ternary-diagram 2.0.2

This package makes it easier for you to draw beautiful ternary diagram without pymatgen.

Ternary Diagram

This package makes it easier for you to draw beautiful ternary diagram without pymatgen.

Meaningly, only need numpy, pandas and matplotlib.

What you will be able to do with this package

• Create beautiful contour maps easily
• Creating a scatter plot
• Draw tie lines
• Automatically format chemical composition using subscripts
• Most of the matplotlib options are available

First of all

This package works well with the element_recognition package (my own package) because it has a function (get_ratio) that converts composition to ratio.

For example,

from element_recognition import get_ratio

get_ratio(products = ['LiLa2TiO6'], materials = ['Li2O', 'La2O3', 'TiO2'])

               Li2O  La2O3  TiO2
    Li2La2TiO6   1.0   1.0   1.0

How to install

pip install ternary-diagram

PyPI project is here.

Usage

See Examples and the documentation.

Examples

An easy example is here.

import matplotlib.pyplot as plt
from ternary_diagram import TernaryDiagram

td = TernaryDiagram(['Li2O', 'La2O3', 'TiO2'])
td.scatter(vector = [[1, 1, 1], [1, 2, 3]], z = [0, 1])
td.scatter(vector = [[2, 1, 3], [3, 2, 1]], marker = 's', c = '#022c5e', s = 30)    # You can set some options in matplotlib.pyplot.scatter like `marker`, `c` etc.
td.plot(r1 = [1, 1, 1], r2 = [1, 2, 3], color = 'black')  # You can set some options in matplotlib.pyplot.plot like `lw`, `c`, and so on.
plt.savefig('figure.png', dpi = 144)

It can be written like this.

import matplotlib.pyplot as plt
from ternary_diagram import TernaryDiagram

fig, ax = plt.subplots(facecolor='w')   # The background color is sometimes transparent in jupyter notebooks, so set facecolor 'white'.
td = TernaryDiagram(['Li2O', 'La2O3', 'TiO2'], ax=ax)   # You can set `ax` to select which axes to draw. If None, automatically select or generate. 
td.scatter(vector = [[1, 1, 1], [1, 2, 3]], z = [0, 1])
td.scatter(vector = [[2, 1, 3], [3, 2, 1]], marker = 's', c = '#022c5e', s = 30)    # You can set some options in matplotlib.pyplot.scatter like `marker`, `c` etc.
td.plot(r1 = [1, 1, 1], r2 = [1, 2, 3], color = 'black')  # You can set some options in matplotlib.pyplot.plot like `lw`, `c`, and so on.
fig.savefig('figure.png', dpi = 144)

It means that you can draw multiple figures in one figure object.

See also the example folder. In particular, if you want to know how to use element_recognition as well, please refer to example/scatter/example _scatter_with_annotations.ipynb.

LICENSE

See LICENSE.