DataRosatRMF

class sherpa.astro.data.DataRosatRMF(name, detchans, energ_lo, energ_hi, n_grp, f_chan, n_chan, matrix, offset=1, e_min=None, e_max=None, header=None, ethresh=None)

Bases: sherpa.astro.data.DataRMF

Attributes Summary

dep	Left for compatibility with older versions
indep	Return the grid of the data space associated with this data set.
mask	Mask array for dependent variable
ui_name
x	Used for compatibility, in particular for __str__ and __repr__
xhi	Property kept for compatibility
xlo	Property kept for compatibility

Methods Summary

apply_filter(data)
apply_rmf(src, *args, **kwargs)	Fold the source array src through the RMF and return the result
eval_model(modelfunc)
eval_model_to_fit(modelfunc)
get_bounding_mask()
get_dep([filter])	Return the dependent axis of a data set.
get_dims([filter])	Return the dimensions of this data space as a tuple of tuples.
get_error([filter, staterrfunc])	Return the total error on the dependent variable.
get_evaluation_indep([filter, model, …])
get_filter([format, delim])
get_filter_expr()
get_img([yfunc])	Return 1D dependent variable as a 1 x N image
get_imgerr()
get_indep([filter])	Return the independent axes of a data set.
get_staterror([filter, staterrfunc])	Return the statistical error on the dependent axis of a data set.
get_syserror([filter])	Return the statistical error on the dependent axis of a data set.
get_x([filter, model, use_evaluation_space])
get_xerr([filter, model])	Return linear view of bin size in independent axis/axes”
get_xlabel()	Return label for linear view of independent axis/axes
get_y([filter, yfunc, use_evaluation_space])	Return dependent axis in N-D view of dependent variable”
get_yerr([filter, staterrfunc])	Return errors in dependent axis in N-D view of dependent variable
get_ylabel()	Return label for dependent axis in N-D view of dependent variable”
ignore(*args, **kwargs)
notice([noticed_chans])
set_dep(val)	Set the dependent variable values”
set_indep(val)
to_component_plot([yfunc, staterrfunc])
to_fit([staterrfunc])
to_guess()
to_plot([yfunc, staterrfunc])

Attributes Documentation

dep

Left for compatibility with older versions

indep

Return the grid of the data space associated with this data set. :returns: :rtype: tuple of array_like

mask

Mask array for dependent variable

Returns:mask Return type:bool or numpy.ndarray

ui_name = 'ROSAT RMF'

x

Used for compatibility, in particular for __str__ and __repr__

xhi

Property kept for compatibility

xlo

Property kept for compatibility

Methods Documentation

apply_filter(data)

apply_rmf(src, *args, **kwargs)

Fold the source array src through the RMF and return the result

eval_model(modelfunc)

eval_model_to_fit(modelfunc)

get_bounding_mask()

get_dep(filter=False)

Return the dependent axis of a data set.

Parameters:filter (bool, optional) – Should the filter attached to the data set be applied to the return value or not. The default is False. Returns:axis – The dependent axis values for the data set. This gives the value of each point in the data set. Return type:array

See also

get_indep()

Return the independent axis of a data set.

get_error()

Return the errors on the dependent axis of a data set.

get_staterror()

Return the statistical errors on the dependent axis of a data set.

get_syserror()

Return the systematic errors on the dependent axis of a data set.

get_dims(filter=False)

Return the dimensions of this data space as a tuple of tuples. The first element in the tuple is a tuple with the dimensions of the data space, while the second element provides the size of the dependent array. :returns: :rtype: tuple

get_error(filter=False, staterrfunc=None)

Return the total error on the dependent variable.

Parameters:

• filter (bool, optional) – Should the filter attached to the data set be applied to the return value or not. The default is False.
• staterrfunc (function) – If no statistical error has been set, the errors will be calculated by applying this function to the dependent axis of the data set.

Returns:

axis – The error for each data point, formed by adding the statistical and systematic errors in quadrature.

Return type:

array or None

See also

get_dep()

Return the independent axis of a data set.

get_staterror()

Return the statistical errors on the dependent axis of a data set.

get_syserror()

Return the systematic errors on the dependent axis of a data set.

get_evaluation_indep(filter=False, model=None, use_evaluation_space=False)

get_filter(format='%.4f', delim=':')

get_filter_expr()

get_img(yfunc=None)

Return 1D dependent variable as a 1 x N image

Parameters:yfunc –

get_imgerr()

get_indep(filter=False)

Return the independent axes of a data set.

Parameters:filter (bool, optional) – Should the filter attached to the data set be applied to the return value or not. The default is False. Returns:axis – The independent axis values for the data set. This gives the coordinates of each point in the data set. Return type:tuple of arrays

See also

get_dep()

Return the dependent axis of a data set.

get_staterror(filter=False, staterrfunc=None)

Return the statistical error on the dependent axis of a data set.

Parameters:

• filter (bool, optional) – Should the filter attached to the data set be applied to the return value or not. The default is False.
• staterrfunc (function) – If no statistical error has been set, the errors will be calculated by applying this function to the dependent axis of the data set.

Returns:

axis – The statistical error for each data point. A value of None is returned if the data set has no statistical error array and staterrfunc is None.

Return type:

array or None

See also

get_error()

Return the errors on the dependent axis of a data set.

get_indep()

Return the independent axis of a data set.

get_syserror()

Return the systematic errors on the dependent axis of a data set.

get_syserror(filter=False)

Return the statistical error on the dependent axis of a data set.

Parameters:filter (bool, optional) – Should the filter attached to the data set be applied to the return value or not. The default is False. Returns:axis – The systematic error for each data point. A value of None is returned if the data set has no systematic errors. Return type:array or None

See also

get_error()

Return the errors on the dependent axis of a data set.

get_indep()

Return the independent axis of a data set.

get_staterror()

Return the statistical errors on the dependent axis of a data set.

get_x(filter=False, model=None, use_evaluation_space=False)

get_xerr(filter=False, model=None)

Return linear view of bin size in independent axis/axes”

Parameters:

• filter –
• yfunc –

get_xlabel()

Return label for linear view of independent axis/axes

get_y(filter=False, yfunc=None, use_evaluation_space=False)

Return dependent axis in N-D view of dependent variable”

Parameters:

• filter –
• yfunc –
• use_evaluation_space –

get_yerr(filter=False, staterrfunc=None)

Return errors in dependent axis in N-D view of dependent variable

Parameters:

• filter –
• staterrfunc –

get_ylabel()

Return label for dependent axis in N-D view of dependent variable”

Parameters:yfunc –

ignore(*args, **kwargs)

notice(noticed_chans=None)

set_dep(val)

Set the dependent variable values”

Parameters:val –

set_indep(val)

to_component_plot(yfunc=None, staterrfunc=None)

to_fit(staterrfunc=None)

to_guess()

to_plot(yfunc=None, staterrfunc=None)