def finder(key_name, id_value):
"""
Find the user sector with the given id value using the provided key name.
Returns a tuple of (True, [(db_id, iata, icao, is_ct_code, lat, lon), ...])
or (False, [])
For example finder('id', 22) find user sector with db id 22
"""
connection = get_geo_db_connection()
context = ctx.CONTEXT
schema = context[ctx.SCHEMA_NAME]
query = "SELECT * from %s.user_defined_sectors where %s = %s;"
params = (AsIs(schema), AsIs(key_name), id_value)
try:
with connection.cursor(cursor_factory=DictCursor) as cursor:
cursor.execute(query, params)
results = cursor.fetchall()
formated_result = [{
'id': result[0],
'org_id': result[1],
'user_id': result[2],
'sector_name': result[3],
'latitude': result[4],
'longitude': result[5],
'radius': result[6],
'min_altitude': result[7],
'max_altitude': result[8],
'is_cylinder': result[9],
'wkt': result[10]
} for result in results]
return [(False, []), (True, formated_result)][len(results) > 0]
except Exception:
log.exception(f"Error trying to find value {id_value} in column "
f"{key_name} in table {schema}.user_defined_sectors")
return False, []
def finder(key_name, id_value):
"""
Find the airport with the given id value using the provided key name.
Returns a tuple of (True, [(db_id, iata, icao, is_ct_code, lat, lon), ...])
or (False, []). If a record is found but the field is missing it will be
None in the result.
"""
connection = get_geo_db_connection()
context = ctx.CONTEXT
schema = context[ctx.SCHEMA_NAME]
query = "SELECT * from %s.airports where %s = %s;"
params = (AsIs(schema), AsIs(key_name), id_value)
try:
with connection.cursor(cursor_factory=DictCursor) as cursor:
cursor.execute(query, params)
results = cursor.fetchall()
formated_result = [{'db_id': result[0],
'iata_ap_code': result[1],
'icao_ap_code': result[2],
'iso_ct_code': result[3], 'latitude': result[4],
'longitude': result[5]} for result in results]
return [(False, []), (True, formated_result)][len(results) > 0]
except Exception:
log.exception("Error trying to find value %s in column %s in table %s.airports", id_value, key_name, schema)
return False, []
def get_elementary_airspace_altitude_range(db_id):
"""
Get the altitude range for the given database id string.
Raise an exception if not found.
Returns a tuple of [lower_altitude, upper_altitude]
Altitudes in [Feet].
"""
connection = get_geo_db_connection()
sector = find_sector(db_id, connection)
if (sector):
return (sector['min_altitude'], sector['max_altitude'])
else:
raise NotFoundException(db_id, "Elementary sector not found.")
def get_elementary_airspace_name(db_id):
"""
Get the elementary airspace sector name for the given database id string.
Raise an exception if not found.
"""
connection = get_geo_db_connection()
sector = find_sector(db_id, connection)
if (sector):
return make_sector_description(sector, False)
else:
raise NotFoundException(db_id, "Elementary sector not found.")
def find_horizontal_sector_intersections(flight_id, latitudes, longitudes,
min_altitude, max_altitude):
"""
Find horizontal airspace sector intersections.
Note: the latitudes and longitudes arrays must be the same length, 2 positions or longer.
Parameters
----------
flight_id: string
The flight id used for logging.
latitudes: a numpy array of floats
Position latitudes in [degrees].
longitudes: a numpy array of floats
Position longitudes in [degrees].
min_altitude: float
The minimum altitude of the positions [feet].
max_altitude: float
The maximum altitude of the positions [feet].
Returns
-------
intersection_latitudes: a list of floats
Intersection position latitudes in [degrees].
intersection_longitudes: a list of floats
Intersection position longitudes in [degrees].
intersection_sector_ids : a list of strings
The database ids of the intersected sectors.
The lists are ordered together, so the same points are at the same index.
E.g.
[latitudes[0], latitudes[-1]], [longitudes[0], longitudes[-1]], ['id1', 'id2']
"""
log.debug(
"Finding sector intersections for flight %s, with min altitude %s and max altitude %s",
flight_id, min_altitude, max_altitude)
# Get the connection string
connection = get_geo_db_connection()
# Make a list of augmented points
augmented_points = make_augmented_points_from_positions(
latitudes, longitudes, flight_id, connection)
# Convert the points to a geographic feature
geographic_trajectory = make_geographic_trajectory(augmented_points,
flight_id, connection)
# Make a trajectory that contains the geo line, the augmented points and
# the 2D intersected sectors
augmented_trajectory = make_augmented_trajectory(augmented_points,
geographic_trajectory,
flight_id, min_altitude,
max_altitude, connection)
# Find the 2D intersections
intersections = find_intersections(augmented_trajectory, min_altitude,
max_altitude, flight_id, connection)
# Organise the outputs
intersection_data_structure = create_intersection_data_structure(
intersections, flight_id)
return intersection_data_structure
def find_airport_cylinder_intersection(flight_id, latitudes, longitudes,
airport_id, radius, is_destination):
"""
Find an airport cylinder intersection.
Note: the latitudes and longitudes arrays must be the same length, 2 positions or longer.
Parameters
----------
flight_id: string
The flight id used for logging.
latitudes: a numpy array of floats
Position latitudes in [degrees].
longitudes: a numpy array of floats
Position longitudes in [degrees].
airport_id: string
The ICAO id of the airport.
radius: float
The radius of the airport cylinder [Nautical Miles].
is_destination: bool
True if the airport is a destination, False if it's a departure.
Returns
-------
A tuple of:
- latitude: the intersection position latitude in [degrees]
- longitude: the intersection position longitude in [degrees]
E.g.
True, latitudes[0], longitudes[0]
"""
log.debug(
"Finding intersection for flight %s, with airport %s at radius %s",
flight_id, airport_id, radius)
radius_m = radius * NM_CONVERSION_TO_M
# Get the connection string
connection = get_geo_db_connection()
# Find the airport
found = airport_finder("icao_ap_code", airport_id)
if found[0]:
airport = found[1][0]
airport_lon = airport['longitude']
airport_lat = airport['latitude']
# Make a list of augmented points
augmented_points = make_augmented_points_from_positions(
latitudes, longitudes, flight_id, connection)
# Convert the points to a geographic feature
geographic_trajectory = make_geographic_trajectory(
augmented_points, flight_id, connection)
# Make the buffer
buffer = create_buffer(airport_lon, airport_lat, radius_m, connection)
# The intersections between path and buffer
intersections = find_line_poly_intersection_without_boundary(
geographic_trajectory, buffer, connection)
# Organise the outputs
intersection_wkts = extract_intersection_wkts(intersections)
# The origin dict included here just tells the extract routine that
# this is not an origin flight.
intersection_details = extract_details_from_intersection(
"", intersection_wkts, {'is_origin': False}, flight_id)
if len(intersection_details) > 0:
x_y_sector_ids = reduce(merge_l_t, [intersection_details],
[[], [], []])
return x_y_sector_ids[0], x_y_sector_ids[1]
else:
return [], []
else:
return [], []
