def saveSimStates(d,f):
# add DIP states
dips = np.zeros((len(d),len(d[0])/3))
for i in range(0,int(len(d[0])/3)):
dips[:,i] = (d[:,i*3+1]*(2./3.))
cnt = 0
for i in range(2,int(len(d[0])+3),4):
d = np.insert(d,i,dips[:,cnt],1)
cnt += 1
datAc.saveStates(f,d)
## combining everything again...
s1_fit = np.append(s1_fit,np.append(s2_fit,np.append(s3_fit,s4_fit,1),1),1)
''' estimating measurements '''
print "estimating ", sstring
''' 11 '''
print "11"
# fi.write(sstring+',')
startT = time.time()
estAngd_A = modDA.estimateSeries(s1_fit[:,:3], fingList, [sensList[0]], jointList, bnds=True, met=1)
d_A = time.time()-startT
d_A /= len(s1_fit)
# print "time d_A11: ", d_A
# fi.write(str(d_A)+',')
datAc.saveStates("../datasets/evalSets/estResults/160217_real/"+sstring+"_dipA11.txt", estAngd_A)
(mean_A, var_A) = sf.getMeanVar(lInd_re,estAngd_A)
# fi.write(str(mean_A)+','+str(var_A)+',')
print "cyl mean_A %s var_A %s" % (mean_A, var_A)
# neglecting ad-ab
# (mean, var) = sf.getMeanVar(lInd_re[:,:3], estAngd_A[:,:3])
# fi.write(str(mean)+','+str(var)+',')
# print "cyl mean %s var %s" % (mean, var)
startT = time.time()
estAngc_A = modCA.estimateSeries(s1_fit[:,:3], fingList, [sensList[0]], jointList, bnds=True, met=1)
c_A = time.time()-startT
c_A /= len(s1_fit)
# print "time c_A11: ", c_A
# fi.write(str(c_A)+',')
#d_A = time.time()-startT
#print "time d_A11: ", d_A
#datAc.saveStates("../datasets/niceOnes/"+dayString+'_'+sstring+"dipA11.txt", estAngd_A)
#
#startT = time.time()
#estAngc_A = modCA.estimateSeries(s1_fit[:,:3], fingList, [sensList[0]], jointList, bnds=True, met=1)
#c_A = time.time()-startT
#datAc.saveStates("../datasets/niceOnes/"+dayString+'_'+sstring+"cylA11.txt", estAngc_A)
#print "time c_A11: ", c_A
#''' 12 '''
startT = time.time()
estAngd_A = modDA.estimateSeries(s1_fit[:,:6], fingList, sensList[:2], jointList, bnds=True, met=1)
d_A = time.time()-startT
print "time d_A12: ", d_A
datAc.saveStates("../datasets/MPU/"+dayString+'_'+sstring+"dipA12.txt", estAngd_A)
startT = time.time()
estAngc_A = modCA.estimateSeries(s1_fit[:,:6], fingList, sensList[:2], jointList, bnds=True, met=1)
c_A = time.time()-startT
datAc.saveStates("../datasets/MPU/"+dayString+'_'+sstring+"cylA12.txt", estAngc_A)
print "time c_A12: ", c_A
''' 14 '''
startT = time.time()
estAngd_A = modDA.estimateSeries(s1_fit, fingList, sensList, jointList, bnds=True, met=1)
d_A = time.time()-startT
print "time d_A14: ", d_A
datAc.saveStates("../datasets/MPU/"+dayString+'_'+sstring+"dipA44.txt", estAngd_A)
startT = time.time()
# d_A = time.time()-startT
# print "time d_A12: ", d_A
# datAc.saveStates("../datasets/niceOnes/"+dayString+'_'+sstring+"dipA12.txt", estAngd_A)
#
# startT = time.time()
# estAngc_A = modCA.estimateSeries(s1_fit[:,:6], fingList, sensList[:2], jointList, bnds=True, met=1)
# c_A = time.time()-startT
# datAc.saveStates("../datasets/niceOnes/"+dayString+'_'+sstring+"cylA12.txt", estAngc_A)
# print "time c_A12: ", c_A
#
""" 14 """
startT = time.time()
estAngd_A = modDA.estimateSeries(s1_fit, fingList, sensList, jointList, bnds=True, met=1)
d_A = time.time() - startT
print "time d_A14: ", d_A
datAc.saveStates("../datasets/44/" + dayString + "_" + sstring + "dipA44.txt", estAngd_A)
startT = time.time()
estAngc_A = modCA.estimateSeries(s1_fit, fingList, sensList, jointList, bnds=True, met=1)
c_A = time.time() - startT
datAc.saveStates("../datasets/44/" + dayString + "_" + sstring + "cylA44.txt", estAngc_A)
print "time c_A14: ", c_A
plo.plotLeapVsMag((tim, estAngd_A), (tim, s1, s1_fit[:, :3]), head="estAngd_A vs B-field " + sstring)
(timLeap, angInd, angMid, angRin, angPin) = datAc.readLeap("../datasets/160210/" + dayString + "_" + sstring + "_leap")
# plo.plotLeapVsMag((timLeap,angInd),(tim,estAngd_A),head="leap state vs estAngd_A "+sstring,dif=False)
# plo.plotLeapVsMag((tim,estAngd_A),(tim,estAngc_A),head="dip vs cyl ad-ab "+sstring,dif=False)
methString = "METHOD:" + str(i)
print methString
f.write(methString + '\n')
''' dip without ad-ab '''
startT = time.time()
estAng_dip = modD.estimateSeries(b_cyl_A, fingList, sensList, jointList, bnds=True, met=i)
endT = time.time()-startT
resString = "model: dipole, without adduction-abduction\n"
resString += "total time[sec] needed: " + str(endT) + "\n"
resString += "avg time per step[sec]: " + str(endT/len(simValues_A)) + "\n\n"
# resString += "max fun value: " + str(max(fun_dip)) + "\n\n"
print resString
f.write(resString)
datAc.saveStates(folderStr+"estAng_dip"+str(i), estAng_dip)
plo.plotter2d((estAng_dip[:,:3], estAng_dip[:,3:6]),
("model: dip without Adduction index","middle"+methString))
# plo.plotter2d((estAng_dip[:,:3], estAng_dip[:,3:6], estAng_dip[:,6:9], estAng_dip[:,9:]),
# ("model: dip without Adduction index","middle"+methString,"ring","pinky"))
plt.savefig(folderStr+str(i)+"dip_nA.png")
''' cyl without ad-ab '''
startT = time.time()
estAng_cyl = modC.estimateSeries(b_cyl_A, fingList, sensList, jointList, bnds=True, met=i)
endT = time.time()-startT
resString = "model: cylindrical, without adduction-abduction\n"
resString += "total time[sec] needed: " + str(endT) + "\n"
resString += "avg time per step[sec]: " + str(endT/len(simValues_A)) + "\n\n"
