def nextFrame(arg):
""" Function called for each successive animation frame; arg is the frame number """
global ADs, ADList, AVG_DIST, SpecDisp, SpecMaint, SpecGrowth, fixed, p, BurnIn, t, num_sims, width, height, Rates, u0, rho, ux, uy, n0, nN, nS, nE, nW, nNE, nNW, nSE, nSW, SpColorDict, GrowthDict, N_RD, P_RD, C_RD, DispDict, MaintDict, one9th, four9ths, one36th, barrier, gmax, dmax, maintmax, IndIDs, Qs, IndID, IndTimeIn, IndExitAge, IndX, IndY, Ind_scatImage, SpeciesIDs, EnvD, TY, tracer_scatImage, TTimeIn, TIDs, TExitAge, TX, RTypes, RX, RY, RID, RIDs, RVals, RTimeIn, RExitAge, resource_scatImage, bN, bS, bE, bW, bNE, bNW, bSE, bSW, ct1, Mu, Maint, motion, reproduction, speciation, seedCom, m, r, nNi, nP, nC, rmax, sim, RAD, splist, N, ct, splist2, WTs, Jcs, Sos, RDens, RDiv, RRich, S, ES, Ev, BP, SD, Nm, sk, T, R, LowerLimit, prod_i, prod_q, viscosity, alpha, Ts, Rs, PRODIs, Ns, TTAUs, INDTAUs, RDENs, RDIVs, RRICHs, Ss, ESs, EVs, BPs, SDs, NMAXs, SKs, MUs, MAINTs, PRODNs, PRODPs, PRODCs, lefts, bottoms, Gs, Ms, NRs, PRs, CRs, Ds, RTAUs, GrowthList, MaintList, N_RList, P_RList, C_RList, DispList, amp, freq, flux, pulse, phase, disturb, envgrads, barriers
ct += 1
#plot_system = 'yes'
plot_system = 'no'
# fluctuate flow according to amplitude, frequency, & phase
u1 = u0 + u0 * (amp * sin(2 * pi * ct * freq + phase))
if u1 > 1: u1 == 1.0
# Fluid dynamics
nN, nS, nE, nW, nNE, nNW, nSE, nSW, barrier = LBM.stream(
[nN, nS, nE, nW, nNE, nNW, nSE, nSW, barrier])
rho, ux, uy, n0, nN, nS, nE, nW, nNE, nNW, nSE, nSW = LBM.collide(
viscosity, rho, ux, uy, n0, nN, nS, nE, nW, nNE, nNW, nSE, nSW, u0)
# Inflow of tracers
if motion == 'white_noise' or motion == 'brown_noise':
numt = 10
TIDs, TTimeIn, TX, TY = bide.NewTracers(numt, motion, TIDs, TX, TY,
TTimeIn, width, height, 2)
elif ct == 1:
numt = 10
TIDs, TTimeIn, TX, TY = bide.NewTracers(numt, motion, TIDs, TX, TY,
TTimeIn, width, height, 2)
else:
numt = 1
TIDs, TTimeIn, TX, TY = bide.NewTracers(numt, motion, TIDs, TX, TY,
TTimeIn, width, height, u0)
# moving tracer particles
if len(TIDs) > 0:
if motion == 'fluid':
TIDs, TX, TY, TExitAge, TTimeIn = bide.fluid_movement(
'tracer', TIDs, TTimeIn, TExitAge, TX, TY, ux, uy, width,
height, u0)
else:
TIDs, TX, TY, TExitAge, TTimeIn = bide.nonfluid_movement(
'tracer', motion, TIDs, TTimeIn, TExitAge, TX, TY, ux, uy,
width, height, u0)
# Inflow of resources
if motion == 'white_noise' or motion == 'brown_noise':
u1 = 2
RTypes, RVals, RX, RY, RIDs, RID, RTimeIn = bide.ResIn(
motion, RTypes, RVals, RX, RY, RID, RIDs, RTimeIn, r, rmax, nNi, nP,
nC, width, height, u1)
# resource flow
Lists = [RTypes, RIDs, RID, RVals]
if len(RTypes) > 0:
if motion == 'fluid':
RTypes, RX, RY, RExitAge, RIDs, RID, RTimeIn, RVals = bide.fluid_movement(
'resource', Lists, RTimeIn, RExitAge, RX, RY, ux, uy, width,
height, u0)
else:
RTypes, RX, RY, RExitAge, RIDs, RID, RTimeIn, RVals = bide.nonfluid_movement(
'resource', motion, Lists, RTimeIn, RExitAge, RX, RY, ux, uy,
width, height, u0)
# Inflow of individuals (immigration)
if ct == 1:
SpeciesIDs, IndX, IndY, MaintDict, EnvD, GrowthDict, DispDict, SpColorDict, IndIDs, IndID, IndTimeIn, Qs, N_RD, P_RD, C_RD, GrowthList, MaintList, N_RList, P_RList, C_RList, DispList, ADList = bide.immigration(
dmax, gmax, maintmax, motion, seedCom, 1, SpeciesIDs, IndX, IndY,
width, height, MaintDict, EnvD, envgrads, GrowthDict, DispDict,
SpColorDict, IndIDs, IndID, IndTimeIn, Qs, N_RD, P_RD, C_RD, nNi,
nP, nC, u1, alpha, GrowthList, MaintList, N_RList, P_RList,
C_RList, DispList, ADList)
else:
SpeciesIDs, IndX, IndY, MaintDict, EnvD, GrowthDict, DispDict, SpColorDict, IndIDs, IndID, IndTimeIn, Qs, N_RD, P_RD, C_RD, GrowthList, MaintList, N_RList, P_RList, C_RList, DispList, ADList = bide.immigration(
dmax, gmax, maintmax, motion, 1, m, SpeciesIDs, IndX, IndY, width,
height, MaintDict, EnvD, envgrads, GrowthDict, DispDict,
SpColorDict, IndIDs, IndID, IndTimeIn, Qs, N_RD, P_RD, C_RD, nNi,
nP, nC, u1, alpha, GrowthList, MaintList, N_RList, P_RList,
C_RList, DispList, ADList)
# dispersal
Lists = [
SpeciesIDs, IndIDs, IndID, Qs, DispDict, GrowthList, MaintList,
N_RList, P_RList, C_RList, DispList, ADList, Qs
]
if len(SpeciesIDs) > 0:
if motion == 'fluid':
SpeciesIDs, IndX, IndY, IndExitAge, IndIDs, IndID, IndTimeIn, Qs, GrowthList, MaintList, N_RList, P_RList, C_RList, DispList, ADList, Qs = bide.fluid_movement(
'individual', Lists, IndTimeIn, IndExitAge, IndX, IndY, ux, uy,
width, height, u0)
else:
SpeciesIDs, IndX, IndY, IndExitAge, IndIDs, IndID, IndTimeIn, Qs, GrowthList, MaintList, N_RList, P_RList, C_RList, DispList, ADList, Qs = bide.nonfluid_movement(
'individual', motion, Lists, IndTimeIn, IndExitAge, IndX, IndY,
ux, uy, width, height, u0)
# Chemotaxis
#SpeciesIDs, Qs, IndIDs, ID, TimeIn, X, Y, GrowthDict, DispDict, GrowthList, MaintList, N_RList, P_RList, C_RList, DispList, ADList = bide.chemotaxis(reproduction, speciation, SpeciesIDs, Qs, IndIDs, IndID, IndTimeIn, IndX, IndY, width, height, GrowthDict, DispDict, SpColorDict, N_RD, P_RD, C_RD, MaintDict, EnvD, envgrads, nNi, nP, nC, GrowthList, MaintList, N_RList, P_RList, C_RList, DispList, ADList)
# Forage
#SpeciesIDs, Qs, IndIDs, ID, TimeIn, X, Y, GrowthDict, DispDict, GrowthList, MaintList, N_RList, P_RList, C_RList, DispList, ADList = bide.density_forage(RVals, RX, RY, reproduction, speciation, SpeciesIDs, Qs, IndIDs, IndID, IndTimeIn, IndX, IndY, width, height, GrowthDict, DispDict, SpColorDict, N_RD, P_RD, C_RD, MaintDict, EnvD, envgrads, nNi, nP, nC, GrowthList, MaintList, N_RList, P_RList, C_RList, DispList, ADList)
PRODI, PRODN, PRODC, PRODP = 0, 0, 0, 0
p1, TNQ1, TPQ1, TCQ1 = metrics.getprod(Qs)
# Consume
RTypes, RVals, RIDs, RID, RTimeIn, RExitAge, RX, RY, SpeciesIDs, Qs, IndIDs, IndID, IndTimeIn, IndX, IndY, GrowthList, MaintList, N_RList, P_RList, C_RList, DispList, ADList = bide.consume(
RTypes, RVals, RIDs, RID, RX, RY, RTimeIn, RExitAge, SpeciesIDs, Qs,
IndIDs, IndID, IndTimeIn, IndX, IndY, width, height, GrowthDict, N_RD,
P_RD, C_RD, DispDict, GrowthList, MaintList, N_RList, P_RList, C_RList,
DispList, ADList)
# Reproduction
SpeciesIDs, Qs, IndIDs, ID, TimeIn, X, Y, GrowthDict, DispDict, GrowthList, MaintList, N_RList, P_RList, C_RList, DispList, ADList = bide.reproduce(
reproduction, speciation, SpeciesIDs, Qs, IndIDs, IndID, IndTimeIn,
IndX, IndY, width, height, GrowthDict, DispDict, SpColorDict, N_RD,
P_RD, C_RD, MaintDict, EnvD, envgrads, nNi, nP, nC, GrowthList,
MaintList, N_RList, P_RList, C_RList, DispList, ADList)
# maintenance
SpeciesIDs, X, Y, IndExitAge, IndIDs, IndTimeIn, Qs, GrowthList, MaintList, N_RList, P_RList, C_RList, DispList, ADList = bide.maintenance(
SpeciesIDs, IndX, IndY, IndExitAge, SpColorDict, MaintDict, EnvD,
IndIDs, IndTimeIn, Qs, GrowthList, MaintList, N_RList, P_RList,
C_RList, DispList, ADList)
# transition to or from dormancy
Sp_IDs, IDs, Qs, GrowthList, MaintList, ADList = bide.transition(
SpeciesIDs, IndIDs, Qs, GrowthList, MaintList, ADList)
p2, TNQ2, TPQ2, TCQ2 = metrics.getprod(Qs)
PRODI = p2 - p1
PRODN = TNQ2 - TNQ1
PRODP = TPQ2 - TPQ1
PRODC = TCQ2 - TCQ1
# disturbance
if np.random.binomial(1, disturb * u0) == 1:
SpeciesIDs, X, Y, IndExitAge, IndIDs, IndTimeIn, Qs, GrowthList, MaintList, N_RList, P_RList, C_RList, DispList, ADList = bide.decimate(
SpeciesIDs, IndX, IndY, IndExitAge, SpColorDict, MaintDict, EnvD,
IndIDs, IndTimeIn, Qs, GrowthList, MaintList, N_RList, P_RList,
C_RList, DispList, ADList)
ax = fig.add_subplot(111)
plt.tick_params(axis='both',
which='both',
bottom='off',
top='off',
left='off',
right='off',
labelbottom='off',
labelleft='off')
if len(SpeciesIDs) >= 1: RAD, splist = bide.GetRAD(SpeciesIDs)
else: RAD, splist, N, S = [], [], 0, 0
N, S, tt, rr = sum(RAD), len(RAD), len(TIDs), len(RIDs)
numD = ADList.count('d')
if N != len(ADList):
print N, len(SpeciesIDs), len(ADList)
print "N != len(ADList)"
sys.exit()
if N > 0:
Title = [
'Individuals consume resources, grow, reproduce, and die as they move through the environment. \nAverage speed on the x-axis is '
+ str(u0) + ' units per time step. ' + str(len(TExitAge)) +
' tracers have passed through.\nN: ' + str(N) + ', S: ' + str(S) +
', tracers: ' + str(tt) + ', resources: ' + str(rr) + ', ct: ' +
str(ct) + ', %dormant: ' + str(round((numD / N) * 100, 2))
]
else:
Title = [
'Individuals consume resources, grow, reproduce, and die as they move through the environment. \nAverage speed on the x-axis is '
+ str(u0) + ' units per time step. ' + str(len(TExitAge)) +
' tracers have passed through.\nN: ' + str(N) + ', S: ' + str(S) +
', tracers: ' + str(tt) + ', resources: ' + str(rr) + ', ct: ' +
str(ct) + ', %dormant: nan'
]
txt.set_text(' '.join(Title))
ax.set_ylim(0, height)
ax.set_xlim(0, width)
if plot_system == 'yes':
##### PLOTTING THE SYSTEM ##############################################
resource_scatImage.remove()
tracer_scatImage.remove()
Ind_scatImage.remove()
colorlist = []
sizelist = []
for i, val in enumerate(SpeciesIDs):
if ADList[i] == 'a':
colorlist.append('red')
elif ADList[i] == 'd':
colorlist.append('0.3')
sizelist.append(min(Qs[i]) * 1000)
resource_scatImage = ax.scatter(RX,
RY,
s=RVals * 100,
c='w',
edgecolor='SpringGreen',
lw=0.6,
alpha=0.3)
Ind_scatImage = ax.scatter(IndX,
IndY,
s=sizelist,
c=colorlist,
edgecolor='0.2',
lw=0.2,
alpha=0.9)
tracer_scatImage = ax.scatter(TX,
TY,
s=200,
c='r',
marker='*',
lw=0.0,
alpha=0.6)
Ns.append(N)
if N == 0 and BurnIn == 'not done':
Ns = [Ns[-1]] # only keep the most recent N value
BurnIn = 'done'
if ct > 200 and BurnIn == 'not done':
if len(Ns) > 100:
AugmentedDickeyFuller = sta.adfuller(Ns)
val, p = AugmentedDickeyFuller[0:2]
if p >= 0.05:
Ns.pop(0)
elif p < 0.05 or isnan(p) == True:
BurnIn = 'done'
Ns = [Ns[-1]] # only keep the most recent N value
if ct > 300 and BurnIn == 'not done':
Ns = [Ns[-1]] # only keep the most recent N value
BurnIn = 'done'
if BurnIn == 'done':
PRODIs.append(PRODI)
PRODNs.append(PRODN)
PRODPs.append(PRODP)
PRODCs.append(PRODC)
if len(RExitAge) > 0:
RTAUs.append(mean(RExitAge))
if len(IndExitAge) > 0:
INDTAUs.append(mean(IndExitAge))
if len(TExitAge) > 0:
TTAUs.append(mean(TExitAge))
# Examining the resource RAD
if len(RTypes) > 0:
RRAD, Rlist = bide.GetRAD(RTypes)
RDens = len(RTypes) / (height * width)
RDiv = float(metrics.Shannons_H(RRAD))
RRich = len(Rlist)
RDENs.append(RDens)
RDIVs.append(RDiv)
RRICHs.append(RRich)
# Number of tracers, resource particles, and individuals
T, R, N = len(TIDs), len(RIDs), len(SpeciesIDs)
Ts.append(T)
Rs.append(R)
Ss.append(S)
if N >= 1:
if R >= 1:
q = min([10, R])
#avg_dist = spatial.avg_dist(X, RX, Y, RY, q)
avg_dist = spatial.nearest_neighbor(X, RX, Y, RY, q)
AVG_DIST.append(avg_dist)
spD = DispDict.values()
spM = MaintDict.values()
spG = GrowthDict.values()
SpecDisp.append(mean(spD))
SpecMaint.append(mean(spM))
SpecGrowth.append(mean(spG))
RAD, splist = bide.GetRAD(SpeciesIDs)
RAD, splist = zip(*sorted(zip(RAD, splist), reverse=True))
RAD = list(RAD)
S = len(RAD)
Ss.append(S)
# Evenness, Dominance, and Rarity measures
Ev = metrics.e_var(RAD)
EVs.append(Ev)
ES = metrics.e_simpson(RAD)
ESs.append(ES)
if len(Ns) == 1:
splist2 = list(splist)
if len(Ns) > 1:
wt = metrics.WhittakersTurnover(splist, splist2)
jc = metrics.jaccard(splist, splist2)
so = metrics.sorensen(splist, splist2)
splist2 = list(splist)
WTs.append(wt)
Jcs.append(jc)
Sos.append(so)
Nm, BP = [max(RAD), Nm / N]
NMAXs.append(Nm)
BPs.append(BP)
SD = metrics.simpsons_dom(RAD)
SDs.append(SD)
sk = stats.skew(RAD)
SKs.append(sk)
Gs.append(mean(GrowthList))
Ms.append(mean(MaintList))
Ds.append(mean(DispList))
numD = ADList.count('d')
ADs.append(numD / len(ADList))
Nmeans = [sum(x) / len(x) for x in zip(*N_RList)]
NRs.append(mean(Nmeans))
Pmeans = [sum(x) / len(x) for x in zip(*P_RList)]
PRs.append(mean(Pmeans))
Cmeans = [sum(x) / len(x) for x in zip(*C_RList)]
CRs.append(mean(Cmeans))
#process = psutil.Process(os.getpid())
#mem = round(process.get_memory_info()[0] / float(2 ** 20), 1)
# return the memory usage in MB
if len(Ns) > 100:
t = time.clock() - t
#print sim, ' N:', int(round(mean(Ns))), 'S:', int(round(mean(Ss))), 'WT:', round(mean(WTs),2), ': flow:', u0, 'time:', round(t,1), 'seconds', ': Ttaus:',round(mean(TTimeIn)), round(mean(TExitAge)), ': Etau:', round(width/u0) #' MB:',int(round(mem)), 'p-val =', round(p,3)
#print sim, ' N:', int(round(mean(Ns))), 'S:', int(round(mean(Ss))), ': flow:', u0, 'time:', round(t,1), 'seconds', ' height:', str(height), ' Avg dist:', round(mean(AVG_DIST),3), ' f(dormant):',round(mean(ADs),3)
print sim, ' N:', int(round(mean(Ns))), 'S:', int(round(
mean(Ss))), ' flow:', u0, 'time:', round(
t,
1), 'Ttaus:', round(mean(TExitAge), 2), ': Etau:', round(
(width - 1) / u0, 2), 'dormant:', round(mean(ADs), 3)
t = time.clock()
SString = str(splist).strip('()')
RADString = str(RAD).strip('()')
RADString = str(RAD).strip('[]')
IndRTD = str(IndExitAge).strip('[]')
TRTD = str(TExitAge).strip('[]')
RRTD = str(RExitAge).strip('[]')
OUT1 = open(GenPath + 'examples/SimData.csv', 'a')
OUT2 = open(GenPath + 'examples/RADs.csv', 'a')
OUT3 = open(GenPath + 'examples/Species.csv', 'a')
OUT4 = open(GenPath + 'examples/IndRTD.csv', 'a')
OUT5 = open(GenPath + 'examples/TracerRTD.csv', 'a')
OUT6 = open(GenPath + 'examples/ResRTD.csv', 'a')
#TTAUs = np.mean(TExitAge), np.mean(TTimeIn)
outlist = [
sim, motion,
mean(PRODIs),
mean(PRODNs),
mean(PRODPs),
mean(PRODCs), r, nNi, nP, nC, rmax, gmax, maintmax, dmax,
barriers, alpha, seedCom, u0, width - 0.2, height, viscosity,
N, m,
mean(RTAUs),
mean(TExitAge),
mean(INDTAUs),
mean(RDENs),
mean(RDIVs),
mean(RRICHs),
mean(Ss),
mean(ESs),
mean(EVs),
mean(BPs),
mean(SDs),
mean(NMAXs),
mean(SKs), T, R, speciation,
mean(WTs),
mean(Jcs),
mean(Sos),
mean(Gs),
mean(Ms),
mean(NRs),
mean(PRs),
mean(CRs),
mean(Ds), amp, flux, freq, phase, disturb,
mean(SpecGrowth),
mean(SpecDisp),
mean(SpecMaint),
mean(AVG_DIST),
mean(ADs)
]
outlist = str(outlist).strip('[]')
print >> OUT1, outlist
print >> OUT2, RADString
print >> OUT3, SString
print >> OUT4, ct1, ',', sim, ',', IndRTD
print >> OUT5, ct1, ',', sim, ',', TRTD
print >> OUT6, ct1, ',', sim, ',', RRTD
OUT1.close()
OUT2.close()
OUT3.close()
OUT4.close()
OUT5.close()
OUT6.close()
ct1 += 1
ct = 0
Rates = np.roll(Rates, -1, axis=0)
u0 = Rates[0]
n0, nN, nS, nE, nW, nNE, nNW, nSE, nSW, barrier, rho, ux, uy, bN, bS, bE, bW, bNE, bNW, bSE, bSW = LBM.SetLattice(
u0, viscosity, width, height, lefts, bottoms, barriers)
u1 = u0 + u0 * (amp * sin(2 * pi * ct * freq + phase))
RDens, RDiv, RRich, S, ES, Ev, BP, SD, Nm, sk, Mu, Maint, ct, IndID, RID, N, ct1, T, R, PRODI, PRODQ = [
0
] * 21
ADList, ADs, AVG_DIST, SpecDisp, SpecMaint, SpecGrowth, SpColorList, GrowthList, MaintList, N_RList, P_RList, C_RList, RColorList, DispList = [
list([]) for _ in xrange(14)
]
RAD, splist, IndTimeIn, SpeciesIDs, IndX, IndY, IndIDs, Qs, IndExitAge, TX, TY, TExitAge, TIDs, TTimeIn, RX, RY, RIDs, RTypes, RExitAge, RTimeIn, RVals, Gs, Ms, NRs, PRs, CRs, Ds, Ts, Rs, PRODIs, PRODNs, PRODPs, PRODCs, Ns, RTAUs, TTAUs, INDTAUs, RDENs, RDIVs, RRICHs, Ss, ESs, EVs, BPs, SDs, NMAXs, SKs, MUs, MAINTs, WTs, Jcs, Sos, splist2 = [
list([]) for _ in xrange(53)
]
p = 0
BurnIn = 'not done'
#if u0 in Rates:
if u0 == max(Rates):
print '\n'
sim += 1
if sim > num_sims:
print "simplex finished"
sys.exit()
width, height, alpha, motion, reproduction, speciation, seedCom, m, r, nNi, nP, nC, rmax, gmax, maintmax, dmax, amp, freq, flux, pulse, phase, disturb, envgrads, barriers, Rates = rp.get_rand_params(
fixed)
for i in range(barriers):
lefts.append(np.random.uniform(0.2, .8))
bottoms.append(np.random.uniform(0.1, 0.7))
n0, nN, nS, nE, nW, nNE, nNW, nSE, nSW, barrier, rho, ux, uy, bN, bS, bE, bW, bNE, bNW, bSE, bSW = LBM.SetLattice(
u0, viscosity, width, height, lefts, bottoms, barriers)
u1 = u0 + u0 * (amp * sin(2 * pi * ct * freq + phase))
SpColorDict, GrowthDict, MaintDict, EnvD, N_RD, P_RD, C_RD, RColorDict, DispDict, EnvD = {}, {}, {}, {}, {}, {}, {}, {}, {}, {}
####################### REPLACE ENVIRONMENT ########################
ax = fig.add_subplot(111)
LowerLimit, sim = 30, 677 #182
viscosity = 10 # unitless but required by an LBM model
#u0 = choice(Rates) # initial in-flow speed
u0 = Rates[0]
############### INITIALIZE GRAPHICS ############################################
fig = plt.figure(figsize=(12, 8))
ax = fig.add_subplot(111) # initiate first plot
Ind_scatImage = ax.scatter([0], [0], alpha=0)
tracer_scatImage = ax.scatter([0], [0], alpha=0)
resource_scatImage = ax.scatter([0], [0], alpha=0)
##################### Lattice Boltzmann PARAMETERS ###################
n0, nN, nS, nE, nW, nNE, nNW, nSE, nSW, barrier, rho, ux, uy, bN, bS, bE, bW, bNE, bNW, bSE, bSW = LBM.SetLattice(
u0, viscosity, width, height, lefts, bottoms, barriers)
Title = ['', '']
txt = fig.suptitle(' '.join(Title), fontsize=12)
t = time.clock()
Ns = []
BurnIn = 'not done'
p = 0.0
ani = animation.FuncAnimation(fig,
nextFrame,
frames=110,
interval=40,
blit=False) # 20000 frames is a long movie
plt.show()