.. algorithm::

.. summary::

.. relatedalgorithms::

.. properties::

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

This algorithm will load a series of runs into a MDHistoWorkspace that
has dimensions x and y detector pixels vs scanIndex.
The scanIndex is the omega rotation of the sample.
The instrument attached to the OutputWorkspace is directly copied from the FIRST run, therefore
it is crucial to have the correct instrument attached to the first run.
In addition the s1 (omega rotation), duration, run_number and monitor count is read from every
file and included in the logs of the OutputWorkspace.

During a recent feature expansion, normalization can be optionally performed in the same process
provided that the necessary Vanadium data is specified.
By default, the algorithm will try to locate the Vanadium data using IPTS and run number.
If failed, it will check the Vanadium filename entry to see if the data can be loaded directly
from file.
If neither is provided, the algorithm will try to check if the Vanadium data is provided as a
workspace in memory.
Currently there are three normalization scheme supported: by Count, by Monitor and by Time.
If None is selected, no normalization will be performed and all normalization related properties
will be ignored (on the GUI end, they will be disabled instead).

If the "HB2C:CS:CrystalAlign:UBMatrix" property exists and apply goniometer tilt is true,
it will be converted into the OrientedLattice on the OutputWorkspace.
The goniometer tilts (sgu and sgl) are combined into the UB Matrix so that only omega (s1) needs to
be taken into account during rotation.

This algorithm doesn't use Mantid loaders but instead h5py and numpy to load and integrate the events.

There is a grouping option to group pixels by either 2x2 or 4x4 which will help in reducing memory
usage and speed up the later reduction steps.
In most cases you will not see a difference in reduced data with 4x4 pixel grouping.
Also, both input data and the Vanadium data will share the same grouping scheme.

The loaded workspace is designed to be the input to
:ref:`algm-ConvertWANDSCDtoQ`.

Usage
-----

**Load one file, Vanadium for normalisation**

.. code-block:: python

    norm = LoadWANDSCD(IPTS=7776, RunNumbers=26509)
    print(repr(norm))

Output:

.. code-block:: none

    MDHistoWorkspace
    Title:
    Dim 0: (y) 0.5 to 512.5 in 512 bins
    Dim 1: (x) 0.5 to 3840.5 in 3840 bins
    Dim 2: (scanIndex) 0.5 to 1.5 in 1 bins

    Inelastic: ki-kf
    Instrument: ...

    Run start: 2018-Mar-12 17:10:59
    Run end:  not available
    Sample: a 1.0, b 1.0, c 1.0; alpha 90, beta 90, gamma 90


**Load data and Vanadium at the same time**

.. code-block:: python

    data = LoadWANDSCD(
        IPTS=7776, RunNumbers='26640-27944',
        VanadiumIPTS=7776, VanadiumRunNumber=26509,
        NormalizedBy='Monitor',
        )


**Load multiple data file**

.. code-block:: python

    data = LoadWANDSCD(IPTS=7776, RunNumbers='26640-27944')
    print("Memory used: {}GiB".format(data.getMemorySize()/2**30))
    print(repr(data))
    print('s1 = {}'.format(data.getExperimentInfo(0).run().getProperty('s1').value[0:10]))
    print('monitor_counts = {}'.format(data.getExperimentInfo(0).run().getProperty('monitor_counts').value[0:10]))
    print('duration = {}'.format(data.getExperimentInfo(0).run().getProperty('duration').value[0:10]))
    print('run_number = {}'.format(data.getExperimentInfo(0).run().getProperty('run_number').value[0:10]))

Output:

.. code-block:: none

    Memory used: 59GB

    MDHistoWorkspace
    Title:
    Dim 0: (y) 0.5 to 512.5 in 512 bins
    Dim 1: (x) 0.5 to 3840.5 in 3840 bins
    Dim 2: (scanIndex) 0.5 to 1305.5 in 1305 bins
    Inelastic: ki-kf
    Instrument: ...
    Run start: 2018-May-02 13:34:10
    Run end:  not available
    Sample: a 5.7, b 5.7, c 5.6; alpha 93, beta 90, gamma 98

    s2 = [-180,-179.9,-179.8,-179.7,-179.6,-179.5,-179.4,-179.3,-179.2,-179.1]
    monitor_count = [44571,44598,44567,44869,44453,44238,44611,44120,44762,44658]
    duration = [2.05,2.05,2.03333,2.05,2.03333,2.03333,2.05,2.01667,2.05,2.05]
    run_number = [26640,26641,26642,26643,26644,26645,26646,26647,26648,26649]


**Load with different grouping comparing memory usage**

.. code-block:: python

    data = LoadWANDSCD(IPTS=7776, RunNumbers='26640-27944')
    data_2x2 = LoadWANDSCD(IPTS=7776, RunNumbers='26640-27944', Grouping='2x2')
    data_4x4 = LoadWANDSCD(IPTS=7776, RunNumbers='26640-27944', Grouping='4x4')
    print("Memory used by {}: {}GiB".format(data,data.getMemorySize()/2**30))
    print("Memory used by {}: {}GiB".format(data_2x2,data_2x2.getMemorySize()/2**30))
    print("Memory used by {}: {}GiB".format(data_4x4,data_4x4.getMemorySize()/2**30))
    print(repr(data_4x4))

    # Integrate y and plot
    data_integrated = IntegrateMDHistoWorkspace('data_4x4', P1Bin='0,129')
    import matplotlib.pyplot as plt
    from mantid import plots
    fig, ax = plt.subplots(subplot_kw={'projection':'mantid'})
    c = ax.pcolormesh(data_integrated, vmax=100)
    cbar=fig.colorbar(c)
    cbar.set_label('Intensity (arb. units)')
    #fig.savefig('LoadWANDSCD.png')

Output:

.. code-block:: none

    Memory used by data: 59GiB
    Memory used by data_2x2: 14GiB
    Memory used by data_4x4: 3GiB

    MDHistoWorkspace
    Title:
    Dim 0: (y) 0.5 to 128.5 in 128 bins
    Dim 1: (x) 0.5 to 960.5 in 960 bins
    Dim 2: (scanIndex) 0.5 to 1305.5 in 1305 bins
    Inelastic: ki-kf
    Instrument: ...
    Run start: 2018-May-02 13:34:10
    Run end:  not available
    Sample: a 5.7, b 5.7, c 5.6; alpha 93, beta 90, gamma 98

.. figure:: /images/LoadWANDSCD.png


Workflow
--------

From left to right:

- main workflow
- Expanded steps of 'Load and Group'
- Expanded steps of 'Normalize by vanadium'

.. diagram:: LoadWANDSCD-v1_wkflw.dot

.. categories::

.. sourcelink::