def FindP_WellPad(Plot_P = True, WellPadNumber = 1, WindSpeed = 2, WindDirection = 0):
#Plot_P is a boolean that determines whether or not the probability distribution is plotted
FD = flightdata.FlightData();
FD.import_wellpad_components("./METEC Site Data/equipment_tags/Pad {}.kml".format(WellPadNumber))
#FD.import_inflight_measurements("./METEC Site Data/sample_uas_dataset.csv") #use this to find the size of the well pad
#determine the range of the coordinates so that we can shift them to make all coordinates (i*delta_x, j*delta_y, k*delta_z)
min_x =0; min_y=0; min_z = 0;
max_x=0; max_y=0; max_z=0;
for item in FD.wellpad_components:
if item.pos[0]<min_x:
min_x = item.pos[0]
elif item.pos[0]>max_x:
max_x = item.pos[0]
if item.pos[1]<min_y:
min_y = item.pos[1]
elif item.pos[1]>max_y:
max_y = item.pos[1]
if item.pos[2]>max_z:
max_z = item.pos[2]
"""
for item in FD.inflight_data['x']:
if item<min_x:
min_x = item;
elif item>max_x:
max_x = item;
for item in FD.inflight_data['y']:
if item<min_y:
min_y = item;
elif item>max_y:
max_y = item;
for item in FD.inflight_data['z']:
if item<min_z:
min_z = item;
elif item>max_z:
max_z = item;
"""
#shift all coordinates
Shift = [min_x-40, min_y-40,0];
for i in range(0,len(FD.wellpad_components)):
#add 3m to the z component of the component location since we don't have the real height of the components
FD.wellpad_components[i].pos = FD.wellpad_components[i].pos - Shift + [0,0,3];
'''
FD.inflight_data['x'] = FD.inflight_data['x'] - min_x;
FD.inflight_data['y'] = FD.inflight_data['y'] - min_y;
FD.inflight_data['z'] = FD.inflight_data['z'] - min_z;
'''
#define the size of the wellpad, in meters
size = [max_x-(min_x)+60, max_y-(min_y)+60, max_z+6];
print(size)
#try changing these numbers as necessary
grid_size = (200,200,20);
#define wind speed as initial speed
#may want to change this to use current wind speed in future
#also need to check that wind direction is defined the way we think
if WellPadNumber == 1:
WindSpeed = FD.inflight_data['wind_speeds'][0];
WindDirection = FD.inflight_data['wind_directions'][0];
Dist = ProbDist(size, grid_size, FD.wellpad_components, WindSpeed, WindDirection);
Spacing = [size[0]/grid_size[0], size[1]/grid_size[1], size[2]/grid_size[2]];
if Plot_P:
#define a 2D array that is a layer of the probability distribution
P_layer = np.zeros((grid_size[0], grid_size[1]))
for i in range(grid_size[0]):
for j in range(grid_size[1]):
P_layer[i,j] = Dist.P[i,j,9];
X = np.zeros(grid_size[0])
Y = np.zeros(grid_size[1])
for i in range(grid_size[0]):
X[i] = i*Spacing[0] + Shift[0];
for j in range(grid_size[1]):
Y[j] = j*Spacing[1] + Shift[1];
Xm, Ym = np.meshgrid(X,Y,indexing='ij')
plt.contourf(Xm,Ym, P_layer)
plt.colorbar()
for item in FD.wellpad_components:
plt.plot(item.pos[0]+Shift[0], item.pos[1]+Shift[1],'ko')
plt.xlabel('x (m)')
plt.ylabel('y (m)')
plt.title('Initial Probability Distribution for Well Pad {}'.format(WellPadNumber))
plt.show()
return Dist.P, Spacing, Shift
if __name__ == "__main__":
browser = screenshot.loadmap()
if browser == None:
print("unable to load browser!")
else:
print("browser loaded!")
alarms = dict() # dictonary of all aircraft that have triggered the alarm
# Indexed by it's hex code, each entry contains a tuple of
# the aircraft data at the closest position so far, and a
# counter. Once the airplane is out of the alarm zone,
# the counter is incremented until we hit [abovetustin_wait_x_updates]
# (defined above), at which point we then Tweet
fd = flightdata.FlightData()
lastTime = fd.time
while True:
sleep(abovetustin_sleep_time)
fd.refresh()
if fd.time == lastTime:
continue
lastTime = fd.time
print("Now: {}".format(fd.time))
current = dict() # current aircraft inside alarm zone
# loop on all the aircarft in the receiver
for a in fd.aircraft:
def get_data_source():
return flightdata.FlightData(data_url=g_data_url,
parser=get_driver()['data']())
