Source code for pycalphad.plot.binary.plot

The plot module handles plotting ZPF boundaries and provides a user-facing
function `binplot` for users to plot binary phase diagrams with a similar API
as `equilibrium`.

import pycalphad.variables as v
import matplotlib.pyplot as plt
from pycalphad.plot.eqplot import _axis_label
from pycalphad.plot.utils import phase_legend
from .map import map_binary

[docs]def plot_boundaries(zpf_boundary_sets, tielines=True, tieline_color=(0, 1, 0, 1), scatter=True, legend_generator=phase_legend, ax=None, gridlines=False): """ Plot a set of ZPFBoundarySets Parameters ---------- zpf_boundary_sets : pycalphad.mapping.zpf_boundary_sets.ZPFBoundarySets tielines : optional, bool Whether the plot the tielines (defaults to True) tieline_color: color A valid matplotlib color, such as a named color string, hex RGB string, or a tuple of RGBA components to set the color of the two phase region tielines. The default is an RGBA tuple for green: (0, 1, 0, 1). scatter : optional, bool Whether to use scatter plot the phase boundaries (True, the default) or to connect lines in the same two phase region by lines. Note that lines may appear broken when the set of phases change, even if the boundary does not change. legend_generator : Callable A function that will be called with the list of phases and will return legend labels and colors for each phase. By default pycalphad.plot.utils.phase_legend is used ax : plt.Axes Matplotlib axes to plot to. If none are pasesed, a new figure will be created. gridlines : False Whether to plot the grid lines in the plot. Defaults to False. Returns ------- plt.Axes """ if ax is None: ax = plt.figure().gca() if scatter: scatter_dict, tieline_coll, legend_handles = zpf_boundary_sets.get_scatter_plot_boundaries(tieline_color=tieline_color, legend_generator=legend_generator) ax.scatter(scatter_dict['x'], scatter_dict['y'], c=scatter_dict['c'], edgecolor='None', s=3, zorder=2) else: boundary_collection, tieline_coll, legend_handles = zpf_boundary_sets.get_line_plot_boundaries(tieline_color=tieline_color, legend_generator=legend_generator) ax.add_collection(boundary_collection) if tielines: ax.add_collection(tieline_coll) box = ax.get_position() ax.set_position([box.x0, box.y0, box.width * 0.8, box.height]) ax.legend(handles=legend_handles, loc='center left', bbox_to_anchor=(1, 0.5)) ax.tick_params(axis='both', which='major', labelsize=14) ax.grid(True) plot_title = '-'.join([component for component in sorted(zpf_boundary_sets.components) if component != 'VA']) ax.set_title(plot_title, fontsize=20) ax.set_xlabel(_axis_label(zpf_boundary_sets.indep_comp_cond), labelpad=15, fontsize=20) ax.set_ylabel(_axis_label(v.T), fontsize=20) ax.set_xlim(0, 1) # autoscale needs to be used in case boundaries are plotted as lines because # only plotting line collections will not rescale the axes ax.autoscale(axis='y') ax.grid(gridlines) return ax
[docs]def binplot(database, components, phases, conditions, plot_kwargs=None, **map_kwargs): """ Calculate the binary isobaric phase diagram. This function is a convenience wrapper around map_binary() and plot_boundaries() Parameters ---------- database : Database Thermodynamic database containing the relevant parameters. components : list Names of components to consider in the calculation. phases : list Names of phases to consider in the calculation. conditions : 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 : dict, optional Keyword arguments to use in equilibrium() within map_binary(). If eq_kwargs is defined in map_kwargs, this argument takes precedence. map_kwargs : dict, optional Additional keyword arguments to map_binary(). plot_kwargs : dict, optional Keyword arguments to plot_boundaries(). Returns ------- Axes Matplotlib Axes of the phase diagram Examples -------- None yet. """ plot_kwargs = plot_kwargs if plot_kwargs is not None else dict() zpf_boundaries = map_binary(database, components, phases, conditions, **map_kwargs) ax = plot_boundaries(zpf_boundaries, **plot_kwargs) return ax