.. _manual: ======================= The Shapely User Manual ======================= :Author: Sean Gillies, :Version: |release| :Date: |today| :Copyright: This work is licensed under a `Creative Commons Attribution 3.0 United States License`__. .. __: https://creativecommons.org/licenses/by/3.0/us/ :Abstract: This document explains how to use the Shapely Python package for computational geometry. .. _intro: Introduction ============ Deterministic spatial analysis is an important component of computational approaches to problems in agriculture, ecology, epidemiology, sociology, and many other fields. What is the surveyed perimeter/area ratio of these patches of animal habitat? Which properties in this town intersect with the 50-year flood contour from this new flooding model? What are the extents of findspots for ancient ceramic wares with maker's marks "A" and "B", and where do the extents overlap? What's the path from home to office that best skirts identified zones of location based spam? These are just a few of the possible questions addressable using non-statistical spatial analysis, and more specifically, computational geometry. Shapely is a Python package for set-theoretic analysis and manipulation of planar features using functions from the well known and widely deployed GEOS_ library. GEOS, a port of the `Java Topology Suite`_ (JTS), is the geometry engine of the PostGIS_ spatial extension for the PostgreSQL RDBMS. The designs of JTS and GEOS are largely guided by the `Open Geospatial Consortium`_'s Simple Features Access Specification [1]_ and Shapely adheres mainly to the same set of standard classes and operations. Shapely is thereby deeply rooted in the conventions of the geographic information systems (GIS) world, but aspires to be equally useful to programmers working on non-conventional problems. The first premise of Shapely is that Python programmers should be able to perform PostGIS type geometry operations outside of an RDBMS. Not all geographic data originate or reside in a RDBMS or are best processed using SQL. We can load data into a spatial RDBMS to do work, but if there's no mandate to manage (the "M" in "RDBMS") the data over time in the database we're using the wrong tool for the job. The second premise is that the persistence, serialization, and map projection of features are significant, but orthogonal problems. You may not need a hundred GIS format readers and writers or the multitude of State Plane projections, and Shapely doesn't burden you with them. The third premise is that Python idioms trump GIS (or Java, in this case, since the GEOS library is derived from JTS, a Java project) idioms. If you enjoy and profit from idiomatic Python, appreciate packages that do one thing well, and agree that a spatially enabled RDBMS is often enough the wrong tool for your computational geometry job, Shapely might be for you. .. _intro-spatial-data-model: Spatial Data Model ------------------ The fundamental types of geometric objects implemented by Shapely are points, curves, and surfaces. Each is associated with three sets of (possibly infinite) points in the plane. The `interior`, `boundary`, and `exterior` sets of a feature are mutually exclusive and their union coincides with the entire plane [2]_. * A `Point` has an `interior` set of exactly one point, a `boundary` set of exactly no points, and an `exterior` set of all other points. A `Point` has a topological dimension of 0. * A `Curve` has an `interior` set consisting of the infinitely many points along its length (imagine a `Point` dragged in space), a `boundary` set consisting of its two end points, and an `exterior` set of all other points. A `Curve` has a topological dimension of 1. * A `Surface` has an `interior` set consisting of the infinitely many points within (imagine a `Curve` dragged in space to cover an area), a `boundary` set consisting of one or more `Curves`, and an `exterior` set of all other points including those within holes that might exist in the surface. A `Surface` has a topological dimension of 2. That may seem a bit esoteric, but will help clarify the meanings of Shapely's spatial predicates, and it's as deep into theory as this manual will go. Consequences of point-set theory, including some that manifest themselves as "gotchas", for different classes will be discussed later in this manual. The point type is implemented by a `Point` class; curve by the `LineString` and `LinearRing` classes; and surface by a `Polygon` class. Shapely implements no smooth (`i.e.` having continuous tangents) curves. All curves must be approximated by linear splines. All rounded patches must be approximated by regions bounded by linear splines. Collections of points are implemented by a `MultiPoint` class, collections of curves by a `MultiLineString` class, and collections of surfaces by a `MultiPolygon` class. These collections aren't computationally significant, but are useful for modeling certain kinds of features. A Y-shaped line feature, for example, is well modeled as a whole by a `MultiLineString`. The standard data model has additional constraints specific to certain types of geometric objects that will be discussed in following sections of this manual. See also https://web.archive.org/web/20160719195511/http://www.vividsolutions.com/jts/discussion.htm for more illustrations of this data model. .. _intro-relationships: Relationships ------------- The spatial data model is accompanied by a group of natural language relationships between geometric objects – `contains`, `intersects`, `overlaps`, `touches`, etc. – and a theoretical framework for understanding them using the 3x3 matrix of the mutual intersections of their component point sets [3]_: the DE-9IM. A comprehensive review of the relationships in terms of the DE-9IM is found in [4]_ and will not be reiterated in this manual. .. _intro-operations: Operations ---------- Following the JTS technical specs [5]_, this manual will make a distinction between constructive (`buffer`, `convex hull`) and set-theoretic operations (`intersection`, `union`, etc.). The individual operations will be fully described in a following section of the manual. .. _intro-coordinate-systems: Coordinate Systems ------------------ Even though the Earth is not flat – and for that matter not exactly spherical – there are many analytic problems that can be approached by transforming Earth features to a Cartesian plane, applying tried and true algorithms, and then transforming the results back to geographic coordinates. This practice is as old as the tradition of accurate paper maps. Shapely does not support coordinate system transformations. All operations on two or more features presume that the features exist in the same Cartesian plane. .. _objects: Geometric Objects ================= Geometric objects are created in the typical Python fashion, using the classes themselves as instance factories. A few of their intrinsic properties will be discussed in this sections, others in the following sections on operations and serializations. Instances of ``Point``, ``LineString``, and ``LinearRing`` have as their most important attribute a finite sequence of coordinates that determines their interior, boundary, and exterior point sets. A line string can be determined by as few as 2 points, but contains an infinite number of points. Coordinate sequences are immutable. A third `z` coordinate value may be used when constructing instances, but has no effect on geometric analysis. All operations are performed in the `x-y` plane. In all constructors, numeric values are converted to type ``float``. In other words, ``Point(0, 0)`` and ``Point(0.0, 0.0)`` produce geometrically equivalent instances. Shapely does not check the topological simplicity or validity of instances when they are constructed as the cost is unwarranted in most cases. Validating factories are easily implemented using the :attr:``is_valid`` predicate by users that require them. .. note:: Shapely is a planar geometry library and `z`, the height above or below the plane, is ignored in geometric analysis. There is a potential pitfall for users here: coordinate tuples that differ only in `z` are not distinguished from each other and their application can result in surprisingly invalid geometry objects. For example, ``LineString([(0, 0, 0), (0, 0, 1)])`` does not return a vertical line of unit length, but an invalid line in the plane with zero length. Similarly, ``Polygon([(0, 0, 0), (0, 0, 1), (1, 1, 1)])`` is not bounded by a closed ring and is invalid. General Attributes and Methods ------------------------------ .. attribute:: object.area Returns the area (``float``) of the object. .. attribute:: object.bounds Returns a ``(minx, miny, maxx, maxy)`` tuple (``float`` values) that bounds the object. .. attribute:: object.length Returns the length (``float``) of the object. .. attribute:: object.minimum_clearance Returns the smallest distance by which a node could be moved to produce an invalid geometry. This can be thought of as a measure of the robustness of a geometry, where larger values of minimum clearance indicate a more robust geometry. If no minimum clearance exists for a geometry, such as a point, this will return `math.infinity`. `New in Shapely 1.7.1` .. code-block:: pycon >>> from shapely import Polygon >>> Polygon([[0, 0], [1, 0], [1, 1], [0, 1], [0, 0]]).minimum_clearance 1.0 .. attribute:: object.geom_type Returns a string specifying the `Geometry Type` of the object in accordance with [1]_. .. code-block:: pycon >>> from shapely import Point, LineString >>> Point(0, 0).geom_type 'Point' .. method:: object.distance(other) Returns the minimum distance (``float``) to the `other` geometric object. .. code-block:: pycon >>> Point(0,0).distance(Point(1,1)) 1.4142135623730951 .. method:: object.hausdorff_distance(other) Returns the Hausdorff distance (``float``) to the `other` geometric object. The Hausdorff distance between two geometries is the furthest distance that a point on either geometry can be from the nearest point to it on the other geometry. `New in Shapely 1.6.0` .. code-block:: pycon >>> point = Point(1, 1) >>> line = LineString([(2, 0), (2, 4), (3, 4)]) >>> point.hausdorff_distance(line) 3.605551275463989 >>> point.distance(Point(3, 4)) 3.605551275463989 .. method:: object.representative_point() Returns a cheaply computed point that is guaranteed to be within the geometric object. .. note:: This is not in general the same as the centroid. .. code-block:: pycon >>> diamond = Point(0, 0).buffer(2.0, 1).difference(Point(0, 0).buffer(1.0, 1)) >>> diamond.centroid >>> diamond.representative_point() .. _points: Points ------ .. class:: Point(coordinates) The `Point` constructor takes positional coordinate values or point tuple parameters. .. code-block:: pycon >>> from shapely import Point >>> point = Point(0.0, 0.0) >>> q = Point((0.0, 0.0)) A `Point` has zero area and zero length. .. code-block:: pycon >>> point.area 0.0 >>> point.length 0.0 Its `x-y` bounding box is a ``(minx, miny, maxx, maxy)`` tuple. .. code-block:: pycon >>> point.bounds (0.0, 0.0, 0.0, 0.0) Coordinate values are accessed via `coords`, `x`, `y`, `z`, and `m` properties. .. code-block:: pycon >>> list(point.coords) [(0.0, 0.0)] >>> point.x 0.0 >>> point.y 0.0 Coordinates may also be sliced. `New in version 1.2.14`. .. code-block:: pycon >>> point.coords[:] [(0.0, 0.0)] When a `Point` instance is passed to the `Point` constructor, it returns a reference to the passed instance. It does not make a copy, as geometry objects are immutable. .. code-block:: pycon >>> Point(point) .. _linestrings: LineStrings ----------- .. class:: LineString(coordinates) The `LineString` constructor takes an ordered sequence of 2 or more ``(x, y[, z])`` point tuples. The constructed `LineString` object represents one or more connected linear splines between the points. Repeated points in the ordered sequence are allowed, but may incur performance penalties and should be avoided. A `LineString` may cross itself (*i.e.* be `complex` and not `simple`). .. plot:: code/linestring.py Figure 1. A simple `LineString` on the left, a complex `LineString` on the right. The (`MultiPoint`) boundary of each is shown in black, the other points that describe the lines are shown in grey. A `LineString` has zero area and non-zero length if it isn't :ref:`empty `. .. code-block:: pycon >>> from shapely import LineString >>> line = LineString([(0, 0), (1, 1)]) >>> line.area 0.0 >>> line.length 1.4142135623730951 Its `x-y` bounding box is a ``(minx, miny, maxx, maxy)`` tuple. .. code-block:: pycon >>> line.bounds (0.0, 0.0, 1.0, 1.0) The defining coordinate values are accessed via the `coords` property. .. code-block:: pycon >>> len(line.coords) 2 >>> list(line.coords) [(0.0, 0.0), (1.0, 1.0)] Coordinates may also be sliced. `New in version 1.2.14`. .. code-block:: pycon >>> line.coords[:] [(0.0, 0.0), (1.0, 1.0)] >>> line.coords[1:] [(1.0, 1.0)] When the constructor is passed another `LineString` instance, a reference to the instance is returned. .. code-block:: pycon >>> LineString(line) A `LineString` may also be constructed using a sequence of mixed `Point` instances or coordinate tuples. The individual coordinates are copied into the new object. .. code-block:: pycon >>> LineString([Point(0.0, 1.0), (2.0, 3.0), Point(4.0, 5.0)]) .. _linearrings: LinearRings ----------- .. class:: LinearRing(coordinates) The `LinearRing` constructor takes an ordered sequence of ``(x, y[, z])`` point tuples. The sequence may be explicitly closed by passing identical values in the first and last indices. Otherwise, the sequence will be implicitly closed by copying the first tuple to the last index. As with a `LineString`, repeated points in the ordered sequence are allowed, but may incur performance penalties and should be avoided. A `LinearRing` may not cross itself, and may not touch itself at a single point. .. plot:: code/linearring.py Figure 2. A valid `LinearRing` on the left, an invalid self-touching `LinearRing` on the right. The points that describe the rings are shown in grey. A ring's boundary is `empty`. .. note:: Shapely will not prevent the creation of such rings, but exceptions will be raised when they are operated on. A `LinearRing` has zero area and non-zero length if it isn't :ref:`empty `. .. code-block:: pycon >>> from shapely import LinearRing >>> ring = LinearRing([(0, 0), (1, 1), (1, 0)]) >>> ring.area 0.0 >>> ring.length 3.414213562373095 Its `x-y` bounding box is a ``(minx, miny, maxx, maxy)`` tuple. .. code-block:: pycon >>> ring.bounds (0.0, 0.0, 1.0, 1.0) Defining coordinate values are accessed via the `coords` property. .. code-block:: pycon >>> len(ring.coords) 4 >>> list(ring.coords) [(0.0, 0.0), (1.0, 1.0), (1.0, 0.0), (0.0, 0.0)] The `LinearRing` constructor also accepts another `LineString` or `LinearRing` instance, returning a new `LinearRing` instance or a reference to the passed instance, respectively. .. code-block:: pycon >>> LinearRing(ring) As with `LineString`, a sequence of `Point` instances is a valid constructor parameter. .. _polygons: Polygons -------- .. class:: Polygon(shell [,holes=None]) The `Polygon` constructor takes two positional parameters. The first is an ordered sequence of ``(x, y[, z])`` point tuples and is treated exactly as in the `LinearRing` case. The second is an optional unordered sequence of ring-like sequences specifying the interior boundaries or "holes" of the feature. Rings of a `valid` `Polygon` may not cross each other, but may touch at a single point only. Again, Shapely will not prevent the creation of invalid features, but when they are operated on the results might be wrong or exceptions might be raised. .. plot:: code/polygon.py Figure 3. On the left, a valid `Polygon` with one interior ring that touches the exterior ring at one point, and on the right a `Polygon` that is `invalid` because its interior ring touches the exterior ring at more than one point. The points that describe the rings are shown in grey. .. plot:: code/polygon2.py Figure 4. On the left, a `Polygon` that is `invalid` because its exterior and interior rings touch along a line, and on the right, a `Polygon` that is `invalid` because its interior rings touch along a line. A `Polygon` has non-zero area and non-zero length if it isn't :ref:`empty `. .. code-block:: pycon >>> from shapely import Polygon >>> polygon = Polygon([(0, 0), (1, 1), (1, 0)]) >>> polygon.area 0.5 >>> polygon.length 3.414213562373095 Its `x-y` bounding box is a ``(minx, miny, maxx, maxy)`` tuple. .. code-block:: pycon >>> polygon.bounds (0.0, 0.0, 1.0, 1.0) Component rings are accessed via `exterior` and `interiors` properties. .. code-block:: pycon >>> list(polygon.exterior.coords) [(0.0, 0.0), (1.0, 1.0), (1.0, 0.0), (0.0, 0.0)] >>> list(polygon.interiors) [] The `Polygon` constructor also accepts instances of `LineString` and `LinearRing`. .. code-block:: pycon >>> coords = [(0, 0), (1, 1), (1, 0)] >>> r = LinearRing(coords) >>> s = Polygon(r) >>> s.area 0.5 >>> t = Polygon(s.buffer(1.0).exterior, [r]) >>> t.area 6.5507620529190325 Rectangular polygons occur commonly, and can be conveniently constructed using the :func:`shapely.geometry.box()` function. .. function:: shapely.geometry.box(minx, miny, maxx, maxy, ccw=True) Makes a rectangular polygon from the provided bounding box values, with counter-clockwise order by default. `New in version 1.2.9`. For example: .. code-block:: pycon >>> from shapely import box >>> b = box(0.0, 0.0, 1.0, 1.0) >>> b >>> list(b.exterior.coords) [(1.0, 0.0), (1.0, 1.0), (0.0, 1.0), (0.0, 0.0), (1.0, 0.0)] This is the first appearance of an explicit polygon handedness in Shapely. To obtain a polygon with a known orientation, use :func:`shapely.geometry.polygon.orient()`: .. function:: shapely.geometry.polygon.orient(polygon, sign=1.0) Returns a new `Polygon` instance with the coordinates of the given polygon in proper orientation. The signed area of the result will have the given sign. A sign of 1.0 means that the coordinates of the product's exterior ring will be oriented counter-clockwise and the interior rings (holes) will be oriented clockwise. `New in version 1.2.10`. .. _collections: Collections ----------- Heterogeneous collections of geometric objects may result from some Shapely operations. For example, two `LineStrings` may intersect along a line and at a point. To represent these kind of results, Shapely provides frozenset_-like, immutable collections of geometric objects. The collections may be homogeneous (`MultiPoint` etc.) or heterogeneous. .. code-block:: python >>> a = LineString([(0, 0), (1, 1), (1,2), (2,2)]) >>> b = LineString([(0, 0), (1, 1), (2,1), (2,2)]) >>> x = a.intersection(b) >>> x >>> list(x.geoms) [, ] .. plot:: code/geometrycollection.py :class: figure Figure 5. a) a green and a yellow line that intersect along a line and at a single point; b) the intersection (in blue) is a collection containing one `LineString` and one `Point`. Members of a `GeometryCollection` are accessed via the ``geoms`` property. .. code-block:: pycon >>> list(x.geoms) [, ] .. note:: When possible, it is better to use one of the homogeneous collection types described below. .. _multipoints: Collections of Points --------------------- .. class:: MultiPoint(points) The `MultiPoint` constructor takes a sequence of ``(x, y[, z ])`` point tuples. A `MultiPoint` has zero area and zero length. .. code-block:: pycon >>> from shapely import MultiPoint >>> points = MultiPoint([(0.0, 0.0), (1.0, 1.0)]) >>> points.area 0.0 >>> points.length 0.0 Its `x-y` bounding box is a ``(minx, miny, maxx, maxy)`` tuple. .. code-block:: pycon >>> points.bounds (0.0, 0.0, 1.0, 1.0) Members of a multi-point collection are accessed via the ``geoms`` property. .. code-block:: pycon >>> list(points.geoms) [, ] The constructor also accepts another `MultiPoint` instance or an unordered sequence of `Point` instances, thereby making copies. .. code-block:: pycon >>> MultiPoint([Point(0, 0), Point(1, 1)]) .. _multilinestrings: Collections of Lines -------------------- .. class:: MultiLineString(lines) The `MultiLineString` constructor takes a sequence of line-like sequences or objects. .. plot:: code/multilinestring.py Figure 6. On the left, a `simple`, disconnected `MultiLineString`, and on the right, a non-simple `MultiLineString`. The points defining the objects are shown in gray, the boundaries of the objects in black. A `MultiLineString` has zero area and non-zero length if it isn't :ref:`empty `. .. code-block:: pycon >>> from shapely import MultiLineString >>> coords = [((0, 0), (1, 1)), ((-1, 0), (1, 0))] >>> lines = MultiLineString(coords) >>> lines.area 0.0 >>> lines.length 3.414213562373095 Its `x-y` bounding box is a ``(minx, miny, maxx, maxy)`` tuple. .. code-block:: pycon >>> lines.bounds (-1.0, 0.0, 1.0, 1.0) Its members are instances of `LineString` and are accessed via the ``geoms`` property. .. code-block:: pycon >>> len(lines.geoms) 2 >>> print(list(lines.geoms)) [, ] The constructor also accepts another instance of `MultiLineString` or an unordered sequence of `LineString` instances, thereby making copies. .. code-block:: pycon >>> MultiLineString(lines) >>> MultiLineString(lines.geoms) .. _multipolygons: Collections of Polygons ----------------------- .. class:: MultiPolygon(polygons) The `MultiPolygon` constructor takes a sequence of exterior ring and hole list tuples: [((a1, ..., aM), [(b1, ..., bN), ...]), ...]. More clearly, the constructor also accepts an unordered sequence of `Polygon` instances, thereby making copies. .. code-block:: pycon >>> from shapely import MultiPolygon >>> polygons = MultiPolygon([polygon, s, t]) >>> len(polygons.geoms) 3 .. plot:: code/multipolygon.py Figure 7. On the left, a `valid` `MultiPolygon` with 2 members, and on the right, a `MultiPolygon` that is invalid because its members touch at an infinite number of points (along a line). Its `x-y` bounding box is a ``(minx, miny, maxx, maxy)`` tuple. .. code-block:: pycon >>> polygons.bounds (-1.0, -1.0, 2.0, 2.0) Its members are instances of `Polygon` and are accessed via the ``geoms`` property. .. code-block:: pycon >>> len(polygons.geoms) 3 .. _empties: Empty features -------------- An "empty" feature is one with a point set that coincides with the empty set; not ``None``, but like ``set([])``. Empty features can be created by calling the various constructors with no arguments. Almost no operations are supported by empty features. .. code-block:: pycon >>> line = LineString() >>> line.is_empty True >>> line.length 0.0 >>> line.bounds (nan, nan, nan, nan) >>> list(line.coords) [] Coordinate sequences -------------------- The list of coordinates that describe a geometry are represented as the ``CoordinateSequence`` object. These sequences should not be initialised directly, but can be accessed from an existing geometry as the ``Geometry.coords`` property. .. code-block:: pycon >>> line = LineString([(0, 1), (2, 3), (4, 5)]) >>> line.coords Coordinate sequences can be indexed, sliced and iterated over as if they were a list of coordinate tuples. .. code-block:: pycon >>> line.coords[0] (0.0, 1.0) >>> line.coords[1:] [(2.0, 3.0), (4.0, 5.0)] >>> for x, y in line.coords: ... print("x={}, y={}".format(x, y)) ... x=0.0, y=1.0 x=2.0, y=3.0 x=4.0, y=5.0 Polygons have a coordinate sequence for their exterior and each of their interior rings. .. code-block:: pycon >>> poly = Polygon([(0, 0), (0, 1), (1, 1), (0, 0)]) >>> poly.exterior.coords Multipart geometries do not have a coordinate sequence. Instead the coordinate sequences are stored on their component geometries. .. code-block:: pycon >>> p = MultiPoint([(0, 0), (1, 1), (2, 2)]) >>> p.geoms[2].coords Linear Referencing Methods -------------------------- It can be useful to specify position along linear features such as `LineStrings` and `MultiLineStrings` with a 1-dimensional referencing system. Shapely supports linear referencing based on length or distance, evaluating the distance along a geometric object to the projection of a given point, or the point at a given distance along the object. .. method:: object.interpolate(distance[, normalized=False]) Return a point at the specified distance along a linear geometric object. If the `normalized` arg is ``True``, the distance will be interpreted as a fraction of the geometric object's length. .. code-block:: pycon >>> ip = LineString([(0, 0), (0, 1), (1, 1)]).interpolate(1.5) >>> ip >>> LineString([(0, 0), (0, 1), (1, 1)]).interpolate(0.75, normalized=True) .. method:: object.project(other[, normalized=False]) Returns the distance along this geometric object to a point nearest the `other` object. If the `normalized` arg is ``True``, return the distance normalized to the length of the object. The :meth:`~object.project` method is the inverse of :meth:`~object.interpolate`. .. code-block:: pycon >>> LineString([(0, 0), (0, 1), (1, 1)]).project(ip) 1.5 >>> LineString([(0, 0), (0, 1), (1, 1)]).project(ip, normalized=True) 0.75 For example, the linear referencing methods might be used to cut lines at a specified distance. .. code-block:: python def cut(line, distance): # Cuts a line in two at a distance from its starting point if distance <= 0.0 or distance >= line.length: return [LineString(line)] coords = list(line.coords) for i, p in enumerate(coords): pd = line.project(Point(p)) if pd == distance: return [ LineString(coords[:i+1]), LineString(coords[i:])] if pd > distance: cp = line.interpolate(distance) return [ LineString(coords[:i] + [(cp.x, cp.y)]), LineString([(cp.x, cp.y)] + coords[i:])] .. code-block:: pycon >>> line = LineString([(0, 0), (1, 0), (2, 0), (3, 0), (4, 0), (5, 0)]) >>> print([list(x.coords) for x in cut(line, 1.0)]) # doctest: +SKIP [[(0.0, 0.0), (1.0, 0.0)], [(1.0, 0.0), (2.0, 0.0), (3.0, 0.0), (4.0, 0.0), (5.0, 0.0)]] >>> print([list(x.coords) for x in cut(line, 2.5)]) # doctest: +SKIP [[(0.0, 0.0), (1.0, 0.0), (2.0, 0.0), (2.5, 0.0)], [(2.5, 0.0), (3.0, 0.0), (4.0, 0.0), (5.0, 0.0)]] .. _predicates: Predicates and Relationships ============================ Objects of the types explained in :ref:`objects` provide standard [1]_ predicates as attributes (for unary predicates) and methods (for binary predicates). Whether unary or binary, all return ``True`` or ``False``. .. _unary-predicates: Unary Predicates ---------------- Standard unary predicates are implemented as read-only property attributes. An example will be shown for each. .. attribute:: object.has_z Returns ``True`` if the feature has `z` coordinates, either with XYZ or XYZM coordinate types. .. code-block:: pycon >>> Point(0, 0).has_z False >>> Point(0, 0, 0).has_z True .. attribute:: object.has_m Returns ``True`` if the feature has `m` coordinates, either with XYM or XYZM coordinate types. `New in version 2.1 with GEOS 3.12`. .. code-block:: pycon >>> Point(0, 0, 0).has_m False >>> from shapely import from_wkt >>> from_wkt("POINT M (0 0 0)").has_m True .. attribute:: object.is_ccw Returns ``True`` if coordinates are in counter-clockwise order (bounding a region with positive signed area). This method applies to `LinearRing` objects only. `New in version 1.2.10`. .. code-block:: pycon >>> LinearRing([(1,0), (1,1), (0,0)]).is_ccw True A ring with an undesired orientation can be reversed like this: .. code-block:: pycon >>> ring = LinearRing([(0,0), (1,1), (1,0)]) >>> ring.is_ccw False >>> ring2 = LinearRing(list(ring.coords)[::-1]) >>> ring2.is_ccw True .. attribute:: object.is_empty Returns ``True`` if the feature's `interior` and `boundary` (in point set terms) coincide with the empty set. .. code-block:: pycon >>> Point().is_empty True >>> Point(0, 0).is_empty False .. note:: With the help of the :external+python:mod:`operator` module's :external+python:func:`~operator.attrgetter` function, unary predicates such as ``is_empty`` can be easily used as predicates for the built in :external+python:func:`filter`. .. code-block:: pycon >>> from operator import attrgetter >>> empties = filter(attrgetter('is_empty'), [Point(), Point(0, 0)]) >>> len(list(empties)) 1 .. attribute:: object.is_ring Returns ``True`` if the feature is a closed and simple ``LineString``. A closed feature's `boundary` coincides with the empty set. .. code-block:: pycon >>> LineString([(0, 0), (1, 1), (1, -1)]).is_ring False >>> LinearRing([(0, 0), (1, 1), (1, -1)]).is_ring True This property is applicable to `LineString` and `LinearRing` instances, but meaningless for others. .. attribute:: object.is_simple Returns ``True`` if the feature does not cross itself. .. note:: The simplicity test is meaningful only for `LineStrings` and `LinearRings`. .. code-block:: pycon >>> LineString([(0, 0), (1, 1), (1, -1), (0, 1)]).is_simple False Operations on non-simple `LineStrings` are fully supported by Shapely. .. attribute:: object.is_valid Returns ``True`` if a feature is "valid" in the sense of [1]_. A valid `Polygon` may not possess any overlapping exterior or interior rings. A valid `MultiPolygon` may not collect any overlapping polygons. A valid `LineString` must have non-zero length if it isn't :ref:`empty `. Operations on invalid features may fail. .. code-block:: pycon >>> MultiPolygon([Point(0, 0).buffer(2.0), Point(1, 1).buffer(2.0)]).is_valid False The two points above are close enough that the polygons resulting from the buffer operations (explained in a following section) overlap. .. note:: The ``is_valid`` predicate can be used to write a validating decorator that could ensure that only valid objects are returned from a constructor function. .. code-block:: python from functools import wraps def validate(func): @wraps(func) def wrapper(*args, **kwargs): ob = func(*args, **kwargs) if not ob.is_valid: raise TopologicalError( "Given arguments do not determine a valid geometric object") return ob return wrapper .. code-block:: pycon >>> @validate # doctest: +SKIP ... def ring(coordinates): ... return LinearRing(coordinates) ... >>> coords = [(0, 0), (1, 1), (1, -1), (0, 1)] >>> ring(coords) # doctest: +SKIP Traceback (most recent call last): File "", line 1, in File "", line 7, in wrapper shapely.geos.TopologicalError: Given arguments do not determine a valid geometric object .. _binary-predicates: Binary Predicates ----------------- Standard binary predicates are implemented as methods. These predicates evaluate topological, set-theoretic relationships. In a few cases the results may not be what one might expect starting from different assumptions. All take another geometric object as argument and return ``True`` or ``False``. .. method:: object.__eq__(other) Returns ``True`` if the two objects are of the same geometric type, and the coordinates of the two objects match precisely. .. method:: object.equals(other) Returns ``True`` if the set-theoretic `boundary`, `interior`, and `exterior` of the object coincide with those of the other. The coordinates passed to the object constructors are of these sets, and determine them, but are not the entirety of the sets. This is a potential "gotcha" for new users. Equivalent lines, for example, can be constructed differently. .. code-block:: pycon >>> a = LineString([(0, 0), (1, 1)]) >>> b = LineString([(0, 0), (0.5, 0.5), (1, 1)]) >>> c = LineString([(0, 0), (0, 0), (1, 1)]) >>> a.equals(b) True >>> a == b False >>> b.equals(c) True >>> b == c False .. method:: object.equals_exact(other, tolerance=0.0, normalize=False) Returns ``True`` if the geometries are structurally equivalent within a given tolerance. This method uses exact coordinate equality, which requires coordinates to be equal (within specified tolerance) and in the same order for all components (vertices, rings, or parts) of a geometry. This is in contrast with the :meth:`~object.equals` function which uses spatial (topological) equality and does not require all components to be in the same order. Because of this, it is possible for :meth:`~object.equals` to be ``True`` while :meth:`~object.equals_exact` is ``False``. The order of the coordinates can be normalized (by setting the `normalize` keyword to ``True``) so that this function will return ``True`` when geometries are structurally equivalent but differ only in the ordering of vertices. However, this function will still return ``False`` if the order of interior rings within a :class:`Polygon` or the order of geometries within a multi geometry are different. .. code-block:: pycon >>> p1 = Point(1.0, 1.0) >>> p2 = Point(2.0, 2.0) >>> p3 = Point(1.0, 1.0 + 1e-7) >>> p1.equals_exact(p2) False >>> p1.equals_exact(p3) False >>> p1.equals_exact(p3, tolerance=1e-6) True .. method:: object.contains(other) Returns ``True`` if no points of `other` lie in the exterior of the `object` and at least one point of the interior of `other` lies in the interior of `object`. This predicate applies to all types, and is inverse to :meth:`~object.within`. The expression ``a.contains(b) == b.within(a)`` always evaluates to ``True``. .. code-block:: pycon >>> coords = [(0, 0), (1, 1)] >>> LineString(coords).contains(Point(0.5, 0.5)) True >>> Point(0.5, 0.5).within(LineString(coords)) True A line's endpoints are part of its `boundary` and are therefore not contained. .. code-block:: pycon >>> LineString(coords).contains(Point(1.0, 1.0)) False .. note:: Binary predicates can be used directly as predicates for ``filter()`` or ``itertools.ifilter()``. .. code-block:: pycon >>> line = LineString(coords) >>> contained = list(filter(line.contains, [Point(), Point(0.5, 0.5)])) >>> len(contained) 1 >>> contained [] .. method:: object.covers(other) Returns ``True`` if every point of `other` is a point on the interior or boundary of `object`. This is similar to ``object.contains(other)`` except that this does not require any interior points of `other` to lie in the interior of `object`. .. method:: object.covered_by(other) Returns ``True`` if every point of `object` is a point on the interior or boundary of `other`. This is equivalent to ``other.covers(object)``. `New in version 1.8`. .. method:: object.crosses(other) Returns ``True`` if the `interior` of the object intersects the `interior` of the other but does not contain it, and the dimension of the intersection is less than the dimension of the one or the other. .. code-block:: pycon >>> LineString(coords).crosses(LineString([(0, 1), (1, 0)])) True A line does not cross a point that it contains. .. code-block:: pycon >>> LineString(coords).crosses(Point(0.5, 0.5)) False .. method:: object.disjoint(other) Returns ``True`` if the `boundary` and `interior` of the object do not intersect at all with those of the other. .. code-block:: pycon >>> Point(0, 0).disjoint(Point(1, 1)) True This predicate applies to all types and is the inverse of :meth:`~object.intersects`. .. method:: object.intersects(other) Returns ``True`` if the `boundary` or `interior` of the object intersect in any way with those of the other. In other words, geometric objects intersect if they have any boundary or interior point in common. .. method:: object.overlaps(other) Returns ``True`` if the geometries have more than one but not all points in common, have the same dimension, and the intersection of the interiors of the geometries has the same dimension as the geometries themselves. .. method:: object.touches(other) Returns ``True`` if the objects have at least one point in common and their interiors do not intersect with any part of the other. Overlapping features do not therefore `touch`, another potential "gotcha". For example, the following lines touch at ``(1, 1)``, but do not overlap. .. code-block:: pycon >>> a = LineString([(0, 0), (1, 1)]) >>> b = LineString([(1, 1), (2, 2)]) >>> a.touches(b) True .. method:: object.within(other) Returns ``True`` if the object's `boundary` and `interior` intersect only with the `interior` of the other (not its `boundary` or `exterior`). This applies to all types and is the inverse of :meth:`~object.contains`. Used in a ``sorted()`` `key`, :meth:`~object.within` makes it easy to spatially sort objects. Let's say we have 4 stereotypic features: a point that is contained by a polygon which is itself contained by another polygon, and a free spirited point contained by none .. code-block:: pycon >>> a = Point(2, 2) >>> b = Polygon([[1, 1], [1, 3], [3, 3], [3, 1]]) >>> c = Polygon([[0, 0], [0, 4], [4, 4], [4, 0]]) >>> d = Point(-1, -1) and that copies of these are collected into a list .. code-block:: pycon >>> features = [c, a, d, b, c] that we'd prefer to have ordered as ``[d, c, c, b, a]`` in reverse containment order. DE-9IM Relationships -------------------- The :meth:`~object.relate` method tests all the DE-9IM [4]_ relationships between objects, of which the named relationship predicates above are a subset. .. method:: object.relate(other) Returns a string representation of the DE-9IM matrix of relationships between an object's `interior`, `boundary`, `exterior` and those of another geometric object. The named relationship predicates (:meth:`~object.contains`, etc.) are typically implemented as wrappers around :meth:`~object.relate`. Two different points have mainly ``F`` (false) values in their matrix; the intersection of their `external` sets (the 9th element) is a ``2`` dimensional object (the rest of the plane). The intersection of the `interior` of one with the `exterior` of the other is a ``0`` dimensional object (3rd and 7th elements of the matrix). .. code-block:: pycon >>> Point(0, 0).relate(Point(1, 1)) 'FF0FFF0F2' The matrix for a line and a point on the line has more "true" (not ``F``) elements. .. code-block:: pycon >>> Point(0, 0).relate(LineString([(0, 0), (1, 1)])) 'F0FFFF102' .. method:: object.relate_pattern(other, pattern) Returns True if the DE-9IM string code for the relationship between the geometries satisfies the pattern, otherwise False. The :meth:`~object.relate_pattern` compares the DE-9IM code string for two geometries against a specified pattern. If the string matches the pattern then ``True`` is returned, otherwise ``False``. The pattern specified can be an exact match (``0``, ``1`` or ``2``), a boolean match (``T`` or ``F``), or a wildcard (``*``). For example, the pattern for the `within` predicate is ``T*****FF*``. .. code-block:: pycon >>> point = Point(0.5, 0.5) >>> square = Polygon([(0, 0), (0, 1), (1, 1), (1, 0)]) >>> square.relate_pattern(point, 'T*****FF*') True >>> point.within(square) True Note that the order or the geometries is significant, as demonstrated below. In this example the square contains the point, but the point does not contain the square. .. code-block:: pycon >>> point.relate(square) '0FFFFF212' >>> square.relate(point) '0F2FF1FF2' Further discussion of the DE-9IM matrix is beyond the scope of this manual. See [4]_ and https://pypi.org/project/de9im/. .. _analysis-methods: Spatial Analysis Methods ======================== As well as boolean attributes and methods, Shapely provides analysis methods that return new geometric objects. .. _set-theoretic-methods: Set-theoretic Methods --------------------- Almost every binary predicate method has a counterpart that returns a new geometric object. In addition, the set-theoretic `boundary` of an object is available as a read-only attribute. .. note:: These methods will `always` return a geometric object. An intersection of disjoint geometries for example will return an empty `GeometryCollection`, not `None` or `False`. To test for a non-empty result, use the geometry's :attr:`~object.is_empty` property. .. attribute:: object.boundary Returns a lower dimensional object representing the object's set-theoretic `boundary`. The boundary of a polygon is a line, the boundary of a line is a collection of points. The boundary of a point is an empty collection. .. code-block:: pycon >>> coords = [((0, 0), (1, 1)), ((-1, 0), (1, 0))] >>> lines = MultiLineString(coords) >>> lines.boundary >>> list(lines.boundary.geoms) [, , , ] >>> lines.boundary.boundary See the figures in :ref:`linestrings` and :ref:`multilinestrings` for the illustration of lines and their boundaries. .. attribute:: object.centroid Returns a representation of the object's geometric centroid (point). .. code-block:: pycon >>> LineString([(0, 0), (1, 1)]).centroid .. note:: The centroid of an object might be one of its points, but this is not guaranteed. .. method:: object.difference(other) Returns a representation of the points making up this geometric object that do not make up the *other* object. .. code-block:: pycon >>> a = Point(1, 1).buffer(1.5) >>> b = Point(2, 1).buffer(1.5) >>> a.difference(b) .. note:: The :meth:`~object.buffer` method is used to produce approximately circular polygons in the examples of this section; it will be explained in detail later in this manual. .. plot:: code/difference.py Figure 8. Differences between two approximately circular polygons. .. note:: Shapely can not represent the difference between an object and a lower dimensional object (such as the difference between a polygon and a line or point) as a single object, and in these cases the difference method returns a deep copy of the object named ``self``. .. method:: object.intersection(other) Returns a representation of the intersection of this object with the `other` geometric object. .. code-block:: pycon >>> a = Point(1, 1).buffer(1.5) >>> b = Point(2, 1).buffer(1.5) >>> a.intersection(b) See the figure under :meth:`~object.symmetric_difference` below. .. method:: object.symmetric_difference(other) Returns a representation of the points in this object not in the `other` geometric object, and the points in the `other` not in this geometric object. .. code-block:: pycon >>> a = Point(1, 1).buffer(1.5) >>> b = Point(2, 1).buffer(1.5) >>> a.symmetric_difference(b) .. plot:: code/intersection-sym-difference.py .. method:: object.union(other) Returns a representation of the union of points from this object and the `other` geometric object. The type of object returned depends on the relationship between the operands. The union of polygons (for example) will be a polygon or a multi-polygon depending on whether they intersect or not. .. code-block:: pycon >>> a = Point(1, 1).buffer(1.5) >>> b = Point(2, 1).buffer(1.5) >>> a.union(b) The semantics of these operations vary with type of geometric object. For example, compare the boundary of the union of polygons to the union of their boundaries. .. code-block:: pycon >>> a.union(b).boundary >>> a.boundary.union(b.boundary) .. plot:: code/union.py .. note:: :meth:`~object.union` is an expensive way to find the cumulative union of many objects. See :func:`shapely.unary_union` for a more effective method. Several of these set-theoretic methods can be invoked using overloaded operators: - `intersection` can be accessed with and, `&` - `union` can be accessed with or, `|` - `difference` can be accessed with minus, `-` - `symmetric_difference` can be accessed with xor, `^` .. code-block:: pycon >>> from shapely import wkt >>> p1 = wkt.loads('POLYGON((0 0, 1 0, 1 1, 0 1, 0 0))') >>> p2 = wkt.loads('POLYGON((0.5 0, 1.5 0, 1.5 1, 0.5 1, 0.5 0))') >>> p1 & p2 >>> p1 | p2 >>> p1 - p2 >>> (p1 ^ p2).wkt 'MULTIPOLYGON (((0 0, 0 1, 0.5 1, 0.5 0, 0 0)), ((1 1, 1.5 1, 1.5 0, 1 0, 1 1)))' Constructive Methods -------------------- Shapely geometric object have several methods that yield new objects not derived from set-theoretic analysis. .. method:: object.buffer(distance, quad_segs=16, cap_style=1, join_style=1, mitre_limit=5.0, single_sided=False) Returns an approximate representation of all points within a given `distance` of the this geometric object. The styles of caps are specified by integer values: 1 (round), 2 (flat), 3 (square). These values are also enumerated by the object :class:`shapely.BufferCapStyle` (see below). The styles of joins between offset segments are specified by integer values: 1 (round), 2 (mitre), and 3 (bevel). These values are also enumerated by the object :class:`shapely.BufferJoinStyle` (see below). .. data:: shapely.BufferCapStyle ========= ===== Attribute Value ========= ===== round 1 flat 2 square 3 ========= ===== .. data:: shapely.BufferJoinStyle ========= ===== Attribute Value ========= ===== round 1 mitre 2 bevel 3 ========= ===== .. code-block:: pycon >>> from shapely import BufferCapStyle, BufferJoinStyle >>> BufferCapStyle.flat.value 2 >>> BufferJoinStyle.bevel.value 3 A positive distance has an effect of dilation; a negative distance, erosion. The optional `quad_segs` argument determines the number of segments used to approximate a quarter circle around a point. .. code-block:: pycon >>> line = LineString([(0, 0), (1, 1), (0, 2), (2, 2), (3, 1), (1, 0)]) >>> dilated = line.buffer(0.5) >>> eroded = dilated.buffer(-0.3) .. plot:: code/buffer.py Figure 9. Dilation of a line (left) and erosion of a polygon (right). New object is shown in blue. The default (`quad_segs` of 16) buffer of a point is a polygonal patch with 99.8% of the area of the circular disk it approximates. .. code-block:: pycon >>> p = Point(0, 0).buffer(10.0) >>> len(p.exterior.coords) 65 >>> p.area 313.6548490545941 With a `quad_segs` of 1, the buffer is a square patch. .. code-block:: pycon >>> q = Point(0, 0).buffer(10.0, 1) >>> len(q.exterior.coords) 5 >>> q.area 200.0 You may want a buffer only on one side. You can achieve this effect with `single_sided` option. The side used is determined by the sign of the buffer distance: - a positive distance indicates the left-hand side - a negative distance indicates the right-hand side .. code-block:: pycon >>> line = LineString([(0, 0), (1, 1), (0, 2), (2, 2), (3, 1), (1, 0)]) >>> left_hand_side = line.buffer(0.5, single_sided=True) >>> right_hand_side = line.buffer(-0.3, single_sided=True) .. plot:: code/buffer_single_side.py Figure 10. Single sided buffer of 0.5 left hand (left) and of 0.3 right hand (right). The single-sided buffer of point geometries is the same as the regular buffer. The End Cap Style for single-sided buffers is always ignored, and forced to the equivalent of `BufferCapStyle.flat`. Passed a `distance` of 0, :meth:`~object.buffer` can sometimes be used to "clean" self-touching or self-crossing polygons such as the classic "bowtie". Users have reported that very small distance values sometimes produce cleaner results than 0. Your mileage may vary when cleaning surfaces. .. code-block:: pycon >>> coords = [(0, 0), (0, 2), (1, 1), (2, 2), (2, 0), (1, 1), (0, 0)] >>> bowtie = Polygon(coords) >>> bowtie.is_valid False >>> clean = bowtie.buffer(0) >>> clean.is_valid True >>> clean >>> len(clean.geoms) 2 >>> list(clean.geoms[0].exterior.coords) [(0.0, 0.0), (0.0, 2.0), (1.0, 1.0), (0.0, 0.0)] >>> list(clean.geoms[1].exterior.coords) [(1.0, 1.0), (2.0, 2.0), (2.0, 0.0), (1.0, 1.0)] Buffering splits the polygon in two at the point where they touch. .. attribute:: object.convex_hull Returns a representation of the smallest convex `Polygon` containing all the points in the object unless the number of points in the object is less than three. For two points, the convex hull collapses to a `LineString`; for 1, a `Point`. .. code-block:: pycon >>> Point(0, 0).convex_hull >>> MultiPoint([(0, 0), (1, 1)]).convex_hull >>> MultiPoint([(0, 0), (1, 1), (1, -1)]).convex_hull .. plot:: code/convex_hull.py Figure 11. Convex hull (blue) of 2 points (left) and of 6 points (right). .. attribute:: object.envelope Returns a representation of the point or smallest rectangular polygon (with sides parallel to the coordinate axes) that contains the object. .. code-block:: pycon >>> Point(0, 0).envelope >>> MultiPoint([(0, 0), (1, 1)]).envelope .. attribute:: object.minimum_rotated_rectangle Returns the general minimum bounding rectangle that contains the object. Unlike envelope this rectangle is not constrained to be parallel to the coordinate axes. If the convex hull of the object is a degenerate (line or point) this degenerate is returned. `New in Shapely 1.6.0` .. code-block:: pycon >>> Point(0, 0).minimum_rotated_rectangle >>> MultiPoint([(0,0),(1,1),(2,0.5)]).minimum_rotated_rectangle.normalize() .. plot:: code/minimum_rotated_rectangle.py Figure 12. Minimum rotated rectangle for a multipoint feature (left) and a linestring feature (right). .. method:: object.parallel_offset(distance, side, resolution=16, join_style=1, mitre_limit=5.0) Returns a LineString or MultiLineString geometry at a distance from the object on its right or its left side. Older alternative method to the :meth:`~object.offset_curve` method, but uses `resolution` instead of `quad_segs` and a `side` keyword ('left' or 'right') instead of sign of the distance. This method is kept for backwards compatibility for now, but is is recommended to use :meth:`~object.offset_curve` instead. .. method:: object.offset_curve(distance, quad_segs=16, join_style=1, mitre_limit=5.0) Returns a LineString or MultiLineString geometry at a distance from the object on its right or its left side. The `distance` parameter must be a float value. The side is determined by the sign of the `distance` parameter (negative for right side offset, positive for left side offset). Left and right are determined by following the direction of the given geometric points of the LineString. Note: the behaviour regarding orientation of the resulting line depends on the GEOS version. With GEOS < 3.11, the line retains the same direction for a left offset (positive distance) or has reverse direction for a right offset (negative distance), and this behaviour was documented as such in previous Shapely versions. Starting with GEOS 3.11, the function tries to preserve the orientation of the original line. The resolution of the offset around each vertex of the object is parameterized as in the :meth:`~object.buffer` method (using `quad_segs`). The `join_style` is for outside corners between line segments. Accepted integer values are 1 (round), 2 (mitre), and 3 (bevel). See also :data:`shapely.BufferJoinStyle`. Severely mitered corners can be controlled by the `mitre_limit` parameter (spelled in British English, en-gb). The corners of a parallel line will be further from the original than most places with the mitre join style. The ratio of this further distance to the specified `distance` is the miter ratio. Corners with a ratio which exceed the limit will be beveled. .. note:: This method may sometimes return a `MultiLineString` where a simple `LineString` was expected; for example, an offset to a slightly curved LineString. .. note:: This method is only available for `LinearRing` and `LineString` objects. .. plot:: code/parallel_offset.py Figure 13. Three styles of parallel offset lines on the left side of a simple line string (its starting point shown as a circle) and one offset on the right side, a multipart. The effect of the `mitre_limit` parameter is shown below. .. plot:: code/parallel_offset_mitre.py Figure 14. Large and small mitre_limit values for left and right offsets. .. method:: object.simplify(tolerance, preserve_topology=True) Returns a simplified representation of the geometric object. All points in the simplified object will be within the `tolerance` distance of the original geometry. By default a slower algorithm is used that preserves topology. If preserve topology is set to ``False`` the much quicker Douglas-Peucker algorithm [6]_ is used. .. code-block:: pycon >>> p = Point(0.0, 0.0) >>> x = p.buffer(1.0) >>> x.area 3.1365484905459398 >>> len(x.exterior.coords) 65 >>> s = x.simplify(0.05, preserve_topology=False) >>> s.area 3.061467458920719 >>> len(s.exterior.coords) 17 .. plot:: code/simplify.py Figure 15. Simplification of a nearly circular polygon using a tolerance of 0.2 (left) and 0.5 (right). .. note:: `Invalid` geometric objects may result from simplification that does not preserve topology and simplification may be sensitive to the order of coordinates: two geometries differing only in order of coordinates may be simplified differently. Affine Transformations ====================== A collection of affine transform functions are in the :mod:`shapely.affinity` module, which return transformed geometries by either directly supplying coefficients to an affine transformation matrix, or by using a specific, named transform (`rotate`, `scale`, etc.). The functions can be used with all geometry types (except `GeometryCollection`), and 3D types are either preserved or supported by 3D affine transformations. `New in version 1.2.17`. .. function:: shapely.affinity.affine_transform(geom, matrix) Returns a transformed geometry using an affine transformation matrix. The coefficient ``matrix`` is provided as a list or tuple with 6 or 12 items for 2D or 3D transformations, respectively. For 2D affine transformations, the 6 parameter ``matrix`` is: ``[a, b, d, e, xoff, yoff]`` which represents the augmented matrix: .. math:: \begin{bmatrix} x' \\ y' \\ 1 \end{bmatrix} = \begin{bmatrix} a & b & x_\mathrm{off} \\ d & e & y_\mathrm{off} \\ 0 & 0 & 1 \end{bmatrix} \begin{bmatrix} x \\ y \\ 1 \end{bmatrix} or the equations for the transformed coordinates: .. math:: x' &= a x + b y + x_\mathrm{off} \\ y' &= d x + e y + y_\mathrm{off}. For 3D affine transformations, the 12 parameter ``matrix`` is: ``[a, b, c, d, e, f, g, h, i, xoff, yoff, zoff]`` which represents the augmented matrix: .. math:: \begin{bmatrix} x' \\ y' \\ z' \\ 1 \end{bmatrix} = \begin{bmatrix} a & b & c & x_\mathrm{off} \\ d & e & f & y_\mathrm{off} \\ g & h & i & z_\mathrm{off} \\ 0 & 0 & 0 & 1 \end{bmatrix} \begin{bmatrix} x \\ y \\ z \\ 1 \end{bmatrix} or the equations for the transformed coordinates: .. math:: x' &= a x + b y + c z + x_\mathrm{off} \\ y' &= d x + e y + f z + y_\mathrm{off} \\ z' &= g x + h y + i z + z_\mathrm{off}. .. function:: shapely.affinity.rotate(geom, angle, origin='center', use_radians=False) Returns a rotated geometry on a 2D plane. The angle of rotation can be specified in either degrees (default) or radians by setting ``use_radians=True``. Positive angles are counter-clockwise and negative are clockwise rotations. The point of origin can be a keyword ``'center'`` for the bounding box center (default), ``'centroid'`` for the geometry's centroid, a `Point` object or a coordinate tuple ``(x0, y0)``. The affine transformation matrix for 2D rotation with angle :math:`\theta` is: .. math:: \begin{bmatrix} \cos{\theta} & -\sin{\theta} & x_\mathrm{off} \\ \sin{\theta} & \cos{\theta} & y_\mathrm{off} \\ 0 & 0 & 1 \end{bmatrix} where the offsets are calculated from the origin :math:`(x_0, y_0)`: .. math:: x_\mathrm{off} &= x_0 - x_0 \cos{\theta} + y_0 \sin{\theta} \\ y_\mathrm{off} &= y_0 - x_0 \sin{\theta} - y_0 \cos{\theta} .. code-block:: pycon >>> from shapely import affinity >>> line = LineString([(1, 3), (1, 1), (4, 1)]) >>> rotated_a = affinity.rotate(line, 90) >>> rotated_b = affinity.rotate(line, 90, origin='centroid') .. plot:: code/rotate.py Figure 16. Rotation of a `LineString` (gray) by an angle of 90° counter-clockwise (blue) using different origins. .. function:: shapely.affinity.scale(geom, xfact=1.0, yfact=1.0, zfact=1.0, origin='center') Returns a scaled geometry, scaled by factors along each dimension. The point of origin can be a keyword ``'center'`` for the 2D bounding box center (default), ``'centroid'`` for the geometry's 2D centroid, a `Point` object or a coordinate tuple ``(x0, y0, z0)``. Negative scale factors will mirror or reflect coordinates. The general 3D affine transformation matrix for scaling is: .. math:: \begin{bmatrix} x_\mathrm{fact} & 0 & 0 & x_\mathrm{off} \\ 0 & y_\mathrm{fact} & 0 & y_\mathrm{off} \\ 0 & 0 & z_\mathrm{fact} & z_\mathrm{off} \\ 0 & 0 & 0 & 1 \end{bmatrix} where the offsets are calculated from the origin :math:`(x_0, y_0, z_0)`: .. math:: x_\mathrm{off} &= x_0 - x_0 x_\mathrm{fact} \\ y_\mathrm{off} &= y_0 - y_0 y_\mathrm{fact} \\ z_\mathrm{off} &= z_0 - z_0 z_\mathrm{fact} .. code-block:: pycon >>> triangle = Polygon([(1, 1), (2, 3), (3, 1)]) >>> triangle_a = affinity.scale(triangle, xfact=1.5, yfact=-1) >>> triangle_a.exterior.coords[:] [(0.5, 3.0), (2.0, 1.0), (3.5, 3.0), (0.5, 3.0)] >>> triangle_b = affinity.scale(triangle, xfact=2, origin=(1,1)) >>> triangle_b.exterior.coords[:] [(1.0, 1.0), (3.0, 3.0), (5.0, 1.0), (1.0, 1.0)] .. plot:: code/scale.py Figure 17. Scaling of a gray triangle to blue result: a) by a factor of 1.5 along x-direction, with reflection across y-axis; b) by a factor of 2 along x-direction with custom origin at (1, 1). .. function:: shapely.affinity.skew(geom, xs=0.0, ys=0.0, origin='center', use_radians=False) Returns a skewed geometry, sheared by angles along x and y dimensions. The shear angle can be specified in either degrees (default) or radians by setting ``use_radians=True``. The point of origin can be a keyword ``'center'`` for the bounding box center (default), ``'centroid'`` for the geometry's centroid, a `Point` object or a coordinate tuple ``(x0, y0)``. The general 2D affine transformation matrix for skewing is: .. math:: \begin{bmatrix} 1 & \tan{x_s} & x_\mathrm{off} \\ \tan{y_s} & 1 & y_\mathrm{off} \\ 0 & 0 & 1 \end{bmatrix} where the offsets are calculated from the origin :math:`(x_0, y_0)`: .. math:: x_\mathrm{off} &= -y_0 \tan{x_s} \\ y_\mathrm{off} &= -x_0 \tan{y_s} .. plot:: code/skew.py Figure 18. Skewing of a gray "R" to blue result: a) by a shear angle of 20° along the x-direction and an origin at (1, 1); b) by a shear angle of 30° along the y-direction, using default origin. .. function:: shapely.affinity.translate(geom, xoff=0.0, yoff=0.0, zoff=0.0) Returns a translated geometry shifted by offsets along each dimension. The general 3D affine transformation matrix for translation is: .. math:: \begin{bmatrix} 1 & 0 & 0 & x_\mathrm{off} \\ 0 & 1 & 0 & y_\mathrm{off} \\ 0 & 0 & 1 & z_\mathrm{off} \\ 0 & 0 & 0 & 1 \end{bmatrix} Other Transformations ===================== Shapely supports map projections and other arbitrary transformations of geometric objects. .. function:: shapely.ops.transform(func, geom) Applies `func` to all coordinates of `geom` and returns a new geometry of the same type from the transformed coordinates. `func` maps x, y, and optionally z to output xp, yp, zp. The input parameters may be iterable types like lists or arrays or single values. The output shall be of the same type: scalars in, scalars out; lists in, lists out. `transform` tries to determine which kind of function was passed in by calling `func` first with n iterables of coordinates, where n is the dimensionality of the input geometry. If `func` raises a `TypeError` when called with iterables as arguments, then it will instead call `func` on each individual coordinate in the geometry. `New in version 1.2.18`. For example, here is an identity function applicable to both types of input (scalar or array). .. code-block:: python def id_func(x, y, z=None): return tuple(filter(None, [x, y, z])) g2 = transform(id_func, g1) If using `pyproj>=2.1.0`, the preferred method to project geometries is: .. code-block:: python import pyproj from shapely import Point from shapely.ops import transform wgs84_pt = Point(-72.2495, 43.886) wgs84 = pyproj.CRS('EPSG:4326') utm = pyproj.CRS('EPSG:32618') project = pyproj.Transformer.from_crs(wgs84, utm, always_xy=True).transform utm_point = transform(project, wgs84_pt) It is important to note that in the example above, the `always_xy` kwarg is required as Shapely only supports coordinates in X,Y order, and in PROJ 6 the WGS84 CRS uses the EPSG-defined Lat/Lon coordinate order instead of the expected Lon/Lat. If using `pyproj < 2.1`, then the canonical example is: .. code-block:: python from functools import partial import pyproj from shapely.ops import transform wgs84 = pyproj.Proj(init='epsg:4326') utm = pyproj.Proj(init='epsg:32618') project = partial( pyproj.transform, wgs84, utm) utm_point = transform(project, wgs84_pt) Lambda expressions such as the one in .. code-block:: python g2 = transform(lambda x, y, z=None: (x+1.0, y+1.0), g1) also satisfy the requirements for `func`. Other Operations ================ Merging Linear Features ----------------------- Sequences of touching lines can be merged into `MultiLineStrings` or `Polygons`. .. function:: shapely.polygonize(lines) Returns an iterator over polygons constructed from the input `lines`. The source should be a sequence of LineString objects. .. code-block:: pycon >>> from shapely import polygonize >>> lines = [ ... LineString([(0, 0), (1, 1)]), ... LineString([(0, 0), (0, 1)]), ... LineString([(0, 1), (1, 1)]), ... LineString([(1, 1), (1, 0)]), ... LineString([(1, 0), (0, 0)]), ... ] >>> list(polygonize(lines).geoms) [, ] .. function:: shapely.polygonize_full(lines) Creates polygons from a source of lines, returning the polygons and leftover geometries. The source should be a sequence of LineString objects. Returns a tuple of objects: (polygons, cut edges, dangles, invalid ring lines). Each are a geometry collection. Dangles are edges which have one or both ends which are not incident on another edge endpoint. Cut edges are connected at both ends but do not form part of polygon. Invalid ring lines form rings which are invalid (bowties, etc). `New in version 1.2.18.` .. code-block:: pycon >>> from shapely import polygonize_full >>> lines = [ ... LineString([(0, 0), (1, 1)]), ... LineString([(0, 0), (0, 1)]), ... LineString([(0, 1), (1, 1)]), ... LineString([(1, 1), (1, 0)]), ... LineString([(1, 0), (0, 0)]), ... LineString([(5, 5), (6, 6)]), ... LineString([(1, 1), (100, 100)]), ... ] >>> result, cuts, dangles, invalids = polygonize_full(lines) >>> len(result.geoms) 2 >>> list(result.geoms) [, ] >>> list(dangles.geoms) [, ] .. function:: shapely.line_merge(multilinestring) Returns `LineString(s)` or `MultiLineString(s)` representing the merger of all contiguous elements of the input `MultiLineString(s)`. .. code-block:: python >>> from shapely import line_merge >>> line_merge(MultiLineString(lines)) >>> list(line_merge(MultiLineString(lines)).geoms) [, , , , ] Efficient Rectangle Clipping ---------------------------- The :func:`~shapely.clip_by_rect` function returns the portion of a geometry within a rectangle. .. function:: shapely.clip_by_rect(geom, xmin, ymin, xmax, ymax) The geometry is clipped in a fast but possibly dirty way. The output is not guaranteed to be valid. No exceptions will be raised for topological errors. `New in version 1.7.` .. code-block:: python >>> from shapely import clip_by_rect >>> polygon = Polygon( ... shell=[(0, 0), (0, 30), (30, 30), (30, 0), (0, 0)], ... holes=[[(10, 10), (20, 10), (20, 20), (10, 20), (10, 10)]], ... ) >>> clipped_polygon = clip_by_rect(polygon, 5, 5, 15, 15) >>> clipped_polygon Efficient Unions ---------------- The :func:`~shapely.unary_union` function is more efficient than accumulating with :meth:`~object.union`. .. plot:: code/unary_union.py .. function:: shapely.unary_union(geoms) Returns a representation of the union of the given geometric objects. Areas of overlapping `Polygons` will get merged. `LineStrings` will get fully dissolved and noded. Duplicate `Points` will get merged. .. code-block:: pycon >>> from shapely import unary_union >>> polygons = [Point(i, 0).buffer(0.7) for i in range(5)] >>> unary_union(polygons) Because the union merges the areas of overlapping `Polygons` it can be used in an attempt to fix invalid `MultiPolygons`. As with the zero distance :meth:`~object.buffer` trick, your mileage may vary when using this. .. code-block:: pycon >>> m = MultiPolygon(polygons) >>> m.area 7.684543801837549 >>> m.is_valid False >>> unary_union(m).area 6.610301355116799 >>> unary_union(m).is_valid True Delaunay triangulation ---------------------- The :func:`~shapely.delaunay_triangles` function calculates a Delaunay triangulation from a collection of points. .. plot:: code/triangulate.py .. function:: shapely.delaunay_triangles(geom, tolerance=0.0, edges=False) Returns a Delaunay triangulation of the vertices of the input geometry. The source may be any geometry type. All vertices of the geometry will be used as the points of the triangulation. The `tolerance` keyword argument sets the snapping tolerance used to improve the robustness of the triangulation computation. A tolerance of 0.0 specifies that no snapping will take place. If the `edges` keyword argument is `False` a list of `Polygon` triangles will be returned. Otherwise a list of `LineString` edges is returned. `New in version 1.4.0` .. code-block:: pycon >>> from shapely import delaunay_triangles >>> points = MultiPoint([(0, 0), (1, 1), (0, 2), (2, 2), (3, 1), (1, 0)]) >>> list(delaunay_triangles(points).geoms) [, , , , ] Voronoi Diagram --------------- The :func:`~shapely.voronoi_polygons` function constructs a Voronoi diagram from a collection points, or the vertices of any geometry. .. plot:: code/voronoi_diagram.py .. function:: shapely.voronoi_polygons(geom, envelope=None, tolerance=0.0, edges=False) Constructs a Voronoi diagram from the vertices of the input geometry. The source may be any geometry type. All vertices of the geometry will be used as the input points to the diagram. The `envelope` keyword argument provides an envelope to use to clip the resulting diagram. If `None`, it will be calculated automatically. The diagram will be clipped to the *larger* of the provided envelope or an envelope surrounding the sites. The `tolerance` keyword argument sets the snapping tolerance used to improve the robustness of the computation. A tolerance of 0.0 specifies that no snapping will take place. The tolerance `argument` can be finicky and is known to cause the algorithm to fail in several cases. If you're using `tolerance` and getting a failure, try removing it. The test cases in `tests/test_voronoi_diagram.py` show more details. If the `edges` keyword argument is `False` a list of `Polygon`s will be returned. Otherwise a list of `LineString` edges is returned. .. code-block:: pycon >>> from shapely import voronoi_polygons >>> points = MultiPoint([(0, 0), (1, 1), (0, 2), (2, 2), (3, 1), (1, 0)]) >>> regions = voronoi_polygons(points) >>> list(regions.geoms) [, , , , , ] Nearest points/shortest line ---------------------------- The :func:`~shapely.shortest_line` function calculates the shortest line between a pair of geometries. .. function:: shapely.shortest_line(geom1, geom2) Returns a tuple of the shortest line between the input geometries. The points are returned in the same order as the input geometries. `New in version 2.0`. .. code-block:: pycon >>> from shapely import shortest_line >>> triangle = Polygon([(0, 0), (1, 0), (0.5, 1), (0, 0)]) >>> square = Polygon([(0, 2), (1, 2), (1, 3), (0, 3), (0, 2)]) >>> shortest_line(triangle, square) Note that the shortest line may not connect to vertices of the input geometries. Snapping -------- The :func:`~shapely.snap` snaps the vertices in one geometry to the vertices in a second geometry with a given tolerance. .. function:: shapely.snap(geom1, geom2, tolerance) Snaps vertices in `geom1` to vertices in the `geom2`. A new instance of type `geom1` is returned. The input geometries are not modified. The `tolerance` argument specifies the minimum distance between vertices for them to be snapped. `New in version 1.5.0` .. code-block:: pycon >>> from shapely import snap >>> square = Polygon([(1,1), (2, 1), (2, 2), (1, 2), (1, 1)]) >>> line = LineString([(0,0), (0.8, 0.8), (1.8, 0.95), (2.6, 0.5)]) >>> result = snap(line, square, 0.5) >>> result Shared paths ------------ The :func:`~shapely.shared_paths` function finds the shared paths between two linear geometries. .. function:: shapely.shared_paths(geom1, geom2) Finds the shared paths between `geom1` and `geom2`, where both geometries are `LineStrings`. A `GeometryCollection` is returned with two elements. The first element is a `MultiLineString` containing shared paths with the same direction for both inputs. The second element is a MultiLineString containing shared paths with the opposite direction for the two inputs. `New in version 1.6.0` .. code-block:: pycon >>> from shapely import shared_paths >>> g1 = LineString([(0, 0), (10, 0), (10, 5), (20, 5)]) >>> g2 = LineString([(5, 0), (30, 0), (30, 5), (0, 5)]) >>> forward, backward = shared_paths(g1, g2).geoms >>> forward >>> backward Splitting --------- The :func:`~shapely.ops.split` function in `shapely.ops` splits a geometry by another geometry. .. function:: shapely.ops.split(geom, splitter) Splits a geometry by another geometry and returns a collection of geometries. This function is the theoretical opposite of the union of the split geometry parts. If the splitter does not split the geometry, a collection with a single geometry equal to the input geometry is returned. The function supports: * Splitting a (Multi)LineString by a (Multi)Point or (Multi)LineString or (Multi)Polygon boundary * Splitting a (Multi)Polygon by a LineString It may be convenient to snap the splitter with low tolerance to the geometry. For example in the case of splitting a line by a point, the point must be exactly on the line, for the line to be correctly split. When splitting a line by a polygon, the boundary of the polygon is used for the operation. When splitting a line by another line, a ValueError is raised if the two overlap at some segment. .. code-block:: pycon >>> from shapely.ops import split >>> pt = Point((1, 1)) >>> line = LineString([(0,0), (2,2)]) >>> result = split(line, pt) >>> result Substring --------- The :func:`~shapely.ops.substring` function in :mod:`shapely.ops` returns a line segment between specified distances along a `LineString`. .. function:: shapely.ops.substring(geom, start_dist, end_dist[, normalized=False]) Return the `LineString` between `start_dist` and `end_dist` or a `Point` if they are at the same location Negative distance values are taken as measured in the reverse direction from the end of the geometry. Out-of-range index values are handled by clamping them to the valid range of values. If the start distance equals the end distance, a point is being returned. If the start distance is actually past the end distance, then the reversed substring is returned such that the start distance is at the first coordinate. If the normalized arg is ``True``, the distance will be interpreted as a fraction of the geometry's length `New in version 1.7.0` Here are some examples that return `LineString` geometries. .. code-block:: pycon >>> from shapely.ops import substring >>> ls = LineString((i, 0) for i in range(6)) >>> ls >>> substring(ls, start_dist=1, end_dist=3) >>> substring(ls, start_dist=3, end_dist=1) >>> substring(ls, start_dist=1, end_dist=-3) >>> substring(ls, start_dist=0.2, end_dist=-0.6, normalized=True) And here is an example that returns a `Point`. .. code-block:: pycon >>> substring(ls, start_dist=2.5, end_dist=-2.5) Prepared Geometry Operations ---------------------------- Shapely geometries can be processed into a state that supports more efficient batches of operations. .. function:: prepared.prep(ob) Creates and returns a prepared geometric object. To test one polygon containment against a large batch of points, one should first use the :func:`prepared.prep` function. .. code-block:: pycon >>> from shapely.prepared import prep >>> points = [...] # large list of points >>> polygon = Point(0.0, 0.0).buffer(1.0) >>> prepared_polygon = prep(polygon) >>> prepared_polygon >>> hits = filter(prepared_polygon.contains, points) Prepared geometries instances have the following methods: ``contains``, ``contains_properly``, ``covers``, and ``intersects``. All have exactly the same arguments and usage as their counterparts in non-prepared geometric objects. Diagnostics ----------- .. function:: validation.explain_validity(ob): Returns a string explaining the validity or invalidity of the object. `New in version 1.2.1`. The messages may or may not have a representation of a problem point that can be parsed out. .. code-block:: pycon >>> coords = [(0, 0), (0, 2), (1, 1), (2, 2), (2, 0), (1, 1), (0, 0)] >>> p = Polygon(coords) >>> from shapely.validation import explain_validity >>> explain_validity(p) 'Ring Self-intersection[1 1]' .. function:: validation.make_valid(ob) Returns a valid representation of the geometry, if it is invalid. If it is valid, the input geometry will be returned. In many cases, in order to create a valid geometry, the input geometry must be split into multiple parts or multiple geometries. If the geometry must be split into multiple parts of the same geometry type, then a multi-part geometry (e.g. a MultiPolygon) will be returned. if the geometry must be split into multiple parts of different types, then a GeometryCollection will be returned. For example, this operation on a geometry with a bow-tie structure: .. code-block:: pycon >>> from shapely.validation import make_valid >>> coords = [(0, 0), (0, 2), (1, 1), (2, 2), (2, 0), (1, 1), (0, 0)] >>> p = Polygon(coords) >>> make_valid(p) Yields a MultiPolygon with two parts: .. plot:: code/make_valid_multipolygon.py While this operation: .. code-block:: pycon >>> from shapely.validation import make_valid >>> coords = [(0, 2), (0, 1), (2, 0), (0, 0), (0, 2)] >>> p = Polygon(coords) >>> make_valid(p) Yields a GeometryCollection with a Polygon and a LineString: .. plot:: code/make_valid_geometrycollection.py `New in version 1.8` The Shapely version, GEOS library version, and GEOS C API version are accessible via ``shapely.__version__``, ``shapely.geos_version_string``, and ``shapely.geos_capi_version``. .. code-block:: pycon >>> import shapely >>> shapely.__version__ # doctest: +SKIP '2.0.0' >>> shapely.geos_version # doctest: +SKIP (3, 10, 2) >>> shapely.geos_capi_version_string # doctest: +SKIP '3.10.2-CAPI-1.16.0' Polylabel --------- .. function:: shapely.ops.polylabel(polygon, tolerance) Finds the approximate location of the pole of inaccessibility for a given polygon. Based on Vladimir Agafonkin's polylabel_. `New in version 1.6.0` .. note:: Prior to 1.7 `polylabel` must be imported from `shapely.algorithms.polylabel` instead of `shapely.ops`. .. code-block:: pycon >>> from shapely.ops import polylabel >>> polygon = LineString([(0, 0), (50, 200), (100, 100), (20, 50), ... (-100, -20), (-150, -200)]).buffer(100) >>> label = polylabel(polygon, tolerance=0.001) >>> label STR-packed R-tree ================= Shapely provides an interface to the query-only GEOS R-tree packed using the Sort-Tile-Recursive algorithm. Pass a list of geometry objects to the STRtree constructor to create a spatial index that you can query with another geometric object. Query-only means that once created, the `STRtree` is immutable. You cannot add or remove geometries. .. class:: strtree.STRtree(geometries) :noindex: The `STRtree` constructor takes a sequence of geometric objects. References to these geometric objects are kept and stored in the R-tree. `New in version 1.4.0`. .. method:: strtree.query(geom) :noindex: Returns the integer indices of all geometries in the `strtree` whose extents intersect the extent of `geom`. This means that a subsequent search through the returned subset using the desired binary predicate (eg. intersects, crosses, contains, overlaps) may be necessary to further filter the results according to their specific spatial relationships. .. code-block:: pycon >>> from shapely import STRtree >>> points = [Point(i, i) for i in range(10)] >>> tree = STRtree(points) >>> query_geom = Point(2,2).buffer(0.99) >>> [points[idx].wkt for idx in tree.query(query_geom)] ['POINT (2 2)'] >>> query_geom = Point(2, 2).buffer(1.0) >>> [points[idx].wkt for idx in tree.query(query_geom)] ['POINT (1 1)', 'POINT (2 2)', 'POINT (3 3)'] >>> [points[idx].wkt for idx in tree.query(query_geom, predicate="intersects")] ['POINT (2 2)'] .. method:: strtree.nearest(geom) :noindex: Returns the nearest geometry in `strtree` to `geom`. .. code-block:: pycon >>> points = [Point(i, i) for i in range(10)] >>> tree = STRtree(points) >>> idx = tree.nearest(Point(2.2, 2.2)) >>> points[idx] Interoperation ============== Shapely provides 4 avenues for interoperation with other software. Well-Known Formats ------------------ A `Well Known Text` (WKT) or `Well Known Binary` (WKB) representation [1]_ of any geometric object can be had via its ``wkt`` or ``wkb`` attribute. These representations allow interchange with many GIS programs. PostGIS, for example, trades in hex-encoded WKB. .. code-block:: pycon >>> Point(0, 0).wkt 'POINT (0 0)' >>> Point(0, 0).wkb b'\x01\x01\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00' >>> Point(0, 0).wkb_hex '010100000000000000000000000000000000000000' The `shapely.wkt` and `shapely.wkb` modules provide `dumps()` and `loads()` functions that work almost exactly as their `pickle` and `simplejson` module counterparts. To serialize a geometric object to a binary or text string, use ``dumps()``. To deserialize a string and get a new geometric object of the appropriate type, use ``loads()``. The default settings for the wkt attribute and `shapely.wkt.dumps()` function are different. By default, the attribute's value is trimmed of excess decimals, while this is not the case for `dumps()`, though it can be replicated by setting `trim=True`. .. function:: shapely.wkb.dumps(ob) Returns a WKB representation of `ob`. .. function:: shapely.wkb.loads(wkb) Returns a geometric object from a WKB representation `wkb`. .. code-block:: pycon >>> from shapely import wkb, Point >>> pt = Point(0, 0) >>> wkb.dumps(pt) b'\x01\x01\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00' >>> pt.wkb b'\x01\x01\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00' >>> wkb.loads(pt.wkb).wkt 'POINT (0 0)' All of Shapely's geometry types are supported by these functions. .. function:: shapely.wkt.dumps(ob) Returns a WKT representation of `ob`. Several keyword arguments are available to alter the WKT which is returned; see the docstrings for more details. .. function:: shapely.wkt.loads(wkt) Returns a geometric object from a WKT representation `wkt`. .. code-block:: pycon >>> from shapely import wkt, Point >>> pt = Point(0, 0) >>> wkt.dumps(pt) 'POINT (0.0000000000000000 0.0000000000000000)' >>> pt.wkt 'POINT (0 0)' >>> wkt.loads(pt.wkt).wkt 'POINT (0 0)' .. _array-interface: Numpy and Python Arrays ----------------------- All geometric objects with coordinate sequences (`Point`, `LinearRing`, `LineString`) provide the Numpy array interface and can thereby be converted or adapted to Numpy arrays. .. code-block:: pycon >>> import numpy as np >>> np.asarray(Point(0, 0).coords) array([[0., 0.]]) >>> np.asarray(LineString([(0, 0), (1, 1)]).coords) array([[0., 0.], [1., 1.]]) The coordinates of the same types of geometric objects can be had as standard Python arrays of `x` and `y` values via the ``xy`` attribute. .. code-block:: pycon >>> Point(0, 0).xy (array('d', [0.0]), array('d', [0.0])) >>> LineString([(0, 0), (1, 1)]).xy (array('d', [0.0, 1.0]), array('d', [0.0, 1.0])) Python Geo Interface -------------------- Any object that provides the GeoJSON-like `Python geo interface`_ can be converted to a Shapely geometry using the :func:`shapely.geometry.shape` function. .. function:: shapely.geometry.shape(context) Returns a new, independent geometry with coordinates `copied` from the context. For example, a dictionary: .. code-block:: pycon >>> from shapely.geometry import shape >>> data = {"type": "Point", "coordinates": (0.0, 0.0)} >>> geom = shape(data) >>> geom.geom_type 'Point' >>> list(geom.coords) [(0.0, 0.0)] Or a simple placemark-type object: .. code-block:: pycon >>> class GeoThing: ... def __init__(self, d): ... self.__geo_interface__ = d >>> thing = GeoThing({"type": "Point", "coordinates": (0.0, 0.0)}) >>> geom = shape(thing) >>> geom.geom_type 'Point' >>> list(geom.coords) [(0.0, 0.0)] The GeoJSON-like mapping of a geometric object can be obtained using :func:`shapely.geometry.mapping`. .. function:: shapely.geometry.mapping(ob) Returns a GeoJSON-like mapping from a Geometry or any object which implements ``__geo_interface__``. `New in version 1.2.3`. For example, using the same `GeoThing` class: .. code-block:: pycon >>> from shapely.geometry import mapping >>> thing = GeoThing({"type": "Point", "coordinates": (0.0, 0.0)}) >>> m = mapping(thing) >>> m['type'] 'Point' >>> m['coordinates'] (0.0, 0.0) Performance =========== Shapely uses the GEOS_ library for all operations. GEOS is written in C++ and used in many applications and you can expect that all operations are highly optimized. The creation of new geometries with many coordinates, however, involves some overhead that might slow down your code. Conclusion ========== We hope that you will enjoy and profit from using Shapely. This manual will be updated and improved regularly. Its source is available at https://github.com/shapely/shapely/tree/main/docs/. References ========== .. [1] John R. Herring, Ed., “OpenGIS Implementation Specification for Geographic information - Simple feature access - Part 1: Common architecture,” Oct. 2006. .. [2] M.J. Egenhofer and John R. Herring, Categorizing Binary Topological Relations Between Regions, Lines, and Points in Geographic Databases, Orono, ME: University of Maine, 1991. .. [3] E. Clementini, P. Di Felice, and P. van Oosterom, “A Small Set of Formal Topological Relationships Suitable for End-User Interaction,” Third International Symposium on Large Spatial Databases (SSD). Lecture Notes in Computer Science no. 692, David Abel and Beng Chin Ooi, Eds., Singapore: Springer Verlag, 1993, pp. 277-295. .. [4] C. Strobl, “Dimensionally Extended Nine-Intersection Model (DE-9IM),” Encyclopedia of GIS, S. Shekhar and H. Xiong, Eds., Springer, 2008, pp. 240-245. [|Strobl-PDF|_] .. [5] Martin Davis, “JTS Technical Specifications,” Mar. 2003. [|JTS-PDF|_] .. [6] David H. Douglas and Thomas K. Peucker, “Algorithms for the Reduction of the Number of Points Required to Represent a Digitized Line or its Caricature,” Cartographica: The International Journal for Geographic Information and Geovisualization, vol. 10, Dec. 1973, pp. 112-122. .. _GEOS: https://libgeos.org/ .. _Java Topology Suite: https://projects.eclipse.org/projects/locationtech.jts .. _PostGIS: https://postgis.net .. _Open Geospatial Consortium: https://www.opengeospatial.org/ .. _Strobl-PDF: https://giswiki.hsr.ch/images/3/3d/9dem_springer.pdf .. |Strobl-PDF| replace:: PDF .. _JTS-PDF: https://github.com/locationtech/jts/raw/master/doc/JTS%20Technical%20Specs.pdf .. |JTS-PDF| replace:: PDF .. _frozenset: https://docs.python.org/library/stdtypes.html#frozenset .. _Sorting HowTo: https://wiki.python.org/moin/HowTo/Sorting/ .. _Python geo interface: https://gist.github.com/2217756 .. _polylabel: https://github.com/mapbox/polylabel