.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "auto_examples/106_network_basics.py" .. LINE NUMBERS ARE GIVEN BELOW. .. only:: html .. note:: :class: sphx-glr-download-link-note Click :ref:`here ` to download the full example code .. rst-class:: sphx-glr-example-title .. _sphx_glr_auto_examples_106_network_basics.py: Network Basics ============== Related MassComposition objects can be managed as a network. In the Process Engineering/Metallurgy disciplines the network will often be called a _flowsheet_. .. GENERATED FROM PYTHON SOURCE LINES 9-19 .. code-block:: default from copy import deepcopy from typing import Dict import pandas as pd from matplotlib import pyplot as plt from elphick.mass_composition import MassComposition, Flowsheet from elphick.mass_composition.mc_node import MCNode from elphick.mass_composition.datasets.sample_data import sample_data .. GENERATED FROM PYTHON SOURCE LINES 20-24 Create some MassComposition objects ----------------------------------- Create an object, and split it to create two more objects. .. GENERATED FROM PYTHON SOURCE LINES 25-30 .. code-block:: default df_data: pd.DataFrame = sample_data() obj_mc: MassComposition = MassComposition(df_data, name='Feed') obj_mc_1, obj_mc_2 = obj_mc.split(0.4, name_1='stream 1', name_2='stream 2') .. GENERATED FROM PYTHON SOURCE LINES 31-33 Placeholder random nodes are created for each MassComposition object. This is done to capture the relationships implicitly defined by any math operations performed on the objects. .. GENERATED FROM PYTHON SOURCE LINES 33-37 .. code-block:: default for obj in [obj_mc, obj_mc_1, obj_mc_2]: print(obj.name, obj._nodes) .. rst-class:: sphx-glr-script-out .. code-block:: none Feed [324494284532216511557115773226938749275, 126424624233062861302886601543594094071] stream 1 [126424624233062861302886601543594094071, 132186196820896510251720553826709908991] stream 2 [126424624233062861302886601543594094071, 220692732893009472278859239807727056057] .. GENERATED FROM PYTHON SOURCE LINES 38-42 Create a Flowsheet object ------------------------- This requires passing an Iterable of MassComposition objects .. GENERATED FROM PYTHON SOURCE LINES 43-46 .. code-block:: default fs: Flowsheet = Flowsheet().from_streams([obj_mc, obj_mc_1, obj_mc_2]) .. GENERATED FROM PYTHON SOURCE LINES 47-48 Print the node object detail .. GENERATED FROM PYTHON SOURCE LINES 48-52 .. code-block:: default for node in fs.graph.nodes: print(fs.graph.nodes[node]['mc']) .. rst-class:: sphx-glr-script-out .. code-block:: none {"node_id": "324494284532216511557115773226938749275", "node_name": "Node", "node_subset": "0", "node_type": "SOURCE"} {"node_id": "126424624233062861302886601543594094071", "node_name": "Node", "node_subset": "0", "node_type": "BALANCE", "balanced": "True"} {"node_id": "132186196820896510251720553826709908991", "node_name": "Node", "node_subset": "0", "node_type": "SINK"} {"node_id": "220692732893009472278859239807727056057", "node_name": "Node", "node_subset": "0", "node_type": "SINK"} .. GENERATED FROM PYTHON SOURCE LINES 53-54 Note that the random node placeholder integers have been renumbered for readability. .. GENERATED FROM PYTHON SOURCE LINES 54-58 .. code-block:: default for obj in [obj_mc, obj_mc_1, obj_mc_2]: print(obj.name, obj._nodes) .. rst-class:: sphx-glr-script-out .. code-block:: none Feed [324494284532216511557115773226938749275, 126424624233062861302886601543594094071] stream 1 [126424624233062861302886601543594094071, 132186196820896510251720553826709908991] stream 2 [126424624233062861302886601543594094071, 220692732893009472278859239807727056057] .. GENERATED FROM PYTHON SOURCE LINES 59-63 Print the overall network balanced status NOTE: presently this only includes node balance status edge balance status will assure the mass-moisture balance is satisfied .. GENERATED FROM PYTHON SOURCE LINES 63-66 .. code-block:: default print(fs.balanced) .. rst-class:: sphx-glr-script-out .. code-block:: none True .. GENERATED FROM PYTHON SOURCE LINES 67-69 Plot the network. Imbalanced Nodes will appear red. Later, Imbalanced Edges will also appear red. .. GENERATED FROM PYTHON SOURCE LINES 69-73 .. code-block:: default fs.plot() plt .. image-sg:: /auto_examples/images/sphx_glr_106_network_basics_001.png :alt: Flowsheet Balanced: True Edge Status OK: True :srcset: /auto_examples/images/sphx_glr_106_network_basics_001.png :class: sphx-glr-single-img .. rst-class:: sphx-glr-script-out .. code-block:: none .. GENERATED FROM PYTHON SOURCE LINES 74-75 Display the weight averages for all edges (streams) in the network (flowsheet) .. GENERATED FROM PYTHON SOURCE LINES 75-79 .. code-block:: default df_report: pd.DataFrame = fs.report() df_report .. raw:: html
mass_wet mass_dry H2O Fe SiO2 Al2O3 LOI
name
Feed 300.0 260.0 13.333333 59.0 3.515385 1.873077 4.0
stream 1 120.0 104.0 13.333333 59.0 3.515385 1.873077 4.0
stream 2 180.0 156.0 13.333333 59.0 3.515385 1.873077 4.0


.. GENERATED FROM PYTHON SOURCE LINES 80-84 .. code-block:: default df_report: pd.DataFrame = fs.report(apply_formats=True) df_report .. raw:: html
mass_wet mass_dry H2O Fe SiO2 Al2O3 LOI
name
Feed 300 260 13.3 59.00 3.52 1.87 4.00
stream 1 120 104 13.3 59.00 3.52 1.87 4.00
stream 2 180 156 13.3 59.00 3.52 1.87 4.00


.. GENERATED FROM PYTHON SOURCE LINES 85-86 Plot the interactive network using plotly .. GENERATED FROM PYTHON SOURCE LINES 86-90 .. code-block:: default fig = fs.plot_network() fig .. raw:: html


.. GENERATED FROM PYTHON SOURCE LINES 91-92 Plot the Sankey .. GENERATED FROM PYTHON SOURCE LINES 92-96 .. code-block:: default fig = fs.plot_sankey() fig .. raw:: html


.. GENERATED FROM PYTHON SOURCE LINES 97-98 Demonstrate the table-plot .. GENERATED FROM PYTHON SOURCE LINES 98-102 .. code-block:: default fig = fs.table_plot(plot_type='sankey', table_pos='top', table_area=0.3) fig .. raw:: html


.. GENERATED FROM PYTHON SOURCE LINES 103-107 .. code-block:: default fig = fs.table_plot(plot_type='network', table_pos='bottom', table_area=0.3) fig .. raw:: html


.. GENERATED FROM PYTHON SOURCE LINES 108-111 Expand the Network with Math Operators -------------------------------------- .. GENERATED FROM PYTHON SOURCE LINES 112-121 .. code-block:: default obj_mc_3, obj_mc_4 = obj_mc_2.split(0.8, name_1='stream 3', name_2='stream 4') obj_mc_5 = obj_mc_1.add(obj_mc_3, name='stream 5') fs2: Flowsheet = Flowsheet().from_streams([obj_mc, obj_mc_1, obj_mc_2, obj_mc_3, obj_mc_4, obj_mc_5]) fig = fs2.table_plot(plot_type='sankey', table_pos='left') fig .. raw:: html


.. GENERATED FROM PYTHON SOURCE LINES 122-124 Setting Node names ------------------ .. GENERATED FROM PYTHON SOURCE LINES 125-129 .. code-block:: default nodes_before: Dict[int, MCNode] = fs.nodes_to_dict() print({n: o.node_name for n, o in nodes_before.items()}) .. rst-class:: sphx-glr-script-out .. code-block:: none {0: 'Node', 1: 'Node', 2: 'Node', 3: 'Node'} .. GENERATED FROM PYTHON SOURCE LINES 130-134 .. code-block:: default fs.set_node_names(node_names={0: 'node_0', 1: 'node_1', 2: 'node_2', 3: 'node_3'}) nodes_after: Dict[int, MCNode] = fs.nodes_to_dict() print({n: o.node_name for n, o in nodes_after.items()}) .. rst-class:: sphx-glr-script-out .. code-block:: none {0: 'node_0', 1: 'node_1', 2: 'node_2', 3: 'node_3'} .. GENERATED FROM PYTHON SOURCE LINES 135-139 Setting Stream data ------------------- First we show how to easily access the stream data as a dictionary .. GENERATED FROM PYTHON SOURCE LINES 140-144 .. code-block:: default stream_data: Dict[str, MassComposition] = fs.streams_to_dict() print(stream_data.keys()) .. rst-class:: sphx-glr-script-out .. code-block:: none dict_keys(['Feed', 'stream 1', 'stream 2']) .. GENERATED FROM PYTHON SOURCE LINES 145-146 We will replace stream 2 with the same data as stream 1. .. GENERATED FROM PYTHON SOURCE LINES 146-153 .. code-block:: default new_stream: MassComposition = deepcopy(fs.get_edge_by_name('stream 1')) # we need to rename to avoid a creating a duplicate stream name new_stream.name = 'stream 1 copy' fs.set_stream_data({'stream 2': new_stream}) print(fs.streams_to_dict().keys()) .. rst-class:: sphx-glr-script-out .. code-block:: none dict_keys(['Feed', 'stream 1', 'stream 1 copy']) .. GENERATED FROM PYTHON SOURCE LINES 154-155 Of course the network is now unbalanced as highlighted in the Sankey .. GENERATED FROM PYTHON SOURCE LINES 155-159 .. code-block:: default fig = fs.table_plot() fig .. raw:: html


.. GENERATED FROM PYTHON SOURCE LINES 160-167 Methods to modify relationships ------------------------------- Sometimes the network that is automatically created may not be what you are after - for example flow may be in the wrong direction. We'll learn how to modify an existing network, by picking up the network above. Let's break the links for the _stream 1_. .. GENERATED FROM PYTHON SOURCE LINES 168-173 .. code-block:: default fs.reset_stream_nodes(stream="stream 1") fig = fs.table_plot() fig .. raw:: html


.. GENERATED FROM PYTHON SOURCE LINES 174-175 We'll now break all remaining connections (we could have done this from the start). .. GENERATED FROM PYTHON SOURCE LINES 175-180 .. code-block:: default fs.reset_stream_nodes() fig = fs.table_plot() fig .. raw:: html


.. GENERATED FROM PYTHON SOURCE LINES 181-182 Now we'll create some linkages - of course they will be completely rubbish and not balance. .. GENERATED FROM PYTHON SOURCE LINES 182-188 .. code-block:: default fs.set_stream_parent(stream="stream 1", parent="Feed") fs.set_stream_child(stream="stream 1", child="stream 1 copy") fig = fs.table_plot() fig .. raw:: html


.. GENERATED FROM PYTHON SOURCE LINES 189-190 Perhaps less useful, but possible, we can build relationships by setting nodes directly. .. GENERATED FROM PYTHON SOURCE LINES 190-196 .. code-block:: default fs.reset_stream_nodes() fs.set_stream_nodes(stream="stream 1", nodes=(1, 2)) fs.set_stream_nodes(stream="stream 1 copy", nodes=(2, 3)) fig = fs.table_plot() fig .. raw:: html


.. rst-class:: sphx-glr-timing **Total running time of the script:** ( 0 minutes 2.194 seconds) .. _sphx_glr_download_auto_examples_106_network_basics.py: .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: 106_network_basics.py <106_network_basics.py>` .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: 106_network_basics.ipynb <106_network_basics.ipynb>` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_