Perform RSA between data and model DSMs.
The data DSM (or list/generator of data DSMs).
The model DSM (or list of model DSMs).
The RSA metric to use to compare the DSMs. Valid options are:
‘spearman’ for Spearman’s correlation (the default)
‘pearson’ for Pearson’s correlation
‘kendall-tau-a’ for Kendall’s Tau (alpha variant)
‘partial’ for partial Pearson correlations
‘partial-spearman’ for partial Spearman correlations
‘regression’ for linear regression weights
Defaults to ‘spearman’.
Whether to treat NaN’s as missing values and ignore them when computing
the distance metric. Defaults to
New in version 0.8.
The number of data DSMs. This is useful when displaying a progress bar,
so an estimate can be made of the computation time remaining. This
information is available if
dsm_data is an array or a list, but if
it is a generator, this information is not available and you may want
to set it explicitly.
The number of processes (=number of CPU cores) to use. Specify -1 to use all available cores. Defaults to 1.
Whether to display a progress bar. In order for this to work, you need the tqdm python module installed. Defaults to False.
Depending on whether one or more data and model DSMs were specified, a single similarity value or a 2D array of similarity values for each data DSM versus each model DSM.