DGGALPandas module

S2Pandas module for S2 cell operations on pandas DataFrames and GeoDataFrames.

DGGALPandas

Source code in vgridpandas/dggalpandas.py

@pd.api.extensions.register_dataframe_accessor("dggal")
class DGGALPandas:
    def __init__(self, df: DataFrame):
        self._df = df

    def latlon2dggal(
        self,
        dggs_type: str,
        resolution: int,
        lat_col: str = "lat",
        lon_col: str = "lon",
        set_index: bool = False,
    ) -> AnyDataFrame:
        """Adds DGGAL id to (Geo)DataFrame.

        pd.DataFrame: uses `lat_col` and `lon_col` (default `lat` and `lon`)
        gpd.GeoDataFrame: uses `geometry`

        Assumes coordinates in epsg=4326.

        Parameters
        ----------
        dggs_type : str
            DGGAL type
        resolution : int
            DGGAL resolution
        lat_col : str
            Name of the latitude column (if used), default 'lat'
        lon_col : str
            Name of the longitude column (if used), default 'lon'
        set_index : bool
            If True, the columns with DGGAL id is set as index, default 'True'

        Returns
        -------
        (Geo)DataFrame with DGGAL ids added

        """

        if isinstance(self._df, gpd.GeoDataFrame):
            lons = self._df.geometry.x
            lats = self._df.geometry.y
        else:
            lons = self._df[lon_col]
            lats = self._df[lat_col]

        dggal_ids = [
            latlon_to_dggal(dggs_type, lat, lon, resolution)
            for lat, lon in zip(lats, lons)
        ]

        dggal_col = f"dggal_{dggs_type}"
        assign_arg = {dggal_col: dggal_ids, f"{dggal_col}_res": resolution}
        df = self._df.assign(**assign_arg)
        if set_index:
            return df.set_index(dggal_col)
        return df

    def dggal2geo(self, dggs_type: str, dggal_col: str = None) -> GeoDataFrame:
        """Add geometry with DGGAL geometry to the DataFrame."""
        if dggal_col is None:
            dggal_col = f"dggal_{dggs_type}"
        if dggal_col not in self._df.columns:
            raise ValueError(f"Column '{dggal_col}' not found in DataFrame")

        def to_geo(token):
            return dggal_to_geo(dggs_type, token)

        return dggs_ids_to_geodataframe(self._df, self._df[dggal_col], to_geo)

    def polyfill(
        self,
        dggs_type: str,
        resolution: int,
        predicate: str = None,
        compact: bool = False,
        explode: bool = False,
    ) -> AnyDataFrame:
        """
        Parameters
        ----------
        resolution : int
            DGGAL resolution
        predicate : str, optional
            Spatial predicate to apply ('intersect', 'within', 'centroid_within', 'largest_overlap')
        compact : bool, optional
            Whether to compact the DGGAL ids
        explode : bool
            If True, will explode the resulting list vertically.
            All other columns' values are copied.
            Default: False
        """

        result = self._df.geometry.apply(
            lambda geom: polyfill_row(dggs_type, geom, resolution, predicate, compact)
        )

        if not explode:
            return self._df.assign(**{f"dggal_{dggs_type}": result})

        result = result.explode().to_frame(f"dggal_{dggs_type}")
        return self._df.join(result)

    def dggalbin(
        self,
        dggs_type: str,
        resolution: int,
        stats: str = "count",
        numeric_col: str = None,
        category_col: str = None,
        lat_col: str = "lat",
        lon_col: str = "lon",
    ) -> GeoDataFrame:
        """Bin points into DGGAL cells and compute statistics."""
        dggal_col = f"dggal_{dggs_type}"
        df = self.latlon2dggal(dggs_type, resolution, lat_col, lon_col)
        result = aggregate_bin(df, dggal_col, stats, numeric_col, category_col)
        return result.dggal.dggal2geo(dggs_type, dggal_col=dggal_col)

dggal2geo(dggs_type, dggal_col=None)

Add geometry with DGGAL geometry to the DataFrame.

Source code in vgridpandas/dggalpandas.py

def dggal2geo(self, dggs_type: str, dggal_col: str = None) -> GeoDataFrame:
    """Add geometry with DGGAL geometry to the DataFrame."""
    if dggal_col is None:
        dggal_col = f"dggal_{dggs_type}"
    if dggal_col not in self._df.columns:
        raise ValueError(f"Column '{dggal_col}' not found in DataFrame")

    def to_geo(token):
        return dggal_to_geo(dggs_type, token)

    return dggs_ids_to_geodataframe(self._df, self._df[dggal_col], to_geo)

dggalbin(dggs_type, resolution, stats='count', numeric_col=None, category_col=None, lat_col='lat', lon_col='lon')

Bin points into DGGAL cells and compute statistics.

Source code in vgridpandas/dggalpandas.py

def dggalbin(
    self,
    dggs_type: str,
    resolution: int,
    stats: str = "count",
    numeric_col: str = None,
    category_col: str = None,
    lat_col: str = "lat",
    lon_col: str = "lon",
) -> GeoDataFrame:
    """Bin points into DGGAL cells and compute statistics."""
    dggal_col = f"dggal_{dggs_type}"
    df = self.latlon2dggal(dggs_type, resolution, lat_col, lon_col)
    result = aggregate_bin(df, dggal_col, stats, numeric_col, category_col)
    return result.dggal.dggal2geo(dggs_type, dggal_col=dggal_col)

latlon2dggal(dggs_type, resolution, lat_col='lat', lon_col='lon', set_index=False)

Adds DGGAL id to (Geo)DataFrame.

pd.DataFrame: uses lat_col and lon_col (default lat and lon) gpd.GeoDataFrame: uses geometry

Assumes coordinates in epsg=4326.

Parameters

dggs_type : str DGGAL type resolution : int DGGAL resolution lat_col : str Name of the latitude column (if used), default 'lat' lon_col : str Name of the longitude column (if used), default 'lon' set_index : bool If True, the columns with DGGAL id is set as index, default 'True'

Returns

(Geo)DataFrame with DGGAL ids added

Source code in vgridpandas/dggalpandas.py

def latlon2dggal(
    self,
    dggs_type: str,
    resolution: int,
    lat_col: str = "lat",
    lon_col: str = "lon",
    set_index: bool = False,
) -> AnyDataFrame:
    """Adds DGGAL id to (Geo)DataFrame.

    pd.DataFrame: uses `lat_col` and `lon_col` (default `lat` and `lon`)
    gpd.GeoDataFrame: uses `geometry`

    Assumes coordinates in epsg=4326.

    Parameters
    ----------
    dggs_type : str
        DGGAL type
    resolution : int
        DGGAL resolution
    lat_col : str
        Name of the latitude column (if used), default 'lat'
    lon_col : str
        Name of the longitude column (if used), default 'lon'
    set_index : bool
        If True, the columns with DGGAL id is set as index, default 'True'

    Returns
    -------
    (Geo)DataFrame with DGGAL ids added

    """

    if isinstance(self._df, gpd.GeoDataFrame):
        lons = self._df.geometry.x
        lats = self._df.geometry.y
    else:
        lons = self._df[lon_col]
        lats = self._df[lat_col]

    dggal_ids = [
        latlon_to_dggal(dggs_type, lat, lon, resolution)
        for lat, lon in zip(lats, lons)
    ]

    dggal_col = f"dggal_{dggs_type}"
    assign_arg = {dggal_col: dggal_ids, f"{dggal_col}_res": resolution}
    df = self._df.assign(**assign_arg)
    if set_index:
        return df.set_index(dggal_col)
    return df

polyfill(dggs_type, resolution, predicate=None, compact=False, explode=False)

Parameters

resolution : int DGGAL resolution predicate : str, optional Spatial predicate to apply ('intersect', 'within', 'centroid_within', 'largest_overlap') compact : bool, optional Whether to compact the DGGAL ids explode : bool If True, will explode the resulting list vertically. All other columns' values are copied. Default: False

Source code in vgridpandas/dggalpandas.py

def polyfill(
    self,
    dggs_type: str,
    resolution: int,
    predicate: str = None,
    compact: bool = False,
    explode: bool = False,
) -> AnyDataFrame:
    """
    Parameters
    ----------
    resolution : int
        DGGAL resolution
    predicate : str, optional
        Spatial predicate to apply ('intersect', 'within', 'centroid_within', 'largest_overlap')
    compact : bool, optional
        Whether to compact the DGGAL ids
    explode : bool
        If True, will explode the resulting list vertically.
        All other columns' values are copied.
        Default: False
    """

    result = self._df.geometry.apply(
        lambda geom: polyfill_row(dggs_type, geom, resolution, predicate, compact)
    )

    if not explode:
        return self._df.assign(**{f"dggal_{dggs_type}": result})

    result = result.explode().to_frame(f"dggal_{dggs_type}")
    return self._df.join(result)

poly2dggal(dggs_type, geometry, resolution, predicate=None, compact=False)

Convert polygon geometries (Polygon, MultiPolygon) to DGGAL grid cells.

Parameters:

Name	Type	Description	Default
dggs_type		str DGGAL type	required
resolution	int	DGGAL resolution level [0..28]	required
geometry	Polygon or MultiPolygon	Polygon geometry to convert	required
predicate	str	Spatial predicate to apply ('intersect', 'within', 'centroid_within', 'largest_overlap')	None

Returns:

Name	Type	Description
list		List of DGGAL tokens intersecting the polygon

Example

from shapely.geometry import Polygon poly = Polygon([(-122.5, 37.7), (-122.3, 37.7), (-122.3, 37.9), (-122.5, 37.9)]) cells = poly2dggal(poly, 10, predicate="intersect", compact=True) len(cells) > 0 True

Source code in vgridpandas/dggalpandas.py

def poly2dggal(dggs_type, geometry, resolution, predicate=None, compact=False):
    """
    Convert polygon geometries (Polygon, MultiPolygon) to DGGAL grid cells.

    Args:
        dggs_type: str
            DGGAL type
        resolution (int): DGGAL resolution level [0..28]
        geometry (shapely.geometry.Polygon or shapely.geometry.MultiPolygon): Polygon geometry to convert
        predicate (str, optional): Spatial predicate to apply ('intersect', 'within', 'centroid_within', 'largest_overlap')

    Returns:
        list: List of DGGAL tokens intersecting the polygon

    Example:
        >>> from shapely.geometry import Polygon
        >>> poly = Polygon([(-122.5, 37.7), (-122.3, 37.7), (-122.3, 37.9), (-122.5, 37.9)])
        >>> cells = poly2dggal(poly, 10, predicate="intersect", compact=True)
        >>> len(cells) > 0
        True
    """

    dggs_class_name = DGGAL_TYPES[dggs_type]["class_name"]
    dggrs = globals()[dggs_class_name]()

    resolution = validate_dggal_resolution(dggs_type, resolution)
    dggal_ids = []
    if isinstance(geometry, (Polygon, LineString)):
        polys = [geometry]
    elif isinstance(geometry, (MultiPolygon, MultiLineString)):
        polys = list(geometry.geoms)
    else:
        return []

    for poly in polys:
        min_lon, min_lat, max_lon, max_lat = poly.bounds
        ll = GeoPoint(min_lat, min_lon)
        ur = GeoPoint(max_lat, max_lon)
        geo_extent = GeoExtent(ll, ur)
        zones = dggrs.listZones(resolution, geo_extent)
        for zone in zones:
            zone_id = dggrs.getZoneTextID(zone)
            cell_polygon = dggal2geo(dggs_type, zone_id)
            if not check_predicate(cell_polygon, poly, predicate):
                continue
            dggal_ids.append(zone_id)
    if compact:
        dggal_ids = dggal_compact(dggs_type, dggal_ids)
    return dggal_ids

polyfill_row(dggs_type, geometry, resolution, predicate=None, compact=False)

Return cell ids covering a single row geometry.

Source code in vgridpandas/dggalpandas.py

def polyfill_row(
    dggs_type, geometry, resolution, predicate=None, compact=False
) -> list:
    """Return cell ids covering a single row geometry."""
    if isinstance(geometry, (Polygon, MultiPolygon)):
        tokens = set(poly2dggal(dggs_type, geometry, resolution, predicate, compact))
    elif isinstance(geometry, (LineString, MultiLineString)):
        tokens = set(
            poly2dggal(
                dggs_type, geometry, resolution, predicate="intersect", compact=False
            )
        )
    else:
        raise TypeError(f"Unknown type {type(geometry)}")
    return list(tokens)