RegionNDMap

class gammapy.maps.RegionNDMap(geom, data=None, dtype='float32', meta=None, unit='')

Bases: gammapy.maps.Map

N-dimensional region map. A RegionNDMap owns a RegionGeom instance as well as a data array containing the values associated to that region in the sky along the non-spatial axis, usually an energy axis. The spatial dimensions of a RegionNDMap are reduced to a single spatial bin with an arbitrary shape, and any extra dimensions are described by an arbitrary number of non-spatial axes.

Parameters

geomRegionGeom

Region geometry object.

datandarray

Data array. If none then an empty array will be allocated.

dtypestr, optional

Data type, default is float32

metadict

Dictionary to store meta data.

unitstr or Unit

The map unit

Attributes Summary

data	Data array (ndarray)
geom	Map geometry (Geom)
is_mask	Whether map is mask with bool dtype
meta	Map meta (dict)
quantity	Map data times unit (Quantity)
tag
unit	Map unit (Unit)

Methods Summary

apply_edisp(edisp)	Apply energy dispersion to map.
coadd(map_in[, weights])	Add the contents of map_in to this map.
copy(**kwargs)	Copy map instance and overwrite given attributes, except for geometry.
create(region[, axes, dtype, meta, unit, …])	Create an empty region map object.
crop()	Crop the spatial dimensions of the map.
cumsum(axis_name)	Compute cumulative sum along a given axis
cutout(*args, **kwargs)	Return self
downsample(factor[, preserve_counts, …])	Downsample the non-spatial dimension by a given factor.
fill_by_coord(coords[, weights])	Fill pixels at coords with given weights.
fill_by_idx(idx[, weights])	Fill pixels at idx with given weights.
fill_by_pix(pix[, weights])	Fill pixels at pix with given weights.
fill_events(events)	Fill event coordinates (EventList).
from_geom(geom[, meta, data, unit, dtype])	Generate an empty map from a Geom instance.
from_hdulist(hdulist[, format, ogip_column, hdu])	Create from HDUList.
from_stack(maps[, axis, axis_name])	Create Map from list of images and a non-spatial axis.
from_table(table[, format, colname])	Create region map from table
get_by_coord(coords[, fill_value])	Return map values at the given map coordinates.
get_by_idx(idxs)	Return map values at the given pixel indices.
get_by_pix(pix[, fill_value])	Return map values at the given pixel coordinates.
get_image_by_coord(coords)	Return spatial map at the given axis coordinates.
get_image_by_idx(idx)	Return spatial map at the given axis pixel indices.
get_image_by_pix(pix)	Return spatial map at the given axis pixel coordinates
get_spectrum(*args, **kwargs)	Return self
integral(axis_name, coords, **kwargs)	Compute integral along a given axis
interp_by_coord(coords, **kwargs)	Interpolate map values at the given map coordinates.
interp_by_pix(pix, **kwargs)	Interpolate map values at the given pixel coordinates.
interp_to_geom(geom[, preserve_counts, …])	Interpolate map to input geometry.
iter_by_axis(axis_name)	Iterate data by axis
iter_by_image()	Iterate over image planes of the map.
mask_nearest_position(position)	Given a sky coordinate return nearest valid position in the mask
normalize([axis_name])	Normalise data in place along a given axis.
pad(pad_width[, axis_name, mode, cval, method])	Pad the spatial dimensions of the map.
plot([ax, axis_name])	Plot the data contained in region map along the non-spatial axis.
plot_grid([figsize, ncols])	Plot map as a grid of subplots for non-spatial axes
plot_hist([ax])	Plot as histogram.
plot_interactive()	Plot map with interactive widgets to explore the non spatial axes.
plot_mask([ax])	Plot the mask as a shaded area in a xmin-xmax range
plot_region([ax])	Plot region
read(filename[, format, ogip_column, hdu])	Read from file.
reduce(axis_name[, func, keepdims, weights])	Reduce map over a single non-spatial axis
reduce_over_axes([func, keepdims, …])	Reduce map over non-spatial axes
resample_axis(axis[, weights, ufunc])	Resample map to a new axis binning by grouping over smaller bins and apply ufunc to the bin contents.
set_by_coord(coords, vals)	Set pixels at coords with given vals.
set_by_idx(idx, value)	Set pixels at idx with given vals.
set_by_pix(pix, vals)	Set pixels at pix with given vals.
slice_by_idx(slices)	Slice sub map from map object.
stack(other[, weights, nan_to_num])	Stack other region map into map.
sum_over_axes([axes_names, keepdims, weights])	To sum map values over all non-spatial axes.
to_cube(axes)	Append non-spatial axes to create a higher-dimensional Map.
to_hdulist([format, hdu, hdu_bands, hdu_region])	Convert to HDUList.
to_region_nd_map(*args, **kwargs)
to_table([format])	Convert to Table.
to_unit(unit)	Convert map to different unit
upsample(factor[, preserve_counts, axis_name])	Upsample the non-spatial dimension by a given factor.
write(filename[, overwrite, format, hdu])	Write map to file

Attributes Documentation

data

Data array (ndarray)

geom

Map geometry (Geom)

is_mask

Whether map is mask with bool dtype

meta

Map meta (dict)

quantity

Map data times unit (Quantity)

tag = 'map'

unit

Map unit (Unit)

Methods Documentation

apply_edisp(edisp)

Apply energy dispersion to map. Requires energy axis.

Parameters

edispgammapy.irf.EDispKernel

Energy dispersion matrix

Returns

mapWcsNDMap

Map with energy dispersion applied.

coadd(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(**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(region, axes=None, dtype='float32', meta=None, unit='', wcs=None, binsz_wcs='0.1deg', data=None)

Create an empty region map object.

Parameters

regionstr or SkyRegion

Region specification

axeslist of MapAxis

Non spatial axes.

dtypestr

Data type, default is ‘float32’

unitstr or Unit

Data unit.

metadict

Dictionary to store meta data.

wcsWCS

WCS projection to use for local projections of the region

datandarray

Data array

Returns

mapRegionNDMap

Region map

crop()

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.

cumsum(axis_name)

Compute cumulative sum along a given axis

Parameters

axis_namestr

Along which axis to integrate.

Returns

cumsumMap

Map with cumulative sum

cutout(*args, **kwargs)

Return self

downsample(factor, preserve_counts=True, axis_name='energy', weights=None)

Downsample the non-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).

axis_namestr

Which axis to downsample. Default is “energy”.

weightsRegionNDMap

Contains the weights to apply to the axis to reduce. Default is just weighs of one.

Returns

mapRegionNDMap

Downsampled region map.

fill_by_coord(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(idx, weights=None)

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(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(events)

Fill event coordinates (EventList).

static from_geom(geom, meta=None, data=None, 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.

unitstr or Unit

Data unit.

Returns

map_outMap

Map object

classmethod from_hdulist(hdulist, format='gadf', ogip_column=None, hdu=None, **kwargs)

Create from HDUList.

Parameters

hdulistHDUList

HDU list.

format{“gadf”, “ogip”, “ogip-arf”}

Format specification

ogip_column{“COUNTS”, “QUALITY”, “BACKSCAL”}

If format ‘ogip’ is chosen which table hdu column to read.

hdustr

Name or index of the HDU with the map data.

Returns

region_nd_mapRegionNDMap

Region map.

classmethod from_stack(maps, axis=None, axis_name=None)

Create Map from list of images and a non-spatial axis.

The image geometries must be aligned, except for the axis that is stacked.

Parameters

mapslist of Map objects

List of maps

axisMapAxis

If a MapAxis is provided the maps are stacked along the last data axis and the new axis is introduced.

axis_namestr

If an axis name is as string the given the maps are stacked along the given axis name.

Returns

mapMap

Map with additional non-spatial axis.

classmethod from_table(table, format='', colname=None)

Create region map from table

Parameters

tableTable

Table with input data

format{“gadf-sed”, “lightcurve”, “profile”}

Format to use

colnamestr

Column name to take the data from.

Returns

region_mapRegionNDMap

Region map

get_by_coord(coords, fill_value=nan)

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.

fill_valuefloat

Value which is returned if the position is outside of the projection footprint

Returns

valsndarray

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

get_by_idx(idxs)

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(pix, fill_value=nan)

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.

fill_valuefloat

Value which is returned if the position is outside of the projection footprint

Returns

valsndarray

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

get_image_by_coord(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_idx, get_image_by_pix

Examples

import numpy as np
from gammapy.maps import Map, MapAxis
from astropy.coordinates import SkyCoord
from astropy import units as u

# Define map axes
energy_axis = MapAxis.from_edges(
    np.logspace(-1., 1., 4), unit='TeV', name='energy',
)

time_axis = MapAxis.from_edges(
    np.linspace(0., 10, 20), unit='h', name='time',
)

# Define map center
skydir = SkyCoord(0, 0, frame='galactic', unit='deg')

# Create map
m_wcs = Map.create(
    map_type='wcs',
    binsz=0.02,
    skydir=skydir,
    width=10.0,
    axes=[energy_axis, time_axis],
)

# Get image by coord tuple
image = m_wcs.get_image_by_coord(('500 GeV', '1 h'))

# Get image by coord dict with strings
image = m_wcs.get_image_by_coord({'energy': '500 GeV', 'time': '1 h'})

# Get image by coord dict with quantities
image = m_wcs.get_image_by_coord({'energy': 0.5 * u.TeV, 'time': 1 * u.h})

get_image_by_idx(idx)

Return spatial map at the given axis pixel indices.

Parameters

idxtuple

Tuple of scalar indices for each non spatial dimension of the map. Tuple should be ordered as (I_0, …, I_n).

Returns

map_outMap

Map with spatial dimensions only.

See also

get_image_by_coord, get_image_by_pix

get_image_by_pix(pix)

Return spatial map at the given axis pixel coordinates

Parameters

pixtuple

Tuple of scalar pixel coordinates for each non-spatial dimension of the map. Tuple should be ordered as (I_0, …, I_n). Pixel coordinates can be either float or integer type.

Returns

map_outMap

Map with spatial dimensions only.

See also

get_image_by_coord, get_image_by_idx

get_spectrum(*args, **kwargs)

Return self

integral(axis_name, coords, **kwargs)

Compute integral along a given axis

This method uses interpolation of the cumulative sum.

Parameters

axis_namestr

Along which axis to integrate.

coordsdict or MapCoord

Map coordinates

**kwargsdict

Coordinates at which to evaluate the IRF

Returns

arrayQuantity

Returns 2D array with axes offset

interp_by_coord(coords, **kwargs)

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.

method{“nearest”, “linear”}

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.

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(pix, **kwargs)

Interpolate map values at the given pixel coordinates.

Parameters

pixtuple

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.

method{“nearest”, “linear”}

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.

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_to_geom(geom, preserve_counts=False, fill_value=0, **kwargs)

Interpolate map to input geometry.

Parameters

geomGeom

Target Map geometry

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)

**kwargsdict

Keyword arguments passed to Map.interp_by_coord

Returns

interp_mapMap

Interpolated Map

iter_by_axis(axis_name)

Iterate data by axis

Parameters

axis_namestr

Axis name

Returns

idx, datatuple, Quantity

Data and index

iter_by_image()

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.

mask_nearest_position(position)

Given a sky coordinate return nearest valid position in the mask

If the mask contains additional axes, the mask is reduced over those.

Parameters

positionSkyCoord

Test position

Returns

positionSkyCoord

Nearest position in the mask

normalize(axis_name=None)

Normalise data in place along a given axis.

Parameters

axis_namestr

Along which axis to normalize.

pad(pad_width, axis_name=None, mode='constant', cval=0, method='linear')

Pad the spatial dimensions of the map.

Parameters

pad_width{sequence, array_like, int}

Number of pixels padded to the edges of each axis.

axis_namestr

Which axis to downsample. By default spatial axes are padded.

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’.

Returns

mapMap

Padded map.

plot(ax=None, axis_name=None, **kwargs)

Plot the data contained in region map along the non-spatial axis.

Parameters

axAxis

Axis used for plotting

axis_namestr

Which axis to plot on the x axis. Extra axes will be plotted as additional lines.

**kwargsdict

Keyword arguments passed to errorbar

Returns

axAxis

Axis used for plotting

plot_grid(figsize=None, ncols=3, **kwargs)

Plot map as a grid of subplots for non-spatial axes

Parameters

figsizetuple of int

Figsize to plot on

ncolsint

Number of columns to plot

**kwargsdict

Keyword arguments passed to Map.plot.

Returns

axesndarray of Axes

Axes grid

plot_hist(ax=None, **kwargs)

Plot as histogram.

kwargs are forwarded to hist

Parameters

axaxis (optional)

Axis instance to be used for the plot

**kwargsdict

Keyword arguments passed to hist

Returns

axAxis

Axis used for plotting

plot_interactive()

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)

plot_mask(ax=None, **kwargs)

Plot the mask as a shaded area in a xmin-xmax range

Parameters

axaxis

Axis instance to be used for the plot.

**kwargsdict

Keyword arguments passed to axvspan

Returns

axAxis

Axis used for plotting

plot_region(ax=None, **kwargs)

Plot region

Parameters

axWCSAxes

Axes to plot on. If no axes are given, the region is shown using the minimal equivalent WCS geometry.

**kwargsdict

Keyword arguments forwarded to as_artist

classmethod read(filename, format='gadf', ogip_column=None, hdu=None)

Read from file.

Parameters

filenamepathlib.Path or str

Filename.

format{“gadf”, “ogip”, “ogip-arf”}

Which format to use.

ogip_column{None, “COUNTS”, “QUALITY”, “BACKSCAL”}

If format ‘ogip’ is chosen which table hdu column to read.

hdustr

Name or index of the HDU with the map data.

Returns

region_mapRegionNDMap

Region nd map

reduce(axis_name, func=<ufunc 'add'>, keepdims=False, weights=None)

Reduce map over a single non-spatial axis

Parameters

axis_name: str

The name of the axis to reduce over

funcufunc

Function to use for reducing the data.

keepdimsbool, optional

If this is set to true, the axes which are summed over are left in the map with a single bin

weightsMap

Weights to be applied.

Returns

map_outMap

Map with the given non-spatial axes reduced

reduce_over_axes(func=<ufunc 'add'>, keepdims=False, axes_names=None, weights=None)

Reduce map over non-spatial axes

Parameters

funcufunc

Function to use for reducing the data.

keepdimsbool, optional

If this is set to true, the axes which are summed over are left in the map with a single bin

axes_names: list

Names of MapAxis to reduce over If None, all will reduced

weightsMap

Weights to be applied.

Returns

map_outMap

Map with non-spatial axes reduced

resample_axis(axis, weights=None, ufunc=<ufunc 'add'>)

Resample map to a new axis binning by grouping over smaller bins and apply ufunc to the bin contents.

By default, the map content are summed over the smaller bins. Other numpy ufunc can be used, e.g. np.logical_and, np.logical_or

Parameters

axisMapAxis

New map axis.

weightsMap

Array to be used as weights. The spatial geometry must be equivalent to other and additional axes must be broadcastable.

ufuncufunc

ufunc to use to resample the axis. Default is numpy.add.

Returns

mapMap

Map with resampled axis.

set_by_coord(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(idx, value)

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(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(slices)

Slice sub map from map object.

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.

stack(other, weights=None, nan_to_num=True)

Stack other region map into map.

Parameters

otherRegionNDMap

Other map to stack

weightsRegionNDMap

Array to be used as weights. The spatial geometry must be equivalent to other and additional axes must be broadcastable.

nan_to_num: bool

Non-finite values are replaced by zero if True (default).

sum_over_axes(axes_names=None, keepdims=True, weights=None)

To sum map values over all non-spatial axes.

Parameters

keepdimsbool, optional

If this is set to true, the axes which are summed over are left in the map with a single bin

axes_names: list of str

Names of MapAxis to reduce over. If None, all will summed over

weightsMap

Weights to be applied. The Map should have the same geometry.

Returns

map_outMap

Map with non-spatial axes summed over

to_cube(axes)

Append non-spatial axes to create a higher-dimensional Map.

This will result in a Map with a new geometry with N+M dimensions where N is the number of current dimensions and M is the number of axes in the list. The data is reshaped onto the new geometry

Parameters

axeslist

Axes that will be appended to this Map. The axes should have only one bin

Returns

mapWcsNDMap

new map

to_hdulist(format='gadf', hdu='SKYMAP', hdu_bands=None, hdu_region=None)

Convert to HDUList.

Parameters

format{“gadf”, “ogip”, “ogip-sherpa”, “ogip-arf”, “ogip-arf-sherpa”}

Format specification

hdustr

Name of the HDU with the map data, used for “gadf” format.

hdu_bandsstr

Name or index of the HDU with the BANDS table, used for “gadf” format.

hdu_regionstr

Name or index of the HDU with the region table.

Returns

hdulistHDUList

HDU list

to_region_nd_map(*args, **kwargs)

to_table(format='gadf')

Convert to Table.

Data format specification: PHA

Parameters

format{“gadf”, “ogip”, “ogip-arf”, “ogip-arf-sherpa”}

Format specification

Returns

tableTable

Table

to_unit(unit)

Convert map to different unit

Parameters

unitUnit or str

New unit

Returns

mapMap

Map with new unit and converted data

upsample(factor, preserve_counts=True, axis_name='energy')

Upsample the non-spatial dimension by a given factor.

Parameters

factorint

Upsampling factor.

preserve_countsbool

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

axis_namestr

Which axis to upsample. Default is “energy”.

Returns

mapRegionNDMap

Upsampled region map.

write(filename, overwrite=False, format='gadf', hdu='SKYMAP')

Write map to file

Parameters

filenamepathlib.Path or str

Filename.

format{“gadf”, “ogip”, “ogip-sherpa”, “ogip-arf”, “ogip-arf-sherpa”}

Which format to use.

overwritebool

Overwrite existing files?