Tibeuleu/KozaiLidov
1
0
Fork 0
Code Activity

modify initialisation parameters and add gif animation saving

Browse Source
This commit is contained in:
Thibault Barnouin
2021-10-30 16:42:12 +02:00
parent 9a16400a89
commit d538dfe7a4
5 changed files with 42 additions and 18 deletions
Download Patch File Download Diff File Expand all files Collapse all files

20
lib/integrator.py
View File

@@ -5,8 +5,9 @@ Implementation of the various integrators for numerical integration.
Comes from the assumption that the problem is analytically defined in position-momentum (q-p) space for a given hamiltonian H.
"""
import numpy as np
from os import system
import time
import numpy as np
from lib.plots import DynamicUpdate
globals()["G"] = 1. #Gravitationnal constant
@@ -19,7 +20,7 @@ def dp_dt(m_array, q_array):
dp_array = np.zeros(q_array.shape)
for i in range(q_array.shape[0]):
q_j = np.delete(q_array, i, 0)
m_j = np.delete(m_array, i).reshape((q_j.shape[0],1))
m_j = np.delete(m_array, i, 0)#.reshape((q_j.shape[0],1))
dp_array[i] = -G*m_array[i]*np.sum(m_j/np.sum(np.sqrt(np.sum((q_j-q_array[i])**2, axis=0)))**3*(q_j-q_array[i]), axis=0)
dp_array[np.isnan(dp_array)] = 0.
return dp_array
@@ -30,9 +31,13 @@ def frogleap(duration, step, dyn_syst, recover_param=False, display=False):
iteration : half-step drift -> full-step kick -> half-step drift
"""
N = np.ceil(duration/step).astype(int)
m_array = dyn_syst.get_masses()
q_array = dyn_syst.get_positions()
p_array = dyn_syst.get_momenta()
masses = dyn_syst.get_masses()
m_array = np.ones(p_array.shape)
for i in range(p_array.shape[0]):
m_array[i,:] = masses[i]
E = np.zeros(N)
L = np.zeros((N,3))
@@ -60,10 +65,13 @@ def frogleap(duration, step, dyn_syst, recover_param=False, display=False):
if display:
# In center of mass frame
q_cm = np.sum(m_array.reshape((q_array.shape[0],1))*q_array, axis=0)/m_array.sum()
q_cm = np.array([0,0])#np.sum(m_array*q_array, axis=0)/masses.sum()
# display progression
d.on_running(q_array[:,0]-q_cm[0], q_array[:,1]-q_cm[1])
time.sleep(0.01)
d.on_running(q_array[:,0]-q_cm[0], q_array[:,1]-q_cm[1], step=j, label="step {0:d}/{1:d}".format(j,N))
time.sleep(1e-4)
if display:
system("convert -delay 5 -loop 0 tmp/????.png tmp/temp.gif && rm tmp/?????.png")
system("convert tmp/temp.gif -fuzz 10% -layers Optimize dynsyst.gif && rm tmp/temp.gif")
if recover_param:
return E, L