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| 1 | +++ a/README.mk | ||
| 1 | +[UTBM - LO53] - Python fingerprinting | ||
| 2 | +Achille Dantz <achille@dantz.fr> | ||
| 3 | + | ||
| 4 | +This program aims to compute the approximate location of a mobile terminal for a known set of Wi-Fi accesspoints in an ideal 12x12m space for which we have 9 fingerprinting values (known RSSI for each accesspoint at a given location) |
| 1 | +++ a/main.py | ||
| 1 | + | ||
| 2 | +from structure import * | ||
| 3 | +import sys | ||
| 4 | + | ||
| 5 | +Tf = [] #cells table | ||
| 6 | +testSample = RSSVector(-26, -42, -13, -46) | ||
| 7 | + | ||
| 8 | + | ||
| 9 | +#cells Table initialization | ||
| 10 | +for i in range (0, 3): | ||
| 11 | + Tf.append([]) | ||
| 12 | + for k in range (0,3): | ||
| 13 | + Tf[i].append([]) | ||
| 14 | + | ||
| 15 | +Tf[0][0] = Cell(RSSVector(-38,-27,-54,-13), Location(2,2)) | ||
| 16 | +Tf[0][1] = Cell(RSSVector(-74,-62,-48,-33), Location(2,6)) | ||
| 17 | +Tf[0][2] = Cell(RSSVector(-13,-28,-12,-40), Location(2,10)) | ||
| 18 | +Tf[1][0] = Cell(RSSVector(-34,-27,-38,-41), Location(6,2)) | ||
| 19 | +Tf[1][1] = Cell(RSSVector(-64,-48,-72,-35), Location(6,6)) | ||
| 20 | +Tf[1][2] = Cell(RSSVector(-45,-37,-20,-15), Location(6,10)) | ||
| 21 | +Tf[2][0] = Cell(RSSVector(-17,-50,-44,-33), Location(10,2)) | ||
| 22 | +Tf[2][1] = Cell(RSSVector(-27,-28,-32,-45), Location(10,6)) | ||
| 23 | +Tf[2][2] = Cell(RSSVector(-30,-20,-60,-40), Location(10,10)) | ||
| 24 | + | ||
| 25 | +def main(args): | ||
| 26 | + | ||
| 27 | + print(Tf[1][1].v.n2) | ||
| 28 | + | ||
| 29 | + | ||
| 30 | + print("\nk neighbors of test sample : ") | ||
| 31 | + neighborsCells = KNeighbors(Tf, testSample) | ||
| 32 | + for k in neighborsCells: | ||
| 33 | + print("(", k.location.x, ";", k.location.y, ")") | ||
| 34 | + | ||
| 35 | + print ("\ndistances : " + str(testSample.distances)) | ||
| 36 | + | ||
| 37 | + testLoc = Location(3,4,5) | ||
| 38 | + loc2 = Location(1,2,3) | ||
| 39 | + print((testLoc+loc2).toString()) | ||
| 40 | + | ||
| 41 | + a = resolve_barycenter(neighborsCells, testSample) | ||
| 42 | + print(a.toString) | ||
| 43 | + return 0; | ||
| 44 | + | ||
| 45 | + | ||
| 46 | +main(sys.argv) | ||
| 0 | \ No newline at end of file | 47 | \ No newline at end of file |
| 1 | +++ a/structure.py | ||
| 1 | +from operator import itemgetter | ||
| 2 | + | ||
| 3 | +class RSSVector(): | ||
| 4 | + distances = [] | ||
| 5 | + def __init__(self, n1, n2, n3, n4): | ||
| 6 | + self.n1 = n1 | ||
| 7 | + self.n2 = n2 | ||
| 8 | + self.n3 = n3 | ||
| 9 | + self.n4 = n4 | ||
| 10 | + | ||
| 11 | +class Location(): | ||
| 12 | + def __init(self): | ||
| 13 | + self.x = self.y = self.z = 0 | ||
| 14 | + | ||
| 15 | + def __init__(self, x, y, z=0): | ||
| 16 | + self.x = x | ||
| 17 | + self.y = y | ||
| 18 | + self.z = z | ||
| 19 | + | ||
| 20 | + def __mul__(self, multiplier): | ||
| 21 | + returnValue = Location(self.x, self.y, self.z) | ||
| 22 | + returnValue.x *= multiplier | ||
| 23 | + returnValue.y *= multiplier | ||
| 24 | + returnValue.z *= multiplier | ||
| 25 | + return returnValue | ||
| 26 | + def __rmul__(self, multiplier): | ||
| 27 | + return self * multiplier | ||
| 28 | + | ||
| 29 | + def __add__(self, added): | ||
| 30 | + returnValue = Location(self.x, self.y, self.z) | ||
| 31 | + returnValue.x += added.x | ||
| 32 | + returnValue.y += added.y | ||
| 33 | + returnValue.z += added.z | ||
| 34 | + return returnValue | ||
| 35 | + | ||
| 36 | + def toString(self): | ||
| 37 | + return "(" + str(self.x) + " ; " + str(self.y) + " ; " + str(self.z) + ")" | ||
| 38 | + | ||
| 39 | + | ||
| 40 | +class Cell(): | ||
| 41 | + def __init__(self, v_, loc): | ||
| 42 | + self.v = v_ | ||
| 43 | + self.location = loc | ||
| 44 | + | ||
| 45 | + | ||
| 46 | +def KNeighbors(fingerprints, sample): | ||
| 47 | + ''' | ||
| 48 | + Returns the 4 closest cells to the given sample and fills sample distance data | ||
| 49 | + :param Cell[3][3] fingerprints: 2D array of all the cells | ||
| 50 | + :param RSSIVector sample: Mobile terminal sample | ||
| 51 | + :return Cell[4]: the 4 nearest cells | ||
| 52 | + ''' | ||
| 53 | + distances = [] | ||
| 54 | + for row in fingerprints: | ||
| 55 | + for currentItem in row: | ||
| 56 | + dist = abs(currentItem.v.n1 - sample.n1) \ | ||
| 57 | + + abs(currentItem.v.n2 - sample.n2) \ | ||
| 58 | + + abs(currentItem.v.n3 - sample.n3) \ | ||
| 59 | + + abs(currentItem.v.n4 - sample.n4) | ||
| 60 | + distances.append((dist, currentItem)) | ||
| 61 | + distances = sorted(distances, key=itemgetter(0)) | ||
| 62 | + neighbours = [] | ||
| 63 | + for k in range (0,4): | ||
| 64 | + neighbours.append(distances[k][1]) | ||
| 65 | + sample.distances.append(distances[k][0]) | ||
| 66 | + return neighbours | ||
| 67 | + | ||
| 68 | + | ||
| 69 | + | ||
| 70 | +def resolve_barycenter(neighbourCells, sample): | ||
| 71 | + ''' | ||
| 72 | + Returns the weighted barycenter of the 4 neighbouring cells | ||
| 73 | + :param Cell[4] neighbourCells: Array containing the 4 closest cells | ||
| 74 | + :param RSSIVector sample: Sample of the mobile terminal | ||
| 75 | + :return Location: Estimated location of the mobile terminal | ||
| 76 | + ''' | ||
| 77 | + d = sample.distances #shorter notation | ||
| 78 | + a1,a2,a3,a4 = 1 / (1+d[0]/d[1]+d[0]/d[2]+d[0]/d[3]), 1 / (1+d[1]/d[0]+d[1]/d[2]+d[1]/d[3]), 1 / (1+d[2]/d[1]+d[2]/d[0]+d[2]/d[3]), 1 / (1+d[3]/d[1]+d[3]/d[2]+d[3]/d[0]) | ||
| 79 | + return a1*neighbourCells[0].location + a2*neighbourCells[1].location + a3*neighbourCells[1].location + a4*neighbourCells[1].location | ||
| 80 | + | ||
| 0 | \ No newline at end of file | 81 | \ No newline at end of file |