Update docs and requirements

README.md

@@ -30,7 +30,7 @@ To install TCT as a python library:
 
 ```bash
 pip install TCT
-# TCT is in development, to get the most recent update, user can install it throught the github repo
+# TCT is in development, to get the most recent update, user can install it through the github repo
 ```
 
 **This the recommended approach for installation.**
@@ -90,8 +90,8 @@ API should be developed following the standard from [TRAPI](https://github.com/N
 An example notebook for add a user's API can be found [here](https://github.com/NCATSTranslator/Translator_component_toolkit/blob/main/notebooks/Connecting_userAPI.ipynb).<br>
 **Note: It does not work if no user' API is established**<br>
 
-### Visulize the results
-After each pipleline, it will generate a result file for visualization. A user can use **[the Visualization html](https://github.com/NCATSTranslator/Translator_component_toolkit/blob/main/notebooks/visulize_path_finder_results.html)** file to visulaize the results.
+### Visualize the results
+After each pipeline, it will generate a result file for visualization. A user can use **[the Visualization html](https://github.com/NCATSTranslator/Translator_component_toolkit/blob/main/notebooks/visulize_path_finder_results.html)** file to visulaize the results.
 
 ## Key Translator components
 Connecting to key Translator components can be found [here](https://github.com/NCATSTranslator/Translator_component_toolkit/blob/main/TranslatorComponentsIntroduction.md)

TCT/TCT.py

@@ -3,7 +3,6 @@
 import pandas as pd
 import  seaborn as sns
 import matplotlib.pyplot as plt
-import ipycytoscape
 import networkx as nx
 import numpy as np
 #import openai
@@ -1875,6 +1874,7 @@ def plot_graph_by_predicates(for_plot):
 
                     ]
 
+    import ipycytoscape
     undirected = ipycytoscape.CytoscapeWidget()
     undirected.graph.add_graph_from_networkx(graph)
     undirected.set_layout(title='Path', nodeSpacing=80, edgeLengthVal=50, )
@@ -1923,6 +1923,7 @@ def plot_graph_by_infores(for_plot):
 
                         ]
 
+    import ipycytoscape
     undirected = ipycytoscape.CytoscapeWidget()
     undirected.graph.add_graph_from_networkx(graph)
     undirected.set_layout(title='Path', nodeSpacing=80, edgeLengthVal=50, )
@@ -1971,6 +1972,7 @@ def plot_graph_by_API(for_plot):
 
                         ]
 
+    import ipycytoscape
     undirected = ipycytoscape.CytoscapeWidget()
     undirected.graph.add_graph_from_networkx(graph)
     undirected.set_layout(title='Path', nodeSpacing=80, edgeLengthVal=50, )
@@ -2258,6 +2260,7 @@ def visulize_path(input_node1_id, intermediate_node, input_node3_id, result, res
                         }},
 
                     ]
+    import ipycytoscape
     pathgraph = ipycytoscape.CytoscapeWidget()
     pathgraph.graph.add_graph_from_networkx(graph)
     pathgraph.set_layout(title='Path', nodeSpacing=80, edgeLengthVal=50, )

TCT/TCT_network_annotator.py

@@ -169,7 +169,7 @@ def network_annotator(gene_list,
 
 def get_connected_graph(result_parsed, input_identifiers):
     """
-    This function is used to extract the connected graph from the returned graph based on neiborhood finder from multiple inputs. 
+    This function is used to extract the connected graph from the returned graph based on neighborhood finder from multiple inputs. 
     It will only include the input nodes and the nodes that are connected to the input nodes with degree greater than 1. 
 
 
@@ -269,4 +269,4 @@ def get_connected_graph(result_parsed, input_identifiers):
         if key not in selected_nodes:
             del result_parsed_copy['knowledge_graph']['nodes'][key]
 
-    return result_parsed_copy
+    return result_parsed_copy

docs/source/index.rst

@@ -22,6 +22,7 @@ Welcome to Translator Component Toolkit's documentation!
    neighborhood
    pathfinder
    network_annotator
+   node_annotator
 
 Indices and tables
 ==================

pyproject.toml

@@ -37,7 +37,6 @@ dependencies = [
     'igraph',
     'pyvis',
     'zstandard',
-    'copy'
 ]
 
 [project.scripts]