From ce6414fe73ec1bb142a0bc82c1c3525884049d27 Mon Sep 17 00:00:00 2001 From: Mika Sorvoja <134925837+msorvoja@users.noreply.github.com> Date: Fri, 15 Nov 2024 15:58:50 +0200 Subject: [PATCH] perf, build(vector_processing): add optimized version of distance computation (#455) * add dependency: Numba * improve documentation * comment out the old implementation Note: distance_to_anomaly, proximity_computation and proximity_to_anomaly all benefit from this optimization --------- Co-authored-by: Niko Aarnio --- .../vector_processing/distance_computation.py | 301 +++++++++++++++--- environment.yml | 1 + poetry.lock | 152 +++++---- pyproject.toml | 1 + 4 files changed, 356 insertions(+), 99 deletions(-) diff --git a/eis_toolkit/vector_processing/distance_computation.py b/eis_toolkit/vector_processing/distance_computation.py index c18722d4..4b7476d5 100644 --- a/eis_toolkit/vector_processing/distance_computation.py +++ b/eis_toolkit/vector_processing/distance_computation.py @@ -4,25 +4,32 @@ import numpy as np from beartype import beartype from beartype.typing import Optional, Union +from numba import njit, prange from rasterio import profiles, transform -from shapely.geometry.base import BaseGeometry, BaseMultipartGeometry -from eis_toolkit.exceptions import EmptyDataFrameException, NonMatchingCrsException, NumericValueSignException +from eis_toolkit import exceptions from eis_toolkit.utilities.checks.raster import check_raster_profile -from eis_toolkit.utilities.miscellaneous import row_points @beartype def distance_computation( geodataframe: gpd.GeoDataFrame, raster_profile: Union[profiles.Profile, dict], max_distance: Optional[Number] = None ) -> np.ndarray: - """Calculate distance from raster cell to nearest geometry. + """ + Calculate distance from each raster cell (centre) to the nearest input geometry. + + Pixels on top of input geometries are assigned distance of 0. + + Uses Numba to perform calculations quickly. The computation time increases (roughly) + linearly with the amount of raster pixels defined by given `raster_profile`. Supports + Polygon, MultiPolygon, LineString, MultiLineString, Point and MultiPoint geometries. Args: geodataframe: The GeoDataFrame with geometries to determine distance to. raster_profile: The raster profile of the raster in which the distances to the nearest geometry are determined. - max_distance: The maximum distance in the output array. + max_distance: The maximum distance in the output array. Pixels beyond this + distance will be assigned `max_distance` value. Returns: A 2D numpy array with the distances computed. @@ -30,13 +37,16 @@ def distance_computation( Raises: NonMatchingCrsException: The input raster profile and geodataframe have mismatching CRS. EmptyDataFrameException: The input geodataframe is empty. + NumericValueSignException: Max distance is defined and is not a positive number. """ if raster_profile.get("crs") != geodataframe.crs: - raise NonMatchingCrsException("Expected coordinate systems to match between raster and GeoDataFrame.") - if geodataframe.shape[0] == 0: - raise EmptyDataFrameException("Expected GeoDataFrame to not be empty.") + raise exceptions.NonMatchingCrsException( + "Expected coordinate systems to match between raster and GeoDataFrame." + ) + if geodataframe.empty: + raise exceptions.EmptyDataFrameException("Expected GeoDataFrame to not be empty.") if max_distance is not None and max_distance <= 0: - raise NumericValueSignException("Expected max distance to be a positive number.") + raise exceptions.NumericValueSignException("Expected max distance to be a positive number.") check_raster_profile(raster_profile=raster_profile) @@ -44,49 +54,254 @@ def distance_computation( raster_height = raster_profile.get("height") raster_transform = raster_profile.get("transform") - distance_matrix = _distance_computation( - raster_width=raster_width, - raster_height=raster_height, - raster_transform=raster_transform, - geodataframe=geodataframe, + # Generate the grid of raster cell center points + raster_points = _generate_raster_points(raster_width, raster_height, raster_transform) + + # Initialize lists needed for Numba-compatible calculations + segment_coords = [] # These will also contain points coords, if present + segment_indices = [0] # Start index + polygon_coords = [] + polygon_indices = [0] # Start index + + for geometry in geodataframe.geometry: + if geometry.geom_type == "Polygon": + coords = list(geometry.exterior.coords) + for x, y in coords: + polygon_coords.extend([x, y]) + polygon_indices.append(len(polygon_coords) // 2) + segments = [ + (coords[i][0], coords[i][1], coords[i + 1][0], coords[i + 1][1]) for i in range(len(coords) - 1) + ] + + elif geometry.geom_type == "MultiPolygon": + # For MultiPolygon, iterate over each polygon + segments = [] + for poly in geometry.geoms: + coords = list(poly.exterior.coords) + for x, y in coords: + polygon_coords.extend([x, y]) + polygon_indices.append(len(polygon_coords) // 2) + + # Add polygon boundary as segments for distance calculations + segments.extend( + [(coords[i][0], coords[i][1], coords[i + 1][0], coords[i + 1][1]) for i in range(len(coords) - 1)] + ) + + elif geometry.geom_type == "LineString": + coords = list(geometry.coords) + segments = [ + (coords[i][0], coords[i][1], coords[i + 1][0], coords[i + 1][1]) for i in range(len(coords) - 1) + ] + + elif geometry.geom_type == "MultiLineString": + # For MultiLineString, iterate through each line string component + segments = [] + for line in geometry.geoms: + coords = list(line.coords) + segments.extend( + [(coords[i][0], coords[i][1], coords[i + 1][0], coords[i + 1][1]) for i in range(len(coords) - 1)] + ) + + elif geometry.geom_type == "Point": + segments = [(geometry.x, geometry.y)] + + elif geometry.geom_type == "MultiPoint": + # For MultiPoint, iterate over each point and add as individual (x, y) tuples + segments = [(point.x, point.y) for point in geometry.geoms] + + else: + raise exceptions.GeometryTypeException(f"Encountered unsupported geometry type: {geometry.geom_type}.") + + segment_coords.extend(segments) + segment_indices.append(len(segment_coords)) # End index for this geometry's segments + + # Convert all lists to numpy arrays + segment_coords = np.array(segment_coords, dtype=np.float64) + segment_indices = np.array(segment_indices, dtype=np.int64) + polygon_coords = np.array(polygon_coords, dtype=np.float64) + polygon_indices = np.array(polygon_indices, dtype=np.int64) + + distance_matrix = _compute_distances_core( + raster_points, + segment_coords, + segment_indices, + polygon_coords, + polygon_indices, + raster_width, + raster_height, + max_distance, ) - if max_distance is not None: - distance_matrix[distance_matrix > max_distance] = max_distance return distance_matrix -def _calculate_row_distances( - row: int, - cols: np.ndarray, - raster_transform: transform.Affine, - geometries_unary_union: Union[BaseGeometry, BaseMultipartGeometry], +@njit(parallel=True) +def _compute_distances_core( + raster_points: np.ndarray, + segment_coords: np.ndarray, + segment_indices: np.ndarray, + polygon_coords: np.ndarray, + polygon_indices: np.ndarray, + width: int, + height: int, + max_distance: Optional[Number], ) -> np.ndarray: - row_distances = np.array( - [ - point.distance(geometries_unary_union) - for point in row_points(row=row, cols=cols, raster_transform=raster_transform) - ] - ) - return row_distances + distance_matrix = np.full((height, width), np.inf) + for i in prange(len(raster_points)): + px, py = raster_points[i] + min_dist = np.inf + # Check if the point is inside any polygon, if polygons are present + if len(polygon_indices) > 1 and _point_in_polygon(px, py, polygon_coords, polygon_indices): + min_dist = 0 # Set distance to zero if point is inside a polygon + else: + # Only calculate distance to segments if point is outside all polygons + for j in range(len(segment_indices) - 1): + for k in range(segment_indices[j], segment_indices[j + 1]): + # Case 1: Point + if len(segment_coords[k]) == 2: + x1, y1 = segment_coords[k] + dist = np.sqrt((px - x1) ** 2 + (py - y1) ** 2) + # Case 2: Line segment + else: + x1, y1, x2, y2 = segment_coords[k] + dist = _point_to_segment_distance(px, py, x1, y1, x2, y2) + if dist < min_dist: + min_dist = dist -def _distance_computation( - raster_width: int, raster_height: int, raster_transform: transform.Affine, geodataframe: gpd.GeoDataFrame -) -> np.ndarray: + # Apply max_distance threshold if specified + if max_distance is not None: + min_dist = min(min_dist, max_distance) - cols = np.arange(raster_width) - rows = np.arange(raster_height) + # Update the distance matrix + distance_matrix[i // width, i % width] = min_dist + return distance_matrix - geometries_unary_union = geodataframe.geometry.unary_union - distance_matrix = np.array( - [ - _calculate_row_distances( - row=row, cols=cols, raster_transform=raster_transform, geometries_unary_union=geometries_unary_union - ) - for row in rows - ] - ) +def _generate_raster_points(width: int, height: int, affine_transform: transform.Affine) -> np.ndarray: + """Generate a full grid of points from the raster dimensions and affine transform.""" + cols, rows = np.meshgrid(np.arange(width), np.arange(height)) + cols = cols.ravel() + rows = rows.ravel() + xs, ys = transform.xy(affine_transform, rows, cols, offset="center") + return np.column_stack([xs, ys]) - return distance_matrix + +@njit +def _point_to_segment_distance(px: Number, py: Number, x1: Number, y1: Number, x2: Number, y2: Number) -> np.ndarray: + """Calculate the minimum distance from a point to a line segment.""" + dx, dy = x2 - x1, y2 - y1 + if dx == 0 and dy == 0: + # Segment is a point (Should not happen) + return np.sqrt((px - x1) ** 2 + (py - y1) ** 2) + t = max(0, min(1, ((px - x1) * dx + (py - y1) * dy) / (dx * dx + dy * dy))) + nearest_x, nearest_y = x1 + t * dx, y1 + t * dy + return np.sqrt((px - nearest_x) ** 2 + (py - nearest_y) ** 2) + + +@njit +def _point_in_polygon(px: Number, py: Number, polygon_coords: np.ndarray, polygon_indices: np.ndarray) -> bool: + """Determine if a point is inside any polygon using the ray-casting algorithm.""" + for p_start, p_end in zip(polygon_indices[:-1], polygon_indices[1:]): + inside = False + xints = 0.0 + n = p_end - p_start + p1x, p1y = polygon_coords[2 * p_start], polygon_coords[2 * p_start + 1] + for i in range(n + 1): + p2x, p2y = polygon_coords[2 * (p_start + i % n)], polygon_coords[2 * (p_start + i % n) + 1] + if py > min(p1y, p2y): + if py <= max(p1y, p2y): + if px <= max(p1x, p2x): + if p1y != p2y: + xints = (py - p1y) * (p2x - p1x) / (p2y - p1y) + p1x + if p1x == p2x or px <= xints: + inside = not inside + p1x, p1y = p2x, p2y + if inside: + return True + return False + + +# @beartype +# def distance_computation( +# geodataframe: gpd.GeoDataFrame, +# raster_profile: Union[profiles.Profile, dict], +# max_distance: Optional[Number] = None +# ) -> np.ndarray: +# """Calculate distance from raster cell to nearest geometry. + +# Args: +# geodataframe: The GeoDataFrame with geometries to determine distance to. +# raster_profile: The raster profile of the raster in which the distances +# to the nearest geometry are determined. +# max_distance: The maximum distance in the output array. + +# Returns: +# A 2D numpy array with the distances computed. + +# Raises: +# NonMatchingCrsException: The input raster profile and geodataframe have mismatching CRS. +# EmptyDataFrameException: The input geodataframe is empty. +# NumericValueSignException: Max distance is defined and is not a positive number. +# """ +# if raster_profile.get("crs") != geodataframe.crs: +# raise exceptions.NonMatchingCrsException( +# "Expected coordinate systems to match between raster and GeoDataFrame." +# ) +# if geodataframe.shape[0] == 0: +# raise exceptions.EmptyDataFrameException("Expected GeoDataFrame to not be empty.") +# if max_distance is not None and max_distance <= 0: +# raise exceptions.NumericValueSignException("Expected max distance to be a positive number.") + +# check_raster_profile(raster_profile=raster_profile) + +# raster_width = raster_profile.get("width") +# raster_height = raster_profile.get("height") +# raster_transform = raster_profile.get("transform") + +# distance_matrix = _distance_computation( +# raster_width=raster_width, +# raster_height=raster_height, +# raster_transform=raster_transform, +# geodataframe=geodataframe, +# ) +# if max_distance is not None: +# distance_matrix[distance_matrix > max_distance] = max_distance + +# return distance_matrix + + +# def _calculate_row_distances( +# row: int, +# cols: np.ndarray, +# raster_transform: transform.Affine, +# geometries_unary_union: Union[BaseGeometry, BaseMultipartGeometry], +# ) -> np.ndarray: +# row_distances = np.array( +# [ +# point.distance(geometries_unary_union) +# for point in row_points(row=row, cols=cols, raster_transform=raster_transform) +# ] +# ) +# return row_distances + + +# def _distance_computation( +# raster_width: int, raster_height: int, raster_transform: transform.Affine, geodataframe: gpd.GeoDataFrame +# ) -> np.ndarray: + +# cols = np.arange(raster_width) +# rows = np.arange(raster_height) + +# geometries_unary_union = geodataframe.geometry.unary_union + +# distance_matrix = np.array( +# [ +# _calculate_row_distances( +# row=row, cols=cols, raster_transform=raster_transform, geometries_unary_union=geometries_unary_union +# ) +# for row in rows +# ] +# ) + +# return distance_matrix diff --git a/environment.yml b/environment.yml index ac852f80..00f52faf 100755 --- a/environment.yml +++ b/environment.yml @@ -22,5 +22,6 @@ dependencies: - imbalanced-learn >= 0.11.0 - mapclassify >= 2.6.1 - esda >= 2.5.1 + - numba >= 0.60.0 # Dependencies for testing - pytest >=7.2.1 diff --git a/poetry.lock b/poetry.lock index ab321a95..ed0272e4 100755 --- a/poetry.lock +++ b/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.6.1 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.4 and should not be changed by hand. 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