elphick.mass_composition.flowsheet.Flowsheet

class elphick.mass_composition.flowsheet.Flowsheet(name='Flowsheet')

__init__(name='Flowsheet')

Methods

__init__([name])
from_dag(dag)	Construct a flowsheet from a dag object
from_dataframe(df[, name, mc_name_col, n_jobs])	Instantiate from a DataFrame
from_streams(streams[, name])	Instantiate from a list of objects
from_yaml(flowsheet_file)	Construct a flowsheet defined in a yaml file
get_column_formats(columns[, strip_percent])	type columns: List[str]
get_edge_by_name(name)	Get the MC object from the network by its name
get_input_streams()	Get the input (feed) streams (edge objects)
get_node_input_outputs(node)	rtype: Tuple
get_output_streams()	Get the output (product) streams (edge objects)
get_stream_names()	Get the names of the streams (MC objects on the edges)
imbalance_report(node)
nodes_to_dict()	Export the MCNode objects to a Dict
plot([orientation])	Plot the network with matplotlib
plot_balance([facet_col_wrap, color])	Plot input versus output across all nodes in the network
plot_network([orientation])	Plot the network with plotly
plot_parallel([names, color, vars_include, ...])	Create an interactive parallel plot
plot_sankey([width_var, color_var, ...])	Plot the Network as a sankey
query(mc_name, queries)	Query/filter across the network
report([apply_formats])	Summary Report
reset_stream_nodes([stream])	Reset stream nodes to break relationships
set_node_names(node_names)	Set the names of network nodes with a Dict
set_stream_child(stream, child)
set_stream_data(stream_data)	Set the data (MassComposition) of network edges (streams) with a Dict
set_stream_nodes(stream, nodes)
set_stream_parent(stream, parent)
streams_to_dict()	Export the Stream objects to a Dict
table_plot([plot_type, cols_exclude, ...])	Plot with table of edge averages
to_dataframe([names])	Return a tidy dataframe
to_json()	rtype: Dict
to_simple([node_name])	Return the simplified flowsheet

Attributes

balanced
edge_status

classmethod from_dag(dag)

Construct a flowsheet from a dag object

Parameters:

dag (DAG) – The dag object that has been run previously.

Return type:

Flowsheet

Returns:

classmethod from_dataframe(df, name='Flowsheet', mc_name_col=None, n_jobs=1)

Instantiate from a DataFrame

Parameters:

• df (DataFrame) – The DataFrame

• name (Optional[str]) – name of the network

• mc_name_col (Optional[str]) – The column specified contains the names of objects to create. If None the DataFrame is assumed to be wide and the mc objects will be extracted from column prefixes.

• n_jobs (int) – The number of parallel jobs to run. If -1, will use all available cores.

Returns:

An instance of the Flowsheet class initialized from the provided DataFrame.

Return type:

Flowsheet

classmethod from_streams(streams, name='Flowsheet')

Instantiate from a list of objects

Parameters:

• streams (List[Union[Stream, MassComposition]]) – List of MassComposition objects

• name (Optional[str]) – name of the network

Return type:

Flowsheet

Returns:

classmethod from_yaml(flowsheet_file)

Construct a flowsheet defined in a yaml file

Parameters:

flowsheet_file (Path) – The yaml file following the prescribed format

Return type:

Flowsheet

Returns:

get_column_formats(columns, strip_percent=False)

Parameters:

• columns (List[str]) – The columns to lookup format strings for

• strip_percent (bool) – If True remove the leading % symbol from the format (for plotly tables)

Return type:

Dict[str, str]

Returns:

get_edge_by_name(name)

Get the MC object from the network by its name

Parameters:

name (str) – The string name of the MassComposition object stored on an edge in the network.

Return type:

MassComposition

Returns:

get_input_streams()

Get the input (feed) streams (edge objects)

Return type:

List[Union[Stream, MassComposition]]

Returns:

List of MassComposition objects

get_output_streams()

Get the output (product) streams (edge objects)

Return type:

List[Union[Stream, MassComposition]]

Returns:

List of MassComposition objects

get_stream_names()

Get the names of the streams (MC objects on the edges)

Returns:

Return type:

List[str]

nodes_to_dict()

Export the MCNode objects to a Dict

Return type:

Dict[int, MCNode]

Returns:

A dictionary keyed by integer containing MCNode objects

plot(orientation='horizontal')

Plot the network with matplotlib

Parameters:

orientation (str) – ‘horizontal’|’vertical’ network layout

Return type:

Figure

Returns:

plot_balance(facet_col_wrap=3, color='node')

Plot input versus output across all nodes in the network

Parameters:

• facet_col_wrap (int) – the number of subplots per row before wrapping

• color (Optional[str]) – The optional variable to color by. If None color will be by Node

Return type:

Figure

Returns:

plot_network(orientation='horizontal')

Plot the network with plotly

Parameters:

orientation (str) – ‘horizontal’|’vertical’ network layout

Return type:

Figure

Returns:

plot_parallel(names=None, color=None, vars_include=None, vars_exclude=None, title=None, include_dims=True, plot_interval_edges=False)

Create an interactive parallel plot

Useful to explore multidimensional data like mass-composition data

Parameters:

• names (Optional[str]) – Optional List of Names to plot

• color (Optional[str]) – Optional color variable

• vars_include (Optional[List[str]]) – Optional List of variables to include in the plot

• vars_exclude (Optional[List[str]]) – Optional List of variables to exclude in the plot

• title (Optional[str]) – Optional plot title

• include_dims (Union[bool, List[str], None]) – Optional boolean or list of dimension to include in the plot. True will show all dims.

• plot_interval_edges (bool) – If True, interval edges will be plotted instead of interval mid

Return type:

Figure

Returns:

plot_sankey(width_var='mass_wet', color_var=None, edge_colormap='copper_r', vmin=None, vmax=None)

Plot the Network as a sankey

Parameters:

• width_var (str) – The variable that determines the sankey width

• color_var (Optional[str]) – The optional variable that determines the sankey edge color

• edge_colormap (Optional[str]) – The optional colormap. Used with color_var.

• vmin (Optional[float]) – The value that maps to the minimum color

• vmax (Optional[float]) – The value that maps to the maximum color

Return type:

Figure

Returns:

query(mc_name, queries)

Query/filter across the network

The queries provided will be applied to the MassComposition object in the network with the mc_name. The indexes for that result are then used to filter the other edges of the network.

Parameters:

• mc_name (str) – The name of the MassComposition object in the network to which the first filter to be applied.

• queries (Dict) – The query or queries to apply to the object with mc_name.

Return type:

Flowsheet

Returns:

report(apply_formats=False)

Summary Report

Total Mass and weight averaged composition Returns:

Return type:

DataFrame

reset_stream_nodes(stream=None)

Reset stream nodes to break relationships

Parameters:

stream (Optional[str]) – The optional stream (edge) within the network. If None all streams nodes on the network will be reset.

Returns:

set_node_names(node_names)

Set the names of network nodes with a Dict

set_stream_data(stream_data)

Set the data (MassComposition) of network edges (streams) with a Dict

streams_to_dict()

Export the Stream objects to a Dict

Return type:

Dict[str, MassComposition]

Returns:

A dictionary keyed by name containing MassComposition objects

table_plot(plot_type='sankey', cols_exclude=None, table_pos='left', table_area=0.4, table_header_color='cornflowerblue', table_odd_color='whitesmoke', table_even_color='lightgray', sankey_width_var='mass_wet', sankey_color_var=None, sankey_edge_colormap='copper_r', sankey_vmin=None, sankey_vmax=None, network_orientation='horizontal')

Plot with table of edge averages

Parameters:

• plot_type (str) – The type of plot [‘sankey’, ‘network’]

• cols_exclude (Optional[List]) – List of columns to exclude from the table

• table_pos (str) – Position of the table [‘left’, ‘right’, ‘top’, ‘bottom’]

• table_area (float) – The proportion of width or height to allocate to the table [0, 1]

• table_header_color (str) – Color of the table header

• table_odd_color (str) – Color of the odd table rows

• table_even_color (str) – Color of the even table rows

• sankey_width_var (str) – If plot_type is sankey, the variable that determines the sankey width

• sankey_color_var (Optional[str]) – If plot_type is sankey, the optional variable that determines the sankey edge color

• sankey_edge_colormap (Optional[str]) – If plot_type is sankey, the optional colormap. Used with sankey_color_var.

• sankey_vmin (Optional[float]) – The value that maps to the minimum color

• sankey_vmax (Optional[float]) – The value that maps to the maximum color

• network_orientation (Optional[str]) – The orientation of the network layout ‘vertical’|’horizontal’

Return type:

Figure

Returns:

to_dataframe(names=None)

Return a tidy dataframe

Adds the mc name to the index so indexes are unique.

Parameters:

names (Optional[str]) – Optional List of names of MassComposition objects (network edges) for export

Returns:

to_simple(node_name=None)

Return the simplified flowsheet

Return type:

Flowsheet