12.3.10.6.2. Sankey diagram

This demo shows how to use the Python plotly package under itom.

In order to show plotly outputs in itom figures, it is only necessary to import the itomPlotlyRenderer module once at the beginning of your script. This adds an itom specific renderer to Plotly and uses it as default.

The plotly outputs are then shown in an itom designerPlugin with the name plotlyPlot.

import itomPlotlyRenderer


import plotly.graph_objects as go
import json

with open("sankey_energy.json") as file:
    data = json.load(file)

# override gray link colors with 'source' colors
opacity = 0.4
# change 'magenta' to its 'rgba' value to add opacity
data["data"][0]["node"]["color"] = [
    "rgba(255,0,255, 0.8)" if color == "magenta" else color
    for color in data["data"][0]["node"]["color"]
]
data["data"][0]["link"]["color"] = [
    data["data"][0]["node"]["color"][src].replace("0.8", str(opacity))
    for src in data["data"][0]["link"]["source"]
]

fig = go.Figure(
    data=[
        go.Sankey(
            valueformat=".0f",
            valuesuffix="TWh",
            # Define nodes
            node=dict(
                pad=15,
                thickness=15,
                line=dict(color="black", width=0.5),
                label=data["data"][0]["node"]["label"],
                color=data["data"][0]["node"]["color"],
            ),
            # Add links
            link=dict(
                source=data["data"][0]["link"]["source"],
                target=data["data"][0]["link"]["target"],
                value=data["data"][0]["link"]["value"],
                label=data["data"][0]["link"]["label"],
                color=data["data"][0]["link"]["color"],
            ),
        )
    ]
)

fig.update_layout(
    title_text="Energy forecast for 2050<br>Source: Department of Energy & Climate Change, "
    "Tom Counsell via <a href='https://bost.ocks.org/mike/sankey/'>Mike Bostock</a>",
    font_size=10,
)
fig.show()