# (C) Copyright IBM Corp. 2019, 2020, 2021, 2022.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import numpy as np
from scipy.integrate import odeint
[docs]class LotkaVolterra:
def __init__(self, alpha=None, beta=None, gamma=None, delta=None):
self.alpha = alpha
self.beta = beta
self.gamma = gamma
self.delta = delta
[docs] def eval(self, state: np.ndarray = None, t: float = None) -> np.ndarray:
x = state[0]
y = state[1]
x_residual = self.alpha * x - self.beta * x * y
y_residual = self.delta * x * y - self.gamma * y
return np.array([x_residual, y_residual])
[docs] def run(self, initial_state, t):
solution = odeint(self.eval, initial_state, t)
return np.vstack(solution)