import numpy as np
from pycalphad.mapping import BinaryStrategy, TernaryStrategy, plot_binary, plot_ternary
import pycalphad.mapping.utils as map_utils
[docs]
def binplot(database, components, phases, conditions, return_strategy=False, plot_kwargs=None, **map_kwargs):
"""
Calculate the binary isobaric phase diagram.
Parameters
----------
database : Database
Thermodynamic database containing the relevant parameters.
components : Sequence[str]
Names of components to consider in the calculation.
phases : Sequence[str]
Names of phases to consider in the calculation.
conditions : Mapping[v.StateVariable, Union[float, Tuple[float, float, float]]]
Maps StateVariables to values and/or iterables of values.
For binplot only one changing composition and one potential coordinate each is supported.
return_strategy : bool, optional
Return the BinaryStrategy object in addition to the Axes. Defaults to False.
map_kwargs : dict, optional
Additional keyword arguments to BinaryStrategy().
plot_kwargs : dict, optional
Keyword arguments to plot_binary()
Possible key,val pairs in plot_kwargs
label_nodes : bool
Whether to plot points for phases on three-phase regions
Default = False
tieline_color : tuple
Color for tielines
Default = (0,1,0,1)
tie_triangle_color : tuple
Color for tie triangles
Default = (1,0,0,1)
Returns
-------
Axes
Matplotlib Axes of the phase diagram
(Axes, BinaryStrategy)
If return_strategy is True.
"""
indep_comps = [key for key, value in conditions.items() if not map_utils.is_state_variable(key) and len(np.atleast_1d(value)) > 1]
indep_pots = [key for key, value in conditions.items() if map_utils.is_state_variable(key) and len(np.atleast_1d(value)) > 1]
if (len(indep_comps) != 1) or (len(indep_pots) != 1):
raise ValueError('binplot() requires exactly one composition coordinate and one potential coordinate')
strategy = BinaryStrategy(database, components, phases, conditions, **map_kwargs)
strategy.do_map()
plot_kwargs = plot_kwargs if plot_kwargs is not None else dict()
ax = plot_binary(strategy, **plot_kwargs)
ax.grid(plot_kwargs.get("gridlines", False))
if return_strategy:
return ax, strategy
else:
return ax
[docs]
def ternplot(dbf, comps, phases, conds, x=None, y=None, return_strategy=False, map_kwargs=None, **plot_kwargs):
"""
Calculate the ternary isothermal, isobaric phase diagram.
Parameters
----------
dbf : Database
Thermodynamic database containing the relevant parameters.
comps : Sequence[str]
Names of components to consider in the calculation.
phases : Sequence[str]
Names of phases to consider in the calculation.
conds : Mapping[v.StateVariable, Union[float, Tuple[float, float, float]]]
Maps StateVariables to values and/or iterables of values.
For ternplot only two changing composition coordinates is supported.
x : v.MoleFraction
instance of a pycalphad.variables.composition to plot on the x-axis.
Must correspond to an independent condition.
y : v.MoleFraction
instance of a pycalphad.variables.composition to plot on the y-axis.
Must correspond to an independent condition.
return_strategy : bool, optional
Return the TernaryStrategy object in addition to the Axes. Defaults to False.
label_nodes : bool (optional)
Whether to plot points for phases on three-phase regions
Default = False
tieline_color : tuple (optional)
Color for tielines
Default = (0,1,0,1)
tie_triangle_color : tuple (optional)
Color for tie triangles
Default = (1,0,0,1)
map_kwargs : dict, optional
Additional keyword arguments to TernaryStrategy().
plot_kwargs : dict, optional
Keyword arguments to plot_ternary().
Returns
-------
Axes
Matplotlib Axes of the phase diagram
(Axes, TernaryStrategy)
If return_strategy is True.
"""
indep_comps = [key for key, value in conds.items() if not map_utils.is_state_variable(key) and len(np.atleast_1d(value)) > 1]
indep_pots = [key for key, value in conds.items() if map_utils.is_state_variable(key) 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')
map_kwargs = map_kwargs if map_kwargs is not None else dict()
strategy = TernaryStrategy(dbf, comps, phases, conds, **map_kwargs)
strategy.do_map()
ax = plot_ternary(strategy, x, y, **plot_kwargs)
ax.set_xlim(0, 1)
ax.set_ylim(0, 1)
if return_strategy:
return ax, strategy
else:
return ax