Stitch1D-v3.rst

.. algorithm::

.. summary::

.. alias::

.. properties::

Description
-----------

Stitches single histogram `Matrix Workspaces <http://www.mantidproject.org/MatrixWorkspace>`_
together outputting a stitched Matrix Workspace. Either the
right-hand-side or left-hand-side workspace can be chosen to be scaled.
Users must provide a Param step (single value), but the binning start
and end are calculated from the input workspaces if not provided.
Likewise, StartOverlap and EndOverlap are optional. If the StartOverlap
or EndOverlap are not provided, then these are taken to be the region of
x-axis intersection.

The workspaces must be histogrammed. Use
:ref:`algm-ConvertToHistogram` on workspaces prior to
passing them to this algorithm.

**Special Value Processing**

Special values, meaning infinite and NaN double precision values, are treated in a different way by the algorithm. The processing is as follows:

#. The workspaces are initially rebinned, as prescribed by the rebin Params (determined automatically if not provided)
#. Each spectra is searched for signal values and error values that are special values. Positions and type of special value are recorded
#. Special values found in the previous step are set to zero
#. Stitching proceeds, integration will not be performed considering any special values
#. Post processing the indexes of the special values are used to put the special values back where they came from

Usage
-----
**Example - a basic example using stitch1D to stitch two workspaces together.**

.. testcode:: ExStitch1DSimple

    import numpy as np

    def gaussian(x, mu, sigma):
      """Creates a gaussian peak centered on mu and with width sigma."""
      return (1/ sigma * np.sqrt(2 * np.pi)) * np.exp( - (x-mu)**2  / (2*sigma**2))

    #create two histograms with a single peak in each one
    x1 = np.arange(-1, 1, 0.02)
    x2 = np.arange(0.4, 1.6, 0.02)
    ws1 = CreateWorkspace(UnitX="1/q", DataX=x1, DataY=gaussian(x1[:-1], 0, 0.1)+1)
    ws2 = CreateWorkspace(UnitX="1/q", DataX=x2, DataY=gaussian(x2[:-1], 1, 0.05)+1)

    #stitch the histograms together
    stitched, scale = Stitch1D(LHSWorkspace=ws1, RHSWorkspace=ws2, StartOverlap=0.4, EndOverlap=0.6, Params=0.02)

Output:

.. image:: /images/Stitch1D1.png
   :scale: 65 %
   :alt: Stitch1D output
   :align: center


**Example - a practical example using reflectometry data and a scale factor.**

.. testcode:: ExStitch1DPractical

    trans1 = Load('INTER00013463')
    trans2 = Load('INTER00013464')

    trans1_wav = CreateTransmissionWorkspaceAuto(trans1)
    trans2_wav = CreateTransmissionWorkspaceAuto(trans2)

    stitched_wav, y = Stitch1D(trans1_wav, trans2_wav, UseManualScaleFactor=True, ManualScaleFactor=0.85)

Output:

.. image:: /images/Stitch1D2.png
   :scale: 65 %
   :alt: Stitch1D output
   :align: center


.. categories::