.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "examples_generated/eos/plot_ag_eos.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download_examples_generated_eos_plot_ag_eos.py>`
        to download the full example code.

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_examples_generated_eos_plot_ag_eos.py:


.. _eos_example:

=======================
Equation of state (EOS)
=======================

First, do a bulk calculation for different lattice constants:

.. GENERATED FROM PYTHON SOURCE LINES 13-34

.. code-block:: Python

    import numpy as np

    from ase import Atoms
    from ase.calculators.emt import EMT
    from ase.eos import EquationOfState
    from ase.io import read
    from ase.io.trajectory import Trajectory
    from ase.units import kJ

    a = 4.0  # approximate lattice constant
    b = a / 2
    ag = Atoms(
        'Ag', cell=[(0, b, b), (b, 0, b), (b, b, 0)], pbc=1, calculator=EMT()
    )  # use EMT potential
    cell = ag.get_cell()
    traj = Trajectory('Ag.traj', 'w')
    for x in np.linspace(0.95, 1.05, 5):
        ag.set_cell(cell * x, scale_atoms=True)
        ag.get_potential_energy()
        traj.write(ag)








.. GENERATED FROM PYTHON SOURCE LINES 35-38

This writes a trajectory file containing five configurations of FCC silver
for five different lattice constants. Now, analyse the result with
the :class:`~ase.eos.EquationOfState` class:

.. GENERATED FROM PYTHON SOURCE LINES 38-48

.. code-block:: Python


    configs = read('Ag.traj@0:5')  # read 5 configurations
    # Extract volumes and energies:
    volumes = [ag.get_volume() for ag in configs]
    energies = [ag.get_potential_energy() for ag in configs]
    eos = EquationOfState(volumes, energies)
    v0, e0, B = eos.fit()
    print(B / kJ * 1.0e24, 'GPa')
    eos.plot('Ag-eos.png')




.. image-sg:: /examples_generated/eos/images/sphx_glr_plot_ag_eos_001.png
   :alt: sj: E: -0.000 eV, V: 16.781 Å$^3$, B: 100.142 GPa
   :srcset: /examples_generated/eos/images/sphx_glr_plot_ag_eos_001.png
   :class: sphx-glr-single-img


.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    100.14189241973199 GPa

    <Axes: title={'center': 'sj: E: -0.000 eV, V: 16.781 Å$^3$, B: 100.142 GPa'}, xlabel='volume [Å$^3$]', ylabel='energy [eV]'>



.. GENERATED FROM PYTHON SOURCE LINES 49-52

A quicker way to do this analysis is to use the :mod:`ase.gui` tool::

    $   ase gui Ag.traj

.. GENERATED FROM PYTHON SOURCE LINES 54-55

And then choose :menuselection:`Tools --> Bulk modulus`.


.. _sphx_glr_download_examples_generated_eos_plot_ag_eos.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: plot_ag_eos.ipynb <plot_ag_eos.ipynb>`

    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: plot_ag_eos.py <plot_ag_eos.py>`

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: plot_ag_eos.zip <plot_ag_eos.zip>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_