Esempio n. 1
1
def get_gibbs(structure, db_file, eos="vinet", t_step=10, t_min=0, t_max=1000, mesh=(20, 20, 20),
              plot=False):
    # other eos options: birch_murnaghan, murnaghan
    # The physical units of V and T are \AA^3 and K, respectively.
    # The unit of eV for Helmholtz and Gibbs energies,
    # J/K/mol for C_V and entropy, GPa for for bulk modulus and pressure are used.
    try:
        from phonopy import PhonopyQHA
    except ImportError:
        print("Install phonopy. Exiting.")
        sys.exit()

    phonon = get_phonopy(structure)
    energies, volumes, force_constants = get_data(db_file, query={
        "task_label": {"$regex": "gibbs*"}, "formula_pretty": structure.composition.reduced_formula})

    temperatures = []
    free_energy = []
    entropy = []
    cv = []

    for f in force_constants:
        phonon.set_force_constants(-np.array(f))
        phonon.set_mesh(list(mesh))
        phonon.set_thermal_properties(t_step=t_step, t_min=t_min, t_max=t_max)
        t, g, e, c = phonon.get_thermal_properties()
        temperatures.append(t)
        free_energy.append(g)
        entropy.append(e)
        cv.append(c)

    phonopy_qha = PhonopyQHA(volumes, energies, eos=eos, temperatures=temperatures[0],
                             free_energy=np.array(free_energy).T, cv=np.array(cv).T,
                             entropy=np.array(entropy).T, t_max=np.max(temperatures[0]))

    # gibbs free energy
    max_t_index = phonopy_qha._qha._max_t_index
    G = phonopy_qha.get_gibbs_temperature()[:max_t_index]
    T = phonopy_qha._qha._temperatures[:max_t_index]
    if plot:
        import warnings
        with warnings.catch_warnings():
            warnings.simplefilter("ignore")
            import matplotlib.pyplot as plt
            plt.plot(T, G)
            plt.savefig("Gibbs.pdf")
            plt.show()
            #phonopy_qha.plot_qha(thin_number=10, volume_temp_exp=None).show()
    else:
        return T, G
Esempio n. 2
0
def get_qha(eos, temperatures, fe_phonon, cv, entropy, t_max=1000):

    from phonopy import PhonopyQHA
    import numpy as np

    phonopy_qha = PhonopyQHA(eos.get_array('volumes'),
                             eos.get_array('energies'),
                             eos="vinet",
                             temperatures=np.array(temperatures),
                             free_energy=np.array(fe_phonon).T,
                             cv=np.array(cv),
                             entropy=np.array(entropy),
                             t_max=t_max,
                             verbose=False)

    # testing
    if __testing__:
        import matplotlib.pyplot as plt
        plt = phonopy_qha.plot_qha()
        plt.show()

    qha_results = {'qha_temperatures': phonopy_qha._qha._temperatures[:phonopy_qha._qha._max_t_index],
                   'helmholtz_volume': phonopy_qha.get_helmholtz_volume(),
                   'thermal_expansion': phonopy_qha.get_thermal_expansion(),
                   'volume_temperature':  phonopy_qha.get_volume_temperature(),
                   'heat_capacity_P_numerical': phonopy_qha.get_heat_capacity_P_numerical(),
                   'volume_expansion': phonopy_qha.get_volume_expansion(),
                   'gibbs_temperature': phonopy_qha.get_gibbs_temperature()}

    return qha_results
Esempio n. 3
0
    def collect_data(self):

        energies = []
        volumes = []
        # Get the calculations from workflow
        from itertools import chain

        #      wf_list = list(chain(self.get_step(self.volume_expansions).get_sub_workflows(),
        #                self.get_step(self.start).get_sub_workflows()))

        wf_list = self.get_step(self.volume_expansions).get_sub_workflows()
        for wf in wf_list:
            dos = wf.get_result('dos').get_array('total_dos')
            #            self.append_to_report('DOS')
            #            self.append_to_report('{}'.format(dos.tolist()))
            energy = wf.get_result(
                'optimized_structure_data').get_dict()['energy']
            volume = wf.get_result('final_structure').get_cell_volume()
            self.append_to_report('{} {}'.format(volume, energy))
            energies.append(energy)
            volumes.append(volume)

        import numpy as np
        #       data = ArrayData()
        #       data.set_array('energy', np.array(energies))
        #       data.set_array('volume', np.array(volumes))
        #       data.store()
        #       self.add_result('data', data)

        volumes = []
        electronic_energies = []
        fe_phonon = []
        entropy = []
        cv = []

        thermal_list = []
        structures = []
        optimized_data = []

        inline_params = {}

        wf_list = list(
            chain(
                self.get_step(self.volume_expansions).get_sub_workflows(),
                self.get_step(self.start).get_sub_workflows()))

        i = 0
        for wf in wf_list:
            # Check if suitable for qha (no imaginary frequencies in DOS)
            try:
                freq = wf.get_result('dos').get_array('frequency')
                dos = wf.get_result('dos').get_array('total_dos')
            except:
                continue

            mask_neg = np.ma.masked_less(freq, 0.0).mask
            mask_pos = np.ma.masked_greater(freq, 0.0).mask
            int_neg = -np.trapz(np.multiply(dos[mask_neg], freq[mask_neg]),
                                x=freq[mask_neg])
            int_pos = np.trapz(np.multiply(dos[mask_pos], freq[mask_pos]),
                               x=freq[mask_pos])

            if int_neg / int_pos > 1e-6:
                volume = wf.get_result('final_structure').get_cell_volume()
                self.append_to_report(
                    'Volume {} not suitable for QHA (imaginary frequencies in DOS), skipping it'
                    .format(volume))
                continue
        #    print ('int_neg: {} int_pos: {}  rel: {}'.format(int_neg, int_pos, int_neg/int_pos))

        # Get necessary data
            thermal_list.append(wf.get_result('thermal_properties'))
            structures.append(wf.get_result('final_structure'))
            optimized_data.append(wf.get_result('optimized_structure_data'))

            electronic_energies.append(
                wf.get_result('optimized_structure_data').get_dict()['energy'])
            volumes.append(wf.get_result('final_structure').get_cell_volume())
            #           fe_phonon.append(wf.get_result('thermal_properties').get_array('free_energy'))
            #           entropy.append(wf.get_result('thermal_properties').get_array('entropy'))
            #           cv.append(wf.get_result('thermal_properties').get_array('cv'))
            temperatures = wf.get_result('thermal_properties').get_array(
                'temperature')

            temperature_fit = np.arange(
                0, 1001,
                10)  #[100, 200, 300, 400, 500, 600, 700, 800, 900, 1000]
            fe_phonon.append(
                np.interp(
                    temperature_fit, temperatures,
                    wf.get_result('thermal_properties').get_array(
                        'free_energy')))
            entropy.append(
                np.interp(
                    temperature_fit, temperatures,
                    wf.get_result('thermal_properties').get_array('entropy')))
            cv.append(
                np.interp(temperature_fit, temperatures,
                          wf.get_result('thermal_properties').get_array('cv')))
            temperatures = temperature_fit

            i += 1

#            inline_params['structure_{}'.format(i)] = wf.get_result('final_structure')
#            inline_params['optimized_data_{}'.format(i)] = wf.get_result('optimized_structure_data')
#            inline_params['thermal_properties_{}'.format(i)] = wf.get_result('thermal_properties')
#            self.append_to_report('accepted: {} {}'.format(i, wf.get_result('thermal_properties').pk))

#       entropy = []
#       cv = []
#       fe_phonon = []
#       temperatures = None

#       volumes = [value.get_cell_volume() for key, value in inline_params.items() if 'structure' in key.lower()]
#       electronic_energies = [value.get_dict()['energy'] for key, value in inline_params.items() if 'optimized_data' in key.lower()]
#
#        thermal_properties_list = [key for key, value in inline_params.items() if 'thermal_properties' in key.lower()]

#        for key in thermal_properties_list:
#            thermal_properties = inline_params[key]
#            fe_phonon.append(thermal_properties.get_array('free_energy'))
#            entropy.append(thermal_properties.get_array('entropy'))
#            cv.append(thermal_properties.get_array('cv'))
#            temperatures = thermal_properties.get_array('temperature')

        from phonopy import PhonopyQHA
        import numpy as np

        # Arrange data sorted by volume and transform them to numpy array
        sort_index = np.argsort(volumes)

        volumes = np.array(volumes)[sort_index]
        electronic_energies = np.array(electronic_energies)[sort_index]
        temperatures = np.array(temperatures)
        fe_phonon = np.array(fe_phonon).T[:, sort_index]
        entropy = np.array(entropy).T[:, sort_index]
        cv = np.array(cv).T[:, sort_index]

        opt = np.argmin(electronic_energies)

        # Check minimum energy volume is within the data
        if np.ma.masked_less_equal(volumes, volumes[opt]).mask.all():
            self.append_to_report(
                'higher volume structures are necessary to compute')

        if np.ma.masked_greater_equal(volumes, volumes[opt]).mask.all():
            self.append_to_report(
                'Lower volume structures are necessary to compute')

        self.append_to_report('Dimensions T{} : FE{}'.format(
            len(temperatures), len(fe_phonon)))

        # Calculate QHA
        phonopy_qha = PhonopyQHA(
            np.array(volumes),
            np.array(electronic_energies),
            eos="vinet",
            temperatures=np.array(temperatures),
            free_energy=np.array(fe_phonon),
            cv=np.array(cv),
            entropy=np.array(entropy),
            #                         t_max=options.t_max,
            verbose=False)

        #Get data
        qha_temperatures = phonopy_qha._qha._temperatures[:phonopy_qha._qha.
                                                          _max_t_index]
        helmholtz_volume = phonopy_qha.get_helmholtz_volume()
        thermal_expansion = phonopy_qha.get_thermal_expansion()
        volume_temperature = phonopy_qha.get_volume_temperature()
        heat_capacity_P_numerical = phonopy_qha.get_heat_capacity_P_numerical()
        volume_expansion = phonopy_qha.get_volume_expansion()
        gibbs_temperature = phonopy_qha.get_gibbs_temperature()

        qha_output = ArrayData()
        qha_output.set_array('temperature', np.array(qha_temperatures))
        qha_output.set_array('helmholtz_volume', np.array(helmholtz_volume))
        qha_output.set_array('thermal_expansion', np.array(thermal_expansion))
        qha_output.set_array('volume_temperature',
                             np.array(volume_temperature))
        qha_output.set_array('heat_capacity_P_numerical',
                             np.array(heat_capacity_P_numerical))
        qha_output.set_array('volume_expansion', np.array(volume_expansion))
        qha_output.set_array('gibbs_temperature', np.array(gibbs_temperature))
        qha_output.store()

        # Test to leave something on folder
        #        phonopy_qha.plot_pdf_bulk_modulus_temperature()
        #        import matplotlib
        #       matplotlib.use('Agg')
        repo_path = self._repo_folder.abspath
        data_folder = self.current_folder.get_subfolder('DATA_FILES')
        data_folder.create()

        #   phonopy_qha.plot_pdf_bulk_modulus_temperature(filename=repo_path + '/bulk_modulus-temperature.pdf')
        phonopy_qha.write_bulk_modulus_temperature(filename='bm')
        file = open('bm')
        data_folder.create_file_from_filelike(file, 'bulk_modulus-temperature')

        #        qha_results = calculate_qha_inline(**inline_params)[1]

        self.append_to_report('QHA properties calculated and retrieved')
        self.add_result('qha', qha_output)

        data = ArrayData()
        data.set_array('energy', np.array(electronic_energies))
        data.set_array('volume', np.array(volumes))
        data.store()
        self.add_result('data', data)

        self.append_to_report('Finishing workflow_workflow')
        self.next(self.exit)
Esempio n. 4
0
def calculate_qha_inline(**kwargs):

    from phonopy import PhonopyQHA
    from phonopy.structure.atoms import Atoms as PhonopyAtoms
    import numpy as np

    #   structures = kwargs.pop('structures')
    #   optimized_data = kwargs.pop('optimized_data')
    #   thermodyamic_properties = kwargs.pop('thermodyamic_properties')

    entropy = []
    cv = []
    #  volumes = []
    fe_phonon = []
    temperatures = None

    #   structures = [key for key, value in kwargs.items() if 'structure' in key.lower()]
    #   for key in structures:
    #       volumes.append(kwargs.pop(key).get_cell_volume())

    volumes = [
        value.get_cell_volume() for key, value in kwargs.items()
        if 'structure' in key.lower()
    ]
    electronic_energies = [
        value.get_dict()['energy'] for key, value in kwargs.items()
        if 'optimized_data' in key.lower()
    ]

    thermal_properties_list = [
        key for key, value in kwargs.items()
        if 'thermal_properties' in key.lower()
    ]

    for key in thermal_properties_list:
        thermal_properties = kwargs[key]
        fe_phonon.append(thermal_properties.get_array('free_energy'))
        entropy.append(thermal_properties.get_array('entropy'))
        cv.append(thermal_properties.get_array('cv'))
        temperatures = thermal_properties.get_array('temperature')

    # Arrange data sorted by volume and transform them to numpy array
    sort_index = np.argsort(volumes)

    volumes = np.array(volumes)[sort_index]
    electronic_energies = np.array(electronic_energies)[sort_index]
    temperatures = np.array(temperatures)
    fe_phonon = np.array(fe_phonon).T[:, sort_index]
    entropy = np.array(entropy).T[:, sort_index]
    cv = np.array(cv).T[:, sort_index]

    opt = np.argmin(electronic_energies)

    # Check minimum energy volume is within the data
    if np.ma.masked_less_equal(volumes, volumes[opt]).mask.all():
        print('higher volume structures are necessary to compute')
        exit()
    if np.ma.masked_greater_equal(volumes, volumes[opt]).mask.all():
        print('Lower volume structures are necessary to compute')
        exit()

#   print volumes.shape
#   print electronic_energies.shape
#   print temperatures.shape
#   print fe_phonon.shape
#   print cv.shape
#   print entropy.shape

    qha_output = ArrayData()
    qha_output.set_array('volumes', volumes)
    qha_output.set_array('electronic_energies', electronic_energies)
    qha_output.set_array('temperatures', temperatures)
    qha_output.set_array('fe_phonon', fe_phonon)
    qha_output.set_array('cv', cv)
    qha_output.set_array('entropy', entropy)

    # Calculate QHA
    phonopy_qha = PhonopyQHA(
        np.array(volumes),
        np.array(electronic_energies),
        eos="vinet",
        temperatures=np.array(temperatures),
        free_energy=np.array(fe_phonon),
        cv=np.array(cv),
        entropy=np.array(entropy),
        #                         t_max=options.t_max,
        verbose=False)

    #   print phonopy_qha.get_gibbs_temperature()

    qha_output = ArrayData()
    qha_output.set_array('volumes', volumes)
    qha_output.set_array('electronic_energies', electronic_energies)
    qha_output.set_array('temperatures', temperatures)
    qha_output.set_array('fe_phonon', fe_phonon)
    qha_output.set_array('cv', cv)
    qha_output.set_array('entropy', entropy)

    return {'qha_output': qha_output}

    #Get data
    helmholtz_volume = phonopy_qha.get_helmholtz_volume()
    thermal_expansion = phonopy_qha.get_thermal_expansion()
    volume_temperature = phonopy_qha.get_volume_temperature()
    heat_capacity_P_numerical = phonopy_qha.get_heat_capacity_P_numerical()
    volume_expansion = phonopy_qha.get_volume_expansion()
    gibbs_temperature = phonopy_qha.get_gibbs_temperature()

    qha_output = ArrayData()
    #    qha_output.set_array('temperature', temperatures)
    #    qha_output.set_array('helmholtz_volume', np.array(helmholtz_volume))
    #    qha_output.set_array('thermal_expansion', np.array(thermal_expansion))
    #    qha_output.set_array('volume_temperature', np.array(volume_temperature))
    #    qha_output.set_array('heat_capacity_P_numerical', np.array(heat_capacity_P_numerical))
    #    qha_output.set_array('volume_expansion', np.array(volume_expansion))
    #    qha_output.set_array('gibbs_temperature', np.array(gibbs_temperature))
    #   qha_output.store()

    return {'qha_output': qha_output}
Esempio n. 5
0
def get_gibbs(structure,
              db_file,
              eos="vinet",
              t_step=10,
              t_min=0,
              t_max=1000,
              mesh=(20, 20, 20),
              plot=False):
    # other eos options: birch_murnaghan, murnaghan
    # The physical units of V and T are \AA^3 and K, respectively.
    # The unit of eV for Helmholtz and Gibbs energies,
    # J/K/mol for C_V and entropy, GPa for for bulk modulus and pressure are used.
    from phonopy import PhonopyQHA

    phonon = get_phonopy(structure)
    energies, volumes, force_constants = get_data(
        db_file,
        query={
            "task_label": {
                "$regex": "gibbs*"
            },
            "formula_pretty": structure.composition.reduced_formula
        })

    temperatures = []
    free_energy = []
    entropy = []
    cv = []

    for f in force_constants:
        phonon.set_force_constants(-np.array(f))
        phonon.set_mesh(list(mesh))
        phonon.set_thermal_properties(t_step=t_step, t_min=t_min, t_max=t_max)
        t, g, e, c = phonon.get_thermal_properties()
        temperatures.append(t)
        free_energy.append(g)
        entropy.append(e)
        cv.append(c)

    phonopy_qha = PhonopyQHA(volumes,
                             energies,
                             eos=eos,
                             temperatures=temperatures[0],
                             free_energy=np.array(free_energy).T,
                             cv=np.array(cv).T,
                             entropy=np.array(entropy).T,
                             t_max=np.max(temperatures[0]))

    # gibbs free energy
    max_t_index = phonopy_qha._qha._max_t_index
    G = phonopy_qha.get_gibbs_temperature()[:max_t_index]
    T = phonopy_qha._qha._temperatures[:max_t_index]
    if plot:
        import warnings
        with warnings.catch_warnings():
            warnings.simplefilter("ignore")
            import matplotlib.pyplot as plt
            plt.plot(T, G)
            plt.savefig("Gibbs.pdf")
            plt.show()
            #phonopy_qha.plot_qha(thin_number=10, volume_temp_exp=None).show()
    else:
        return T, G
def calculate_qha_inline(**kwargs):

    from phonopy import PhonopyQHA
    import numpy as np

    #    thermal_properties_list = [key for key, value in kwargs.items() if 'thermal_properties' in key.lower()]
    #    optimized_structure_data_list = [key for key, value in kwargs.items() if 'optimized_structure_data' in key.lower()]
    structure_list = [
        key for key, value in kwargs.items()
        if 'final_structure' in key.lower()
    ]

    volumes = []
    electronic_energies = []
    fe_phonon = []
    entropy = []
    cv = []

    for i in range(len(structure_list)):
        # volumes.append(kwargs.pop(key).get_cell_volume())
        volumes.append(
            kwargs.pop('final_structure_{}'.format(i)).get_cell_volume())
        electronic_energies.append(
            kwargs.pop('optimized_structure_data_{}'.format(i)).dict.energy)
        thermal_properties = kwargs.pop('thermal_properties_{}'.format(i))
        temperatures = thermal_properties.get_array('temperature')
        fe_phonon.append(thermal_properties.get_array('free_energy'))
        entropy.append(thermal_properties.get_array('entropy'))
        cv.append(thermal_properties.get_array('cv'))

    sort_index = np.argsort(volumes)

    temperatures = np.array(temperatures)
    volumes = np.array(volumes)[sort_index]
    electronic_energies = np.array(electronic_energies)[sort_index]
    fe_phonon = np.array(fe_phonon).T[:, sort_index]
    entropy = np.array(entropy).T[:, sort_index]
    cv = np.array(cv).T[:, sort_index]

    print volumes
    print electronic_energies
    print temperatures
    print fe_phonon
    print cv
    print entropy

    # Calculate QHA
    phonopy_qha = PhonopyQHA(
        volumes,
        electronic_energies,
        eos="vinet",
        temperatures=temperatures,
        free_energy=fe_phonon,
        cv=cv,
        entropy=entropy,
        #                         t_max=options.t_max,
        verbose=True)

    try:
        qha_output = ArrayData()
        qha_output.set_array('temperature', np.array([1, 2, 3, 4]))
        qha_output.store()
    except:
        print qha_output
        exit()

    # Get data
    qha_temperatures = phonopy_qha._qha._temperatures[:phonopy_qha._qha.
                                                      _max_t_index]
    helmholtz_volume = phonopy_qha.get_helmholtz_volume()
    thermal_expansion = phonopy_qha.get_thermal_expansion()
    volume_temperature = phonopy_qha.get_volume_temperature()
    heat_capacity_P_numerical = phonopy_qha.get_heat_capacity_P_numerical()
    volume_expansion = phonopy_qha.get_volume_expansion()
    gibbs_temperature = phonopy_qha.get_gibbs_temperature()

    qha_output = ArrayData()

    qha_output.set_array('temperature', np.array(qha_temperatures))
    qha_output.set_array('helmholtz_volume', np.array(helmholtz_volume))
    qha_output.set_array('thermal_expansion', np.array(thermal_expansion))
    qha_output.set_array('volume_temperature', np.array(volume_temperature))
    qha_output.set_array('heat_capacity_P_numerical',
                         np.array(heat_capacity_P_numerical))
    qha_output.set_array('volume_expansion', np.array(volume_expansion))
    qha_output.set_array('gibbs_temperature', np.array(gibbs_temperature))

    qha_output.store()

    return {'qha_data': qha_output}
Esempio n. 7
0
def calculate_qha_inline(**kwargs):

    from phonopy import PhonopyQHA
    from phonon_common import get_helmholtz_volume_from_phonopy_qha
    import numpy as np

    #    thermal_properties_list = [key for key, value in kwargs.items() if 'thermal_properties' in key.lower()]
    #    optimized_structure_data_list = [key for key, value in kwargs.items() if 'optimized_structure_data' in key.lower()]
    structure_list = [
        key for key, value in kwargs.items()
        if 'final_structure' in key.lower()
    ]

    volumes = []
    electronic_energies = []
    fe_phonon = []
    entropy = []
    cv = []

    for i in range(len(structure_list)):
        # volumes.append(kwargs.pop(key).get_cell_volume())
        volumes.append(
            kwargs.pop('final_structure_{}'.format(i)).get_cell_volume())
        electronic_energies.append(
            kwargs.pop('optimized_structure_data_{}'.format(i)).dict.energy)
        thermal_properties = kwargs.pop('thermal_properties_{}'.format(i))
        temperatures = thermal_properties.get_array('temperature')
        fe_phonon.append(thermal_properties.get_array('free_energy'))
        entropy.append(thermal_properties.get_array('entropy'))
        cv.append(thermal_properties.get_array('cv'))

    sort_index = np.argsort(volumes)

    temperatures = np.array(temperatures)
    volumes = np.array(volumes)[sort_index]
    electronic_energies = np.array(electronic_energies)[sort_index]
    fe_phonon = np.array(fe_phonon).T[:, sort_index]
    entropy = np.array(entropy).T[:, sort_index]
    cv = np.array(cv).T[:, sort_index]

    # Calculate QHA
    phonopy_qha = PhonopyQHA(
        np.array(volumes),
        np.array(electronic_energies),
        eos="vinet",
        temperatures=np.array(temperatures),
        free_energy=np.array(fe_phonon),
        cv=np.array(cv),
        entropy=np.array(entropy),
        #                         t_max=options.t_max,
        verbose=False)

    # Get data
    free_energy_volume_fitting = get_helmholtz_volume_from_phonopy_qha(
        phonopy_qha)

    qha_temperatures = phonopy_qha._qha._temperatures[:phonopy_qha._qha.
                                                      _max_t_index]
    helmholtz_volume = phonopy_qha.get_helmholtz_volume()
    thermal_expansion = phonopy_qha.get_thermal_expansion()
    volume_temperature = phonopy_qha.get_volume_temperature()
    heat_capacity_P_numerical = phonopy_qha.get_heat_capacity_P_numerical()
    volume_expansion = phonopy_qha.get_volume_expansion()
    gibbs_temperature = phonopy_qha.get_gibbs_temperature()

    qha_output = ArrayData()

    qha_output.set_array('temperatures', np.array(qha_temperatures))
    #qha_output.set_array('helmholtz_volume', np.array(helmholtz_volume))
    qha_output.set_array('thermal_expansion', np.array(thermal_expansion))
    qha_output.set_array('volume_temperature', np.array(volume_temperature))
    qha_output.set_array('heat_capacity_P_numerical',
                         np.array(heat_capacity_P_numerical))
    qha_output.set_array('volume_expansion', np.array(volume_expansion))
    qha_output.set_array('gibbs_temperature', np.array(gibbs_temperature))

    qha_output.set_array('helmholtz_volume_points',
                         np.array(free_energy_volume_fitting['points']))
    qha_output.set_array('helmholtz_volume_fit',
                         np.array(free_energy_volume_fitting['fit']))
    qha_output.set_array('helmholtz_volume_minimum',
                         np.array(free_energy_volume_fitting['minimum']))

    return {'qha_output': qha_output}
Esempio n. 8
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    temperatures=np.array(temperatures),
    free_energy=np.array(fe_phonon),
    cv=np.array(cv),
    entropy=np.array(entropy),
    #                         t_max=options.t_max,
    verbose=False)

# Get data
qha_temperatures = phonopy_qha._qha._temperatures[:phonopy_qha._qha.
                                                  _max_t_index]
helmholtz_volume = phonopy_qha.get_helmholtz_volume()
thermal_expansion = phonopy_qha.get_thermal_expansion()
volume_temperature = phonopy_qha.get_volume_temperature()
heat_capacity_P_numerical = phonopy_qha.get_heat_capacity_P_numerical()
volume_expansion = phonopy_qha.get_volume_expansion()
gibbs_temperature = phonopy_qha.get_gibbs_temperature()

#phonopy_qha.plot_bulk_modulus()
#plt.show()

phonopy_qha.plot_qha()
plt.show()
phonopy_qha.plot_gruneisen_temperature()
plt.show()
phonopy_qha.plot_gibbs_temperature()
plt.show()
phonopy_qha.plot_heat_capacity_P_numerical()
plt.show()

phonopy_qha.write_gibbs_temperature()
phonopy_qha.write_heat_capacity_P_numerical()