Network Layouts

Related MassComposition objects can be represented in network using the Flowsheet object.

This example demonstrates layouts of such networks.

import plotly
import pandas as pd

from elphick.mass_composition.flowsheet import Flowsheet
from elphick.mass_composition.datasets.sample_data import size_by_assay
from elphick.mass_composition import MassComposition

# sphinx_gallery_thumbnail_number = -1

Create a mass-composition object

We get some demo data in the form of a pandas DataFrame

df_data: pd.DataFrame = size_by_assay()

Create the object

mc_feed: MassComposition = MassComposition(df_data, name='feed')

Split the Sample

mc_1, mc_2 = mc_feed.split(0.5, 'split 1', 'split 2')
mc_3, mc_4 = mc_1.split(0.5, 'split 3', 'split 4')
mc_5, mc_6 = mc_2.split(0.5, 'split 5', 'split 6')

Create a network and plot with both orientations

fs: Flowsheet = Flowsheet().from_streams([mc_feed,
                                           mc_1, mc_2,
                                           mc_3, mc_4, mc_5, mc_6])

fig = fs.plot_network(orientation='horizontal')
fig

fig = fs.plot_network(orientation='vertical')
fig

The table plot also supports orientation with the network_orientation argument.

fig = fs.table_plot(table_pos='left', plot_type='network', network_orientation='vertical')
# noinspection PyTypeChecker
plotly.io.show(fig)  # this call to show will set the thumbnail for use in the gallery