Fix release version (#21)

andresliszt · Feb 7, 2025 · b7c2f9e · b7c2f9e
1 parent 97b6494
commit b7c2f9e
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Showing 6 changed files with 10 additions and 26 deletions.
diff --git a/Cargo.lock b/Cargo.lock
diff --git 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
@@ -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
@@ -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
@@ -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
@@ -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