From 3fe916988fcb814372affbcabe0ef100ef55007b Mon Sep 17 00:00:00 2001
From: "Lorenzo (Mec-iS)" <tunedconsulting@gmail.com>
Date: Fri, 26 Aug 2022 16:14:31 +0100
Subject: [PATCH 1/2] Init issue 11 implementation

---
 src/cluster/hierarchical.rs | 62 +++++++++++++++++++++++++++++++++++++
 1 file changed, 62 insertions(+)
 create mode 100644 src/cluster/hierarchical.rs

diff --git a/src/cluster/hierarchical.rs b/src/cluster/hierarchical.rs
new file mode 100644
index 00000000..154cbfa5
--- /dev/null
+++ b/src/cluster/hierarchical.rs
@@ -0,0 +1,62 @@
+/// # Hierarchical clustering
+/// 
+/// Implement hierarchical clustering methods:
+/// * Agglomerative clustering (current)
+/// * Bisecting K-Means (future)
+/// * Fastcluster (future)
+/// 
+
+/* 
+class AgglomerativeClustering():
+    """
+    Parameters
+    ----------
+    n_clusters : int or None, default=2
+        The number of clusters to find. It must be ``None`` if
+        ``distance_threshold`` is not ``None``.
+    affinity : str or callable, default='euclidean'
+        If linkage is "ward", only "euclidean" is accepted.
+    linkage : {'ward',}, default='ward'
+        Which linkage criterion to use. The linkage criterion determines which
+        distance to use between sets of observation. The algorithm will merge
+        the pairs of cluster that minimize this criterion.
+        - 'ward' minimizes the variance of the clusters being merged.
+    compute_distances : bool, default=False
+        Computes distances between clusters even if `distance_threshold` is not
+        used. This can be used to make dendrogram visualization, but introduces
+        a computational and memory overhead.
+    """
+
+    def fit(X):
+        # compute tree 
+        parents, childern = ward_tree(X, ....)
+        # compute clusters
+        labels = _hierarchical.hc_get_heads(parents)
+        # assign cluster numbers
+        self.labels_ = np.searchsorted(np.unique(labels), labels)
+
+*/
+
+// implement ward tree
+
+
+// implement hierarchical cut (only needed if we want to allwo compute_full_tree) (future)
+
+
+// HOT: try to implement fastcluster <https://arxiv.org/pdf/1109.2378.pdf> (future)
+
+
+// additional: implement BisectingKMeans (future)
+
+
+mod tests {
+    // >>> from sklearn.cluster import AgglomerativeClustering
+    // >>> import numpy as np
+    // >>> X = np.array([[1, 2], [1, 4], [1, 0],
+    // ...               [4, 2], [4, 4], [4, 0]])
+    // >>> clustering = AgglomerativeClustering().fit(X)
+    // >>> clustering
+    // AgglomerativeClustering()
+    // >>> clustering.labels_
+    // array([1, 1, 1, 0, 0, 0])
+}
\ No newline at end of file

From 20ca5c9647fe564013ccaccc0ac79002099a50aa Mon Sep 17 00:00:00 2001
From: "Lorenzo (Mec-iS)" <tunedconsulting@gmail.com>
Date: Tue, 30 Aug 2022 11:50:00 +0100
Subject: [PATCH 2/2] Add detailed tasks to docstring

---
 src/cluster/hierarchical.rs | 21 +++++++++++----------
 1 file changed, 11 insertions(+), 10 deletions(-)

diff --git a/src/cluster/hierarchical.rs b/src/cluster/hierarchical.rs
index 154cbfa5..4e1477f9 100644
--- a/src/cluster/hierarchical.rs
+++ b/src/cluster/hierarchical.rs
@@ -28,9 +28,11 @@ class AgglomerativeClustering():
     """
 
     def fit(X):
-        # compute tree 
+        # compute tree
+        # <https://github.com/scikit-learn/scikit-learn/blob/02ebf9e68fe1fc7687d9e1047b9e465ae0fd945e/sklearn/cluster/_agglomerative.py#L172>
         parents, childern = ward_tree(X, ....)
         # compute clusters
+        # <https://github.com/scikit-learn/scikit-learn/blob/70c495250fea7fa3c8c1a4631e6ddcddc9f22451/sklearn/cluster/_hierarchical_fast.pyx#L98>
         labels = _hierarchical.hc_get_heads(parents)
         # assign cluster numbers
         self.labels_ = np.searchsorted(np.unique(labels), labels)
@@ -38,15 +40,14 @@ class AgglomerativeClustering():
 */
 
 // implement ward tree
-
-
-// implement hierarchical cut (only needed if we want to allwo compute_full_tree) (future)
-
-
-// HOT: try to implement fastcluster <https://arxiv.org/pdf/1109.2378.pdf> (future)
-
-
-// additional: implement BisectingKMeans (future)
+// use scipy.cluster.hierarchy.ward
+// <https://github.com/scipy/scipy/blob/main/scipy/cluster/hierarchy.py#L738>
+// use linkage
+// <https://github.com/scipy/scipy/blob/main/scipy/cluster/hierarchy.py#L837>
+// use nn_chain
+// <https://github.com/scipy/scipy/blob/main/scipy/cluster/_hierarchy.pyx#L906>
+
+// implement hc_get_heads
 
 
 mod tests {