further variable changes

.gitignore

@@ -174,3 +174,4 @@ cython_debug/
 # PyPI configuration file
 .pypirc
 
+/individual_images

changelog.md

@@ -1,4 +1,44 @@
-# Next Release
+# Version 1.2.0
+
+- Added new parameters to the right side of the screen
+- These parameters include SHOW_OPTODE_NAMES, SECONDS_TO_STRIP_HR, MAX_LOW_HR, MAX_HIGH_HR, SMOOTHING_WINDOW_HR, HEART_RATE_WINDOW, BAD_CHANNELS_HANDLING, MAX_DIST, MIN_NEIGHBORS, L_TRANS_BANDWIDTH, H_TRANS_BANDWIDTH, RESAMPLE, RESAMPLE_FREQ, STIM_DUR, HRF_MODEL, HIGH_PASS, DRIFT_ORDER, FIR_DELAYS, MIN_ONSET, OVERSAMPLING, SHORT_CHANNEL_REGRESSION, NOISE_MODEL, BINS, and VERBOSITY.
+- All the new parameters have default values matching the underlying values in version 1.1.7
+- The order of the parameters have changed to match the order that the code runs when the Process button is clicked
+- Moved TIME_WINDOW_START and TIME_WINDOW_END to the 'Other' category
+- Fixed a bug causing SCI to not work when HEART_RATE was set to False
+- Bad channels can now be dealt with by taking no action, removing them completely, or interpolating them based on their neighbours. Interpolation remains the default option
+- Fixed an underlying deprecation warning
+- Fixed an issue causing some overlay elements to not render on the brain for certain devices
+- Fixed a crash when rendering some Inter-Group images with only one participant in a group
+- Fixed a crash when attempting to fOLD channels without the fOLD dataset installed
+- Lowered the number of rectangles in the progress bar to 24 after combining some actions
+- Fixed the User Guide window to properly display information about the 24 stages and added a link to the Git wiki page
+- MAX_WORKERS should now properly repect the value set
+- Added a new CSV export option to be used by other applications
+
+
+# Version 1.1.7
+
+- Fixed a bug where having both a L_FREQ and H_FREQ would cause only the L_FREQ to be used
+- Changed the default H_FREQ from 0.7 to 0.3
+- Added a PSD graph, along with 2 heart rate images to the individual participant viewer
+- The PSD graph is used to help calculate the heart rate, whereas the other 2 are currently just for show
+- SCI is now done using a .6hz window around the calculated heart rate compared to a window around an average heart rate
+- Fixed an issue with some epochs figures not showing under the participant analysis
+- Removed SECONDS_TO_STRIP from the preprocessing options
+- Added new parameters to the right side of the screen
+- These parameters include TRIM, SECONDS_TO_KEEP, OPTODE_PLACEMENT, HEART_RATE, WAVELET, IQR, WAVELET_TYPE, WAVELET_LEVEL, ENHANCE_NEGATIVE_CORRELATION, SHORT_CHANNEL_THRESH, LONG_CHANNEL_THRESH, and DRIFT_MODEL
+- Changed number of rectangles in the progress bar to 25 to account for the new options
+
+
+# Version 1.1.6
+
+- Fixed Process button from appearing when no files are selected
+- Fixed a bug that would cause an instant child process crash on Windows
+- Added L_FREQ and H_FREQ parameters for more user control over low and high pass filtering
+
+
+# Version 1.1.5
 
 - Fixed Windows saves not being able to be opened by a Mac (hopefully the other way too!)
 - Added the option to right click loaded snirf files to reveal them in a file browser or delete them if they are no longer desired
@@ -14,6 +54,7 @@
 - Added a clickable link below the selected file's metadata explaining the independent parameters and why they are useful
 - Updated some tooltips to provide better, more accurate information
 - Added details about the processing steps and their order into the user guide
+- Changed the default bandpass filtering parameters
 
 
 # Version 1.1.4

main.py

@@ -22,11 +22,11 @@ import subprocess
 from pathlib import Path, PurePosixPath
 from datetime import datetime
 from multiprocessing import Process, current_process, freeze_support, Manager
-
+from enum import Enum, auto
-import numpy as np
-import pandas as pd
 
 # External library imports
+import numpy as np
+import pandas as pd
 import psutil
 import requests
 
@@ -46,7 +46,7 @@ from PySide6.QtGui import QAction, QKeySequence, QIcon, QIntValidator, QDoubleVa
 from PySide6.QtSvgWidgets import QSvgWidget # needed to show svgs when app is not frozen
 
 
-CURRENT_VERSION = "1.0.0"
+CURRENT_VERSION = "1.2.0"
 
 API_URL = "https://git.research.dezeeuw.ca/api/v1/repos/tyler/flares/releases"
 API_URL_SECONDARY = "https://git.research2.dezeeuw.ca/api/v1/repos/tyler/flares/releases"
@@ -58,11 +58,43 @@ SECTIONS = [
     {
         "title": "Preprocessing",
         "params": [
-            {"name": "SECONDS_TO_STRIP", "default": 0, "type": int, "help": "Seconds to remove from beginning of all loaded snirf files. Setting this to 0 will remove nothing from the files."},
             {"name": "DOWNSAMPLE", "default": True, "type": bool, "help": "Should the snirf files be downsampled? If this is set to True, DOWNSAMPLE_FREQUENCY will be used as the target frequency to downsample to."},
             {"name": "DOWNSAMPLE_FREQUENCY", "default": 25, "type": int, "help": "Frequency (Hz) to downsample to. If this is set higher than the input data, new data will be interpolated. Only used if DOWNSAMPLE is set to True"},
         ]
     },
+    {
+        "title": "Trimming",
+        "params": [
+            {"name": "TRIM", "default": True, "type": bool, "help": "Trim the file start."},
+            {"name": "SECONDS_TO_KEEP", "default": 5, "type": float, "help": "Seconds to keep at the beginning of all loaded snirf files before the first annotation/event occurs. Calculation is done seperatly on all loaded snirf files. Setting this to 0 will have the first annotation/event be at time point 0."},
+        ]
+    },
+    {
+        "title": "Verify Optode Placement",
+        "params": [
+            {"name": "OPTODE_PLACEMENT", "default": True, "type": bool, "help": "Generate an image for each participant outlining their optode placement."},
+            {"name": "SHOW_OPTODE_NAMES", "default": True, "type": bool, "help": "Should the optode names be written next to their location or not."},
+        ]
+    },
+    {
+        "title": "Short/Long Channels",
+        "params": [
+            {"name": "SHORT_CHANNEL", "default": True, "type": bool, "help": "This should be set to True if the data has a short channel present in the data."},
+            {"name": "SHORT_CHANNEL_THRESH", "default": 0.015, "type": float, "help": "The maximum distance the short channel can be in metres."},
+            {"name": "LONG_CHANNEL_THRESH", "default": 0.045, "type": float, "help": "The maximum distance the long channel can be in metres."},
+        ]
+    },
+    {
+        "title": "Heart Rate",
+        "params": [
+            {"name": "HEART_RATE", "default": True, "type": bool, "help": "Attempt to calculate the participants heart rate."},
+            {"name": "SECONDS_TO_STRIP_HR", "default": 5, "type": int, "help": "Will remove this many seconds from the start and end of the file. Useful if recording before cap is firmly placed, or participant removes cap while still recording."},
+            {"name": "MAX_LOW_HR", "default": 40, "type": int, "help": "Any heart rate windows that average below this value will be rounded up to this value."},
+            {"name": "MAX_HIGH_HR", "default": 200, "type": int, "help": "Any heart rate windows that average above this value will be rounded down to this value."},
+            {"name": "SMOOTHING_WINDOW_HR", "default": 100, "type": int, "help": "How many individual data points to smooth into a single window."},
+            {"name": "HEART_RATE_WINDOW", "default": 25, "type": int, "help": "Used for visualization. Shows the range of the calculated heart rate +- this value."},
+        ]
+    },
     {
         "title": "Scalp Coupling Index",
         "params": [
@@ -75,14 +107,12 @@ SECTIONS = [
         "title": "Signal to Noise Ratio",
         "params": [
             {"name": "SNR", "default": True, "type": bool, "help": "Calculate and mark channels bad based on their Signal to Noise Ratio. This metric calculates how much of the observed signal was noise versus how much of it was a useful signal."},
-            # {"name": "SNR_TIME_WINDOW", "default": -1, "type": int, "help": "SNR time window."},
             {"name": "SNR_THRESHOLD", "default": 5.0, "type": float, "help": "SNR threshold (dB). A typical scale would be 0-25, but it is possible for values to be both above and below this range. Higher values correspond to a better signal. If SNR is True, any channels lower than this value will be marked as bad."},
         ]
     },
     {
         "title": "Peak Spectral Power",
         "params": [
-
             {"name": "PSP", "default": True, "type": bool, "help": "Calculate and mark channels bad based on their Peak Spectral Power. This metric calculates the amplitude or strength of a frequency component that is most prominent in a particular frequency range or spectrum."},
             {"name": "PSP_TIME_WINDOW", "default": 3, "type": int, "help": "Independent PSP calculations will be perfomed in a time window for the duration of the value provided, until the end of the file is reached."},
             {"name": "PSP_THRESHOLD", "default": 0.1, "type": float, "help": "PSP threshold. A typical scale would be 0-0.5, but it is possible for values to be above this range. Higher values correspond to a better signal. If PSP is True, any channels lower than this value will be marked as bad."},
@@ -91,15 +121,15 @@ SECTIONS = [
     {
         "title": "Bad Channels Handling",
         "params": [
-            # {"name": "NOT_IMPLEMENTED", "default": True, "type": bool, "help": "Calculate Peak Spectral Power."},
+            {"name": "BAD_CHANNELS_HANDLING", "default": [], "type": list, "options": ["Interpolate", "Remove", "None"], "exclusive": True, "help": "How should we deal with the bad channels that occurred? Note: Some analysis options will only work when this is set to 'Interpolate'."},
-            # {"name": "NOT_IMPLEMENTED", "default": 3, "type": int, "help": "PSP time window."},
+            {"name": "MAX_DIST", "default": 0.03, "type": float, "help": "The maximum distance to look for neighbours when interpolating. Used only when BAD_CHANNELS_HANDLING is set to 'Interpolate'."},
-            # {"name": "NOT_IMPLEMENTED", "default": 0.1, "type": float, "help": "PSP threshold."},
+            {"name": "MIN_NEIGHBORS", "default": 2, "type": int, "help": "The minimumn amount of neighbours needed within the MAX_DIST parameter. Used only when BAD_CHANNELS_HANDLING is set to 'Interpolate'."},
         ]
     },
     {
         "title": "Optical Density",
         "params": [
-            # Intentionally empty (TODO)
+            # NOTE: Intentionally empty
         ]
     },
     {
@@ -108,38 +138,45 @@ SECTIONS = [
             {"name": "TDDR", "default": True, "type": bool, "help": "Apply Temporal Derivitave Distribution Repair filtering - a method that removes baseline shift and spike artifacts from the data."},
         ]
     },
+    {
+        "title": "Wavelet filtering",
+        "params": [
+            {"name": "WAVELET", "default": True, "type": bool, "help": "Apply Wavelet filtering."},
+            {"name": "IQR", "default": 1.5, "type": float, "help": "Inter-Quartile Range."},
+            {"name": "WAVELET_TYPE", "default": "db4", "type": str, "help": "Wavelet type."},
+            {"name": "WAVELET_LEVEL", "default": 3, "type": int, "help": "Wavelet level."},
+        ]
+    },
     {
         "title": "Haemoglobin Concentration",
         "params": [
-            # Intentionally empty (TODO)
+            # NOTE: Intentionally empty
         ]
     },
     {
         "title": "Enhance Negative Correlation",
         "params": [
-            #{"name": "ENHANCE_NEGATIVE_CORRELATION", "default": False, "type": bool, "help": "Calculate Peak Spectral Power."},
+            {"name": "ENHANCE_NEGATIVE_CORRELATION", "default": False, "type": bool, "help": "Apply Enhance Negative Correlation."},
         ]
     },
     {
         "title": "Filtering",
         "params": [
-            #{"name": "FILTER", "default": True, "type": bool, "help": "Calculate Peak Spectral Power."},
+            {"name": "FILTER", "default": True, "type": bool, "help": "Filter the data."},
+            {"name": "L_FREQ", "default": 0.005, "type": float, "help": "Any frequencies lower than this value will be removed."},
+            {"name": "H_FREQ", "default": 0.3, "type": float, "help": "Any frequencies higher than this value will be removed."},
+            {"name": "L_TRANS_BANDWIDTH", "default": 0.002, "type": float, "help": "How wide the transitional period should be so the data doesn't just drop off on the lower bound."},
+            {"name": "H_TRANS_BANDWIDTH", "default": 0.002, "type": float, "help": "How wide the transitional period should be so the data doesn't just drop off on the upper bound."},
         ]
     },
     {
-        "title": "Short Channels",
+        "title": "Extracting Events*",
-        "params": [
-            {"name": "SHORT_CHANNEL", "default": True, "type": bool, "help": "This should be set to True if the data has a short channel present in the data."},
-        ]
-    },
-    {
-        "title": "Extracting Events",
         "params": [
             #{"name": "EVENTS", "default": True, "type": bool, "help": "Calculate Peak Spectral Power."},
         ]
     },
     {
-        "title": "Epoch Calculations",
+        "title": "Epoch Calculations*",
         "params": [
             #{"name": "EVENTS", "default": True, "type": bool, "help": "Calculate Peak Spectral Power."},
         ]
@@ -147,18 +184,27 @@ SECTIONS = [
     {
         "title": "Design Matrix",
         "params": [
+            {"name": "RESAMPLE", "default": True, "type": bool, "help": "The length of your stimulus."},
+            {"name": "RESAMPLE_FREQ", "default": 1, "type": int, "help": "The length of your stimulus."},
+            
+            {"name": "STIM_DUR", "default": 0.5, "type": float, "help": "The length of your stimulus."},
+            {"name": "HRF_MODEL", "default": "fir", "type": str, "help": "Specifies the hemodynamic response function."},
+            {"name": "DRIFT_MODEL", "default": "cosine", "type": str, "help": "Specifies the desired drift model."},
+            {"name": "HIGH_PASS", "default": 0.01, "type": float, "help": "High-pass frequency in case of a cosine model (in Hz)."},
+            {"name": "DRIFT_ORDER", "default": 1, "type": int, "help": "Order of the drift model (in case it is polynomial)"},
+            {"name": "FIR_DELAYS", "default": "None", "type": range, "help": "In case of FIR design, yields the array of delays used in the FIR model (in scans)."},
+            {"name": "MIN_ONSET", "default": -24, "type": int, "help": "Minimal onset relative to frame times (in seconds)"},
+            {"name": "OVERSAMPLING", "default": 50, "type": int, "help": "Oversampling factor used in temporal convolutions."},
             {"name": "REMOVE_EVENTS", "default": "None", "type": list, "help": "Remove events matching the names provided before generating the Design Matrix"},
-            # {"name": "DRIFT_MODEL", "default": "cosine", "type": str, "help": "Drift model for GLM."},
+            {"name": "SHORT_CHANNEL_REGRESSION", "default": True, "type": bool, "help": "Whether to use short channel regression and regress out the short channels. Requires SHORT_CHANNELS to be True and at least one short channel to be found."},
-            # {"name": "DURATION_BETWEEN_ACTIVITIES", "default": 35, "type": int, "help": "Time between activities (s)."},
-            # {"name": "SHORT_CHANNEL_REGRESSION", "default": True, "type": bool, "help": "Use short channel regression."},
         ]
     },
     {
         "title": "General Linear Model",
         "params": [
-            {"name": "TIME_WINDOW_START", "default": "0", "type": int, "help": "Where to start averaging the fir model bins. Only affects the significance and contrast images."},
+            {"name": "NOISE_MODEL", "default": "ar1", "type": str, "help": "Number of jobs for GLM processing."},
-            {"name": "TIME_WINDOW_END", "default": "15", "type": int, "help": "Where to end averaging the fir model bins. Only affects the significance and contrast images."},
+            {"name": "BINS", "default": 0, "type": int, "help": "Number of jobs for GLM processing."},
-            #{"name": "N_JOBS", "default": 1, "type": int, "help": "Number of jobs for GLM processing."},
+            {"name": "N_JOBS", "default": 1, "type": int, "help": "Number of jobs for GLM processing."},
         ]
     },
         {
@@ -170,7 +216,10 @@ SECTIONS = [
     {
         "title": "Other",
         "params": [
-            {"name": "MAX_WORKERS", "default": 4, "type": int, "help": "Number of files to be processed at once. Lowering this value may help on underpowered systems."},
+            {"name": "TIME_WINDOW_START", "default": 0, "type": int, "help": "Where to start averaging the fir model bins. Only affects the significance and contrast images."},
+            {"name": "TIME_WINDOW_END", "default": 15, "type": int, "help": "Where to end averaging the fir model bins. Only affects the significance and contrast images."},
+            {"name": "MAX_WORKERS", "default": 4, "type": str, "help": "Number of files to be processed at once. Setting this to a small integer value may help on underpowered systems. Remove the value to use an automatic amount."},
+            {"name": "VERBOSITY", "default": False, "type": bool, "help": "True will log lots of debugging information to the log file. False will only log required data."},
         ]
     },
 ]
@@ -451,29 +500,38 @@ class UserGuideWindow(QWidget):
 
         layout = QVBoxLayout()
         label = QLabel("Progress Bar Stages:", self)
-        label2 = QLabel("Stage 1: Load the snirf file\n"
+        label2 = QLabel("Stage 1: Preprocessing\n"
-                        "Stage 2: Check the optode positions\n"
+                        "Stage 2: Trimming\n"
-                        "Stage 3: Scalp Coupling Index\n"
+                        "Stage 3: Verify Optode Placement\n"
-                        "Stage 4: Signal to Noise Ratio\n"
+                        "Stage 4: Short/Long Cannels\n"
-                        "Stage 5: Peak Spectral Power\n"
+                        "Stage 5: Heart Rate\n"
-                        "Stage 6: Identify bad channels\n"
+                        "Stage 6: Scalp Coupling Index\n"
-                        "Stage 7: Interpolate bad channels\n"
+                        "Stage 7: Signal to Noise Ratio\n"
-                        "Stage 8: Optical Density\n"
+                        "Stage 8: Peak Spectral Power\n"
-                        "Stage 9: Temporal Derivative Distribution Repair\n"
+                        "Stage 9: Bad Channels Handling\n"
-                        "Stage 10: Beer Lambert Law\n"
+                        "Stage 10: Optical Density\n"
-                        "Stage 11: Heart Rate Filtering\n"
+                        "Stage 11: Temporal Derivative Distribution Repair Filtering\n"
-                        "Stage 12: Get Short/Long Channels\n"
+                        "Stage 12: Wavelet Filtering\n"
-                        "Stage 13: Calculate Events from Annotations\n"
+                        "Stage 13: Haemoglobin Concentration\n"
-                        "Stage 14: Epoch Calculations\n"
+                        "Stage 14: Enhance Negative Correlation\n"
-                        "Stage 15: Design Matrix\n"
+                        "Stage 15: Filter\n"
-                        "Stage 16: General Linear Model\n"
+                        "Stage 16: Extracting Events\n"
-                        "Stage 17: Generate Plots from the GLM\n"
+                        "Stage 17: Epoch Calculations\n"
-                        "Stage 18: Individual Significance\n"
+                        "Stage 18: Design Matrix\n"
-                        "Stage 19: Channel, Region of Interest, and Contrast Results\n"
+                        "Stage 19: General Linear Model\n"
-                        "Stage 20: Image Conversion\n", self)
+                        "Stage 20: Generate GLM Results\n"
+                        "Stage 21: Generate Channel Significance\n"
+                        "Stage 22: Generate Channel, Region of Interest, and Contrast Results\n"
+                        "Stage 23: Compute Contrast Results\n"
+                        "Stage 24: Finishing Up\n", self)
 
+        label3 = QLabel("For more information, visit the Git wiki page <a href='https://git.research.dezeeuw.ca/tyler/flares/wiki'>here</a>.", self)
+        label3.setTextFormat(Qt.TextFormat.RichText)
+        label3.setTextInteractionFlags(Qt.TextInteractionFlag.TextBrowserInteraction)
+        label3.setOpenExternalLinks(True)
         layout.addWidget(label)
         layout.addWidget(label2)
+        layout.addWidget(label3)
 
         self.setLayout(layout)
 
@@ -710,15 +768,23 @@ class UpdateOptodesWindow(QWidget):
         write_raw_snirf(raw, save_path)
 
 
+class EventUpdateMode(Enum):
+    WRITE_SNIRF = auto()   # destructive
+    WRITE_JSON = auto()    # non-destructive
 
 
 class UpdateEventsWindow(QWidget):
 
-    def __init__(self, parent=None):
+    def __init__(self, parent=None, mode=EventUpdateMode.WRITE_SNIRF, caller=None):
         super().__init__(parent, Qt.WindowType.Window)
+
+        self.mode = mode
+        self.caller = caller or self.__class__.__name__
         self.setWindowTitle("Update event markers")
         self.resize(760, 200)
 
+        print("INIT MODE:", mode)
+
         self.label_file_a = QLabel("SNIRF file:")
         self.line_edit_file_a = QLineEdit()
         self.line_edit_file_a.setReadOnly(True)
@@ -1019,120 +1085,139 @@ class UpdateEventsWindow(QWidget):
             QMessageBox.warning(self, "No SNIRF file", "Please select a SNIRF file.")
             return
 
+
+        boris_obs = self.boris_data["observations"][selected_obs]
+
+        # --- Extract videos + delays ---
+        files = boris_obs.get("file", {})
+        offsets = boris_obs.get("media_info", {}).get("offset", {})
+
+        videos = {}
+        for key, path in files.items():
+            if path:  # only include videos that exist
+                delay = offsets.get(key, 0.0)  # default 0 if missing
+                videos[key] = {"file": path, "delay": delay}
+
         base_name = os.path.splitext(os.path.basename(file_a))[0]
-        suggested_name = f"{base_name}_{suffix}.snirf"
 
-        # Open save dialog
+        if self.mode == EventUpdateMode.WRITE_SNIRF:
-        save_path, _ = QFileDialog.getSaveFileName(
+            # Open save dialog for SNIRF
-            self,
+            base_name = os.path.splitext(os.path.basename(file_a))[0]
-            "Save SNIRF File As",
+            suggested_name = f"{base_name}_{suffix}.snirf"
-            suggested_name,
+            save_path, _ = QFileDialog.getSaveFileName(
-            "SNIRF Files (*.snirf)"
+                self,
-        )
+                "Save SNIRF File As",
+                suggested_name,
+                "SNIRF Files (*.snirf)"
+            )
+            if not save_path:
+                print("SNIRF save cancelled.")
+                return
+            if not save_path.lower().endswith(".snirf"):
+                save_path += ".snirf"
 
-        if not save_path:
+            try:
-            print("Save cancelled.")
+                raw = read_raw_snirf(file_a, preload=True)
-            return
 
-        if not save_path.lower().endswith(".snirf"):
+                # --- Align BORIS events to SNIRF ---
-            save_path += ".snirf"
+                boris_events = boris_obs.get("events", [])
+                onsets, durations, descriptions = [], [], []
+                open_events = {}  # label -> list of start times
+                label_counts = {}
+                used_times = set()
+                sfreq = raw.info['sfreq']
+                min_shift = 1.0 / sfreq
+                max_attempts = 10
 
-        try:
+                for event in boris_events:
-            raw = read_raw_snirf(snirf_path, preload=True)
+                    if not isinstance(event, list) or len(event) < 3:
+                        continue
+                    event_time = event[0]
+                    label = event[2]
+                    count = label_counts.get(label, 0) + 1
+                    label_counts[label] = count
 
-            onsets = []
+                    if label not in open_events:
-            durations = []
+                        open_events[label] = []
-            descriptions = []
 
-            open_events = {}  # label -> list of start times
+                    if count % 2 == 1:
-            label_counts = {}
+                        open_events[label].append(event_time)
+                    else:
+                        if open_events[label]:
+                            start_time = open_events[label].pop(0)
+                            duration = event_time - start_time
+                            if duration <= 0:
+                                continue
 
-            used_times = set()
+                            adjusted_time = start_time + time_shift
-            sfreq = raw.info['sfreq']  # sampling frequency in Hz
+                            attempts = 0
-            min_shift = 1.0 / sfreq
+                            while round(adjusted_time, 6) in used_times and attempts < max_attempts:
-            max_attempts = 10
+                                adjusted_time += min_shift
+                                attempts += 1
+                            if attempts == max_attempts:
+                                continue
 
-            for event in boris_events:
+                            adjusted_time = round(adjusted_time, 6)
-                if not isinstance(event, list) or len(event) < 3:
+                            used_times.add(adjusted_time)
-                    continue
+                            onsets.append(adjusted_time)
-
+                            durations.append(duration)
-                event_time = event[0]
+                            descriptions.append(label)
-                label = event[2]
+                # Handle unmatched starts
-
+                for label, starts in open_events.items():
-                count = label_counts.get(label, 0) + 1
+                    for start_time in starts:
-                label_counts[label] = count
+                        adjusted_time = start_time + time_shift
-
-                if label not in open_events:
-                    open_events[label] = []
-
-                if count % 2 == 1:
-                    # Odd occurrence = start event
-                    open_events[label].append(event_time)
-                else:
-                    # Even occurrence = end event
-                    if open_events[label]:
-                        matched_start = open_events[label].pop(0)
-                        duration = event_time - matched_start
-
-                        if duration <= 0:
-                            print(f"Warning: Duration for {label} is non-positive ({duration}). Skipping.")
-                            continue
-
-                        shifted_start = matched_start + time_shift
-
-                        adjusted_time = shifted_start
                         attempts = 0
                         while round(adjusted_time, 6) in used_times and attempts < max_attempts:
                             adjusted_time += min_shift
                             attempts += 1
-
                         if attempts == max_attempts:
-                            print(f"Warning: Couldn't find unique time for {label} @ {matched_start}s. Skipping.")
                             continue
-
                         adjusted_time = round(adjusted_time, 6)
                         used_times.add(adjusted_time)
-
-                        print(f"Adding event: {label} @ {adjusted_time:.3f}s for {duration:.3f}s")
-
                         onsets.append(adjusted_time)
-                        durations.append(duration)
+                        durations.append(0.0)
                         descriptions.append(label)
-                    else:
-                        print(f"Warning: Unmatched end for label '{label}' at {event_time:.3f}s. Skipping.")
 
-            # Optionally warn about any unmatched starts left open
+                new_annotations = Annotations(onset=onsets, duration=durations, description=descriptions)
-            for label, starts in open_events.items():
+                raw.set_annotations(new_annotations)
-                for start_time in starts:
+                write_raw_snirf(raw, save_path)
-                    shifted_start = start_time + time_shift
+                QMessageBox.information(self, "Success", "SNIRF file updated with aligned BORIS events.")
 
-                    adjusted_time = shifted_start
+            except Exception as e:
-                    attempts = 0
+                QMessageBox.critical(self, "Error", f"Failed to update SNIRF file:\n{e}")
-                    while round(adjusted_time, 6) in used_times and attempts < max_attempts:
-                        adjusted_time += min_shift
-                        attempts += 1
 
-                    if attempts == max_attempts:
+        elif self.mode == EventUpdateMode.WRITE_JSON:
-                        print(f"Warning: Couldn't find unique time for unmatched start {label} @ {start_time}s. Skipping.")
+            # Open save dialog for JSON
-                        continue
+            base_name = os.path.splitext(os.path.basename(file_a))[0]
+            suggested_name = f"{base_name}_{suffix}_alignment.json"
+            save_path, _ = QFileDialog.getSaveFileName(
+                self,
+                "Save Event Alignment JSON As",
+                suggested_name,
+                "JSON Files (*.json)"
+            )
+            if not save_path:
+                print("JSON save cancelled.")
+                return
+            if not save_path.lower().endswith(".json"):
+                save_path += ".json"
 
-                    adjusted_time = round(adjusted_time, 6)
+            # Build JSON dict
-                    used_times.add(adjusted_time)
+            json_data = {
+                "observation": selected_obs,
+                "snirf_anchor": {"label": snirf_label, "time": snirf_anchor_time},
+                "boris_anchor": {"label": boris_label, "time": boris_anchor_time},
+                "time_shift": time_shift,
+                "videos": videos
+            }
 
-                    print(f"Warning: Unmatched start for label '{label}' at {start_time:.3f}s. Adding with duration 0.")
+            # Write JSON
-                    onsets.append(adjusted_time)
+            try:
-                    durations.append(0.0)
+                with open(save_path, "w", encoding="utf-8") as f:
-                    descriptions.append(label)
+                    json.dump(json_data, f, indent=4)
-
+                QMessageBox.information(self, "Success", f"Event alignment saved to:\n{save_path}")
-            new_annotations = Annotations(onset=onsets, duration=durations, description=descriptions)
+            except Exception as e:
-
+                QMessageBox.critical(self, "Error", f"Failed to write JSON:\n{e}")
-            raw.set_annotations(new_annotations)
-            write_raw_snirf(raw, save_path)
-
-            QMessageBox.information(self, "Success", "SNIRF file updated with aligned BORIS events.")
-
-        except Exception as e:
-            QMessageBox.critical(self, "Error", f"Failed to update SNIRF file:\n{e}")
 
 
     def update_optode_positions(self, file_a, file_b, save_path):
@@ -1165,6 +1250,47 @@ class UpdateEventsWindow(QWidget):
         write_raw_snirf(raw, save_path)
 
 
+    def _apply_events_to_snirf(self, raw, new_annotations, save_path):
+        raw.set_annotations(new_annotations)
+        write_raw_snirf(raw, save_path)
+        
+    def _write_event_mapping_json(
+        self,
+        file_a,
+        file_b,
+        selected_obs,
+        snirf_anchor,
+        boris_anchor,
+        time_shift,
+        mapped_events,
+        save_path
+    ):
+        import json
+        from datetime import datetime
+        import os
+
+        payload = {
+            "source": {
+                "called_from": self.caller,
+                "snirf_file": os.path.basename(file_a),
+                "boris_file": os.path.basename(file_b),
+                "observation": selected_obs
+            },
+            "alignment": {
+                "snirf_anchor": snirf_anchor,
+                "boris_anchor": boris_anchor,
+                "time_shift_seconds": time_shift
+            },
+            "events": mapped_events,
+            "created_at": datetime.utcnow().isoformat() + "Z"
+        }
+
+        with open(save_path, "w", encoding="utf-8") as f:
+            json.dump(payload, f, indent=2)
+
+        return save_path
+
+
 class ProgressBubble(QWidget):
     """
     A clickable widget displaying a progress bar made of colored rectangles and a label.
@@ -1197,7 +1323,7 @@ class ProgressBubble(QWidget):
         self.progress_layout = QHBoxLayout()
 
         self.rects = []
-        for _ in range(20):
+        for _ in range(24):
             rect = QFrame()
             rect.setFixedSize(10, 18)
             rect.setStyleSheet("background-color: white; border: 1px solid gray;")
@@ -1326,7 +1452,12 @@ class ParamSection(QWidget):
                 widget.setValidator(QDoubleValidator())
                 widget.setText(str(param["default"]))
             elif param["type"] == list:
-                widget = self._create_multiselect_dropdown(None)
+                if param.get("exclusive", True):
+                    widget = QComboBox()
+                    widget.addItems(param.get("options", []))
+                    widget.setCurrentText(str(param.get("default", "<None Selected>")))
+                else:
+                    widget = self._create_multiselect_dropdown(None)
             else: 
                 widget = QLineEdit()
                 widget.setText(str(param["default"]))
@@ -1434,7 +1565,10 @@ class ParamSection(QWidget):
             if expected_type == bool:
                 values[name] = widget.currentText() == "True"
             elif expected_type == list:
-                values[name] = [x.strip() for x in widget.lineEdit().text().split(",") if x.strip()]
+                if isinstance(widget, FullClickComboBox):
+                    values[name] = [x.strip() for x in widget.lineEdit().text().split(",") if x.strip()]
+                elif isinstance(widget, QComboBox):
+                    values[name] = widget.currentText()
             else:
                 raw_text = widget.text()
                 try:
@@ -2390,9 +2524,23 @@ class ParticipantFoldChannelsWidget(QWidget):
 
             for idx in selected_indexes:
                 if idx == 0:
-
+                    try:
-                    flares.fold_channels(haemo_obj)
+                        flares.fold_channels(haemo_obj)
-
+                    except:
+                        msg_box = QMessageBox()
+                        msg_box.setIcon(QMessageBox.Icon.Critical)
+                        msg_box.setWindowTitle("Something went wrong!")
+                        message = (
+                            "Unable to locate the fOLD files!<br><br>"
+                            f"Please download the 'Supplementary' folder from <a href='https://github.com/nirx/fOLD-public'>here</a>. "
+                            "Once the folder is downloaded, place it in C:/Users/your username/mne_data/fOLD/fOLD-public-master/Supplementary.<br><br>"
+                            "If you are not using Windows, please go to the FLARES Git page for more information."
+                        )
+                        msg_box.setTextFormat(Qt.TextFormat.RichText)
+                        msg_box.setText(message)
+                        msg_box.setTextInteractionFlags(Qt.TextInteractionFlag.TextBrowserInteraction)
+                        msg_box.setStandardButtons(QMessageBox.StandardButton.Ok)
+                        msg_box.exec()
                 else:
                     print(f"No method defined for index {idx}")
 
@@ -2428,7 +2576,7 @@ class ExportDataAsCSVViewerWidget(QWidget):
               
         self.index_texts = [
             "0 (Export Data to CSV)",
-            # "1 (second image)",
+            "1 (CSV for SPARKS)",
             # "2 (third image)",
             # "3 (fourth image)",
             ]
@@ -2580,7 +2728,6 @@ class ExportDataAsCSVViewerWidget(QWidget):
         # Pass the necessary arguments to each method
         for file_path in selected_file_paths:
             haemo_obj = self.haemo_dict.get(file_path)
-
             if haemo_obj is None:
                 continue
 
@@ -2614,10 +2761,63 @@ class ExportDataAsCSVViewerWidget(QWidget):
                         QMessageBox.critical(self, "Error", f"Failed to update SNIRF file:\n{e}")
 
 
+                elif idx == 1:
+                    try:
+                        suggested_name = f"{file_path}_sparks.csv"
+
+                        # Open save dialog
+                        save_path, _ = QFileDialog.getSaveFileName(
+                            self,
+                            "Save SNIRF File As",
+                            suggested_name,
+                            "CSV Files (*.csv)"
+                        )
+
+                        if not save_path:
+                            print("Save cancelled.")
+                            return
+
+                        if not save_path.lower().endswith(".csv"):
+                            save_path += ".csv"
+                        # Save the CSV here
+                        
+                        raw = haemo_obj
+
+                        data, times = raw.get_data(return_times=True)
+
+
+                        ann_col = np.full(times.shape, "", dtype=object)
+
+                        if raw.annotations is not None and len(raw.annotations) > 0:
+                            for onset, duration, desc in zip(
+                                raw.annotations.onset,
+                                raw.annotations.duration,
+                                raw.annotations.description
+                            ):
+                                mask = (times >= onset) & (times < onset + duration)
+                                ann_col[mask] = desc
+
+                        df = pd.DataFrame(data.T, columns=raw.ch_names)
+                        df.insert(0, "annotation", ann_col)
+
+                        df.insert(0, "time", times)
+                        df.to_csv(save_path, index=False)
+                        QMessageBox.information(self, "Success", "CSV file has been saved.")
+
+                        win = UpdateEventsWindow(
+                            parent=self,
+                            mode=EventUpdateMode.WRITE_JSON,
+                            caller="Video Alignment Tool"
+                        )
+                        win.show()
+
+                    except Exception as e:
+                        QMessageBox.critical(self, "Error", f"Failed to update SNIRF file:\n{e}")
+
+
                 else:
                     print(f"No method defined for index {idx}")
 
-
 class ClickableLabel(QLabel):
     def __init__(self, full_pixmap: QPixmap, thumbnail_pixmap: QPixmap):
         super().__init__()
@@ -4044,7 +4244,7 @@ class MainApplication(QMainWindow):
         self.button2.setMinimumSize(100, 40)
         self.button3.setMinimumSize(100, 40)
 
-        # self.button1.setVisible(False)
+        self.button1.setVisible(False)
         self.button3.setVisible(False) 
 
         self.button1.clicked.connect(self.on_run_task)
@@ -4243,7 +4443,7 @@ class MainApplication(QMainWindow):
 
     def update_event_markers(self):
         if self.events is None or not self.events.isVisible():
-            self.events = UpdateEventsWindow(self)
+            self.events = UpdateEventsWindow(self, EventUpdateMode.WRITE_SNIRF, "Manual SNIRF Edit")
             self.events.show()
 
     def open_file_dialog(self):

mne/transforms.py

@@ -12,7 +12,7 @@ from pathlib import Path
 import numpy as np
 from scipy import linalg
 from scipy.spatial.distance import cdist
-from scipy.special import sph_harm
+from scipy.special import sph_harm_y
 
 from ._fiff.constants import FIFF
 from ._fiff.open import fiff_open

mne/viz/_3d.py

@@ -1025,7 +1025,7 @@ def _handle_sensor_types(meg, eeg, fnirs):
         fnirs=dict(channels="fnirs", pairs="fnirs_pairs"),
     )
     sensor_alpha = {
-        key: dict(meg_helmet=0.25, meg=0.25).get(key, 0.8)
+        key: dict(meg_helmet=0.25, meg=0.25).get(key, 1.0)
         for ch_dict in alpha_map.values()
         for key in ch_dict.values()
     }

mne/viz/backends/_pyvista.py

@@ -586,7 +586,7 @@ class _PyVistaRenderer(_AbstractRenderer):
                 color = None
             else:
                 scalars = None
-            tube = line.tube(radius, n_sides=self.tube_n_sides)
+            tube = line.tube(radius=radius, n_sides=self.tube_n_sides)
             actor = _add_mesh(
                 plotter=self.plotter,
                 mesh=tube,

version_main.txt

@@ -18,7 +18,7 @@ VSVersionInfo(
            StringStruct('FileDescription', 'FLARES main application'),
            StringStruct('FileVersion', '1.0.0.0'),
            StringStruct('InternalName', 'flares.exe'),
-           StringStruct('LegalCopyright', '© 2025 Tyler de Zeeuw'),
+           StringStruct('LegalCopyright', '© 2025-2026 Tyler de Zeeuw'),
            StringStruct('OriginalFilename', 'flares.exe'),
            StringStruct('ProductName', 'FLARES'),
            StringStruct('ProductVersion', '1.0.0.0')])

version_updater.txt

@@ -18,7 +18,7 @@ VSVersionInfo(
            StringStruct('FileDescription', 'FLARES updater application'),
            StringStruct('FileVersion', '1.0.0.0'),
            StringStruct('InternalName', 'main.exe'),
-           StringStruct('LegalCopyright', '© 2025 Tyler de Zeeuw'),
+           StringStruct('LegalCopyright', '© 2025-2026 Tyler de Zeeuw'),
            StringStruct('OriginalFilename', 'flares_updater.exe'),
            StringStruct('ProductName', 'FLARES Updater'),
            StringStruct('ProductVersion', '1.0.0.0')])