self.models = OrderedDict()
self.build_phase(dbe)

for name, value in self.models.items():
    # XXX: xreplace hack because SymEngine seems to let Symbols slip in somehow
    self.models[name] = self.symbol_replace(value, symbols).xreplace(v.supported_variables_in_databases)

from symengine import Symbol

class MyModel(Model):
    def build_phase(self, dbe):
        super(MyModel, self).build_phase(dbe)
        symbols = {Symbol(s): val for s, val in dbf.symbols.items()}
        for name, value in self.models.items():
            # XXX: xreplace hack because SymEngine seems to let Symbols slip in somehow
            self.models[name] = self.symbol_replace(value, symbols).xreplace(v.supported_variables_in_databases)
        self.entropyval = self.build_entropy(dbe)

    def build_entropy(self, _):
        Gibbs_energy = self.GM
        entropy = -Gibbs_energy.diff(v.T)
        return entropy

from tinydb import where
import pycalphad
from pycalphad import Model, variables as v
from pycalphad import Database
from pycalphad import calculate
from symengine import Symbol

import pandas
import numpy as np
print('Version:', pycalphad.__version__)

with open('unary50edt.tdb') as fp:
    dbf = Database(fp.read().upper())

class MyModel(Model):
    def build_phase(self, dbe):
        super(MyModel, self).build_phase(dbe)
        symbols = {Symbol(s): val for s, val in dbf.symbols.items()}
        for name, value in self.models.items():
            # XXX: xreplace hack because SymEngine seems to let Symbols slip in somehow
            self.models[name] = self.symbol_replace(value, symbols).xreplace(v.supported_variables_in_databases)
        
        self.entropyval = self.build_entropy(dbe)

    def build_entropy(self, _):
        Gibbs_energy = self.GM
        entropy = -Gibbs_energy.diff(v.T)
        return entropy

for atom in ['Ni']:
    mod = MyModel(dbf, [atom], 'LIQUID')

    # NOTICE: we need to tell pycalphad about our model for this phase
    models = {'LIQUID': mod}

    o = []
    for temp in np.arange(950, 2000, 200):
        res = calculate(dbf, [atom], 'LIQUID', P=101325, T=temp, model=models, output='SM')
        sA = res.SM.values.squeeze()
        res = calculate(dbf, [atom], 'LIQUID', P=101325, T=temp, model=models, output='entropyval')
        sB = res.entropyval.values.squeeze()
        print(temp, sA, sB)
        
    pandas.DataFrame(o).to_csv(f'{atom}_CALPHAD_test.csv', index=False)

    def build_phase(self, dbe):
        """
        Generate the symbolic form of all the contributions to this phase.
        Parameters
        ----------
        dbe : Database
        """
        contrib_vals = list(OrderedDict(self.__class__.contributions).values())
        if 'atomic_ordering_energy' in contrib_vals:
            if contrib_vals.index('atomic_ordering_energy') != (len(contrib_vals) - 1):
                # Check for a common mistake in custom models
                # Users that need to override this behavior should override build_phase
                raise ValueError('\'atomic_ordering_energy\' must be the final contribution')
        self.models.clear()
        for key, value in self.__class__.contributions:
            self.models[key] = S(getattr(self, value)(dbe))

        symbols = {Symbol(s): val for s, val in dbe.symbols.items()}

        for name, value in self.models.items():
            # XXX: xreplace hack because SymEngine seems to let Symbols slip in somehow
            self.models[name] = self.symbol_replace(value, symbols).xreplace(v.supported_variables_in_databases)