Ternary Overlay in Python

How to make a scatter plot overlaid on ternary contour in Python with Plotly.

Plotly is known for its graphing libraries, but it's also a broader ecosystem for building interactive data apps, AI data analysis tools, and deploying and hosting Dash apps. Explore the full set of tools and platforms designed to help turn data into action. Discover Plotly.

Load and Process Data Files¶

In [1]:

import json
import pandas as pd

contour_raw_data = pd.read_json('https://raw.githubusercontent.com/plotly/datasets/master/contour_data.json')
scatter_raw_data = pd.read_json('https://raw.githubusercontent.com/plotly/datasets/master/scatter_data.json')

scatter_data =  scatter_raw_data['Data']

def clean_data(data_in):
    """
    Cleans data in a format which can be conveniently
    used for drawing traces. Takes a dictionary as the
    input, and returns a list in the following format:

    input = {'key': ['a b c']}
    output = [key, [a, b, c]]
    """
    key = list(data_in.keys())[0]
    data_out = [key]
    for i in data_in[key]:
        data_out.append(list(map(float, i.split(' '))))

    return data_out


#Example:
print(clean_data({'L1': ['.03 0.5 0.47','0.4 0.5 0.1']}))

['L1', [0.03, 0.5, 0.47], [0.4, 0.5, 0.1]]

Create Ternary Scatter Plot:¶

In [2]:

import plotly.graph_objects as go

a_list = []
b_list = []
c_list = []
text = []

for raw_data in scatter_data:
    data = clean_data(raw_data)
    text.append(data[0])
    c_list.append(data[1][0])
    a_list.append(data[1][1])
    b_list.append(data[1][2])

fig = go.Figure(go.Scatterternary(
  text=text,
  a=a_list,
  b=b_list,
  c=c_list,
  mode='markers',
  marker={'symbol': 100,
          'color': 'green',
          'size': 10},
))

fig.update_layout({
    'title': 'Ternary Scatter Plot',
    'ternary':
        {
        'sum':1,
        'aaxis':{'title': 'X', 'min': 0.01, 'linewidth':2, 'ticks':'outside' },
        'baxis':{'title': 'W', 'min': 0.01, 'linewidth':2, 'ticks':'outside' },
        'caxis':{'title': 'S', 'min': 0.01, 'linewidth':2, 'ticks':'outside' }
    },
    'showlegend': False
})

fig.show()

Create Ternary Contour Plot:¶

In [3]:

import plotly.graph_objects as go


contour_dict = contour_raw_data['Data']

# Defining a colormap:
colors = ['#8dd3c7','#ffffb3','#bebada',
          '#fb8072','#80b1d3','#fdb462',
          '#b3de69','#fccde5','#d9d9d9',
          '#bc80bd']
colors_iterator = iter(colors)

fig = go.Figure()

for raw_data in contour_dict:
    data = clean_data(raw_data)

    a = [inner_data[0] for inner_data in data[1:]]
    a.append(data[1][0]) # Closing the loop

    b = [inner_data[1] for inner_data in data[1:]]
    b.append(data[1][1]) # Closing the loop

    c = [inner_data[2] for inner_data in data[1:]]
    c.append(data[1][2]) # Closing the loop

    fig.add_trace(go.Scatterternary(
        text = data[0],
        a=a, b=b, c=c, mode='lines',
        line=dict(color='#444', shape='spline'),
        fill='toself',
        fillcolor = colors_iterator.__next__()
    ))

fig.update_layout(title = 'Ternary Contour Plot')
fig.show()

In [ ]:

What About Dash?¶

Dash is an open-source framework for building analytical applications, with no Javascript required, and it is tightly integrated with the Plotly graphing library.

Learn about how to install Dash at https://dash.plot.ly/installation.

Everywhere in this page that you see fig.show(), you can display the same figure in a Dash application by passing it to the figure argument of the Graph component from the built-in dash_core_components package like this:

import plotly.graph_objects as go # or plotly.express as px
fig = go.Figure() # or any Plotly Express function e.g. px.bar(...)
# fig.add_trace( ... )
# fig.update_layout( ... )

from dash import Dash, dcc, html

app = Dash()
app.layout = html.Div([
    dcc.Graph(figure=fig)
])

app.run(debug=True, use_reloader=False)  # Turn off reloader if inside Jupyter