def returnSumOfThroughput(self, bsnumber, step):
ue = devices.UE()
sumOfInternalThroughput = 0
internalBS = 0
sumOfExternalThroughput = 0
externalBS = 0
for x in range(0, round(self.constraintAreaMaxX), step):
for y in range(0, round(self.constraintAreaMaxY), step):
ue.x = x
ue.y = y
ue.connectToNearestBS(self.bs)
if ue.connectedToBS == bsnumber:
#if ue.distanceToBS(self.bs[bsnumber]) < self.bs[bsnumber].mi * self.bs[bsnumber].Rc:
if ue.inside:
sumOfInternalThroughput = sumOfInternalThroughput + ue.calculateMaxThroughputOfTheNode(
self.bs)
internalBS = internalBS + 1
else:
sumOfExternalThroughput = sumOfExternalThroughput + ue.calculateMaxThroughputOfTheNode(
self.bs)
externalBS = externalBS + 1
if externalBS != 0:
sumOfExternalThroughput = sumOfExternalThroughput / externalBS
if internalBS != 0:
sumOfInternalThroughput = sumOfInternalThroughput / internalBS
sumOfThroughput = sumOfExternalThroughput + sumOfInternalThroughput
return sumOfThroughput
def insertUErandomly(self, numberOfDevices):
number = 0
for i in range(0, numberOfDevices):
ue = devices.UE()
ue.ID = number
ue.x = random.uniform(0, self.parent.constraintAreaMaxX)
ue.y = random.uniform(0, self.parent.constraintAreaMaxY)
self.parent.ue.append(ue)
number = number+1
def insertUEingrid(self, numberOfDevices):
numberOfNodesInRow = math.ceil(math.sqrt(numberOfDevices))
number = 0
x_step = int(self.parent.constraintAreaMaxX)/numberOfNodesInRow
y_step = int(self.parent.constraintAreaMaxY)/numberOfNodesInRow
for x_pos in range(0, numberOfNodesInRow):
for y_pos in range(0, numberOfNodesInRow):
ue = devices.UE()
ue.ID = number
ue.x = 0.5*x_step + (x_pos*x_step)
ue.y = 0.5*y_step + (y_pos*y_step)
self.parent.ue.append(ue)
number = number+1
def insertUEingroup(self, numberOfDevices, percentSpace):
number = 0
center_x = 0.5 + random.uniform(-(0.5 - percentSpace / 200),
(0.5 - percentSpace / 200))
center_y = 0.5 + random.uniform(-(0.5 - percentSpace / 200),
(0.5 - percentSpace / 200))
print("percentSpace = ", percentSpace)
print("center_x = ", center_x)
print("center_y = ", center_y)
for i in range(0, numberOfDevices):
ue = devices.UE()
ue.ID = number
min_x = (center_x -
percentSpace / 200) * self.parent.constraintAreaMaxX
max_x = (center_x +
percentSpace / 200) * self.parent.constraintAreaMaxX
min_y = (center_y -
percentSpace / 200) * self.parent.constraintAreaMaxY
max_y = (center_y +
percentSpace / 200) * self.parent.constraintAreaMaxY
ue.x = random.uniform(min_x, max_x)
ue.y = random.uniform(min_y, max_y)
self.parent.ue.append(ue)
number = number + 1
def loadNodesFromKMLFile(self, filename, numberOfDevices):
ppk = PointPolygonKML(self)
xyp = ppk.generatePointsFromKML(filename, numberOfDevices)
lat_min = 999
long_min = 999
for row in xyp:
if row.x < long_min: long_min = row.x
if row.y < lat_min: lat_min = row.y
R = 6371e3
number = 0
max_x = 0
max_y = 0
for row in xyp:
fi1 = math.radians(row.y)
fi2 = math.radians(lat_min)
deltafi = math.radians(row.y - lat_min)
deltalambda = math.radians(row.x - long_min)
a = math.sin(deltafi / 2.0) * math.sin(
deltafi / 2.0) + math.cos(fi1) * math.cos(fi2) * math.sin(
deltalambda / 2.0) * math.sin(deltalambda / 2.0)
c = 2 * math.atan2(math.sqrt(a), math.sqrt(1 - a))
d = R * c
fi1 = math.radians(row.y)
fi2 = math.radians(lat_min)
deltafi = math.radians(row.y - lat_min)
deltalambda = math.radians(row.x - row.x)
a = math.sin(deltafi / 2.0) * math.sin(
deltafi / 2.0) + math.cos(fi1) * math.cos(fi2) * math.sin(
deltalambda / 2.0) * math.sin(deltalambda / 2.0)
c = 2 * math.atan2(math.sqrt(a), math.sqrt(1 - a))
y = R * c
fi1 = math.radians(row.y)
fi2 = math.radians(row.y)
deltafi = math.radians(row.y - lat_min)
deltalambda = math.radians(row.x - long_min)
a = math.sin(deltafi / 2.0) * math.sin(
deltafi / 2.0) + math.cos(fi1) * math.cos(fi2) * math.sin(
deltalambda / 2.0) * math.sin(deltalambda / 2.0)
c = 2 * math.atan2(math.sqrt(a), math.sqrt(1 - a))
x = R * c
if type(self.parent) is network.LoRaNetwork:
ue = devices.Node(self.parent)
else:
ue = devices.UE(self.parent)
if max_x < x: max_x = x
if max_y < y: max_y = y
print("gen", number, x, y, row.x, row.y)
ue.x = x
ue.y = y
ue.lat = row.y
ue.long = row.x
ue.height = 15
ue.ID = number
self.parent.ue.append(ue)
number = number + 1
# print(len(self.parent.ue), "wspolrzednych dodane, teraz kubelki")
# print("lat", lat, "long", long, "d", round(d,2), "x", round(x,2), "y", round(y,2))
self.parent.constraintAreaMaxX = int(max_x + 0.05 * max_x)
self.parent.constraintAreaMaxY = int(max_y + 0.05 * max_y)
for ue in self.parent.ue:
self.addToBucket(ue.ID, ue.x, ue.y)
def loadNodesFromFile(self, filename):
# print("Jestem w loadNodesFromFile")
file = open(filename)
file.readline()
networkcsv = csv.reader(file, delimiter=';')
lat_min = 999
long_min = 999
for row in networkcsv:
if len(row) == 5:
lat = float(row[1].replace(',', '.'))
long = float(row[2].replace(',', '.'))
if int(lat) == 0 or int(long) != 0:
if lat < lat_min: lat_min = lat
if long < long_min: long_min = long
file.seek(0)
file.readline()
# print(lat_min, long_min)
# print("min maks znaleziony")
R = 6371e3
number = 0
max_x = 0
max_y = 0
for row in networkcsv:
if len(row) == 5:
lat = float(row[1].replace(',', '.'))
long = float(row[2].replace(',', '.'))
height = float(row[3].replace(',', '.'))
dtype = int(row[4])
if int(lat) == 0 or int(long) != 0:
fi1 = math.radians(lat)
fi2 = math.radians(lat_min)
deltafi = math.radians(lat - lat_min)
deltalambda = math.radians(long - long_min)
a = math.sin(deltafi / 2.0) * math.sin(
deltafi /
2.0) + math.cos(fi1) * math.cos(fi2) * math.sin(
deltalambda / 2.0) * math.sin(deltalambda / 2.0)
c = 2 * math.atan2(math.sqrt(a), math.sqrt(1 - a))
d = R * c
fi1 = math.radians(lat)
fi2 = math.radians(lat_min)
deltafi = math.radians(lat - lat_min)
deltalambda = math.radians(long - long)
a = math.sin(deltafi / 2.0) * math.sin(
deltafi /
2.0) + math.cos(fi1) * math.cos(fi2) * math.sin(
deltalambda / 2.0) * math.sin(deltalambda / 2.0)
c = 2 * math.atan2(math.sqrt(a), math.sqrt(1 - a))
y = R * c
fi1 = math.radians(lat)
fi2 = math.radians(lat)
deltafi = math.radians(lat - lat_min)
deltalambda = math.radians(long - long_min)
a = math.sin(deltafi / 2.0) * math.sin(
deltafi /
2.0) + math.cos(fi1) * math.cos(fi2) * math.sin(
deltalambda / 2.0) * math.sin(deltalambda / 2.0)
c = 2 * math.atan2(math.sqrt(a), math.sqrt(1 - a))
x = R * c
if type(self.parent) is network.LoRaNetwork:
ue = devices.Node(self.parent)
else:
ue = devices.UE(self.parent)
if max_x < x: max_x = x
if max_y < y: max_y = y
ue.x = x
ue.y = y
ue.lat = lat
ue.long = long
ue.height = height
ue.type = dtype
ue.ID = number
self.parent.ue.append(ue)
number = number + 1
# print(len(self.parent.ue), "wspolrzednych dodane, teraz kubelki")
# print("lat", lat, "long", long, "d", round(d,2), "x", round(x,2), "y", round(y,2))
self.parent.constraintAreaMaxX = int(max_x + 0.05 * max_x)
self.parent.constraintAreaMaxY = int(max_y + 0.05 * max_y)
# print("X", self.parent.constraintAreaMaxX / 1000, "Y", self.parent.constraintAreaMaxY / 1000)
for ue in self.parent.ue:
# None
self.addToBucket(ue.ID, ue.x, ue.y)
# print("kubelki dodane")
file.close()
def drawNetwork(self,
filename,
BS=True,
UE=True,
links=True,
obstacles=True,
fillMethod="SINR",
colorMap=None,
drawLegend=True,
tilesInLine=100,
figSize=(8, 8),
colorMinValue=None,
colorMaxValue=None,
outputFileFormat=["png"]):
main_draw = plt.figure(1, figsize=figSize)
ax = main_draw.add_subplot(111)
if fillMethod == "SINR":
if colorMap == None:
cm = plt.cm.get_cmap("viridis")
else:
cm = plt.cm.get_cmap(colorMap)
ue = devices.UE()
imageMatrix = np.zeros((tilesInLine, tilesInLine))
d_x = round(self.parent.constraintAreaMaxX / tilesInLine)
d_y = round(self.parent.constraintAreaMaxY / tilesInLine)
for x in range(0, tilesInLine):
for y in range(0, tilesInLine):
ue.x = x * d_x
ue.y = y * d_y
ue.connectToTheBestBS(self.parent.bs,
self.parent.obstacles)
SINR = ue.calculateSINR(self.parent.bs,
self.parent.obstacles)
imageMatrix[y][x] = SINR
if colorMinValue != None:
colorMin = colorMinValue
else:
colorMin = imageMatrix.min()
if colorMaxValue != None:
colorMax = colorMaxValue
else:
colorMax = imageMatrix.max()
image = plt.imshow(imageMatrix,
vmin=colorMin,
vmax=colorMax,
origin='lower',
extent=[
0, self.parent.constraintAreaMaxX, 0,
self.parent.constraintAreaMaxY
],
interpolation='nearest',
cmap=cm)
if drawLegend == True:
from mpl_toolkits.axes_grid1 import make_axes_locatable
divider = make_axes_locatable(ax)
cax1 = divider.append_axes("right", size="5%", pad=0.05)
cbar = plt.colorbar(image, cax=cax1)
#cbar.set_clim(-60, 50)
#cbar.ax.set_yticklabels(['0','1','2','>3'])
#cbar.set_label('# of contacts', rotation=270)
elif fillMethod == "Sectors":
if colorMap == None:
cm = plt.cm.get_cmap("Paired")
else:
cm = plt.cm.get_cmap(colorMap)
ue = devices.UE()
imageMatrix = np.zeros((tilesInLine, tilesInLine))
d_x = round(self.parent.constraintAreaMaxX / tilesInLine)
d_y = round(self.parent.constraintAreaMaxY / tilesInLine)
for x in range(0, tilesInLine):
for y in range(0, tilesInLine):
RSSI_best = -1000
BS_best = -1
for bs in self.parent.bs:
ue.x = x * d_x
ue.y = y * d_y
if ue.isSeenFromBS(bs) == False:
continue
ue.connectedToBS = bs.ID
temp_RSSI = ue.calculateSINR(self.parent.bs)
if temp_RSSI > RSSI_best:
RSSI_best = temp_RSSI
BS_best = bs.ID
imageMatrix[y][x] = BS_best
plt.imshow(imageMatrix,
origin='lower',
extent=[
0, self.parent.constraintAreaMaxX, 0,
self.parent.constraintAreaMaxY
],
interpolation='nearest',
cmap=cm)
if BS == True:
bs_x_locations = []
bs_y_locations = []
for bs in self.parent.bs:
bs_x_locations.append(bs.x)
bs_y_locations.append(bs.y)
ax.plot(bs_x_locations,
bs_y_locations,
'r^',
color="black",
markersize=10)
if UE == True:
ue_x_locations = []
ue_y_locations = []
for ue in self.parent.ue:
ue_x_locations.append(ue.x)
ue_y_locations.append(ue.y)
ax.plot(ue_x_locations,
ue_y_locations,
'b*',
color="black",
markersize=10)
if links == True:
for ue in self.parent.ue:
ax.arrow(ue.x, ue.y, self.parent.bs[ue.connectedToBS].x - ue.x,
self.parent.bs[ue.connectedToBS].y - ue.y)
if obstacles == True:
for obstacle in self.parent.obstacles:
ax.arrow(obstacle[0], obstacle[1], obstacle[2] - obstacle[0],
obstacle[3] - obstacle[1])
networkBorder = plt.Rectangle((0, 0),
self.parent.constraintAreaMaxX,
self.parent.constraintAreaMaxY,
color='black',
fill=False)
ax.add_patch(networkBorder)
ax.axis('equal')
ax.axis([
0, self.parent.constraintAreaMaxX, 0,
self.parent.constraintAreaMaxY
])
ax.axis('off')
ax.xaxis.set_visible(False)
ax.yaxis.set_visible(False)
for outputFormat in outputFileFormat:
if outputFormat == "png":
main_draw.savefig(filename + ".png",
format="png",
dpi=300,
bbox_inches='tight')
if outputFormat == "pdf":
main_draw.savefig(filename + ".pdf",
format="pdf",
dpi=300,
bbox_inches='tight')
plt.clf()
def insertUE(self, xPos, yPos, ueNum):
ue = devices.UE()
ue.ID = ueNum
ue.x = xPos
ue.y = yPos
self.parent.ue.append(ue)
def drawNetwork(self, filename, BS=True, UE=True, links=True, obstacles=True, fillMethod="SINR", colorMap = 'viridis', drawLegend=True, tilesInLine = 100, figSize = (8, 8), colorMinValue = None, colorMaxValue = None, outputFileFormat = ["png"], forceRedraw = False):
main_draw = plt.figure(1, figsize=figSize)
ax = main_draw.add_subplot(111)
cm = plt.cm.get_cmap(colorMap)
ue = devices.UE()
# check if tilesInLine changed
if (forceRedraw == True):
self.imageMatrixValid = False
if (self.tilesInLine != tilesInLine):
self.tilesInLine = tilesInLine
self.imageMatrixValid = False
if (self.fillMethod != fillMethod):
self.fillMethod = fillMethod
self.imageMatrixValid = False
# If this is the fist time, or if something changed
if(self.imageMatrixValid == False):
self.imageMatrix = np.zeros((tilesInLine, tilesInLine))
d_x = self.parent.constraintAreaMaxX/tilesInLine
d_y = self.parent.constraintAreaMaxY/tilesInLine
for x in range(0, tilesInLine):
for y in range(0, tilesInLine):
ue.x = round(x * d_x)
ue.y = round(y * d_y)
if fillMethod == "SINR":
ue.connectToTheBestBS(self.parent.bs, self.parent.obstacles)
SINR, RSSI = ue.calculateSINR(self.parent.bs, self.parent.obstacles)
self.imageMatrix[y][x] = SINR
if fillMethod == "RSSI":
ue.connectToTheBestBS(self.parent.bs, self.parent.obstacles)
SINR, RSSI = ue.calculateSINR(self.parent.bs, self.parent.obstacles)
self.imageMatrix[y][x] = RSSI
if fillMethod == "Sectors":
SINR_best = -1000
BS_best = -1
for bs in self.parent.bs:
ue.connectedToBS = bs.ID
temp_SINR, RSSI = ue.calculateSINR(self.parent.bs, self.parent.obstacles)
if (temp_SINR > SINR_best) and (RSSI > -120):
SINR_best = temp_SINR
BS_best = bs.ID
self.imageMatrix[y][x] = BS_best
self.imageMatrixValid = True
if colorMinValue != None:
colorMin = colorMinValue
else:
colorMin = self.imageMatrix.min()
if colorMaxValue != None:
colorMax = colorMaxValue
else:
colorMax = self.imageMatrix.max()
image = plt.imshow(self.imageMatrix, vmin=colorMin, vmax=colorMax, origin='lower', extent=[0, self.parent.constraintAreaMaxX, 0, self.parent.constraintAreaMaxY], interpolation='nearest', cmap=cm)
if drawLegend == True:
from mpl_toolkits.axes_grid1 import make_axes_locatable
divider = make_axes_locatable(ax)
cax1 = divider.append_axes("right", size="5%", pad=0.05)
cbar = plt.colorbar(image, cax = cax1)
cbar.set_clim(-40, 40) #end
if BS == True:
bs_x_locations = []
bs_y_locations = []
bs_ID = []
bs_angle = []
bs_count = 0
for bs in self.parent.bs:
bs_x_locations.append(bs.x)
bs_y_locations.append(bs.y)
bs_ID.append(bs.ID)
bs_angle.append(bs.angle)
bs_count+=1
ax.plot(bs_x_locations, bs_y_locations, 'r^', color="red", markersize=10)
for i in range(0,bs_count):
offsetAngle = math.radians(bs_angle[i])
distance = (self.parent.constraintAreaMaxX + self.parent.constraintAreaMaxY) / 50
z = distance*complex(math.sin(offsetAngle), -math.cos(offsetAngle))
ax.annotate(bs_ID[i], xy=(bs_x_locations[i],bs_y_locations[i]), xytext=(bs_x_locations[i]+z.real, bs_y_locations[i]+z.imag), color='red')
if UE == True:
for ue in self.parent.ue:
ax.annotate(ue.ID, xy=(ue.x, ue.y), xytext=(ue.x, ue.y), color='black')
if links == True:
for ue in self.parent.ue:
ax.arrow(ue.x, ue.y, self.parent.bs[ue.connectedToBS].x - ue.x, self.parent.bs[ue.connectedToBS].y - ue.y)
if obstacles == True:
for obstacle in self.parent.obstacles:
ax.arrow(obstacle[0], obstacle[1], obstacle[2] - obstacle[0], obstacle[3] - obstacle[1], width=10, color="red")
networkBorder = plt.Rectangle((0,0), self.parent.constraintAreaMaxX, self.parent.constraintAreaMaxY, color='black', fill=False)
ax.add_patch(networkBorder)
ax.axis('equal')
ax.axis([0, self.parent.constraintAreaMaxX, 0, self.parent.constraintAreaMaxY])
ax.axis('off')
ax.xaxis.set_visible(False)
ax.yaxis.set_visible(False)
for outputFormat in outputFileFormat:
if outputFormat == "png":
main_draw.savefig(filename+".png", format="png", dpi=300, bbox_inches='tight')
if outputFormat == "pdf":
main_draw.savefig(filename+".pdf", format="pdf", dpi=300, bbox_inches='tight')