Merge branch 'master' into dev

.github/workflows/TagBot.yml

@@ -1,11 +1,20 @@
 name: TagBot
 on:
-  schedule:
-    - cron: 0 * * * *
+  issue_comment:
+    types:
+      - created
+  workflow_dispatch:
+    inputs:
+      lookback:
+        default: 3
+permissions:
+  contents: write
 jobs:
   TagBot:
+    if: github.event_name == 'workflow_dispatch' || github.actor == 'JuliaTagBot'
     runs-on: ubuntu-latest
     steps:
       - uses: JuliaRegistries/TagBot@v1
         with:
           token: ${{ secrets.GITHUB_TOKEN }}
+          ssh: ${{ secrets.DOCUMENTER_KEY }}

README.md

@@ -1,11 +1,48 @@
 # PosDefManifold.jl
 
-[![](https://img.shields.io/badge/docs-dev-blue.svg)](https://Marco-Congedo.github.io/PosDefManifold.jl/latest)
+| **Documentation**  | 
+|:---------------------------------------:|
+| [![](https://img.shields.io/badge/docs-dev-blue.svg)](https://marco-congedo.github.io/PosDefManifold.jl/dev/) |
 
 **PosDefManifold** is a [**Julia**](https://julialang.org/) package for manipulating data in the manifold **P** of real or complex [**positive definite matrices**](https://en.wikipedia.org/wiki/Definiteness_of_a_matrix). The package supports **10 metrics** acting on **P**, two of which define [**Riemannian manifolds**](https://en.wikipedia.org/wiki/Riemannian_manifold).
 
-This package computes **distances**, **geodesics** and **weighted Fréchet means** for the supported metrics, **graph Laplacians**, **Lapacian eigen maps** and a special solution of the [**Procrustes problem**](https://en.wikipedia.org/wiki/Orthogonal_Procrustes_problem) in **P**. Key functions are multi-threaded.
+![](/docs/src/assets/Fig1.jpg)
 
-The documentation is rich and gives all mathematical details pertaining to the implemented functions (click the 'docs|dev' button).
+This package computes **distances**, **geodesics**, **weighted Fréchet means** and **inductive Fréchet means** for the supported metrics, **graph Laplacians**, **Lapacian eigen maps**, **tangent space projections**, **parallel transport**, the **geometric midrange**, matrix **approximations** and a special solution of the [**Procrustes problem**](https://en.wikipedia.org/wiki/Orthogonal_Procrustes_problem) in **P**. Key functions are *multi-threaded*.
+
+The [documentation](https://marco-congedo.github.io/PosDefManifold.jl/dev/) is rich and gives all mathematical details pertaining to the implemented functions.
+
+For **machine learning** in **P** see [PosDefManifoldML.jl](https://github.com/Marco-Congedo/PosDefManifoldML.jl).
+
+For **optimization** in **P** see [Manopt.jl](http://www.manoptjl.org/stable/).
+
+See also [Manifolds.jl](https://github.com/JuliaNLSolvers/Manifolds.jl).
 
 For similar code resources in other programming languages see [here](https://sites.google.com/site/marcocongedo/science/code-resources).
+
+## About the author
+
+[Marco Congedo](https://sites.google.com/site/marcocongedo) is
+a Research Director of [CNRS](http://www.cnrs.fr/en) (Centre National de la Recherche Scientifique), working at [UGA](https://www.univ-grenoble-alpes.fr/english/) (University of Grenoble Alpes), in Grenoble (France).
+
+## Contact
+
+marco *dot* congedo *at* gmail *dot* com
+
+## Examples:
+
+```
+using PosDefManifold
+ 
+P, Q = randP(20), randP(20)       # random Positive Definite Matrices (PDMs) of size 20x20
+d = distance(Fisher, P, Q)        # distance between P and Q 
+R = geodesic(Fisher, P, Q, 0.1)   # move on the geodesic relying P and Q 
+G = mean(Fisher, P, Q)            # mean of P and Q (geodesic mid-point) 
+U = procrustes(P, Q)              # solution to a special Procrustes problem
+S = logMap(Fisher, P, G)          # tangent space mapping  
+ 
+𝐏 = randP(20, 100)                 # random set 𝐏 of 100 PDMs of size 20x20
+G = mean(Fisher, 𝐏)                # mean of all matrices in set 𝐏 
+λ, U, i, c = spEmb(Fisher, 𝐏, 3)   # spectral embedding in 3D
+```
+