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

# # Introduction
# 
# This notebook shows how to plot and analyze a phase diagram.

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# Uncomment the subsequent lines in this cell to install dependencies for Google Colab.
# !pip install pymatgen==2022.7.19


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from pymatgen.analysis.phase_diagram import PDPlotter, PhaseDiagram
from pymatgen.ext.matproj import MPRester

get_ipython().run_line_magic('matplotlib', 'inline')


# ## Generating the phase diagram
# 
# To generate a phase diagram, we obtain entries from the Materials Project and call the PhaseDiagram class in pymatgen.

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# This initializes the REST adaptor. You may need to put your own API key in as an arg.
mpr = MPRester()

# Entries are the basic unit for thermodynamic and other analyses in pymatgen.
# This gets all entries belonging to the Ca-C-O system.
entries = mpr.get_entries_in_chemsys(["Ca", "C", "O"])

# With entries, you can do many sophisticated analyses, like creating phase diagrams.
pd = PhaseDiagram(entries)


# ## Plotting the phase diagram
# 
# To plot a phase diagram, we send our phase diagram object into the PDPlotter class.

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# Let's show all phases, including unstable ones
plotter = PDPlotter(pd, show_unstable=0.2, backend="matplotlib")
plotter.show()


# ## Calculating energy above hull and other phase equilibria properties

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import collections

data = collections.defaultdict(list)
for e in entries:
    decomp, ehull = pd.get_decomp_and_e_above_hull(e)
    data["Materials ID"].append(e.entry_id)
    data["Composition"].append(e.composition.reduced_formula)
    data["Ehull"].append(ehull)
    data["Decomposition"].append(
        " + ".join([f"{v:.2f} {k.composition.formula}" for k, v in decomp.items()])
    )

from pandas import DataFrame

df = DataFrame(data, columns=["Materials ID", "Composition", "Ehull", "Decomposition"])

print(df.head(30))