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Converters

DHyDAMO Converters API

df2hydrolibmodel

Df2HydrolibModel

Source code in hydrolib/dhydamo/converters/df2hydrolibmodel.py 
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class Df2HydrolibModel:
    def __init__(self, hydamo, assign_default_profiles=False):
        self.hydamo = hydamo
        self.structures = []
        self.crossdefs = []
        self.crosslocs = []
        self.boundaries = []
        self.boundaries_ext = []
        self.boundaries_bc = []
        self.laterals_ext = []
        self.laterals_bc = []
        self.friction_defs = []
        self.obspoints = []
        self.storagenodes = []
        self.inifields = []
        self.onedfields = []

        self.assign_default_profiles = assign_default_profiles
        self.forcingmodel = ForcingModel()
        self.forcingmodel.filepath = "boundaryconditions.bc"
        self.forcingmodel.forcing = []

        self.onedfieldmodels = []

        self.write_all()

    def write_all(self):
        """Wrapper function to convert all seperate objects"""
        self.regular_weirs_to_dhydro()
        self.orifices_to_dhydro()
        self.universal_weirs_to_dhydro()
        self.bridges_to_dhydro()
        self.culverts_to_dhydro()
        self.pumps_to_dhydro()
        self.compounds_to_dhydro()
        self.crosssection_locations_to_dhydro()
        self.crosssection_definitions_to_dhydro()
        self.friction_definitions_to_dhydro()
        self.boundaries_to_dhydro()
        self.laterals_to_dhydro()
        self.observation_points_to_dhydro()
        self.storagenodes_to_dhydro()
        self.inifields_to_dhydro()

    @staticmethod
    def _clear_comments(lst):
        """Convenience function to remove comment statements in INI files"""
        if isinstance(lst, list):
            for item in lst:
                [setattr(item.comments, field[0], "") for field in item.comments]
        else:
            [setattr(lst.comments, field[0], "") for field in lst.comments]

    def compounds_to_dhydro(self):
        """Convert compound structures to Compound-model"""
        structs = [
            Compound(**struc)
            for struc in self.hydamo.structures.compounds_df.to_dict("records")
        ]
        self._clear_comments(structs)
        self.structures += structs

    def regular_weirs_to_dhydro(self):
        """Convert regular weirs to Weir-model"""
        structs = [
            Weir(**struc)
            for struc in self.hydamo.structures.rweirs_df.to_dict("records")
        ]
        self._clear_comments(structs)
        self.structures += structs

    def orifices_to_dhydro(self):
        """Convert orifices to Orfice-models"""
        structs = [
            Orifice(**struc)
            for struc in self.hydamo.structures.orifices_df.to_dict("records")
        ]
        self._clear_comments(structs)
        self.structures += structs

    def universal_weirs_to_dhydro(self):
        """Convert universal weirs to UniversalWeir-models"""
        structs = [
            UniversalWeir(**struc)
            for struc in self.hydamo.structures.uweirs_df.to_dict("records")
        ]
        self._clear_comments(structs)
        self.structures += structs

    def bridges_to_dhydro(self):
        """Convert bridges to Bridge-models"""
        structs = [
            Bridge(**struc)
            for struc in self.hydamo.structures.bridges_df.to_dict("records")
        ]
        self._clear_comments(structs)
        self.structures += structs

    def culverts_to_dhydro(self):
        """Convert culverts to Culvert-models"""
        structs = [
            Culvert(**struc)
            for struc in self.hydamo.structures.culverts_df.to_dict("records")
        ]
        self._clear_comments(structs)
        self.structures += structs

    def pumps_to_dhydro(self):
        """Convert pumps to Pump-models"""
        structs = [
            Pump(**struc)
            for struc in self.hydamo.structures.pumps_df.to_dict("records")
        ]
        self._clear_comments(structs)
        self.structures += structs

    def crosssection_locations_to_dhydro(self):
        """Convert crosssection locations to CrossLoc models"""
        # Check which of the branches do not have a cross section. Add the default one to those
        branchids = set(
            [
                dct["branchid"]
                for dct in self.hydamo.crosssections.crosssection_loc.values()
            ]
        )

        # check if there locations specified where a default profile should be added
        if hasattr(self.hydamo.crosssections, "default_locations"):
            default_locs = self.hydamo.crosssections.default_locations
        else:
            default_locs = self.hydamo.branches.index[
                ~self.hydamo.branches["code"].isin(branchids)
            ]

        # If any are missing, check if a default cross section definition has been defined
        if (len(default_locs) > 0) & (self.assign_default_profiles):
            if self.hydamo.crosssections.default_definition is None:
                 logger.warning(
                    "Not all branches have a cross section appointed to them. We assume D-Hydro can interpolate over these branches, otherwise errors will occur."
                )
            logger.info(
                f"Adding default cross section definition to branches with ids: {', '.join(list(default_locs))}"
            )
            for branchid in default_locs:
                self.hydamo.crosssections.add_crosssection_location(
                    branchid=branchid,
                    chainage=self.hydamo.branches.at[branchid, "geometry"].length / 2,
                    definition=self.hydamo.crosssections.default_definition,
                    minz=np.nan,
                    shift=self.hydamo.crosssections.default_definition_shift,
                )

        # Add cross sections to dhydro format
        css = [
            CrossSection(**cloc)
            for cloc in self.hydamo.crosssections.crosssection_loc.values()
        ]

        self._clear_comments(css)
        self.crosslocs += css

    def crosssection_definitions_to_dhydro(self) -> None:
        """Convert crosssection definitions to Crossdef models"""

        def _get_cstype_part_of_dict(cstype: str) -> dict:
            """Reorganize the csdef dict"""
            return {
                key: dct
                for key, dct in self.hydamo.crosssections.crosssection_def.items()
                if dct["type"] == cstype
            }

        # Circles
        cs_circle = _get_cstype_part_of_dict("circle")
        cs = [CircleCrsDef(**cs) for cs in cs_circle.values()]
        self._clear_comments(cs)
        self.crossdefs += cs

        # YZ
        cs_yz = _get_cstype_part_of_dict("yz")
        cs = [YZCrsDef(**cs) for cs in cs_yz.values()]
        self._clear_comments(cs)
        self.crossdefs += cs

        # Rectangle
        cs_rect = _get_cstype_part_of_dict("rectangle")
        cs = [RectangleCrsDef(**cs) for cs in cs_rect.values()]
        self._clear_comments(cs)
        self.crossdefs += cs

        # Trapezium
        cs_zw = _get_cstype_part_of_dict("zw")
        cs = [ZWCrsDef(**cs) for cs in cs_zw.values()]
        self._clear_comments(cs)
        self.crossdefs += cs

    def boundaries_to_dhydro(self) -> None:
        """Convert dataframe of boundaries to ext and bc models"""
        for bound in self.hydamo.external_forcings.boundary_nodes.values():
            if bound["vec1"] is None:
                bnd_bc = Constant(
                    name=bound["nodeid"],
                    function="constant",
                    quantity=bound["quantity"],
                    unit=bound["unit2"],
                    datablock=[[bound["vec2"]]],
                )
            elif bound['unit1'].startswith('minutes'):
                bnd_bc = TimeSeries(
                    name=bound["nodeid"],
                    function="timeseries",
                    timeinterpolation="linear",
                    quantityunitpair=[
                        QuantityUnitPair(quantity="time", unit=bound["unit1"]),
                        QuantityUnitPair(
                            quantity=bound["quantity"], unit=bound["unit2"]
                        ),
                    ],
                    datablock=list(map(list, zip(bound["vec1"], bound["vec2"]))),
                )
            else:
                bnd_bc = QHTable(                 
                        name=bound["nodeid"],
                        function="qhtable",
                        timeinterpolation="linear",
                        quantityunitpair=[
                            QuantityUnitPair(quantity="qhbnd waterlevel", unit=bound["unit2"]),
                        QuantityUnitPair(
                            quantity="qhbnd discharge", unit=bound["unit1"]
                        ),
                    ],
                    datablock=list(map(list, zip(bound["vec2"], bound["vec1"]))),
                )

            self.forcingmodel.forcing.append(bnd_bc)
        for bound in self.hydamo.external_forcings.boundary_nodes.values():
            bnd_ext = Boundary(
                nodeid=bound["nodeid"],
                quantity=bound["quantity"],
                forcingfile=self.forcingmodel,
            )
            bnd_ext.forcingfile.filepath = Path("boundaryconditions.bc")
            self.boundaries_ext.append(bnd_ext)

    def laterals_to_dhydro(self) -> None:
        """Convert dataframe of laterals to ext and bc models"""

        for key, lateral in self.hydamo.external_forcings.lateral_nodes.items():
            if isinstance(lateral["discharge"], str):
                # realtime boundary
                lat_ext = Lateral(
                    id=key,                    
                    locationType="1d",
                    branchId=lateral["branchid"],
                    chainage=lateral["chainage"],
                    discharge=lateral["discharge"],
                )
            else:
                # time series or constant value
                if isinstance(lateral["discharge"], pd.Series):
                    lat_bc = TimeSeries(
                        name=key,
                        function="timeseries",
                        timeinterpolation="linear",
                        quantityunitpair=[
                            QuantityUnitPair(quantity="time", unit=lateral["time_unit"]),
                            QuantityUnitPair(
                                quantity="lateral_discharge", unit="m3/s"
                            ),
                        ],
                        datablock=list(map(list, zip(lateral["time"], lateral["value"]))),
                    )
                    self.laterals_bc.append(lat_bc)
                elif isinstance(lateral["discharge"], float):
                    lat_bc = Constant(
                        name=key,
                        function="constant",
                        quantity="lateral_discharge",
                        unit="m3/s",
                        datablock=[[lateral["discharge"]]],
                    )
                self.forcingmodel.forcing.append(lat_bc)
                lat_ext = Lateral(
                    id=key,                    
                    locationtype=lateral["locationtype"],
                    branchId=lateral["branchid"],
                    chainage=lateral["chainage"],
                    discharge=self.forcingmodel,
                )
            self.laterals_ext.append(lat_ext)

    def friction_definitions_to_dhydro(self):
        """Convert friction definitions to FrictGlobal-objects"""
        frictdefs = [
            FrictGlobal(**frictdef)
            for frictdef in self.hydamo.roughness_definitions.values()
        ]
        self._clear_comments(frictdefs)
        self.friction_defs += frictdefs

    def storagenodes_to_dhydro(self):
        """Convert dataframe of storagenodes to StorageNode-objects"""
        stornodes = [
            StorageNode(**stornode)
            for stornode in self.hydamo.storagenodes.storagenodes.values()
        ]
        self._clear_comments(stornodes)
        self.storagenodes += stornodes

    def observation_points_to_dhydro(self):
        """Convert dataframe of observationpoints to ObserationPoint-objects"""
        if hasattr(self.hydamo.observationpoints, 'observation_points'):
            obspoints = [
                ObservationPoint(**obs)
                for obs in self.hydamo.observationpoints.observation_points.drop(columns="geometry").to_dict(
                    "records"
                )
            ]
            self._clear_comments(obspoints)
            self.obspoints += obspoints

    def inifields_to_dhydro(self):
        """Convert initial conditions to InitialField objects"""
        for (
            level
        ) in self.hydamo.external_forcings.initial_waterlevel_polygons.itertuples():
            inifield = InitialField(
                quantity="waterlevel",
                datafiletype="1dField",
                unit="m",
                datafile="initialwaterdepth.ini",
            )
            if level.geometry is None:
                onedfield = OneDFieldGlobal(
                    quantity="waterlevel",
                    locationtype=level.locationtype,
                    unit="m",
                    value=str(level.value),
                )
            self._clear_comments(inifield)
            self._clear_comments(onedfield)
            self.inifields.append(inifield)
            self.onedfields.append(onedfield)

        for (
            depth
        ) in self.hydamo.external_forcings.initial_waterdepth_polygons.itertuples():
            inifield = InitialField(
                quantity="waterdepth",
                datafiletype="1dField",
                datafile="initialwaterdepth.ini",
            )
            if depth.geometry is None:
                onedfield = OneDFieldGlobal(
                    quantity="waterdepth",
                    unit="m",
                    value=str(depth.waterdepth),
                )
            self._clear_comments(inifield)
            self._clear_comments(onedfield)
            self.inifields.append(inifield)
            self.onedfieldmodels.append(onedfield)
boundaries_to_dhydro() -> None

Convert dataframe of boundaries to ext and bc models

Source code in hydrolib/dhydamo/converters/df2hydrolibmodel.py 
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def boundaries_to_dhydro(self) -> None:
    """Convert dataframe of boundaries to ext and bc models"""
    for bound in self.hydamo.external_forcings.boundary_nodes.values():
        if bound["vec1"] is None:
            bnd_bc = Constant(
                name=bound["nodeid"],
                function="constant",
                quantity=bound["quantity"],
                unit=bound["unit2"],
                datablock=[[bound["vec2"]]],
            )
        elif bound['unit1'].startswith('minutes'):
            bnd_bc = TimeSeries(
                name=bound["nodeid"],
                function="timeseries",
                timeinterpolation="linear",
                quantityunitpair=[
                    QuantityUnitPair(quantity="time", unit=bound["unit1"]),
                    QuantityUnitPair(
                        quantity=bound["quantity"], unit=bound["unit2"]
                    ),
                ],
                datablock=list(map(list, zip(bound["vec1"], bound["vec2"]))),
            )
        else:
            bnd_bc = QHTable(                 
                    name=bound["nodeid"],
                    function="qhtable",
                    timeinterpolation="linear",
                    quantityunitpair=[
                        QuantityUnitPair(quantity="qhbnd waterlevel", unit=bound["unit2"]),
                    QuantityUnitPair(
                        quantity="qhbnd discharge", unit=bound["unit1"]
                    ),
                ],
                datablock=list(map(list, zip(bound["vec2"], bound["vec1"]))),
            )

        self.forcingmodel.forcing.append(bnd_bc)
    for bound in self.hydamo.external_forcings.boundary_nodes.values():
        bnd_ext = Boundary(
            nodeid=bound["nodeid"],
            quantity=bound["quantity"],
            forcingfile=self.forcingmodel,
        )
        bnd_ext.forcingfile.filepath = Path("boundaryconditions.bc")
        self.boundaries_ext.append(bnd_ext)
bridges_to_dhydro()

Convert bridges to Bridge-models

Source code in hydrolib/dhydamo/converters/df2hydrolibmodel.py 
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def bridges_to_dhydro(self):
    """Convert bridges to Bridge-models"""
    structs = [
        Bridge(**struc)
        for struc in self.hydamo.structures.bridges_df.to_dict("records")
    ]
    self._clear_comments(structs)
    self.structures += structs
compounds_to_dhydro()

Convert compound structures to Compound-model

Source code in hydrolib/dhydamo/converters/df2hydrolibmodel.py 
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def compounds_to_dhydro(self):
    """Convert compound structures to Compound-model"""
    structs = [
        Compound(**struc)
        for struc in self.hydamo.structures.compounds_df.to_dict("records")
    ]
    self._clear_comments(structs)
    self.structures += structs
crosssection_definitions_to_dhydro() -> None

Convert crosssection definitions to Crossdef models

Source code in hydrolib/dhydamo/converters/df2hydrolibmodel.py 
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def crosssection_definitions_to_dhydro(self) -> None:
    """Convert crosssection definitions to Crossdef models"""

    def _get_cstype_part_of_dict(cstype: str) -> dict:
        """Reorganize the csdef dict"""
        return {
            key: dct
            for key, dct in self.hydamo.crosssections.crosssection_def.items()
            if dct["type"] == cstype
        }

    # Circles
    cs_circle = _get_cstype_part_of_dict("circle")
    cs = [CircleCrsDef(**cs) for cs in cs_circle.values()]
    self._clear_comments(cs)
    self.crossdefs += cs

    # YZ
    cs_yz = _get_cstype_part_of_dict("yz")
    cs = [YZCrsDef(**cs) for cs in cs_yz.values()]
    self._clear_comments(cs)
    self.crossdefs += cs

    # Rectangle
    cs_rect = _get_cstype_part_of_dict("rectangle")
    cs = [RectangleCrsDef(**cs) for cs in cs_rect.values()]
    self._clear_comments(cs)
    self.crossdefs += cs

    # Trapezium
    cs_zw = _get_cstype_part_of_dict("zw")
    cs = [ZWCrsDef(**cs) for cs in cs_zw.values()]
    self._clear_comments(cs)
    self.crossdefs += cs
crosssection_locations_to_dhydro()

Convert crosssection locations to CrossLoc models

Source code in hydrolib/dhydamo/converters/df2hydrolibmodel.py 
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def crosssection_locations_to_dhydro(self):
    """Convert crosssection locations to CrossLoc models"""
    # Check which of the branches do not have a cross section. Add the default one to those
    branchids = set(
        [
            dct["branchid"]
            for dct in self.hydamo.crosssections.crosssection_loc.values()
        ]
    )

    # check if there locations specified where a default profile should be added
    if hasattr(self.hydamo.crosssections, "default_locations"):
        default_locs = self.hydamo.crosssections.default_locations
    else:
        default_locs = self.hydamo.branches.index[
            ~self.hydamo.branches["code"].isin(branchids)
        ]

    # If any are missing, check if a default cross section definition has been defined
    if (len(default_locs) > 0) & (self.assign_default_profiles):
        if self.hydamo.crosssections.default_definition is None:
             logger.warning(
                "Not all branches have a cross section appointed to them. We assume D-Hydro can interpolate over these branches, otherwise errors will occur."
            )
        logger.info(
            f"Adding default cross section definition to branches with ids: {', '.join(list(default_locs))}"
        )
        for branchid in default_locs:
            self.hydamo.crosssections.add_crosssection_location(
                branchid=branchid,
                chainage=self.hydamo.branches.at[branchid, "geometry"].length / 2,
                definition=self.hydamo.crosssections.default_definition,
                minz=np.nan,
                shift=self.hydamo.crosssections.default_definition_shift,
            )

    # Add cross sections to dhydro format
    css = [
        CrossSection(**cloc)
        for cloc in self.hydamo.crosssections.crosssection_loc.values()
    ]

    self._clear_comments(css)
    self.crosslocs += css
culverts_to_dhydro()

Convert culverts to Culvert-models

Source code in hydrolib/dhydamo/converters/df2hydrolibmodel.py 
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def culverts_to_dhydro(self):
    """Convert culverts to Culvert-models"""
    structs = [
        Culvert(**struc)
        for struc in self.hydamo.structures.culverts_df.to_dict("records")
    ]
    self._clear_comments(structs)
    self.structures += structs
friction_definitions_to_dhydro()

Convert friction definitions to FrictGlobal-objects

Source code in hydrolib/dhydamo/converters/df2hydrolibmodel.py 
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def friction_definitions_to_dhydro(self):
    """Convert friction definitions to FrictGlobal-objects"""
    frictdefs = [
        FrictGlobal(**frictdef)
        for frictdef in self.hydamo.roughness_definitions.values()
    ]
    self._clear_comments(frictdefs)
    self.friction_defs += frictdefs
inifields_to_dhydro()

Convert initial conditions to InitialField objects

Source code in hydrolib/dhydamo/converters/df2hydrolibmodel.py 
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def inifields_to_dhydro(self):
    """Convert initial conditions to InitialField objects"""
    for (
        level
    ) in self.hydamo.external_forcings.initial_waterlevel_polygons.itertuples():
        inifield = InitialField(
            quantity="waterlevel",
            datafiletype="1dField",
            unit="m",
            datafile="initialwaterdepth.ini",
        )
        if level.geometry is None:
            onedfield = OneDFieldGlobal(
                quantity="waterlevel",
                locationtype=level.locationtype,
                unit="m",
                value=str(level.value),
            )
        self._clear_comments(inifield)
        self._clear_comments(onedfield)
        self.inifields.append(inifield)
        self.onedfields.append(onedfield)

    for (
        depth
    ) in self.hydamo.external_forcings.initial_waterdepth_polygons.itertuples():
        inifield = InitialField(
            quantity="waterdepth",
            datafiletype="1dField",
            datafile="initialwaterdepth.ini",
        )
        if depth.geometry is None:
            onedfield = OneDFieldGlobal(
                quantity="waterdepth",
                unit="m",
                value=str(depth.waterdepth),
            )
        self._clear_comments(inifield)
        self._clear_comments(onedfield)
        self.inifields.append(inifield)
        self.onedfieldmodels.append(onedfield)
laterals_to_dhydro() -> None

Convert dataframe of laterals to ext and bc models

Source code in hydrolib/dhydamo/converters/df2hydrolibmodel.py 
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def laterals_to_dhydro(self) -> None:
    """Convert dataframe of laterals to ext and bc models"""

    for key, lateral in self.hydamo.external_forcings.lateral_nodes.items():
        if isinstance(lateral["discharge"], str):
            # realtime boundary
            lat_ext = Lateral(
                id=key,                    
                locationType="1d",
                branchId=lateral["branchid"],
                chainage=lateral["chainage"],
                discharge=lateral["discharge"],
            )
        else:
            # time series or constant value
            if isinstance(lateral["discharge"], pd.Series):
                lat_bc = TimeSeries(
                    name=key,
                    function="timeseries",
                    timeinterpolation="linear",
                    quantityunitpair=[
                        QuantityUnitPair(quantity="time", unit=lateral["time_unit"]),
                        QuantityUnitPair(
                            quantity="lateral_discharge", unit="m3/s"
                        ),
                    ],
                    datablock=list(map(list, zip(lateral["time"], lateral["value"]))),
                )
                self.laterals_bc.append(lat_bc)
            elif isinstance(lateral["discharge"], float):
                lat_bc = Constant(
                    name=key,
                    function="constant",
                    quantity="lateral_discharge",
                    unit="m3/s",
                    datablock=[[lateral["discharge"]]],
                )
            self.forcingmodel.forcing.append(lat_bc)
            lat_ext = Lateral(
                id=key,                    
                locationtype=lateral["locationtype"],
                branchId=lateral["branchid"],
                chainage=lateral["chainage"],
                discharge=self.forcingmodel,
            )
        self.laterals_ext.append(lat_ext)
observation_points_to_dhydro()

Convert dataframe of observationpoints to ObserationPoint-objects

Source code in hydrolib/dhydamo/converters/df2hydrolibmodel.py 
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def observation_points_to_dhydro(self):
    """Convert dataframe of observationpoints to ObserationPoint-objects"""
    if hasattr(self.hydamo.observationpoints, 'observation_points'):
        obspoints = [
            ObservationPoint(**obs)
            for obs in self.hydamo.observationpoints.observation_points.drop(columns="geometry").to_dict(
                "records"
            )
        ]
        self._clear_comments(obspoints)
        self.obspoints += obspoints
orifices_to_dhydro()

Convert orifices to Orfice-models

Source code in hydrolib/dhydamo/converters/df2hydrolibmodel.py 
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def orifices_to_dhydro(self):
    """Convert orifices to Orfice-models"""
    structs = [
        Orifice(**struc)
        for struc in self.hydamo.structures.orifices_df.to_dict("records")
    ]
    self._clear_comments(structs)
    self.structures += structs
pumps_to_dhydro()

Convert pumps to Pump-models

Source code in hydrolib/dhydamo/converters/df2hydrolibmodel.py 
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def pumps_to_dhydro(self):
    """Convert pumps to Pump-models"""
    structs = [
        Pump(**struc)
        for struc in self.hydamo.structures.pumps_df.to_dict("records")
    ]
    self._clear_comments(structs)
    self.structures += structs
regular_weirs_to_dhydro()

Convert regular weirs to Weir-model

Source code in hydrolib/dhydamo/converters/df2hydrolibmodel.py 
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def regular_weirs_to_dhydro(self):
    """Convert regular weirs to Weir-model"""
    structs = [
        Weir(**struc)
        for struc in self.hydamo.structures.rweirs_df.to_dict("records")
    ]
    self._clear_comments(structs)
    self.structures += structs
storagenodes_to_dhydro()

Convert dataframe of storagenodes to StorageNode-objects

Source code in hydrolib/dhydamo/converters/df2hydrolibmodel.py 
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def storagenodes_to_dhydro(self):
    """Convert dataframe of storagenodes to StorageNode-objects"""
    stornodes = [
        StorageNode(**stornode)
        for stornode in self.hydamo.storagenodes.storagenodes.values()
    ]
    self._clear_comments(stornodes)
    self.storagenodes += stornodes
universal_weirs_to_dhydro()

Convert universal weirs to UniversalWeir-models

Source code in hydrolib/dhydamo/converters/df2hydrolibmodel.py 
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def universal_weirs_to_dhydro(self):
    """Convert universal weirs to UniversalWeir-models"""
    structs = [
        UniversalWeir(**struc)
        for struc in self.hydamo.structures.uweirs_df.to_dict("records")
    ]
    self._clear_comments(structs)
    self.structures += structs
write_all()

Wrapper function to convert all seperate objects

Source code in hydrolib/dhydamo/converters/df2hydrolibmodel.py 
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def write_all(self):
    """Wrapper function to convert all seperate objects"""
    self.regular_weirs_to_dhydro()
    self.orifices_to_dhydro()
    self.universal_weirs_to_dhydro()
    self.bridges_to_dhydro()
    self.culverts_to_dhydro()
    self.pumps_to_dhydro()
    self.compounds_to_dhydro()
    self.crosssection_locations_to_dhydro()
    self.crosssection_definitions_to_dhydro()
    self.friction_definitions_to_dhydro()
    self.boundaries_to_dhydro()
    self.laterals_to_dhydro()
    self.observation_points_to_dhydro()
    self.storagenodes_to_dhydro()
    self.inifields_to_dhydro()

hydamo2df

CrossSectionsIO

Source code in hydrolib/dhydamo/converters/hydamo2df.py 
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class CrossSectionsIO:
    def __init__(self, crosssections):
        self.crosssections = crosssections

    @validate_arguments(config=ConfigDict(arbitrary_types_allowed=True))
    def from_datamodel(
        self, crsdefs: pd.DataFrame = None, crslocs: pd.DataFrame = None
    ) -> None:
        """ "
        From parsed data models of crsdefs and crslocs
        """

        if crslocs is not None:
            for _, crsloc in crslocs.iterrows():
                # add location
                self.crosssections.add_crosssection_location(
                    branchid=crsloc["branch_id"],
                    chainage=crsloc["branch_offset"],
                    shift=crsloc["shift"],
                    definition=crsloc["crosssectiondefinitionid"],
                )

        if crsdefs is not None:
            crsdefs = crsdefs.drop_duplicates(subset=["crosssectiondefinitionid"])
            for _, crsdef in crsdefs.iterrows():
                # Set roughness value on default if cross-section has non defined (e.g. culverts)
                if isinstance(crsdef["frictionid"], str):
                    roughtype = crsdef["frictionid"].split("_")[0]
                else:
                    roughtype = "Chezy"

                if isinstance(crsdef["frictionid"], str):
                    roughval = float(crsdef["frictionid"].split("_")[-1])
                else:
                    roughval = 45

                # add definition
                if crsdef["type"] == "circle":
                    self.crosssections.add_circle_definition(
                        diameter=crsdef["diameter"],
                        roughnesstype=roughtype,
                        roughnessvalue=roughval,
                        name=crsdef["crosssectiondefinitionid"],
                    )
                elif crsdef["type"] == "rectangle":
                    self.crosssections.add_rectangle_definition(
                        height=crsdef["height"],
                        width=crsdef["width"],
                        closed=crsdef["closed"],
                        roughnesstype=roughtype,
                        roughnessvalue=roughval,
                        name=crsdef["crosssectiondefinitionid"],
                    )
                elif crsdef["type"] == "trapezium":
                    self.crosssections.add_trapezium_definition(
                        slope=(crsdef["t_width"] - crsdef["width"])
                        / 2
                        / crsdef["height"],
                        maximumflowwidth=crsdef["t_width"],
                        bottomwidth=crsdef["width"],
                        closed=crsdef["closed"],
                        roughnesstype=roughtype,
                        roughnessvalue=roughval,
                        name=crsdef["crosssectiondefinitionid"],
                    )
                elif crsdef["type"] == "zw":
                    self.crosssections.add_zw_definition(
                        numLevels=crsdef["numlevels"],
                        levels=crsdef["levels"],
                        flowWidths=crsdef["flowwidths"],
                        totalWidths=crsdef["totalwidths"],
                        roughnesstype=roughtype,
                        roughnessvalue=roughval,
                        name=crsdef["crosssectiondefinitionid"],
                    )

                else:
                    raise NotImplementedError

    @validate_arguments(config=ConfigDict(arbitrary_types_allowed=True))
    def profiles(
        self,
        branches: ExtendedGeoDataFrame, # = None,
        roughness_variant: RoughnessVariant,# =None,
        crosssections: ExtendedGeoDataFrame | None = None,
        crosssection_roughness: ExtendedDataFrame | None = None,
        profile_groups: ExtendedDataFrame | None = None,
        profile_lines: ExtendedGeoDataFrame | None = None,
        param_profile: ExtendedDataFrame | None = None,
        param_profile_values: ExtendedDataFrame | None = None,
    ) -> None:
        """
        Method to add cross section from hydamo files. Two files
        can be handed to the function, the cross section file (dwarsprofiel) and the
        parametrised file (normgeparametriseerd). The
        hierarchical order is 1. dwarsprofiel, 2. normgeparametriseerd.
        Each branch will be assigned a profile following this order. If parametrised
        and standard are not given, branches can be wit hout cross section. In that case
        a standard profile should be assigned
        """
        dp_branches = None
        dp_structures = None
        if profile_groups is not None:
            # check for profile_groups items with valid brugid or stuwid. They need to be droppped from profiles.
            groupidx = [
                idx
                for idx, group in profile_groups.iterrows()
                if ("brugid" in profile_groups.columns) & (not pd.isna(group.brugid))
            ]

            groupidx = groupidx + [
                idx
                for idx, group in profile_groups.iterrows()
                if ("stuwid" in profile_groups.columns) & (not pd.isna(group.stuwid))
            ]

            # index of the lines that are associated to these groups
            lineidx = [
                profile_lines[
                    profile_lines["profielgroepid"]
                    == profile_groups.loc[grindex, "globalid"]
                ].index.to_numpy()[0]
                for grindex in groupidx
            ]
            # index of the profiles associated to these lines
            profidx = [
                crosssections[
                    crosssections["profiellijnid"]
                    == profile_lines.loc[lindex, "globalid"]
                ].index.to_numpy()[0]
                for lindex in lineidx
            ]
            # make a copy and drop the profiles corresponding to a structure
            dp_branches = crosssections.copy(deep=True)
            dp_branches.drop(profidx, axis=0, inplace=True)

            dp_structures = crosssections.copy(deep=True)
            dp_structures = dp_structures.loc[profidx, :]
        else:
            dp_branches = crosssections.copy(deep=True)

        # Assign cross-sections to branches
        nnocross = len(self.crosssections.get_branches_without_crosssection())
        logger.info(
            f"Before adding the number of branches without cross section is: {nnocross}."
        )

        if dp_branches is not None:
            # 1. Collect cross sections from 'dwarsprofielen'
            yz_profiles = self.crosssections.crosssection_to_yzprofiles(
                dp_branches,
                crosssection_roughness,
                branches,
                roughness_variant=roughness_variant,
            )

            for name, css in yz_profiles.items():
                # Add definition
                self.crosssections.add_yz_definition(
                    yz=css["yz"],
                    thalweg=css["thalweg"],
                    name=name,
                    roughnesstype=css["typeruwheid"],
                    roughnessvalue=css["ruwheid"],
                )
                # Add location
                self.crosssections.add_crosssection_location(
                    branchid=css["branchid"], chainage=css["chainage"], definition=name
                )

        # Check the number of branches with cross sections
        no_crosssection_id = self.crosssections.get_branches_without_crosssection()
        no_crosssection = [
            b for b in branches.itertuples() if b.code in no_crosssection_id
        ]

        nnocross = len(no_crosssection)
        logger.info(
            f"After adding 'dwarsprofielen' the number of branches without cross section is: {nnocross}."
        )
        if nnocross == 0:
            logger.info("No further branches without a profile.")
        elif param_profile is None:
            logger.info("No parametrised crossections available for branches.")
        else:
            # Derive norm cross sections for norm parametrised
            param_profiles_converted = self.crosssections.parametrised_to_profiles(
                param_profile,
                param_profile_values,
                no_crosssection,
                roughness_variant=roughness_variant,
            )
            # Get branch information
            branchdata = self.crosssections.hydamo.branches.loc[
                list(param_profiles_converted.keys())
            ]
            branchdata["chainage_upper"] = 0.05 * branchdata.length
            branchdata["chainage_lower"] = 0.95 * branchdata.length


            # Add cross sections
            for branchid, css in param_profiles_converted.items():
                chainage_upper = branchdata.at[branchid, "chainage_upper"]
                chainage_lower = branchdata.at[branchid, "chainage_lower"]

                if css["type"] == "rectangle":
                    name = self.crosssections.add_rectangle_definition(
                        height=css["height"],
                        width=css["width"],
                        closed=css["closed"],
                        roughnesstype=css["typeruwheid"],
                        roughnessvalue=css["ruwheid"],
                    )

                if css["type"] == "trapezium":
                    name = self.crosssections.add_trapezium_definition(
                        slope=css["slope"],
                        maximumflowwidth=css["maximumflowwidth"],
                        bottomwidth=css["bottomwidth"],
                        closed=css["closed"],
                        roughnesstype=css["typeruwheid"],
                        roughnessvalue=css["ruwheid"],
                    )

                # Add location
                self.crosssections.add_crosssection_location(
                    branchid=branchid,
                    chainage=chainage_upper,
                    definition=name,
                    shift=css["bottomlevel_upper"],
                )

                self.crosssections.add_crosssection_location(
                    branchid=branchid,
                    chainage=chainage_lower,
                    definition=name,
                    shift=css["bottomlevel_lower"],
                )

        nnocross = len(self.crosssections.get_branches_without_crosssection())
        logger.info(
            f"After adding 'normgeparametriseerd' the number of branches without cross section is: {nnocross}."
        )

        if dp_structures is not None:
            # 1. Collect cross sections from 'dwarsprofielen'
            yz_profiles = self.crosssections.crosssection_to_yzprofiles(
                dp_structures,
                crosssection_roughness,
                None,
                roughness_variant=roughness_variant,
            )

            for name, css in yz_profiles.items():
                # Add definition
                self.crosssections.add_yz_definition(
                    yz=css["yz"],
                    thalweg=css["thalweg"],
                    name=name,
                    roughnesstype=css["typeruwheid"],
                    roughnessvalue=css["ruwheid"],
                )
from_datamodel(crsdefs: pd.DataFrame = None, crslocs: pd.DataFrame = None) -> None

" From parsed data models of crsdefs and crslocs

Source code in hydrolib/dhydamo/converters/hydamo2df.py 
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@validate_arguments(config=ConfigDict(arbitrary_types_allowed=True))
def from_datamodel(
    self, crsdefs: pd.DataFrame = None, crslocs: pd.DataFrame = None
) -> None:
    """ "
    From parsed data models of crsdefs and crslocs
    """

    if crslocs is not None:
        for _, crsloc in crslocs.iterrows():
            # add location
            self.crosssections.add_crosssection_location(
                branchid=crsloc["branch_id"],
                chainage=crsloc["branch_offset"],
                shift=crsloc["shift"],
                definition=crsloc["crosssectiondefinitionid"],
            )

    if crsdefs is not None:
        crsdefs = crsdefs.drop_duplicates(subset=["crosssectiondefinitionid"])
        for _, crsdef in crsdefs.iterrows():
            # Set roughness value on default if cross-section has non defined (e.g. culverts)
            if isinstance(crsdef["frictionid"], str):
                roughtype = crsdef["frictionid"].split("_")[0]
            else:
                roughtype = "Chezy"

            if isinstance(crsdef["frictionid"], str):
                roughval = float(crsdef["frictionid"].split("_")[-1])
            else:
                roughval = 45

            # add definition
            if crsdef["type"] == "circle":
                self.crosssections.add_circle_definition(
                    diameter=crsdef["diameter"],
                    roughnesstype=roughtype,
                    roughnessvalue=roughval,
                    name=crsdef["crosssectiondefinitionid"],
                )
            elif crsdef["type"] == "rectangle":
                self.crosssections.add_rectangle_definition(
                    height=crsdef["height"],
                    width=crsdef["width"],
                    closed=crsdef["closed"],
                    roughnesstype=roughtype,
                    roughnessvalue=roughval,
                    name=crsdef["crosssectiondefinitionid"],
                )
            elif crsdef["type"] == "trapezium":
                self.crosssections.add_trapezium_definition(
                    slope=(crsdef["t_width"] - crsdef["width"])
                    / 2
                    / crsdef["height"],
                    maximumflowwidth=crsdef["t_width"],
                    bottomwidth=crsdef["width"],
                    closed=crsdef["closed"],
                    roughnesstype=roughtype,
                    roughnessvalue=roughval,
                    name=crsdef["crosssectiondefinitionid"],
                )
            elif crsdef["type"] == "zw":
                self.crosssections.add_zw_definition(
                    numLevels=crsdef["numlevels"],
                    levels=crsdef["levels"],
                    flowWidths=crsdef["flowwidths"],
                    totalWidths=crsdef["totalwidths"],
                    roughnesstype=roughtype,
                    roughnessvalue=roughval,
                    name=crsdef["crosssectiondefinitionid"],
                )

            else:
                raise NotImplementedError
profiles(branches: ExtendedGeoDataFrame, roughness_variant: RoughnessVariant, crosssections: ExtendedGeoDataFrame | None = None, crosssection_roughness: ExtendedDataFrame | None = None, profile_groups: ExtendedDataFrame | None = None, profile_lines: ExtendedGeoDataFrame | None = None, param_profile: ExtendedDataFrame | None = None, param_profile_values: ExtendedDataFrame | None = None) -> None

Method to add cross section from hydamo files. Two files can be handed to the function, the cross section file (dwarsprofiel) and the parametrised file (normgeparametriseerd). The hierarchical order is 1. dwarsprofiel, 2. normgeparametriseerd. Each branch will be assigned a profile following this order. If parametrised and standard are not given, branches can be wit hout cross section. In that case a standard profile should be assigned

Source code in hydrolib/dhydamo/converters/hydamo2df.py 
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@validate_arguments(config=ConfigDict(arbitrary_types_allowed=True))
def profiles(
    self,
    branches: ExtendedGeoDataFrame, # = None,
    roughness_variant: RoughnessVariant,# =None,
    crosssections: ExtendedGeoDataFrame | None = None,
    crosssection_roughness: ExtendedDataFrame | None = None,
    profile_groups: ExtendedDataFrame | None = None,
    profile_lines: ExtendedGeoDataFrame | None = None,
    param_profile: ExtendedDataFrame | None = None,
    param_profile_values: ExtendedDataFrame | None = None,
) -> None:
    """
    Method to add cross section from hydamo files. Two files
    can be handed to the function, the cross section file (dwarsprofiel) and the
    parametrised file (normgeparametriseerd). The
    hierarchical order is 1. dwarsprofiel, 2. normgeparametriseerd.
    Each branch will be assigned a profile following this order. If parametrised
    and standard are not given, branches can be wit hout cross section. In that case
    a standard profile should be assigned
    """
    dp_branches = None
    dp_structures = None
    if profile_groups is not None:
        # check for profile_groups items with valid brugid or stuwid. They need to be droppped from profiles.
        groupidx = [
            idx
            for idx, group in profile_groups.iterrows()
            if ("brugid" in profile_groups.columns) & (not pd.isna(group.brugid))
        ]

        groupidx = groupidx + [
            idx
            for idx, group in profile_groups.iterrows()
            if ("stuwid" in profile_groups.columns) & (not pd.isna(group.stuwid))
        ]

        # index of the lines that are associated to these groups
        lineidx = [
            profile_lines[
                profile_lines["profielgroepid"]
                == profile_groups.loc[grindex, "globalid"]
            ].index.to_numpy()[0]
            for grindex in groupidx
        ]
        # index of the profiles associated to these lines
        profidx = [
            crosssections[
                crosssections["profiellijnid"]
                == profile_lines.loc[lindex, "globalid"]
            ].index.to_numpy()[0]
            for lindex in lineidx
        ]
        # make a copy and drop the profiles corresponding to a structure
        dp_branches = crosssections.copy(deep=True)
        dp_branches.drop(profidx, axis=0, inplace=True)

        dp_structures = crosssections.copy(deep=True)
        dp_structures = dp_structures.loc[profidx, :]
    else:
        dp_branches = crosssections.copy(deep=True)

    # Assign cross-sections to branches
    nnocross = len(self.crosssections.get_branches_without_crosssection())
    logger.info(
        f"Before adding the number of branches without cross section is: {nnocross}."
    )

    if dp_branches is not None:
        # 1. Collect cross sections from 'dwarsprofielen'
        yz_profiles = self.crosssections.crosssection_to_yzprofiles(
            dp_branches,
            crosssection_roughness,
            branches,
            roughness_variant=roughness_variant,
        )

        for name, css in yz_profiles.items():
            # Add definition
            self.crosssections.add_yz_definition(
                yz=css["yz"],
                thalweg=css["thalweg"],
                name=name,
                roughnesstype=css["typeruwheid"],
                roughnessvalue=css["ruwheid"],
            )
            # Add location
            self.crosssections.add_crosssection_location(
                branchid=css["branchid"], chainage=css["chainage"], definition=name
            )

    # Check the number of branches with cross sections
    no_crosssection_id = self.crosssections.get_branches_without_crosssection()
    no_crosssection = [
        b for b in branches.itertuples() if b.code in no_crosssection_id
    ]

    nnocross = len(no_crosssection)
    logger.info(
        f"After adding 'dwarsprofielen' the number of branches without cross section is: {nnocross}."
    )
    if nnocross == 0:
        logger.info("No further branches without a profile.")
    elif param_profile is None:
        logger.info("No parametrised crossections available for branches.")
    else:
        # Derive norm cross sections for norm parametrised
        param_profiles_converted = self.crosssections.parametrised_to_profiles(
            param_profile,
            param_profile_values,
            no_crosssection,
            roughness_variant=roughness_variant,
        )
        # Get branch information
        branchdata = self.crosssections.hydamo.branches.loc[
            list(param_profiles_converted.keys())
        ]
        branchdata["chainage_upper"] = 0.05 * branchdata.length
        branchdata["chainage_lower"] = 0.95 * branchdata.length


        # Add cross sections
        for branchid, css in param_profiles_converted.items():
            chainage_upper = branchdata.at[branchid, "chainage_upper"]
            chainage_lower = branchdata.at[branchid, "chainage_lower"]

            if css["type"] == "rectangle":
                name = self.crosssections.add_rectangle_definition(
                    height=css["height"],
                    width=css["width"],
                    closed=css["closed"],
                    roughnesstype=css["typeruwheid"],
                    roughnessvalue=css["ruwheid"],
                )

            if css["type"] == "trapezium":
                name = self.crosssections.add_trapezium_definition(
                    slope=css["slope"],
                    maximumflowwidth=css["maximumflowwidth"],
                    bottomwidth=css["bottomwidth"],
                    closed=css["closed"],
                    roughnesstype=css["typeruwheid"],
                    roughnessvalue=css["ruwheid"],
                )

            # Add location
            self.crosssections.add_crosssection_location(
                branchid=branchid,
                chainage=chainage_upper,
                definition=name,
                shift=css["bottomlevel_upper"],
            )

            self.crosssections.add_crosssection_location(
                branchid=branchid,
                chainage=chainage_lower,
                definition=name,
                shift=css["bottomlevel_lower"],
            )

    nnocross = len(self.crosssections.get_branches_without_crosssection())
    logger.info(
        f"After adding 'normgeparametriseerd' the number of branches without cross section is: {nnocross}."
    )

    if dp_structures is not None:
        # 1. Collect cross sections from 'dwarsprofielen'
        yz_profiles = self.crosssections.crosssection_to_yzprofiles(
            dp_structures,
            crosssection_roughness,
            None,
            roughness_variant=roughness_variant,
        )

        for name, css in yz_profiles.items():
            # Add definition
            self.crosssections.add_yz_definition(
                yz=css["yz"],
                thalweg=css["thalweg"],
                name=name,
                roughnesstype=css["typeruwheid"],
                roughnessvalue=css["ruwheid"],
            )

ExternalForcingsIO

Source code in hydrolib/dhydamo/converters/hydamo2df.py 
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class ExternalForcingsIO:
    def __init__(self, external_forcings):
        self.external_forcings = external_forcings

    @validate_arguments(config=ConfigDict(arbitrary_types_allowed=True))
    def boundaries(
        self, boundary_conditions: ExtendedGeoDataFrame, mesh1d: Network = None
    ) -> None:
        """
        Generate boundary conditions from hydamo 'randvoorwaarden' file. The file format does not allow for timeseries.

        To add a time series, use 'add_boundary' from the workflow.

        Parameters
        ----------
        boundary_conditions: gpd.GeoDataFrame
            geodataframe with the locations and properties of the boundary conditions

        Returns
        -------
        dictionary
            Dictionary with attributes of boundary conditions, usable for dflowfm
        """
        # Read from Hydamo
        bcdct = {}

        for bndcnd in boundary_conditions.itertuples():
            if "waterstand" in bndcnd.typerandvoorwaarde:
                quantity = "waterlevelbnd"
            elif "debiet" in bndcnd.typerandvoorwaarde:
                quantity = "dischargebnd"

            # Add boundary condition
            bcdct[bndcnd.code] = {
                "code": bndcnd.code,
                "quantity": quantity,
                "value": bndcnd.waterstand
                if not np.isnan(bndcnd.waterstand)
                else bndcnd.debiet,
                "time": None,
                "geometry": bndcnd.geometry,
            }

        # Add all items
        for key, item in bcdct.items():
            self.external_forcings.add_boundary_condition(
                key, item["geometry"], item["quantity"], item["value"], mesh1d=mesh1d
            )

    @validate_arguments(config=ConfigDict(arbitrary_types_allowed=True))
    def laterals(
        self,
        locations: ExtendedGeoDataFrame,
        overflows: ExtendedGeoDataFrame | None = None,
        greenhouse_laterals: ExtendedGeoDataFrame | None = None,
        lateral_discharges: pd.DataFrame | pd.Series | None=None,
        rr_boundaries: dict | None = None,
    ) -> None:
        """
        Process laterals

        Parameters
        ----------
        locations: gpd.GeoDataFrame
            GeoDataFrame with at least 'geometry' (Point) and the column 'code'
        lateral_discharges: pd.DataFrame
            DataFrame with lateral discharges. The index should be a time object (datetime or similar).
        rr_boundaries: pd.DataFrame
            DataFrame with RR-catchments that are coupled
        """

        if rr_boundaries is None:
            rr_boundaries = []

        locations.geometry = locations.geometry.force_2d()

        latdct = {}
        if overflows is not None:
            locations = pd.concat([locations, overflows], ignore_index=True)
        if greenhouse_laterals is not None:
            locations = pd.concat([locations, greenhouse_laterals], ignore_index=True)

        # Get time series and add to dictionary
        # for nidx, lateral in zip(nearest_idx, locations.itertuples()):
        for lateral in locations.itertuples():
            # Check if a time is provided for the lateral
            if lateral.code in rr_boundaries:
                # Add to dictionary
                latdct[lateral.code] = {
                    "branchid": lateral.branch_id,
                    "chainage": str(lateral.branch_offset),
                    "discharge": "realtime",
                }

            else:
                if lateral_discharges is None:
                    logger.warning(
                        "No lateral_discharges provided. %s expects them. Skipping.",
                        lateral.code,
                    )
                else:
                    if isinstance(lateral_discharges, pd.Series):
                        series = lateral_discharges.loc[lateral.code]

                        # Add to dictionary
                        latdct[lateral.code] = {
                            "branchid": lateral.branch_id,
                            "chainage": str(lateral.branch_offset),
                            "discharge": series,
                        }

                    else:
                        if lateral.code not in lateral_discharges.columns:
                            logger.warning(
                                "No data found for %s. Skipping.",
                                lateral.code,
                            )
                            continue

                        # Get timeseries
                        series = lateral_discharges.loc[:, lateral.code]

                        # Add to dictionary
                        latdct[lateral.code] = {
                            "branchid": lateral.branch_id,
                            "chainage": str(lateral.branch_offset),
                            "discharge": series,
                        }

        # Add all items
        for key, item in latdct.items():
            self.external_forcings.add_lateral(
                id=key,
                branchid=item["branchid"],
                chainage=item["chainage"],
                discharge=item["discharge"],
            )


    @validate_arguments(config=ConfigDict(arbitrary_types_allowed=True))
    def timeseries_from_other_model(self,
                                  his_file: Path | str,
                                  location_type: str,
                                  location_id: str, 
                                  variable: str,
                                  starttime: str | pd.Timestamp | None = None,
                                  endtime: str | pd.Timestamp | None = None,
                                ) -> tuple[Point | None, pd.Series]:
        """
        Obtain timeseries from results from a different model. The HIS.nc file is read and a time series is extracted for the specified location/discharge combination.
        Point geometry and timeseries (pd.Series) are returned. 


        Args:
            his_file (Union[Path, str]): _description_.
            location_type (str): type of location. One of ['weir', 'observation_point', 'pump', 'uweir', 'bridge', culvert']. 
            location_id (str): ID of the location to read from the HIS-file
            variable (str): variable to read. One of ['discharge', 'waterlevel', 'waterlevel_upstream', 'waterlevel_downstream']
            starttime (Optional[Union[str, pd.Timestamp]], optional): start of selected time period for the output. Defaults to None.
            endtime (Optional[Union[str, pd.Timestamp]], optional): end of selected time period for the output. Defaults to None.

        Raises:
            ValueError: if no data can be found for the specified location and variable.

        Returns:
            tuple[Optional[Point], pd.Series]: Point geometry of the location (if available) and the timeseries as a pandas Series.
        """


       # if timesteps are strings, convert them to datetime objects
        if starttime is not None:
            if isinstance(starttime, str):
                starttime = pd.to_datetime(starttime)
            if isinstance(endtime, str):
                endtime = pd.to_datetime(endtime)
        # read the contents of the his file
        his = Dataset(his_file, 'r')

        his_time = his.variables['time'][:]
        time_unit=his['time'].units.split(' ')
        refdate = pd.to_datetime(time_unit[2] + ' ' + time_unit[3])
        interval_seconds = his_time[1]-his_time[0]
        times = pd.date_range(start=refdate, end=refdate+pd.Timedelta(hours=np.max(his_time)/3600.), freq=f'{interval_seconds}S')

        if location_type == 'weir':
            dtype = 'weirgen'
            loc_ids = chartostring(his[f'{dtype}_name'][:])
            coord_string_x = 'weir_input_geom_node_coordx'
            coord_string_y = 'weir_input_geom_node_coordy'

        elif location_type == 'observation_point':
            dtype = 'station'
            loc_ids = chartostring(his[f'{dtype}_name'][:])
            coord_string_x = 'station_x_coordinate'
            coord_string_y = 'station_y_coordinate'
        elif location_type == 'pump':                 
            coord_string_x = f'{location_type}_input_geom_node_coordx'
            coord_string_y = f'{location_type}_input_geom_node_coordy'
            loc_ids = chartostring(his[f'{location_type}_name'][:])       
            if variable == 'discharge':
                dtype = 'pump_structure'
            else:
                dtype = location_type
        elif location_type == 'uweir':
            dtype = 'uniweir'
            loc_ids = chartostring(his[f'{dtype}_name'][:])
            coord_string_x = f'{dtype}_input_geom_node_coordx'
            coord_string_y = f'{dtype}_input_geom_node_coordy'   
        elif location_type == 'compound':
            dtype = 'cmpstru'
            loc_ids = chartostring(his[f'{dtype}_name'][:])            
        else:
            dtype = location_type
            loc_ids = chartostring(his[f'{dtype}_name'][:])
            coord_string_x = f'{dtype}_input_geom_node_coordx'
            coord_string_y = f'{dtype}_input_geom_node_coordy'
        try:
            loc_index = np.nonzero(loc_ids == location_id)[0][0]
        except Exception:
            raise ValueError(f'Location ID {location_id} of type {location_type} not found in {his_file}. Available IDs: {loc_ids}') 

        if variable == 'waterlevel_upstream':
            variable = 's1up'
        elif variable == 'waterlevel_downstream':
            variable = 's1dn'
        if dtype != 'cmpstru':
            loc_x = his[coord_string_x][:][loc_index]
            loc_y = his[coord_string_y][:][loc_index]

            loc_geom = Point(loc_x, loc_y)
        else:
            logger.warning('Geometry for compound structures not supported yet. Get the location of one of its structures.')
            loc_geom = None

        if location_type == 'observation_point':
            timeseries = his['waterlevel'][:,loc_index]
        else:
            timeseries = his[f'{dtype}_{variable}'][:, loc_index]
        loc_series = pd.Series(timeseries, index=times, name=location_id)
        if starttime is not None:
            loc_series = loc_series.loc[starttime:endtime]            
            if loc_series.empty: 
                logger.error(f'No data available for {location_id} between {starttime} and {endtime}.')
        return loc_geom, loc_series
boundaries(boundary_conditions: ExtendedGeoDataFrame, mesh1d: Network = None) -> None

Generate boundary conditions from hydamo 'randvoorwaarden' file. The file format does not allow for timeseries.

To add a time series, use 'add_boundary' from the workflow.

Parameters

boundary_conditions: gpd.GeoDataFrame geodataframe with the locations and properties of the boundary conditions

Returns

dictionary Dictionary with attributes of boundary conditions, usable for dflowfm

Source code in hydrolib/dhydamo/converters/hydamo2df.py 
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@validate_arguments(config=ConfigDict(arbitrary_types_allowed=True))
def boundaries(
    self, boundary_conditions: ExtendedGeoDataFrame, mesh1d: Network = None
) -> None:
    """
    Generate boundary conditions from hydamo 'randvoorwaarden' file. The file format does not allow for timeseries.

    To add a time series, use 'add_boundary' from the workflow.

    Parameters
    ----------
    boundary_conditions: gpd.GeoDataFrame
        geodataframe with the locations and properties of the boundary conditions

    Returns
    -------
    dictionary
        Dictionary with attributes of boundary conditions, usable for dflowfm
    """
    # Read from Hydamo
    bcdct = {}

    for bndcnd in boundary_conditions.itertuples():
        if "waterstand" in bndcnd.typerandvoorwaarde:
            quantity = "waterlevelbnd"
        elif "debiet" in bndcnd.typerandvoorwaarde:
            quantity = "dischargebnd"

        # Add boundary condition
        bcdct[bndcnd.code] = {
            "code": bndcnd.code,
            "quantity": quantity,
            "value": bndcnd.waterstand
            if not np.isnan(bndcnd.waterstand)
            else bndcnd.debiet,
            "time": None,
            "geometry": bndcnd.geometry,
        }

    # Add all items
    for key, item in bcdct.items():
        self.external_forcings.add_boundary_condition(
            key, item["geometry"], item["quantity"], item["value"], mesh1d=mesh1d
        )
laterals(locations: ExtendedGeoDataFrame, overflows: ExtendedGeoDataFrame | None = None, greenhouse_laterals: ExtendedGeoDataFrame | None = None, lateral_discharges: pd.DataFrame | pd.Series | None = None, rr_boundaries: dict | None = None) -> None

Process laterals

Parameters

locations: gpd.GeoDataFrame GeoDataFrame with at least 'geometry' (Point) and the column 'code' lateral_discharges: pd.DataFrame DataFrame with lateral discharges. The index should be a time object (datetime or similar). rr_boundaries: pd.DataFrame DataFrame with RR-catchments that are coupled

Source code in hydrolib/dhydamo/converters/hydamo2df.py 
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@validate_arguments(config=ConfigDict(arbitrary_types_allowed=True))
def laterals(
    self,
    locations: ExtendedGeoDataFrame,
    overflows: ExtendedGeoDataFrame | None = None,
    greenhouse_laterals: ExtendedGeoDataFrame | None = None,
    lateral_discharges: pd.DataFrame | pd.Series | None=None,
    rr_boundaries: dict | None = None,
) -> None:
    """
    Process laterals

    Parameters
    ----------
    locations: gpd.GeoDataFrame
        GeoDataFrame with at least 'geometry' (Point) and the column 'code'
    lateral_discharges: pd.DataFrame
        DataFrame with lateral discharges. The index should be a time object (datetime or similar).
    rr_boundaries: pd.DataFrame
        DataFrame with RR-catchments that are coupled
    """

    if rr_boundaries is None:
        rr_boundaries = []

    locations.geometry = locations.geometry.force_2d()

    latdct = {}
    if overflows is not None:
        locations = pd.concat([locations, overflows], ignore_index=True)
    if greenhouse_laterals is not None:
        locations = pd.concat([locations, greenhouse_laterals], ignore_index=True)

    # Get time series and add to dictionary
    # for nidx, lateral in zip(nearest_idx, locations.itertuples()):
    for lateral in locations.itertuples():
        # Check if a time is provided for the lateral
        if lateral.code in rr_boundaries:
            # Add to dictionary
            latdct[lateral.code] = {
                "branchid": lateral.branch_id,
                "chainage": str(lateral.branch_offset),
                "discharge": "realtime",
            }

        else:
            if lateral_discharges is None:
                logger.warning(
                    "No lateral_discharges provided. %s expects them. Skipping.",
                    lateral.code,
                )
            else:
                if isinstance(lateral_discharges, pd.Series):
                    series = lateral_discharges.loc[lateral.code]

                    # Add to dictionary
                    latdct[lateral.code] = {
                        "branchid": lateral.branch_id,
                        "chainage": str(lateral.branch_offset),
                        "discharge": series,
                    }

                else:
                    if lateral.code not in lateral_discharges.columns:
                        logger.warning(
                            "No data found for %s. Skipping.",
                            lateral.code,
                        )
                        continue

                    # Get timeseries
                    series = lateral_discharges.loc[:, lateral.code]

                    # Add to dictionary
                    latdct[lateral.code] = {
                        "branchid": lateral.branch_id,
                        "chainage": str(lateral.branch_offset),
                        "discharge": series,
                    }

    # Add all items
    for key, item in latdct.items():
        self.external_forcings.add_lateral(
            id=key,
            branchid=item["branchid"],
            chainage=item["chainage"],
            discharge=item["discharge"],
        )
timeseries_from_other_model(his_file: Path | str, location_type: str, location_id: str, variable: str, starttime: str | pd.Timestamp | None = None, endtime: str | pd.Timestamp | None = None) -> tuple[Point | None, pd.Series]

Obtain timeseries from results from a different model. The HIS.nc file is read and a time series is extracted for the specified location/discharge combination. Point geometry and timeseries (pd.Series) are returned.

Parameters:

Name Type Description Default
his_file Union[Path, str]

description.

 required
location_type str

type of location. One of ['weir', 'observation_point', 'pump', 'uweir', 'bridge', culvert'].

required
location_id str

ID of the location to read from the HIS-file

 required
variable str

variable to read. One of ['discharge', 'waterlevel', 'waterlevel_upstream', 'waterlevel_downstream']

 required
starttime Optional[Union[str, Timestamp]]

start of selected time period for the output. Defaults to None.

 None
endtime Optional[Union[str, Timestamp]]

end of selected time period for the output. Defaults to None.

 None

Raises:

Type Description
ValueError

if no data can be found for the specified location and variable.

Returns:

Type Description
tuple[Point | None, Series]

tuple[Optional[Point], pd.Series]: Point geometry of the location (if available) and the timeseries as a pandas Series.
Source code in hydrolib/dhydamo/converters/hydamo2df.py 
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@validate_arguments(config=ConfigDict(arbitrary_types_allowed=True))
def timeseries_from_other_model(self,
                              his_file: Path | str,
                              location_type: str,
                              location_id: str, 
                              variable: str,
                              starttime: str | pd.Timestamp | None = None,
                              endtime: str | pd.Timestamp | None = None,
                            ) -> tuple[Point | None, pd.Series]:
    """
    Obtain timeseries from results from a different model. The HIS.nc file is read and a time series is extracted for the specified location/discharge combination.
    Point geometry and timeseries (pd.Series) are returned. 


    Args:
        his_file (Union[Path, str]): _description_.
        location_type (str): type of location. One of ['weir', 'observation_point', 'pump', 'uweir', 'bridge', culvert']. 
        location_id (str): ID of the location to read from the HIS-file
        variable (str): variable to read. One of ['discharge', 'waterlevel', 'waterlevel_upstream', 'waterlevel_downstream']
        starttime (Optional[Union[str, pd.Timestamp]], optional): start of selected time period for the output. Defaults to None.
        endtime (Optional[Union[str, pd.Timestamp]], optional): end of selected time period for the output. Defaults to None.

    Raises:
        ValueError: if no data can be found for the specified location and variable.

    Returns:
        tuple[Optional[Point], pd.Series]: Point geometry of the location (if available) and the timeseries as a pandas Series.
    """


   # if timesteps are strings, convert them to datetime objects
    if starttime is not None:
        if isinstance(starttime, str):
            starttime = pd.to_datetime(starttime)
        if isinstance(endtime, str):
            endtime = pd.to_datetime(endtime)
    # read the contents of the his file
    his = Dataset(his_file, 'r')

    his_time = his.variables['time'][:]
    time_unit=his['time'].units.split(' ')
    refdate = pd.to_datetime(time_unit[2] + ' ' + time_unit[3])
    interval_seconds = his_time[1]-his_time[0]
    times = pd.date_range(start=refdate, end=refdate+pd.Timedelta(hours=np.max(his_time)/3600.), freq=f'{interval_seconds}S')

    if location_type == 'weir':
        dtype = 'weirgen'
        loc_ids = chartostring(his[f'{dtype}_name'][:])
        coord_string_x = 'weir_input_geom_node_coordx'
        coord_string_y = 'weir_input_geom_node_coordy'

    elif location_type == 'observation_point':
        dtype = 'station'
        loc_ids = chartostring(his[f'{dtype}_name'][:])
        coord_string_x = 'station_x_coordinate'
        coord_string_y = 'station_y_coordinate'
    elif location_type == 'pump':                 
        coord_string_x = f'{location_type}_input_geom_node_coordx'
        coord_string_y = f'{location_type}_input_geom_node_coordy'
        loc_ids = chartostring(his[f'{location_type}_name'][:])       
        if variable == 'discharge':
            dtype = 'pump_structure'
        else:
            dtype = location_type
    elif location_type == 'uweir':
        dtype = 'uniweir'
        loc_ids = chartostring(his[f'{dtype}_name'][:])
        coord_string_x = f'{dtype}_input_geom_node_coordx'
        coord_string_y = f'{dtype}_input_geom_node_coordy'   
    elif location_type == 'compound':
        dtype = 'cmpstru'
        loc_ids = chartostring(his[f'{dtype}_name'][:])            
    else:
        dtype = location_type
        loc_ids = chartostring(his[f'{dtype}_name'][:])
        coord_string_x = f'{dtype}_input_geom_node_coordx'
        coord_string_y = f'{dtype}_input_geom_node_coordy'
    try:
        loc_index = np.nonzero(loc_ids == location_id)[0][0]
    except Exception:
        raise ValueError(f'Location ID {location_id} of type {location_type} not found in {his_file}. Available IDs: {loc_ids}') 

    if variable == 'waterlevel_upstream':
        variable = 's1up'
    elif variable == 'waterlevel_downstream':
        variable = 's1dn'
    if dtype != 'cmpstru':
        loc_x = his[coord_string_x][:][loc_index]
        loc_y = his[coord_string_y][:][loc_index]

        loc_geom = Point(loc_x, loc_y)
    else:
        logger.warning('Geometry for compound structures not supported yet. Get the location of one of its structures.')
        loc_geom = None

    if location_type == 'observation_point':
        timeseries = his['waterlevel'][:,loc_index]
    else:
        timeseries = his[f'{dtype}_{variable}'][:, loc_index]
    loc_series = pd.Series(timeseries, index=times, name=location_id)
    if starttime is not None:
        loc_series = loc_series.loc[starttime:endtime]            
        if loc_series.empty: 
            logger.error(f'No data available for {location_id} between {starttime} and {endtime}.')
    return loc_geom, loc_series

StorageNodesIO

Source code in hydrolib/dhydamo/converters/hydamo2df.py 
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class StorageNodesIO:
    def __init__(self, storagenodes):
        self.storagenodes = storagenodes

    def storagenodes_from_datamodel(self, storagenodes):
        """ "From parsed data model of storage nodes"""
        for storagenode_idx, storagenode in storagenodes.iterrows():
            self.add_storagenode(
                id=storagenode.id,
                name=storagenode.name if "name" in storagenode.index else np.nan,
                usestreetstorage=storagenode.usestreetstorage,
                nodetype="unspecified",
                nodeid=storagenode.nodeid,
                usetable="false",
                bedlevel=storagenode.bedlevel,
                area=storagenode.area,
                streetlevel=storagenode.streetlevel,
                streetstoragearea=storagenode.streetstoragearea,
                storagetype=storagenode.storagetype,
            )

    def storagenodes_from_input(self, storagenodes=None, nodeid=None, xy=None, storagedata=None, usestreetstorage= True, network=None):
        """ "From parsed data model of storage nodes"""

        for storagenode_idx, storagenode in storagenodes.iterrows():
            data = storagedata[storagedata.code == storagenode_idx]
            name = storagenode.name
            if pd.isna(name):
                name = storagenode.code
            self.storagenodes.add_storagenode(
                id=storagenode_idx,
                name=name,
                usestreetstorage=usestreetstorage,
                nodetype="unspecified",
                nodeid=nodeid,
                xy=xy,
                branchid=storagenode.branch_id,
                chainage=storagenode.branch_offset,
                usetable="true",
                storagearea=' '.join(data.area.astype(str)),
                levels=' '.join(data.level.astype(str)),
                network=network
            )
storagenodes_from_datamodel(storagenodes)

"From parsed data model of storage nodes

Source code in hydrolib/dhydamo/converters/hydamo2df.py 
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def storagenodes_from_datamodel(self, storagenodes):
    """ "From parsed data model of storage nodes"""
    for storagenode_idx, storagenode in storagenodes.iterrows():
        self.add_storagenode(
            id=storagenode.id,
            name=storagenode.name if "name" in storagenode.index else np.nan,
            usestreetstorage=storagenode.usestreetstorage,
            nodetype="unspecified",
            nodeid=storagenode.nodeid,
            usetable="false",
            bedlevel=storagenode.bedlevel,
            area=storagenode.area,
            streetlevel=storagenode.streetlevel,
            streetstoragearea=storagenode.streetstoragearea,
            storagetype=storagenode.storagetype,
        )
storagenodes_from_input(storagenodes=None, nodeid=None, xy=None, storagedata=None, usestreetstorage=True, network=None)

"From parsed data model of storage nodes

Source code in hydrolib/dhydamo/converters/hydamo2df.py 
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def storagenodes_from_input(self, storagenodes=None, nodeid=None, xy=None, storagedata=None, usestreetstorage= True, network=None):
    """ "From parsed data model of storage nodes"""

    for storagenode_idx, storagenode in storagenodes.iterrows():
        data = storagedata[storagedata.code == storagenode_idx]
        name = storagenode.name
        if pd.isna(name):
            name = storagenode.code
        self.storagenodes.add_storagenode(
            id=storagenode_idx,
            name=name,
            usestreetstorage=usestreetstorage,
            nodetype="unspecified",
            nodeid=nodeid,
            xy=xy,
            branchid=storagenode.branch_id,
            chainage=storagenode.branch_offset,
            usetable="true",
            storagearea=' '.join(data.area.astype(str)),
            levels=' '.join(data.level.astype(str)),
            network=network
        )

StructuresIO

Source code in hydrolib/dhydamo/converters/hydamo2df.py 
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class StructuresIO:
    def __init__(self, structures):
        self.structures = structures

    def _name_or_nan(self, row):
        return row.name if "name" in row.index else np.nan

    def _common_structure_kwargs(self, row, id_attr="id"):
        return {
            "id": getattr(row, id_attr),
            "name": self._name_or_nan(row),
            "branchid": row.branch_id,
            "chainage": row.branch_offset,
        }

    @validate_arguments(config=ConfigDict(arbitrary_types_allowed=True))
    def generalstructures_from_datamodel(self, generalstructures: pd.DataFrame) -> None:
        """From parsed data model of orifices

        Args:
            generalstructures (pd.DataFrame): dataframe containing the data
        """

        for generalstructure_idx, generalstructure in generalstructures.iterrows():
            base = self._common_structure_kwargs(generalstructure)
            self.structures.add_generalstructure(
                **base,
                allowedflowdir="both",
                upstream1width=generalstructure.upstream1width
                if "upstream1width" in generalstructure.index
                else np.nan,
                upstream1level=generalstructure.upstream1level
                if "upstream1level" in generalstructure.index
                else np.nan,
                upstream2width=generalstructure.upstream2width
                if "upstream2width" in generalstructure.index
                else np.nan,
                upstream2level=generalstructure.upstream2level
                if "upstream2level" in generalstructure.index
                else np.nan,
                crestwidth=generalstructure.crestwidth
                if "crestwidth" in generalstructure.index
                else np.nan,
                crestlevel=generalstructure.crestlevel
                if "crestlevel" in generalstructure.index
                else np.nan,
                crestlength=generalstructure.crestlength
                if "crestlength" in generalstructure.index
                else np.nan,
                downstream1width=generalstructure.downstream1width
                if "downstream1width" in generalstructure.index
                else np.nan,
                downstream1level=generalstructure.downstream1level
                if "downstream1level" in generalstructure.index
                else np.nan,
                downstream2width=generalstructure.downstream2width
                if "downstream2width" in generalstructure.index
                else np.nan,
                downstream2level=generalstructure.downstream2level
                if "downstream2level" in generalstructure.index
                else np.nan,
                gateloweredgelevel=generalstructure.gateloweredgelevel
                if "gateloweredgelevel" in generalstructure.index
                else np.nan,
                posfreegateflowcoeff=generalstructure.posfreegateflowcoeff
                if "posfreegateflowcoeff" in generalstructure.index
                else np.nan,
                posdrowngateflowcoeff=generalstructure.posdrowngateflowcoeff
                if "posdrowngateflowcoeff" in generalstructure.index
                else np.nan,
                posfreeweirflowcoeff=generalstructure.posfreeweirflowcoeff
                if "posfreeweirflowcoeff" in generalstructure.index
                else np.nan,
                posdrownweirflowcoeff=generalstructure.posdrownweirflowcoeff
                if "posdrownweirflowcoeff" in generalstructure.index
                else np.nan,
                poscontrcoeffreegate=generalstructure.poscontrcoeffreegate
                if "poscontrcoeffreegate" in generalstructure.index
                else np.nan,
                negfreegateflowcoeff=generalstructure.negfreegateflowcoeff
                if "negfreegateflowcoeff" in generalstructure.index
                else np.nan,
                negdrowngateflowcoeff=generalstructure.negdrowngateflowcoeff
                if "negdrowngateflowcoeff" in generalstructure.index
                else np.nan,
                negfreeweirflowcoeff=generalstructure.negfreeweirflowcoeff
                if "negfreeweirflowcoeff" in generalstructure.index
                else np.nan,
                negdrownweirflowcoeff=generalstructure.negdrownweirflowcoeff
                if "negdrownweirflowcoeff" in generalstructure.index
                else np.nan,
                negcontrcoeffreegate=generalstructure.negcontrcoeffreegate
                if "negcontrcoeffreegate" in generalstructure.index
                else np.nan,
                extraresistance=generalstructure.extraresistance
                if "extraresistance" in generalstructure.index
                else np.nan,
                gateheight=generalstructure.gateheight
                if "gateheight" in generalstructure.index
                else np.nan,
                gateopeningwidth=generalstructure.gateopeningwidth
                if "gateopeningwidth" in generalstructure.index
                else np.nan,
                gateopeninghorizontaldirection=generalstructure.gateopeninghorizontaldirection
                if "gateopeninghorizontaldirection" in generalstructure.index
                else np.nan,
                usevelocityheight=generalstructure.usevelocityheight
                if "usevelocityheight" in generalstructure.index
                else np.nan,
            )

    @validate_arguments(config=ConfigDict(arbitrary_types_allowed=True))
    def weirs(
        self,
        weirs: ExtendedGeoDataFrame = None,
        profile_groups = None,
        profile_lines = None,
        profiles: ExtendedGeoDataFrame | None = None,
        opening: ExtendedDataFrame = None,
        management_device: ExtendedDataFrame = None,
        usevelocityheight: str | None = "true",
    ) -> None:
        """
        Method to convert HyDAMO weirs to DFlowFM structures: regular weirs, orifices and universal weirs.
        If a weir ID corresponds to a 'stuwid' in the profile_groups object, a universal weir is created.
        If the management_device corresponding to a weir has the field "overlaatonderlaat" set to "onderlaat', an orifice is schematized. In all other cases, a regular (rectangular) weir is created.

        Parameters corrspond to the HyDAMO DAMO2.2 objects. DFlowFM keyword 'usevelocityheight' can be specificied as a string, default is 'true'.
        """
        # bypass HyDAMO and add stuwid directly to managment for use in RTC
        if not self.structures.hydamo.management.empty:
            self.structures.hydamo.management['stuwid'] = None

        index = np.zeros(len(weirs.code))
        if profile_groups is not None and hasattr(profile_groups, "stuwid"):
            index[np.isin(weirs.globalid, np.asarray(profile_groups.stuwid))] = 1

        rweirs = weirs[index == 0]
        for weir in rweirs.itertuples():
            weir_opening = opening[opening.stuwid == weir.globalid]

            # check if a separate name field is present
            if "naam" in weirs:
                name = weir.naam
                if not name:
                    name = weir.code
            else:
                name = weir.code

            if weir_opening.shape[0] > 1:
                logger.info(
                    "Weir %s contains %d openings. Creating a compound structure with a fictional weir for each one.",
                    weir.code,
                    weir_opening.shape[0],
                )
                cmp_list = []
                for num_op, (_, op_row) in enumerate(weir_opening.iterrows()):
                    weir_mandev = management_device[
                        management_device.kunstwerkopeningid
                        == op_row.globalid
                    ]

                    if weir_mandev.empty:
                        logger.warning(
                            "Skipping opening %s (weir %s) because there is no associated management device.",
                            op_row.code,
                            weir.code
                        )
                        continue
                    if weir_mandev.shape[0] > 1:
                        logger.warning(
                            "Multiple management devices associated to opening %s (weir %s). Taking the first one.",
                            op_row.code,
                            weir.code
                        )
                        weir_mandev = weir_mandev.iloc[[0]]                    


                    weir_id = f'{weir.code}_{num_op+1}'
                    if (not self.structures.hydamo.management.empty) & (hasattr(self.structures.hydamo.management, 'regelmiddelid')):
                        if weir_mandev.globalid.isin(self.structures.hydamo.management.regelmiddelid).item():
                            self.structures.hydamo.management.loc[self.structures.hydamo.management.regelmiddelid == weir_mandev.globalid.squeeze(), 'stuwid'] = weir_id
                    if weir_mandev.overlaatonderlaat.squeeze().lower() == 'overlaat':
                        cmp_list.append(weir_id)
                        self.structures.add_rweir(id=weir_id,
                                                    name=name,
                                                    branchid=weir.branch_id,
                                                    chainage=weir.branch_offset,
                                                    crestlevel=op_row.laagstedoorstroomhoogte,
                                                    crestwidth=op_row.laagstedoorstroombreedte,
                                                    corrcoeff=weir.afvoercoefficient,
                                                    allowedflowdir="both",
                                                    usevelocityheight=usevelocityheight,
                                                 )
                    elif weir_mandev.overlaatonderlaat.squeeze().lower() == 'onderlaat':
                        cmp_list.append(weir_id)
                        if "maximaaldebiet" not in weir_mandev or pd.isna(weir_mandev.maximaaldebiet.to_numpy()[0]):
                            limitflow = "false"
                            maxq = 0.0
                        else:
                            limitflow = "true"
                            maxq = float(weir_mandev.maximaaldebiet.to_numpy()[0])
                        self.structures.add_orifice(
                            id=weir_id,
                            name=name,
                            branchid=weir.branch_id,
                            chainage=weir.branch_offset,
                            crestlevel=float(weir_opening.laagstedoorstroomhoogte.to_numpy()[0]),
                            crestwidth=float(weir_opening.laagstedoorstroombreedte.to_numpy()[0]),
                            corrcoeff=weir.afvoercoefficient,
                            allowedflowdir="both",
                            usevelocityheight=usevelocityheight,
                            gateloweredgelevel=float(weir_opening.laagstedoorstroomhoogte.to_numpy()[0])
                            + float(weir_mandev.hoogteopening.to_numpy()[0]),
                            uselimitflowpos=limitflow,
                            limitflowpos=maxq,
                            uselimitflowneg=limitflow,
                            limitflowneg=maxq,
                        )
                    else:
                        logger.warning(
                            'Skipping weir %s - from "overlaatonderlaat" %s the type of structure could not be determined.',
                            weir.code,
                            weir_mandev.overlaatonderlaat,
                        )
                self.structures.add_compound(id=f'cmp_{weir.code}', structureids =cmp_list)
                # self.structures.rweirs_df.drop(weir.code)
            else:
                if weir_opening.empty:
                    logger.warning(
                        "Skipping weir %s because there is no associated opening.",
                        weir.code,
                    )
                    continue

                weir_id = weir.code
                weir_mandev = management_device[
                        management_device.kunstwerkopeningid
                        == weir_opening.globalid.to_numpy()[0]
                    ]

                if weir_mandev.empty:
                    logger.warning(
                        "Skipping opening %s (weir %s) because there is no associated management device.",
                        weir_opening.code.squeeze(),
                        weir_id
                    )
                    continue
                if weir_mandev.shape[0] > 1:
                    logger.warning(
                        "Multiple management devices associated to opening %s (weir %s). Taking the first one.",
                        weir_opening.code.squeeze(),
                        weir_id
                    )
                    weir_mandev = weir_mandev.iloc[[0]]                    


                if (not self.structures.hydamo.management.empty) & hasattr(self.structures.hydamo.management, 'regelmiddelid'):
                    if weir_mandev.globalid.isin(self.structures.hydamo.management.regelmiddelid).item():
                        self.structures.hydamo.management.loc[self.structures.hydamo.management.regelmiddelid == weir_mandev.globalid.squeeze(), 'stuwid'] = weir_id

                if isinstance(weir_mandev.overlaatonderlaat, pd.Series):
                    overlaatonderlaat = weir_mandev.overlaatonderlaat.squeeze()
                else:
                    overlaatonderlaat = weir_mandev.overlaatonderlaat

                if (
                    overlaatonderlaat.lower()
                    == "overlaat"
                ):
                    self.structures.add_rweir(
                        id=weir_id,
                        name=name,
                        branchid=weir.branch_id,
                        chainage=weir.branch_offset,
                        crestlevel=weir_opening.laagstedoorstroomhoogte.to_numpy()[0],
                        crestwidth=weir_opening.laagstedoorstroombreedte.to_numpy()[0],
                        corrcoeff=weir.afvoercoefficient,
                        allowedflowdir="both",
                        usevelocityheight=usevelocityheight,
                    )

                elif (
                    overlaatonderlaat.lower()
                    == "onderlaat"
                ):
                    if "maximaaldebiet" not in weir_mandev or pd.isna(weir_mandev.maximaaldebiet.to_numpy()[0]):
                        limitflow = "false"
                        maxq = 0.0
                    else:
                        limitflow = "true"
                        maxq = float(weir_mandev.maximaaldebiet.to_numpy()[0])
                    self.structures.add_orifice(
                        id=weir_id,
                        name=name,
                        branchid=weir.branch_id,
                        chainage=weir.branch_offset,
                        crestlevel=float(weir_opening.laagstedoorstroomhoogte.to_numpy()[0]),
                        crestwidth=float(weir_opening.laagstedoorstroombreedte.to_numpy()[0]),
                        corrcoeff=weir.afvoercoefficient,
                        allowedflowdir="both",
                        usevelocityheight=usevelocityheight,
                        gateloweredgelevel=float(weir_opening.laagstedoorstroomhoogte.to_numpy()[0])
                        + float(weir_mandev.hoogteopening.to_numpy()[0]),
                        uselimitflowpos=limitflow,
                        limitflowpos=maxq,
                        uselimitflowneg=limitflow,
                        limitflowneg=maxq,
                    )
                else:
                    logger.warning(
                        'Skipping %s - from "overlaatonderlaat" %s the type of structure could not be determined.',
                        weir.code,
                        weir_mandev.overlaatonderlaat,
                    )

        uweirs = weirs[index == 1]
        for uweir in uweirs.itertuples():
            # check if a separate name field is present
            if "naam" in uweirs:
                name = uweir.naam
            else:
                name = uweir.code

            prof = np.empty(0)
            if (profiles is not None) & ("stuwid" in profile_groups):
                group = profile_groups[profile_groups["stuwid"] == uweir.globalid]
                line = profile_lines[
                    profile_lines["profielgroepid"] == group["globalid"].to_numpy()[0]
                ]
                prof = profiles[profiles["profiellijnid"] == line["globalid"].to_numpy()[0]]
                if not prof.empty:
                    counts = len(prof.geometry.iloc[0].coords[:])
                    xyz = np.vstack(prof.geometry.iloc[0].coords[:])
                    length = np.r_[
                        0,
                        np.cumsum(np.hypot(np.diff(xyz[:, 0]), np.diff(xyz[:, 1]))),
                    ]
                    yzvalues = np.c_[length, xyz[:, -1] - np.min(xyz[:, -1])]

            if not hasattr(uweir, 'laagstedoorstroomhoogte') or pd.isna(uweir.laagstedoorstroomhoogte):
                kruinhoogte = np.min(xyz[:,-1])
            else:
                kruinhoogte = uweir.laagstedoorstroomhoogte

            if len(prof) == 0:
                # return an error it is still not found
                raise ValueError(f"{uweir.code} is not found in any cross-section.")
            self.structures.add_uweir(
                id=uweir.code,
                name=name,
                branchid=uweir.branch_id,
                chainage=uweir.branch_offset,
                crestlevel=kruinhoogte,
                dischargecoeff=uweir.afvoercoefficient,
                allowedflowdir="both",
                numlevels=counts,
                yvalues=" ".join([f"{yz[0]:7.3f}" for yz in yzvalues]),
                zvalues=" ".join([f"{yz[1]:7.3f}" for yz in yzvalues]),
            )

    @validate_arguments(config=ConfigDict(arbitrary_types_allowed=True))
    def weirs_from_datamodel(self, weirs: pd.DataFrame) -> None:
        """ "From parsed data model of weirs"""
        for weir_idx, weir in weirs.iterrows():
            base = self._common_structure_kwargs(weir)
            self.structures.add_weir(
                **base,
                crestlevel=weir.crestlevel,
                crestwidth=weir.crestwidth,
                corrcoeff=weir.corrcoeff,
            )

    @validate_arguments(config=ConfigDict(arbitrary_types_allowed=True))
    def orifices_from_datamodel(self, orifices: pd.DataFrame) -> None:
        """ "From parsed data model of orifices"""
        for orifice_idx, orifice in orifices.iterrows():
            base = self._common_structure_kwargs(orifice)
            self.structures.add_orifice(
                **base,
                allowedflowdir="both",
                crestlevel=orifice.crestlevel,
                crestwidth=orifice.crestwidth,
                gateloweredgelevel=orifice.gateloweredgelevel,
                corrcoeff=orifice.corrcoef,
                uselimitflowpos=orifice.uselimitflowpos,
                limitflowpos=orifice.limitflowpos,
                uselimitflowneg=orifice.uselimitflowneg,
                limitflowneg=orifice.limitflowneg,
            )

    @validate_arguments(config=ConfigDict(arbitrary_types_allowed=True))
    def uweirs_from_datamodel(self, uweirs: pd.DataFrame) -> None:
        """ "From parsed data model of universal weirs"""
        for uweir_idx, uweir in uweirs.iterrows():
            base = self._common_structure_kwargs(uweir)
            self.structures.add_uweir(
                **base,
                crestlevel=uweir.crestlevel,
                yvalues=uweir.yvalues,
                zvalues=uweir.zvalues,
                allowedflowdir="both",
                dischargecoeff=uweir.dischargecoeff,
            )

    @validate_arguments(config=ConfigDict(arbitrary_types_allowed=True))
    def bridges(
        self,
        bridges: ExtendedGeoDataFrame,
        profile_groups: ExtendedDataFrame = None,
        profile_lines: ExtendedGeoDataFrame = None,
        profiles: ExtendedGeoDataFrame = None,
    ) -> None:
        """
        Method to convert HyDAMO bridges to DFlowFM bridges. Every bridge needs an associated YZ-profile through profile_groups ('brugid'), profile_lines and profiles.

        Parameters corrspond to the HyDAMO DAMO2.2 objects.
        """
        for bridge in bridges.itertuples():
            # first search in yz-profiles
            group = profile_groups[profile_groups["brugid"] == bridge.globalid]
            line = profile_lines[
                profile_lines["profielgroepid"] == group["globalid"].to_numpy()[0]
            ]
            prof = profiles[profiles["profiellijnid"] == line["globalid"].to_numpy()[0]]

            if len(prof) == 0:
                raise ValueError(f"{bridge.code} is not found in any cross-section.")

            if "naam" in bridges:
                name = bridge.naam
            else:
                name = bridge.code

            profile_id = prof.code.to_numpy()[0]
            self.structures.add_bridge(
                id=bridge.code,
                name=name,
                branchid=bridge.branch_id,
                chainage=bridge.branch_offset,
                csdefid=profile_id,
                shift=0.0,
                allowedflowdir="both",
                inletlosscoeff=bridge.intreeverlies,
                outletlosscoeff=bridge.uittreeverlies,
                length=bridge.lengte,
                frictiontype=bridge.typeruwheid,
                friction=bridge.ruwheid,
            )

    @validate_arguments(config=ConfigDict(arbitrary_types_allowed=True))
    def bridges_from_datamodel(self, bridges: pd.DataFrame) -> None:
        """ "From parsed data model of bridges"""
        for bridge_idx, bridge in bridges.iterrows():
            base = self._common_structure_kwargs(bridge, id_attr="code")
            self.structures.add_bridge(
                **base,
                csdefid=bridge.csdefid,
                shift=0.0,
                allowedflowdir="both",
                inletlosscoeff=bridge.intreeverlies,
                outletlosscoeff=bridge.uittreeverlies,
                length=bridge.lengte,
                frictiontype=bridge.typeruwheid,
                friction=bridge.ruwheid,
            )

    @validate_arguments(config=ConfigDict(arbitrary_types_allowed=True))
    def culverts(
        self,
        culverts: ExtendedGeoDataFrame,
        management_device: ExtendedDataFrame | None = None,
    ) -> None:
        """
        Method to convert HyDAMO culverts to DFlowFM culverts. Devices like a valve and a slide can be schematized from the management_device object.
        According to HyDAMO DAMO2.2 a closing_device ('afsluitmiddel') could also be used but this is not supported.

        Parameters corrspond to the HyDAMO DAMO2.2 objects.
        """
        if management_device is not None:
            if 'soortafsluitmiddel' not in management_device.columns:
               management_device['soortafsluitmiddel'] = management_device['soortregelmiddel']

        for culvert in culverts.itertuples():
            # Generate cross section definition name
            if culvert.vormkoker.lower() == "rond" or culvert.vormkoker.lower() == "ellipsvormig":
                crosssection = {"shape": "circle", "diameter": culvert.hoogteopening}
            elif (
                culvert.vormkoker.lower() == "rechthoekig"
                or culvert.vormkoker.lower() == "onbekend"
                or culvert.vormkoker.lower() == "eivormig"
                or culvert.vormkoker.lower() == "muilprofiel"
                or culvert.vormkoker.lower() == "heulprofiel"
            ):
                crosssection = {
                    "shape": "rectangle",
                    "height": culvert.hoogteopening,
                    "width": culvert.breedteopening,
                    "closed": 1,
                }
            else:
                crosssection = {"shape": "circle", "diameter": 0.40}
                logger.info(
                    f"Culvert {culvert.code} has an unknown shape: {culvert.vormkoker}. Applying a default profile (round - 40cm)"
                )

            # check whether an afsluitmiddel is present and take action dependent on its settings
            if management_device is not None:
                mandev = management_device[
                    management_device.duikersifonhevelid == culvert.globalid
                ]
                if 'soortafsluitmiddel' not in mandev:
                    mandev.loc[mandev.index,'soortafsluitmiddel'] = mandev['soortregelmiddel']
            else:
                mandev = pd.DataFrame()

            if mandev.empty:
                allowedflowdir = "both"
                valveonoff = 0
                numlosscoeff = None
                valveopeningheight = 0
                relopening = None
                losscoeff = None
            else:
                for _, i in mandev.iterrows():
                    if i["soortafsluitmiddel"] == "terugslagklep":
                        allowedflowdir = "positive"
                        valveonoff = 0
                        numlosscoeff = None
                        valveopeningheight = 0
                        relopening = None
                        losscoeff = None
                    elif i["soortafsluitmiddel"] == "schuif":
                        allowedflowdir = "positive"
                        valveonoff = 1
                        valveopeningheight = float(i["hoogteopening"])
                        numlosscoeff = 1
                        relopening = [float(i["hoogteopening"]) / culvert.hoogteopening]
                        losscoeff = [float(i["afvoercoefficient"])]
                    else:
                        raise NotImplementedError(
                            f'Type of management device for culvert {culvert.code} is not implemented; only "schuif" and "terugslagklep" are allowed.'
                        )

            # check if a separate name field is present
            if "naam" in culverts:
                name = culvert.naam
            else:
                name = culvert.code

            self.structures.add_culvert(
                id=culvert.code,
                name=name,
                branchid=culvert.branch_id,
                chainage=culvert.branch_offset,
                leftlevel=culvert.hoogtebinnenonderkantbov,
                rightlevel=culvert.hoogtebinnenonderkantbene,
                length=culvert.lengte,
                inletlosscoeff=culvert.intreeverlies,
                outletlosscoeff=culvert.uittreeverlies,
                crosssection=crosssection,
                allowedflowdir=allowedflowdir,
                valveonoff=valveonoff,
                numlosscoeff=numlosscoeff,
                valveopeningheight=valveopeningheight,
                relopening=relopening,
                losscoeff=losscoeff,
                bedfrictiontype=culvert.typeruwheid,
                bedfriction=culvert.ruwheid,
            )

    @validate_arguments(config=ConfigDict(arbitrary_types_allowed=True))
    def culverts_from_datamodel(self, culverts: pd.DataFrame) -> None:
        """
        From parsed model of culverts
        """

        # Add to dict
        for culvert_idx, culvert in culverts.iterrows():
            base = self._common_structure_kwargs(culvert)
            self.structures.add_culvert(
                **base,
                leftlevel=culvert.leftlevel,
                rightlevel=culvert.rightlevel,
                crosssection=culvert.crosssectiondefinitionid,
                length=culvert.geometry.length
                if "geometry" in culvert.index
                else culvert.length,
                inletlosscoeff=culvert.inletlosscoeff,
                outletlosscoeff=culvert.outletlosscoeff,
                allowedflowdir="both",
                valveonoff=0,
                numlosscoeff=0,
                valveopeningheight=np.nan,
                relopening=np.nan,
                losscoeff=np.nan,
                frictiontype=culvert.frictiontype,
                frictionvalue=culvert.frictionvalue,
            )

    @validate_arguments(config=ConfigDict(arbitrary_types_allowed=True))
    def pumps(
        self,
        pumpstations: ExtendedGeoDataFrame,
        pumps: ExtendedDataFrame = None,
        management: ExtendedDataFrame = None,
    ) -> None:
        """
        Method to convert HyDAMO pumps to DFlowFM pumps. Three objects are required: pumpstations, pumps and management ('sturing').

        Parameters corrspond to the HyDAMO DAMO2.2 objects.
        """

        # Add sturing to pumps
        for pumpstation in pumpstations.itertuples():

            # find pumps for gemaal
            pumps_subset = pumps[pumps.gemaalid == pumpstation.globalid]
            if pumps_subset.empty:
                logger.warning(
                    "Skipping %s because there is no associated pump.",
                    pumpstation.code,
                )
                continue

            if "naam" in pumpstation:
                name = pumpstation.name
            else:
                name = pumpstation.code
            if pumps_subset.shape[0] > 1:
                # more than one pump
                cmp_list = []
                logger.info(
                    "Pumpstation %s contains %d openings. Creating a compound structure with a fictional pump for each one.",
                    pumpstation.code,
                    pumps_subset.shape[0],
                )
                for ipump, (_,pump) in enumerate(pumps_subset.iterrows()):

                    pump_control = management[management.pompid== pump.globalid]
                    if pump_control.empty:
                        logger.warning("No management found for %s", pump.code)
                        continue

                    startlevelsuctionside = [pump_control["bovengrens"]]
                    stoplevelsuctionside = [pump_control["ondergrens"]]

                    pumpid = f'{pumpstation.code}_{ipump+1}'
                    cmp_list.append(pumpid)

                    self.structures.add_pump(
                        id=pumpid,
                        name=name,
                        branchid=pumpstation.branch_id,
                        chainage=pumpstation.branch_offset,
                        orientation="positive",
                        numstages=1,
                        controlside="suctionside",
                        capacity=pump.maximalecapaciteit/60.,
                        startlevelsuctionside=startlevelsuctionside,
                        stoplevelsuctionside=stoplevelsuctionside,
                        startleveldeliveryside=startlevelsuctionside,
                        stopleveldeliveryside=stoplevelsuctionside,
                    )
                self.structures.add_compound(id=f'cmp_{pumpstation.code}', structureids =cmp_list)

            else:
                #  only one pump
                pump_control = management[management.pompid== pumps_subset.globalid.to_numpy()[0]]
                if pump_control.empty:
                    logger.warning(
                        "Skipping %s because there is no associated management.",
                        pumpstation.code,
                    )

                startlevelsuctionside = [pump_control["bovengrens"]]
                stoplevelsuctionside = [pump_control["ondergrens"]]


                # the pumpstation has only one pump
                self.structures.add_pump(
                    id=pumpstation.code,
                    name=name,
                    branchid=pumpstation.branch_id,
                    chainage=pumpstation.branch_offset,
                    orientation="positive",
                    numstages=1,
                    controlside="suctionside",
                    capacity=pumps_subset.maximalecapaciteit.to_numpy()[0]/60.,
                    startlevelsuctionside=startlevelsuctionside,
                    stoplevelsuctionside=stoplevelsuctionside,
                    startleveldeliveryside=startlevelsuctionside,
                    stopleveldeliveryside=stoplevelsuctionside,
                )

    @validate_arguments(config=ConfigDict(arbitrary_types_allowed=True))
    def pumps_from_datamodel(self, pumps: pd.DataFrame) -> None:
        """From parsed data model of pumps"""

        for pump_idx, pump in pumps.iterrows():
            base = self._common_structure_kwargs(pump)
            self.structures.add_pump(
                **base,
                orientation="positive",
                numstages=1,
                controlside=pump.controlside,
                capacity=pump.maximumcapacity,
                startlevelsuctionside=pump.startlevelsuctionside,
                stoplevelsuctionside=pump.stoplevelsuctionside,
                startleveldeliveryside=pump.startleveldeliveryside,
                stopleveldeliveryside=pump.stopleveldeliveryside,
            )

    @staticmethod
    def move_structure(struc, struc_dict, branch, offset):
        """
        Function the move a structure if needed for a compound structure.

        Parameters
        ----------
        struc : string
            current sub-structure id
        struc_dict : dict
            dict with all structures of a certain type
        branch : string
            branch id of the first structure in the compound
        offset : float
            chainage of the first structure in the compound

        Returns
        -------
        Dict with shifted coordinates.

        """
        branch2 = struc_dict[struc]["branchid"]
        if branch2 != branch:
            logger.warning(
                f"Structures of not on the same branche. Moving structure {struc} to branch {branch}."
            )
        struc_dict[struc]["branchid"] = branch
        struc_dict[struc]["chainage"] = offset
        return struc_dict

    def _structure_frames(self):
        return (
            self.structures.pumps_df,
            self.structures.rweirs_df,
            self.structures.uweirs_df,
            self.structures.culverts_df,
            self.structures.bridges_df,
            self.structures.orifices_df,
        )

    def _get_structure_location(self, structure_id):
        branch = None
        offset = None
        for df in self._structure_frames():
            if df.empty:
                continue
            match = df[df.id == structure_id]
            if not match.empty:
                branch = match.branchid.to_numpy()[0]
                offset = match.chainage.to_numpy()[0]
        return branch, offset

    def _set_structure_location(self, structure_id, branch, offset):
        for df in self._structure_frames():
            if df.empty:
                continue
            idx = df.index[df.id == structure_id]
            if not idx.empty:
                df.loc[idx, "branchid"] = branch
                df.loc[idx, "chainage"] = offset

    def compound_structures(self, idlist, structurelist):
        # probably the coordinates should all be set to those of the first structure (still to do)
        for c_i, c_id in enumerate(idlist):
            branch = None
            offset = None
            # check the substructure coordinates. If they do not coincide, move subsequent structures to the coordinates of the first
            for s_i, struc in enumerate(structurelist[c_i]):
                if s_i == 0:
                    # find out what type the first structure it is and get its coordinates
                    branch, offset = self._get_structure_location(struc)
                else:
                    # move a subsequent structure to the location of the first
                    if branch is not None and offset is not None:
                        self._set_structure_location(struc, branch, offset)

            self.structures.add_compound(id=c_id, structureids=structurelist[c_i])
bridges(bridges: ExtendedGeoDataFrame, profile_groups: ExtendedDataFrame = None, profile_lines: ExtendedGeoDataFrame = None, profiles: ExtendedGeoDataFrame = None) -> None

Method to convert HyDAMO bridges to DFlowFM bridges. Every bridge needs an associated YZ-profile through profile_groups ('brugid'), profile_lines and profiles.

Parameters corrspond to the HyDAMO DAMO2.2 objects.

Source code in hydrolib/dhydamo/converters/hydamo2df.py 
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@validate_arguments(config=ConfigDict(arbitrary_types_allowed=True))
def bridges(
    self,
    bridges: ExtendedGeoDataFrame,
    profile_groups: ExtendedDataFrame = None,
    profile_lines: ExtendedGeoDataFrame = None,
    profiles: ExtendedGeoDataFrame = None,
) -> None:
    """
    Method to convert HyDAMO bridges to DFlowFM bridges. Every bridge needs an associated YZ-profile through profile_groups ('brugid'), profile_lines and profiles.

    Parameters corrspond to the HyDAMO DAMO2.2 objects.
    """
    for bridge in bridges.itertuples():
        # first search in yz-profiles
        group = profile_groups[profile_groups["brugid"] == bridge.globalid]
        line = profile_lines[
            profile_lines["profielgroepid"] == group["globalid"].to_numpy()[0]
        ]
        prof = profiles[profiles["profiellijnid"] == line["globalid"].to_numpy()[0]]

        if len(prof) == 0:
            raise ValueError(f"{bridge.code} is not found in any cross-section.")

        if "naam" in bridges:
            name = bridge.naam
        else:
            name = bridge.code

        profile_id = prof.code.to_numpy()[0]
        self.structures.add_bridge(
            id=bridge.code,
            name=name,
            branchid=bridge.branch_id,
            chainage=bridge.branch_offset,
            csdefid=profile_id,
            shift=0.0,
            allowedflowdir="both",
            inletlosscoeff=bridge.intreeverlies,
            outletlosscoeff=bridge.uittreeverlies,
            length=bridge.lengte,
            frictiontype=bridge.typeruwheid,
            friction=bridge.ruwheid,
        )
bridges_from_datamodel(bridges: pd.DataFrame) -> None

"From parsed data model of bridges

Source code in hydrolib/dhydamo/converters/hydamo2df.py 
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@validate_arguments(config=ConfigDict(arbitrary_types_allowed=True))
def bridges_from_datamodel(self, bridges: pd.DataFrame) -> None:
    """ "From parsed data model of bridges"""
    for bridge_idx, bridge in bridges.iterrows():
        base = self._common_structure_kwargs(bridge, id_attr="code")
        self.structures.add_bridge(
            **base,
            csdefid=bridge.csdefid,
            shift=0.0,
            allowedflowdir="both",
            inletlosscoeff=bridge.intreeverlies,
            outletlosscoeff=bridge.uittreeverlies,
            length=bridge.lengte,
            frictiontype=bridge.typeruwheid,
            friction=bridge.ruwheid,
        )
culverts(culverts: ExtendedGeoDataFrame, management_device: ExtendedDataFrame | None = None) -> None

Method to convert HyDAMO culverts to DFlowFM culverts. Devices like a valve and a slide can be schematized from the management_device object. According to HyDAMO DAMO2.2 a closing_device ('afsluitmiddel') could also be used but this is not supported.

Parameters corrspond to the HyDAMO DAMO2.2 objects.

Source code in hydrolib/dhydamo/converters/hydamo2df.py 
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@validate_arguments(config=ConfigDict(arbitrary_types_allowed=True))
def culverts(
    self,
    culverts: ExtendedGeoDataFrame,
    management_device: ExtendedDataFrame | None = None,
) -> None:
    """
    Method to convert HyDAMO culverts to DFlowFM culverts. Devices like a valve and a slide can be schematized from the management_device object.
    According to HyDAMO DAMO2.2 a closing_device ('afsluitmiddel') could also be used but this is not supported.

    Parameters corrspond to the HyDAMO DAMO2.2 objects.
    """
    if management_device is not None:
        if 'soortafsluitmiddel' not in management_device.columns:
           management_device['soortafsluitmiddel'] = management_device['soortregelmiddel']

    for culvert in culverts.itertuples():
        # Generate cross section definition name
        if culvert.vormkoker.lower() == "rond" or culvert.vormkoker.lower() == "ellipsvormig":
            crosssection = {"shape": "circle", "diameter": culvert.hoogteopening}
        elif (
            culvert.vormkoker.lower() == "rechthoekig"
            or culvert.vormkoker.lower() == "onbekend"
            or culvert.vormkoker.lower() == "eivormig"
            or culvert.vormkoker.lower() == "muilprofiel"
            or culvert.vormkoker.lower() == "heulprofiel"
        ):
            crosssection = {
                "shape": "rectangle",
                "height": culvert.hoogteopening,
                "width": culvert.breedteopening,
                "closed": 1,
            }
        else:
            crosssection = {"shape": "circle", "diameter": 0.40}
            logger.info(
                f"Culvert {culvert.code} has an unknown shape: {culvert.vormkoker}. Applying a default profile (round - 40cm)"
            )

        # check whether an afsluitmiddel is present and take action dependent on its settings
        if management_device is not None:
            mandev = management_device[
                management_device.duikersifonhevelid == culvert.globalid
            ]
            if 'soortafsluitmiddel' not in mandev:
                mandev.loc[mandev.index,'soortafsluitmiddel'] = mandev['soortregelmiddel']
        else:
            mandev = pd.DataFrame()

        if mandev.empty:
            allowedflowdir = "both"
            valveonoff = 0
            numlosscoeff = None
            valveopeningheight = 0
            relopening = None
            losscoeff = None
        else:
            for _, i in mandev.iterrows():
                if i["soortafsluitmiddel"] == "terugslagklep":
                    allowedflowdir = "positive"
                    valveonoff = 0
                    numlosscoeff = None
                    valveopeningheight = 0
                    relopening = None
                    losscoeff = None
                elif i["soortafsluitmiddel"] == "schuif":
                    allowedflowdir = "positive"
                    valveonoff = 1
                    valveopeningheight = float(i["hoogteopening"])
                    numlosscoeff = 1
                    relopening = [float(i["hoogteopening"]) / culvert.hoogteopening]
                    losscoeff = [float(i["afvoercoefficient"])]
                else:
                    raise NotImplementedError(
                        f'Type of management device for culvert {culvert.code} is not implemented; only "schuif" and "terugslagklep" are allowed.'
                    )

        # check if a separate name field is present
        if "naam" in culverts:
            name = culvert.naam
        else:
            name = culvert.code

        self.structures.add_culvert(
            id=culvert.code,
            name=name,
            branchid=culvert.branch_id,
            chainage=culvert.branch_offset,
            leftlevel=culvert.hoogtebinnenonderkantbov,
            rightlevel=culvert.hoogtebinnenonderkantbene,
            length=culvert.lengte,
            inletlosscoeff=culvert.intreeverlies,
            outletlosscoeff=culvert.uittreeverlies,
            crosssection=crosssection,
            allowedflowdir=allowedflowdir,
            valveonoff=valveonoff,
            numlosscoeff=numlosscoeff,
            valveopeningheight=valveopeningheight,
            relopening=relopening,
            losscoeff=losscoeff,
            bedfrictiontype=culvert.typeruwheid,
            bedfriction=culvert.ruwheid,
        )
culverts_from_datamodel(culverts: pd.DataFrame) -> None

From parsed model of culverts

Source code in hydrolib/dhydamo/converters/hydamo2df.py 
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@validate_arguments(config=ConfigDict(arbitrary_types_allowed=True))
def culverts_from_datamodel(self, culverts: pd.DataFrame) -> None:
    """
    From parsed model of culverts
    """

    # Add to dict
    for culvert_idx, culvert in culverts.iterrows():
        base = self._common_structure_kwargs(culvert)
        self.structures.add_culvert(
            **base,
            leftlevel=culvert.leftlevel,
            rightlevel=culvert.rightlevel,
            crosssection=culvert.crosssectiondefinitionid,
            length=culvert.geometry.length
            if "geometry" in culvert.index
            else culvert.length,
            inletlosscoeff=culvert.inletlosscoeff,
            outletlosscoeff=culvert.outletlosscoeff,
            allowedflowdir="both",
            valveonoff=0,
            numlosscoeff=0,
            valveopeningheight=np.nan,
            relopening=np.nan,
            losscoeff=np.nan,
            frictiontype=culvert.frictiontype,
            frictionvalue=culvert.frictionvalue,
        )
generalstructures_from_datamodel(generalstructures: pd.DataFrame) -> None

From parsed data model of orifices

Parameters:

Name Type Description Default
generalstructures DataFrame

dataframe containing the data

 required
Source code in hydrolib/dhydamo/converters/hydamo2df.py 
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@validate_arguments(config=ConfigDict(arbitrary_types_allowed=True))
def generalstructures_from_datamodel(self, generalstructures: pd.DataFrame) -> None:
    """From parsed data model of orifices

    Args:
        generalstructures (pd.DataFrame): dataframe containing the data
    """

    for generalstructure_idx, generalstructure in generalstructures.iterrows():
        base = self._common_structure_kwargs(generalstructure)
        self.structures.add_generalstructure(
            **base,
            allowedflowdir="both",
            upstream1width=generalstructure.upstream1width
            if "upstream1width" in generalstructure.index
            else np.nan,
            upstream1level=generalstructure.upstream1level
            if "upstream1level" in generalstructure.index
            else np.nan,
            upstream2width=generalstructure.upstream2width
            if "upstream2width" in generalstructure.index
            else np.nan,
            upstream2level=generalstructure.upstream2level
            if "upstream2level" in generalstructure.index
            else np.nan,
            crestwidth=generalstructure.crestwidth
            if "crestwidth" in generalstructure.index
            else np.nan,
            crestlevel=generalstructure.crestlevel
            if "crestlevel" in generalstructure.index
            else np.nan,
            crestlength=generalstructure.crestlength
            if "crestlength" in generalstructure.index
            else np.nan,
            downstream1width=generalstructure.downstream1width
            if "downstream1width" in generalstructure.index
            else np.nan,
            downstream1level=generalstructure.downstream1level
            if "downstream1level" in generalstructure.index
            else np.nan,
            downstream2width=generalstructure.downstream2width
            if "downstream2width" in generalstructure.index
            else np.nan,
            downstream2level=generalstructure.downstream2level
            if "downstream2level" in generalstructure.index
            else np.nan,
            gateloweredgelevel=generalstructure.gateloweredgelevel
            if "gateloweredgelevel" in generalstructure.index
            else np.nan,
            posfreegateflowcoeff=generalstructure.posfreegateflowcoeff
            if "posfreegateflowcoeff" in generalstructure.index
            else np.nan,
            posdrowngateflowcoeff=generalstructure.posdrowngateflowcoeff
            if "posdrowngateflowcoeff" in generalstructure.index
            else np.nan,
            posfreeweirflowcoeff=generalstructure.posfreeweirflowcoeff
            if "posfreeweirflowcoeff" in generalstructure.index
            else np.nan,
            posdrownweirflowcoeff=generalstructure.posdrownweirflowcoeff
            if "posdrownweirflowcoeff" in generalstructure.index
            else np.nan,
            poscontrcoeffreegate=generalstructure.poscontrcoeffreegate
            if "poscontrcoeffreegate" in generalstructure.index
            else np.nan,
            negfreegateflowcoeff=generalstructure.negfreegateflowcoeff
            if "negfreegateflowcoeff" in generalstructure.index
            else np.nan,
            negdrowngateflowcoeff=generalstructure.negdrowngateflowcoeff
            if "negdrowngateflowcoeff" in generalstructure.index
            else np.nan,
            negfreeweirflowcoeff=generalstructure.negfreeweirflowcoeff
            if "negfreeweirflowcoeff" in generalstructure.index
            else np.nan,
            negdrownweirflowcoeff=generalstructure.negdrownweirflowcoeff
            if "negdrownweirflowcoeff" in generalstructure.index
            else np.nan,
            negcontrcoeffreegate=generalstructure.negcontrcoeffreegate
            if "negcontrcoeffreegate" in generalstructure.index
            else np.nan,
            extraresistance=generalstructure.extraresistance
            if "extraresistance" in generalstructure.index
            else np.nan,
            gateheight=generalstructure.gateheight
            if "gateheight" in generalstructure.index
            else np.nan,
            gateopeningwidth=generalstructure.gateopeningwidth
            if "gateopeningwidth" in generalstructure.index
            else np.nan,
            gateopeninghorizontaldirection=generalstructure.gateopeninghorizontaldirection
            if "gateopeninghorizontaldirection" in generalstructure.index
            else np.nan,
            usevelocityheight=generalstructure.usevelocityheight
            if "usevelocityheight" in generalstructure.index
            else np.nan,
        )
move_structure(struc, struc_dict, branch, offset) staticmethod

Function the move a structure if needed for a compound structure.

Parameters

struc : string current sub-structure id struc_dict : dict dict with all structures of a certain type branch : string branch id of the first structure in the compound offset : float chainage of the first structure in the compound

Returns

Dict with shifted coordinates.

Source code in hydrolib/dhydamo/converters/hydamo2df.py 
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@staticmethod
def move_structure(struc, struc_dict, branch, offset):
    """
    Function the move a structure if needed for a compound structure.

    Parameters
    ----------
    struc : string
        current sub-structure id
    struc_dict : dict
        dict with all structures of a certain type
    branch : string
        branch id of the first structure in the compound
    offset : float
        chainage of the first structure in the compound

    Returns
    -------
    Dict with shifted coordinates.

    """
    branch2 = struc_dict[struc]["branchid"]
    if branch2 != branch:
        logger.warning(
            f"Structures of not on the same branche. Moving structure {struc} to branch {branch}."
        )
    struc_dict[struc]["branchid"] = branch
    struc_dict[struc]["chainage"] = offset
    return struc_dict
orifices_from_datamodel(orifices: pd.DataFrame) -> None

"From parsed data model of orifices

Source code in hydrolib/dhydamo/converters/hydamo2df.py 
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@validate_arguments(config=ConfigDict(arbitrary_types_allowed=True))
def orifices_from_datamodel(self, orifices: pd.DataFrame) -> None:
    """ "From parsed data model of orifices"""
    for orifice_idx, orifice in orifices.iterrows():
        base = self._common_structure_kwargs(orifice)
        self.structures.add_orifice(
            **base,
            allowedflowdir="both",
            crestlevel=orifice.crestlevel,
            crestwidth=orifice.crestwidth,
            gateloweredgelevel=orifice.gateloweredgelevel,
            corrcoeff=orifice.corrcoef,
            uselimitflowpos=orifice.uselimitflowpos,
            limitflowpos=orifice.limitflowpos,
            uselimitflowneg=orifice.uselimitflowneg,
            limitflowneg=orifice.limitflowneg,
        )
pumps(pumpstations: ExtendedGeoDataFrame, pumps: ExtendedDataFrame = None, management: ExtendedDataFrame = None) -> None

Method to convert HyDAMO pumps to DFlowFM pumps. Three objects are required: pumpstations, pumps and management ('sturing').

Parameters corrspond to the HyDAMO DAMO2.2 objects.

Source code in hydrolib/dhydamo/converters/hydamo2df.py 
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@validate_arguments(config=ConfigDict(arbitrary_types_allowed=True))
def pumps(
    self,
    pumpstations: ExtendedGeoDataFrame,
    pumps: ExtendedDataFrame = None,
    management: ExtendedDataFrame = None,
) -> None:
    """
    Method to convert HyDAMO pumps to DFlowFM pumps. Three objects are required: pumpstations, pumps and management ('sturing').

    Parameters corrspond to the HyDAMO DAMO2.2 objects.
    """

    # Add sturing to pumps
    for pumpstation in pumpstations.itertuples():

        # find pumps for gemaal
        pumps_subset = pumps[pumps.gemaalid == pumpstation.globalid]
        if pumps_subset.empty:
            logger.warning(
                "Skipping %s because there is no associated pump.",
                pumpstation.code,
            )
            continue

        if "naam" in pumpstation:
            name = pumpstation.name
        else:
            name = pumpstation.code
        if pumps_subset.shape[0] > 1:
            # more than one pump
            cmp_list = []
            logger.info(
                "Pumpstation %s contains %d openings. Creating a compound structure with a fictional pump for each one.",
                pumpstation.code,
                pumps_subset.shape[0],
            )
            for ipump, (_,pump) in enumerate(pumps_subset.iterrows()):

                pump_control = management[management.pompid== pump.globalid]
                if pump_control.empty:
                    logger.warning("No management found for %s", pump.code)
                    continue

                startlevelsuctionside = [pump_control["bovengrens"]]
                stoplevelsuctionside = [pump_control["ondergrens"]]

                pumpid = f'{pumpstation.code}_{ipump+1}'
                cmp_list.append(pumpid)

                self.structures.add_pump(
                    id=pumpid,
                    name=name,
                    branchid=pumpstation.branch_id,
                    chainage=pumpstation.branch_offset,
                    orientation="positive",
                    numstages=1,
                    controlside="suctionside",
                    capacity=pump.maximalecapaciteit/60.,
                    startlevelsuctionside=startlevelsuctionside,
                    stoplevelsuctionside=stoplevelsuctionside,
                    startleveldeliveryside=startlevelsuctionside,
                    stopleveldeliveryside=stoplevelsuctionside,
                )
            self.structures.add_compound(id=f'cmp_{pumpstation.code}', structureids =cmp_list)

        else:
            #  only one pump
            pump_control = management[management.pompid== pumps_subset.globalid.to_numpy()[0]]
            if pump_control.empty:
                logger.warning(
                    "Skipping %s because there is no associated management.",
                    pumpstation.code,
                )

            startlevelsuctionside = [pump_control["bovengrens"]]
            stoplevelsuctionside = [pump_control["ondergrens"]]


            # the pumpstation has only one pump
            self.structures.add_pump(
                id=pumpstation.code,
                name=name,
                branchid=pumpstation.branch_id,
                chainage=pumpstation.branch_offset,
                orientation="positive",
                numstages=1,
                controlside="suctionside",
                capacity=pumps_subset.maximalecapaciteit.to_numpy()[0]/60.,
                startlevelsuctionside=startlevelsuctionside,
                stoplevelsuctionside=stoplevelsuctionside,
                startleveldeliveryside=startlevelsuctionside,
                stopleveldeliveryside=stoplevelsuctionside,
            )
pumps_from_datamodel(pumps: pd.DataFrame) -> None

From parsed data model of pumps

Source code in hydrolib/dhydamo/converters/hydamo2df.py 
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@validate_arguments(config=ConfigDict(arbitrary_types_allowed=True))
def pumps_from_datamodel(self, pumps: pd.DataFrame) -> None:
    """From parsed data model of pumps"""

    for pump_idx, pump in pumps.iterrows():
        base = self._common_structure_kwargs(pump)
        self.structures.add_pump(
            **base,
            orientation="positive",
            numstages=1,
            controlside=pump.controlside,
            capacity=pump.maximumcapacity,
            startlevelsuctionside=pump.startlevelsuctionside,
            stoplevelsuctionside=pump.stoplevelsuctionside,
            startleveldeliveryside=pump.startleveldeliveryside,
            stopleveldeliveryside=pump.stopleveldeliveryside,
        )
uweirs_from_datamodel(uweirs: pd.DataFrame) -> None

"From parsed data model of universal weirs

Source code in hydrolib/dhydamo/converters/hydamo2df.py 
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@validate_arguments(config=ConfigDict(arbitrary_types_allowed=True))
def uweirs_from_datamodel(self, uweirs: pd.DataFrame) -> None:
    """ "From parsed data model of universal weirs"""
    for uweir_idx, uweir in uweirs.iterrows():
        base = self._common_structure_kwargs(uweir)
        self.structures.add_uweir(
            **base,
            crestlevel=uweir.crestlevel,
            yvalues=uweir.yvalues,
            zvalues=uweir.zvalues,
            allowedflowdir="both",
            dischargecoeff=uweir.dischargecoeff,
        )
weirs(weirs: ExtendedGeoDataFrame = None, profile_groups=None, profile_lines=None, profiles: ExtendedGeoDataFrame | None = None, opening: ExtendedDataFrame = None, management_device: ExtendedDataFrame = None, usevelocityheight: str | None = 'true') -> None

Method to convert HyDAMO weirs to DFlowFM structures: regular weirs, orifices and universal weirs. If a weir ID corresponds to a 'stuwid' in the profile_groups object, a universal weir is created. If the management_device corresponding to a weir has the field "overlaatonderlaat" set to "onderlaat', an orifice is schematized. In all other cases, a regular (rectangular) weir is created.

Parameters corrspond to the HyDAMO DAMO2.2 objects. DFlowFM keyword 'usevelocityheight' can be specificied as a string, default is 'true'.

Source code in hydrolib/dhydamo/converters/hydamo2df.py 
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@validate_arguments(config=ConfigDict(arbitrary_types_allowed=True))
def weirs(
    self,
    weirs: ExtendedGeoDataFrame = None,
    profile_groups = None,
    profile_lines = None,
    profiles: ExtendedGeoDataFrame | None = None,
    opening: ExtendedDataFrame = None,
    management_device: ExtendedDataFrame = None,
    usevelocityheight: str | None = "true",
) -> None:
    """
    Method to convert HyDAMO weirs to DFlowFM structures: regular weirs, orifices and universal weirs.
    If a weir ID corresponds to a 'stuwid' in the profile_groups object, a universal weir is created.
    If the management_device corresponding to a weir has the field "overlaatonderlaat" set to "onderlaat', an orifice is schematized. In all other cases, a regular (rectangular) weir is created.

    Parameters corrspond to the HyDAMO DAMO2.2 objects. DFlowFM keyword 'usevelocityheight' can be specificied as a string, default is 'true'.
    """
    # bypass HyDAMO and add stuwid directly to managment for use in RTC
    if not self.structures.hydamo.management.empty:
        self.structures.hydamo.management['stuwid'] = None

    index = np.zeros(len(weirs.code))
    if profile_groups is not None and hasattr(profile_groups, "stuwid"):
        index[np.isin(weirs.globalid, np.asarray(profile_groups.stuwid))] = 1

    rweirs = weirs[index == 0]
    for weir in rweirs.itertuples():
        weir_opening = opening[opening.stuwid == weir.globalid]

        # check if a separate name field is present
        if "naam" in weirs:
            name = weir.naam
            if not name:
                name = weir.code
        else:
            name = weir.code

        if weir_opening.shape[0] > 1:
            logger.info(
                "Weir %s contains %d openings. Creating a compound structure with a fictional weir for each one.",
                weir.code,
                weir_opening.shape[0],
            )
            cmp_list = []
            for num_op, (_, op_row) in enumerate(weir_opening.iterrows()):
                weir_mandev = management_device[
                    management_device.kunstwerkopeningid
                    == op_row.globalid
                ]

                if weir_mandev.empty:
                    logger.warning(
                        "Skipping opening %s (weir %s) because there is no associated management device.",
                        op_row.code,
                        weir.code
                    )
                    continue
                if weir_mandev.shape[0] > 1:
                    logger.warning(
                        "Multiple management devices associated to opening %s (weir %s). Taking the first one.",
                        op_row.code,
                        weir.code
                    )
                    weir_mandev = weir_mandev.iloc[[0]]                    


                weir_id = f'{weir.code}_{num_op+1}'
                if (not self.structures.hydamo.management.empty) & (hasattr(self.structures.hydamo.management, 'regelmiddelid')):
                    if weir_mandev.globalid.isin(self.structures.hydamo.management.regelmiddelid).item():
                        self.structures.hydamo.management.loc[self.structures.hydamo.management.regelmiddelid == weir_mandev.globalid.squeeze(), 'stuwid'] = weir_id
                if weir_mandev.overlaatonderlaat.squeeze().lower() == 'overlaat':
                    cmp_list.append(weir_id)
                    self.structures.add_rweir(id=weir_id,
                                                name=name,
                                                branchid=weir.branch_id,
                                                chainage=weir.branch_offset,
                                                crestlevel=op_row.laagstedoorstroomhoogte,
                                                crestwidth=op_row.laagstedoorstroombreedte,
                                                corrcoeff=weir.afvoercoefficient,
                                                allowedflowdir="both",
                                                usevelocityheight=usevelocityheight,
                                             )
                elif weir_mandev.overlaatonderlaat.squeeze().lower() == 'onderlaat':
                    cmp_list.append(weir_id)
                    if "maximaaldebiet" not in weir_mandev or pd.isna(weir_mandev.maximaaldebiet.to_numpy()[0]):
                        limitflow = "false"
                        maxq = 0.0
                    else:
                        limitflow = "true"
                        maxq = float(weir_mandev.maximaaldebiet.to_numpy()[0])
                    self.structures.add_orifice(
                        id=weir_id,
                        name=name,
                        branchid=weir.branch_id,
                        chainage=weir.branch_offset,
                        crestlevel=float(weir_opening.laagstedoorstroomhoogte.to_numpy()[0]),
                        crestwidth=float(weir_opening.laagstedoorstroombreedte.to_numpy()[0]),
                        corrcoeff=weir.afvoercoefficient,
                        allowedflowdir="both",
                        usevelocityheight=usevelocityheight,
                        gateloweredgelevel=float(weir_opening.laagstedoorstroomhoogte.to_numpy()[0])
                        + float(weir_mandev.hoogteopening.to_numpy()[0]),
                        uselimitflowpos=limitflow,
                        limitflowpos=maxq,
                        uselimitflowneg=limitflow,
                        limitflowneg=maxq,
                    )
                else:
                    logger.warning(
                        'Skipping weir %s - from "overlaatonderlaat" %s the type of structure could not be determined.',
                        weir.code,
                        weir_mandev.overlaatonderlaat,
                    )
            self.structures.add_compound(id=f'cmp_{weir.code}', structureids =cmp_list)
            # self.structures.rweirs_df.drop(weir.code)
        else:
            if weir_opening.empty:
                logger.warning(
                    "Skipping weir %s because there is no associated opening.",
                    weir.code,
                )
                continue

            weir_id = weir.code
            weir_mandev = management_device[
                    management_device.kunstwerkopeningid
                    == weir_opening.globalid.to_numpy()[0]
                ]

            if weir_mandev.empty:
                logger.warning(
                    "Skipping opening %s (weir %s) because there is no associated management device.",
                    weir_opening.code.squeeze(),
                    weir_id
                )
                continue
            if weir_mandev.shape[0] > 1:
                logger.warning(
                    "Multiple management devices associated to opening %s (weir %s). Taking the first one.",
                    weir_opening.code.squeeze(),
                    weir_id
                )
                weir_mandev = weir_mandev.iloc[[0]]                    


            if (not self.structures.hydamo.management.empty) & hasattr(self.structures.hydamo.management, 'regelmiddelid'):
                if weir_mandev.globalid.isin(self.structures.hydamo.management.regelmiddelid).item():
                    self.structures.hydamo.management.loc[self.structures.hydamo.management.regelmiddelid == weir_mandev.globalid.squeeze(), 'stuwid'] = weir_id

            if isinstance(weir_mandev.overlaatonderlaat, pd.Series):
                overlaatonderlaat = weir_mandev.overlaatonderlaat.squeeze()
            else:
                overlaatonderlaat = weir_mandev.overlaatonderlaat

            if (
                overlaatonderlaat.lower()
                == "overlaat"
            ):
                self.structures.add_rweir(
                    id=weir_id,
                    name=name,
                    branchid=weir.branch_id,
                    chainage=weir.branch_offset,
                    crestlevel=weir_opening.laagstedoorstroomhoogte.to_numpy()[0],
                    crestwidth=weir_opening.laagstedoorstroombreedte.to_numpy()[0],
                    corrcoeff=weir.afvoercoefficient,
                    allowedflowdir="both",
                    usevelocityheight=usevelocityheight,
                )

            elif (
                overlaatonderlaat.lower()
                == "onderlaat"
            ):
                if "maximaaldebiet" not in weir_mandev or pd.isna(weir_mandev.maximaaldebiet.to_numpy()[0]):
                    limitflow = "false"
                    maxq = 0.0
                else:
                    limitflow = "true"
                    maxq = float(weir_mandev.maximaaldebiet.to_numpy()[0])
                self.structures.add_orifice(
                    id=weir_id,
                    name=name,
                    branchid=weir.branch_id,
                    chainage=weir.branch_offset,
                    crestlevel=float(weir_opening.laagstedoorstroomhoogte.to_numpy()[0]),
                    crestwidth=float(weir_opening.laagstedoorstroombreedte.to_numpy()[0]),
                    corrcoeff=weir.afvoercoefficient,
                    allowedflowdir="both",
                    usevelocityheight=usevelocityheight,
                    gateloweredgelevel=float(weir_opening.laagstedoorstroomhoogte.to_numpy()[0])
                    + float(weir_mandev.hoogteopening.to_numpy()[0]),
                    uselimitflowpos=limitflow,
                    limitflowpos=maxq,
                    uselimitflowneg=limitflow,
                    limitflowneg=maxq,
                )
            else:
                logger.warning(
                    'Skipping %s - from "overlaatonderlaat" %s the type of structure could not be determined.',
                    weir.code,
                    weir_mandev.overlaatonderlaat,
                )

    uweirs = weirs[index == 1]
    for uweir in uweirs.itertuples():
        # check if a separate name field is present
        if "naam" in uweirs:
            name = uweir.naam
        else:
            name = uweir.code

        prof = np.empty(0)
        if (profiles is not None) & ("stuwid" in profile_groups):
            group = profile_groups[profile_groups["stuwid"] == uweir.globalid]
            line = profile_lines[
                profile_lines["profielgroepid"] == group["globalid"].to_numpy()[0]
            ]
            prof = profiles[profiles["profiellijnid"] == line["globalid"].to_numpy()[0]]
            if not prof.empty:
                counts = len(prof.geometry.iloc[0].coords[:])
                xyz = np.vstack(prof.geometry.iloc[0].coords[:])
                length = np.r_[
                    0,
                    np.cumsum(np.hypot(np.diff(xyz[:, 0]), np.diff(xyz[:, 1]))),
                ]
                yzvalues = np.c_[length, xyz[:, -1] - np.min(xyz[:, -1])]

        if not hasattr(uweir, 'laagstedoorstroomhoogte') or pd.isna(uweir.laagstedoorstroomhoogte):
            kruinhoogte = np.min(xyz[:,-1])
        else:
            kruinhoogte = uweir.laagstedoorstroomhoogte

        if len(prof) == 0:
            # return an error it is still not found
            raise ValueError(f"{uweir.code} is not found in any cross-section.")
        self.structures.add_uweir(
            id=uweir.code,
            name=name,
            branchid=uweir.branch_id,
            chainage=uweir.branch_offset,
            crestlevel=kruinhoogte,
            dischargecoeff=uweir.afvoercoefficient,
            allowedflowdir="both",
            numlevels=counts,
            yvalues=" ".join([f"{yz[0]:7.3f}" for yz in yzvalues]),
            zvalues=" ".join([f"{yz[1]:7.3f}" for yz in yzvalues]),
        )
weirs_from_datamodel(weirs: pd.DataFrame) -> None

"From parsed data model of weirs

Source code in hydrolib/dhydamo/converters/hydamo2df.py 
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@validate_arguments(config=ConfigDict(arbitrary_types_allowed=True))
def weirs_from_datamodel(self, weirs: pd.DataFrame) -> None:
    """ "From parsed data model of weirs"""
    for weir_idx, weir in weirs.iterrows():
        base = self._common_structure_kwargs(weir)
        self.structures.add_weir(
            **base,
            crestlevel=weir.crestlevel,
            crestwidth=weir.crestwidth,
            corrcoeff=weir.corrcoeff,
        )