def test_float_profile(self, time, burst, wind, const, linear):
wind_ds = Mock()
time.return_value = 'time'
burst.return_value = 'burst'
wind.return_value = 'wind'
const.return_value = 'const'
linear.return_value = 'linear'
model = models.float_profile(5.0, 12000.0, 7200.0, wind_ds)
const.assert_called_with(5.0)
wind.assert_called_with(wind_ds)
linear.assert_called_with(['const', 'wind'])
burst.assert_called_with(12000.0)
time.assert_called_with(7200.0)
assert_equal(model, (('linear', 'burst'), ('wind', 'time')))
def test_float_profile(self, time, burst, wind, const, linear):
wind_ds = Mock()
time.return_value = 'time'
burst.return_value = 'burst'
wind.return_value = 'wind'
const.return_value = 'const'
linear.return_value = 'linear'
model = models.float_profile(5.0, 12000.0, 7200.0, wind_ds)
const.assert_called_with(5.0)
wind.assert_called_with(wind_ds)
linear.assert_called_with(['const', 'wind'])
burst.assert_called_with(12000.0)
time.assert_called_with(7200.0)
assert_equal(model, (('linear', 'burst'), ('wind', 'time')))
def run_prediction(req):
"""
Run the prediction.
"""
# Response dict
resp = {
"request": req,
"prediction": [],
}
# Dataset
try:
if req['dataset'] == LATEST_DATASET_KEYWORD:
tawhiri_ds = WindDataset.open_latest(persistent=True)
else:
tawhiri_ds = WindDataset(datetime.fromtimestamp(req['dataset']))
except IOError:
raise InvalidDatasetException("No matching dataset found.")
except ValueError as e:
raise InvalidDatasetException(*e.args)
# Note that hours and minutes are set to 00 as Tawhiri uses hourly datasets
resp['request']['dataset'] = tawhiri_ds.ds_time.strftime(
"%Y-%m-%dT%H:00:00Z")
# Stages
if req['profile'] == PROFILE_STANDARD:
stages = models.standard_profile(req['ascent_rate'],
req['burst_altitude'],
req['descent_rate'], tawhiri_ds,
ruaumoko_ds())
elif req['profile'] == PROFILE_FLOAT:
stages = models.float_profile(req['ascent_rate'],
req['float_altitude'],
req['stop_datetime'], tawhiri_ds)
else:
raise InternalException("No implementation for known profile.")
# Run solver
try:
result = solver.solve(req['launch_datetime'], req['launch_latitude'],
req['launch_longitude'], req['launch_altitude'],
stages)
except Exception as e:
raise PredictionException("Prediction did not complete: '%s'." %
str(e))
# Format trajectory
if req['profile'] == PROFILE_STANDARD:
resp['prediction'] = _parse_stages(["ascent", "descent"], result)
elif req['profile'] == PROFILE_FLOAT:
resp['prediction'] = _parse_stages(["ascent", "float"], result)
else:
raise InternalException("No implementation for known profile.")
# Convert request UNIX timestamps to RFC3339 timestamps
for key in resp['request']:
if "datetime" in key:
resp['request'][key] = _timestamp_to_rfc3339(resp['request'][key])
return resp
from datetime import datetime
import json
import calendar
from tawhiri import solver, models, kml
from tawhiri.dataset import Dataset as WindDataset
from ruaumoko import Dataset as ElevationDataset
lat0 = 52.5563
lng0 = 360 - 3.1970
alt0 = 0.0
t0 = calendar.timegm(datetime(2014, 2, 19, 15).timetuple())
tE = calendar.timegm(datetime(2014, 2, 20, 6, 1).timetuple())
wind = WindDataset.open_latest()
stages = models.float_profile(2.0, 10000, tE, wind)
rise, float = solver.solve(t0, lat0, lng0, alt0, stages)
assert rise[-1] == float[0]
with open("test_prediction_data.js", "w") as f:
f.write("var data = ")
json.dump([(lat, lon) for _, lat, lon, _ in rise + float], f, indent=4)
f.write(";\n")
markers = [
{'name': 'launch', 'description': 'TODO', 'point': rise[0]},
{'name': 'reached float', 'description': 'TODO', 'point': float[0]}
]
def run_prediction(req):
"""
Run the prediction.
"""
# Response dict
resp = {
"request": req,
"prediction": [],
}
warningcounts = WarningCounts()
# Find wind data location
ds_dir = app.config.get('WIND_DATASET_DIR', WindDataset.DEFAULT_DIRECTORY)
# Dataset
try:
if req['dataset'] == LATEST_DATASET_KEYWORD:
tawhiri_ds = WindDataset.open_latest(persistent=True, directory=ds_dir)
else:
tawhiri_ds = WindDataset(datetime.fromtimestamp(req['dataset']), directory=ds_dir)
except IOError:
raise InvalidDatasetException("No matching dataset found.")
except ValueError as e:
raise InvalidDatasetException(*e.args)
# Note that hours and minutes are set to 00 as Tawhiri uses hourly datasets
resp['request']['dataset'] = \
tawhiri_ds.ds_time.strftime("%Y-%m-%dT%H:00:00Z")
# Stages
if req['profile'] == PROFILE_STANDARD:
stages = models.standard_profile(req['ascent_rate'],
req['burst_altitude'],
req['descent_rate'],
tawhiri_ds,
ruaumoko_ds(),
warningcounts)
elif req['profile'] == PROFILE_FLOAT:
stages = models.float_profile(req['ascent_rate'],
req['float_altitude'],
req['stop_datetime'],
tawhiri_ds,
warningcounts)
else:
raise InternalException("No implementation for known profile.")
# Run solver
try:
result = solver.solve(req['launch_datetime'], req['launch_latitude'],
req['launch_longitude'], req['launch_altitude'],
stages)
except Exception as e:
raise PredictionException("Prediction did not complete: '%s'." %
str(e))
# Format trajectory
if req['profile'] == PROFILE_STANDARD:
resp['prediction'] = _parse_stages(["ascent", "descent"], result)
elif req['profile'] == PROFILE_FLOAT:
resp['prediction'] = _parse_stages(["ascent", "float"], result)
else:
raise InternalException("No implementation for known profile.")
# Convert request UNIX timestamps to RFC3339 timestamps
for key in resp['request']:
if "datetime" in key:
resp['request'][key] = _timestamp_to_rfc3339(resp['request'][key])
resp["warnings"] = warningcounts.to_dict()
return resp
from datetime import datetime
import json
import calendar
from tawhiri import solver, models, kml
from tawhiri.dataset import Dataset as WindDataset
from ruaumoko import Dataset as ElevationDataset
lat0 = 52.5563
lng0 = 360 - 3.1970
alt0 = 0.0
t0 = calendar.timegm(datetime(2014, 2, 19, 15).timetuple())
tE = calendar.timegm(datetime(2014, 2, 20, 6, 1).timetuple())
wind = WindDataset.open_latest()
stages = models.float_profile(2.0, 10000, tE, wind)
rise, float = solver.solve(t0, lat0, lng0, alt0, stages)
assert rise[-1] == float[0]
with open("test_prediction_data.js", "w") as f:
f.write("var data = ")
json.dump([(lat, lon) for _, lat, lon, _ in rise + float], f, indent=4)
f.write(";\n")
markers = [{
'name': 'launch',
'description': 'TODO',
'point': rise[0]
}, {