.. _17_reduced_density_gradient:

.. include:: ../../examples/17_reduced_density_gradient/README.rst

----

.. code-block:: python

   import matplotlib.pyplot as plt
   
   from eminus import Atoms, SCF
   from eminus.tools import get_reduced_gradient
   from eminus.units import ang2bohr
   

Do an RKS calculation for hydrogen with the given bond distance

.. code-block:: python

   atoms = Atoms("H2", [[0.0, 0.0, 0.0], [0.0, 0.0, ang2bohr(0.75)]], center=True)
   scf = SCF(atoms)
   scf.run()
   

One can even use thermal exchange-correlation functionals using Libxc

One example would be the following, where the temperature parameter of the functional gets modified (in Hartree)

.. code-block:: python

   # scf = SCF(atoms, xc=":LDA_XC_GDSMFB")
   # print(scf.xc_params_defaults)
   # scf.xc_params = {"T": 0.1}
   # scf.run()
   

Calculate the truncated reduced density gradient

.. code-block:: python

   s = get_reduced_gradient(scf, eps=1e-5)
   

Write n and s to CUBE files

One can view them, e.g., with the :code:`eminus.extras.view` function in a notebook

.. code-block:: python

   # scf.write("density.cube", scf.n)
   # scf.write("reduced_density_gradient.cube", s)
   

Plot s over n

Compare with figure 2 of the supplemental material

Find the plot named :code:`density_finger.png`

.. image:: density_finger.png
   :align: center


.. code-block:: python

   plt.style.use("../eminus.mplstyle")
   plt.figure()
   plt.scatter(scf.n, s, c=s)
   plt.xlabel("$n$")
   plt.ylabel("$s$[$n$]")
   plt.savefig("density_finger.png")

Download :download:`17_reduced_density_gradient.py <../../examples/17_reduced_density_gradient/17_reduced_density_gradient.py>` :download:`density_finger.png <../../examples/17_reduced_density_gradient/density_finger.png>`