Error in Outlier correction

[JensBlack]

Describe the bug
After starting the outlier correction with both parameters set to 0 (the plan was to skip the correction with this), i got the following error message:

Exception in Tkinter callback Traceback (most recent call last): File "D:\Anaconda\envs\simba-gpu\lib\tkinter\__init__.py", line 1705, in __call__ return self.func(*args) File "simba.py", line 3818, in correct_outlier dev_loc_user_defined(configini) File "C:\Users\schwa\PycharmProjects\simba\simba\outlier_scripts\location\correct_devs_loc_user_defined.py", line 100, in dev_loc_user_defined currentArray[currentPosition][0] = reliableCoordinates[currentPosition][0] IndexError: index 7 is out of bounds for axis 0 with size 7

The csv file was transfered/created in the correct folder i assume "project_folder\csv\outlier_corrected_movement" but there is no file in "outlier_corrected_movement_location".
I checked your code and i guess it did not go through as the error occurs in one of the essential scripts.

To Reproduce
My user defined settings are: 9 points , 1 Animal (directly from DLC analysis)
The csv file is ca. 55k rows long

I am using a Windows 10 computer and your newest simba version (updated at 10 am local time)

Additional context
I cannot continue with extraction of features however.
It results in a message within your app:
Pose-estimation body part setting for feature extraction: user_defined Extracting features from 0 files... All feature extraction complete.
which is probably due a non working import in your code:

def extract_features_wotarget(inifile): .... csv_dir_in = os.path.join(csv_dir, 'outlier_corrected_movement_location') ....

########### FIND CSV FILES ########### for i in os.listdir(csv_dir_in): if i.__contains__(".csv"): fname = os.path.join(csv_dir_in, i) filesFound.append(fname) print('Extracting features from ' + str(len(filesFound)) + ' files...')

I can however continue if i copy+paste the same csv file (from outlier_corrected_movement) into the other folder. I haven't read through all of your code, but i assume that you keep the general structure of the dataframe that comes from dlc so this can work as a workaround for now (especially since i did not want to do a outlier correction anyway).

[JensBlack]

I just noticed that it wasn't very smart to set the boundary for the corretion to 0 if i wanted to skip everything.
It actually corrected 100% of the data, which is definetly as intended by you...
Setting the boundary higher than the resolution solved that minor hickup and solved the issue.

I will leave this open for you to check out, but i guess the whole issue was an unlikely user interaction you didn't count in when writing your code. You can close it anytime.