main.py
1.63 KB
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from structure import RSSVector, Location, Cell, newCell, KNeighbors, resolve_barycenter, MarkovModel, MarkovValue
import sys
Tf = [] #cells table
testSamples = [RSSVector(-26, -42, -13, -46), RSSVector(-26, -42, -13, -46), RSSVector(-26, -42, -13, -46)]
testSample = testSamples[0]
#cells Table initialization
for i in range (0, 3):
Tf.append([])
for k in range (0,3):
Tf[i].append([])
#known fingerprints
Tf[0][0] = newCell(-38,-27,-54,-13,2,2)
Tf[0][1] = newCell(-74,-62,-48,-33,2,6)
Tf[0][2] = newCell(-13,-28,-12,-40,2,10)
Tf[1][0] = newCell(-34,-27,-38,-41,6,2)
Tf[1][1] = newCell(-64,-48,-72,-35,6,6)
Tf[1][2] = newCell(-45,-37,-20,-15,6,10)
Tf[2][0] = newCell(-17,-50,-44,-33,10,2)
Tf[2][1] = newCell(-27,-28,-32,-45,10,6)
Tf[2][2] = newCell(-30,-20,-60,-40,10,10)
def main(args):
#### K neighbours ####
print("\nk neighbors of test sample : ")
neighborsCells = KNeighbors(Tf, testSample)
for k in neighborsCells:
print("(", k.location.x, ";", k.location.y, ")")
#### Distances ####
print ("\ndistances : " + str(testSample.distances))
#### Barycenter ####
a = resolve_barycenter(neighborsCells, testSample.distances)
print(a.toString())
#### Markov ####
MM = MarkovModel(Tf)
MM.path([8,7,8,7,8,7,8,5,8,2,9,8,1,9,8,9])
MM.printValues()
print("")
MM.printPercentages()
print("\r\ncurrent cell is #" + str(MM.previousCell) + " , most likely next cell is #" + str(MM.getMostLikely()) + " which is located at " + str(Location.fromID(MM.getMostLikely()).toString()))
main(sys.argv)