Source code for gammapy.maps.wcs.geom

# 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 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 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, 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 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 data array 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 _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"} Cutout slices mode. 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=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): """Is this geometry is regular in non-spatial dimensions (bool)? - 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 deg 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 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. 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. binsz : float or tuple or list 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. 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 deg in the coordinate system of the map. frame : {"icrs", "galactic"}, optional Coordinate system, either Galactic ("galactic") or Equatorial ("icrs"). axes : list List of non-spatial axes. 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 refpix : tuple Reference pixel of the projection. If None this will be set to the center of the map. 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[0].flat[0], npix[1].flat[0] wcs.wcs.datfix() return cls(wcs, npix, cdelt=binsz, axes=axes)
@property def footprint(self): """Footprint of the geometry""" coords = self.wcs.calc_footprint() return SkyCoord(coords, frame=self.frame, unit="deg")
[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 deg 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 + npix[0] / 2.0)) + geom.wcs.wcs.crpix[0] yref = int(np.floor(-yref + 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, )
[docs] @classmethod def from_header(cls, header, hdu_bands=None, format="gadf"): """Create a WCS geometry object from a FITS header. Parameters ---------- header : `~astropy.io.fits.Header` The FITS header hdu_bands : `~astropy.io.fits.BinTableHDU` The BANDS table HDU. format : {'gadf', 'fgst-ccube','fgst-template'} FITS format convention. Returns ------- wcs : `~WcsGeom` WCS geometry object. """ wcs = WCS(header, naxis=2) # TODO: see https://github.com/astropy/astropy/issues/9259 wcs._naxis = wcs._naxis[:2] axes = MapAxes.from_table_hdu(hdu_bands, format=format) shape = axes.shape if hdu_bands is not None and "NPIX" in hdu_bands.columns.names: npix = hdu_bands.data.field("NPIX").reshape(shape + (2,)) npix = (npix[..., 0], npix[..., 1]) cdelt = hdu_bands.data.field("CDELT").reshape(shape + (2,)) cdelt = (cdelt[..., 0], cdelt[..., 1]) elif "WCSSHAPE" in header: wcs_shape = eval(header["WCSSHAPE"]) npix = (wcs_shape[0], wcs_shape[1]) cdelt = None wcs.array_shape = npix else: npix = (header["NAXIS1"], header["NAXIS2"]) cdelt = None return cls(wcs, npix, cdelt=cdelt, axes=axes)
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 to_header(self): header = self.wcs.to_header() header.update(self.axes.to_header()) shape = "{},{}".format(np.max(self.npix[0]), np.max(self.npix[1])) for ax in self.axes: shape += f",{ax.nbin}" header["WCSSHAPE"] = f"({shape})" return header
[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 idx 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 pix coordinates from the geometry. Parameters ---------- mode : {'center', 'edges'} Get center or edge pix coordinates for the spatial axes. Returns ------- coord : tuple Map pix 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'} Get center or edge coordinates for the spatial axes. frame : str or `~astropy.coordinates.Frame` Coordinate frame sparse : bool Compute sparse coordinates axis_name : str If mode = "edges", the edges will be returned for this axis. 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 (`~astropy.units.Quantity` in ``sr``). The array has the same dimension as the WcsGeom object. To return solid angles for the spatial dimensions only use:: WcsGeom.to_image().solid_angle() """ return self._solid_angle
@lazyproperty def _solid_angle(self): 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 return np.abs(u.Quantity(area_low_right + area_up_left, "sr", copy=False))
[docs] def bin_volume(self): """Bin volume (`~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 wrt 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'} Mode option for Cutout2D, for details see `~astropy.nddata.utils.Cutout2D`. odd_npix : bool Force width to odd number of pixels. 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) width = width_npix * binsz if odd_npix: width = round_up_to_odd(width_npix) dummy_data = np.empty(self.to_image().data_shape) c2d = Cutout2D( data=dummy_data, wcs=self.wcs, position=position, # Cutout2D takes size with order (lat, lon) size=width[::-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 geom 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 For ``inside=True``, pixels in the region to True (the default). For ``inside=False``, pixels in the region are False. 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 Over-sampling factor to compute the region weights 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'} Kernel shape Returns ------- structure : `~numoy.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 __repr__(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 geom object with an odd number of pixel and a maximum size. This is useful for PSF kernel creation. Parameters ---------- max_radius : `~astropy.units.Quantity` Max. radius of the geometry (half the width) Returns ------- geom : `WcsGeom` Geom 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 geom object with an even number of pixel and a maximum size. Returns ------- geom : `WcsGeom` Geom 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 geom. tolerance : float Tolerance for the comparison. 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 Relative tolerance for the axes comparison. atol_axes : float Relative tolerance for the axes comparison. rtol_wcs : float Relative tolerance for the wcs comparison. 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, )