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# -*- coding: utf-8 -*-
# Licensed under a 3-clause BSD style license - see LICENSE.rst
"""
The `spherical_geometry.polygon` module defines the `SphericalPolygon` class for
managing polygons on the unit sphere.
"""
from __future__ import division, print_function, unicode_literals, absolute_import
# STDLIB
from copy import copy, deepcopy
# THIRD-PARTY
import numpy as np
# LOCAL
from . import great_circle_arc
from . import vector
__all__ = ['SingleSphericalPolygon', 'SphericalPolygon']
class SingleSphericalPolygon(object):
r"""
Polygons are represented by both a set of points (in Cartesian
(*x*, *y*, *z*) normalized on the unit sphere), and an inside
point. The inside point is necessary, because both the inside and
outside of the polygon are finite areas on the great sphere, and
therefore we need a way of specifying which is which.
"""
def __init__(self, points, inside=None):
r"""
Parameters
----------
points : An Nx3 array of (*x*, *y*, *z*) triples in vector space
These points define the boundary of the polygon.
It may contain zero points, in which it defines the null
polygon. It may not contain one, two or three points.
Four points are needed to define a triangle, since the
polygon must be closed.
inside : An (*x*, *y*, *z*) triple, optional
This point must be inside the polygon. If not provided, an
interior point will be calculated
"""
if len(points) == 0:
# handle special case of initializing with an empty list of
# vertices (ticket #1079).
self._inside = np.zeros(3)
self._points = np.asanyarray(points)
return
if not np.array_equal(points[0], points[-1]):
points = list(points[:])
points.append(points[0])
if len(points) < 3:
raise ValueError("Polygon made of too few points")
self._points = points = np.asanyarray(points)
new_inside = self._find_new_inside()
if inside is None:
self._inside = np.asanyarray(new_inside)
if not self.is_clockwise():
self._points = points[::-1]
else:
self._inside = np.asanyarray(inside)
if self.contains_point(new_inside) != self.is_clockwise():
self._points = points[::-1]
def __copy__(self):
return deepcopy(self)
copy = __copy__
def __len__(self):
return 1
def __repr__(self):
return '%s(%r, %r)' % (self.__class__.__name__,
self.points, self.inside)
def __iter__(self):
"""
Iterate over all base polygons that make up this multi-polygon
set.
"""
yield self
# Alias for backwards compatibility
iter_polygons_flat = __iter__
@property
def points(self):
"""
The points defining the polygon. It is an Nx3 array of
(*x*, *y*, *z*) vectors. The polygon will be explicitly
closed, i.e., the first and last points are the same.
"""
return self._points
@property
def inside(self):
"""
Get the inside point of the polygon.
"""
return self._inside
def is_clockwise(self):
"""
Return True if the points in this polygon are in clockwise order.
The normal vector to the two arcs containing a vertes points outward
from the sphere if the angle is clockwise and inward if the angle is
counter-clockwise. The sign of the inner product of the normal vector
with the vertex tells you this. The polygon is ordered clockwise if
the vertices are predominantly clockwise and counter-clockwise if
the reverse.
"""
points = np.vstack((self._points, self._points[1]))
A = points[:-2]
B = points[1:-1]
C = points[2:]
orient = great_circle_arc.triple_product(A-B, C-B, B)
return np.sum(orient) > 0.0
def to_lonlat(self):
"""
Convert `SingleSphericalPolygon` footprint to longitude and latitutde.
Returns
-------
lon, lat : list of float
List of *lon* and *lat* in degrees corresponding
to `points`.
"""
if len(self.points) == 0:
return np.array([])
return vector.vector_to_lonlat(self.points[:,0], self.points[:,1],
self.points[:,2], degrees=True)
# Alias for to_lonlat
to_radec = to_lonlat
@classmethod
def from_lonlat(cls, lon, lat, center=None, degrees=True):
r"""
Create a new `SingleSphericalPolygon` from a list of
(*longitude*, *latitude*) points.
Parameters
----------
lon, lat : 1-D arrays of the same length
The vertices of the polygon in longitude and
latitude.
center : (*lon*, *lat*) pair, optional
A point inside of the polygon to define its inside.
degrees : bool, optional
If `True`, (default) *lon* and *lat* are in decimal degrees,
otherwise in radians.
Returns
-------
polygon : `SingleSphericalPolygon` object
"""
# Convert to Cartesian
x, y, z = vector.lonlat_to_vector(lon, lat, degrees=degrees)
points = np.dstack((x, y, z))[0]
if center is not None:
center = vector.lonlat_to_vector(*center, degrees=degrees)
return cls(points, center)
# from_radec is an alias for from_lon_lat
from_radec = from_lonlat
@classmethod
def from_cone(cls, lon, lat, radius, degrees=True, steps=16):
r"""
Create a new `SingleSphericalPolygon` from a cone (otherwise known
as a "small circle") defined using (*lon*, *lat*, *radius*).
The cone is not represented as an ideal circle on the sphere,
but as a series of great circle arcs. The resolution of this
conversion can be controlled using the *steps* parameter.
Parameters
----------
lon, lat : float scalars
This defines the center of the cone
radius : float scalar
The radius of the cone
degrees : bool, optional
If `True`, (default) *lon*, *lat* and *radius* are in
decimal degrees, otherwise in radians.
steps : int, optional
The number of steps to use when converting the small
circle to a polygon.
Returns
-------
polygon : `SingleSphericalPolygon` object
"""
u, v, w = vector.lonlat_to_vector(lon, lat, degrees=degrees)
if degrees:
radius = np.deg2rad(radius)
# Get an arbitrary perpendicular vector. This be be obtained
# by crossing (u, v, w) with any unit vector that is not itself.
which_min = np.argmin([u*u, v*v, w*w])
if which_min == 0:
perp = np.cross([u, v, w], [1., 0., 0.])
elif which_min == 1:
perp = np.cross([u, v, w], [0., 1., 0.])
else:
perp = np.cross([u, v, w], [0., 0., 1.])
perp = vector.normalize_vector(perp)
# Rotate by radius around the perpendicular vector to get the
# "pen"
x, y, z = vector.rotate_around(
u, v, w, perp[0], perp[1], perp[2], radius, degrees=False)
# Then rotate the pen around the center point all 360 degrees
C = np.linspace(0, np.pi * 2.0, steps)
# Ensure that the first and last elements are exactly the
# same. 2π should equal 0, but with rounding error that isn't
# always the case.
C[-1] = 0
C = C[::-1]
X, Y, Z = vector.rotate_around(x, y, z, u, v, w, C, degrees=False)
return cls(np.dstack((X, Y, Z))[0], (u, v, w))
@classmethod
def from_wcs(cls, fitspath, steps=1, crval=None):
r"""
Create a new `SingleSphericalPolygon` from the footprint of a FITS
WCS specification.
This method requires having `astropy <http://astropy.org>`__
installed.
Parameters
----------
fitspath : path to a FITS file, `astropy.io.fits.Header`, or `astropy.wcs.WCS`
Refers to a FITS header containing a WCS specification.
steps : int, optional
The number of steps along each edge to convert into
polygon edges.
Returns
-------
polygon : `SingleSphericalPolygon` object
"""
from astropy import wcs as pywcs, version as astropy_ver
from astropy.io import fits
if isinstance(fitspath, fits.Header):
header = fitspath
wcs = pywcs.WCS(header)
elif isinstance(fitspath, pywcs.WCS):
wcs = fitspath
else:
wcs = pywcs.WCS(fitspath)
if crval is not None:
wcs.wcs.crval = crval
try:
xa, ya = wcs.pixel_shape
except AttributeError:
xa, ya = (wcs._naxis1, wcs._naxis2)
length = steps * 4 + 1
X = np.empty(length)
Y = np.empty(length)
# Now define each of the 4 edges of the quadrilateral
X[0 :steps ] = np.linspace(1, xa, steps, False)
Y[0 :steps ] = 1
X[steps :steps*2] = xa
Y[steps :steps*2] = np.linspace(1, ya, steps, False)
X[steps*2:steps*3] = np.linspace(xa, 1, steps, False)
Y[steps*2:steps*3] = ya
X[steps*3:steps*4] = 1
Y[steps*3:steps*4] = np.linspace(ya, 1, steps, False)
X[-1] = 1
Y[-1] = 1
# Use wcslib to convert to (lon, lat)
lon, lat = wcs.all_pix2world(X, Y, 1)
# Convert to Cartesian
x, y, z = vector.lonlat_to_vector(lon, lat)
# Calculate an inside point
lon, lat = wcs.all_pix2world(xa / 2.0, ya / 2.0, 1)
xc, yc, zc = vector.lonlat_to_vector(lon, lat)
return cls(np.dstack((x, y, z))[0], (xc, yc, zc))
@classmethod
def convex_hull(cls, points):
"""
Create a new `SingleSphericalPolygon` from the convex hull of a
list of points using the Graham Scan algorithm
Parameters
----------
points: A list of points on the unit sphere
Returns
-------
polygon : `SingleSphericalPolygon` object
"""
points = np.asarray(points)
# Find an extremal point, it must be on boundary
j = np.argmin(np.arctan2(points[:,1], points[:,0]))
extreme = points[j,:]
points = np.vstack((points[0:j,:], points[j+1:,:]))
# Sort points around extreme point by angle from true north
north = [0., 0., 1.]
ang = great_circle_arc.angle(north, extreme, points)
pt = [points[i,:] for i in range(points.shape[0])]
duo = list(zip(pt, ang))
duo = sorted(duo, key=lambda d: d[1])
points = np.asarray([d[0] for d in duo])
# Set the first point on the hull to the extreme point
pbottom = extreme
hull = [pbottom]
# If a point is to the left of previous points on the
# hull, add it to the hull. If to the right, the top
# point is an inside point and is popped off the hull.
# See any description of the Graham Scan algorithm
# for a more detailed explanation.
i = 0
inside = None
while i < points.shape[0]:
ptop = hull[-1]
if ptop is pbottom:
hull.append(points[i,:])
i += 1
else:
pprevious = hull[-2]
if great_circle_arc.triple_product(pprevious, ptop,
points[i,:]) > 0.0:
hull.append(points[i,:])
i += 1
else:
inside = hull.pop()
# Create a polygon from points on the hull
return cls(hull, inside)
def invert_polygon(self):
"""
Compute the inverse (complement) of a single polygon
"""
poly = self.copy()
poly._points = poly._points[::-1]
poly._inside = np.asanyarray(self._find_new_outside())
return poly
def _contains_point(self, point, P, r):
point = np.asanyarray(point)
if np.array_equal(r, point):
return True
intersects = great_circle_arc.intersects(P[:-1], P[1:], r, point)
crossings = np.sum(intersects)
return (crossings % 2) == 0
def contains_point(self, point):
r"""
Determines if this `SingleSphericalPolygon` contains a given point.
Parameters
----------
point : an (*x*, *y*, *z*) triple
The point to test.
Returns
-------
contains : bool
Returns `True` if the polygon contains the given *point*.
"""
return self._contains_point(point, self._points, self._inside)
def contains_lonlat(self, lon, lat, degrees=True):
r"""
Determines if this `SingleSphericalPolygon` contains a given
longitude and latitude.
Parameters
----------
lon, lat: Longitude and latitude. Must be scalars.
degrees : bool, optional
If `True`, (default) *lon* and *lat* are in decimal degrees,
otherwise in radians.
Returns
-------
contains : bool
Returns `True` if the polygon contains the given *point*.
"""
point = vector.lonlat_to_vector(lon, lat, degrees=degrees)
return self._contains_point(point, self._points, self._inside)
# Alias for contains_lonlat
contains_radec = contains_lonlat
def intersects_poly(self, other):
r"""
Determines if this `SingleSphericalPolygon` intersects another
`SingleSphericalPolygon`.
This method is much faster than actually computing the
intersection region between two polygons.
Parameters
----------
other : `SingleSphericalPolygon`
Returns
-------
intersects : bool
Returns `True` if this polygon intersects the *other*
polygon.
Notes
-----
The algorithm proceeds as follows:
1. Determine if any single point of one polygon is contained
within the other.
2. Deal with the case where only the edges overlap as in::
: o---------o
: o----+---------+----o
: | | | |
: o----+---------+----o
: o---------o
In this case, an edge from one polygon must cross an
edge from the other polygon.
"""
assert isinstance(other, SingleSphericalPolygon)
# The easy case is in which a point of one polygon is
# contained in the other polygon.
for point in other._points:
if self.contains_point(point):
return True
for point in self._points:
if other.contains_point(point):
return True
# The hard case is when only the edges overlap, as in:
#
# o---------o
# o----+---------+----o
# | | | |
# o----+---------+----o
# o---------o
#
for i in range(len(self._points) - 1):
A = self._points[i]
B = self._points[i+1]
if np.any(great_circle_arc.intersects(
A, B, other._points[:-1], other._points[1:])):
return True
return False
def intersects_arc(self, a, b):
"""
Determines if this `SingleSphericalPolygon` intersects or contains
the given arc.
"""
P = self._points
if self.contains_arc(a, b):
return True
intersects = great_circle_arc.intersects(P[:-1], P[1:], a, b)
return np.any(intersects)
def contains_arc(self, a, b):
"""
Returns `True` if the polygon fully encloses the arc given by a
and b.
"""
return self.contains_point(a) and self.contains_point(b)
def area(self):
r"""
Returns the area of the polygon on the unit sphere, in
steradians.
The area is computed using a generalization of Girard's Theorem.
if :math:`\theta` is the sum of the internal angles of the
polygon, and *n* is the number of vertices, the area is:
.. math::
S = \theta - (n - 2) \pi
The area can be negative if the points on the polygon are ordered
counter-clockwise. Take the absolute value if that is not desired.
"""
if len(self._points) < 3:
return np.array(0.0)
points = np.vstack((self._points, self._points[1]))
angles = great_circle_arc.angle(points[:-2], points[1:-1],
points[2:], degrees=False)
return np.sum(angles) - (len(angles) - 2) * np.pi
def union(self, other):
"""
Return a new `SphericalPolygon` that is the union of *self*
and *other*.
Parameters
----------
other : `SingleSphericalPolygon`
Returns
-------
polygon : `SphericalPolygon` object
See also
--------
SphericalPolygon.multi_union
Notes
-----
For implementation details, see the
:mod:`~spherical_geometry.graph` module.
"""
from . import graph
if len(self._points) < 3:
return SphericalPolygon([other.copy()])
elif len(other._points) < 3:
return SphericalPolygon([self.copy()])
g = graph.Graph([self, other])
return g.union()
def _find_new_inside(self):
"""
Finds an acceptable inside point inside of *points* that is
also inside of *polygons*.
"""
npoints = len(self._points)
if npoints > 4:
points = np.vstack((self._points, self._points[1]))
A = points[:-2]
B = points[1:-1]
C = points[2:]
orient = great_circle_arc.triple_product(A-B, C-B, B)
if np.sum(orient) < 0.0:
orient = -1.0 * orient
midpoint = great_circle_arc.midpoint(A, C)
candidate = max(zip(orient, midpoint), key=lambda x: x[0])
inside = candidate[1]
else:
# Fall back on computing the mean point
inside = self._points.mean(axis=0)
vector.normalize_vector(inside, output=inside)
return inside
def _find_new_outside(self):
"""
Finds an acceptable point outside of the polygon
"""
tagged_points = []
points = self._points[:-1]
# Compute the minimum distance between all polygon points
# and each antipode to a polygon point
for point in points:
point = -1.0 * point
dot = great_circle_arc.inner1d(point, points)
tag = np.amax(dot)
tagged_points.append((tag, point))
# find the antipode with the maximum distance
# to any polygon point. It is our outside point.
(tag, point) = min(tagged_points, key=lambda p: p[0])
return point
def intersection(self, other):
"""
Return a new `SphericalPolygon` that is the intersection of
*self* and *other*.
If the intersection is empty, a `SphericalPolygon` with zero
subpolyons will be returned.
Parameters
----------
other : `SingleSphericalPolygon`
Returns
-------
polygon : `SphericalPolygon` object
See also
--------
SphericalPolygon.multi_union
Notes
-----
For implementation details, see the
:mod:`~spherical_geometry.graph` module.
"""
from . import graph
if len(self._points) < 3 or len(other._points) < 3:
return SphericalPolygon([])
g = graph.Graph([self, other])
return g.intersection()
def overlap(self, other):
r"""
Returns the fraction of *self* that is overlapped by *other*.
Let *self* be *a* and *other* be *b*, then the overlap is
defined as:
.. math::
\frac{S_a}{S_{a \cap b}}
Parameters
----------
other : `SingleSphericalPolygon`
Returns
-------
frac : float
The fraction of *self* that is overlapped by *other*.
"""
s1 = self.area()
intersection = self.intersection(other)
s2 = intersection.area()
return abs(s2 / s1)
def draw(self, m, **plot_args):
"""
Draws the polygon in a matplotlib.Basemap axes.
Parameters
----------
m : Basemap axes object
**plot_args : Any plot arguments to pass to basemap
"""
if not len(self._points):
return
if not len(plot_args):
plot_args = {'color': 'blue'}
points = self._points
if 'alpha' in plot_args:
del plot_args['alpha']
alpha = 1.0
for A, B in zip(points[0:-1], points[1:]):
length = great_circle_arc.length(A, B, degrees=True)
if not np.isfinite(length):
length = 2
interpolated = great_circle_arc.interpolate(A, B, length * 4)
lon, lat = vector.vector_to_lonlat(
interpolated[:, 0], interpolated[:, 1], interpolated[:, 2],
degrees=True)
for lon0, lat0, lon1, lat1 in zip(lon[0:-1], lat[0:-1], lon[1:], lat[1:]):
m.drawgreatcircle(lon0, lat0, lon1, lat1, alpha=alpha, **plot_args)
alpha -= 1.0 / len(points)
lon, lat = vector.vector_to_lonlat(
*self._inside, degrees=True)
x, y = m(lon, lat)
m.scatter(x, y, 1, **plot_args)
# For backwards compatibility
_SingleSphericalPolygon = SingleSphericalPolygon
class SphericalPolygon(SingleSphericalPolygon):
r"""
Polygons are represented by both a set of points (in Cartesian
(*x*, *y*, *z*) normalized on the unit sphere), and an inside
point. The inside point is necessary, because both the inside and
outside of the polygon are finite areas on the great sphere, and
therefore we need a way of specifying which is which.
This class contains a list of disjoint closed polygons.
"""
def __init__(self, init, inside=None):
r"""
Parameters
----------
init : object
May be either:
- A list of disjoint `SphericalPolygon` objects.
- An Nx3 array of (*x*, *y*, *z*) triples in Cartesian
space. These points define the boundary of the
polygon.
It may contain zero points, in which it defines the
null polygon. It may not contain one or two points.
inside : An (*x*, *y*, *z*) triple, optional
If *init* is an array of points, this point must be inside
the polygon. If it is not provided, one will be created.
"""
from . import graph
for polygon in init:
if not isinstance(polygon, (SphericalPolygon, SingleSphericalPolygon)):
break
else:
self._polygons = tuple(init)
return
self._polygons = (SingleSphericalPolygon(init, inside),)
polygons = []
for polygon in self:
g = graph.Graph((polygon,))
polygons.extend(g.disjoint_polygons())
self._polygons = polygons
def __copy__(self):
return deepcopy(self)
copy = __copy__
def __len__(self):
return len(self._polygons)
def __repr__(self):
buffer = []
for polygon in self._polygons:
buffer.append(repr(polygon))
return '[' + ',\n'.join(buffer) + ']'
def __iter__(self):
"""
Iterate over all base polygons that make up this multi-polygon
set.
"""
for polygon in self._polygons:
for subpolygon in polygon:
yield subpolygon
# Alias for backwards compatibility
iter_polygons_flat = __iter__
@property
def points(self):
"""
The points defining the polygons. It is an iterator over
disjoint closed polygons, where each element is an Nx3 array
of (*x*, *y*, *z*) vectors. Each polygon is explicitly
closed, i.e., the first and last points are the same.
"""
for polygon in self:
yield polygon.points
@property
def inside(self):
"""
Iterate over the inside point of each of the polygons.
"""
for polygon in self:
yield polygon.inside
@property
def polygons(self):
"""
Get a sequence of all of the subpolygons. Each subpolygon may
itself have subpolygons. To get a flattened sequence of all
base polygons, use `iter_polygons_flat`.
"""
return self._polygons
def is_clockwise(self):
"""
Return True if all subpolygons are clockwise
"""
all = True
any = False
for polygon in self._polygons:
cw = polygon.is_clockwise()
all = all and cw
any = any or cw
if all and any:
cw = True
elif not all and not any:
cw = False
else:
cw = None
return cw
@staticmethod
def self_intersect(points):
"""
Return true if the path defined by a list of points
intersects itself
"""
from . import graph
polygon = SingleSphericalPolygon(points)
g = graph.Graph((polygon,))
return g._find_all_intersections()
def to_lonlat(self):
"""
Convert the `SphericalPolygon` footprint to longitude and latitude
coordinates.
Returns
-------
polyons : iterator
Each element in the iterator is a tuple of the form (*lon*,
*lat*), where each is an array of points.
"""
for polygon in self:
yield polygon.to_lonlat()
# to_ra_dec is an alias for to_lonlat
to_radec = to_lonlat
@classmethod
def from_lonlat(cls, lon, lat, center=None, degrees=True):
## TODO Move into SingleSphericalPolygon
r"""
Create a new `SphericalPolygon` from a list of
(*longitude*, *latitude*) points.
Parameters
----------
lon, lat : 1-D arrays of the same length
The vertices of the polygon in longitude and
latitude.
center : (*lon*, *lat*) pair, optional
A point inside of the polygon to define its inside.
degrees : bool, optional
If `True`, (default) *lon* and *lat* are in decimal degrees,
otherwise in radians.
Returns
-------
polygon : `SphericalPolygon` object
"""
polygon = SingleSphericalPolygon.from_lonlat(lon, lat,
center, degrees)
return cls((polygon,))
# from_radec is an alias for from_lon_lat
from_radec = from_lonlat
@classmethod
def from_cone(cls, lon, lat, radius, degrees=True, steps=16):
r"""
Create a new `SphericalPolygon` from a cone (otherwise known
as a "small circle") defined using (*lon*, *lat*, *radius*).
The cone is not represented as an ideal circle on the sphere,
but as a series of great circle arcs. The resolution of this
conversion can be controlled using the *steps* parameter.
Parameters
----------
lon, lat : float scalars
This defines the center of the cone
radius : float scalar
The radius of the cone
degrees : bool, optional
If `True`, (default) *lon*, *lat* and *radius* are in
decimal degrees, otherwise in radians.
steps : int, optional
The number of steps to use when converting the small
circle to a polygon.
Returns
-------
polygon : `SphericalPolygon` object
"""
polygon = SingleSphericalPolygon.from_cone(lon, lat, radius,
degrees=degrees, steps=steps)
return cls((polygon,))
@classmethod
def from_wcs(cls, fitspath, steps=1, crval=None):
r"""
Create a new `SphericalPolygon` from the footprint of a FITS
WCS specification.
This method requires having `astropy <http://astropy.org>`__
installed.
Parameters
----------
fitspath : path to a FITS file, `astropy.io.fits.Header`, or `astropy.wcs.WCS`
Refers to a FITS header containing a WCS specification.
steps : int, optional
The number of steps along each edge to convert into
polygon edges.
Returns
-------
polygon : `SphericalPolygon` object
"""
polygon = SingleSphericalPolygon.from_wcs(fitspath,
steps=steps, crval=crval)
return cls((polygon,))
@classmethod
def convex_hull(cls, points):
r"""
Create a new `SphericalPolygon` from the convex hull of a
list of points.
Parameters
----------
points: A list of points on the unit sphere
Returns
-------
polygon : `SphericalPolygon` object
"""
polygon = SingleSphericalPolygon.convex_hull(points)
return cls((polygon,))
def invert_polygon(self):
"""
Construct a polygon which is the inverse (complement) of the
original polygon
"""
if len(self._polygons) != 1:
raise RuntimeErrror("Can only invert a single polygon")
klass = self.__class__
inverted_polygon = self._polygons[0].invert_polygon()
return klass((inverted_polygon, ))
def contains_point(self, point):
r"""
Determines if this `SphericalPolygon` contains a given point.
Parameters
----------
point : an (*x*, *y*, *z*) triple
The point to test.
Returns
-------
contains : bool
Returns `True` if the polygon contains the given *point*.
"""
for polygon in self:
if polygon.contains_point(point):
return True
return False
def contains_lonlat(self, lon, lat, degrees=True):
r"""
Determines if this `SphericalPolygon` contains a given
longitude and latitude.
Parameters
----------
lon, lat: Longitude and latitude. Must be scalars.
degrees : bool, optional
If `True`, (default) *lon* and *lat* are in decimal degrees,
otherwise in radians.
Returns
-------
contains : bool
Returns `True` if the polygon contains the given *point*.
"""
for polygon in self:
if polygon.contains_lonlat(lon, lat, degrees=degrees):
return True
return False
# Alias for contains_lonlat
contains_radec = contains_lonlat
def intersects_poly(self, other):
r"""
Determines if this `SphericalPolygon` intersects another
`SphericalPolygon`.
This method is much faster than actually computing the
intersection region between two polygons.
Parameters
----------
other : `SphericalPolygon`
Returns
-------
intersects : bool
Returns `True` if this polygon intersects the *other*
polygon.
"""
assert isinstance(other, SphericalPolygon)
for polya in self:
for polyb in other:
if polya.intersects_poly(polyb):
return True
return False
def intersects_arc(self, a, b):
"""
Determines if this `SphericalPolygon` intersects or contains
the given arc.
"""
for subpolygon in self:
if subpolygon.intersects_arc(a, b):
return True
return False
def contains_arc(self, a, b):
"""
Returns `True` if the polygon fully encloses the arc given by a
and b.
"""
for subpolygon in self:
if subpolygon.contains_arc(a, b):
return True
return False
def area(self):
r"""
Returns the area of the polygon on the unit sphere in
steradians.
The area is computed using a generalization of Girard's Theorem.
if :math:`\theta` is the sum of the internal angles of the
polygon, and *n* is the number of vertices, the area is:
.. math::
S = \theta - (n - 2) \pi
"""
area = 0.0
for subpoly in self:
area += subpoly.area()
return area
def union(self, other):
"""
Return a new `SphericalPolygon` that is the union of *self*
and *other*.
Parameters
----------
other : `SphericalPolygon`
Returns
-------
polygon : `SphericalPolygon` object
See also
--------
multi_union
Notes
-----
For implementation details, see the :mod:`~spherical_geometry.graph`
module.
"""
from . import graph
if self.area() == 0.0:
return other.copy()
elif other.area() == 0.0:
return self.copy()
g = graph.Graph(list(self.iter_polygons_flat()) +
list(other.iter_polygons_flat()))
return g.union()
@classmethod
def multi_union(cls, polygons):
"""
Return a new `SphericalPolygon` that is the union of all of the
polygons in *polygons*.
Parameters
----------
polygons : sequence of `SphericalPolygon`
Returns
-------
polygon : `SphericalPolygon` object
See also
--------
union
"""
assert len(polygons)
for polygon in polygons:
assert isinstance(polygon, SphericalPolygon)
from . import graph
all_polygons = []
for polygon in polygons:
all_polygons.extend(polygon.iter_polygons_flat())
g = graph.Graph(all_polygons)
return g.union()
def intersection(self, other):
"""
Return a new `SphericalPolygon` that is the intersection of
*self* and *other*.
If the intersection is empty, a `SphericalPolygon` with zero
subpolygons will be returned.
Parameters
----------
other : `SphericalPolygon`
Returns
-------
polygon : `SphericalPolygon` object
Notes
-----
For implementation details, see the
:mod:`~spherical_geometry.graph` module.
"""
if self.area() == 0.0:
return SphericalPolygon([])
elif other.area() == 0.0:
return SphericalPolygon([])
all_polygons = []
for polya in self:
for polyb in other:
if polya.intersects_poly(polyb):
subpolygons = polya.intersection(polyb)
all_polygons.extend(subpolygons.iter_polygons_flat())
return SphericalPolygon(all_polygons)
@classmethod
def multi_intersection(cls, polygons):
"""
Return a new `SphericalPolygon` that is the intersection of
all of the polygons in *polygons*.
Parameters
----------
polygons : sequence of `SphericalPolygon`
Returns
-------
polygon : `SphericalPolygon` object
"""
assert len(polygons)
for polygon in polygons:
assert isinstance(polygon, SphericalPolygon)
results = None
for polygon in polygons:
if results is None:
results = polygon
elif len(results.polygons) == 0:
return results
else:
results = results.intersection(polygon)
return results
def draw(self, m, **plot_args):
"""
Draws the polygon in a matplotlib.Basemap axes.
Parameters
----------
m : Basemap axes object
**plot_args : Any plot arguments to pass to basemap
"""
for polygon in self._polygons:
polygon.draw(m, **plot_args)
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