Loading Graph

This notebook takes a dataset from a file or (Geo)DataFrame as well as graphs of processed flights and visualises the graph, as well as checking individual flights or handovers to extract a confidence value.

Before using this notebook ensure you have dumped some flight data using demo-export-flights.ipynb and processed them using demo-process-flights.ipynb.

from flight_processing import DataConfig
from flight_processing.data import AirspaceGraph, FlightDownloader

import geopandas
from datetime import datetime, timedelta
from dateutil import parser
import logging

logger = logging.getLogger()
logger.setLevel(level=logging.INFO)

logging.getLogger('traffic').disabled = True

Example 1: known dataset from file, graph output in standard location

This example loads data from the expected location as defined in ~/.config/flight_processing/flight_processing.conf.

airspacegraph = AirspaceGraph("switzerland")
airspacegraph.load_graphs("2020-03-05 00:00", "2020-04-24 00:00")

INFO:flight_processing.data.airspace_graph:Loading airspace dataset from disk at location /mnt/cold_data/josh/processing/regions_switzerland_wkt.json.
INFO:flight_processing.data.airspace_graph:Initialising AirspaceHandler C++ object.
INFO:flight_processing.data.airspace_graph:Successfully loaded airspaces, 152 in total.
INFO:flight_processing.data.airspace_graph:Loading matrix of handovers.
INFO:flight_processing.data.airspace_graph:Loading 1200 saved NPZ files, from 2020-03-05 00:00:00 to 2020-04-24 00:00:00.
INFO:flight_processing.data.airspace_graph:Loading saved graph from location /mnt/cold_data/josh/processing/graphs/switzerland/20200305/0000.npz.
INFO:flight_processing.data.airspace_graph:Loading saved graph from location /mnt/cold_data/josh/processing/graphs/switzerland/20200305/0100.npz.
INFO:flight_processing.data.airspace_graph:Loading saved graph from location /mnt/cold_data/josh/processing/graphs/switzerland/20200305/0200.npz.
...
INFO:flight_processing.data.airspace_graph:Loading saved graph from location /mnt/cold_data/josh/processing/graphs/switzerland/20200423/2100.npz.
INFO:flight_processing.data.airspace_graph:Loading saved graph from location /mnt/cold_data/josh/processing/graphs/switzerland/20200423/2200.npz.
INFO:flight_processing.data.airspace_graph:Loading saved graph from location /mnt/cold_data/josh/processing/graphs/switzerland/20200423/2300.npz.
INFO:flight_processing.data.airspace_graph:Building graph from matrix.
INFO:flight_processing.data.data_utils:Generating new graph from dataframe.
INFO:flight_processing.data.airspace_graph:Computing adjusted weights.

airspacegraph.visualise_graph()

INFO:flight_processing.data.airspace_graph:Drawing graph using holoviews.

airspacegraph.draw_graph_map(logscale=True)

INFO:flight_processing.data.airspace_graph:Downloading terrain data from Stamen.
INFO:flight_processing.data.airspace_graph:Plotting airspace boundaries on map.
INFO:flight_processing.data.airspace_graph:Extracting edge weights from graph.
INFO:flight_processing.data.airspace_graph:Plotting graph on map.
_images/demo_airspace_graph_5_1.png 
# Cleanup
del airspacegraph

Example 2: known dataset from file, custom graph location

We’re doing the same sort of thing as example 1, but calling load_graph_files instead of load_graphs, which allows us to input a custom file location instead of time bounds.

template = "/mnt/cold_data/josh/processing/graphs/switzerland/{date}/{time}.npz"
template_date = "%Y%m%d"
template_time = "%H%M"

start_time = parser.parse("2020-03-05 00:00")
time_delta = timedelta(hours=2)
count = 50 * 12

files = []

for i in range(count):
    time = start_time + (i * time_delta)
    file = template.format(
        date = time.strftime(template_date),
        time = time.strftime(template_time)
    )
    files.append(file)

airspacegraph = AirspaceGraph("switzerland")
airspacegraph.load_graph_files(files)

INFO:flight_processing.data.airspace_graph:Loading airspace dataset from disk at location /mnt/cold_data/josh/processing/regions_switzerland_wkt.json.
INFO:flight_processing.data.airspace_graph:Initialising AirspaceHandler C++ object.
INFO:flight_processing.data.airspace_graph:Successfully loaded airspaces, 152 in total.
INFO:flight_processing.data.airspace_graph:Loading matrix of handovers.
INFO:flight_processing.data.airspace_graph:Building graph from matrix.
INFO:flight_processing.data.data_utils:Generating new graph from dataframe.
INFO:flight_processing.data.airspace_graph:Computing adjusted weights.

airspacegraph.visualise_graph()

INFO:flight_processing.data.airspace_graph:Drawing graph using holoviews.

airspacegraph.draw_graph_map(logscale=True)

INFO:flight_processing.data.airspace_graph:Downloading terrain data from Stamen.
INFO:flight_processing.data.airspace_graph:Plotting airspace boundaries on map.
INFO:flight_processing.data.airspace_graph:Extracting edge weights from graph.
INFO:flight_processing.data.airspace_graph:Plotting graph on map.
_images/demo_airspace_graph_10_1.png 
# Cleanup
del airspacegraph

Example 3: Custom dataset, graph output in standard location

In this example we use a custom DataConfig as in example 2 of demo-export-flights.ipynb and demo-process-flights.ipynb. We also specify a custom dataset location.

dataset = DataConfig("switzerland-custom", minlon=5.3, maxlon=10.7, minlat=45.5, maxlat=48, detail=6)
location = "/mnt/cold_data/josh/processing/regions_switzerland_wkt.json"
airspacegraph = AirspaceGraph(dataset, dataset_location=location)

airspacegraph.load_graphs("2020-03-05 00:00", "2020-03-06 00:00")

INFO:flight_processing.data.airspace_graph:Loading airspace dataset from disk at location /mnt/cold_data/josh/processing/regions_switzerland_wkt.json.
INFO:flight_processing.data.airspace_graph:Initialising AirspaceHandler C++ object.
INFO:flight_processing.data.airspace_graph:Successfully loaded airspaces, 152 in total.
INFO:flight_processing.data.airspace_graph:Loading matrix of handovers.
INFO:flight_processing.data.airspace_graph:Loading 24 saved NPZ files, from 2020-03-05 00:00:00 to 2020-03-06 00:00:00.
INFO:flight_processing.data.airspace_graph:Loading saved graph from location /mnt/cold_data/josh/processing/graphs/switzerland-custom/20200305/0000.npz.
INFO:flight_processing.data.airspace_graph:Loading saved graph from location /mnt/cold_data/josh/processing/graphs/switzerland-custom/20200305/0100.npz.
INFO:flight_processing.data.airspace_graph:Loading saved graph from location /mnt/cold_data/josh/processing/graphs/switzerland-custom/20200305/0200.npz.
...
INFO:flight_processing.data.airspace_graph:Loading saved graph from location /mnt/cold_data/josh/processing/graphs/switzerland-custom/20200305/2100.npz.
INFO:flight_processing.data.airspace_graph:Loading saved graph from location /mnt/cold_data/josh/processing/graphs/switzerland-custom/20200305/2200.npz.
INFO:flight_processing.data.airspace_graph:Loading saved graph from location /mnt/cold_data/josh/processing/graphs/switzerland-custom/20200305/2300.npz.
INFO:flight_processing.data.airspace_graph:Building graph from matrix.
INFO:flight_processing.data.data_utils:Generating new graph from dataframe.
INFO:flight_processing.data.airspace_graph:Computing adjusted weights.

airspacegraph.visualise_graph()

INFO:flight_processing.data.airspace_graph:Drawing graph using holoviews.

airspacegraph.draw_graph_map(logscale=True)

INFO:flight_processing.data.airspace_graph:Downloading terrain data from Stamen.
INFO:flight_processing.data.airspace_graph:Plotting airspace boundaries on map.
INFO:flight_processing.data.airspace_graph:Extracting edge weights from graph.
INFO:flight_processing.data.airspace_graph:Plotting graph on map.
_images/demo_airspace_graph_15_1.png 
# Cleanup
del airspacegraph

Example 4: Processing handovers and flights

In this example we load our graph and use it to obtain a confidence rating at a given point and for a given handover. We also do the same for all the potential handovers on a given flight.

We are using the UK dataset here - dump and process some flights for this dataset if you have not already done so.

airspacegraph = AirspaceGraph("uk")
airspacegraph.load_graphs("2020-01-01 00:00", "2020-01-02 00:00")

downloader = FlightDownloader("uk")

INFO:flight_processing.data.airspace_graph:Loading airspace dataset from disk at location /mnt/cold_data/josh/processing/regions_uk_wkt.json.
INFO:flight_processing.data.airspace_graph:Initialising AirspaceHandler C++ object.
INFO:flight_processing.data.airspace_graph:Successfully loaded airspaces, 616 in total.
INFO:flight_processing.data.airspace_graph:Loading matrix of handovers.
INFO:flight_processing.data.airspace_graph:Loading 24 saved NPZ files, from 2020-01-01 00:00:00 to 2020-01-02 00:00:00.
INFO:flight_processing.data.airspace_graph:Loading saved graph from location /mnt/cold_data/josh/processing/graphs/uk/20200101/0000.npz.
INFO:flight_processing.data.airspace_graph:Loading saved graph from location /mnt/cold_data/josh/processing/graphs/uk/20200101/0100.npz.
INFO:flight_processing.data.airspace_graph:Loading saved graph from location /mnt/cold_data/josh/processing/graphs/uk/20200101/0200.npz.
...
INFO:flight_processing.data.airspace_graph:Loading saved graph from location /mnt/cold_data/josh/processing/graphs/uk/20200101/2100.npz.
INFO:flight_processing.data.airspace_graph:Loading saved graph from location /mnt/cold_data/josh/processing/graphs/uk/20200101/2200.npz.
INFO:flight_processing.data.airspace_graph:Loading saved graph from location /mnt/cold_data/josh/processing/graphs/uk/20200101/2300.npz.
INFO:flight_processing.data.airspace_graph:Building graph from matrix.
INFO:flight_processing.data.data_utils:Generating new graph from dataframe.
INFO:flight_processing.data.airspace_graph:Computing adjusted weights.

airspacegraph.draw_graph_map(logscale=True)

INFO:flight_processing.data.airspace_graph:Downloading terrain data from Stamen.
INFO:flight_processing.data.airspace_graph:Plotting airspace boundaries on map.
INFO:flight_processing.data.airspace_graph:Extracting edge weights from graph.
INFO:flight_processing.data.airspace_graph:Plotting graph on map.
_images/demo_airspace_graph_19_1.png

Setup

First we need to (optionally) set the values and weights used for the functions that follow.

average_weight = airspacegraph.average_edge_weight(median=True)
print("Median edge weight: {}".format(average_weight))

airspacegraph.set_confidence_values(
    distance_zero = 5000,
    distance_one = 3000,
    minimum_weight = average_weight,
    minimum_weight_adjusted = 0.05,
    confidence_distance = 1.0,
    confidence_distance_modifier = 0.8,
    confidence_weight = 1.0,
    confidence_weight_adjusted = 1.0
)

INFO:flight_processing.data.airspace_graph:Computing median edge weight in graph.

Median edge weight: 24

Test a single point

Next we can test a point - for each airspace contained within the point we are given a number of nearby airspaces, and information on the confidence of that potential handover.

long = -0.453350
lat = 51.470569
alt = 6000
airspacegraph.test_point(long, lat, alt)

INFO:flight_processing.data.airspace_graph:Getting airspaces at the given point using AirspaceHandler C++ object.
INFO:flight_processing.data.airspace_graph:Getting airspaces near to the given point using AirspaceHandler C++ object.
INFO:flight_processing.data.airspace_graph:Computing confidence in a handover to each nearby airspace.
INFO:flight_processing.data.airspace_graph:Computing confidence based on distance from airspace borders.
INFO:flight_processing.data.airspace_graph:Computing confidence based on non-position-based data sources.
INFO:flight_processing.data.airspace_graph:Computing confidence based on distance from airspace borders.
INFO:flight_processing.data.airspace_graph:Computing confidence based on non-position-based data sources.
INFO:flight_processing.data.airspace_graph:Computing confidence based on distance from airspace borders.
INFO:flight_processing.data.airspace_graph:Computing confidence based on non-position-based data sources.
INFO:flight_processing.data.airspace_graph:Getting edge weights.
...
INFO:flight_processing.data.airspace_graph:Computing confidence based on distance from airspace borders.
INFO:flight_processing.data.airspace_graph:Computing confidence based on non-position-based data sources.
INFO:flight_processing.data.airspace_graph:Computing confidence based on distance from airspace borders.
INFO:flight_processing.data.airspace_graph:Computing confidence based on non-position-based data sources.

[{'distance1': 0.0,
  'distance2': 869.841552734375,
  'confidence': 1.0,
  'weight': 0,
  'weight_adjusted': 0,
  'confidence_distance': 1.0,
  'confidence_weight': 0.0,
  'confidence_weight_adjusted': 0.0,
  'airspace1': 506,
  'airspace2': 264,
  'name1': 'LONDON TMA 3',
  'name2': 'LONDON LUTON CTA 4'},
 {'distance1': 0.0,
  'distance2': 869.841552734375,
  'confidence': 1.0,
  'weight': 0,
  'weight_adjusted': 0,
  'confidence_distance': 1.0,
  'confidence_weight': 0.0,
  'confidence_weight_adjusted': 0.0,
  'airspace1': 506,
  'airspace2': 262,
  'name1': 'LONDON TMA 3',
  'name2': 'LONDON LUTON CTA 4'},
 {'distance1': 0.0,
  'distance2': 869.841552734375,
  'confidence': 1.0,
  'weight': 0,
  'weight_adjusted': 0,
  'confidence_distance': 1.0,
  'confidence_weight': 0.0,
  'confidence_weight_adjusted': 0.0,
  'airspace1': 506,
  'airspace2': 263,
  'name1': 'LONDON TMA 3',
  'name2': 'LONDON LUTON CTA 4'},

  ...

 {'distance1': 0.0,
  'distance2': 126746.1953125,
  'confidence': 0.0,
  'weight': 0,
  'weight_adjusted': 0,
  'confidence_distance': 0.0,
  'confidence_weight': 0.0,
  'confidence_weight_adjusted': 0.0,
  'airspace1': 513,
  'airspace2': 314,
  'name1': 'LONDON TMA 3',
  'name2': 'MIDLANDS CTA'},
 {'distance1': 0.0,
  'distance2': 126746.1953125,
  'confidence': 0.0,
  'weight': 0,
  'weight_adjusted': 0,
  'confidence_distance': 0.0,
  'confidence_weight': 0.0,
  'confidence_weight_adjusted': 0.0,
  'airspace1': 513,
  'airspace2': 313,
  'name1': 'LONDON TMA 3',
  'name2': 'MIDLANDS CTA'},
 {'distance1': 0.0,
  'distance2': 126746.1953125,
  'confidence': 0.0,
  'weight': 0,
  'weight_adjusted': 0,
  'confidence_distance': 0.0,
  'confidence_weight': 0.0,
  'confidence_weight_adjusted': 0.0,
  'airspace1': 513,
  'airspace2': 311,
  'name1': 'LONDON TMA 3',
  'name2': 'MIDLANDS CTA'}]

Look at a single airspace

We can get information about a specific airspace:

a1 = "LONDON TMA 3"

airspacegraph.get_airspace(a1)

name                                                      LONDON TMA 3
lateral_limits       514021N 0004916W -514542N 0005550W -515021N 00...
upper_limit                                                      19500
lower_limit                                                       3500
class_of_airspace                                                    A
unit                                         LONDON CONTROL (SWANWICK)
callsign                                                LONDON CONTROL
language                                                       English
hours                                                              H24
frequency                                                      118.825
purpose                                                           None
remarks              Parts of the following ATS Routes are incorpor...
wkt                  MULTIPOLYGON (((-0.4916 51.4021, -0.555 51.454...
geometry             (POLYGON ((-0.4916 51.4021, -0.555 51.4542, -0...
total_weight                                                     46450
Name: 504, dtype: object

airspacegraph.get_airspace(a1).geometry
_images/demo_airspace_graph_26_0.svg
airspacegraph.graph["LONDON TMA 3"]

AtlasView({'LONDON STANSTED CTA 1': {'weight': 1960, 'weight_adjusted': 0.04219590958019376}, 'SOUTHERN CTA': {'weight': 19350, 'weight_adjusted': 0.41657696447793324}, 'UPPER AIRSPACE CTA': {'weight': 4620, 'weight_adjusted': 0.09946178686759957}, 'LONDON TMA 1': {'weight': 17100, 'weight_adjusted': 0.3681377825618945}, 'LONDON TMA 5': {'weight': 220, 'weight_adjusted': 0.004736275565123789}, 'LONDON TMA 6': {'weight': 1000, 'weight_adjusted': 0.021528525296017224}, 'LONDON TMA 7': {'weight': 910, 'weight_adjusted': 0.019590958019375673}, 'LONDON TMA 9': {'weight': 160, 'weight_adjusted': 0.003444564047362756}, 'LONDON TMA 16': {'weight': 650, 'weight_adjusted': 0.013993541442411194}, 'LONDON TMA 18': {'weight': 200, 'weight_adjusted': 0.004305705059203444}, 'LONDON TMA 19': {'weight': 280, 'weight_adjusted': 0.0060279870828848225}})

Test a handover

Given two airspaces, we can get information on the confidence of a handover between those two airspaces at a given position:

a2 = "LONDON TMA 19"

airspacegraph.test_handover(long, lat, alt, a1, a2)

INFO:flight_processing.data.airspace_graph:Getting edge weights.
INFO:flight_processing.data.airspace_graph:Computing confidence based on distance from airspace borders.
INFO:flight_processing.data.airspace_graph:Computing confidence based on non-position-based data sources.

{'distance1': 0.0,
 'distance2': 6929.1259765625,
 'confidence': 1.0,
 'weight': 280,
 'weight_adjusted': 0.0060279870828848225,
 'confidence_distance': 0.0,
 'confidence_weight': 1.0,
 'confidence_weight_adjusted': 0.0}

Test a flight

Finally, we can test an entire flight, giving us a list of airspace handovers which could have occurred along the flight and the model’s confidence in that handover.

# Download some flights
flights = downloader.download_flights("2019-01-01 00:00", "2019-01-01 01:00")
flights

INFO:flight_processing.data.flight_downloader:Downloading flights between 2019-01-01 00:00:00 and 2019-01-01 01:00:00 from OpenSky.
INFO:root:Sending request between time 2019-01-01 00:00:00+00:00 and 2019-01-01 01:00:00+00:00 and hour 2019-01-01 00:00:00+00:00 and 2019-01-01 01:00:00+00:00
INFO:paramiko.transport:Connected (version 2.0, client OpenSSH_7.6p1)
INFO:paramiko.transport:Authentication (password) successful!
INFO:root:Sending request: select time, icao24, lat, lon, velocity, heading, vertrate, callsign, onground, alert, spi, squawk, baroaltitude, geoaltitude, lastposupdate, lastcontact, hour from state_vectors_data4  where hour>=1546300800.0 and hour<1546304400.0 and time>=1546300800.0 and time<1546304400.0 and lon>=-11 and lon<=6 and lat>=48 and lat<=61.5
INFO:root:Reading request in cache /mnt/cold_data/josh/traffic_cache/opensky/25a2c24888155b039a81e36a56c86679
INFO:numexpr.utils:Note: NumExpr detected 32 cores but "NUMEXPR_MAX_THREADS" not set, so enforcing safe limit of 8.
INFO:numexpr.utils:NumExpr defaulting to 8 threads.
Traffic with 34 identifiers
count
icao24 callsign
44c46f LGGRU10 3599
44c46d LGGRU1 3599
484ad0 TFL554 3413
3c4582 BOX317 2932
c058d5 ACA2082 2785
8004e0 AIC144 2466
4952c1 TAP746 2171
4074d2 NRS7409 1939
4073a0 EZY6950 1730
7380c5 ELY028 1582 
# Isolate one specific flight
flight = flights[9]
flight

INFO:root:Loading @junzis aircraft database
Flight EZY6950
  • aircraft: 4073a0 · 🇬🇧 G-UZHC (A20N)
  • from: 2019-01-01 00:00:01+00:00
  • to: 2019-01-01 00:28:50+00:00
handovers = airspacegraph.test_flight(flight)
handovers

INFO:flight_processing.data.airspace_graph:Getting all handovers along the flight.
INFO:flight_processing.data.airspace_graph:Converting flight to arrays of coordinates.
INFO:flight_processing.data.airspace_graph:Processing flight using AirspaceHandler C++ object.
INFO:flight_processing.data.airspace_graph:Computing confidence values for each handover.
INFO:flight_processing.data.airspace_graph:Getting edge weights.
INFO:flight_processing.data.airspace_graph:Computing confidence based on non-position-based data sources.
INFO:flight_processing.data.airspace_graph:Getting edge weights.
INFO:flight_processing.data.airspace_graph:Computing confidence based on non-position-based data sources.
INFO:flight_processing.data.airspace_graph:Getting edge weights.
INFO:flight_processing.data.airspace_graph:Computing confidence based on non-position-based data sources.
INFO:flight_processing.data.airspace_graph:Getting edge weights.
INFO:flight_processing.data.airspace_graph:Computing confidence based on non-position-based data sources.
INFO:flight_processing.data.airspace_graph:Getting edge weights.
INFO:flight_processing.data.airspace_graph:Computing confidence based on non-position-based data sources.
INFO:flight_processing.data.airspace_graph:Getting edge weights.
INFO:flight_processing.data.airspace_graph:Computing confidence based on non-position-based data sources.
INFO:flight_processing.data.airspace_graph:Getting edge weights.
INFO:flight_processing.data.airspace_graph:Computing confidence based on non-position-based data sources.
INFO:flight_processing.data.airspace_graph:Getting edge weights.
INFO:flight_processing.data.airspace_graph:Computing confidence based on non-position-based data sources.
INFO:flight_processing.data.airspace_graph:Getting edge weights.
INFO:flight_processing.data.airspace_graph:Computing confidence based on non-position-based data sources.
INFO:flight_processing.data.airspace_graph:Getting edge weights.
INFO:flight_processing.data.airspace_graph:Computing confidence based on non-position-based data sources.
INFO:flight_processing.data.airspace_graph:Getting edge weights.
INFO:flight_processing.data.airspace_graph:Computing confidence based on non-position-based data sources.
INFO:flight_processing.data.airspace_graph:Getting edge weights.
INFO:flight_processing.data.airspace_graph:Computing confidence based on non-position-based data sources.
INFO:flight_processing.data.airspace_graph:Getting edge weights.
INFO:flight_processing.data.airspace_graph:Computing confidence based on non-position-based data sources.
INFO:flight_processing.data.airspace_graph:Getting edge weights.
INFO:flight_processing.data.airspace_graph:Computing confidence based on non-position-based data sources.
INFO:flight_processing.data.airspace_graph:Getting edge weights.
INFO:flight_processing.data.airspace_graph:Computing confidence based on non-position-based data sources.
INFO:flight_processing.data.airspace_graph:Getting edge weights.
INFO:flight_processing.data.airspace_graph:Computing confidence based on non-position-based data sources.
INFO:flight_processing.data.airspace_graph:Getting edge weights.
INFO:flight_processing.data.airspace_graph:Computing confidence based on non-position-based data sources.
INFO:flight_processing.data.airspace_graph:Getting edge weights.
INFO:flight_processing.data.airspace_graph:Computing confidence based on non-position-based data sources.
INFO:flight_processing.data.airspace_graph:Getting edge weights.
INFO:flight_processing.data.airspace_graph:Computing confidence based on non-position-based data sources.
INFO:flight_processing.data.airspace_graph:Getting edge weights.
INFO:flight_processing.data.airspace_graph:Computing confidence based on non-position-based data sources.
INFO:flight_processing.data.airspace_graph:Getting edge weights.
INFO:flight_processing.data.airspace_graph:Computing confidence based on non-position-based data sources.

[{'distance1': None,
  'distance2': None,
  'confidence': 1.0,
  'weight': 966,
  'weight_adjusted': 0.011811023622047244,
  'confidence_distance': 0.0,
  'confidence_weight': 1.0,
  'confidence_weight_adjusted': 0.0,
  'airspace1': 457,
  'airspace2': 602,
  'name1': 'UPPER AIRSPACE CTA',
  'name2': 'SCOTTISH TMA 3'},
 {'distance1': None,
  'distance2': None,
  'confidence': 1.0,
  'weight': 966,
  'weight_adjusted': 0.011811023622047244,
  'confidence_distance': 0.0,
  'confidence_weight': 1.0,
  'confidence_weight_adjusted': 0.0,
  'airspace1': 458,
  'airspace2': 602,
  'name1': 'UPPER AIRSPACE CTA',
  'name2': 'SCOTTISH TMA 3'},
 {'distance1': None,
  'distance2': None,
  'confidence': 1.0,
  'weight': 966,
  'weight_adjusted': 0.011811023622047244,
  'confidence_distance': 0.0,
  'confidence_weight': 1.0,
  'confidence_weight_adjusted': 0.0,
  'airspace1': 459,
  'airspace2': 602,
  'name1': 'UPPER AIRSPACE CTA',
  'name2': 'SCOTTISH TMA 3'},
 {'distance1': None,
  'distance2': None,
  'confidence': 1.0,
  'weight': 966,
  'weight_adjusted': 0.011811023622047244,
  'confidence_distance': 0.0,
  'confidence_weight': 1.0,
  'confidence_weight_adjusted': 0.0,
  'airspace1': 460,
  'airspace2': 602,
  'name1': 'UPPER AIRSPACE CTA',
  'name2': 'SCOTTISH TMA 3'},
 {'distance1': None,
  'distance2': None,
  'confidence': 1.0,
  'weight': 966,
  'weight_adjusted': 0.011811023622047244,
  'confidence_distance': 0.0,
  'confidence_weight': 1.0,
  'confidence_weight_adjusted': 0.0,
  'airspace1': 461,
  'airspace2': 602,
  'name1': 'UPPER AIRSPACE CTA',
  'name2': 'SCOTTISH TMA 3'},
 {'distance1': None,
  'distance2': None,
  'confidence': 1.0,
  'weight': 966,
  'weight_adjusted': 0.011811023622047244,
  'confidence_distance': 0.0,
  'confidence_weight': 1.0,
  'confidence_weight_adjusted': 0.0,
  'airspace1': 462,
  'airspace2': 602,
  'name1': 'UPPER AIRSPACE CTA',
  'name2': 'SCOTTISH TMA 3'},
 {'distance1': None,
  'distance2': None,
  'confidence': 1.0,
  'weight': 966,
  'weight_adjusted': 0.011811023622047244,
  'confidence_distance': 0.0,
  'confidence_weight': 1.0,
  'confidence_weight_adjusted': 0.0,
  'airspace1': 463,
  'airspace2': 602,
  'name1': 'UPPER AIRSPACE CTA',
  'name2': 'SCOTTISH TMA 3'},
 {'distance1': None,
  'distance2': None,
  'confidence': 1.0,
  'weight': 966,
  'weight_adjusted': 0.011811023622047244,
  'confidence_distance': 0.0,
  'confidence_weight': 1.0,
  'confidence_weight_adjusted': 0.0,
  'airspace1': 457,
  'airspace2': 601,
  'name1': 'UPPER AIRSPACE CTA',
  'name2': 'SCOTTISH TMA 3'},
 {'distance1': None,
  'distance2': None,
  'confidence': 1.0,
  'weight': 966,
  'weight_adjusted': 0.011811023622047244,
  'confidence_distance': 0.0,
  'confidence_weight': 1.0,
  'confidence_weight_adjusted': 0.0,
  'airspace1': 458,
  'airspace2': 601,
  'name1': 'UPPER AIRSPACE CTA',
  'name2': 'SCOTTISH TMA 3'},
 {'distance1': None,
  'distance2': None,
  'confidence': 1.0,
  'weight': 966,
  'weight_adjusted': 0.011811023622047244,
  'confidence_distance': 0.0,
  'confidence_weight': 1.0,
  'confidence_weight_adjusted': 0.0,
  'airspace1': 459,
  'airspace2': 601,
  'name1': 'UPPER AIRSPACE CTA',
  'name2': 'SCOTTISH TMA 3'},
 {'distance1': None,
  'distance2': None,
  'confidence': 1.0,
  'weight': 966,
  'weight_adjusted': 0.011811023622047244,
  'confidence_distance': 0.0,
  'confidence_weight': 1.0,
  'confidence_weight_adjusted': 0.0,
  'airspace1': 460,
  'airspace2': 601,
  'name1': 'UPPER AIRSPACE CTA',
  'name2': 'SCOTTISH TMA 3'},
 {'distance1': None,
  'distance2': None,
  'confidence': 1.0,
  'weight': 966,
  'weight_adjusted': 0.011811023622047244,
  'confidence_distance': 0.0,
  'confidence_weight': 1.0,
  'confidence_weight_adjusted': 0.0,
  'airspace1': 461,
  'airspace2': 601,
  'name1': 'UPPER AIRSPACE CTA',
  'name2': 'SCOTTISH TMA 3'},
 {'distance1': None,
  'distance2': None,
  'confidence': 1.0,
  'weight': 966,
  'weight_adjusted': 0.011811023622047244,
  'confidence_distance': 0.0,
  'confidence_weight': 1.0,
  'confidence_weight_adjusted': 0.0,
  'airspace1': 462,
  'airspace2': 601,
  'name1': 'UPPER AIRSPACE CTA',
  'name2': 'SCOTTISH TMA 3'},
 {'distance1': None,
  'distance2': None,
  'confidence': 1.0,
  'weight': 966,
  'weight_adjusted': 0.011811023622047244,
  'confidence_distance': 0.0,
  'confidence_weight': 1.0,
  'confidence_weight_adjusted': 0.0,
  'airspace1': 463,
  'airspace2': 601,
  'name1': 'UPPER AIRSPACE CTA',
  'name2': 'SCOTTISH TMA 3'},
 {'distance1': None,
  'distance2': None,
  'confidence': 1.0,
  'weight': 966,
  'weight_adjusted': 0.011811023622047244,
  'confidence_distance': 0.0,
  'confidence_weight': 1.0,
  'confidence_weight_adjusted': 0.0,
  'airspace1': 457,
  'airspace2': 603,
  'name1': 'UPPER AIRSPACE CTA',
  'name2': 'SCOTTISH TMA 3'},
 {'distance1': None,
  'distance2': None,
  'confidence': 1.0,
  'weight': 966,
  'weight_adjusted': 0.011811023622047244,
  'confidence_distance': 0.0,
  'confidence_weight': 1.0,
  'confidence_weight_adjusted': 0.0,
  'airspace1': 458,
  'airspace2': 603,
  'name1': 'UPPER AIRSPACE CTA',
  'name2': 'SCOTTISH TMA 3'},
 {'distance1': None,
  'distance2': None,
  'confidence': 1.0,
  'weight': 966,
  'weight_adjusted': 0.011811023622047244,
  'confidence_distance': 0.0,
  'confidence_weight': 1.0,
  'confidence_weight_adjusted': 0.0,
  'airspace1': 459,
  'airspace2': 603,
  'name1': 'UPPER AIRSPACE CTA',
  'name2': 'SCOTTISH TMA 3'},
 {'distance1': None,
  'distance2': None,
  'confidence': 1.0,
  'weight': 966,
  'weight_adjusted': 0.011811023622047244,
  'confidence_distance': 0.0,
  'confidence_weight': 1.0,
  'confidence_weight_adjusted': 0.0,
  'airspace1': 460,
  'airspace2': 603,
  'name1': 'UPPER AIRSPACE CTA',
  'name2': 'SCOTTISH TMA 3'},
 {'distance1': None,
  'distance2': None,
  'confidence': 1.0,
  'weight': 966,
  'weight_adjusted': 0.011811023622047244,
  'confidence_distance': 0.0,
  'confidence_weight': 1.0,
  'confidence_weight_adjusted': 0.0,
  'airspace1': 461,
  'airspace2': 603,
  'name1': 'UPPER AIRSPACE CTA',
  'name2': 'SCOTTISH TMA 3'},
 {'distance1': None,
  'distance2': None,
  'confidence': 1.0,
  'weight': 966,
  'weight_adjusted': 0.011811023622047244,
  'confidence_distance': 0.0,
  'confidence_weight': 1.0,
  'confidence_weight_adjusted': 0.0,
  'airspace1': 462,
  'airspace2': 603,
  'name1': 'UPPER AIRSPACE CTA',
  'name2': 'SCOTTISH TMA 3'},
 {'distance1': None,
  'distance2': None,
  'confidence': 1.0,
  'weight': 966,
  'weight_adjusted': 0.011811023622047244,
  'confidence_distance': 0.0,
  'confidence_weight': 1.0,
  'confidence_weight_adjusted': 0.0,
  'airspace1': 463,
  'airspace2': 603,
  'name1': 'UPPER AIRSPACE CTA',
  'name2': 'SCOTTISH TMA 3'}]

Visualisation

We can plot this flight on a map along with the airspaces it intersected along the way.

regions = set()
for h in handovers:
    regions.add(int(h['airspace1']))
    regions.add(int(h['airspace2']))

regions

{457, 458, 459, 460, 461, 462, 463, 601, 602, 603}

airspacegraph.draw_graph_map(flight=flight, subset=regions)

INFO:flight_processing.data.airspace_graph:Downloading terrain data from Stamen.
INFO:flight_processing.data.airspace_graph:Plotting airspace boundaries on map.
INFO:flight_processing.data.airspace_graph:Extracting edge weights from graph.
INFO:flight_processing.data.airspace_graph:Plotting graph on map.
INFO:flight_processing.data.airspace_graph:Plotting flight(s) on map.
INFO:flight_processing.data.airspace_graph:Plotting subset of airspaces on map.
_images/demo_airspace_graph_36_1.png 
# Cleanup
del airspacegraph