rsatoolbox.rdm.calc_unbalanced module¶
Calculation of RDMs from unbalanced datasets, i.e. datasets with different channels or numbers of measurements per dissimilarity
@author: heiko
- rsatoolbox.rdm.calc_unbalanced.calc_one_similarity(data_i: DatasetBase, data_j: DatasetBase, cv_desc_i: NDArray, cv_desc_j: NDArray, method='euclidean', noise=None, weighting='number', prior_lambda=1, prior_weight=0.1) Tuple[NDArray, NDArray] [source]¶
finds all pairs of vectors to be compared and calculates one distance
- Parameters:
data_i (rsatoolbox.data.DatasetBase) – dataset for condition i
data_j (rsatoolbox.data.DatasetBase) – dataset for condition j
cv_desc_i (numpy.ndarray) – crossvalidation descriptor for condition i
cv_desc_j (numpy.ndarray) – crossvalidation descriptor for condition j
method (string) – which dissimilarity to compute
noise – numpy.ndarray (n_channels x n_channels), optional the covariance or precision matrix over channels necessary for calculation of mahalanobis distances
- Returns:
- (value, weight)
value is the dissimilarity weight is the weight of the samples
- Return type:
(np.ndarray, np.ndarray)
- rsatoolbox.rdm.calc_unbalanced.calc_rdm_unbalanced(dataset: SingleOrMultiDataset, method='euclidean', descriptor=None, noise=None, cv_descriptor=None, prior_lambda=1, prior_weight=0.1, weighting='number', enforce_same=False) RDMs [source]¶
calculate a RDM from an input dataset for unbalanced datasets.
- Parameters:
dataset (rsatoolbox.data.dataset.DatasetBase) – The dataset the RDM is computed from
method (String) – a description of the dissimilarity measure (e.g. ‘Euclidean’)
descriptor (String) – obs_descriptor used to define the rows/columns of the RDM
noise (numpy.ndarray) – dataset.n_channel x dataset.n_channel precision matrix used to calculate the RDM used only for Mahalanobis and Crossnobis estimators defaults to an identity matrix, i.e. euclidean distance
- Returns:
RDMs object with the one RDM
- Return type:
- rsatoolbox.rdm.calc_unbalanced.ensure_double(a: NDArray) NDArray[np.float64] [source]¶
If required, will convert the array datatype to Float64
This ensures compatibility with the underlying c type “double”. If the array is already compatible, it will pass through. If it is an integer, a converted copy will be made.
- Parameters:
a (NDArray) – Numeric numpy array
- Returns:
The float64 version of the array
- Return type:
NDArray[np.float64]