def RLmain(i):
import RLSim as rl
import numpy as np
X_0 = [1.1,1.1,1.1]
Y_0 = [0.01,0.01,.01]
Z_0 = [0, 0, 0]
N = len(X_0) # number of parallel runs
# run first round of simulation
my_sim = rl.mockSimulation()
W_0 = [[1/6, 1/6], [1/6, 1/6], [1/6, 1/6]] # initial geuss of weights for + - in x and y directions
Ws = [] # series of weights
# first round
trj1 = my_sim.run_noPlt([X_0, Y_0, Z_0], nstepmax = 10)
trj1 = my_sim.PreAll(trj1)
trjs = trj1
trj1_Sp = my_sim.PreSamp(trj1, starting_n = N, myn_clusters = 20) # pre analysis
trj1_Sp_theta = my_sim.map(trj1_Sp)
newPoints = my_sim.findStarting(trj1_Sp_theta, trj1_Sp, W_0, starting_n = N , method = 'RL')
trjs_theta = trj1_Sp_theta
trjs_Sp_theta = trj1_Sp_theta
for round in range(700):
# updates the std and mean
#my_sim.updateStat(trjs_Sp_theta) # based on min count trajectories
my_sim.updateStat(trjs_theta) # based on all trajectories
#W_1 = my_sim.updateW(trj1_Sp_theta, W_0) # rewigth weigths using last round
W_1 = my_sim.updateW(trjs_Sp_theta, W_0) # important
W_0 = W_1
Ws.append(W_0)
#print('Weight', W_0)
trj1 = my_sim.run_noPlt(newPoints, nstepmax = 5)
trj1 = my_sim.PreAll(trj1) # 2 x all points of this round
#trjs = np.array([np.array(np.concatenate((trj1[0],trjs[0]))), np.array(np.concatenate((trj1[1],trjs[1])))]) # 2 x all points
com_trjs = []
for theta in range(len(trj1)):
com_trjs.append(np.concatenate((trjs[theta], trj1[theta])))
trjs = np.array(com_trjs)
trjs_theta = np.array(my_sim.map(trjs))
trjs_Sp = my_sim.PreSamp(trjs, starting_n = N)
trjs_Sp_theta = np.array(my_sim.map(trjs_Sp))
newPoints = my_sim.findStarting(trjs_Sp_theta, trjs_Sp, W_1, starting_n = N , method = 'RL')
#print(Ws)
np.save('w'+str(i), Ws)
np.save('trjs_theta'+str(i), trjs_theta)
import RLSim as rl
import numpy as np
#X_0 = [1.1,1.1,1.1,1.1,1.1,1.1,1.1,1.1,1.1,1.1,1.1,1.1,1.1,1.1,1.1,1.1,1.1,1.1,1.1,1.1,1.1,1.1,1.1,1.1]
#Y_0 = [0.01,0.01,.01,0.01,0.01,.01,0.01,0.01,.01,0.01,0.01,.01,0.01,0.01,.01,0.01,0.01,.01,0.01,0.01,.01,0.01,0.01,.01]
X_0 = [1.1, 1.1, 1.1]
Y_0 = [0.01, 0.01, .01]
N = len(X_0) # number of parallel runs
# run first round of simulation
my_sim = rl.mockSimulation()
W_0 = [[1 / 4, 1 / 4],
[1 / 4,
1 / 4]] # initial geuss of weights for + - in x and y directions
Ws = [] # series of weights
# first round
trj1 = my_sim.run_noPlt([X_0, Y_0], nstepmax=10)
trj1 = my_sim.PreAll(trj1)
trjs = trj1
trj1_Sp = my_sim.PreSamp(trj1, starting_n=N, myn_clusters=20) # pre analysis
trj1_Sp_theta = my_sim.map(trj1_Sp)
newPoints = my_sim.findStarting(trj1_Sp_theta,
trj1_Sp,
W_0,
starting_n=N,
method='RL')
trjs_theta = trj1_Sp_theta
import numpy as np
import RLSim as rl
stepS = 0.001 * 120 # microSecond WW
times = np.loadtxt('times.txt')
times2 = stepS * times
rl.pltTimes_folding(times2)
def rlmain(i):
from scipy import io as sio
import RLSim as rl
import numpy as np
# inital state
S_0 = [0] # inactive
N = len(S_0) # number of parallel runs
nstepmax = 40
print('Simulation length: ', nstepmax * 0.005)
W_0 = [[0.25, 0.25],
[0.25,
0.25]] # initial geuss of weights for + - in x and y directions
Ws = [] # series of weights
newPoints_all = []
Ws.append(W_0)
print('Weight', W_0)
# run simulation
my_sim = rl.mockSimulation()
my_sim.tp = sio.mmread('../tProb.mtx')
my_sim.x = np.load('../Gens_aloopRMSD.npy')
my_sim.y = np.load('../Gens_y_KE.npy')
my_sim.mapping = np.load('../map_Macro2micro.npy')
#### first round
trj1 = my_sim.run(S_0, nstepmax=nstepmax) # 1 x 1 x n_frames
trj1 = my_sim.PreAll(trj1) # 1 x 1 x n_frames
trjs = trj1[0] # 1 x n_frames
trj1_Sp = my_sim.PreSamp_MC(trjs, N=10) # pre analysis # 1 x n_samples
trj1_Sp_theta = np.array(my_sim.map(trj1_Sp)) # [trjx, trjy]
newPoints = my_sim.findStarting(trj1_Sp_theta,
trj1_Sp,
W_0,
starting_n=N,
method='RL') # needs 2 x something
trjs_theta = trj1_Sp_theta
trjs_Sp_theta = trj1_Sp_theta
bad = False
for round in range(100):
my_sim.updateStat(trjs_theta) # based on all trajectories
W_1 = my_sim.updateW(trjs_Sp_theta, W_0) # important
W_0 = W_1
Ws.append(W_0)
print('Weight', W_0)
if np.any(np.isnan(W_0)):
bad = True
print(bad)
break
oldTrjs = trjs
trj1 = my_sim.run(newPoints, nstepmax=5)
trj1 = my_sim.PreAll(trj1)[0] # 2 x all points of this round
com_trjs = np.concatenate((trjs, trj1))
trjs = np.array(com_trjs)
trjs_theta = np.array(my_sim.map(trjs))
trjs_Sp = my_sim.PreSamp_MC(trjs, N=10)
trjs_Sp_theta = np.array(my_sim.map(trjs_Sp))
newPoints = my_sim.findStarting(trjs_Sp_theta,
trjs_Sp,
W_1,
starting_n=N,
method='RL')
newPoints_all.append(newPoints)
#my_sim.pltPoints(trjs_theta, trjs_Sp_theta, newPoints, round, weights=Ws)
my_sim.pltPoints(trjs_theta[0], trjs_theta[1])
print(newPoints_all)
if not bad:
np.save('w' + str(i), Ws)
np.save('trjs_theta' + str(i), trjs_theta)
import RLSim as rl z = rl.mockSimulation() z.runSimulation(R=1000, N=1,s=1000, method='RL')
import numpy as np
import RLSim as rl
stepS = 0.001*0.001*50 # milli Second B2AR
times = np.loadtxt('times.txt')
times2 = stepS * times
rl.pltTimes(times2)