Data1DInt

class sherpa.data.Data1DInt(name, xlo, xhi, y, staterror=None, syserror=None)

Bases: sherpa.data.Data1D

1-D integrated data set

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
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)
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([yfunc])	Return label for dependent axis in N-D view of dependent variable”
ignore(*args, **kwargs)
notice([xlo, xhi, ignore])
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

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)

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(yfunc=None)

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

Parameters

yfunc –

ignore(*args, **kwargs)

notice(xlo=None, xhi=None, ignore=False)

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)