aurora-asi-lib 0.7.4

Easily download, plot, animate, and analyze auroral all sky imager (ASI) data.

aurora-asi-lib

Easily download, plot, animate, and analyze aurora all sky imager (ASI) data. Currently the two supported camera systems (missions) are:

• Red-line Emission Geospace Observatory (REGO)
• Time History of Events and Macroscale Interactions during Substorms (THEMIS).

API Documentation / Code on GitHub

Easily make ASI plots (example 1)!

And movies! (example4; the track and mean ASI intensity plot is a little bit more work.)

Feel free to contact me and request that I add other ASI missions to asilib.

Examples

Before you can run these examples, make sure that asilib is configured with the installation steps below. These examples, and more, are in the asilib/examples/ folder.

Example 1

This example uses asilib to plot one image of a bright auroral arc.

from datetime import datetime

import matplotlib.pyplot as plt

import asilib

# A bright auroral arc that was analyzed by Imajo et al., 2021 "Active 
# auroral arc powered by accelerated electrons from very high altitudes"
image_time, image, ax, im = asilib.plot_image(datetime(2017, 9, 15, 2, 34, 0), 'THEMIS', 'RANK', 
                    color_norm='log', force_download=False)
plt.colorbar(im)
ax.axis('off')
plt.show()

Example 2

This example uses asilib to plot a 5 minute movie of an auroral arc brightening right as a meteor burns up at zenith!

from datetime import datetime

import asilib

time_range = (datetime(2015, 3, 26, 6, 7), datetime(2015, 3, 26, 6, 12))
asilib.plot_movie(time_range, 'THEMIS', 'FSMI')
print(f'Movie saved in {asilib.config.ASI_DATA_DIR / "movies"}')

Example 3

This example is longer and it shows how to superpose a hypothetical satellite path through the THEMIS camera located at Rankin Inlet.

from datetime import datetime

import numpy as np
import matplotlib.pyplot as plt

import asilib


# ASI parameters
mission = 'THEMIS'
station = 'RANK'
time_range = (datetime(2017, 9, 15, 2, 32, 0), datetime(2017, 9, 15, 2, 35, 0))

fig, ax = plt.subplots(2, 1, figsize=(7, 10), gridspec_kw={'height_ratios':[4, 1]}, 
                        constrained_layout=True)

# Load the calibration data. This is only necessary to create a fake satellite track.
skymap_dict = asilib.load_skymap(mission, station, time_range[0])

# Create the fake satellite track coordinates: latitude, longitude, altitude (LLA).
# This is a north-south satellite track oriented to the east of the THEMIS/RANK 
# station.
n = int((time_range[1] - time_range[0]).total_seconds() / 3)  # 3 second cadence.
lats = np.linspace(skymap_dict["SITE_MAP_LATITUDE"] + 5, skymap_dict["SITE_MAP_LATITUDE"] - 5, n)
lons = (skymap_dict["SITE_MAP_LONGITUDE"]-0.5) * np.ones(n)
alts = 110 * np.ones(n)
lla = np.array([lats, lons, alts]).T

# Map the satellite track to the station's azimuth and elevation coordinates and
# image pixels. NOTE: the mapping is not along the magnetic field lines! You need
# to install IRBEM and then use asilib.lla2footprint() before 
# lla2azel() is called.
sat_azel, sat_azel_pixels = asilib.lla2azel(mission, station, time_range[0], lla)

# Initiate the movie generator function. Any errors with the data will be raised here.
movie_generator = asilib.plot_movie_generator(
    time_range, mission, station, azel_contours=True, overwrite=True,
    ax=ax[0]
)

# Use the generator to get the images and time stamps to estimate mean the ASI
# brightness along the satellite path and in a (10x10 km) box.
image_data = movie_generator.send('data')

# Calculate what pixels are in a box_km around the satellite, and convolve it
# with the images to pick out the ASI intensity in that box.
area_box_mask = asilib.equal_area(mission, station, time_range[0], lla, box_km=(20, 20))
asi_brightness = np.nanmean(image_data.images*area_box_mask, axis=(1,2))
area_box_mask[np.isnan(area_box_mask)] = 0  # To play nice with plt.contour()

for i, (time, image, _, im) in enumerate(movie_generator):
    # Note that because we are drawing moving data: ASI image in ax[0] and 
    # the ASI time series + a vertical bar at the image time in ax[1], we need
    # to redraw everything at every iteration.
     
    # Clear ax[1] (ax[0] cleared by asilib.plot_movie_generator())
    ax[1].clear()
    # Plot the entire satellite track
    ax[0].plot(sat_azel_pixels[:, 0], sat_azel_pixels[:, 1], 'red')
    ax[0].contour(area_box_mask[i, :, :], levels=[0.99], colors=['yellow'])
    # Plot the current satellite position.
    ax[0].scatter(sat_azel_pixels[i, 0], sat_azel_pixels[i, 1], c='red', marker='o', s=50)

    # Plot the time series of the mean ASI intensity along the satellite path
    ax[1].plot(image_data.time, asi_brightness)
    ax[1].axvline(time, c='k') # At the current image time.

    # Annotate the station and satellite info in the top-left corner.
    station_str = (
        f'{mission}/{station} '
        f'LLA=({skymap_dict["SITE_MAP_LATITUDE"]:.2f}, '
        f'{skymap_dict["SITE_MAP_LONGITUDE"]:.2f}, {skymap_dict["SITE_MAP_ALTITUDE"]:.2f})'
    )
    satellite_str = f'Satellite LLA=({lla[i, 0]:.2f}, {lla[i, 1]:.2f}, {lla[i, 2]:.2f})'
    ax[0].text(0, 1, station_str + '\n' + satellite_str, va='top', 
            transform=ax[0].transAxes, color='red')
    ax[1].set(xlabel='Time', ylabel='Mean ASI intensity [counts]')

print(f'Movie saved in {asilib.config["ASI_DATA_DIR"] / "movies"}')

Installation

To install this package as a user, run:

python3 -m pip install aurora-asi-lib

To install this package as a developer, run:

git clone [e-mail]:mshumko/aurora-asi-lib.git
cd aurora-asi-lib
python3 -m pip install -r requirements.txt # or
python3 -m pip install -e .

In either case, you'll need to configure your system paths to tell asilib (the import name) where to save the ASI data and movies. Run python3 -m asilib config to set up the data directory where the image, skymap, and movie files will be saved. Your settings will be stored in config.py. If you configure asilib, but don't specify a data directory, a default directory in ~/asilib-data will be created if it doesn't exist.

ffmpeg dependency

To make movies you'll also need to install the ffmpeg library.

• Ubuntu: apt install ffmpeg
• Mac: brew install ffmpeg

NOTES

• If you get the "ERROR: Could not build wheels for pymap3d which use PEP 517 and cannot be installed directly" error when installing, you need to upgrade your pip, setuptools, and wheel libaries via python3 -m pip install --upgrade pip setuptools wheel.