sihnpy.datasets
Module Contents
Functions
Loads paths to functional connectivity data from a subset of 15 participants of the |
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Loads the spreadsheets for the 521 PREVENT-AD FreeSurfer-processed structural scans. |
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Loads the spreadsheets for the simulated tau-PET data for the 308 PREVENT-AD participants |
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Loads the spreadsheet for the simulated age data for the 308 PREVENT-AD participants |
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Loads the spreadsheets for the 521 PREVENT-AD FreeSurfer-processed structural scans. |
- sihnpy.datasets.pad_fp_input()[source]
Loads paths to functional connectivity data from a subset of 15 participants of the Prevent-AD open data ready for the fingerprinting analysis.
The dataset contains functional connectivity matrices from three tasks: resting state, memory encoding and memory retrieval.
The data was taken from two timepoints: at baseline and 12 months later.
- Returns
Returns, in order, a pandas.DataFrame with the participants information from the dataset, a path to file where this DataFrame was imported from and a dictionary of paths to individual connectivity matrices for each timepoint.
- Return type
pandas.DataFrame, str, dict
- sihnpy.datasets.pad_fptab_input()[source]
Loads the spreadsheets for the 521 PREVENT-AD FreeSurfer-processed structural scans. It outputs one spreadsheet for volume, one for thickness, and one for the rest (sub-cortical), TIV, etc.
- Returns
Returns three pandas.DataFrame containing the structural data for the PREVENT-AD participants.
- Return type
pandas.DataFrame
- sihnpy.datasets.pad_spex_input()[source]
Loads the spreadsheets for the simulated tau-PET data for the 308 PREVENT-AD participants available in the Open dataset. This data is used to test and practice the spatial extent module.
Note that all tau-PET data is simulated (i.e., was randomly generated and assigned to a participant). As such, the data should only be used for educational purposes.
- Returns
Returns three dataframes: the simulated tau-PET data for the 308 participants, a dataframe containing pre-computed thresholds (3SD from negative participants) and a dataframe with the averages and SDs used to simulate the data.
- Return type
pandas.DataFrame
- sihnpy.datasets.pad_sw_input()[source]
Loads the spreadsheet for the simulated age data for the 308 PREVENT-AD participants available in the Open dataset. This data is used to test and practice the sliding-window module.
Note that all age data is simulated (i.e., was randomly generated and assigned to a participant). As such, the data should only be used for educational purposes.
- Returns
Returns a pandas DataFrame containing the simulated age of 308 participants from the PREVENT-AD.
- Return type
pandas.DataFrame
- sihnpy.datasets.pad_imb_input()[source]
Loads the spreadsheets for the 521 PREVENT-AD FreeSurfer-processed structural scans. It outputs one spreadsheet for volume, one for thickness, and one for the rest (sub-cortical), TIV, etc.
- Returns
Returns three pandas.DataFrame containing the structural data for the PREVENT-AD participants.
- Return type
pandas.DataFrame