Instantly share code, notes, and snippets.

Embed
What would you like to do?
Ant Colony Neighbourhood Function
def get_probability(self, d, y, x, n, c):
"""
This gets the probability of drop / pickup for any given Datum, d
:param d: the datum
:param x: the x location of the datum / ant carrying datum
:param y: the y location of the datum / ant carrying datum
:param n: the size of the neighbourhood function
:param c: constant for convergence control
:return: the probability of
"""
# Starting x and y locations
y_s = y - n
x_s = x - n
total = 0.0
# For each neighbour
for i in range((n*2)+1):
xi = (x_s + i) % self.dim[0]
for j in range((n*2)+1):
# If we are looking at a neighbour
if j != x and i != y:
yj = (y_s + j) % self.dim[1]
# Get the neighbour, o
o = self.grid[xi][yj]
# Get the similarity of o to x
if o is not None:
s = d.similarity(o)
total += s
# Normalize the density by the max seen distance to date
# (math.pow((n*2)+1, 2) - 1) is the number of points considered
md = total / (math.pow((n*2)+1, 2) - 1)
# Update the maximum distance seen
if md > self.max_d:
self.max_d = md
# Compute the density function and return it
density = total / (self.max_d * (math.pow((n*2)+1, 2) - 1))
density = max(min(density, 1), 0)
t = math.exp(-c * density)
probability = (1-t)/(1+t)
return probability
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment