multifit.py 文件源码

def _build_cov_mat_datapoints(self, axis):
        '''
        Builds the Cov_mat for the data points for the given axis. The cov_mat will take in account
        if 2 datasets are the same and correlate them, if self.corelate_datasets is True.


        '''
        dummy2 = []
        __querry_dummy2 = []
        for i,fit in enumerate(self.fit_list):
            # Create mask to store points where a non 0 matrix is needed.
            __querry = [False] * len(self.fit_list)
            # Diagonal entrys are never 0
            __querry[i] = True
            dummy2.append([0] * len(self.fit_list))
            # Check if datsets are correlated. If so change non diagonal elements.
            if self.corelate_datasets:
                if np.allclose(self.fit_list[i].dataset.get_data(axis), self.fit_list[i-1].dataset.get_data(axis),
                               atol=0, rtol=1e-4):
                    __querry[i-1] = True
            __querry_dummy2.append(__querry)

        for i,list in enumerate(dummy2):
            for j,entry in enumerate(list):
                if __querry_dummy2[i][j]:
                    dummy2[i][j] = self.fit_list[i].current_cov_mat
                else:
                    dummy2[i][j] = np.zeros((self.fit_list[i].dataset.get_size(), self.fit_list[j].dataset.get_size()))
        return np.bmat(dummy2)