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.github/workflows/release.yaml

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@@ -110,7 +110,7 @@ jobs:
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verbose: true # For better debugging
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github_release:
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needs: [setup_and_build, pypi_publish]
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needs: [details, setup_and_build, pypi_publish]
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runs-on: ubuntu-latest
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permissions:
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contents: write
@@ -125,7 +125,7 @@ jobs:
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path: dist/
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- name: Create Release
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uses: softprops/action-gh-release@v1
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uses: softprops/action-gh-release@v2
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with:
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tag_name: ${{ needs.details.outputs.tag_name }}
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files: |

chordspy/app.py

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@@ -22,7 +22,6 @@
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from pathlib import Path # For handling file paths in a platform-independent way
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import os # For file and directory operations
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import webbrowser # For opening the web interface in a browser
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import logging # For logging errors and information
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console_queue = queue.Queue() # Global queue for console messages to be displayed in the web interface
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app = Flask(__name__) # Initialize Flask application

chordspy/chords_wifi.py

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@@ -8,7 +8,6 @@
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import sys
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import websocket
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import socket
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from scipy.signal import butter, filtfilt
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class Chords_WIFI:
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"""

chordspy/connection.py

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@@ -41,7 +41,7 @@ class Connection:
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- Data streaming to LSL
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- Data recording to CSV files
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- Connection state management
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- Sample validation and rate monitoring
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- Sample validation and rate monitorin
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The class maintains separate connection handlers for each protocol (USB/WiFi/BLE)
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and manages their lifecycle. It implements thread-safe operations for concurrent
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data handling and provides clean shutdown procedures.
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self.ble_samples_received = 0 # Count of BLE-specific samples
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async def get_ble_device(self):
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"""c
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"""
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Scan for and select a BLE device interactively.
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This asynchronous method: Scans for available BLE devices using Chords_BLE scanner, presents discovered devices to user, handles user selection, returns selected device object.
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Returns:
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self.sample_count = 0
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self.last_timestamp = now
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def lsl_rate_checker(self, duration=1.0): # For USB Only(Need modification)
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def lsl_rate_checker(self, duration=1.0):
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"""
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Independently verifies the actual streaming rate of the LSL outlet.
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This method: Collects timestamps over a measurement period -> calculates rate from timestamp differences.

chordspy/static/script.js

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@@ -13,7 +13,7 @@ function logError(error) {
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headers: { 'Content-Type': 'application/json' },
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body: JSON.stringify({ error: errorMessage })
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}).catch(() => {
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console.error('Failed to log error:', errorMessage);
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consoled.error('Failed to log error:', errorMessage);
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});
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console.error(errorMessage);

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