enhanced timeline, improved handling of odd cases

scripts/analyse_dataset.py

@@ -9,6 +9,7 @@ from lang_main.analysis.graphs import (
     save_to_GraphML,
 )
 from lang_main.constants import (
+    CYTO_BASE_NETWORK_NAME,
     PATH_TO_DATASET,
     SAVE_PATH_FOLDER,
     SKIP_GRAPH_POSTPROCESSING,
@@ -26,7 +27,7 @@ from lang_main.pipelines.predefined import (
     build_timeline_pipe,
     build_tk_graph_pipe,
     build_tk_graph_post_pipe,
-    build_tk_graph_rendering_pipe,
+    build_tk_graph_render_pipe,
     build_tk_graph_rescaling_pipe,
 )
 from lang_main.types import (
@@ -42,8 +43,14 @@ pipe_target_feat = build_base_target_feature_pipe()
 pipe_merge = build_merge_duplicates_pipe()
 pipe_token_analysis = build_tk_graph_pipe()
 pipe_graph_postprocessing = build_tk_graph_post_pipe()
-pipe_graph_rescaling = build_tk_graph_rescaling_pipe()
+pipe_graph_rescaling = build_tk_graph_rescaling_pipe(
-pipe_static_graph_rendering = build_tk_graph_rendering_pipe()
+    save_result=True,
+    exit_point=EntryPoints.TK_GRAPH_ANALYSIS_RESCALED,
+)
+pipe_static_graph_rendering = build_tk_graph_render_pipe(
+    with_subgraphs=True,
+    base_network_name=CYTO_BASE_NETWORK_NAME,
+)
 pipe_timeline = build_timeline_pipe()
 
 
@@ -98,11 +105,11 @@ def run_graph_edge_rescaling() -> None:
         load_pickle(entry_point_path),
     )
     tk_graph = loaded_results[0]
-    ret = cast(
+    tk_graph_rescaled, tk_graph_rescaled_undirected = cast(
         tuple[TokenGraph, Graph], pipe_graph_rescaling.run(starting_values=(tk_graph,))
     )
-    tk_graph_rescaled = ret[0]
+    # tk_graph_rescaled = ret[0]
-    tk_graph_rescaled_undirected = ret[1]
+    # tk_graph_rescaled_undirected = ret[1]
     tk_graph_rescaled.to_GraphML(
         SAVE_PATH_FOLDER, filename='TokenGraph-directed-rescaled', directed=False
     )

scripts/dash_timeline.py

@@ -20,13 +20,15 @@ from pandas import DataFrame
 
 import lang_main.io
 from lang_main.analysis import graphs, tokens
-from lang_main.constants import SPCY_MODEL
+from lang_main.constants import SAVE_PATH_FOLDER, SPCY_MODEL
-from lang_main.types import ObjectID, TimelineCandidates
+from lang_main.types import EntryPoints, ObjectID, TimelineCandidates
 
 # ** data
-p_df = Path(r'../results/test_20240619/TIMELINE.pkl').resolve()
+# p_df = Path(r'../results/test_20240619/TIMELINE.pkl').resolve()
+p_df = lang_main.io.get_entry_point(SAVE_PATH_FOLDER, EntryPoints.TIMELINE)
 (data,) = cast(tuple[DataFrame], lang_main.io.load_pickle(p_df))
-p_tl = Path(r'../results/test_20240619/TIMELINE_POSTPROCESSING.pkl').resolve()
+# p_tl = Path(r'../results/test_20240619/TIMELINE_POSTPROCESSING.pkl').resolve()
+p_tl = lang_main.io.get_entry_point(SAVE_PATH_FOLDER, EntryPoints.TIMELINE_POST)
 cands, texts = cast(
     tuple[TimelineCandidates, dict[ObjectID, str]], lang_main.io.load_pickle(p_tl)
 )
@@ -58,9 +60,10 @@ HOVER_DATA: Final[dict[str, Any]] = {
 }
 
 # ** graph
-target = '../results/test_20240529/Pipe-Token_Analysis_Step-1_build_token_graph.pkl'
+# target = '../results/test_20240529/Pipe-Token_Analysis_Step-1_build_token_graph.pkl'
-p = Path(target).resolve()
+# p = Path(target).resolve()
-ret = lang_main.io.load_pickle(p)
+p_tk_graph = lang_main.io.get_entry_point(SAVE_PATH_FOLDER, EntryPoints.TK_GRAPH_POST)
+ret = lang_main.io.load_pickle(p_tk_graph)
 tk_graph = cast(graphs.TokenGraph, ret[0])
 tk_graph_filtered = graphs.filter_graph_by_edge_weight(tk_graph, 150, None)
 tk_graph_filtered = graphs.filter_graph_by_node_degree(tk_graph_filtered, 1, None)

scripts/dash_timeline_static.py

@@ -0,0 +1,413 @@
+import time
+import webbrowser
+from pathlib import Path
+from threading import Thread
+from typing import Any, Final, cast
+
+# import dash_cytoscape as cyto
+import plotly.express as px
+from dash import (
+    Dash,
+    Input,
+    Output,
+    State,
+    callback,
+    dash_table,
+    dcc,
+    html,
+)
+from pandas import DataFrame
+from plotly.graph_objects import Figure
+
+import lang_main.io
+from lang_main.analysis import graphs, tokens
+from lang_main.constants import SAVE_PATH_FOLDER, SPCY_MODEL
+from lang_main.errors import EmptyEdgesError, EmptyGraphError
+from lang_main.pipelines.predefined import (
+    build_tk_graph_render_pipe,
+    build_tk_graph_rescaling_pipe,
+)
+from lang_main.types import EntryPoints, ObjectID, TimelineCandidates
+
+# ** data
+# p_df = Path(r'../results/test_20240619/TIMELINE.pkl').resolve()
+p_df = lang_main.io.get_entry_point(SAVE_PATH_FOLDER, EntryPoints.TIMELINE)
+(data,) = cast(tuple[DataFrame], lang_main.io.load_pickle(p_df))
+# p_tl = Path(r'../results/test_20240619/TIMELINE_POSTPROCESSING.pkl').resolve()
+p_tl = lang_main.io.get_entry_point(SAVE_PATH_FOLDER, EntryPoints.TIMELINE_POST)
+cands, texts = cast(
+    tuple[TimelineCandidates, dict[ObjectID, str]], lang_main.io.load_pickle(p_tl)
+)
+# ** necessary pipelines
+rescaling_pipe = build_tk_graph_rescaling_pipe(
+    exit_point=EntryPoints.TIMELINE_TK_GRAPH_RESCALED,
+    save_result=False,
+)
+BASE_NETWORK_NAME: Final[str] = 'test_timeline'
+# RENDER_FOLDER: Final[Path] = Path.cwd() / 'assets/'
+graph_render_pipe = build_tk_graph_render_pipe(
+    with_subgraphs=False,
+    base_network_name=BASE_NETWORK_NAME,
+)
+# PTH_RENDERED_GRAPH = f'assets/{BASE_NETWORK_NAME}.svg'
+PTH_RENDERED_GRAPH = lang_main.io.get_entry_point(
+    SAVE_PATH_FOLDER,
+    BASE_NETWORK_NAME,
+    file_ext='.svg',
+)
+
+
+TABLE_FEATS: Final[list[str]] = [
+    'ErstellungsDatum',
+    'ErledigungsDatum',
+    'VorgangsTypName',
+    'VorgangsBeschreibung',
+]
+TABLE_FEATS_DATES: Final[list[str]] = [
+    'ErstellungsDatum',
+    'ErledigungsDatum',
+]
+
+# ** figure config
+MARKERS_OCCURRENCES: Final[dict[str, Any]] = {
+    'size': 12,
+    'color': 'yellow',
+    'line': {
+        'width': 2,
+        'color': 'red',
+    },
+}
+MARKERS_DELTA: Final[dict[str, Any]] = {
+    'size': 8,
+    'color': 'red',
+    'symbol': 'cross',
+}
+HOVER_DATA: Final[dict[str, Any]] = {
+    'ErstellungsDatum': '|%d.%m.%Y',
+    'ErledigungsDatum': '|%d.%m.%Y',
+    'VorgangsBeschreibung': True,
+}
+HOVER_DATA_DELTA: Final[dict[str, Any]] = {
+    'ErstellungsDatum': '|%d.%m.%Y',
+    'ErledigungsDatum': '|%d.%m.%Y',
+    'VorgangsDatum': '|%d.%m.%Y',
+    'delta': True,
+    'VorgangsBeschreibung': True,
+}
+
+# ** graph
+p_tk_graph = lang_main.io.get_entry_point(SAVE_PATH_FOLDER, EntryPoints.TK_GRAPH_POST)
+ret = lang_main.io.load_pickle(p_tk_graph)
+tk_graph = cast(graphs.TokenGraph, ret[0])
+tk_graph_filtered = graphs.filter_graph_by_edge_weight(tk_graph, 150, None)
+tk_graph_filtered = graphs.filter_graph_by_node_degree(tk_graph_filtered, 1, None)
+
+
+graph_layout = html.Div(
+    [
+        dcc.Store(id='graph-store', storage_type='memory'),
+        # dcc.Store(id='graph-store-cyto-curr_cands', storage_type='memory'),
+        html.Div(id='output'),
+        html.Div(
+            [
+                html.H2('Token Graph', style={'margin': 0}),
+            ],
+            style={
+                'display': 'flex',
+                'marginBottom': '1em',
+            },
+        ),
+        html.Div(
+            [
+                html.H3('Graph'),
+                html.Button(
+                    'Download Bild',
+                    id='bt-reset',
+                    style={
+                        'marginLeft': 'auto',
+                        'width': '300px',
+                    },
+                ),
+                dcc.Download(id='static-graph-download'),
+                dcc.Loading(
+                    id='loading-graph-render',
+                    children=html.Div(
+                        [
+                            html.Img(
+                                id='static-graph-img',
+                                alt='static rendered graph',
+                                # style={
+                                #     'width': 'auto',
+                                #     'height': 'auto',
+                                # },
+                            ),
+                            html.P(id='info-graph-errors', children=[]),
+                        ],
+                        style={
+                            'border': '3px solid black',
+                            'borderRadius': '25px',
+                            'marginTop': '1em',
+                            'marginBottom': '2em',
+                            'padding': '7px',
+                        },
+                    ),
+                ),
+            ],
+            style={'marginTop': '1em'},
+        ),
+    ],
+)
+
+
+# ** app
+external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']
+app = Dash(__name__, external_stylesheets=external_stylesheets)
+
+
+app.layout = html.Div(
+    [
+        html.H1(children='Demo Zeitreihenanalyse', style={'textAlign': 'center'}),
+        html.Div(
+            children=[
+                html.H2('Wählen Sie ein Objekt aus (ObjektID):'),
+                dcc.Dropdown(
+                    list(cands.keys()),
+                    id='selector-obj_id',
+                    placeholder='ObjektID auswählen...',
+                ),
+            ]
+        ),
+        html.Div(
+            children=[
+                html.H3(id='object-text'),
+                dcc.Dropdown(id='selector-candidates'),
+                dcc.Graph(id='figure-occurrences'),
+                dcc.Graph(id='figure-delta'),
+            ]
+        ),
+        html.Div(
+            [dash_table.DataTable(id='table-candidates')], style={'marginBottom': '2em'}
+        ),
+        graph_layout,
+    ],
+    style={'margin': '2em'},
+)
+
+
+# ** selectors of candidates
+@callback(
+    Output('object-text', 'children'),
+    Input('selector-obj_id', 'value'),
+    prevent_initial_call=True,
+)
+def update_obj_text(obj_id):
+    obj_id = int(obj_id)
+    obj_text = texts[obj_id]
+    headline = f'HObjektText: {obj_text}'
+    return headline
+
+
+@callback(
+    [
+        Output('selector-candidates', 'options'),
+        Output('selector-candidates', 'value'),
+    ],
+    Input('selector-obj_id', 'value'),
+    prevent_initial_call=True,
+)
+def update_choice_candidates(obj_id):
+    obj_id = int(obj_id)
+    choices = list(range(1, len(cands[obj_id]) + 1))
+    return choices, choices[0]
+
+
+# ** helpers to filter DataFrame
+def pre_filter_data(
+    data: DataFrame,
+    idx: int,
+    obj_id: ObjectID,
+) -> DataFrame:
+    idx = int(idx)
+    obj_id = int(obj_id)
+    # data = data.copy()
+    cands_for_obj_id = cands[obj_id]
+    cands_choice = cands_for_obj_id[int(idx) - 1]
+    # data
+    data = data.loc[list(cands_choice)].sort_index()  # type: ignore
+    data['delta'] = data['ErledigungsDatum'] - data['ErstellungsDatum']
+    data['delta'] = data['delta'].dt.days
+
+    return data
+
+
+# ** figure generation
+# TODO check possible storage of pre-filtered result
+# TODO change input of ``update_table_candidates`` and ``display_candidates_as_graph``
+# TODO to storage component
+@callback(
+    [
+        Output('figure-occurrences', 'figure'),
+        Output('figure-delta', 'figure'),
+    ],
+    Input('selector-candidates', 'value'),
+    State('selector-obj_id', 'value'),
+    prevent_initial_call=True,
+)
+def update_timeline(index, obj_id):
+    obj_id = int(obj_id)
+    obj_text = texts[obj_id]
+    title_occurrences = f'HObjektText: {obj_text}'
+    title_delta = f'HObjektText: {obj_text}, Differenz Erstellung und Erledigung'
+    df = pre_filter_data(data, idx=index, obj_id=obj_id)
+    # figure
+    fig_occurrences = fig_timeline_occurrences(df, title_occurrences)
+    fig_delta = fig_timeline_delta(df, title_delta)
+
+    return fig_occurrences, fig_delta
+
+
+def fig_timeline_occurrences(
+    df: DataFrame,
+    title: str,
+) -> Figure:
+    fig = px.line(
+        data_frame=df,
+        x='ErstellungsDatum',
+        y='ObjektID',
+        title=title,
+        hover_data=HOVER_DATA,
+    )
+    fig.update_traces(
+        mode='markers+lines', marker=MARKERS_OCCURRENCES, marker_symbol='diamond'
+    )
+    fig.update_xaxes(
+        tickformat='%B\n%Y',
+        rangeslider_visible=True,
+    )
+    fig.update_yaxes(type='category')
+    fig.update_layout(hovermode='x unified')
+
+    return fig
+
+
+def fig_timeline_delta(
+    df: DataFrame,
+    title: str,
+) -> Figure:
+    fig = px.scatter(
+        data_frame=df,
+        x='ErstellungsDatum',
+        y='delta',
+        title=title,
+        hover_data=HOVER_DATA_DELTA,
+    )
+    fig.update_traces(marker=MARKERS_DELTA)
+    fig.update_xaxes(tickformat='%B\n%Y')
+    fig.update_yaxes(dtick=1)
+    fig.update_layout(hovermode='x unified')
+
+    return fig
+
+
+# ** HTML table
+@callback(
+    [Output('table-candidates', 'data'), Output('table-candidates', 'columns')],
+    Input('selector-candidates', 'value'),
+    State('selector-obj_id', 'value'),
+    prevent_initial_call=True,
+)
+def update_table_candidates(index, obj_id):
+    df = pre_filter_data(data, idx=index, obj_id=obj_id)
+    df = df.filter(items=TABLE_FEATS, axis=1).sort_values(
+        by='ErstellungsDatum', ascending=True
+    )
+    cols = [{'name': i, 'id': i} for i in df.columns]
+    # convert dates to strings
+    for col in TABLE_FEATS_DATES:
+        df[col] = df[col].dt.strftime(r'%Y-%m-%d')
+
+    table_data = df.to_dict('records')
+    return table_data, cols
+
+
+# ** graph callbacks
+@app.callback(
+    [
+        Output('graph-store', 'data'),
+        Output('static-graph-img', 'src'),
+        Output('info-graph-errors', 'children'),
+    ],
+    # Input('graph-build-btn', 'n_clicks'),
+    Input('selector-candidates', 'value'),
+    State('selector-obj_id', 'value'),
+    prevent_initial_call=True,
+)
+def display_candidates_as_graph(index, obj_id):
+    error_msg = ''
+    t1 = time.perf_counter()
+    df = pre_filter_data(data, idx=index, obj_id=obj_id)
+    t2 = time.perf_counter()
+    print(f'Time for filtering: {t2 - t1} s')
+
+    t1 = time.perf_counter()
+    tk_graph_cands, _ = tokens.build_token_graph(
+        data=df,
+        model=SPCY_MODEL,
+        target_feature='VorgangsBeschreibung',
+        build_map=False,
+        logging_graph=False,
+    )
+    t2 = time.perf_counter()
+    print(f'Time for graph building: {t2 - t1} s')
+
+    # ** now start rendering pipeline in Cytoscape
+    # rescale graph
+    try:
+        t1 = time.perf_counter()
+        _, tk_graph_rescaled_undirected = cast(
+            tuple[graphs.TokenGraph, graphs.Graph],
+            rescaling_pipe.run(starting_values=(tk_graph_cands,)),
+        )
+        # render graph in Cytoscape and export image
+        _ = graph_render_pipe.run(starting_values=(tk_graph_rescaled_undirected,))
+        # load image as b64 encoded string
+        b64_img = lang_main.io.encode_file_to_base64_str(PTH_RENDERED_GRAPH)
+        static_img = f'data:image/svg+xml;base64,{b64_img}'
+        graph_to_store = lang_main.io.encode_to_base64_str(tk_graph_cands)
+
+        # place image in browser
+        t2 = time.perf_counter()
+        print(f'Time for graph rescaling and rendering: {t2 - t1} s')
+    except (EmptyGraphError, EmptyEdgesError):
+        graph_to_store = ''
+        static_img = ''
+        error_msg = 'Graph ist leer und konnte nicht generiert werden!'
+    finally:
+        return graph_to_store, static_img, error_msg
+
+
+@callback(
+    Output('static-graph-download', 'data'),
+    Input('bt-reset', 'n_clicks'),
+    prevent_initial_call=True,
+)
+def func(n_clicks):
+    return dcc.send_file(path=PTH_RENDERED_GRAPH)
+
+
+def _start_webbrowser():
+    host = '127.0.0.1'
+    port = '8050'
+    adress = f'http://{host}:{port}/'
+    time.sleep(2)
+    webbrowser.open_new(adress)
+
+
+def main():
+    webbrowser_thread = Thread(target=_start_webbrowser, daemon=True)
+    webbrowser_thread.start()
+    app.run(debug=True)
+
+
+if __name__ == '__main__':
+    main()

scripts/dashboard/lang_main_config.toml

@@ -1,56 +0,0 @@
-# lang_main: Config file
-
-[paths]
-inputs = './inputs/'
-results = './results/test_new2/'
-dataset = './01_2_Rohdaten_neu/Export4.csv'
-#results = './results/Export7/'
-#dataset = './01_03_Rohdaten_202403/Export7_59499_Zeilen.csv'
-#results = './results/Export7_trunc/'
-#dataset = './01_03_Rohdaten_202403/Export7_trunc.csv'
-
-[control]
-preprocessing = true
-preprocessing_skip = false
-token_analysis = false
-token_analysis_skip = false
-graph_postprocessing = false
-graph_postprocessing_skip = false
-time_analysis = false
-time_analysis_skip = false
-
-#[export_filenames]
-#filename_cossim_filter_candidates = 'CosSim-FilterCandidates'
-
-[preprocess]
-filename_cossim_filter_candidates = 'CosSim-FilterCandidates'
-date_cols = [
-    "VorgangsDatum", 
-    "ErledigungsDatum", 
-    "Arbeitsbeginn", 
-    "ErstellungsDatum",
-]
-threshold_amount_characters = 5
-threshold_similarity = 0.8
-
-[graph_postprocessing]
-threshold_edge_weight = 150
-
-[time_analysis.uniqueness]
-threshold_unique_texts = 4
-criterion_feature = 'HObjektText'
-feature_name_obj_id = 'ObjektID'
-
-[time_analysis.model_input]
-input_features = [
-    'VorgangsTypName',
-    'VorgangsArtText',
-    'VorgangsBeschreibung',
-]
-activity_feature = 'VorgangsTypName'
-activity_types = [
-    'Reparaturauftrag (Portal)',
-    'Störungsmeldung',
-]
-threshold_num_acitivities = 1
-threshold_similarity = 0.8

scripts/dashboard/test.py

@@ -1,18 +0,0 @@
-from pathlib import Path
-from typing import cast
-import statistics
-
-import lang_main.io
-from lang_main.analysis import graphs
-
-# target = '../results/test_20240529/Pipe-Token_Analysis_Step-1_build_token_graph.pkl'
-# p = Path(target).resolve()
-# ret = lang_main.io.load_pickle(p)
-# tk_graph = cast(graphs.TokenGraph, ret[0])
-# tk_graph_filtered = tk_graph.filter_by_edge_weight(150, None)
-# tk_graph_filtered = tk_graph_filtered.filter_by_node_degree(1, None)
-# cyto_data_base, weight_data, all_weights = graphs.convert_graph_to_cytoscape(tk_graph_filtered)
-
-
-test = [1, 1, 1, 2, 2, 3, 3, 4, 4, 1000]
-print(statistics.mean(test))

src/lang_main/analysis/graphs.py

@@ -17,7 +17,7 @@ from lang_main.constants import (
     EDGE_WEIGHT_DECIMALS,
     PROPERTY_NAME_DEGREE_WEIGHTED,
 )
-from lang_main.errors import EdgePropertyNotContainedError
+from lang_main.errors import EdgePropertyNotContainedError, EmptyEdgesError, EmptyGraphError
 from lang_main.io import load_pickle, save_pickle
 from lang_main.loggers import logger_graphs as logger
 from lang_main.types import (
@@ -381,9 +381,12 @@ def normalise_array_linear(
     npt.NDArray[np.float32]
         min/max normalised array
     """
-    arr_norm = (array - array.min()) / (array.max() - array.min())
+    div = array.max() - array.min()
-
+    if div != 0:
+        arr_norm = (array - array.min()) / div
         return arr_norm.astype(np.float32)
+    else:
+        return np.zeros(shape=array.shape, dtype=np.float32)
 
 
 def weight_scaling(
@@ -459,6 +462,8 @@ def rescale_edge_weights(
     weight_property: str = 'weight',
 ) -> Graph | DiGraph | TokenGraph:
     graph = graph.copy()
+    # check non-emptiness
+    verify_non_empty_graph(graph, including_edges=True)
     # check if all edges contain weight property
     verify_property(graph, property=weight_property)
 
@@ -473,6 +478,33 @@ def rescale_edge_weights(
     return graph
 
 
+def verify_non_empty_graph(
+    graph: DiGraph | Graph,
+    including_edges: bool = True,
+) -> None:
+    """check if the given graph is empty, presence of nodes is checked first,
+    then of edges
+
+    Parameters
+    ----------
+    graph : DiGraph | Graph
+        graph to check for emptiness
+    including_edges : bool, optional
+        whether to check for non-existence of edges, by default True
+
+    Raises
+    ------
+    EmptyGraphError
+        if graph does not contain any nodes and therefore edges
+    EmptyEdgesError
+        if graph does not contain any edges
+    """
+    if not tuple(graph.nodes):
+        raise EmptyGraphError(f'Graph object >>{graph}<< does not contain any nodes.')
+    elif including_edges and not tuple(graph.edges):
+        raise EmptyEdgesError(f'Graph object >>{graph}<< does not contain any edges.')
+
+
 # ** ---------------------------------------
 class TokenGraph(DiGraph):
     def __init__(

src/lang_main/cytoscape_config/lang_main.xml

@@ -1,128 +1,128 @@
 <?xml version="1.0" encoding="UTF-8" standalone="yes"?>
-<vizmap id="VizMap-2024_07_12-08_08" documentVersion="3.1">
+<vizmap id="VizMap-2024_07_24-08_54" documentVersion="3.1">
     <visualStyle name="lang_main">
         <network>
-            <visualProperty default="0.0" name="NETWORK_CENTER_X_LOCATION"/>
-            <visualProperty default="0.0" name="NETWORK_CENTER_Y_LOCATION"/>
-            <visualProperty default="0.0" name="NETWORK_CENTER_Z_LOCATION"/>
-            <visualProperty default="false" name="NETWORK_ANNOTATION_SELECTION"/>
             <visualProperty default="1.0" name="NETWORK_SCALE_FACTOR"/>
-            <visualProperty default="false" name="NETWORK_NODE_LABEL_SELECTION"/>
-            <visualProperty default="400.0" name="NETWORK_HEIGHT"/>
-            <visualProperty default="true" name="NETWORK_NODE_SELECTION"/>
-            <visualProperty default="550.0" name="NETWORK_WIDTH"/>
-            <visualProperty default="0.0" name="NETWORK_DEPTH"/>
-            <visualProperty default="false" name="NETWORK_FORCE_HIGH_DETAIL"/>
-            <visualProperty default="" name="NETWORK_TITLE"/>
-            <visualProperty default="true" name="NETWORK_EDGE_SELECTION"/>
             <visualProperty default="#F7FFFF" name="NETWORK_BACKGROUND_PAINT"/>
+            <visualProperty default="0.0" name="NETWORK_DEPTH"/>
+            <visualProperty default="0.0" name="NETWORK_CENTER_Z_LOCATION"/>
+            <visualProperty default="true" name="NETWORK_EDGE_SELECTION"/>
+            <visualProperty default="false" name="NETWORK_ANNOTATION_SELECTION"/>
+            <visualProperty default="" name="NETWORK_TITLE"/>
+            <visualProperty default="false" name="NETWORK_FORCE_HIGH_DETAIL"/>
+            <visualProperty default="true" name="NETWORK_NODE_SELECTION"/>
+            <visualProperty default="0.0" name="NETWORK_CENTER_Y_LOCATION"/>
+            <visualProperty default="0.0" name="NETWORK_CENTER_X_LOCATION"/>
+            <visualProperty default="false" name="NETWORK_NODE_LABEL_SELECTION"/>
+            <visualProperty default="550.0" name="NETWORK_WIDTH"/>
+            <visualProperty default="400.0" name="NETWORK_HEIGHT"/>
         </network>
         <node>
             <dependency value="true" name="nodeCustomGraphicsSizeSync"/>
             <dependency value="true" name="nodeSizeLocked"/>
-            <visualProperty default="ROUND_RECTANGLE" name="NODE_LABEL_BACKGROUND_SHAPE"/>
-            <visualProperty default="org.cytoscape.cg.model.NullCustomGraphics,0,[ Remove Graphics ]," name="NODE_CUSTOMGRAPHICS_9"/>
-            <visualProperty default="C,C,c,0.00,0.00" name="NODE_CUSTOMGRAPHICS_POSITION_7"/>
-            <visualProperty default="true" name="NODE_NESTED_NETWORK_IMAGE_VISIBLE"/>
-            <visualProperty default="0.0" name="NODE_LABEL_ROTATION"/>
-            <visualProperty default="175" name="NODE_LABEL_BACKGROUND_TRANSPARENCY"/>
-            <visualProperty default="0.0" name="NODE_CUSTOMGRAPHICS_SIZE_8"/>
-            <visualProperty default="C,C,c,0.00,0.00" name="NODE_CUSTOMGRAPHICS_POSITION_2"/>
-            <visualProperty default="org.cytoscape.cg.model.NullCustomGraphics,0,[ Remove Graphics ]," name="NODE_CUSTOMGRAPHICS_6"/>
-            <visualProperty default="org.cytoscape.cg.model.NullCustomGraphics,0,[ Remove Graphics ]," name="NODE_CUSTOMGRAPHICS_7"/>
-            <visualProperty default="org.cytoscape.cg.model.NullCustomGraphics,0,[ Remove Graphics ]," name="NODE_CUSTOMGRAPHICS_1"/>
-            <visualProperty default="org.cytoscape.cg.model.NullCustomGraphics,0,[ Remove Graphics ]," name="NODE_CUSTOMGRAPHICS_4"/>
-            <visualProperty default="0.0" name="NODE_CUSTOMGRAPHICS_SIZE_9"/>
-            <visualProperty default="ROUND_RECTANGLE" name="COMPOUND_NODE_SHAPE"/>
-            <visualProperty default="0.0" name="NODE_CUSTOMGRAPHICS_SIZE_5"/>
-            <visualProperty default="C,C,c,0.00,0.00" name="NODE_CUSTOMGRAPHICS_POSITION_9"/>
-            <visualProperty default="C,C,c,0.00,0.00" name="NODE_CUSTOMGRAPHICS_POSITION_5"/>
-            <visualProperty default="10.0" name="COMPOUND_NODE_PADDING"/>
-            <visualProperty default="0.0" name="NODE_CUSTOMGRAPHICS_SIZE_3"/>
-            <visualProperty default="0.0" name="NODE_CUSTOMGRAPHICS_SIZE_6"/>
-            <visualProperty default="C,C,c,0.00,0.00" name="NODE_CUSTOMGRAPHICS_POSITION_8"/>
-            <visualProperty default="SE,NW,c,-2.00,3.00" name="NODE_LABEL_POSITION"/>
-            <visualProperty default="ELLIPSE" name="NODE_SHAPE"/>
-            <visualProperty default="C,C,c,0.00,0.00" name="NODE_CUSTOMGRAPHICS_POSITION_3"/>
-            <visualProperty default="0.0" name="NODE_CUSTOMGRAPHICS_SIZE_4"/>
-            <visualProperty default="SansSerif.plain,plain,12" name="NODE_LABEL_FONT_FACE"/>
-            <visualProperty default="#D1F5BE" name="NODE_BORDER_PAINT"/>
-            <visualProperty default="40.0" name="NODE_HEIGHT"/>
-            <visualProperty default="255" name="NODE_LABEL_TRANSPARENCY"/>
-            <visualProperty default="#E1E1E1" name="NODE_LABEL_BACKGROUND_COLOR"/>
-            <visualProperty default="C,C,c,0.00,0.00" name="NODE_CUSTOMGRAPHICS_POSITION_6"/>
-            <visualProperty default="false" name="NODE_SELECTED"/>
-            <visualProperty default="0.0" name="NODE_DEPTH"/>
-            <visualProperty default="SOLID" name="NODE_BORDER_STROKE"/>
-            <visualProperty default="" name="NODE_TOOLTIP"/>
-            <visualProperty default="7.0" name="NODE_BORDER_WIDTH"/>
-            <visualProperty default="0.0" name="NODE_CUSTOMGRAPHICS_SIZE_2"/>
-            <visualProperty default="#A63C06" name="NODE_LABEL_COLOR"/>
-            <visualProperty default="0.0" name="NODE_X_LOCATION"/>
-            <visualProperty default="18.0" name="NODE_SIZE"/>
-            <visualProperty default="org.cytoscape.cg.model.NullCustomGraphics,0,[ Remove Graphics ]," name="NODE_CUSTOMGRAPHICS_8"/>
-            <visualProperty default="0.0" name="NODE_Z_LOCATION"/>
-            <visualProperty default="#FE9929" name="NODE_FILL_COLOR"/>
-            <visualProperty default="0.0" name="NODE_CUSTOMGRAPHICS_SIZE_1"/>
-            <visualProperty default="255" name="NODE_BORDER_TRANSPARENCY"/>
             <visualProperty default="C,C,c,0.00,0.00" name="NODE_CUSTOMGRAPHICS_POSITION_1"/>
-            <visualProperty default="org.cytoscape.cg.model.NullCustomGraphics,0,[ Remove Graphics ]," name="NODE_CUSTOMGRAPHICS_2"/>
+            <visualProperty default="C,C,c,0.00,0.00" name="NODE_CUSTOMGRAPHICS_POSITION_6"/>
-            <visualProperty default="org.cytoscape.cg.model.NullCustomGraphics,0,[ Remove Graphics ]," name="NODE_CUSTOMGRAPHICS_3"/>
+            <visualProperty default="C,C,c,0.00,0.00" name="NODE_CUSTOMGRAPHICS_POSITION_9"/>
-            <visualProperty default="60.0" name="NODE_WIDTH"/>
+            <visualProperty default="18.0" name="NODE_SIZE"/>
+            <visualProperty default="#A63C06" name="NODE_LABEL_COLOR"/>
+            <visualProperty default="0.0" name="NODE_LABEL_ROTATION"/>
+            <visualProperty default="0.0" name="NODE_CUSTOMGRAPHICS_SIZE_3"/>
+            <visualProperty default="C,C,c,0.00,0.00" name="NODE_CUSTOMGRAPHICS_POSITION_3"/>
+            <visualProperty default="#E1E1E1" name="NODE_LABEL_BACKGROUND_COLOR"/>
+            <visualProperty default="0.0" name="NODE_CUSTOMGRAPHICS_SIZE_4"/>
+            <visualProperty default="#D1F5BE" name="NODE_BORDER_PAINT"/>
+            <visualProperty default="org.cytoscape.cg.model.NullCustomGraphics,0,[ Remove Graphics ]," name="NODE_CUSTOMGRAPHICS_8"/>
+            <visualProperty default="40.0" name="NODE_HEIGHT"/>
+            <visualProperty default="org.cytoscape.cg.model.NullCustomGraphics,0,[ Remove Graphics ]," name="NODE_CUSTOMGRAPHICS_7"/>
+            <visualProperty default="255" name="NODE_LABEL_TRANSPARENCY"/>
+            <visualProperty default="" name="NODE_TOOLTIP"/>
+            <visualProperty default="false" name="NODE_SELECTED"/>
+            <visualProperty default="255" name="NODE_BORDER_TRANSPARENCY"/>
+            <visualProperty default="0.0" name="NODE_CUSTOMGRAPHICS_SIZE_5"/>
+            <visualProperty default="14" name="NODE_LABEL_FONT_SIZE"/>
+            <visualProperty default="0.0" name="NODE_CUSTOMGRAPHICS_SIZE_2"/>
+            <visualProperty default="0.0" name="NODE_CUSTOMGRAPHICS_SIZE_6"/>
             <visualProperty default="" name="NODE_LABEL">
                 <passthroughMapping attributeName="name" attributeType="string"/>
             </visualProperty>
-            <visualProperty default="org.cytoscape.cg.model.NullCustomGraphics,0,[ Remove Graphics ]," name="NODE_CUSTOMGRAPHICS_5"/>
+            <visualProperty default="org.cytoscape.cg.model.NullCustomGraphics,0,[ Remove Graphics ]," name="NODE_CUSTOMGRAPHICS_2"/>
-            <visualProperty default="500.0" name="NODE_LABEL_WIDTH"/>
+            <visualProperty default="C,C,c,0.00,0.00" name="NODE_CUSTOMGRAPHICS_POSITION_2"/>
-            <visualProperty default="C,C,c,0.00,0.00" name="NODE_CUSTOMGRAPHICS_POSITION_4"/>
+            <visualProperty default="#FE9929" name="NODE_FILL_COLOR"/>
-            <visualProperty default="0.0" name="NODE_CUSTOMGRAPHICS_SIZE_7"/>
             <visualProperty default="#FFFF00" name="NODE_SELECTED_PAINT"/>
-            <visualProperty default="0.0" name="NODE_Y_LOCATION"/>
-            <visualProperty default="true" name="NODE_VISIBLE"/>
             <visualProperty default="255" name="NODE_TRANSPARENCY"/>
-            <visualProperty default="14" name="NODE_LABEL_FONT_SIZE"/>
+            <visualProperty default="500.0" name="NODE_LABEL_WIDTH"/>
+            <visualProperty default="C,C,c,0.00,0.00" name="NODE_CUSTOMGRAPHICS_POSITION_8"/>
+            <visualProperty default="org.cytoscape.cg.model.NullCustomGraphics,0,[ Remove Graphics ]," name="NODE_CUSTOMGRAPHICS_5"/>
+            <visualProperty default="60.0" name="NODE_WIDTH"/>
+            <visualProperty default="org.cytoscape.cg.model.NullCustomGraphics,0,[ Remove Graphics ]," name="NODE_CUSTOMGRAPHICS_4"/>
+            <visualProperty default="10.0" name="COMPOUND_NODE_PADDING"/>
+            <visualProperty default="SansSerif.plain,plain,12" name="NODE_LABEL_FONT_FACE"/>
+            <visualProperty default="0.0" name="NODE_Y_LOCATION"/>
+            <visualProperty default="ELLIPSE" name="NODE_SHAPE"/>
+            <visualProperty default="SE,NW,c,-2.00,3.00" name="NODE_LABEL_POSITION"/>
+            <visualProperty default="true" name="NODE_VISIBLE"/>
+            <visualProperty default="org.cytoscape.cg.model.NullCustomGraphics,0,[ Remove Graphics ]," name="NODE_CUSTOMGRAPHICS_1"/>
+            <visualProperty default="ROUND_RECTANGLE" name="NODE_LABEL_BACKGROUND_SHAPE"/>
+            <visualProperty default="0.0" name="NODE_Z_LOCATION"/>
+            <visualProperty default="org.cytoscape.cg.model.NullCustomGraphics,0,[ Remove Graphics ]," name="NODE_CUSTOMGRAPHICS_6"/>
+            <visualProperty default="ROUND_RECTANGLE" name="COMPOUND_NODE_SHAPE"/>
+            <visualProperty default="org.cytoscape.cg.model.NullCustomGraphics,0,[ Remove Graphics ]," name="NODE_CUSTOMGRAPHICS_9"/>
+            <visualProperty default="SOLID" name="NODE_BORDER_STROKE"/>
+            <visualProperty default="C,C,c,0.00,0.00" name="NODE_CUSTOMGRAPHICS_POSITION_5"/>
+            <visualProperty default="C,C,c,0.00,0.00" name="NODE_CUSTOMGRAPHICS_POSITION_7"/>
+            <visualProperty default="0.0" name="NODE_CUSTOMGRAPHICS_SIZE_8"/>
+            <visualProperty default="0.0" name="NODE_X_LOCATION"/>
+            <visualProperty default="5.0" name="NODE_BORDER_WIDTH"/>
+            <visualProperty default="true" name="NODE_NESTED_NETWORK_IMAGE_VISIBLE"/>
+            <visualProperty default="org.cytoscape.cg.model.NullCustomGraphics,0,[ Remove Graphics ]," name="NODE_CUSTOMGRAPHICS_3"/>
+            <visualProperty default="175" name="NODE_LABEL_BACKGROUND_TRANSPARENCY"/>
+            <visualProperty default="0.0" name="NODE_CUSTOMGRAPHICS_SIZE_1"/>
+            <visualProperty default="C,C,c,0.00,0.00" name="NODE_CUSTOMGRAPHICS_POSITION_4"/>
+            <visualProperty default="0.0" name="NODE_DEPTH"/>
+            <visualProperty default="0.0" name="NODE_CUSTOMGRAPHICS_SIZE_7"/>
+            <visualProperty default="0.0" name="NODE_CUSTOMGRAPHICS_SIZE_9"/>
         </node>
         <edge>
             <dependency value="true" name="arrowColorMatchesEdge"/>
-            <visualProperty default="false" name="EDGE_SELECTED"/>
-            <visualProperty default="255" name="EDGE_TRANSPARENCY"/>
-            <visualProperty default="10" name="EDGE_LABEL_FONT_SIZE"/>
-            <visualProperty default="#577399" name="EDGE_UNSELECTED_PAINT"/>
-            <visualProperty default="" name="EDGE_LABEL"/>
-            <visualProperty default="#FFFFFF" name="EDGE_STROKE_UNSELECTED_PAINT"/>
-            <visualProperty default="200.0" name="EDGE_LABEL_WIDTH"/>
-            <visualProperty default="#000000" name="EDGE_LABEL_COLOR"/>
-            <visualProperty default="SansSerif.plain,plain,10" name="EDGE_LABEL_FONT_FACE"/>
-            <visualProperty default="0.728545744495502,-0.684997151948455,0.6456513365424503" name="EDGE_BEND"/>
-            <visualProperty default="#B6B6B6" name="EDGE_LABEL_BACKGROUND_COLOR"/>
-            <visualProperty default="AUTO_BEND" name="EDGE_STACKING"/>
-            <visualProperty default="#000000" name="EDGE_TARGET_ARROW_UNSELECTED_PAINT"/>
-            <visualProperty default="0.5" name="EDGE_STACKING_DENSITY"/>
-            <visualProperty default="NONE" name="EDGE_TARGET_ARROW_SHAPE"/>
-            <visualProperty default="true" name="EDGE_VISIBLE"/>
-            <visualProperty default="C,C,c,0.00,0.00" name="EDGE_LABEL_POSITION"/>
-            <visualProperty default="0.0" name="EDGE_LABEL_ROTATION"/>
-            <visualProperty default="" name="EDGE_TOOLTIP"/>
             <visualProperty default="0.0" name="EDGE_Z_ORDER"/>
             <visualProperty default="#FFFF00" name="EDGE_TARGET_ARROW_SELECTED_PAINT"/>
-            <visualProperty default="#FF0000" name="EDGE_STROKE_SELECTED_PAINT"/>
+            <visualProperty default="" name="EDGE_TOOLTIP"/>
-            <visualProperty default="NONE" name="EDGE_SOURCE_ARROW_SHAPE"/>
+            <visualProperty default="10" name="EDGE_LABEL_FONT_SIZE"/>
-            <visualProperty default="#FFFF00" name="EDGE_SOURCE_ARROW_SELECTED_PAINT"/>
+            <visualProperty default="255" name="EDGE_TRANSPARENCY"/>
-            <visualProperty default="false" name="EDGE_LABEL_AUTOROTATE"/>
+            <visualProperty default="#000000" name="EDGE_TARGET_ARROW_UNSELECTED_PAINT"/>
-            <visualProperty default="true" name="EDGE_CURVED"/>
+            <visualProperty default="200.0" name="EDGE_LABEL_WIDTH"/>
-            <visualProperty default="#000000" name="EDGE_SOURCE_ARROW_UNSELECTED_PAINT"/>
+            <visualProperty default="SansSerif.plain,plain,10" name="EDGE_LABEL_FONT_FACE"/>
-            <visualProperty default="255" name="EDGE_LABEL_TRANSPARENCY"/>
+            <visualProperty default="0.728545744495502,-0.684997151948455,0.6456513365424503" name="EDGE_BEND"/>
-            <visualProperty default="6.0" name="EDGE_TARGET_ARROW_SIZE"/>
+            <visualProperty default="0.5" name="EDGE_STACKING_DENSITY"/>
-            <visualProperty default="NONE" name="EDGE_LABEL_BACKGROUND_SHAPE"/>
+            <visualProperty default="false" name="EDGE_SELECTED"/>
-            <visualProperty default="255" name="EDGE_LABEL_BACKGROUND_TRANSPARENCY"/>
-            <visualProperty default="SOLID" name="EDGE_LINE_TYPE"/>
-            <visualProperty default="6.0" name="EDGE_SOURCE_ARROW_SIZE"/>
             <visualProperty default="3.0" name="EDGE_WIDTH">
                 <continuousMapping attributeName="weight" attributeType="float">
                     <continuousMappingPoint attrValue="0.09520000219345093" equalValue="2.0" greaterValue="2.0" lesserValue="1.0"/>
                     <continuousMappingPoint attrValue="1.0" equalValue="10.0" greaterValue="1.0" lesserValue="10.0"/>
                 </continuousMapping>
             </visualProperty>
+            <visualProperty default="#577399" name="EDGE_UNSELECTED_PAINT"/>
+            <visualProperty default="6.0" name="EDGE_SOURCE_ARROW_SIZE"/>
+            <visualProperty default="255" name="EDGE_LABEL_BACKGROUND_TRANSPARENCY"/>
+            <visualProperty default="#000000" name="EDGE_LABEL_COLOR"/>
+            <visualProperty default="SOLID" name="EDGE_LINE_TYPE"/>
+            <visualProperty default="#FF0000" name="EDGE_STROKE_SELECTED_PAINT"/>
+            <visualProperty default="" name="EDGE_LABEL"/>
+            <visualProperty default="true" name="EDGE_VISIBLE"/>
+            <visualProperty default="255" name="EDGE_LABEL_TRANSPARENCY"/>
+            <visualProperty default="#000000" name="EDGE_SOURCE_ARROW_UNSELECTED_PAINT"/>
+            <visualProperty default="#B6B6B6" name="EDGE_LABEL_BACKGROUND_COLOR"/>
+            <visualProperty default="true" name="EDGE_CURVED"/>
+            <visualProperty default="#FFFFFF" name="EDGE_STROKE_UNSELECTED_PAINT"/>
+            <visualProperty default="0.0" name="EDGE_LABEL_ROTATION"/>
+            <visualProperty default="AUTO_BEND" name="EDGE_STACKING"/>
+            <visualProperty default="#FFFF00" name="EDGE_SOURCE_ARROW_SELECTED_PAINT"/>
+            <visualProperty default="NONE" name="EDGE_TARGET_ARROW_SHAPE"/>
+            <visualProperty default="NONE" name="EDGE_SOURCE_ARROW_SHAPE"/>
+            <visualProperty default="6.0" name="EDGE_TARGET_ARROW_SIZE"/>
+            <visualProperty default="NONE" name="EDGE_LABEL_BACKGROUND_SHAPE"/>
+            <visualProperty default="false" name="EDGE_LABEL_AUTOROTATE"/>
+            <visualProperty default="C,C,c,0.00,0.00" name="EDGE_LABEL_POSITION"/>
         </edge>
     </visualStyle>
 </vizmap>

src/lang_main/errors.py

@@ -1,2 +1,12 @@
 class EdgePropertyNotContainedError(Exception):
     """Error raised if a needed edge property is not contained in graph edges"""
+
+
+class EmptyGraphError(Exception):
+    """Error raised if an operation should be performed on the graph,
+    but it does not contain any nodes or edges"""
+
+
+class EmptyEdgesError(EmptyGraphError):
+    """Error raised if action should be performed on a graph's edges, but
+    it does not contain any"""

src/lang_main/io.py

@@ -71,6 +71,15 @@ def encode_to_base64_str(
     return b64_bytes.decode(encoding=encoding)
 
 
+def encode_file_to_base64_str(
+    path: Path,
+    encoding: str = 'utf-8',
+) -> str:
+    with open(path, 'rb') as file:
+        b64_bytes = base64.b64encode(file.read())
+    return b64_bytes.decode(encoding=encoding)
+
+
 def decode_from_base64_str(
     b64_str: str,
     encoding: str = 'utf-8',
@@ -83,8 +92,9 @@ def decode_from_base64_str(
 def get_entry_point(
     saving_path: Path,
     filename: str,
+    file_ext: str = '.pkl',
 ) -> Path:
-    entry_point_path = (saving_path / filename).with_suffix('.pkl')
+    entry_point_path = (saving_path / filename).with_suffix(file_ext)
     if not entry_point_path.exists():
         raise FileNotFoundError(
             f'Could not find provided entry data under path: >>{entry_point_path}<<'

src/lang_main/pipelines/predefined.py

@@ -1,3 +1,5 @@
+from pathlib import Path
+
 from lang_main.analysis import graphs
 from lang_main.analysis.preprocessing import (
     analyse_feature,
@@ -168,37 +170,75 @@ def build_tk_graph_post_pipe() -> Pipeline:
     return pipe_graph_postprocessing
 
 
-def build_tk_graph_rescaling_pipe() -> Pipeline:
+def build_tk_graph_rescaling_pipe(
+    save_result: bool,
+    exit_point: EntryPoints,
+) -> Pipeline:
     pipe_graph_rescaling = Pipeline(name='Graph_Rescaling', working_dir=SAVE_PATH_FOLDER)
     pipe_graph_rescaling.add(
         graphs.pipe_rescale_graph_edge_weights,
     )
     pipe_graph_rescaling.add(
         graphs.pipe_add_graph_metrics,
-        save_result=True,
+        save_result=save_result,
-        filename=EntryPoints.TK_GRAPH_ANALYSIS_RESCALED,
+        filename=exit_point,
+        # filename=EntryPoints.TK_GRAPH_ANALYSIS_RESCALED,
     )
 
     return pipe_graph_rescaling
 
 
 # ** token analysis: rendering
-def build_tk_graph_rendering_pipe() -> Pipeline:
+def build_tk_graph_render_pipe(
+    with_subgraphs: bool,
+    export_folder: Path = SAVE_PATH_FOLDER,
+    base_network_name: str = CYTO_BASE_NETWORK_NAME,
+) -> Pipeline:
     pipe_graph_rendering = Pipeline(
         name='Graph_Static-Rendering',
         working_dir=SAVE_PATH_FOLDER,
     )
-    pipe_graph_rendering.add(cyto.import_to_cytoscape)
+    pipe_graph_rendering.add(
-    pipe_graph_rendering.add(cyto.layout_network)
+        cyto.import_to_cytoscape,
-    pipe_graph_rendering.add(cyto.apply_style_to_network)
+        {
+            'network_name': base_network_name,
+        },
+    )
+    pipe_graph_rendering.add(
+        cyto.layout_network,
+        {
+            'network_name': base_network_name,
+        },
+    )
+    pipe_graph_rendering.add(
+        cyto.apply_style_to_network,
+        {
+            'network_name': base_network_name,
+        },
+    )
     pipe_graph_rendering.add(
         cyto.export_network_to_image,
-        {'filename': CYTO_BASE_NETWORK_NAME},
+        {
+            'filename': base_network_name,
+            'target_folder': export_folder,
+            'network_name': base_network_name,
+        },
+    )
+
+    if with_subgraphs:
+        pipe_graph_rendering.add(
+            cyto.get_subgraph_node_selection,
+            {
+                'network_name': base_network_name,
+            },
         )
-    pipe_graph_rendering.add(cyto.get_subgraph_node_selection)
         pipe_graph_rendering.add(
             cyto.build_subnetworks,
-        {'export_image': True},
+            {
+                'export_image': True,
+                'target_folder': export_folder,
+                'network_name': base_network_name,
+            },
         )
 
     return pipe_graph_rendering

src/lang_main/render/cytoscape.py

@@ -1,7 +1,7 @@
 import time
 from collections.abc import Iterable
 from pathlib import Path
-from typing import cast
+from typing import Literal, cast
 
 import py4cytoscape as p4c
 from networkx import DiGraph, Graph
@@ -55,6 +55,7 @@ def verify_connection():
 
 def import_to_cytoscape(
     graph: DiGraph | Graph,
+    network_name: str = CYTO_BASE_NETWORK_NAME,
 ) -> None:
     """Cytoscape: import NetworkX graph as new network collection
 
@@ -65,15 +66,49 @@ def import_to_cytoscape(
     """
     logger.debug('Checking Cytoscape connection...')
     verify_connection()
-    logger.debug('Importing network to Cytoscape...')
+    logger.debug('Importing to and analysing network in Cytoscape...')
     p4c.delete_all_networks()
     p4c.create_network_from_networkx(
         graph,
-        title=CYTO_BASE_NETWORK_NAME,
+        title=network_name,
         collection=CYTO_COLLECTION_NAME,
     )
+    analyse_network(network_name=network_name)
+    logger.debug('Import and analysis of network to Cytoscape successful.')
+
+
+def verify_table_property(
+    property: str,
+    table_type: Literal['node', 'edge', 'network'] = 'node',
+    network_name: str = CYTO_BASE_NETWORK_NAME,
+) -> bool:
+    table = p4c.get_table_columns(table=table_type, network=network_name)
+
+    return property in table.columns
+
+
+def analyse_network(
+    property_degree_weighted: str = PROPERTY_NAME_DEGREE_WEIGHTED,
+    network_name: str = CYTO_BASE_NETWORK_NAME,
+) -> None:
+    node_table = p4c.get_table_columns(table='node', network=network_name)
+    net_analyse_possible: bool = True
+    if len(node_table) < 4:
+        net_analyse_possible = False
+
+    if net_analyse_possible:
         p4c.analyze_network(directed=False)
-    logger.debug('Importing network to Cytoscape successful.')
+        node_table = p4c.get_table_columns(table='node', network=network_name)
+        node_table['stress_norm'] = node_table['Stress'] / node_table['Stress'].max()
+        node_table[CYTO_SELECTION_PROPERTY] = (
+            node_table[property_degree_weighted]
+            * node_table['BetweennessCentrality']
+            * node_table['stress_norm']
+        )
+    else:
+        node_table[CYTO_SELECTION_PROPERTY] = 1
+
+    p4c.load_table_data(node_table, data_key_column='name', network=network_name)
 
 
 def reset_current_network_to_base() -> None:
@@ -83,6 +118,7 @@ def reset_current_network_to_base() -> None:
 
 def export_network_to_image(
     filename: str,
+    target_folder: Path = SAVE_PATH_FOLDER,
     filetype: CytoExportFileTypes = 'SVG',
     network_name: str = CYTO_BASE_NETWORK_NAME,
     pdf_export_page_size: CytoExportPageSizes = 'A4',
@@ -102,7 +138,6 @@ def export_network_to_image(
         by default 'A4'
     """
     logger.debug('Exporting image to file...')
-    target_folder = SAVE_PATH_FOLDER
     if not target_folder.exists():
         target_folder.mkdir(parents=True)
     file_pth = target_folder / filename
@@ -138,7 +173,8 @@ def layout_network(
         necessarily match the name in the Cytoscape UI),
         by default CYTO_LAYOUT_NAME
     layout_properties : CytoLayoutProperties, optional
-        configuration of parameters for the given layout algorithm, by default CYTO_LAYOUT_PROPERTIES
+        configuration of parameters for the given layout algorithm,
+        by default CYTO_LAYOUT_PROPERTIES
     network_name : str, optional
         network to apply the layout algorithm on, by default CYTO_BASE_NETWORK_NAME
     """
@@ -153,6 +189,9 @@ def apply_style_to_network(
     style_name: str = CYTO_STYLESHEET_NAME,
     pth_to_stylesheet: Path = CYTO_PATH_STYLESHEET,
     network_name: str = CYTO_BASE_NETWORK_NAME,
+    node_size_property: str = 'node_selection',
+    min_node_size: int = 15,
+    max_node_size: int = 40,
 ) -> None:
     """Cytoscape: apply a chosen Cytoscape style to the defined network
 
@@ -185,14 +224,36 @@ def apply_style_to_network(
         p4c.import_visual_styles(str(pth_to_stylesheet))
 
     p4c.set_visual_style(style_name, network=network_name)
-    time.sleep(1)  # if not waited image export could be without applied style
+    # node size mapping, only if needed property is available
+    # TODO check removal
+    # size_prop_available = verify_table_property(
+    #     property=node_size_property,
+    #     network_name=network_name,
+    # )
+    # if size_prop_available:
+    scheme = p4c.scheme_c_number_continuous(
+        start_value=min_node_size, end_value=max_node_size
+    )
+    node_size_map = p4c.gen_node_size_map(
+        node_size_property,
+        number_scheme=scheme,
+        mapping_type='c',
+        style_name='lang_main',
+        default_number=min_node_size,
+    )
+    p4c.set_node_size_mapping(**node_size_map)
+    # else:
+    #     node_table = p4c.get_table_columns(table='node', network=network_name)
+    #     nodes_SUID = node_table['SUID'].to_list()
+    #     p4c.set_node_size_bypass(nodes_SUID, new_sizes=min_node_size, network=network_name)
+    # p4c.set_visual_style(style_name, network=network_name)
+    # time.sleep(1)  # if not waited image export could be without applied style
     p4c.fit_content(selected_only=False, network=network_name)
     logger.debug('Style application to network successful.')
 
 
 def get_subgraph_node_selection(
     network_name: str = CYTO_BASE_NETWORK_NAME,
-    property_degree_weighted: str = PROPERTY_NAME_DEGREE_WEIGHTED,
     num_subgraphs: int = CYTO_NUMBER_SUBGRAPHS,
 ) -> list[CytoNodeID]:
     """Cytoscape: obtain the relevant nodes for iterative subgraph generation
@@ -214,14 +275,9 @@ def get_subgraph_node_selection(
         list containing all relevant Cytoscape nodes
     """
     logger.debug('Selecting nodes for subgraph generation...')
-    node_table = p4c.get_table_columns(network=network_name)
+    node_table = p4c.get_table_columns(table='node', network=network_name)
-    node_table['stress_norm'] = node_table['Stress'] / node_table['Stress'].max()
-    node_table[CYTO_SELECTION_PROPERTY] = (
-        node_table[property_degree_weighted]
-        * node_table['BetweennessCentrality']
-        * node_table['stress_norm']
-    )
     node_table = node_table.sort_values(by=CYTO_SELECTION_PROPERTY, ascending=False)
+    p4c.load_table_data(node_table, data_key_column='name', network=network_name)
     node_table_choice = node_table.iloc[:num_subgraphs, :]
     logger.debug('Selection of nodes for subgraph generation successful.')
 
@@ -264,6 +320,7 @@ def make_subnetwork(
     index: int,
     network_name: str = CYTO_BASE_NETWORK_NAME,
     export_image: bool = True,
+    target_folder: Path = SAVE_PATH_FOLDER,
 ) -> None:
     """Cytoscape: generate a new subnetwork based on the currently
     selected nodes and edges
@@ -289,7 +346,11 @@ def make_subnetwork(
     p4c.fit_content(selected_only=False, network=subnetwork_name)
     if export_image:
         time.sleep(1)
-        export_network_to_image(filename=subnetwork_name, network_name=subnetwork_name)
+        export_network_to_image(
+            filename=subnetwork_name,
+            target_folder=target_folder,
+            network_name=subnetwork_name,
+        )
 
     logger.debug('Generation of subnetwork with index %d successful.', index)
 
@@ -298,6 +359,7 @@ def build_subnetworks(
     nodes_to_analyse: Iterable[CytoNodeID],
     network_name: str = CYTO_BASE_NETWORK_NAME,
     export_image: bool = True,
+    target_folder: Path = SAVE_PATH_FOLDER,
 ) -> None:
     """Cytoscape: iteratively build subnetworks from a collection of nodes
     and their respective neighbouring nodes
@@ -316,5 +378,10 @@ def build_subnetworks(
     logger.debug('Generating all subnetworks for node selection...')
     for idx, node in enumerate(nodes_to_analyse):
         select_neighbours_of_node(node=node, network_name=network_name)
-        make_subnetwork(index=idx, network_name=network_name, export_image=export_image)
+        make_subnetwork(
+            index=idx,
+            network_name=network_name,
+            export_image=export_image,
+            target_folder=target_folder,
+        )
     logger.debug('Generation of all subnetworks for node selection successful.')

src/lang_main/types.py

@@ -33,6 +33,7 @@ ResultHandling: TypeAlias = list[tuple[bool, str | None]]
 class EntryPoints(enum.StrEnum):
     TIMELINE = 'TIMELINE'
     TIMELINE_POST = 'TIMELINE_POSTPROCESSING'
+    TIMELINE_TK_GRAPH_RESCALED = 'TIMELINE_TK_GRAPH_RESCALED'
     TK_GRAPH_POST = 'TK-GRAPH_POSTPROCESSING'
     TK_GRAPH_ANALYSIS = 'TK-GRAPH_ANALYSIS'
     TK_GRAPH_ANALYSIS_RESCALED = 'TK-GRAPH_ANALYSIS_RESCALED'

test-notebooks/lang_main_config.toml

@@ -2,7 +2,7 @@
 
 [paths]
 inputs = './inputs/'
-results = './results/test_20240619/'
+results = '../scripts/results/test_20240619/'
 dataset = '../data/02_202307/Export4.csv'
 #results = './results/Export7/'
 #dataset = './01_03_Rohdaten_202403/Export7_59499_Zeilen.csv'