Update behaviors.py

A "normalized" option was implemented in the lennard_jones behavior.

README.md

@@ -2,7 +2,7 @@
 [![Tests](https://github.com/mrsonandrade/pyswarming/actions/workflows/tests_package.yml/badge.svg)](https://github.com/mrsonandrade/pyswarming/actions/workflows/tests_package.yml)
 [![Project Status: Active – The project has reached a stable, usable state and is being actively developed.](https://www.repostatus.org/badges/latest/active.svg)](https://www.repostatus.org/#active)
 [![Documentation Status](https://readthedocs.org/projects/pyswarming/badge/?version=latest)](https://pyswarming.readthedocs.io/en/latest/?badge=latest)
-![version](https://img.shields.io/badge/version-1.1.4-blue)
+![version](https://img.shields.io/badge/version-1.1.5-blue)
 [![Downloads](https://static.pepy.tech/personalized-badge/pyswarming?period=total&units=none&left_color=black&right_color=blue&left_text=Downloads)](https://pepy.tech/project/pyswarming)
 [![DOI](https://joss.theoj.org/papers/10.21105/joss.05647/status.svg)](https://doi.org/10.21105/joss.05647)
 

pyswarming/__init__.py

@@ -38,6 +38,6 @@
         __all__.append(module_j)
 
 name = "pyswarming"
-__version__ = "1.1.4"
+__version__ = "1.1.5"
 __author__ = "Emerson Martins de Andrade, Antonio Carlos Fernandes and Joel Sena Sales Jr"
 __author_email__ = "[email protected]"

pyswarming/behaviors.py

@@ -515,7 +515,7 @@ def preferred_direction(theta_i, k_i, w=0.0):
     return new_theta_i
 
 
-def lennard_jones(r_i, r_j, epsilon, sigma):
+def lennard_jones(r_i, r_j, epsilon, sigma, normalized=False):
     """
     Calculates an output force that produces
     lattice formations, based on the "Lennard-Jones
@@ -538,6 +538,10 @@ def lennard_jones(r_i, r_j, epsilon, sigma):
     sigma : float
         desired distance between the robots.
 
+    normalized : boolean
+        boolean parameter to normalize each
+        term in the sum when normalized = True.
+
     Returns
     -------
     f_i : numpy.array
@@ -550,7 +554,13 @@ def lennard_jones(r_i, r_j, epsilon, sigma):
 
     for j in r_j:
         r_ij = (j - r_i)
-        f_i += ((12.0*epsilon)/r_ij) * (np.power(sigma/r_ij, 12) - np.power(sigma/r_ij, 6)) * (r_ij / np.linalg.norm(r_ij))
+
+        if normalized == True:
+            normalization_term = (r_ij / np.linalg.norm(r_ij))
+        else: 
+            normalization_term = 1.0
+
+        f_i += ((12.0*epsilon)/r_ij) * (np.power(sigma/r_ij, 12) - np.power(sigma/r_ij, 6)) * normalization_term
 
     f_i = (1.0/N) * f_i
 

setup.py

@@ -12,7 +12,7 @@
 
 setuptools.setup(
     name="pyswarming",
-    version="1.1.4",
+    version="1.1.5",
     author="Emerson Martins de Andrade",
     author_email="[email protected]",
     description="A research toolkit for Swarm Robotics",

tests/test_behaviors.py

@@ -348,7 +348,7 @@ def test_lennard_jones():
     for r_ind in range(len(r)):
         r_i = r[r_ind]
         r_j = np.delete(r, np.array([r_ind]), axis=0)
-        f[r_ind] += pb.lennard_jones(r_i, r_j, epsilon, sigma)
+        f[r_ind] += pb.lennard_jones(r_i, r_j, epsilon, sigma, normalized=True)
     assert type(f) == np.ndarray
     assert len(f) > 0
     assert (f!=f0).all() == True