def box_actions(results, times, N_matrix, ifprint):
"""
Finds actions, angles and frequencies for box orbit.
Takes a series of phase-space points from an orbit integration at times t and returns
L = (act,ang,n_vec,toy_aa, pars) -- explained in find_actions() below.
"""
if ifprint:
print ("\n=====\nUsing triaxial harmonic toy potential")
t = time.time()
# Find best toy parameters
omega = toy.findbestparams_ho(results)
if ifprint:
print ("Best omega " + str(omega) + " found in " + str(time.time() - t) + " seconds")
# Now find toy actions and angles
AA = np.array([toy.angact_ho(i, omega) for i in results])
AA = AA[~np.isnan(AA).any(1)]
if len(AA) == 0:
return
t = time.time()
act = solver.solver(AA, N_matrix)
if act == None:
return
if ifprint:
print (
"Action solution found for N_max = "
+ str(N_matrix)
+ ", size "
+ str(len(act[0]))
+ " symmetric matrix in "
+ str(time.time() - t)
+ " seconds"
)
np.savetxt("GF.Sn_box", np.vstack((act[1].T, act[0][3:])).T)
ang = solver.angle_solver(AA, times, N_matrix, np.ones(3))
if ifprint:
print (
"Angle solution found for N_max = "
+ str(N_matrix)
+ ", size "
+ str(len(ang))
+ " symmetric matrix in "
+ str(time.time() - t)
+ " seconds"
)
# Just some checks
if len(ang) > len(AA):
print ("More unknowns than equations")
return act[0], ang, act[1], AA, omega
def loop_actions(results, times, N_matrix, ifprint):
"""
Finds actions, angles and frequencies for loop orbit.
Takes a series of phase-space points from an orbit integration at times t and returns
L = (act,ang,n_vec,toy_aa, pars) -- explained in find_actions() below.
results must be oriented such that circulation is about the z-axis
"""
if (ifprint):
print("\n=====\nUsing isochrone toy potential")
t = time.time()
# First find the best set of toy parameters
params = toy.findbestparams_iso(results)
if (params[0] != params[0]):
params = np.array([10., 10.])
if (ifprint):
print("Best params " + str(params) + " found in " +
str(time.time() - t) + " seconds")
# Now find the toy angles and actions in this potential
AA = np.array([toy.angact_iso(i, params) for i in results])
AA = AA[~np.isnan(AA).any(1)]
if (len(AA) == 0):
return
t = time.time()
act = solver.solver(AA, N_matrix, symNx=1)
if act == None:
return
if (ifprint):
print("Action solution found for N_max = " + str(N_matrix) +
", size " + str(len(act[0])) + " symmetric matrix in " +
str(time.time() - t) + " seconds")
# Store Sn
np.savetxt("GF.Sn_loop", np.vstack((act[1].T, act[0][3:])).T)
# Find angles
sign = np.array([
1.,
np.sign(results[0][0] * results[0][4] - results[0][1] * results[0][3]),
1.
])
ang = solver.angle_solver(AA, times, N_matrix, sign, symNx=1)
if (ifprint):
print("Angle solution found for N_max = " + str(N_matrix) + ", size " +
str(len(ang)) + " symmetric matrix in " + str(time.time() - t) +
" seconds")
# Just some checks
if (len(ang) > len(AA)):
print("More unknowns than equations")
return act[0], ang, act[1], AA, params
def loop_actions(results, times, N_matrix, ifprint):
"""
Finds actions, angles and frequencies for loop orbit.
Takes a series of phase-space points from an orbit integration at times t and returns
L = (act,ang,n_vec,toy_aa, pars) -- explained in find_actions() below.
results must be oriented such that circulation is about the z-axis
"""
if(ifprint):
print("\n=====\nUsing isochrone toy potential")
t = time.time()
# First find the best set of toy parameters
params = toy.findbestparams_iso(results)
if(params[0]!=params[0]):
params = np.array([10.,10.])
if(ifprint):
print("Best params "+str(params)+" found in "+str(time.time()-t)+" seconds")
# Now find the toy angles and actions in this potential
AA = np.array([toy.angact_iso(i,params) for i in results])
AA = AA[~np.isnan(AA).any(1)]
if(len(AA)==0):
return
t = time.time()
act = solver.solver(AA, N_matrix,symNx = 1)
if act==None:
return
if(ifprint):
print("Action solution found for N_max = "+str(N_matrix)+", size "+str(len(act[0]))+" symmetric matrix in "+str(time.time()-t)+" seconds")
# Store Sn
np.savetxt("GF.Sn_loop",np.vstack((act[1].T,act[0][3:])).T)
# Find angles
sign = np.array([1.,np.sign(results[0][0]*results[0][4]-results[0][1]*results[0][3]),1.])
ang = solver.angle_solver(AA,times,N_matrix,sign,symNx = 1)
if(ifprint):
print("Angle solution found for N_max = "+str(N_matrix)+", size "+str(len(ang))+" symmetric matrix in "+str(time.time()-t)+" seconds")
# Just some checks
if(len(ang)>len(AA)):
print("More unknowns than equations")
return act[0], ang, act[1], AA, params
def box_actions(results, times, N_matrix, ifprint):
"""
Finds actions, angles and frequencies for box orbit.
Takes a series of phase-space points from an orbit integration at times t and returns
L = (act,ang,n_vec,toy_aa, pars) -- explained in find_actions() below.
"""
if (ifprint):
print("\n=====\nUsing triaxial harmonic toy potential")
t = time.time()
# Find best toy parameters
omega = toy.findbestparams_ho(results)
if (ifprint):
print("Best omega " + str(omega) + " found in " +
str(time.time() - t) + " seconds")
# Now find toy actions and angles
AA = np.array([toy.angact_ho(i, omega) for i in results])
AA = AA[~np.isnan(AA).any(1)]
if (len(AA) == 0):
return
t = time.time()
act = solver.solver(AA, N_matrix)
if act == None:
return
if (ifprint):
print("Action solution found for N_max = " + str(N_matrix) +
", size " + str(len(act[0])) + " symmetric matrix in " +
str(time.time() - t) + " seconds")
np.savetxt("GF.Sn_box", np.vstack((act[1].T, act[0][3:])).T)
ang = solver.angle_solver(AA, times, N_matrix, np.ones(3))
if (ifprint):
print("Angle solution found for N_max = " + str(N_matrix) + ", size " +
str(len(ang)) + " symmetric matrix in " + str(time.time() - t) +
" seconds")
# Just some checks
if (len(ang) > len(AA)):
print("More unknowns than equations")
return act[0], ang, act[1], AA, omega
def test_compare_action_prepare():
from ..actionangle import _action_prepare, _angle_prepare
import solver
logger.setLevel(logging.ERROR)
AA = np.random.uniform(0., 100., size=(1000,6))
t = np.linspace(0., 100., 1000)
act_san,n_vectors = solver.solver(AA, N_max=6, symNx=2)
A2,b2,n = _action_prepare(AA, N_max=6, dx=2, dy=2, dz=2)
act_apw = np.array(solve(A2,b2))
ang_san = solver.angle_solver(AA, t, N_max=6, symNx=2, sign=1)
A2,b2,n = _angle_prepare(AA, t, N_max=6, dx=2, dy=2, dz=2)
ang_apw = np.array(solve(A2,b2))
assert np.allclose(act_apw, act_san)
assert np.allclose(ang_apw, ang_san)
