ---------------------------------------------------------------------------


def _write_pt(tmp_path: Path, stem: str, n_tokens: int) -> Path:
    """Write a dummy .pt file with sequential token IDs."""
    tokens = torch.arange(n_tokens, dtype=torch.long)
    path = tmp_path / f"{stem}.pt"
    torch.save({"tokens": tokens, "meta": {"style": "user", "function": "verse"}}, path)
    return path


def _write_real_pt(tmp_path: Path, fixture_name: str) -> tuple[Path, int]:
    """Tokenize a real fixture and write its .pt file. Returns (path, n_tokens)."""
    period = parse_chord_file(FIXTURES / fixture_name)
    ids = tokenize_period(period)
    tokens = torch.tensor(ids, dtype=torch.long)
    out = tmp_path / f"{fixture_name}.pt"
    torch.save({"tokens": tokens, "meta": {"style": period.style}}, out)
    return out, len(ids)


# ---------------------------------------------------------------------------
# Length and file discovery
# ---------------------------------------------------------------------------


class TestChordDatasetLength:
    def test_empty_directory(self, tmp_path):
        ds = ChordDataset(tmp_path)
        assert len(ds) == 0

    def test_single_file(self, tmp_path):
        _write_pt(tmp_path, "a", 10)
        assert len(ChordDataset(tmp_path)) == 1

    def test_multiple_files(self, tmp_path):
        for name in ("a", "b", "c"):
            _write_pt(tmp_path, name, 10)
        assert len(ChordDataset(tmp_path)) == 3

    def test_non_pt_files_ignored(self, tmp_path):
        _write_pt(tmp_path, "a", 10)
        (tmp_path / "notes.txt").write_text("ignored")
        (tmp_path / "model.pth").write_text("ignored")
        assert len(ChordDataset(tmp_path)) == 1


# ---------------------------------------------------------------------------
# Output shape
# ---------------------------------------------------------------------------


class TestChordDatasetShape:
    def test_returns_tensor(self, tmp_path):
        _write_pt(tmp_path, "a", 50)
        item = ChordDataset(tmp_path)[0]
        assert isinstance(item, torch.Tensor)

    def test_dtype_is_long(self, tmp_path):
        _write_pt(tmp_path, "a", 50)
        item = ChordDataset(tmp_path)[0]
        assert item.dtype == torch.long

    def test_shape_equals_max_length_when_shorter(self, tmp_path):
        _write_pt(tmp_path, "a", 50)
        assert ChordDataset(tmp_path, max_length=100)[0].shape[0] == 100

    def test_shape_equals_max_length_when_longer(self, tmp_path):
        _write_pt(tmp_path, "a", 600)
        assert ChordDataset(tmp_path, max_length=512)[0].shape[0] == 512

    def test_shape_equals_max_length_exact(self, tmp_path):
        _write_pt(tmp_path, "a", 512)
        assert ChordDataset(tmp_path, max_length=512)[0].shape[0] == 512

    def test_custom_max_length(self, tmp_path):
        _write_pt(tmp_path, "a", 30)
        assert ChordDataset(tmp_path, max_length=64)[0].shape[0] == 64


# ---------------------------------------------------------------------------
# Padding
# ---------------------------------------------------------------------------


class TestChordDatasetPadding:
    def test_trailing_tokens_are_pad_id(self, tmp_path):
        n = 50
        _write_pt(tmp_path, "a", n)
        item = ChordDataset(tmp_path, max_length=100)[0]
        assert (item[n:] == _PAD_ID).all()

    def test_prefix_matches_original_tokens(self, tmp_path):
        n = 50
        _write_pt(tmp_path, "a", n)
        item = ChordDataset(tmp_path, max_length=100)[0]
        expected = torch.arange(n, dtype=torch.long)
        assert (item[:n] == expected).all()

    def test_no_padding_when_exact_length(self, tmp_path):
        n = 100
        _write_pt(tmp_path, "a", n)
        item = ChordDataset(tmp_path, max_length=n)[0]
        expected = torch.arange(n, dtype=torch.long)
        assert (item == expected).all()


# ---------------------------------------------------------------------------
# Truncation
# ---------------------------------------------------------------------------


class TestChordDatasetTruncation:
    def test_truncated_length(self, tmp_path):
        _write_pt(tmp_path, "a", 600)
        item = ChordDataset(tmp_path, max_length=512)[0]
        assert item.shape[0] == 512

    def test_truncated_prefix_matches_original(self, tmp_path):
        _write_pt(tmp_path, "a", 600)
        item = ChordDataset(tmp_path, max_length=512)[0]
        expected = torch.arange(512, dtype=torch.long)
        assert (item == expected).all()


# ---------------------------------------------------------------------------
# Real fixture round-trip
# ---------------------------------------------------------------------------


class TestChordDatasetRealFixture:
    def test_bos_at_position_zero(self, tmp_path):
        _write_real_pt(tmp_path, "valid_c_major.chord")
        item = ChordDataset(tmp_path, max_length=512)[0]
        assert item[0] == TOKEN_TO_ID["<BOS>"]

    def test_eos_at_correct_position(self, tmp_path):
        _, n = _write_real_pt(tmp_path, "valid_c_major.chord")
        item = ChordDataset(tmp_path, max_length=512)[0]
        assert item[n - 1] == TOKEN_TO_ID["<EOS>"]

    def test_tokens_after_eos_are_pad(self, tmp_path):
        _, n = _write_real_pt(tmp_path, "valid_c_major.chord")
        item = ChordDataset(tmp_path, max_length=512)[0]
        assert (item[n:] == _PAD_ID).all()

    def test_all_valid_fixture_files_loadable(self, tmp_path):
        for name in (
            "valid_c_major.chord",
            "valid_fsharp_major.chord",
            "valid_b_minor.chord",
            "valid_gsharp_minor.chord",
        ):
            _write_real_pt(tmp_path, name)
        ds = ChordDataset(tmp_path, max_length=512)
        assert len(ds) == 4
        for i in range(4):
            item = ds[i]
            assert item.shape[0] == 512
            assert item[0] == TOKEN_TO_ID["<BOS>"]