def get_longitude_of_periastron_stats(row):
print('Processing ', row.simarchive_filename)
sa = rebound.SimulationArchive(row.simarchive_filename,
process_warnings=False)
oa = chaincalc.OrbitArray(sa)
tlook = 1e4 * keplertime #probably 1e2-1e3 times the output cadence
lko = oa.tail_orbitarray(tlook)
mean_dlongitude_of_periastron = []
std_dlongitude_of_periastron = []
for n in range(lko['pomega'].shape[0] - 1):
longstats = [{
'mean':
chaincalc.wrap2pi(lko['pomega'][n + 1, :] - lko['pomega'][n, :] +
a).mean() - a,
'std':
chaincalc.wrap2pi(lko['pomega'][n + 1, :] - lko['pomega'][n, :] +
a).std()
} for a in [0.0, np.pi]]
if longstats[0]['std'] < longstats[1]['std']:
mean_dlongitude_of_periastron.append(longstats[0]['mean'])
std_dlongitude_of_periastron.append(longstats[0]['std'])
else:
mean_dlongitude_of_periastron.append(longstats[1]['mean'])
std_dlongitude_of_periastron.append(longstats[1]['std'])
#print(mean_dlongitude_of_periastron)
#print(std_dlongitude_of_periastron)
#if max(mean_dlongitude_of_periastron) > -np.pi/2:
# print(row.hash)
# print(mean_dlongitude_of_periastron)
return {
'delta_longitude_of_periastron': mean_dlongitude_of_periastron,
'std_delta_longitude_of_periastron': std_dlongitude_of_periastron
}
def doublecheck(row):
sa = rebound.SimulationArchive(row.simarchive_filename, process_warnings=False)
oa = chaincalc.OrbitArray(sa)
tlook = 1e4*keplertime #probably 1e2-1e3 times the output cadence
lko = oa.tail_orbitarray(tlook)
finding = oa.is_this_a_constant_ratio_chain(oa.compute_tight_angles(lko,pratiocut=0.02))
print(row.hash, finding)
return finding[0]
def targettime_hook(self, model):
#This gets called whenever a model is being run, even if not
# evolved because it was already finished, so avoid doing this twice.
findingdkey = 'is_this_a_constant_ratio_chain'
if not (findingdkey in model.status):
sa = rebound.SimulationArchive(model.status['simarchive_filename'], process_warnings=False)
oa = chaincalc.OrbitArray(sa)
tlook = 1e4*keplertime #probably 1e2-1e3 times the output cadence
lko = oa.tail_orbitarray(tlook)
finding = oa.is_this_a_constant_ratio_chain(oa.compute_tight_angles(lko))
model.status['is_this_a_constant_ratio_chain'] = finding
model.overwrite_status()
import json
import numpy as np
import rebound
import chaincalc
import matplotlib.pyplot as plt
import matplotlib
matplotlib.rcParams['axes.formatter.limits'] = (-2, 2)
status_filename = sys.argv[1]
with open(status_filename,'r') as json_file:
status = json.load(json_file)
sa = rebound.SimulationArchive(status['simarchive_filename'])
oa = chaincalc.OrbitArray(sa)
keplertime = 2.0*np.pi*1.0**1.5
print('Number of snapshots {:d}'.format(len(sa)))
print('Time limits {:e} {:e}'.format(sa.tmin, sa.tmax))
nchain = len(sa[0].particles) -1
print('nchain',nchain)
for ip in range(0,nchain):
plt.plot(oa.orbitdata['t'][ip,:]/keplertime, oa.orbitdata['a'][ip,:],'-')
plt.xlim(left=0)
plt.title('semimajor axis')