Bases: object
Methods
contrast(vector) | Compute images of contrast and contrast variance. |
dump(filename) | Dump GLM fit as npz file. |
Compute images of contrast and contrast variance.
Dump GLM fit as npz file.
Return a list of clusters, each cluster being represented by a dictionary. Clusters are sorted by descending size order. Within each cluster, local maxima are sorted by descending depth order.
Parameters : | zimg: z-score image : mask: mask image : height_th: cluster forming threshold : height_control: string :
cluster_th: cluster size threshold : null_s : cluster-level calibration method: None|’rft’|array |
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Notes
This works only with three dimensional data
returns all the peaks of image that are with the mask and above the provided threshold
Parameters : | image, (3d) test image : mask=None, (3d) mask image :
threshold=0., float, threshold value above which peaks are considered : nn=18, int, number of neighbours of the topological spatial model : order_th=0, int, threshold on topological order to validate the peaks : |
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Returns : | peaks, a list of dictionray, where each dic has the fields: : vals, map value at the peak : order, topological order of the peak : ijk, array of shape (1,3) grid coordinate of the peak : pos, array of shape (n_maxima,3) mm coordinates (mapped by affine) :
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Helper function for group data analysis using arbitrary design matrix
Helper function for permutation-based mass univariate onesample group analysis.
Helper function for permutation-based mass univariate twosample group analysis. Labels is a binary vector (1-2). Regions more active for group 1 than group 2 are inferred.