rsatoolbox.rdm.compare module

Comparison methods for comparing two RDMs objects

rsatoolbox.rdm.compare.compare(rdm1, rdm2, method='cosine', sigma_k=None)

calculates the similarity between two RDMs objects using a chosen method

Parameters:

• rdm1 (rsatoolbox.rdm.RDMs) – first set of RDMs

• rdm2 (rsatoolbox.rdm.RDMs) – second set of RDMs

• method (string) –

  which method to use, options are:

  ’cosine’ = cosine similarity

  ’spearman’ = spearman rank correlation

  ’corr’ = pearson correlation

  ’kendall’ = kendall-tau b

  ’tau-a’ = kendall-tau a

  ’rho-a’ = spearman correlation without tie correction

  ’corr_cov’ = pearson correlation after whitening

  ’cosine_cov’ = unbiased distance correlation which is equivalent to the cosine dinstance after whitening

  ’neg_riem_dist’ = negative riemannian distance

• sigma_k (numpy.ndarray) – covariance matrix of the pattern estimates. Used only for methods ‘corr_cov’ and ‘cosine_cov’.

Returns:

dist:

pariwise similarities between the RDMs from the RDMs objects

Return type:

numpy.ndarray

rsatoolbox.rdm.compare.compare_correlation(rdm1, rdm2)

calculates the correlations between two RDMs objects

Parameters:

• rdm1 (rsatoolbox.rdm.RDMs) – first set of RDMs

• rdm2 (rsatoolbox.rdm.RDMs) – second set of RDMs

Returns:

dist:

correlations between the two RDMs

Return type:

numpy.ndarray

rsatoolbox.rdm.compare.compare_correlation_cov_weighted(rdm1, rdm2, sigma_k=None)

calculates the correlations between two RDMs objects after whitening with the covariance of the entries

Parameters:

• rdm1 (rsatoolbox.rdm.RDMs) – first set of RDMs

• rdm2 (rsatoolbox.rdm.RDMs) – second set of RDMs

Returns:

dist:

correlations between the two RDMs

Return type:

numpy.ndarray

rsatoolbox.rdm.compare.compare_cosine(rdm1, rdm2)

calculates the cosine similarities between two RDMs objects

Parameters:

• rdm1 (rsatoolbox.rdm.RDMs) – first set of RDMs

• rdm2 (rsatoolbox.rdm.RDMs) – second set of RDMs

Returns:

dist

cosine similarity between the two RDMs

Return type:

numpy.ndarray

rsatoolbox.rdm.compare.compare_cosine_cov_weighted(rdm1, rdm2, sigma_k=None)

calculates the cosine similarities between two RDMs objects

Parameters:

• rdm1 (rsatoolbox.rdm.RDMs) – first set of RDMs

• rdm2 (rsatoolbox.rdm.RDMs) – second set of RDMs

Returns:

dist:

cosine similarities between the two RDMs

Return type:

numpy.ndarray

rsatoolbox.rdm.compare.compare_kendall_tau(rdm1, rdm2)

calculates the Kendall-tau bs between two RDMs objects. Kendall-tau b is the version, which corrects for ties. We here use the implementation from scipy.

Parameters:

• rdm1 (rsatoolbox.rdm.RDMs) – first set of RDMs

• rdm2 (rsatoolbox.rdm.RDMs) – second set of RDMs

Returns:

dist:

kendall-tau correlation between the two RDMs

Return type:

numpy.ndarray

rsatoolbox.rdm.compare.compare_kendall_tau_a(rdm1, rdm2)

calculates the Kendall-tau a based distance between two RDMs objects. adequate when some models predict ties

Parameters:

• rdm1 (rsatoolbox.rdm.RDMs) – first set of RDMs

• rdm2 (rsatoolbox.rdm.RDMs) – second set of RDMs

Returns:

dist:

kendall-tau a between the two RDMs

Return type:

numpy.ndarray

rsatoolbox.rdm.compare.compare_neg_riemannian_distance(rdm1, rdm2, sigma_k=None)

calculates the negative Riemannian distance between two RDMs objects.

Parameters:

• rdm1 (rsatoolbox.rdm.RDMs) – first set of RDMs

• rdm2 (rsatoolbox.rdm.RDMs) – second set of RDMs

Returns:

dist:

negative Riemannian distance between the two RDMs

Return type:

numpy.ndarray

rsatoolbox.rdm.compare.compare_rho_a(rdm1, rdm2)

calculates the spearman rank correlations between two RDMs objects without tie correction

Parameters:

• rdm1 (rsatoolbox.rdm.RDMs) – first set of RDMs

• rdm2 (rsatoolbox.rdm.RDMs) – second set of RDMs

Returns:

dist:

rank correlations between the two RDMs

Return type:

numpy.ndarray

rsatoolbox.rdm.compare.compare_spearman(rdm1, rdm2)

calculates the spearman rank correlations between two RDMs objects

Parameters:

• rdm1 (rsatoolbox.rdm.RDMs) – first set of RDMs

• rdm2 (rsatoolbox.rdm.RDMs) – second set of RDMs

Returns:

dist:

rank correlations between the two RDMs

Return type:

numpy.ndarray