def compute(self):
fn = "dop_{}/r_{}/output_job_0" # ugly
depl_length, mobile_fraction = np.zeros(self.n_r), np.zeros(self.n_r)
for i_d in range(0, self.n_d):
for i_r in range(0, self.n_r):
print("read-in i_dop = {}, i_r = {}".format(i_d, i_r))
depl_length[i_r] = extract.extract_float(
fn.format(i_d, i_r), "depletion length: ")
mobile_fraction[i_r] = extract.extract_float(
fn.format(i_d, i_r), "mobile carrier fraction: ")
#self.depl_length[i_d] = gmean(-depl_length)
#self.mobile_fraction[i_d] = gmean(mobile_fraction)
self.depl_length[i_d] = np.mean(-depl_length)
self.mobile_fraction[i_d] = np.mean(mobile_fraction)
self.std_err_de[i_d] = np.std(depl_length) / self.n_r
self.std_err_mo[i_d] = np.std(mobile_fraction) / self.n_r
np.savetxt('postprocessing/depl_length.dat', self.depl_length)
np.savetxt('postprocessing/mobile_fraction.dat', self.mobile_fraction)
np.savetxt('postprocessing/std_err_de.dat', self.std_err_de)
np.savetxt('postprocessing/std_err_mo.dat', self.std_err_mo)
def compute(self):
fn = "dop_{}/r_{}/output_job_0" # ugly
depl_length, mobile_fraction = np.zeros(self.n_r).tolist(), np.zeros(
self.n_r).tolist()
for i_d in range(0, self.n_d):
for i_r in range(0, self.n_r):
print("read-in i_dop = {}, i_r = {}".format(i_d, i_r))
depl_length[i_r] = extract.extract_float(
fn.format(i_d, i_r), "depletion length: ")
mobile_fraction[i_r] = extract.extract_float(
fn.format(i_d, i_r), "mobile carrier fraction: ")
#self.depl_length[i_d] = gmean(-depl_length)
#self.mobile_fraction[i_d] = gmean(mobile_fraction)
self.depl_length[i_d] = np.mean(-np.array(depl_length)).tolist()
self.mobile_fraction[i_d] = np.mean(
np.array(mobile_fraction)).tolist()
self.std_err_de[i_d] = (np.std(np.array(depl_length)) /
self.n_r).tolist()
self.std_err_mo[i_d] = (np.std(np.array(mobile_fraction)) /
self.n_r).tolist()
self.dop = np.loadtxt(
'doping.txt').tolist() # TODO read from the yaml of r_0
IPIP_0_0 = np.zeros(NE)
EA_plus_0_0 = np.zeros([nr,NE])
EAEA_plus_0_0 = np.zeros(NE)
EA_1_0 = np.zeros([nr,NE])
EAEA_1_0 = np.zeros(NE)
IP_minus_1_0 = np.zeros([nr,NE])
IPIP_minus_1_0 = np.zeros(NE)
for i_r in range(0,nr):
fn = 'jobs/r_{}/output_job_0'.format(i_r)
print(fn)
J[i_r] = extract.extract_float(fn, "Ionized dopant fraction: ")
if np.log(J[i_r])>=0:
J[i_r] = extract.extract_e(fn, "Ionized dopant fraction: ")
IP_0_0[i_r,:] = np.loadtxt("jobs/r_{}/experiments/tmp/IP_0_0.dat".format(i_r))
EA_1_0[i_r,:] = np.loadtxt("jobs/r_{}/experiments/tmp/EA_1_0.dat".format(i_r))
EA_plus_0_0[i_r,:] = np.loadtxt("jobs/r_{}/experiments/tmp/EA_plus_0_0.dat".format(i_r))
IP_minus_1_0[i_r,:] = np.loadtxt("jobs/r_{}/experiments/tmp/IP_minus_1_0.dat".format(i_r))
JJ = np.mean(J[:])
IPIP_0_0[:]= np.mean(IP_0_0[:,:], 0)
EAEA_1_0[:]= np.mean(EA_1_0[:,:], 0)
EAEA_plus_0_0[:]= np.mean(EA_plus_0_0[:,:], 0)
IPIP_minus_1_0[:]= np.mean(IP_minus_1_0[:,:], 0)
print("Av. ionized dopant fraction: {}".format(JJ))
# Plot DOS vs. Energy to see if smooth enough
PlotDOSPreview(IPIP_0_0,EAEA_plus_0_0,IPIP_minus_1_0,EAEA_1_0,Energy,figname)
if count_nan:
savename = 'ion_dop_frac_fig5a_withnan.txt'
else:
savename = 'ion_dop_frac_fig5a.txt'
if not os.path.exists(savename):
ion_dop_frac_av = np.zeros((n_dis, n_temp))
std_ion_dop_frac = np.zeros((n_dis, n_temp))
for i_dis in range(n_dis):
for i_temp in range(n_temp):
ion_dop_frac_r = []
num_nan = 0
for i_r in range(n_replica):
fn = 'jobs/dis_{}/temp_{}/r_{}/output_job_0'.format(
i_dis, i_temp, i_r)
print(fn)
extract_ion_dop_frac = extract.extract_float(
fn, "Ionized dopant fraction: ")
if type(extract_ion_dop_frac) == float:
if np.log(extract_ion_dop_frac) >= 0:
ion_dop_frac_r.append(
extract.extract_e(fn, "Ionized dopant fraction: "))
else:
ion_dop_frac_r.append(extract_ion_dop_frac)
else:
num_nan += 1
if count_nan:
ion_dop_frac_r.append(0.0)
print(ion_dop_frac_r)
print('{} times nan encountered in {}'.format(num_nan, fn))
ion_dop_frac_av[i_dis, i_temp] = np.mean(ion_dop_frac_r)
std_ion_dop_frac[i_dis, i_temp] = np.std(ion_dop_frac_r) / np.sqrt(