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'))
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}
e=0.1,
i=75,
omega=0,
Omega=79,
anom=72,
epoch=53005.0)
print(orb)
p.start('equidistant_sampling')
t = sorts.equidistant_sampling(
orbit=orb,
start_t=0,
end_t=3600 * 24 * 1,
max_dpos=1e4,
)
p.stop('equidistant_sampling')
print(f'Temporal points: {len(t)}')
p.start('propagate')
states = prop.propagate(t,
orb.cartesian[:, 0],
orb.epoch,
A=1.0,
C_R=1.0,
C_D=1.0)
p.stop('propagate')
# fig = plt.figure(figsize=(15,15))
# ax = fig.add_subplot(111, projection='3d')
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')
data0 = scheduler.observe_passes(passes0,
space_object=objs[0],
snr_limit=False)
p.stop('total')
print(p.fmt(normalize='total'))
data1 = scheduler.observe_passes(passes1,
space_object=objs[1],
snr_limit=False)
#create a tdm file example
# pth = pathlib.Path(__file__).parent / 'data' / 'test_tdm.tdm'
# print(f'Writing TDM data to: {pth}')
# dat = data0[0][0][0]
# sorts.io.write_tdm(
# pth,
# dat['t'],
# dat['range'],
logger=logger,
profiler=p,
)
t = np.arange(0.0, end_t, 30.0)
datas = []
passes = []
states = []
for ind in range(len(objs)):
print(f'Temporal points obj {ind}: {len(t)}')
p.start('get_state')
states += [objs[ind].get_state(t)]
p.stop('get_state')
interpolator = Legendre8(states[ind], t)
p.start('find_passes')
#rename cache_data to something more descriptive
passes += [eiscat3d.find_passes(t, states[ind], cache_data=False)]
p.stop('find_passes')
p.start('observe_passes')
data = scheduler.observe_passes(passes[ind],
space_object=objs[ind],
interpolator=None,
snr_limit=False)
p.stop('observe_passes')
logger=logger,
profiler=p,
)
datas = []
passes = []
states = []
for ind in range(len(objs)):
p.start('equidistant_sampling')
t = sorts.equidistant_sampling(
orbit=objs[ind].state,
start_t=0,
end_t=end_t,
max_dpos=1e3,
)
p.stop('equidistant_sampling')
print(f'Temporal points obj {ind}: {len(t)}')
p.start('get_state')
states += [objs[ind].get_state(t)]
p.stop('get_state')
p.start('find_passes')
#rename cache_data to something more descriptive
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],
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)
mjd0 = 53005
p.start('propagate')
states = prop.propagate(t, orb.cartesian[:, 0], mjd0, A=1.0, C_R=1.0, C_D=1.0)
p.stop('propagate')
e3d = Tracker(radar=eiscat3d, t=t, ecefs=states[:3, :], profiler=p)
fig = plt.figure(figsize=(15, 15))
ax = fig.add_subplot(111, projection='3d')
ax.plot(states[0, :], states[1, :], states[2, :], "or")
for tx in e3d.radar.tx:
ax.plot([tx.ecef[0]], [tx.ecef[1]], [tx.ecef[2]], 'or')
for rx in e3d.radar.rx:
ax.plot([rx.ecef[0]], [rx.ecef[1]], [rx.ecef[2]], 'og')
for radm, ti in zip(e3d(t), range(len(t))):
radar, meta = radm
#!/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)