#!/usr/bin/env python
# coding: utf-8

# # Plotting Ternary Phase Diagrams and Using Triangular Axes
# 
# Often in thermodynamics, it is useful to use a two dimensional plot to express equilibria in a three component system with fixed potentials. The `ternplot` API provides a straightforward way to calculate equilibria and generate ternary phase diagrams. Alternatively, if you already have an equilibrium calculation, you can directly import and use `eqplot`.

# ## ternplot
# 
# Here we well use the ternplot API to plot an isothermal section of the Al-Cu-Y system from the thermodynamic database found at the [NIST CALPHAD assessments](http://hdl.handle.net/11115/101) assessed by Zhang et al. [Calphad 35 (2011)](https://doi.org/10.1016/j.calphad.2011.09.008). Note that we have commented out the Cu6Y phase in the TDB because it utilized the Cu2 species. Species are not currently supported in pycalphad.

# In[1]:


get_ipython().run_line_magic('matplotlib', 'inline')
from pycalphad import Database, ternplot
from pycalphad import variables as v

db_al_cu_y = Database('Al-Cu-Y.tdb')
comps = ['AL', 'CU', 'Y', 'VA']
phases = list(db_al_cu_y.phases.keys())
conds = {v.T: 830, v.P:101325, v.X('AL'): (0,1,0.015), v.X('Y'): (0,1,0.015)}

ternplot(db_al_cu_y, comps, phases, conds, x=v.X('AL'), y=v.X('Y'))


# ## triangular projection
# 
# Importing the `pycalphad.plot.triangular` module automatically registers a `'triangular'` projection in matplotlib for you to use in custom plots, such as liquidus projections or contour plots of custom property models.
# 
# Here we will use pycalphad to calculate the mixing enthalpy of the FCC phase in our Al-Cu-Y system. Then we will the triangular projection to plot the calculated points as a colored scatterplot on the triangular axes.

# In[2]:


import matplotlib.pyplot as plt
from pycalphad.plot import triangular
from pycalphad import calculate

# some sample data, these could be from an equilibrium calculation or a property model.
# here we are calculating the mixing enthlapy of the FCC_A1 phase at 830K. 
c = calculate(db_al_cu_y, comps, 'FCC_A1', output='HM_MIX', T=830, P=101325, pdens=5000)

# Here we are getting the values from our plot. 
xs = c.X.values[0, 0, :, 0]  # 1D array of Al compositions
ys = c.X.values[0, 0, :, 1]  # 1D array of Cu compositions
zs = c.HM_MIX.values[0,0, :]  # 1D array of mixing enthalpies at these compositions

# when we imported the pycalphad.plot.triangular module, it made the 'triangular' projection available for us to use.
fig = plt.figure()
ax = fig.gca(projection='triangular')
ax.scatter(xs, ys, c=c.HM_MIX.values[0,0, :], 
           cmap='coolwarm', 
           linewidth=0.0)

# label the figure
ax.set_xlabel('X (AL)')
ax.set_ylabel('X (CU)')
ax.yaxis.label.set_rotation(60)  # rotate ylabel
ax.yaxis.set_label_coords(x=0.12, y=0.5)  # move the label to a pleasing position
ax.set_title('AL-CU-Y HM_MIX at 830K')

# set up the colorbar
cm = plt.cm.ScalarMappable(cmap='coolwarm')
cm.set_array(zs)
fig.colorbar(cm)


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