# Set bin width and range
bin_width = 0.20
Emax = 20
Nbins = int(np.ceil(Emax / bin_width))
Emax_adjusted = bin_width * Nbins # Trick to get an integer number of bins
bins = np.linspace(0, Emax_adjusted, Nbins + 1)
# Define list of calculation input files and corresponding label names
inputfile = ""
# Instantiate figure which we will fill
f_rho, ax_rho = plt.subplots(1, 1)
# Read energy levels from file
levels = smutil.read_energy_levels(inputfile)
# Calculate level density
rho = smutil.total_level_density(levels, bin_width, Emax)
# Plot it
ax_rho.step(bins, np.append(0, rho), where='pre', label="Level density")
# Make the plot nice
ax_rho.set_yscale('log')
ax_rho.set_xlabel(r'$E_x \, \mathrm{(MeV)}$')
ax_rho.set_ylabel(r'$\rho \, \mathrm{(MeV^{-1})}$')
ax_rho.legend()
# Show plot
plt.show()
def run(self, spe_tbme):
# Add some test in case spe_tbme is a Theano tensor?
# print type(spe_tbme)
# print spe_tbme.ndim
# if type(spe_tbme) == "<class 'theano.tensor.var.TensorVariable'>":
# print "Oh hello"
# Nspetbme = spe_tbme.ndim
# else:
# Nspetbme = len(spe_tbme)
# calc_tbme_matrix = np.zeros((self.Ntot,self.Nspe+self.Ntbme))
calc_dict = {}
# print "From smensemble.run(): calc_tbme_matrix.shape =", calc_tbme_matrix.shape
SPE = spe_tbme[0:self.Nspe]
tbme_template = self.tbme_template
# print "SPE =", SPE
# TBME = np.copy(self.tbme_template)
# print TBME[:,5]
# print "spe_tbme =", spe_tbme
# print "spe_tbme.shape =", spe_tbme.shape
# TBME[:,5] = spe_tbme[self.Nspe:]
# TBME_th = th.tensor.stack([tbme_template[0:5,:], spe_tbme[self.Nspe:].reshape((self.Ntbme,1))])
TBME_input1 = th.tensor.dmatrix("TBME_input1")
TBME_input1.tag.test_value = self.tbme_template[:, 0:5]
# print "TBME_input1.tag.test_value.shape =", TBME_input1.tag.test_value.shape
TBME_input2 = th.tensor.dvector("TBME_input2")
TBME_input2.tag.test_value = np.random.rand(self.Ntbme)
# print "TBME_input2.tag.test_value.shape =", TBME_input2.tag.test_value.shape
TBME_th = th.tensor.concatenate(
[TBME_input1,
TBME_input2.reshape((TBME_input2.shape[0], 1))],
axis=1)
TBME_values = th.function([TBME_input1, TBME_input2], TBME_th)
TBME = TBME_values(tbme_template[:, 0:5], spe_tbme[self.Nspe:])
# Make new directory for each calculation to store everything
os.chdir(self.fname_allstepsdir)
fname_currentstepdir = "{:d}".format(
int((np.abs(spe_tbme) *
np.linspace(1,
len(spe_tbme) + 1, len(spe_tbme))).sum() *
1e25)) # Each folder is named by the sum of parameter values.
# This is to make it identifiable so we don't rerun an
# ensemble with the same parameters, e.g. for taking
# the gradient. It may be a stupid way to do it, suggestions
# welcome.
if not os.path.exists(fname_currentstepdir):
os.makedirs(fname_currentstepdir)
os.chdir(fname_currentstepdir)
# Write interaction file:
# print self.mass_scaling, self.scaling_A0, self.scaling_p
smutil.write_interaction_file_msdict(
"interaction.snt",
SPE,
TBME,
self.model_space,
self.core,
comments="Autogenerated by ShellModelEnsemble class.",
mass_scaling=self.mass_scaling,
scaling_A0=self.scaling_A0,
scaling_p=self.scaling_p)
i_level = 0
for nucleusName, nucleusAttr in self.nucleiList.items():
rundirName = "{:s}".format(
nucleusName
) # Temporary directory where KSHELL runs for current nucleus, e.g. O18
outputFilename = "summary_{:s}.txt".format(
nucleusName
) # The name of the summary file for current nucleus that we want to keep by moving it up
# outputFilenameFinal = "summary-{:s}.txt".format(nucleusName) # TODO remove if not needed
# nucleusSMC = smcalc.shellmodelcalculation(nucleusName,
# A=nucleusAttr["A"], Z=nucleusAttr["Z"],
# levels=nucleusAttr["levels"],
# truncation=nucleusAttr["truncation"],
# core=self.core, model_space=self.model_space, SPE=SPE,
# TBME=TBME, kshell_dir=KSHELL_DIR, calc_tbme=True,
# ensemble_run=True)
nucleusSMC = smcalc.shellmodelcalculation(
nucleusName,
A=nucleusAttr["A"],
Z=nucleusAttr["Z"],
levels=nucleusAttr["levels"],
truncation=nucleusAttr["truncation"],
core=self.core,
model_space=self.model_space,
SPE=SPE,
TBME=TBME,
kshell_dir=KSHELL_DIR,
calc_tbme=True,
ensemble_run=False)
# Run calculation and extract spe&tbme expectation values, wrapped in some tests to avoid unnecessary steps:
if os.path.isfile(
os.path.join(rundirName, outputFilename)
): # If the rundir exists for current nucleus then we must
try: # It could be that the step was cancelled in the middle of this nucleus. So we try to catch the exception that the results file is not complete
# levels = smutil.read_energy_levels(os.path.join(rundirName, outputFilename))
calc_tbmes = smutil.read_calc_tbme(
os.path.join(rundirName, outputFilename),
self.tbme_template)
calc_E = smutil.read_energy_levels(
os.path.join(rundirName, outputFilename))
except: # If exception is raised then it means the output file is incomplete and we need to rerun this nucleus.
# nucleusSMC.run(is_mpi=self.is_mpi, n_restart_vec=n_restart_vec, max_lanc_vec=max_lanc_vec)
nucleusSMC.run(
is_mpi=self.is_mpi
) # n_restart_vec, max_lanc_vec set in initialization for tuning run
levels = smutil.read_energy_levels(
os.path.join(rundirName, outputFilename))
calc_tbmes = smutil.read_calc_tbme(
os.path.join(rundirName, outputFilename),
self.tbme_template)
calc_E = smutil.read_energy_levels(
os.path.join(rundirName, outputFilename))
shutil.copyfile(
os.path.join(rundirName,
outputFilename), outputFilename
) # Copy results file to current step directory and remove current rundir
shutil.rmtree(rundirName)
elif os.path.isfile(
outputFilename
): # The current nucleus has been completed, and the summary has been copied to outputFilenameFinal, which we then read
# levels = smutil.read_energy_levels(outputFilename)
calc_tbmes = smutil.read_calc_tbme(outputFilename,
self.tbme_template)
calc_E = smutil.read_energy_levels(outputFilename)
else: # Nothing exists for this nucleus, so we run it from scratch
# nucleusSMC.run(is_mpi=self.is_mpi, n_restart_vec=n_restart_vec, max_lanc_vec=max_lanc_vec)
nucleusSMC.run(
is_mpi=self.is_mpi
) # n_restart_vec, max_lanc_vec set in initialization for tuning run
# levels = smutil.read_energy_levels(os.path.join(rundirName, outputFilename))
calc_tbmes = smutil.read_calc_tbme(
os.path.join(rundirName, outputFilename),
self.tbme_template)
calc_E = smutil.read_energy_levels(
os.path.join(rundirName, outputFilename))
# Copy summary file to current step directory and remove current rundir
shutil.copyfile(os.path.join(rundirName, outputFilename),
outputFilename)
#shutil.rmtree(rundirName) # May be commented out for debug
# Transfer entries in calc_tbmes from current nucleus to total matrix for current run:
# print calc_tbmes
# for i in range(len(calc_tbmes[:,0])):
# calc_tbme_matrix[i_level,:] = calc_tbmes[i,:]
# i_level += 1
calc_dict[nucleusName] = {
"calc_tbme": calc_tbmes,
"calc_E": calc_E
} # Make dictionary containing both energy levels and tbme expectation values for current nucleus.
# calc_tbme have the same ordering as calc_E by construction
# clean up
os.chdir(
"../../") # Exit current fname_currentstepdir and steps folder
# 20180116: Adding an option to remove the complete current fname_currentstepdir, to avoid using a lot of storage. This means all information we store is the PyMC3 trace. Not sure it's the best solution.
# shutil.rmtree(os.path.join(self.fname_allstepsdir, fname_currentstepdir))
return calc_dict