Merge pull request #899 from brs96/closeness-mem-est

Add closeness centrality mem est in doc

Author: brs96

doc/sphinx/algorithms.json

@@ -1502,6 +1502,14 @@
     },
     "description": "Closeness centrality is a way of detecting nodes that are able to spread information very efficiently through a graph."
   },
+  {
+    "function": {
+      "name": "gds.closeness.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.stats",
@@ -1510,6 +1518,14 @@
     },
     "description": "Closeness centrality is a way of detecting nodes that are able to spread information very efficiently through a graph."
   },
+  {
+    "function": {
+      "name": "gds.closeness.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.stream",
@@ -1518,6 +1534,14 @@
     },
     "description": "Closeness centrality is a way of detecting nodes that are able to spread information very efficiently through a graph."
   },
+  {
+    "function": {
+      "name": "gds.closeness.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.write",
@@ -1526,6 +1550,14 @@
     },
     "description": "Closeness centrality is a way of detecting nodes that are able to spread information very efficiently through a graph."
   },
+  {
+    "function": {
+      "name": "gds.closeness.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.closeness.harmonic.mutate",

doc/sphinx/source/algorithms.rst

@@ -856,18 +856,34 @@ These all assume that an object of :class:`.GraphDataScience` is available as `g
 
     Closeness centrality is a way of detecting nodes that are able to spread information very efficiently through a graph.
 
+.. py:function:: gds.closeness.mutate.estimate(G: Graph, **config: Any) -> Series[Any]
+
+    Returns an estimation of the memory consumption for that procedure.
+
 .. py:function:: gds.closeness.stats(G: Graph, **config: Any) -> Series[Any]
 
     Closeness centrality is a way of detecting nodes that are able to spread information very efficiently through a graph.
 
+.. py:function:: gds.closeness.stats.estimate(G: Graph, **config: Any) -> Series[Any]
+
+    Returns an estimation of the memory consumption for that procedure.
+
 .. py:function:: gds.closeness.stream(G: Graph, **config: Any) -> DataFrame
 
     Closeness centrality is a way of detecting nodes that are able to spread information very efficiently through a graph.
 
+.. py:function:: gds.closeness.stream.estimate(G: Graph, **config: Any) -> Series[Any]
+
+    Returns an estimation of the memory consumption for that procedure.
+
 .. py:function:: gds.closeness.write(G: Graph, **config: Any) -> Series[Any]
 
     Closeness centrality is a way of detecting nodes that are able to spread information very efficiently through a graph.
 
+.. py:function:: gds.closeness.write.estimate(G: Graph, **config: Any) -> Series[Any]
+
+    Returns an estimation of the memory consumption for that procedure.
+
 .. py:function:: gds.closeness.harmonic.mutate(G: Graph, **config: Any) -> DataFrame
 
     Harmonic centrality is a way of detecting nodes that are able to spread information