From ab0e500e8e5d37c240d9ada105aef1f9be203c9e Mon Sep 17 00:00:00 2001
From: ioannispan <ioannis.panagiotas@neotechnology.com>
Date: Wed, 4 Jun 2025 15:46:37 +0200
Subject: [PATCH] harmonic estimaton endpoints

---
 doc/sphinx/algorithms.json       | 32 ++++++++++++++++++++++++++++++++
 doc/sphinx/source/algorithms.rst | 16 ++++++++++++++++
 2 files changed, 48 insertions(+)

diff --git a/doc/sphinx/algorithms.json b/doc/sphinx/algorithms.json
index e932b48b6..783a88f48 100644
--- a/doc/sphinx/algorithms.json
+++ b/doc/sphinx/algorithms.json
@@ -1534,6 +1534,14 @@
     },
     "description": "Harmonic centrality is a way of detecting nodes that are able to spread information\nvery efficiently through a graph."
   },
+  {
+    "function": {
+      "name": "gds.closeness.harmonic.mutate.estimate",
+      "signature": "G: Graph, **config: Any",
+      "return_type": "Series[Any]"
+    },
+    "description": "Returns an estimation of the memory consumption for that procedure."
+  },
   {
     "function": {
       "name": "gds.closeness.harmonic.stats",
@@ -1542,6 +1550,14 @@
     },
     "description": "Harmonic centrality is a way of detecting nodes that are able to spread information\nvery efficiently through a graph."
   },
+  {
+    "function": {
+      "name": "gds.closeness.harmonic.stats.estimate",
+      "signature": "G: Graph, **config: Any",
+      "return_type": "Series[Any]"
+    },
+    "description": "Returns an estimation of the memory consumption for that procedure."
+  },
   {
     "function": {
       "name": "gds.closeness.harmonic.stream",
@@ -1550,6 +1566,14 @@
     },
     "description": "Harmonic centrality is a way of detecting nodes that are able to spread information\nvery efficiently through a graph."
   },
+  {
+    "function": {
+      "name": "gds.closeness.harmonic.stream.estimate",
+      "signature": "G: Graph, **config: Any",
+      "return_type": "Series[Any]"
+    },
+    "description": "Returns an estimation of the memory consumption for that procedure."
+  },
   {
     "function": {
       "name": "gds.closeness.harmonic.write",
@@ -1558,6 +1582,14 @@
     },
     "description": "Harmonic centrality is a way of detecting nodes that are able to spread information\nvery efficiently through a graph."
   },
+  {
+    "function": {
+      "name": "gds.closeness.harmonic.write.estimate",
+      "signature": "G: Graph, **config: Any",
+      "return_type": "Series[Any]"
+    },
+    "description": "Returns an estimation of the memory consumption for that procedure."
+  },
   {
     "function": {
       "name": "gds.collapsePath.mutate",
diff --git a/doc/sphinx/source/algorithms.rst b/doc/sphinx/source/algorithms.rst
index 7ef7e7958..0a0b88a0e 100644
--- a/doc/sphinx/source/algorithms.rst
+++ b/doc/sphinx/source/algorithms.rst
@@ -873,21 +873,37 @@ These all assume that an object of :class:`.GraphDataScience` is available as `g
     Harmonic centrality is a way of detecting nodes that are able to spread information
     very efficiently through a graph.
 
+.. py:function:: gds.closeness.harmonic.mutate.estimate(G: Graph, **config: Any) -> Series[Any]
+
+    Returns an estimation of the memory consumption for that procedure.
+
 .. py:function:: gds.closeness.harmonic.stats(G: Graph, **config: Any) -> DataFrame
 
     Harmonic centrality is a way of detecting nodes that are able to spread information
     very efficiently through a graph.
 
+.. py:function:: gds.closeness.harmonic.stats.estimate(G: Graph, **config: Any) -> Series[Any]
+
+    Returns an estimation of the memory consumption for that procedure.
+
 .. py:function:: gds.closeness.harmonic.stream(G: Graph, **config: Any) -> DataFrame
 
     Harmonic centrality is a way of detecting nodes that are able to spread information
     very efficiently through a graph.
 
+.. py:function:: gds.closeness.harmonic.stream.estimate(G: Graph, **config: Any) -> Series[Any]
+
+    Returns an estimation of the memory consumption for that procedure.
+
 .. py:function:: gds.closeness.harmonic.write(G: Graph, **config: Any) -> Series[Any]
 
     Harmonic centrality is a way of detecting nodes that are able to spread information
     very efficiently through a graph.
 
+.. py:function:: gds.closeness.harmonic.write.estimate(G: Graph, **config: Any) -> Series[Any]
+
+    Returns an estimation of the memory consumption for that procedure.
+
 .. py:function:: gds.collapsePath.mutate(G: Graph, **config: Any) -> Series[Any]
 
     Collapse Path algorithm is a traversal algorithm capable of creating relationships between the start