def eqdataplot(eq, datasets, ax=None, plot_kwargs=None):
"""
Plot datapoints corresponding to the components and phases in the eq Dataset.
A convenience function for dataplot.
Parameters
----------
eq : xarray.Dataset
Result of equilibrium calculation.
datasets : PickleableTinyDB
Database of phase equilibria datasets
ax : matplotlib.Axes
Default axes used if not specified.
plot_kwargs : dict
Keyword arguments to pass to dataplot
Returns
-------
A plot of phase equilibria points as a figure
Examples
--------
>>> from pycalphad import equilibrium, 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())
>>> eq = equilibrium(dbf, ['CU', 'MG', 'VA'], my_phases, {v.P: 101325, v.T: (500, 1000, 10), v.X('MG'): (0, 1, 0.01)})
>>> ax = eqplot(eq)
>>> ax = eqdataplot(eq, datasets, ax=ax)
"""
# TODO: support reference legend
conds = OrderedDict([
(_map_coord_to_variable(key), unpack_condition(np.asarray(value)))
for key, value in sorted(eq.coords.items(), key=str)
if (key == 'T') or (key == 'P') or (key.startswith('X_'))
])
phases = list(
map(
str,
sorted(set(np.array(eq.Phase.values.ravel(), dtype='U')) - {''},
key=str)))
comps = list(
map(
str,
sorted(np.array(eq.coords['component'].values, dtype='U'),
key=str)))
ax = dataplot(comps,
phases,
conds,
datasets,
ax=ax,
plot_kwargs=plot_kwargs)
return ax
def eqdataplot(eq, datasets, ax=None, plot_kwargs=None):
"""
Plot datapoints corresponding to the components and phases in the eq Dataset.
A convenience function for dataplot.
Parameters
----------
eq : xarray.Dataset
Result of equilibrium calculation.
datasets : PickleableTinyDB
Database of phase equilibria datasets
ax : matplotlib.Axes
Default axes used if not specified.
plot_kwargs : dict
Keyword arguments to pass to dataplot
Returns
-------
A plot of phase equilibria points as a figure
Examples
--------
>>> from pycalphad import equilibrium, 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
>>> eq = equilibrium(dbf, ['CU', 'MG', 'VA'], my_phases, {v.P: 101325, v.T: (500, 1000, 10), v.X('MG'): (0, 1, 0.01)}) # doctest: +SKIP
>>> ax = eqplot(eq) # doctest: +SKIP
>>> ax = eqdataplot(eq, datasets, ax=ax) # doctest: +SKIP
"""
deprecation_msg = (
"`espei.plot.eqdataplot` is deprecated and will be removed in ESPEI 0.9. "
"Users depending on plotting from an `pycalphad.equilibrium` result should use "
"`pycalphad.plot.eqplot.eqplot` along with `espei.plot.dataplot` directly. "
"Note that pycalphad's mapping can offer signficant reductions in calculation "
"time compared to using `equilibrium` followed by `eqplot`."
)
warnings.warn(deprecation_msg, category=FutureWarning)
# TODO: support reference legend
conds = OrderedDict([(_map_coord_to_variable(key), unpack_condition(np.asarray(value)))
for key, value in sorted(eq.coords.items(), key=str)
if (key == 'T') or (key == 'P') or (key.startswith('X_'))])
phases = list(map(str, sorted(set(np.array(eq.Phase.values.ravel(), dtype='U')) - {''}, key=str)))
comps = list(map(str, sorted(np.array(eq.coords['component'].values, dtype='U'), key=str)))
ax = dataplot(comps, phases, conds, datasets, ax=ax, plot_kwargs=plot_kwargs)
return ax
