#!/usr/bin/env python3
"""
Test framework to verify JAX primitives match Python primitives.

Compares output of each primitive through:
1. Python/NumPy path
2. JAX path (CPU)
3. JAX path (GPU) - if available

Reports any mismatches with detailed diffs.
"""
import sys
sys.path.insert(0, '/home/giles/art/art-celery')

import numpy as np
import json
from pathlib import Path
from typing import Dict, List, Tuple, Any, Optional
from dataclasses import dataclass, field

# Test configuration
TEST_WIDTH = 64
TEST_HEIGHT = 48
TOLERANCE_MEAN = 1.0  # Max allowed mean difference
TOLERANCE_MAX = 10.0  # Max allowed single pixel difference
TOLERANCE_PCT = 0.95  # Min % of pixels within ±1


@dataclass
class TestResult:
    primitive: str
    passed: bool
    python_mean: float = 0.0
    jax_mean: float = 0.0
    diff_mean: float = 0.0
    diff_max: float = 0.0
    pct_within_1: float = 0.0
    error: str = ""


def create_test_frame(w=TEST_WIDTH, h=TEST_HEIGHT, pattern='gradient'):
    """Create a test frame with known pattern."""
    if pattern == 'gradient':
        # Diagonal gradient
        y, x = np.mgrid[0:h, 0:w]
        r = (x * 255 / w).astype(np.uint8)
        g = (y * 255 / h).astype(np.uint8)
        b = ((x + y) * 127 / (w + h)).astype(np.uint8)
        return np.stack([r, g, b], axis=2)
    elif pattern == 'checkerboard':
        y, x = np.mgrid[0:h, 0:w]
        check = ((x // 8) + (y // 8)) % 2
        v = (check * 255).astype(np.uint8)
        return np.stack([v, v, v], axis=2)
    elif pattern == 'solid':
        return np.full((h, w, 3), 128, dtype=np.uint8)
    else:
        return np.random.randint(0, 255, (h, w, 3), dtype=np.uint8)


def compare_outputs(py_out, jax_out) -> Tuple[float, float, float]:
    """Compare two outputs, return (mean_diff, max_diff, pct_within_1)."""
    if py_out is None or jax_out is None:
        return float('inf'), float('inf'), 0.0

    if isinstance(py_out, dict) and isinstance(jax_out, dict):
        # Compare coordinate maps
        diffs = []
        for k in py_out:
            if k in jax_out:
                py_arr = np.asarray(py_out[k])
                jax_arr = np.asarray(jax_out[k])
                if py_arr.shape == jax_arr.shape:
                    diff = np.abs(py_arr.astype(float) - jax_arr.astype(float))
                    diffs.append(diff)
        if diffs:
            all_diff = np.concatenate([d.flatten() for d in diffs])
            return float(np.mean(all_diff)), float(np.max(all_diff)), float(np.mean(all_diff <= 1))
        return float('inf'), float('inf'), 0.0

    py_arr = np.asarray(py_out)
    jax_arr = np.asarray(jax_out)

    if py_arr.shape != jax_arr.shape:
        return float('inf'), float('inf'), 0.0

    diff = np.abs(py_arr.astype(float) - jax_arr.astype(float))
    return float(np.mean(diff)), float(np.max(diff)), float(np.mean(diff <= 1))


# ============================================================================
# Primitive Test Definitions
# ============================================================================

PRIMITIVE_TESTS = {
    # Geometry primitives
    'geometry:ripple-displace': {
        'args': [TEST_WIDTH, TEST_HEIGHT, 5, 10, TEST_WIDTH/2, TEST_HEIGHT/2, 1, 0.5],
        'returns': 'coords',
    },
    'geometry:rotate-img': {
        'args': ['frame', 45],
        'returns': 'frame',
    },
    'geometry:scale-img': {
        'args': ['frame', 1.5],
        'returns': 'frame',
    },
    'geometry:flip-h': {
        'args': ['frame'],
        'returns': 'frame',
    },
    'geometry:flip-v': {
        'args': ['frame'],
        'returns': 'frame',
    },

    # Color operations
    'color_ops:invert': {
        'args': ['frame'],
        'returns': 'frame',
    },
    'color_ops:grayscale': {
        'args': ['frame'],
        'returns': 'frame',
    },
    'color_ops:brightness': {
        'args': ['frame', 1.5],
        'returns': 'frame',
    },
    'color_ops:contrast': {
        'args': ['frame', 1.5],
        'returns': 'frame',
    },
    'color_ops:hue-shift': {
        'args': ['frame', 90],
        'returns': 'frame',
    },

    # Image operations
    'image:width': {
        'args': ['frame'],
        'returns': 'scalar',
    },
    'image:height': {
        'args': ['frame'],
        'returns': 'scalar',
    },
    'image:channel': {
        'args': ['frame', 0],
        'returns': 'array',
    },

    # Blending
    'blending:blend': {
        'args': ['frame', 'frame2', 0.5],
        'returns': 'frame',
    },
    'blending:blend-add': {
        'args': ['frame', 'frame2'],
        'returns': 'frame',
    },
    'blending:blend-multiply': {
        'args': ['frame', 'frame2'],
        'returns': 'frame',
    },
}


def run_python_primitive(interp, prim_name: str, test_def: dict, frame: np.ndarray, frame2: np.ndarray) -> Any:
    """Run a primitive through the Python interpreter."""
    if prim_name not in interp.primitives:
        return None

    func = interp.primitives[prim_name]
    args = []
    for a in test_def['args']:
        if a == 'frame':
            args.append(frame.copy())
        elif a == 'frame2':
            args.append(frame2.copy())
        else:
            args.append(a)

    try:
        return func(*args)
    except Exception as e:
        return None


def run_jax_primitive(prim_name: str, test_def: dict, frame: np.ndarray, frame2: np.ndarray) -> Any:
    """Run a primitive through the JAX compiler."""
    try:
        from streaming.sexp_to_jax import JaxCompiler
        import jax.numpy as jnp

        compiler = JaxCompiler()

        # Build a simple expression to test the primitive
        from sexp_effects.parser import Symbol, Keyword

        args = []
        env = {'frame': jnp.array(frame), 'frame2': jnp.array(frame2)}

        for a in test_def['args']:
            if a == 'frame':
                args.append(Symbol('frame'))
            elif a == 'frame2':
                args.append(Symbol('frame2'))
            else:
                args.append(a)

        # Create expression: (prim_name arg1 arg2 ...)
        expr = [Symbol(prim_name)] + args

        result = compiler._eval(expr, env)

        if hasattr(result, '__array__'):
            return np.asarray(result)
        return result

    except Exception as e:
        return None


def test_primitive(interp, prim_name: str, test_def: dict) -> TestResult:
    """Test a single primitive."""
    frame = create_test_frame(pattern='gradient')
    frame2 = create_test_frame(pattern='checkerboard')

    result = TestResult(primitive=prim_name, passed=False)

    # Run Python version
    try:
        py_out = run_python_primitive(interp, prim_name, test_def, frame, frame2)
        if py_out is not None and hasattr(py_out, 'shape'):
            result.python_mean = float(np.mean(py_out))
    except Exception as e:
        result.error = f"Python error: {e}"
        return result

    # Run JAX version
    try:
        jax_out = run_jax_primitive(prim_name, test_def, frame, frame2)
        if jax_out is not None and hasattr(jax_out, 'shape'):
            result.jax_mean = float(np.mean(jax_out))
    except Exception as e:
        result.error = f"JAX error: {e}"
        return result

    if py_out is None:
        result.error = "Python returned None"
        return result
    if jax_out is None:
        result.error = "JAX returned None"
        return result

    # Compare
    diff_mean, diff_max, pct = compare_outputs(py_out, jax_out)
    result.diff_mean = diff_mean
    result.diff_max = diff_max
    result.pct_within_1 = pct

    # Check pass/fail
    result.passed = (
        diff_mean <= TOLERANCE_MEAN and
        diff_max <= TOLERANCE_MAX and
        pct >= TOLERANCE_PCT
    )

    if not result.passed:
        result.error = f"Diff too large: mean={diff_mean:.2f}, max={diff_max:.1f}, pct={pct:.1%}"

    return result


def discover_primitives(interp) -> List[str]:
    """Discover all primitives available in the interpreter."""
    return sorted(interp.primitives.keys())


def run_all_tests(verbose=True):
    """Run all primitive tests."""
    import warnings
    warnings.filterwarnings('ignore')

    import os
    os.chdir('/home/giles/art/test')

    from streaming.stream_sexp_generic import StreamInterpreter
    from sexp_effects.primitive_libs import core as core_mod

    core_mod.set_random_seed(42)

    # Create interpreter to get Python primitives
    interp = StreamInterpreter('effects/quick_test_explicit.sexp', use_jax=False)
    interp._init()

    results = []

    print("=" * 60)
    print("JAX PRIMITIVE TEST SUITE")
    print("=" * 60)

    # Test defined primitives
    for prim_name, test_def in PRIMITIVE_TESTS.items():
        result = test_primitive(interp, prim_name, test_def)
        results.append(result)

        status = "✓ PASS" if result.passed else "✗ FAIL"
        if verbose:
            print(f"{status} {prim_name}")
            if not result.passed:
                print(f"       {result.error}")

    # Summary
    passed = sum(1 for r in results if r.passed)
    failed = sum(1 for r in results if not r.passed)

    print("\n" + "=" * 60)
    print(f"SUMMARY: {passed} passed, {failed} failed")
    print("=" * 60)

    if failed > 0:
        print("\nFailed primitives:")
        for r in results:
            if not r.passed:
                print(f"  - {r.primitive}: {r.error}")

    return results


if __name__ == '__main__':
    run_all_tests()