Diagnostic Stem Delivery

import numpy as np

def generate_stem(name, duration_sec, sample_rate, subtype='FLOAT', section_timing=None):
    """Generate a single stem with explicit sample type."""
    frames = int(duration_sec * sample_rate)
    t = np.linspace(0, duration_sec, frames)
    
    # Generate stem-specific content (customize per stem type)
    if name == 'bass':
        freq = 110  # A2
        audio_data = np.sin(2 * np.pi * freq * t) * 0.8
    elif name == 'guitars':
        freq = 440  # A4
        audio_data = np.sin(2 * np.pi * freq * t) * 0.6
    elif name == 'synths':
        freq = 880  # A5
        audio_data = np.sin(2 * np.pi * freq * t) * 0.5
    elif name == 'bridge':
        freq = 220  # A3
        audio_data = np.sin(2 * np.pi * freq * t) * 0.7
    else:
        audio_data = np.sin(2 * np.pi * 440 * t) * 0.5
    
    # Ensure proper data type
    if subtype == 'FLOAT':
        audio_data = audio_data.astype(np.float32)
    elif subtype == 'PCM_24':
        audio_data = np.clip(audio_data, -1, 1) * (2**23 - 1)
        audio_data = audio_data.astype(np.int32)
    
    filepath = f'{name}_stem.wav'
    sf.write(filepath, audio_data, sample_rate, subtype=subtype, format='WAV')
    
    return filepath, audio_data

def verify_stem(filepath, expected_sample_rate, expected_duration, tolerance_sec=1.0):
    """Verify a single stem meets specifications."""
    if not os.path.exists(filepath):
        return {'success': False, 'error': f'File not found: {filepath}'}
    
    info = sf.info(filepath)
    errors = []
    
    if info.samplerate != expected_sample_rate:
        errors.append(f'sample_rate: expected {expected_sample_rate}, got {info.samplerate}')
    
    if abs(info.duration - expected_duration) > tolerance_sec:
        errors.append(f'duration: expected ~{expected_duration}s, got {info.duration}s')
    
    if errors:
        return {'success': False, 'error': '; '.join(errors)}
    
    return {'success': True, 'info': info}

# Generate stems one at a time with verification
SAMPLE_RATE = 48000
STEM_NAMES = ['bass', 'guitars', 'synths', 'bridge']

generated_stems = []
stem_info = {}

for stem_name in STEM_NAMES:
    print(f'\\n=== Generating {stem_name} stem ===')
    
    # Generate
    filepath, data = generate_stem(stem_name, DURATION, SAMPLE_RATE, subtype='FLOAT')
    
    # Verify immediately
    result = verify_stem(filepath, SAMPLE_RATE, TARGET_DURATION)
    
    if result['success']:
        print(f'✓ {stem_name} stem verified: {result["info"].duration:.2f}s @ {result["info"].samplerate}Hz')
        generated_stems.append(filepath)
        stem_info[stem_name] = result
    else:
        print(f'✗ {stem_name} stem FAILED: {result["error"]}')
        raise RuntimeError(f'Stem generation failed for {stem_name}: {result["error"]}')

print(f'\\nAll {len(generated_stems)} stems generated and verified successfully')

def apply_edit_based_on_diagnostics(stem_filepath, edit_spot, analysis, output_filepath):
    """
    Apply targeted edit at a specific timecode based on diagnostic analysis.
    
    Decisions based on diagnostics:
    - High click/pop score (>0.3): Apply fade or click removal
    - Very low pitch (<40Hz): May need high-pass filter
    - Near-silence: Consider removal or gain adjustment
    - Potential clipping: Apply gain reduction
    """
    data, sr = sf.read(stem_filepath)
    
    timecode_sec = analysis['seconds']
    edit_start = max(0, int((timecode_sec - 0.05) * sr))
    edit_end = min(len(data), int((timecode_sec + 0.05) * sr))
    
    # Apply edits based on diagnostics
    if analysis['click_pop_score'] > 0.3:
        # Apply short crossfade to smooth clicks
        fade_len = min(100, (edit_end - edit_start) // 4)
        if fade_len > 0:
            fade_in = np.linspace(0, 1, fade_len)
            fade_out = np.linspace(1, 0, fade_len)
            data[edit_start:edit_start + fade_len] *= fade_in
            data[edit_end - fade_len:edit_end] *= fade_out
        print(f'  Applied click smoothing at {timecode_sec:.2f}s')
    
    if analysis['amplitude_rms'] > 0.9:
        # Apply gentle gain reduction to prevent clipping
        gain = 0.8
        data[edit_start:edit_end] *= gain
        print(f'  Applied gain reduction ({gain:.1f}x) at {timecode_sec:.2f}s')
    
    # Save edited stem
    sf.write(output_filepath, data, sr, subtype='FLOAT', format='WAV')
    return output_filepath

# Apply edits to stems based on diagnostic analysis
for stem_name in ['bass']:  # Customize as needed
    stem_file = f'{stem_name}_stem.wav'
    edited_file = f'{stem_name}_stem_edited.wav'
    
    print(f'\\n=== Applying edits to {stem_name} based on diagnostics ===')
    
    for i, spot in enumerate(edit_spots):
        # Re-analyze or use cached analysis
        analysis = analyze_audio_at_timecode('reference.wav', spot['timecode'])
        if 'error' not in analysis:
            apply_edit_based_on_diagnostics(stem_file, spot, analysis, edited_file)
    
    print(f'Edited {stem_name} stem saved to {edited_file}')

def mix_stems(stem_files, output_filepath, sample_rate=48000):
    """Mix multiple stems into a single output file."""
    mixed_data = None
    
    for stem_file in stem_files:
        if not os.path.exists(stem_file):
            raise FileNotFoundError(f'Stem not found: {stem_file}')
        
        data, sr = sf.read(stem_file)
        
        # Resample if needed
        if sr != sample_rate:
            data = librosa.resample(data, orig_sr=sr, target_sr=sample_rate)
        
        # Ensure same length
        if mixed_data is None:
            mixed_data = np.zeros(len(data), dtype=np.float32)
        elif len(data) != len(mixed_data):
            min_len = min(len(data), len(mixed_data))
            mixed_data = mixed_data[:min_len]
            data = data[:min_len]
        
        mixed_data += data
    
    # Normalize to prevent clipping
    if np.max(np.abs(mixed_data)) > 0.95:
        mixed_data *= 0.95 / np.max(np.abs(mixed_data))
    
    sf.write(output_filepath, mixed_data, sample_rate, subtype='FLOAT', format='WAV')
    
    return {
        'filepath': output_filepath,
        'duration': len(mixed_data) / sample_rate,
        'peak': float(np.max(np.abs(mixed_data))),
        'rms': float(np.sqrt(np.mean(mixed_data ** 2)))
    }

# Mix all stems
print('\\n=== Mixing all stems ===')
all_stems = [f'{name}_stem_edited.wav' if os.path.exists(f'{name}_stem_edited.wav') 
             else f'{name}_stem.wav' for name in STEM_NAMES]

mix_info = mix_stems(all_stems, 'State_of_Affairs_FULL_EDIT_MIX.wav')
print(f'Mix complete: {mix_info["duration"]:.2f}s, peak={mix_info["peak"]:.3f}, RMS={mix_info["rms"]:.6f}')

def verify_deliverable(filepath, required_sample_rate=48000, required_channels=None, min_duration=None):
    """
    Comprehensive verification of final deliverable.
    
    Returns dict with verification status and details.
    Task CANNOT complete if verification fails.
    """
    if not os.path.exists(filepath):
        return {
            'success': False,
            'error': f'DELIVERABLE MISSING: {filepath}',
            'blocking': True
        }
    
    try:
        info = sf.info(filepath)
    except Exception as e:
        return {
            'success': False,
            'error': f'DELIVERABLE CORRUPT: {str(e)}',
            'blocking': True
        }
    
    errors = []
    warnings = []
    
    # Critical checks (blocking)
    if info.samplerate != required_sample_rate:
        errors.append(f'CRITICAL: Sample rate {info.samplerate}Hz != required {required_sample_rate}Hz')
    
    if required_channels and info.channels != required_channels:
        errors.append(f'CRITICAL: Channels {info.channels} != required {required_channels}')
    
    if min_duration and info.duration < min_duration:
        errors.append(f'CRITICAL: Duration {info.duration:.2f}s < minimum {min_duration}s')
    
    # Verify file is not empty
    if info.duration < 0.1:
        errors.append('CRITICAL: File appears to be empty or silent')
    
    # Non-critical checks (warnings)
    if info.duration < 60:
        warnings.append(f'Short duration: {info.duration:.2f}s')
    
    if os.path.getsize(filepath) < 1000:
        warnings.append('File size unusually small')
    
    # Load and analyze audio content
    data, sr = sf.read(filepath)
    peak = np.max(np.abs(data))
    rms = np.sqrt(np.mean(data ** 2))
    
    if peak > 0.99:
        warnings.append(f'Potential clipping: peak={peak:.4f}')
    
    if rms < 0.001:
        errors.append('CRITICAL: Audio appears to be silent (RMS too low)')
    
    # Final verdict
    success = len(errors) == 0
    
    result = {
        'success': success,
        'blocking': not success,
        'filepath': filepath,
        'info': {
            'duration': info.duration,
            'sample_rate': info.samplerate,
            'channels': info.channels,
            'subtype': info.subtype,
            'format': info.format,
            'peak': float(peak),
            'rms': float(rms),
            'file_size': os.path.getsize(filepath)
        },
        'errors': errors,
        'warnings': warnings
    }
    
    return result

# MANDATORY deliverable verification
print('\\n=== DELIVERABLE VERIFICATION (MANDATORY) ===')
deliverable_path = 'State_of_Affairs_FULL_EDIT_MIX.wav'

verification = verify_deliverable(
    deliverable_path,
    required_sample_rate=48000,
    required_channels=2,  # stereo
    min_duration=60  # minimum 60 seconds
)

if verification['success']:
    print('✓ DELIVERABLE VERIFIED SUCCESSFULLY')
    print(f'  File: {verification["filepath"]}')
    print(f'  Duration: {verification["info"]["duration"]:.2f}s')
    print(f'  Sample Rate: {verification["info"]["sample_rate"]}Hz')
    print(f'  Channels: {verification["info"]["channels"]}')
    print(f'  Peak: {verification["info"]["peak"]:.4f}')
    print(f'  RMS: {verification["info"]["rms"]:.6f}')
    
    if verification['warnings']:
        print('  Warnings:')
        for warn in verification['warnings']:
            print(f'    ⚠ {warn}')
    
    print('\\n✓ TASK COMPLETE - All deliverables verified')
    
else:
    print('✗ DELIVERABLE VERIFICATION FAILED')
    print('  ERRORS (blocking):')
    for err in verification['errors']:
        print(f'    ✗ {err}')
    
    if verification['warnings']:
        print('  Warnings:')
        for warn in verification['warnings']:
            print(f'    ⚠ {warn}')
    
    raise RuntimeError(f'Task cannot complete: {verification["errors"]}')

python3 -c "import soundfile as sf; import numpy as np; ...your code..."