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Infer default view state from data (#78)
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,24 @@ | ||
| import pyarrow as pa | ||
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| GEOARROW_EXTENSION_TYPE_NAMES = { | ||
| b"geoarrow.point", | ||
| b"geoarrow.linestring", | ||
| b"geoarrow.polygon", | ||
| b"geoarrow.multipoint", | ||
| b"geoarrow.multilinestring", | ||
| b"geoarrow.multipolygon", | ||
| } | ||
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| def get_geometry_column_index(schema: pa.Schema) -> int: | ||
| """Get the positional index of the geometry column in a pyarrow Schema""" | ||
| for field_idx in range(len(schema)): | ||
| field_metadata = schema.field(field_idx).metadata | ||
| if ( | ||
| field_metadata | ||
| and field_metadata.get(b"ARROW:extension:name") | ||
| in GEOARROW_EXTENSION_TYPE_NAMES | ||
| ): | ||
| return field_idx | ||
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| raise ValueError("No geometry column in table schema.") |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,200 @@ | ||
| """Helpers for viewport operations | ||
| This is partially derived from pydeck at | ||
| (https://github.com/visgl/deck.gl/blob/63728ecbdaa2f99811900ec3709e5df0f9f8d228/bindings/pydeck/pydeck/data_utils/viewport_helpers.py) | ||
| under the Apache 2 license. | ||
| """ | ||
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| from __future__ import annotations | ||
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| import math | ||
| from dataclasses import dataclass | ||
| from typing import Optional, Tuple | ||
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| import numpy as np | ||
| import pyarrow as pa | ||
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| from lonboard.utils import get_geometry_column_index | ||
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| @dataclass | ||
| class Bbox: | ||
| minx: float = math.inf | ||
| miny: float = math.inf | ||
| maxx: float = -math.inf | ||
| maxy: float = -math.inf | ||
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| def update(self, other: Bbox): | ||
| if other.minx < self.minx: | ||
| self.minx = other.minx | ||
| if other.miny < self.miny: | ||
| self.miny = other.miny | ||
| if other.maxx > self.maxx: | ||
| self.maxx = other.maxx | ||
| if other.maxy > self.maxy: | ||
| self.maxy = other.maxy | ||
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| def to_tuple(self) -> Tuple[float, float, float, float]: | ||
| return (self.minx, self.miny, self.maxx, self.maxy) | ||
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| def geo_mean_overflow(iterable): | ||
| return np.exp(np.log(iterable).mean()) | ||
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| def geo_mean(iterable): | ||
| a = np.array(iterable) | ||
| return a.prod() ** (1.0 / len(a)) | ||
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| @dataclass | ||
| class WeightedCentroid: | ||
| # Existing average for x and y | ||
| x: Optional[float] = None | ||
| y: Optional[float] = None | ||
| num_items: int = 0 | ||
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| def update(self, coords: pa.FixedSizeListArray): | ||
| """Update the average for x and y based on a new chunk of data | ||
| Note that this does not keep a cumulative sum due to precision concerns. Rather | ||
| it incrementally updates based on a delta, and never multiplies to large | ||
| constant values. | ||
| Note: this currently computes the mean weighted _per coordinate_ and not _per | ||
| geometry_. | ||
| """ | ||
| np_arr = coords.flatten().to_numpy().reshape(-1, coords.type.list_size) | ||
| new_chunk_len = np_arr.shape[0] | ||
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| if self.x is None or self.y is None: | ||
| assert self.x is None and self.y is None and self.num_items == 0 | ||
| self.x = np.mean(np_arr[:, 0]) | ||
| self.y = np.mean(np_arr[:, 1]) | ||
| self.num_items = new_chunk_len | ||
| return | ||
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| existing_modifier = self.num_items / (self.num_items + new_chunk_len) | ||
| new_chunk_modifier = new_chunk_len / (self.num_items + new_chunk_len) | ||
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| new_chunk_avg_x = np.mean(np_arr[:, 0]) | ||
| new_chunk_avg_y = np.mean(np_arr[:, 0]) | ||
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| existing_x_avg = self.x | ||
| existing_y_avg = self.y | ||
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| self.x = ( | ||
| existing_x_avg * existing_modifier + new_chunk_avg_x * new_chunk_modifier | ||
| ) | ||
| self.y = ( | ||
| existing_y_avg * existing_modifier + new_chunk_avg_y * new_chunk_modifier | ||
| ) | ||
| self.num_items += new_chunk_len | ||
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| def get_bbox_center(table: pa.Table) -> Tuple[Bbox, WeightedCentroid]: | ||
| """Get the bounding box and geometric (weighted) center of the geometries in the | ||
| table.""" | ||
| geom_col_idx = get_geometry_column_index(table.schema) | ||
| geom_col = table.column(geom_col_idx) | ||
| extension_type_name = table.schema.field(geom_col_idx).metadata[ | ||
| b"ARROW:extension:name" | ||
| ] | ||
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| if extension_type_name == b"geoarrow.point": | ||
| return _get_bbox_center_nest_0(geom_col) | ||
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| if extension_type_name in [b"geoarrow.linestring", b"geoarrow.multipoint"]: | ||
| return _get_bbox_center_nest_1(geom_col) | ||
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| if extension_type_name in [b"geoarrow.polygon", b"geoarrow.multilinestring"]: | ||
| return _get_bbox_center_nest_2(geom_col) | ||
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| if extension_type_name == b"geoarrow.multipolygon": | ||
| return _get_bbox_center_nest_3(geom_col) | ||
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| assert False | ||
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| def _coords_bbox(arr: pa.FixedSizeListArray) -> Bbox: | ||
| np_arr = arr.flatten().to_numpy().reshape(-1, arr.type.list_size) | ||
| min_vals = np.min(np_arr, axis=0) | ||
| max_vals = np.max(np_arr, axis=0) | ||
| return Bbox(minx=min_vals[0], miny=min_vals[1], maxx=max_vals[0], maxy=max_vals[1]) | ||
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| def _get_bbox_center_nest_0(column: pa.ChunkedArray) -> Tuple[Bbox, WeightedCentroid]: | ||
| bbox = Bbox() | ||
| centroid = WeightedCentroid() | ||
| for chunk in column.chunks: | ||
| coords = chunk | ||
| bbox.update(_coords_bbox(coords)) | ||
| centroid.update(coords) | ||
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| return (bbox, centroid) | ||
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| def _get_bbox_center_nest_1(column: pa.ChunkedArray) -> Tuple[Bbox, WeightedCentroid]: | ||
| bbox = Bbox() | ||
| centroid = WeightedCentroid() | ||
| for chunk in column.chunks: | ||
| coords = chunk.flatten() | ||
| bbox.update(_coords_bbox(coords)) | ||
| centroid.update(coords) | ||
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| return (bbox, centroid) | ||
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| def _get_bbox_center_nest_2(column: pa.ChunkedArray) -> Tuple[Bbox, WeightedCentroid]: | ||
| bbox = Bbox() | ||
| centroid = WeightedCentroid() | ||
| for chunk in column.chunks: | ||
| coords = chunk.flatten().flatten() | ||
| bbox.update(_coords_bbox(coords)) | ||
| centroid.update(coords) | ||
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| return (bbox, centroid) | ||
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| def _get_bbox_center_nest_3(column: pa.ChunkedArray) -> Tuple[Bbox, WeightedCentroid]: | ||
| bbox = Bbox() | ||
| centroid = WeightedCentroid() | ||
| for chunk in column.chunks: | ||
| coords = chunk.flatten().flatten().flatten() | ||
| bbox.update(_coords_bbox(coords)) | ||
| centroid.update(coords) | ||
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| return (bbox, centroid) | ||
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| def bbox_to_zoom_level(bbox: Bbox) -> int: | ||
| """Computes the zoom level of a bounding box | ||
| This is copied from pydeck: https://github.com/visgl/deck.gl/blob/63728ecbdaa2f99811900ec3709e5df0f9f8d228/bindings/pydeck/pydeck/data_utils/viewport_helpers.py#L125C1-L149C22 | ||
| Returns: | ||
| Zoom level of map in a WGS84 Mercator projection | ||
| """ | ||
| lat_diff = max(bbox.miny, bbox.maxy) - min(bbox.miny, bbox.maxy) | ||
| lng_diff = max(bbox.minx, bbox.maxx) - min(bbox.minx, bbox.maxx) | ||
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| max_diff = max(lng_diff, lat_diff) | ||
| zoom_level = None | ||
| if max_diff < (360.0 / math.pow(2, 20)): | ||
| zoom_level = 21 | ||
| else: | ||
| zoom_level = int( | ||
| -1 | ||
| * ((math.log(max_diff) / math.log(2.0)) - (math.log(360.0) / math.log(2))) | ||
| ) | ||
| if zoom_level < 1: | ||
| zoom_level = 1 | ||
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| return zoom_level | ||
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| def compute_view(table: pa.Table): | ||
| """Automatically computes a view state for the data passed in.""" | ||
| bbox, center = get_bbox_center(table) | ||
| zoom = bbox_to_zoom_level(bbox) | ||
| return {"longitude": center.x, "latitude": center.y, "zoom": zoom} |
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