Solid is a Python framework for gradient-free optimization.
It contains basic versions of many of the most common optimization algorithms that do not require the calculation of gradients, and allows for very rapid development using them.
It's a very versatile library that's great for learning, modifying, and of course, using out-of-the-box.
See the detailed documentation here.
Current Features:
- Genetic Algorithm
- Evolutionary Algorithm
- Simulated Annealing
- Particle Swarm Optimization
- Tabu Search
- Harmony Search
- Stochastic Hill Climb
Usage:
pip install solidpy- Import the relevant algorithm
- Create a class that inherits from that algorithm, and that implements the necessary abstract methods
- Call its
.run()method, which always returns the best solution and its objective function value
Example:
from random import choice, randint, random
from string import lowercase
from Solid.EvolutionaryAlgorithm import EvolutionaryAlgorithm
class Algorithm(EvolutionaryAlgorithm):
"""
Tries to get a randomly-generated string to match string "clout"
"""
def _initial_population(self):
return list(''.join([choice(lowercase) for _ in range(5)]) for _ in range(50))
def _fitness(self, member):
return float(sum(member[i] == "clout"[i] for i in range(5)))
def _crossover(self, parent1, parent2):
partition = randint(0, len(self.population[0]) - 1)
return parent1[0:partition] + parent2[partition:]
def _mutate(self, member):
if self.mutation_rate >= random():
member = list(member)
member[randint(0,4)] = choice(lowercase)
member = ''.join(member)
return member
def test_algorithm():
algorithm = Algorithm(.5, .7, 500, max_fitness=None)
best_solution, best_objective_value = algorithm.run()
Testing
To run tests, look in the tests folder.
Use pytest; it should automatically find the test files.
Contributing
Feel free to send a pull request if you want to add any features or if you find a bug.
Check the issues tab for some potential things to do.
42 Dec 28, 2022
22 Dec 08, 2022
109 Dec 31, 2022
394 Dec 30, 2022
1 Dec 30, 2021
19 Dec 08, 2022
77 Nov 30, 2022
1 Jun 28, 2022
3.2k Jan 05, 2023
1.4k Jan 07, 2023
43 Dec 26, 2022
3 Jun 07, 2022
191 Dec 22, 2022
306 Jan 06, 2023
569 Dec 29, 2022
19 Nov 30, 2022
5.1k Jan 04, 2023
64 Dec 12, 2022
97 Jan 03, 2023
2 Dec 04, 2022