ovrlpy.compute_VSI
==================

.. py:function:: ovrlpy.compute_VSI(df, pca_components, min_expression = None, KDE_bandwidth = 1, patch_length = 500, n_workers = 8, dtype=np.float32)

   Calculate the vertical signal integrity (VSI).

   :param df: The spatial transcriptomics dataset.
              This dataframe should contain a *gene*, *x*, *y*, and *z* column.
              Needs to be prepared by calling pre_process_coordinates
   :type df: pandas.DataFrame
   :param pca_components: PCA components from fitted local maxima.
   :type pca_components: pandas.DataFrame
   :param min_expression: Minimal gene expression level to include in the VSI computation.
                          Defaults to the 110% of the maximum expression profile of two molecules in the KDE.
   :type min_expression: float, optional
   :param KDE_bandwidth: Bandwidth for the kernel density estimation.
   :type KDE_bandwidth: float, optional
   :param patch_length: Data will be processed in patches. Upperbound for the length in x/y of a patch.
   :type patch_length: int, optional
   :param n_workers: Number of threads to use for processing.
   :type n_workers: int, optional
   :param dtype: Datatype used for the calculations.

   :returns: * **VSI** (*numpy.ndarray*) -- The vertical signal integrity score.
             * **signal** (*numpy.ndarray*) -- The total gene expression signal.