==================
Viewing Image Data
==================

``xrd-image-util``'s ``ImageDataGUI`` provides an lightweight, interactive way for users to visualize 3D image data. 


Accessing the ``ImageDataGUI``
------------------------------

Depending on the use case, there are multiple ways to access the GUI:

#. Scans

    The raw data for a ``Scan`` object can be visualized by simply calling the ``Scan.view_image_data`` function. To view 
    a scan's gridded reciprocal space mapped image, you must ensure that the ``Scan`` object's gridded data has been set up 
    with the ``Scan.grid_data`` function. After gridding the data, the ``Scan.view_image_data`` function will reveal a GUI 
    with two separate tabs: "Raw" and "Gridded".

    .. code-block:: python

        # Displays raw image data only
        scan_70.view_image_data()

    .. figure:: ../images/scan_70_raw.png
        :width: 75 %
        :align: center

    .. code-block:: python

        # Displays raw and gridded image data
        scan_70.grid_data((200, 200, 200))
        scan_70.view_image_data()

    .. figure:: ../images/scan_70_raw_and_gridded.png
        :width: 75 %
        :align: center

#. General 3D Numpy data

    The ``ImageDataGUI`` also works with generalized data using the ``xiu.gui.view_image_data`` function. With this function, 
    a user can provide a 3D numpy array and, as an option, a dictionary of labels and linear coordinates for each dimension.

    .. code-block:: python

        import numpy as np

        # Generating a 3D array of data
        data_shape = (100, 150, 200)
        data = np.zeros(shape=data_shape)

        for i in range(data_shape[0]):
            for j in range(data_shape[1]):
                for k in range(data_shape[2]):
                    data[i, j, k] = np.random.randint(i + 1, i + j + k + 2) 

        # Displaying the GUI
        xiu.gui.view_image_data(data)

    .. figure:: ../images/numpy_no_coords.png
        :width: 75 %
        :align: center


    .. code-block:: python

        import numpy as np

        # Generating a 3D array of data
        data_shape = (100, 150, 200)
        data = np.zeros(shape=data_shape)

        for i in range(data_shape[0]):
            for j in range(data_shape[1]):
                for k in range(data_shape[2]):
                    data[i, j, k] = np.random.randint(i + 1, i + j + k + 2) 

        # Defining linear coordinates for each dimension
        coords = {
            "Time": np.linspace(0, 100, 100),
            "A": np.linspace(-15, 15, 150),
            "B": np.linspace(-75, 75, 200)
        }

        # Displaying the GUI
        xiu.gui.view_image_data(data, coords)

    .. figure:: ../images/numpy_with_coords.png
        :width: 75 %
        :align: center