MeerKAT Extension (SCU) (lib)rary for the MKE antennas and some basic simulators
Project description
mke_sculib
MeerKAT Extension (MKE) (SCU) Science Computation Unit interface (lib)rary for the MKE antennas and some basic simulators
See also examples
(especially examples/getting_started.ipynb
) for examples on how to use this library.
Installing
pip install mke_sculib
Usage for Antenna Control:
The main class is scu_api.scu.scu which can be loaded as scu_api
from mke_sculib
. This class provides an interface to the MeerKAT Extension Telescopes' dish structure controllers.
It does so by connecting to the Antenna Control Unit (ACU) via the HTTP REST API and websockets of the Science Computation Unit (SCU) both developed by OHB Digital Connect GmbH. It's designed for use with the SKA-MPI Demonstrator Radio Telescope in South Africa and the MeerKAT Extension Radio Telescopes.
Construct
In order to connect to the REST API of the Telescope SCU use the library as follows:
import mke_sculib
dish = mke_sculib.scu_api(ip='134.104.22.44')
dish.determine_dish_type()
dish.status()
Load
NOTE: This only works for telescopes in the Karoo with access to the Karoo site network (engineering network)
import mke_sculib
# direct loading by full name
dish = mke_sculib.load('skampi')
dish.status()
# partial names "119" vs "119A" also work
dish = mke_sculib.load('119')
dish.status()
# If you want to interactively select which dish to load use load withut an antenna_id
dish = mke_sculib.load()
dish.status()
Dish Status
show full status by:
dish = mke_sculib.scu_api(ip='134.104.22.44')
dish.show() # dish.print_info() to force ascii
Antenna Movement
This is how to control the dish:
dish.status()
dish.start()
dish.move(az=15, el=85) # or equivalent dish.move(15, 85)
dish.status()
dish.move(band='Band 5b')
dish.shutdown()
dish.status()
Minimal Tracking Table Example
minimal example
import pandas as pd
import numpy as np
tmjd = (Time.now() + np.arange(-10, 30, 0.5) * u.s).mjd
azs = np.arange(0, 40, 0.5)
els = np.arange(90, 50, 0.5)
dish.run_track_table(tmjd, azs, els)
history = dish.get_session_as_df()
Minimal Tracking Table Example for a Position On Sky
this is how to observe an astronomical Target using a tracking table
import pandas as pd
import numpy as np
from astropy.time import Time
from astropy import units as u
from astropy.coordinates import get_icrs_coordinates, EarthLocation, AltAz, SkyCoord
# make a tracking table for 'HIP104382' using astropy
loc = EarthLocation(lat = -30.778551, lon = 21.397161, height = 1094.6*u.m)
t = Time.now() + np.arange(-10, 60, 1.0) * u.s
altaz = get_icrs_coordinates('HIP104382').transform_to(AltAz(location=loc, obstime=t))
tracking_table = pd.DataFrame({'time': t.mjd, 'az': altaz.az.deg, 'el': altaz.alt.deg})
with dish.with_tt(df=tracking_table) as track:
print('tracking...')
while track.get_t_remaining() > 0:
print(f'{track.get_t_remaining()=} {dish.azel=} {dish.get_state()}')
dish.wait_duration(1)
last_session = track.session
mke_sculib.plot_motion(last_session, df_tt = tracking_table)
Interfacing with a Local Instance of Stellarium
If you have Stellarium installed on a machine somewhere (or locally) and have "remote control" plugin enabled (see below for instructions how to do this) you can interface between a MKE dish and Stellarium like this.
dish = scu('134.104.22.44', use_socket=True, wait_done_by_uuid=True)
dish.link_stellarium() # url for stellatium is 'http://localhost:8090' by default
or in one go using the convenience function in the mke_sculib
root library:
import mke_sculib
# will query data for dish on pad 119 automatically and interface with stellarium
mke_sculib.link_stellarium('119')
The remote Control Plugin in Stellarium can be enabled by
- starting or opening Stellarium
- opening "Config" (the "Wrench" icon in the lower left corner menu),
- opening Tab "Plugins"
- selecting "Remote Control" on the left
- click "configure"
- check "Server enabled"
- check "Enable automatically on startup"
- set your desired port (8090 recommended)
- click "Save setting"
- close window
- check "Load at startup" in the previous menu
- close window
- restart Stellarium
you now able to interface between stellarium and the mke_sculib as shown above.
Subscribing to callbacks
Data callbacks subscription example:
# this is a simple logging function, which will log data updates to stdout
def print_new_data(time_astropy, data_dict):
print(f'{time.time():.2f} new data tick at {time_astropy.iso}, with data for N={len(data_dict)} channels | {id(data_dict)=}, {sys.getsizeof(data_dict)=}')
dish.callbacks_on_new_data.append(print_new_data)
Event callback subscription example:
def on_new_event(e):
print(f'{time.time():.2f}, new event wiith uuid {e.uuid}!')
print(e.to_str())
dish.callbacks_on_new_events.append(on_new_event)
clear callbacks like this:
dish.clear_all_callbacks()
Usage as Simulator:
Using the simulator with the same script as used for operating the telescope can be achieved like this:
from mke_sculib.sim import plot_motion_pyplot as plot_motion
# instead of THIS:
# from mke_sculib.scu import scu
# mpi = scu('134.104.22.44', '8080')
# do THIS for simulation:
from mke_sculib.sim import scu_sim as scu
mpi = scu()
After a test has been done, the whole test history can be plotted in pyplot via:
# show the history data
dfh = mpi.get_history_df(interval_ms = None)
axs = plot_motion(dfh)
Using the library within Test Scripts:
After installation, the library can be used to script automatic tests. A minimal example for a tracking test is given below:
# Init
import astropy.units as u
from astropy.time import Time
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from mke_sculib.sim import plot_motion_pyplot as plot_motion
from mke_sculib.sim import scu_sim as scu
mpi = scu()
# Startup
mpi.unstow()
mpi.wait_duration(30) # sec
mpi.activate_dmc()
mpi.wait_duration(wait10)
# Move to starting az, el
mpi.abs_azimuth(-90, 3) # degree, degree / s
mpi.abs_elevation(53, 1) # degree, degree / s
mpi.wait_settle()
mpi.wait_duration(5) # sec
# move to Band 2
mpi.move_to_band('Band 2')
mpi.wait_settle()
mpi.wait_duration(wait5)
# make a dummy tracking table
t = mpi.t_internal + (np.arange(5) * astropy.units.u.s)
az = np.linspace(-90, -89, len(t))
el = np.linspace(53, 54, len(t))
# start a tracking table
mpi.upload_track_table(t, az, el)
# start logging for my testrun
mpi.start_logger('full_configuration')
# wait for track table to finish
mpi.wait_duration(np.ptp(t) + 5)
# shut down
mpi.stop_logger()
mpi.wait_duration(5)
mpi.deactivate_dmc()
mpi.wait_duration(10)
mpi.stow()
# show the sessions data
df = mpi.get_session_as_df(interval_ms = 100)
plot_motion(df)
df.to_csv('testdata_acu.csv')
HTTP Dummy server
This library has a dummy server with dashboard implemented which can run on any machine with anaconda installed.
See: servers
for the examples.
NOTE: Change the absolut path in the files if necessary
python /servers/dashboard.py
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