Merge pull request #6 from Grid-FM/test/pre-commits

Solved pre-commit checks

Author: MatteoMazzonelli

.pre-commit-config.yaml

@@ -6,47 +6,21 @@ repos:
     -   id: end-of-file-fixer
     -   id: check-yaml
     -   id: debug-statements
-    -   id: double-quote-string-fixer
-    -   id: name-tests-test
-    -   id: requirements-txt-fixer
 - repo: https://github.com/astral-sh/ruff-pre-commit
   rev: v0.12.0
   hooks:
     - id: ruff-check
     - id: ruff-format
--   repo: https://github.com/asottile/setup-cfg-fmt
-    rev: v2.8.0
-    hooks:
-    -   id: setup-cfg-fmt
--   repo: https://github.com/asottile/reorder-python-imports
-    rev: v3.15.0
-    hooks:
-    -   id: reorder-python-imports
-        args: [--py39-plus, --add-import, 'from __future__ import annotations']
--   repo: https://github.com/asottile/add-trailing-comma
-    rev: v3.2.0
-    hooks:
-    -   id: add-trailing-comma
--   repo: https://github.com/asottile/pyupgrade
-    rev: v3.20.0
-    hooks:
-    -   id: pyupgrade
-        args: [--py39-plus]
--   repo: https://github.com/hhatto/autopep8
-    rev: v2.3.2
-    hooks:
-    -   id: autopep8
 -   repo: https://github.com/PyCQA/flake8
     rev: 7.2.0
     hooks:
     -   id: flake8
--   repo: https://github.com/pre-commit/mirrors-mypy
-    rev: v1.16.0
+        args: ["--ignore=E501,W503,E203"]
+-   repo: https://github.com/asottile/add-trailing-comma
+    rev: v3.2.0
     hooks:
-    -   id: mypy
-
+    -   id: add-trailing-comma
 -   repo: https://github.com/ibm/detect-secrets
-
     rev: 0.13.1+ibm.62.dss
     hooks:
         - id: detect-secrets # pragma: whitelist secret

README.md

@@ -110,5 +110,3 @@ python eval.py --config config/case300_ieee_base.yaml --eval_name eval_case300 -
 - **Outputs:**
   - Evaluation results are saved in MLflow.
   - Optional plots are stored as **HTML** files
-
-

docs/datasets/data_normalization.md

@@ -2,12 +2,12 @@
 
 
 
-Normalization improves neural network training by ensuring features are well-scaled, preventing issues like exploding gradients and slow convergence. In power grids, where variables like voltage and power span wide ranges, normalization is essential.  
+Normalization improves neural network training by ensuring features are well-scaled, preventing issues like exploding gradients and slow convergence. In power grids, where variables like voltage and power span wide ranges, normalization is essential.
 The `gridFM` package offers four methods:
 
-- [`Min-Max Normalization`](#minmaxnormalizer)  
-- [`Standardization (Z-score)`](#standardizer)  
-- [`Identity (no normalization)`](#identitynormalizer)  
+- [`Min-Max Normalization`](#minmaxnormalizer)
+- [`Standardization (Z-score)`](#standardizer)
+- [`Identity (no normalization)`](#identitynormalizer)
 - [`BaseMVA Normalization`](#basemvanormalizer)
 
 Each of these strategies implements a unified interface and can be used interchangeably depending on the learning task and data characteristics.
@@ -27,7 +27,7 @@ Each of these strategies implements a unified interface and can be used intercha
 
 ### `MinMaxNormalizer`
 
-::: gridFM.datasets.data_normalization.MinMaxNormalizer 
+::: gridFM.datasets.data_normalization.MinMaxNormalizer
 
 ---
 
@@ -63,4 +63,4 @@ normalizer = MinMaxNormalizer()
 params = normalizer.fit(data)
 normalized = normalizer.transform(data)
 restored = normalizer.inverse_transform(normalized)
-```
+```

docs/datasets/powergrid.md

@@ -11,7 +11,7 @@ from gridFM.datasets.powergrid import GridDatasetMem
 dataset = GridDatasetMem(
     root="./data",
     norm_method="identity",
-    node_normalizer=IdentityNormalizer(), 
+    node_normalizer=IdentityNormalizer(),
     edge_normalizer=IdentityNormalizer(),
     pe_dim=10,
     mask_dim=6,

docs/datasets/transforms.md

@@ -6,7 +6,7 @@
 
 ::: gridFM.datasets.transforms.AddNormalizedRandomWalkPE
 
-### `AddEdgeWeights` 
+### `AddEdgeWeights`
 
 ::: gridFM.datasets.transforms.AddEdgeWeights
 
@@ -23,5 +23,5 @@
 ::: gridFM.datasets.transforms.AddPFMask
 
 ### `AddOPFMask`
- 
-::: gridFM.datasets.transforms.AddOPFMask
+
+::: gridFM.datasets.transforms.AddOPFMask

docs/examples/fine_tuning.md

@@ -1 +1 @@
-# GridFM Fine-Tuning workflow
+# GridFM Fine-Tuning workflow

docs/examples/inference.md

@@ -1 +1 @@
-# GridFM Inference workflow
+# GridFM Inference workflow

docs/index.md

@@ -5,4 +5,4 @@
 <p align="center">
   <img src="figs/pre_training.png" alt="GridFM logo"/>
   <br/>
-</p>
+</p>

docs/install/installation.md

@@ -10,4 +10,4 @@ Install the package in editable mode during development phase:
 
 ```bash
 pip install -e .
-```
+```

docs/javascripts/katex.js

@@ -7,4 +7,4 @@ document$.subscribe(({ body }) => {
             { left: "\\[", right: "\\]", display: true }
         ],
     })
-})
+})