def plot_for(z, d):
cs = CalcSimWrapper()
ds = InputDatastore('../InputData', 'NiCu', 973)
ce = ComparisonEngine(cs)
D = ds.interpolated_diffusivity(10001)
R = ds.interpolated_resistivity(10001)
dx = 0.5 * 35e-8
ndx = 200
dt = 0.01
ndt = int(2 * 60 * 60 / 0.01)
init = ones(ndx)
init[ndx/2:] = 0
x = linspace(0, 25, 200)
ddict = ds.interpolated_experiment_dict(x)
for I in ddict.keys():
if I == 0:
dv = 1
else:
dv = d
r = cs.emigration_factor(z, I, 973)
mdl = cs.calc_simulation(D, R, init, ndt, dt, dx, r, dv)
ce = ComparisonEngine(cs)
lsq, shfit = ce.calibrate(mdl, ddict[I])
smdl = ce.shift_data(mdl)
plot(x, ddict[I], label=str.format('Exper. (I={} A/cm^2)', I/100/100))
plot(x, smdl, label=str.format('Model. (I={} A/cm^2)', I/100/100))
legend(loc=3)
show()
def quicksim(z, cvf, I, exper, direction):
ce = ComparisonEngine(accelcs)
if direction == 'reverse':
I = -np.abs(I)
else:
I = np.abs(I)
diffusivity = dstore.interpolated_diffusivity(10001, args.temperature, precise=True)
resistivity = dstore.interpolated_resistivity(10001, args.temperature)
r = accelcs.emigration_factor(z, I * 100 * 100, args.temperature)
simd = accelcs.calc_simulation(diffusivity, resistivity, init_cond, ndt, dt, dx, r, cvf)
lsq, shift = ce.calibrate(simd, exper)
shifted_simd = ce.shift_data(simd)
return shifted_simd, lsq
def do_stage1(self):
"""Our stage 1 is to do the requested simulation and spit out a csv file with (x, sim, exper)
"""
simexec = CalcSimExecutor(self.dstore, self.args.temperature)
try:
simdata = simexec.compute(self.args.z, self.args.cvf, self.args.current, self.args.direction)
except SimulationUnstableError:
print('Bang! Dmax = {}, Dmin = {}'.format(simexec.Dvector.max(), simexec.Dvector.min()))
raise
experdata = self.dstore.interpolated_experiment(self.args.current, simdata[:, 0], self.args.direction)
ce = ComparisonEngine(CalcSimWrapper())
ce.calibrate(simdata[:, 1], experdata)
simdata[:, 1] = ce.shift_data(simdata[:, 1])
self.fulldata = np.column_stack((simdata, experdata))
self.ostore.add_matrix(self.fulldata, '.csv')
for I in I_plot:
ebars_list_lower.append(cbounds[I][0])
ebars_list_upper.append(cbounds[I][2])
ebars = np.array([ebars_list_lower, ebars_list_upper])
plot_data = np.column_stack((I_plot, cvf_plot))
outfile = get_fname('cvfplot_combined.png')
dmplots.plot_cvf_function_ebars(plot_data, ebars, 'combined', outfile)
#and politely output simulations
cse = CalcSimExecutor(ds, T)
ce = ComparisonEngine(cse.cs)
x = linspace(0, 25, 100)
for direction in ('forward', 'reverse'):
for I in cresults.keys():
for idx, edge in ((0, 'lower'), (1, 'best'), (2, 'upper')):
outfile = get_fname(str.format('Comparison_I{}_{}_{}bound.png', I, direction, edge))
cvf = cbounds[I][1]
if idx == 0:
cvf -= cbounds[I][idx]
elif idx == 2:
cvf += cbounds[I][idx]
print('using cvf = ' + str(cvf))
edict = ds.edict_for_direction(direction)
exper = ds.interpolated_experiment_dict(x, edict)[I]
simd = cse.compute(zaverage_rounded, cvf, I, direction)
exper = np.column_stack((x, exper))
ce.calibrate(simd[:, 1], exper[:, 1])
simd[:, 1] = ce.shift_data(simd[:, 1])
f = dmplots.plot_sim_fit(simd, exper, I, zaverage_rounded, cvf, direction)
c = FigureCanvasAgg(f)
c.print_figure(outfile)
I = 3000
cvfunc = lambda ID: 0.0014 * ID
ioff()
figure()
for T in (1000, 1100, 1200):
Davg = dstore.interpolated_diffusivity(1001, T).mean()
n_secs_sim = 1e-12 / Davg
ndt = int(n_secs_sim / defaults.simulation_dt)
cse = CalcSimExecutor(dstore, T)
current_whole = cse.compute(z, cvfunc(I), I, "forward")
nocurrent = cse.compute(0, 1, 0, "forward")[:, 1]
x = current_whole[:, 0]
current = current_whole[:, 1]
shiftengine = ComparisonEngine(cse.cs)
lsq, _ = shiftengine.calibrate(current, nocurrent)
s_current = shiftengine.shift_data(current)
plot(x, s_current, label="{}K, current".format(T))
plot(x, nocurrent, label="{}K, no current".format(T))
xlabel("x coordinate (micron)")
ylabel("Cu concentration (at. fraction)")
title("Comparison of different Temps with correction")
legend(loc="lower left")
show()
ylabel("Cu. Composition (at. fraction)")
title("Investigation of checkerboard")
subplot(212)
xlabel("Position (micron)")
ylabel(r"$\Delta$Cu Composition (at. fraction)")
for T in (1046, 1048, 1050, 1052):
Davg = dstore.interpolated_diffusivity(1001, T).mean()
n_secs_sim = 1e-12 / Davg
dt = n_secs_sim / (defaults.simulation_tsteps * 1)
cse = CalcSimExecutor(dstore, T, dt=dt, ndt=(defaults.simulation_tsteps * 1))
simd_lc = cse.compute(z, cvfunc(2600), 2600, "forward")
simd_hc = cse.compute(z, cvfunc(2700), 2700, "forward")
shiftengine = ComparisonEngine(cse.cs)
shiftengine.calibrate(simd_lc[:, 1], simd_hc[:, 1])
simd_lc[:, 1] = shiftengine.shift_data(simd_lc[:, 1])
subplot(211)
plot(simd_lc[:, 0], simd_lc[:, 1], label="T = {}K, I = {}A/cm^2".format(T, 2600))
plot(simd_hc[:, 0], simd_hc[:, 1], label="T = {}K, I = {}A/cm^2".format(T, 2700))
subplot(212)
plot(simd_lc[:, 0], simd_hc[:, 1] - simd_lc[:, 1], label="T = {}K".format(T))
subplot(211)
legend(loc="best")
subplot(212)
legend(loc="best")
savefig("../checkerboard_investigation.png")
aparser.add_argument('--cvf', type=float, required=True,
help='Vacancy concentration factor')
aparser.add_argument('--direction', type=str, default='forward',
help='Direction of application of current')
args = aparser.parse_args()
accelcs = CalcSimWrapper()
dstore = InputDatastore(args.inputdata, args.dataprefix, 973, args.direction)
ce = ComparisonEngine(accelcs)
x = np.linspace(0, 25, num=100)
exper_data = dstore.interpolated_experiment_dict(x)[args.current]
diffusivity = dstore.interpolated_diffusivity(10001)
resistivity = dstore.interpolated_resistivity(10001)
init_cond = np.ones(100)
init_cond[50:] = 0
emigration_T = 973
dt = 0.05
ndt = int(2 * 60 * 60 / 0.05)
dx = 25e-6 / 100
r = accelcs.emigration_factor(args.z, args.current * 100 * 100, emigration_T)
simd = accelcs.calc_simulation(diffusivity, resistivity, init_cond, ndt, dt, dx, r, args.cvf)
lsq, shift = ce.calibrate(simd, exper_data)
shifted_simd = ce.shift_data(simd)
full_simd = np.column_stack((x, shifted_simd))
full_exper = np.column_stack((x, exper_data))
dmplots.plot_sim_fit(full_simd, full_exper, args.current, args.z, args.cvf, args.direction, args.output)
print('lsq = ' + str(lsq))