def ternplot(dbf,
comps,
phases,
conds,
x=None,
y=None,
eq_kwargs=None,
**plot_kwargs):
"""
Calculate the ternary isothermal, isobaric phase diagram.
This function is a convenience wrapper around equilibrium() and eqplot().
Parameters
----------
dbf : Database
Thermodynamic database containing the relevant parameters.
comps : list
Names of components to consider in the calculation.
phases : list
Names of phases to consider in the calculation.
conds : dict
Maps StateVariables to values and/or iterables of values.
For ternplot only one changing composition and one potential coordinate each is supported.
x : Composition
instance of a pycalphad.variables.composition to plot on the x-axis.
Must correspond to an independent condition.
y : Composition
instance of a pycalphad.variables.composition to plot on the y-axis.
Must correspond to an independent condition.
eq_kwargs : optional
Keyword arguments to equilibrium().
plot_kwargs : optional
Keyword arguments to eqplot().
Returns
-------
A phase diagram as a figure.
Examples
--------
None yet.
"""
eq_kwargs = eq_kwargs if eq_kwargs is not None else dict()
indep_comps = [
key for key, value in conds.items()
if isinstance(key, v.Composition) and len(np.atleast_1d(value)) > 1
]
indep_pots = [
key for key, value in conds.items()
if ((key == v.T) or (key == v.P)) and len(np.atleast_1d(value)) > 1
]
if (len(indep_comps) != 2) or (len(indep_pots) != 0):
raise ValueError(
'ternplot() requires exactly two composition coordinates')
full_eq = equilibrium(dbf, comps, phases, conds, **eq_kwargs)
# TODO: handle x and y as strings with #87
x = x if x in indep_comps else indep_comps[0]
y = y if y in indep_comps else indep_comps[1]
return eqplot(full_eq, x=x, y=y, **plot_kwargs)
def multiplot(dbf, comps, phases, conds, datasets, eq_kwargs=None, plot_kwargs=None, data_kwargs=None):
"""
Plot a phase diagram with datapoints described by datasets.
This is a wrapper around pycalphad.equilibrium, pycalphad's eqplot, and dataplot.
Parameters
----------
dbf : Database
pycalphad thermodynamic database containing the relevant parameters.
comps : list
Names of components to consider in the calculation.
phases : list
Names of phases to consider in the calculation.
conds : dict
Maps StateVariables to values and/or iterables of values.
datasets : PickleableTinyDB
Database of phase equilibria datasets
eq_kwargs : dict
Keyword arguments passed to pycalphad equilibrium()
plot_kwargs : dict
Keyword arguments passed to pycalphad eqplot()
data_kwargs : dict
Keyword arguments passed to dataplot()
Returns
-------
A phase diagram with phase equilibria data as a figure
Examples
--------
>>> from pycalphad import Database, variables as v # doctest: +SKIP
>>> from pycalphad.plot.eqplot import eqplot # doctest: +SKIP
>>> from espei.datasets import load_datasets, recursive_glob # doctest: +SKIP
>>> datasets = load_datasets(recursive_glob('.', '*.json')) # doctest: +SKIP
>>> dbf = Database('my_databases.tdb') # doctest: +SKIP
>>> my_phases = list(dbf.phases.keys()) # doctest: +SKIP
>>> multiplot(dbf, ['CU', 'MG', 'VA'], my_phases, {v.P: 101325, v.T: 1000, v.X('MG'): (0, 1, 0.01)}, datasets) # doctest: +SKIP
"""
deprecation_msg = (
"`espei.plot.multiplot` is deprecated and will be removed in ESPEI 0.9. "
"Users depending on `multiplot` should use pycalphad's `binplot` or `ternplot` "
"followed by `espei.plot.dataplot`. Note that pycalphad's mapping can offer "
"signficant reductions in calculation time compared to using `multiplot`. See "
"ESPEI's recipes for an example: "
"https://espei.org/en/latest/recipes.html#plot-phase-diagram-with-data"
)
warnings.warn(deprecation_msg, category=FutureWarning)
eq_kwargs = eq_kwargs or dict()
plot_kwargs = plot_kwargs or dict()
data_kwargs = data_kwargs or dict()
eq_result = equilibrium(dbf, comps, phases, conds, **eq_kwargs)
ax = eqplot(eq_result, **plot_kwargs)
ax = eqdataplot(eq_result, datasets, ax=ax, plot_kwargs=data_kwargs)
return ax
def multiplot(dbf,
comps,
phases,
conds,
datasets,
eq_kwargs=None,
plot_kwargs=None,
data_kwargs=None):
"""
Plot a phase diagram with datapoints described by datasets.
This is a wrapper around pycalphad.equilibrium, pycalphad's eqplot, and dataplot.
Parameters
----------
dbf : Database
pycalphad thermodynamic database containing the relevant parameters.
comps : list
Names of components to consider in the calculation.
phases : list
Names of phases to consider in the calculation.
conds : dict
Maps StateVariables to values and/or iterables of values.
datasets : PickleableTinyDB
Database of phase equilibria datasets
eq_kwargs : dict
Keyword arguments passed to pycalphad equilibrium()
plot_kwargs : dict
Keyword arguments passed to pycalphad eqplot()
data_kwargs : dict
Keyword arguments passed to dataplot()
Returns
-------
A phase diagram with phase equilibria data as a figure
Examples
--------
>>> from pycalphad import Database, variables as v
>>> from pycalphad.plot.eqplot import eqplot
>>> from espei.datasets import load_datasets, recursive_glob
>>> datasets = load_datasets(recursive_glob('.', '*.json'))
>>> dbf = Database('my_databases.tdb')
>>> my_phases = list(dbf.phases.keys())
>>> multiplot(dbf, ['CU', 'MG', 'VA'], my_phases, {v.P: 101325, v.T: 1000, v.X('MG'): (0, 1, 0.01)}, datasets)
"""
eq_kwargs = eq_kwargs or dict()
plot_kwargs = plot_kwargs or dict()
data_kwargs = data_kwargs or dict()
eq_result = equilibrium(dbf, comps, phases, conds, **eq_kwargs)
ax = eqplot(eq_result, **plot_kwargs)
ax = eqdataplot(eq_result, datasets, ax=ax, plot_kwargs=data_kwargs)
return ax
def binplot(dbf, comps, phases, conds, eq_kwargs=None, **plot_kwargs):
"""
Calculate the binary isobaric phase diagram.
This function is a convenience wrapper around equilibrium() and eqplot().
Parameters
----------
dbf : Database
Thermodynamic database containing the relevant parameters.
comps : list
Names of components to consider in the calculation.
phases : list
Names of phases to consider in the calculation.
conds : dict
Maps StateVariables to values and/or iterables of values.
For binplot only one changing composition and one potential coordinate each is supported.
eq_kwargs : optional
Keyword arguments to equilibrium().
plot_kwargs : optional
Keyword arguments to eqplot().
Returns
-------
A phase diagram as a figure.
Examples
--------
None yet.
"""
eq_kwargs = eq_kwargs if eq_kwargs is not None else dict()
indep_comp = [
key for key, value in conds.items()
if isinstance(key, v.Composition) and len(np.atleast_1d(value)) > 1
]
indep_pot = [
key for key, value in conds.items()
if ((key == v.T) or (key == v.P)) and len(np.atleast_1d(value)) > 1
]
if (len(indep_comp) != 1) or (len(indep_pot) != 1):
raise ValueError(
'binplot() requires exactly one composition and one potential coordinate'
)
indep_comp = indep_comp[0]
indep_pot = indep_pot[0]
full_eq = equilibrium(dbf, comps, phases, conds, **eq_kwargs)
return eqplot(full_eq, x=indep_comp, y=indep_pot, **plot_kwargs)
def ternplot(dbf, comps, phases, conds, x=None, y=None, eq_kwargs=None, **plot_kwargs):
"""
Calculate the ternary isothermal, isobaric phase diagram.
This function is a convenience wrapper around equilibrium() and eqplot().
Parameters
----------
dbf : Database
Thermodynamic database containing the relevant parameters.
comps : list
Names of components to consider in the calculation.
phases : list
Names of phases to consider in the calculation.
conds : dict
Maps StateVariables to values and/or iterables of values.
For ternplot only one changing composition and one potential coordinate each is supported.
x : Composition
instance of a pycalphad.variables.composition to plot on the x-axis.
Must correspond to an independent condition.
y : Composition
instance of a pycalphad.variables.composition to plot on the y-axis.
Must correspond to an independent condition.
eq_kwargs : optional
Keyword arguments to equilibrium().
plot_kwargs : optional
Keyword arguments to eqplot().
Returns
-------
A phase diagram as a figure.
Examples
--------
None yet.
"""
eq_kwargs = eq_kwargs if eq_kwargs is not None else dict()
indep_comps = [key for key, value in conds.items() if isinstance(key, v.Composition) and len(np.atleast_1d(value)) > 1]
indep_pots = [key for key, value in conds.items() if ((key == v.T) or (key == v.P)) and len(np.atleast_1d(value)) > 1]
if (len(indep_comps) != 2) or (len(indep_pots) != 0):
raise ValueError('ternplot() requires exactly two composition coordinates')
full_eq = equilibrium(dbf, comps, phases, conds, **eq_kwargs)
# TODO: handle x and y as strings with #87
x = x if x in indep_comps else indep_comps[0]
y = y if y in indep_comps else indep_comps[1]
return eqplot(full_eq, x=x, y=y, **plot_kwargs)
def binplot(dbf, comps, phases, conds, eq_kwargs=None, **plot_kwargs):
"""
Calculate the binary isobaric phase diagram.
This function is a convenience wrapper around equilibrium() and eqplot().
Parameters
----------
dbf : Database
Thermodynamic database containing the relevant parameters.
comps : list
Names of components to consider in the calculation.
phases : list
Names of phases to consider in the calculation.
conds : dict
Maps StateVariables to values and/or iterables of values.
For binplot only one changing composition and one potential coordinate each is supported.
eq_kwargs : optional
Keyword arguments to equilibrium().
plot_kwargs : optional
Keyword arguments to eqplot().
Returns
-------
A phase diagram as a figure.
Examples
--------
None yet.
"""
eq_kwargs = eq_kwargs if eq_kwargs is not None else dict()
# TODO: Temporarily disable refinement until we improve the algorithm
eq_kwargs['_approx'] = True
indep_comp = [key for key, value in conds.items() if isinstance(key, v.Composition) and len(np.atleast_1d(value)) > 1]
indep_pot = [key for key, value in conds.items() if ((key == v.T) or (key == v.P)) and len(np.atleast_1d(value)) > 1]
if (len(indep_comp) != 1) or (len(indep_pot) != 1):
raise ValueError('binplot() requires exactly one composition and one potential coordinate')
indep_comp = indep_comp[0]
indep_pot = indep_pot[0]
full_eq = equilibrium(dbf, comps, phases, conds, **eq_kwargs)
return eqplot(full_eq, x=indep_comp, y=indep_pot, **plot_kwargs)