Exemplo n.º 1
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    def test_geodb_barefile_with_num(self):
        with utils.WorkSpace(self.geodbworkspace):
            known_raster = os.path.join(self.geodbworkspace, '_temp_test_7')
            temp_raster = utils.create_temp_filename('test', filetype='raster', num=7)
            nt.assert_equal(temp_raster, known_raster)

            known_shape = os.path.join(self.geodbworkspace, '_temp_test_22')
            temp_shape = utils.create_temp_filename('test', filetype='shape', num=22)
            nt.assert_equal(temp_shape, known_shape)
Exemplo n.º 2
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    def test_geodb_barefile(self):
        with utils.WorkSpace(self.geodbworkspace):
            known_raster = os.path.join(self.geodbworkspace, '_temp_test')
            temp_raster = utils.create_temp_filename('test', filetype='raster')
            nt.assert_equal(temp_raster, known_raster)

            known_shape = os.path.join(self.geodbworkspace, '_temp_test')
            temp_shape = utils.create_temp_filename('test', filetype='shape')
            nt.assert_equal(temp_shape, known_shape)
Exemplo n.º 3
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    def test_folderworkspace_barefile_with_num(self):
        with utils.WorkSpace(self.folderworkspace):
            known_raster = os.path.join(self.folderworkspace, '_temp_test_14.tif')
            temp_raster = utils.create_temp_filename('test', filetype='raster', num=14)
            nt.assert_equal(temp_raster, known_raster)

            known_shape = os.path.join(self.folderworkspace, '_temp_test_3.shp')
            temp_shape = utils.create_temp_filename('test', filetype='shape', num=3)
            nt.assert_equal(temp_shape, known_shape)
Exemplo n.º 4
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    def test_folderworkspace_withsubfolder_with_num(self):
        with utils.WorkSpace(self.folderworkspace):
            known_raster = os.path.join(self.folderworkspace, 'subfolder', '_temp_test_1.tif')
            temp_raster = utils.create_temp_filename(os.path.join('subfolder', 'test'), filetype='raster', num=1)
            nt.assert_equal(temp_raster, known_raster)

            known_shape = os.path.join(self.folderworkspace, 'subfolder', '_temp_test_12.shp')
            temp_shape = utils.create_temp_filename(os.path.join('subfolder','test'), filetype='shape', num=12)
            nt.assert_equal(temp_shape, known_shape)
Exemplo n.º 5
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    def test_with_extension_folder_with_num(self):
        with utils.WorkSpace(self.folderworkspace):
            filename = 'test'
            known_raster = os.path.join(self.folderworkspace, '_temp_test_4.tif')
            temp_raster = utils.create_temp_filename(filename + '.tif', filetype='raster', num=4)
            nt.assert_equal(temp_raster, known_raster)

            known_shape = os.path.join(self.folderworkspace, '_temp_test_4.shp')
            temp_shape = utils.create_temp_filename(filename + '.shp', filetype='shape', num=4)
            nt.assert_equal(temp_shape, known_shape)
Exemplo n.º 6
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    def test_with_extension_geodb_with_num(self):
        with utils.WorkSpace(self.folderworkspace):
            filename = os.path.join(self.geodbworkspace, 'test')
            known_raster = os.path.join(self.folderworkspace, self.geodbworkspace, '_temp_test_2000')
            temp_raster = utils.create_temp_filename(filename + '.tif', filetype='raster', num=2000)
            nt.assert_equal(temp_raster, known_raster)

            known_shape = os.path.join(self.folderworkspace, self.geodbworkspace, '_temp_test_999')
            temp_shape = utils.create_temp_filename(filename + '.tif', filetype='shape', num=999)
            nt.assert_equal(temp_shape, known_shape)
Exemplo n.º 7
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    def test_geodb_as_subfolder_with_num(self):
        with utils.WorkSpace(self.folderworkspace):
            filename = os.path.join(self.geodbworkspace, 'test')
            known_raster = os.path.join(self.folderworkspace, self.geodbworkspace, '_temp_test_5')
            temp_raster = utils.create_temp_filename(filename, filetype='raster', num=5)
            nt.assert_equal(temp_raster, known_raster)

            known_shape = os.path.join(self.folderworkspace, self.geodbworkspace, '_temp_test_99')
            temp_shape = utils.create_temp_filename(filename, filetype='shape', num=99)
            nt.assert_equal(temp_shape, known_shape)
Exemplo n.º 8
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    def test_with_extension_folder(self):
        with utils.WorkSpace(self.folderworkspace):
            filename = 'test'
            known_raster = os.path.join(self.folderworkspace, '_temp_test.tif')
            temp_raster = utils.create_temp_filename(filename + '.tif',
                                                     filetype='raster')
            nt.assert_equal(temp_raster, known_raster)

            known_shape = os.path.join(self.folderworkspace, '_temp_test.shp')
            temp_shape = utils.create_temp_filename(filename + '.shp',
                                                    filetype='shape')
            nt.assert_equal(temp_shape, known_shape)
Exemplo n.º 9
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    def test_geodb_as_subfolder(self):
        with utils.WorkSpace(self.folderworkspace):
            filename = os.path.join(self.geodbworkspace, 'test')
            known_raster = os.path.join(self.folderworkspace,
                                        self.geodbworkspace, '_temp_test')
            temp_raster = utils.create_temp_filename(filename,
                                                     filetype='raster')
            nt.assert_equal(temp_raster, known_raster)

            known_shape = os.path.join(self.folderworkspace,
                                       self.geodbworkspace, '_temp_test')
            temp_shape = utils.create_temp_filename(filename, filetype='shape')
            nt.assert_equal(temp_shape, known_shape)
Exemplo n.º 10
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    def test_folderworkspace_withsubfolder(self):
        with utils.WorkSpace(self.folderworkspace):
            known_raster = os.path.join(self.folderworkspace, 'subfolder',
                                        '_temp_test.tif')
            temp_raster = utils.create_temp_filename(os.path.join(
                'subfolder', 'test'),
                                                     filetype='raster')
            nt.assert_equal(temp_raster, known_raster)

            known_shape = os.path.join(self.folderworkspace, 'subfolder',
                                       '_temp_test.shp')
            temp_shape = utils.create_temp_filename(os.path.join(
                'subfolder', 'test'),
                                                    filetype='shape')
            nt.assert_equal(temp_shape, known_shape)
Exemplo n.º 11
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    def test_folderworkspace_barefile_with_num(self):
        with utils.WorkSpace(self.folderworkspace):
            known_raster = os.path.join(self.folderworkspace,
                                        '_temp_test_14.tif')
            temp_raster = utils.create_temp_filename('test',
                                                     filetype='raster',
                                                     num=14)
            nt.assert_equal(temp_raster, known_raster)

            known_shape = os.path.join(self.folderworkspace,
                                       '_temp_test_3.shp')
            temp_shape = utils.create_temp_filename('test',
                                                    filetype='shape',
                                                    num=3)
            nt.assert_equal(temp_shape, known_shape)
Exemplo n.º 12
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    def test_with_extension_geodb_with_num(self):
        with utils.WorkSpace(self.folderworkspace):
            filename = os.path.join(self.geodbworkspace, 'test')
            known_raster = os.path.join(self.folderworkspace,
                                        self.geodbworkspace, '_temp_test_2000')
            temp_raster = utils.create_temp_filename(filename + '.tif',
                                                     filetype='raster',
                                                     num=2000)
            nt.assert_equal(temp_raster, known_raster)

            known_shape = os.path.join(self.folderworkspace,
                                       self.geodbworkspace, '_temp_test_999')
            temp_shape = utils.create_temp_filename(filename + '.tif',
                                                    filetype='shape',
                                                    num=999)
            nt.assert_equal(temp_shape, known_shape)
Exemplo n.º 13
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    def _prep_flooder_input(elev=None,
                            surge=None,
                            slr=None,
                            num=None,
                            flood_output=None):
        """ Prepares the basic inputs to the :meth:`.analyze` method.

        Parameters
        ----------
        elev, slr : float, optional
            Final elevation and sea level rise associated with the
            scenario.
        surge : str, optional
            The name of the storm surge associated with the scenario
            (e.g., MHHW, 100yr).
        flood_output : str
            Path/filename to where the final flooded areas will be
            saved.

        Returns
        -------
        elevation : float
            Flood elevation for this scenario.
        title : str
            The basis of the header to be displayed as an arcpy.Message.
        temp_fname : str
            Path/name of the temporary file where the intermediate
            output will be saved.

        """
        if elev is None:
            elevation = float(slr + SURGES[surge])
            title = "Analyzing flood elevation: {} ft ({}, {})".format(
                elevation, surge, slr)
        else:
            elevation = float(elev)
            title = "Analyzing flood elevation: {} ft".format(elevation)

        if flood_output is None:
            raise ValueError('must provide a `flood_output`')

        basename, ext = os.path.splitext(flood_output)
        _temp_fname = basename + str(elevation).replace('.', '_') + ext
        temp_fname = utils.create_temp_filename(_temp_fname,
                                                num=num,
                                                prefix='',
                                                filetype='shape')

        return elevation, title, temp_fname
Exemplo n.º 14
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    def _prep_flooder_input(elev=None, surge=None, slr=None, num=None,
                            flood_output=None):
        """ Prepares the basic inputs to the :meth:`.analyze` method.

        Parameters
        ----------
        elev, slr : float, optional
            Final elevation and sea level rise associated with the
            scenario.
        surge : str, optional
            The name of the storm surge associated with the scenario
            (e.g., MHHW, 100yr).
        flood_output : str
            Path/filename to where the final flooded areas will be
            saved.

        Returns
        -------
        elevation : float
            Flood elevation for this scenario.
        title : str
            The basis of the header to be displayed as an arcpy.Message.
        temp_fname : str
            Path/name of the temporary file where the intermediate
            output will be saved.

        """
        if elev is None:
            elevation = float(slr + SURGES[surge])
            title = "Analyzing flood elevation: {} ft ({}, {})".format(elevation, surge, slr)
        else:
            elevation = float(elev)
            title = "Analyzing flood elevation: {} ft".format(elevation)

        if flood_output is None:
            raise ValueError('must provide a `flood_output`')

        basename, ext = os.path.splitext(flood_output)
        _temp_fname = basename + str(elevation).replace('.', '_') + ext
        temp_fname = utils.create_temp_filename(_temp_fname, num=num, prefix='', filetype='shape')

        return elevation, title, temp_fname
Exemplo n.º 15
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    def finish_results(outputname, results, **kwargs):
        """ Merges and cleans up compiled output from `analyze`.

        Parameters
        ----------
        outputname : str
            Path to where the final file sould be saved.
        results : list of str
            Lists of all of the floods, flooded wetlands, and flooded
            buildings, respectively, that will be merged and deleted.
        sourcename : str, optional
            Path to the original source file of the results. If
            provided, its attbutes will be spatially joined to the
            concatenated results.

        Returns
        -------
        None

        """

        sourcename = kwargs.pop('sourcename', None)
        cleanup = kwargs.pop('cleanup', True)

        if outputname is not None:
            if sourcename is not None:
                tmp_fname = utils.create_temp_filename(outputname, filetype='shape')
                utils.concat_results(tmp_fname, *results)
                utils.join_results_to_baseline(
                    outputname,
                    utils.load_data(tmp_fname, 'layer'),
                    utils.load_data(sourcename, 'layer')
                )
                utils.cleanup_temp_results(tmp_fname)

            else:
                utils.concat_results(outputname, *results)

        if cleanup:
            utils.cleanup_temp_results(*results)
Exemplo n.º 16
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    def finish_results(outputname, results, **kwargs):
        """ Merges and cleans up compiled output from `analyze`.

        Parameters
        ----------
        outputname : str
            Path to where the final file sould be saved.
        results : list of str
            Lists of all of the floods, flooded wetlands, and flooded
            buildings, respectively, that will be merged and deleted.
        sourcename : str, optional
            Path to the original source file of the results. If
            provided, its attbutes will be spatially joined to the
            concatenated results.

        Returns
        -------
        None

        """

        sourcename = kwargs.pop('sourcename', None)
        cleanup = kwargs.pop('cleanup', True)

        if outputname is not None:
            if sourcename is not None:
                tmp_fname = utils.create_temp_filename(outputname, filetype='shape')
                utils.concat_results(tmp_fname, *results)
                utils.join_results_to_baseline(
                    outputname,
                    utils.load_data(tmp_fname, 'layer'),
                    utils.load_data(sourcename, 'layer')
                )
                utils.cleanup_temp_results(tmp_fname)

            else:
                utils.concat_results(outputname, *results)

        if cleanup:
            utils.cleanup_temp_results(*results)
Exemplo n.º 17
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    def main_execute(self, **params):
        """ Performs the flood-impact analysis on multiple flood
        elevations.

        Parameters
        ----------
        workspace : str
            The folder or geodatabase where the analysis will be
            executed.
        dem : str
            Filename of the digital elevation model (topography data)
            to be used in determinging the inundated areas.
        zones : str
            Name of zones of influence layer.
        ID_column : str
            Name of the field in ``zones`` that uniquely identifies
            each zone of influence.
        elevation : list, optional
            List of (custom) flood elevations to be analyzed. If this is
            not provided, *all* of the standard scenarios will be
            evaluated.
        flood_output : str
            Filename where the extent of flooding and damage will be
            saved.
        wetlands, buildings : str, optional
            Names of the wetland and building footprint layers.
        wetland_output, building_output : str, optional
            Filenames where the flooded wetlands and building footprints
            will be saved.

        Returns
        -------
        None

        """

        wetlands = params.get('wetlands', None)
        buildings = params.get('buildings', None)

        all_floods = []
        all_wetlands = []
        all_buildings = []

        with utils.WorkSpace(params['workspace']), utils.OverwriteState(True):

            topo_array, zones_array, template = tidegates.process_dem_and_zones(
                dem=params['dem'],
                zones=params['zones'],
                ID_column=params['ID_column']
            )

            for scenario in self.make_scenarios(**params):
                fldlyr, wtlndlyr, blgdlyr = self.analyze(
                    topo_array=topo_array,
                    zones_array=zones_array,
                    template=template,
                    elev=scenario['elev'],
                    surge=scenario['surge_name'],
                    slr=scenario['slr'],
                    **params
                )
                all_floods.append(fldlyr.dataSource)
                if wetlands is not None:
                    all_wetlands.append(wtlndlyr.dataSource)

                if buildings is not None:
                    all_buildings.append(blgdlyr.dataSource)

            self.finish_results(
                params['flood_output'],
                all_floods,
                msg="Merging and cleaning up all flood results",
                verbose=True,
                asMessage=True,
            )

            if wetlands is not None:
                wtld_output = params.get(
                    'wetland_output',
                    utils.create_temp_filename(params['wetlands'], prefix='output_', filetype='shape')
                )
                self.finish_results(
                    wtld_output,
                    all_wetlands,
                    sourcename=params['wetlands'],
                    msg="Merging and cleaning up all wetlands results",
                    verbose=True,
                    asMessage=True,
                )

            if buildings is not None:
                bldg_output = params.get(
                    'building_output',
                    utils.create_temp_filename(params['buildings'], prefix='output_', filetype='shape')
                )
                self.finish_results(
                    bldg_output,
                    all_buildings,
                    sourcename=params['buildings'],
                    msg="Merging and cleaning up all buildings results",
                    verbose=True,
                    asMessage=True,
                )
Exemplo n.º 18
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    def analyze(self, elev=None, surge=None, slr=None, **params):
        """ Tool-agnostic helper function for :meth:`.main_execute`.

        Parameters
        ----------
        elev : float, optional
            Custom elevation to be analyzed
        slr : float, optional
            Sea level rise associated with the standard scenario.
        surge : str, optional
            The name of the storm surge associated with the scenario
            (e.g., MHHW, 100yr).
        **params : keyword arguments
            Keyword arguments of analysis parameters generated by
            `self._get_parameter_values`

        Returns
        -------
        floods, flooded_wetlands, flooded_buildings : arcpy.mapping.Layers
            Layers (or None) of the floods and flood-impacted wetlands
            and buildings, respectively.

        """

        # prep input
        elev, title, floods_path = self._prep_flooder_input(
            flood_output=params['flood_output'],
            elev=elev,
            surge=surge,
            slr=slr,
        )

        # define the scenario in the message windows
        self._show_header(title)

        # run the scenario and add its info the output attribute table
        flooded_zones = tidegates.flood_area(
            dem=params['dem'],
            zones=params['zones'],
            ID_column=params['ID_column'],
            elevation_feet=elev,
            filename=floods_path,
            verbose=True,
            asMessage=True
        )
        self._add_scenario_columns(flooded_zones.dataSource, elev=elev, surge=surge, slr=slr)

        # setup temporary files for impacted wetlands and buildings
        wl_path = utils.create_temp_filename(floods_path, prefix="_wetlands_", filetype='shape')
        bldg_path = utils.create_temp_filename(floods_path, prefix="_buildings_", filetype='shape')

        # asses impacts due to flooding
        fldlyr, wtlndlyr, blgdlyr = tidegates.assess_impact(
            floods_path=floods_path,
            flood_idcol=params['ID_column'],
            wetlands_path=params.get('wetlands', None),
            wetlands_output=wl_path,
            buildings_path=params.get('buildings', None),
            buildings_output=bldg_path,
            cleanup=False,
            verbose=True,
            asMessage=True,
        )

        if wtlndlyr is not None:
            self._add_scenario_columns(wtlndlyr.dataSource, elev=elev, surge=surge, slr=slr)

        return fldlyr, wtlndlyr, blgdlyr
Exemplo n.º 19
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    def main_execute(self, **params):
        """ Performs the flood-impact analysis on multiple flood
        elevations.

        Parameters
        ----------
        workspace : str
            The folder or geodatabase where the analysis will be
            executed.
        dem : str
            Filename of the digital elevation model (topography data)
            to be used in determinging the inundated areas.
        zones : str
            Name of zones of influence layer.
        ID_column : str
            Name of the field in ``zones`` that uniquely identifies
            each zone of influence.
        elevation : list, optional
            List of (custom) flood elevations to be analyzed. If this is
            not provided, *all* of the standard scenarios will be
            evaluated.
        flood_output : str
            Filename where the extent of flooding and damage will be
            saved.
        wetlands, buildings : str, optional
            Names of the wetland and building footprint layers.
        wetland_output, building_output : str, optional
            Filenames where the flooded wetlands and building footprints
            will be saved.

        Returns
        -------
        None

        """

        wetlands = params.get('wetlands', None)
        buildings = params.get('buildings', None)

        all_floods = []
        all_wetlands = []
        all_buildings = []

        with utils.WorkSpace(params['workspace']), utils.OverwriteState(True):

            topo_array, zones_array, template = tidegates.process_dem_and_zones(
                dem=params['dem'],
                zones=params['zones'],
                ID_column=params['ID_column']
            )

            for num, scenario in enumerate(self.make_scenarios(**params)):
                fldlyr, wtlndlyr, blgdlyr = self.analyze(
                    topo_array=topo_array,
                    zones_array=zones_array,
                    template=template,
                    elev=scenario['elev'],
                    surge=scenario['surge_name'],
                    slr=scenario['slr'],
                    num=num,
                    **params
                )
                all_floods.append(fldlyr.dataSource)
                if wetlands is not None:
                    all_wetlands.append(wtlndlyr.dataSource)

                if buildings is not None:
                    all_buildings.append(blgdlyr.dataSource)

            self.finish_results(
                params['flood_output'],
                all_floods,
                msg="Merging and cleaning up all flood results",
                verbose=True,
                asMessage=True,
            )

            if wetlands is not None:
                wtld_output = params.get(
                    'wetland_output',
                    utils.create_temp_filename(params['wetlands'], prefix='output_', filetype='shape')
                )
                self.finish_results(
                    wtld_output,
                    all_wetlands,
                    sourcename=params['wetlands'],
                    msg="Merging and cleaning up all wetlands results",
                    verbose=True,
                    asMessage=True,
                )

            if buildings is not None:
                bldg_output = params.get(
                    'building_output',
                    utils.create_temp_filename(params['buildings'], prefix='output_', filetype='shape')
                )
                self.finish_results(
                    bldg_output,
                    all_buildings,
                    sourcename=params['buildings'],
                    msg="Merging and cleaning up all buildings results",
                    verbose=True,
                    asMessage=True,
                )
Exemplo n.º 20
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    def analyze(self, topo_array, zones_array, template,
                elev=None, surge=None, slr=None, num=0, **params):
        """ Tool-agnostic helper function for :meth:`.main_execute`.

        Parameters
        ----------
        topo_array : numpy array
            Floating point array of the digital elevation model.
        zones_array : numpy array
            Categorical (integer) array of where each non-zero value
            delineates a tidegate's zone of influence.
        template : arcpy.Raster or tidegates.utils.RasterTemplate
            A raster or raster-like object that define the spatial
            extent of the analysis area. Required attributes are:
              - templatemeanCellWidth
              - templatemeanCellHeight
              - templateextent.lowerLeft
        elev : float, optional
            Custom elevation to be analyzed
        slr : float, optional
            Sea level rise associated with the standard scenario.
        surge : str, optional
            The name of the storm surge associated with the scenario
            (e.g., MHHW, 100yr).
        **params : keyword arguments
            Keyword arguments of analysis parameters generated by
            `self._get_parameter_values`

        Returns
        -------
        floods, flooded_wetlands, flooded_buildings : arcpy.mapping.Layers
            Layers (or None) of the floods and flood-impacted wetlands
            and buildings, respectively.

        """

        # prep input
        elev, title, floods_path = self._prep_flooder_input(
            flood_output=params['flood_output'],
            elev=elev,
            surge=surge,
            slr=slr,
            num=num,
        )

        # define the scenario in the message windows
        self._show_header(title)

        # run the scenario and add its info the output attribute table
        flooded_zones = tidegates.flood_area(
            topo_array=topo_array,
            zones_array=zones_array,
            template=template,
            ID_column=params['ID_column'],
            elevation_feet=elev,
            filename=floods_path,
            num=num,
            verbose=True,
            asMessage=True
        )
        self._add_scenario_columns(flooded_zones.dataSource, elev=elev, surge=surge, slr=slr)

        # setup temporary files for impacted wetlands and buildings
        wl_path = utils.create_temp_filename(floods_path, prefix="_wetlands_", filetype='shape', num=num)
        bldg_path = utils.create_temp_filename(floods_path, prefix="_buildings_", filetype='shape', num=num)

        # asses impacts due to flooding
        fldlyr, wtlndlyr, blgdlyr = tidegates.assess_impact(
            floods_path=floods_path,
            flood_idcol=params['ID_column'],
            wetlands_path=params.get('wetlands', None),
            wetlands_output=wl_path,
            buildings_path=params.get('buildings', None),
            buildings_output=bldg_path,
            cleanup=False,
            verbose=True,
            asMessage=True,
        )

        if wtlndlyr is not None:
            self._add_scenario_columns(wtlndlyr.dataSource, elev=elev, surge=surge, slr=slr)

        return fldlyr, wtlndlyr, blgdlyr
Exemplo n.º 21
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    def analyze(self, topo_array, zones_array, template,
                elev=None, surge=None, slr=None, **params):
        """ Tool-agnostic helper function for :meth:`.main_execute`.

        Parameters
        ----------
        topo_array : numpy array
            Floating point array of the digital elevation model.
        zones_array : numpy array
            Categorical (integer) array of where each non-zero value
            delineates a tidegate's zone of influence.
        template : arcpy.Raster or tidegates.utils.RasterTemplate
            A raster or raster-like object that define the spatial
            extent of the analysis area. Required attributes are:
              - templatemeanCellWidth
              - templatemeanCellHeight
              - templateextent.lowerLeft
        elev : float, optional
            Custom elevation to be analyzed
        slr : float, optional
            Sea level rise associated with the standard scenario.
        surge : str, optional
            The name of the storm surge associated with the scenario
            (e.g., MHHW, 100yr).
        **params : keyword arguments
            Keyword arguments of analysis parameters generated by
            `self._get_parameter_values`

        Returns
        -------
        floods, flooded_wetlands, flooded_buildings : arcpy.mapping.Layers
            Layers (or None) of the floods and flood-impacted wetlands
            and buildings, respectively.

        """

        # prep input
        elev, title, floods_path = self._prep_flooder_input(
            flood_output=params['flood_output'],
            elev=elev,
            surge=surge,
            slr=slr,
        )

        # define the scenario in the message windows
        self._show_header(title)

        # run the scenario and add its info the output attribute table
        flooded_zones = tidegates.flood_area(
            topo_array=topo_array,
            zones_array=zones_array,
            template=template,
            ID_column=params['ID_column'],
            elevation_feet=elev,
            filename=floods_path,
            verbose=True,
            asMessage=True
        )
        self._add_scenario_columns(flooded_zones.dataSource, elev=elev, surge=surge, slr=slr)

        # setup temporary files for impacted wetlands and buildings
        wl_path = utils.create_temp_filename(floods_path, prefix="_wetlands_", filetype='shape')
        bldg_path = utils.create_temp_filename(floods_path, prefix="_buildings_", filetype='shape')

        # asses impacts due to flooding
        fldlyr, wtlndlyr, blgdlyr = tidegates.assess_impact(
            floods_path=floods_path,
            flood_idcol=params['ID_column'],
            wetlands_path=params.get('wetlands', None),
            wetlands_output=wl_path,
            buildings_path=params.get('buildings', None),
            buildings_output=bldg_path,
            cleanup=False,
            verbose=True,
            asMessage=True,
        )

        if wtlndlyr is not None:
            self._add_scenario_columns(wtlndlyr.dataSource, elev=elev, surge=surge, slr=slr)

        return fldlyr, wtlndlyr, blgdlyr