Quick Start

This guide walks through a minimal working example. By the end you will have generated an interactive Duval's Triangle plot from DGA data.

Prerequisites

Make sure the library is installed:

pip install duvals-triangle-plotter

Step 1: Import the library

import duvals_triangle_plotter as dtp

Step 2: Prepare gas concentration data

Provide methane (CH₄), acetylene (C₂H₂), and ethylene (C₂H₄) concentrations in ppm. Each parameter is a list so you can plot multiple samples at once.

methane   = [0.09]
acetylene = [0.0]
ethylene  = [0.91]
date      = "2000-08-16"

Step 3: Create a scatterternary trace

get_duval_points_traces builds a Plotly scatterternary trace dict from the concentration data:

trace = dtp.get_duval_points_traces(
    methane, acetylene, ethylene, date
)

Step 4: Generate the figure

get_duvals_triangle_plot combines fault region polygons with the data trace and returns a Plotly Figure:

fig = dtp.get_duvals_triangle_plot(
    [trace], show_plot=True
)

Set show_plot=True to display the figure immediately. Set it to False when saving or further customising the figure.

Understanding the output

The resulting figure shows:

Seven shaded fault regions (PD, D1, D2, DT, T1, T2, T3)
Your data point plotted as a marker within the ternary axes
Axis labels for CH₄, C₂H₂, and C₂H₄ percentages
A title with the equipment name and the Duval's Triangle label
Hover information showing sample date and gas concentrations

Using in Jupyter notebooks

This library works natively in Jupyter notebooks. When show_plot=True, the Plotly figure renders inline. No special configuration is needed.

Full example

import duvals_triangle_plotter as dtp

methane   = [0.09]
acetylene = [0.0]
ethylene  = [0.91]
date      = "2000-08-16"

trace = dtp.get_duval_points_traces(
    methane, acetylene, ethylene, date
)

fig = dtp.get_duvals_triangle_plot(
    [trace], show_plot=True,
    equipment_name="Site 1"
)