def test_pool(self):
pool = InterruptiblePool(2)
params = [1., 1.1]
res = pool.map(runsim, params)
self.assertAlmostEqual(res, [0.9950041652780258, 1.095870355119381],
delta=1e-15)
def test_nopool(self):
pool = InterruptiblePool(2)
params = [1., 1.1]
res = [runsim(params[0]), runsim(params[1])]
self.assertAlmostEqual(res[0], 0.9950041652780258, delta=1e-15)
self.assertAlmostEqual(res[1], 1.095870355119381, delta=1e-15)
pool.close()
return 10. # At least one particle got ejected, returning large MEGNO.
import rebound
import numpy as np
print simulation((7, 0.1))
Ngrid = 500
par_a = np.linspace(7., 10., Ngrid)
par_e = np.linspace(0., 0.5, Ngrid)
parameters = []
for e in par_e:
for a in par_a:
parameters.append((a, e))
from rebound.interruptible_pool import InterruptiblePool
pool = InterruptiblePool()
results = pool.map(simulation, parameters)
results2d = np.array(results).reshape(Ngrid, Ngrid)
#%matplotlib inline
import matplotlib.pyplot as plt
fig = plt.figure(figsize=(7, 5))
ax = plt.subplot(111)
extent = [min(par_a), max(par_a), min(par_e), max(par_e)]
ax.set_xlim(extent[0], extent[1])
ax.set_xlabel("semi-major axis $a$")
ax.set_ylim(extent[2], extent[3])
ax.set_ylabel("inclination $i$")
im = ax.imshow(results2d,
interpolation="none",
vmin=1.9,
colors = {
'whfast-nocor': "#00AA00",
'whfast': "#FF0000",
'mercury': "#6E6E6E",
'swifter-whm': "#444444",
'swifter-helio': "#AABBBB",
'swifter-tu4': "#FFAAAA",
'ias15': "g",
'janus': "#0000FF",
}
trials = 4
parameters = [(inte, i * trials + j, j) for i, inte in enumerate(integrators)
for j in xrange(trials)]
if len(sys.argv) != 2:
pool = InterruptiblePool()
print("Running %d simulations" % (len(parameters)))
res = np.array(pool.map(simulation,
parameters)).reshape(len(integrators), trials, 4,
Ngrid)
np.save("res.npy", res)
else:
print("Loading %d simulations" % (len(parameters)))
print(sys.argv[1])
res = np.load(sys.argv[1])
f, axarr = plt.subplots(1, 1, figsize=(13, 4))
#extent=[res[:,:,0,:].min()/orbit, res[:,:,0,:].max()/orbit, 1e-16, 1e-9]
extent = [
res[:, :, 0, :].min() / orbit, res[:, :, 0, :].max() / orbit, 1e-24, 1e-7
]
'whfast-nocor': "#FF0000",
'whfast': "#00AA00",
'mercury': "#6E6E6E",
'wh': "b",
'swifter-whm': "#444444",
'swifter-helio':"#AABBBB",
'swifter-tu4': "#FFAAAA",
'ias15': "g",
}
trials = 4
parameters = [(inte,i*trials+j,j) for i,inte in enumerate(integrators) for j in xrange(trials)]
if len(sys.argv)!=2:
pool = InterruptiblePool()
print "Running %d simulations" % (len(parameters))
res = np.array(pool.map(simulation,parameters)).reshape(len(integrators),trials,2,Ngrid)
np.save("res.npy",res)
else:
print "Loading %d simulations" % (len(parameters))
print sys.argv[1]
res = np.load(sys.argv[1])
import matplotlib; matplotlib.use("pdf")
import matplotlib.pyplot as plt
from matplotlib import ticker
from matplotlib.colors import LogNorm
f,axarr = plt.subplots(1,1,figsize=(13,4))
tmax = orbit*1e3
integrators = ["wh","swifter-whm","swifter-tu4","swifter-helio","mercury","whfast-nocor","whfast"]
colors = {
'whfast-nocor': "#FF0000",
'whfast': "#00AA00",
'mercury': "#6E6E6E",
'wh': "b",
'swifter-whm': "#444444",
'swifter-helio':"#AABBBB",
'swifter-tu4': "#FFAAAA",
'ias15': "g",
}
parameters = [(inte,dt,i*len(dts)+j) for i,inte in enumerate(integrators) for j, dt in enumerate(dts)]
if len(sys.argv)!=2:
pool = InterruptiblePool(8)
print "Running %d simulations" % (len(parameters))
res = np.array(pool.map(simulation,parameters)).reshape(len(integrators),len(dts),2)
np.save("res.npy",res)
else:
print "Loading %d simulations" % (len(parameters))
print sys.argv[1]
res = np.load(sys.argv[1])
print res.shape
import matplotlib; matplotlib.use("pdf")
import matplotlib.pyplot as plt
from matplotlib import ticker
from matplotlib.colors import LogNorm
from matplotlib.font_manager import FontProperties
colors = {
'whfast-nocor': "#FF0000",
'whfast': "#00AA00",
'mercury': "#6E6E6E",
'wh': "b",
'swifter-whm': "#444444",
'swifter-helio': "#AABBBB",
'swifter-tu4': "#FFAAAA",
'ias15': "g",
}
parameters = [(inte, dt, i * len(dts) + j)
for i, inte in enumerate(integrators)
for j, dt in enumerate(dts)]
if len(sys.argv) != 2:
pool = InterruptiblePool(8)
print "Running %d simulations" % (len(parameters))
res = np.array(pool.map(simulation,
parameters)).reshape(len(integrators), len(dts), 2)
np.save("res.npy", res)
else:
print "Loading %d simulations" % (len(parameters))
print sys.argv[1]
res = np.load(sys.argv[1])
print res.shape
import matplotlib
matplotlib.use("pdf")
import matplotlib.pyplot as plt
from matplotlib import ticker
interpolation='nearest',
cmap="RdYlGn",
extent=extent)
if first:
cb1 = plt.colorbar(im1, ax=axarr[0])
cb1.solids.set_rasterized(True)
cb1.set_label("MEGNO $\\langle Y \\rangle$")
cb2 = plt.colorbar(im2, ax=axarr[1])
cb2.solids.set_rasterized(True)
cb2.set_label("Lyapunov timescale [years]")
plt.draw()
pool = InterruptiblePool(
) # Number of threads default to the number of CPUs on the system
def runSim(p):
print("Running %d simulations." % len(p))
res = np.nan_to_num(np.array(pool.map(simulation, p)))
for i, r in enumerate(res):
resd[p[i]] = r
# Setup grid and run many simulations in parallel
a = np.array([7., 10.]) # range of saturn semi-major axis in AU
e = np.array([0., 0.5]) # range of saturn eccentricity
# Setup plots
f, axarr = plt.subplots(2, figsize=(10, 8))
except rebound.Escape:
return 10. # At least one particle got ejected, returning large MEGNO.
import rebound
import numpy as np
print simulation((7,0.1))
Ngrid = 500
par_a = np.linspace(7.,10.,Ngrid)
par_e = np.linspace(0.,0.5,Ngrid)
parameters = []
for e in par_e:
for a in par_a:
parameters.append((a,e))
from rebound.interruptible_pool import InterruptiblePool
pool = InterruptiblePool()
results = pool.map(simulation,parameters)
results2d = np.array(results).reshape(Ngrid,Ngrid)
#%matplotlib inline
import matplotlib.pyplot as plt
fig = plt.figure(figsize=(7,5))
ax = plt.subplot(111)
extent = [min(par_a),max(par_a),min(par_e),max(par_e)]
ax.set_xlim(extent[0],extent[1])
ax.set_xlabel("semi-major axis $a$")
ax.set_ylim(extent[2],extent[3])
ax.set_ylabel("inclination $i$")
im = ax.imshow(results2d, interpolation="none", vmin=1.9, vmax=4, cmap="jet", origin="lower", aspect='auto', extent=extent)
cb = plt.colorbar(im, ax=ax)
def test_pool(self):
pool = InterruptiblePool(2)
params = [1.,1.1]
res = pool.map(runsim,params)
self.assertAlmostEqual(res,[0.9950041652780258,1.095870355119381],delta=1e-15)
return pgraph
def varpi_graph(vp1, vp2, times):
plt.figure()
plt.scatter(times, vp1, color='purple', s=10)
plt.scatter(times, vp2, color='blue', s=10)
plt.xlabel('Time (years)', fontsize=12)
plt.ylabel('Pericentre Distance (m)', fontsize=12)
scatter(times, vp1, color='purple', label='smaller planet varpi')
scatter(times, vp2, color='blue', label='larger planet varpi')
vpgraph = plt.savefig('sin,pericentre_distance_taupo=e={0}.pdf'.format(
taues[1]))
return vpgraph
args = np.logspace(4, 8, 20)
pool = InterruptiblePool(10)
pool.map(calc, args)
filenames = []
f = open('onlytaue,filenames.txt', 'w')
for count in range(len(args)):
filenames.append('onlytaue={0}.txt'.format(args[count]))
print(filenames[count])
f.write(str(filenames[count]))
f.write('\t')
f.write(str(args[count]))
f.write('\n')
f.close()
return [rebound.get_megno(),1./(rebound.get_lyapunov()*2.*np.pi)] # returns MEGNO and Lypunov timescale in years
### Setup grid and run many simulations in parallel
N = 100 # Grid size, increase this number to see more detail
a = np.linspace(7.,10.,N) # range of saturn semi-major axis in AU
e = np.linspace(0.,0.5,N) # range of saturn eccentricity
parameters = []
for _e in e:
for _a in a:
parameters.append([_a,_e])
# Run simulations in parallel
pool = InterruptiblePool() # Number of threads default to the number of CPUs on the system
print("Running %d simulations on %d threads..." % (len(parameters), pool._processes))
res = np.nan_to_num(np.array(pool.map(simulation,parameters)))
megno = np.clip(res[:,0].reshape((N,N)),1.8,4.) # clip arrays to plot saturated
lyaptimescale = np.clip(np.absolute(res[:,1].reshape((N,N))),1e1,1e5)
### Create plot and save as pdf
import matplotlib; matplotlib.use("pdf")
import matplotlib.pyplot as plt
from matplotlib.colors import LogNorm
# Setup plots
f, axarr = plt.subplots(2,figsize=(10,10))
extent = [a.min(), a.max(), e.min(), e.max()]
for ax in axarr:
ax.set_xlim(extent[0],extent[1])
scatter(times[840:1000], phi6[840:1000], color = 'purple', label = '7:6')
pgraph = plt.savefig('sin,resonance_angles_taupo=e={0}.pdf'.format(taues[1]))
return pgraph
def varpi_graph(vp1, vp2, times):
plt.figure()
plt.scatter(times, vp1, color = 'purple', s=10)
plt.scatter(times, vp2, color = 'blue', s=10)
plt.xlabel('Time (years)', fontsize = 12)
plt.ylabel('Pericentre Distance (m)', fontsize = 12)
scatter(times,vp1, color = 'purple', label = 'smaller planet varpi')
scatter(times, vp2, color = 'blue', label = 'larger planet varpi')
vpgraph = plt.savefig('sin,pericentre_distance_taupo=e={0}.pdf'.format(taues[1]))
return vpgraph
args = np.logspace(4,8,20)
pool = InterruptiblePool(10)
pool.map(calc,args)
filenames=[]
f=open('onlytaue,filenames.txt','w')
for count in range(len(args)):
filenames.append('onlytaue={0}.txt'.format(args[count]))
print(filenames[count])
f.write(str(filenames[count]))
f.write('\t')
f.write(str(args[count]))
f.write('\n')
f.close()
