Updated readmes with notebooks

EBjerrum · Apr 12, 2024 · a10998f · a10998f
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diff --git a/README.md b/README.md
@@ -1,11 +1,13 @@
 # scikit-mol
+
 ![Fancy logo](./ressources/logo/ScikitMol_Logo_DarkBG_300px.png#gh-dark-mode-only)
 ![Fancy logo](./ressources/logo/ScikitMol_Logo_LightBG_300px.png#gh-light-mode-only)
+
 ## Scikit-Learn classes for molecular vectorization using RDKit
 
 The intended usage is to be able to add molecular vectorization directly into scikit-learn pipelines, so that the final model directly predict on RDKit molecules or SMILES strings
 
-As example with the needed scikit-learn and -mol imports and RDKit mol objects in the mol_list_train and _test lists:
+As example with the needed scikit-learn and -mol imports and RDKit mol objects in the mol_list_train and \_test lists:
 
     pipe = Pipeline([('mol_transformer', MorganFingerprintTransformer()), ('Regressor', Ridge())])
     pipe.fit(mol_list_train, y_train)
@@ -18,39 +20,40 @@ The scikit-learn compatibility should also make it easier to include the fingerp
 
 The first draft for the project was created at the [RDKIT UGM 2022 hackathon](https://github.com/rdkit/UGM_2022) 2022-October-14
 
-
 ## Implemented
-* Descriptors
-    * MolecularDescriptorTransformer
+
+- Descriptors
+  - MolecularDescriptorTransformer
 
 <br>
 
-* Fingerprints
-    * MorganFingerprintTransformer
-    * MACCSKeysFingerprintTransformer
-    * RDKitFingerprintTransformer
-    * AtomPairFingerprintTransformer
-    * TopologicalTorsionFingerprintTransformer
-    * MHFingerprintTransformer
-    * SECFingerprintTransformer
-    * AvalonFingerprintTransformer
+- Fingerprints
+  - MorganFingerprintTransformer
+  - MACCSKeysFingerprintTransformer
+  - RDKitFingerprintTransformer
+  - AtomPairFingerprintTransformer
+  - TopologicalTorsionFingerprintTransformer
+  - MHFingerprintTransformer
+  - SECFingerprintTransformer
+  - AvalonFingerprintTransformer
 
 <br>
 
-* Conversions
-    * SmilesToMol
+- Conversions
+  - SmilesToMol
 
 <br>
 
-* Standardizer
-    * Standardizer
+- Standardizer
+  - Standardizer
 
 <br>
 
-* Utilities
-    * CheckSmilesSanitazion
+- Utilities
+  - CheckSmilesSanitazion
 
 ## Installation
+
 Users can install latest tagged release from pip
 
     pip install scikit-mol
@@ -63,35 +66,37 @@ Bleeding edge
 
 There are a collection of notebooks in the notebooks directory which demonstrates some different aspects and use cases
 
-* [Basic Usage and fingerprint transformers](https://github.com/EBjerrum/scikit-mol/blob/main/notebooks/01_basic_usage.ipynb)
-* [Descriptor transformer](https://github.com/EBjerrum/scikit-mol/blob/main/notebooks/02_descriptor_transformer.ipynb)
-* [Pipelining with Scikit-Learn classes](https://github.com/EBjerrum/scikit-mol/blob/main/notebooks/03_example_pipeline.ipynb)
-* [Molecular standardization](https://github.com/EBjerrum/scikit-mol/blob/main/notebooks/04_standardizer.ipynb)
-* [Sanitizing SMILES input](https://github.com/EBjerrum/scikit-mol/blob/main/notebooks/05_smiles_sanitaztion.ipynb)
-* [Integrated hyperparameter tuning of Scikit-Learn estimator and Scikit-Mol transformer](https://github.com/EBjerrum/scikit-mol/blob/main/notebooks/06_hyperparameter_tuning.ipynb)
-* [Using parallel execution to speed up descriptor and fingerprint calculations](https://github.com/EBjerrum/scikit-mol/blob/main/notebooks/07_parallel_transforms.ipynb)
-* [Testing different fingerprints as part of the hyperparameter optimization](https://github.com/EBjerrum/scikit-mol/blob/main/notebooks/09_Combinatorial_Method_Usage_with_FingerPrint_Transformers.ipynb)
-* [Using pandas output for easy feature importance analysis and combine pre-exisitng values with new computations](https://github.com/EBjerrum/scikit-mol/blob/main/notebooks/10_pipeline_pandas_output.ipynb)
-
+- [Basic Usage and fingerprint transformers](https://github.com/EBjerrum/scikit-mol/tree/main/notebooks/01_basic_usage.ipynb)
+- [Descriptor transformer](https://github.com/EBjerrum/scikit-mol/tree/main/notebooks/02_descriptor_transformer.ipynb)
+- [Pipelining with Scikit-Learn classes](https://github.com/EBjerrum/scikit-mol/tree/main/notebooks/03_example_pipeline.ipynb)
+- [Molecular standardization](https://github.com/EBjerrum/scikit-mol/tree/main/notebooks/04_standardizer.ipynb)
+- [Sanitizing SMILES input](https://github.com/EBjerrum/scikit-mol/tree/main/notebooks/05_smiles_sanitaztion.ipynb)
+- [Integrated hyperparameter tuning of Scikit-Learn estimator and Scikit-Mol transformer](https://github.com/EBjerrum/scikit-mol/tree/main/notebooks/06_hyperparameter_tuning.ipynb)
+- [Using parallel execution to speed up descriptor and fingerprint calculations](https://github.com/EBjerrum/scikit-mol/tree/main/notebooks/07_parallel_transforms.ipynb)
+- [Using skopt for hyperparameter tuning](https://github.com/EBjerrum/scikit-mol/tree/main/notebooks/08_external_library_skopt.ipynb)
+- [Testing different fingerprints as part of the hyperparameter optimization](https://github.com/EBjerrum/scikit-mol/blob/main/notebooks/09_Combinatorial_Method_Usage_with_FingerPrint_Transformers.ipynb)
+- [Using pandas output for easy feature importance analysis and combine pre-exisitng values with new computations](https://github.com/EBjerrum/scikit-mol/blob/main/notebooks/10_pipeline_pandas_output.ipynb)
 
-  We also put a software note on ChemRxiv. [https://doi.org/10.26434/chemrxiv-2023-fzqwd](https://doi.org/10.26434/chemrxiv-2023-fzqwd) 
+  We also put a software note on ChemRxiv. [https://doi.org/10.26434/chemrxiv-2023-fzqwd](https://doi.org/10.26434/chemrxiv-2023-fzqwd)
 
 ## Contributing
 
 There are more information about how to contribute to the project in [CONTRIBUTION.md](https://github.com/EBjerrum/scikit-mol/CONTRIBUTION.md)
 
 ## BUGS
+
 Probably still, please check issues at GitHub and report there
 
 ## Contributers:
-* Esben Jannik Bjerrum [@ebjerrum](https://github.com/ebjerrum), esbenbjerrum+scikit_mol@gmail.com
-* Carmen Esposito [@cespos](https://github.com/cespos)
-* Son Ha, sonha@uni-mainz.de
-* Oh-hyeon Choung, ohhyeon.choung@gmail.com
-* Andreas Poehlmann, [@ap--](https://github.com/ap--)
-* Ya Chen, [@anya-chen](https://github.com/anya-chen)
-* Rafał Bachorz [@rafalbachorz](https://github.com/rafalbachorz)
-* Adrien Chaton [@adrienchaton](https://github.com/adrienchaton)
-* [@VincentAlexanderScholz](https://github.com/VincentAlexanderScholz)
-* [@RiesBen](https://github.com/RiesBen)
-* [@enricogandini](https://github.com/enricogandini)
+
+- Esben Jannik Bjerrum [@ebjerrum](https://github.com/ebjerrum), esbenbjerrum+scikit_mol@gmail.com
+- Carmen Esposito [@cespos](https://github.com/cespos)
+- Son Ha, sonha@uni-mainz.de
+- Oh-hyeon Choung, ohhyeon.choung@gmail.com
+- Andreas Poehlmann, [@ap--](https://github.com/ap--)
+- Ya Chen, [@anya-chen](https://github.com/anya-chen)
+- Rafał Bachorz [@rafalbachorz](https://github.com/rafalbachorz)
+- Adrien Chaton [@adrienchaton](https://github.com/adrienchaton)
+- [@VincentAlexanderScholz](https://github.com/VincentAlexanderScholz)
+- [@RiesBen](https://github.com/RiesBen)
+- [@enricogandini](https://github.com/enricogandini)
diff --git a/notebooks/README.md b/notebooks/README.md
@@ -4,12 +4,13 @@
 
 This is a collection of notebooks in the notebooks directory which demonstrates some different aspects and use cases
 
-* [Basic Usage and fingerprint transformers](https://github.com/EBjerrum/scikit-mol/tree/main/notebooks/01_basic_usage.ipynb)
-* [Descriptor transformer](https://github.com/EBjerrum/scikit-mol/tree/main/notebooks/02_descriptor_transformer.ipynb)
-* [Pipelining with Scikit-Learn classes](https://github.com/EBjerrum/scikit-mol/tree/main/notebooks/03_example_pipeline.ipynb)
-* [Molecular standardization](https://github.com/EBjerrum/scikit-mol/tree/main/notebooks/04_standardizer.ipynb)
-* [Sanitizing SMILES input](https://github.com/EBjerrum/scikit-mol/tree/main/notebooks/05_smiles_sanitaztion.ipynb)
-* [Integrated hyperparameter tuning of Scikit-Learn estimator and Scikit-Mol transformer](https://github.com/EBjerrum/scikit-mol/tree/main/notebooks/06_hyperparameter_tuning.ipynb)
-* [Using parallel execution to speed up descriptor and fingerprint calculations](https://github.com/EBjerrum/scikit-mol/tree/main/notebooks/07_parallel_transforms.ipynb)
-* [Testing different fingerprints as part of the hyperparameter optimization](https://github.com/EBjerrum/scikit-mol/blob/main/notebooks/09_Combinatorial_Method_Usage_with_FingerPrint_Transformers.ipynb)
-* [Using pandas output for easy feature importance analysis and combine pre-exisitng values with new computations](https://github.com/EBjerrum/scikit-mol/blob/main/notebooks/10_pipeline_pandas_output.ipynb)
+- [Basic Usage and fingerprint transformers](https://github.com/EBjerrum/scikit-mol/tree/main/notebooks/01_basic_usage.ipynb)
+- [Descriptor transformer](https://github.com/EBjerrum/scikit-mol/tree/main/notebooks/02_descriptor_transformer.ipynb)
+- [Pipelining with Scikit-Learn classes](https://github.com/EBjerrum/scikit-mol/tree/main/notebooks/03_example_pipeline.ipynb)
+- [Molecular standardization](https://github.com/EBjerrum/scikit-mol/tree/main/notebooks/04_standardizer.ipynb)
+- [Sanitizing SMILES input](https://github.com/EBjerrum/scikit-mol/tree/main/notebooks/05_smiles_sanitaztion.ipynb)
+- [Integrated hyperparameter tuning of Scikit-Learn estimator and Scikit-Mol transformer](https://github.com/EBjerrum/scikit-mol/tree/main/notebooks/06_hyperparameter_tuning.ipynb)
+- [Using parallel execution to speed up descriptor and fingerprint calculations](https://github.com/EBjerrum/scikit-mol/tree/main/notebooks/07_parallel_transforms.ipynb)
+- [Using skopt for hyperparameter tuning](https://github.com/EBjerrum/scikit-mol/tree/main/notebooks/08_external_library_skopt.ipynb)
+- [Testing different fingerprints as part of the hyperparameter optimization](https://github.com/EBjerrum/scikit-mol/blob/main/notebooks/09_Combinatorial_Method_Usage_with_FingerPrint_Transformers.ipynb)
+- [Using pandas output for easy feature importance analysis and combine pre-exisitng values with new computations](https://github.com/EBjerrum/scikit-mol/blob/main/notebooks/10_pipeline_pandas_output.ipynb)