modify paper.md

paper/paper.md

@@ -39,9 +39,9 @@ Leveraging the principles of object-oriented programming (OOP) and the meta-prog
 
 As one of the earliest developed optimization algorithms [@holland; @katoch], the genetic algorithm (GA) has found extensive application across various domains and has undergone modifications and integrations with new algorithms [@alam; @cheng; @katoch]. The principles of GA will not be reviewed in this article. For a detailed understanding, please refer to references [@holland; @simon] and the associated literatures.
 
-In a typical Python implementation, populations are initially defined as lists of individuals, with each individual represented by a chromosome composed of a list of genes. Creating an individual can be achieved utilizing either the standard library's `array` or the widely-used third-party library [`numpy`](https://numpy.org/) [@numpy]. Following this, evolutionary operators are defined and applied to these structures.
+In a typical Python implementation, populations are initially defined as lists of individuals, with each individual represented by a chromosome composed of a list of genes. Creating an individual can be achieved utilizing either the standard library's `array` or the widely-used third-party library [`numpy`](https://numpy.org/) [@numpy]. The evolutionary operators are defined and applied to these structures.
 
-A concise comparison between `pyrimidine` and several popular frameworks is provided in \autoref{frameworks}, such as [`DEAP`](https://deap.readthedocs.io/) [@fortin] and [`gaft`](https://github.com/PytLab/gaft), which have significantly influenced the design of `pyrimidine`.
+A concise comparison between `pyrimidine` and other frameworks is provided in \autoref{frameworks}, such as [`DEAP`](https://deap.readthedocs.io/) [@fortin] and [`gaft`](https://github.com/PytLab/gaft), which have significantly influenced the design of `pyrimidine`.
 
 <!-- +-------------------+------------+----------+----------+----------+ -->
 | Library   | Design Style      | Versatility | Extensibility | Visualization           |

pyrimidine/misc/__init__.py

@@ -1,4 +1,7 @@
 #!/usr/bin/env python3
 
 from .aco import *
-from .fa import *
+from .fa import *
+from .gsa import *
+from .sma import *
+from .ssa import *

tests/test_ga.py

@@ -1,5 +1,11 @@
 #!/usr/bin/env python3
 
+"""
+Test for Classical Genetic Algo.
+
+HOFPopulation: Population with a hof.
+"""
+
 from pyrimidine import HOFPopulation
 
 class TestGA: