ISEA3HPandas module

ISEA3HPandas

Source code in vgridpandas/isea3hpandas.py

@pd.api.extensions.register_dataframe_accessor("isea3h")
class ISEA3HPandas:
    def __init__(self, df: DataFrame):
        self._df = df

    def latlon2isea3h(
        self,
        resolution: int,
        lat_col: str = "lat",
        lon_col: str = "lon",
        set_index: bool = False,
    ) -> AnyDataFrame:
        """Adds isea3h 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
        ----------
        resolution : int
            isea3h 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 isea3h ID is set as index, default 'True'

        Returns
        -------
        (Geo)DataFrame with isea3h 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]

        isea3h_ids = [
            latlon_to_isea3h(lat, lon, resolution) for lat, lon in zip(lats, lons)
        ]

        isea3h_col = ISEA3H_COL
        assign_arg = {isea3h_col: isea3h_ids, f"{isea3h_col}_res": resolution}
        df = self._df.assign(**assign_arg)
        if set_index:
            return df.set_index(isea3h_col)
        return df

    def isea3h2geo(
        self, isea3h_col: str = None, fix_antimeridian: Optional[str] = None
    ) -> GeoDataFrame:
        """Add geometry with ISEA3H geometry to the DataFrame."""
        if isea3h_col is not None:
            if isea3h_col not in self._df.columns:
                raise ValueError(f"Column '{isea3h_col}' not found in DataFrame")
            ids = self._df[isea3h_col]
        else:
            if ISEA3H_COL not in self._df.columns:
                raise ValueError(f"Column '{ISEA3H_COL}' not found in DataFrame")
            ids = self._df[ISEA3H_COL]
        return dggs_ids_to_geodataframe(
            self._df, ids, isea3h_to_geo, fix_antimeridian=fix_antimeridian
        )

    def polyfill(
        self,
        resolution: int,
        predicate: str = None,
        compact: bool = False,
        explode: bool = False,
        fix_antimeridian: Optional[str] = None,
    ) -> AnyDataFrame:
        """
        Parameters
        ----------
        resolution : int
            isea3h resolution
        predicate : str, optional
            Spatial predicate to apply ('intersect', 'within', 'centroid_within', 'largest_overlap')
        compact : bool, optional
            Whether to compact the isea3h IDs
        explode : bool
            If True, will explode the resulting list vertically.
            All other columns' values are copied.
            Default: False
        fix_antimeridian : str, optional
            Antimeridian fixing method passed to ``isea3h2geo``
        """

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

        if not explode:
            assign_args = {ISEA3H_COL: result}
            return self._df.assign(**assign_args)

        result = result.explode().to_frame(ISEA3H_COL)
        return self._df.join(result)

    def isea3hbin(
        self,
        resolution: int,
        stats: str = "count",
        numeric_col: str = None,
        category_col: str = None,
        lat_col: str = "lat",
        lon_col: str = "lon",
        fix_antimeridian: Optional[str] = None,
    ) -> GeoDataFrame:
        """
        Bin points into isea3h cells and compute statistics.
        """
        isea3h_col = ISEA3H_COL
        df = self.latlon2isea3h(resolution, lat_col, lon_col)
        result = aggregate_bin(df, isea3h_col, stats, numeric_col, category_col)
        return result.isea3h.isea3h2geo(
            isea3h_col=isea3h_col, fix_antimeridian=fix_antimeridian
        )

isea3h2geo(isea3h_col=None, fix_antimeridian=None)

Add geometry with ISEA3H geometry to the DataFrame.

Source code in vgridpandas/isea3hpandas.py

def isea3h2geo(
    self, isea3h_col: str = None, fix_antimeridian: Optional[str] = None
) -> GeoDataFrame:
    """Add geometry with ISEA3H geometry to the DataFrame."""
    if isea3h_col is not None:
        if isea3h_col not in self._df.columns:
            raise ValueError(f"Column '{isea3h_col}' not found in DataFrame")
        ids = self._df[isea3h_col]
    else:
        if ISEA3H_COL not in self._df.columns:
            raise ValueError(f"Column '{ISEA3H_COL}' not found in DataFrame")
        ids = self._df[ISEA3H_COL]
    return dggs_ids_to_geodataframe(
        self._df, ids, isea3h_to_geo, fix_antimeridian=fix_antimeridian
    )

isea3hbin(resolution, stats='count', numeric_col=None, category_col=None, lat_col='lat', lon_col='lon', fix_antimeridian=None)

Bin points into isea3h cells and compute statistics.

Source code in vgridpandas/isea3hpandas.py

def isea3hbin(
    self,
    resolution: int,
    stats: str = "count",
    numeric_col: str = None,
    category_col: str = None,
    lat_col: str = "lat",
    lon_col: str = "lon",
    fix_antimeridian: Optional[str] = None,
) -> GeoDataFrame:
    """
    Bin points into isea3h cells and compute statistics.
    """
    isea3h_col = ISEA3H_COL
    df = self.latlon2isea3h(resolution, lat_col, lon_col)
    result = aggregate_bin(df, isea3h_col, stats, numeric_col, category_col)
    return result.isea3h.isea3h2geo(
        isea3h_col=isea3h_col, fix_antimeridian=fix_antimeridian
    )

latlon2isea3h(resolution, lat_col='lat', lon_col='lon', set_index=False)

Adds isea3h 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

resolution : int isea3h 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 isea3h ID is set as index, default 'True'

Returns

(Geo)DataFrame with isea3h IDs added

Source code in vgridpandas/isea3hpandas.py

def latlon2isea3h(
    self,
    resolution: int,
    lat_col: str = "lat",
    lon_col: str = "lon",
    set_index: bool = False,
) -> AnyDataFrame:
    """Adds isea3h 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
    ----------
    resolution : int
        isea3h 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 isea3h ID is set as index, default 'True'

    Returns
    -------
    (Geo)DataFrame with isea3h 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]

    isea3h_ids = [
        latlon_to_isea3h(lat, lon, resolution) for lat, lon in zip(lats, lons)
    ]

    isea3h_col = ISEA3H_COL
    assign_arg = {isea3h_col: isea3h_ids, f"{isea3h_col}_res": resolution}
    df = self._df.assign(**assign_arg)
    if set_index:
        return df.set_index(isea3h_col)
    return df

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

Parameters

resolution : int isea3h resolution predicate : str, optional Spatial predicate to apply ('intersect', 'within', 'centroid_within', 'largest_overlap') compact : bool, optional Whether to compact the isea3h IDs explode : bool If True, will explode the resulting list vertically. All other columns' values are copied. Default: False fix_antimeridian : str, optional Antimeridian fixing method passed to isea3h2geo

Source code in vgridpandas/isea3hpandas.py

def polyfill(
    self,
    resolution: int,
    predicate: str = None,
    compact: bool = False,
    explode: bool = False,
    fix_antimeridian: Optional[str] = None,
) -> AnyDataFrame:
    """
    Parameters
    ----------
    resolution : int
        isea3h resolution
    predicate : str, optional
        Spatial predicate to apply ('intersect', 'within', 'centroid_within', 'largest_overlap')
    compact : bool, optional
        Whether to compact the isea3h IDs
    explode : bool
        If True, will explode the resulting list vertically.
        All other columns' values are copied.
        Default: False
    fix_antimeridian : str, optional
        Antimeridian fixing method passed to ``isea3h2geo``
    """

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

    if not explode:
        assign_args = {ISEA3H_COL: result}
        return self._df.assign(**assign_args)

    result = result.explode().to_frame(ISEA3H_COL)
    return self._df.join(result)

poly2isea3h(geometry, resolution, predicate=None, compact=False, fix_antimeridian=None)

Convert polygon or line geometries to ISEA3H grid cells.

Mirrors polygon2isea3h and polyline2isea3h in vgrid (Windows only). Polygons are filtered with predicate; lines use intersection. Compact mode applies to polygons after predicate filtering.

Parameters:

Name	Type	Description	Default
resolution	int	ISEA3H resolution level [0..32]	required
geometry		Polygon, MultiPolygon, LineString, or MultiLineString	required
predicate	str	Spatial predicate for polygons ('intersect', 'within', 'centroid_within', 'largest_overlap')	None
compact	bool	Enable ISEA3H compact mode for polygons	False
fix_antimeridian	str	Antimeridian fixing method passed to isea3h2geo: shift, shift_balanced, shift_west, shift_east, split, none	None

Returns:

Name	Type	Description
list	list	List of ISEA3H cell ids

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 = poly2isea3h(poly, 10, predicate="intersect", compact=True) len(cells) > 0 True

Source code in vgridpandas/isea3hpandas.py

def poly2isea3h(
    geometry,
    resolution: int,
    predicate: str = None,
    compact: bool = False,
    fix_antimeridian: Optional[str] = None,
) -> list:
    """
    Convert polygon or line geometries to ISEA3H grid cells.

    Mirrors ``polygon2isea3h`` and ``polyline2isea3h`` in vgrid (Windows only).
    Polygons are filtered with ``predicate``; lines use intersection.
    Compact mode applies to polygons after predicate filtering.

    Args:
        resolution (int): ISEA3H resolution level [0..32]
        geometry: Polygon, MultiPolygon, LineString, or MultiLineString
        predicate (str, optional): Spatial predicate for polygons
            ('intersect', 'within', 'centroid_within', 'largest_overlap')
        compact (bool, optional): Enable ISEA3H compact mode for polygons
        fix_antimeridian (str, optional): Antimeridian fixing method passed to
            ``isea3h2geo``: shift, shift_balanced, shift_west, shift_east, split, none

    Returns:
        list: List of ISEA3H cell ids

    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 = poly2isea3h(poly, 10, predicate="intersect", compact=True)
        >>> len(cells) > 0
        True
    """
    if platform.system() != "Windows":
        return []

    resolution = validate_isea3h_resolution(resolution)
    isea3h_ids = []
    if isinstance(geometry, (Polygon, LineString)):
        polys = [geometry]
    elif isinstance(geometry, (MultiPolygon, MultiLineString)):
        polys = list(geometry.geoms)
    else:
        return []

    for poly in polys:
        if poly is None or poly.is_empty:
            continue

        is_line = isinstance(poly, LineString)
        bounding_child_cells = _isea3h_children_for_bounds(poly.bounds, resolution)

        poly_ids = []
        for child in bounding_child_cells:
            isea3h_cell = DggsCell(child)
            isea3h_id = isea3h_cell.get_cell_id()
            cell_polygon = isea3h_to_geo(
                isea3h_id, fix_antimeridian=fix_antimeridian
            )
            if is_line:
                if not cell_polygon.intersects(poly):
                    continue
            elif not check_predicate(cell_polygon, poly, predicate):
                continue
            poly_ids.append(isea3h_id)

        if compact and poly_ids and not is_line:
            poly_ids = list(isea3h_compact(poly_ids))

        isea3h_ids.extend(poly_ids)

    return list(dict.fromkeys(isea3h_ids))

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

Return cell ids covering a single row geometry.

Source code in vgridpandas/isea3hpandas.py

def polyfill_row(
    geometry,
    resolution,
    predicate=None,
    compact=False,
    fix_antimeridian: Optional[str] = None,
) -> list:
    """Return cell ids covering a single row geometry."""
    if isinstance(geometry, (Polygon, MultiPolygon)):
        tokens = set(
            poly2isea3h(geometry, resolution, predicate, compact, fix_antimeridian)
        )
    elif isinstance(geometry, (LineString, MultiLineString)):
        tokens = set(
            poly2isea3h(
                geometry,
                resolution,
                predicate="intersect",
                compact=False,
                fix_antimeridian=fix_antimeridian,
            )
        )
    else:
        raise TypeError(f"Unknown type {type(geometry)}")
    return list(tokens)