diff --git a/EP/Cora_node_classification/README.md b/EP/Cora_node_classification/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/EP/Cora_node_classification/cora.py b/EP/Cora_node_classification/cora.py
index cb8520a9592145f63bd5801d8436e15d58058cc1..a8cfc3c075d14c02a836e5b399ca3e811b1891c1 100644
--- a/EP/Cora_node_classification/cora.py
+++ b/EP/Cora_node_classification/cora.py
@@ -1,16 +1,16 @@
"""
+@info
Getting a networkx graph from Cora. Graph can be saved in txt file. CARE: numpy-arrays are converted to lists due to errors (NumPy array is not JSON serializable).
Initialize Embeddings for n dimensions with initialize-module.
Arrays are initialized in normal or uniform random format (default = normal).
-
-#Usage
-get_graph(path_nodes="/home/utaemon/SP/cora/cora.content", path_edges="/home/utaemon/SP/cora/cora.cites")
+@usage
+get_graph(path_nodes="/cora_data/cora.content", path_edges="/cora_data/cora.cites")
-> return graph with nodes and edges
To write the graph informations in file:
-def write_graph_to_file(path_nodes="/home/utaemon/SP/cora/cora.content", path_edges="/home/utaemon/SP/cora/cora.cites", path_output_graph = "/home/utaemon/SP/")
+def write_graph_to_file(path_nodes="/cora_data/cora.content", path_edges="/cora_data/cora.cites", path_output_graph = "")
To write the dictionary with initalizing Embeddings in file:
-def write_dict_to_file(rand_type="normal_random", dimension = 128, quantity=1433, path_output_emb = "/home/utaemon/SP/")
+def write_dict_to_file(rand_type="normal_random", dimension = 128, quantity=1433, path_output_emb = "")
"""
import networkx as nx
@@ -21,7 +21,7 @@ import pickle as pkl
def list_of_classes():
return ["Case_Based", "Genetic_Algorithms", "Neural_Networks", "Probabilistic_Methods", "Reinforcement_Learning", "Rule_Learning", "Theory"]
-def read_file_and_get_nodes(graph_name, path="/home/utaemon/SP/cora/cora.content"):
+def read_file_and_get_nodes(graph_name, path="/cora_data/cora.content"):
class_list = list_of_classes()
max_bow_len = 0
node_mapping = {}
@@ -49,7 +49,7 @@ def read_file_and_get_nodes(graph_name, path="/home/utaemon/SP/cora/cora.content
graph_name.graph["paper_id"] = {"maxlen": 1, "vocab": (len(graph_name)), "lengths": np.ones(len(graph_name))}
return node_mapping
-def read_file_and_get_edges(graph_name, node_mapping, path="/home/utaemon/SP/cora/cora.cites"):
+def read_file_and_get_edges(graph_name, node_mapping, path="/cora_data/cora.cites"):
with open(path) as file:
for line in file.readlines():
a, b = line.split()
@@ -114,12 +114,12 @@ def add_max_values_to_graph(path_nodes, path_edges): #update
def get_init_emb(rand_type="normal_random", dimension = 128, quantity=1433):
return initialize.get_embeddings(rand_type=rand_type, dimension = dimension, quantity=quantity)
-def write_pickle_graph_file(path_nodes="/home/utaemon/SP/cora/cora.content", path_edges="/home/utaemon/SP/cora/cora.cites", path_output_graph = "/home/utaemon/SP/"):
+def write_pickle_graph_file(path_nodes="/cora_data/cora.content", path_edges="/cora_data/cora.cites", path_output_graph = ""):
g = add_max_values_to_graph(path_nodes, path_edges)
with open(path_output_graph + "graph.pkl", "wb") as output:
pkl.dump(g, output)
-def read_pickle_graph(path = "/home/utaemon/SP/graph.pkl"):
+def read_pickle_graph(path = "graph.pkl"):
with open(path, 'rb') as f:
graph = pkl.load(f)
return graph
@@ -127,5 +127,5 @@ def read_pickle_graph(path = "/home/utaemon/SP/graph.pkl"):
if __name__ == "__main__":
# execute only if run as a script
- get_graph(path_nodes="/home/utaemon/SP/cora/cora.content", path_edges="/home/utaemon/SP/cora/cora.cites")
+ get_graph(path_nodes="/cora_data/cora.content", path_edges="/cora_data/cora.cites")
get_init_emb(rand_type="normal_random", dimension = 128, quantity=1433)
diff --git a/EP/Cora_node_classification/node_classification.py b/EP/Cora_node_classification/node_classification.py
index ee430ae94089cf105cb1e07d9c84362ba34358b1..1ab131557a918ca1caecbe2a294c4ac6fffa1cb8 100644
--- a/EP/Cora_node_classification/node_classification.py
+++ b/EP/Cora_node_classification/node_classification.py
@@ -4,6 +4,7 @@
@author: Utaemon Toyota
@date: 31.1.2019
@project: Software Projekt @ Heidelberg University, Institute for Computational Linguistics
+@requirements: cora.py and random_nodes_for_node_classification.py as well as the cora data
@usage: python3 node_classification.py [-g] [-e] [-s] [-i] [-n]
-g / --graph Path to pickled networkX-graph
-e / --embeddings Path to pickled embeddings
diff --git a/EP/Cora_node_classification/random_nodes_for_node_classification.py b/EP/Cora_node_classification/random_nodes_for_node_classification.py
index 59212b91ca26a340dae12ecbf094292a58793645..b4ae51dd2f2eb182d662b9733add75291a55c8a2 100644
--- a/EP/Cora_node_classification/random_nodes_for_node_classification.py
+++ b/EP/Cora_node_classification/random_nodes_for_node_classification.py
@@ -1,3 +1,9 @@
+"""
+@requirements: cora.py
+@info: Will be imported from node_classification.
+"""
+
+
import cora
import pickle as pkl
import random
@@ -21,7 +27,7 @@ def get_random_num_nodes(set_elm, num, seed):
random.seed(seed)
return set(random.sample(set_elm, num))
-def get_num_random_nodes_for_all_classes_read(path = "/home/utaemon/SP/graph.pkl", num = 20, seed = 1):
+def get_num_random_nodes_for_all_classes_read(path = "graph.pkl", num = 20, seed = 1):
"""get specific number of nodes per class, same number for all classes"""
cora_dict = dict_of_node_classes_read(path)
sampled_random_id_set = set()
@@ -29,17 +35,3 @@ def get_num_random_nodes_for_all_classes_read(path = "/home/utaemon/SP/graph.pkl
for id in get_random_num_nodes(cora_dict[key], num, seed):
sampled_random_id_set.add(id)
return sampled_random_id_set
-
-
-#unused
-'''
-def get_num_of_random_nodes(path = "/home/utaemon/SP/graph.pkl", seed=0, num = 3):
- """Get random nodes."""
- random.seed(seed)
- cora_nodes = set(read_graph(path).nodes)
- return set(random.sample(cora_nodes, num))
-
-def pickle_output(method = get_num_random_nodes_for_all_classes_read(), output = "random_nodes.pkl"):
- with open(output, "wb") as file:
- pkl.dump(method, file)
-'''
\ No newline at end of file
diff --git a/EP/cora_embeddings_2.pkl b/EP/cora_embeddings_2.pkl
deleted file mode 100644
index adaa623ac5ff1f21584b7675263c197f34443b58..0000000000000000000000000000000000000000
Binary files a/EP/cora_embeddings_2.pkl and /dev/null differ
diff --git a/EP/cora_embeddings_norm.pkl b/EP/cora_embeddings_norm.pkl
deleted file mode 100644
index 41e8144fb8472ca1fffa492e1593e6d334b8e8c8..0000000000000000000000000000000000000000
Binary files a/EP/cora_embeddings_norm.pkl and /dev/null differ
diff --git a/EP/node_classification_1000.txt b/EP/node_classification_1000.txt
deleted file mode 100644
index 795ab1dd26085081773fd854d5795d71b89c95d2..0000000000000000000000000000000000000000
--- a/EP/node_classification_1000.txt
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