Feat/0.5.1

CONTRIBUTING.md

@@ -0,0 +1,17 @@
+# Contributing Guidelines
+
+- Fork the repo.
+- Install env with `python>=3.7`, e.g., for linux run:
+
+```bash
+# install python 3.7.16, e.g, if using pyenv run:
+# pyenv install 3.7.16
+# pyenv local 3.7.16
+$ bash .ci/install-dev.sh
+$ bash .ci/install.sh
+
+# activate env:-
+$ activate .venv/bin/activate
+```
+
+- Modify the code, commit the changes and create a PR.

README.md

@@ -8,6 +8,11 @@
 
 ## Installation
 
+- python>=3.7
+- torch>=1.12
+- torch_geometric>=2.0
+- dgl>=1.1
+
 ```bash
 $ python -m pip install graph_datasets
 ```
@@ -44,21 +49,6 @@ $ nohup bash scripts/install.sh > logs/install.log &
 
 <!-- Statistics begins -->
 
-## Contribution
-- Fork the repo.
-- Install env with `python>=3.7`. For linux run:
-```bash
-# install python 3.7.16, e.g, if using pyenv run:
-# pyenv install 3.7.16
-# pyenv local 3.7.16
-bash .ci/install-dev.sh
-bash .ci/install.sh
-
-# activate env:-
-activate .venv/bin/activate
-```
-- Modify the code, commit the changes and create a PR.
-
 ## Statistics
 |   idx | source   | dataset         | n_nodes   | n_feats   | n_edges     |   n_clusters |
 |------:|:---------|:----------------|:----------|:----------|:------------|-------------:|
@@ -124,3 +114,7 @@ activate .venv/bin/activate
 ## Requirements
 
 See [requirements-dev.txt](./requirements-dev.txt) and [requirements.txt](./requirements.txt).
+
+## Contributing
+
+See [CONTRIBUTING.md](./CONTRIBUTING.md).

docs/rst/graph_datasets.utils.rst

@@ -1,38 +1,35 @@
-utils
-======================
-
 evaluation
-------------
+======================
 .. automodule:: graph_datasets.utils.evaluation.evaluation
    :members:
    :show-inheritance:
-   :exclude-members:
+   :exclude-members: save_to_csv_files
    :no-undoc-members:
 
 statistics
-------------
+======================
 .. automodule:: graph_datasets.utils.statistics
    :members:
    :show-inheritance:
    :exclude-members: get_long_edges, get_same_class_deg
    :no-undoc-members:
 
 model management
------------------
+======================
 .. automodule:: graph_datasets.utils.model_management
    :members:
    :show-inheritance:
    :no-undoc-members:
 
 output
--------
+======================
 .. automodule:: graph_datasets.utils.output
    :members:
    :show-inheritance:
    :no-undoc-members:
 
 common
--------
+======================
 .. automodule:: graph_datasets.utils.common
    :members:
    :show-inheritance:

docs/rst/table.rst

@@ -1,4 +1,4 @@
-statistics
+dataset cheatsheet
 ===========
 +-----+----------+-------------+-----------+---------+------------+------------+
 | idx |  source  |   dataset   |  n_nodes  | n_feats |  n_edges   | n_clusters |

graph_datasets/datasets/critical.py

@@ -36,7 +36,8 @@ def load_critical_dataset(
     Returns:
         Tuple[dgl.DGLGraph, torch.Tensor, int]: [graph, label, n_clusters]
     """
-    data_file = os.path.join(directory, f"{dataset_name.replace('-','_')}.npz")
+    dataset_name = dataset_name.replace("-", "_")
+    data_file = os.path.join(directory, f"{dataset_name}.npz")
 
     if not os.path.exists(data_file):
         url = f"{CRITICAL_URL}/{dataset_name}.npz?raw=true"

graph_datasets/utils/__init__.py

@@ -3,7 +3,6 @@
 # pylint:disable=invalid-name
 from .common import *
 from .evaluation import evaluate_from_embed_file
-from .evaluation import save_to_csv_files
 from .model_management import check_modelfile_exists
 from .model_management import get_modelfile_path
 from .model_management import load_model
@@ -13,6 +12,7 @@
 from .output import csv2file
 from .output import make_parent_dirs
 from .output import refresh_file
+from .output import save_to_csv_files
 from .statistics import edge_homo
 from .statistics import node_homo
 from .statistics import statistics

graph_datasets/utils/evaluation/__init__.py

@@ -1,4 +1,3 @@
 """Evalutaion
 """
 from .evaluation import evaluate_from_embed_file
-from .evaluation import save_to_csv_files

graph_datasets/utils/evaluation/evaluation.py

@@ -7,7 +7,6 @@
 
 import torch
 
-from ..output import csv2file
 from .eval_tools import evaluate_results_nc
 
 
@@ -44,12 +43,12 @@ def evaluate_from_embed_file(
     Example:
         .. code-block:: python
 
-            from graph_datasets import evaluate_embed_file
+            from graph_datasets import evaluate_from_embed_file
 
             method_name='orderedgnn'
             data_name='texas'
 
-            clustering_res, classification_res = evaluate_embed_file(
+            clustering_res, classification_res = evaluate_from_embed_file(
                 f'{data_name}_{method_name}_embeds.pth',
                 f'{data_name}_data.pth',
                 save_path='./save/',
@@ -102,52 +101,6 @@ def evaluate_from_embed_file(
     return clustering_results, classification_results
 
 
-def save_to_csv_files(
-    results: dict,
-    add_info: dict,
-    csv_name: str,
-    save_path="./results",
-):
-    """Save the evaluation results to a local csv file.
-
-    Args:
-        results (dict): Evaluation results document.
-        add_info (dict): Additional information, such as data set name, method name.
-        csv_name (str): csv file name to store.
-        save_path (str, optional): Folder path to store. Defaults to './results'.
-
-    Example:
-        .. code-block:: python
-
-            from graph_datasets import evaluate_embed_file
-            from graph_datasets import save_to_csv_files
-
-            method_name='orderedgnn'
-            data_name='texas'
-
-            clustering_res, classification_res = evaluate_embed_file(
-                f'{data_name}_{method_name}_embeds.pth',
-                f'{data_name}_data.pth',
-                save_path='./save/',
-            )
-
-            add_info = {'data': data_name, 'method': method_name,}
-            save_to_csv_files(clustering_res, add_info, 'clutering.csv')
-            save_to_csv_files(classification_res, add_info, 'classification.csv')
-    """
-    # save to csv file
-    results.update(add_info)
-
-    # list of values
-    csv2file(
-        target_path=os.path.join(save_path, csv_name),
-        thead=list(results.keys()),
-        tbody=list(results.values()),
-        refresh=False,
-        is_dict=False,
-    )
-
-
 # if __name__ == "__main__":
 #     method_name = 'orderedgnn'  # 'selene' 'greet' 'hgrl' 'nwr-gae' 'orderedgnn'
 #     data_name = 'texas'  # 'actor' 'chameleon' 'cornell' 'squirrel' 'texas' 'wisconsin'
@@ -159,7 +112,7 @@ def save_to_csv_files(
 #         save_path='/data/gnn/heter/save/',
 #         quiet=True,
 #     )
-#     from graph_datasets.utils import tab_printer
+#     from graph_datasets.utils import tab_printer, save_to_csv_files
 #     tab_printer(clu_res, sort=False)
 #     tab_printer(cls_res, sort=False)
 

graph_datasets/utils/output.py

@@ -104,3 +104,49 @@ def csv2file(
                     dict_writer.writerow(elem)
             else:
                 csv_write.writerow(tbody)
+
+
+def save_to_csv_files(
+    results: dict,
+    add_info: dict,
+    csv_name: str,
+    save_path="./results",
+) -> None:
+    """Save the evaluation results to a local csv file.
+
+    Args:
+        results (dict): Evaluation results document.
+        add_info (dict): Additional information, such as data set name, method name.
+        csv_name (str): csv file name to store.
+        save_path (str, optional): Folder path to store. Defaults to './results'.
+
+    Example:
+        .. code-block:: python
+
+            from graph_datasets import evaluate_from_embed_file
+            from graph_datasets import save_to_csv_files
+
+            method_name='orderedgnn'
+            data_name='texas'
+
+            clustering_res, classification_res = evaluate_from_embed_file(
+                f'{data_name}_{method_name}_embeds.pth',
+                f'{data_name}_data.pth',
+                save_path='./save/',
+            )
+
+            add_info = {'data': data_name, 'method': method_name,}
+            save_to_csv_files(clustering_res, add_info, 'clutering.csv')
+            save_to_csv_files(classification_res, add_info, 'classification.csv')
+    """
+    # save to csv file
+    results.update(add_info)
+
+    # list of values
+    csv2file(
+        target_path=os.path.join(save_path, csv_name),
+        thead=list(results.keys()),
+        tbody=list(results.values()),
+        refresh=False,
+        is_dict=False,
+    )

pyproject.toml

@@ -17,8 +17,8 @@ classifiers = [
     "Topic :: Software Development :: Libraries :: Python Modules",
 ]
 dependencies = [
-    "torch>=1.10.2",
-    "torch-geometric>=2.0.3",
+    "torch>=1.12",
+    "torch-geometric>=2.0",
     "torchaudio>=0.10.2",
     "torchvision>=0.11.3",
     "dgl>=1.1.0",