HpxNDMap¶

class gammapy.maps.HpxNDMap(geom, data=None, dtype='float32', meta=None, unit='')[source]¶

Bases: gammapy.maps.HpxMap

HEALPix map with any number of non-spatial dimensions.

This class uses a N+1D numpy array to represent the sequence of HEALPix image planes. Following the convention of WCS-based maps this class uses a column-wise ordering for the data array with the spatial dimension being tied to the last index of the array.

Parameters

geomHpxGeom: HEALPIX geometry object.
datandarray: HEALPIX data array. If none then an empty array will be allocated.
metadict: Dictionary to store meta data.
unitstr or Unit: The map unit

Attributes Summary

`data`	Data array (`ndarray`)
`geom`	Map geometry (`Geom`)
`meta`	Map meta (`dict`)
`quantity`	Map data times unit (`Quantity`)
`unit`	Map unit (`Unit`)

Methods Summary

`coadd`(self, map_in[, weights])	Add the contents of `map_in` to this map.
`copy`(self, \\kwargs)	Copy map instance and overwrite given attributes, except for geometry.
`create`([nside, binsz, nest, map_type, …])	Factory method to create an empty HEALPix map.
`crop`(self, crop_width)	Crop the spatial dimensions of the map.
`downsample`(self, factor[, preserve_counts])	Downsample the spatial dimension by a given factor.
`fill_by_coord`(self, coords[, weights])	Fill pixels at `coords` with given `weights`.
`fill_by_idx`(self, idx[, weights])	Fill pixels at `idx` with given `weights`.
`fill_by_pix`(self, pix[, weights])	Fill pixels at `pix` with given `weights`.
`fill_events`(self, events)	Fill event coordinates (`EventList`).
`from_geom`(geom[, meta, data, map_type, …])	Generate an empty map from a `Geom` instance.
`from_hdu`(hdu[, hdu_bands])	Make a HpxNDMap object from a FITS HDU.
`from_hdulist`(hdu_list[, hdu, hdu_bands])	Make a HpxMap object from a FITS HDUList.
`get_by_coord`(self, coords)	Return map values at the given map coordinates.
`get_by_idx`(self, idx)	Return map values at the given pixel indices.
`get_by_pix`(self, pix)	Return map values at the given pixel coordinates.
`get_image_by_coord`(self, coords)	Return spatial map at the given axis coordinates.
`get_image_by_idx`(self, idx)	Return spatial map at the given axis pixel indices.
`get_image_by_pix`(self, pix)	Return spatial map at the given axis pixel coordinates
`interp_by_coord`(self, coords[, interp])	Interpolate map values at the given map coordinates.
`interp_by_pix`(self, pix[, interp])	Interpolate map values at the given pixel coordinates.
`iter_by_image`(self)	Iterate over image planes of the map.
`make_hdu`(self[, hdu, hdu_bands, sparse, conv])	Make a FITS HDU with input data.
`make_wcs_mapping`(self[, sum_bands, proj, …])	Make a HEALPix to WCS mapping object.
`pad`(self, pad_width[, mode, cval, order])	Pad the spatial dimensions of the map.
`plot`(self[, method, ax, normalize, proj, …])	Quickplot method.
`plot_interactive`(self[, rc_params])	Plot map with interactive widgets to explore the non spatial axes.
`read`(filename[, hdu, hdu_bands, map_type])	Read a map from a FITS file.
`set_by_coord`(self, coords, vals)	Set pixels at `coords` with given `vals`.
`set_by_idx`(self, idx, vals)	Set pixels at `idx` with given `vals`.
`set_by_pix`(self, pix, vals)	Set pixels at `pix` with given `vals`.
`slice_by_idx`(self, slices)	Slice sub map from map object.
`sum_over_axes`(self)	Sum over all non-spatial dimensions.
`to_hdulist`(self[, hdu, hdu_bands, sparse, conv])	Convert to `HDUList`.
`to_swapped`(self)	Return a new map with the opposite scheme (ring or nested).
`to_ud_graded`(self, nside[, preserve_counts])	Upgrade or downgrade the resolution of the map to the chosen nside.
`to_wcs`(self[, sum_bands, normalize, proj, …])	Make a WCS object and convert HEALPIX data into WCS projection.
`upsample`(self, factor[, preserve_counts])	Upsample the spatial dimension by a given factor.
`write`(self, filename[, overwrite])	Write to a FITS file.

Attributes Documentation

data¶: Data array (ndarray)

geom¶: Map geometry (Geom)

meta¶: Map meta (dict)

quantity¶: Map data times unit (Quantity)

unit¶: Map unit (Unit)

Methods Documentation

coadd(self, map_in, weights=None)¶

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_inMap: Input map.
weights: `Map` or `~numpy.ndarray`: The weight factors while adding

copy(self, **kwargs)¶

Copy map instance and overwrite given attributes, except for geometry.

Parameters

**kwargsdict: Keyword arguments to overwrite in the map constructor.

Returns

copyMap: Copied Map.

classmethod create(nside=None, binsz=None, nest=True, map_type='hpx', coordsys='CEL', data=None, skydir=None, width=None, dtype='float32', region=None, axes=None, meta=None, unit='')¶

Factory method to create an empty HEALPix map.

Parameters

nsideint or ndarray: HEALPix NSIDE parameter. This parameter sets the size of the spatial pixels in the map.
binszfloat or ndarray: Approximate pixel size in degrees. An NSIDE will be chosen that correponds to a pixel size closest to this value. This option is superseded by nside.
nestbool: True for HEALPix “NESTED” indexing scheme, False for “RING” scheme.
coordsys{‘CEL’, ‘GAL’}, optional: Coordinate system, either Galactic (‘GAL’) or Equatorial (‘CEL’).
skydirtuple 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.
map_type{‘hpx’, ‘hpx-sparse’}: Map type. Selects the class that will be used to instantiate the map.
widthfloat: Diameter of the map in degrees. If None then an all-sky geometry will be created.
axeslist: List of MapAxis objects for each non-spatial dimension.
metadict: Dictionary to store meta data.
unitstr or Unit: The map unit

Returns

mapHpxMap: A HPX map object.

crop(self, crop_width)[source]¶

Crop the spatial dimensions 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 numpy.pad.

Returns

mapMap: Cropped map.

downsample(self, factor, preserve_counts=True)[source]¶

Downsample the spatial dimension by a given factor.

Parameters

factorint: Downsampling factor.
preserve_countsbool: 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).
axisstr: Which axis to downsample. By default spatial axes are downsampled.

Returns

mapMap: Downsampled map.

fill_by_coord(self, coords, weights=None)¶

Fill pixels at coords with given weights.

Parameters

coordstuple or MapCoord: 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.
weightsndarray: Weights vector. Default is weight of one.

fill_by_idx(self, idx, weights=None)[source]¶

Fill pixels at idx with given weights.

Parameters

idxtuple: 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.
weightsndarray: Weights vector. Default is weight of one.

fill_by_pix(self, pix, weights=None)¶

Fill pixels at pix with given weights.

Parameters

pixtuple: 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.
weightsndarray: Weights vector. Default is weight of one.

fill_events(self, events)¶: Fill event coordinates (EventList).

static from_geom(geom, meta=None, data=None, map_type='auto', unit='', dtype='float32')¶

Generate an empty map from a Geom instance.

Parameters

geomGeom: Map geometry.
datanumpy.ndarray: data array
metadict: 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.
unitstr or Unit: Data unit.

Returns

map_outMap: Map object

classmethod from_hdu(hdu, hdu_bands=None)[source]¶

Make a HpxNDMap object from a FITS HDU.

Parameters

hduBinTableHDU: The FITS HDU
hdu_bandsBinTableHDU: The BANDS table HDU

classmethod from_hdulist(hdu_list, hdu=None, hdu_bands=None)¶

Make a HpxMap object from a FITS HDUList.

Parameters

hdu_listHDUList: HDU list containing HDUs for map data and bands.
hdustr: Name or index of the HDU with the map data. If None then the method will try to load map data from the first BinTableHDU in the file.
hdu_bandsstr: Name or index of the HDU with the BANDS table.

Returns

hpx_mapHpxMap: Map object

get_by_coord(self, coords)¶

Return map values at the given map coordinates.

Parameters

coordstuple or MapCoord: 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

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

get_by_idx(self, idx)[source]¶

Return map values at the given pixel indices.

Parameters

idxtuple: 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

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

get_by_pix(self, pix)¶

Return map values at the given pixel coordinates.

Parameters

pixtuple: 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

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

get_image_by_coord(self, coords)¶

Return spatial map at the given axis coordinates.

Parameters

coordstuple or dict: Tuple should be ordered as (x_0, …, x_n) where x_i are coordinates for non-spatial dimensions of the map. Dict should specify the axis names of the non-spatial axes such as {‘axes0’: x_0, …, ‘axesn’: x_n}.

Returns

map_outMap: Map with spatial dimensions only.

See also

get_image_by_coord, get_image_by_idx

interp_by_coord(self, coords, interp=1)[source]¶

Interpolate map values at the given map coordinates.

Parameters

coordstuple or MapCoord: 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.
fill_valueNone or float value: The value to use for points outside of the interpolation domain. If None, values outside the domain are extrapolated.

Returns

valsndarray: Interpolated pixel values.

interp_by_pix(self, pix, interp=None)[source]¶: Interpolate map values at the given pixel coordinates.

iter_by_image(self)¶

Iterate over image planes of the map.

This is a generator yielding (data, idx) tuples, where data is a numpy.ndarray view of the image plane data, and idx is a tuple of int, the index of the image plane.

The image plane index is in data order, so that the data array can be indexed directly. See Iterating by image for further information.

make_hdu(self, hdu=None, hdu_bands=None, sparse=False, conv=None)¶

Make a FITS HDU with input data.

Parameters

hdustr: The HDU extension name.
hdu_bandsstr: The HDU extension name for BANDS table.
sparsebool: Set INDXSCHM to SPARSE and 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_outBinTableHDU or ImageHDU: Output HDU containing map data.

make_wcs_mapping(self, sum_bands=False, proj='AIT', oversample=2, width_pix=None)[source]¶

Make a HEALPix to WCS mapping object.

Parameters

sum_bandsbool: sum over non-spatial dimensions before reprojecting
projstr: WCS-projection
oversamplefloat: Oversampling factor for WCS map. This will be the approximate ratio of the width of a HPX pixel to a WCS pixel. If this parameter is None then the width will be set from width_pix.
width_pixint: Width of the WCS geometry in pixels. The pixel size will be set to the number of pixels satisfying oversample or width_pix whichever is smaller. If this parameter is None then the width will be set from oversample.

Returns

hpx2wcsHpxToWcsMapping

pad(self, pad_width, mode='constant', cval=0, order=1)[source]¶

Pad the spatial dimensions of the map.

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.
cvalfloat: Padding value when mode=’consant’.
orderint: Order of interpolation when mode=’constant’ (0 = nearest-neighbor, 1 = linear, 2 = quadratic, 3 = cubic).

Returns

mapMap: Padded map.

plot(self, method='raster', ax=None, normalize=False, proj='AIT', oversample=2, width_pix=1000, **kwargs)[source]¶

Quickplot method.

This will generate a visualization of the map by converting to a rasterized WCS image (method=’raster’) or drawing polygons for each pixel (method=’poly’).

Parameters

method{‘raster’,’poly’}: Method for mapping HEALPix pixels to a two-dimensional image. Can be set to ‘raster’ (rasterization to cartesian image plane) or ‘poly’ (explicit polygons for each pixel). WARNING: The ‘poly’ method is much slower than ‘raster’ and only suitable for maps with less than ~10k pixels.
projstring, optional: Any valid WCS projection type.
oversamplefloat: Oversampling factor for WCS map. This will be the approximate ratio of the width of a HPX pixel to a WCS pixel. If this parameter is None then the width will be set from width_pix.
width_pixint: Width of the WCS geometry in pixels. The pixel size will be set to the number of pixels satisfying oversample or width_pix whichever is smaller. If this parameter is None then the width will be set from oversample.
**kwargsdict: Keyword arguments passed to imshow.

Returns

figFigure: Figure object.
axWCSAxes: WCS axis object
imAxesImage or PatchCollection: Image object.

plot_interactive(self, rc_params=None, **kwargs)¶

Plot map with interactive widgets to explore the non spatial axes.

Parameters

rc_paramsdict: Passed to matplotlib.rc_context(rc=rc_params) to style the plot.
**kwargsdict: Keyword arguments passed to WcsNDMap.plot.

Examples

You can try this out e.g. using a Fermi-LAT diffuse model cube with an energy axis:

from gammapy.maps import Map

m = Map.read("$GAMMAPY_DATA/fermi_3fhl/gll_iem_v06_cutout.fits")
m.plot_interactive(add_cbar=True, stretch="sqrt")

If you would like to adjust the figure size you can use the rc_params argument:

rc_params = {'figure.figsize': (12, 6), 'font.size': 12}
m.plot_interactive(rc_params=rc_params)

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

Read a map from a FITS file.

Parameters

filenamestr or Path: Name of the FITS file.
hdustr: Name or index of the HDU with the map data.
hdu_bandsstr: 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_outMap: Map object

set_by_coord(self, coords, vals)¶

Set pixels at coords with given vals.

Parameters

coordstuple or MapCoord: 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.
valsndarray: Values vector.

set_by_idx(self, idx, vals)[source]¶

Set pixels at idx with given vals.

Parameters

idxtuple: 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.
valsndarray: Values vector.

set_by_pix(self, pix, vals)¶

Set pixels at pix with given vals.

Parameters

pixtuple: 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.
valsndarray: Values vector.

slice_by_idx(self, slices)¶

Slice sub map from map object.

For usage examples, see Indexing and Slicing.

Parameters

slicesdict: Dict of axes names and integers or slice object pairs. Contains one element for each non-spatial dimension. For integer indexing the corresponding axes is dropped from the map. Axes not specified in the dict are kept unchanged.

Returns

map_outMap: Sliced map object.

sum_over_axes(self)[source]¶

Sum over all non-spatial dimensions.

Returns

map_outHpxNDMap: Summed map.

to_hdulist(self, hdu='SKYMAP', hdu_bands=None, sparse=False, conv='gadf')¶

Convert to HDUList.

Parameters

hdustr: The HDU extension name.
hdu_bandsstr: The HDU extension name for BANDS table.
sparsebool: Set INDXSCHM to SPARSE and 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_listHDUList

to_swapped(self)[source]¶

Return a new map with the opposite scheme (ring or nested).

Returns

mapHpxMap: Map object.

to_ud_graded(self, nside, preserve_counts=False)[source]¶

Upgrade or downgrade the resolution of the map to the chosen nside.

Parameters

nsideint: NSIDE parameter of the new map.
preserve_countsbool: Choose whether to preserve counts (total amplitude) or intensity (amplitude per unit solid angle).

Returns

mapHpxMap: Map object.

to_wcs(self, sum_bands=False, normalize=True, proj='AIT', oversample=2, width_pix=None, hpx2wcs=None)[source]¶

Make a WCS object and convert HEALPIX data into WCS projection.

Parameters

sum_bandsbool: Sum over non-spatial axes before reprojecting. If False then the WCS map will have the same dimensionality as the HEALPix one.
normalizebool: Preserve integral by splitting HEALPIX values between bins?
projstr: WCS-projection
oversamplefloat: Oversampling factor for WCS map. This will be the approximate ratio of the width of a HPX pixel to a WCS pixel. If this parameter is None then the width will be set from width_pix.
width_pixint: Width of the WCS geometry in pixels. The pixel size will be set to the number of pixels satisfying oversample or width_pix whichever is smaller. If this parameter is None then the width will be set from oversample.
hpx2wcsHpxToWcsMapping: Set the HPX to WCS mapping object that will be used to generate the WCS map. If none then a new mapping will be generated based on proj and oversample arguments.

Returns

map_outWcsMap: WCS map object.

upsample(self, factor, preserve_counts=True)[source]¶

Upsample the spatial dimension by a given factor.

Parameters

factorint: Upsampling factor.
orderint: Order of the interpolation used for upsampling.
preserve_countsbool: 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).
axisstr: Which axis to upsample. By default spatial axes are upsampled.

Returns

mapMap: Upsampled map.

write(self, filename, overwrite=False, **kwargs)¶

Write to a FITS file.

Parameters

filenamestr: Output file name.
overwritebool: Overwrite existing file?
hdustr: Set the name of the image extension. By default this will be set to SKYMAP (for BINTABLE HDU) or PRIMARY (for IMAGE HDU).
hdu_bandsstr: Set the name of the bands table extension. By default this will be set to BANDS.
convstr: 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’.
sparsebool: Sparsify the map by dropping pixels with zero amplitude. This option is only compatible with the ‘gadf’ format.