.. code:: python

    %matplotlib inline
    import matplotlib.pyplot as plt
    import matplotlib.tri as tri
    import numpy as np
    import adios as ad
    plt.rcParams['figure.figsize'] = (6, 4)
    cm = plt.cm.jet

.. code:: python

    subdir = 'totalf_itg_tiny/'

XGC mesh structure
------------------

XGC mesh file (xgc.mesh.bp) contains the following variables: \* n\_n:
the number of nodes \* n\_t: the number of cells \* rz: node coodinates
(shape: {n\_n, 2}) \* nd\_connect\_list: connection list or cell
definition (shape: {n\_t, 3})

.. code:: python

    with ad.file(subdir + 'xgc.mesh.bp') as f:
        nnodes = f['n_n'][...]
        ncells = f['n_t'][...]
        rz = f['rz'][...]
        conn = f['nd_connect_list'][...]
    
    R = rz[:,0]
    Z = rz[:,1]

.. code:: python

    plt.plot(R, Z, ',');
    plt.axis('equal');



.. image:: XGC-mesh-and-field-data_files/XGC-mesh-and-field-data_4_0.png


If we zoom, we can see the unstructued mesh clearly:

.. code:: python

    trimesh = tri.Triangulation(R, Z, conn)
    plt.triplot(trimesh);
    plt.xlim([1.05, 1.2])
    plt.ylim([0.0, 0.2]);



.. image:: XGC-mesh-and-field-data_files/XGC-mesh-and-field-data_6_0.png


XGC field data
--------------

Let's draw one of XGC field data: dpot in xgc.3d.xxxxx.bp.

The shape of dpot is (n\_n, nphi) where n\_n is the number of grid
nondes and nphi is the number of planes used in XGC simulation.

.. code:: python

    with ad.file(subdir + 'xgc.3d.08800.bp') as f:
        dpot = f['dpot'][...,0]

.. code:: python

    plt.scatter(R, Z, c=dpot, marker='.', lw = 0);
    plt.xlim([1.2, 2.2])
    plt.ylim([0.0, 0.7]);



.. image:: XGC-mesh-and-field-data_files/XGC-mesh-and-field-data_9_0.png


.. code:: python

    trimesh = tri.Triangulation(R, Z, conn)
    plt.tricontourf(trimesh, dpot, cmap=cm);
    plt.axis('equal');
    plt.colorbar();



.. image:: XGC-mesh-and-field-data_files/XGC-mesh-and-field-data_10_0.png


Let's refine the plot by restricting the dpot range to see more
turbulent behavior.

.. code:: python

    plt.hist(dpot);



.. image:: XGC-mesh-and-field-data_files/XGC-mesh-and-field-data_12_0.png


.. code:: python

    def plot_dpot(dpot, levels=np.linspace(-20, 20, num=101), title=''):
        dp = dpot.copy()
        dp[dpot >= levels[-1]] = levels[-2]
        dp[dpot <= levels[0]] = levels[0]
        plt.tricontourf(trimesh, dp, levels, cmap=cm);
        plt.axis('equal');
        plt.colorbar();
        plt.title(title)

.. code:: python

    plot_dpot(dpot)



.. image:: XGC-mesh-and-field-data_files/XGC-mesh-and-field-data_14_0.png