Map¶
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class
gammapy.maps.Map(geom, data, meta=None)[source]¶ Bases:
objectAbstract map class.
This can represent WCS- or HEALPIX-based maps with 2 spatial dimensions and N non-spatial dimensions.
Parameters: geom :
MapGeomGeometry
data :
ndarrayData array
meta :
OrderedDictDictionary to store meta data.
Attributes Summary
dataData array ( ndarray)geomMap geometry ( MapGeom)Methods Summary
coadd(map_in)Add the contents of map_into this map.create(**kwargs)Create an empty map object. 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 weightsvector.fill_by_idx(idx[, weights])Fill pixels at the given pixel indices with values in weightsvector.fill_by_pix(pix[, weights])Fill pixels at the given pixel coordinates with values in weightsvector.from_geom(geom[, meta, map_type])Generate an empty map from a Geominstance.from_hdu_list(hdulist[, hdu, hdu_bands, …])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. 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 valsvector.set_by_idx(idx, vals)Set pixels at the given pixel indices to the values in valsvector.set_by_pix(pix, vals)Set pixels at the given pixel coordinates to the values in valsvector.sum_over_axes()Reduce to a 2D image by summing over non-spatial dimensions. 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
Methods Documentation
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coadd(map_in)[source]¶ Add the contents of
map_into 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 :
MapInput map.
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classmethod
create(**kwargs)[source]¶ Create an empty map object.
This method accepts generic options listed below as well as options for
HpxMapandWcsMapobjects (seecreateandcreatefor WCS- and HPX-specific options).Parameters: coordsys : str
Coordinate system, either Galactic (‘GAL’) or Equatorial (‘CEL’).
map_type : {‘wcs’, ‘wcs-sparse’, ‘hpx’, ‘hpx-sparse’}
Map type. Selects the class that will be used to instantiate the map.
binsz : float or
ndarrayPixel size in degrees.
skydir :
SkyCoordCoordinate of map center.
axes : list
List of
MapAxisobjects for each non-spatial dimension. If None then the map will be a 2D image.dtype : str
Data type, default is
float32unit : str or
UnitData unit.
meta :
OrderedDictDictionary to store meta data.
Returns: map :
MapEmpty map object.
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crop(crop_width)[source]¶ 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_withfrompad.Returns: map :
MapCropped map.
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downsample(factor, preserve_counts=True)[source]¶ 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 :
MapDownsampled map.
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fill_by_coord(coords, weights=None)[source]¶ Fill pixels at the given map coordinates with values in
weightsvector.Parameters: coords : tuple or
MapCoordMapCoordobject 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 :
ndarrayWeights vector. If None then a unit weight will be assumed for each element in
coords.
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fill_by_idx(idx, weights=None)[source]¶ Fill pixels at the given pixel indices with values in
weightsvector.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 :
ndarrayWeights vector. If None then a unit weight will be assumed for each element in
idx.
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fill_by_pix(pix, weights=None)[source]¶ Fill pixels at the given pixel coordinates with values in
weightsvector.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 :
ndarrayWeights vector. If None then a unit weight will be assumed for each element in
pix.
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classmethod
from_geom(geom, meta=None, map_type='auto')[source]¶ Generate an empty map from a
Geominstance.Parameters: geom :
MapGeomMap geometry.
meta :
OrderedDictDictionary 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 :
MapMap object
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get_by_coord(coords)[source]¶ Return map values at the given map coordinates.
Parameters: coords : tuple or
MapCoordMapCoordobject 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 :
ndarrayValues of pixels in the map. np.nan used to flag coords outside of map.
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get_by_idx(idx)[source]¶ 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 :
ndarrayArray of pixel values. np.nan used to flag coordinate outside of map
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get_by_pix(pix)[source]¶ 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 :
ndarrayArray of pixel values. np.nan used to flag coordinates outside of map
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interp_by_coord(coords, interp=None)[source]¶ Interpolate map values at the given map coordinates.
Parameters: coords : tuple or
MapCoordMapCoordobject 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 :
ndarrayInterpolated pixel values.
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interp_by_pix(pix, interp=None)[source]¶ 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 :
ndarrayInterpolated pixel values.
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iter_by_coord(buffersize=1)[source]¶ 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 :
ndarrayMap values.
coords : tuple
Tuple of map coordinates.
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iter_by_image()[source]¶ Iterate over image planes of the map returning a tuple with the image array and image plane index.
Returns: val :
ndarrayArray of image plane values.
idx : tuple
Index of image plane.
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iter_by_pix(buffersize=1)[source]¶ 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 :
ndarrayMap values.
pix : tuple
Tuple of pixel coordinates.
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pad(pad_width, mode='constant', cval=0, order=1)[source]¶ 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 :
MapPadded map.
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classmethod
read(filename, hdu=None, hdu_bands=None, map_type='auto')[source]¶ 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 :
MapMap object
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reproject(geom, order=1, mode='interp')[source]¶ Reproject this map to a different geometry.
Parameters: geom :
MapGeomGeometry 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 :
MapReprojected map.
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set_by_coord(coords, vals)[source]¶ Set pixels at the given map coordinates to the values in
valsvector.Parameters: coords : tuple or
MapCoordMapCoordobject 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 :
ndarrayValues vector. Pixels at
coordswill be set to these values.
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set_by_idx(idx, vals)[source]¶ Set pixels at the given pixel indices to the values in
valsvector.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 :
ndarrayValues vector. Pixels at
idxwill be set to these values.
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set_by_pix(pix, vals)[source]¶ Set pixels at the given pixel coordinates to the values in
valsvector.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 :
ndarrayValues vector. Pixels at
pixwill be set to these values.
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upsample(factor, order=0, preserve_counts=True)[source]¶ 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 :
MapUpsampled map.
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write(filename, **kwargs)[source]¶ 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.
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