def e(self): '''Calculate eccentricity of an object's orbit''' val = 1.+2.*self.eps()*Merc.mag(self.h())**2./self.gm()**2. if ((val < 0) & (-val < tol)): val = 0 e = sqrt(val) return(np.array(e))
def i(self): '''Calculate inclination of an object's orbit. Takes mks, returns degrees''' i = arccos(self.h()[2]/Merc.mag(self.h()))*180./pi return(np.array(i))
def v(self): return(Merc.mag(self.vel))
def dr(self,other): '''Distance between two objects.''' x1 = self.pos x2 = other.pos dr = Merc.mag(x1-x2) return(dr)
def r(self): return(Merc.mag( self.pos))
# calculate minimum pericenter, last time it happens, and final i
for ind, l in enumerate([0, 1, 2]):
# get basic stats of this sim
dr = d
vrs = vers[l]
tf = t[l][-1]
aBf = aB[l][-1]
eBf = eB[l][-1]
pBf = aBf * (1 - eBf)
apBf = aBf * (1 + eBf)
aCf = aC[l][-1]
eCf = eC[l][-1]
pCf = aCf * (1 - eCf)
apCf = aCf * (1 + eCf)
minpB = min(pB[l])
mintB = t[l][Merc.which(pB[l], minpB)]
if not all(np.isnan(pC[l])):
minpC = min(pC[l])
mintC = t[l][Merc.which(pC[l], minpC)]
elif l == 1:
minpC, mintC = np.nan, np.array([np.nan])
else:
print('Warning: pC = nan, but vers not B-2!')
iMf = iM[l][-1]
rtrf = rtr[l][-1]
rpf = rtrf / pBf
rpm = rtrf / minpB
# add to summary
# line = np.array([[dr,vrs,tf, aBf,eBf,pBf,apBf,
# aCf,eCf,pCf,apCf,
# minpB,max(mintB),minpC,max(mintC),iMf,rtrf]])
thisdir = pd.read_csv('TimeData/TimeData-' + simID + '.txt',
delim_whitespace=True)
# Calculate non-time-dependent stats for this sim, and add to summary
dr = d
vrs = s
tf = thisdir.t.iloc[-1]
aBf = thisdir.aB.iloc[-1]
eBf = thisdir.eB.iloc[-1]
pBf = aBf * (1 - eBf)
apBf = aBf * (1 + eBf)
aCf = thisdir.aC.iloc[-1]
eCf = thisdir.eC.iloc[-1]
pCf = aCf * (1 - eCf)
apCf = aCf * (1 + eCf)
minpB = min(thisdir.pB)
mintB = max(thisdir.t.iloc[Merc.which(thisdir.pB, minpB)])
if not all(np.isnan(thisdir.pC)):
minpC = min(thisdir.pC)
mintC = max(thisdir.t.iloc[Merc.which(thisdir.pC, minpC)])
elif '2' in s:
minpC, mintC = np.nan, np.nan
else:
print(
'Warning: pC = nan, but subdir is {}, not a disk binary!'.
format(s))
iMf = thisdir.iC.iloc[-1] - thisdir.iB.iloc[-1]
rtrf = thisdir.rtr.iloc[-1]
rpf = rtrf / pBf
rpm = rtrf / minpB
# make a dictionary of these stats, to enter as one line in the dataframe
# calculate minimum pericenter, last time it happens, and final i
for ind,l in enumerate([0,1,2]):
# get basic stats of this sim
dr = d
vrs = vers[l]
tf = t[l][-1]
aBf = aB[l][-1]
eBf = eB[l][-1]
pBf = aBf*(1-eBf)
apBf = aBf*(1+eBf)
aCf = aC[l][-1]
eCf = eC[l][-1]
pCf = aCf*(1-eCf)
apCf = aCf*(1+eCf)
minpB = min(pB[l])
mintB = t[l][Merc.which(pB[l],minpB)]
if not all(np.isnan(pC[l])):
minpC = min(pC[l])
mintC = t[l][Merc.which(pC[l],minpC)]
elif l==1:
minpC, mintC = np.nan, np.array([np.nan])
else:
print('Warning: pC = nan, but vers not B-2!')
iMf = iM[l][-1]
rtrf = rtr[l][-1]
rpf = rtrf/pBf
rpm = rtrf/minpB
# add to summary
# line = np.array([[dr,vrs,tf, aBf,eBf,pBf,apBf,
# aCf,eCf,pCf,apCf,
# minpB,max(mintB),minpC,max(mintC),iMf,rtrf]])
simID = d+'-'+s
thisdir = pd.read_csv('TimeData/TimeData-'+simID+'.txt',delim_whitespace=True)
# Calculate non-time-dependent stats for this sim, and add to summary
dr = d
vrs = s
tf = thisdir.t.iloc[-1]
aBf = thisdir.aB.iloc[-1]
eBf = thisdir.eB.iloc[-1]
pBf = aBf*(1-eBf)
apBf = aBf*(1+eBf)
aCf = thisdir.aC.iloc[-1]
eCf = thisdir.eC.iloc[-1]
pCf = aCf*(1-eCf)
apCf = aCf*(1+eCf)
minpB = min(thisdir.pB)
mintB = max(thisdir.t.iloc[Merc.which(thisdir.pB,minpB)])
if not all(np.isnan(thisdir.pC)):
minpC = min(thisdir.pC)
mintC = max(thisdir.t.iloc[Merc.which(thisdir.pC,minpC)])
elif '2' in s:
minpC, mintC = np.nan, np.nan
else:
print('Warning: pC = nan, but subdir is {}, not a disk binary!'.format(s))
iMf = thisdir.iC.iloc[-1]-thisdir.iB.iloc[-1]
rtrf = thisdir.rtr.iloc[-1]
rpf = rtrf/pBf
rpm = rtrf/minpB
# make a dictionary of these stats, to enter as one line in the dataframe
line = {}
for c in cols:
