Beispiel #1
0
 def get_w(self, x, confounds):
     ### extract w values
     W = []
     W2 = []
     for ii in range(len(self.st_crm)):
         W.append(self.st_crm[ii][1].compute_weights(
             self.st_crm[ii][0].transform(confounds, x[:, ii, :]),
             mask_part=self.mask_part))
         W2.append(self.st_crm[ii][2].compute_weights(
             self.st_crm[ii][0].transform(confounds, x[:, ii, :]),
             mask_part=self.mask_part))
     xw = np.hstack(W)
     xw2 = np.hstack(W2)
     return subtypes.reshapeW(xw), subtypes.reshapeW(xw2)
Beispiel #2
0
 def get_w(self,x,confounds):
     ### extract w values
     W = []
     for ii in range(len(self.st_crm)):
         W.append(self.st_crm[ii][1].compute_weights(self.st_crm[ii][0].transform(confounds,x[:,ii,:]),mask_part=self.mask_part))
     xw = np.hstack(W)
     return subtypes.reshapeW(xw)
Beispiel #3
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    def get_w_files(self,files_path,subjects_id_list,confounds):
        ### extract w values
        W = []
        for ii in range(len(self.st_crm)):
            x_ref = sbp_util.grab_rmap(subjects_id_list,files_path,ii,dynamic=False)
            ## compute w values
            W.append(self.st_crm[ii][1].compute_weights(self.st_crm[ii][0].transform(confounds,x_ref),mask_part=self.mask_part))
            del x_ref

        xw = np.hstack(W)
        return subtypes.reshapeW(xw)
Beispiel #4
0
    def get_w_files(self, files_path, subjects_id_list, confounds):
        ### extract w values
        W = []
        W2 = []
        for ii in range(len(self.st_crm)):
            x_ref = sbp_util.grab_rmap(subjects_id_list,
                                       files_path,
                                       ii,
                                       dynamic=False)
            ## compute w values
            W.append(self.st_crm[ii][1].compute_weights(
                self.st_crm[ii][0].transform(confounds, x_ref),
                mask_part=self.mask_part))

            W2.append(self.st_crm[ii][2].compute_weights(
                self.st_crm[ii][0].transform(confounds, x_ref),
                mask_part=self.mask_part))
            del x_ref

        xw = np.hstack(W)
        xw2 = np.hstack(W2)
        return subtypes.reshapeW(xw), subtypes.reshapeW(xw2)