import matplotlib.pyplot as plt
# Required Inputs
payload = 6.0
balloonWeight = 1000
parachuteDia = 6.0
helium = 1.5
desiredLat = 42.290977
desiredLon = -83.717548
launchTime = '2019-08-23 23:00:00'
tolerace = 5 #ft
#ans = balloon.plotStations('US')
# Do a single prediction
data = balloon.prediction(payload, balloonWeight, parachuteDia, helium,
desiredLat, desiredLon, -1, 1, launchTime, 100, 0.2)
# Animate the result
balloon.PredictionAni(data, 0)
# Do backwards prediction calculation
launchLoc = balloon.launchPrediction(payload, balloonWeight, parachuteDia,
helium, desiredLat, desiredLon,
launchTime, tolerace)
print('Distance reached: ' + str(launchLoc['Tolerace']))
# Check work
data = balloon.prediction(payload, balloonWeight, parachuteDia, helium,
launchLoc['Lat'], launchLoc['Lon'], -1, 1,
launchTime, 50, 0.2)
balloon.plotPrediction(data)
CycleError = True
ErrorCode = 8
# If no error has occurred yet, Do Prediction
if CycleError == False:
try:
# Prediction
print("Preforming Prediction: Status " + str(status))
data = balloon.prediction(
payload,
balloonWeight,
parachuteDia,
helium,
APRS_data["lat"],
APRS_data["lng"],
APRS_data["altitude"] * 3.281,
status,
"now",
ensembles,
errInEnsembles,
TESTINGtimeDiff,
ARcorr,
UTCdiff,
)
# Save prediction data to file (package data into a file)
balloon.package(data, predictionNum, flightID)
predictionNum = predictionNum + 1
# Stick landing coordinates in vector
predLat.append(data["Landing Lat"])
predLon.append(data["Landing Lon"])
except:
import balloon
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
# Import Flight Data
data = balloon.prediction(6.0, 1000, 6.0, 1, 41.64, -83.243, 40000, 1, 'now',
500, 0.2)
# Plot Nominal Data
fig = plt.figure(figsize=(40, 35))
ax = fig.gca(projection='3d')
ax.plot(data['TimeData']['Latitude'], data['TimeData']['Longitude'],
data['TimeData']['Altitude'])
for ensembles in data['Secondary Tracks']:
ax.plot(data['Secondary Tracks'][str(ensembles)]['Lat'],
data['Secondary Tracks'][str(ensembles)]['Lon'],
data['Secondary Tracks'][str(ensembles)]['Alt'])
plt.show()
import datetime
import balloon
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
# Define what predictions you want
flightID = '01'
predictionNum = 5
deltaHour = 8
# Get list of times and convert to strings
timeList = list()
start = datetime.datetime.strptime(
datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S"), "%Y-%m-%d %H:%M:%S")
timeList.append(str(start))
new = start
for predictionNum in range(1, predictionNum + 1):
last = new
new = last + datetime.timedelta(hours=deltaHour)
timeList.append(str(new))
# Import Flight Data for each time and record to pickle file
i = 1
for times in timeList:
data = balloon.prediction(6.0, 1000, 6.0, 1, 41.64, -83.243, 5000, -1,
times, 100, 0.2)
balloon.package(data, 'p_' + flightID + '_' + str(i))
i = i + 1
break
# Check if location is reporting same position twice - If so send message to group
if APRS_data['lasttime'] != APRS_data['time']:
message = 'Warning: Tracker may have lost GPS signal. Data transmission remains nominal.'
balloon.send_slack(message,messageType,recipient,slackURL)
except:
CycleError = True
ErrorCode = 3
# Do Prediction
if CycleError == False:
try:
# Prediction
print('Preforming Prediction: Status ' + str(status))
data = balloon.prediction(payload,balloonWeight,parachuteDia,helium,APRS_data['lat'],APRS_data['lng'],APRS_data['altitude'] * 3.281,status,'now',ensembles,errInEnsembles,TESTINGtimeDiff)
# Save prediction data to file
balloon.package(data,predictionNum,flightID)
predictionNum = predictionNum + 1
# Stick landing coordinates in vector
predLat.append(data['Landing Lat'])
predLon.append(data['Landing Lon'])
except:
CycleError = True
ErrorCode = 4
# Do deviation calculation
if CycleError == False:
try:
# If more than one predction exists, figure out if it has shifted by a certain tolerace since the last NOTIFICATION
tolerace,
0,
UTCdiff,
)
print("Launch Location: " + str(launchLoc["Lat"]) + "," + str(launchLoc["Lon"]))
print("Distance reached: " + str(launchLoc["Tolerace"]))
# Check work from backwards calculation
data = balloon.prediction(
payload,
balloonWeight,
parachuteDia,
helium,
launchLoc["Lat"],
launchLoc["Lon"],
-1,
1,
launchTime,
ensem,
ensem_per,
0,
-1,
UTCdiff,
)
# balloon.plotPrediction(data)
print("Requested: " + str(desiredLat) + "," + str(desiredLon))
print("Actual: " + str(data["Landing Lat"]) + "," + str(data["Landing Lon"]))
print("Popping Altitude: " + str(data["Burst Altitude"]) + " ft")
popTime = data["TimeData"].loc[data["TimeData"]["Status"] == 1].index[-1]
print("Rise time: " + str(popTime - data["Inputs"]["Launch Time"]))
print("Flight time: " + str(data["Landing Time"] - data["Inputs"]["Launch Time"]))
if doDrivingCalc == True: