WcsMap

class gammapy.maps.WcsMap(geom, data, meta=None)[source]

Bases: gammapy.maps.Map

Base class for WCS map classes.

Parameters:

geom : WcsGeom

A WCS geometry object.

data : ndarray

Data array.

Attributes Summary

data Data array (ndarray)
geom Map geometry (MapGeom)

Methods Summary

coadd(map_in) Add the contents of map_in to this map.
create([map_type, npix, binsz, width, proj, …]) Factory method to create an empty WCS map.
crop(crop_width) Crop the spatial dimension of the map by removing a number of pixels from the edge of the map.
downsample(factor[, preserve_counts]) Downsample the spatial dimension of the map by a given factor.
fill_by_coord(coords[, weights]) Fill pixels at the given map coordinates with values in weights vector.
fill_by_idx(idx[, weights]) Fill pixels at the given pixel indices with values in weights vector.
fill_by_pix(pix[, weights]) Fill pixels at the given pixel coordinates with values in weights vector.
from_geom(geom[, meta, map_type]) Generate an empty map from a Geom instance.
from_hdu_list(hdulist[, hdu, hdu_bands, …])
from_hdulist(hdu_list[, hdu, hdu_bands]) Make a WcsMap object from a FITS HDUList.
get_by_coord(coords) Return map values at the given map coordinates.
get_by_idx(idx) Return map values at the given pixel indices.
get_by_pix(pix) Return map values at the given pixel coordinates.
interp_by_coord(coords[, interp]) Interpolate map values at the given map coordinates.
interp_by_pix(pix[, interp]) Interpolate map values at the given pixel coordinates.
iter_by_coord([buffersize]) Iterate over elements of the map returning a tuple with values and map coordinates.
iter_by_image() Iterate over image planes of the map returning a tuple with the image array and image plane index.
iter_by_pix([buffersize]) Iterate over elements of the map returning a tuple with values and pixel coordinates.
make_hdu([hdu, hdu_bands, sparse, conv]) Make a FITS HDU from this map.
pad(pad_width[, mode, cval, order]) Pad the spatial dimension of the map by extending the edge of the map by the given number of pixels.
read(filename[, hdu, hdu_bands, map_type]) Read a map from a FITS file.
reproject(geom[, order, mode]) Reproject this map to a different geometry.
set_by_coord(coords, vals) Set pixels at the given map coordinates to the values in vals vector.
set_by_idx(idx, vals) Set pixels at the given pixel indices to the values in vals vector.
set_by_pix(pix, vals) Set pixels at the given pixel coordinates to the values in vals vector.
sum_over_axes() Reduce to a 2D image by summing over non-spatial dimensions.
to_hdulist([hdu, hdu_bands, sparse, conv]) Convert to HDUList.
upsample(factor[, order, preserve_counts]) Upsample the spatial dimension of the map by a given factor.
write(filename, **kwargs) Write to a FITS file.

Attributes Documentation

data

Data array (ndarray)

geom

Map geometry (MapGeom)

Methods Documentation

coadd(map_in)

Add the contents of map_in to this map. This method can be used to combine maps containing integral quantities (e.g. counts) or differential quantities if the maps have the same binning.

Parameters:

map_in : Map

Input map.

classmethod create(map_type='wcs', npix=None, binsz=0.1, width=None, proj='CAR', coordsys='CEL', refpix=None, axes=None, skydir=None, dtype='float32', conv='gadf', meta=None)[source]

Factory method to create an empty WCS map.

Parameters:

map_type : {‘wcs’, ‘wcs-sparse’}

Map type. Selects the class that will be used to instantiate the map.

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

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 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.

coordsys : {‘CEL’, ‘GAL’}, optional

Coordinate system, either Galactic (‘GAL’) or Equatorial (‘CEL’).

axes : list

List of non-spatial axes.

proj : string, optional

Any valid WCS projection type. Default is ‘CAR’ (cartesian).

refpix : tuple

Reference pixel of the projection. If None then this will be chosen to be center of the map.

dtype : str, optional

Data type, default is float32

conv : {‘fgst-ccube’,’fgst-template’,’gadf’}, optional

FITS format convention. Default is ‘gadf’.

meta : OrderedDict

Dictionary to store meta data.

Returns:

map : WcsMap

A WCS map object.

crop(crop_width)

Crop the spatial dimension of the map by removing a number of pixels from the edge of the map.

Parameters:

crop_width : {sequence, array_like, int}

Number of pixels cropped from the edges of each axis. Defined analogously to pad_with from pad.

Returns:

map : Map

Cropped map.

downsample(factor, preserve_counts=True)

Downsample the spatial dimension of the map by a given factor.

Parameters:

factor : int

Downsampling factor.

preserve_counts : bool

Preserve the integral over each bin. This should be true if the map is an integral quantity (e.g. counts) and false if the map is a differential quantity (e.g. intensity).

Returns:

map : Map

Downsampled map.

fill_by_coord(coords, weights=None)

Fill pixels at the given map coordinates with values in weights vector.

Parameters:

coords : tuple or MapCoord

MapCoord object or tuple of coordinate arrays for each dimension of the map. Tuple should be ordered as (lon, lat, x_0, …, x_n) where x_i are coordinates for non-spatial dimensions of the map.

weights : ndarray

Weights vector. If None then a unit weight will be assumed for each element in coords.

fill_by_idx(idx, weights=None)

Fill pixels at the given pixel indices with values in weights vector.

Parameters:

idx : tuple

Tuple of pixel index arrays for each dimension of the map. Tuple should be ordered as (I_lon, I_lat, I_0, …, I_n) for WCS maps and (I_hpx, I_0, …, I_n) for HEALPix maps.

weights : ndarray

Weights vector. If None then a unit weight will be assumed for each element in idx.

fill_by_pix(pix, weights=None)

Fill pixels at the given pixel coordinates with values in weights vector.

Parameters:

pix : tuple

Tuple of pixel index arrays for each dimension of the map. Tuple should be ordered as (I_lon, I_lat, I_0, …, I_n) for WCS maps and (I_hpx, I_0, …, I_n) for HEALPix maps. Pixel indices can be either float or integer type. Float indices will be rounded to the nearest integer.

weights : ndarray

Weights vector. If None then a unit weight will be assumed for each element in pix.

from_geom(geom, meta=None, map_type='auto')

Generate an empty map from a Geom instance.

Parameters:

geom : MapGeom

Map geometry.

meta : OrderedDict

Dictionary to store meta data.

map_type : {‘wcs’, ‘wcs-sparse’, ‘hpx’, ‘hpx-sparse’, ‘auto’}

Map type. Selects the class that will be used to instantiate the map. The map type should be consistent with the geometry. If map_type is ‘auto’ then an appropriate map type will be inferred from type of geom.

Returns:

map_out : Map

Map object

from_hdu_list(hdulist, hdu=None, hdu_bands=None, map_type='auto')
classmethod from_hdulist(hdu_list, hdu=None, hdu_bands=None)[source]

Make a WcsMap object from a FITS HDUList.

Parameters:

hdu_list : HDUList

HDU list containing HDUs for map data and bands.

hdu : str

Name or index of the HDU with the map data.

hdu_bands : str

Name or index of the HDU with the BANDS table.

Returns:

wcs_map : WcsMap

Map object

get_by_coord(coords)

Return map values at the given map coordinates.

Parameters:

coords : tuple or MapCoord

MapCoord object or tuple of coordinate arrays for each dimension of the map. Tuple should be ordered as (lon, lat, x_0, …, x_n) where x_i are coordinates for non-spatial dimensions of the map.

Returns:

vals : ndarray

Values of pixels in the map. np.nan used to flag coords outside of map.

get_by_idx(idx)

Return map values at the given pixel indices.

Parameters:

idx : tuple

Tuple of pixel index arrays for each dimension of the map. Tuple should be ordered as (I_lon, I_lat, I_0, …, I_n) for WCS maps and (I_hpx, I_0, …, I_n) for HEALPix maps.

Returns:

vals : ndarray

Array of pixel values. np.nan used to flag coordinate outside of map

get_by_pix(pix)

Return map values at the given pixel coordinates.

Parameters:

pix : tuple

Tuple of pixel index arrays for each dimension of the map. Tuple should be ordered as (I_lon, I_lat, I_0, …, I_n) for WCS maps and (I_hpx, I_0, …, I_n) for HEALPix maps. Pixel indices can be either float or integer type.

Returns:

vals : ndarray

Array of pixel values. np.nan used to flag coordinates outside of map

interp_by_coord(coords, interp=None)

Interpolate map values at the given map coordinates.

Parameters:

coords : tuple or MapCoord

MapCoord object or tuple of coordinate arrays for each dimension of the map. Tuple should be ordered as (lon, lat, x_0, …, x_n) where x_i are coordinates for non-spatial dimensions of the map.

interp : {None, ‘nearest’, ‘linear’, ‘cubic’, 0, 1, 2, 3}

Method to interpolate data values. By default no interpolation is performed and the return value will be the amplitude of the pixel encompassing the given coordinate. Integer values can be used in lieu of strings to choose the interpolation method of the given order (0=’nearest’, 1=’linear’, 2=’quadratic’, 3=’cubic’). Note that only ‘nearest’ and ‘linear’ methods are supported for all map types.

Returns:

vals : ndarray

Interpolated pixel values.

interp_by_pix(pix, interp=None)

Interpolate map values at the given pixel coordinates.

Parameters:

pix : tuple

Tuple of pixel coordinate arrays for each dimension of the map. Tuple should be ordered as (p_lon, p_lat, p_0, …, p_n) where p_i are pixel coordinates for non-spatial dimensions of the map.

interp : {None, ‘nearest’, ‘linear’, ‘cubic’, 0, 1, 2, 3}

Method to interpolate data values. By default no interpolation is performed and the return value will be the amplitude of the pixel encompassing the given coordinate. Integer values can be used in lieu of strings to choose the interpolation method of the given order (0=’nearest’, 1=’linear’, 2=’quadratic’, 3=’cubic’). Note that only ‘nearest’ and ‘linear’ methods are supported for all map types.

Returns:

vals : ndarray

Interpolated pixel values.

iter_by_coord(buffersize=1)

Iterate over elements of the map returning a tuple with values and map coordinates.

Parameters:

buffersize : int

Set the size of the buffer. The map will be returned in chunks of the given size.

Returns:

val : ndarray

Map values.

coords : tuple

Tuple of map coordinates.

iter_by_image()

Iterate over image planes of the map returning a tuple with the image array and image plane index.

Returns:

val : ndarray

Array of image plane values.

idx : tuple

Index of image plane.

iter_by_pix(buffersize=1)

Iterate over elements of the map returning a tuple with values and pixel coordinates.

Parameters:

buffersize : int

Set the size of the buffer. The map will be returned in chunks of the given size.

Returns:

val : ndarray

Map values.

pix : tuple

Tuple of pixel coordinates.

make_hdu(hdu='SKYMAP', hdu_bands=None, sparse=False, conv=None)[source]

Make a FITS HDU from this map.

Parameters:

hdu : str

The HDU extension name.

hdu_bands : str

The HDU extension name for BANDS table.

sparse : bool

Set INDXSCHM to SPARSE and sparsify the map by only writing pixels with non-zero amplitude.

Returns:

hdu : BinTableHDU or ImageHDU

HDU containing the map data.

pad(pad_width, mode='constant', cval=0, order=1)

Pad the spatial dimension of the map by extending the edge of the map by the given number of pixels.

Parameters:

pad_width : {sequence, array_like, int}

Number of pixels padded to the edges of each axis.

mode : {‘edge’, ‘constant’, ‘interp’}

Padding mode. ‘edge’ pads with the closest edge value. ‘constant’ pads with a constant value. ‘interp’ pads with an extrapolated value.

cval : float

Padding value when mode=’consant’.

order : int

Order of interpolation when mode=’constant’ (0 = nearest-neighbor, 1 = linear, 2 = quadratic, 3 = cubic).

Returns:

map : Map

Padded map.

read(filename, hdu=None, hdu_bands=None, map_type='auto')

Read a map from a FITS file.

Parameters:

filename : str

Name of the FITS file.

hdu : str

Name or index of the HDU with the map data.

hdu_bands : str

Name or index of the HDU with the BANDS table. If not defined this will be inferred from the FITS header of the map HDU.

map_type : {‘wcs’, ‘wcs-sparse’, ‘hpx’, ‘hpx-sparse’, ‘auto’}

Map type. Selects the class that will be used to instantiate the map. The map type should be consistent with the format of the input file. If map_type is ‘auto’ then an appropriate map type will be inferred from the input file.

Returns:

map_out : Map

Map object

reproject(geom, order=1, mode='interp')

Reproject this map to a different geometry.

Parameters:

geom : MapGeom

Geometry of projection.

mode : {‘interp’, ‘exact’}

Method for reprojection. ‘interp’ method interpolates at pixel centers. ‘exact’ method integrates over intersection of pixels.

order : int or str

Order of interpolating polynomial (0 = nearest-neighbor, 1 = linear, 2 = quadratic, 3 = cubic).

Returns:

map : Map

Reprojected map.

set_by_coord(coords, vals)

Set pixels at the given map coordinates to the values in vals vector.

Parameters:

coords : tuple or MapCoord

MapCoord object or tuple of coordinate arrays for each dimension of the map. Tuple should be ordered as (lon, lat, x_0, …, x_n) where x_i are coordinates for non-spatial dimensions of the map.

vals : ndarray

Values vector. Pixels at coords will be set to these values.

set_by_idx(idx, vals)

Set pixels at the given pixel indices to the values in vals vector.

Parameters:

idx : tuple

Tuple of pixel index arrays for each dimension of the map. Tuple should be ordered as (I_lon, I_lat, I_0, …, I_n) for WCS maps and (I_hpx, I_0, …, I_n) for HEALPix maps.

vals : ndarray

Values vector. Pixels at idx will be set to these values.

set_by_pix(pix, vals)

Set pixels at the given pixel coordinates to the values in vals vector.

Parameters:

pix : tuple

Tuple of pixel index arrays for each dimension of the map. Tuple should be ordered as (I_lon, I_lat, I_0, …, I_n) for WCS maps and (I_hpx, I_0, …, I_n) for HEALPix maps. Pixel indices can be either float or integer type. Float indices will be rounded to the nearest integer.

vals : ndarray

Values vector. Pixels at pix will be set to these values.

sum_over_axes()

Reduce to a 2D image by summing over non-spatial dimensions.

to_hdulist(hdu=None, hdu_bands=None, sparse=False, conv=None)[source]

Convert to HDUList.

Parameters:

hdu : str

Name or index of the HDU with the map data.

hdu_bands : str

Name or index of the HDU with the BANDS table.

sparse : bool

Sparsify the map by only writing pixels with non-zero amplitude.

conv : {‘fgst-ccube’,’fgst-template’,’gadf’,None}, optional

FITS format convention. If None this will be set to the default convention of the map.

Returns:

hdu_list : HDUList

upsample(factor, order=0, preserve_counts=True)

Upsample the spatial dimension of the map by a given factor.

Parameters:

factor : int

Upsampling factor.

order : int

Order of the interpolation used for upsampling.

preserve_counts : bool

Preserve the integral over each bin. This should be true if the map is an integral quantity (e.g. counts) and false if the map is a differential quantity (e.g. intensity).

Returns:

map : Map

Upsampled map.

write(filename, **kwargs)

Write to a FITS file.

Parameters:

filename : str

Output file name.

hdu : str

Set the name of the image extension. By default this will be set to SKYMAP (for BINTABLE HDU) or PRIMARY (for IMAGE HDU).

hdu_bands : str

Set the name of the bands table extension. By default this will be set to BANDS.

conv : str

FITS format convention. By default files will be written to the gamma-astro-data-formats (GADF) format. This option can be used to write files that are compliant with format conventions required by specific software (e.g. the Fermi Science Tools). Supported conventions are ‘gadf’, ‘fgst-ccube’, ‘fgst-ltcube’, ‘fgst-bexpcube’, ‘fgst-template’, ‘fgst-srcmap’, ‘fgst-srcmap-sparse’, ‘galprop’, and ‘galprop2’.

sparse : bool

Sparsify the map by dropping pixels with zero amplitude. This option is only compatible with the ‘gadf’ format.