Create a sherpa data object from arrays of data.

The object returned by unpack_arrays can be used in a set_data call.

  • args (array_like) – Arrays of data. The order, and number, is determined by the dstype parameter, and listed in the load_arrays routine.

  • dstype – The data set type. The default is Data1D and values include: Data1D, Data1DInt, Data2D, Data2DInt, DataPHA, and DataIMG. The class is expected to be derived from sherpa.data.BaseData.


The data set object matching the requested dstype parameter.

Return type:


See also


Return the data set by identifier.


Create a data set from array values.


Set a data set.


Create a sherpa data object from a file.


Create a 1D (unbinned) data set from the values in the x and y arrays. Use the returned object to create a data set labelled “oned”:

>>> x = [1, 3, 7, 12]
>>> y = [2.3, 3.2, -5.4, 12.1]
>>> dat = unpack_arrays(x, y)
>>> set_data("oned", dat)

Include statistical errors on the data:

>>> edat = unpack_arrays(x, y, dy)

Create a “binned” 1D data set, giving the low, and high edges of the independent axis (xlo and xhi respectively) and the dependent values for this grid (y):

>>> hdat = unpack_arrays(xlo, xhi, y, Data1DInt)

Create a 3 column by 4 row image:

>>> ivals = np.arange(12)
>>> y, x = np.mgrid[0:3, 0:4]
>>> x = x.flatten()
>>> y = y.flatten()
>>> idat = unpack_arrays(x, y, ivals, (3, 4), DataIMG)