docs: fix broken links in cookbook and documentation

f-aguzzi · Jun 27, 2024 · 2353ba9 · 2353ba9
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diff --git a/docs/cookbook/structure.md b/docs/cookbook/structure.md
@@ -12,6 +12,10 @@ In this cookbook page, you will be shown how the project is structured, and the
 chemfusekit
  │
  ├── base
+ |    ├── BaseActionClass
+ |    ├── BaseClassifier
+ |    ├── BaseReducer
+ |    ├── ReducerDataModel
  │    └── BaseDataModel
  │
  ├── lda
@@ -28,8 +32,7 @@ chemfusekit
  │ 
  ├── pca
  │    ├── PCASettings
- │    ├── PCA
- │    └── PCADataModel
+ │    └── PCA
  │
  ├── lldf
  │    ├── LLDFSettings
@@ -80,7 +83,7 @@ The training method is always called like its container class, but in lower case
 
 ### Modular settings
 
-The settings for all classifiers (that is, all classes except `LLDF` and `PCA`) inherit from a base class called [`BaseSettings`](/docs/base/basesettings) in the `base` module:
+The settings for all classifiers (that is, all classes except `LLDF` and `PCA`) inherit from a base class called `BaseSettings` in the `base` module:
 
 ```mermaid
 classDiagram
@@ -120,7 +123,7 @@ classDiagram
 
 ### Modular classifiers
 
-The classifiers themselves all inherit from a base class called [`BaseClassifier`](/docs/base/baseclassifier) in the `base` module:
+The classifiers themselves all inherit from a base class called `BaseClassifier` in the `base` module:
 
 ```mermaid
 classDiagram
@@ -199,7 +202,7 @@ classDiagram
 
 ### Modular data types
 
-The data types are modular and interexchangeable too. Both [`LLDFDataModel`](/docs/lldf/lldfmodel) and [`PCADataModel`](/docs/pca/pcadatamodel) inherit from [`BaseDataModel`](/docs/base/basedatamodel) as shown in the following diagram:
+The data types are modular and interexchangeable too. Both `DFDataModel` and `PCADataModel` inherit from `BaseDataModel` as shown in the following diagram:
 
 ```mermaid
 classDiagram
@@ -224,15 +227,15 @@ classDiagram
     BaseDataModel *-- ReducerDataModel
 ```
 
-This allows all the classifiers to use the `LLDF` data, dimension-reduced `PCA` data, or any other type of data as long as it follows the `BaseDataModel` template.
+This allows all the classifiers to use the `DF` data, dimension-reduced `PCA` data, or any other type of data as long as it follows the `BaseDataModel` template.
 
 
 ## File import and export
 
-All the data models (`BaseDataModel`, and its derived, `LLDFDataModel` and `PCADataModel`) can export their content to Excel tables.
+All the data models (`BaseDataModel`, and its derived, `DFDataModel` and `PCADataModel`) can export their content to Excel tables.
 
 All classes derived from `BaseActionClass` (that is, all which derive from `BaseClassifier`, `BaseReducer`, or both) can import and export their sklearn data model from and to file.
 
 All classifiers derived from `BaseClassifier` (`KNN`, `LDA`, `LR`, `PLSDA`, `SVM`) can perform training and inference.
 
-All reducers derived from `BaseReducer` (`LDA`, `PCA`) can perform dimensionality reduction.
+All reducers derived from `BaseReducer` (`LDA`, `PCA`, `PLSDA`) can perform dimensionality reduction.
diff --git a/docs/cookbook_versioned_docs/version-2.0.0/structure.md b/docs/cookbook_versioned_docs/version-2.0.0/structure.md
@@ -47,7 +47,7 @@ As you can see, each module contains a class with the same name of the module, a
 
 ## Modular design features
 
-The settings for all classifiers (that is, all classes except `LLDF` and `PCA`) inherit from a base class called [`BaseSettings`](/docs/base/basesettings) in the `base` module:
+The settings for all classifiers (that is, all classes except `LLDF` and `PCA`) inherit from a base class called `BaseSettings` in the `base` module:
 
 ```mermaid
 classDiagram
@@ -86,7 +86,7 @@ classDiagram
 
 \
 \
-The classifiers themselves all inherit from a base class called [`BaseClassifier`](/docs/base/baseclassifier) in the `base` module:
+The classifiers themselves all inherit from a base class called `BaseClassifier` in the `base` module:
 
 ```mermaid
 classDiagram
@@ -130,7 +130,7 @@ classDiagram
 
 \
 \
-The data types are modular and interexchangeable too. Both [`LLDFDataModel`](/docs/lldf/lldfmodel) and [`PCADataModel`](/docs/pca/pcadatamodel) inherit from [`BaseDataModel`](/docs/base/basedatamodel) as shown in the following diagram:
+The data types are modular and interexchangeable too. Both `LLDFDataModel` and `PCADataModel` inherit from `BaseDataModel` as shown in the following diagram:
 
 ```mermaid
 classDiagram

diff --git a/docs/cookbook_versioned_docs/version-2.1.0/structure.md b/docs/cookbook_versioned_docs/version-2.1.0/structure.md
@@ -77,7 +77,7 @@ The training method is always called like its container class, but in lower case
 
 ### Modular settings
 
-The settings for all classifiers (that is, all classes except `LLDF` and `PCA`) inherit from a base class called [`BaseSettings`](/docs/base/basesettings) in the `base` module:
+The settings for all classifiers (that is, all classes except `LLDF` and `PCA`) inherit from a base class called `BaseSettings` in the `base` module:
 
 ```mermaid
 classDiagram
@@ -117,7 +117,7 @@ classDiagram
 
 ### Modular classifiers
 
-The classifiers themselves all inherit from a base class called [`BaseClassifier`](/docs/base/baseclassifier) in the `base` module:
+The classifiers themselves all inherit from a base class called `BaseClassifier` in the `base` module:
 
 ```mermaid
 classDiagram
@@ -162,7 +162,7 @@ classDiagram
 
 ### Modular data types
 
-The data types are modular and interexchangeable too. Both [`LLDFDataModel`](/docs/lldf/lldfmodel) and [`PCADataModel`](/docs/pca/pcadatamodel) inherit from [`BaseDataModel`](/docs/base/basedatamodel) as shown in the following diagram:
+The data types are modular and interexchangeable too. Both `LLDFDataModel` and `PCADataModel` inherit from `BaseDataModel` as shown in the following diagram:
 
 ```mermaid
 classDiagram

diff --git a/docs/cookbook_versioned_docs/version-2.2.0/structure.md b/docs/cookbook_versioned_docs/version-2.2.0/structure.md
@@ -77,7 +77,7 @@ The training method is always called like its container class, but in lower case
 
 ### Modular settings
 
-The settings for all classifiers (that is, all classes except `LLDF` and `PCA`) inherit from a base class called [`BaseSettings`](/docs/base/basesettings) in the `base` module:
+The settings for all classifiers (that is, all classes except `LLDF` and `PCA`) inherit from a base class called `BaseSettings` in the `base` module:
 
 ```mermaid
 classDiagram
@@ -117,7 +117,7 @@ classDiagram
 
 ### Modular classifiers
 
-The classifiers themselves all inherit from a base class called [`BaseClassifier`](/docs/base/baseclassifier) in the `base` module:
+The classifiers themselves all inherit from a base class called `BaseClassifier` in the `base` module:
 
 ```mermaid
 classDiagram
@@ -162,7 +162,7 @@ classDiagram
 
 ### Modular data types
 
-The data types are modular and interexchangeable too. Both [`LLDFDataModel`](/docs/lldf/lldfmodel) and [`PCADataModel`](/docs/pca/pcadatamodel) inherit from [`BaseDataModel`](/docs/base/basedatamodel) as shown in the following diagram:
+The data types are modular and interexchangeable too. Both `LLDFDataModel` and `PCADataModel` inherit from `BaseDataModel` as shown in the following diagram:
 
 ```mermaid
 classDiagram

diff --git a/docs/cookbook_versioned_docs/version-2.3.0/structure.md b/docs/cookbook_versioned_docs/version-2.3.0/structure.md
@@ -77,7 +77,7 @@ The training method is always called like its container class, but in lower case
 
 ### Modular settings
 
-The settings for all classifiers (that is, all classes except `LLDF` and `PCA`) inherit from a base class called [`BaseSettings`](/docs/base/basesettings) in the `base` module:
+The settings for all classifiers (that is, all classes except `LLDF` and `PCA`) inherit from a base class called `BaseSettings` in the `base` module:
 
 ```mermaid
 classDiagram
@@ -117,7 +117,7 @@ classDiagram
 
 ### Modular classifiers
 
-The classifiers themselves all inherit from a base class called [`BaseClassifier`](/docs/base/baseclassifier) in the `base` module:
+The classifiers themselves all inherit from a base class called `BaseClassifier` in the `base` module:
 
 ```mermaid
 classDiagram
@@ -162,7 +162,7 @@ classDiagram
 
 ### Modular data types
 
-The data types are modular and interexchangeable too. Both [`LLDFDataModel`](/docs/lldf/lldfmodel) and [`PCADataModel`](/docs/pca/pcadatamodel) inherit from [`BaseDataModel`](/docs/base/basedatamodel) as shown in the following diagram:
+The data types are modular and interexchangeable too. Both `LLDFDataModel` and `PCADataModel` inherit from `BaseDataModel` as shown in the following diagram:
 
 ```mermaid
 classDiagram

diff --git a/docs/cookbook_versioned_docs/version-2.4.0/structure.md b/docs/cookbook_versioned_docs/version-2.4.0/structure.md
@@ -77,7 +77,7 @@ The training method is always called like its container class, but in lower case
 
 ### Modular settings
 
-The settings for all classifiers (that is, all classes except `LLDF` and `PCA`) inherit from a base class called [`BaseSettings`](/docs/base/basesettings) in the `base` module:
+The settings for all classifiers (that is, all classes except `LLDF` and `PCA`) inherit from a base class called `BaseSettings` in the `base` module:
 
 ```mermaid
 classDiagram
@@ -117,7 +117,7 @@ classDiagram
 
 ### Modular classifiers
 
-The classifiers themselves all inherit from a base class called [`BaseClassifier`](/docs/base/baseclassifier) in the `base` module:
+The classifiers themselves all inherit from a base class called `BaseClassifier` in the `base` module:
 
 ```mermaid
 classDiagram
@@ -162,7 +162,7 @@ classDiagram
 
 ### Modular data types
 
-The data types are modular and interexchangeable too. Both [`LLDFDataModel`](/docs/lldf/lldfmodel) and [`PCADataModel`](/docs/pca/pcadatamodel) inherit from [`BaseDataModel`](/docs/base/basedatamodel) as shown in the following diagram:
+The data types are modular and interexchangeable too. Both `LLDFDataModel` and `PCADataModel` inherit from `BaseDataModel` as shown in the following diagram:
 
 ```mermaid
 classDiagram

diff --git a/docs/cookbook_versioned_docs/version-2.5.0/structure.md b/docs/cookbook_versioned_docs/version-2.5.0/structure.md
@@ -80,7 +80,7 @@ The training method is always called like its container class, but in lower case
 
 ### Modular settings
 
-The settings for all classifiers (that is, all classes except `LLDF` and `PCA`) inherit from a base class called [`BaseSettings`](/docs/base/basesettings) in the `base` module:
+The settings for all classifiers (that is, all classes except `LLDF` and `PCA`) inherit from a base class called `BaseSettings` in the `base` module:
 
 ```mermaid
 classDiagram
@@ -120,7 +120,7 @@ classDiagram
 
 ### Modular classifiers
 
-The classifiers themselves all inherit from a base class called [`BaseClassifier`](/docs/base/baseclassifier) in the `base` module:
+The classifiers themselves all inherit from a base class called `BaseClassifier` in the `base` module:
 
 ```mermaid
 classDiagram
@@ -188,7 +188,7 @@ classDiagram
 
 ### Modular data types
 
-The data types are modular and interexchangeable too. Both [`LLDFDataModel`](/docs/lldf/lldfmodel) and [`PCADataModel`](/docs/pca/pcadatamodel) inherit from [`BaseDataModel`](/docs/base/basedatamodel) as shown in the following diagram:
+The data types are modular and interexchangeable too. Both `LLDFDataModel` and `PCADataModel` inherit from `BaseDataModel` as shown in the following diagram:
 
 ```mermaid
 classDiagram

diff --git a/docs/cookbook_versioned_docs/version-3.0.0/structure.md b/docs/cookbook_versioned_docs/version-3.0.0/structure.md
@@ -12,6 +12,10 @@ In this cookbook page, you will be shown how the project is structured, and the
 chemfusekit
  │
  ├── base
+ |    ├── BaseActionClass
+ |    ├── BaseClassifier
+ |    ├── BaseReducer
+ |    ├── ReducerDataModel
  │    └── BaseDataModel
  │
  ├── lda
@@ -28,8 +32,7 @@ chemfusekit
  │ 
  ├── pca
  │    ├── PCASettings
- │    ├── PCA
- │    └── PCADataModel
+ │    └── PCA
  │
  ├── lldf
  │    ├── LLDFSettings
@@ -80,7 +83,7 @@ The training method is always called like its container class, but in lower case
 
 ### Modular settings
 
-The settings for all classifiers (that is, all classes except `LLDF` and `PCA`) inherit from a base class called [`BaseSettings`](/docs/base/basesettings) in the `base` module:
+The settings for all classifiers (that is, all classes except `LLDF` and `PCA`) inherit from a base class called `BaseSettings` in the `base` module:
 
 ```mermaid
 classDiagram
@@ -120,7 +123,7 @@ classDiagram
 
 ### Modular classifiers
 
-The classifiers themselves all inherit from a base class called [`BaseClassifier`](/docs/base/baseclassifier) in the `base` module:
+The classifiers themselves all inherit from a base class called `BaseClassifier` in the `base` module:
 
 ```mermaid
 classDiagram
@@ -199,7 +202,7 @@ classDiagram
 
 ### Modular data types
 
-The data types are modular and interexchangeable too. Both [`LLDFDataModel`](/docs/lldf/lldfmodel) and [`PCADataModel`](/docs/pca/pcadatamodel) inherit from [`BaseDataModel`](/docs/base/basedatamodel) as shown in the following diagram:
+The data types are modular and interexchangeable too. Both `DFDataModel` and `PCADataModel` inherit from `BaseDataModel` as shown in the following diagram:
 
 ```mermaid
 classDiagram
@@ -224,15 +227,15 @@ classDiagram
     BaseDataModel *-- ReducerDataModel
 ```
 
-This allows all the classifiers to use the `LLDF` data, dimension-reduced `PCA` data, or any other type of data as long as it follows the `BaseDataModel` template.
+This allows all the classifiers to use the `DF` data, dimension-reduced `PCA` data, or any other type of data as long as it follows the `BaseDataModel` template.
 
 
 ## File import and export
 
-All the data models (`BaseDataModel`, and its derived, `LLDFDataModel` and `PCADataModel`) can export their content to Excel tables.
+All the data models (`BaseDataModel`, and its derived, `DFDataModel` and `PCADataModel`) can export their content to Excel tables.
 
 All classes derived from `BaseActionClass` (that is, all which derive from `BaseClassifier`, `BaseReducer`, or both) can import and export their sklearn data model from and to file.
 
 All classifiers derived from `BaseClassifier` (`KNN`, `LDA`, `LR`, `PLSDA`, `SVM`) can perform training and inference.
 
-All reducers derived from `BaseReducer` (`LDA`, `PCA`) can perform dimensionality reduction.
+All reducers derived from `BaseReducer` (`LDA`, `PCA`, `PLSDA`) can perform dimensionality reduction.
diff --git a/docs/versioned_docs/version-1.1.3/knn/knn.md b/docs/versioned_docs/version-1.1.3/knn/knn.md
@@ -15,14 +15,14 @@ KNN(settings: KNNSettings, fused_data: LLDFModel)
 ## Constructor parameters
 
 - `fused_data`: object of type [`LLDFModel`](../lldf/lldfmodel.md). Contains the data to be analyzed.
-- `settings`: object of type [`KNNSettings`](knnsettings.md). Contains the settings for
+- `settings`: object of type [`KNNSettings`](./knnsettings.md). Contains the settings for
   the `KNN` object.
 
 ## Fields
 
-- `settings`: object of type [`KNNSettings`](/tesi/docs/knn/knnsettings). Contains the settings for
+- `settings`: object of type [`KNNSettings`](./knnsettings). Contains the settings for
   the `KNN` object. 
-- `fused_data`: onject of type ['LLDFModel`](/tesi/docs/lldf/lldfmodel). Contains the
+- `fused_data`: onject of type ['LLDFModel`](../lldf/lldfmodel). Contains the
   artifacts from the data fusion process.
 - `model`: a `KNeighborsClassifier` model from `scikit-learn`. Defaults to `None`.
 

diff --git a/docs/versioned_docs/version-1.2.0/knn/knn.md b/docs/versioned_docs/version-1.2.0/knn/knn.md
@@ -20,9 +20,9 @@ KNN(settings: KNNSettings, fused_data: LLDFModel)
 
 ## Fields
 
-- `settings`: object of type [`KNNSettings`](/tesi/docs/knn/knnsettings). Contains the settings for
+- `settings`: object of type [`KNNSettings`](./knnsettings). Contains the settings for
   the `KNN` object. 
-- `fused_data`: onject of type ['LLDFModel`](/tesi/docs/lldf/lldfmodel). Contains the
+- `fused_data`: onject of type ['LLDFModel`](../lldf/lldfmodel). Contains the
   artifacts from the data fusion process.
 - `model`: a `KNeighborsClassifier` model from `scikit-learn`. Defaults to `None`.
 

diff --git a/docs/versioned_docs/version-2.0.0/knn/knn.md b/docs/versioned_docs/version-2.0.0/knn/knn.md
@@ -14,15 +14,15 @@ KNN(settings: KNNSettings, data: LLDFModel)
 
 ## Constructor parameters
 
-- `settings`: object of type [`KNNSettings`](knnsettings.md). Contains the settings for
+- `settings`: object of type [`KNNSettings`](./knnsettings.md). Contains the settings for
   the `KNN` object.
 - `data`: object of type [`BaseDataModel`](../base/basedatamodel.md). Contains the data to be analyzed.
 
 ## Fields
 
-- `settings`: object of type [`KNNSettings`](/tesi/docs/knn/knnsettings). Contains the settings for
+- `settings`: object of type [`KNNSettings`](./knnsettings). Contains the settings for
   the `KNN` object. 
-- `fused_data`: onject of type ['LLDFModel`](/tesi/docs/lldf/lldfmodel). Contains the
+- `fused_data`: onject of type ['LLDFModel`](../lldf/lldfmodel). Contains the
   artifacts from the data fusion process.
 - `model`: a `KNeighborsClassifier` model from `scikit-learn`. Defaults to `None`.
 

diff --git a/docs/versioned_docs/version-2.1.0/knn/knn.md b/docs/versioned_docs/version-2.1.0/knn/knn.md
@@ -20,9 +20,9 @@ KNN(settings: KNNSettings, data: LLDFModel)
 
 ## Fields
 
-- `settings`: object of type [`KNNSettings`](/tesi/docs/knn/knnsettings). Contains the settings for
+- `settings`: object of type [`KNNSettings`](./knnsettings). Contains the settings for
   the `KNN` object. 
-- `fused_data`: onject of type ['LLDFModel`](/tesi/docs/lldf/lldfmodel). Contains the
+- `fused_data`: onject of type ['LLDFModel`](../lldf/lldfmodel). Contains the
   artifacts from the data fusion process.
 - `model`: a `KNeighborsClassifier` model from `scikit-learn`. Defaults to `None`.
 

diff --git a/docs/versioned_docs/version-2.2.0/knn/knn.md b/docs/versioned_docs/version-2.2.0/knn/knn.md
@@ -14,15 +14,15 @@ KNN(settings: KNNSettings, data: LLDFModel)
 
 ## Constructor parameters
 
-- `settings`: object of type [`KNNSettings`](knnsettings.md). Contains the settings for
+- `settings`: object of type [`KNNSettings`](./knnsettings.md). Contains the settings for
   the `KNN` object.
 - `data`: object of type [`BaseDataModel`](../base/basedatamodel.md). Contains the data to be analyzed.
 
 ## Fields
 
-- `settings`: object of type [`KNNSettings`](/tesi/docs/knn/knnsettings). Contains the settings for
+- `settings`: object of type [`KNNSettings`](./knnsettings). Contains the settings for
   the `KNN` object. 
-- `fused_data`: onject of type ['LLDFModel`](/tesi/docs/lldf/lldfmodel). Contains the
+- `fused_data`: onject of type ['LLDFModel`](../lldf/lldfmodel). Contains the
   artifacts from the data fusion process.
 - `model`: a `KNeighborsClassifier` model from `scikit-learn`. Defaults to `None`.
 

diff --git a/docs/versioned_docs/version-2.3.0/knn/knn.md b/docs/versioned_docs/version-2.3.0/knn/knn.md
@@ -14,15 +14,15 @@ KNN(settings: KNNSettings, data: LLDFModel)
 
 ## Constructor parameters
 
-- `settings`: object of type [`KNNSettings`](knnsettings.md). Contains the settings for
+- `settings`: object of type [`KNNSettings`](./knnsettings.md). Contains the settings for
   the `KNN` object.
 - `data`: object of type [`BaseDataModel`](../base/basedatamodel.md). Contains the data to be analyzed.
 
 ## Fields
 
-- `settings`: object of type [`KNNSettings`](/tesi/docs/knn/knnsettings). Contains the settings for
+- `settings`: object of type [`KNNSettings`](./knnsettings). Contains the settings for
   the `KNN` object. 
-- `fused_data`: onject of type ['LLDFModel`](/tesi/docs/lldf/lldfmodel). Contains the
+- `fused_data`: onject of type ['LLDFModel`](../lldf/lldfmodel). Contains the
   artifacts from the data fusion process.
 - `model`: a `KNeighborsClassifier` model from `scikit-learn`. Defaults to `None`.