# Licensed under a 3-clause BSD style license - see LICENSE.rst
"""Regions helper functions.
Throughout Gammapy, we use `regions` to represent and work with regions.
https://astropy-regions.readthedocs.io
We might add in other conveniences and features here, e.g. sky coord contains
without a WCS (see "sky and pixel regions" in PIG 10), or some HEALPix integration.
"""
import operator
import numpy as np
from scipy.optimize import Bounds, minimize
from astropy import units as u
from astropy.coordinates import SkyCoord
from astropy.table import Table
from gammapy.utils.scripts import make_path
from regions import (
CircleAnnulusSkyRegion,
CircleSkyRegion,
CompoundSkyRegion,
EllipseSkyRegion,
RectangleSkyRegion,
Regions,
PolygonSkyRegion,
PolygonPixelRegion,
)
from regions.core.pixcoord import PixCoord
from regions.core.metadata import RegionMeta, RegionVisual
from regions._utils.wcs_helpers import pixel_scale_angle_at_skycoord
__all__ = [
"compound_region_to_regions",
"make_concentric_annulus_sky_regions",
"make_orthogonal_rectangle_sky_regions",
"regions_to_compound_region",
"region_to_frame",
]
def compound_region_center(compound_region):
"""Compute center for a CompoundRegion.
The center of the compound region is defined here as the geometric median
of the individual centers of the regions. The geometric median is defined
as the point the minimises the distance to all other points.
Parameters
----------
compound_region : `CompoundRegion`
Compound region.
Returns
-------
center : `~astropy.coordinates.SkyCoord`
Geometric median of the positions of the individual regions.
"""
regions = compound_region_to_regions(compound_region)
if len(regions) == 1:
return regions[0].center
positions = SkyCoord([region.center.icrs for region in regions])
def f(x, coords):
"""Function to minimize."""
lon, lat = x
center = SkyCoord(lon * u.deg, lat * u.deg)
return np.sum(center.separation(coords).deg)
ra, dec = positions.ra.wrap_at("180d").deg, positions.dec.deg
ub = np.array([np.max(ra), np.max(dec)])
lb = np.array([np.min(ra), np.min(dec)])
if np.all(ub == lb):
bounds = None
else:
bounds = Bounds(ub=ub, lb=lb)
result = minimize(
f,
x0=[np.mean(ra), np.mean(dec)],
args=(positions,),
bounds=bounds,
method="L-BFGS-B",
)
return SkyCoord(result.x[0], result.x[1], frame="icrs", unit="deg")
[docs]
def compound_region_to_regions(region):
"""Create list of regions from compound regions.
Parameters
----------
region : `~regions.CompoundSkyRegion` or `~regions.SkyRegion`
Compound sky region.
Returns
-------
regions : `~regions.Regions`
List of regions.
"""
regions = Regions([])
if isinstance(region, CompoundSkyRegion):
if region.operator is operator.or_:
regions_1 = compound_region_to_regions(region.region1)
regions.extend(regions_1)
regions_2 = compound_region_to_regions(region.region2)
regions.extend(regions_2)
else:
raise ValueError("Only union operator supported")
else:
return Regions([region])
return regions
[docs]
def regions_to_compound_region(regions):
"""Create compound region from list of regions, by creating the union.
Parameters
----------
regions : `~regions.Regions`
List of regions.
Returns
-------
compound : `~regions.CompoundSkyRegion` or `~regions.CompoundPixelRegion`
Compound sky region.
"""
region_union = regions[0]
for region in regions[1:]:
region_union = region_union.union(region)
return region_union
def get_centroid(vertices):
"""Compute centroid of a polygon. Implicitly assumes a flat
cartesian projection, will probably break for very large polygons.
Code comes from:
https://stackoverflow.com/questions/75699024/finding-the-centroid-of-a-polygon-in-python
Parameters
----------
vertices : `~astropy.coordinates.SkyCoord`
List of vertices.
Returns
-------
centroid : `~astropy.coordinates.SkyCoord`
Centroid of the polygon.
"""
polygon = []
for vertex in vertices:
polygon.append((vertex.ra.degree, vertex.dec.degree))
polygon = np.array(polygon)
# Same polygon, but with vertices cycled around. Now the polygon
# decomposes into triangles of the form origin-polygon[i]-polygon2[i]
polygon2 = np.roll(polygon, -1, axis=0)
# Compute signed area of each triangle
signed_areas = 0.5 * np.cross(polygon, polygon2)
# Compute centroid of each triangle
centroids = (polygon + polygon2) / 3.0
# Get average of those centroids, weighted by the signed areas.
centroid = np.average(centroids, axis=0, weights=signed_areas)
return SkyCoord(centroid[0] * u.deg, centroid[1] * u.deg, frame=vertices.frame)
class SphericalCircleSkyRegion(CircleSkyRegion):
"""Spherical circle sky region.
TODO: is this separate class a good idea?
- If yes, we could move it to the ``regions`` package?
- If no, we should implement some other solution.
Probably the alternative is to add extra methods to
the ``CircleSkyRegion`` class and have that support
both planar approximation and spherical case?
Or we go with the approach to always make a
TAN WCS and not have true cone select at all?
"""
def contains(self, skycoord, wcs=None):
"""Defined by spherical distance."""
separation = self.center.separation(skycoord)
return separation < self.radius
class PolygonPointsSkyRegion(PolygonSkyRegion):
"""Polygon sky region defined by a list of points."""
def __init__(self, vertices, meta=None, visual=None):
"""Create a polygon sky region.
Parameters
----------
vertices : `~astropy.coordinates.SkyCoord`
List of vertices.
meta : `~regions.RegionMeta`, optional
Region meta data.
visual : `~regions.RegionVisual`, optional
Region visual meta data.
"""
self.vertices = vertices
self.meta = meta or RegionMeta()
self.center = get_centroid(vertices)
self.visual = visual or RegionVisual()
def to_pixel(self, wcs):
"""Convert to pixel region."""
x, y = wcs.world_to_pixel(self.vertices)
center, _, _ = pixel_scale_angle_at_skycoord(self.center, wcs)
vertices_pix = PixCoord(x, y)
return PolygonPointsPixelRegion(
vertices_pix,
center=center,
meta=self.meta.copy(),
visual=self.visual.copy(),
)
class PolygonPointsPixelRegion(PolygonPixelRegion):
"""Polygon pixel region defined by a list of points."""
def __init__(self, vertices, center=None, meta=None, visual=None, origin=None):
"""Create a polygon pixel region.
Parameters
----------
vertices : `~regions.PixCoord`
List of vertices.
center : `~regions.PixCoord`, optional
Center of the region.
meta : `~regions.RegionMeta`, optional
Region meta data.
visual : `~regions.RegionVisual`, optional
Region visual meta data.
origin : `~regions.PixCoord`, optional
Origin of the region. Default is `PixCoord(0, 0)`
"""
if origin is None:
origin = PixCoord(0, 0)
self._vertices = vertices
self.meta = meta or RegionMeta()
self.visual = visual or RegionVisual()
self.origin = origin
self.vertices = vertices + origin
self.center = center
def to_sky(self, wcs):
"""Convert to sky region.
Parameters
----------
wcs : `~astropy.wcs.WCS`
WCS transformation object.
"""
vertices_sky = wcs.pixel_to_world(self.vertices.x, self.vertices.y)
return PolygonPointsSkyRegion(
vertices=vertices_sky, meta=self.meta.copy(), visual=self.visual.copy()
)
def rotate(self, center, angle):
"""
Rotate the region.
Positive ``angle`` corresponds to counter-clockwise rotation.
Parameters
----------
center : `~regions.PixCoord`
The rotation center point.
angle : `~astropy.coordinates.Angle`
The rotation angle.
Returns
-------
region : `PolygonPixelRegion`
The rotated region (which is an independent copy).
"""
vertices = self.vertices.rotate(center, angle)
center = self.center.rotate(center, angle)
return self.copy(vertices=vertices, center=center)
[docs]
def make_orthogonal_rectangle_sky_regions(start_pos, end_pos, wcs, height, nbin=1):
"""Utility returning an array of regions to make orthogonal projections.
Parameters
----------
start_pos : `~astropy.regions.SkyCoord`
First sky coordinate defining the line to which the orthogonal boxes made.
end_pos : `~astropy.regions.SkyCoord`
Second sky coordinate defining the line to which the orthogonal boxes made.
height : `~astropy.quantity.Quantity`
Height of the rectangle region.
wcs : `~astropy.wcs.WCS`
WCS projection object.
nbin : int, optional
Number of boxes along the line. Default is 1.
Returns
-------
regions : list of `~regions.RectangleSkyRegion`
Regions in which the profiles are made.
"""
pix_start = start_pos.to_pixel(wcs)
pix_stop = end_pos.to_pixel(wcs)
points = np.linspace(start=pix_start, stop=pix_stop, num=nbin + 1).T
centers = 0.5 * (points[:, :-1] + points[:, 1:])
coords = SkyCoord.from_pixel(centers[0], centers[1], wcs)
width = start_pos.separation(end_pos).to("rad") / nbin
angle = end_pos.position_angle(start_pos) - 90 * u.deg
regions = []
for center in coords:
reg = RectangleSkyRegion(
center=center, width=width, height=u.Quantity(height), angle=angle
)
regions.append(reg)
return regions
[docs]
def make_concentric_annulus_sky_regions(
center, radius_max, radius_min=1e-5 * u.deg, nbin=11
):
"""Make a list of concentric annulus regions.
Parameters
----------
center : `~astropy.coordinates.SkyCoord`
Center coordinate.
radius_max : `~astropy.units.Quantity`
Maximum radius.
radius_min : `~astropy.units.Quantity`, optional
Minimum radius. Default is 1e-5 deg.
nbin : int, optional
Number of boxes along the line. Default is 11.
Returns
-------
regions : list of `~regions.RectangleSkyRegion`
Regions in which the profiles are made.
"""
regions = []
edges = np.linspace(radius_min, u.Quantity(radius_max), nbin)
for r_in, r_out in zip(edges[:-1], edges[1:]):
region = CircleAnnulusSkyRegion(
center=center,
inner_radius=r_in,
outer_radius=r_out,
)
regions.append(region)
return regions
[docs]
def region_to_frame(region, frame):
"""Convert a region to a different frame.
Parameters
----------
region : `~regions.SkyRegion`
Region to transform.
frame : {"icrs", "galactic"}
Frame to transform the region into.
Returns
-------
region_new : `~regions.SkyRegion`
Region in the given frame.
"""
from gammapy.maps import WcsGeom
wcs = WcsGeom.create(skydir=region.center, binsz=0.01, frame=frame).wcs
region_new = region.to_pixel(wcs).to_sky(wcs)
return region_new
def region_circle_to_ellipse(region):
"""Convert a CircleSkyRegion to an EllipseSkyRegion.
Parameters
----------
region : `~regions.CircleSkyRegion`
Region to transform.
Returns
-------
region_new : `~regions.EllipseSkyRegion`
Elliptical region with same major and minor axis.
"""
region_new = EllipseSkyRegion(
center=region.center, width=region.radius, height=region.radius
)
return region_new
def extract_bright_star_regions(
geom, max_star_mag=6, star_rad=0.3 * u.deg, star_table=None
):
"""
Find bright star exclusion regions from a catalog `~astropy.table.Table`
contained in a given `~gammapy.maps.Geom` and returns a list of `~regions.CircleSkyRegion`.
Parameters
----------
geom : `~gammapy.maps.WcsGeom`
WcsGeom within which to search for bright stars
max_star_mag : float, optional
The maximum stellar magnitude (Johnson-Cousins B-band) to exclude. Default is 6th magnitude.
star_rad : `~astropy.units.Quantity`, optional
Radius to exclude around each star. Default is 0.3 degrees.
star_table : str, optional
Full name of the file containing a table containing the list of stars to search for exclusion regions.
If None, the Hipparcos Catalog (Perryman et al., 1997) contained in ``$GAMMAPY_DATA//veritas/crab-point-like-ED`` is used.
The table's column names should match those in ``$GAMMAPY_DATA//veritas/crab-point-like-ED``.
Default is None.
Returns
-------
regions : list of `~regions.CircleSkyRegion`
Star exclusion regions.
"""
regions = []
if star_table is None:
filename = make_path(
"$GAMMAPY_DATA/veritas/crab-point-like-ED/Hipparcos_MAG8_1997.dat"
)
star_cat = Table.read(filename, format="ascii.commented_header")
else:
star_cat = Table.read(star_table)
star_mask = geom.contains(
SkyCoord(star_cat["_RAJ2000"] * u.deg, star_cat["_DEJ2000"] * u.deg)
)
for src in star_cat[
(star_mask) & (star_cat["B-V"] + star_cat["Vmag"] < max_star_mag)
]:
regions.append(
CircleSkyRegion(
center=SkyCoord(
src["_RAJ2000"], src["_DEJ2000"], unit="deg", frame="icrs"
),
radius=star_rad,
)
)
return regions
