Representational (dis)similarity analysis
Functions
pdist(X[, metric, p, w, V, VI]) | Computes the pairwise distances between m original observations in n-dimensional space. |
pearsonr(x, y) | Calculates a Pearson correlation coefficient and the p-value for testing |
rankdata(a) | Assign ranks to the data in a, dealing with ties appropriately. |
squareform(X[, force, checks]) | Converts a vector-form distance vector to a square-form distance matrix, and vice-versa. |
Classes
Dataset(samples[, sa, fa, a]) | Generic storage class for datasets with multiple attributes. |
EnsureChoice(*values) | Ensure an input is element of a set of possible values .. |
Measure([null_dist]) | A measure computed from a Dataset |
PDist(**kwargs) | Compute dissimiliarity matrix for samples in a dataset |
PDistConsistency(**kwargs) | Calculate the correlations of PDist measures across chunks |
PDistTargetSimilarity(target_dsm, **kwargs) | Calculate the correlations of PDist measures with a target |
Parameter(default[, constraints, ro, index, ...]) | This class shall serve as a representation of a parameter. |
combinations | combinations(iterable, r) –> combinations object |