From b7c2f9e2beaa309bf9d80af9ea010bf07c13ce8b Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Andr=C3=A9s=20Sandoval?= Date: Thu, 6 Feb 2025 21:17:07 -0300 Subject: [PATCH] Fix release version (#21) --- Cargo.lock | 2 +- Cargo.toml | 2 +- README.md | 9 +++------ docs/getting_started.md | 4 ++-- docs/user_guide/algorithms.md | 16 ---------------- mkdocs.yml | 3 +++ 6 files changed, 10 insertions(+), 26 deletions(-) diff --git a/Cargo.lock b/Cargo.lock index 80809aa..975e855 100644 --- a/Cargo.lock +++ b/Cargo.lock @@ -690,7 +690,7 @@ dependencies = [ [[package]] name = "pymoors" -version = "0.1.0" +version = "0.1.1-rc1" dependencies = [ "criterion", "ndarray 0.16.1", diff --git a/Cargo.toml b/Cargo.toml index af18583..9a374ee 100644 --- a/Cargo.toml +++ b/Cargo.toml @@ -1,6 +1,6 @@ [package] name = "pymoors" -version = "0.1.0" +version = "0.1.1-rc1" edition = "2021" [lib] diff --git a/README.md b/README.md index d877e55..9571b10 100644 --- a/README.md +++ b/README.md @@ -1,11 +1,8 @@ # pymoors ![License](https://img.shields.io/badge/License-MIT-blue.svg) -![Python 3.10](https://img.shields.io/badge/Python-3.10-blue.svg) -![Python 3.11](https://img.shields.io/badge/Python-3.11-blue.svg) -![Python 3.12](https://img.shields.io/badge/Python-3.12-blue.svg) -![Python 3.13](https://img.shields.io/badge/Python-3.13-blue.svg) -![Black](https://img.shields.io/badge/Code%20Style-Black-000000.svg) +![Python Versions](https://img.shields.io/badge/Python-3.10%20%7C%203.11%20%7C%203.12%20%7C%203.13-blue) [![codecov](https://codecov.io/gh/andresliszt/pymoors/graph/badge.svg)](https://codecov.io/gh/andresliszt/pymoors) +[![Docs](https://img.shields.io/website?label=Docs&style=flat&url=https%3A%2F%2Fandresliszt.github.io%2Fpymoors%2F)](https://andresliszt.github.io/pymoors/) ## Overview @@ -57,7 +54,7 @@ def knapsack_fitness(genes: TwoDArray) -> TwoDArray: quality_sum = np.sum(QUALITIES * genes, axis=1, keepdims=True) # We want to maximize profit and quality, - # so in pymoo we minimize the negative values + # so in pymoors we minimize the negative values f1 = -profit_sum f2 = -quality_sum return np.column_stack([f1, f2]) diff --git a/docs/getting_started.md b/docs/getting_started.md index 12c9a4b..f0da091 100644 --- a/docs/getting_started.md +++ b/docs/getting_started.md @@ -56,7 +56,7 @@ def knapsack_fitness(genes: TwoDArray) -> TwoDArray: quality_sum = np.sum(QUALITIES * genes, axis=1, keepdims=True) # We want to maximize profit and quality, - # so in pymoo we minimize the negative values + # so in pymoors we minimize the negative values f1 = -profit_sum f2 = -quality_sum return np.column_stack([f1, f2]) @@ -276,4 +276,4 @@ This simple problem has a known Pareto Optimal Each point on that curve represents a different trade-off between minimizing the distance to \((0,0)\) and to \((1,0)\). -![pymoo best front](images/pymoors_moo_real_pf.png) +![pymoors best front](images/pymoors_moo_real_pf.png) diff --git a/docs/user_guide/algorithms.md b/docs/user_guide/algorithms.md index 66121c5..89f6f2e 100644 --- a/docs/user_guide/algorithms.md +++ b/docs/user_guide/algorithms.md @@ -51,22 +51,6 @@ Thus, the Pareto front is given by: This continuous set of solutions along the boundary represents the trade-off between minimizing \( f_1 \) and \( f_2 \) within the given constraints. - -```python - -# Formulation in pymoors for a Constrained Multi-Objective Problem - -Consider the following mathematical formulation: - -\[ -\begin{aligned} -\min_{x_1, x_2} \quad & f_1(x_1,x_2) = x_1^2 + x_2^2 \\ -\min_{x_1, x_2} \quad & f_2(x_1,x_2) = (x_1-1)^2 + x_2^2 \\ -\text{subject to} \quad & x_1 + x_2 \leq 1, \\ -& x_1 \geq 0,\quad x_2 \geq 0. -\end{aligned} -\] - Below is how you can formulate and solve this problem in pymoors: ```python diff --git a/mkdocs.yml b/mkdocs.yml index 77712a9..b533ee5 100644 --- a/mkdocs.yml +++ b/mkdocs.yml @@ -4,6 +4,9 @@ theme: palette: scheme: default highlightjs: true +repo_url: https://github.com/andresliszt/pymoors +repo_name: "GitHub" + nav: - Home: index.md - Getting Started: getting_started.md