qlat_utils.get_threshold_x_arr

qlat_utils.get_threshold_x_arr(data_arr, data_x_arr, threshold_arr, axis=-1)

return x_arr `` data_x_arr.shape == (data_arr.shape[axis],) `` let shape = np.moveaxis(data_arr, axis, -1)[…, 0].shape `` threshold_arr = np.broadcast_to(threshold_arr, shape) `` such that `` for index in np.ndindex(shape):

q.interp_x(data_arr[index], data_x_arr, x_arr[index]) approx threshold_arr[index]

``