# Licensed under a 3-clause BSD style license - see LICENSE.rst
import copy
from functools import lru_cache
import numpy as np
import astropy.units as u
from astropy.convolution import Tophat2DKernel
from astropy.coordinates import Angle, SkyCoord
from astropy.io import fits
from astropy.nddata import Cutout2D
from astropy.nddata.utils import overlap_slices
from astropy.utils import lazyproperty
from astropy.wcs import WCS
from astropy.wcs.utils import (
celestial_frame_to_wcs,
proj_plane_pixel_scales,
wcs_to_celestial_frame,
)
from regions import RectangleSkyRegion
from gammapy.utils.array import round_up_to_even, round_up_to_odd
from ..axes import MapAxes
from ..coord import MapCoord, skycoord_to_lonlat
from ..geom import Geom, get_shape, pix_tuple_to_idx
from ..utils import INVALID_INDEX, _check_binsz, _check_width
__all__ = ["WcsGeom"]
def cast_to_shape(param, shape, dtype):
"""Cast a tuple of parameter arrays to a given shape."""
if not isinstance(param, tuple):
param = [param]
param = [np.array(p, ndmin=1, dtype=dtype) for p in param]
if len(param) == 1:
param = [param[0].copy(), param[0].copy()]
for i, p in enumerate(param):
if p.size > 1 and p.shape != shape:
raise ValueError
if p.shape == shape:
continue
param[i] = p * np.ones(shape, dtype=dtype)
return tuple(param)
def get_resampled_wcs(wcs, factor, downsampled):
"""Get resampled WCS object."""
wcs = wcs.deepcopy()
if not downsampled:
factor = 1.0 / factor
wcs.wcs.cdelt *= factor
wcs.wcs.crpix = (wcs.wcs.crpix - 0.5) / factor + 0.5
return wcs
[docs]
class WcsGeom(Geom):
"""Geometry class for WCS maps.
This class encapsulates both the WCS transformation object and
the image extent (number of pixels in each dimension). Provides
methods for accessing the properties of the WCS object and
performing transformations between pixel and world coordinates.
Parameters
----------
wcs : `~astropy.wcs.WCS`
WCS projection object.
npix : tuple
Number of pixels in each spatial dimension.
cdelt : tuple
Pixel size in each image plane. If None then a constant pixel size will be used.
crpix : tuple
Reference pixel coordinate in each image plane.
axes : list
Axes for non-spatial dimensions.
"""
_slice_spatial_axes = slice(0, 2)
_slice_non_spatial_axes = slice(2, None)
is_hpx = False
is_region = False
def __init__(self, wcs, npix=None, cdelt=None, crpix=None, axes=None):
self._wcs = wcs
self._frame = wcs_to_celestial_frame(wcs).name
self._projection = wcs.wcs.ctype[0][5:]
self._axes = MapAxes.from_default(axes, n_spatial_axes=2)
if npix is None:
if wcs.array_shape is not None:
npix = wcs.array_shape[::-1]
else:
npix = (0, 0)
if cdelt is None:
cdelt = tuple(np.abs(self.wcs.wcs.cdelt))
# Shape to use for WCS transformations
wcs_shape = max([get_shape(t) for t in [npix, cdelt]])
self._npix = cast_to_shape(npix, wcs_shape, int)
self._cdelt = cast_to_shape(cdelt, wcs_shape, float)
# By convention CRPIX is indexed from 1
if crpix is None:
crpix = tuple(1.0 + (np.array(self._npix) - 1.0) / 2.0)
self._crpix = crpix
# define cached methods
self.get_coord = lru_cache()(self.get_coord)
self.get_pix = lru_cache()(self.get_pix)
def __setstate__(self, state):
for key, value in state.items():
if key in ["get_coord", "get_pix"]:
state[key] = lru_cache()(value)
self.__dict__ = state
@property
def data_shape(self):
"""Shape of the `~numpy.ndarray` matching this geometry."""
return self._shape[::-1]
@property
def axes_names(self):
"""All axes names."""
return ["lon", "lat"] + self.axes.names
@property
def data_shape_axes(self):
"""Shape of data of the non-spatial axes and unit spatial axes."""
return self.axes.shape[::-1] + (1, 1)
@property
def data_shape_image(self):
"""Shape of data of the spatial axes and unit non-spatial axes."""
return (1,) * len(self.axes) + self.data_shape[len(self.axes) :]
@property
def _shape(self):
npix_shape = tuple([np.max(self.npix[0]), np.max(self.npix[1])])
return npix_shape + self.axes.shape
@property
def _shape_edges(self):
npix_shape = tuple([np.max(self.npix[0]) + 1, np.max(self.npix[1]) + 1])
return npix_shape + self.axes.shape
@property
def shape_axes(self):
"""Shape of non-spatial axes."""
return self._shape[self._slice_non_spatial_axes]
@property
def wcs(self):
"""WCS projection object."""
return self._wcs
@property
def frame(self):
"""Coordinate system of the projection.
Galactic ("galactic") or Equatorial ("icrs").
"""
return self._frame
[docs]
def cutout_slices(self, geom, mode="partial"):
"""Compute cutout slices.
Parameters
----------
geom : `WcsGeom`
Parent geometry.
mode : {"trim", "partial", "strict"}, optional
Cutout slices mode. Default is "partial".
Returns
-------
slices : dict
Dictionary containing "parent-slices" and "cutout-slices".
"""
position = geom.to_image().coord_to_pix(self.center_skydir)
slices = overlap_slices(
large_array_shape=geom.data_shape[-2:],
small_array_shape=self.data_shape[-2:],
position=[_[0] for _ in position[::-1]],
mode=mode,
)
return {
"parent-slices": slices[0],
"cutout-slices": slices[1],
}
@property
def projection(self):
"""Map projection."""
return self._projection
@property
def is_allsky(self):
"""Flag for all-sky maps."""
if np.all(np.isclose(self._npix[0] * self._cdelt[0], 360.0)) and np.all(
np.isclose(self._npix[1] * self._cdelt[1], 180.0)
):
return True
else:
return False
@property
def is_regular(self):
"""If geometry is regular in non-spatial dimensions as a boolean.
- False for multi-resolution or irregular geometries.
- True if all image planes have the same pixel geometry.
"""
if self.npix[0].size > 1:
return False
else:
return True
@property
def width(self):
"""Tuple with image dimension in degrees in longitude and latitude."""
dlon = self._cdelt[0] * self._npix[0]
dlat = self._cdelt[1] * self._npix[1]
return (dlon, dlat) * u.deg
@property
def pixel_area(self):
"""Pixel area in deg^2."""
# FIXME: Correctly compute solid angle for projection
return self._cdelt[0] * self._cdelt[1]
@property
def npix(self):
"""Tuple with image dimension in pixels in longitude and latitude."""
return self._npix
@property
def axes(self):
"""List of non-spatial axes."""
return self._axes
@property
def ndim(self):
return len(self.data_shape)
@property
def center_coord(self):
"""Map coordinate of the center of the geometry.
Returns
-------
coord : tuple
"""
return self.pix_to_coord(self.center_pix)
@property
def center_pix(self):
"""Pixel coordinate of the center of the geometry.
Returns
-------
pix : tuple
"""
return tuple((np.array(self.data_shape) - 1.0) / 2)[::-1]
@property
def center_skydir(self):
"""Sky coordinate of the center of the geometry.
Returns
-------
pix : `~astropy.coordinates.SkyCoord`
"""
return SkyCoord.from_pixel(self.center_pix[0], self.center_pix[1], self.wcs)
@property
def pixel_scales(self):
"""
Pixel scale.
Returns angles along each axis of the image at the CRPIX location once
it is projected onto the plane of intermediate world coordinates.
Returns
-------
angle: `~astropy.coordinates.Angle`
"""
return Angle(proj_plane_pixel_scales(self.wcs), "deg")
[docs]
@classmethod
def create(
cls,
npix=None,
binsz=0.5,
proj="CAR",
frame="icrs",
refpix=None,
axes=None,
skydir=None,
width=None,
):
"""Create a WCS geometry object.
Pixelization of the map is set with
``binsz`` and one of either ``npix`` or ``width`` arguments.
For maps with non-spatial dimensions a different pixelization
can be used for each image plane by passing a list or array
argument for any of the pixelization parameters. If both npix
and width are None then an all-sky geometry will be created.
Parameters
----------
npix : int or tuple or list, optional
Width of the map in pixels. A tuple will be interpreted as
parameters for longitude and latitude axes. For maps with
non-spatial dimensions, list input can be used to define a
different map width in each image plane. This option
supersedes width. Default is None.
binsz : float or tuple or list, optional
Map pixel size in degrees. A tuple will be interpreted
as parameters for longitude and latitude axes. For maps
with non-spatial dimensions, list input can be used to
define a different bin size in each image plane.
Default is 0.5
proj : string, optional
Any valid WCS projection type. Default is 'CAR' (Plate-Carrée projection).
See `WCS supported projections <https://docs.astropy.org/en/stable/wcs/supported_projections.html>`__ # noqa: E501
frame : {"icrs", "galactic"}, optional
Coordinate system, either Galactic ("galactic") or Equatorial ("icrs").
Default is "icrs".
refpix : tuple, optional
Reference pixel of the projection. If None this will be
set to the center of the map. Default is None.
axes : list, optional
List of non-spatial axes.
skydir : tuple or `~astropy.coordinates.SkyCoord`, optional
Sky position of map center. Can be either a SkyCoord
object or a tuple of longitude and latitude in deg in the
coordinate system of the map. Default is None.
width : float or tuple or list or string, optional
Width of the map in degrees. A tuple will be interpreted
as parameters for longitude and latitude axes. For maps
with non-spatial dimensions, list input can be used to
define a different map width in each image plane.
Default is None.
Returns
-------
geom : `~WcsGeom`
A WCS geometry object.
Examples
--------
>>> from gammapy.maps import WcsGeom
>>> from gammapy.maps import MapAxis
>>> axis = MapAxis.from_bounds(0,1,2)
>>> geom = WcsGeom.create(npix=(100,100), binsz=0.1)
>>> geom = WcsGeom.create(npix=(100,100), binsz="0.1deg")
>>> geom = WcsGeom.create(npix=[100,200], binsz=[0.1,0.05], axes=[axis])
>>> geom = WcsGeom.create(npix=[100,200], binsz=["0.1deg","0.05deg"], axes=[axis])
>>> geom = WcsGeom.create(width=[5.0,8.0], binsz=[0.1,0.05], axes=[axis])
>>> geom = WcsGeom.create(npix=([100,200],[100,200]), binsz=0.1, axes=[axis])
"""
if skydir is None:
crval = (0.0, 0.0)
elif isinstance(skydir, tuple):
crval = skydir
elif isinstance(skydir, SkyCoord):
xref, yref, frame = skycoord_to_lonlat(skydir, frame=frame)
crval = (xref, yref)
else:
raise ValueError(f"Invalid type for skydir: {type(skydir)!r}")
if width is not None:
width = _check_width(width)
binsz = _check_binsz(binsz)
shape = max([get_shape(t) for t in [npix, binsz, width]])
binsz = cast_to_shape(binsz, shape, float)
# If both npix and width are None then create an all-sky geometry
if npix is None and width is None:
width = (360.0, 180.0)
if npix is None:
width = cast_to_shape(width, shape, float)
npix = (
np.rint(width[0] / binsz[0]).astype(int),
np.rint(width[1] / binsz[1]).astype(int),
)
else:
npix = cast_to_shape(npix, shape, int)
if refpix is None:
nxpix = int(npix[0].flat[0])
nypix = int(npix[1].flat[0])
refpix = ((nxpix + 1) / 2.0, (nypix + 1) / 2.0)
# get frame class
frame = SkyCoord(np.nan, np.nan, frame=frame, unit="deg").frame
wcs = celestial_frame_to_wcs(frame, projection=proj)
wcs.wcs.crpix = refpix
wcs.wcs.crval = crval
cdelt = (-binsz[0].flat[0], binsz[1].flat[0])
wcs.wcs.cdelt = cdelt
wcs.array_shape = npix[1].flat[0], npix[0].flat[0]
wcs.wcs.datfix()
return cls(wcs, npix, cdelt=binsz, axes=axes)
@property
def footprint(self):
"""Footprint of the geometry as a `~astropy.coordinates.SkyCoord`."""
coords = self.wcs.calc_footprint()
return SkyCoord(coords, frame=self.frame, unit="deg")
@property
def footprint_rectangle_sky_region(self):
"""Footprint of the geometry as a `~regions.RectangleSkyRegion`."""
width, height = self.width
return RectangleSkyRegion(
center=self.center_skydir, width=width[0], height=height[0]
)
[docs]
@classmethod
def from_aligned(cls, geom, skydir, width):
"""Create an aligned geometry from an existing one.
Parameters
----------
geom : `~WcsGeom`
A reference WCS geometry object.
skydir : tuple or `~astropy.coordinates.SkyCoord`
Sky position of map center. Can be either a SkyCoord
object or a tuple of longitude and latitude in degrees in the
coordinate system of the map.
width : float or tuple or list or string
Width of the map in degrees. A tuple will be interpreted
as parameters for longitude and latitude axes. For maps
with non-spatial dimensions, list input can be used to
define a different map width in each image plane.
Returns
-------
geom : `~WcsGeom`
An aligned WCS geometry object with specified size and center.
"""
width = _check_width(width) * u.deg
npix = tuple(np.round(width / geom.pixel_scales).astype(int))
xref, yref = geom.to_image().coord_to_pix(skydir)
xref = int(np.floor(-xref[0] + npix[0] / 2.0)) + geom.wcs.wcs.crpix[0]
yref = int(np.floor(-yref[0] + npix[1] / 2.0)) + geom.wcs.wcs.crpix[1]
return cls.create(
skydir=tuple(geom.wcs.wcs.crval),
npix=npix,
refpix=(xref, yref),
frame=geom.frame,
binsz=tuple(geom.pixel_scales.deg),
axes=geom.axes,
proj=geom.projection,
)
def _make_bands_cols(self):
cols = []
if not self.is_regular:
cols += [
fits.Column(
"NPIX",
"2I",
dim="(2)",
array=np.vstack((np.ravel(self.npix[0]), np.ravel(self.npix[1]))).T,
)
]
cols += [
fits.Column(
"CDELT",
"2E",
dim="(2)",
array=np.vstack(
(np.ravel(self._cdelt[0]), np.ravel(self._cdelt[1]))
).T,
)
]
cols += [
fits.Column(
"CRPIX",
"2E",
dim="(2)",
array=np.vstack(
(np.ravel(self._crpix[0]), np.ravel(self._crpix[1]))
).T,
)
]
return cols
[docs]
def get_idx(self, idx=None, flat=False):
pix = self.get_pix(idx=idx, mode="center")
if flat:
pix = tuple([p[np.isfinite(p)] for p in pix])
return pix_tuple_to_idx(pix)
def _get_pix_all(
self, idx=None, mode="center", sparse=False, axis_name=("lon", "lat")
):
"""Get index coordinate array without footprint of the projection applied."""
pix_all = []
for name, nbin in zip(self.axes_names, self._shape):
if mode == "edges" and name in axis_name:
pix = np.arange(-0.5, nbin, dtype=float)
else:
pix = np.arange(nbin, dtype=float)
pix_all.append(pix)
# TODO: improve varying bin size coordinate handling
if idx is not None:
pix_all = pix_all[self._slice_spatial_axes] + [float(t) for t in idx]
return np.meshgrid(*pix_all[::-1], indexing="ij", sparse=sparse)[::-1]
[docs]
def get_pix(self, idx=None, mode="center"):
"""Get map pixel coordinates from the geometry.
Parameters
----------
mode : {'center', 'edges'}, optional
Get center or edge pix coordinates for the spatial axes.
Default is "center".
Returns
-------
coord : tuple
Map pixel coordinate tuple.
"""
pix = self._get_pix_all(idx=idx, mode=mode)
coords = self.pix_to_coord(pix)
m = np.isfinite(coords[0])
for _ in pix:
_[~m] = INVALID_INDEX.float
return pix
[docs]
def get_coord(
self, idx=None, mode="center", frame=None, sparse=False, axis_name=None
):
"""Get map coordinates from the geometry.
Parameters
----------
mode : {'center', 'edges'}, optional
Get center or edge coordinates for the spatial axes.
Default is "center".
frame : str or `~astropy.coordinates.Frame`, optional
Coordinate frame. Default is None.
sparse : bool, optional
Compute sparse coordinates. Default is False.
axis_name : str, optional
If mode = "edges", the edges will be returned for this axis.
Default is None.
Returns
-------
coord : `~MapCoord`
Map coordinate object.
"""
if axis_name is None:
axis_name = ("lon", "lat")
if frame is None:
frame = self.frame
pix = self._get_pix_all(idx=idx, mode=mode, sparse=sparse, axis_name=axis_name)
data = self.pix_to_coord(pix)
coords = MapCoord.create(
data=data, frame=self.frame, axis_names=self.axes.names
)
return coords.to_frame(frame)
[docs]
def coord_to_pix(self, coords):
coords = MapCoord.create(coords, frame=self.frame, axis_names=self.axes.names)
if coords.size == 0:
return tuple([np.array([]) for i in range(coords.ndim)])
# Variable Bin Size
if not self.is_regular:
idxs = self.axes.coord_to_idx(coords, clip=True)
crpix = [t[idxs] for t in self._crpix]
cdelt = [t[idxs] for t in self._cdelt]
pix = world2pix(self.wcs, cdelt, crpix, (coords.lon, coords.lat))
pix = list(pix)
else:
pix = self._wcs.wcs_world2pix(coords.lon, coords.lat, 0)
pix += self.axes.coord_to_pix(coords)
return tuple(pix)
[docs]
def pix_to_coord(self, pix):
# Variable Bin Size
if not self.is_regular:
idxs = pix_tuple_to_idx(pix[self._slice_non_spatial_axes])
crpix = [t[idxs] for t in self._crpix]
cdelt = [t[idxs] for t in self._cdelt]
coords = pix2world(self.wcs, cdelt, crpix, pix[self._slice_spatial_axes])
else:
coords = self._wcs.wcs_pix2world(pix[0], pix[1], 0)
coords = (
u.Quantity(coords[0], unit="deg", copy=False),
u.Quantity(coords[1], unit="deg", copy=False),
)
coords += self.axes.pix_to_coord(pix[self._slice_non_spatial_axes])
return coords
[docs]
def pix_to_idx(self, pix, clip=False):
pix = pix_tuple_to_idx(pix)
idx_non_spatial = self.axes.pix_to_idx(
pix[self._slice_non_spatial_axes], clip=clip
)
if not self.is_regular:
npix = (self.npix[0][idx_non_spatial], self.npix[1][idx_non_spatial])
else:
npix = self.npix
idx_spatial = []
for idx, npix_ in zip(pix[self._slice_spatial_axes], npix):
if clip:
idx = np.clip(idx, 0, npix_)
else:
idx = np.where((idx < 0) | (idx >= npix_), -1, idx)
idx_spatial.append(idx)
return tuple(idx_spatial) + idx_non_spatial
[docs]
def contains(self, coords):
idx = self.coord_to_idx(coords)
return np.all(np.stack([t != INVALID_INDEX.int for t in idx]), axis=0)
[docs]
def to_image(self):
return self._image_geom
@lazyproperty
def _image_geom(self):
npix = (np.max(self._npix[0]), np.max(self._npix[1]))
cdelt = (np.max(self._cdelt[0]), np.max(self._cdelt[1]))
return self.__class__(self._wcs, npix, cdelt=cdelt)
[docs]
def to_cube(self, axes):
npix = (np.max(self._npix[0]), np.max(self._npix[1]))
cdelt = (np.max(self._cdelt[0]), np.max(self._cdelt[1]))
axes = copy.deepcopy(self.axes) + axes
return self.__class__(
self._wcs.deepcopy(),
npix,
cdelt=cdelt,
axes=axes,
)
def _pad_spatial(self, pad_width):
if np.isscalar(pad_width):
pad_width = (pad_width, pad_width)
npix = (self.npix[0] + 2 * pad_width[0], self.npix[1] + 2 * pad_width[1])
wcs = self._wcs.deepcopy()
wcs.wcs.crpix += np.array(pad_width)
cdelt = copy.deepcopy(self._cdelt)
return self.__class__(wcs, npix, cdelt=cdelt, axes=copy.deepcopy(self.axes))
[docs]
def crop(self, crop_width):
if np.isscalar(crop_width):
crop_width = (crop_width, crop_width)
npix = (self.npix[0] - 2 * crop_width[0], self.npix[1] - 2 * crop_width[1])
wcs = self._wcs.deepcopy()
wcs.wcs.crpix -= np.array(crop_width)
cdelt = copy.deepcopy(self._cdelt)
return self.__class__(wcs, npix, cdelt=cdelt, axes=copy.deepcopy(self.axes))
[docs]
def downsample(self, factor, axis_name=None):
if axis_name is None:
if np.any(np.mod(self.npix, factor) > 0):
raise ValueError(
f"Spatial shape not divisible by factor {factor!r} in all axes."
f" You need to pad prior to calling downsample."
)
npix = (self.npix[0] / factor, self.npix[1] / factor)
cdelt = (self._cdelt[0] * factor, self._cdelt[1] * factor)
wcs = get_resampled_wcs(self.wcs, factor, True)
return self._init_copy(wcs=wcs, npix=npix, cdelt=cdelt)
else:
if not self.is_regular:
raise NotImplementedError(
"Upsampling in non-spatial axes not supported for irregular geometries"
)
axes = self.axes.downsample(factor=factor, axis_name=axis_name)
return self._init_copy(axes=axes)
[docs]
def upsample(self, factor, axis_name=None):
if axis_name is None:
npix = (self.npix[0] * factor, self.npix[1] * factor)
cdelt = (self._cdelt[0] / factor, self._cdelt[1] / factor)
wcs = get_resampled_wcs(self.wcs, factor, False)
return self._init_copy(wcs=wcs, npix=npix, cdelt=cdelt)
else:
if not self.is_regular:
raise NotImplementedError(
"Upsampling in non-spatial axes not supported for irregular geometries"
)
axes = self.axes.upsample(factor=factor, axis_name=axis_name)
return self._init_copy(axes=axes)
[docs]
def to_binsz(self, binsz):
"""Change pixel size of the geometry.
Parameters
----------
binsz : float or tuple or list
New pixel size in degree.
Returns
-------
geom : `WcsGeom`
Geometry with new pixel size.
"""
return self.create(
skydir=self.center_skydir,
binsz=binsz,
width=self.width,
proj=self.projection,
frame=self.frame,
axes=copy.deepcopy(self.axes),
)
[docs]
def solid_angle(self):
"""Solid angle array as a `~astropy.units.Quantity` in ``sr``.
The array has the same dimension as the WcsGeom object
if the spatial shape is not unique along the extra axis,
otherwise the array shape matches the spatial dimensions.
To return solid angles for the spatial dimensions only use::
WcsGeom.to_image().solid_angle()
"""
return self._solid_angle
@lazyproperty
def _solid_angle(self):
if self.is_regular:
coord = self.to_image().get_coord(mode="edges").skycoord
else:
coord = self.get_coord(mode="edges").skycoord
# define pixel corners
low_left = coord[..., :-1, :-1]
low_right = coord[..., 1:, :-1]
up_left = coord[..., :-1, 1:]
up_right = coord[..., 1:, 1:]
# compute side lengths
low = low_left.separation(low_right)
left = low_left.separation(up_left)
up = up_left.separation(up_right)
right = low_right.separation(up_right)
# compute enclosed angles
angle_low_right = low_right.position_angle(up_right) - low_right.position_angle(
low_left
)
angle_up_left = up_left.position_angle(up_right) - low_left.position_angle(
up_left
)
# compute area assuming a planar triangle
area_low_right = 0.5 * low * right * np.sin(angle_low_right)
area_up_left = 0.5 * up * left * np.sin(angle_up_left)
# TODO: for non-negative cdelt a negative solid angle is returned
# find out why and fix properly
value = np.abs(u.Quantity(area_low_right + area_up_left, "sr", copy=False))
if self.is_regular:
value = value.reshape(self.data_shape_image)
return value
[docs]
def bin_volume(self):
"""Bin volume as a `~astropy.units.Quantity`."""
return self._bin_volume
@lazyproperty
def _bin_volume(self):
"""Cached property of bin volume."""
value = self.to_image().solid_angle()
if not self.is_image:
value = value * self.axes.bin_volume()
return value
[docs]
def separation(self, center):
"""Compute sky separation with respect to a given center.
Parameters
----------
center : `~astropy.coordinates.SkyCoord`
Center position.
Returns
-------
separation : `~astropy.coordinates.Angle`
Separation angle array (2D).
"""
coord = self.to_image().get_coord()
return center.separation(coord.skycoord)
[docs]
def cutout(self, position, width, mode="trim", odd_npix=False):
"""
Create a cutout around a given position.
Parameters
----------
position : `~astropy.coordinates.SkyCoord`
Center position of the cutout region.
width : tuple of `~astropy.coordinates.Angle`
Angular sizes of the region in (lon, lat) in that specific order.
If only one value is passed, a square region is extracted.
mode : {'trim', 'partial', 'strict'}, optional
Mode option for Cutout2D, for details see `~astropy.nddata.utils.Cutout2D`.
Default is "trim".
odd_npix : bool, optional
Force width to odd number of pixels.
Default is False.
Returns
-------
cutout : `~gammapy.maps.WcsNDMap`
Cutout map.
"""
width = _check_width(width) * u.deg
binsz = self.pixel_scales
width_npix = np.clip((width / binsz).to_value(""), 1, None)
if odd_npix:
width_npix = round_up_to_odd(width_npix)
dummy_data = np.empty(self.to_image().data_shape, dtype=bool)
c2d = Cutout2D(
data=dummy_data,
wcs=self.wcs,
position=position,
# Cutout2D takes size with order (lat, lon)
size=width_npix[::-1],
mode=mode,
)
return self._init_copy(wcs=c2d.wcs, npix=c2d.shape[::-1])
[docs]
def boundary_mask(self, width):
"""Create a mask applying binary erosion with a given width from geometry edges.
Parameters
----------
width : tuple of `~astropy.units.Quantity`
Angular sizes of the margin in (lon, lat) in that specific order.
If only one value is passed, the same margin is applied in (lon, lat).
Returns
-------
mask_map : `~gammapy.maps.WcsNDMap` of boolean type
Boundary mask.
"""
from .ndmap import WcsNDMap
data = np.ones(self.data_shape, dtype=bool)
return WcsNDMap.from_geom(self, data=data).binary_erode(
width=2 * u.Quantity(width), kernel="box"
)
[docs]
def region_mask(self, regions, inside=True):
"""Create a mask from a given list of regions.
The mask is filled such that a pixel inside the region is filled with
"True". To invert the mask, e.g. to create a mask with exclusion regions
the tilde (~) operator can be used (see example below).
Parameters
----------
regions : str, `~regions.Region` or list of `~regions.Region`
Region or list of regions (pixel or sky regions accepted).
A region can be defined as a string ind DS9 format as well.
See http://ds9.si.edu/doc/ref/region.html for details.
inside : bool, optional
For ``inside=True``, set pixels in the region to True.
For ``inside=False``, set pixels in the region to False.
Default is True.
Returns
-------
mask_map : `~gammapy.maps.WcsNDMap` of boolean type
Boolean region mask.
Examples
--------
Make an exclusion mask for a circular region::
from regions import CircleSkyRegion
from astropy.coordinates import SkyCoord, Angle
from gammapy.maps import WcsNDMap, WcsGeom
pos = SkyCoord(0, 0, unit='deg')
geom = WcsGeom.create(skydir=pos, npix=100, binsz=0.1)
region = CircleSkyRegion(
SkyCoord(3, 2, unit='deg'),
Angle(1, 'deg'),
)
# the Gammapy convention for exclusion regions is to take the inverse
mask = ~geom.region_mask([region])
Note how we made a list with a single region,
since this method expects a list of regions.
"""
from gammapy.maps import Map, RegionGeom
if not self.is_regular:
raise ValueError("Multi-resolution maps not supported yet")
geom = RegionGeom.from_regions(regions, wcs=self.wcs)
idx = self.get_idx()
mask = geom.contains_wcs_pix(idx)
if not inside:
np.logical_not(mask, out=mask)
return Map.from_geom(self, data=mask)
[docs]
def region_weights(self, regions, oversampling_factor=10):
"""Compute regions weights.
Parameters
----------
regions : str, `~regions.Region` or list of `~regions.Region`
Region or list of regions (pixel or sky regions accepted).
A region can be defined as a string ind DS9 format as well.
See http://ds9.si.edu/doc/ref/region.html for details.
oversampling_factor : int, optional
Over-sampling factor to compute the region weights.
Default is 10.
Returns
-------
map : `~gammapy.maps.WcsNDMap` of boolean type
Weights region mask.
"""
geom = self.upsample(factor=oversampling_factor)
m = geom.region_mask(regions=regions)
m.data = m.data.astype(float)
return m.downsample(factor=oversampling_factor, preserve_counts=False)
[docs]
def binary_structure(self, width, kernel="disk"):
"""Get binary structure.
Parameters
----------
width : `~astropy.units.Quantity`, str or float
If a float is given it interpreted as width in pixels. If an (angular)
quantity is given it converted to pixels using ``geom.wcs.wcs.cdelt``.
The width corresponds to radius in case of a disk kernel, and
the side length in case of a box kernel.
kernel : {'disk', 'box'}, optional
Kernel shape. Default is "disk".
Returns
-------
structure : `~numpy.ndarray`
Binary structure.
"""
width = u.Quantity(width)
if width.unit.is_equivalent("deg"):
width = width / self.pixel_scales
width = round_up_to_odd(width.to_value(""))
if kernel == "disk":
disk = Tophat2DKernel(width[0])
disk.normalize("peak")
structure = disk.array
elif kernel == "box":
structure = np.ones(width)
else:
raise ValueError(f"Invalid kernel: {kernel!r}")
shape = (1,) * len(self.axes) + structure.shape
return structure.reshape(shape)
def __str__(self):
lon = self.center_skydir.data.lon.deg
lat = self.center_skydir.data.lat.deg
lon_ref, lat_ref = self.wcs.wcs.crval
return (
f"{self.__class__.__name__}\n\n"
f"\taxes : {self.axes_names}\n"
f"\tshape : {self.data_shape[::-1]}\n"
f"\tndim : {self.ndim}\n"
f"\tframe : {self.frame}\n"
f"\tprojection : {self.projection}\n"
f"\tcenter : {lon:.1f} deg, {lat:.1f} deg\n"
f"\twidth : {self.width[0][0]:.1f} x {self.width[1][0]:.1f}\n"
f"\twcs ref : {lon_ref:.1f} deg, {lat_ref:.1f} deg\n"
)
[docs]
def to_odd_npix(self, max_radius=None):
"""Create a new geometry object with an odd number of pixels and a maximum size.
This is useful for PSF kernel creation.
Parameters
----------
max_radius : `~astropy.units.Quantity`, optional
Maximum radius of the geometry (half the width).
Default is None.
Returns
-------
geom : `WcsGeom`
Geometry with odd number of pixels.
"""
if max_radius is None:
width = self.width.max()
else:
width = 2 * u.Quantity(max_radius)
binsz = self.pixel_scales.max()
width_npix = (width / binsz).to_value("")
npix = round_up_to_odd(width_npix)
return WcsGeom.create(
skydir=self.center_skydir,
binsz=binsz,
npix=npix,
proj=self.projection,
frame=self.frame,
axes=self.axes,
)
[docs]
def to_even_npix(self):
"""Create a new geometry object with an even number of pixels and a maximum size.
Returns
-------
geom : `WcsGeom`
Geometry with odd number of pixels.
"""
width = self.width.max()
binsz = self.pixel_scales.max()
width_npix = (width / binsz).to_value("")
npix = round_up_to_even(width_npix)
return WcsGeom.create(
skydir=self.center_skydir,
binsz=binsz,
npix=npix,
proj=self.projection,
frame=self.frame,
axes=self.axes,
)
[docs]
def is_aligned(self, other, tolerance=1e-6):
"""Check if WCS and extra axes are aligned.
Parameters
----------
other : `WcsGeom`
Other geometry.
tolerance : float, optional
Tolerance for the comparison.
Default is 1e-6.
Returns
-------
aligned : bool
Whether geometries are aligned.
"""
for axis, otheraxis in zip(self.axes, other.axes):
if axis != otheraxis:
return False
# check WCS consistency with a priori tolerance of 1e-6
return self.wcs.wcs.compare(other.wcs.wcs, cmp=2, tolerance=tolerance)
[docs]
def is_allclose(self, other, rtol_axes=1e-6, atol_axes=1e-6, rtol_wcs=1e-6):
"""Compare two data IRFs for equivalency.
Parameters
----------
other : `WcsGeom`
Geom to compare against.
rtol_axes : float, optional
Relative tolerance for the axes comparison.
Default is 1e-6.
atol_axes : float, optional
Relative tolerance for the axes comparison.
Default is 1e-6.
rtol_wcs : float, optional
Relative tolerance for the WCS comparison.
Default is 1e-6.
Returns
-------
is_allclose : bool
Whether the geometry is all close.
"""
if not isinstance(other, self.__class__):
return TypeError(f"Cannot compare {type(self)} and {type(other)}")
if self.data_shape != other.data_shape:
return False
axes_eq = self.axes.is_allclose(other.axes, rtol=rtol_axes, atol=atol_axes)
# check WCS consistency with a priori tolerance of 1e-6
# cmp=1 parameter ensures no comparison with ancillary information
# see https://github.com/astropy/astropy/pull/4522/files
wcs_eq = self.wcs.wcs.compare(other.wcs.wcs, cmp=1, tolerance=rtol_wcs)
return axes_eq and wcs_eq
def __eq__(self, other):
if not isinstance(other, self.__class__):
return False
if not (self.is_regular and other.is_regular):
raise NotImplementedError(
"Geom comparison is not possible for irregular geometries."
)
return self.is_allclose(other=other, rtol_wcs=1e-6, rtol_axes=1e-6)
def __ne__(self, other):
return not self.__eq__(other)
def __hash__(self):
return id(self)
def pix2world(wcs, cdelt, crpix, pix):
"""Perform pixel to world coordinate transformation.
For a WCS projection with a given pixel size (CDELT) and reference pixel
(CRPIX). This method can be used to perform WCS transformations
for projections with different pixelizations but the same
reference coordinate (CRVAL), projection type, and coordinate system.
Parameters
----------
wcs : `~astropy.wcs.WCS`
WCS transform object.
cdelt : tuple
Tuple of X/Y pixel size in deg. Each element should have the
same length as ``pix``.
crpix : tuple
Tuple of reference pixel parameters in X and Y dimensions. Each
element should have the same length as ``pix``.
pix : tuple
Tuple of pixel coordinates.
"""
pix_ratio = [
np.abs(wcs.wcs.cdelt[0] / cdelt[0]),
np.abs(wcs.wcs.cdelt[1] / cdelt[1]),
]
pix = (
(pix[0] - (crpix[0] - 1.0)) / pix_ratio[0] + wcs.wcs.crpix[0] - 1.0,
(pix[1] - (crpix[1] - 1.0)) / pix_ratio[1] + wcs.wcs.crpix[1] - 1.0,
)
return wcs.wcs_pix2world(pix[0], pix[1], 0)
def world2pix(wcs, cdelt, crpix, coord):
pix_ratio = [
np.abs(wcs.wcs.cdelt[0] / cdelt[0]),
np.abs(wcs.wcs.cdelt[1] / cdelt[1]),
]
pix = wcs.wcs_world2pix(coord[0], coord[1], 0)
return (
(pix[0] - (wcs.wcs.crpix[0] - 1.0)) * pix_ratio[0] + crpix[0] - 1.0,
(pix[1] - (wcs.wcs.crpix[1] - 1.0)) * pix_ratio[1] + crpix[1] - 1.0,
)
