9 Commits

Author SHA1 Message Date
5361f6ea21 changed the changelog 2025-10-15 16:12:51 -07:00
ee023c26c1 changelog fix 2025-10-15 16:10:48 -07:00
06c9ff0ecf update changelog 2025-10-15 15:59:26 -07:00
542dd85a78 general fixes 2025-10-15 15:51:02 -07:00
3e0f70ea49 fixes to build version 1.1.3 2025-10-15 12:59:24 -07:00
d6c71e0ab2 changelog fixes and further updates to cancel running process 2025-10-15 10:48:07 -07:00
87073fb218 more boris implementation 2025-10-15 10:00:44 -07:00
3d0fbd5c5e fix to boris events 2025-10-03 16:58:49 -07:00
3f38f5a978 updates for boris support 2025-09-26 14:01:32 -07:00
5 changed files with 1416 additions and 41 deletions

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@@ -1,3 +1,34 @@
# Version 1.1.4
- Fixed some display text to now display the correct information
- A new option under Analysis has been added to export the data from a specified participant as a csv file. Fixes [Issue 19](https://git.research.dezeeuw.ca/tyler/flares/issues/19), [Issue 27](https://git.research.dezeeuw.ca/tyler/flares/issues/27)
- Added 2 new parameters - TIME_WINDOW_START and TIME_WINDOW_END. Fixes [Issue 29](https://git.research.dezeeuw.ca/tyler/flares/issues/29)
- These parameters affect the visualization of the significance and contrast images but do not change the total time modeled underneath
- Fixed the duration of annotations edited from a BORIS file from 0 seconds to their proper duration
- Added the annotation information to each participant under their "File information" window
- Fixed Macs not being able to save snirfs attempting to be updated from BORIS files, and in general the updated files not respecting the path chosen by the user
# Version 1.1.3
- Added back the ability to use the fOLD dataset. Fixes [Issue 23](https://git.research.dezeeuw.ca/tyler/flares/issues/23)
- 5th option has been added under Analysis to get to fOLD channels per participant
- Added an option to cancel the running process. Fixes [Issue 15](https://git.research.dezeeuw.ca/tyler/flares/issues/15)
- Prevented graph images from showing when participants are being processed. Fixes [Issue 24](https://git.research.dezeeuw.ca/tyler/flares/issues/24)
- Allow the option to remove all events of a type from all loaded snirfs. Fixes [Issue 25](https://git.research.dezeeuw.ca/tyler/flares/issues/25)
- Added new icons in the menu bar
- Added a terminal to interact with the app in a more command-like form
- Currently the terminal has no functionality but some features for batch operations will be coming soon!
- Inter-Group viewer now has the option to visualize the average response on the brain of all participants in the group. Fixes [Issue 26](https://git.research.dezeeuw.ca/tyler/flares/issues/24)
- Fixed the description under "Update events in snirf file..."
# Version 1.1.2
- Fixed incorrect colormaps being applied
- Added functionality to utilize external event markers from a file. Fixes [Issue 6](https://git.research.dezeeuw.ca/tyler/flares/issues/6)
# Version 1.1.1 # Version 1.1.1
- Fixed the number of rectangles in the progress bar to 19 - Fixed the number of rectangles in the progress bar to 19

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@@ -50,12 +50,12 @@ from scipy.spatial.distance import cdist
# Backen visualization needed to be defined for pyinstaller # Backen visualization needed to be defined for pyinstaller
import pyvistaqt # type: ignore import pyvistaqt # type: ignore
import vtkmodules.util.data_model # import vtkmodules.util.data_model
import vtkmodules.util.execution_model # import vtkmodules.util.execution_model
# External library imports for mne # External library imports for mne
from mne import ( from mne import (
EvokedArray, SourceEstimate, Info, Epochs, Label, EvokedArray, SourceEstimate, Info, Epochs, Label, Annotations,
events_from_annotations, read_source_spaces, events_from_annotations, read_source_spaces,
stc_near_sensors, pick_types, grand_average, get_config, set_config, read_labels_from_annot stc_near_sensors, pick_types, grand_average, get_config, set_config, read_labels_from_annot
) # type: ignore ) # type: ignore
@@ -132,6 +132,11 @@ ENHANCE_NEGATIVE_CORRELATION: bool
SHORT_CHANNEL: bool SHORT_CHANNEL: bool
REMOVE_EVENTS: list
TIME_WINDOW_START: int
TIME_WINDOW_END: int
VERBOSITY = True VERBOSITY = True
# FIXME: Shouldn't need each ordering - just order it before checking # FIXME: Shouldn't need each ordering - just order it before checking
@@ -179,6 +184,9 @@ REQUIRED_KEYS: dict[str, Any] = {
"PSP_THRESHOLD": float, "PSP_THRESHOLD": float,
"SHORT_CHANNEL": bool, "SHORT_CHANNEL": bool,
"REMOVE_EVENTS": list,
"TIME_WINDOW_START": int,
"TIME_WINDOW_END": int
# "REJECT_PAIRS": bool, # "REJECT_PAIRS": bool,
# "FORCE_DROP_ANNOTATIONS": list, # "FORCE_DROP_ANNOTATIONS": list,
# "FILTER_LOW_PASS": float, # "FILTER_LOW_PASS": float,
@@ -1074,7 +1082,7 @@ def epochs_calculations(raw_haemo, events, event_dict):
# Plot drop log # Plot drop log
# TODO: Why show this if we never use epochs2? # TODO: Why show this if we never use epochs2?
fig_epochs_dropped = epochs2.plot_drop_log() fig_epochs_dropped = epochs2.plot_drop_log(show=False)
fig_epochs.append(("fig_epochs_dropped", fig_epochs_dropped)) fig_epochs.append(("fig_epochs_dropped", fig_epochs_dropped))
# Plot for each condition # Plot for each condition
@@ -1108,7 +1116,7 @@ def epochs_calculations(raw_haemo, events, event_dict):
evokeds3 = [] evokeds3 = []
colors = [] colors = []
conditions = list(epochs.event_id.keys()) conditions = list(epochs.event_id.keys())
cmap = plt.cm.get_cmap("tab10", len(conditions)) cmap = plt.get_cmap("tab10", len(conditions))
for idx, cond in enumerate(conditions): for idx, cond in enumerate(conditions):
evoked = epochs[cond].average(picks="hbo") evoked = epochs[cond].average(picks="hbo")
@@ -1470,9 +1478,15 @@ def resource_path(relative_path):
def fold_channels(raw: BaseRaw) -> None: def fold_channels(raw: BaseRaw) -> None:
# if getattr(sys, 'frozen', False):
path = os.path.expanduser("~") + "/mne_data/fOLD/fOLD-public-master/Supplementary"
logger.info(path)
set_config('MNE_NIRS_FOLD_PATH', resource_path(path)) # type: ignore
# Locate the fOLD excel files # # Locate the fOLD excel files
set_config('MNE_NIRS_FOLD_PATH', resource_path("../../mne_data/fOLD/fOLD-public-master/Supplementary")) # type: ignore # else:
# logger.info("yabba")
# set_config('MNE_NIRS_FOLD_PATH', resource_path("../../mne_data/fOLD/fOLD-public-master/Supplementary")) # type: ignore
output = None output = None
@@ -1534,8 +1548,8 @@ def fold_channels(raw: BaseRaw) -> None:
"Brain_Outside", "Brain_Outside",
] ]
cmap1 = plt.cm.get_cmap('tab20') # First 20 colors cmap1 = plt.get_cmap('tab20') # First 20 colors
cmap2 = plt.cm.get_cmap('tab20b') # Next 20 colors cmap2 = plt.get_cmap('tab20b') # Next 20 colors
# Combine the colors from both colormaps # Combine the colors from both colormaps
colors = [cmap1(i) for i in range(20)] + [cmap2(i) for i in range(20)] # Total 40 colors colors = [cmap1(i) for i in range(20)] + [cmap2(i) for i in range(20)] # Total 40 colors
@@ -1611,6 +1625,7 @@ def fold_channels(raw: BaseRaw) -> None:
for ax in axes[len(hbo_channel_names):]: for ax in axes[len(hbo_channel_names):]:
ax.axis('off') ax.axis('off')
plt.show()
return fig, legend_fig return fig, legend_fig
@@ -2935,6 +2950,19 @@ def process_participant(file_path, progress_callback=None):
logger.info("14") logger.info("14")
# Step 14: Design Matrix # Step 14: Design Matrix
events_to_remove = REMOVE_EVENTS
filtered_annotations = [ann for ann in raw.annotations if ann['description'] not in events_to_remove]
new_annot = Annotations(
onset=[ann['onset'] for ann in filtered_annotations],
duration=[ann['duration'] for ann in filtered_annotations],
description=[ann['description'] for ann in filtered_annotations]
)
# Set the new annotations
raw_haemo.set_annotations(new_annot)
design_matrix, fig_design_matrix = make_design_matrix(raw_haemo, short_chans) design_matrix, fig_design_matrix = make_design_matrix(raw_haemo, short_chans)
fig_individual["Design Matrix"] = fig_design_matrix fig_individual["Design Matrix"] = fig_design_matrix
if progress_callback: progress_callback(15) if progress_callback: progress_callback(15)
@@ -3008,7 +3036,11 @@ def process_participant(file_path, progress_callback=None):
contrast_dict = {} contrast_dict = {}
for condition in all_conditions: for condition in all_conditions:
delay_cols = [col for col in all_delay_cols if col.startswith(f"{condition}_delay_")] delay_cols = [
col for col in all_delay_cols
if col.startswith(f"{condition}_delay_") and
TIME_WINDOW_START <= int(col.split("_delay_")[-1]) <= TIME_WINDOW_END
]
if not delay_cols: if not delay_cols:
continue # skip if no columns found (shouldn't happen?) continue # skip if no columns found (shouldn't happen?)

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main.py

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