HALO position and attitude

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HALO position and attitude#

Data access#

Some of the data, like the preliminary data of the HALO-(AC)3 campaign, is stored on the (AC)3 nextcloud server. This requires username and password as credentials (registration) that need to be loaded from environment variables.

import ac3airborne
from ac3airborne.tools import flightphase
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.colors import to_hex
import matplotlib.dates as mdates
from matplotlib import cm
import ipyleaflet
from ipyleaflet import Polyline, Map, basemaps, basemap_to_tiles
from ipywidgets import Layout
from simplification.cutil import simplify_coords_idx
%matplotlib inline

import os
from dotenv import load_dotenv

load_dotenv()

kwds = {'simplecache': dict(
    cache_storage=os.environ['INTAKE_CACHE'], 
    same_names=True
)}

import ac3airborne

Show available data sets

cat = ac3airborne.get_intake_catalog()
meta = ac3airborne.get_flight_segments()

mission = 'HALO-AC3'
platform = 'HALO'
flight_id = 'HALO-AC3_HALO_RF03'

flight = meta[mission][platform][flight_id]

# read gps
ds_gps_ins = cat[mission][platform]['GPS_INS'][flight_id](storage_options=kwds).to_dask()

/net/sever/mech/miniconda3/envs/howtoac3/lib/python3.11/site-packages/intake_xarray/base.py:21: FutureWarning: The return type of `Dataset.dims` will be changed to return a set of dimension names in future, in order to be more consistent with `DataArray.dims`. To access a mapping from dimension names to lengths, please use `Dataset.sizes`.
  'dims': dict(self._ds.dims),

def colors(n):
    """Creates set of random colors of length n"""
    
    cmap = cm.get_cmap('gist_rainbow')
    rnd = np.random.uniform(low=0, high=1, size=n)
    cols = cmap(rnd)
    
    return cols


def simplify_dataset(ds, tolerance):
    indices_to_take = simplify_coords_idx(np.stack([ds.lat.values, ds.lon.values], axis=1), tolerance)
    return ds.isel(time=indices_to_take)

# plot map
m = Map(basemap=basemap_to_tiles(basemaps.NASAGIBS.ModisTerraTrueColorCR, str(flight['date'])),
        center=(80, 10),
        zoom=4,
        scroll_wheel_zoom=True,
        layout=Layout(width='1000px', height='1000px')
        )

col_segments = colors(len(flight['segments']))

for i, segment in enumerate(flight['segments']):
    
    # reduce flight segment
    ds_reduced = simplify_dataset(ds_gps_ins.sel(time=slice(segment['start'], 
                                                            segment['end'])), 
                                  1e-5)
    
    # plot flight segment
    line = Polyline(locations=np.stack([ds_reduced.lat.values, ds_reduced.lon.values], axis=1).tolist(),
                    color=to_hex(col_segments[i]),
                    fill=False,
                    weight=2,
                    name=str(i) + ': ' + segment['name'])
    m.add_layer(line)

m.add_control(ipyleaflet.ScaleControl())
m.add_control(ipyleaflet.LayersControl(position='topright'))
m.add_control(ipyleaflet.FullScreenControl())

display(m)

/tmp/ipykernel_2018440/4205725992.py:4: MatplotlibDeprecationWarning: The get_cmap function was deprecated in Matplotlib 3.7 and will be removed in 3.11. Use ``matplotlib.colormaps[name]`` or ``matplotlib.colormaps.get_cmap()`` or ``pyplot.get_cmap()`` instead.
  cmap = cm.get_cmap('gist_rainbow')
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