momepy API reference

elements

Blocks(tessellation, edges, buildings, ...)	Generate blocks based on buildings, tessellation, and street network.
buffered_limit(gdf[, buffer])	Define limit for momepy.Tessellation as a buffer around buildings.
COINS(edge_gdf[, angle_threshold])	Calculates natural continuity and hierarchy of street networks in a given GeoDataFrame using the COINS algorithm.
enclosures(primary_barriers[, limit, ...])	Generate enclosures based on passed barriers.
get_network_id(left, right, network_id[, ...])	Snap each element (preferably building) to the closest street network segment and save its ID.
get_network_ratio(df, edges[, initial_buffer])	Link polygons to network edges based on the proportion of overlap (if a cell intersects more than one edge).
get_node_id(objects, nodes, edges, node_id)	Snap each building to the closest street network node on the closest network edge.
Tessellation(gdf, unique_id[, limit, ...])	Generates tessellation.

dimension

Area(gdf)	Calculates the area of each object in a given GeoDataFrame.
AverageCharacter(gdf, values, ...[, rng, ...])	Calculates the average of a character within a set neighbourhood defined in spatial_weights.
CourtyardArea(gdf[, areas])	Calculates area of holes within geometry - area of courtyards.
CoveredArea(gdf, spatial_weights, unique_id)	Calculates the area covered by neighbours, which is total area covered by neighbours defined in spatial_weights and the element itself.
FloorArea(gdf, heights[, areas])	Calculates floor area of each object based on height and area.
LongestAxisLength(gdf)	Calculates the length of the longest axis of object.
Perimeter(gdf)	Calculates perimeter of each object in a given GeoDataFrame.
PerimeterWall(gdf[, spatial_weights, verbose])	Calculate the perimeter wall length of the joined structure.
SegmentsLength(gdf[, spatial_weights, mean, ...])	Calculate the cummulative and/or mean length of segments.
StreetProfile(left, right[, heights, ...])	Calculates the street profile characters.
Volume(gdf, heights[, areas])	Calculates the volume of each object in a given GeoDataFrame based on its height and area.
WeightedCharacter(gdf, values, ...[, areas, ...])	Calculates the weighted character.

shape

CentroidCorners(gdf[, verbose])	Calculates the mean distance centroid - corners and standard deviation.
CircularCompactness(gdf[, areas])	Calculates the compactness index of each object in a given GeoDataFrame.
CompactnessWeightedAxis(gdf[, areas, ...])	Calculates the compactness-weighted axis of each object in a given GeoDataFrame.
Convexity(gdf[, areas])	Calculates the Convexity index of each object in a given GeoDataFrame.
Corners(gdf[, verbose])	Calculates the number of corners of each object in a given GeoDataFrame.
CourtyardIndex(gdf, courtyard_areas[, areas])	Calculates the courtyard index of each object in a given GeoDataFrame.
Elongation(gdf)	Calculates the elongation of each object seen as elongation of its minimum bounding rectangle.
EquivalentRectangularIndex(gdf[, areas, ...])	Calculates the equivalent rectangular index of each object in a given GeoDataFrame.
FormFactor(gdf, volumes[, areas, heights])	Calculates the form factor of each object in a given GeoDataFrame.
FractalDimension(gdf[, areas, perimeters])	Calculates fractal dimension of each object in given GeoDataFrame.
Linearity(gdf)	Calculates the linearity of each LineString object in a given GeoDataFrame.
Rectangularity(gdf[, areas])	Calculates the rectangularity of each object in a given GeoDataFrame.
ShapeIndex(gdf, longest_axis[, areas])	Calculates the shape index of each object in a given GeoDataFrame.
SquareCompactness(gdf[, areas, perimeters])	Calculates the compactness index of each object in a given GeoDataFrame.
Squareness(gdf[, verbose])	Calculates the squareness of each object in a given GeoDataFrame.
VolumeFacadeRatio(gdf, heights[, volumes, ...])	Calculates the volume/facade ratio of each object in a given GeoDataFrame.

spatial distribution

Alignment(gdf, spatial_weights, unique_id, ...)	Calculate the mean deviation of solar orientation of objects on adjacent cells from an object.
BuildingAdjacency(gdf, ...[, ...])	Calculate the level of building adjacency.
CellAlignment(left, right, ...)	Calculate the difference between cell orientation and the orientation of object.
MeanInterbuildingDistance(gdf, ...[, order, ...])	Calculate the mean interbuilding distance.
NeighborDistance(gdf, spatial_weights, unique_id)	Calculate the mean distance to adjacent buildings (based on spatial_weights).
NeighboringStreetOrientationDeviation(gdf)	Calculate the mean deviation of solar orientation of adjacent streets.
Neighbors(gdf, spatial_weights, unique_id[, ...])	Calculate the number of neighbours captured by spatial_weights.
Orientation(gdf[, verbose])	Calculate the orientation of object.
SharedWalls(gdf)	Calculate the length of shared walls of adjacent elements (typically buildings).
SharedWallsRatio(gdf[, perimeters])	Calculate shared walls ratio of adjacent elements (typically buildings).
StreetAlignment(left, right, orientations[, ...])	Calculate the difference between street orientation and orientation of another object in degrees.

intensity

AreaRatio(left, right, left_areas, right_areas)	Calculate covered area ratio or floor area ratio of objects.
BlocksCount(gdf, block_id, spatial_weights, ...)	Calculates the weighted number of blocks.
Count(left, right, left_id, right_id[, weighted])	Calculate the number of elements within an aggregated structure.
Courtyards(gdf[, spatial_weights, verbose])	Calculate the number of courtyards within the joined structure.
Density(gdf, values, spatial_weights, unique_id)	Calculate the gross density.
NodeDensity(left, right, spatial_weights[, ...])	Calculate the density of nodes neighbours on street network defined in spatial_weights.
Reached(left, right, left_id, right_id[, ...])	Calculates the number of objects reached within neighbours on a street network.

graph

betweenness_centrality(graph[, name, mode, ...])	Calculates the shortest-path betweenness centrality for nodes.
cds_length(graph[, radius, mode, name, ...])	Calculates length of cul-de-sacs for subgraph around each node if radius is set, or for whole graph, if radius=None.
closeness_centrality(graph[, name, weight, ...])	Calculates the closeness centrality for nodes.
clustering(graph[, name])	Calculates the squares clustering coefficient for nodes.
cyclomatic(graph[, radius, name, distance, ...])	Calculates cyclomatic complexity for subgraph around each node if radius is set, or for whole graph, if radius=None.
edge_node_ratio(graph[, radius, name, ...])	Calculates edge / node ratio for subgraph around each node if radius is set, or for whole graph, if radius=None.
gamma(graph[, radius, name, distance, verbose])	Calculates connectivity gamma index for subgraph around each node if radius is set, or for whole graph, if radius=None.
mean_node_degree(graph[, radius, name, ...])	Calculates mean node degree for subgraph around each node if radius is set, or for whole graph, if radius=None.
mean_node_dist(graph[, name, length, verbose])	Calculates mean distance to neighbouring nodes.
mean_nodes(graph, attr)	Calculates mean value of nodes attr for each edge.
meshedness(graph[, radius, name, distance, ...])	Calculates meshedness for subgraph around each node if radius is set, or for whole graph, if radius=None.
node_degree(graph[, name])	Calculates node degree for each node.
proportion(graph[, radius, three, four, ...])	Calculates the proportion of intersection types for subgraph around each node if radius is set, or for whole graph, if radius=None.
straightness_centrality(graph[, weight, ...])	Calculates the straightness centrality for nodes.
subgraph(graph[, radius, distance, ...])	Calculates all subgraph-based characters.

diversity

Gini(gdf, values, spatial_weights, unique_id)	Calculates the Gini index of values within neighbours defined in spatial_weights.
Percentiles(gdf, values, spatial_weights, ...)	Calculates the percentiles of values within neighbours defined in spatial_weights.
Range(gdf, values, spatial_weights, unique_id)	Calculates the range of values within neighbours defined in spatial_weights.
Shannon(gdf, values, spatial_weights, unique_id)	Calculates the Shannon index of values within neighbours defined in spatial_weights.
Simpson(gdf, values, spatial_weights, unique_id)	Calculates the Simpson's diversity index of values within neighbours defined in spatial_weights.
Theil(gdf, values, spatial_weights, unique_id)	Calculates the Theil measure of inequality of values within neighbours defined in spatial_weights.
Unique(gdf, values, spatial_weights, unique_id)	Calculates the number of unique values within neighbours defined in spatial_weights.
shannon_diversity(data[, bins, categorical, ...])	Calculates the Shannon's diversity index of data.
simpson_diversity(values[, bins, categorical])	Calculates the Simpson's diversity index of data.

spatial weights

DistanceBand(gdf, threshold[, centroid, ids])	On demand distance-based spatial weights-like class.
sw_high(k[, gdf, weights, ids, contiguity, ...])	Generate spatial weights based on Queen or Rook contiguity of order k.

preprocessing

close_gaps(gdf, tolerance)	Close gaps in LineString geometry where it should be contiguous.
CheckTessellationInput(gdf[, shrink, ...])	Check input data for Tessellation for potential errors.
extend_lines(gdf, tolerance[, target, ...])	Extends lines from gdf to itself or target within a set tolerance
FaceArtifacts(gdf[, index, height_mins, ...])	Identify face artifacts in street networks
remove_false_nodes(gdf)	Clean topology of existing LineString geometry by removal of nodes of degree 2.
preprocess(buildings[, size, compactness, ...])	Preprocesses building geometry to eliminate additional structures being single features.
roundabout_simplification(edges[, polys, ...])	Selects the roundabouts from polys to create a center point to merge all incoming edges.

utilities

gdf_to_nx(gdf_network[, approach, length, ...])	Convert a LineString GeoDataFrame to a networkx.MultiGraph or other Graph as per specification.
limit_range(vals, rng)	Extract values within selected range.
nx_to_gdf(net[, points, lines, ...])	Convert a networkx.Graph to a LineString GeoDataFrame and Point GeoDataFrame.
unique_id(objects)	Add an attribute with a unique ID to each row of a GeoDataFrame.

previous

Examples

next

momepy.Blocks