Implement threading, logging, and CJK font support
Major improvements to GUI stability and internationalization: - Fix GUI freezing by implementing threaded audio analysis - Add AudioAnalysisWorker thread for background processing - Progress signals with percentage updates - Thread-safe communication via Qt signals - Add comprehensive CLI logging system - 5 log levels: ERROR, WARN, INFO, DEBUG, TRACE - Command line control: --log-level, --log-file - Real-time feedback during analysis operations - Implement CJK font fallback system - FontManager with 3-tier fallback (custom → system → default) - Cross-platform CJK font detection (Windows/macOS/Linux) - Licensing-safe fonts/ directory with gitignored font files - Setup utility and comprehensive documentation - Fix numpy array formatting issue with BPM detection - Add progress indicators for long-running operations - Preserve fonts directory structure with placeholder file 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
This commit is contained in:
Mikkeli Matlock
+91
-32
@@ -3,10 +3,11 @@ Analysis Results Manager - Bridge between audio processing and GUI.
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Manages analysis queue and coordinates between components.
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"""
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from PyQt5.QtCore import QObject, pyqtSignal
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from PyQt5.QtCore import QObject, pyqtSignal, QThread
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from dataclasses import dataclass
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from typing import Optional
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import os
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import logging
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from master_core import AudioFile
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from plotting_engine import PlottingEngine
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@@ -26,26 +27,86 @@ class AnalysisResult:
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error_message: str = ""
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class AudioAnalysisWorker(QThread):
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"""
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Worker thread for audio analysis to prevent GUI freezing.
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Performs heavy librosa operations in background.
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"""
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# Signals for communicating with main thread
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progressUpdate = pyqtSignal(str, int) # message, percentage
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analysisCompleted = pyqtSignal(str, object) # file_path, AnalysisResult
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analysisError = pyqtSignal(str, str) # file_path, error_message
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def __init__(self, file_path: str, window: int = 10, hop: int = 2):
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super().__init__()
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self.file_path = file_path
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self.window = window
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self.hop = hop
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self.logger = logging.getLogger(__name__)
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def run(self):
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"""Main thread execution - performs audio analysis."""
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try:
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self.logger.info(f"Starting analysis of: {os.path.basename(self.file_path)}")
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self.progressUpdate.emit("Loading audio file...", 10)
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# Create AudioFile and load audio data
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audio_file = AudioFile(self.file_path)
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self.progressUpdate.emit("Audio loaded, detecting tempo...", 30)
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# BPM is already calculated in __init__, now do RMS analysis
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self.progressUpdate.emit("Computing RMS power levels...", 60)
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audio_file.get_energy_levels_over_time(window=self.window, hop=self.hop)
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self.progressUpdate.emit("Finalizing analysis...", 90)
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# Extract analysis results
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result = AnalysisResult(
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file_path=self.file_path,
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song_name=audio_file.song_name,
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bpm=audio_file.get_bpm(),
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max_amplitude=audio_file.max_amplitude,
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avg_amplitude=audio_file.avg_amplitude,
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times=audio_file._get_times(),
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rms_array=audio_file.rms_array,
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analysis_successful=True
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)
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self.progressUpdate.emit("Analysis complete!", 100)
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self.logger.info(f"Analysis completed: {os.path.basename(self.file_path)} (BPM: {result.bpm:.1f})")
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# Emit success signal
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self.analysisCompleted.emit(self.file_path, result)
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except Exception as e:
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error_msg = f"Analysis failed: {str(e)}"
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self.logger.error(f"Analysis error for {self.file_path}: {error_msg}")
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self.analysisError.emit(self.file_path, error_msg)
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class AnalysisResultsManager(QObject):
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"""
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Manages audio file analysis and coordinates between processing and GUI.
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Threading-ready architecture for future background processing.
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Now uses background threads to prevent GUI freezing.
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"""
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# Signals for GUI communication
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analysisStarted = pyqtSignal(str) # file_path
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analysisCompleted = pyqtSignal(str, object) # file_path, AnalysisResult
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analysisError = pyqtSignal(str, str) # file_path, error_message
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progressUpdate = pyqtSignal(str, int) # message, percentage
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def __init__(self):
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super().__init__()
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self.results_cache = {} # Store analysis results
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self.plotting_engine = PlottingEngine()
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self.current_worker = None # Track active worker thread
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self.logger = logging.getLogger(__name__)
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def analyze_file(self, file_path: str, window: int = 10, hop: int = 2):
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"""
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Analyze an audio file and emit results.
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Currently synchronous - ready for threading later.
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Analyze an audio file using background thread to prevent GUI freezing.
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Args:
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file_path: Path to audio file
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@@ -54,40 +115,38 @@ class AnalysisResultsManager(QObject):
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"""
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if not os.path.exists(file_path):
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error_msg = f"File not found: {file_path}"
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self.logger.error(error_msg)
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self.analysisError.emit(file_path, error_msg)
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return
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# Stop any existing worker
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if self.current_worker and self.current_worker.isRunning():
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self.logger.info("Stopping previous analysis to start new one")
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self.current_worker.quit()
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self.current_worker.wait()
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# Emit analysis started signal
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self.analysisStarted.emit(file_path)
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self.logger.info(f"Queuing analysis: {os.path.basename(file_path)}")
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try:
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# Create AudioFile and perform analysis
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audio_file = AudioFile(file_path)
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# Get RMS analysis data
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audio_file.get_energy_levels_over_time(window=window, hop=hop)
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# Extract analysis results
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result = AnalysisResult(
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file_path=file_path,
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song_name=audio_file.song_name,
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bpm=audio_file.get_bpm(),
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max_amplitude=audio_file.max_amplitude,
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avg_amplitude=audio_file.avg_amplitude,
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times=audio_file._get_times(), # We'll need to add this method
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rms_array=audio_file.rms_array,
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analysis_successful=True
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)
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# Cache the result
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self.results_cache[file_path] = result
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# Emit completion signal
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self.analysisCompleted.emit(file_path, result)
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except Exception as e:
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error_msg = f"Analysis failed: {str(e)}"
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self.analysisError.emit(file_path, error_msg)
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# Create and start worker thread
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self.current_worker = AudioAnalysisWorker(file_path, window, hop)
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# Connect worker signals
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self.current_worker.progressUpdate.connect(self.progressUpdate.emit)
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self.current_worker.analysisCompleted.connect(self._on_worker_completed)
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self.current_worker.analysisError.connect(self.analysisError.emit)
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# Start the background analysis
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self.current_worker.start()
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def _on_worker_completed(self, file_path: str, result: AnalysisResult):
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"""Handle completion of worker thread analysis."""
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# Cache the result
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self.results_cache[file_path] = result
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# Forward the signal to GUI
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self.analysisCompleted.emit(file_path, result)
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def get_analysis_figure(self, file_path: str):
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"""
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