add docs

docs/src/api.md

@@ -1,7 +1,5 @@
 # Library
 
----
-
 ```@meta
 CurrentModule = SpinGlassNetworks
 ```
@@ -64,4 +62,5 @@ select_numstate_best
 ## Auxiliary Functions
 ```@docs
 zephyr_to_linear
+load_openGM
 ```

docs/src/clh.md

@@ -3,16 +3,6 @@ A clustered Hamiltonian is a graphical representation that allows for a convenie
 
 The concept of a clustered Hamiltonian within `SpinGlassNetworks.jl` introduces a powerful mechanism for organizing spins into desired geometries, facilitating a structured approach to modeling complex spin systems. Analogous to a factor graph, the clustered Hamiltonian involves nodes that represent tensors within the underlying network. The edges connecting these nodes in the clustered Hamiltonian correspond to the indices shared between the respective tensors in the tensor network.
 
-The Ising problem in translates to:
-$$ H(\conf{x}{\Nbar}) = \sum_{\langle m,n\rangle \in \mathcal{F}} E_{x_m x_n} + \sum_{n=1}^{\Nbar} E_{x_n} $$
-$\mathcal{F}$ forms a 2D graph, see the figure below, where we indicate nearest-neighbour interactions with blue lines, and diagonal connections with green lines.
-Each $x_n$ takes $d$ values with  $d=2^4$ for square diagonal, $d=2^{24}$ for Pegasus and $2^{16}$ for Zephyr geometry. 
-$E_{x_n}$ is an intra--node energy of the corresponding binary-variables configuration, and $E_{x_n x_m}$ is inter--node energy.
-
-```@raw html
-<img src="../images/clh.pdf" width="200%" class="center"/>
-```
-
 ```@docs
 clustered_hamiltonian
 ```
@@ -26,7 +16,7 @@ using SpinGlassNetworks
 instance = "$(@__DIR__)/../../src/instances/square_diagonal/5x5/diagonal.txt"
 ig = ising_graph(instance)
 
-# Create clustered Hamiltonian.
+# Create clustered Hamiltonian
 cl_h = clustered_hamiltonian(
     ig,
     cluster_assignment_rule = super_square_lattice((5,5,4))

docs/src/ising.md

@@ -2,17 +2,17 @@
 
 The Ising model is a mathematical model used to describe the behavior of interacting particles, such as atoms or molecules, in a magnetic field. In the Ising model, each particle is represented as a binary variable $s_i$ that can take on the values of either +1 or -1. The total energy of the system is given by the Hamiltonian:
 
-$$H =  \sum_{(i,j) \in \mathcal{E}} J_{ij} s_i s_j + \sum_{i} h_i s_i$$
+$H =  \sum_{(i,j) \in \mathcal{E}} J_{ij} s_i s_j + \sum_{i} h_i s_i$
 
 where $J_{ij}$ is the coupling constant between particles $i$ and $j$, $h_i$ is the external magnetic field at particle $i$, and the sum is taken over all pairs of particles and all particles in the system $\mathcal{E}$, respectively.
 
-In `SpinGlassPEPS.jl` package, an ising graph can be created using the command `ising_graph`.
+In `SpinGlassPEPS.jl` package, an Ising graph can be created using the command `ising_graph`.
 ```@docs
 ising_graph
 ```
 
 ## Simple example
-In this simple example below we show how to create ising_graph of a instance given as txt file in a format (i, j, Jij). The resulting graph has vertices (black circles) corresponding to positions of spins in the system and edges defining coupling strength between spins. Each vertex contains information about local field.
+In this simple example below we show how to create Ising graph of a instance given as txt file in a format (i, j, Jij). The resulting graph has vertices (black circles) corresponding to positions of spins in the system and edges defining coupling strength between spins. Each vertex contains information about local field.
 
 ```@example
 using SpinGlassNetworks
@@ -22,8 +22,4 @@ ig = ising_graph(instance)
 
 # View graph properties
 @show biases(ig), couplings(ig)
-```
-
-```@raw html
-<img src="../images/sd_ising.pdf" width="200%" class="center"/>
 ```

docs/src/userguide.md

@@ -2,4 +2,4 @@
 
 A [Julia](http://julialang.org) package for building and interacting with Ising spin glass models in context of tensor networks. Part of [SpinGlassPEPS](https://github.com/euro-hpc-pl/SpinGlassPEPS.jl) package.
 
-The contents of our package are richly illustrated through comprehensive examples, showcasing the practical utilization of key functions. Specifically, the 'ising_graph' function is highlighted, demonstrating its capacity to generate Ising model graphs—a fundamental step in modeling spin systems. Additionally, the 'clustered_hamiltonian' function is presented as a pivotal tool for converting Ising graphs into clustered Hamiltonians. The package delves into various lattice geometries, providing insights into constructing diverse structures such as the super_square_lattice, pegasus lattice, and zephyr lattice. Moreover, the documentation outlines methods for local dimensional reduction, shedding light on techniques to streamline computations and enhance the efficiency of spin system simulations.
+The contents of our package are richly illustrated through comprehensive examples, showcasing the practical utilization of key functions. Specifically, the `ising_graph` function is highlighted, demonstrating its capacity to generate Ising model graphs—a fundamental step in modeling spin systems. Additionally, the `clustered_hamiltonian` function is presented as a pivotal tool for converting Ising graphs into clustered Hamiltonians. The package delves into various lattice geometries, providing insights into constructing diverse structures such as the `super_square_lattice`, `pegasus_lattice`, and `zephyr-lattice`. Moreover, the documentation outlines methods for local dimensional reduction, shedding light on techniques to streamline computations and enhance the efficiency of spin system simulations.