Start working on a proper test of the functionality

.github/workflows/ci.yml

@@ -36,12 +36,13 @@ jobs:
   checks:
     name: Check Python ${{ matrix.python-version }} on ${{ matrix.runs-on }}
     runs-on: ${{ matrix.runs-on }}
+    timeout-minutes: 15
     needs: [pre-commit]
     strategy:
       fail-fast: false
       matrix:
         python-version: ["3.8", "3.11"]
-        runs-on: [ubuntu-latest, macos-latest]
+        runs-on: [ubuntu-latest]
 
     steps:
       - uses: actions/checkout@v3

README.md

@@ -15,22 +15,25 @@ steps:
 - clone the repo
 - install the module in a virtual environment with `pip install -e .`
 - initialise submodules with `git submodule update --init --recursive`
+  - if you're having problems, you can directly clone poke-env with
+    `git clone https://github.com/aoifehughes/poke-env.git`
 - cd into `poke-env` and run `pip install -e .`
 - cd back to the root directory and clone the `pokemon-showdown` repo with
   `git clone https://github.com/smogon/pokemon-showdown`
-- install with `npm install pokemon-showdown` in the `pokemon-showdown`
-  directory
+- if you don't have node, install it with `brew install node` (mac) or
+  `sudo apt install nodejs` (linux)
+- install with `npm install` in the `pokemon-showdown` directory
 - start a local server with `node pokemon-showdown start --no-security` in the
   `pokemon-showdown` directory
-- cd back to the root directory and run `python run.py` to run the demo!
+- to run a small demo, you should be able to just run `p2lab` from the command
+  line!
 
 or via Docker:
 
 `docker build -t p2:latest .` `docker run -it p2:latest`
 `docker exec -it your_container_id /bin/bash`
 
-then go to the P2 root and run the script. Run docker build with `--no-cache` to
-rebuild with newer versions of the repos.
+Run docker build with `--no-cache` to rebuild with newer versions of the repos.
 
 ## Components
 

pyproject.toml

@@ -8,7 +8,7 @@ name = "p2lab"
 authors = [
   { name = "Scientists of the P2 Laboratory", email = "[email protected]" },
 ]
-description = "a secret package for genetic optimisation of pokemon teams"
+description = "a package for genetic optimisation of pokemon teams"
 readme = "README.md"
 requires-python = ">=3.8"
 classifiers = [
@@ -37,14 +37,10 @@ dependencies = [
 ]
 
 [project.optional-dependencies]
-
 test = [
   "pytest >=6",
   "pytest-cov >=3",
-]
-dev = [
-  "pytest >=6",
-  "pytest-cov >=3",
+  "pytest-asyncio",
 ]
 docs = [
   "sphinx>=4.0",
@@ -64,6 +60,7 @@ version.path = "src/p2lab/__init__.py"
 envs.default.dependencies = [
   "pytest",
   "pytest-cov",
+  "pytest-asyncio",
 ]
 
 

src/p2lab/genetic/genetic.py

@@ -115,54 +115,56 @@ async def genetic_algorithm(
 
     # Genetic Loop
     for i in range(num_generations):
-        # Step 1: selection
-        # An odd number of teams is an edge case for crossover, as it uses 2 teams
-        # at a time. This adds an extra team to selection if we are using crossover.
-        # the extra team will be removed by the crossover function.
-        extra = num_teams % 2 - mutate_with_fitness
-
-        # Returns new fitnesses in case we are doing fitness-mutate
-        new_teams, new_fitness = selection(
-            teams=teams,
-            fitness=fitness,
-            num_teams=num_teams + extra,
-        )
-
-        # Step 2: crossover
-        # Only do this step if not mutating with fitness, as fitness scores become
-        # invalid after crossover if doing so
-        if not mutate_with_fitness:
-            new_teams = crossover_fn(
-                teams=new_teams,
-                num_teams=num_teams,
-                num_pokemon=team_size,
-                crossover_prob=crossover_prob,
-                allow_all=allow_all,
+        # account for team size of 1
+        if team_size != 1:
+            # Step 1: selection
+            # An odd number of teams is an edge case for crossover, as it uses 2 teams
+            # at a time. This adds an extra team to selection if we are using crossover.
+            # the extra team will be removed by the crossover function.
+            extra = num_teams % 2 - mutate_with_fitness
+
+            # Returns new fitnesses in case we are doing fitness-mutate
+            new_teams, new_fitness = selection(
+                teams=teams,
+                fitness=fitness,
+                num_teams=num_teams + extra,
             )
 
-        # Step 3: mutate
-        # If mutating with fitness, skip the crossover step. Otherwise, crossover +
-        # mutate.
-        if mutate_with_fitness:
-            teams = fitness_mutate(
-                teams=new_teams,
-                num_pokemon=team_size,
-                fitness=new_fitness,
-                pokemon_population=pokemon_pool,
-                allow_all=allow_all,
-                k=mutate_k,
-            )
-
-        else:
-            # Mutate the new teams
-            teams = mutate(
-                teams=new_teams,
-                num_pokemon=team_size,
-                mutate_prob=mutate_prob,
-                pokemon_population=pokemon_pool,
-                allow_all=allow_all,
-                k=mutate_k,
-            )
+            # Step 2: crossover
+            # Only do this step if not mutating with fitness, as fitness scores become
+            # invalid after crossover if doing so
+            if not mutate_with_fitness:
+                new_teams = crossover_fn(
+                    teams=new_teams,
+                    num_teams=num_teams,
+                    num_pokemon=team_size,
+                    crossover_prob=crossover_prob,
+                    allow_all=allow_all,
+                )
+
+            # Step 3: mutate
+            # If mutating with fitness, skip the crossover step. Otherwise, crossover +
+            # mutate.
+            if mutate_with_fitness:
+                teams = fitness_mutate(
+                    teams=new_teams,
+                    num_pokemon=team_size,
+                    fitness=new_fitness,
+                    pokemon_population=pokemon_pool,
+                    allow_all=allow_all,
+                    k=mutate_k,
+                )
+
+            else:
+                # Mutate the new teams
+                teams = mutate(
+                    teams=new_teams,
+                    num_pokemon=team_size,
+                    mutate_prob=mutate_prob,
+                    pokemon_population=pokemon_pool,
+                    allow_all=allow_all,
+                    k=mutate_k,
+                )
 
         # Generate matches from list of teams
         matches = match_fn(teams)

tests/test_workflow.py

@@ -0,0 +1,61 @@
+from __future__ import annotations
+
+import numpy as np
+import pytest
+
+from p2lab.genetic.genetic import genetic_algorithm
+from p2lab.genetic.operations import (
+    build_crossover_fn,
+)
+from p2lab.pokemon.premade import gen_1_pokemon
+from p2lab.pokemon.teams import generate_teams, import_pool
+
+
+@pytest.mark.asyncio()
+@pytest.mark.parametrize(
+    ("team_size", "crossover_fn"),
+    [
+        (1, None),
+        # (2, None),
+        # (6, locus_swap),
+        # (6, slot_swap),
+        # (6, sample_swap),
+    ],
+)
+async def test_main_loop(team_size, crossover_fn):
+    num_teams = 10
+    # generate the pool
+    pool = import_pool(gen_1_pokemon())
+    seed_teams = generate_teams(pool, num_teams, team_size, unique=True)
+    crossover_fn = (
+        build_crossover_fn(crossover_fn) if crossover_fn is not None else None
+    )
+    # run the genetic algorithm
+    teams, fitnesses = await genetic_algorithm(
+        pokemon_pool=pool,
+        seed_teams=seed_teams,
+        num_teams=num_teams,
+        team_size=team_size,
+        num_generations=3,
+        progress_bars=True,
+        crossover_fn=crossover_fn,
+        mutate_with_fitness=crossover_fn is None,
+        mutate_k=1,
+    )
+
+    print("Best team:")
+    best_team = teams[np.argmax(fitnesses)]
+    fitness = fitnesses[np.argmax(fitnesses)]
+    for mon in best_team.pokemon:
+        print(mon.formatted)
+
+    print(f"Fitness: {fitness}")
+
+    print("Worst team:")
+
+    worst_team = teams[np.argmin(fitnesses)]
+    fitness = fitnesses[np.argmin(fitnesses)]
+    for mon in worst_team.pokemon:
+        print(mon.formatted)
+
+    print(f"Fitness: {fitness}")