Upgrading to mango 0.5. Refactored tests.

Author: rcschrg

.github/workflows/test-do.yml

@@ -1,4 +1,4 @@
-name: Test DistributedOptimization.jl
+name: Test DistributedResourceOptimization.jl
 
 on: 
   push:
@@ -37,7 +37,7 @@ jobs:
       - uses: codecov/codecov-action@v5
         with:
           token: ${{ secrets.CODECOV_TOKEN }}
-          slug: Digitalized-Energy-Systems/DistributedOptimization.jl
+          slug: Digitalized-Energy-Systems/DistributedResourceOptimization.jl
           fail_ci_if_error: false
 
   test_linux:
@@ -61,5 +61,5 @@ jobs:
       - uses: codecov/codecov-action@v5
         with:
           token: ${{ secrets.CODECOV_TOKEN }}
-          slug: Digitalized-Energy-Systems/DistributedOptimization.jl
+          slug: Digitalized-Energy-Systems/DistributedResourceOptimization.jl
           fail_ci_if_error: false

CODE_OF_CONDUCT.md

@@ -1,4 +1,4 @@
-# Code of Conduct - DistributedOptimization.jl
+# Code of Conduct - DistributedResourceOptimization.jl
 
 ## Our Pledge
 

CONTRIBUTING.md

@@ -1,5 +1,5 @@
 <!-- omit in toc -->
-# Contributing to DistributedOptimization.jl
+# Contributing to DistributedResourceOptimization.jl
 
 First off, thanks for taking the time to contribute! ❤️
 
@@ -28,20 +28,20 @@ All types of contributions are encouraged and valued. See the [Table of Contents
 ## Code of Conduct
 
 This project and everyone participating in it is governed by the
-[DistributedOptimization.jl Code of Conduct](https://github.com/OFFIS-DAI/DistributedOptimization.jl/blob/master/CODE_OF_CONDUCT.md).
+[DistributedResourceOptimization.jl Code of Conduct](https://github.com/OFFIS-DAI/DistributedResourceOptimization.jl/blob/master/CODE_OF_CONDUCT.md).
 By participating, you are expected to uphold this code. Please report unacceptable behavior
 to <rico.schrage@uol.de>.
 
 
 ## I Have a Question
 
-> If you want to ask a question, we assume that you have read the available [Documentation](https://offis-dai.github.io/DistributedOptimization.jl/stable/).
+> If you want to ask a question, we assume that you have read the available [Documentation](https://offis-dai.github.io/DistributedResourceOptimization.jl/stable/).
 
-Before you ask a question, it is best to search for existing [Issues](https://github.com/OFFIS-DAI/DistributedOptimization.jl/issues) that might help you. In case you have found a suitable issue and still need clarification, you can write your question in this issue. It is also advisable to search the internet for answers first.
+Before you ask a question, it is best to search for existing [Issues](https://github.com/OFFIS-DAI/DistributedResourceOptimization.jl/issues) that might help you. In case you have found a suitable issue and still need clarification, you can write your question in this issue. It is also advisable to search the internet for answers first.
 
 If you then still feel the need to ask a question and need clarification, we recommend the following:
 
-- Open an [Issue](https://github.com/OFFIS-DAI/DistributedOptimization.jl/issues/new) with the label `question`.
+- Open an [Issue](https://github.com/OFFIS-DAI/DistributedResourceOptimization.jl/issues/new) with the label `question`.
 - Provide as much context as you can about what you're running into.
 - Provide project and platform versions (julia version, os, etc), depending on what seems relevant.
 
@@ -60,8 +60,8 @@ We will then take care of the issue as soon as possible.
 A good bug report shouldn't leave others needing to chase you up for more information. Therefore, we ask you to investigate carefully, collect information and describe the issue in detail in your report. Please complete the following steps in advance to help us fix any potential bug as fast as possible.
 
 - Make sure that you are using the latest version.
-- Determine if your bug is really a bug and not an error on your side e.g. using incompatible environment components/versions (Make sure that you have read the [documentation](https://offis-dai.github.io/DistributedOptimization.jl/stable/). If you are looking for support, you might want to check [this section](#i-have-a-question)).
-- To see if other users have experienced (and potentially already solved) the same issue you are having, check if there is not already a bug report existing for your bug or error in the [bug tracker](https://github.com/OFFIS-DAI/DistributedOptimization.jl/issues?q=label%3Abug).
+- Determine if your bug is really a bug and not an error on your side e.g. using incompatible environment components/versions (Make sure that you have read the [documentation](https://offis-dai.github.io/DistributedResourceOptimization.jl/stable/). If you are looking for support, you might want to check [this section](#i-have-a-question)).
+- To see if other users have experienced (and potentially already solved) the same issue you are having, check if there is not already a bug report existing for your bug or error in the [bug tracker](https://github.com/OFFIS-DAI/DistributedResourceOptimization.jl/issues?q=label%3Abug).
 - Also make sure to search the internet (including Stack Overflow) to see if users outside of the GitHub community have discussed the issue.
 - Collect information about the bug:
   - Stack trace (Traceback)
@@ -75,7 +75,7 @@ A good bug report shouldn't leave others needing to chase you up for more inform
 
 We use GitHub issues to track bugs and errors. If you run into an issue with the project:
 
-- Open an [Issue](https://github.com/OFFIS-DAI/DistributedOptimization.jl/issues/new). (Since we can't be sure at this point whether it is a bug or not, we ask you not to talk about a bug yet and not to label the issue.)
+- Open an [Issue](https://github.com/OFFIS-DAI/DistributedResourceOptimization.jl/issues/new). (Since we can't be sure at this point whether it is a bug or not, we ask you not to talk about a bug yet and not to label the issue.)
 - Explain the behavior you would expect and the actual behavior.
 - Please provide as much context as possible and describe the *reproduction steps* that someone else can follow to recreate the issue on their own. This usually includes your code. For good bug reports you should isolate the problem and create a reduced test case.
 - Provide the information you collected in the previous section.
@@ -90,36 +90,36 @@ Once it's filed:
 
 ### Suggesting Enhancements
 
-This section guides you through submitting an enhancement suggestion for DistributedOptimization.jl, **including completely new features and minor improvements to existing functionality**. Following these guidelines will help maintainers and the community to understand your suggestion and find related suggestions.
+This section guides you through submitting an enhancement suggestion for DistributedResourceOptimization.jl, **including completely new features and minor improvements to existing functionality**. Following these guidelines will help maintainers and the community to understand your suggestion and find related suggestions.
 
 <!-- omit in toc -->
 #### Before Submitting an Enhancement
 
 - Make sure that you are using the latest version.
-- Read the [documentation](https://offis-dai.github.io/DistributedOptimization.jl/stable/) carefully and find out if the functionality is already covered, maybe by an individual configuration.
-- Perform a [search](https://github.com/OFFIS-DAI/DistributedOptimization.jl/issues) to see if the enhancement has already been suggested. If it has, add a comment to the existing issue instead of opening a new one.
+- Read the [documentation](https://offis-dai.github.io/DistributedResourceOptimization.jl/stable/) carefully and find out if the functionality is already covered, maybe by an individual configuration.
+- Perform a [search](https://github.com/OFFIS-DAI/DistributedResourceOptimization.jl/issues) to see if the enhancement has already been suggested. If it has, add a comment to the existing issue instead of opening a new one.
 - Find out whether your idea fits with the scope and aims of the project. It's up to you to make a strong case to convince the project's developers of the merits of this feature. Keep in mind that we want features that will be useful to the majority of our users and not just a small subset. If you're just targeting a minority of users, consider writing an add-on/plugin library.
 
 <!-- omit in toc -->
 #### How Do I Submit a Good Enhancement Suggestion?
 
-Enhancement suggestions are tracked as [GitHub issues](https://github.com/OFFIS-DAI/DistributedOptimization.jl/issues).
+Enhancement suggestions are tracked as [GitHub issues](https://github.com/OFFIS-DAI/DistributedResourceOptimization.jl/issues).
 
 - Use a **clear and descriptive title** for the issue to identify the suggestion.
 - Provide a **step-by-step description of the suggested enhancement** in as many details as possible.
 - **Describe the current behavior** and **explain which behavior you expected to see instead** and why. At this point you can also tell which alternatives do not work for you.
-- **Explain why this enhancement would be useful** to most DistributedOptimization.jl users. You may also want to point out the other projects that solved it better and which could serve as inspiration.
+- **Explain why this enhancement would be useful** to most DistributedResourceOptimization.jl users. You may also want to point out the other projects that solved it better and which could serve as inspiration.
 
 ### Your First Code Contribution
 
-DistributedOptimization.jl follows the typical guidelines for Julia-projects and it is mainly developed using the vscode julia extension. 
+DistributedResourceOptimization.jl follows the typical guidelines for Julia-projects and it is mainly developed using the vscode julia extension. 
 
 The necessary steps for every contribution are:
 * Fork the repository.
 * Make your changes, ideally connected to an issue.
 * Make sure you followed the styleguide below.
 * Make sure you have written unit and integration tests.
-* Execute the DistributedOptimization.jl tests locally! Some tests require a running MQTT broker, for details take a look at (https://github.com/OFFIS-DAI/DistributedOptimization.jl/blob/development/.github/workflows/test-mango.yml).
+* Execute the DistributedResourceOptimization.jl tests locally! Some tests require a running MQTT broker, for details take a look at (https://github.com/OFFIS-DAI/DistributedResourceOptimization.jl/blob/development/.github/workflows/test-mango.yml).
 * Create a pull request.
 * Look at the output of github actions, we require that all tests pass and that the code-coverage of the diff is at least on par with the existing codebase
 * If all checks look fine, a maintainer will start to handle the pull request 

Project.toml

@@ -1,7 +1,7 @@
-name = "DistributedOptimization"
+name = "DistributedResourceOptimization"
 uuid = "bad89516-e02f-43f9-a1d3-8f2ce98dd1a2"
 authors = ["Rico Schrage"]
-repo = "https://github.com/Digitalized-Energy-Systems/DistributedOptimization.jl"
+repo = "https://github.com/Digitalized-Energy-Systems/DistributedResourceOptimization.jl"
 version = "0.1.0"
 
 [deps]
@@ -20,7 +20,7 @@ Distributions = "0.25.115"
 ECOS = "1.1.3"
 JuMP = "1.25.0"
 LinearAlgebra = "^1.9"
-Mango = "^0.4"
+Mango = "^0.5"
 OSQP = "0.8.1"
 Revise = "3.6.4"
 julia = "^1.9"

README.md

@@ -1,12 +1,13 @@
 ![lifecycle](https://img.shields.io/badge/lifecycle-experimental-blue.svg)
-[![MIT License](https://img.shields.io/badge/license-MIT-green.svg)](https://github.com/Digitalized-Energy-Systems/DistributedOptimization.jl/blob/development/LICENSE)
+[![MIT License](https://img.shields.io/badge/license-MIT-green.svg)](https://github.com/Digitalized-Energy-Systems/DistributedResourceOptimization.jl/blob/development/LICENSE)
 
 # Distributed Resource Optimization for Julia
 
-The package DistributedOptimization.jl (DO) aims to provide a collection of distributed optimization algorithms. The algorithms are implemented without considering one special communication technique or package. DO provides abstract types and function interfaces to implement so-called carriers, which are able to execute the distributed algorithms asynchronous. All algorithms can also be used without carrier using fitting @spawn or @async statements.
+The package DistributedResourceOptimization.jl (DRO) aims to provide a collection of distributed optimization algorithms for optimizing distributed resources. The algorithms are implemented without considering one special communication technique or package. DRO provides abstract types and function interfaces to implement so-called carriers, which are able to execute the distributed algorithms asynchronous. All algorithms can also be used without carrier using fitting @spawn or @async statements.
 
-Currently there are two tested algorithms:
+Currently there are three tested algorithms:
 * ADMM multi-value consensus such that the sum of all resp values equals a target vector
+* ADMM sharing variant on flexibility providing resources
 * COHDA, Combinatorial Optimization Heuristic for Distributed Agents, which minimizes the distance of schedule sums to a given target schedule
 
 There is one carrier implemented:
@@ -18,7 +19,7 @@ Note that the package is highly work in progress.
 
 ```julia
 using Mango
-using DistributedOptimization
+using DistributedResourceOptimization
 
 @role struct HandleOptimizationResultRole
     got_it::Bool = false
@@ -68,7 +69,7 @@ end
 
 ```julia
 using Mango
-using DistributedOptimization
+using DistributedResourceOptimization
 
 container = create_tcp_container("127.0.0.1", 5555)
 

test/consensus_admm_tests.jl renamed to test/admm/consensus_admm_tests.jl

@@ -1,5 +1,5 @@
 using Mango
-using DistributedOptimization
+using DistributedResourceOptimization
 using Test
 
 @role struct HandleOptimizationResultRole

test/sharing_admm_tests.jl renamed to test/admm/sharing_admm_tests.jl

@@ -1,5 +1,5 @@
 using Mango
-using DistributedOptimization
+using DistributedResourceOptimization
 using Test
 
 @role struct HandleOptimizationResultRole

test/cohda_local_search_tests.jl renamed to test/cohda/cohda_local_search_tests.jl

@@ -1,5 +1,5 @@
 using Mango
-using DistributedOptimization
+using DistributedResourceOptimization
 
 @testset "TestCOHDAWithMangoCarrier" begin
     container = create_tcp_container("127.0.0.1", 5555)

test/cohda_mango_tests.jl renamed to test/cohda/cohda_mango_tests.jl

@@ -1,7 +1,7 @@
 using Test
-using DistributedOptimization
+using DistributedResourceOptimization
 
-import DistributedOptimization: cohda_default_performance, merge_sysconfigs, merge_candidates,
+import DistributedResourceOptimization: cohda_default_performance, merge_sysconfigs, merge_candidates,
     perceive, decide
 
 @testset "TestCohdaDefaultPerformance" begin