self = <lsst.ap.association.diaPipe.DiaPipelineTask object at 0x7f7284351ab0>

diaSourceTable = <MagicMock spec='DataFrame' id='140129819267504'>

solarSystemObjectTable = <MagicMock spec='DataFrame' id='140129822736096'>

diffIm = <Mock spec='ExposureF' id='140129819266736'>, exposure = <Mock spec='ExposureF' id='140129819267264'>

template = <Mock spec='ExposureF' id='140129819267552'>, ccdExposureIdBits = 32, band = 'g'

    @timeMethod

    def run(self,

            diaSourceTable,

            solarSystemObjectTable,

            diffIm,

            exposure,

            template,

            ccdExposureIdBits,

            band):

        """Process DiaSources and DiaObjects.

        Load previous DiaObjects and their DiaSource history. Calibrate the

        values in the diaSourceCat. Associate new DiaSources with previous

        DiaObjects. Run forced photometry at the updated DiaObject locations.

        Store the results in the Alert Production Database (Apdb).

        Parameters

        ----------

        diaSourceTable : `pandas.DataFrame`

            Newly detected DiaSources.

        diffIm : `lsst.afw.image.ExposureF`

            Difference image exposure in which the sources in ``diaSourceCat``

            were detected.

        exposure : `lsst.afw.image.ExposureF`

            Calibrated exposure differenced with a template to create

            ``diffIm``.

        template : `lsst.afw.image.ExposureF`

            Template exposure used to create diffIm.

        ccdExposureIdBits : `int`

            Number of bits used for a unique ``ccdVisitId``.

        band : `str`

            The band in which the new DiaSources were detected.

        Returns

        -------

        results : `lsst.pipe.base.Struct`

            Results struct with components.

            - ``apdbMaker`` : Marker dataset to store in the Butler indicating

              that this ccdVisit has completed successfully.

              (`lsst.dax.apdb.ApdbConfig`)

            - ``associatedDiaSources`` : Catalog of newly associated

              DiaSources. (`pandas.DataFrame`)

        """

        # Load the DiaObjects and DiaSource history.

        loaderResult = self.diaCatalogLoader.run(diffIm, self.apdb)

        # Associate new DiaSources with existing DiaObjects.

        assocResults = self.associator.run(diaSourceTable,

                                           loaderResult.diaObjects)

        if self.config.doSolarSystemAssociation:

            ssoAssocResult = self.solarSystemAssociator.run(

                assocResults.unAssocDiaSources,

                solarSystemObjectTable,

                diffIm)

            createResults = self.createNewDiaObjects(

                ssoAssocResult.unAssocDiaSources)

            associatedDiaSources = pd.concat(

                [assocResults.matchedDiaSources,

                 ssoAssocResult.ssoAssocDiaSources,

                 createResults.diaSources])

            nTotalSsObjects = ssoAssocResult.nTotalSsObjects

            nAssociatedSsObjects = ssoAssocResult.nAssociatedSsObjects

        else:

            createResults = self.createNewDiaObjects(

                assocResults.unAssocDiaSources)

            associatedDiaSources = pd.concat(

                [assocResults.matchedDiaSources,

                 createResults.diaSources])

            nTotalSsObjects = 0

            nAssociatedSsObjects = 0

        # Create new DiaObjects from unassociated diaSources.

        self._add_association_meta_data(assocResults.nUpdatedDiaObjects,

                                        assocResults.nUnassociatedDiaObjects,

                                        createResults.nNewDiaObjects,

                                        nTotalSsObjects,

                                        nAssociatedSsObjects)

        # Index the DiaSource catalog for this visit after all associations

        # have been made.

        updatedDiaObjectIds = associatedDiaSources["diaObjectId"][

            associatedDiaSources["diaObjectId"] != 0].to_numpy()

        associatedDiaSources.set_index(["diaObjectId",

                                        "filterName",

                                        "diaSourceId"],

                                       drop=False,

                                       inplace=True)

        # Append new DiaObjects and DiaSources to their previous history.

>       diaObjects = pd.concat(

            [loaderResult.diaObjects,

             createResults.newDiaObjects.set_index("diaObjectId", drop=False)],

            sort=True)

E       TypeError: TestDiaPipelineTask._testRun.<locals>.concatMock() got an unexpected keyword argument 'sort'

(Pdb) pd.concat([loaderResult.diaObjects, createResults.newDiaObjects.set_index("diaObjectId", drop=False)], sort=True)

*** TypeError: cannot concatenate object of type '<class 'unittest.mock.MagicMock'>'; only Series and DataFrame objs are valid