def run_scanning_simulation(radar_ctrl):
p = Profiler()
radar_ctrl.profiler = p
p.start('total')
scheduler = ObservedScanning(
radar=eiscat3d,
controllers=[radar_ctrl],
logger=logger,
profiler=p,
)
p.start('equidistant_sampling')
t = sorts.equidistant_sampling(
orbit=obj.state,
start_t=0,
end_t=end_t,
max_dpos=1e3,
)
p.stop('equidistant_sampling')
print(f'Temporal points obj: {len(t)}')
p.start('get_state')
states = obj.get_state(t)
p.stop('get_state')
p.start('find_passes')
#rename cache_data to something more descriptive
passes = eiscat3d.find_passes(t, states, cache_data=True)
p.stop('find_passes')
p.start('observe_passes')
data = scheduler.observe_passes(passes, space_object=obj, snr_limit=False)
p.stop('observe_passes')
for psi in data:
for txps in psi:
for rxtxps in txps:
print(f'Max SNR={10*np.log10(rxtxps["snr"].max())} dB')
p.stop('total')
print(f'\n {radar_ctrl.__class__}: len(t) = {len(radar_ctrl.t)} \n')
print(p.fmt(normalize='total'))
data[:, 0] = t
names = []
targets = []
for ind, mrad in enumerate(generator):
radar, meta = mrad
names.append(meta['controller_type'].__name__)
targets.append(meta['target'])
for ri, rx in enumerate(radar.rx):
data[ind, 1 + ri * 2] = rx.beam.azimuth
data[ind, 2 + ri * 2] = rx.beam.elevation
data = data.T.tolist() + [names, targets]
data = list(map(list, zip(*data)))
return data
p = Profiler()
scheduler = MyStaticList(radar=eiscat3d, controllers=[e3d_tracker], profiler=p)
sched_data = scheduler.schedule()
rx_head = [
f'rx{i} {co}' for i in range(len(scheduler.radar.rx))
for co in ['az', 'el']
]
sched_tab = tabulate(sched_data,
headers=["t [s]"] + rx_head + ['Controller', 'Target'])
print(sched_tab)
p.start('total')
'''
import numpy as np
import matplotlib.pyplot as plt
import pyorb
import sorts
eiscat3d = sorts.radars.eiscat3d
from sorts.profiling import Profiler
from sorts.propagator import SGP4
Prop_cls = SGP4
Prop_opts = dict(settings=dict(out_frame='ITRF', ), )
prop = Prop_cls(**Prop_opts)
p = Profiler()
p.start('total')
orb = pyorb.Orbit(M0=pyorb.M_earth,
direct_update=True,
auto_update=True,
degrees=True,
a=7200e3,
e=0.1,
i=75,
omega=0,
Omega=79,
anom=72,
epoch=53005.0)
print(orb)
#!/usr/bin/env python
'''
Interpolation
======================
'''
import numpy as np
import matplotlib.pyplot as plt
from sorts.profiling import Profiler
from sorts.propagator import SGP4
from sorts import interpolation
p = Profiler()
prop = SGP4(
settings=dict(out_frame='TEME', ),
profiler=p,
)
state0 = np.array(
[-7100297.113, -3897715.442, 18568433.707, 86.771, -3407.231, 2961.571])
t = np.arange(0.0, 360.0, 30.0)
mjd0 = 53005
states = prop.propagate(t, state0, mjd0, A=1.0, C_R=1.0, C_D=1.0)
interpolator = interpolation.Legendre8(states, t)
t_f = np.arange(0.0, 360.0, 1.0)
finer_states = interpolator.get_state(t_f)
orekit_data = '/home/danielk/IRF/IRF_GITLAB/orekit_build/orekit-data-master.zip'
Prop_cls = Orekit
Prop_opts = dict(
orekit_data=orekit_data,
settings=dict(
in_frame='GCRS',
out_frame='ITRS',
),
)
end_t = 12 * 3600.0
scan = Fence(azimuth=90, num=40, dwell=0.1, min_elevation=30)
p = Profiler()
logger = sorts.profiling.get_logger('scanning')
objs = [
SpaceObject(
Prop_cls,
propagator_options=Prop_opts,
a=7200e3,
e=0.02,
i=75,
raan=86,
aop=0,
mu0=60,
epoch=53005.0,
parameters=dict(d=0.1, ),
======================================
'''
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import pyorb
import sorts
eiscat3d = sorts.radars.eiscat3d
from sorts.controller import Tracker
from sorts.propagator import SGP4
from sorts.profiling import Profiler
p = Profiler()
p.start('total')
prop = SGP4(settings=dict(out_frame='ITRF', ), )
orb = pyorb.Orbit(M0=pyorb.M_earth,
direct_update=True,
auto_update=True,
degrees=True,
a=6700e3,
e=0,
i=75,
omega=0,
Omega=80,
anom=72)
t = np.linspace(0, 120, num=10)
from sorts.scheduler import StaticList, ObservedParameters
from sorts.controller import Scanner
from sorts import SpaceObject
from sorts.profiling import Profiler
from sorts.radar.scans import Fence
from sorts.propagator import SGP4
Prop_cls = SGP4
Prop_opts = dict(settings=dict(out_frame='ITRF', ), )
end_t = 600.0
scan = Fence(azimuth=90, num=40, dwell=0.1, min_elevation=30)
p = Profiler()
logger = sorts.profiling.get_logger('scanning')
objs = [
SpaceObject(
Prop_cls,
propagator_options=Prop_opts,
a=7200e3,
e=0.02,
i=75,
raan=86,
aop=0,
mu0=60,
epoch=53005.0,
parameters=dict(d=0.1, ),
#!/usr/bin/env python
'''
Profiling save and load
================================
'''
import pathlib
from sorts.profiling import Profiler
p = Profiler()
p.start('program')
p.start('list init')
lst = list(range(200))
p.stop('list init')
for i in range(1000):
p.start('list reversal')
lst = lst[::-1]
p.stop('list reversal')
p.stop('program')
print(p)
pth = pathlib.Path(__file__).parent / 'data' / 'profiler_data.txt'
print(f'Writing profiler data to: {pth}')
p.to_txt(pth)
new_profiler = Profiler.from_txt(pth)
def observe_objects(objs, controllers, end_t=600.0, dt=10.0, verbose=True):
p = Profiler()
class ObservedScanning(StaticList, ObservedParameters):
pass
#set radar
for ctrl in controllers:
ctrl.radar = eiscat3d
ctrl.profiler = p
ctrl.logger = logger
p.start('total')
scheduler = ObservedScanning(
radar=eiscat3d,
controllers=controllers,
logger=logger,
profiler=p,
)
t = np.arange(0, end_t, dt)
if verbose:
for obj in objs:
print(obj)
datas = []
passes = []
states = []
for ind in range(len(objs)):
p.start('get_state')
states += [objs[ind].get_state(t)]
p.stop('get_state')
p.start('find_passes')
passes += [eiscat3d.find_passes(t, states[ind], cache_data=True)]
p.stop('find_passes')
p.start('observe_passes')
data = scheduler.observe_passes(passes[ind],
space_object=objs[ind],
snr_limit=False)
p.stop('observe_passes')
datas.append(data)
p.stop('total')
if verbose:
print(p.fmt(normalize='total'))
return {'t': t, 'observations': datas, 'passes': passes, 'states': states}
#!/usr/bin/env python
'''
Profiling
==========
'''
from sorts.profiling import Profiler
p = Profiler()
p.start('program')
p.start('list init')
lst = list(range(200))
p.stop('list init')
for i in range(1000):
p.start('list reversal')
lst = lst[::-1]
p.stop('list reversal')
p.stop('program')
print(p)
#!/usr/bin/env python
'''
Profiling Orekit
======================
'''
import numpy as np
from sorts.profiling import Profiler
from sorts.propagator import Orekit
p = Profiler()
p.start('total')
orekit_data = '/home/danielk/IRF/IRF_GITLAB/orekit_build/orekit-data-master.zip'
prop = Orekit(
orekit_data=orekit_data,
settings=dict(
in_frame='ITRS',
out_frame='GCRS',
drag_force=False,
radiation_pressure=False,
),
profiler=p,
)
print(prop)
state0 = np.array(
[-7100297.113, -3897715.442, 18568433.707, 86.771, -3407.231, 2961.571])
#!/usr/bin/env python
'''
Profiling memory leaks
=========================
'''
import matplotlib.pyplot as plt
from sorts.profiling import Profiler
p = Profiler(track_memory=True)
#As the profiler data is also stored in Python tracked memory
# a diff of "nothing" will still result in more allocation of memory
# including initialization for structures and the like
p.snapshot('nothing')
p.memory_diff('nothing')
#this allocates memory
p.snapshot('one list')
lst = list(range(2000))
p.memory_diff('one list')
#and if we take care to delete the variable
#only profiling allocations are left over
del lst
p.memory_diff('one list', save='one list - and clear')
#this iteration changes allocation each iteration and does not clean up
lsts = []