Source code for pyswarms.utils.decorators.decorators

# Import modules
import numpy as np
from functools import wraps

[docs]def cost(cost_func): """A decorator for the cost function This decorator allows the creation of much simpler cost functions. Instead of writing a cost function that returns a shape of :code:`(n_particles, 0)` it enables the usage of shorter and simpler cost functions that directly return the cost. A simple example might be: .. code-block:: python import pyswarms import numpy as np @pyswarms.cost def cost_func(x): cost = np.abs(np.sum(x)) return cost The decorator expects your cost function to use a d-dimensional array (where d is the number of dimensions for the optimization) as and argument. .. note:: Some :code:`numpy` functions return a :code:`np.ndarray` with single values in it. Be aware of the fact that without unpacking the value the optimizer will raise an exception. Parameters ---------- cost_func : callable A callable object that can be used as cost function in the optimization (must return a :code:`float` or an :code:`int`). Returns ------- callable The vectorized output for all particles as defined by :code:`cost_func` """ @wraps(cost_func) def cost_dec(particles, **kwargs): n_particles = particles.shape[0] vector = np.array( [cost_func(particles[i], **kwargs) for i in range(n_particles)] ) if vector.shape != (n_particles,): msg = "Cost function must return int or float. You passed: {}" cost_return_type = type(cost_func(particles[0], **kwargs)) raise ValueError(msg.format(cost_return_type)) return vector return cost_dec