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Removed docstring ruins. (#367)
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@ -143,7 +143,7 @@ class CompanyMongoService:
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company (Company): _description_
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Returns:
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_type_: _description_
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_description_
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"""
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with self.lock:
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return self.collection.insert_one(company.to_dict())
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@ -18,17 +18,17 @@ def create_2d_graph( # noqa PLR0913
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"""This Method creates a 2d Network in Plotly with a Scatter Graph and retuns it.
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Args:
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graph (_type_): NetworkX Graph.
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nodes (_type_): List of Nodes
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edges (_type_): List of Edges
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metrics (_type_): DataFrame with the MEtrics
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metric (_type_): Selected Metric
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graph: NetworkX Graph.
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nodes: List of Nodes
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edges: List of Edges
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metrics: DataFrame with the Metrics
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metric: Selected Metric
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edge_annotation: Enables the Description of Edges
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edge_thickness: Int Value of the Edge thickness
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layout: String which defines the Graph Layout
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Returns:
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_type_: Plotly Figure
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Plotly Figure
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"""
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# Set 2D Layout
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pos = nx.spring_layout(graph)
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@ -87,7 +87,7 @@ def create_2d_graph( # noqa PLR0913
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hoverinfo="none",
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mode="lines",
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)
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# Add the Edgedescriptiontext to the scatter plot according to its Position.
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# Add the Edge description text to the scatter plot according to its Position.
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edge_weights_trace = go.Scatter(
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x=edge_weight_x,
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y=edge_weight_y,
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@ -144,7 +144,7 @@ def create_2d_graph( # noqa PLR0913
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node_trace.marker.color = colors
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node_trace.text = node_names
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# Highlight the Node Size in regards to the selected Metric.
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# Highlight the Node Size with regard to the selected Metric.
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if metric != "None":
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node_trace.marker.size = list(np.sqrt(metrics[metric]) * 200)
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@ -25,7 +25,7 @@ def create_3d_graph( # noqa : PLR0913
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metric: Selected Metric
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Returns:
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_type_: Plotly Figure
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Plotly Figure
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"""
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# 3d spring layout
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pos = nx.spring_layout(graph, dim=3)
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@ -173,7 +173,7 @@ def create_edge_and_node_list(
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company_relations (pd.DataFrame): _description_
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Returns:
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_type_: _description_
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_description_
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"""
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nodes: dict = {}
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edges: list = []
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@ -296,7 +296,7 @@ def create_edge_and_node_list_for_company(
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company_relations (pd.DataFrame): _description_
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Returns:
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_type_: _description_
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_description_
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"""
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nodes: dict = {}
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edges: list = []
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