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* projectors in factor graph are 1-dimensional

* clean up

* new way of loading J and states

* clean up

* add ! in decode_projector

* clean up

* forma and clean up code

* clean up more

* formate code

* clean up

* add test full_pegasus

* brodcast all_states

* add instances and example for Lukasz

* add benchmarks

* correct a type

* clean up

* correct typo

* simplify spectrum.jl

* remove decode_projector

* threaded spectrum works

* clean up

* clean up

* add rudementary gpu brute force

* clen up

* rm commented functions

* fix binary conversion

* add sortperm (requires cuda from master)

* compare energies

* add my_digits

* add new kernel (still does not work, but close)

* something works

* fix bits

* should work but it does not

* gnoj

* fix indexing

* improve stuff a bit but still :(

* almost there

* fix issues with Spectrum

* works

* check all states

* all work

* clean up

* add more control over CUDA lauch

* all tests pass

* add specializiation for brute_force devices

* clean up

* clean up

* clean up energy mess

* clean up tests

* clean up 2

* clean up benchmarks

* clean factor.jl

* introducing Pegasus geometry

* clean up pegasus_lattice

* towards new pegasus geometry

* new indexing of pegasus lattice

* clean up

* add energy

* fix up

* energy in factor

* fix energy

* clean up

* clean up

* add comment

* fix

* ecv

* energy fg to fix

* add energy for factor graph

* add energy

* add energy

* fix energy

* add changes for 1.7

* add energy from factor graph

* clean up energy

* energy works

* cleam up

* clean up

* simplify energy for fg

* clean up energy

* energy

* fix energy for fg

* clear types and add cluster_size for fg

* test

* start documenting code

* start commenting code

* fixing pegasus conventions

* begin writing tests for numbering functions

* begun rewriting code wrom python

* tests for written functions

* all main functions for numerate

* add ref

* clean up

* clean up

* add pegasus_lattice_masoud

* add pegasus_lattice_tomek

* early work on zephyr lattice

* zephyr lattice (Z1)

* started work on zephyr lattice boundary

* clean up Z1

* horizontal spins in zephyr

* zephyr_to_linear, linear_to_zephy

* started work on lattice_5_tuple

* zephyr lattice Z2 square

* fix bug

* zephyr lattice rotated works for z1 and z2

* clean up

* add empty clusters in zephyr

* add zephyr lattice

* idea projectors

* aa

* correct syntax

* add comments

* add periodic lattice (PBCs)

* pool of projectors

* fg

* energy

* decode states in sampling

* lp size

* remove PoolOfProjectors

* no CUDA

* removed unnecessary functions

* start working on a proper types propagation

* clean up tests

* restor tests

* fix a bug

* clean up - all test pass

* add more tests

* rearange code a bit

* final clean up

* add truncated factor graph

* truncate factor graph another method

* fix bug in truncate_factor_graph

* fix export truncate_factor_graph

* truncate_factor_graph partialsortperm

* precise truncate

* fix truncate factor

* repaired test of renumerations

* Truncate factor graph based on belief propagation

* iterations as a parameter in BP

* remove println

* clean belief propagation

* clean up BP

* belief propagation

* remove println

* BP tests

* truncate_factor_graph_2site_BP

* fix the bug in BP

* new BP

* BP 2-site

* rewrite update message, add tests

* bp (pathological not working)

* bp example

* cleaning

* clean bp

* updatemessage

* sparse

* bp

* separate truncation and BP

* rm tol

* truncate fg for zephyr

* comment projectors

* states_int in Spectrum

* fix the bug in Spectrum, all tests pass

* change types in matrix_to_integers

* rename factor_graph to clustered_hamiltonian

* add bond energy

* try to move PoolOfProjectors

* add CUDA

* try to remove :pl, :pr

* PoolOfProjectors in clustered_hamiltonian

* add tests on projectors

* final cleaning projectors

* add types

* splitting overly long lines

* exception in states_int

* add docs

* docs

* add docstrings

* add $(TYPEDSIGNATURES)

* split the lines

* corrected the function names

* clean up toml

* added function for loading openGM images

* WIP rmf

* add the docs

* rmf clustered hamiltonian v1.0

* add the docs

* bugfix

* fix the bug in RMF clustered hamiltonian

* clean up cluster hamiltonian for RMF

* change cl_h spectrum

* added sizes for benchmark instances and
allowed diagonal conections

* fix the bug in reading h5 instances

* add docs

* add the docs

* add png images

* moved projectors.jl to SpinGlassTensors

* moved tests

* git push

* added SpinGlassTensors to dependencies

* removed projectors.jl

* changed version to 1.0

* moved rank_reveal to SpinGlassTensors

* save BP results to file

* rewrite truncate_hamiltonian_2site_BP

* clean up

* correct test

* fix versions, switch to Graphs from LightGraphs

* reformat

* fix ci, make

* update CI workflow

* remove tensor cast

* add push run

* fix test

* update readme

* move benchmarks to other repo

* fix test

* update compat

---------

Co-authored-by: annamariadziubyna <[email protected]>
Co-authored-by: bartekGardas <[email protected]>
Co-authored-by: Łukasz Pawela <[email protected]>
Co-authored-by: Marek Rams <[email protected]>
Co-authored-by: annamariadziubyna <[email protected]>
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33 changes: 13 additions & 20 deletions .github/workflows/CI.yml
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@@ -1,48 +1,41 @@
name: CI
on:
- push
- pull_request
pull_request:
branches:
- master
push:
jobs:
test:
name: Julia ${{ matrix.version }} - ${{ matrix.os }} - ${{ matrix.arch }}
runs-on: ${{ matrix.os }}
name: Julia ${{ matrix.version }}
runs-on: [self-hosted,titan,gpu]
strategy:
fail-fast: false
matrix:
version:
- '1.9'
- '1.10'
os:
- ubuntu-latest
- macOS-latest
arch:
- x64
steps:
- uses: actions/checkout@v2
- uses: julia-actions/setup-julia@v1
- uses: actions/checkout@v4
- uses: julia-actions/setup-julia@v2
with:
version: ${{ matrix.version }}
arch: ${{ matrix.arch }}
- uses: julia-actions/julia-buildpkg@latest
- uses: julia-actions/julia-runtest@latest
env:
JULIA_NUM_THREADS: 4
- uses: julia-actions/julia-processcoverage@v1
# - uses: codecov/codecov-action@v1
# with:
# file: lcov.info
- uses: coverallsapp/github-action@master
with:
github-token: ${{ secrets.GITHUB_TOKEN }}
path-to-lcov: lcov.info
flag-name: job-${{ matrix.version }}-${{ matrix.os }}-${{ matrix.arch }}
parallel: true

flag-name: run-${{ matrix.version }}
finish:
needs: test
runs-on: ubuntu-latest
runs-on: [self-hosted,titan]
steps:
- uses: coverallsapp/github-action@master
- name: Close parallel build
uses: coverallsapp/github-action@v1
with:
github-token: ${{ secrets.GITHUB_TOKEN }}
parallel-finished: true
carryforward: "run-1.9,run-1.10"
26 changes: 19 additions & 7 deletions Project.toml
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@@ -1,22 +1,34 @@
name = "SpinGlassNetworks"
uuid = "b7f6bd3e-55dc-4da6-96a9-ef9dbec6ac19"
authors = ["Krzysztof Domino <[email protected]>", "Anna Maria Dziubyna <annamariadziubyna@gmail.com>", "Bartłomiej Gardas <[email protected]>", "Konrad Jałowiecki <[email protected]>", "Łukasz Pawela <[email protected]>", "Marek M. Rams <[email protected]>"]
version = "0.3.2"
authors = ["Anna Maria Dziubyna <[email protected]>", "Tomasz Śmierzchalski <smierzchalski.tomek@gmail.com>", "Bartłomiej Gardas <[email protected]>", "Konrad Jałowiecki <[email protected]>", "Łukasz Pawela <[email protected]>", "Marek M. Rams <[email protected]>"]
version = "1.0.0"

[deps]
CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"
CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"
DocStringExtensions = "ffbed154-4ef7-542d-bbb7-c09d3a79fcae"
Graphs = "86223c79-3864-5bf0-83f7-82e725a168b6"
HDF5 = "f67ccb44-e63f-5c2f-98bd-6dc0ccc4ba2f"
JLD2 = "033835bb-8acc-5ee8-8aae-3f567f8a3819"
LabelledGraphs = "605abd48-4d17-4660-b914-d4df33194460"
LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
MKL = "33e6dc65-8f57-5167-99aa-e5a354878fb2"
MetaGraphs = "626554b9-1ddb-594c-aa3c-2596fe9399a5"
SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
SpinGlassTensors = "7584fc6a-5a23-4eeb-8277-827aab0146ea"

[compat]
CSV = "0.8 - 0.10"
DocStringExtensions = "0.8"
Graphs = "1.9"
LabelledGraphs = "^0.4.4"
MetaGraphs = "0.7.2"
CSV = "0.8"
CUDA = "4.4"
DocStringExtensions = "0.9"
Graphs = "1.9.0"
HDF5 = "0.17"
JLD2 = "0.4"
LabelledGraphs = "0.4.4"
MKL = "0.4.2"
MetaGraphs = "0.7"
SparseArrays = "1.9"
SpinGlassTensors = "1"
julia = "1.9, 1.10"

[extras]
Expand Down
3 changes: 3 additions & 0 deletions README.md
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@@ -1,2 +1,5 @@
[![Coverage Status](https://coveralls.io/repos/github/iitis/SpinGlassNetworks.jl/badge.svg?branch=master)](https://coveralls.io/github/iitis/SpinGlassNetworks.jl?branch=master)
# SpinGlassNetworks.jl
Part of SpinGlassPEPS package. It constitutes the basis for the preparation of tensors and operations on them.

We don't expect the user to interact with this package, as it is more of a "back-end" type. Nevertheless, we provide API references should the need arise.
18 changes: 10 additions & 8 deletions docs/make.jl
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@@ -1,21 +1,23 @@
using Documenter, SpinGlassNetworks

_pages = [
"Introduction" => "index.md",
"User guide" => "userguide.md",
"API Reference" => "api.md"
"Ising graph" => "ising.md",
"Lattice geometries" => "lattice.md",
"Clustered hamiltonian" => "clh.md",
"Local dimensional reduction" => "bp.md",
"API Reference for auxiliary functions" => "api.md",
]

# ============================
format = Documenter.HTML(edit_link = "master",
prettyurls = get(ENV, "CI", nothing) == "true",
)
format =
Documenter.HTML(edit_link = "master", prettyurls = get(ENV, "CI", nothing) == "true")

# format = Documenter.LaTeX(platform="none")

makedocs(
sitename="SpinGlassNetworks.jl",
sitename = "SpinGlassNetworks.jl",
modules = [SpinGlassNetworks],
pages = _pages,
format = format
)
format = format,
)
64 changes: 47 additions & 17 deletions docs/src/api.md
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# Library

---

```@meta
CurrentModule = SpinGlassNetworks
```

## Ising Graphs

```@docs
ising_graph
biases
couplings
cluster
inter_cluster_edges
prune
rank_vec
couplings
```

## Factor Graphs
## Clustered Hamiltonian
```@docs
split_into_clusters
decode_clustered_hamiltonian_state
rank_reveal
energy
energy_2site
cluster_size
bond_energy
exact_cond_prob
truncate_clustered_hamiltonian
```

## Belief propagation
```@docs
factor_graph
decode_factor_graph_state
local_energy
interaction_energy
get_neighbors
MergedEnergy
update_message
merge_vertices_cl_h
projector
SparseCSC
```

## Auxiliary Functions
## Projectors
```@docs
PoolOfProjectors
get_projector!
add_projector!
empty!
```

## Spectrum
```@docs
brute_force
energy
full_spectrum
Spectrum
matrix_to_integers
gibbs_tensor
rank_reveal
super_square_lattice
brute_force
```

## Truncate
```@docs
truncate_clustered_hamiltonian_1site_BP
truncate_clustered_hamiltonian_2site_energy
select_numstate_best
```

## Auxiliary Functions
```@docs
zephyr_to_linear
load_openGM
```
9 changes: 9 additions & 0 deletions docs/src/bp.md
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## Belief propagation

Local dimensional reduction can be achieved by selectively choosing states in the clustered Hamiltonian that have the lowest local energy in the cluster. This approach aims to reduce the dimensionality of the problem by focusing on the most relevant and energetically favorable states. It can be done by truncation based on energy or truncation based on Loopy Belief Propagation.

```@docs
clustered_hamiltonian_2site
belief_propagation
truncate_clustered_hamiltonian_2site_BP
```
24 changes: 24 additions & 0 deletions docs/src/clh.md
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# Introduction
A clustered Hamiltonian is a graphical representation that allows for a convenient and intuitive way to describe the structure of a network.

The concept of a clustered Hamiltonian within `SpinGlassNetworks.jl` introduces a mechanism for organizing spins into desired geometries, facilitating a structured approach to modeling complex spin systems. Analogous to a standard 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.

```@docs
clustered_hamiltonian
```

## Simple example

```@example
using SpinGlassNetworks
# Prepare simple instance
instance = "$(@__DIR__)/../../src/instances/square_diagonal/5x5/diagonal.txt"
ig = ising_graph(instance)
# Create clustered Hamiltonian
cl_h = clustered_hamiltonian(
ig,
cluster_assignment_rule = super_square_lattice((5,5,4))
)
```
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25 changes: 25 additions & 0 deletions docs/src/ising.md
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# Ising model

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:

$H = \sum_{(i,j) \in \mathcal{E}} J_{ij} s_i s_j + \sum_{i} h_i s_i$

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`.
```@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 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
# Create Ising instance
instance = "$(@__DIR__)/../../src/instances/square_diagonal/5x5/diagonal.txt"
ig = ising_graph(instance)
# View graph properties
@show biases(ig), couplings(ig)
```
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Registration pull request created: JuliaRegistries/General/104567

Tip: Release Notes

Did you know you can add release notes too? Just add markdown formatted text underneath the comment after the text
"Release notes:" and it will be added to the registry PR, and if TagBot is installed it will also be added to the
release that TagBot creates. i.e.

@JuliaRegistrator register

Release notes:

## Breaking changes

- blah

To add them here just re-invoke and the PR will be updated.

Tagging

After the above pull request is merged, it is recommended that a tag is created on this repository for the registered package version.

This will be done automatically if the Julia TagBot GitHub Action is installed, or can be done manually through the github interface, or via:

git tag -a v1.0.0 -m "<description of version>" fb35876f9bb3c767b0d7a39991024154d558f97d
git push origin v1.0.0

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