Module dchain_tools
This module serves to function as a library of functions related to DCHAIN which can be easily imported into and used by scripts for processing DCHIAN output. They are summarized below.
Main function for DCHAIN output parsing
process_dchain_simulation_output(): This is main master function for parsing DCHAIN output and is generally the function one should use for this purpose. It processes all DCHAIN output for a given DCHAIN run.
DCHAIN output file parsing
parse_DCHAIN_act_file(): parser for the *.act file from DCHAINgenerate_nuclide_time_profiles(): processes nuclide output from parse_DCHAIN_act_file into a more usable formparse_DCS_file_from_DCHAIN(): parser for the *.dcs file from DCHAINparse_dtrk_file(): parser for the *.dtrk file from PHITS meant for DCHAINparse_dyld_files(): parser for the *.dyld files from PHITS meant for DCHAIN
DCHAIN output data plotting
plot_top10_nuclides(): generates a nice visualization on the ranking of nuclides
Relating to DCHAIN data libraries
rxn_to_dchain_str(): converts a reaction to the format used by the neutron reaction cross section librariesZZZAAAM_to_dchain_xs_lib_str(): converts a ZZZAAAM number to the 7-character nuclide string used by the n rxn xs libsECCO1968_Ebins(): returns the n highest energy bins of the ECCO 1968-group structureretrieve_rxn_xs_from_lib(): returns cross section for a reaction from a provided n rxn xs library filecalc_one_group_nrxn_xs_dchain(): provided a neutron flux, reaction, and library file, determine 1-grp nrxn xs
For handling nuclide names and identities with DCHAIN
Dname_to_ZAM(): converts a DCHAIN-formatted nuclide name to a ZZZAAAM numberZAM_to_Dname(): converts a ZZZAAAM number to a DCHAIN-formatted nuclide nameDname_to_Latex(): converts a DCHAIN-formatted nuclide name to pretty LaTeX formattingnuclide_plain_str_to_Dname(): converts a plaintext string for a nuclide to a DCHAIN-formatted nuclide name string
Other
parse_DCHAIN_act_file_legacy(): legacy version of parse_DCHAIN_act_file from before error implementationgenerate_nuclide_time_profiles_legacy(): legacy version of generate_nuclide_time_profiles from before error implementationfind(): return index of the first instance of a value in a listElement_Z_to_Sym(): returns elemental symbol provided the atomic number ZElement_Sym_to_Z(): returns an atomic number Z provided the elemental symbolElement_ZorSym_to_name(): returns a string of the name of an element provided its atomic number Z or symbolElement_ZorSym_to_mass(): returns the average atomic mass of an element provided its atomic number Z or symbolnuclide_to_Latex_form(): form a LaTeX-formatted string of a nuclide provided its informationnuclide_plain_str_to_latex_str(): convert a plaintext string for a nuclide to a LaTeX formatted raw stringnuclide_plain_str_ZZZAAAM(): convert a plaintext string for a nuclide to an integer ZZZAAAM valuetime_str_to_sec_multiplier(): determine multiplier to convert a time unit to secondsseconds_to_dhms(): convert a time in seconds to a string of human-relatable time unitsseconds_to_ydhms(): convert a time in seconds to a string of human-relatable time units (also with years)
Expand source code
'''
This module serves to function as a library of functions related to DCHAIN which can be easily
imported into and used by scripts for processing DCHIAN output. They are summarized below.
### Main function for DCHAIN output parsing
- `process_dchain_simulation_output` : **This is main master function for parsing DCHAIN output and is generally the function one should use for this purpose.** It processes all DCHAIN output for a given DCHAIN run.
### DCHAIN output file parsing
- `parse_DCHAIN_act_file` : parser for the *.act file from DCHAIN
- `generate_nuclide_time_profiles` : processes nuclide output from parse_DCHAIN_act_file into a more usable form
- `parse_DCS_file_from_DCHAIN` : parser for the *.dcs file from DCHAIN
- `parse_dtrk_file` : parser for the *.dtrk file from PHITS meant for DCHAIN
- `parse_dyld_files` : parser for the *.dyld files from PHITS meant for DCHAIN
### DCHAIN output data plotting
- `plot_top10_nuclides` : generates a nice visualization on the ranking of nuclides
### Relating to DCHAIN data libraries
- `rxn_to_dchain_str` : converts a reaction to the format used by the neutron reaction cross section libraries
- `ZZZAAAM_to_dchain_xs_lib_str` : converts a ZZZAAAM number to the 7-character nuclide string used by the n rxn xs libs
- `ECCO1968_Ebins` : returns the n highest energy bins of the ECCO 1968-group structure
- `retrieve_rxn_xs_from_lib` : returns cross section for a reaction from a provided n rxn xs library file
- `calc_one_group_nrxn_xs_dchain` : provided a neutron flux, reaction, and library file, determine 1-grp nrxn xs
### For handling nuclide names and identities with DCHAIN
- `Dname_to_ZAM` : converts a DCHAIN-formatted nuclide name to a ZZZAAAM number
- `ZAM_to_Dname` : converts a ZZZAAAM number to a DCHAIN-formatted nuclide name
- `Dname_to_Latex` : converts a DCHAIN-formatted nuclide name to pretty LaTeX formatting
- `nuclide_plain_str_to_Dname` : converts a plaintext string for a nuclide to a DCHAIN-formatted nuclide name string
### Other
- `parse_DCHAIN_act_file_legacy` : legacy version of parse_DCHAIN_act_file from before error implementation
- `generate_nuclide_time_profiles_legacy` : legacy version of generate_nuclide_time_profiles from before error implementation
- `find` : return index of the first instance of a value in a list
- `Element_Z_to_Sym` : returns elemental symbol provided the atomic number Z
- `Element_Sym_to_Z` : returns an atomic number Z provided the elemental symbol
- `Element_ZorSym_to_name` : returns a string of the name of an element provided its atomic number Z or symbol
- `Element_ZorSym_to_mass` : returns the average atomic mass of an element provided its atomic number Z or symbol
- `nuclide_to_Latex_form` : form a LaTeX-formatted string of a nuclide provided its information
- `nuclide_plain_str_to_latex_str` : convert a plaintext string for a nuclide to a LaTeX formatted raw string
- `nuclide_plain_str_ZZZAAAM` : convert a plaintext string for a nuclide to an integer ZZZAAAM value
- `time_str_to_sec_multiplier` : determine multiplier to convert a time unit to seconds
- `seconds_to_dhms` : convert a time in seconds to a string of human-relatable time units
- `seconds_to_ydhms` : convert a time in seconds to a string of human-relatable time units (also with years)
'''
import numpy as np
import os
import sys
import matplotlib.pyplot as plt
import time
import re
import bisect
import unicodedata as ud
try:
from munch import *
except:
pass
try:
from Hunters_tools import fancy_plot
Hunters_tools_is_available = True
except:
Hunters_tools_is_available = False
def process_dchain_simulation_output(simulation_folder_path,simulation_basename,dtrk_filepath=None,dyld_filepath=None,process_DCS_file=False):
'''
Description:
This is intended to be a single master function for processing DCHAIN output.
Dependencies:
from munch import *
Inputs:
- `simulation_folder_path` = text string of path to folder containing simulation output (should end with forward slash `/` or backslash `\`)
- `simulation_basename` = common string of the DCHAIN simulations; output files are named THIS_NAME.*
- `dtrk_filepath` = file path to \*.dtrk file, only necessary if it has a different basename and there are multiple \*.dtrk files in the folder
- `dyld_filepath` = file path to \*.dyld files, only necessary if it has a different basename and there are multiple \*.dyld files in the folder
- `process_DCS_file` (optional) = Boolean variable specifying whether the DCS file should be processed too. (D=False)
Outputs:
- `dchain_output` = a dictionary object containing all information from DCHAIN's output files. See the keys breakdown below.
Technically, it tries to return a "munchify" object which can be used both exactly like a dictionary but also
provides attribute-style access like a namedtuple or Class object such as `dchain_output.time.of_EOB_sec` rather
than the dictionary style `dchain_output['time']['of_EOB_sec']`
dchain_output dictionary structure:
--------
# Notation for output array dimensions
# R regions
# T time steps
# N max number of nuclides found in a single region
# E number of gamma energy bins
# le10 for top 10 lists, a number <= 10
{
dchain_output = {
'time':{ # ~ Time information
'from_start_sec' # [T] list of times from start time [sec]
'from_EOB_sec' # [T] times from end of final bombardment [sec]
'of_EOB_sec' # scalar time of end of final bombardment [sec]
}
'region':{ # ~ Information which only varies with region
'numbers' # [R] region numbers
'number' # [R] region numbers
'irradiation_time_sec' # [R] irradiation time per region
'volume' # [R] volume in [cc] per region
'neutron_flux' # [R] neutron flux in [n/cm^2/s] per region
'beam_power_MW' # [R] beam power in [MW] per region
'beam_energy_GeV' # [R] beam energy in [GeV] per region
'beam_current_mA' # [R] beam current in [mA] per region
}
'nuclides':{ # ~ Main nuclide results from *.act file
'names' # [R][N] names of nuclides produced in each region
'TeX_names' # [R][N] LaTeX-formatted names of nuclides produced
'ZZZAAAM' # [R][N] ZZZAAAM values (=10000Z+10A+M) of nuclides
# (ground state m=0, metastable m=1,2,etc.)
'half_life' # [R][N] half lives of nuclides produced [sec]
'inventory':{'value' # [R][T,N] atoms [#/cc]
'error'} # [R][T,N] atoms [#/cc]
'activity':{'value' # [R][T,N] activity [Bq/cc]
'error'} # [R][T,N] activity [Bq/cc]
'dose_rate':{'value' # [R][T,N] dose-rate [uSv/h*m^2]
'error'} # [R][T,N] dose-rate [uSv/h*m^2]
'decay_heat':{
'total':{'value' # [R][T,N] total decay heat [W/cc]
'error'} # [R][T,N] total decay heat [W/cc]
'beta':{'value' # [R][T,N] beta decay heat [W/cc]
'error'} # [R][T,N] beta decay heat [W/cc]
'gamma':{'value' # [R][T,N] gamma decay heat [W/cc]
'error'} # [R][T,N] gamma decay heat [W/cc]
'alpha':{'value' # [R][T,N] alpha decay heat [W/cc]
'error'} # [R][T,N] alpha decay heat [W/cc]
}
'column_headers' # Length 7 list of the *.act columns' descriptions
'total':{ # ~ Total values summed over all nuclides
'activity':{'value' # [R][T] total activity [Bq/cc]
'error'} # [R][T] total activity [Bq/cc]
'decay_heat':{'value' # [R][T] total decay heat [W/cc]
'error'} # [R][T] total decay heat [W/cc]
'beta_heat':{'value' # [R][T] total beta decay heat [W/cc]
'error'} # [R][T] total beta decay heat [W/cc]
'gamma_heat':{'value' # [R][T] total gamma decay heat [W/cc]
'error'} # [R][T] total gamma decay heat [W/cc]
'alpha_heat':{'value' # [R][T] total alpha decay heat [W/cc]
'error'} # [R][T] total alpha decay heat [W/cc]
'activated_atoms':{'value' # [R][T] total activated atoms [#/cc]
'error'} # [R][T] total activated atoms [#/cc]
'gamma_dose_rate':{'value' # [R][T] total gamma dose rate [uSV/h*m^2]
'error'} # [R][T] total gamma dose rate [uSV/h*m^2]
}
}
'gamma':{ # ~ Gamma spectra and totals
'spectra':{
'group_number' # [R][T,E] group number
'E_lower' # [R][T,E] bin energy lower-bound [MeV]
'E_upper' # [R][T,E] bin energy upper-bound [MeV]
'flux':{'value' # [R][T,E] flux [#/s/cc]
'error'} # [R][T,E] flux [#/s/cc]
'energy_flux':{'value' # [R][T,E] energy flux [MeV/s/cc]
'error'} # [R][T,E] energy flux [MeV/s/cc]
}
'total_flux':{'value' # [R][T] total gamma flux [#/s/cc]
'error'} # [R][T] total gamma flux [#/s/cc]
'total_energy_flux':{'value' # [R][T] total gamma energy flux [MeV/s/cc]
'error'} # [R][T] total gamma energy flux [MeV/s/cc]
'annihilation_flux':{'value' # [R][T] annihilation gamma flux [#/s/cc]
'error'} # [R][T] annihilation gamma flux [#/s/cc]
'current_underflow':{'value' # [R][T] gamma current underflow [#/s]
'error'} # no error reported
'current_overflow':{'value' # [R][T] gamma current overflow [#/s]
'error'} # no error reported
}
'top10':{ # ~ Top 10 lists from *.act file
'activity':{
'rank' # [R][T,le10] rank
'nuclide' # [R][T,le10] nuclide name
'value' # [R][T,le10] activity [Bq/cc]
'error' # [R][T,le10] activity [Bq/cc]
'percent' # [R][T,le10] percent of total activity
}
'decay_heat':{
'rank' # [R][T,le10] rank
'nuclide' # [R][T,le10] nuclide name
'value' # [R][T,le10] decay heat [W/cc]
'error' # [R][T,le10] decay heat [W/cc]
'percent' # [R][T,le10] percent of total decay heat
}
'gamma_dose':{
'rank': # [R][T,le10] rank
'nuclide' # [R][T,le10] nuclide name
'value' # [R][T,le10] dose-rate [uSv/h*m^2]
'error' # [R][T,le10] dose-rate [uSv/h*m^2]
'percent' # [R][T,le10] percent of total gamma dose rate
}
}
'number_of':{ # ~ Maximum values of R, T, N, and E
'regions' # R = total number of regions
'time_steps' # T = total number of time steps
'max_nuclides_in_any_region' # N = maximum unique nuclides found in any region
'gamma_energy_bins' # E = number of gamma energy bins (default=42)
}
}
if process_dtrk_file:
dchain_output.update({
'neutron':{ # ~ Neutron spectra and totals
'spectra':{ # - Actual values used in DCHAIN
'E_lower' # [R][E] bin energy lower-bound [MeV]
'E_upper' # [R][E] bin energy upper-bound [MeV]
'flux':{'value' # [R][E] neutron flux [#/s/cm^2]
'error'} # [R][E] neutron flux [#/s/cm^2]
}
'total_flux':{'value' # [R] total neutron flux [#/s/cm^2]
'error'} # [R] total neutron flux [#/s/cm^2]
'unit_spectra':{ # - Flux per unit source particle
'E_lower' # [R][E] bin energy lower-bound [MeV]
'E_upper' # [R][E] bin energy upper-bound [MeV]
'flux':{'value' # [R][E] neutron flux [#/s/cm^2/s.p.]
'error'} # [R][E] neutron flux [#/s/cm^2/s.p.]
}
}
})
if process_dyld_files:
dchain_output.update({
'yields':{ # ~ Yield spectra
'all_names' # [N] names of all nuclides produced
'names' # [R][N] names of nuclides produced in each region
'TeX_names' # [R][N] LaTeX-formatted names of nuclides produced
'ZZZAAAM' # [R][N] ZZZAAAM values (=10000Z+10A+M) of nuclides
# (ground state m=0, metastable m=1,2,etc.)
'rate':{ # - Actual values used in DCHAIN (100% beam power)
'value' # [R][E] nuclide yield rate [#/s/cm^3]
'error' # [R][E] nuclide yield rate [#/s/cm^3]
}
'unit_spectra':{ # - Yields per unit source particle
'value' # [R][E] nuclide yield rate [#/s.p.]
'error' # [R][E] nuclide yield rate [#/s.p.]
}
}
})
if process_DCS_file: # add extra information
# Notation for output array dimensions
# R (n_reg) regions
# Td (ntsteps) time steps in DCS file (usually differs from that of *.act file!)
# Nd (nnuc_max) max number of nuclides (this index differs from the *.act N index)
# C (chni_max) maximum index of relevant chains
# L (chln_max) maximum number of links per chain
dchain_output.update({
'DCS':{
'time':{
'from_start_sec' # [Td] list of times from start time [sec]
'from_EOB_sec' # [Td] times from end of final bombardment [sec]
'of_EOB_sec' # scalar time of end of final bombardment [sec]
}
'number_of':{ # ~ Maximum values of R, Td, Nd, C, and L
'regions' # R = total number of regions
'time_steps' # Td = total number of time steps
'max_nuclides' # Nd = max number of end nuclides in any time step
'max_number_of_chains' # C = highest index of a relevant chain found
'max_chain_length' # L = max number of links (nuclides) in any chain
}
'end_nuclide':{ # ~ Informtaion on nuclides ending each chain
'names' # [R][Td,Nd] nuclide names
'inventory':{
'N_previous' # [R][Td,Nd,C] N in previous time step [atoms/cc]
'N_now' # [R][Td,Nd,C] N in current time step [atoms/cc]
'dN' # [R][Td,Nd,C] change in N of end nuclide from
# prev. to current time step [atoms/cc]
}
'activity':{
'A_previous' # [R][Td,Nd,C] A in previous time step [Bq/cc]
'A_now' # [R][Td,Nd,C] A in the current time step [Bq/cc]
'dA' # [R][Td,Nd,C] change in A of end nuclide from
# prev. to current time step [Bq/cc]
}
}
'chains':{ # ~ Chains, links, and their contributions
'indices_of_printed_chains' # [R][Td,Nd] list of chain indices printed to
# *.dcs, valid values of C index
'length' # [R][Td,Nd,C] length of listed chain, L max index
'link_nuclides' # [R][Td,Nd,C,L] strings of nuclides in each chain
'link_decay_modes' # [R][Td,Nd,C,L] strings of decay modes each link
# undergoes to produce the next link
'link_dN':{ # (only filled if values in file, 'None' otherwise)
'beam' # [R][Td,Nd,C,L] beam contribution to dN per link
'decay_nrxn' # [R][Td,Nd,C,L] decay/neutron rxn dN contribution
'total' # [R][Td,Nd,C,L] total contribution to dN per link
}
}
'relevant_nuclides':{ # ~ A vs t of nuclides over relevancy threshold
'names' # [R] list of relevant nuclides per region
'times' # [R][Td,Nd] time [s]
'inventory' # [R][Td,Nd] inventory [atm/cc]
'activity' # [R][Td,Nd] activity [Bq/cc]
}
}
})
'''
global start
try:
start_time = start
except:
start_time = time.time()
start = start_time
if simulation_basename[-3:] == '.in': simulation_basename = simulation_basename[:-3]
simulation_file_basic_path = simulation_folder_path + simulation_basename # only need to add output file extension
act_file = simulation_file_basic_path + '.act'
dcs_file = simulation_file_basic_path + '.dcs'
process_dtrk_file = True
if dtrk_filepath: # DTRK file manually provided
dtrk_file = dtrk_filepath
if not os.path.exists(dtrk_file):
print(' Provided .dtrk file could not be found: {}'.format(dtrk_filepath))
process_dtrk_file = False
else: # automatically find DTRK file
dtrk_file = simulation_file_basic_path + '.dtrk'
if not os.path.exists(dtrk_file):
# look for any files with the .dtrk extension in the simulation folder path
valid_files = []
valid_filepaths = []
for file in os.listdir(simulation_folder_path):
if file.endswith(".dtrk"):
valid_files.append(file)
valid_filepaths.append(os.path.join(simulation_folder_path, file))
if len(valid_files)>0:
print(' Could not find default .dtrk file {}, using {} in same directory instead.'.format(simulation_basename + '.dtrk',valid_files[0]))
dtrk_file = valid_filepaths[0]
else:
print(' No .dtrk files could not be found in provided simulation folder: {}'.format(simulation_folder_path))
process_dtrk_file = False
if process_dtrk_file:
neutron_flux, dtrk_metadata = parse_dtrk_file(dtrk_file,return_metadata=True)
process_dyld_file = True
if dyld_filepath: # dyld file manually provided
dyld_file = dyld_filepath
if not os.path.exists(dyld_file):
print(' Provided .dyld file could not be found: {}'.format(dyld_filepath))
process_dyld_file = False
else: # automatically find dyld file
dyld_file = simulation_file_basic_path + '.dyld'
if not os.path.exists(dyld_file):
# look for any files with the .dyld extension in the simulation folder path
valid_files = []
valid_filepaths = []
for file in os.listdir(simulation_folder_path):
if file.endswith(".dyld"):
valid_files.append(file)
valid_filepaths.append(os.path.join(simulation_folder_path, file))
if len(valid_files)>0:
print(' Could not find default .dyld file {}, using {} in same directory instead.'.format(simulation_basename + '.dyld',valid_files[0]))
dyld_file = valid_filepaths[0]
else:
print(' No .dyld files could not be found in provided simulation folder: {}'.format(simulation_folder_path))
process_dyld_file = False
print('{:<50} ({:0.2f} seconds elapsed)'.format(' Parsing DCHAIN activation file...',time.time()-start))
parse_DCHAIN_act_file_OUTPUT = parse_DCHAIN_act_file(act_file)
reg_nos = parse_DCHAIN_act_file_OUTPUT[0] # length R list of region numbers
time_list_sec = parse_DCHAIN_act_file_OUTPUT[1] # length T list of measurement times (in sec) from start of irradiation
time_list_sec_after_EOB = parse_DCHAIN_act_file_OUTPUT[2] # length T list of measurement times (in sec) from end of last irradiation
irradiation_end_t = parse_DCHAIN_act_file_OUTPUT[3] # time of end of irradiation (in sec)
nuclides_produced = parse_DCHAIN_act_file_OUTPUT[4] # NumPy array of dimension RxTxNx11x2 of nuclide table data (N=max recorded table lenth) (last index 0=value, 1=abs error) [0='nuclide',1='atoms [#/cc]',2='activity [Bq/cc]',3='activity [Bq]',4='rate [%]',5='beta decay heat [W/cc]',6='gamma decay heat [W/cc]',7='alpha decay heat [W/cc]',8='total decay heat [W/cc]',9='half life [s]',10='dose-rate [uSv/h*m^2]']
gamma_spectra = parse_DCHAIN_act_file_OUTPUT[5] # NumPy array of dimension RxTxEx5x2 of gamma spectrum table data (last index 0=value, 1=abs error) [0='group number',1='bin energy lower-bound [MeV]',2='bin energy upper-bound [MeV]',3='flux [#/s/cc]',4='energy flux [MeV/s/cc]']
top10_lists = parse_DCHAIN_act_file_OUTPUT[6] # NumPy array of dimension RxTxNx12x2 of top-10 list table data (last index 0=value, 1=abs error) [0='rank',1='nuclide - Activity ranking',2='activity [Bq/cc]',3='activity [Bq]',4='rate [%]',5='nuclide - Decay heat ranking',6='decay heat [W/cc]',7='decay heat [W]',8='rate [%]',9='nuclide - Dose rate ranking',10='dose-rate [uSv/h*m^2]',11='rate [%]']
column_headers = parse_DCHAIN_act_file_OUTPUT[7] # List containing 3 lists of column headers for the preceding three NumPy arrays
summary_info = parse_DCHAIN_act_file_OUTPUT[8] # list of the below lists/arrays of summary information
r_summary_info = summary_info[0] # NumPy array of dimension Rx7 of region-specific summary info [0='region number',1='irradiation time [s]',2='region volume [cc]',3='neutron flux [n/cm^2/s]',4='beam power [MW]',5='beam energy [GeV]',6='beam current [mA]']
r_summary_info_description = summary_info[1] # list of length 7 containing descriptions of the above items [0='region number',1='irradiation time [s]',2='region volume [cc]',3='neutron flux [n/cm^2/s]',4='beam power [MW]',5='beam energy [GeV]',6='beam current [mA]']
rt_summary_info = summary_info[2] # NumPy array of dimension RxTx12x2 of region and time-specific summary info (last index 0=value, 1=abs error) [0='total gamma flux [#/s/cc]',1='total gamma energy flux [MeV/s/cc]',2='annihilation gamma flux [#/s/cc]',3='gamma current underflow [#/s]',4='gamma current overflow [#/s]',5='total activity [Bq/cc]',6='total decay heat [W/cc]',7='beta decay heat [W/cc]',8='gamma decay heat [W/cc]',9='alpha decay heat [W/cc]',10='activated atoms [#/cc]',11='total gamma dose rate [uSV/h*m^2]']
rt_summary_info_description = summary_info[3] # list of length 12 containing descriptions of the above items [0='total gamma flux [#/s/cc]',1='total gamma energy flux [MeV/s/cc]',2='annihilation gamma flux [#/s/cc]',3='gamma current underflow [#/s]',4='gamma current overflow [#/s]',5='total activity [Bq/cc]',6='total decay heat [W/cc]',7='beta decay heat [W/cc]',8='gamma decay heat [W/cc]',9='alpha decay heat [W/cc]',10='activated atoms [#/cc]',11='total gamma dose rate [uSV/h*m^2]']
print('{:<50} ({:0.2f} seconds elapsed)'.format(' Restructuring nuclide data table array...',time.time()-start))
generate_nuclide_time_profiles_OUTPUT = generate_nuclide_time_profiles(nuclides_produced)
nuclide_names = generate_nuclide_time_profiles_OUTPUT[0] # List of length R of lists containing names of nuclides produced in each region
LaTeX_nuclide_names = generate_nuclide_time_profiles_OUTPUT[1] # List of length R of lists containing LaTeX-formatted names of nuclides produced in each region
nuclide_ZAM_vals = generate_nuclide_time_profiles_OUTPUT[2] # List of length R of lists containing ZZZAAAM values (=10000*Z+10*A+M) of nuclides produced in each region (ground state m=0, metastable m=1,2,etc.)
nuclide_half_lives = generate_nuclide_time_profiles_OUTPUT[3] # List of length R of lists containing half lives of nuclides produced in each region (in seconds)
nuclide_info = generate_nuclide_time_profiles_OUTPUT[4] # List of length R of NumPy arrays of dimension TxNx7x2 of nuclide info (last index 0=value, 1=abs error) [0='atoms [#/cc]',1='activity [Bq/cc]','2=beta decay heat [W/cc]','3=gamma decay heat [W/cc]','4=alpha decay heat [W/cc]','5=total decay heat [W/cc]','6=dose-rate [uSv/h*m^2]']
nuclide_info_headers = generate_nuclide_time_profiles_OUTPUT[5] # List of length 7 containing text descriptions of the 7 columns of the info arrays [0='atoms [#/cc]',1='activity [Bq/cc]','2=beta decay heat [W/cc]','3=gamma decay heat [W/cc]','4=alpha decay heat [W/cc]','5=total decay heat [W/cc]','6=dose-rate [uSv/h*m^2]']
if process_dyld_file:
if process_dtrk_file:
if dtrk_metadata[0]=='dchain':
iredufmt=1
else: # dtrk_metadata[0]=='eng'
iredufmt=0
else:
iredufmt=0
yields, nuclide_names_yld = parse_dyld_files(dyld_file,iredufmt=iredufmt)
# Now reformat for more user-friendly output values
# regionwise values
beam_fluxs = (6.2415064e15)*r_summary_info[:,6] # particles/sec (converted from mA)
reg_vols = r_summary_info[:,2]
nregs,nnuc = np.shape(yields)[0],np.shape(yields)[1]
reg_yld_names = []
reg_yld_texnames = []
reg_yld_zam = []
yield_values_by_reg = [[],[],[],[]] # yield, yield abs err, unit yield, unit yield abs err
for ri in range(nregs):
for ni in range(nnuc):
if ni==0:
reg_yld_names.append([])
reg_yld_texnames.append([])
reg_yld_zam.append([])
for j in range(4):
yield_values_by_reg[j].append([])
if yields[ri,ni,0] != 0.0:
reg_yld_names[-1].append(nuclide_names_yld[ni])
reg_yld_texnames[-1].append(Dname_to_Latex(nuclide_names_yld[ni]))
reg_yld_zam[-1].append(Dname_to_ZAM(nuclide_names_yld[ni]))
yield_values_by_reg[0][-1].append(beam_fluxs[ri]*yields[ri,ni,0]/reg_vols[ri])
yield_values_by_reg[1][-1].append(beam_fluxs[ri]*yields[ri,ni,1]/reg_vols[ri])
yield_values_by_reg[2][-1].append(yields[ri,ni,0])
yield_values_by_reg[3][-1].append(yields[ri,ni,1])
if process_DCS_file:
# Control parameters
relevancy_threshold=0.01 # fraction of total activity an isotope must be at any time step in DCS file to be placed in the "relevant" array
fcn_out = parse_DCS_file_from_DCHAIN(dcs_file,relevancy_threshold=relevancy_threshold)
# Notation for output array dimensions
# R (n_reg) regions
# T (ntsteps) time steps
# N (nnuc_max) max number of nuclides
# C (chni_max) maximum index of relevant chains
# L (chln_max) maximum number of links per chain
inventory = fcn_out[0] # universal columns of DCS file [R,T,N,C,vi], vi: 0=N_i-1/V, 1=dN/V, 2=N_i/V, 3=A_i/V, 4=A_i
l_chains = fcn_out[1] # [R,T,N,C], length of listed chain
prod_nuc = fcn_out[2] # [R,T,N], strings of the nuclide being produced
chn_indx = fcn_out[3] # [R,T,N], lists of the chain indices printed
link_nuc = fcn_out[4] # [R,T,N,C,L], strings of the nuclides in each chain
decay_mode = fcn_out[5] # [R,T,N,C,L], strings of the decay modes each link undergoes to produce the next link
link_dN_info=fcn_out[6] # [R,T,N,C,L,di], extra dN info di: 0=dN_Beam, 1=dN_Decay/nrxn, 2=dN_Total (only generated if these values are found in file, 'None' otherwise)
end_of_irradiation_time = fcn_out[7] # time of end of final irradiation step [seconds]
notable_nuclides_names_by_region = fcn_out[8] # list of lists (one per region) containing the relevant nuclides per region
notable_nuclides_AvT_by_region = fcn_out[9] # list of arrays (one per region, [T,N_rlv-nuc,3]) containing the time[s]/inventory[atm/cc]/activity[Bq/cc] data of relevant nuclides
n_reg,ntsteps,nnuc_max,chni_max,chln_max = np.shape(decay_mode)
relevant_nuclides = notable_nuclides_names_by_region[0]
n_relevant_nuclides = len(relevant_nuclides)
relv_nuc_inv = notable_nuclides_AvT_by_region[0]
t_from_start = relv_nuc_inv[:,0,0]
t_after_irrad_sec = ((relv_nuc_inv[:,0,0]-end_of_irradiation_time))
nreg = len(reg_nos)
rilist = range(nreg)
#regionwise_gamma_spectra = [gamma_spectra[ri,:,:,:,:] for ri in range(nreg)]
#rw_totgflux_val = [rt_summary_info[ri,:,0,0] for ri in range(nreg)]
#rw_totgflux_ae = [rt_summary_info[ri,:,0,1] for ri in range(nreg)]
#rw_totegflux = [rt_summary_info[ri,:,1,:] for ri in range(nreg)]
# Notation for output array dimensions
# R regions
# T time steps
# N max number of nuclides found in a single region
# E number of gamma energy bins
# le10 for top 10 lists, a number <= 10
dchain_output = {
'time':{ # ~ Time information
'from_start_sec':time_list_sec, # [T] list of times from start time [sec]
'from_EOB_sec':time_list_sec_after_EOB, # [T] list of times from end of final bombardment [sec]
'of_EOB_sec':irradiation_end_t, # scalar time marking end of final bombardment [sec]
},
'region':{ # ~ Information which only varies with region
'numbers':reg_nos, # [R] list of all region numbers
'number': r_summary_info[:,0], # [R] list of all region numbers
'irradiation_time_sec': r_summary_info[:,1], # [R] list of irradiation time per region
'volume': r_summary_info[:,2], # [R] list of volume in cc per region
'neutron_flux': r_summary_info[:,3], # [R] list of neutron flux in n/cm^2/s per region
'beam_power_MW': r_summary_info[:,4], # [R] list of beam power in MW per region
'beam_energy_GeV': r_summary_info[:,5], # [R] list of beam energy in GeV per region
'beam_current_mA': r_summary_info[:,6] # [R] list of beam current in mA per region
},
'nuclides':{ # ~ Main nuclide results from *.act file
'names':nuclide_names, # [R][N] list of lists containing names of nuclides produced in each region
'TeX_names':LaTeX_nuclide_names, # [R][N] list of lists containing LaTeX-formatted names of nuclides produced in each region
'ZZZAAAM':nuclide_ZAM_vals, # [R][N] list of lists containing ZZZAAAM values (=10000*Z+10*A+M) of nuclides produced in each region (ground state m=0, metastable m=1,2,etc.)
'half_life':nuclide_half_lives, # [R][N] list of lists containing half lives of nuclides produced in each region (in seconds)
'inventory':{'value':[nuclide_info[ri][:,:,0,0] for ri in rilist], # [R][T,N] atoms [#/cc]
'error':[nuclide_info[ri][:,:,0,1] for ri in rilist]}, # [R][T,N] atoms [#/cc]
'activity':{'value':[nuclide_info[ri][:,:,1,0] for ri in rilist], # [R][T,N] activity [Bq/cc]
'error':[nuclide_info[ri][:,:,1,1] for ri in rilist]}, # [R][T,N] activity [Bq/cc]
'dose_rate':{'value':[nuclide_info[ri][:,:,6,0] for ri in rilist], # [R][T,N] dose-rate [uSv/h*m^2]
'error':[nuclide_info[ri][:,:,6,1] for ri in rilist]}, # [R][T,N] dose-rate [uSv/h*m^2]
'decay_heat':{
'total':{'value':[nuclide_info[ri][:,:,5,0] for ri in rilist], # [R][T,N] total decay heat [W/cc]
'error':[nuclide_info[ri][:,:,5,1] for ri in rilist]}, # [R][T,N] total decay heat [W/cc]
'beta':{'value':[nuclide_info[ri][:,:,2,0] for ri in rilist], # [R][T,N] beta decay heat [W/cc]
'error':[nuclide_info[ri][:,:,2,1] for ri in rilist]}, # [R][T,N] beta decay heat [W/cc]
'gamma':{'value':[nuclide_info[ri][:,:,3,0] for ri in rilist], # [R][T,N] gamma decay heat [W/cc]
'error':[nuclide_info[ri][:,:,3,1] for ri in rilist]}, # [R][T,N] gamma decay heat [W/cc]
'alpha':{'value':[nuclide_info[ri][:,:,4,0] for ri in rilist], # [R][T,N] alpha decay heat [W/cc]
'error':[nuclide_info[ri][:,:,4,1] for ri in rilist]}, # [R][T,N] alpha decay heat [W/cc]
},
'column_headers':nuclide_info_headers, # List of length 7 containing text descriptions of the 7 columns of the info arrays [0='atoms [#/cc]',1='activity [Bq/cc]','2=beta decay heat [W/cc]','3=gamma decay heat [W/cc]','4=alpha decay heat [W/cc]','5=total decay heat [W/cc]','6=dose-rate [uSv/h*m^2]']
'total':{ # ~ Total values summed over all nuclides
'activity':{'value':[rt_summary_info[ri,:,5,0] for ri in rilist] , # [R][T] total activity [Bq/cc]
'error':[rt_summary_info[ri,:,5,1] for ri in rilist]}, # [R][T] total activity [Bq/cc]
'decay_heat':{'value':[rt_summary_info[ri,:,6,0] for ri in rilist] , # [R][T] total decay heat [W/cc]
'error':[rt_summary_info[ri,:,6,1] for ri in rilist]}, # [R][T] total decay heat [W/cc]
'beta_heat':{'value':[rt_summary_info[ri,:,7,0] for ri in rilist] , # [R][T] total beta decay heat [W/cc]
'error':[rt_summary_info[ri,:,7,1] for ri in rilist]}, # [R][T] total beta decay heat [W/cc]
'gamma_heat':{'value':[rt_summary_info[ri,:,8,0] for ri in rilist] , # [R][T] total gamma decay heat [W/cc]
'error':[rt_summary_info[ri,:,8,1] for ri in rilist]}, # [R][T] total gamma decay heat [W/cc]
'alpha_heat':{'value':[rt_summary_info[ri,:,9,0] for ri in rilist] , # [R][T] total alpha decay heat [W/cc]
'error':[rt_summary_info[ri,:,9,1] for ri in rilist]}, # [R][T] total alpha decay heat [W/cc]
'activated_atoms':{'value':[rt_summary_info[ri,:,10,0] for ri in rilist], # [R][T] total activated atoms [#/cc]
'error':[rt_summary_info[ri,:,10,1] for ri in rilist]}, # [R][T] total activated atoms [#/cc]
'gamma_dose_rate':{'value':[rt_summary_info[ri,:,11,0] for ri in rilist], # [R][T] total gamma dose rate [uSV/h*m^2]
'error':[rt_summary_info[ri,:,11,1] for ri in rilist]} # [R][T] total gamma dose rate [uSV/h*m^2]
}
},
'gamma':{ # ~ Gamma spectra and totals
'spectra':{
'group_number':[gamma_spectra[ri,:,:,0,0] for ri in rilist], # [R][T,E] group number
'E_lower':[gamma_spectra[ri,:,:,1,0] for ri in rilist], # [R][T,E] bin energy lower-bound [MeV]
'E_upper':[gamma_spectra[ri,:,:,2,0] for ri in rilist], # [R][T,E] bin energy upper-bound [MeV]
'flux':{'value':[gamma_spectra[ri,:,:,3,0] for ri in rilist], # [R][T,E] flux [#/s/cc]
'error':[gamma_spectra[ri,:,:,3,0]*gamma_spectra[ri,:,:,3,1] for ri in rilist]}, # [R][T,E] flux [#/s/cc]
'energy_flux':{'value':[gamma_spectra[ri,:,:,4,0] for ri in rilist], # [R][T,E] energy flux [MeV/s/cc]
'error':[gamma_spectra[ri,:,:,4,0]*gamma_spectra[ri,:,:,4,1] for ri in rilist]} # [R][T,E] energy flux [MeV/s/cc]
},
'total_flux':{'value':[rt_summary_info[ri,:,0,0] for ri in rilist], # [R][T] total gamma flux [#/s/cc]
'error':[rt_summary_info[ri,:,0,1] for ri in rilist]}, # [R][T] total gamma flux [#/s/cc]
'total_energy_flux':{'value':[rt_summary_info[ri,:,1,0] for ri in rilist] , # [R][T] total gamma energy flux [MeV/s/cc]
'error':[rt_summary_info[ri,:,1,1] for ri in rilist]}, # [R][T] total gamma energy flux [MeV/s/cc]
'annihilation_flux':{'value':[rt_summary_info[ri,:,2,0] for ri in rilist] , # [R][T] annihilation gamma flux [#/s/cc]
'error':[rt_summary_info[ri,:,2,1] for ri in rilist]}, # [R][T] annihilation gamma flux [#/s/cc]
'current_underflow':{'value':[rt_summary_info[ri,:,3,0] for ri in rilist] , # [R][T] gamma current underflow [#/s]
'error':[rt_summary_info[ri,:,3,1] for ri in rilist]}, # no error reported
'current_overflow':{'value':[rt_summary_info[ri,:,4,0] for ri in rilist], # [R][T] gamma current overflow [#/s]
'error':[rt_summary_info[ri,:,4,1] for ri in rilist]} # no error reported
},
'top10':{ # ~ Top 10 lists from *.act file
'activity':{
'rank':[top10_lists[ri,:,:,0,0] for ri in rilist], # [R][T,le10] rank
'nuclide':[top10_lists[ri,:,:,1,0] for ri in rilist], # [R][T,le10] nuclide name
'value':[top10_lists[ri,:,:,2,0] for ri in rilist], # [R][T,le10] activity [Bq/cc]
'error':[top10_lists[ri,:,:,2,1] for ri in rilist], # [R][T,le10] activity [Bq/cc]
'percent':[top10_lists[ri,:,:,4,0] for ri in rilist], # [R][T,le10] percent of total activity
},
'decay_heat':{
'rank':[top10_lists[ri,:,:,0,0] for ri in rilist], # [R][T,le10] rank
'nuclide':[top10_lists[ri,:,:,5,0] for ri in rilist], # [R][T,le10] nuclide name
'value':[top10_lists[ri,:,:,6,0] for ri in rilist], # [R][T,le10] decay heat [W/cc]
'error':[top10_lists[ri,:,:,6,1] for ri in rilist], # [R][T,le10] decay heat [W/cc]
'percent':[top10_lists[ri,:,:,8,0] for ri in rilist], # [R][T,le10] percent of total decay heat
},
'gamma_dose':{
'rank':[top10_lists[ri,:,:,0,0] for ri in rilist], # [R][T,le10] rank
'nuclide':[top10_lists[ri,:,:,9,0] for ri in rilist], # [R][T,le10] nuclide name
'value':[top10_lists[ri,:,:,10,0] for ri in rilist], # [R][T,le10] dose-rate [uSv/h*m^2]
'error':[top10_lists[ri,:,:,10,1] for ri in rilist], # [R][T,le10] dose-rate [uSv/h*m^2]
'percent':[top10_lists[ri,:,:,11,0] for ri in rilist], # [R][T,le10] percent of total gamma dose rate
}
},
'number_of':{ # ~ Maximum values of R, T, N, and E
'regions':nreg, # R = total number of regions
'time_steps':len(time_list_sec), # T = total number of time steps
'max_nuclides_in_any_region':np.shape(nuclides_produced)[2], # N = maximum unique nuclides found in any region
'gamma_energy_bins':np.shape(gamma_spectra)[2] # E = number of gamma energy bins (default=42)
}
}
if process_dtrk_file:
dflux_norm = []
for ri in rilist:
if np.sum(neutron_flux[ri,:,2]) != 0:
dflux_norm.append(r_summary_info[ri,3]/np.sum(neutron_flux[ri,:,2]))
else:
dflux_norm.append(0.0)
#dflux_norm = [r_summary_info[ri,3]/np.sum(neutron_flux[ri,:,2]) for ri in rilist] # normalize unit flux to total flux
dchain_output.update({
'neutron':{
'spectra':{ # Actual values used by DCHAIN for rate calcs
'E_lower':[neutron_flux[ri,:,0] for ri in rilist], # [R][E] bin energy lower-bound [MeV]
'E_upper':[neutron_flux[ri,:,1] for ri in rilist], # [R][E] bin energy upper-bound [MeV]
'flux':{'value':[neutron_flux[ri,:,2]*dflux_norm[ri] for ri in rilist], # [R][E] neutron flux [#/s/cm^2]
'error':[neutron_flux[ri,:,3]*dflux_norm[ri] for ri in rilist]}, # [R][E] neutron flux [#/s/cm^2]
},
'total_flux':{'value':[np.sum(neutron_flux[ri,:,2])*dflux_norm[ri] for ri in rilist], # [R] total neutron flux [#/s/cm^2]
'error':[np.sqrt(np.sum(neutron_flux[ri,:,3]**2))*dflux_norm[ri] for ri in rilist]}, # [R] total neutron flux [#/s/cm^2]
'unit_spectra':{ # Raw T-Track output from PHITS
'E_lower':[neutron_flux[ri,:,0] for ri in rilist], # [R][E] bin energy lower-bound [MeV]
'E_upper':[neutron_flux[ri,:,1] for ri in rilist], # [R][E] bin energy upper-bound [MeV]
'flux':{'value':[neutron_flux[ri,:,2] for ri in rilist], # [R][E] neutron flux [#/s/cm^2]
'error':[neutron_flux[ri,:,3] for ri in rilist]}, # [R][E] neutron flux [#/s/cm^2]
},
}
})
if process_dyld_file:
dchain_output.update({
'yields':{ # ~ Yield spectra
'all_names':nuclide_names_yld, # [N] names of nuclides produced in all regions
'names':reg_yld_names, # [R][N] names of nuclides produced in each region
'TeX_names':reg_yld_texnames, # [R][N] LaTeX-formatted names of nuclides produced
'ZZZAAAM':reg_yld_zam, # [R][N] ZZZAAAM values (=10000Z+10A+M) of nuclides
'rate':{'value':yield_values_by_reg[0], # [R][E] nuclide yield rate [#/s/cm^3]
'error':yield_values_by_reg[1]}, # [R][E] nuclide yield rate [#/s/cm^3]
'unit_rate':{'value':yield_values_by_reg[2], # [R][E] unit nuclide yield rate [#/s.p.]
'error':yield_values_by_reg[3]} # [R][E] unit nuclide yield rate [#/s.p.]
}
})
if process_DCS_file: # add extra information
# Notation for output array dimensions
# R (n_reg) regions
# Td (ntsteps) time steps in DCS file (usually different from that of ACT file!)
# Nd (nnuc_max) max number of nuclides (this index differs from the ACT N index)
# C (chni_max) maximum index of relevant chains
# L (chln_max) maximum number of links per chain
dchain_output.update({'DCS':{
'time':{
'from_start_sec':t_from_start, # [Td] list
'from_EOB_sec':t_after_irrad_sec, # [Td] list
'of_EOB_sec':irradiation_end_t # scalar
},
'number_of':{ # ~ Maximum values of R, Td, Nd, C, and L
'regions':n_reg, # R = total number of regions
'time_steps':ntsteps, # Td = total number of time steps
'max_nuclides':nnuc_max, # Nd = maximum number of nuclides listed in a time step
'max_number_of_chains':chni_max, # C = highest index of a relevant chain found
'max_chain_length':chln_max # L = maximum number of links (nuclides) found in any chain
},
'end_nuclide':{
'names':[prod_nuc[ri,:,:] for ri in rilist], # [R][Td,Nd] nuclide names
'inventory':{
'N_previous':[inventory[ri,:,:,:,0] for ri in rilist], # [R][Td,Nd,C] inventory of end nuclide in previous time step [atoms/cc]
'N_now':[inventory[ri,:,:,:,2] for ri in rilist], # [R][Td,Nd,C] inventory of end nuclide in the current time step [atoms/cc]
'dN':[inventory[ri,:,:,:,1] for ri in rilist] # [R][Td,Nd,C] change in inventory of end nuclide from the previous to the current time step [atoms/cc]
},
'activity':{
'A_previous':[inventory[ri,:,:,:,0]*(inventory[ri,:,:,:,3]/inventory[ri,:,:,:,2]) for ri in rilist], # [R][Td,Nd,C] activity of end nuclide in previous time step [Bq/cc]
'A_now':[inventory[ri,:,:,:,3] for ri in rilist], # [R][Td,Nd,C] activity of end nuclide in the current time step [Bq/cc]
'dA':[inventory[ri,:,:,:,1]*(inventory[ri,:,:,:,3]/inventory[ri,:,:,:,2]) for ri in rilist] # [R][Td,Nd,C] change in activity of end nuclide from the previous to the current time step [Bq/cc]
}
},
'chains':{
'indices_of_printed_chains':[chn_indx[ri,:,:] for ri in rilist], # [R][Td,Nd] lists of the chain indices printed
'length':[l_chains[ri,:,:,:] for ri in rilist], # [R][Td,Nd,C] length of listed chain
'link_nuclides':[link_nuc[ri,:,:,:,:] for ri in rilist], # [R][Td,Nd,C,L] strings of the nuclides in each chain
'link_decay_modes':[decay_mode[ri,:,:,:,:] for ri in rilist], # [R][Td,Nd,C,L] strings of the decay modes each link undergoes to produce the next link
'link_dN':{
'beam':[None if link_dN_info==None else link_dN_info[ri,:,:,:,:,0] for ri in rilist], # [R][Td,Nd,C,L] beam contribution to dN from each link (only generated if these values are found in file, 'None' otherwise)
'decay_nrxn':[None if link_dN_info==None else link_dN_info[ri,:,:,:,:,1] for ri in rilist], # [R][Td,Nd,C,L] decay + neutron rxn contribution to dN from each link (only generated if these values are found in file, 'None' otherwise)
'total':[None if link_dN_info==None else link_dN_info[ri,:,:,:,:,2] for ri in rilist] # [R][Td,Nd,C,L] total contribution to dN from each link (only generated if these values are found in file, 'None' otherwise)
}
},
'relevant_nuclides':{
'names':notable_nuclides_names_by_region, # [R] list of relevant nuclides per region
'times':[notable_nuclides_AvT_by_region[ri][:,:,0] for ri in rilist], # [R][Td,Nd] time [s]
'inventory':[notable_nuclides_AvT_by_region[ri][:,:,1] for ri in rilist], # [R][Td,Nd] inventory [atm/cc]
'activity':[notable_nuclides_AvT_by_region[ri][:,:,2] for ri in rilist] # [R][Td,Nd] activity [Bq/cc]
}
}})
# https://github.com/Infinidat/munch
try:
dchain_output = munchify(dchain_output)
except:
print("munchify failed. Returned object is a conventional dictionary rather than a munchify object.")
return dchain_output
def parse_DCHAIN_act_file(act_file_path):
'''
Description:
This code parses the .act file generated by DCHAIN
Inputs:
- path to a DCHAIN-generated .act file
Outputs:
- length R list of region numbers
- length T list of measurement times (in sec) from start of irradiation
- time of end of irradiation (in sec)
- NumPy array of dimension RxTxNx11x2 of nuclide table data (N=max recorded table length)
- NumPy array of dimension RxTxEx5x2 of gamma spectrum table data (E=number of energy groups of gamma spectra)
- NumPy array of dimension RxTxNx12x2 of top-10 list table data
- List containing 3 lists of column headers for the preceding three NumPy arrays
- list of the below lists/arrays of summary information
+ NumPy array of dimension Rx7 of region-specific summary info:
Beam current, beam energy, beam power, total neutron flux, region volume, irradiation time, region number
+ list of length 7 containing descriptions of the above items
+ NumPy array of dimension RxTx12x2 of region and time-specific summary info
Rank, [nuclide, A/cc, A, %], [nuclide, P/cc, P, %], [nuclide, H, %] with values and absolute uncertainties
+ list of length 12 containing descriptions of the above items
'''
# Extract file info
f = open(act_file_path)
lines = f.readlines()
f.close()
# Parse file to determine number of regions
nreg = 0
reg_nos = []
for line in lines:
if 'region number' in line:
nreg += 1
reg_nos.append(int(line[21:31]))
# Parse file again to determine number of time steps
current_reg_no = -1
#irradiation_time = -1.0 # seconds
end_of_irradiation_time = -1.0 # seconds
ntimes = 0
time_strs = []
time_list_sec = [] # time steps in seconds
time_list_sec_after_EOB = [] # time steps in seconds after EOB
for line in lines:
#if 'irradiation time' in line: irradiation_time = float(line[21:31])*time_str_to_sec_multiplier(line[33])
if 'region number' in line: current_reg_no = int(line[21:31])
if current_reg_no != reg_nos[0]: continue # only read times from first region
if '--- output time ---' in line:
ntimes += 1
time_strs.append(line)
time_list_sec.append(float(line[40:53]))
time_list_sec_after_EOB.append(0.0)
if ('--- output time ---' in line) and ('after the last shutdown' in line):
time_list_sec_after_EOB[ntimes-1] = float(line[87:97])*time_str_to_sec_multiplier(line[99])
if end_of_irradiation_time == -1:
end_of_irradiation_time = float(line[21:31])*time_str_to_sec_multiplier(line[33]) - float(line[87:97])*time_str_to_sec_multiplier(line[99])
for ti in range(len(time_list_sec_after_EOB)):
if time_list_sec_after_EOB[ti]==0.0:
time_list_sec_after_EOB[ti] = time_list_sec[ti] - end_of_irradiation_time
# Extract "summary info" from file
ri = -1 # region index
ti = -1 # time index
r_summary_info = np.empty((nreg,7), dtype='object') # (regionwise) initialize Rx7 array
r_summary_info_description = ['region number','irradiation time [s]','region volume [cc]','neutron flux [n/cm^2/s]','beam power [MW]','beam energy [GeV]','beam current [mA]'] # (regionwise) initialize Rx7 array
'''
r_summary_info[i,j,k]
i = region number
j = category (see table below)
index meaning
0 region number
1 irradiation time [sec]
2 region volume [cc]
3 neutron flux [n/cm^2/s]
4 beam power [MW]
5 beam energy [GeV]
6 beam current [mA]
'''
rt_summary_info = np.empty((nreg,ntimes,12,2), dtype='object') # (region-and-timewise) initialize RxTx12x2 array
rt_summary_info_description = ['total gamma flux [#/s/cc]','total gamma energy flux [MeV/s/cc]','annihilation gamma flux [#/s/cc]','gamma current underflow [#/s]','gamma current overflow [#/s]','total activity [Bq/cc]','total decay heat [W/cc]','beta decay heat [W/cc]','gamma decay heat [W/cc]','alpha decay heat [W/cc]','activated atoms [#/cc]','total gamma dose rate [uSV/h*m^2]'] # (region-and-timewise) initialize RxTx12 array
'''
rt_summary_info[i,j,k,m]
i = region number
j = output time step
k = category (see table below)
m = value (k=0) or absolute uncertainty (k=1)
index meaning
0 total gamma flux [#/s/cc]
1 total gamma energy flux [MeV/s/cc]
2 annihilation gamma flux [#/s/cc]
3 gamma current underflow [#/s] (gammas below lowest energy bin)
4 gamma current overflow [#/s] (gammas above highest energy bin)
5 total activity [Bq/cc]
6 total decay heat [W/cc]
7 beta decay heat [W/cc]
8 gamma decay heat [W/cc]
9 alpha decay heat [W/cc]
10 activated atoms [#/cc]
11 total gamma dose rate [uSV/h*m^2]
'''
for li in range(len(lines)):
line = lines[li]
if 'region number' in line:
ri = find(int(line[21:31]),reg_nos)
# region-specific summary info
r_summary_info[ri,0] = int(line[21:31])
r_summary_info[ri,1] = float(lines[li-1][21:31])*time_str_to_sec_multiplier(lines[li-1][33])
r_summary_info[ri,2] = float(lines[li-2][21:31])
r_summary_info[ri,3] = float(lines[li-3][21:31])
r_summary_info[ri,4] = float(lines[li-4][21:31])
r_summary_info[ri,5] = float(lines[li-5][21:31])
r_summary_info[ri,6] = float(lines[li-6][21:31])
if '--- output time ---' in line:
ti = find(line,time_strs)
# gamma info specific to region and time
if 'total gamma-ray flux' in line:
rt_summary_info[ri,ti,0,0] = float(line[38:49])
rt_summary_info[ri,ti,1,0] = float(lines[li+1][38:49])
rt_summary_info[ri,ti,2,0] = float(lines[li+2][38:49])
rt_summary_info[ri,ti,0,1] = float(line[53:64])
rt_summary_info[ri,ti,1,1] = float(lines[li+1][53:64])
rt_summary_info[ri,ti,2,1] = float(lines[li+2][53:64])
if 'group limitation' in lines[li+3]:
rt_summary_info[ri,ti,3,0] = float(lines[li+3][91:101])
rt_summary_info[ri,ti,4,0] = float(lines[li+3][64:74])
else:
rt_summary_info[ri,ti,3,0] = 0.0
rt_summary_info[ri,ti,4,0] = 0.0
if 'no gamma-ray' in line:
rt_summary_info[ri,ti,0,0] = 0.0
rt_summary_info[ri,ti,1,0] = 0.0
rt_summary_info[ri,ti,2,0] = 0.0
rt_summary_info[ri,ti,0,1] = 0.0
rt_summary_info[ri,ti,1,1] = 0.0
rt_summary_info[ri,ti,2,1] = 0.0
rt_summary_info[ri,ti,3,0] = 0.0
rt_summary_info[ri,ti,4,0] = 0.0
# activation info specific to region and time
if 'total activity' in line:
rt_summary_info[ri,ti,5,0] = float(line[24:36])
rt_summary_info[ri,ti,6,0] = float(lines[li+1][24:36])
rt_summary_info[ri,ti,7,0] = float(lines[li+2][24:36])
rt_summary_info[ri,ti,8,0] = float(lines[li+3][24:36])
rt_summary_info[ri,ti,9,0] = float(lines[li+4][24:36])
rt_summary_info[ri,ti,10,0]= float(lines[li+5][24:36])
rt_summary_info[ri,ti,11,0]= float(lines[li+6][24:36])
rt_summary_info[ri,ti,5,1] = float(line[40:52])
rt_summary_info[ri,ti,6,1] = float(lines[li+1][40:52])
rt_summary_info[ri,ti,7,1] = float(lines[li+2][40:52])
rt_summary_info[ri,ti,8,1] = float(lines[li+3][40:52])
rt_summary_info[ri,ti,9,1] = float(lines[li+4][40:52])
rt_summary_info[ri,ti,10,1]= float(lines[li+5][40:52])
rt_summary_info[ri,ti,11,1]= float(lines[li+6][40:52])
summary_info = [r_summary_info, r_summary_info_description, rt_summary_info, rt_summary_info_description]
# Extract major "blocks" (nuclides, gamma spec, top10 list) for each time step in each region
act_block_text = np.empty((nreg,ntimes,3), dtype='object') # initialize RxTx3 array to hold character strings where final index 0=nuclides, 1=gamma-spec, and 2=top10-list
ri = -1 # region index
ti = -1 # time index
qi = -1 # quantity index - 0=nuclides, 1=gamma-spec, and 2=top10-list
max_array_len = [0,0,0] # maximum number of entries for a given quantity
current_array_len = [0,0,0] # current number of entries for a given quantity
for line in lines:
if 'region number' in line:
ri = find(int(line[21:31]),reg_nos)
if '--- output time ---' in line:
ti = find(line,time_strs)
qi = 0 # reset quantity index
if 'gamma-ray spectrum weighted by energy' in line:
qi = 1
if 'dominant nuclides (top 10)' in line:
qi = 2
if 'total' in line[:20] or line=='\n': # no longer reading info block
if current_array_len[qi] > max_array_len[qi]:
max_array_len[qi] = current_array_len[qi]
current_array_len[qi] = 0
qi = -1
if qi < 0: continue # not in region of interest
try:
act_block_text[ri,ti,qi] += line
except:
act_block_text[ri,ti,qi] = line
current_array_len[qi] += 1
header_len = [3,4,3] # number of lines present in table header
nuclides_produced = np.empty((nreg,ntimes,max_array_len[0]-header_len[0],11,2), dtype='object') # initialize RxTxNx11x2 array to hold nuclide information
gamma_spectra = np.empty((nreg,ntimes,max_array_len[1]-header_len[1], 5,2), dtype='object') # initialize RxTxNx5x2 array to hold gamma spec information
top10_lists = np.empty((nreg,ntimes,max_array_len[2]-header_len[2],12,2), dtype='object') # initialize RxTxNx12x2 array to hold top 10 list information
column_headers = [ [],[],[] ]
# Now, populate each array
# Nuclides produced
column_headers[0] = ['nuclide','atoms [#/cc]','activity [Bq/cc]','activity [Bq]','rate [%]','beta decay heat [W/cc]','gamma decay heat [W/cc]','alpha decay heat [W/cc]','total decay heat [W/cc]','half life [s]','dose-rate [uSv/h*m^2]']
for ri in range(nreg):
for ti in range(ntimes):
table_text = act_block_text[ri,ti,0].split('\n')
for ei in range(len(table_text)):
if ei < header_len[0]: continue # in header lines
ii = ei - header_len[0] # actual number index
line = table_text[ei]
if line=='' or line==None: continue # skip blank/nonexistent lines
rel_err = float(line[51:61])
nuclides_produced[ri,ti,ii,0,0] = line[3:9] # nuclide
nuclides_produced[ri,ti,ii,1,0] = float(line[12:23].replace(' ','0.0')) # atoms [#/cc]
nuclides_produced[ri,ti,ii,2,0] = float(line[25:36].replace(' ','0.0')) # activity [Bq/cc]
nuclides_produced[ri,ti,ii,3,0] = float(line[38:49].replace(' ','0.0')) # activity [Bq]
nuclides_produced[ri,ti,ii,4,0] = float(line[61:68].replace(' ','0.0')) # rate [%]
nuclides_produced[ri,ti,ii,5,0] = float(line[70:80].replace(' ','0.0')) # beta decay heat [W/cc]
nuclides_produced[ri,ti,ii,6,0] = float(line[81:91].replace(' ','0.0')) # gamma decay heat [W/cc]
nuclides_produced[ri,ti,ii,7,0] = float(line[92:102].replace(' ','0.0')) # alpha decay heat [W/cc]
nuclides_produced[ri,ti,ii,8,0] = float(line[103:113].replace(' ','0.0')) # total decay heat [W/cc]
nuclides_produced[ri,ti,ii,9,0] = float(line[116:126].replace('stable','0.0')) # half life [s]
if nuclides_produced[ri,ti,ii,9,0] == 0:
nuclides_produced[ri,ti,ii,10,0]= 0.0 # dose-rate [uSv/h*m^2]
else:
nuclides_produced[ri,ti,ii,10,0]= float(line[128:138].replace(' ','0.0')) # dose-rate [uSv/h*m^2]
# absolute errors for corresponding values
nuclides_produced[ri,ti,ii,1,1] = nuclides_produced[ri,ti,ii,1,0]*rel_err
nuclides_produced[ri,ti,ii,2,1] = nuclides_produced[ri,ti,ii,2,0]*rel_err
nuclides_produced[ri,ti,ii,3,1] = nuclides_produced[ri,ti,ii,3,0]*rel_err
nuclides_produced[ri,ti,ii,4,1] = nuclides_produced[ri,ti,ii,4,0]*rel_err
nuclides_produced[ri,ti,ii,5,1] = nuclides_produced[ri,ti,ii,5,0]*rel_err
nuclides_produced[ri,ti,ii,6,1] = nuclides_produced[ri,ti,ii,6,0]*rel_err
nuclides_produced[ri,ti,ii,7,1] = nuclides_produced[ri,ti,ii,7,0]*rel_err
nuclides_produced[ri,ti,ii,8,1] = nuclides_produced[ri,ti,ii,8,0]*rel_err
nuclides_produced[ri,ti,ii,9,1] = nuclides_produced[ri,ti,ii,9,0]*rel_err
nuclides_produced[ri,ti,ii,10,1]= nuclides_produced[ri,ti,ii,10,0]*rel_err
# Gamma-ray spectra
column_headers[1] = ['group number','bin energy lower-bound [MeV]','bin energy upper-bound [MeV]','flux [#/s/cc]','energy flux [MeV/s/cc]']
for ri in range(nreg):
for ti in range(ntimes):
if not act_block_text[ri,ti,1]:
gamma_spectra[ri,ti,:,0,0] = None # group number
gamma_spectra[ri,ti,:,1,0] = None # bin energy lower-bound [MeV]
gamma_spectra[ri,ti,:,2,0] = None # bin energy upper-bound [MeV]
gamma_spectra[ri,ti,:,3,0] = 0.0 # flux [#/s/cc]
gamma_spectra[ri,ti,:,4,0] = 0.0 # energy flux [MeV/s/cc]
gamma_spectra[ri,ti,:,3,1] = 0.0 # flux absolute error [#/s/cc]
gamma_spectra[ri,ti,:,4,1] = 0.0 # energy flux absolute error [MeV/s/cc]
continue
table_text = act_block_text[ri,ti,1].split('\n')
for ei in range(len(table_text)):
if ei < header_len[1]: continue # in header lines
ii = ei - header_len[1] # actual number index
line = table_text[ei]
if line=='' or line==None: continue # skip blank/nonexistent lines
gamma_spectra[ri,ti,ii,0,0] = int(line[1:4]) # group number
gamma_spectra[ri,ti,ii,1,0] = float(line[17:25]) # bin energy lower-bound [MeV]
gamma_spectra[ri,ti,ii,2,0] = float(line[7:15]) # bin energy upper-bound [MeV]
gamma_spectra[ri,ti,ii,3,0] = float(line[27:38]) # flux [#/s/cc]
gamma_spectra[ri,ti,ii,4,0] = float(line[40:51]) # energy flux [MeV/s/cc]
gamma_spectra[ri,ti,ii,3,1] = gamma_spectra[ri,ti,ii,3,0]*float(line[53:64]) # flux absolute error [#/s/cc]
gamma_spectra[ri,ti,ii,4,1] = gamma_spectra[ri,ti,ii,4,0]*float(line[53:64]) # energy flux absolute error [MeV/s/cc]
# Top 10 lists
column_headers[2] = ['rank','nuclide - Activity ranking','activity [Bq/cc]','activity [Bq]','rate [%]','nuclide - Decay heat ranking','decay heat [W/cc]','decay heat [W]','rate [%]','nuclide - Dose rate ranking','dose-rate [uSv/h*m^2]','rate [%]']
for ri in range(nreg):
for ti in range(ntimes):
if not act_block_text[ri,ti,2]: continue
table_text = act_block_text[ri,ti,2].split('\n')
for ei in range(len(table_text)):
if ei < header_len[2]: continue # in header lines
ii = ei - header_len[2] # actual number index
line = table_text[ei]
if line=='' or line==None: continue # skip blank/nonexistent lines
top10_lists[ri,ti,ii,0,0] = int(line[1:5]) # number/rank
top10_lists[ri,ti,ii,1,0] = line[8:14] # nuclide - Activity ranking
top10_lists[ri,ti,ii,2,0] = float(line[15:26]) # activity [Bq/cc]
top10_lists[ri,ti,ii,3,0] = float(line[26:37]) # activity [Bq]
top10_lists[ri,ti,ii,4,0] = float(line[48:55]) # rate [%]
rel_err = float(line[37:48])
top10_lists[ri,ti,ii,2,1] = top10_lists[ri,ti,ii,2,0]*rel_err # activity absolute error [Bq/cc]
top10_lists[ri,ti,ii,3,1] = top10_lists[ri,ti,ii,3,0]*rel_err # activity absolute error [Bq]
top10_lists[ri,ti,ii,4,1] = top10_lists[ri,ti,ii,4,0]*rel_err # rate absolute error [%]
top10_lists[ri,ti,ii,5,0] = line[60:66] # nuclide - Decay heat ranking
top10_lists[ri,ti,ii,6,0] = float(line[67:78]) # decay heat [W/cc]
top10_lists[ri,ti,ii,7,0] = float(line[78:89]) # decay heat [W]
top10_lists[ri,ti,ii,8,0] = float(line[100:107]) # rate [%]
rel_err = float(line[89:100])
top10_lists[ri,ti,ii,6,1] = top10_lists[ri,ti,ii,6,0]*rel_err # decay heat absolute error [W/cc]
top10_lists[ri,ti,ii,7,1] = top10_lists[ri,ti,ii,7,0]*rel_err # decay heat absolute error [W]
top10_lists[ri,ti,ii,8,1] = top10_lists[ri,ti,ii,8,0]*rel_err # rate absolute error [%]
top10_lists[ri,ti,ii,9,0] = line[112:118] # nuclide - Dose rate ranking
top10_lists[ri,ti,ii,10,0]= float(line[119:130]) # dose-rate [uSv/h*m^2]
top10_lists[ri,ti,ii,11,0]= float(line[142:149]) # rate [%]
rel_err = float(line[131:142])
top10_lists[ri,ti,ii,10,1]= top10_lists[ri,ti,ii,10,0]*rel_err # dose-rate absolute error [uSv/h*m^2]
top10_lists[ri,ti,ii,11,1]= top10_lists[ri,ti,ii,11,0]*rel_err # rate absolute error [%]
return reg_nos, time_list_sec, time_list_sec_after_EOB, end_of_irradiation_time, nuclides_produced, gamma_spectra, top10_lists, column_headers, summary_info
def generate_nuclide_time_profiles(nuclides_info_array):
'''
Description:
Reformats DCHAIN's tabular nuclide data into time profiles of each nuclide in each region
Inputs:
- the `nuclides_produced` array from function "parse_DCHAIN_act_file"
Outputs:
- List of length R of lists containing names of nuclides produced in each region
- List of length R of lists containing LaTeX-formatted names of nuclides produced in each region
- List of length R of lists containing ZZZAAAM values (10000Z+10A+M) of nuclides produced in each region
- List of length R of lists containing half lives of nuclides produced in each region (in seconds)
- List of length R of NumPy arrays of dimension NxTx7x2 of nuclide info
- List of length 7 containing text descriptions of the 7 columns of the info arrays
'''
nuclide_names = []
nuclide_ZAM_vals = []
nuclide_Latex_names = []
nuclide_half_lives = []
nuclide_info = []
nuclide_info_headers = ['Atoms [#/cc]','Activity [Bq/cc]','Beta decay heat [W/cc]','Gamma decay heat [W/cc]','Alpha decay heat [W/cc]','Total decay heat [W/cc]','Dose-rate [uSv/h*m^2]']
nreg = np.shape(nuclides_info_array)[0]
ntime= np.shape(nuclides_info_array)[1]
nnuc = np.shape(nuclides_info_array)[2]
# Get nuclide name info first, ordering them by increasing Z and A
for ri in range(nreg):
reg_nuclides = []
reg_t_halves = []
reg_ZAM_vals = []
reg_tex_nuclides = []
for ti in range(ntime):
for ni in range(nnuc):
Dname = nuclides_info_array[ri,ti,ni,0,0]
if Dname == None: continue
ZAM = Dname_to_ZAM(Dname)
if ZAM not in reg_ZAM_vals:
bisect.insort_left(reg_ZAM_vals, ZAM)
zami = reg_ZAM_vals.index(ZAM)
#zami = find(ZAM,reg_ZAM_vals)
reg_nuclides.insert(zami,Dname)
reg_t_halves.insert(zami,nuclides_info_array[ri,ti,ni,9,0])
reg_tex_nuclides.insert(zami,Dname_to_Latex(Dname))
nuclide_names.append(reg_nuclides)
nuclide_ZAM_vals.append(reg_ZAM_vals)
nuclide_half_lives.append(reg_t_halves)
nuclide_Latex_names.append(reg_tex_nuclides)
# Now get arrays of nuclide info
for ri in range(nreg):
reg_nnuc = len(nuclide_names[ri])
reg_nuclide_info = np.zeros((ntime,reg_nnuc,7,2))
for ti in range(ntime):
for ni in range(reg_nnuc):
if nuclide_names[ri][ni] not in nuclides_info_array[ri,ti,:,0,0]: continue
sni = find(nuclide_names[ri][ni],nuclides_info_array[ri,ti,:,0,0])
reg_nuclide_info[ti,ni,0,0] = nuclides_info_array[ri,ti,sni,1,0] # atoms [#/cc]
reg_nuclide_info[ti,ni,1,0] = nuclides_info_array[ri,ti,sni,2,0] # activity [Bq/cc]
reg_nuclide_info[ti,ni,2,0] = nuclides_info_array[ri,ti,sni,5,0] # beta decay heat [W/cc]
reg_nuclide_info[ti,ni,3,0] = nuclides_info_array[ri,ti,sni,6,0] # gamma decay heat [W/cc]
reg_nuclide_info[ti,ni,4,0] = nuclides_info_array[ri,ti,sni,7,0] # alpha decay heat [W/cc]
reg_nuclide_info[ti,ni,5,0] = nuclides_info_array[ri,ti,sni,8,0] # total decay heat [W/cc]
reg_nuclide_info[ti,ni,6,0] = nuclides_info_array[ri,ti,sni,10,0] # dose-rate [uSv/h*m^2]
reg_nuclide_info[ti,ni,0,1] = nuclides_info_array[ri,ti,sni,1,1] # atoms absolute error [#/cc]
reg_nuclide_info[ti,ni,1,1] = nuclides_info_array[ri,ti,sni,2,1] # activity absolute error [Bq/cc]
reg_nuclide_info[ti,ni,2,1] = nuclides_info_array[ri,ti,sni,5,1] # beta decay heat absolute error [W/cc]
reg_nuclide_info[ti,ni,3,1] = nuclides_info_array[ri,ti,sni,6,1] # gamma decay heat absolute error [W/cc]
reg_nuclide_info[ti,ni,4,1] = nuclides_info_array[ri,ti,sni,7,1] # alpha decay heat absolute error [W/cc]
reg_nuclide_info[ti,ni,5,1] = nuclides_info_array[ri,ti,sni,8,1] # total decay heat absolute error [W/cc]
reg_nuclide_info[ti,ni,6,1] = nuclides_info_array[ri,ti,sni,10,1] # dose-rate absolute error [uSv/h*m^2]
nuclide_info.append(reg_nuclide_info)
return nuclide_names, nuclide_Latex_names, nuclide_ZAM_vals, nuclide_half_lives, nuclide_info, nuclide_info_headers
def parse_DCS_file_from_DCHAIN(filepath,relevancy_threshold=0.01,print_progress=False,nch_max=100):
'''
Description:
Parse a decay chain information file produced by DCHAIN-SP
Dependencies:
`import numpy as np`
`import time`
Inputs:
(required)
- `filepath` = string, path to DCS file
Inputs:
(optional, keyword)
- `print_progress` = logical variable denoting whether time and significant nuclide info will be printed while scanning file (D=`False`)
- `nch_max` = maximum number of chains per isotope (D=`100`)
- `relevancy_threshold` = what fraction of total activity must a nuclide contribute to be deemed relevant
Outputs:
| dimension | meaning for output array dimensions |
| :------------- | :-------------------------------- |
| R (n_reg) | regions |
| T (ntsteps) | time steps |
| N (nnuc_max) | max number of nuclides |
| C (chni_max) | maximum index of relevant chains |
| L (chln_max) | maximum number of links per chain |
- 0) `inventory` = universal columns of DCS file `[R,T,N,C,vi]`, vi: 0=N_i-1/V, 1=dN/V, 2=N_i/V, 3=A_i/V, 4=A_i
- 1) `l_chains` = `[R,T,N,C]`, length of listed chain
- 2) `prod_nuc` = `[R,T,N]`, strings of the nuclide being produced
- 3) `chn_indx` = `[R,T,N]`, lists of the chain indices printed
- 4) `link_nuc` = `[R,T,N,C,L]`, strings of the nuclides in each chain
- 5) `decay_mode` = `[R,T,N,C,L]`, strings of the decay modes each link undergoes to produce the next link
- 6) `link_dN_info` = `[R,T,N,C,L,di]`, extra dN info di: 0=dN_Beam, 1=dN_Decay/nrxn, 2=dN_Total (only generated if these values are found in file, 'None' otherwise)
- 7) `end_of_irradiation_time` = time of end of final irradiation step [seconds]
- 8) `notable_nuclides_names_by_region` = list of lists (one per region) containing the relevant nuclides per region
- 9) `notable_nuclides_AvT_by_region` = list of arrays (one per region, `[T,N_rlv-nuc,3]`) containing the time[s]/inventory[atm/cc]/activity[Bq/cc] data of relevant nuclides
'''
global start
try:
start_time = start
except:
start_time = time.time()
start = start_time
print('Processing the *.DCS decay chain file... ({:0.2f} seconds elapsed)'.format(time.time()-start))
# Extract text from file
f = open(filepath)
lines = f.readlines()
f.close()
# Determine if extra data is written per isotope by querying whether an isotope's name or blank spaces are present in the line immediately below the first nuclide
if len(lines[9][3:9].strip())==0:
extra_chain_data_present = True
else:
extra_chain_data_present = False
# First, scan for regions
n_reg = 0
reg_nos = []
reg_labels = []
for line in lines:
if 'c<>-<> no.' in line:
n_reg += 1
reg_nos.append(int(line[12:19]))
if 'c<>-<> region label :' in line:
reg_labels.append(line[23:52].strip())
print('{} regions found... ({:0.2f} seconds elapsed)'.format(n_reg,time.time()-start))
# Then, scan for time steps. Need all individual times from beginning and time of end of irradiation.
ntsteps = 0
wtimes = [] # written times since start of calculations in seconds (so, the times at the end of each time step)
beam_state = [] # in each time step, 1 if beam on, 0 if beam off
end_of_irradiation_time = 0.0 # time (in seconds since start of irradiation) at which beam was switched off for the final time
end_irr_time_located = False
for line in lines:
if ' --- during' in line:
if 'irradiation' in line:
beam_state.append(1)
elif 'cooling' in line:
beam_state.append(0)
else:
beam_state.append(None)
print('found weird beam condition')
elif ' --- output time' in line:
ntsteps += 1
t = float(line[39:53])
wtimes.append(t)
if 'after the last shutdown:' in line and not end_irr_time_located:
taeoi_val = float(line[88:97])
taeoi_unit = line[99]
taeoi = taeoi_val*(time_str_to_sec_multiplier(taeoi_unit))
end_of_irradiation_time = t - taeoi
end_irr_time_located = True
elif 'end of irradiation and decay calculation for this region' in line:
break
wtimes = np.array(wtimes)
pstr = '{} time steps found\nend of irradiation at t = {:g} sec ({})\nend of calculation at t = {:g} sec ({})... ({:0.2f} seconds elapsed)'.format(
ntsteps,end_of_irradiation_time,seconds_to_ydhms(end_of_irradiation_time),wtimes[-1],seconds_to_ydhms(wtimes[-1]),time.time()-start)
print(pstr)
# Next, scan for other maximum limiting dimensions
nnuc_max = 0 # maximum number of nuclides listed in a time step
chni_max = 0 # highest index of a relevant chain found
chln_max = 0 # maximum number of links (nuclides) found in any chain
current_tstep_nnuc = 0 # number of nuclides in current time step
chni = 0 # chain number index
chln = 0 # chain length
for line in lines:
if len(line) < 5: continue
if ' --- output time' in line or 'end of irradiation' in line:
if current_tstep_nnuc > nnuc_max: nnuc_max = current_tstep_nnuc
current_tstep_nnuc = 0 # reset count of nuclides in time step
if len(line[3:9].strip())!=0 and line[11]=='(': # first chain entry of a nuclide
current_tstep_nnuc += 1
if line[11]=='(': # all chains have this in common
chni = int(line[12:16])
if chni > chni_max: chni_max = chni
chln = 1 + line.count(')->')
if chln > chln_max: chln_max = chln
pstr = '{} = maximum number of nuclides listed in a single time step\n'.format(nnuc_max)
pstr += '{} = highest index found of all relevant chains\n'.format(chni_max)
pstr += '{} = length of longest chain listed... ({:0.2f} seconds elapsed)'.format(chln_max,time.time()-start)
print(pstr)
# Construct arrays to hold decay chain information
# R (n_reg) regions
# T (ntsteps) time steps
# N (nnuc_max) max number of nuclides
# C (chni_max) maximum index of relevant chains
# L (chln_max) maximum number of links per chain
inventory = np.zeros((n_reg,ntsteps,nnuc_max,chni_max,5)) # universal columns of DCS file [R,T,N,C,vi], vi: 0=N_i-1/V, 1=dN/V, 2=N_i/V, 3=A_i/V, 4=A_i
l_chains = np.zeros((n_reg,ntsteps,nnuc_max,chni_max)) # [R,T,N,C], length of listed chain
prod_nuc = np.empty((n_reg,ntsteps,nnuc_max), dtype='object') # [R,T,N], strings of the nuclide being produced
chn_indx = np.empty((n_reg,ntsteps,nnuc_max), dtype='object') # [R,T,N], lists of the chain indices printed
link_nuc = np.empty((n_reg,ntsteps,nnuc_max,chni_max,chln_max), dtype='object') # [R,T,N,C,L], strings of the nuclides in each chain
decay_mode= np.empty((n_reg,ntsteps,nnuc_max,chni_max,chln_max), dtype='object') # [R,T,N,C,L], strings of the decay modes each link undergoes to produce the next link
nuc_relvnt= np.empty((n_reg,ntsteps,nnuc_max), dtype='object') # [R,T,N], True/False denoting whether a nuclide meets the relevancy threshold in each time step
if extra_chain_data_present:
link_dN_info = np.zeros((n_reg,ntsteps,nnuc_max,chni_max,chln_max,3)) # [R,T,N,C,L,di], extra dN info di: 0=dN_Beam, 1=dN_Decay/nrxn, 2=dN_Total
col_strs = ['dN_Beam','dN_Decay/nx','dN_Total']
nexcol = len(col_strs)
else:
link_dN_info = None
# Populate these arrays
ri = None # region index
ti = None # time step index
ni = None # nuclide index
ci = None # chain index (1 lower than Fortran value)
# character column and spacing numbers for decay chains
ch_sci = 95 # chain start column index
dc_sci = 105 # column index of first decay mode listing
vl_sci = 94 # column index of first extra decay chain value
link_gap_sts = 17 # number of characters between start of one link and the next
for line in lines:
if len(line) < 5: continue
if 'c<>-<> no.' in line: # entering new region
ri = find(int(line[12:19]),reg_nos)
continue
elif ' --- output time' in line: # entering new time step
t = float(line[39:53])
ti = find(t,wtimes)
ni = -1 # reset nuclide index
continue
elif len(line[3:9].strip())!=0 and line[11]=='(': # entering new output nuclide
ni += 1
prod_nuc[ri,ti,ni] = line[3:9]
if line[11]=='(': # if line contains a chain
ci = int(line[12:16]) - 1 # chain index
if not chn_indx[ri,ti,ni]:
chn_indx[ri,ti,ni] = [ci]
else:
chn_indx[ri,ti,ni].append(ci)
col_vals = line[25:92].strip().split()
for vi in range(len(col_vals)):
inventory[ri,ti,ni,ci,vi] = float(col_vals[vi])
chln = 1 + line.count(')->')
l_chains[ri,ti,ni,ci] = chln
for li in range(chln):
nci1 = ch_sci + li*link_gap_sts
nci2 = nci1 + 6
link_nuc[ri,ti,ni,ci,li] = line[nci1:nci2]
if li != chln:
dci1 = dc_sci + li*link_gap_sts
dci2 = dci1 + 2
decay_mode[ri,ti,ni,ci,li] = line[dci1:dci2]
continue
if len(line[3:9].strip())==0 and extra_chain_data_present:
vi = None
for i in range(nexcol):
if col_strs[i] in line:
vi = i
for li in range(chln):
vci1 = vl_sci + li*link_gap_sts
vci2 = vci1 + 14
if len(line[vci1:vci2].strip())==0:
val = 0
else:
val = float(line[vci1:vci2])
link_dN_info[ri,ti,ni,ci,li,vi] = val
# Now extract results from the data arrays
print('\nNow processing decay chain results... ({:0.2f} seconds elapsed)'.format(time.time()-start))
notable_nuclides_AvT_by_region = [] # list of arrays (one per region) containing the time/inventory/activity data of relevant nuclides
notable_nuclides_names_by_region = [] # list of lists (one per region) containing the relevant nuclides per region
for ri in range(n_reg):
print('Region no. {} ({})'.format(reg_nos[ri],reg_labels[ri]))
relevant_nuclides = []
for ti in range(ntsteps):
t = wtimes[ti]
if print_progress:
if t > end_of_irradiation_time:
tai = t - end_of_irradiation_time
print('\tAt time {:g} sec ({}), which is {:g} sec ({}) after end of final irradiation'.format(t,seconds_to_ydhms(t),tai,seconds_to_ydhms(tai)))
else:
print('\tAt time {:g} sec ({})'.format(t,seconds_to_ydhms(t)))
# First, get total information for the time step
N0 = [] # inventory at start of time step
N1 = [] # inventory at end of time step
A0 = [] # activity at start of time step
A1 = [] # activity at end of time step
for ni in range(nnuc_max):
if not prod_nuc[ri,ti,ni]: continue # skip empty nuclide indices
chain_indices = chn_indx[ri,ti,ni]
ci0 = chain_indices[0] # First chain
ci1 = chain_indices[-1] # Last (nonzero) chain
N0.append(inventory[ri,ti,ni,ci0,0])
N1.append(inventory[ri,ti,ni,ci1,2])
lam = inventory[ri,ti,ni,ci0,3]/inventory[ri,ti,ni,ci0,2]
A0.append(lam*inventory[ri,ti,ni,ci0,0])
A1.append(inventory[ri,ti,ni,ci1,3])
N0_tot_tstep = np.sum(N0) # total inventory at start of time step
N1_tot_tstep = np.sum(N1) # total inventory at end of time step
A0_tot_tstep = np.sum(A0) # total activity at start of time step
A1_tot_tstep = np.sum(A1) # total activity at end of time step
# Determine which nuclides meet the relevancy threshold
pstr = ('\t\tRelevant radionuclides include:\n')
nii = -1
for ni in range(nnuc_max):
if not prod_nuc[ri,ti,ni]: continue # skip empty nuclide indices
nii += 1
A1_fract_threshold = relevancy_threshold # Nuclide must be responsible for at least 0.1% total activity at end of time step
A1_nuc_frac = A1[nii]/A1_tot_tstep
if A1_nuc_frac > A1_fract_threshold:
nuc_relvnt[ri,ti,ni] = True
if prod_nuc[ri,ti,ni] not in relevant_nuclides: relevant_nuclides.append(prod_nuc[ri,ti,ni])
pstr += ('\t\t - {} with {:0.2f}% total activity\n'.format(prod_nuc[ri,ti,ni],100*A1_nuc_frac))
else:
nuc_relvnt[ri,ti,ni] = False
if print_progress:
print(pstr)
n_relevant_nuclides = len(relevant_nuclides)
# now collect activity of each nuclide at each time step
relv_nuc_inv = np.zeros((ntsteps,n_relevant_nuclides,3)) # [T,rlvN,3], time[s]/inventory[atm/cc]/activity[Bq/cc] for relevant nuclides
for ti in range(ntsteps):
t = wtimes[ti]
relv_nuc_inv[ti,:,0] = t
for ni in range(nnuc_max):
if not prod_nuc[ri,ti,ni]: continue # skip empty nuclide indices
if prod_nuc[ri,ti,ni] not in relevant_nuclides: continue # only want nuclides which are at some point relevant
chain_indices = chn_indx[ri,ti,ni]
ci1 = chain_indices[-1]
#if nuclide is relevant, find its index among the relevant ones
rni = find(prod_nuc[ri,ti,ni],relevant_nuclides)
relv_nuc_inv[ti,rni,1] = inventory[ri,ti,ni,ci1,2]
relv_nuc_inv[ti,rni,2] = inventory[ri,ti,ni,ci1,3]
notable_nuclides_names_by_region.append(relevant_nuclides)
notable_nuclides_AvT_by_region.append(relv_nuc_inv)
return inventory, l_chains, prod_nuc, chn_indx, link_nuc, decay_mode, link_dN_info, end_of_irradiation_time, notable_nuclides_names_by_region, notable_nuclides_AvT_by_region
def parse_dtrk_file(path_to_dtrk_file,return_metadata=False):
'''
Description:
Parses the output file of a T-Track tally generated by PHITS. Note that this specific function assumes that the T-Track
tally was one automatically generated by and corresponding to a T-Dchain tally but in principle works with any T-Track tally.
This works for region, xyz, and tetrahedral mesh geometries in either the original or reduced format.
Inputs:
- `path_to_dtrk_file` = path to the T-Track tally output file to be parsed
- `return_metadata` = Boolean indicating whether additional information is outputted with the flux (D=`False`)
Outputs:
- `flux` = a RxEx4 array containing regionwise fluxes [Elower/Eupper/flux/abs_error]
- `dtrk_metadata` (only returned if `return_metadata=True`) = list of length two
- `dtrk_metadata[0]` = string denoting axis type 'eng' (old full format) or 'dchain' (new reduced format)
- `dtrk_metadata[1]` = string denoting mesh type as either 'reg', 'xyz', or 'tet'
'''
# Extract text from file
f = open(path_to_dtrk_file)
file_text = f.read()
lines = file_text.split('\n')
f.close()
# Determine geometry type (mesh = reg, xyz, or tet)
for line in lines:
if 'mesh =' in line:
meshtype = line.replace('mesh =','').strip().split()[0]
break
# Determine if original or reduced format (axis = eng or axis = dchain)
for line in lines:
if 'axis =' in line:
axistype = line.replace('axis =','').strip().split()[0]
break
# Double check
for li, line in enumerate(lines):
if li>500: break
if '# e-lower e-upper neutron r.err ' in line:
axistype='eng'
break
dtrk_metadata = [axistype,meshtype]
# Determine number of regions
if axistype=='eng':
nreg = file_text.count('# no. =')
elif axistype=='dchain':
for li, line in reversed(list(enumerate(lines))):
#print(line)
if '0 0 0.0000E+00 0.0000' in line:
nreg = int(lines[li-1].split()[0])
break
if axistype=='dchain':
nEbins = 1968
else:
for line in lines:
if 'ne =' in line:
nEbins = int(line.replace('ne =','').strip().split()[0])
break
flux = np.zeros((nreg,nEbins,4))
if axistype=='eng':
in_flux_lines = False
ei = 0
ri = -1
for line in lines:
if '# no. =' in line:
ri += 1
if '# e-lower e-upper neutron r.err ' in line:
in_flux_lines = True
continue
if in_flux_lines:
flux[ri,ei,:] = [float(x) for x in line.split()]
flux[ri,ei,3] = flux[ri,ei,3]*flux[ri,ei,2] # convert relative error to absolute error
ei += 1
if ei == nEbins:
in_flux_lines = False
ei = 0
elif axistype=='dchain':
ebins = [20.0] + ECCO1968_Ebins(1968)
ebins = ebins[::-1]
in_flux_lines = False
for line in lines:
if '# num ie flux r.err' in line:
in_flux_lines = True
continue
if '0 0 0.0000E+00 0.0000' in line:
in_flux_lines = False
break
if in_flux_lines:
vals = line.split()
ri = int(vals[0])-1
ei = int(vals[1])-1
fval = float(vals[2])
ferr = float(vals[3])
flux[ri,ei,0] = ebins[ei]
flux[ri,ei,1] = ebins[ei+1]
flux[ri,ei,2] = fval
flux[ri,ei,3] = fval*ferr
if return_metadata:
return flux, dtrk_metadata
else:
return flux
def parse_dyld_files(path_to_dyld_file,iredufmt=None):
'''
Description:
Parses the output files of a T-Yield tally generated by PHITS with axis=dchain. This function assumes
that the T-Yield tally was one automatically generated by and corresponding to a T-Dchain tally (axis=dchain).
This works for region, xyz, and tetrahedral mesh geometries in either the original or reduced format.
Inputs:
- `path_to_dyld_file` = path to the T-Yield tally output file to be parsed
(the *_err.dyld file of the same name is automatically searched for and read, if present)
- `iredufmt` = (DEPRICATED; this is now determined automatically)
integer 1 or 0 specifying how the xyz meshes are ordered relative to the internal region numbers.
In the new format (1), region indices are incremented as x->y->z (x=innermost loop); this is reversed in the old format (0).
Ultimately, this corresponds to the same iredufmt parameter in PHITS/DCHAIN, 1='new' and 0='old'.
This variable is only used for xyz meshes where this ordering matters.
Outputs:
- `yields` = a RxNx2 array containing regionwise yields (and their absolute uncertainties) for all nuclides produced in T-Yield
- `nuclide_names_yld` = a length N list of all nuclide names in order
'''
# Extract text from file
f = open(path_to_dyld_file)
file_text = f.read()
lines = file_text.split('\n')
f.close()
# determine if in reduced format
iredufmt=0
for li, line in enumerate(lines):
if "# num nucleusID yield r.err" in line:
iredufmt=1
break
if "isotope production #" in line:
iredufmt=0
break
# Get error data if available
if iredufmt==0:
try:
f_err = open(path_to_dyld_file.replace('.dyld','_err.dyld'))
file_text_err = f_err.read()
lines_err = file_text_err.split('\n')
f_err.close()
err_dyld_found = True
except:
file_text_err = None
lines_err = None
err_dyld_found = False
# Determine geometry type (mesh = reg, xyz, or tet)
for line in lines:
if 'mesh =' in line:
meshtype = line.replace('mesh =','').strip().split()[0]
break
# If xyz mesh, need to find mesh dimensions:
if meshtype=='xyz':
for line in lines:
if 'nx =' in line:
nx = int(line.replace('nx =','').strip().split()[0])
elif 'ny =' in line:
ny = int(line.replace('ny =','').strip().split()[0])
elif 'nz =' in line:
nz = int(line.replace('nz =','').strip().split()[0])
break
# Find starting line
for li, line in enumerate(lines):
if 'nuclear yield (or production)' in line:
li_start = li
break
if iredufmt==1:
# Count number of nuclides present in whole file
nreg = 0
nuc_id_list = []
for li, line in enumerate(lines):
if li <= li_start+3: continue # in header
vals = line.strip().split()
if int(vals[0])==0: break # reached end
if int(vals[0])>nreg: nreg = int(vals[0])
zzzaaam = int(vals[1])
if zzzaaam not in nuc_id_list: nuc_id_list.append(zzzaaam)
nnuc = len(nuc_id_list)
yields = np.zeros((nreg,nnuc,2))
nuclide_names_yld = []
# Get names
nuc_id_list = sorted(nuc_id_list)
for id in nuc_id_list:
nuclide_names_yld.append(ZAM_to_Dname(id))
# Get values
for li, line in enumerate(lines):
if li <= li_start+3: continue # in header
vals = line.strip().split()
if int(vals[0])==0: break # reached end
ri = int(vals[0]) - 1
zzzaaam = int(vals[1])
ni = nuc_id_list.index(zzzaaam)
yields[ri,ni,0] = float(vals[2])
yields[ri,ni,1] = float(vals[3])*float(vals[2])
else: # old ''traditional'' format
# Count number of nuclides present in whole file
nnuc = 0
for li, line in enumerate(lines):
if li <= li_start+2: continue # skip header lines
if 'isotope production' in line:
N_bounds = line.strip().split('=')[-1].split()
N_bounds = [int(i) for i in N_bounds]
nnuc += N_bounds[1] - N_bounds[0] + 1
# Determine number of regions
nreg = 0
for li, line in enumerate(lines):
if li <= li_start+4: continue # skip header lines
if len(line) < 2: break # reached end of first element block
nreg += 1
yields = np.zeros((nreg,nnuc,2))
nuclide_names_yld = []
# Extract yield data
ni = 0 # nuclide index
ni_newstart = 0
ri = 0 # region index
for li, line in enumerate(lines):
if li <= li_start+2: continue # skip header lines
if len(line) < 2: continue # skip line breaks
if 'isotope production' in line:
# extract Z and A info
Z = int(line.strip().split('-')[0])
N_bounds = line.strip().split('=')[-1].split()
N_bounds = [int(i) for i in N_bounds]
N_list = []
for i in range(N_bounds[1]-N_bounds[0]+1):
N_list.append(N_bounds[0]+i)
nisotopes = len(N_list)
A_list = [N+Z for N in N_list]
ni_newstart = len(nuclide_names_yld)
for A in A_list:
ZAM = 10*A + 10000*Z
nuclide_names_yld.append(ZAM_to_Dname(ZAM))
on_buffer_line = True
continue
if on_buffer_line:
ri = 0
on_buffer_line = False
continue
if '# Information for Restart Calculation' in line: break # reached end of useful info
# Only lines making it to this point will be ones with region and yield data
vals = line.strip().split()
if meshtype=='xyz':
yvals = vals[3:]
if err_dyld_found: yvals_rerr = lines_err[li].strip().split()[3:]
jx,jy,jz = int(vals[0]),int(vals[1]),int(vals[2])
rii = jz + (jy-1)*nz + (jx-1)*(nz*ny)
#if iredufmt==1:
# rii = jx + (jy-1)*nx + (jz-1)*(nx*ny)
#else:
# rii = jz + (jy-1)*nz + (jx-1)*(nz*ny)
else:
yvals = vals[1:]
if err_dyld_found: yvals_rerr = lines_err[li].split()[1:]
rii = ri
for i in range(nisotopes):
yields[rii,ni_newstart+i,0] = float(yvals[i])
if err_dyld_found: yields[rii,ni_newstart+i,1] = float(yvals_rerr[i])*yields[rii,ni_newstart+i,0]
ri += 1
return yields, nuclide_names_yld
def Dname_to_ZAM(Dname):
'''
Description:
Converts a DCHAIN-formatted nuclide name to a ZZZAAAM number
Inputs:
- `Dname` = nuclide identification string in DCHAIN format
Outputs:
- `ZZZAAAM` = nuclide identification ineger, calculated as 10000\*Z + 10\*A + m
'''
elms = ["n ",\
"H ","He","Li","Be","B ","C ","N ","O ","F ","Ne",\
"Na","Mg","Al","Si","P ","S ","Cl","Ar","K ","Ca",\
"Sc","Ti","V ","Cr","Mn","Fe","Co","Ni","Cu","Zn",\
"Ga","Ge","As","Se","Br","Kr","Rb","Sr","Y ","Zr",\
"Nb","Mo","Tc","Ru","Rh","Pd","Ag","Cd","In","Sn",\
"Sb","Te","I ","Xe","Cs","Ba","La","Ce","Pr","Nd",\
"Pm","Sm","Eu","Gd","Tb","Dy","Ho","Er","Tm","Yb",\
"Lu","Hf","Ta","W ","Re","Os","Ir","Pt","Au","Hg",\
"Tl","Pb","Bi","Po","At","Rn","Fr","Ra","Ac","Th",\
"Pa","U ","Np","Pu","Am","Cm","Bk","Cf","Es","Fm",\
"Md","No","Lr","Rf","Db","Sg","Bh","Hs","Mt","Ds",\
"Rg","Cn","Nh","Fl","Mc","Lv","Ts","Og"]
AAA = Dname[2:5]
A = int(AAA)
symbol = Dname[0:2]
if 'XX' in symbol: symbol='n '
Z = find(symbol,elms)
if Dname[-1] == ' ':
m = 0
elif Dname[-1] == 'm':
m = 1
elif Dname[-1] == 'n':
m = 2
ZAM = int(10000*Z + 10*A + m)
return ZAM
def ZAM_to_Dname(ZAM):
'''
Description:
Converts a ZZZAAAM number to a DCHAIN-formatted nuclide name
Inputs:
- `ZZZAAAM` = nuclide identification ineger, calculated as 10000\*Z + 10\*A + m
Outputs:
- `Dname` = nuclide identification string in DCHAIN format
'''
elms = ["n ",\
"H ","He","Li","Be","B ","C ","N ","O ","F ","Ne",\
"Na","Mg","Al","Si","P ","S ","Cl","Ar","K ","Ca",\
"Sc","Ti","V ","Cr","Mn","Fe","Co","Ni","Cu","Zn",\
"Ga","Ge","As","Se","Br","Kr","Rb","Sr","Y ","Zr",\
"Nb","Mo","Tc","Ru","Rh","Pd","Ag","Cd","In","Sn",\
"Sb","Te","I ","Xe","Cs","Ba","La","Ce","Pr","Nd",\
"Pm","Sm","Eu","Gd","Tb","Dy","Ho","Er","Tm","Yb",\
"Lu","Hf","Ta","W ","Re","Os","Ir","Pt","Au","Hg",\
"Tl","Pb","Bi","Po","At","Rn","Fr","Ra","Ac","Th",\
"Pa","U ","Np","Pu","Am","Cm","Bk","Cf","Es","Fm",\
"Md","No","Lr","Rf","Db","Sg","Bh","Hs","Mt","Ds",\
"Rg","Cn","Nh","Fl","Mc","Lv","Ts","Og"]
m = int(str(ZAM)[-1])
A = int(str(ZAM)[-4:-1])
Z = int(str(ZAM)[:-4])
sym = elms[Z]
A_str = '{:>3}'.format(A)
m_str_list = [' ','m','n']
m_str = m_str_list[m]
Dname = sym + A_str + m_str
return Dname
def Dname_to_Latex(Dname):
'''
Description:
Converts a DCHAIN-formatted nuclide name to a LaTeX-formatted string
Inputs:
- `Dname` = nuclide identification string in DCHAIN format
Outputs:
- nuclide name as a LaTeX-formatted raw string
'''
AAA = Dname[2:5].strip()
symbol = Dname[0:2].strip()
m = Dname[-1].strip()
latex_str = r"$^{{{}{}}}$".format(AAA,m) + "{}".format(symbol)
return latex_str
def nuclide_plain_str_to_Dname(nuc_str):
'''
Description:
Converts a plaintext string of a nuclide to a DCHAIN-formatted nuclide string
Dependencies:
- `nuclide_plain_str_ZZZAAAM`
- `ZAM_to_Dname`
Inputs:
- `nuc_str` = string to be converted; a huge variety of formats are supported, but they all must follow the following rules:
+ Isomeric/metastable state characters must always immediately follow the atomic mass characters.
Isomeric state labels MUST either:
- (1) be a single lower-case character
- (2) begin with any non-numeric character and end with a number
+ Atomic mass numbers must be nonnegative integers OR the string `"nat"` (in which case no metastable states can be written)
+ Elemental symbols MUST begin with an upper-case character
Outputs:
- DCHAIN-formatted string of nuclide name
'''
return ZAM_to_Dname(nuclide_plain_str_ZZZAAAM(nuc_str))
def rxn_to_dchain_str(target,reaction=None,product=None):
'''
Desription:
Provided a target nuclide and reaction, and optionally a target, generate a reaction string in the format used in DCHAIN's nrxn libs
Dependencies:
`nuclide_plain_str_ZZZAAAM`
`ZZZAAAM_to_dchain_xs_lib_str`
Inputs:
- `target` = string in general format of target nuclide
- Note: at least one of the below options must be provided.
- `reaction` = (optional) either an int MT number (ENDF6 format) or a string of the ejectiles from the neutron reaction (case-insensitive), the "X" in (N,X)
- `product` = (optional) string in general format of product nuclide (if omitted, product in ground state is assumed)
Outputs:
- `rxn_dchain_str` = string formatted identically as that found in DCHAIN's neutron reaction cross section libraries
'''
if not reaction and not product:
print('Warning: no reaction or product provided with target {}.'.format(target))
ZZZAAAM = nuclide_plain_str_ZZZAAAM(target)
target_dstr = ZZZAAAM_to_dchain_xs_lib_str(ZZZAAAM)
dstr = target_dstr + '(N,'
return dstr
ZZZAAAM = nuclide_plain_str_ZZZAAAM(target)
target_dstr = ZZZAAAM_to_dchain_xs_lib_str(ZZZAAAM)
if product: # if not None (product is provided)
ZZZAAAM_prod = nuclide_plain_str_ZZZAAAM(product)
product_dstr = ZZZAAAM_to_dchain_xs_lib_str(ZZZAAAM_prod)
react = [' ', ' ', ' ', ' ', 'N ', ' ', ' ', ' ', ' ', ' ', ' ', '2ND', ' ', ' ', ' ', ' ', '2N ', '3N ', 'FIS', ' ',
' ', ' ', 'NA ', 'N3A', '2NA', '3NA', ' ', ' ', 'NP ', 'N2A', '2N2', ' ', 'ND ', 'NT ', 'NE ', 'ND2', 'NT2', '4N ', ' ', ' ',
' ', '2NP', '3NP', ' ', 'N2P', 'NPA', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ',
' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ',
' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ',
' ', ' ', 'G ', 'P ', 'D ', 'T ', 'HE3', 'A ', '2A ', '3A ', ' ', '2P ', 'PA ', 'T2A', 'D2A', 'PD ', 'PT ', 'DA ', ' ', ' ']
dZ = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, -6, -2, -2, 0, 0, -1, -4, -4, 0, -1, -1, -2, -5, -5, 0, 0, 0, 0, -1, -1,
0, -2, -3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -1, -1, -1, -2, -2, -4, -6, 0, -2, -3, -5, -5, -2, -2, -3, 0, 0]
dA = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -3, 0, 0, 0, 0, -1, -2, 0, 0, 0, 0, -4, -12, -5, -6, 0, 0, -1, -8, -9, 0, -2, -3, -3, -10, -11, -3, 0, 0, 0, -2,
-3, 0, -2, -5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, -1, -2, -2, -3, -7, -11, 0, -1, -4, -10, -9, -2, -3, -5, 0, 0]
if reaction: # reaction is provided
# Get reaction from MT / check if valid reaction
if isinstance(reaction, float): reaction = int(reaction)
if isinstance(reaction, int):
MT = reaction
rxn = react[MT]
else:
rxn = "{:3}".format(reaction.upper())
if rxn not in react:
print('Reaction "{}" not in reaction list for DCHAIN, check formatting or enter ENDF MT number (0-119)'.format(rxn))
return None
else:
MT = react.index(rxn)
if not product: # need to figure out product from parent and rxn, assume ground state (but omit final isomeric characters from string in case xslib has other states too)
ZAM_str = str(ZZZAAAM)
M = 0
A = int(ZAM_str[-4:-1]) + dA[MT]
Z = int(ZAM_str[:-4]) + dZ[MT]
ZZZAAAM_prod = 10000*Z + 10*A + M
product_dstr = ZZZAAAM_to_dchain_xs_lib_str(ZZZAAAM_prod)[:-2]
if MT == 18: product_dstr = '' # fission
if not reaction: # need to find missing reaction from target and product, isomeric states are ignored
ZAM_str = str(ZZZAAAM)
A_tar = int(ZAM_str[-4:-1])
Z_tar = int(ZAM_str[:-4])
ZAM_str_prod = str(ZZZAAAM_prod)
A_prod = int(ZAM_str_prod[-4:-1])
Z_prod = int(ZAM_str_prod[:-4])
rxn_dA = A_prod - A_tar
rxn_dZ = Z_prod - Z_tar
matching_dA = [index for index,value in enumerate(dA) if value == rxn_dA]
matching_dZ = [index for index,value in enumerate(dZ) if value == rxn_dZ]
MT = set(matching_dA).intersection(matching_dZ).pop() # gets the value which is common between the two lists, in this case the index of the reaction
rxn = react[MT]
if reaction and product: # check to make sure they are compatible
# if mismatch occurs, assume product is more likely correct than rxn
ZAM_str = str(ZZZAAAM)
A_tar = int(ZAM_str[-4:-1])
Z_tar = int(ZAM_str[:-4])
ZAM_str_prod = str(ZZZAAAM_prod)
A_prod = int(ZAM_str_prod[-4:-1])
Z_prod = int(ZAM_str_prod[:-4])
rxn_dA = A_prod - A_tar
rxn_dZ = Z_prod - Z_tar
matching_dA = [index for index,value in enumerate(dA) if value == rxn_dA]
matching_dZ = [index for index,value in enumerate(dZ) if value == rxn_dZ]
if A_tar==A_prod and Z_tar==Z_prod:
MT_calc = 4
else:
MT_calc = set(matching_dA).intersection(matching_dZ).pop() # gets the value which is common between the two lists, in this case the index of the reaction
rxn_calc = react[MT_calc]
if rxn_calc != rxn:
print('Warning, mismatch between reaction (N,{}) and product ({}) with target {}; assuming product ({}) is correct and reaction should be (N,{}) instead.'.format(rxn.strip(),product,target,product_dstr,rxn_calc.strip()))
rxn = rxn_calc
dstr = target_dstr + '(N,{})'.format(rxn) + product_dstr
return dstr
def ZZZAAAM_to_dchain_xs_lib_str(ZZZAAAM):
'''
Description:
Converts a ZZZAAAM number to the 7-character nuclide string used by the DCHAIN neutron reaction cross section libraries.
Inputs:
- `ZZZAAAM` = nuclide identification ineger, calculated as 10000\*Z + 10\*A + m
Outputs:
- `D_xs_name` = nuclide identification string in DCHAIN's cross section library format
'''
ZAM_str = str(ZZZAAAM)
M = int(ZAM_str[-1])
A = str(int(ZAM_str[-4:-1]))
Z = ZAM_str[:-4]
sym = Element_Z_to_Sym(int(Z)).upper()
if M==0:
M_str = ' '
else:
M_str = 'M' + str(M)
dstr = "{:2}{:>3}{:2}".format(sym,A,M_str)
return dstr
def ECCO1968_Ebins(n):
'''
Description:
Returns the n highest energy bin values of the ECCO 1968-group energy binning structure.
Inputs:
- `n` = number of energy bins (from 20 MeV down) to be returned
Outputs:
- list of `n` energy bins of the ECCO 1968-group structure
'''
ECCO_bins = [
1.964033E+01,1.947734E+01,1.931570E+01,1.915541E+01,1.899644E+01,1.883880E+01,1.868246E+01,1.852742E+01,1.837367E+01,1.822119E+01,1.806998E+01,1.792002E+01,1.777131E+01,1.762383E+01,1.747757E+01,1.733253E+01,1.718869E+01,1.704605E+01,1.690459E+01,1.676430E+01,1.662518E+01,
1.648721E+01,1.635039E+01,1.621470E+01,1.608014E+01,1.594670E+01,1.581436E+01,1.568312E+01,1.555297E+01,1.542390E+01,1.529590E+01,1.516897E+01,1.504309E+01,1.491825E+01,1.479444E+01,1.467167E+01,1.454991E+01,1.442917E+01,1.430943E+01,1.419068E+01,1.407291E+01,
1.395612E+01,1.384031E+01,1.372545E+01,1.361155E+01,1.349859E+01,1.338657E+01,1.327548E+01,1.316531E+01,1.305605E+01,1.294770E+01,1.284025E+01,1.273370E+01,1.262802E+01,1.252323E+01,1.241930E+01,1.231624E+01,1.221403E+01,1.211267E+01,1.201215E+01,1.191246E+01,
1.181360E+01,1.171557E+01,1.161834E+01,1.152193E+01,1.142631E+01,1.133148E+01,1.123745E+01,1.114419E+01,1.105171E+01,1.095999E+01,1.086904E+01,1.077884E+01,1.068939E+01,1.060068E+01,1.051271E+01,1.042547E+01,1.033895E+01,1.025315E+01,1.016806E+01,1.008368E+01,
1.000000E+01,9.917013E+00,9.834715E+00,9.753099E+00,9.672161E+00,9.591895E+00,9.512294E+00,9.433354E+00,9.355070E+00,9.277435E+00,9.200444E+00,9.124092E+00,9.048374E+00,8.973284E+00,8.898818E+00,8.824969E+00,8.751733E+00,8.679105E+00,8.607080E+00,8.535652E+00,
8.464817E+00,8.394570E+00,8.324906E+00,8.255820E+00,8.187308E+00,8.119363E+00,8.051983E+00,7.985162E+00,7.918896E+00,7.853179E+00,7.788008E+00,7.723377E+00,7.659283E+00,7.595721E+00,7.532687E+00,7.470175E+00,7.408182E+00,7.346704E+00,7.285736E+00,7.225274E+00,
7.165313E+00,7.105850E+00,7.046881E+00,6.988401E+00,6.930406E+00,6.872893E+00,6.815857E+00,6.759294E+00,6.703200E+00,6.647573E+00,6.592406E+00,6.537698E+00,6.483443E+00,6.429639E+00,6.376282E+00,6.323367E+00,6.270891E+00,6.218851E+00,6.167242E+00,6.116062E+00,
6.065307E+00,6.014972E+00,5.965056E+00,5.915554E+00,5.866462E+00,5.817778E+00,5.769498E+00,5.721619E+00,5.674137E+00,5.627049E+00,5.580351E+00,5.534042E+00,5.488116E+00,5.442572E+00,5.397406E+00,5.352614E+00,5.308195E+00,5.264143E+00,5.220458E+00,5.177135E+00,
5.134171E+00,5.091564E+00,5.049311E+00,5.007408E+00,4.965853E+00,4.924643E+00,4.883775E+00,4.843246E+00,4.803053E+00,4.763194E+00,4.723666E+00,4.684465E+00,4.645590E+00,4.607038E+00,4.568805E+00,4.530890E+00,4.493290E+00,4.456001E+00,4.419022E+00,4.382350E+00,
4.345982E+00,4.309916E+00,4.274149E+00,4.238679E+00,4.203504E+00,4.168620E+00,4.134026E+00,4.099719E+00,4.065697E+00,4.031957E+00,3.998497E+00,3.965314E+00,3.932407E+00,3.899773E+00,3.867410E+00,3.835316E+00,3.803488E+00,3.771924E+00,3.740621E+00,3.709579E+00,
3.678794E+00,3.648265E+00,3.617989E+00,3.587965E+00,3.558189E+00,3.528661E+00,3.499377E+00,3.470337E+00,3.441538E+00,3.412978E+00,3.384654E+00,3.356566E+00,3.328711E+00,3.301087E+00,3.273692E+00,3.246525E+00,3.219583E+00,3.192864E+00,3.166368E+00,3.140091E+00,
3.114032E+00,3.088190E+00,3.062562E+00,3.037147E+00,3.011942E+00,2.986947E+00,2.962159E+00,2.937577E+00,2.913199E+00,2.889023E+00,2.865048E+00,2.841272E+00,2.817693E+00,2.794310E+00,2.771121E+00,2.748124E+00,2.725318E+00,2.702701E+00,2.680272E+00,2.658030E+00,
2.635971E+00,2.614096E+00,2.592403E+00,2.570889E+00,2.549554E+00,2.528396E+00,2.507414E+00,2.486605E+00,2.465970E+00,2.445505E+00,2.425211E+00,2.405085E+00,2.385126E+00,2.365332E+00,2.345703E+00,2.326237E+00,2.306932E+00,2.287787E+00,2.268802E+00,2.249973E+00,
2.231302E+00,2.212785E+00,2.194421E+00,2.176211E+00,2.158151E+00,2.140241E+00,2.122480E+00,2.104866E+00,2.087398E+00,2.070076E+00,2.052897E+00,2.035860E+00,2.018965E+00,2.002210E+00,1.985595E+00,1.969117E+00,1.952776E+00,1.936570E+00,1.920499E+00,1.904561E+00,
1.888756E+00,1.873082E+00,1.857538E+00,1.842122E+00,1.826835E+00,1.811675E+00,1.796640E+00,1.781731E+00,1.766944E+00,1.752281E+00,1.737739E+00,1.723318E+00,1.709017E+00,1.694834E+00,1.680770E+00,1.666821E+00,1.652989E+00,1.639271E+00,1.625667E+00,1.612176E+00,
1.598797E+00,1.585530E+00,1.572372E+00,1.559323E+00,1.546383E+00,1.533550E+00,1.520823E+00,1.508202E+00,1.495686E+00,1.483274E+00,1.470965E+00,1.458758E+00,1.446652E+00,1.434646E+00,1.422741E+00,1.410934E+00,1.399225E+00,1.387613E+00,1.376098E+00,1.364678E+00,
1.353353E+00,1.342122E+00,1.330984E+00,1.319938E+00,1.308985E+00,1.298122E+00,1.287349E+00,1.276666E+00,1.266071E+00,1.255564E+00,1.245145E+00,1.234812E+00,1.224564E+00,1.214402E+00,1.204324E+00,1.194330E+00,1.184418E+00,1.174589E+00,1.164842E+00,1.155175E+00,
1.145588E+00,1.136082E+00,1.126654E+00,1.117304E+00,1.108032E+00,1.098836E+00,1.089717E+00,1.080674E+00,1.071706E+00,1.062812E+00,1.053992E+00,1.045245E+00,1.036571E+00,1.027969E+00,1.019438E+00,1.010978E+00,1.002588E+00,9.942682E-01,9.860171E-01,9.778344E-01,
9.697197E-01,9.616723E-01,9.536916E-01,9.457772E-01,9.379285E-01,9.301449E-01,9.224259E-01,9.147709E-01,9.071795E-01,8.996511E-01,8.921852E-01,8.847812E-01,8.774387E-01,8.701570E-01,8.629359E-01,8.557746E-01,8.486728E-01,8.416299E-01,8.346455E-01,8.277190E-01,
8.208500E-01,8.140380E-01,8.072825E-01,8.005831E-01,7.939393E-01,7.873507E-01,7.808167E-01,7.743369E-01,7.679109E-01,7.615382E-01,7.552184E-01,7.489511E-01,7.427358E-01,7.365720E-01,7.304594E-01,7.243976E-01,7.183860E-01,7.124243E-01,7.065121E-01,7.006490E-01,
6.948345E-01,6.890683E-01,6.833499E-01,6.776790E-01,6.720551E-01,6.664779E-01,6.609470E-01,6.554620E-01,6.500225E-01,6.446282E-01,6.392786E-01,6.339734E-01,6.287123E-01,6.234948E-01,6.183206E-01,6.131893E-01,6.081006E-01,6.030542E-01,5.980496E-01,5.930866E-01,
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4.040057E-04,4.006530E-04,3.973281E-04,3.940308E-04,3.907608E-04,3.875180E-04,3.843021E-04,3.811129E-04,3.779502E-04,3.748137E-04,3.717032E-04,3.686185E-04,3.655595E-04,3.625258E-04,3.595173E-04,3.565338E-04,3.535750E-04,3.506408E-04,3.477309E-04,3.448452E-04,
3.419834E-04,3.391454E-04,3.363309E-04,3.335398E-04,3.307719E-04,3.280269E-04,3.253047E-04,3.226051E-04,3.199279E-04,3.172729E-04,3.146399E-04,3.120288E-04,3.094394E-04,3.068715E-04,3.043248E-04,3.017993E-04,2.992948E-04,2.968110E-04,2.943479E-04,2.919052E-04,
2.894827E-04,2.870804E-04,2.846980E-04,2.823354E-04,2.799924E-04,2.776688E-04,2.753645E-04,2.730793E-04,2.708131E-04,2.685657E-04,2.663370E-04,2.641267E-04,2.619348E-04,2.597611E-04,2.576054E-04,2.554676E-04,2.533476E-04,2.512451E-04,2.491601E-04,2.470924E-04,
2.450418E-04,2.430083E-04,2.409917E-04,2.389917E-04,2.370084E-04,2.350416E-04,2.330910E-04,2.311567E-04,2.292384E-04,2.273360E-04,2.254494E-04,2.235784E-04,2.217230E-04,2.198830E-04,2.180583E-04,2.162487E-04,2.144541E-04,2.126744E-04,2.109095E-04,2.091592E-04,
2.074234E-04,2.057021E-04,2.039950E-04,2.023021E-04,2.006233E-04,1.989584E-04,1.973073E-04,1.956699E-04,1.940461E-04,1.924358E-04,1.908388E-04,1.892551E-04,1.876845E-04,1.861269E-04,1.845823E-04,1.830505E-04,1.815315E-04,1.800250E-04,1.785310E-04,1.770494E-04,
1.755802E-04,1.741231E-04,1.726781E-04,1.712451E-04,1.698239E-04,1.684146E-04,1.670170E-04,1.656310E-04,1.642565E-04,1.628933E-04,1.615415E-04,1.602010E-04,1.588715E-04,1.575531E-04,1.562456E-04,1.549489E-04,1.536631E-04,1.523879E-04,1.511232E-04,1.498691E-04,
1.486254E-04,1.473920E-04,1.461688E-04,1.449558E-04,1.437529E-04,1.425599E-04,1.413768E-04,1.402036E-04,1.390401E-04,1.378862E-04,1.367420E-04,1.356072E-04,1.344818E-04,1.333658E-04,1.322590E-04,1.311615E-04,1.300730E-04,1.289935E-04,1.279231E-04,1.268615E-04,
1.258087E-04,1.247646E-04,1.237292E-04,1.227024E-04,1.216842E-04,1.206744E-04,1.196729E-04,1.186798E-04,1.176949E-04,1.167182E-04,1.157496E-04,1.147890E-04,1.138364E-04,1.128917E-04,1.119548E-04,1.110258E-04,1.101044E-04,1.091907E-04,1.082845E-04,1.073859E-04,
1.064947E-04,1.056110E-04,1.047345E-04,1.038654E-04,1.030034E-04,1.021486E-04,1.013009E-04,1.004603E-04,9.962658E-05,9.879981E-05,9.797990E-05,9.716679E-05,9.636043E-05,9.556076E-05,9.476773E-05,9.398128E-05,9.320136E-05,9.242791E-05,9.166088E-05,9.090021E-05,
9.014586E-05,8.939776E-05,8.865588E-05,8.792015E-05,8.719052E-05,8.646695E-05,8.574939E-05,8.503778E-05,8.433208E-05,8.363223E-05,8.293819E-05,8.224991E-05,8.156734E-05,8.089044E-05,8.021915E-05,7.955344E-05,7.889325E-05,7.823854E-05,7.758926E-05,7.694537E-05,
7.630682E-05,7.567357E-05,7.504558E-05,7.442280E-05,7.380518E-05,7.319270E-05,7.258529E-05,7.198293E-05,7.138556E-05,7.079316E-05,7.020566E-05,6.962305E-05,6.904527E-05,6.847228E-05,6.790405E-05,6.734053E-05,6.678169E-05,6.622749E-05,6.567789E-05,6.513285E-05,
6.459233E-05,6.405630E-05,6.352471E-05,6.299754E-05,6.247474E-05,6.195628E-05,6.144212E-05,6.093223E-05,6.042657E-05,5.992511E-05,5.942781E-05,5.893464E-05,5.844556E-05,5.796053E-05,5.747954E-05,5.700253E-05,5.652948E-05,5.606036E-05,5.559513E-05,5.513376E-05,
5.467623E-05,5.422248E-05,5.377251E-05,5.332626E-05,5.288373E-05,5.244486E-05,5.200963E-05,5.157802E-05,5.114999E-05,5.072551E-05,5.030456E-05,4.988709E-05,4.947309E-05,4.906253E-05,4.865538E-05,4.825160E-05,4.785117E-05,4.745407E-05,4.706026E-05,4.666972E-05,
4.628243E-05,4.589834E-05,4.551744E-05,4.513971E-05,4.476511E-05,4.439361E-05,4.402521E-05,4.365985E-05,4.329753E-05,4.293822E-05,4.258189E-05,4.222851E-05,4.187807E-05,4.153054E-05,4.118589E-05,4.084410E-05,4.050514E-05,4.016900E-05,3.983565E-05,3.950507E-05,
3.917723E-05,3.885211E-05,3.852969E-05,3.820994E-05,3.789285E-05,3.757838E-05,3.726653E-05,3.695727E-05,3.665057E-05,3.634642E-05,3.604479E-05,3.574566E-05,3.544902E-05,3.515484E-05,3.486310E-05,3.457378E-05,3.428686E-05,3.400233E-05,3.372015E-05,3.344032E-05,
3.316281E-05,3.288760E-05,3.261467E-05,3.234401E-05,3.207560E-05,3.180942E-05,3.154544E-05,3.128365E-05,3.102404E-05,3.076658E-05,3.051126E-05,3.025805E-05,3.000695E-05,2.975793E-05,2.951098E-05,2.926607E-05,2.902320E-05,2.878235E-05,2.854349E-05,2.830662E-05,
2.807171E-05,2.783875E-05,2.760773E-05,2.737862E-05,2.715141E-05,2.692609E-05,2.670264E-05,2.648104E-05,2.626128E-05,2.604335E-05,2.582722E-05,2.561289E-05,2.540033E-05,2.518954E-05,2.498050E-05,2.477320E-05,2.456761E-05,2.436373E-05,2.416154E-05,2.396104E-05,
2.376219E-05,2.356499E-05,2.336944E-05,2.317550E-05,2.298317E-05,2.279244E-05,2.260329E-05,2.241572E-05,2.222969E-05,2.204522E-05,2.186227E-05,2.168084E-05,2.150092E-05,2.132249E-05,2.114554E-05,2.097006E-05,2.079603E-05,2.062345E-05,2.045231E-05,2.028258E-05,
2.011426E-05,1.994734E-05,1.978180E-05,1.961764E-05,1.945484E-05,1.929339E-05,1.913328E-05,1.897449E-05,1.881703E-05,1.866087E-05,1.850601E-05,1.835244E-05,1.820013E-05,1.804910E-05,1.789931E-05,1.775077E-05,1.760346E-05,1.745738E-05,1.731250E-05,1.716883E-05,
1.702635E-05,1.688506E-05,1.674493E-05,1.660597E-05,1.646816E-05,1.633150E-05,1.619597E-05,1.606156E-05,1.592827E-05,1.579609E-05,1.566500E-05,1.553500E-05,1.540608E-05,1.527823E-05,1.515144E-05,1.502570E-05,1.490101E-05,1.477735E-05,1.465472E-05,1.453310E-05,
1.441250E-05,1.429289E-05,1.417428E-05,1.405665E-05,1.394000E-05,1.382431E-05,1.370959E-05,1.359582E-05,1.348299E-05,1.337110E-05,1.326014E-05,1.315010E-05,1.304097E-05,1.293274E-05,1.282542E-05,1.271898E-05,1.261343E-05,1.250876E-05,1.240495E-05,1.230201E-05,
1.219991E-05,1.209867E-05,1.199827E-05,1.189870E-05,1.179995E-05,1.170203E-05,1.160492E-05,1.150861E-05,1.141311E-05,1.131839E-05,1.122446E-05,1.113132E-05,1.103894E-05,1.094733E-05,1.085648E-05,1.076639E-05,1.067704E-05,1.058843E-05,1.050056E-05,1.041342E-05,
1.032701E-05,1.024130E-05,1.015631E-05,1.007203E-05,9.988446E-06,9.905554E-06,9.823351E-06,9.741830E-06,9.660985E-06,9.580812E-06,9.501303E-06,9.422455E-06,9.344261E-06,9.266715E-06,9.189814E-06,9.113550E-06,9.037919E-06,8.962916E-06,8.888536E-06,8.814772E-06,
8.741621E-06,8.669077E-06,8.597135E-06,8.525790E-06,8.455037E-06,8.384871E-06,8.315287E-06,8.246281E-06,8.177848E-06,8.109982E-06,8.042680E-06,7.975936E-06,7.909746E-06,7.844105E-06,7.779009E-06,7.714454E-06,7.650434E-06,7.586945E-06,7.523983E-06,7.461544E-06,
7.399622E-06,7.338215E-06,7.277317E-06,7.216925E-06,7.157034E-06,7.097640E-06,7.038739E-06,6.980326E-06,6.922399E-06,6.864952E-06,6.807981E-06,6.751484E-06,6.695455E-06,6.639892E-06,6.584789E-06,6.530144E-06,6.475952E-06,6.422210E-06,6.368914E-06,6.316060E-06,
6.263645E-06,6.211665E-06,6.160116E-06,6.108995E-06,6.058298E-06,6.008022E-06,5.958164E-06,5.908719E-06,5.859684E-06,5.811056E-06,5.762832E-06,5.715008E-06,5.667581E-06,5.620547E-06,5.573904E-06,5.527647E-06,5.481775E-06,5.436284E-06,5.391169E-06,5.346430E-06,
5.302061E-06,5.258061E-06,5.214426E-06,5.171153E-06,5.128239E-06,5.085681E-06,5.043477E-06,4.918953E-06,4.797503E-06,4.679053E-06,4.563526E-06,4.450853E-06,4.340961E-06,4.233782E-06,4.129250E-06,4.000000E-06,3.927860E-06,3.830880E-06,3.736300E-06,3.644050E-06,
3.554080E-06,3.466330E-06,3.380750E-06,3.300000E-06,3.217630E-06,3.137330E-06,3.059020E-06,2.983490E-06,2.909830E-06,2.837990E-06,2.767920E-06,2.720000E-06,2.659320E-06,2.600000E-06,2.550000E-06,2.485030E-06,2.421710E-06,2.382370E-06,2.360000E-06,2.300270E-06,
2.242050E-06,2.185310E-06,2.130000E-06,2.100000E-06,2.059610E-06,2.020000E-06,1.974490E-06,1.930000E-06,1.884460E-06,1.855390E-06,1.840000E-06,1.797000E-06,1.755000E-06,1.711970E-06,1.670000E-06,1.629510E-06,1.590000E-06,1.544340E-06,1.500000E-06,1.475000E-06,
1.440000E-06,1.404560E-06,1.370000E-06,1.337500E-06,1.300000E-06,1.267080E-06,1.235000E-06,1.202060E-06,1.170000E-06,1.150000E-06,1.123000E-06,1.110000E-06,1.097000E-06,1.080000E-06,1.071000E-06,1.045000E-06,1.035000E-06,1.020000E-06,9.960000E-07,9.860000E-07,
9.720000E-07,9.500000E-07,9.300000E-07,9.100000E-07,8.764250E-07,8.600000E-07,8.500000E-07,8.194500E-07,7.900000E-07,7.800000E-07,7.415500E-07,7.050000E-07,6.825600E-07,6.531500E-07,6.250000E-07,5.952800E-07,5.669600E-07,5.400000E-07,5.315800E-07,5.196200E-07,
5.000000E-07,4.850000E-07,4.670100E-07,4.496800E-07,4.330000E-07,4.139900E-07,4.000000E-07,3.910000E-07,3.699300E-07,3.500000E-07,3.346600E-07,3.200000E-07,3.145000E-07,3.000000E-07,2.800000E-07,2.635100E-07,2.480000E-07,2.335800E-07,2.200000E-07,2.091400E-07,
1.988100E-07,1.890000E-07,1.800000E-07,1.697100E-07,1.600000E-07,1.530300E-07,1.463700E-07,1.400000E-07,1.340000E-07,1.150000E-07,1.000000E-07,9.500000E-08,8.000000E-08,7.700000E-08,6.700000E-08,5.800000E-08,5.000000E-08,4.200000E-08,3.500000E-08,3.000000E-08,
2.500000E-08,2.000000E-08,1.500000E-08,1.000000E-08,6.900000E-09,5.000000E-09,3.000000E-09,1.000010E-11
]
#pstr = ''
#for i in range(len(ECCO_bins)):
# pstr += ECCO_bins[i] + ','
# if i!=0 and i%20==0:
# pstr += '\n'
#print(pstr)
return ECCO_bins[:n]
def retrieve_rxn_xs_from_lib(libfile,target,reaction=None,product=None):
'''
Description:
Provided a DCHAIN neutron rxn cross section library file and sufficient information
about a reaction, return that reaction's cross section.
Dependencies:
`rxn_to_dchain_str`
`ECCO1968_Ebins`
Inputs:
- `libfile` = string of file path to data library file to be searched
- `target` = string in general format of target nuclide
- `reaction` = (optional) either an int MT number (ENDF6 format) or a string of the ejectiles from the neutron reaction (case-insensitive), the "X" in (N,X)
if `reaction = 'tot'` or `'total'`, the summed total transmutation xs (reactions which change the target's nuclide species) is provided and input for product is ignored;
this behavior is also assumed when missing both reaction and product information
- `product` = (optional) string in general format of product nuclide (if omitted, sum of all isomeric states is assumed; if provided product but not isomeric state, ground state is assumed)
Outputs:
- `xs` = a 2x1968 numpy array containing energy [eV] (i=0) and cross sections [b] (i=1) for all 1968 ECCO bins
- `rxn_tex_str` = a LaTeX-formatted string of the reaction
'''
datafolder, lib = os.path.split(libfile.replace('_n_act_xs_lib',''))
n_occurances = 0
rxn_locations= []
rxn_listings = []
xs_data_raw = []
# determine if rxn or product is provided
if (not reaction and not product) or (reaction=='tot' or reaction=='total'): # only target provided
#print('Total transmutation cross section of {}'.format(target))
calc_total_xs = True
else:
calc_total_xs = False
if calc_total_xs: # only concerned with target, not target or reaction
# First, assemble reaction string
rt = rxn_to_dchain_str(target,None,target)[:10] # only concerned with target + '(N,'
rt_alt = None # alternate string to cover ground state when 'g' is present in product too
catalog_rxn_text = rt[0] + rt[1:].lower()
catalog_rxn_text_alt = None
# make pretty Latex str of reaction too
target_str = rt[0] + rt[1:7].lower()
not_symbol = r'$\neg$' # '!'
rxn_str = '(n,*)'
tex_target = nuclide_plain_str_to_latex_str(target_str)
if target_str[-2:] == ' ':
tex_product = nuclide_plain_str_to_latex_str(target_str[:-2]+'g ')
else:
tex_product = tex_target
rxn_tex_str = tex_target + rxn_str + not_symbol + tex_product
else:
# First, assemble reaction string
rt = rxn_to_dchain_str(target,reaction,product)
rt_alt = None # alternate string to cover ground state when 'g' is present in product too
if product:
if rt[-2] == ' ': rt_alt = rt[:-2] + 'G '
# Format string found in the catalog file
catalog_rxn_text = rt[0] + rt[1:14].lower()
if reaction.lower() != 'fis': catalog_rxn_text+= rt[14] + rt[15:].lower()
catalog_rxn_text_alt = None
if rt_alt: catalog_rxn_text_alt = rt_alt[0] + rt_alt[1:14].lower() + rt_alt[14] + rt_alt[15:].lower()
# make pretty Latex str of reaction too
target_str = rt[0] + rt[1:7].lower()
if reaction.lower() == 'fis':
product_str = ''
else:
product_str= rt[14] + rt[15:22].lower()
rxn_str = rt[7:14].lower().replace(' ','')
if 'a' in rxn_str: rxn_str = rxn_str.replace('a',r'$\alpha$')
if 'g' in rxn_str: rxn_str = rxn_str.replace('g',r'$\gamma$')
if 'he3' in rxn_str: rxn_str = rxn_str.replace('he3',r'$^3$He')
tex_target = nuclide_plain_str_to_latex_str(target_str)
if product_str:
tex_product= nuclide_plain_str_to_latex_str(product_str)
else:
tex_product = ''
rxn_tex_str = tex_target + rxn_str + tex_product
if lib[0]=='h': # in hybrid_lib_dchain_names:
hlib = True
else:
hlib = False
catalog_file = libfile.replace('_n_act_xs_lib','_n_reaction_list.txt')
library_file = libfile
if os.path.isfile(catalog_file): # catalog file exists
search_file = catalog_file
search_text = catalog_rxn_text
search_text_alt = catalog_rxn_text_alt
using_catalog_file = True
elif os.path.isfile(library_file): # library file exists
search_file = library_file
search_text = rt
search_text_alt = rt_alt
using_catalog_file = False
else:
print('\t{} library files not found.'.format(lib))
return None
with open(search_file) as f:
asterisk_counter = -1
for num, line in enumerate(f, 1):
if '*' in line: asterisk_counter += 1
if search_text in line or (rt_alt and search_text_alt in line):
n_occurances += 1
if using_catalog_file:
rxn_locations.append(num-2) # index of reaction in reaction lib
rxn_listings.append(line.replace('\n',''))
else: # searching through actual library file
rxn_locations.append(asterisk_counter) # index of reaction in reaction lib
rxn_listings.append(line[20:41])
if n_occurances == 0:
print('Reaction "{}" not found in library "{}".'.format(catalog_rxn_text,lib))
return None, 'null'
if n_occurances > 1:
if calc_total_xs:
print(' Multiple reactions found. The sum of all will be used.')
else:
print(' Multiple product isomers for reaction found. The sum of all isomeric states will be used.')
for j in range(n_occurances):
print('\t{} (lib entry index {} of {})'.format(rxn_listings[j],rxn_locations[j],lib))
if hlib:
print('Hybrid library {} uses data from {} for reaction {}.'.format(lib,rxn_listings[0][26:],catalog_rxn_text))
# State library availability
#if hlib and n_occurances>0: # this is a hybrid library
# src_lib = rxn_listings[libi][0][26:]
# print('\t{} {} (from {})'.format(lib,n_occurances,src_lib))
# lib_colors[libi] = lib_colors[lib_names.index(src_lib)]
#else: # normal library
# print('\t{} {}'.format(lib,n_occurances[libi]))
#if n_occurances[libi]>0 and libi in libis_to_compare: n_plotable_lines += 1
if not os.path.isfile(library_file):
print('\t{} library file not found.'.format(lib))
return None, 'null'
if n_occurances == 0:
print('\t\tCross section not present in this library, skipping')
return None, 'null'
entry_index = -1
with open(library_file) as f:
lines = f.readlines()
for line in lines:
if '*' in line: entry_index += 1
if entry_index in rxn_locations: # reached bookmarked entry index of interest for this lib
found_entry = True
enti = rxn_locations.index(entry_index)
if '*' in line:
if rxn_listings[enti][:22].upper() not in line: # double check that entry is correct
print('Library index mismatch!')
found_entry = False
xs_vals = []
entry_li = -1
if found_entry:
entry_li += 1
if entry_li == 0: # first line
nEbins = int(line[12:18])
elif entry_li == 1 or entry_li == 2: # skip descriptive lines
continue
else:
xs_vals += [float(xsi) for xsi in line.replace('\n','').split()]
if len(xs_vals) == nEbins:
if len(xs_data_raw)==0: # need to initialize entry
xs_data_raw = np.zeros(1968)
xs_data_raw[:nEbins] += np.array(xs_vals)
# Now pretty up the results to be provided to the user
xs = np.zeros((2,1968))
xs[0,:] = (1e6)*np.array(ECCO1968_Ebins(1968)[::-1]) # all energy bins in increasing order in eV
# now flip order of lists to have them in energy increasing order
for i in range(len(xs_data_raw)):
xs[1,1967-i] = xs_data_raw[i]
return xs, rxn_tex_str
def calc_one_group_nrxn_xs_dchain(neutron_flux,neutron_flux_errors,libfile,target,reaction=None,product=None):
'''
Description:
Combines a neutron flux and cross section into a flux-weighted single-group cross section.
Inputs:
- `neutron_flux` = 1D array of flux values
- `neutron_flux_errors` = 1D array of flux absolute uncertainties
- `libfile` = string of file path to data library file to be searched
- `target` = string in general format of target nuclide
- `reaction` = (optional) either an int MT number (ENDF6 format) or a string of the ejectiles from the neutron reaction (case-insensitive), the "X" in (N,X)
if `reaction = 'tot'` or `'total'`, the summed total transmutation xs (reactions which change the target's nuclide species) is provided and input for product is ignored;
this behavior is also assumed when missing both reaction and product information
- `product` = (optional) string in general format of product nuclide (if omitted, sum of all isomeric states is assumed; if provided product but not isomeric state, ground state is assumed)
Outputs:
- `xs` = a length-2 list of the single group cross section and its absolute uncertainty
'''
xs_out, rxn_str_out = retrieve_rxn_xs_from_lib(libfile,target,reaction,product)
xs_vals = xs_out[1,:]
flux_val = neutron_flux
flux_err = neutron_flux_errors
if len(xs_vals) != len(flux_val):
print('Warning: mismatch in flux and cross section energy binning!')
xs = np.sum(flux_val*xs_vals)/np.sum(flux_val)
xs_fer_num = np.sqrt(np.sum((flux_err*xs_vals)**2))/np.sum(flux_val*xs_vals)
xs_fer_denom = np.sqrt(np.sum(flux_err**2))/np.sum(flux_val)
xs_fer = np.sqrt(xs_fer_num**2 + xs_fer_denom**2)
xs_aer = xs*xs_fer
return [xs, xs_aer]
def parse_DCHAIN_act_file_legacy(act_file_path):
'''
Description:
This code parses the .act file generated by DCHAIN (without uncertainty values)
Inputs:
- path to a DCHAIN-generated .act file
Outputs:
- length R list of region numbers
- length T list of measurement times (in sec) from start of irradiation
- time of end of irradiation (in sec)
- NumPy array of dimension RxTxNx11 of nuclide table data (N=max recorded table lenth)
- NumPy array of dimension RxTxNx5 of gamma spectrum table data
- NumPy array of dimension RxTxNx12 of top-10 list table data
- List containing 3 lists of column headers for the preceding three NumPy arrays
- list of the below lists/arrays of summary information
- NumPy array of dimension Rx7 of region-specific summary info
- list of length 7 containing descriptions of the above items
- NumPy array of dimension RxTx12 of region and time-specific summary info
- list of length 12 containing descriptions of the above items
'''
# Extract file info
f = open(act_file_path)
lines = f.readlines()
f.close()
# Parse file to determine number of regions
nreg = 0
reg_nos = []
for line in lines:
if 'region number' in line:
nreg += 1
reg_nos.append(int(line[21:31]))
# Parse file again to determine number of time steps
current_reg_no = -1
#irradiation_time = -1.0 # seconds
end_of_irradiation_time = -1.0 # seconds
ntimes = 0
time_strs = []
time_list_sec = [] # time steps in seconds
for line in lines:
#if 'irradiation time' in line: irradiation_time = float(line[21:31])*time_str_to_sec_multiplier(line[33])
if 'region number' in line: current_reg_no = int(line[21:31])
if current_reg_no != reg_nos[0]: continue # only read times from first region
if '--- output time ---' in line:
ntimes += 1
time_strs.append(line)
time_list_sec.append(float(line[40:53]))
if ('--- output time ---' in line) and ('after the last shutdown' in line) and end_of_irradiation_time == -1:
end_of_irradiation_time = float(line[21:31])*time_str_to_sec_multiplier(line[33]) - float(line[88:97])*time_str_to_sec_multiplier(line[99])
# Extract "summary info" from file
ri = -1 # region index
ti = -1 # time index
r_summary_info = np.empty((nreg,7), dtype='object') # (regionwise) initialize Rx7 array
r_summary_info_description = ['region number','irradiation time [s]','region volume [cc]','neutron flux [n/cm^2/s]','beam power [MW]','beam energy [GeV]','beam current [mA]'] # (regionwise) initialize Rx7 array
'''
index meaning
0 region number
1 irradiation time [sec]
2 region volume [cc]
3 neutron flux [n/cm^2/s]
4 beam power [MW]
5 beam energy [GeV]
6 beam current [mA]
'''
rt_summary_info = np.empty((nreg,ntimes,12), dtype='object') # (region-and-timewise) initialize RxTx12 array
rt_summary_info_description = ['total gamma flux [#/s/cc]','total gamma energy flux [MeV/s/cc]','annihilation gamma flux [#/s/cc]','gamma current underflow [#/s]','gamma current overflow [#/s]','total activity [Bq/cc]','total decay heat [W/cc]','beta decay heat [W/cc]','gamma decay heat [W/cc]','alpha decay heat [W/cc]','activated atoms [#/cc]','total gamma dose rate [uSV/h*m^2]'] # (region-and-timewise) initialize RxTx12 array
'''
index meaning
0 total gamma flux [#/s/cc]
1 total gamma energy flux [MeV/s/cc]
2 annihilation gamma flux [#/s/cc]
3 gamma current underflow [#/s] (gammas below lowest energy bin)
4 gamma current overflow [#/s] (gammas above highest energy bin)
5 total activity [Bq/cc]
6 total decay heat [W/cc]
7 beta decay heat [W/cc]
8 gamma decay heat [W/cc]
9 alpha decay heat [W/cc]
10 activated atoms [#/cc]
11 total gamma dose rate [uSV/h*m^2]
'''
for li in range(len(lines)):
line = lines[li]
if 'region number' in line:
ri = find(int(line[21:31]),reg_nos)
# region-specific summary info
r_summary_info[ri,0] = int(line[21:31])
r_summary_info[ri,1] = float(lines[li-1][21:31])*time_str_to_sec_multiplier(lines[li-1][33])
r_summary_info[ri,2] = float(lines[li-2][21:31])
r_summary_info[ri,3] = float(lines[li-3][21:31])
r_summary_info[ri,4] = float(lines[li-4][21:31])
r_summary_info[ri,5] = float(lines[li-5][21:31])
r_summary_info[ri,6] = float(lines[li-6][21:31])
if '--- output time ---' in line:
ti = find(line,time_strs)
# gamma info specific to region and time
if 'total gamma-ray flux' in line:
rt_summary_info[ri,ti,0] = float(line[39:49])
rt_summary_info[ri,ti,1] = float(lines[li+1][39:49])
rt_summary_info[ri,ti,2] = float(lines[li+2][39:49])
if 'group limitation' in lines[li+3]:
rt_summary_info[ri,ti,3] = float(lines[li+3][91:101])
rt_summary_info[ri,ti,4] = float(lines[li+3][64:74])
else:
rt_summary_info[ri,ti,3] = 0.0
rt_summary_info[ri,ti,4] = 0.0
# activation info specific to region and time
if 'total activity' in line:
rt_summary_info[ri,ti,5] = float(line[25:36])
rt_summary_info[ri,ti,6] = float(lines[li+1][25:36])
rt_summary_info[ri,ti,7] = float(lines[li+2][25:36])
rt_summary_info[ri,ti,8] = float(lines[li+3][25:36])
rt_summary_info[ri,ti,9] = float(lines[li+4][25:36])
rt_summary_info[ri,ti,10]= float(lines[li+5][25:36])
rt_summary_info[ri,ti,11]= float(lines[li+6][25:36])
summary_info = [r_summary_info, r_summary_info_description, rt_summary_info, rt_summary_info_description]
# Extract major "blocks" (nuclides, gamma spec, top10 list) for each time step in each region
act_block_text = np.empty((nreg,ntimes,3), dtype='object') # initialize RxTx3 array to hold character strings where final index 0=nuclides, 1=gamma-spec, and 2=top10-list
ri = -1 # region index
ti = -1 # time index
qi = -1 # quantity index - 0=nuclides, 1=gamma-spec, and 2=top10-list
max_array_len = [0,0,0] # maximum number of entries for a given quantity
current_array_len = [0,0,0] # current number of entries for a given quantity
for line in lines:
if 'region number' in line:
ri = find(int(line[21:31]),reg_nos)
if '--- output time ---' in line:
ti = find(line,time_strs)
qi = 0 # reset quantity index
if 'gamma-ray spectrum weighted by energy' in line:
qi = 1
if 'dominant nuclides (top 10)' in line:
qi = 2
if 'total' in line[:20] or line=='\n': # no longer reading info block
if current_array_len[qi] > max_array_len[qi]:
max_array_len[qi] = current_array_len[qi]
current_array_len[qi] = 0
qi = -1
if qi < 0: continue # not in region of interest
try:
act_block_text[ri,ti,qi] += line
except:
act_block_text[ri,ti,qi] = line
current_array_len[qi] += 1
header_len = [3,4,3] # number of lines present in table header
nuclides_produced = np.empty((nreg,ntimes,max_array_len[0]-header_len[0],11), dtype='object') # initialize RxTxNx11 array to hold nuclide information
gamma_spectra = np.empty((nreg,ntimes,max_array_len[1]-header_len[1], 5), dtype='object') # initialize RxTxNx5 array to hold gamma spec information
top10_lists = np.empty((nreg,ntimes,max_array_len[2]-header_len[2],12), dtype='object') # initialize RxTxNx12 array to hold top 10 list information
column_headers = [ [],[],[] ]
# Now, populate each array
# Nuclides produced
column_headers[0] = ['nuclide','atoms [#/cc]','activity [Bq/cc]','activity [Bq]','rate [%]','beta decay heat [W/cc]','gamma decay heat [W/cc]','alpha decay heat [W/cc]','total decay heat [W/cc]','half life [s]','dose-rate [uSv/h*m^2]']
for ri in range(nreg):
for ti in range(ntimes):
table_text = act_block_text[ri,ti,0].split('\n')
for ei in range(len(table_text)):
if ei < header_len[0]: continue # in header lines
ii = ei - header_len[0] # actual number index
line = table_text[ei]
if line=='' or line==None: continue # skip blank/nonexistent lines
nuclides_produced[ri,ti,ii,0] = line[3:9] # nuclide
nuclides_produced[ri,ti,ii,1] = float(line[13:23]) # atoms [#/cc]
nuclides_produced[ri,ti,ii,2] = float(line[26:36]) # activity [Bq/cc]
nuclides_produced[ri,ti,ii,3] = float(line[38:48]) # activity [Bq]
nuclides_produced[ri,ti,ii,4] = float(line[49:56].replace(' ','0.0')) # rate [%]
nuclides_produced[ri,ti,ii,5] = float(line[58:67]) # beta decay heat [W/cc]
nuclides_produced[ri,ti,ii,6] = float(line[69:78]) # gamma decay heat [W/cc]
nuclides_produced[ri,ti,ii,7] = float(line[80:89]) # alpha decay heat [W/cc]
nuclides_produced[ri,ti,ii,8] = float(line[91:100]) # total decay heat [W/cc]
nuclides_produced[ri,ti,ii,9] = float(line[104:113]) # half life [s]
nuclides_produced[ri,ti,ii,10]= float(line[116:125]) # dose-rate [uSv/h*m^2]
# Gamma-ray spectra
column_headers[1] = ['group number','bin energy lower-bound [MeV]','bin energy upper-bound [MeV]','flux [#/s/cc]','energy flux [MeV/s/cc]']
for ri in range(nreg):
for ti in range(ntimes):
table_text = act_block_text[ri,ti,1].split('\n')
for ei in range(len(table_text)):
if ei < header_len[1]: continue # in header lines
ii = ei - header_len[1] # actual number index
line = table_text[ei]
if line=='' or line==None: continue # skip blank/nonexistent lines
gamma_spectra[ri,ti,ii,0] = int(line[1:4]) # group number
gamma_spectra[ri,ti,ii,1] = float(line[17:25]) # bin energy lower-bound [MeV]
gamma_spectra[ri,ti,ii,2] = float(line[7:15]) # bin energy upper-bound [MeV]
gamma_spectra[ri,ti,ii,3] = float(line[28:38]) # flux [#/s/cc]
gamma_spectra[ri,ti,ii,4] = float(line[41:51]) # energy flux [MeV/s/cc]
# Top 10 lists
column_headers[2] = ['rank','nuclide - Activity ranking','activity [Bq/cc]','activity [Bq]','rate [%]','nuclide - Decay heat ranking','decay heat [W/cc]','decay heat [W]','rate [%]','nuclide - Dose rate ranking','dose-rate [uSv/h*m^2]','rate [%]']
for ri in range(nreg):
for ti in range(ntimes):
table_text = act_block_text[ri,ti,2].split('\n')
for ei in range(len(table_text)):
if ei < header_len[2]: continue # in header lines
ii = ei - header_len[2] # actual number index
line = table_text[ei]
if line=='' or line==None: continue # skip blank/nonexistent lines
top10_lists[ri,ti,ii,0] = int(line[1:5]) # number/rank
top10_lists[ri,ti,ii,1] = line[8:14] # nuclide - Activity ranking
top10_lists[ri,ti,ii,2] = float(line[16:26]) # activity [Bq/cc]
top10_lists[ri,ti,ii,3] = float(line[27:37]) # activity [Bq]
top10_lists[ri,ti,ii,4] = float(line[38:43]) # rate [%]
top10_lists[ri,ti,ii,5] = line[48:54] # nuclide - Decay heat ranking
top10_lists[ri,ti,ii,6] = float(line[56:66]) # decay heat [W/cc]
top10_lists[ri,ti,ii,7] = float(line[67:77]) # decay heat [W]
top10_lists[ri,ti,ii,8] = float(line[78:83]) # rate [%]
top10_lists[ri,ti,ii,9] = line[88:94] # nuclide - Dose rate ranking
top10_lists[ri,ti,ii,10]= float(line[96:106]) # dose-rate [uSv/h*m^2]
top10_lists[ri,ti,ii,11]= float(line[107:113]) # rate [%]
return reg_nos, time_list_sec, end_of_irradiation_time, nuclides_produced, gamma_spectra, top10_lists, column_headers, summary_info
def generate_nuclide_time_profiles_legacy(nuclides_info_array):
'''
Description:
Reformats DCHAIN's tabular nuclide data into time profiles of each nuclide in each region (without uncertainty values)
Inputs:
- the `nuclides_produced' array from function "parse_DCHAIN_act_file"
Outputs:
- List of length R of lists containing names of nuclides produced in each region
- List of length R of lists containing LaTeX-formatted names of nuclides produced in each region
- List of length R of lists containing ZZZAAAM values (10000Z+10A+M) of nuclides produced in each region
- List of length R of lists containing half lives of nuclides produced in each region (in seconds)
- List of length R of NumPy arrays of dimension NxTx7 of nuclide info
- List of length 7 containing text descriptions of the 7 columns of the info arrays
'''
nuclide_names = []
nuclide_ZAM_vals = []
nuclide_Latex_names = []
nuclide_half_lives = []
nuclide_info = []
nuclide_info_headers = ['Atoms [#/cc]','Activity [Bq/cc]','Beta decay heat [W/cc]','Gamma decay heat [W/cc]','Alpha decay heat [W/cc]','Total decay heat [W/cc]','Dose-rate [uSv/h*m^2]']
nreg = np.shape(nuclides_info_array)[0]
ntime= np.shape(nuclides_info_array)[1]
nnuc = np.shape(nuclides_info_array)[2]
# Get nuclide name info first, ordering them by increasing Z and A
for ri in range(nreg):
reg_nuclides = []
reg_t_halves = []
reg_ZAM_vals = []
reg_tex_nuclides = []
for ti in range(ntime):
for ni in range(nnuc):
Dname = nuclides_info_array[ri,ti,ni,0]
if Dname == None: continue
ZAM = Dname_to_ZAM(Dname)
if ZAM not in reg_ZAM_vals:
bisect.insort_left(reg_ZAM_vals, ZAM)
zami = reg_ZAM_vals.index(ZAM)
#zami = find(ZAM,reg_ZAM_vals)
reg_nuclides.insert(zami,Dname)
reg_t_halves.insert(zami,nuclides_info_array[ri,ti,ni,9])
reg_tex_nuclides.insert(zami,Dname_to_Latex(Dname))
nuclide_names.append(reg_nuclides)
nuclide_ZAM_vals.append(reg_ZAM_vals)
nuclide_half_lives.append(reg_t_halves)
nuclide_Latex_names.append(reg_tex_nuclides)
# Now get arrays of nuclide info
for ri in range(nreg):
reg_nnuc = len(nuclide_names[ri])
reg_nuclide_info = np.zeros((ntime,reg_nnuc,7))
for ti in range(ntime):
for ni in range(reg_nnuc):
if nuclide_names[ri][ni] not in nuclides_info_array[ri,ti,:,0]: continue
sni = find(nuclide_names[ri][ni],nuclides_info_array[ri,ti,:,0])
reg_nuclide_info[ti,ni,0] = nuclides_info_array[ri,ti,sni,1] # atoms [#/cc]
reg_nuclide_info[ti,ni,1] = nuclides_info_array[ri,ti,sni,2] # activity [Bq/cc]
reg_nuclide_info[ti,ni,2] = nuclides_info_array[ri,ti,sni,5] # beta decay heat [W/cc]
reg_nuclide_info[ti,ni,3] = nuclides_info_array[ri,ti,sni,6] # gamma decay heat [W/cc]
reg_nuclide_info[ti,ni,4] = nuclides_info_array[ri,ti,sni,7] # alpha decay heat [W/cc]
reg_nuclide_info[ti,ni,5] = nuclides_info_array[ri,ti,sni,8] # total decay heat [W/cc]
reg_nuclide_info[ti,ni,6] = nuclides_info_array[ri,ti,sni,10] # dose-rate [uSv/h*m^2]
nuclide_info.append(reg_nuclide_info)
return nuclide_names, nuclide_Latex_names, nuclide_ZAM_vals, nuclide_half_lives, nuclide_info, nuclide_info_headers
def plot_top10_nuclides(dchain_output,rank_val='activity',xaxis_val='time',xaxis_type='indices',regions=None,region_indices=None,times=None,time_indices=None,rank_cutoff=10,xscale='linear'):
'''
Description:
Generate a nice plot illustrating dominant nuclides as a function of time or region
Dependencies:
- `import numpy as np`
- `import matplotlib.pyplot as plt`
- `process_dchain_simulation_output`
Inputs:
(required)
- `dchain_output` = dictionary output from the process_dchain_simulation_output for a simulation
Inputs:
(optional, keyword)
- `rank_val` = which top 10 list is selected. (D=`'activity'`, options include `'activity'`, `'decay_heat'`, and `'gamma_dose'`)
- `xaxis_val` = value to be plotted on x-axis; can be either `"time"` (default) or `"region"`
- `xaxis_type` = space xaxis entries either equally by `"indices"` (default) or realistically by `"values"`
- `regions` = list of region numbers (or individual value) to generate plots for (D=`None`, plotting all regions)
- `region_indices` = same as above but uses indices rather than region numbers; this has higher priority if specified (D=`None`, plot all regions)
- `times` = list of times (from start in seconds) (or individual value) to generate plots for (D=`None`, plotting all times)
- `time_indices` = same as above but uses indices rather than time values; this has higher priority if specified (D=`None`, plot all times)
- `rank_cutoff` = highest rank (or number of ranks) to be displayed (D=`10`, cannot be any greater than 10)
- `xscale` = string specifying scale of x-axis, either `'linear'` (default) or `'log'`
Outputs:
- `fig_list` = list of figures which can be plotted.
'''
max_nregs = len(dchain_output['region']['numbers'])
all_regs = dchain_output['region']['numbers']
max_ntimes = len(dchain_output['time']['from_start_sec'])
all_times = dchain_output['time']['from_start_sec']
if not regions and not region_indices:
regions = dchain_output['region']['numbers']
region_indices = range(len(regions))
elif region_indices:
if isinstance(region_indices, list):
regions = []
for i in region_indices:
if i >= max_nregs:
print('region index {} greater than number of regions {}, skipping...'.format(i,max_nregs))
region_indices.remove(i)
continue
regions.append(dchain_output['region']['numbers'][i])
else:
if region_indices < max_nregs:
regions = [dchain_output['region']['numbers'][region_indices]]
region_indices = [region_indices]
else:
print('Single provided region index {} is out of bounds of total number of regions {}, aborting...'.format(region_indices,max_nregs))
return None
elif regions:
if isinstance(regions, list):
region_indices = []
for i in regions:
if i not in all_regs:
print('region {} is not contained in list of region numbers, skipping...'.format(i))
regions.remove(i)
continue
region_indices.append(dchain_output['region']['numbers'].index(i))
else:
if regions in all_regs:
region_indices = [dchain_output['region']['numbers'].index(regions)]
regions = [regions]
else:
print('Single provided region {} is not in the simulated region numbers, aborting...'.format(region_indices))
return None
if not times and not time_indices:
times = dchain_output['time']['from_start_sec']
time_indices = range(len(times))
elif time_indices:
if isinstance(time_indices, list):
times = []
for i in time_indices:
if i >= max_ntimes:
print('time index {} greater than number of times {}, skipping...'.format(i,max_ntimes))
time_indices.remove(i)
continue
times.append(dchain_output['time']['from_start_sec'][i])
else:
if time_indices < max_ntimes:
times = [dchain_output['time']['from_start_sec'][time_indices]]
time_indices = [time_indices]
else:
print('Single provided time index {} is out of bounds of total number of times {}, aborting...'.format(time_indices,max_ntimes))
return None
elif times:
if isinstance(times, list):
time_indices = []
for i in times:
if i not in all_times:
print('time {} is not contained in list of times, skipping...'.format(i))
times.remove(i)
continue
time_indices.append(dchain_output['time']['from_start_sec'].index(i))
else:
if times in all_times:
time_indices = [dchain_output['time']['from_start_sec'].index(times)]
times = [times]
else:
print('Single provided time {} is not in the outputted times, aborting...'.format(time_indices))
return None
if rank_val=='photon_dose':
rank_val = 'gamma_dose'
if rank_val not in ['activity','decay_heat','gamma_dose']:
print("rank_val must be either 'activity', 'decay_heat', or 'gamma_dose', aborting...")
return None
if xaxis_val not in ['time','region']:
print("xaxis_val must be either 'time' or 'region', aborting...")
return None
if xaxis_type=='index': xaxis_type = 'indices'
if xaxis_type=='value': xaxis_type = 'values'
if xaxis_type not in ['indices','values']:
print("xaxis_val must be either 'indices' or 'values', aborting...")
return None
fig_list = []
ax_list = []
figi = 0
if xaxis_val=='time':
major_indices = region_indices
minor_indices = time_indices
major_values = regions
minor_values = times
xstr = 'Time'
else:
major_indices = time_indices
minor_indices = region_indices
major_values = times
minor_values = regions
xstr = 'Region'
if xaxis_type=='indices':
xdata = minor_indices
xstr += ' (index)'
else:
xdata = minor_values
for majori in major_indices:
figi += 1
# Assemble list of all ranked nuclides
nuclides = []
for minori in minor_indices:
if xaxis_val=='time':
ri = majori
ti = minori
else:
ri = minori
ti = majori
for tti in range(len(dchain_output['top10'][rank_val]['nuclide'][ri][ti,:])):
if (dchain_output['top10'][rank_val]['nuclide'][ri][ti,tti]!=None) and (dchain_output['top10'][rank_val]['nuclide'][ri][ti,tti] not in nuclides) and (dchain_output['top10'][rank_val]['rank'][ri][ti,tti]<=rank_cutoff):
nuclides.append(dchain_output['top10'][rank_val]['nuclide'][ri][ti,tti])
# Now assemble plot for each nuclide
plot_dicts = []
for nuclide in nuclides:
ni = nuclides.index(nuclide)
ydata = []
for minori in minor_indices:
if xaxis_val=='time':
ri = majori
ti = minori
else:
ri = minori
ti = majori
if nuclide in dchain_output['top10'][rank_val]['nuclide'][ri][ti,:]:
tti = dchain_output['top10'][rank_val]['nuclide'][ri][ti,:].tolist().index(nuclide)
#tti = np.where(dchain_output['top10'][rank_val]['nuclide'][ri][ti,:]==nuclide)
if dchain_output['top10'][rank_val]['rank'][ri][ti,tti]<=rank_cutoff:
ydata.append( 1 + rank_cutoff - dchain_output['top10'][rank_val]['rank'][ri][ti,tti] )
else:
ydata.append(np.nan)
else:
ydata.append(np.nan)
tex_name = nuclide_plain_str_to_latex_str(nuclide)
# dict = {'xdata':xdata,'ydata':ydata,'marker':tex_name,'markersize':30,'color':colors_list_12(ni%12)}
dict = {'xdata':xdata,'ydata':ydata,'marker':tex_name,'markersize':30}
plot_dicts.append(dict)
# Now generate plot
if xaxis_val=='time':
title_str = 'Top {} nuclides by {} in region {}'.format(rank_cutoff,rank_val.replace('_',' '),major_values[major_indices.index(majori)])
else:
title_str = 'Top {} nuclides by {} at t = {} seconds'.format(rank_cutoff,rank_val.replace('_',' '),major_values[major_indices.index(majori)])
ystr = 'Rank'
if Hunters_tools_is_available:
fig1, ax1 = fancy_plot(
xdata_lists=None,
ydata_lists=None,
dictionaries=plot_dicts,
figi=figi,
title_str=title_str,
x_label_str=xstr,
y_label_str=ystr,
x_scale=xscale,
y_scale='linear',
fig_height_inch=6.5*(rank_cutoff/10)+0.1*(10-rank_cutoff)
)
else:
# For public version, just make this a basic plot rather than using my complicated personal plotting function
fig1 = plt.figure()
ax1 = plt.subplot(111)
for entry in plot_dicts:
ax1.plot(entry['xdata'],entry['ydata'],marker=entry['marker'],markersize=entry['markersize'],ls='')
plt.xlabel(xstr,fontsize=14)
plt.ylabel(ystr,fontsize=14)
plt.xscale(xscale)
fig1.tight_layout()
fig1.set_size_inches(0.2+6.3*(len(plot_dicts[0]['xdata'])/12),6.5*(rank_cutoff/10)+0.1*(10-rank_cutoff))
ax1.set_yticks(range(1,rank_cutoff+1))
ax1.set_yticklabels([str(i) for i in range(rank_cutoff,0,-1)])
if xaxis_type=='indices':
ax1.set_xticks(minor_indices)
ax1.set_xticklabels([str(i) for i in minor_indices])
plt.grid(visible=True, which='major', linestyle='-', alpha=0)#0.25)
plt.grid(visible=True, which='minor', linestyle='-', alpha=0)#0.10)
fig_list.append(fig1)
ax_list.append(ax1)
return fig_list #, ax_list
'''
**************************************************************************************************
------------------------------------ Other misc. functions ---------------------------------------
**************************************************************************************************
'''
def find(target, myList):
'''
Description:
Search for and return the index of the first occurance of a value in a list.
Inputs:
- `target` = value to be searched for
- `myList` = list of values
Outputs:
- index of first instance of `target` in `myList`
'''
for i in range(len(myList)):
if myList[i] == target:
return i
def Element_Z_to_Sym(Z):
'''
Description:
Returns elemental symbol for a provided atomic number Z
Inputs:
- `Z` = atomic number
Outputs:
- `sym` = string of elemental symbol for element of atomic number Z
'''
elms = ["n ",\
"H ","He","Li","Be","B ","C ","N ","O ","F ","Ne",\
"Na","Mg","Al","Si","P ","S ","Cl","Ar","K ","Ca",\
"Sc","Ti","V ","Cr","Mn","Fe","Co","Ni","Cu","Zn",\
"Ga","Ge","As","Se","Br","Kr","Rb","Sr","Y ","Zr",\
"Nb","Mo","Tc","Ru","Rh","Pd","Ag","Cd","In","Sn",\
"Sb","Te","I ","Xe","Cs","Ba","La","Ce","Pr","Nd",\
"Pm","Sm","Eu","Gd","Tb","Dy","Ho","Er","Tm","Yb",\
"Lu","Hf","Ta","W ","Re","Os","Ir","Pt","Au","Hg",\
"Tl","Pb","Bi","Po","At","Rn","Fr","Ra","Ac","Th",\
"Pa","U ","Np","Pu","Am","Cm","Bk","Cf","Es","Fm",\
"Md","No","Lr","Rf","Db","Sg","Bh","Hs","Mt","Ds",\
"Rg","Cn","Nh","Fl","Mc","Lv","Ts","Og"]
i = int(Z)
if i < 0 or i > len(elms):
print('Z={} is not valid, please select a number from 0 to 118 (inclusive).'.format(str(Z)))
return None
return elms[i].strip()
def Element_Sym_to_Z(sym):
'''
Description:
Returns atomic number Z for a provided elemental symbol
Dependencies:
`find`
Inputs:
- `sym` = string of elemental symbol for element of atomic number Z
Outputs:
- `Z` = atomic number
'''
elms = ["n ",\
"H ","He","Li","Be","B ","C ","N ","O ","F ","Ne",\
"Na","Mg","Al","Si","P ","S ","Cl","Ar","K ","Ca",\
"Sc","Ti","V ","Cr","Mn","Fe","Co","Ni","Cu","Zn",\
"Ga","Ge","As","Se","Br","Kr","Rb","Sr","Y ","Zr",\
"Nb","Mo","Tc","Ru","Rh","Pd","Ag","Cd","In","Sn",\
"Sb","Te","I ","Xe","Cs","Ba","La","Ce","Pr","Nd",\
"Pm","Sm","Eu","Gd","Tb","Dy","Ho","Er","Tm","Yb",\
"Lu","Hf","Ta","W ","Re","Os","Ir","Pt","Au","Hg",\
"Tl","Pb","Bi","Po","At","Rn","Fr","Ra","Ac","Th",\
"Pa","U ","Np","Pu","Am","Cm","Bk","Cf","Es","Fm",\
"Md","No","Lr","Rf","Db","Sg","Bh","Hs","Mt","Ds",\
"Rg","Cn","Nh","Fl","Mc","Lv","Ts","Og"]
if len(sym.strip())>2:
print('Please provide a valid elemental symbol (1 or 2 characters), {} is too long'.format(sym))
return -1
# handle exception for neutron first
if sym.strip()=='XX':
return 0
# make sure string is formatted to match entries in elms list
sym2 = sym.strip()
if len(sym2)==1: sym2 += ' '
sym2 = sym2[0].upper() + sym2[1].lower()
Z = find(sym2,elms)
if Z==None:
print('Z could not be found for element "{}"; please make sure entry is correct.'.format(sym))
return -1
return Z
def Element_ZorSym_to_name(Z):
'''
Description:
Returns an element's name provided its atomic number Z or elemental symbol
Inputs:
- `Z` = string of elemental symbol or atomic number Z
Outputs:
- `name` = element name
'''
element_names = ['neutron','Hydrogen','Helium','Lithium','Beryllium','Boron','Carbon','Nitrogen','Oxygen','Fluorine',
'Neon','Sodium','Magnesium','Aluminium','Silicon','Phosphorus','Sulfur','Chlorine','Argon',
'Potassium','Calcium','Scandium','Titanium','Vanadium','Chromium','Manganese','Iron','Cobalt',
'Nickel','Copper','Zinc','Gallium','Germanium','Arsenic','Selenium','Bromine','Krypton',
'Rubidium','Strontium','Yttrium','Zirconium','Niobium','Molybdenum','Technetium','Ruthenium',
'Rhodium','Palladium','Silver','Cadmium','Indium','Tin','Antimony','Tellurium','Iodine','Xenon',
'Caesium','Barium','Lanthanum','Cerium','Praseodymium','Neodymium','Promethium','Samarium',
'Europium','Gadolinium','Terbium','Dysprosium','Holmium','Erbium','Thulium','Ytterbium',
'Lutetium','Hafnium','Tantalum','Tungsten','Rhenium','Osmium','Iridium','Platinum','Gold',
'Mercury','Thallium','Lead','Bismuth','Polonium','Astatine','Radon','Francium','Radium',
'Actinium','Thorium','Protactinium','Uranium','Neptunium','Plutonium','Americium','Curium',
'Berkelium','Californium','Einsteinium','Fermium','Mendelevium','Nobelium','Lawrencium',
'Rutherfordium','Dubnium','Seaborgium','Bohrium','Hassium','Meitnerium','Darmstadtium',
'Roentgenium','Copernicium','Nihonium','Flerovium','Moscovium','Livermorium','Tennessine','Oganesson']
try:
zi = int(Z)
except:
zi = Element_Sym_to_Z(Z)
return element_names[zi]
def Element_ZorSym_to_mass(Z):
'''
Description:
Returns an element's average atomic mass provided its atomic number Z or elemental symbol
Inputs:
- `Z` = string of elemental symbol or atomic number Z
Outputs:
- `A_avg` = average atomic mass
'''
average_atomic_masses = [1.008664,1.007,4.002602,6.941,9.012182,10.811,12.0107,14.0067,15.9994,18.9984032,
20.1797,22.98976928,24.305,26.9815386,28.0855,30.973762,32.065,35.453,39.948,39.0983,
40.078,44.955912,47.867,50.9415,51.9961,54.938045,55.845,58.933195,58.6934,63.546,65.38,
69.723,72.63,74.9216,78.96,79.904,83.798,85.4678,87.62,88.90585,91.224,92.90638,95.96,98,
101.07,102.9055,106.42,107.8682,112.411,114.818,118.71,121.76,127.6,126.90447,131.293,
132.9054519,137.327,138.90547,140.116,140.90765,144.242,145,150.36,151.964,157.25,
158.92535,162.5,164.93032,167.259,168.93421,173.054,174.9668,178.49,180.94788,183.84,
186.207,190.23,192.217,195.084,196.966569,200.59,204.3833,207.2,208.9804,209,210,222,
223,226,227,232.03806,231.03588,238.02891,237,244,243,247,247,251,252,257,258,259,
266,267,268,269,270,277,278,281,282,285,286,289,290,293,294,294]
try:
zi = int(Z)
except:
zi = Element_Sym_to_Z(Z)
return average_atomic_masses[zi]
def nuclide_to_Latex_form(Z,A,m=''):
'''
Description:
Form a LaTeX-formatted string of a nuclide provided its information
Dependencies:
`Element_Z_to_Sym`
(only required if inputed Z is not already an elemental symbol)
Inputs:
- `Z` = atomic number of nuclide (int, float, or string) or elemental symbol (string)
- `A` = atomic mass of nuclide (int, float, or string) or string to go in place of A (ex. 'nat')
- `m` = metastable state (D='', ground state); this will be appended to the end of A
if not a string already, it will be converted into one and appended to 'm' (ex. 1 -> 'm1')
Outputs:
- LaTeX-formatted raw string of a nuclide, excellent for plot titles, labels, and auto-generated LaTeX documents
'''
if isinstance(A,(int,float)): A = str(int(A))
if not isinstance(Z,str): symbol = Element_Z_to_Sym(int(Z))
if isinstance(m,float): m = int(m)
if isinstance(m,int): m = 'm' + str(m)
latex_str = r"$^{{{}{}}}$".format(A,m) + "{}".format(symbol)
return latex_str
def nuclide_plain_str_to_latex_str(nuc_str,include_Z=False):
'''
Description:
Converts a plaintext string of a nuclide to a LaTeX-formatted raw string
Note: if you already have the Z, A, and isomeric state information determined, the "nuclide_to_Latex_form" function can be used instead
Dependencies:
- `Element_Z_to_Sym` (only required if `include_Z = True`)
Inputs:
(required)
- `nuc_str` = string to be converted; a huge variety of formats are supported, but they all must follow the following rules:
+ Isomeric/metastable state characters must always immediately follow the atomic mass characters.
Isomeric state labels MUST either:
- (1) be a single lower-case character OR
- (2) begin with any non-numeric character and end with a number
+ Atomic mass numbers must be nonnegative integers OR the string `"nat"` (in which case no metastable states can be written)
+ Elemental symbols MUST begin with an upper-case character
Inputs:
(optional)
- `include_Z` = `True`/`False` determining whether the nuclide's atomic number Z will be printed as a subscript beneath the atomic mass
Outputs:
- LaTeX-formatted raw string of nuclide
'''
tex_str = r''
# remove unwanted characters from provided string
delete_characters_list = [' ', '-', '_']
for dc in delete_characters_list:
nuc_str = nuc_str.replace(dc,'')
# determine which characters are letters versus numbers
isalpha_list = []
isdigit_list = []
for c in nuc_str:
isalpha_list.append(c.isalpha())
isdigit_list.append(c.isdigit())
symbol = ''
mass = ''
isost = ''
# string MUST begin with either mass number or elemental symbol
if isdigit_list[0] or nuc_str[0:3]=='nat': # mass first
mass_first = True
else:
mass_first = False
if mass_first:
if nuc_str[0:3]=='nat':
mass = 'nat'
ci = 3
else:
ci = 0
while isdigit_list[ci]:
mass += nuc_str[ci]
ci += 1
mass = str(int(mass)) # eliminate any extra leading zeros
# encountered a non-numeric character, end of mass
# now, determine if metastable state is listed or if element is listed next
# first, check to see if any other numerals are in string
lni = 0 # last numeral index
for i in range(ci,len(nuc_str)):
if isdigit_list[i]:
lni = i
if lni != 0:
# grab all characters between ci and last numeral as metastable state
isost = nuc_str[ci:lni+1]
ci = lni + 1
else: # no more numerals in string, now check for single lower-case letter
if isalpha_list[ci] and nuc_str[ci].islower():
isost = nuc_str[ci]
ci += 1
# Now extract elemental symbol
for i in range(ci,len(nuc_str)):
if isalpha_list[i]:
symbol += nuc_str[i]
else: # if elemental symbol is listed first
if 'nat' in nuc_str:
mass = 'nat'
nuc_str = nuc_str.replace('nat','')
ci = 0
# Extract all characters before first number as the elemental symbol
while nuc_str[ci].isalpha():
symbol += nuc_str[ci]
ci += 1
# now, extract mass
if mass != 'nat':
while nuc_str[ci].isdigit():
mass += nuc_str[ci]
ci += 1
if ci == len(nuc_str):
break
# lastly, extract isomeric state, if present
if ci != len(nuc_str):
isost = nuc_str[ci:]
# treating the cases of lowercase-specified particles (n, d, t, etc.)
if symbol == '' and isost != '':
symbol = isost
isost = ''
# Now assemble LaTeX string for nuclides
if include_Z:
if symbol == 'n':
Z = 0
elif symbol == 'p' or symbol == 'd' or symbol == 't':
Z = 1
else:
Z = Element_Sym_to_Z(symbol)
Z = str(int(Z))
tex_str = r"$^{{{}{}}}_{{{}}}$".format(mass,isost,Z) + "{}".format(symbol)
else:
tex_str = r"$^{{{}{}}}$".format(mass,isost) + "{}".format(symbol)
return tex_str
def nuclide_plain_str_ZZZAAAM(nuc_str):
'''
Description:
Converts a plaintext string of a nuclide to an integer ZZZAAAM = 10000\*Z + 10\*A + M
Dependencies:
`Element_Z_to_Sym`
Inputs:
- `nuc_str` = string to be converted; a huge variety of formats are supported, but they all must follow the following rules:
+ Isomeric/metastable state characters must always immediately follow the atomic mass characters.
Isomeric state labels MUST either:
- (1) be a single lower-case character OR
- (2) begin with any non-numeric character and end with a number
+ Atomic mass numbers must be nonnegative integers OR the string "nat" (in which case no metastable states can be written)
+ Elemental symbols MUST begin with an upper-case character
Outputs:
- ZZZAAAM integer
'''
# remove unwanted characters from provided string
delete_characters_list = [' ', '-', '_']
for dc in delete_characters_list:
nuc_str = nuc_str.replace(dc,'')
# determine which characters are letters versus numbers
isalpha_list = []
isdigit_list = []
for c in nuc_str:
isalpha_list.append(c.isalpha())
isdigit_list.append(c.isdigit())
symbol = ''
mass = ''
isost = ''
if 'nat' in nuc_str:
print('Must specify a specific nuclide, not natural abundances')
return None
# string MUST begin with either mass number or elemental symbol
if isdigit_list[0]: # mass first
mass_first = True
else:
mass_first = False
if mass_first:
ci = 0
while isdigit_list[ci]:
mass += nuc_str[ci]
ci += 1
mass = str(int(mass)) # eliminate any extra leading zeros
# encountered a non-numeric character, end of mass
# now, determine if metastable state is listed or if element is listed next
# first, check to see if any other numerals are in string
lni = 0 # last numeral index
for i in range(ci,len(nuc_str)):
if isdigit_list[i]:
lni = i
if lni != 0:
# grab all characters between ci and last numeral as metastable state
isost = nuc_str[ci:lni+1]
ci = lni + 1
else: # no more numerals in string, now check for single lower-case letter
if isalpha_list[ci] and nuc_str[ci].islower():
isost = nuc_str[ci]
ci += 1
# Now extract elemental symbol
for i in range(ci,len(nuc_str)):
if isalpha_list[i]:
symbol += nuc_str[i]
else: # if elemental symbol is listed first
ci = 0
# Extract all characters before first number as the elemental symbol
while nuc_str[ci].isalpha():
symbol += nuc_str[ci]
ci += 1
# now, extract mass
while nuc_str[ci].isdigit():
mass += nuc_str[ci]
ci += 1
if ci == len(nuc_str):
break
# lastly, extract isomeric state, if present
if ci != len(nuc_str):
isost = nuc_str[ci:]
# treating the cases of lowercase-specified particles (n, d, t, etc.)
if symbol == '' and isost != '':
symbol = isost
isost = ''
if symbol == 'n':
Z = 0
elif symbol == 'p' or symbol == 'd' or symbol == 't':
Z = 1
else:
Z = Element_Sym_to_Z(symbol)
A = int(mass)
if isost.strip()=='' or isost=='g':
M = 0
elif isost=='m' or isost=='m1':
M = 1
elif isost=='n' or isost=='m2':
M = 2
elif isost=='o' or isost=='m3':
M = 3
elif isost=='p' or isost=='m4':
M = 4
elif isost=='q' or isost=='m5':
M = 5
else:
print("Unknown isomeric state {}, assumed ground state".format(isost))
M = 0
ZZZAAAM = 10000*Z + 10*A + M
return ZZZAAAM
def time_str_to_sec_multiplier(time_str):
'''
Description:
Provide a time unit and this function provides what those time units need to be multiplied by to obtain seconds.
Inputs:
- `time_str` = string containing time units character(s) [s,m,h,d,y,ms,us,ns,ps,fs]
Outputs:
- `m` = multiplier to convert a time of the supplied units to seconds
'''
try:
if time_str == 's':
m = 1
elif time_str == 'm':
m = 60
elif time_str == 'h':
m = 60*60
elif time_str == 'd':
m = 60*60*24
elif time_str == 'y':
m = 60*60*24*365.25
elif time_str == 'ms':
m = 1e-3
elif time_str == 'us':
m = 1e-6
elif time_str == 'ns':
m = 1e-9
elif time_str == 'ps':
m = 1e-12
elif time_str == 'fs':
m = 1e-15
return m
except:
print('"{}" is not a valid time unit; please use one of the following: [s,m,h,d,y,ms,us,ns,ps,fs]'.format(time_str))
return None
def seconds_to_dhms(t_sec):
'''
Description:
Provide a time in seconds and obtain a string with the time in days, hours, minutes, and seconds
Inputs:
- `t_sec` = a time in seconds (float or int)
Outputs:
- `time_str` = string containing the time prettily formatted in d/h/m/s format
'''
m, s = divmod(t_sec, 60)
h, m = divmod(m, 60)
d, h = divmod(h, 24)
if d != 0:
time_str = "{:0.0f}d {:0.0f}h {:0.0f}m {:0.2f}s".format(d,h,m,s)
elif h != 0:
time_str = "{:0.0f}h {:0.0f}m {:0.2f}s".format(h,m,s)
elif m != 0:
time_str = "{:0.0f}m {:0.2f}s".format(m,s)
elif s != 0:
time_str = "{:0.2f}s".format(s)
else:
time_str = ""
return time_str
def seconds_to_ydhms(t_sec):
'''
Description:
Provide a time in seconds and obtain a string with the time in years, days, hours, minutes, and seconds
Inputs:
- `t_sec` = a time in seconds (float or int)
Outputs:
- `time_str` = string containing the time prettily formatted in y/d/h/m/s format
'''
m, s = divmod(t_sec, 60)
h, m = divmod(m, 60)
d, h = divmod(h, 24)
y, d = divmod(d, 365)
if y>=4 : # if leap year occurred
n_leap_years = int(y/4)
d = d-n_leap_years
if y != 0:
time_str = "{:0.0f}y {:0.0f}d {:0.0f}h {:0.0f}m {:0.2f}s".format(y,d,h,m,s)
elif d != 0:
time_str = "{:0.0f}d {:0.0f}h {:0.0f}m {:0.2f}s".format(d,h,m,s)
elif h != 0:
time_str = "{:0.0f}h {:0.0f}m {:0.2f}s".format(h,m,s)
elif m != 0:
time_str = "{:0.0f}m {:0.2f}s".format(m,s)
elif s != 0:
time_str = "{:0.2f}s".format(s)
else:
time_str = ""
return time_str
show_output_from_example = False
if show_output_from_example:
test_folder = r'example\\'
test_basename = 'example_Na22'
output = process_dchain_simulation_output(test_folder,test_basename)
print('\n')
print('Output times relative to start (in seconds):',output['time']['from_start_sec'])
print('Output times relative to EOB (in seconds): ',output.time.from_EOB_sec)
print('\n')
print('Total neutron flux in first region (in n/cm^2/sec):',output['region']['neutron_flux'][0])
print('Fractional uncertainty in total neutron flux in first region:',output['neutron']['total_flux']['error'][0]/output['neutron']['total_flux']['value'][0])
print('\n')
print('All produced nuclides (in DCHAIN-formatted strings):',output['nuclides']['names'])
#print(np.shape(np.array(output['gamma']['spectra']['flux']['value'])))
#print(output['gamma']['spectra']['flux']['value'][0][0,:])
#pprint.pprint(output['top10']['activity']['rank'][0][0,:])
print('\n')
print('[T-Yield] high energy reaction-produced nuclides:',output['yields']['names'][0])
print('[T-Yield] nuclide yields per source particle:',output['yields']['unit_rate']['value'][0])
print('\n')
library_file = r'C:\phits\dchain-sp\data\JEFF-3-3--_n_act_xs_lib'
#xs_out, rxn_str_out = retrieve_rxn_xs_from_lib(library_file,'F-19','p')
xs_1g = calc_one_group_nrxn_xs_dchain(output['neutron']['unit_spectra']['flux']['value'][0],output['neutron']['unit_spectra']['flux']['error'][0],library_file,'F-19','p')
print('Single group cross section (and its absolute uncertainty) for 19F(n,p)19O reaction in provided neutron flux (in barns): ',xs_1g)
figs = plot_top10_nuclides(output,region_indices=1,rank_cutoff=5,xaxis_val='time',xaxis_type='indices',xscale='linear')
plt.show()Functions
def process_dchain_simulation_output(simulation_folder_path, simulation_basename, dtrk_filepath=None, dyld_filepath=None, process_DCS_file=False)-
Description
This is intended to be a single master function for processing DCHAIN output.
Dependencies
from munch import *
Inputs
simulation_folder_path= text string of path to folder containing simulation output (should end with forward slash/or backslash\)simulation_basename= common string of the DCHAIN simulations; output files are named THIS_NAME.*dtrk_filepath= file path to *.dtrk file, only necessary if it has a different basename and there are multiple *.dtrk files in the folderdyld_filepath= file path to *.dyld files, only necessary if it has a different basename and there are multiple *.dyld files in the folderprocess_DCS_file(optional) = Boolean variable specifying whether the DCS file should be processed too. (D=False)
Outputs
-
dchain_output= a dictionary object containing all information from DCHAIN's output files. See the keys breakdown below.Technically, it tries to return a "munchify" object which can be used both exactly like a dictionary but also provides attribute-style access like a namedtuple or Class object such as
dchain_output.time.of_EOB_secrather than the dictionary styledchain_output['time']['of_EOB_sec']
dchain_output dictionary structure:
# Notation for output array dimensions # R regions # T time steps # N max number of nuclides found in a single region # E number of gamma energy bins # le10 for top 10 lists, a number <= 10 { dchain_output = { 'time':{ # ~ Time information 'from_start_sec' # [T] list of times from start time [sec] 'from_EOB_sec' # [T] times from end of final bombardment [sec] 'of_EOB_sec' # scalar time of end of final bombardment [sec] } 'region':{ # ~ Information which only varies with region 'numbers' # [R] region numbers 'number' # [R] region numbers 'irradiation_time_sec' # [R] irradiation time per region 'volume' # [R] volume in [cc] per region 'neutron_flux' # [R] neutron flux in [n/cm^2/s] per region 'beam_power_MW' # [R] beam power in [MW] per region 'beam_energy_GeV' # [R] beam energy in [GeV] per region 'beam_current_mA' # [R] beam current in [mA] per region } 'nuclides':{ # ~ Main nuclide results from *.act file 'names' # [R][N] names of nuclides produced in each region 'TeX_names' # [R][N] LaTeX-formatted names of nuclides produced 'ZZZAAAM' # [R][N] ZZZAAAM values (=10000Z+10A+M) of nuclides # (ground state m=0, metastable m=1,2,etc.) 'half_life' # [R][N] half lives of nuclides produced [sec] 'inventory':{'value' # [R][T,N] atoms [#/cc] 'error'} # [R][T,N] atoms [#/cc] 'activity':{'value' # [R][T,N] activity [Bq/cc] 'error'} # [R][T,N] activity [Bq/cc] 'dose_rate':{'value' # [R][T,N] dose-rate [uSv/h*m^2] 'error'} # [R][T,N] dose-rate [uSv/h*m^2] 'decay_heat':{ 'total':{'value' # [R][T,N] total decay heat [W/cc] 'error'} # [R][T,N] total decay heat [W/cc] 'beta':{'value' # [R][T,N] beta decay heat [W/cc] 'error'} # [R][T,N] beta decay heat [W/cc] 'gamma':{'value' # [R][T,N] gamma decay heat [W/cc] 'error'} # [R][T,N] gamma decay heat [W/cc] 'alpha':{'value' # [R][T,N] alpha decay heat [W/cc] 'error'} # [R][T,N] alpha decay heat [W/cc] } 'column_headers' # Length 7 list of the *.act columns' descriptions 'total':{ # ~ Total values summed over all nuclides 'activity':{'value' # [R][T] total activity [Bq/cc] 'error'} # [R][T] total activity [Bq/cc] 'decay_heat':{'value' # [R][T] total decay heat [W/cc] 'error'} # [R][T] total decay heat [W/cc] 'beta_heat':{'value' # [R][T] total beta decay heat [W/cc] 'error'} # [R][T] total beta decay heat [W/cc] 'gamma_heat':{'value' # [R][T] total gamma decay heat [W/cc] 'error'} # [R][T] total gamma decay heat [W/cc] 'alpha_heat':{'value' # [R][T] total alpha decay heat [W/cc] 'error'} # [R][T] total alpha decay heat [W/cc] 'activated_atoms':{'value' # [R][T] total activated atoms [#/cc] 'error'} # [R][T] total activated atoms [#/cc] 'gamma_dose_rate':{'value' # [R][T] total gamma dose rate [uSV/h*m^2] 'error'} # [R][T] total gamma dose rate [uSV/h*m^2] } } 'gamma':{ # ~ Gamma spectra and totals 'spectra':{ 'group_number' # [R][T,E] group number 'E_lower' # [R][T,E] bin energy lower-bound [MeV] 'E_upper' # [R][T,E] bin energy upper-bound [MeV] 'flux':{'value' # [R][T,E] flux [#/s/cc] 'error'} # [R][T,E] flux [#/s/cc] 'energy_flux':{'value' # [R][T,E] energy flux [MeV/s/cc] 'error'} # [R][T,E] energy flux [MeV/s/cc] } 'total_flux':{'value' # [R][T] total gamma flux [#/s/cc] 'error'} # [R][T] total gamma flux [#/s/cc] 'total_energy_flux':{'value' # [R][T] total gamma energy flux [MeV/s/cc] 'error'} # [R][T] total gamma energy flux [MeV/s/cc] 'annihilation_flux':{'value' # [R][T] annihilation gamma flux [#/s/cc] 'error'} # [R][T] annihilation gamma flux [#/s/cc] 'current_underflow':{'value' # [R][T] gamma current underflow [#/s] 'error'} # no error reported 'current_overflow':{'value' # [R][T] gamma current overflow [#/s] 'error'} # no error reported } 'top10':{ # ~ Top 10 lists from *.act file 'activity':{ 'rank' # [R][T,le10] rank 'nuclide' # [R][T,le10] nuclide name 'value' # [R][T,le10] activity [Bq/cc] 'error' # [R][T,le10] activity [Bq/cc] 'percent' # [R][T,le10] percent of total activity } 'decay_heat':{ 'rank' # [R][T,le10] rank 'nuclide' # [R][T,le10] nuclide name 'value' # [R][T,le10] decay heat [W/cc] 'error' # [R][T,le10] decay heat [W/cc] 'percent' # [R][T,le10] percent of total decay heat } 'gamma_dose':{ 'rank': # [R][T,le10] rank 'nuclide' # [R][T,le10] nuclide name 'value' # [R][T,le10] dose-rate [uSv/h*m^2] 'error' # [R][T,le10] dose-rate [uSv/h*m^2] 'percent' # [R][T,le10] percent of total gamma dose rate } } 'number_of':{ # ~ Maximum values of R, T, N, and E 'regions' # R = total number of regions 'time_steps' # T = total number of time steps 'max_nuclides_in_any_region' # N = maximum unique nuclides found in any region 'gamma_energy_bins' # E = number of gamma energy bins (default=42) } } if process_dtrk_file: dchain_output.update({ 'neutron':{ # ~ Neutron spectra and totals 'spectra':{ # - Actual values used in DCHAIN 'E_lower' # [R][E] bin energy lower-bound [MeV] 'E_upper' # [R][E] bin energy upper-bound [MeV] 'flux':{'value' # [R][E] neutron flux [#/s/cm^2] 'error'} # [R][E] neutron flux [#/s/cm^2] } 'total_flux':{'value' # [R] total neutron flux [#/s/cm^2] 'error'} # [R] total neutron flux [#/s/cm^2] 'unit_spectra':{ # - Flux per unit source particle 'E_lower' # [R][E] bin energy lower-bound [MeV] 'E_upper' # [R][E] bin energy upper-bound [MeV] 'flux':{'value' # [R][E] neutron flux [#/s/cm^2/s.p.] 'error'} # [R][E] neutron flux [#/s/cm^2/s.p.] } } }) if process_dyld_files: dchain_output.update({ 'yields':{ # ~ Yield spectra 'all_names' # [N] names of all nuclides produced 'names' # [R][N] names of nuclides produced in each region 'TeX_names' # [R][N] LaTeX-formatted names of nuclides produced 'ZZZAAAM' # [R][N] ZZZAAAM values (=10000Z+10A+M) of nuclides # (ground state m=0, metastable m=1,2,etc.) 'rate':{ # - Actual values used in DCHAIN (100% beam power) 'value' # [R][E] nuclide yield rate [#/s/cm^3] 'error' # [R][E] nuclide yield rate [#/s/cm^3] } 'unit_spectra':{ # - Yields per unit source particle 'value' # [R][E] nuclide yield rate [#/s.p.] 'error' # [R][E] nuclide yield rate [#/s.p.] } } }) if process_DCS_file: # add extra information # Notation for output array dimensions # R (n_reg) regions # Td (ntsteps) time steps in DCS file (usually differs from that of *.act file!) # Nd (nnuc_max) max number of nuclides (this index differs from the *.act N index) # C (chni_max) maximum index of relevant chains # L (chln_max) maximum number of links per chain dchain_output.update({ 'DCS':{ 'time':{ 'from_start_sec' # [Td] list of times from start time [sec] 'from_EOB_sec' # [Td] times from end of final bombardment [sec] 'of_EOB_sec' # scalar time of end of final bombardment [sec] } 'number_of':{ # ~ Maximum values of R, Td, Nd, C, and L 'regions' # R = total number of regions 'time_steps' # Td = total number of time steps 'max_nuclides' # Nd = max number of end nuclides in any time step 'max_number_of_chains' # C = highest index of a relevant chain found 'max_chain_length' # L = max number of links (nuclides) in any chain } 'end_nuclide':{ # ~ Informtaion on nuclides ending each chain 'names' # [R][Td,Nd] nuclide names 'inventory':{ 'N_previous' # [R][Td,Nd,C] N in previous time step [atoms/cc] 'N_now' # [R][Td,Nd,C] N in current time step [atoms/cc] 'dN' # [R][Td,Nd,C] change in N of end nuclide from # prev. to current time step [atoms/cc] } 'activity':{ 'A_previous' # [R][Td,Nd,C] A in previous time step [Bq/cc] 'A_now' # [R][Td,Nd,C] A in the current time step [Bq/cc] 'dA' # [R][Td,Nd,C] change in A of end nuclide from # prev. to current time step [Bq/cc] } } 'chains':{ # ~ Chains, links, and their contributions 'indices_of_printed_chains' # [R][Td,Nd] list of chain indices printed to # *.dcs, valid values of C index 'length' # [R][Td,Nd,C] length of listed chain, L max index 'link_nuclides' # [R][Td,Nd,C,L] strings of nuclides in each chain 'link_decay_modes' # [R][Td,Nd,C,L] strings of decay modes each link # undergoes to produce the next link 'link_dN':{ # (only filled if values in file, 'None' otherwise) 'beam' # [R][Td,Nd,C,L] beam contribution to dN per link 'decay_nrxn' # [R][Td,Nd,C,L] decay/neutron rxn dN contribution 'total' # [R][Td,Nd,C,L] total contribution to dN per link } } 'relevant_nuclides':{ # ~ A vs t of nuclides over relevancy threshold 'names' # [R] list of relevant nuclides per region 'times' # [R][Td,Nd] time [s] 'inventory' # [R][Td,Nd] inventory [atm/cc] 'activity' # [R][Td,Nd] activity [Bq/cc] } } })Expand source code
def process_dchain_simulation_output(simulation_folder_path,simulation_basename,dtrk_filepath=None,dyld_filepath=None,process_DCS_file=False): ''' Description: This is intended to be a single master function for processing DCHAIN output. Dependencies: from munch import * Inputs: - `simulation_folder_path` = text string of path to folder containing simulation output (should end with forward slash `/` or backslash `\`) - `simulation_basename` = common string of the DCHAIN simulations; output files are named THIS_NAME.* - `dtrk_filepath` = file path to \*.dtrk file, only necessary if it has a different basename and there are multiple \*.dtrk files in the folder - `dyld_filepath` = file path to \*.dyld files, only necessary if it has a different basename and there are multiple \*.dyld files in the folder - `process_DCS_file` (optional) = Boolean variable specifying whether the DCS file should be processed too. (D=False) Outputs: - `dchain_output` = a dictionary object containing all information from DCHAIN's output files. See the keys breakdown below. Technically, it tries to return a "munchify" object which can be used both exactly like a dictionary but also provides attribute-style access like a namedtuple or Class object such as `dchain_output.time.of_EOB_sec` rather than the dictionary style `dchain_output['time']['of_EOB_sec']` dchain_output dictionary structure: -------- # Notation for output array dimensions # R regions # T time steps # N max number of nuclides found in a single region # E number of gamma energy bins # le10 for top 10 lists, a number <= 10 { dchain_output = { 'time':{ # ~ Time information 'from_start_sec' # [T] list of times from start time [sec] 'from_EOB_sec' # [T] times from end of final bombardment [sec] 'of_EOB_sec' # scalar time of end of final bombardment [sec] } 'region':{ # ~ Information which only varies with region 'numbers' # [R] region numbers 'number' # [R] region numbers 'irradiation_time_sec' # [R] irradiation time per region 'volume' # [R] volume in [cc] per region 'neutron_flux' # [R] neutron flux in [n/cm^2/s] per region 'beam_power_MW' # [R] beam power in [MW] per region 'beam_energy_GeV' # [R] beam energy in [GeV] per region 'beam_current_mA' # [R] beam current in [mA] per region } 'nuclides':{ # ~ Main nuclide results from *.act file 'names' # [R][N] names of nuclides produced in each region 'TeX_names' # [R][N] LaTeX-formatted names of nuclides produced 'ZZZAAAM' # [R][N] ZZZAAAM values (=10000Z+10A+M) of nuclides # (ground state m=0, metastable m=1,2,etc.) 'half_life' # [R][N] half lives of nuclides produced [sec] 'inventory':{'value' # [R][T,N] atoms [#/cc] 'error'} # [R][T,N] atoms [#/cc] 'activity':{'value' # [R][T,N] activity [Bq/cc] 'error'} # [R][T,N] activity [Bq/cc] 'dose_rate':{'value' # [R][T,N] dose-rate [uSv/h*m^2] 'error'} # [R][T,N] dose-rate [uSv/h*m^2] 'decay_heat':{ 'total':{'value' # [R][T,N] total decay heat [W/cc] 'error'} # [R][T,N] total decay heat [W/cc] 'beta':{'value' # [R][T,N] beta decay heat [W/cc] 'error'} # [R][T,N] beta decay heat [W/cc] 'gamma':{'value' # [R][T,N] gamma decay heat [W/cc] 'error'} # [R][T,N] gamma decay heat [W/cc] 'alpha':{'value' # [R][T,N] alpha decay heat [W/cc] 'error'} # [R][T,N] alpha decay heat [W/cc] } 'column_headers' # Length 7 list of the *.act columns' descriptions 'total':{ # ~ Total values summed over all nuclides 'activity':{'value' # [R][T] total activity [Bq/cc] 'error'} # [R][T] total activity [Bq/cc] 'decay_heat':{'value' # [R][T] total decay heat [W/cc] 'error'} # [R][T] total decay heat [W/cc] 'beta_heat':{'value' # [R][T] total beta decay heat [W/cc] 'error'} # [R][T] total beta decay heat [W/cc] 'gamma_heat':{'value' # [R][T] total gamma decay heat [W/cc] 'error'} # [R][T] total gamma decay heat [W/cc] 'alpha_heat':{'value' # [R][T] total alpha decay heat [W/cc] 'error'} # [R][T] total alpha decay heat [W/cc] 'activated_atoms':{'value' # [R][T] total activated atoms [#/cc] 'error'} # [R][T] total activated atoms [#/cc] 'gamma_dose_rate':{'value' # [R][T] total gamma dose rate [uSV/h*m^2] 'error'} # [R][T] total gamma dose rate [uSV/h*m^2] } } 'gamma':{ # ~ Gamma spectra and totals 'spectra':{ 'group_number' # [R][T,E] group number 'E_lower' # [R][T,E] bin energy lower-bound [MeV] 'E_upper' # [R][T,E] bin energy upper-bound [MeV] 'flux':{'value' # [R][T,E] flux [#/s/cc] 'error'} # [R][T,E] flux [#/s/cc] 'energy_flux':{'value' # [R][T,E] energy flux [MeV/s/cc] 'error'} # [R][T,E] energy flux [MeV/s/cc] } 'total_flux':{'value' # [R][T] total gamma flux [#/s/cc] 'error'} # [R][T] total gamma flux [#/s/cc] 'total_energy_flux':{'value' # [R][T] total gamma energy flux [MeV/s/cc] 'error'} # [R][T] total gamma energy flux [MeV/s/cc] 'annihilation_flux':{'value' # [R][T] annihilation gamma flux [#/s/cc] 'error'} # [R][T] annihilation gamma flux [#/s/cc] 'current_underflow':{'value' # [R][T] gamma current underflow [#/s] 'error'} # no error reported 'current_overflow':{'value' # [R][T] gamma current overflow [#/s] 'error'} # no error reported } 'top10':{ # ~ Top 10 lists from *.act file 'activity':{ 'rank' # [R][T,le10] rank 'nuclide' # [R][T,le10] nuclide name 'value' # [R][T,le10] activity [Bq/cc] 'error' # [R][T,le10] activity [Bq/cc] 'percent' # [R][T,le10] percent of total activity } 'decay_heat':{ 'rank' # [R][T,le10] rank 'nuclide' # [R][T,le10] nuclide name 'value' # [R][T,le10] decay heat [W/cc] 'error' # [R][T,le10] decay heat [W/cc] 'percent' # [R][T,le10] percent of total decay heat } 'gamma_dose':{ 'rank': # [R][T,le10] rank 'nuclide' # [R][T,le10] nuclide name 'value' # [R][T,le10] dose-rate [uSv/h*m^2] 'error' # [R][T,le10] dose-rate [uSv/h*m^2] 'percent' # [R][T,le10] percent of total gamma dose rate } } 'number_of':{ # ~ Maximum values of R, T, N, and E 'regions' # R = total number of regions 'time_steps' # T = total number of time steps 'max_nuclides_in_any_region' # N = maximum unique nuclides found in any region 'gamma_energy_bins' # E = number of gamma energy bins (default=42) } } if process_dtrk_file: dchain_output.update({ 'neutron':{ # ~ Neutron spectra and totals 'spectra':{ # - Actual values used in DCHAIN 'E_lower' # [R][E] bin energy lower-bound [MeV] 'E_upper' # [R][E] bin energy upper-bound [MeV] 'flux':{'value' # [R][E] neutron flux [#/s/cm^2] 'error'} # [R][E] neutron flux [#/s/cm^2] } 'total_flux':{'value' # [R] total neutron flux [#/s/cm^2] 'error'} # [R] total neutron flux [#/s/cm^2] 'unit_spectra':{ # - Flux per unit source particle 'E_lower' # [R][E] bin energy lower-bound [MeV] 'E_upper' # [R][E] bin energy upper-bound [MeV] 'flux':{'value' # [R][E] neutron flux [#/s/cm^2/s.p.] 'error'} # [R][E] neutron flux [#/s/cm^2/s.p.] } } }) if process_dyld_files: dchain_output.update({ 'yields':{ # ~ Yield spectra 'all_names' # [N] names of all nuclides produced 'names' # [R][N] names of nuclides produced in each region 'TeX_names' # [R][N] LaTeX-formatted names of nuclides produced 'ZZZAAAM' # [R][N] ZZZAAAM values (=10000Z+10A+M) of nuclides # (ground state m=0, metastable m=1,2,etc.) 'rate':{ # - Actual values used in DCHAIN (100% beam power) 'value' # [R][E] nuclide yield rate [#/s/cm^3] 'error' # [R][E] nuclide yield rate [#/s/cm^3] } 'unit_spectra':{ # - Yields per unit source particle 'value' # [R][E] nuclide yield rate [#/s.p.] 'error' # [R][E] nuclide yield rate [#/s.p.] } } }) if process_DCS_file: # add extra information # Notation for output array dimensions # R (n_reg) regions # Td (ntsteps) time steps in DCS file (usually differs from that of *.act file!) # Nd (nnuc_max) max number of nuclides (this index differs from the *.act N index) # C (chni_max) maximum index of relevant chains # L (chln_max) maximum number of links per chain dchain_output.update({ 'DCS':{ 'time':{ 'from_start_sec' # [Td] list of times from start time [sec] 'from_EOB_sec' # [Td] times from end of final bombardment [sec] 'of_EOB_sec' # scalar time of end of final bombardment [sec] } 'number_of':{ # ~ Maximum values of R, Td, Nd, C, and L 'regions' # R = total number of regions 'time_steps' # Td = total number of time steps 'max_nuclides' # Nd = max number of end nuclides in any time step 'max_number_of_chains' # C = highest index of a relevant chain found 'max_chain_length' # L = max number of links (nuclides) in any chain } 'end_nuclide':{ # ~ Informtaion on nuclides ending each chain 'names' # [R][Td,Nd] nuclide names 'inventory':{ 'N_previous' # [R][Td,Nd,C] N in previous time step [atoms/cc] 'N_now' # [R][Td,Nd,C] N in current time step [atoms/cc] 'dN' # [R][Td,Nd,C] change in N of end nuclide from # prev. to current time step [atoms/cc] } 'activity':{ 'A_previous' # [R][Td,Nd,C] A in previous time step [Bq/cc] 'A_now' # [R][Td,Nd,C] A in the current time step [Bq/cc] 'dA' # [R][Td,Nd,C] change in A of end nuclide from # prev. to current time step [Bq/cc] } } 'chains':{ # ~ Chains, links, and their contributions 'indices_of_printed_chains' # [R][Td,Nd] list of chain indices printed to # *.dcs, valid values of C index 'length' # [R][Td,Nd,C] length of listed chain, L max index 'link_nuclides' # [R][Td,Nd,C,L] strings of nuclides in each chain 'link_decay_modes' # [R][Td,Nd,C,L] strings of decay modes each link # undergoes to produce the next link 'link_dN':{ # (only filled if values in file, 'None' otherwise) 'beam' # [R][Td,Nd,C,L] beam contribution to dN per link 'decay_nrxn' # [R][Td,Nd,C,L] decay/neutron rxn dN contribution 'total' # [R][Td,Nd,C,L] total contribution to dN per link } } 'relevant_nuclides':{ # ~ A vs t of nuclides over relevancy threshold 'names' # [R] list of relevant nuclides per region 'times' # [R][Td,Nd] time [s] 'inventory' # [R][Td,Nd] inventory [atm/cc] 'activity' # [R][Td,Nd] activity [Bq/cc] } } }) ''' global start try: start_time = start except: start_time = time.time() start = start_time if simulation_basename[-3:] == '.in': simulation_basename = simulation_basename[:-3] simulation_file_basic_path = simulation_folder_path + simulation_basename # only need to add output file extension act_file = simulation_file_basic_path + '.act' dcs_file = simulation_file_basic_path + '.dcs' process_dtrk_file = True if dtrk_filepath: # DTRK file manually provided dtrk_file = dtrk_filepath if not os.path.exists(dtrk_file): print(' Provided .dtrk file could not be found: {}'.format(dtrk_filepath)) process_dtrk_file = False else: # automatically find DTRK file dtrk_file = simulation_file_basic_path + '.dtrk' if not os.path.exists(dtrk_file): # look for any files with the .dtrk extension in the simulation folder path valid_files = [] valid_filepaths = [] for file in os.listdir(simulation_folder_path): if file.endswith(".dtrk"): valid_files.append(file) valid_filepaths.append(os.path.join(simulation_folder_path, file)) if len(valid_files)>0: print(' Could not find default .dtrk file {}, using {} in same directory instead.'.format(simulation_basename + '.dtrk',valid_files[0])) dtrk_file = valid_filepaths[0] else: print(' No .dtrk files could not be found in provided simulation folder: {}'.format(simulation_folder_path)) process_dtrk_file = False if process_dtrk_file: neutron_flux, dtrk_metadata = parse_dtrk_file(dtrk_file,return_metadata=True) process_dyld_file = True if dyld_filepath: # dyld file manually provided dyld_file = dyld_filepath if not os.path.exists(dyld_file): print(' Provided .dyld file could not be found: {}'.format(dyld_filepath)) process_dyld_file = False else: # automatically find dyld file dyld_file = simulation_file_basic_path + '.dyld' if not os.path.exists(dyld_file): # look for any files with the .dyld extension in the simulation folder path valid_files = [] valid_filepaths = [] for file in os.listdir(simulation_folder_path): if file.endswith(".dyld"): valid_files.append(file) valid_filepaths.append(os.path.join(simulation_folder_path, file)) if len(valid_files)>0: print(' Could not find default .dyld file {}, using {} in same directory instead.'.format(simulation_basename + '.dyld',valid_files[0])) dyld_file = valid_filepaths[0] else: print(' No .dyld files could not be found in provided simulation folder: {}'.format(simulation_folder_path)) process_dyld_file = False print('{:<50} ({:0.2f} seconds elapsed)'.format(' Parsing DCHAIN activation file...',time.time()-start)) parse_DCHAIN_act_file_OUTPUT = parse_DCHAIN_act_file(act_file) reg_nos = parse_DCHAIN_act_file_OUTPUT[0] # length R list of region numbers time_list_sec = parse_DCHAIN_act_file_OUTPUT[1] # length T list of measurement times (in sec) from start of irradiation time_list_sec_after_EOB = parse_DCHAIN_act_file_OUTPUT[2] # length T list of measurement times (in sec) from end of last irradiation irradiation_end_t = parse_DCHAIN_act_file_OUTPUT[3] # time of end of irradiation (in sec) nuclides_produced = parse_DCHAIN_act_file_OUTPUT[4] # NumPy array of dimension RxTxNx11x2 of nuclide table data (N=max recorded table lenth) (last index 0=value, 1=abs error) [0='nuclide',1='atoms [#/cc]',2='activity [Bq/cc]',3='activity [Bq]',4='rate [%]',5='beta decay heat [W/cc]',6='gamma decay heat [W/cc]',7='alpha decay heat [W/cc]',8='total decay heat [W/cc]',9='half life [s]',10='dose-rate [uSv/h*m^2]'] gamma_spectra = parse_DCHAIN_act_file_OUTPUT[5] # NumPy array of dimension RxTxEx5x2 of gamma spectrum table data (last index 0=value, 1=abs error) [0='group number',1='bin energy lower-bound [MeV]',2='bin energy upper-bound [MeV]',3='flux [#/s/cc]',4='energy flux [MeV/s/cc]'] top10_lists = parse_DCHAIN_act_file_OUTPUT[6] # NumPy array of dimension RxTxNx12x2 of top-10 list table data (last index 0=value, 1=abs error) [0='rank',1='nuclide - Activity ranking',2='activity [Bq/cc]',3='activity [Bq]',4='rate [%]',5='nuclide - Decay heat ranking',6='decay heat [W/cc]',7='decay heat [W]',8='rate [%]',9='nuclide - Dose rate ranking',10='dose-rate [uSv/h*m^2]',11='rate [%]'] column_headers = parse_DCHAIN_act_file_OUTPUT[7] # List containing 3 lists of column headers for the preceding three NumPy arrays summary_info = parse_DCHAIN_act_file_OUTPUT[8] # list of the below lists/arrays of summary information r_summary_info = summary_info[0] # NumPy array of dimension Rx7 of region-specific summary info [0='region number',1='irradiation time [s]',2='region volume [cc]',3='neutron flux [n/cm^2/s]',4='beam power [MW]',5='beam energy [GeV]',6='beam current [mA]'] r_summary_info_description = summary_info[1] # list of length 7 containing descriptions of the above items [0='region number',1='irradiation time [s]',2='region volume [cc]',3='neutron flux [n/cm^2/s]',4='beam power [MW]',5='beam energy [GeV]',6='beam current [mA]'] rt_summary_info = summary_info[2] # NumPy array of dimension RxTx12x2 of region and time-specific summary info (last index 0=value, 1=abs error) [0='total gamma flux [#/s/cc]',1='total gamma energy flux [MeV/s/cc]',2='annihilation gamma flux [#/s/cc]',3='gamma current underflow [#/s]',4='gamma current overflow [#/s]',5='total activity [Bq/cc]',6='total decay heat [W/cc]',7='beta decay heat [W/cc]',8='gamma decay heat [W/cc]',9='alpha decay heat [W/cc]',10='activated atoms [#/cc]',11='total gamma dose rate [uSV/h*m^2]'] rt_summary_info_description = summary_info[3] # list of length 12 containing descriptions of the above items [0='total gamma flux [#/s/cc]',1='total gamma energy flux [MeV/s/cc]',2='annihilation gamma flux [#/s/cc]',3='gamma current underflow [#/s]',4='gamma current overflow [#/s]',5='total activity [Bq/cc]',6='total decay heat [W/cc]',7='beta decay heat [W/cc]',8='gamma decay heat [W/cc]',9='alpha decay heat [W/cc]',10='activated atoms [#/cc]',11='total gamma dose rate [uSV/h*m^2]'] print('{:<50} ({:0.2f} seconds elapsed)'.format(' Restructuring nuclide data table array...',time.time()-start)) generate_nuclide_time_profiles_OUTPUT = generate_nuclide_time_profiles(nuclides_produced) nuclide_names = generate_nuclide_time_profiles_OUTPUT[0] # List of length R of lists containing names of nuclides produced in each region LaTeX_nuclide_names = generate_nuclide_time_profiles_OUTPUT[1] # List of length R of lists containing LaTeX-formatted names of nuclides produced in each region nuclide_ZAM_vals = generate_nuclide_time_profiles_OUTPUT[2] # List of length R of lists containing ZZZAAAM values (=10000*Z+10*A+M) of nuclides produced in each region (ground state m=0, metastable m=1,2,etc.) nuclide_half_lives = generate_nuclide_time_profiles_OUTPUT[3] # List of length R of lists containing half lives of nuclides produced in each region (in seconds) nuclide_info = generate_nuclide_time_profiles_OUTPUT[4] # List of length R of NumPy arrays of dimension TxNx7x2 of nuclide info (last index 0=value, 1=abs error) [0='atoms [#/cc]',1='activity [Bq/cc]','2=beta decay heat [W/cc]','3=gamma decay heat [W/cc]','4=alpha decay heat [W/cc]','5=total decay heat [W/cc]','6=dose-rate [uSv/h*m^2]'] nuclide_info_headers = generate_nuclide_time_profiles_OUTPUT[5] # List of length 7 containing text descriptions of the 7 columns of the info arrays [0='atoms [#/cc]',1='activity [Bq/cc]','2=beta decay heat [W/cc]','3=gamma decay heat [W/cc]','4=alpha decay heat [W/cc]','5=total decay heat [W/cc]','6=dose-rate [uSv/h*m^2]'] if process_dyld_file: if process_dtrk_file: if dtrk_metadata[0]=='dchain': iredufmt=1 else: # dtrk_metadata[0]=='eng' iredufmt=0 else: iredufmt=0 yields, nuclide_names_yld = parse_dyld_files(dyld_file,iredufmt=iredufmt) # Now reformat for more user-friendly output values # regionwise values beam_fluxs = (6.2415064e15)*r_summary_info[:,6] # particles/sec (converted from mA) reg_vols = r_summary_info[:,2] nregs,nnuc = np.shape(yields)[0],np.shape(yields)[1] reg_yld_names = [] reg_yld_texnames = [] reg_yld_zam = [] yield_values_by_reg = [[],[],[],[]] # yield, yield abs err, unit yield, unit yield abs err for ri in range(nregs): for ni in range(nnuc): if ni==0: reg_yld_names.append([]) reg_yld_texnames.append([]) reg_yld_zam.append([]) for j in range(4): yield_values_by_reg[j].append([]) if yields[ri,ni,0] != 0.0: reg_yld_names[-1].append(nuclide_names_yld[ni]) reg_yld_texnames[-1].append(Dname_to_Latex(nuclide_names_yld[ni])) reg_yld_zam[-1].append(Dname_to_ZAM(nuclide_names_yld[ni])) yield_values_by_reg[0][-1].append(beam_fluxs[ri]*yields[ri,ni,0]/reg_vols[ri]) yield_values_by_reg[1][-1].append(beam_fluxs[ri]*yields[ri,ni,1]/reg_vols[ri]) yield_values_by_reg[2][-1].append(yields[ri,ni,0]) yield_values_by_reg[3][-1].append(yields[ri,ni,1]) if process_DCS_file: # Control parameters relevancy_threshold=0.01 # fraction of total activity an isotope must be at any time step in DCS file to be placed in the "relevant" array fcn_out = parse_DCS_file_from_DCHAIN(dcs_file,relevancy_threshold=relevancy_threshold) # Notation for output array dimensions # R (n_reg) regions # T (ntsteps) time steps # N (nnuc_max) max number of nuclides # C (chni_max) maximum index of relevant chains # L (chln_max) maximum number of links per chain inventory = fcn_out[0] # universal columns of DCS file [R,T,N,C,vi], vi: 0=N_i-1/V, 1=dN/V, 2=N_i/V, 3=A_i/V, 4=A_i l_chains = fcn_out[1] # [R,T,N,C], length of listed chain prod_nuc = fcn_out[2] # [R,T,N], strings of the nuclide being produced chn_indx = fcn_out[3] # [R,T,N], lists of the chain indices printed link_nuc = fcn_out[4] # [R,T,N,C,L], strings of the nuclides in each chain decay_mode = fcn_out[5] # [R,T,N,C,L], strings of the decay modes each link undergoes to produce the next link link_dN_info=fcn_out[6] # [R,T,N,C,L,di], extra dN info di: 0=dN_Beam, 1=dN_Decay/nrxn, 2=dN_Total (only generated if these values are found in file, 'None' otherwise) end_of_irradiation_time = fcn_out[7] # time of end of final irradiation step [seconds] notable_nuclides_names_by_region = fcn_out[8] # list of lists (one per region) containing the relevant nuclides per region notable_nuclides_AvT_by_region = fcn_out[9] # list of arrays (one per region, [T,N_rlv-nuc,3]) containing the time[s]/inventory[atm/cc]/activity[Bq/cc] data of relevant nuclides n_reg,ntsteps,nnuc_max,chni_max,chln_max = np.shape(decay_mode) relevant_nuclides = notable_nuclides_names_by_region[0] n_relevant_nuclides = len(relevant_nuclides) relv_nuc_inv = notable_nuclides_AvT_by_region[0] t_from_start = relv_nuc_inv[:,0,0] t_after_irrad_sec = ((relv_nuc_inv[:,0,0]-end_of_irradiation_time)) nreg = len(reg_nos) rilist = range(nreg) #regionwise_gamma_spectra = [gamma_spectra[ri,:,:,:,:] for ri in range(nreg)] #rw_totgflux_val = [rt_summary_info[ri,:,0,0] for ri in range(nreg)] #rw_totgflux_ae = [rt_summary_info[ri,:,0,1] for ri in range(nreg)] #rw_totegflux = [rt_summary_info[ri,:,1,:] for ri in range(nreg)] # Notation for output array dimensions # R regions # T time steps # N max number of nuclides found in a single region # E number of gamma energy bins # le10 for top 10 lists, a number <= 10 dchain_output = { 'time':{ # ~ Time information 'from_start_sec':time_list_sec, # [T] list of times from start time [sec] 'from_EOB_sec':time_list_sec_after_EOB, # [T] list of times from end of final bombardment [sec] 'of_EOB_sec':irradiation_end_t, # scalar time marking end of final bombardment [sec] }, 'region':{ # ~ Information which only varies with region 'numbers':reg_nos, # [R] list of all region numbers 'number': r_summary_info[:,0], # [R] list of all region numbers 'irradiation_time_sec': r_summary_info[:,1], # [R] list of irradiation time per region 'volume': r_summary_info[:,2], # [R] list of volume in cc per region 'neutron_flux': r_summary_info[:,3], # [R] list of neutron flux in n/cm^2/s per region 'beam_power_MW': r_summary_info[:,4], # [R] list of beam power in MW per region 'beam_energy_GeV': r_summary_info[:,5], # [R] list of beam energy in GeV per region 'beam_current_mA': r_summary_info[:,6] # [R] list of beam current in mA per region }, 'nuclides':{ # ~ Main nuclide results from *.act file 'names':nuclide_names, # [R][N] list of lists containing names of nuclides produced in each region 'TeX_names':LaTeX_nuclide_names, # [R][N] list of lists containing LaTeX-formatted names of nuclides produced in each region 'ZZZAAAM':nuclide_ZAM_vals, # [R][N] list of lists containing ZZZAAAM values (=10000*Z+10*A+M) of nuclides produced in each region (ground state m=0, metastable m=1,2,etc.) 'half_life':nuclide_half_lives, # [R][N] list of lists containing half lives of nuclides produced in each region (in seconds) 'inventory':{'value':[nuclide_info[ri][:,:,0,0] for ri in rilist], # [R][T,N] atoms [#/cc] 'error':[nuclide_info[ri][:,:,0,1] for ri in rilist]}, # [R][T,N] atoms [#/cc] 'activity':{'value':[nuclide_info[ri][:,:,1,0] for ri in rilist], # [R][T,N] activity [Bq/cc] 'error':[nuclide_info[ri][:,:,1,1] for ri in rilist]}, # [R][T,N] activity [Bq/cc] 'dose_rate':{'value':[nuclide_info[ri][:,:,6,0] for ri in rilist], # [R][T,N] dose-rate [uSv/h*m^2] 'error':[nuclide_info[ri][:,:,6,1] for ri in rilist]}, # [R][T,N] dose-rate [uSv/h*m^2] 'decay_heat':{ 'total':{'value':[nuclide_info[ri][:,:,5,0] for ri in rilist], # [R][T,N] total decay heat [W/cc] 'error':[nuclide_info[ri][:,:,5,1] for ri in rilist]}, # [R][T,N] total decay heat [W/cc] 'beta':{'value':[nuclide_info[ri][:,:,2,0] for ri in rilist], # [R][T,N] beta decay heat [W/cc] 'error':[nuclide_info[ri][:,:,2,1] for ri in rilist]}, # [R][T,N] beta decay heat [W/cc] 'gamma':{'value':[nuclide_info[ri][:,:,3,0] for ri in rilist], # [R][T,N] gamma decay heat [W/cc] 'error':[nuclide_info[ri][:,:,3,1] for ri in rilist]}, # [R][T,N] gamma decay heat [W/cc] 'alpha':{'value':[nuclide_info[ri][:,:,4,0] for ri in rilist], # [R][T,N] alpha decay heat [W/cc] 'error':[nuclide_info[ri][:,:,4,1] for ri in rilist]}, # [R][T,N] alpha decay heat [W/cc] }, 'column_headers':nuclide_info_headers, # List of length 7 containing text descriptions of the 7 columns of the info arrays [0='atoms [#/cc]',1='activity [Bq/cc]','2=beta decay heat [W/cc]','3=gamma decay heat [W/cc]','4=alpha decay heat [W/cc]','5=total decay heat [W/cc]','6=dose-rate [uSv/h*m^2]'] 'total':{ # ~ Total values summed over all nuclides 'activity':{'value':[rt_summary_info[ri,:,5,0] for ri in rilist] , # [R][T] total activity [Bq/cc] 'error':[rt_summary_info[ri,:,5,1] for ri in rilist]}, # [R][T] total activity [Bq/cc] 'decay_heat':{'value':[rt_summary_info[ri,:,6,0] for ri in rilist] , # [R][T] total decay heat [W/cc] 'error':[rt_summary_info[ri,:,6,1] for ri in rilist]}, # [R][T] total decay heat [W/cc] 'beta_heat':{'value':[rt_summary_info[ri,:,7,0] for ri in rilist] , # [R][T] total beta decay heat [W/cc] 'error':[rt_summary_info[ri,:,7,1] for ri in rilist]}, # [R][T] total beta decay heat [W/cc] 'gamma_heat':{'value':[rt_summary_info[ri,:,8,0] for ri in rilist] , # [R][T] total gamma decay heat [W/cc] 'error':[rt_summary_info[ri,:,8,1] for ri in rilist]}, # [R][T] total gamma decay heat [W/cc] 'alpha_heat':{'value':[rt_summary_info[ri,:,9,0] for ri in rilist] , # [R][T] total alpha decay heat [W/cc] 'error':[rt_summary_info[ri,:,9,1] for ri in rilist]}, # [R][T] total alpha decay heat [W/cc] 'activated_atoms':{'value':[rt_summary_info[ri,:,10,0] for ri in rilist], # [R][T] total activated atoms [#/cc] 'error':[rt_summary_info[ri,:,10,1] for ri in rilist]}, # [R][T] total activated atoms [#/cc] 'gamma_dose_rate':{'value':[rt_summary_info[ri,:,11,0] for ri in rilist], # [R][T] total gamma dose rate [uSV/h*m^2] 'error':[rt_summary_info[ri,:,11,1] for ri in rilist]} # [R][T] total gamma dose rate [uSV/h*m^2] } }, 'gamma':{ # ~ Gamma spectra and totals 'spectra':{ 'group_number':[gamma_spectra[ri,:,:,0,0] for ri in rilist], # [R][T,E] group number 'E_lower':[gamma_spectra[ri,:,:,1,0] for ri in rilist], # [R][T,E] bin energy lower-bound [MeV] 'E_upper':[gamma_spectra[ri,:,:,2,0] for ri in rilist], # [R][T,E] bin energy upper-bound [MeV] 'flux':{'value':[gamma_spectra[ri,:,:,3,0] for ri in rilist], # [R][T,E] flux [#/s/cc] 'error':[gamma_spectra[ri,:,:,3,0]*gamma_spectra[ri,:,:,3,1] for ri in rilist]}, # [R][T,E] flux [#/s/cc] 'energy_flux':{'value':[gamma_spectra[ri,:,:,4,0] for ri in rilist], # [R][T,E] energy flux [MeV/s/cc] 'error':[gamma_spectra[ri,:,:,4,0]*gamma_spectra[ri,:,:,4,1] for ri in rilist]} # [R][T,E] energy flux [MeV/s/cc] }, 'total_flux':{'value':[rt_summary_info[ri,:,0,0] for ri in rilist], # [R][T] total gamma flux [#/s/cc] 'error':[rt_summary_info[ri,:,0,1] for ri in rilist]}, # [R][T] total gamma flux [#/s/cc] 'total_energy_flux':{'value':[rt_summary_info[ri,:,1,0] for ri in rilist] , # [R][T] total gamma energy flux [MeV/s/cc] 'error':[rt_summary_info[ri,:,1,1] for ri in rilist]}, # [R][T] total gamma energy flux [MeV/s/cc] 'annihilation_flux':{'value':[rt_summary_info[ri,:,2,0] for ri in rilist] , # [R][T] annihilation gamma flux [#/s/cc] 'error':[rt_summary_info[ri,:,2,1] for ri in rilist]}, # [R][T] annihilation gamma flux [#/s/cc] 'current_underflow':{'value':[rt_summary_info[ri,:,3,0] for ri in rilist] , # [R][T] gamma current underflow [#/s] 'error':[rt_summary_info[ri,:,3,1] for ri in rilist]}, # no error reported 'current_overflow':{'value':[rt_summary_info[ri,:,4,0] for ri in rilist], # [R][T] gamma current overflow [#/s] 'error':[rt_summary_info[ri,:,4,1] for ri in rilist]} # no error reported }, 'top10':{ # ~ Top 10 lists from *.act file 'activity':{ 'rank':[top10_lists[ri,:,:,0,0] for ri in rilist], # [R][T,le10] rank 'nuclide':[top10_lists[ri,:,:,1,0] for ri in rilist], # [R][T,le10] nuclide name 'value':[top10_lists[ri,:,:,2,0] for ri in rilist], # [R][T,le10] activity [Bq/cc] 'error':[top10_lists[ri,:,:,2,1] for ri in rilist], # [R][T,le10] activity [Bq/cc] 'percent':[top10_lists[ri,:,:,4,0] for ri in rilist], # [R][T,le10] percent of total activity }, 'decay_heat':{ 'rank':[top10_lists[ri,:,:,0,0] for ri in rilist], # [R][T,le10] rank 'nuclide':[top10_lists[ri,:,:,5,0] for ri in rilist], # [R][T,le10] nuclide name 'value':[top10_lists[ri,:,:,6,0] for ri in rilist], # [R][T,le10] decay heat [W/cc] 'error':[top10_lists[ri,:,:,6,1] for ri in rilist], # [R][T,le10] decay heat [W/cc] 'percent':[top10_lists[ri,:,:,8,0] for ri in rilist], # [R][T,le10] percent of total decay heat }, 'gamma_dose':{ 'rank':[top10_lists[ri,:,:,0,0] for ri in rilist], # [R][T,le10] rank 'nuclide':[top10_lists[ri,:,:,9,0] for ri in rilist], # [R][T,le10] nuclide name 'value':[top10_lists[ri,:,:,10,0] for ri in rilist], # [R][T,le10] dose-rate [uSv/h*m^2] 'error':[top10_lists[ri,:,:,10,1] for ri in rilist], # [R][T,le10] dose-rate [uSv/h*m^2] 'percent':[top10_lists[ri,:,:,11,0] for ri in rilist], # [R][T,le10] percent of total gamma dose rate } }, 'number_of':{ # ~ Maximum values of R, T, N, and E 'regions':nreg, # R = total number of regions 'time_steps':len(time_list_sec), # T = total number of time steps 'max_nuclides_in_any_region':np.shape(nuclides_produced)[2], # N = maximum unique nuclides found in any region 'gamma_energy_bins':np.shape(gamma_spectra)[2] # E = number of gamma energy bins (default=42) } } if process_dtrk_file: dflux_norm = [] for ri in rilist: if np.sum(neutron_flux[ri,:,2]) != 0: dflux_norm.append(r_summary_info[ri,3]/np.sum(neutron_flux[ri,:,2])) else: dflux_norm.append(0.0) #dflux_norm = [r_summary_info[ri,3]/np.sum(neutron_flux[ri,:,2]) for ri in rilist] # normalize unit flux to total flux dchain_output.update({ 'neutron':{ 'spectra':{ # Actual values used by DCHAIN for rate calcs 'E_lower':[neutron_flux[ri,:,0] for ri in rilist], # [R][E] bin energy lower-bound [MeV] 'E_upper':[neutron_flux[ri,:,1] for ri in rilist], # [R][E] bin energy upper-bound [MeV] 'flux':{'value':[neutron_flux[ri,:,2]*dflux_norm[ri] for ri in rilist], # [R][E] neutron flux [#/s/cm^2] 'error':[neutron_flux[ri,:,3]*dflux_norm[ri] for ri in rilist]}, # [R][E] neutron flux [#/s/cm^2] }, 'total_flux':{'value':[np.sum(neutron_flux[ri,:,2])*dflux_norm[ri] for ri in rilist], # [R] total neutron flux [#/s/cm^2] 'error':[np.sqrt(np.sum(neutron_flux[ri,:,3]**2))*dflux_norm[ri] for ri in rilist]}, # [R] total neutron flux [#/s/cm^2] 'unit_spectra':{ # Raw T-Track output from PHITS 'E_lower':[neutron_flux[ri,:,0] for ri in rilist], # [R][E] bin energy lower-bound [MeV] 'E_upper':[neutron_flux[ri,:,1] for ri in rilist], # [R][E] bin energy upper-bound [MeV] 'flux':{'value':[neutron_flux[ri,:,2] for ri in rilist], # [R][E] neutron flux [#/s/cm^2] 'error':[neutron_flux[ri,:,3] for ri in rilist]}, # [R][E] neutron flux [#/s/cm^2] }, } }) if process_dyld_file: dchain_output.update({ 'yields':{ # ~ Yield spectra 'all_names':nuclide_names_yld, # [N] names of nuclides produced in all regions 'names':reg_yld_names, # [R][N] names of nuclides produced in each region 'TeX_names':reg_yld_texnames, # [R][N] LaTeX-formatted names of nuclides produced 'ZZZAAAM':reg_yld_zam, # [R][N] ZZZAAAM values (=10000Z+10A+M) of nuclides 'rate':{'value':yield_values_by_reg[0], # [R][E] nuclide yield rate [#/s/cm^3] 'error':yield_values_by_reg[1]}, # [R][E] nuclide yield rate [#/s/cm^3] 'unit_rate':{'value':yield_values_by_reg[2], # [R][E] unit nuclide yield rate [#/s.p.] 'error':yield_values_by_reg[3]} # [R][E] unit nuclide yield rate [#/s.p.] } }) if process_DCS_file: # add extra information # Notation for output array dimensions # R (n_reg) regions # Td (ntsteps) time steps in DCS file (usually different from that of ACT file!) # Nd (nnuc_max) max number of nuclides (this index differs from the ACT N index) # C (chni_max) maximum index of relevant chains # L (chln_max) maximum number of links per chain dchain_output.update({'DCS':{ 'time':{ 'from_start_sec':t_from_start, # [Td] list 'from_EOB_sec':t_after_irrad_sec, # [Td] list 'of_EOB_sec':irradiation_end_t # scalar }, 'number_of':{ # ~ Maximum values of R, Td, Nd, C, and L 'regions':n_reg, # R = total number of regions 'time_steps':ntsteps, # Td = total number of time steps 'max_nuclides':nnuc_max, # Nd = maximum number of nuclides listed in a time step 'max_number_of_chains':chni_max, # C = highest index of a relevant chain found 'max_chain_length':chln_max # L = maximum number of links (nuclides) found in any chain }, 'end_nuclide':{ 'names':[prod_nuc[ri,:,:] for ri in rilist], # [R][Td,Nd] nuclide names 'inventory':{ 'N_previous':[inventory[ri,:,:,:,0] for ri in rilist], # [R][Td,Nd,C] inventory of end nuclide in previous time step [atoms/cc] 'N_now':[inventory[ri,:,:,:,2] for ri in rilist], # [R][Td,Nd,C] inventory of end nuclide in the current time step [atoms/cc] 'dN':[inventory[ri,:,:,:,1] for ri in rilist] # [R][Td,Nd,C] change in inventory of end nuclide from the previous to the current time step [atoms/cc] }, 'activity':{ 'A_previous':[inventory[ri,:,:,:,0]*(inventory[ri,:,:,:,3]/inventory[ri,:,:,:,2]) for ri in rilist], # [R][Td,Nd,C] activity of end nuclide in previous time step [Bq/cc] 'A_now':[inventory[ri,:,:,:,3] for ri in rilist], # [R][Td,Nd,C] activity of end nuclide in the current time step [Bq/cc] 'dA':[inventory[ri,:,:,:,1]*(inventory[ri,:,:,:,3]/inventory[ri,:,:,:,2]) for ri in rilist] # [R][Td,Nd,C] change in activity of end nuclide from the previous to the current time step [Bq/cc] } }, 'chains':{ 'indices_of_printed_chains':[chn_indx[ri,:,:] for ri in rilist], # [R][Td,Nd] lists of the chain indices printed 'length':[l_chains[ri,:,:,:] for ri in rilist], # [R][Td,Nd,C] length of listed chain 'link_nuclides':[link_nuc[ri,:,:,:,:] for ri in rilist], # [R][Td,Nd,C,L] strings of the nuclides in each chain 'link_decay_modes':[decay_mode[ri,:,:,:,:] for ri in rilist], # [R][Td,Nd,C,L] strings of the decay modes each link undergoes to produce the next link 'link_dN':{ 'beam':[None if link_dN_info==None else link_dN_info[ri,:,:,:,:,0] for ri in rilist], # [R][Td,Nd,C,L] beam contribution to dN from each link (only generated if these values are found in file, 'None' otherwise) 'decay_nrxn':[None if link_dN_info==None else link_dN_info[ri,:,:,:,:,1] for ri in rilist], # [R][Td,Nd,C,L] decay + neutron rxn contribution to dN from each link (only generated if these values are found in file, 'None' otherwise) 'total':[None if link_dN_info==None else link_dN_info[ri,:,:,:,:,2] for ri in rilist] # [R][Td,Nd,C,L] total contribution to dN from each link (only generated if these values are found in file, 'None' otherwise) } }, 'relevant_nuclides':{ 'names':notable_nuclides_names_by_region, # [R] list of relevant nuclides per region 'times':[notable_nuclides_AvT_by_region[ri][:,:,0] for ri in rilist], # [R][Td,Nd] time [s] 'inventory':[notable_nuclides_AvT_by_region[ri][:,:,1] for ri in rilist], # [R][Td,Nd] inventory [atm/cc] 'activity':[notable_nuclides_AvT_by_region[ri][:,:,2] for ri in rilist] # [R][Td,Nd] activity [Bq/cc] } }}) # https://github.com/Infinidat/munch try: dchain_output = munchify(dchain_output) except: print("munchify failed. Returned object is a conventional dictionary rather than a munchify object.") return dchain_output def parse_DCHAIN_act_file(act_file_path)-
Description
This code parses the .act file generated by DCHAIN
Inputs
- path to a DCHAIN-generated .act file
Outputs
- length R list of region numbers
- length T list of measurement times (in sec) from start of irradiation
- time of end of irradiation (in sec)
- NumPy array of dimension RxTxNx11x2 of nuclide table data (N=max recorded table length)
- NumPy array of dimension RxTxEx5x2 of gamma spectrum table data (E=number of energy groups of gamma spectra)
- NumPy array of dimension RxTxNx12x2 of top-10 list table data
- List containing 3 lists of column headers for the preceding three NumPy arrays
- list of the below lists/arrays of summary information
- NumPy array of dimension Rx7 of region-specific summary info: Beam current, beam energy, beam power, total neutron flux, region volume, irradiation time, region number
- list of length 7 containing descriptions of the above items
- NumPy array of dimension RxTx12x2 of region and time-specific summary info Rank, [nuclide, A/cc, A, %], [nuclide, P/cc, P, %], [nuclide, H, %] with values and absolute uncertainties
- list of length 12 containing descriptions of the above items
Expand source code
def parse_DCHAIN_act_file(act_file_path): ''' Description: This code parses the .act file generated by DCHAIN Inputs: - path to a DCHAIN-generated .act file Outputs: - length R list of region numbers - length T list of measurement times (in sec) from start of irradiation - time of end of irradiation (in sec) - NumPy array of dimension RxTxNx11x2 of nuclide table data (N=max recorded table length) - NumPy array of dimension RxTxEx5x2 of gamma spectrum table data (E=number of energy groups of gamma spectra) - NumPy array of dimension RxTxNx12x2 of top-10 list table data - List containing 3 lists of column headers for the preceding three NumPy arrays - list of the below lists/arrays of summary information + NumPy array of dimension Rx7 of region-specific summary info: Beam current, beam energy, beam power, total neutron flux, region volume, irradiation time, region number + list of length 7 containing descriptions of the above items + NumPy array of dimension RxTx12x2 of region and time-specific summary info Rank, [nuclide, A/cc, A, %], [nuclide, P/cc, P, %], [nuclide, H, %] with values and absolute uncertainties + list of length 12 containing descriptions of the above items ''' # Extract file info f = open(act_file_path) lines = f.readlines() f.close() # Parse file to determine number of regions nreg = 0 reg_nos = [] for line in lines: if 'region number' in line: nreg += 1 reg_nos.append(int(line[21:31])) # Parse file again to determine number of time steps current_reg_no = -1 #irradiation_time = -1.0 # seconds end_of_irradiation_time = -1.0 # seconds ntimes = 0 time_strs = [] time_list_sec = [] # time steps in seconds time_list_sec_after_EOB = [] # time steps in seconds after EOB for line in lines: #if 'irradiation time' in line: irradiation_time = float(line[21:31])*time_str_to_sec_multiplier(line[33]) if 'region number' in line: current_reg_no = int(line[21:31]) if current_reg_no != reg_nos[0]: continue # only read times from first region if '--- output time ---' in line: ntimes += 1 time_strs.append(line) time_list_sec.append(float(line[40:53])) time_list_sec_after_EOB.append(0.0) if ('--- output time ---' in line) and ('after the last shutdown' in line): time_list_sec_after_EOB[ntimes-1] = float(line[87:97])*time_str_to_sec_multiplier(line[99]) if end_of_irradiation_time == -1: end_of_irradiation_time = float(line[21:31])*time_str_to_sec_multiplier(line[33]) - float(line[87:97])*time_str_to_sec_multiplier(line[99]) for ti in range(len(time_list_sec_after_EOB)): if time_list_sec_after_EOB[ti]==0.0: time_list_sec_after_EOB[ti] = time_list_sec[ti] - end_of_irradiation_time # Extract "summary info" from file ri = -1 # region index ti = -1 # time index r_summary_info = np.empty((nreg,7), dtype='object') # (regionwise) initialize Rx7 array r_summary_info_description = ['region number','irradiation time [s]','region volume [cc]','neutron flux [n/cm^2/s]','beam power [MW]','beam energy [GeV]','beam current [mA]'] # (regionwise) initialize Rx7 array ''' r_summary_info[i,j,k] i = region number j = category (see table below) index meaning 0 region number 1 irradiation time [sec] 2 region volume [cc] 3 neutron flux [n/cm^2/s] 4 beam power [MW] 5 beam energy [GeV] 6 beam current [mA] ''' rt_summary_info = np.empty((nreg,ntimes,12,2), dtype='object') # (region-and-timewise) initialize RxTx12x2 array rt_summary_info_description = ['total gamma flux [#/s/cc]','total gamma energy flux [MeV/s/cc]','annihilation gamma flux [#/s/cc]','gamma current underflow [#/s]','gamma current overflow [#/s]','total activity [Bq/cc]','total decay heat [W/cc]','beta decay heat [W/cc]','gamma decay heat [W/cc]','alpha decay heat [W/cc]','activated atoms [#/cc]','total gamma dose rate [uSV/h*m^2]'] # (region-and-timewise) initialize RxTx12 array ''' rt_summary_info[i,j,k,m] i = region number j = output time step k = category (see table below) m = value (k=0) or absolute uncertainty (k=1) index meaning 0 total gamma flux [#/s/cc] 1 total gamma energy flux [MeV/s/cc] 2 annihilation gamma flux [#/s/cc] 3 gamma current underflow [#/s] (gammas below lowest energy bin) 4 gamma current overflow [#/s] (gammas above highest energy bin) 5 total activity [Bq/cc] 6 total decay heat [W/cc] 7 beta decay heat [W/cc] 8 gamma decay heat [W/cc] 9 alpha decay heat [W/cc] 10 activated atoms [#/cc] 11 total gamma dose rate [uSV/h*m^2] ''' for li in range(len(lines)): line = lines[li] if 'region number' in line: ri = find(int(line[21:31]),reg_nos) # region-specific summary info r_summary_info[ri,0] = int(line[21:31]) r_summary_info[ri,1] = float(lines[li-1][21:31])*time_str_to_sec_multiplier(lines[li-1][33]) r_summary_info[ri,2] = float(lines[li-2][21:31]) r_summary_info[ri,3] = float(lines[li-3][21:31]) r_summary_info[ri,4] = float(lines[li-4][21:31]) r_summary_info[ri,5] = float(lines[li-5][21:31]) r_summary_info[ri,6] = float(lines[li-6][21:31]) if '--- output time ---' in line: ti = find(line,time_strs) # gamma info specific to region and time if 'total gamma-ray flux' in line: rt_summary_info[ri,ti,0,0] = float(line[38:49]) rt_summary_info[ri,ti,1,0] = float(lines[li+1][38:49]) rt_summary_info[ri,ti,2,0] = float(lines[li+2][38:49]) rt_summary_info[ri,ti,0,1] = float(line[53:64]) rt_summary_info[ri,ti,1,1] = float(lines[li+1][53:64]) rt_summary_info[ri,ti,2,1] = float(lines[li+2][53:64]) if 'group limitation' in lines[li+3]: rt_summary_info[ri,ti,3,0] = float(lines[li+3][91:101]) rt_summary_info[ri,ti,4,0] = float(lines[li+3][64:74]) else: rt_summary_info[ri,ti,3,0] = 0.0 rt_summary_info[ri,ti,4,0] = 0.0 if 'no gamma-ray' in line: rt_summary_info[ri,ti,0,0] = 0.0 rt_summary_info[ri,ti,1,0] = 0.0 rt_summary_info[ri,ti,2,0] = 0.0 rt_summary_info[ri,ti,0,1] = 0.0 rt_summary_info[ri,ti,1,1] = 0.0 rt_summary_info[ri,ti,2,1] = 0.0 rt_summary_info[ri,ti,3,0] = 0.0 rt_summary_info[ri,ti,4,0] = 0.0 # activation info specific to region and time if 'total activity' in line: rt_summary_info[ri,ti,5,0] = float(line[24:36]) rt_summary_info[ri,ti,6,0] = float(lines[li+1][24:36]) rt_summary_info[ri,ti,7,0] = float(lines[li+2][24:36]) rt_summary_info[ri,ti,8,0] = float(lines[li+3][24:36]) rt_summary_info[ri,ti,9,0] = float(lines[li+4][24:36]) rt_summary_info[ri,ti,10,0]= float(lines[li+5][24:36]) rt_summary_info[ri,ti,11,0]= float(lines[li+6][24:36]) rt_summary_info[ri,ti,5,1] = float(line[40:52]) rt_summary_info[ri,ti,6,1] = float(lines[li+1][40:52]) rt_summary_info[ri,ti,7,1] = float(lines[li+2][40:52]) rt_summary_info[ri,ti,8,1] = float(lines[li+3][40:52]) rt_summary_info[ri,ti,9,1] = float(lines[li+4][40:52]) rt_summary_info[ri,ti,10,1]= float(lines[li+5][40:52]) rt_summary_info[ri,ti,11,1]= float(lines[li+6][40:52]) summary_info = [r_summary_info, r_summary_info_description, rt_summary_info, rt_summary_info_description] # Extract major "blocks" (nuclides, gamma spec, top10 list) for each time step in each region act_block_text = np.empty((nreg,ntimes,3), dtype='object') # initialize RxTx3 array to hold character strings where final index 0=nuclides, 1=gamma-spec, and 2=top10-list ri = -1 # region index ti = -1 # time index qi = -1 # quantity index - 0=nuclides, 1=gamma-spec, and 2=top10-list max_array_len = [0,0,0] # maximum number of entries for a given quantity current_array_len = [0,0,0] # current number of entries for a given quantity for line in lines: if 'region number' in line: ri = find(int(line[21:31]),reg_nos) if '--- output time ---' in line: ti = find(line,time_strs) qi = 0 # reset quantity index if 'gamma-ray spectrum weighted by energy' in line: qi = 1 if 'dominant nuclides (top 10)' in line: qi = 2 if 'total' in line[:20] or line=='\n': # no longer reading info block if current_array_len[qi] > max_array_len[qi]: max_array_len[qi] = current_array_len[qi] current_array_len[qi] = 0 qi = -1 if qi < 0: continue # not in region of interest try: act_block_text[ri,ti,qi] += line except: act_block_text[ri,ti,qi] = line current_array_len[qi] += 1 header_len = [3,4,3] # number of lines present in table header nuclides_produced = np.empty((nreg,ntimes,max_array_len[0]-header_len[0],11,2), dtype='object') # initialize RxTxNx11x2 array to hold nuclide information gamma_spectra = np.empty((nreg,ntimes,max_array_len[1]-header_len[1], 5,2), dtype='object') # initialize RxTxNx5x2 array to hold gamma spec information top10_lists = np.empty((nreg,ntimes,max_array_len[2]-header_len[2],12,2), dtype='object') # initialize RxTxNx12x2 array to hold top 10 list information column_headers = [ [],[],[] ] # Now, populate each array # Nuclides produced column_headers[0] = ['nuclide','atoms [#/cc]','activity [Bq/cc]','activity [Bq]','rate [%]','beta decay heat [W/cc]','gamma decay heat [W/cc]','alpha decay heat [W/cc]','total decay heat [W/cc]','half life [s]','dose-rate [uSv/h*m^2]'] for ri in range(nreg): for ti in range(ntimes): table_text = act_block_text[ri,ti,0].split('\n') for ei in range(len(table_text)): if ei < header_len[0]: continue # in header lines ii = ei - header_len[0] # actual number index line = table_text[ei] if line=='' or line==None: continue # skip blank/nonexistent lines rel_err = float(line[51:61]) nuclides_produced[ri,ti,ii,0,0] = line[3:9] # nuclide nuclides_produced[ri,ti,ii,1,0] = float(line[12:23].replace(' ','0.0')) # atoms [#/cc] nuclides_produced[ri,ti,ii,2,0] = float(line[25:36].replace(' ','0.0')) # activity [Bq/cc] nuclides_produced[ri,ti,ii,3,0] = float(line[38:49].replace(' ','0.0')) # activity [Bq] nuclides_produced[ri,ti,ii,4,0] = float(line[61:68].replace(' ','0.0')) # rate [%] nuclides_produced[ri,ti,ii,5,0] = float(line[70:80].replace(' ','0.0')) # beta decay heat [W/cc] nuclides_produced[ri,ti,ii,6,0] = float(line[81:91].replace(' ','0.0')) # gamma decay heat [W/cc] nuclides_produced[ri,ti,ii,7,0] = float(line[92:102].replace(' ','0.0')) # alpha decay heat [W/cc] nuclides_produced[ri,ti,ii,8,0] = float(line[103:113].replace(' ','0.0')) # total decay heat [W/cc] nuclides_produced[ri,ti,ii,9,0] = float(line[116:126].replace('stable','0.0')) # half life [s] if nuclides_produced[ri,ti,ii,9,0] == 0: nuclides_produced[ri,ti,ii,10,0]= 0.0 # dose-rate [uSv/h*m^2] else: nuclides_produced[ri,ti,ii,10,0]= float(line[128:138].replace(' ','0.0')) # dose-rate [uSv/h*m^2] # absolute errors for corresponding values nuclides_produced[ri,ti,ii,1,1] = nuclides_produced[ri,ti,ii,1,0]*rel_err nuclides_produced[ri,ti,ii,2,1] = nuclides_produced[ri,ti,ii,2,0]*rel_err nuclides_produced[ri,ti,ii,3,1] = nuclides_produced[ri,ti,ii,3,0]*rel_err nuclides_produced[ri,ti,ii,4,1] = nuclides_produced[ri,ti,ii,4,0]*rel_err nuclides_produced[ri,ti,ii,5,1] = nuclides_produced[ri,ti,ii,5,0]*rel_err nuclides_produced[ri,ti,ii,6,1] = nuclides_produced[ri,ti,ii,6,0]*rel_err nuclides_produced[ri,ti,ii,7,1] = nuclides_produced[ri,ti,ii,7,0]*rel_err nuclides_produced[ri,ti,ii,8,1] = nuclides_produced[ri,ti,ii,8,0]*rel_err nuclides_produced[ri,ti,ii,9,1] = nuclides_produced[ri,ti,ii,9,0]*rel_err nuclides_produced[ri,ti,ii,10,1]= nuclides_produced[ri,ti,ii,10,0]*rel_err # Gamma-ray spectra column_headers[1] = ['group number','bin energy lower-bound [MeV]','bin energy upper-bound [MeV]','flux [#/s/cc]','energy flux [MeV/s/cc]'] for ri in range(nreg): for ti in range(ntimes): if not act_block_text[ri,ti,1]: gamma_spectra[ri,ti,:,0,0] = None # group number gamma_spectra[ri,ti,:,1,0] = None # bin energy lower-bound [MeV] gamma_spectra[ri,ti,:,2,0] = None # bin energy upper-bound [MeV] gamma_spectra[ri,ti,:,3,0] = 0.0 # flux [#/s/cc] gamma_spectra[ri,ti,:,4,0] = 0.0 # energy flux [MeV/s/cc] gamma_spectra[ri,ti,:,3,1] = 0.0 # flux absolute error [#/s/cc] gamma_spectra[ri,ti,:,4,1] = 0.0 # energy flux absolute error [MeV/s/cc] continue table_text = act_block_text[ri,ti,1].split('\n') for ei in range(len(table_text)): if ei < header_len[1]: continue # in header lines ii = ei - header_len[1] # actual number index line = table_text[ei] if line=='' or line==None: continue # skip blank/nonexistent lines gamma_spectra[ri,ti,ii,0,0] = int(line[1:4]) # group number gamma_spectra[ri,ti,ii,1,0] = float(line[17:25]) # bin energy lower-bound [MeV] gamma_spectra[ri,ti,ii,2,0] = float(line[7:15]) # bin energy upper-bound [MeV] gamma_spectra[ri,ti,ii,3,0] = float(line[27:38]) # flux [#/s/cc] gamma_spectra[ri,ti,ii,4,0] = float(line[40:51]) # energy flux [MeV/s/cc] gamma_spectra[ri,ti,ii,3,1] = gamma_spectra[ri,ti,ii,3,0]*float(line[53:64]) # flux absolute error [#/s/cc] gamma_spectra[ri,ti,ii,4,1] = gamma_spectra[ri,ti,ii,4,0]*float(line[53:64]) # energy flux absolute error [MeV/s/cc] # Top 10 lists column_headers[2] = ['rank','nuclide - Activity ranking','activity [Bq/cc]','activity [Bq]','rate [%]','nuclide - Decay heat ranking','decay heat [W/cc]','decay heat [W]','rate [%]','nuclide - Dose rate ranking','dose-rate [uSv/h*m^2]','rate [%]'] for ri in range(nreg): for ti in range(ntimes): if not act_block_text[ri,ti,2]: continue table_text = act_block_text[ri,ti,2].split('\n') for ei in range(len(table_text)): if ei < header_len[2]: continue # in header lines ii = ei - header_len[2] # actual number index line = table_text[ei] if line=='' or line==None: continue # skip blank/nonexistent lines top10_lists[ri,ti,ii,0,0] = int(line[1:5]) # number/rank top10_lists[ri,ti,ii,1,0] = line[8:14] # nuclide - Activity ranking top10_lists[ri,ti,ii,2,0] = float(line[15:26]) # activity [Bq/cc] top10_lists[ri,ti,ii,3,0] = float(line[26:37]) # activity [Bq] top10_lists[ri,ti,ii,4,0] = float(line[48:55]) # rate [%] rel_err = float(line[37:48]) top10_lists[ri,ti,ii,2,1] = top10_lists[ri,ti,ii,2,0]*rel_err # activity absolute error [Bq/cc] top10_lists[ri,ti,ii,3,1] = top10_lists[ri,ti,ii,3,0]*rel_err # activity absolute error [Bq] top10_lists[ri,ti,ii,4,1] = top10_lists[ri,ti,ii,4,0]*rel_err # rate absolute error [%] top10_lists[ri,ti,ii,5,0] = line[60:66] # nuclide - Decay heat ranking top10_lists[ri,ti,ii,6,0] = float(line[67:78]) # decay heat [W/cc] top10_lists[ri,ti,ii,7,0] = float(line[78:89]) # decay heat [W] top10_lists[ri,ti,ii,8,0] = float(line[100:107]) # rate [%] rel_err = float(line[89:100]) top10_lists[ri,ti,ii,6,1] = top10_lists[ri,ti,ii,6,0]*rel_err # decay heat absolute error [W/cc] top10_lists[ri,ti,ii,7,1] = top10_lists[ri,ti,ii,7,0]*rel_err # decay heat absolute error [W] top10_lists[ri,ti,ii,8,1] = top10_lists[ri,ti,ii,8,0]*rel_err # rate absolute error [%] top10_lists[ri,ti,ii,9,0] = line[112:118] # nuclide - Dose rate ranking top10_lists[ri,ti,ii,10,0]= float(line[119:130]) # dose-rate [uSv/h*m^2] top10_lists[ri,ti,ii,11,0]= float(line[142:149]) # rate [%] rel_err = float(line[131:142]) top10_lists[ri,ti,ii,10,1]= top10_lists[ri,ti,ii,10,0]*rel_err # dose-rate absolute error [uSv/h*m^2] top10_lists[ri,ti,ii,11,1]= top10_lists[ri,ti,ii,11,0]*rel_err # rate absolute error [%] return reg_nos, time_list_sec, time_list_sec_after_EOB, end_of_irradiation_time, nuclides_produced, gamma_spectra, top10_lists, column_headers, summary_info def generate_nuclide_time_profiles(nuclides_info_array)-
Description
Reformats DCHAIN's tabular nuclide data into time profiles of each nuclide in each region
Inputs
- the
nuclides_producedarray from function "parse_DCHAIN_act_file"
Outputs
- List of length R of lists containing names of nuclides produced in each region
- List of length R of lists containing LaTeX-formatted names of nuclides produced in each region
- List of length R of lists containing ZZZAAAM values (10000Z+10A+M) of nuclides produced in each region
- List of length R of lists containing half lives of nuclides produced in each region (in seconds)
- List of length R of NumPy arrays of dimension NxTx7x2 of nuclide info
- List of length 7 containing text descriptions of the 7 columns of the info arrays
Expand source code
def generate_nuclide_time_profiles(nuclides_info_array): ''' Description: Reformats DCHAIN's tabular nuclide data into time profiles of each nuclide in each region Inputs: - the `nuclides_produced` array from function "parse_DCHAIN_act_file" Outputs: - List of length R of lists containing names of nuclides produced in each region - List of length R of lists containing LaTeX-formatted names of nuclides produced in each region - List of length R of lists containing ZZZAAAM values (10000Z+10A+M) of nuclides produced in each region - List of length R of lists containing half lives of nuclides produced in each region (in seconds) - List of length R of NumPy arrays of dimension NxTx7x2 of nuclide info - List of length 7 containing text descriptions of the 7 columns of the info arrays ''' nuclide_names = [] nuclide_ZAM_vals = [] nuclide_Latex_names = [] nuclide_half_lives = [] nuclide_info = [] nuclide_info_headers = ['Atoms [#/cc]','Activity [Bq/cc]','Beta decay heat [W/cc]','Gamma decay heat [W/cc]','Alpha decay heat [W/cc]','Total decay heat [W/cc]','Dose-rate [uSv/h*m^2]'] nreg = np.shape(nuclides_info_array)[0] ntime= np.shape(nuclides_info_array)[1] nnuc = np.shape(nuclides_info_array)[2] # Get nuclide name info first, ordering them by increasing Z and A for ri in range(nreg): reg_nuclides = [] reg_t_halves = [] reg_ZAM_vals = [] reg_tex_nuclides = [] for ti in range(ntime): for ni in range(nnuc): Dname = nuclides_info_array[ri,ti,ni,0,0] if Dname == None: continue ZAM = Dname_to_ZAM(Dname) if ZAM not in reg_ZAM_vals: bisect.insort_left(reg_ZAM_vals, ZAM) zami = reg_ZAM_vals.index(ZAM) #zami = find(ZAM,reg_ZAM_vals) reg_nuclides.insert(zami,Dname) reg_t_halves.insert(zami,nuclides_info_array[ri,ti,ni,9,0]) reg_tex_nuclides.insert(zami,Dname_to_Latex(Dname)) nuclide_names.append(reg_nuclides) nuclide_ZAM_vals.append(reg_ZAM_vals) nuclide_half_lives.append(reg_t_halves) nuclide_Latex_names.append(reg_tex_nuclides) # Now get arrays of nuclide info for ri in range(nreg): reg_nnuc = len(nuclide_names[ri]) reg_nuclide_info = np.zeros((ntime,reg_nnuc,7,2)) for ti in range(ntime): for ni in range(reg_nnuc): if nuclide_names[ri][ni] not in nuclides_info_array[ri,ti,:,0,0]: continue sni = find(nuclide_names[ri][ni],nuclides_info_array[ri,ti,:,0,0]) reg_nuclide_info[ti,ni,0,0] = nuclides_info_array[ri,ti,sni,1,0] # atoms [#/cc] reg_nuclide_info[ti,ni,1,0] = nuclides_info_array[ri,ti,sni,2,0] # activity [Bq/cc] reg_nuclide_info[ti,ni,2,0] = nuclides_info_array[ri,ti,sni,5,0] # beta decay heat [W/cc] reg_nuclide_info[ti,ni,3,0] = nuclides_info_array[ri,ti,sni,6,0] # gamma decay heat [W/cc] reg_nuclide_info[ti,ni,4,0] = nuclides_info_array[ri,ti,sni,7,0] # alpha decay heat [W/cc] reg_nuclide_info[ti,ni,5,0] = nuclides_info_array[ri,ti,sni,8,0] # total decay heat [W/cc] reg_nuclide_info[ti,ni,6,0] = nuclides_info_array[ri,ti,sni,10,0] # dose-rate [uSv/h*m^2] reg_nuclide_info[ti,ni,0,1] = nuclides_info_array[ri,ti,sni,1,1] # atoms absolute error [#/cc] reg_nuclide_info[ti,ni,1,1] = nuclides_info_array[ri,ti,sni,2,1] # activity absolute error [Bq/cc] reg_nuclide_info[ti,ni,2,1] = nuclides_info_array[ri,ti,sni,5,1] # beta decay heat absolute error [W/cc] reg_nuclide_info[ti,ni,3,1] = nuclides_info_array[ri,ti,sni,6,1] # gamma decay heat absolute error [W/cc] reg_nuclide_info[ti,ni,4,1] = nuclides_info_array[ri,ti,sni,7,1] # alpha decay heat absolute error [W/cc] reg_nuclide_info[ti,ni,5,1] = nuclides_info_array[ri,ti,sni,8,1] # total decay heat absolute error [W/cc] reg_nuclide_info[ti,ni,6,1] = nuclides_info_array[ri,ti,sni,10,1] # dose-rate absolute error [uSv/h*m^2] nuclide_info.append(reg_nuclide_info) return nuclide_names, nuclide_Latex_names, nuclide_ZAM_vals, nuclide_half_lives, nuclide_info, nuclide_info_headers - the
def parse_DCS_file_from_DCHAIN(filepath, relevancy_threshold=0.01, print_progress=False, nch_max=100)-
Description
Parse a decay chain information file produced by DCHAIN-SP
Dependencies
import numpy as npimport timeInputs
(required)
filepath= string, path to DCS file
Inputs
(optional, keyword)
print_progress= logical variable denoting whether time and significant nuclide info will be printed while scanning file (D=False)nch_max= maximum number of chains per isotope (D=100)relevancy_threshold= what fraction of total activity must a nuclide contribute to be deemed relevant
Outputs
dimension meaning for output array dimensions R (n_reg) regions T (ntsteps) time steps N (nnuc_max) max number of nuclides C (chni_max) maximum index of relevant chains L (chln_max) maximum number of links per chain - 0)
inventory= universal columns of DCS file[R,T,N,C,vi], vi: 0=N_i-1/V, 1=dN/V, 2=N_i/V, 3=A_i/V, 4=A_i - 1)
l_chains=[R,T,N,C], length of listed chain - 2)
prod_nuc=[R,T,N], strings of the nuclide being produced - 3)
chn_indx=[R,T,N], lists of the chain indices printed - 4)
link_nuc=[R,T,N,C,L], strings of the nuclides in each chain - 5)
decay_mode=[R,T,N,C,L], strings of the decay modes each link undergoes to produce the next link - 6)
link_dN_info=[R,T,N,C,L,di], extra dN info di: 0=dN_Beam, 1=dN_Decay/nrxn, 2=dN_Total (only generated if these values are found in file, 'None' otherwise) - 7)
end_of_irradiation_time= time of end of final irradiation step [seconds] - 8)
notable_nuclides_names_by_region= list of lists (one per region) containing the relevant nuclides per region - 9)
notable_nuclides_AvT_by_region= list of arrays (one per region,[T,N_rlv-nuc,3]) containing the time[s]/inventory[atm/cc]/activity[Bq/cc] data of relevant nuclides
Expand source code
def parse_DCS_file_from_DCHAIN(filepath,relevancy_threshold=0.01,print_progress=False,nch_max=100): ''' Description: Parse a decay chain information file produced by DCHAIN-SP Dependencies: `import numpy as np` `import time` Inputs: (required) - `filepath` = string, path to DCS file Inputs: (optional, keyword) - `print_progress` = logical variable denoting whether time and significant nuclide info will be printed while scanning file (D=`False`) - `nch_max` = maximum number of chains per isotope (D=`100`) - `relevancy_threshold` = what fraction of total activity must a nuclide contribute to be deemed relevant Outputs: | dimension | meaning for output array dimensions | | :------------- | :-------------------------------- | | R (n_reg) | regions | | T (ntsteps) | time steps | | N (nnuc_max) | max number of nuclides | | C (chni_max) | maximum index of relevant chains | | L (chln_max) | maximum number of links per chain | - 0) `inventory` = universal columns of DCS file `[R,T,N,C,vi]`, vi: 0=N_i-1/V, 1=dN/V, 2=N_i/V, 3=A_i/V, 4=A_i - 1) `l_chains` = `[R,T,N,C]`, length of listed chain - 2) `prod_nuc` = `[R,T,N]`, strings of the nuclide being produced - 3) `chn_indx` = `[R,T,N]`, lists of the chain indices printed - 4) `link_nuc` = `[R,T,N,C,L]`, strings of the nuclides in each chain - 5) `decay_mode` = `[R,T,N,C,L]`, strings of the decay modes each link undergoes to produce the next link - 6) `link_dN_info` = `[R,T,N,C,L,di]`, extra dN info di: 0=dN_Beam, 1=dN_Decay/nrxn, 2=dN_Total (only generated if these values are found in file, 'None' otherwise) - 7) `end_of_irradiation_time` = time of end of final irradiation step [seconds] - 8) `notable_nuclides_names_by_region` = list of lists (one per region) containing the relevant nuclides per region - 9) `notable_nuclides_AvT_by_region` = list of arrays (one per region, `[T,N_rlv-nuc,3]`) containing the time[s]/inventory[atm/cc]/activity[Bq/cc] data of relevant nuclides ''' global start try: start_time = start except: start_time = time.time() start = start_time print('Processing the *.DCS decay chain file... ({:0.2f} seconds elapsed)'.format(time.time()-start)) # Extract text from file f = open(filepath) lines = f.readlines() f.close() # Determine if extra data is written per isotope by querying whether an isotope's name or blank spaces are present in the line immediately below the first nuclide if len(lines[9][3:9].strip())==0: extra_chain_data_present = True else: extra_chain_data_present = False # First, scan for regions n_reg = 0 reg_nos = [] reg_labels = [] for line in lines: if 'c<>-<> no.' in line: n_reg += 1 reg_nos.append(int(line[12:19])) if 'c<>-<> region label :' in line: reg_labels.append(line[23:52].strip()) print('{} regions found... ({:0.2f} seconds elapsed)'.format(n_reg,time.time()-start)) # Then, scan for time steps. Need all individual times from beginning and time of end of irradiation. ntsteps = 0 wtimes = [] # written times since start of calculations in seconds (so, the times at the end of each time step) beam_state = [] # in each time step, 1 if beam on, 0 if beam off end_of_irradiation_time = 0.0 # time (in seconds since start of irradiation) at which beam was switched off for the final time end_irr_time_located = False for line in lines: if ' --- during' in line: if 'irradiation' in line: beam_state.append(1) elif 'cooling' in line: beam_state.append(0) else: beam_state.append(None) print('found weird beam condition') elif ' --- output time' in line: ntsteps += 1 t = float(line[39:53]) wtimes.append(t) if 'after the last shutdown:' in line and not end_irr_time_located: taeoi_val = float(line[88:97]) taeoi_unit = line[99] taeoi = taeoi_val*(time_str_to_sec_multiplier(taeoi_unit)) end_of_irradiation_time = t - taeoi end_irr_time_located = True elif 'end of irradiation and decay calculation for this region' in line: break wtimes = np.array(wtimes) pstr = '{} time steps found\nend of irradiation at t = {:g} sec ({})\nend of calculation at t = {:g} sec ({})... ({:0.2f} seconds elapsed)'.format( ntsteps,end_of_irradiation_time,seconds_to_ydhms(end_of_irradiation_time),wtimes[-1],seconds_to_ydhms(wtimes[-1]),time.time()-start) print(pstr) # Next, scan for other maximum limiting dimensions nnuc_max = 0 # maximum number of nuclides listed in a time step chni_max = 0 # highest index of a relevant chain found chln_max = 0 # maximum number of links (nuclides) found in any chain current_tstep_nnuc = 0 # number of nuclides in current time step chni = 0 # chain number index chln = 0 # chain length for line in lines: if len(line) < 5: continue if ' --- output time' in line or 'end of irradiation' in line: if current_tstep_nnuc > nnuc_max: nnuc_max = current_tstep_nnuc current_tstep_nnuc = 0 # reset count of nuclides in time step if len(line[3:9].strip())!=0 and line[11]=='(': # first chain entry of a nuclide current_tstep_nnuc += 1 if line[11]=='(': # all chains have this in common chni = int(line[12:16]) if chni > chni_max: chni_max = chni chln = 1 + line.count(')->') if chln > chln_max: chln_max = chln pstr = '{} = maximum number of nuclides listed in a single time step\n'.format(nnuc_max) pstr += '{} = highest index found of all relevant chains\n'.format(chni_max) pstr += '{} = length of longest chain listed... ({:0.2f} seconds elapsed)'.format(chln_max,time.time()-start) print(pstr) # Construct arrays to hold decay chain information # R (n_reg) regions # T (ntsteps) time steps # N (nnuc_max) max number of nuclides # C (chni_max) maximum index of relevant chains # L (chln_max) maximum number of links per chain inventory = np.zeros((n_reg,ntsteps,nnuc_max,chni_max,5)) # universal columns of DCS file [R,T,N,C,vi], vi: 0=N_i-1/V, 1=dN/V, 2=N_i/V, 3=A_i/V, 4=A_i l_chains = np.zeros((n_reg,ntsteps,nnuc_max,chni_max)) # [R,T,N,C], length of listed chain prod_nuc = np.empty((n_reg,ntsteps,nnuc_max), dtype='object') # [R,T,N], strings of the nuclide being produced chn_indx = np.empty((n_reg,ntsteps,nnuc_max), dtype='object') # [R,T,N], lists of the chain indices printed link_nuc = np.empty((n_reg,ntsteps,nnuc_max,chni_max,chln_max), dtype='object') # [R,T,N,C,L], strings of the nuclides in each chain decay_mode= np.empty((n_reg,ntsteps,nnuc_max,chni_max,chln_max), dtype='object') # [R,T,N,C,L], strings of the decay modes each link undergoes to produce the next link nuc_relvnt= np.empty((n_reg,ntsteps,nnuc_max), dtype='object') # [R,T,N], True/False denoting whether a nuclide meets the relevancy threshold in each time step if extra_chain_data_present: link_dN_info = np.zeros((n_reg,ntsteps,nnuc_max,chni_max,chln_max,3)) # [R,T,N,C,L,di], extra dN info di: 0=dN_Beam, 1=dN_Decay/nrxn, 2=dN_Total col_strs = ['dN_Beam','dN_Decay/nx','dN_Total'] nexcol = len(col_strs) else: link_dN_info = None # Populate these arrays ri = None # region index ti = None # time step index ni = None # nuclide index ci = None # chain index (1 lower than Fortran value) # character column and spacing numbers for decay chains ch_sci = 95 # chain start column index dc_sci = 105 # column index of first decay mode listing vl_sci = 94 # column index of first extra decay chain value link_gap_sts = 17 # number of characters between start of one link and the next for line in lines: if len(line) < 5: continue if 'c<>-<> no.' in line: # entering new region ri = find(int(line[12:19]),reg_nos) continue elif ' --- output time' in line: # entering new time step t = float(line[39:53]) ti = find(t,wtimes) ni = -1 # reset nuclide index continue elif len(line[3:9].strip())!=0 and line[11]=='(': # entering new output nuclide ni += 1 prod_nuc[ri,ti,ni] = line[3:9] if line[11]=='(': # if line contains a chain ci = int(line[12:16]) - 1 # chain index if not chn_indx[ri,ti,ni]: chn_indx[ri,ti,ni] = [ci] else: chn_indx[ri,ti,ni].append(ci) col_vals = line[25:92].strip().split() for vi in range(len(col_vals)): inventory[ri,ti,ni,ci,vi] = float(col_vals[vi]) chln = 1 + line.count(')->') l_chains[ri,ti,ni,ci] = chln for li in range(chln): nci1 = ch_sci + li*link_gap_sts nci2 = nci1 + 6 link_nuc[ri,ti,ni,ci,li] = line[nci1:nci2] if li != chln: dci1 = dc_sci + li*link_gap_sts dci2 = dci1 + 2 decay_mode[ri,ti,ni,ci,li] = line[dci1:dci2] continue if len(line[3:9].strip())==0 and extra_chain_data_present: vi = None for i in range(nexcol): if col_strs[i] in line: vi = i for li in range(chln): vci1 = vl_sci + li*link_gap_sts vci2 = vci1 + 14 if len(line[vci1:vci2].strip())==0: val = 0 else: val = float(line[vci1:vci2]) link_dN_info[ri,ti,ni,ci,li,vi] = val # Now extract results from the data arrays print('\nNow processing decay chain results... ({:0.2f} seconds elapsed)'.format(time.time()-start)) notable_nuclides_AvT_by_region = [] # list of arrays (one per region) containing the time/inventory/activity data of relevant nuclides notable_nuclides_names_by_region = [] # list of lists (one per region) containing the relevant nuclides per region for ri in range(n_reg): print('Region no. {} ({})'.format(reg_nos[ri],reg_labels[ri])) relevant_nuclides = [] for ti in range(ntsteps): t = wtimes[ti] if print_progress: if t > end_of_irradiation_time: tai = t - end_of_irradiation_time print('\tAt time {:g} sec ({}), which is {:g} sec ({}) after end of final irradiation'.format(t,seconds_to_ydhms(t),tai,seconds_to_ydhms(tai))) else: print('\tAt time {:g} sec ({})'.format(t,seconds_to_ydhms(t))) # First, get total information for the time step N0 = [] # inventory at start of time step N1 = [] # inventory at end of time step A0 = [] # activity at start of time step A1 = [] # activity at end of time step for ni in range(nnuc_max): if not prod_nuc[ri,ti,ni]: continue # skip empty nuclide indices chain_indices = chn_indx[ri,ti,ni] ci0 = chain_indices[0] # First chain ci1 = chain_indices[-1] # Last (nonzero) chain N0.append(inventory[ri,ti,ni,ci0,0]) N1.append(inventory[ri,ti,ni,ci1,2]) lam = inventory[ri,ti,ni,ci0,3]/inventory[ri,ti,ni,ci0,2] A0.append(lam*inventory[ri,ti,ni,ci0,0]) A1.append(inventory[ri,ti,ni,ci1,3]) N0_tot_tstep = np.sum(N0) # total inventory at start of time step N1_tot_tstep = np.sum(N1) # total inventory at end of time step A0_tot_tstep = np.sum(A0) # total activity at start of time step A1_tot_tstep = np.sum(A1) # total activity at end of time step # Determine which nuclides meet the relevancy threshold pstr = ('\t\tRelevant radionuclides include:\n') nii = -1 for ni in range(nnuc_max): if not prod_nuc[ri,ti,ni]: continue # skip empty nuclide indices nii += 1 A1_fract_threshold = relevancy_threshold # Nuclide must be responsible for at least 0.1% total activity at end of time step A1_nuc_frac = A1[nii]/A1_tot_tstep if A1_nuc_frac > A1_fract_threshold: nuc_relvnt[ri,ti,ni] = True if prod_nuc[ri,ti,ni] not in relevant_nuclides: relevant_nuclides.append(prod_nuc[ri,ti,ni]) pstr += ('\t\t - {} with {:0.2f}% total activity\n'.format(prod_nuc[ri,ti,ni],100*A1_nuc_frac)) else: nuc_relvnt[ri,ti,ni] = False if print_progress: print(pstr) n_relevant_nuclides = len(relevant_nuclides) # now collect activity of each nuclide at each time step relv_nuc_inv = np.zeros((ntsteps,n_relevant_nuclides,3)) # [T,rlvN,3], time[s]/inventory[atm/cc]/activity[Bq/cc] for relevant nuclides for ti in range(ntsteps): t = wtimes[ti] relv_nuc_inv[ti,:,0] = t for ni in range(nnuc_max): if not prod_nuc[ri,ti,ni]: continue # skip empty nuclide indices if prod_nuc[ri,ti,ni] not in relevant_nuclides: continue # only want nuclides which are at some point relevant chain_indices = chn_indx[ri,ti,ni] ci1 = chain_indices[-1] #if nuclide is relevant, find its index among the relevant ones rni = find(prod_nuc[ri,ti,ni],relevant_nuclides) relv_nuc_inv[ti,rni,1] = inventory[ri,ti,ni,ci1,2] relv_nuc_inv[ti,rni,2] = inventory[ri,ti,ni,ci1,3] notable_nuclides_names_by_region.append(relevant_nuclides) notable_nuclides_AvT_by_region.append(relv_nuc_inv) return inventory, l_chains, prod_nuc, chn_indx, link_nuc, decay_mode, link_dN_info, end_of_irradiation_time, notable_nuclides_names_by_region, notable_nuclides_AvT_by_region def parse_dtrk_file(path_to_dtrk_file, return_metadata=False)-
Description
Parses the output file of a T-Track tally generated by PHITS. Note that this specific function assumes that the T-Track tally was one automatically generated by and corresponding to a T-Dchain tally but in principle works with any T-Track tally. This works for region, xyz, and tetrahedral mesh geometries in either the original or reduced format.
Inputs
path_to_dtrk_file= path to the T-Track tally output file to be parsedreturn_metadata= Boolean indicating whether additional information is outputted with the flux (D=False)
Outputs
flux= a RxEx4 array containing regionwise fluxes [Elower/Eupper/flux/abs_error]dtrk_metadata(only returned ifreturn_metadata=True) = list of length twodtrk_metadata[0]= string denoting axis type 'eng' (old full format) or 'dchain' (new reduced format)dtrk_metadata[1]= string denoting mesh type as either 'reg', 'xyz', or 'tet'
Expand source code
def parse_dtrk_file(path_to_dtrk_file,return_metadata=False): ''' Description: Parses the output file of a T-Track tally generated by PHITS. Note that this specific function assumes that the T-Track tally was one automatically generated by and corresponding to a T-Dchain tally but in principle works with any T-Track tally. This works for region, xyz, and tetrahedral mesh geometries in either the original or reduced format. Inputs: - `path_to_dtrk_file` = path to the T-Track tally output file to be parsed - `return_metadata` = Boolean indicating whether additional information is outputted with the flux (D=`False`) Outputs: - `flux` = a RxEx4 array containing regionwise fluxes [Elower/Eupper/flux/abs_error] - `dtrk_metadata` (only returned if `return_metadata=True`) = list of length two - `dtrk_metadata[0]` = string denoting axis type 'eng' (old full format) or 'dchain' (new reduced format) - `dtrk_metadata[1]` = string denoting mesh type as either 'reg', 'xyz', or 'tet' ''' # Extract text from file f = open(path_to_dtrk_file) file_text = f.read() lines = file_text.split('\n') f.close() # Determine geometry type (mesh = reg, xyz, or tet) for line in lines: if 'mesh =' in line: meshtype = line.replace('mesh =','').strip().split()[0] break # Determine if original or reduced format (axis = eng or axis = dchain) for line in lines: if 'axis =' in line: axistype = line.replace('axis =','').strip().split()[0] break # Double check for li, line in enumerate(lines): if li>500: break if '# e-lower e-upper neutron r.err ' in line: axistype='eng' break dtrk_metadata = [axistype,meshtype] # Determine number of regions if axistype=='eng': nreg = file_text.count('# no. =') elif axistype=='dchain': for li, line in reversed(list(enumerate(lines))): #print(line) if '0 0 0.0000E+00 0.0000' in line: nreg = int(lines[li-1].split()[0]) break if axistype=='dchain': nEbins = 1968 else: for line in lines: if 'ne =' in line: nEbins = int(line.replace('ne =','').strip().split()[0]) break flux = np.zeros((nreg,nEbins,4)) if axistype=='eng': in_flux_lines = False ei = 0 ri = -1 for line in lines: if '# no. =' in line: ri += 1 if '# e-lower e-upper neutron r.err ' in line: in_flux_lines = True continue if in_flux_lines: flux[ri,ei,:] = [float(x) for x in line.split()] flux[ri,ei,3] = flux[ri,ei,3]*flux[ri,ei,2] # convert relative error to absolute error ei += 1 if ei == nEbins: in_flux_lines = False ei = 0 elif axistype=='dchain': ebins = [20.0] + ECCO1968_Ebins(1968) ebins = ebins[::-1] in_flux_lines = False for line in lines: if '# num ie flux r.err' in line: in_flux_lines = True continue if '0 0 0.0000E+00 0.0000' in line: in_flux_lines = False break if in_flux_lines: vals = line.split() ri = int(vals[0])-1 ei = int(vals[1])-1 fval = float(vals[2]) ferr = float(vals[3]) flux[ri,ei,0] = ebins[ei] flux[ri,ei,1] = ebins[ei+1] flux[ri,ei,2] = fval flux[ri,ei,3] = fval*ferr if return_metadata: return flux, dtrk_metadata else: return flux def parse_dyld_files(path_to_dyld_file, iredufmt=None)-
Description
Parses the output files of a T-Yield tally generated by PHITS with axis=dchain. This function assumes that the T-Yield tally was one automatically generated by and corresponding to a T-Dchain tally (axis=dchain). This works for region, xyz, and tetrahedral mesh geometries in either the original or reduced format.
Inputs
path_to_dyld_file= path to the T-Yield tally output file to be parsed (the *_err.dyld file of the same name is automatically searched for and read, if present)iredufmt= (DEPRICATED; this is now determined automatically) integer 1 or 0 specifying how the xyz meshes are ordered relative to the internal region numbers. In the new format (1), region indices are incremented as x->y->z (x=innermost loop); this is reversed in the old format (0). Ultimately, this corresponds to the same iredufmt parameter in PHITS/DCHAIN, 1='new' and 0='old'. This variable is only used for xyz meshes where this ordering matters.
Outputs
yields= a RxNx2 array containing regionwise yields (and their absolute uncertainties) for all nuclides produced in T-Yieldnuclide_names_yld= a length N list of all nuclide names in order
Expand source code
def parse_dyld_files(path_to_dyld_file,iredufmt=None): ''' Description: Parses the output files of a T-Yield tally generated by PHITS with axis=dchain. This function assumes that the T-Yield tally was one automatically generated by and corresponding to a T-Dchain tally (axis=dchain). This works for region, xyz, and tetrahedral mesh geometries in either the original or reduced format. Inputs: - `path_to_dyld_file` = path to the T-Yield tally output file to be parsed (the *_err.dyld file of the same name is automatically searched for and read, if present) - `iredufmt` = (DEPRICATED; this is now determined automatically) integer 1 or 0 specifying how the xyz meshes are ordered relative to the internal region numbers. In the new format (1), region indices are incremented as x->y->z (x=innermost loop); this is reversed in the old format (0). Ultimately, this corresponds to the same iredufmt parameter in PHITS/DCHAIN, 1='new' and 0='old'. This variable is only used for xyz meshes where this ordering matters. Outputs: - `yields` = a RxNx2 array containing regionwise yields (and their absolute uncertainties) for all nuclides produced in T-Yield - `nuclide_names_yld` = a length N list of all nuclide names in order ''' # Extract text from file f = open(path_to_dyld_file) file_text = f.read() lines = file_text.split('\n') f.close() # determine if in reduced format iredufmt=0 for li, line in enumerate(lines): if "# num nucleusID yield r.err" in line: iredufmt=1 break if "isotope production #" in line: iredufmt=0 break # Get error data if available if iredufmt==0: try: f_err = open(path_to_dyld_file.replace('.dyld','_err.dyld')) file_text_err = f_err.read() lines_err = file_text_err.split('\n') f_err.close() err_dyld_found = True except: file_text_err = None lines_err = None err_dyld_found = False # Determine geometry type (mesh = reg, xyz, or tet) for line in lines: if 'mesh =' in line: meshtype = line.replace('mesh =','').strip().split()[0] break # If xyz mesh, need to find mesh dimensions: if meshtype=='xyz': for line in lines: if 'nx =' in line: nx = int(line.replace('nx =','').strip().split()[0]) elif 'ny =' in line: ny = int(line.replace('ny =','').strip().split()[0]) elif 'nz =' in line: nz = int(line.replace('nz =','').strip().split()[0]) break # Find starting line for li, line in enumerate(lines): if 'nuclear yield (or production)' in line: li_start = li break if iredufmt==1: # Count number of nuclides present in whole file nreg = 0 nuc_id_list = [] for li, line in enumerate(lines): if li <= li_start+3: continue # in header vals = line.strip().split() if int(vals[0])==0: break # reached end if int(vals[0])>nreg: nreg = int(vals[0]) zzzaaam = int(vals[1]) if zzzaaam not in nuc_id_list: nuc_id_list.append(zzzaaam) nnuc = len(nuc_id_list) yields = np.zeros((nreg,nnuc,2)) nuclide_names_yld = [] # Get names nuc_id_list = sorted(nuc_id_list) for id in nuc_id_list: nuclide_names_yld.append(ZAM_to_Dname(id)) # Get values for li, line in enumerate(lines): if li <= li_start+3: continue # in header vals = line.strip().split() if int(vals[0])==0: break # reached end ri = int(vals[0]) - 1 zzzaaam = int(vals[1]) ni = nuc_id_list.index(zzzaaam) yields[ri,ni,0] = float(vals[2]) yields[ri,ni,1] = float(vals[3])*float(vals[2]) else: # old ''traditional'' format # Count number of nuclides present in whole file nnuc = 0 for li, line in enumerate(lines): if li <= li_start+2: continue # skip header lines if 'isotope production' in line: N_bounds = line.strip().split('=')[-1].split() N_bounds = [int(i) for i in N_bounds] nnuc += N_bounds[1] - N_bounds[0] + 1 # Determine number of regions nreg = 0 for li, line in enumerate(lines): if li <= li_start+4: continue # skip header lines if len(line) < 2: break # reached end of first element block nreg += 1 yields = np.zeros((nreg,nnuc,2)) nuclide_names_yld = [] # Extract yield data ni = 0 # nuclide index ni_newstart = 0 ri = 0 # region index for li, line in enumerate(lines): if li <= li_start+2: continue # skip header lines if len(line) < 2: continue # skip line breaks if 'isotope production' in line: # extract Z and A info Z = int(line.strip().split('-')[0]) N_bounds = line.strip().split('=')[-1].split() N_bounds = [int(i) for i in N_bounds] N_list = [] for i in range(N_bounds[1]-N_bounds[0]+1): N_list.append(N_bounds[0]+i) nisotopes = len(N_list) A_list = [N+Z for N in N_list] ni_newstart = len(nuclide_names_yld) for A in A_list: ZAM = 10*A + 10000*Z nuclide_names_yld.append(ZAM_to_Dname(ZAM)) on_buffer_line = True continue if on_buffer_line: ri = 0 on_buffer_line = False continue if '# Information for Restart Calculation' in line: break # reached end of useful info # Only lines making it to this point will be ones with region and yield data vals = line.strip().split() if meshtype=='xyz': yvals = vals[3:] if err_dyld_found: yvals_rerr = lines_err[li].strip().split()[3:] jx,jy,jz = int(vals[0]),int(vals[1]),int(vals[2]) rii = jz + (jy-1)*nz + (jx-1)*(nz*ny) #if iredufmt==1: # rii = jx + (jy-1)*nx + (jz-1)*(nx*ny) #else: # rii = jz + (jy-1)*nz + (jx-1)*(nz*ny) else: yvals = vals[1:] if err_dyld_found: yvals_rerr = lines_err[li].split()[1:] rii = ri for i in range(nisotopes): yields[rii,ni_newstart+i,0] = float(yvals[i]) if err_dyld_found: yields[rii,ni_newstart+i,1] = float(yvals_rerr[i])*yields[rii,ni_newstart+i,0] ri += 1 return yields, nuclide_names_yld def Dname_to_ZAM(Dname)-
Description
Converts a DCHAIN-formatted nuclide name to a ZZZAAAM number
Inputs
Dname= nuclide identification string in DCHAIN format
Outputs
ZZZAAAM= nuclide identification ineger, calculated as 10000*Z + 10*A + m
Expand source code
def Dname_to_ZAM(Dname): ''' Description: Converts a DCHAIN-formatted nuclide name to a ZZZAAAM number Inputs: - `Dname` = nuclide identification string in DCHAIN format Outputs: - `ZZZAAAM` = nuclide identification ineger, calculated as 10000\*Z + 10\*A + m ''' elms = ["n ",\ "H ","He","Li","Be","B ","C ","N ","O ","F ","Ne",\ "Na","Mg","Al","Si","P ","S ","Cl","Ar","K ","Ca",\ "Sc","Ti","V ","Cr","Mn","Fe","Co","Ni","Cu","Zn",\ "Ga","Ge","As","Se","Br","Kr","Rb","Sr","Y ","Zr",\ "Nb","Mo","Tc","Ru","Rh","Pd","Ag","Cd","In","Sn",\ "Sb","Te","I ","Xe","Cs","Ba","La","Ce","Pr","Nd",\ "Pm","Sm","Eu","Gd","Tb","Dy","Ho","Er","Tm","Yb",\ "Lu","Hf","Ta","W ","Re","Os","Ir","Pt","Au","Hg",\ "Tl","Pb","Bi","Po","At","Rn","Fr","Ra","Ac","Th",\ "Pa","U ","Np","Pu","Am","Cm","Bk","Cf","Es","Fm",\ "Md","No","Lr","Rf","Db","Sg","Bh","Hs","Mt","Ds",\ "Rg","Cn","Nh","Fl","Mc","Lv","Ts","Og"] AAA = Dname[2:5] A = int(AAA) symbol = Dname[0:2] if 'XX' in symbol: symbol='n ' Z = find(symbol,elms) if Dname[-1] == ' ': m = 0 elif Dname[-1] == 'm': m = 1 elif Dname[-1] == 'n': m = 2 ZAM = int(10000*Z + 10*A + m) return ZAM def ZAM_to_Dname(ZAM)-
Description
Converts a ZZZAAAM number to a DCHAIN-formatted nuclide name
Inputs
ZZZAAAM= nuclide identification ineger, calculated as 10000*Z + 10*A + m
Outputs
Dname= nuclide identification string in DCHAIN format
Expand source code
def ZAM_to_Dname(ZAM): ''' Description: Converts a ZZZAAAM number to a DCHAIN-formatted nuclide name Inputs: - `ZZZAAAM` = nuclide identification ineger, calculated as 10000\*Z + 10\*A + m Outputs: - `Dname` = nuclide identification string in DCHAIN format ''' elms = ["n ",\ "H ","He","Li","Be","B ","C ","N ","O ","F ","Ne",\ "Na","Mg","Al","Si","P ","S ","Cl","Ar","K ","Ca",\ "Sc","Ti","V ","Cr","Mn","Fe","Co","Ni","Cu","Zn",\ "Ga","Ge","As","Se","Br","Kr","Rb","Sr","Y ","Zr",\ "Nb","Mo","Tc","Ru","Rh","Pd","Ag","Cd","In","Sn",\ "Sb","Te","I ","Xe","Cs","Ba","La","Ce","Pr","Nd",\ "Pm","Sm","Eu","Gd","Tb","Dy","Ho","Er","Tm","Yb",\ "Lu","Hf","Ta","W ","Re","Os","Ir","Pt","Au","Hg",\ "Tl","Pb","Bi","Po","At","Rn","Fr","Ra","Ac","Th",\ "Pa","U ","Np","Pu","Am","Cm","Bk","Cf","Es","Fm",\ "Md","No","Lr","Rf","Db","Sg","Bh","Hs","Mt","Ds",\ "Rg","Cn","Nh","Fl","Mc","Lv","Ts","Og"] m = int(str(ZAM)[-1]) A = int(str(ZAM)[-4:-1]) Z = int(str(ZAM)[:-4]) sym = elms[Z] A_str = '{:>3}'.format(A) m_str_list = [' ','m','n'] m_str = m_str_list[m] Dname = sym + A_str + m_str return Dname def Dname_to_Latex(Dname)-
Description
Converts a DCHAIN-formatted nuclide name to a LaTeX-formatted string
Inputs
Dname= nuclide identification string in DCHAIN format
Outputs
- nuclide name as a LaTeX-formatted raw string
Expand source code
def Dname_to_Latex(Dname): ''' Description: Converts a DCHAIN-formatted nuclide name to a LaTeX-formatted string Inputs: - `Dname` = nuclide identification string in DCHAIN format Outputs: - nuclide name as a LaTeX-formatted raw string ''' AAA = Dname[2:5].strip() symbol = Dname[0:2].strip() m = Dname[-1].strip() latex_str = r"$^{{{}{}}}$".format(AAA,m) + "{}".format(symbol) return latex_str def nuclide_plain_str_to_Dname(nuc_str)-
Description
Converts a plaintext string of a nuclide to a DCHAIN-formatted nuclide string
Dependencies
Inputs
nuc_str= string to be converted; a huge variety of formats are supported, but they all must follow the following rules:- Isomeric/metastable state characters must always immediately follow the atomic mass characters.
Isomeric state labels MUST either:
- (1) be a single lower-case character
- (2) begin with any non-numeric character and end with a number
- Atomic mass numbers must be nonnegative integers OR the string
"nat"(in which case no metastable states can be written) - Elemental symbols MUST begin with an upper-case character
- Isomeric/metastable state characters must always immediately follow the atomic mass characters.
Isomeric state labels MUST either:
Outputs
- DCHAIN-formatted string of nuclide name
Expand source code
def nuclide_plain_str_to_Dname(nuc_str): ''' Description: Converts a plaintext string of a nuclide to a DCHAIN-formatted nuclide string Dependencies: - `nuclide_plain_str_ZZZAAAM` - `ZAM_to_Dname` Inputs: - `nuc_str` = string to be converted; a huge variety of formats are supported, but they all must follow the following rules: + Isomeric/metastable state characters must always immediately follow the atomic mass characters. Isomeric state labels MUST either: - (1) be a single lower-case character - (2) begin with any non-numeric character and end with a number + Atomic mass numbers must be nonnegative integers OR the string `"nat"` (in which case no metastable states can be written) + Elemental symbols MUST begin with an upper-case character Outputs: - DCHAIN-formatted string of nuclide name ''' return ZAM_to_Dname(nuclide_plain_str_ZZZAAAM(nuc_str)) def rxn_to_dchain_str(target, reaction=None, product=None)-
Desription
Provided a target nuclide and reaction, and optionally a target, generate a reaction string in the format used in DCHAIN's nrxn libs
Dependencies
ZZZAAAM_to_dchain_xs_lib_str()Inputs
target= string in general format of target nuclide- Note: at least one of the below options must be provided.
reaction= (optional) either an int MT number (ENDF6 format) or a string of the ejectiles from the neutron reaction (case-insensitive), the "X" in (N,X)product= (optional) string in general format of product nuclide (if omitted, product in ground state is assumed)
Outputs
rxn_dchain_str= string formatted identically as that found in DCHAIN's neutron reaction cross section libraries
Expand source code
def rxn_to_dchain_str(target,reaction=None,product=None): ''' Desription: Provided a target nuclide and reaction, and optionally a target, generate a reaction string in the format used in DCHAIN's nrxn libs Dependencies: `nuclide_plain_str_ZZZAAAM` `ZZZAAAM_to_dchain_xs_lib_str` Inputs: - `target` = string in general format of target nuclide - Note: at least one of the below options must be provided. - `reaction` = (optional) either an int MT number (ENDF6 format) or a string of the ejectiles from the neutron reaction (case-insensitive), the "X" in (N,X) - `product` = (optional) string in general format of product nuclide (if omitted, product in ground state is assumed) Outputs: - `rxn_dchain_str` = string formatted identically as that found in DCHAIN's neutron reaction cross section libraries ''' if not reaction and not product: print('Warning: no reaction or product provided with target {}.'.format(target)) ZZZAAAM = nuclide_plain_str_ZZZAAAM(target) target_dstr = ZZZAAAM_to_dchain_xs_lib_str(ZZZAAAM) dstr = target_dstr + '(N,' return dstr ZZZAAAM = nuclide_plain_str_ZZZAAAM(target) target_dstr = ZZZAAAM_to_dchain_xs_lib_str(ZZZAAAM) if product: # if not None (product is provided) ZZZAAAM_prod = nuclide_plain_str_ZZZAAAM(product) product_dstr = ZZZAAAM_to_dchain_xs_lib_str(ZZZAAAM_prod) react = [' ', ' ', ' ', ' ', 'N ', ' ', ' ', ' ', ' ', ' ', ' ', '2ND', ' ', ' ', ' ', ' ', '2N ', '3N ', 'FIS', ' ', ' ', ' ', 'NA ', 'N3A', '2NA', '3NA', ' ', ' ', 'NP ', 'N2A', '2N2', ' ', 'ND ', 'NT ', 'NE ', 'ND2', 'NT2', '4N ', ' ', ' ', ' ', '2NP', '3NP', ' ', 'N2P', 'NPA', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', 'G ', 'P ', 'D ', 'T ', 'HE3', 'A ', '2A ', '3A ', ' ', '2P ', 'PA ', 'T2A', 'D2A', 'PD ', 'PT ', 'DA ', ' ', ' '] dZ = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -2, -6, -2, -2, 0, 0, -1, -4, -4, 0, -1, -1, -2, -5, -5, 0, 0, 0, 0, -1, -1, 0, -2, -3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -1, -1, -1, -2, -2, -4, -6, 0, -2, -3, -5, -5, -2, -2, -3, 0, 0] dA = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -3, 0, 0, 0, 0, -1, -2, 0, 0, 0, 0, -4, -12, -5, -6, 0, 0, -1, -8, -9, 0, -2, -3, -3, -10, -11, -3, 0, 0, 0, -2, -3, 0, -2, -5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, -1, -2, -2, -3, -7, -11, 0, -1, -4, -10, -9, -2, -3, -5, 0, 0] if reaction: # reaction is provided # Get reaction from MT / check if valid reaction if isinstance(reaction, float): reaction = int(reaction) if isinstance(reaction, int): MT = reaction rxn = react[MT] else: rxn = "{:3}".format(reaction.upper()) if rxn not in react: print('Reaction "{}" not in reaction list for DCHAIN, check formatting or enter ENDF MT number (0-119)'.format(rxn)) return None else: MT = react.index(rxn) if not product: # need to figure out product from parent and rxn, assume ground state (but omit final isomeric characters from string in case xslib has other states too) ZAM_str = str(ZZZAAAM) M = 0 A = int(ZAM_str[-4:-1]) + dA[MT] Z = int(ZAM_str[:-4]) + dZ[MT] ZZZAAAM_prod = 10000*Z + 10*A + M product_dstr = ZZZAAAM_to_dchain_xs_lib_str(ZZZAAAM_prod)[:-2] if MT == 18: product_dstr = '' # fission if not reaction: # need to find missing reaction from target and product, isomeric states are ignored ZAM_str = str(ZZZAAAM) A_tar = int(ZAM_str[-4:-1]) Z_tar = int(ZAM_str[:-4]) ZAM_str_prod = str(ZZZAAAM_prod) A_prod = int(ZAM_str_prod[-4:-1]) Z_prod = int(ZAM_str_prod[:-4]) rxn_dA = A_prod - A_tar rxn_dZ = Z_prod - Z_tar matching_dA = [index for index,value in enumerate(dA) if value == rxn_dA] matching_dZ = [index for index,value in enumerate(dZ) if value == rxn_dZ] MT = set(matching_dA).intersection(matching_dZ).pop() # gets the value which is common between the two lists, in this case the index of the reaction rxn = react[MT] if reaction and product: # check to make sure they are compatible # if mismatch occurs, assume product is more likely correct than rxn ZAM_str = str(ZZZAAAM) A_tar = int(ZAM_str[-4:-1]) Z_tar = int(ZAM_str[:-4]) ZAM_str_prod = str(ZZZAAAM_prod) A_prod = int(ZAM_str_prod[-4:-1]) Z_prod = int(ZAM_str_prod[:-4]) rxn_dA = A_prod - A_tar rxn_dZ = Z_prod - Z_tar matching_dA = [index for index,value in enumerate(dA) if value == rxn_dA] matching_dZ = [index for index,value in enumerate(dZ) if value == rxn_dZ] if A_tar==A_prod and Z_tar==Z_prod: MT_calc = 4 else: MT_calc = set(matching_dA).intersection(matching_dZ).pop() # gets the value which is common between the two lists, in this case the index of the reaction rxn_calc = react[MT_calc] if rxn_calc != rxn: print('Warning, mismatch between reaction (N,{}) and product ({}) with target {}; assuming product ({}) is correct and reaction should be (N,{}) instead.'.format(rxn.strip(),product,target,product_dstr,rxn_calc.strip())) rxn = rxn_calc dstr = target_dstr + '(N,{})'.format(rxn) + product_dstr return dstr def ZZZAAAM_to_dchain_xs_lib_str(ZZZAAAM)-
Description
Converts a ZZZAAAM number to the 7-character nuclide string used by the DCHAIN neutron reaction cross section libraries.
Inputs
ZZZAAAM= nuclide identification ineger, calculated as 10000*Z + 10*A + m
Outputs
D_xs_name= nuclide identification string in DCHAIN's cross section library format
Expand source code
def ZZZAAAM_to_dchain_xs_lib_str(ZZZAAAM): ''' Description: Converts a ZZZAAAM number to the 7-character nuclide string used by the DCHAIN neutron reaction cross section libraries. Inputs: - `ZZZAAAM` = nuclide identification ineger, calculated as 10000\*Z + 10\*A + m Outputs: - `D_xs_name` = nuclide identification string in DCHAIN's cross section library format ''' ZAM_str = str(ZZZAAAM) M = int(ZAM_str[-1]) A = str(int(ZAM_str[-4:-1])) Z = ZAM_str[:-4] sym = Element_Z_to_Sym(int(Z)).upper() if M==0: M_str = ' ' else: M_str = 'M' + str(M) dstr = "{:2}{:>3}{:2}".format(sym,A,M_str) return dstr def ECCO1968_Ebins(n)-
Description
Returns the n highest energy bin values of the ECCO 1968-group energy binning structure.
Inputs
n= number of energy bins (from 20 MeV down) to be returned
Outputs
- list of
nenergy bins of the ECCO 1968-group structure
Expand source code
def ECCO1968_Ebins(n): ''' Description: Returns the n highest energy bin values of the ECCO 1968-group energy binning structure. Inputs: - `n` = number of energy bins (from 20 MeV down) to be returned Outputs: - list of `n` energy bins of the ECCO 1968-group structure ''' ECCO_bins = [ 1.964033E+01,1.947734E+01,1.931570E+01,1.915541E+01,1.899644E+01,1.883880E+01,1.868246E+01,1.852742E+01,1.837367E+01,1.822119E+01,1.806998E+01,1.792002E+01,1.777131E+01,1.762383E+01,1.747757E+01,1.733253E+01,1.718869E+01,1.704605E+01,1.690459E+01,1.676430E+01,1.662518E+01, 1.648721E+01,1.635039E+01,1.621470E+01,1.608014E+01,1.594670E+01,1.581436E+01,1.568312E+01,1.555297E+01,1.542390E+01,1.529590E+01,1.516897E+01,1.504309E+01,1.491825E+01,1.479444E+01,1.467167E+01,1.454991E+01,1.442917E+01,1.430943E+01,1.419068E+01,1.407291E+01, 1.395612E+01,1.384031E+01,1.372545E+01,1.361155E+01,1.349859E+01,1.338657E+01,1.327548E+01,1.316531E+01,1.305605E+01,1.294770E+01,1.284025E+01,1.273370E+01,1.262802E+01,1.252323E+01,1.241930E+01,1.231624E+01,1.221403E+01,1.211267E+01,1.201215E+01,1.191246E+01, 1.181360E+01,1.171557E+01,1.161834E+01,1.152193E+01,1.142631E+01,1.133148E+01,1.123745E+01,1.114419E+01,1.105171E+01,1.095999E+01,1.086904E+01,1.077884E+01,1.068939E+01,1.060068E+01,1.051271E+01,1.042547E+01,1.033895E+01,1.025315E+01,1.016806E+01,1.008368E+01, 1.000000E+01,9.917013E+00,9.834715E+00,9.753099E+00,9.672161E+00,9.591895E+00,9.512294E+00,9.433354E+00,9.355070E+00,9.277435E+00,9.200444E+00,9.124092E+00,9.048374E+00,8.973284E+00,8.898818E+00,8.824969E+00,8.751733E+00,8.679105E+00,8.607080E+00,8.535652E+00, 8.464817E+00,8.394570E+00,8.324906E+00,8.255820E+00,8.187308E+00,8.119363E+00,8.051983E+00,7.985162E+00,7.918896E+00,7.853179E+00,7.788008E+00,7.723377E+00,7.659283E+00,7.595721E+00,7.532687E+00,7.470175E+00,7.408182E+00,7.346704E+00,7.285736E+00,7.225274E+00, 7.165313E+00,7.105850E+00,7.046881E+00,6.988401E+00,6.930406E+00,6.872893E+00,6.815857E+00,6.759294E+00,6.703200E+00,6.647573E+00,6.592406E+00,6.537698E+00,6.483443E+00,6.429639E+00,6.376282E+00,6.323367E+00,6.270891E+00,6.218851E+00,6.167242E+00,6.116062E+00, 6.065307E+00,6.014972E+00,5.965056E+00,5.915554E+00,5.866462E+00,5.817778E+00,5.769498E+00,5.721619E+00,5.674137E+00,5.627049E+00,5.580351E+00,5.534042E+00,5.488116E+00,5.442572E+00,5.397406E+00,5.352614E+00,5.308195E+00,5.264143E+00,5.220458E+00,5.177135E+00, 5.134171E+00,5.091564E+00,5.049311E+00,5.007408E+00,4.965853E+00,4.924643E+00,4.883775E+00,4.843246E+00,4.803053E+00,4.763194E+00,4.723666E+00,4.684465E+00,4.645590E+00,4.607038E+00,4.568805E+00,4.530890E+00,4.493290E+00,4.456001E+00,4.419022E+00,4.382350E+00, 4.345982E+00,4.309916E+00,4.274149E+00,4.238679E+00,4.203504E+00,4.168620E+00,4.134026E+00,4.099719E+00,4.065697E+00,4.031957E+00,3.998497E+00,3.965314E+00,3.932407E+00,3.899773E+00,3.867410E+00,3.835316E+00,3.803488E+00,3.771924E+00,3.740621E+00,3.709579E+00, 3.678794E+00,3.648265E+00,3.617989E+00,3.587965E+00,3.558189E+00,3.528661E+00,3.499377E+00,3.470337E+00,3.441538E+00,3.412978E+00,3.384654E+00,3.356566E+00,3.328711E+00,3.301087E+00,3.273692E+00,3.246525E+00,3.219583E+00,3.192864E+00,3.166368E+00,3.140091E+00, 3.114032E+00,3.088190E+00,3.062562E+00,3.037147E+00,3.011942E+00,2.986947E+00,2.962159E+00,2.937577E+00,2.913199E+00,2.889023E+00,2.865048E+00,2.841272E+00,2.817693E+00,2.794310E+00,2.771121E+00,2.748124E+00,2.725318E+00,2.702701E+00,2.680272E+00,2.658030E+00, 2.635971E+00,2.614096E+00,2.592403E+00,2.570889E+00,2.549554E+00,2.528396E+00,2.507414E+00,2.486605E+00,2.465970E+00,2.445505E+00,2.425211E+00,2.405085E+00,2.385126E+00,2.365332E+00,2.345703E+00,2.326237E+00,2.306932E+00,2.287787E+00,2.268802E+00,2.249973E+00, 2.231302E+00,2.212785E+00,2.194421E+00,2.176211E+00,2.158151E+00,2.140241E+00,2.122480E+00,2.104866E+00,2.087398E+00,2.070076E+00,2.052897E+00,2.035860E+00,2.018965E+00,2.002210E+00,1.985595E+00,1.969117E+00,1.952776E+00,1.936570E+00,1.920499E+00,1.904561E+00, 1.888756E+00,1.873082E+00,1.857538E+00,1.842122E+00,1.826835E+00,1.811675E+00,1.796640E+00,1.781731E+00,1.766944E+00,1.752281E+00,1.737739E+00,1.723318E+00,1.709017E+00,1.694834E+00,1.680770E+00,1.666821E+00,1.652989E+00,1.639271E+00,1.625667E+00,1.612176E+00, 1.598797E+00,1.585530E+00,1.572372E+00,1.559323E+00,1.546383E+00,1.533550E+00,1.520823E+00,1.508202E+00,1.495686E+00,1.483274E+00,1.470965E+00,1.458758E+00,1.446652E+00,1.434646E+00,1.422741E+00,1.410934E+00,1.399225E+00,1.387613E+00,1.376098E+00,1.364678E+00, 1.353353E+00,1.342122E+00,1.330984E+00,1.319938E+00,1.308985E+00,1.298122E+00,1.287349E+00,1.276666E+00,1.266071E+00,1.255564E+00,1.245145E+00,1.234812E+00,1.224564E+00,1.214402E+00,1.204324E+00,1.194330E+00,1.184418E+00,1.174589E+00,1.164842E+00,1.155175E+00, 1.145588E+00,1.136082E+00,1.126654E+00,1.117304E+00,1.108032E+00,1.098836E+00,1.089717E+00,1.080674E+00,1.071706E+00,1.062812E+00,1.053992E+00,1.045245E+00,1.036571E+00,1.027969E+00,1.019438E+00,1.010978E+00,1.002588E+00,9.942682E-01,9.860171E-01,9.778344E-01, 9.697197E-01,9.616723E-01,9.536916E-01,9.457772E-01,9.379285E-01,9.301449E-01,9.224259E-01,9.147709E-01,9.071795E-01,8.996511E-01,8.921852E-01,8.847812E-01,8.774387E-01,8.701570E-01,8.629359E-01,8.557746E-01,8.486728E-01,8.416299E-01,8.346455E-01,8.277190E-01, 8.208500E-01,8.140380E-01,8.072825E-01,8.005831E-01,7.939393E-01,7.873507E-01,7.808167E-01,7.743369E-01,7.679109E-01,7.615382E-01,7.552184E-01,7.489511E-01,7.427358E-01,7.365720E-01,7.304594E-01,7.243976E-01,7.183860E-01,7.124243E-01,7.065121E-01,7.006490E-01, 6.948345E-01,6.890683E-01,6.833499E-01,6.776790E-01,6.720551E-01,6.664779E-01,6.609470E-01,6.554620E-01,6.500225E-01,6.446282E-01,6.392786E-01,6.339734E-01,6.287123E-01,6.234948E-01,6.183206E-01,6.131893E-01,6.081006E-01,6.030542E-01,5.980496E-01,5.930866E-01, 5.881647E-01,5.832837E-01,5.784432E-01,5.736429E-01,5.688824E-01,5.641614E-01,5.594796E-01,5.548366E-01,5.502322E-01,5.456660E-01,5.411377E-01,5.366469E-01,5.321934E-01,5.277769E-01,5.233971E-01,5.190535E-01,5.147461E-01,5.104743E-01,5.062381E-01,5.020369E-01, 4.978707E-01,4.937390E-01,4.896416E-01,4.855782E-01,4.815485E-01,4.775523E-01,4.735892E-01,4.696591E-01,4.657615E-01,4.618963E-01,4.580631E-01,4.542618E-01,4.504920E-01,4.467535E-01,4.430460E-01,4.393693E-01,4.357231E-01,4.321072E-01,4.285213E-01,4.249651E-01, 4.214384E-01,4.179410E-01,4.144727E-01,4.110331E-01,4.076220E-01,4.042393E-01,4.008846E-01,3.975578E-01,3.942586E-01,3.909868E-01,3.877421E-01,3.845243E-01,3.813333E-01,3.781687E-01,3.750304E-01,3.719181E-01,3.688317E-01,3.657708E-01,3.627354E-01,3.597252E-01, 3.567399E-01,3.537795E-01,3.508435E-01,3.479320E-01,3.450446E-01,3.421812E-01,3.393415E-01,3.365254E-01,3.337327E-01,3.309631E-01,3.282166E-01,3.254928E-01,3.227916E-01,3.201129E-01,3.174564E-01,3.148219E-01,3.122093E-01,3.096183E-01,3.070489E-01,3.045008E-01, 3.019738E-01,2.994678E-01,2.985000E-01,2.972000E-01,2.969826E-01,2.945181E-01,2.920740E-01,2.896501E-01,2.872464E-01,2.848626E-01,2.824986E-01,2.801543E-01,2.778293E-01,2.755237E-01,2.732372E-01,2.709697E-01,2.687210E-01,2.664910E-01,2.642794E-01,2.620863E-01, 2.599113E-01,2.577544E-01,2.556153E-01,2.534941E-01,2.513904E-01,2.493042E-01,2.472353E-01,2.451835E-01,2.431488E-01,2.411310E-01,2.391299E-01,2.371455E-01,2.351775E-01,2.332258E-01,2.312903E-01,2.293709E-01,2.274674E-01,2.255797E-01,2.237077E-01,2.218512E-01, 2.200102E-01,2.181844E-01,2.163737E-01,2.145781E-01,2.127974E-01,2.110314E-01,2.092801E-01,2.075434E-01,2.058210E-01,2.041130E-01,2.024191E-01,2.007393E-01,1.990734E-01,1.974214E-01,1.957830E-01,1.941583E-01,1.925470E-01,1.909491E-01,1.893645E-01,1.877930E-01, 1.862346E-01,1.846891E-01,1.831564E-01,1.816364E-01,1.801291E-01,1.786342E-01,1.771518E-01,1.756817E-01,1.742237E-01,1.727779E-01,1.713441E-01,1.699221E-01,1.685120E-01,1.671136E-01,1.657268E-01,1.643514E-01,1.629875E-01,1.616349E-01,1.602936E-01,1.589634E-01, 1.576442E-01,1.563359E-01,1.550385E-01,1.537519E-01,1.524760E-01,1.512106E-01,1.499558E-01,1.487113E-01,1.474772E-01,1.462533E-01,1.450396E-01,1.438360E-01,1.426423E-01,1.414586E-01,1.402847E-01,1.391205E-01,1.379660E-01,1.368210E-01,1.356856E-01,1.345596E-01, 1.334429E-01,1.323355E-01,1.312373E-01,1.301482E-01,1.290681E-01,1.279970E-01,1.269348E-01,1.258814E-01,1.248368E-01,1.238008E-01,1.227734E-01,1.217545E-01,1.207441E-01,1.197421E-01,1.187484E-01,1.177629E-01,1.167857E-01,1.158165E-01,1.148554E-01,1.139022E-01, 1.129570E-01,1.120196E-01,1.110900E-01,1.101681E-01,1.092538E-01,1.083471E-01,1.074480E-01,1.065563E-01,1.056720E-01,1.047951E-01,1.039254E-01,1.030630E-01,1.022077E-01,1.013595E-01,1.005184E-01,9.968419E-02,9.885694E-02,9.803655E-02,9.722297E-02,9.641615E-02, 9.561602E-02,9.482253E-02,9.403563E-02,9.325525E-02,9.248135E-02,9.171388E-02,9.095277E-02,9.019798E-02,8.944945E-02,8.870714E-02,8.797098E-02,8.724094E-02,8.651695E-02,8.579897E-02,8.508695E-02,8.438084E-02,8.368059E-02,8.298615E-02,8.250000E-02,8.229747E-02, 8.161451E-02,8.093721E-02,8.026554E-02,7.959944E-02,7.950000E-02,7.893887E-02,7.828378E-02,7.763412E-02,7.698986E-02,7.635094E-02,7.571733E-02,7.508897E-02,7.446583E-02,7.384786E-02,7.323502E-02,7.262726E-02,7.202455E-02,7.142684E-02,7.083409E-02,7.024626E-02, 6.966330E-02,6.908519E-02,6.851187E-02,6.794331E-02,6.737947E-02,6.682031E-02,6.626579E-02,6.571586E-02,6.517051E-02,6.462968E-02,6.409333E-02,6.356144E-02,6.303396E-02,6.251086E-02,6.199211E-02,6.147765E-02,6.096747E-02,6.046151E-02,5.995976E-02,5.946217E-02, 5.896871E-02,5.847935E-02,5.799405E-02,5.751277E-02,5.703549E-02,5.656217E-02,5.609278E-02,5.562728E-02,5.516564E-02,5.470784E-02,5.425384E-02,5.380360E-02,5.335710E-02,5.291430E-02,5.247518E-02,5.203971E-02,5.160785E-02,5.117957E-02,5.075484E-02,5.033364E-02, 4.991594E-02,4.950170E-02,4.909090E-02,4.868351E-02,4.827950E-02,4.787884E-02,4.748151E-02,4.708747E-02,4.669671E-02,4.630919E-02,4.592488E-02,4.554376E-02,4.516581E-02,4.479099E-02,4.441928E-02,4.405066E-02,4.368510E-02,4.332257E-02,4.296305E-02,4.260651E-02, 4.225293E-02,4.190229E-02,4.155455E-02,4.120970E-02,4.086771E-02,4.052857E-02,4.019223E-02,3.985869E-02,3.952791E-02,3.919988E-02,3.887457E-02,3.855196E-02,3.823203E-02,3.791476E-02,3.760011E-02,3.728808E-02,3.697864E-02,3.667176E-02,3.636743E-02,3.606563E-02, 3.576633E-02,3.546952E-02,3.517517E-02,3.488326E-02,3.459377E-02,3.430669E-02,3.402199E-02,3.373965E-02,3.345965E-02,3.318198E-02,3.290662E-02,3.263353E-02,3.236272E-02,3.209415E-02,3.182781E-02,3.156368E-02,3.130174E-02,3.104198E-02,3.078437E-02,3.052890E-02, 3.027555E-02,3.002430E-02,2.977514E-02,2.952804E-02,2.928300E-02,2.903999E-02,2.879899E-02,2.856000E-02,2.850000E-02,2.832299E-02,2.808794E-02,2.785485E-02,2.762369E-02,2.739445E-02,2.716711E-02,2.700000E-02,2.694166E-02,2.671808E-02,2.649635E-02,2.627647E-02, 2.605841E-02,2.584215E-02,2.562770E-02,2.541502E-02,2.520411E-02,2.499495E-02,2.478752E-02,2.458182E-02,2.437782E-02,2.417552E-02,2.397489E-02,2.377593E-02,2.357862E-02,2.338295E-02,2.318890E-02,2.299646E-02,2.280562E-02,2.261636E-02,2.242868E-02,2.224255E-02, 2.205796E-02,2.187491E-02,2.169338E-02,2.151335E-02,2.133482E-02,2.115777E-02,2.098218E-02,2.080806E-02,2.063538E-02,2.046413E-02,2.029431E-02,2.012589E-02,1.995887E-02,1.979324E-02,1.962898E-02,1.946608E-02,1.930454E-02,1.914434E-02,1.898547E-02,1.882791E-02, 1.867166E-02,1.851671E-02,1.836305E-02,1.821066E-02,1.805953E-02,1.790966E-02,1.776104E-02,1.761364E-02,1.746747E-02,1.732251E-02,1.717876E-02,1.703620E-02,1.689482E-02,1.675461E-02,1.661557E-02,1.647768E-02,1.634094E-02,1.620533E-02,1.607085E-02,1.593748E-02, 1.580522E-02,1.567406E-02,1.554398E-02,1.541499E-02,1.528706E-02,1.516020E-02,1.503439E-02,1.490963E-02,1.478590E-02,1.466319E-02,1.454151E-02,1.442083E-02,1.430116E-02,1.418247E-02,1.406478E-02,1.394806E-02,1.383231E-02,1.371752E-02,1.360368E-02,1.349079E-02, 1.337883E-02,1.326780E-02,1.315770E-02,1.304851E-02,1.294022E-02,1.283283E-02,1.272634E-02,1.262073E-02,1.251599E-02,1.241212E-02,1.230912E-02,1.220697E-02,1.210567E-02,1.200521E-02,1.190558E-02,1.180678E-02,1.170880E-02,1.161163E-02,1.151527E-02,1.141970E-02, 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4.628243E-05,4.589834E-05,4.551744E-05,4.513971E-05,4.476511E-05,4.439361E-05,4.402521E-05,4.365985E-05,4.329753E-05,4.293822E-05,4.258189E-05,4.222851E-05,4.187807E-05,4.153054E-05,4.118589E-05,4.084410E-05,4.050514E-05,4.016900E-05,3.983565E-05,3.950507E-05, 3.917723E-05,3.885211E-05,3.852969E-05,3.820994E-05,3.789285E-05,3.757838E-05,3.726653E-05,3.695727E-05,3.665057E-05,3.634642E-05,3.604479E-05,3.574566E-05,3.544902E-05,3.515484E-05,3.486310E-05,3.457378E-05,3.428686E-05,3.400233E-05,3.372015E-05,3.344032E-05, 3.316281E-05,3.288760E-05,3.261467E-05,3.234401E-05,3.207560E-05,3.180942E-05,3.154544E-05,3.128365E-05,3.102404E-05,3.076658E-05,3.051126E-05,3.025805E-05,3.000695E-05,2.975793E-05,2.951098E-05,2.926607E-05,2.902320E-05,2.878235E-05,2.854349E-05,2.830662E-05, 2.807171E-05,2.783875E-05,2.760773E-05,2.737862E-05,2.715141E-05,2.692609E-05,2.670264E-05,2.648104E-05,2.626128E-05,2.604335E-05,2.582722E-05,2.561289E-05,2.540033E-05,2.518954E-05,2.498050E-05,2.477320E-05,2.456761E-05,2.436373E-05,2.416154E-05,2.396104E-05, 2.376219E-05,2.356499E-05,2.336944E-05,2.317550E-05,2.298317E-05,2.279244E-05,2.260329E-05,2.241572E-05,2.222969E-05,2.204522E-05,2.186227E-05,2.168084E-05,2.150092E-05,2.132249E-05,2.114554E-05,2.097006E-05,2.079603E-05,2.062345E-05,2.045231E-05,2.028258E-05, 2.011426E-05,1.994734E-05,1.978180E-05,1.961764E-05,1.945484E-05,1.929339E-05,1.913328E-05,1.897449E-05,1.881703E-05,1.866087E-05,1.850601E-05,1.835244E-05,1.820013E-05,1.804910E-05,1.789931E-05,1.775077E-05,1.760346E-05,1.745738E-05,1.731250E-05,1.716883E-05, 1.702635E-05,1.688506E-05,1.674493E-05,1.660597E-05,1.646816E-05,1.633150E-05,1.619597E-05,1.606156E-05,1.592827E-05,1.579609E-05,1.566500E-05,1.553500E-05,1.540608E-05,1.527823E-05,1.515144E-05,1.502570E-05,1.490101E-05,1.477735E-05,1.465472E-05,1.453310E-05, 1.441250E-05,1.429289E-05,1.417428E-05,1.405665E-05,1.394000E-05,1.382431E-05,1.370959E-05,1.359582E-05,1.348299E-05,1.337110E-05,1.326014E-05,1.315010E-05,1.304097E-05,1.293274E-05,1.282542E-05,1.271898E-05,1.261343E-05,1.250876E-05,1.240495E-05,1.230201E-05, 1.219991E-05,1.209867E-05,1.199827E-05,1.189870E-05,1.179995E-05,1.170203E-05,1.160492E-05,1.150861E-05,1.141311E-05,1.131839E-05,1.122446E-05,1.113132E-05,1.103894E-05,1.094733E-05,1.085648E-05,1.076639E-05,1.067704E-05,1.058843E-05,1.050056E-05,1.041342E-05, 1.032701E-05,1.024130E-05,1.015631E-05,1.007203E-05,9.988446E-06,9.905554E-06,9.823351E-06,9.741830E-06,9.660985E-06,9.580812E-06,9.501303E-06,9.422455E-06,9.344261E-06,9.266715E-06,9.189814E-06,9.113550E-06,9.037919E-06,8.962916E-06,8.888536E-06,8.814772E-06, 8.741621E-06,8.669077E-06,8.597135E-06,8.525790E-06,8.455037E-06,8.384871E-06,8.315287E-06,8.246281E-06,8.177848E-06,8.109982E-06,8.042680E-06,7.975936E-06,7.909746E-06,7.844105E-06,7.779009E-06,7.714454E-06,7.650434E-06,7.586945E-06,7.523983E-06,7.461544E-06, 7.399622E-06,7.338215E-06,7.277317E-06,7.216925E-06,7.157034E-06,7.097640E-06,7.038739E-06,6.980326E-06,6.922399E-06,6.864952E-06,6.807981E-06,6.751484E-06,6.695455E-06,6.639892E-06,6.584789E-06,6.530144E-06,6.475952E-06,6.422210E-06,6.368914E-06,6.316060E-06, 6.263645E-06,6.211665E-06,6.160116E-06,6.108995E-06,6.058298E-06,6.008022E-06,5.958164E-06,5.908719E-06,5.859684E-06,5.811056E-06,5.762832E-06,5.715008E-06,5.667581E-06,5.620547E-06,5.573904E-06,5.527647E-06,5.481775E-06,5.436284E-06,5.391169E-06,5.346430E-06, 5.302061E-06,5.258061E-06,5.214426E-06,5.171153E-06,5.128239E-06,5.085681E-06,5.043477E-06,4.918953E-06,4.797503E-06,4.679053E-06,4.563526E-06,4.450853E-06,4.340961E-06,4.233782E-06,4.129250E-06,4.000000E-06,3.927860E-06,3.830880E-06,3.736300E-06,3.644050E-06, 3.554080E-06,3.466330E-06,3.380750E-06,3.300000E-06,3.217630E-06,3.137330E-06,3.059020E-06,2.983490E-06,2.909830E-06,2.837990E-06,2.767920E-06,2.720000E-06,2.659320E-06,2.600000E-06,2.550000E-06,2.485030E-06,2.421710E-06,2.382370E-06,2.360000E-06,2.300270E-06, 2.242050E-06,2.185310E-06,2.130000E-06,2.100000E-06,2.059610E-06,2.020000E-06,1.974490E-06,1.930000E-06,1.884460E-06,1.855390E-06,1.840000E-06,1.797000E-06,1.755000E-06,1.711970E-06,1.670000E-06,1.629510E-06,1.590000E-06,1.544340E-06,1.500000E-06,1.475000E-06, 1.440000E-06,1.404560E-06,1.370000E-06,1.337500E-06,1.300000E-06,1.267080E-06,1.235000E-06,1.202060E-06,1.170000E-06,1.150000E-06,1.123000E-06,1.110000E-06,1.097000E-06,1.080000E-06,1.071000E-06,1.045000E-06,1.035000E-06,1.020000E-06,9.960000E-07,9.860000E-07, 9.720000E-07,9.500000E-07,9.300000E-07,9.100000E-07,8.764250E-07,8.600000E-07,8.500000E-07,8.194500E-07,7.900000E-07,7.800000E-07,7.415500E-07,7.050000E-07,6.825600E-07,6.531500E-07,6.250000E-07,5.952800E-07,5.669600E-07,5.400000E-07,5.315800E-07,5.196200E-07, 5.000000E-07,4.850000E-07,4.670100E-07,4.496800E-07,4.330000E-07,4.139900E-07,4.000000E-07,3.910000E-07,3.699300E-07,3.500000E-07,3.346600E-07,3.200000E-07,3.145000E-07,3.000000E-07,2.800000E-07,2.635100E-07,2.480000E-07,2.335800E-07,2.200000E-07,2.091400E-07, 1.988100E-07,1.890000E-07,1.800000E-07,1.697100E-07,1.600000E-07,1.530300E-07,1.463700E-07,1.400000E-07,1.340000E-07,1.150000E-07,1.000000E-07,9.500000E-08,8.000000E-08,7.700000E-08,6.700000E-08,5.800000E-08,5.000000E-08,4.200000E-08,3.500000E-08,3.000000E-08, 2.500000E-08,2.000000E-08,1.500000E-08,1.000000E-08,6.900000E-09,5.000000E-09,3.000000E-09,1.000010E-11 ] #pstr = '' #for i in range(len(ECCO_bins)): # pstr += ECCO_bins[i] + ',' # if i!=0 and i%20==0: # pstr += '\n' #print(pstr) return ECCO_bins[:n] def retrieve_rxn_xs_from_lib(libfile, target, reaction=None, product=None)-
Description
Provided a DCHAIN neutron rxn cross section library file and sufficient information about a reaction, return that reaction's cross section.
Dependencies
Inputs
libfile= string of file path to data library file to be searchedtarget= string in general format of target nuclidereaction= (optional) either an int MT number (ENDF6 format) or a string of the ejectiles from the neutron reaction (case-insensitive), the "X" in (N,X) ifreaction = 'tot'or'total', the summed total transmutation xs (reactions which change the target's nuclide species) is provided and input for product is ignored; this behavior is also assumed when missing both reaction and product informationproduct= (optional) string in general format of product nuclide (if omitted, sum of all isomeric states is assumed; if provided product but not isomeric state, ground state is assumed)
Outputs
xs= a 2x1968 numpy array containing energy [eV] (i=0) and cross sections [b] (i=1) for all 1968 ECCO binsrxn_tex_str= a LaTeX-formatted string of the reaction
Expand source code
def retrieve_rxn_xs_from_lib(libfile,target,reaction=None,product=None): ''' Description: Provided a DCHAIN neutron rxn cross section library file and sufficient information about a reaction, return that reaction's cross section. Dependencies: `rxn_to_dchain_str` `ECCO1968_Ebins` Inputs: - `libfile` = string of file path to data library file to be searched - `target` = string in general format of target nuclide - `reaction` = (optional) either an int MT number (ENDF6 format) or a string of the ejectiles from the neutron reaction (case-insensitive), the "X" in (N,X) if `reaction = 'tot'` or `'total'`, the summed total transmutation xs (reactions which change the target's nuclide species) is provided and input for product is ignored; this behavior is also assumed when missing both reaction and product information - `product` = (optional) string in general format of product nuclide (if omitted, sum of all isomeric states is assumed; if provided product but not isomeric state, ground state is assumed) Outputs: - `xs` = a 2x1968 numpy array containing energy [eV] (i=0) and cross sections [b] (i=1) for all 1968 ECCO bins - `rxn_tex_str` = a LaTeX-formatted string of the reaction ''' datafolder, lib = os.path.split(libfile.replace('_n_act_xs_lib','')) n_occurances = 0 rxn_locations= [] rxn_listings = [] xs_data_raw = [] # determine if rxn or product is provided if (not reaction and not product) or (reaction=='tot' or reaction=='total'): # only target provided #print('Total transmutation cross section of {}'.format(target)) calc_total_xs = True else: calc_total_xs = False if calc_total_xs: # only concerned with target, not target or reaction # First, assemble reaction string rt = rxn_to_dchain_str(target,None,target)[:10] # only concerned with target + '(N,' rt_alt = None # alternate string to cover ground state when 'g' is present in product too catalog_rxn_text = rt[0] + rt[1:].lower() catalog_rxn_text_alt = None # make pretty Latex str of reaction too target_str = rt[0] + rt[1:7].lower() not_symbol = r'$\neg$' # '!' rxn_str = '(n,*)' tex_target = nuclide_plain_str_to_latex_str(target_str) if target_str[-2:] == ' ': tex_product = nuclide_plain_str_to_latex_str(target_str[:-2]+'g ') else: tex_product = tex_target rxn_tex_str = tex_target + rxn_str + not_symbol + tex_product else: # First, assemble reaction string rt = rxn_to_dchain_str(target,reaction,product) rt_alt = None # alternate string to cover ground state when 'g' is present in product too if product: if rt[-2] == ' ': rt_alt = rt[:-2] + 'G ' # Format string found in the catalog file catalog_rxn_text = rt[0] + rt[1:14].lower() if reaction.lower() != 'fis': catalog_rxn_text+= rt[14] + rt[15:].lower() catalog_rxn_text_alt = None if rt_alt: catalog_rxn_text_alt = rt_alt[0] + rt_alt[1:14].lower() + rt_alt[14] + rt_alt[15:].lower() # make pretty Latex str of reaction too target_str = rt[0] + rt[1:7].lower() if reaction.lower() == 'fis': product_str = '' else: product_str= rt[14] + rt[15:22].lower() rxn_str = rt[7:14].lower().replace(' ','') if 'a' in rxn_str: rxn_str = rxn_str.replace('a',r'$\alpha$') if 'g' in rxn_str: rxn_str = rxn_str.replace('g',r'$\gamma$') if 'he3' in rxn_str: rxn_str = rxn_str.replace('he3',r'$^3$He') tex_target = nuclide_plain_str_to_latex_str(target_str) if product_str: tex_product= nuclide_plain_str_to_latex_str(product_str) else: tex_product = '' rxn_tex_str = tex_target + rxn_str + tex_product if lib[0]=='h': # in hybrid_lib_dchain_names: hlib = True else: hlib = False catalog_file = libfile.replace('_n_act_xs_lib','_n_reaction_list.txt') library_file = libfile if os.path.isfile(catalog_file): # catalog file exists search_file = catalog_file search_text = catalog_rxn_text search_text_alt = catalog_rxn_text_alt using_catalog_file = True elif os.path.isfile(library_file): # library file exists search_file = library_file search_text = rt search_text_alt = rt_alt using_catalog_file = False else: print('\t{} library files not found.'.format(lib)) return None with open(search_file) as f: asterisk_counter = -1 for num, line in enumerate(f, 1): if '*' in line: asterisk_counter += 1 if search_text in line or (rt_alt and search_text_alt in line): n_occurances += 1 if using_catalog_file: rxn_locations.append(num-2) # index of reaction in reaction lib rxn_listings.append(line.replace('\n','')) else: # searching through actual library file rxn_locations.append(asterisk_counter) # index of reaction in reaction lib rxn_listings.append(line[20:41]) if n_occurances == 0: print('Reaction "{}" not found in library "{}".'.format(catalog_rxn_text,lib)) return None, 'null' if n_occurances > 1: if calc_total_xs: print(' Multiple reactions found. The sum of all will be used.') else: print(' Multiple product isomers for reaction found. The sum of all isomeric states will be used.') for j in range(n_occurances): print('\t{} (lib entry index {} of {})'.format(rxn_listings[j],rxn_locations[j],lib)) if hlib: print('Hybrid library {} uses data from {} for reaction {}.'.format(lib,rxn_listings[0][26:],catalog_rxn_text)) # State library availability #if hlib and n_occurances>0: # this is a hybrid library # src_lib = rxn_listings[libi][0][26:] # print('\t{} {} (from {})'.format(lib,n_occurances,src_lib)) # lib_colors[libi] = lib_colors[lib_names.index(src_lib)] #else: # normal library # print('\t{} {}'.format(lib,n_occurances[libi])) #if n_occurances[libi]>0 and libi in libis_to_compare: n_plotable_lines += 1 if not os.path.isfile(library_file): print('\t{} library file not found.'.format(lib)) return None, 'null' if n_occurances == 0: print('\t\tCross section not present in this library, skipping') return None, 'null' entry_index = -1 with open(library_file) as f: lines = f.readlines() for line in lines: if '*' in line: entry_index += 1 if entry_index in rxn_locations: # reached bookmarked entry index of interest for this lib found_entry = True enti = rxn_locations.index(entry_index) if '*' in line: if rxn_listings[enti][:22].upper() not in line: # double check that entry is correct print('Library index mismatch!') found_entry = False xs_vals = [] entry_li = -1 if found_entry: entry_li += 1 if entry_li == 0: # first line nEbins = int(line[12:18]) elif entry_li == 1 or entry_li == 2: # skip descriptive lines continue else: xs_vals += [float(xsi) for xsi in line.replace('\n','').split()] if len(xs_vals) == nEbins: if len(xs_data_raw)==0: # need to initialize entry xs_data_raw = np.zeros(1968) xs_data_raw[:nEbins] += np.array(xs_vals) # Now pretty up the results to be provided to the user xs = np.zeros((2,1968)) xs[0,:] = (1e6)*np.array(ECCO1968_Ebins(1968)[::-1]) # all energy bins in increasing order in eV # now flip order of lists to have them in energy increasing order for i in range(len(xs_data_raw)): xs[1,1967-i] = xs_data_raw[i] return xs, rxn_tex_str def calc_one_group_nrxn_xs_dchain(neutron_flux, neutron_flux_errors, libfile, target, reaction=None, product=None)-
Description
Combines a neutron flux and cross section into a flux-weighted single-group cross section.
Inputs
neutron_flux= 1D array of flux valuesneutron_flux_errors= 1D array of flux absolute uncertaintieslibfile= string of file path to data library file to be searchedtarget= string in general format of target nuclide-
reaction= (optional) either an int MT number (ENDF6 format) or a string of the ejectiles from the neutron reaction (case-insensitive), the "X" in (N,X)if
reaction = 'tot'or'total', the summed total transmutation xs (reactions which change the target's nuclide species) is provided and input for product is ignored; this behavior is also assumed when missing both reaction and product information -product= (optional) string in general format of product nuclide (if omitted, sum of all isomeric states is assumed; if provided product but not isomeric state, ground state is assumed)
Outputs
xs= a length-2 list of the single group cross section and its absolute uncertainty
Expand source code
def calc_one_group_nrxn_xs_dchain(neutron_flux,neutron_flux_errors,libfile,target,reaction=None,product=None): ''' Description: Combines a neutron flux and cross section into a flux-weighted single-group cross section. Inputs: - `neutron_flux` = 1D array of flux values - `neutron_flux_errors` = 1D array of flux absolute uncertainties - `libfile` = string of file path to data library file to be searched - `target` = string in general format of target nuclide - `reaction` = (optional) either an int MT number (ENDF6 format) or a string of the ejectiles from the neutron reaction (case-insensitive), the "X" in (N,X) if `reaction = 'tot'` or `'total'`, the summed total transmutation xs (reactions which change the target's nuclide species) is provided and input for product is ignored; this behavior is also assumed when missing both reaction and product information - `product` = (optional) string in general format of product nuclide (if omitted, sum of all isomeric states is assumed; if provided product but not isomeric state, ground state is assumed) Outputs: - `xs` = a length-2 list of the single group cross section and its absolute uncertainty ''' xs_out, rxn_str_out = retrieve_rxn_xs_from_lib(libfile,target,reaction,product) xs_vals = xs_out[1,:] flux_val = neutron_flux flux_err = neutron_flux_errors if len(xs_vals) != len(flux_val): print('Warning: mismatch in flux and cross section energy binning!') xs = np.sum(flux_val*xs_vals)/np.sum(flux_val) xs_fer_num = np.sqrt(np.sum((flux_err*xs_vals)**2))/np.sum(flux_val*xs_vals) xs_fer_denom = np.sqrt(np.sum(flux_err**2))/np.sum(flux_val) xs_fer = np.sqrt(xs_fer_num**2 + xs_fer_denom**2) xs_aer = xs*xs_fer return [xs, xs_aer] def parse_DCHAIN_act_file_legacy(act_file_path)-
Description
This code parses the .act file generated by DCHAIN (without uncertainty values)
Inputs
- path to a DCHAIN-generated .act file
Outputs
- length R list of region numbers
- length T list of measurement times (in sec) from start of irradiation
- time of end of irradiation (in sec)
- NumPy array of dimension RxTxNx11 of nuclide table data (N=max recorded table lenth)
- NumPy array of dimension RxTxNx5 of gamma spectrum table data
- NumPy array of dimension RxTxNx12 of top-10 list table data
- List containing 3 lists of column headers for the preceding three NumPy arrays
- list of the below lists/arrays of summary information
- NumPy array of dimension Rx7 of region-specific summary info
- list of length 7 containing descriptions of the above items
- NumPy array of dimension RxTx12 of region and time-specific summary info
- list of length 12 containing descriptions of the above items
Expand source code
def parse_DCHAIN_act_file_legacy(act_file_path): ''' Description: This code parses the .act file generated by DCHAIN (without uncertainty values) Inputs: - path to a DCHAIN-generated .act file Outputs: - length R list of region numbers - length T list of measurement times (in sec) from start of irradiation - time of end of irradiation (in sec) - NumPy array of dimension RxTxNx11 of nuclide table data (N=max recorded table lenth) - NumPy array of dimension RxTxNx5 of gamma spectrum table data - NumPy array of dimension RxTxNx12 of top-10 list table data - List containing 3 lists of column headers for the preceding three NumPy arrays - list of the below lists/arrays of summary information - NumPy array of dimension Rx7 of region-specific summary info - list of length 7 containing descriptions of the above items - NumPy array of dimension RxTx12 of region and time-specific summary info - list of length 12 containing descriptions of the above items ''' # Extract file info f = open(act_file_path) lines = f.readlines() f.close() # Parse file to determine number of regions nreg = 0 reg_nos = [] for line in lines: if 'region number' in line: nreg += 1 reg_nos.append(int(line[21:31])) # Parse file again to determine number of time steps current_reg_no = -1 #irradiation_time = -1.0 # seconds end_of_irradiation_time = -1.0 # seconds ntimes = 0 time_strs = [] time_list_sec = [] # time steps in seconds for line in lines: #if 'irradiation time' in line: irradiation_time = float(line[21:31])*time_str_to_sec_multiplier(line[33]) if 'region number' in line: current_reg_no = int(line[21:31]) if current_reg_no != reg_nos[0]: continue # only read times from first region if '--- output time ---' in line: ntimes += 1 time_strs.append(line) time_list_sec.append(float(line[40:53])) if ('--- output time ---' in line) and ('after the last shutdown' in line) and end_of_irradiation_time == -1: end_of_irradiation_time = float(line[21:31])*time_str_to_sec_multiplier(line[33]) - float(line[88:97])*time_str_to_sec_multiplier(line[99]) # Extract "summary info" from file ri = -1 # region index ti = -1 # time index r_summary_info = np.empty((nreg,7), dtype='object') # (regionwise) initialize Rx7 array r_summary_info_description = ['region number','irradiation time [s]','region volume [cc]','neutron flux [n/cm^2/s]','beam power [MW]','beam energy [GeV]','beam current [mA]'] # (regionwise) initialize Rx7 array ''' index meaning 0 region number 1 irradiation time [sec] 2 region volume [cc] 3 neutron flux [n/cm^2/s] 4 beam power [MW] 5 beam energy [GeV] 6 beam current [mA] ''' rt_summary_info = np.empty((nreg,ntimes,12), dtype='object') # (region-and-timewise) initialize RxTx12 array rt_summary_info_description = ['total gamma flux [#/s/cc]','total gamma energy flux [MeV/s/cc]','annihilation gamma flux [#/s/cc]','gamma current underflow [#/s]','gamma current overflow [#/s]','total activity [Bq/cc]','total decay heat [W/cc]','beta decay heat [W/cc]','gamma decay heat [W/cc]','alpha decay heat [W/cc]','activated atoms [#/cc]','total gamma dose rate [uSV/h*m^2]'] # (region-and-timewise) initialize RxTx12 array ''' index meaning 0 total gamma flux [#/s/cc] 1 total gamma energy flux [MeV/s/cc] 2 annihilation gamma flux [#/s/cc] 3 gamma current underflow [#/s] (gammas below lowest energy bin) 4 gamma current overflow [#/s] (gammas above highest energy bin) 5 total activity [Bq/cc] 6 total decay heat [W/cc] 7 beta decay heat [W/cc] 8 gamma decay heat [W/cc] 9 alpha decay heat [W/cc] 10 activated atoms [#/cc] 11 total gamma dose rate [uSV/h*m^2] ''' for li in range(len(lines)): line = lines[li] if 'region number' in line: ri = find(int(line[21:31]),reg_nos) # region-specific summary info r_summary_info[ri,0] = int(line[21:31]) r_summary_info[ri,1] = float(lines[li-1][21:31])*time_str_to_sec_multiplier(lines[li-1][33]) r_summary_info[ri,2] = float(lines[li-2][21:31]) r_summary_info[ri,3] = float(lines[li-3][21:31]) r_summary_info[ri,4] = float(lines[li-4][21:31]) r_summary_info[ri,5] = float(lines[li-5][21:31]) r_summary_info[ri,6] = float(lines[li-6][21:31]) if '--- output time ---' in line: ti = find(line,time_strs) # gamma info specific to region and time if 'total gamma-ray flux' in line: rt_summary_info[ri,ti,0] = float(line[39:49]) rt_summary_info[ri,ti,1] = float(lines[li+1][39:49]) rt_summary_info[ri,ti,2] = float(lines[li+2][39:49]) if 'group limitation' in lines[li+3]: rt_summary_info[ri,ti,3] = float(lines[li+3][91:101]) rt_summary_info[ri,ti,4] = float(lines[li+3][64:74]) else: rt_summary_info[ri,ti,3] = 0.0 rt_summary_info[ri,ti,4] = 0.0 # activation info specific to region and time if 'total activity' in line: rt_summary_info[ri,ti,5] = float(line[25:36]) rt_summary_info[ri,ti,6] = float(lines[li+1][25:36]) rt_summary_info[ri,ti,7] = float(lines[li+2][25:36]) rt_summary_info[ri,ti,8] = float(lines[li+3][25:36]) rt_summary_info[ri,ti,9] = float(lines[li+4][25:36]) rt_summary_info[ri,ti,10]= float(lines[li+5][25:36]) rt_summary_info[ri,ti,11]= float(lines[li+6][25:36]) summary_info = [r_summary_info, r_summary_info_description, rt_summary_info, rt_summary_info_description] # Extract major "blocks" (nuclides, gamma spec, top10 list) for each time step in each region act_block_text = np.empty((nreg,ntimes,3), dtype='object') # initialize RxTx3 array to hold character strings where final index 0=nuclides, 1=gamma-spec, and 2=top10-list ri = -1 # region index ti = -1 # time index qi = -1 # quantity index - 0=nuclides, 1=gamma-spec, and 2=top10-list max_array_len = [0,0,0] # maximum number of entries for a given quantity current_array_len = [0,0,0] # current number of entries for a given quantity for line in lines: if 'region number' in line: ri = find(int(line[21:31]),reg_nos) if '--- output time ---' in line: ti = find(line,time_strs) qi = 0 # reset quantity index if 'gamma-ray spectrum weighted by energy' in line: qi = 1 if 'dominant nuclides (top 10)' in line: qi = 2 if 'total' in line[:20] or line=='\n': # no longer reading info block if current_array_len[qi] > max_array_len[qi]: max_array_len[qi] = current_array_len[qi] current_array_len[qi] = 0 qi = -1 if qi < 0: continue # not in region of interest try: act_block_text[ri,ti,qi] += line except: act_block_text[ri,ti,qi] = line current_array_len[qi] += 1 header_len = [3,4,3] # number of lines present in table header nuclides_produced = np.empty((nreg,ntimes,max_array_len[0]-header_len[0],11), dtype='object') # initialize RxTxNx11 array to hold nuclide information gamma_spectra = np.empty((nreg,ntimes,max_array_len[1]-header_len[1], 5), dtype='object') # initialize RxTxNx5 array to hold gamma spec information top10_lists = np.empty((nreg,ntimes,max_array_len[2]-header_len[2],12), dtype='object') # initialize RxTxNx12 array to hold top 10 list information column_headers = [ [],[],[] ] # Now, populate each array # Nuclides produced column_headers[0] = ['nuclide','atoms [#/cc]','activity [Bq/cc]','activity [Bq]','rate [%]','beta decay heat [W/cc]','gamma decay heat [W/cc]','alpha decay heat [W/cc]','total decay heat [W/cc]','half life [s]','dose-rate [uSv/h*m^2]'] for ri in range(nreg): for ti in range(ntimes): table_text = act_block_text[ri,ti,0].split('\n') for ei in range(len(table_text)): if ei < header_len[0]: continue # in header lines ii = ei - header_len[0] # actual number index line = table_text[ei] if line=='' or line==None: continue # skip blank/nonexistent lines nuclides_produced[ri,ti,ii,0] = line[3:9] # nuclide nuclides_produced[ri,ti,ii,1] = float(line[13:23]) # atoms [#/cc] nuclides_produced[ri,ti,ii,2] = float(line[26:36]) # activity [Bq/cc] nuclides_produced[ri,ti,ii,3] = float(line[38:48]) # activity [Bq] nuclides_produced[ri,ti,ii,4] = float(line[49:56].replace(' ','0.0')) # rate [%] nuclides_produced[ri,ti,ii,5] = float(line[58:67]) # beta decay heat [W/cc] nuclides_produced[ri,ti,ii,6] = float(line[69:78]) # gamma decay heat [W/cc] nuclides_produced[ri,ti,ii,7] = float(line[80:89]) # alpha decay heat [W/cc] nuclides_produced[ri,ti,ii,8] = float(line[91:100]) # total decay heat [W/cc] nuclides_produced[ri,ti,ii,9] = float(line[104:113]) # half life [s] nuclides_produced[ri,ti,ii,10]= float(line[116:125]) # dose-rate [uSv/h*m^2] # Gamma-ray spectra column_headers[1] = ['group number','bin energy lower-bound [MeV]','bin energy upper-bound [MeV]','flux [#/s/cc]','energy flux [MeV/s/cc]'] for ri in range(nreg): for ti in range(ntimes): table_text = act_block_text[ri,ti,1].split('\n') for ei in range(len(table_text)): if ei < header_len[1]: continue # in header lines ii = ei - header_len[1] # actual number index line = table_text[ei] if line=='' or line==None: continue # skip blank/nonexistent lines gamma_spectra[ri,ti,ii,0] = int(line[1:4]) # group number gamma_spectra[ri,ti,ii,1] = float(line[17:25]) # bin energy lower-bound [MeV] gamma_spectra[ri,ti,ii,2] = float(line[7:15]) # bin energy upper-bound [MeV] gamma_spectra[ri,ti,ii,3] = float(line[28:38]) # flux [#/s/cc] gamma_spectra[ri,ti,ii,4] = float(line[41:51]) # energy flux [MeV/s/cc] # Top 10 lists column_headers[2] = ['rank','nuclide - Activity ranking','activity [Bq/cc]','activity [Bq]','rate [%]','nuclide - Decay heat ranking','decay heat [W/cc]','decay heat [W]','rate [%]','nuclide - Dose rate ranking','dose-rate [uSv/h*m^2]','rate [%]'] for ri in range(nreg): for ti in range(ntimes): table_text = act_block_text[ri,ti,2].split('\n') for ei in range(len(table_text)): if ei < header_len[2]: continue # in header lines ii = ei - header_len[2] # actual number index line = table_text[ei] if line=='' or line==None: continue # skip blank/nonexistent lines top10_lists[ri,ti,ii,0] = int(line[1:5]) # number/rank top10_lists[ri,ti,ii,1] = line[8:14] # nuclide - Activity ranking top10_lists[ri,ti,ii,2] = float(line[16:26]) # activity [Bq/cc] top10_lists[ri,ti,ii,3] = float(line[27:37]) # activity [Bq] top10_lists[ri,ti,ii,4] = float(line[38:43]) # rate [%] top10_lists[ri,ti,ii,5] = line[48:54] # nuclide - Decay heat ranking top10_lists[ri,ti,ii,6] = float(line[56:66]) # decay heat [W/cc] top10_lists[ri,ti,ii,7] = float(line[67:77]) # decay heat [W] top10_lists[ri,ti,ii,8] = float(line[78:83]) # rate [%] top10_lists[ri,ti,ii,9] = line[88:94] # nuclide - Dose rate ranking top10_lists[ri,ti,ii,10]= float(line[96:106]) # dose-rate [uSv/h*m^2] top10_lists[ri,ti,ii,11]= float(line[107:113]) # rate [%] return reg_nos, time_list_sec, end_of_irradiation_time, nuclides_produced, gamma_spectra, top10_lists, column_headers, summary_info def generate_nuclide_time_profiles_legacy(nuclides_info_array)-
Description
Reformats DCHAIN's tabular nuclide data into time profiles of each nuclide in each region (without uncertainty values)
Inputs
- the `nuclides_produced' array from function "parse_DCHAIN_act_file"
Outputs
- List of length R of lists containing names of nuclides produced in each region
- List of length R of lists containing LaTeX-formatted names of nuclides produced in each region
- List of length R of lists containing ZZZAAAM values (10000Z+10A+M) of nuclides produced in each region
- List of length R of lists containing half lives of nuclides produced in each region (in seconds)
- List of length R of NumPy arrays of dimension NxTx7 of nuclide info
- List of length 7 containing text descriptions of the 7 columns of the info arrays
Expand source code
def generate_nuclide_time_profiles_legacy(nuclides_info_array): ''' Description: Reformats DCHAIN's tabular nuclide data into time profiles of each nuclide in each region (without uncertainty values) Inputs: - the `nuclides_produced' array from function "parse_DCHAIN_act_file" Outputs: - List of length R of lists containing names of nuclides produced in each region - List of length R of lists containing LaTeX-formatted names of nuclides produced in each region - List of length R of lists containing ZZZAAAM values (10000Z+10A+M) of nuclides produced in each region - List of length R of lists containing half lives of nuclides produced in each region (in seconds) - List of length R of NumPy arrays of dimension NxTx7 of nuclide info - List of length 7 containing text descriptions of the 7 columns of the info arrays ''' nuclide_names = [] nuclide_ZAM_vals = [] nuclide_Latex_names = [] nuclide_half_lives = [] nuclide_info = [] nuclide_info_headers = ['Atoms [#/cc]','Activity [Bq/cc]','Beta decay heat [W/cc]','Gamma decay heat [W/cc]','Alpha decay heat [W/cc]','Total decay heat [W/cc]','Dose-rate [uSv/h*m^2]'] nreg = np.shape(nuclides_info_array)[0] ntime= np.shape(nuclides_info_array)[1] nnuc = np.shape(nuclides_info_array)[2] # Get nuclide name info first, ordering them by increasing Z and A for ri in range(nreg): reg_nuclides = [] reg_t_halves = [] reg_ZAM_vals = [] reg_tex_nuclides = [] for ti in range(ntime): for ni in range(nnuc): Dname = nuclides_info_array[ri,ti,ni,0] if Dname == None: continue ZAM = Dname_to_ZAM(Dname) if ZAM not in reg_ZAM_vals: bisect.insort_left(reg_ZAM_vals, ZAM) zami = reg_ZAM_vals.index(ZAM) #zami = find(ZAM,reg_ZAM_vals) reg_nuclides.insert(zami,Dname) reg_t_halves.insert(zami,nuclides_info_array[ri,ti,ni,9]) reg_tex_nuclides.insert(zami,Dname_to_Latex(Dname)) nuclide_names.append(reg_nuclides) nuclide_ZAM_vals.append(reg_ZAM_vals) nuclide_half_lives.append(reg_t_halves) nuclide_Latex_names.append(reg_tex_nuclides) # Now get arrays of nuclide info for ri in range(nreg): reg_nnuc = len(nuclide_names[ri]) reg_nuclide_info = np.zeros((ntime,reg_nnuc,7)) for ti in range(ntime): for ni in range(reg_nnuc): if nuclide_names[ri][ni] not in nuclides_info_array[ri,ti,:,0]: continue sni = find(nuclide_names[ri][ni],nuclides_info_array[ri,ti,:,0]) reg_nuclide_info[ti,ni,0] = nuclides_info_array[ri,ti,sni,1] # atoms [#/cc] reg_nuclide_info[ti,ni,1] = nuclides_info_array[ri,ti,sni,2] # activity [Bq/cc] reg_nuclide_info[ti,ni,2] = nuclides_info_array[ri,ti,sni,5] # beta decay heat [W/cc] reg_nuclide_info[ti,ni,3] = nuclides_info_array[ri,ti,sni,6] # gamma decay heat [W/cc] reg_nuclide_info[ti,ni,4] = nuclides_info_array[ri,ti,sni,7] # alpha decay heat [W/cc] reg_nuclide_info[ti,ni,5] = nuclides_info_array[ri,ti,sni,8] # total decay heat [W/cc] reg_nuclide_info[ti,ni,6] = nuclides_info_array[ri,ti,sni,10] # dose-rate [uSv/h*m^2] nuclide_info.append(reg_nuclide_info) return nuclide_names, nuclide_Latex_names, nuclide_ZAM_vals, nuclide_half_lives, nuclide_info, nuclide_info_headers def plot_top10_nuclides(dchain_output, rank_val='activity', xaxis_val='time', xaxis_type='indices', regions=None, region_indices=None, times=None, time_indices=None, rank_cutoff=10, xscale='linear')-
Description
Generate a nice plot illustrating dominant nuclides as a function of time or region
Dependencies
import numpy as npimport matplotlib.pyplot as pltprocess_dchain_simulation_output()
Inputs
(required)
dchain_output= dictionary output from the process_dchain_simulation_output for a simulation
Inputs
(optional, keyword)
rank_val= which top 10 list is selected. (D='activity', options include'activity','decay_heat', and'gamma_dose')xaxis_val= value to be plotted on x-axis; can be either"time"(default) or"region"xaxis_type= space xaxis entries either equally by"indices"(default) or realistically by"values"regions= list of region numbers (or individual value) to generate plots for (D=None, plotting all regions)region_indices= same as above but uses indices rather than region numbers; this has higher priority if specified (D=None, plot all regions)times= list of times (from start in seconds) (or individual value) to generate plots for (D=None, plotting all times)time_indices= same as above but uses indices rather than time values; this has higher priority if specified (D=None, plot all times)rank_cutoff= highest rank (or number of ranks) to be displayed (D=10, cannot be any greater than 10)xscale= string specifying scale of x-axis, either'linear'(default) or'log'
Outputs
fig_list= list of figures which can be plotted.
Expand source code
def plot_top10_nuclides(dchain_output,rank_val='activity',xaxis_val='time',xaxis_type='indices',regions=None,region_indices=None,times=None,time_indices=None,rank_cutoff=10,xscale='linear'): ''' Description: Generate a nice plot illustrating dominant nuclides as a function of time or region Dependencies: - `import numpy as np` - `import matplotlib.pyplot as plt` - `process_dchain_simulation_output` Inputs: (required) - `dchain_output` = dictionary output from the process_dchain_simulation_output for a simulation Inputs: (optional, keyword) - `rank_val` = which top 10 list is selected. (D=`'activity'`, options include `'activity'`, `'decay_heat'`, and `'gamma_dose'`) - `xaxis_val` = value to be plotted on x-axis; can be either `"time"` (default) or `"region"` - `xaxis_type` = space xaxis entries either equally by `"indices"` (default) or realistically by `"values"` - `regions` = list of region numbers (or individual value) to generate plots for (D=`None`, plotting all regions) - `region_indices` = same as above but uses indices rather than region numbers; this has higher priority if specified (D=`None`, plot all regions) - `times` = list of times (from start in seconds) (or individual value) to generate plots for (D=`None`, plotting all times) - `time_indices` = same as above but uses indices rather than time values; this has higher priority if specified (D=`None`, plot all times) - `rank_cutoff` = highest rank (or number of ranks) to be displayed (D=`10`, cannot be any greater than 10) - `xscale` = string specifying scale of x-axis, either `'linear'` (default) or `'log'` Outputs: - `fig_list` = list of figures which can be plotted. ''' max_nregs = len(dchain_output['region']['numbers']) all_regs = dchain_output['region']['numbers'] max_ntimes = len(dchain_output['time']['from_start_sec']) all_times = dchain_output['time']['from_start_sec'] if not regions and not region_indices: regions = dchain_output['region']['numbers'] region_indices = range(len(regions)) elif region_indices: if isinstance(region_indices, list): regions = [] for i in region_indices: if i >= max_nregs: print('region index {} greater than number of regions {}, skipping...'.format(i,max_nregs)) region_indices.remove(i) continue regions.append(dchain_output['region']['numbers'][i]) else: if region_indices < max_nregs: regions = [dchain_output['region']['numbers'][region_indices]] region_indices = [region_indices] else: print('Single provided region index {} is out of bounds of total number of regions {}, aborting...'.format(region_indices,max_nregs)) return None elif regions: if isinstance(regions, list): region_indices = [] for i in regions: if i not in all_regs: print('region {} is not contained in list of region numbers, skipping...'.format(i)) regions.remove(i) continue region_indices.append(dchain_output['region']['numbers'].index(i)) else: if regions in all_regs: region_indices = [dchain_output['region']['numbers'].index(regions)] regions = [regions] else: print('Single provided region {} is not in the simulated region numbers, aborting...'.format(region_indices)) return None if not times and not time_indices: times = dchain_output['time']['from_start_sec'] time_indices = range(len(times)) elif time_indices: if isinstance(time_indices, list): times = [] for i in time_indices: if i >= max_ntimes: print('time index {} greater than number of times {}, skipping...'.format(i,max_ntimes)) time_indices.remove(i) continue times.append(dchain_output['time']['from_start_sec'][i]) else: if time_indices < max_ntimes: times = [dchain_output['time']['from_start_sec'][time_indices]] time_indices = [time_indices] else: print('Single provided time index {} is out of bounds of total number of times {}, aborting...'.format(time_indices,max_ntimes)) return None elif times: if isinstance(times, list): time_indices = [] for i in times: if i not in all_times: print('time {} is not contained in list of times, skipping...'.format(i)) times.remove(i) continue time_indices.append(dchain_output['time']['from_start_sec'].index(i)) else: if times in all_times: time_indices = [dchain_output['time']['from_start_sec'].index(times)] times = [times] else: print('Single provided time {} is not in the outputted times, aborting...'.format(time_indices)) return None if rank_val=='photon_dose': rank_val = 'gamma_dose' if rank_val not in ['activity','decay_heat','gamma_dose']: print("rank_val must be either 'activity', 'decay_heat', or 'gamma_dose', aborting...") return None if xaxis_val not in ['time','region']: print("xaxis_val must be either 'time' or 'region', aborting...") return None if xaxis_type=='index': xaxis_type = 'indices' if xaxis_type=='value': xaxis_type = 'values' if xaxis_type not in ['indices','values']: print("xaxis_val must be either 'indices' or 'values', aborting...") return None fig_list = [] ax_list = [] figi = 0 if xaxis_val=='time': major_indices = region_indices minor_indices = time_indices major_values = regions minor_values = times xstr = 'Time' else: major_indices = time_indices minor_indices = region_indices major_values = times minor_values = regions xstr = 'Region' if xaxis_type=='indices': xdata = minor_indices xstr += ' (index)' else: xdata = minor_values for majori in major_indices: figi += 1 # Assemble list of all ranked nuclides nuclides = [] for minori in minor_indices: if xaxis_val=='time': ri = majori ti = minori else: ri = minori ti = majori for tti in range(len(dchain_output['top10'][rank_val]['nuclide'][ri][ti,:])): if (dchain_output['top10'][rank_val]['nuclide'][ri][ti,tti]!=None) and (dchain_output['top10'][rank_val]['nuclide'][ri][ti,tti] not in nuclides) and (dchain_output['top10'][rank_val]['rank'][ri][ti,tti]<=rank_cutoff): nuclides.append(dchain_output['top10'][rank_val]['nuclide'][ri][ti,tti]) # Now assemble plot for each nuclide plot_dicts = [] for nuclide in nuclides: ni = nuclides.index(nuclide) ydata = [] for minori in minor_indices: if xaxis_val=='time': ri = majori ti = minori else: ri = minori ti = majori if nuclide in dchain_output['top10'][rank_val]['nuclide'][ri][ti,:]: tti = dchain_output['top10'][rank_val]['nuclide'][ri][ti,:].tolist().index(nuclide) #tti = np.where(dchain_output['top10'][rank_val]['nuclide'][ri][ti,:]==nuclide) if dchain_output['top10'][rank_val]['rank'][ri][ti,tti]<=rank_cutoff: ydata.append( 1 + rank_cutoff - dchain_output['top10'][rank_val]['rank'][ri][ti,tti] ) else: ydata.append(np.nan) else: ydata.append(np.nan) tex_name = nuclide_plain_str_to_latex_str(nuclide) # dict = {'xdata':xdata,'ydata':ydata,'marker':tex_name,'markersize':30,'color':colors_list_12(ni%12)} dict = {'xdata':xdata,'ydata':ydata,'marker':tex_name,'markersize':30} plot_dicts.append(dict) # Now generate plot if xaxis_val=='time': title_str = 'Top {} nuclides by {} in region {}'.format(rank_cutoff,rank_val.replace('_',' '),major_values[major_indices.index(majori)]) else: title_str = 'Top {} nuclides by {} at t = {} seconds'.format(rank_cutoff,rank_val.replace('_',' '),major_values[major_indices.index(majori)]) ystr = 'Rank' if Hunters_tools_is_available: fig1, ax1 = fancy_plot( xdata_lists=None, ydata_lists=None, dictionaries=plot_dicts, figi=figi, title_str=title_str, x_label_str=xstr, y_label_str=ystr, x_scale=xscale, y_scale='linear', fig_height_inch=6.5*(rank_cutoff/10)+0.1*(10-rank_cutoff) ) else: # For public version, just make this a basic plot rather than using my complicated personal plotting function fig1 = plt.figure() ax1 = plt.subplot(111) for entry in plot_dicts: ax1.plot(entry['xdata'],entry['ydata'],marker=entry['marker'],markersize=entry['markersize'],ls='') plt.xlabel(xstr,fontsize=14) plt.ylabel(ystr,fontsize=14) plt.xscale(xscale) fig1.tight_layout() fig1.set_size_inches(0.2+6.3*(len(plot_dicts[0]['xdata'])/12),6.5*(rank_cutoff/10)+0.1*(10-rank_cutoff)) ax1.set_yticks(range(1,rank_cutoff+1)) ax1.set_yticklabels([str(i) for i in range(rank_cutoff,0,-1)]) if xaxis_type=='indices': ax1.set_xticks(minor_indices) ax1.set_xticklabels([str(i) for i in minor_indices]) plt.grid(visible=True, which='major', linestyle='-', alpha=0)#0.25) plt.grid(visible=True, which='minor', linestyle='-', alpha=0)#0.10) fig_list.append(fig1) ax_list.append(ax1) return fig_list #, ax_list def find(target, myList)-
Description
Search for and return the index of the first occurance of a value in a list.
Inputs
target= value to be searched formyList= list of values
Outputs
- index of first instance of
targetinmyList
Expand source code
def find(target, myList): ''' Description: Search for and return the index of the first occurance of a value in a list. Inputs: - `target` = value to be searched for - `myList` = list of values Outputs: - index of first instance of `target` in `myList` ''' for i in range(len(myList)): if myList[i] == target: return i def Element_Z_to_Sym(Z)-
Description
Returns elemental symbol for a provided atomic number Z
Inputs
Z= atomic number
Outputs
sym= string of elemental symbol for element of atomic number Z
Expand source code
def Element_Z_to_Sym(Z): ''' Description: Returns elemental symbol for a provided atomic number Z Inputs: - `Z` = atomic number Outputs: - `sym` = string of elemental symbol for element of atomic number Z ''' elms = ["n ",\ "H ","He","Li","Be","B ","C ","N ","O ","F ","Ne",\ "Na","Mg","Al","Si","P ","S ","Cl","Ar","K ","Ca",\ "Sc","Ti","V ","Cr","Mn","Fe","Co","Ni","Cu","Zn",\ "Ga","Ge","As","Se","Br","Kr","Rb","Sr","Y ","Zr",\ "Nb","Mo","Tc","Ru","Rh","Pd","Ag","Cd","In","Sn",\ "Sb","Te","I ","Xe","Cs","Ba","La","Ce","Pr","Nd",\ "Pm","Sm","Eu","Gd","Tb","Dy","Ho","Er","Tm","Yb",\ "Lu","Hf","Ta","W ","Re","Os","Ir","Pt","Au","Hg",\ "Tl","Pb","Bi","Po","At","Rn","Fr","Ra","Ac","Th",\ "Pa","U ","Np","Pu","Am","Cm","Bk","Cf","Es","Fm",\ "Md","No","Lr","Rf","Db","Sg","Bh","Hs","Mt","Ds",\ "Rg","Cn","Nh","Fl","Mc","Lv","Ts","Og"] i = int(Z) if i < 0 or i > len(elms): print('Z={} is not valid, please select a number from 0 to 118 (inclusive).'.format(str(Z))) return None return elms[i].strip() def Element_Sym_to_Z(sym)-
Description
Returns atomic number Z for a provided elemental symbol
Dependencies
Inputs
sym= string of elemental symbol for element of atomic number Z
Outputs
Z= atomic number
Expand source code
def Element_Sym_to_Z(sym): ''' Description: Returns atomic number Z for a provided elemental symbol Dependencies: `find` Inputs: - `sym` = string of elemental symbol for element of atomic number Z Outputs: - `Z` = atomic number ''' elms = ["n ",\ "H ","He","Li","Be","B ","C ","N ","O ","F ","Ne",\ "Na","Mg","Al","Si","P ","S ","Cl","Ar","K ","Ca",\ "Sc","Ti","V ","Cr","Mn","Fe","Co","Ni","Cu","Zn",\ "Ga","Ge","As","Se","Br","Kr","Rb","Sr","Y ","Zr",\ "Nb","Mo","Tc","Ru","Rh","Pd","Ag","Cd","In","Sn",\ "Sb","Te","I ","Xe","Cs","Ba","La","Ce","Pr","Nd",\ "Pm","Sm","Eu","Gd","Tb","Dy","Ho","Er","Tm","Yb",\ "Lu","Hf","Ta","W ","Re","Os","Ir","Pt","Au","Hg",\ "Tl","Pb","Bi","Po","At","Rn","Fr","Ra","Ac","Th",\ "Pa","U ","Np","Pu","Am","Cm","Bk","Cf","Es","Fm",\ "Md","No","Lr","Rf","Db","Sg","Bh","Hs","Mt","Ds",\ "Rg","Cn","Nh","Fl","Mc","Lv","Ts","Og"] if len(sym.strip())>2: print('Please provide a valid elemental symbol (1 or 2 characters), {} is too long'.format(sym)) return -1 # handle exception for neutron first if sym.strip()=='XX': return 0 # make sure string is formatted to match entries in elms list sym2 = sym.strip() if len(sym2)==1: sym2 += ' ' sym2 = sym2[0].upper() + sym2[1].lower() Z = find(sym2,elms) if Z==None: print('Z could not be found for element "{}"; please make sure entry is correct.'.format(sym)) return -1 return Z def Element_ZorSym_to_name(Z)-
Description
Returns an element's name provided its atomic number Z or elemental symbol
Inputs
Z= string of elemental symbol or atomic number Z
Outputs
name= element name
Expand source code
def Element_ZorSym_to_name(Z): ''' Description: Returns an element's name provided its atomic number Z or elemental symbol Inputs: - `Z` = string of elemental symbol or atomic number Z Outputs: - `name` = element name ''' element_names = ['neutron','Hydrogen','Helium','Lithium','Beryllium','Boron','Carbon','Nitrogen','Oxygen','Fluorine', 'Neon','Sodium','Magnesium','Aluminium','Silicon','Phosphorus','Sulfur','Chlorine','Argon', 'Potassium','Calcium','Scandium','Titanium','Vanadium','Chromium','Manganese','Iron','Cobalt', 'Nickel','Copper','Zinc','Gallium','Germanium','Arsenic','Selenium','Bromine','Krypton', 'Rubidium','Strontium','Yttrium','Zirconium','Niobium','Molybdenum','Technetium','Ruthenium', 'Rhodium','Palladium','Silver','Cadmium','Indium','Tin','Antimony','Tellurium','Iodine','Xenon', 'Caesium','Barium','Lanthanum','Cerium','Praseodymium','Neodymium','Promethium','Samarium', 'Europium','Gadolinium','Terbium','Dysprosium','Holmium','Erbium','Thulium','Ytterbium', 'Lutetium','Hafnium','Tantalum','Tungsten','Rhenium','Osmium','Iridium','Platinum','Gold', 'Mercury','Thallium','Lead','Bismuth','Polonium','Astatine','Radon','Francium','Radium', 'Actinium','Thorium','Protactinium','Uranium','Neptunium','Plutonium','Americium','Curium', 'Berkelium','Californium','Einsteinium','Fermium','Mendelevium','Nobelium','Lawrencium', 'Rutherfordium','Dubnium','Seaborgium','Bohrium','Hassium','Meitnerium','Darmstadtium', 'Roentgenium','Copernicium','Nihonium','Flerovium','Moscovium','Livermorium','Tennessine','Oganesson'] try: zi = int(Z) except: zi = Element_Sym_to_Z(Z) return element_names[zi] def Element_ZorSym_to_mass(Z)-
Description
Returns an element's average atomic mass provided its atomic number Z or elemental symbol
Inputs
Z= string of elemental symbol or atomic number Z
Outputs
A_avg= average atomic mass
Expand source code
def Element_ZorSym_to_mass(Z): ''' Description: Returns an element's average atomic mass provided its atomic number Z or elemental symbol Inputs: - `Z` = string of elemental symbol or atomic number Z Outputs: - `A_avg` = average atomic mass ''' average_atomic_masses = [1.008664,1.007,4.002602,6.941,9.012182,10.811,12.0107,14.0067,15.9994,18.9984032, 20.1797,22.98976928,24.305,26.9815386,28.0855,30.973762,32.065,35.453,39.948,39.0983, 40.078,44.955912,47.867,50.9415,51.9961,54.938045,55.845,58.933195,58.6934,63.546,65.38, 69.723,72.63,74.9216,78.96,79.904,83.798,85.4678,87.62,88.90585,91.224,92.90638,95.96,98, 101.07,102.9055,106.42,107.8682,112.411,114.818,118.71,121.76,127.6,126.90447,131.293, 132.9054519,137.327,138.90547,140.116,140.90765,144.242,145,150.36,151.964,157.25, 158.92535,162.5,164.93032,167.259,168.93421,173.054,174.9668,178.49,180.94788,183.84, 186.207,190.23,192.217,195.084,196.966569,200.59,204.3833,207.2,208.9804,209,210,222, 223,226,227,232.03806,231.03588,238.02891,237,244,243,247,247,251,252,257,258,259, 266,267,268,269,270,277,278,281,282,285,286,289,290,293,294,294] try: zi = int(Z) except: zi = Element_Sym_to_Z(Z) return average_atomic_masses[zi] def nuclide_to_Latex_form(Z, A, m='')-
Description
Form a LaTeX-formatted string of a nuclide provided its information
Dependencies
Element_Z_to_Sym()(only required if inputed Z is not already an elemental symbol)Inputs
Z= atomic number of nuclide (int, float, or string) or elemental symbol (string)A= atomic mass of nuclide (int, float, or string) or string to go in place of A (ex. 'nat')m= metastable state (D='', ground state); this will be appended to the end of A if not a string already, it will be converted into one and appended to 'm' (ex. 1 -> 'm1')
Outputs
- LaTeX-formatted raw string of a nuclide, excellent for plot titles, labels, and auto-generated LaTeX documents
Expand source code
def nuclide_to_Latex_form(Z,A,m=''): ''' Description: Form a LaTeX-formatted string of a nuclide provided its information Dependencies: `Element_Z_to_Sym` (only required if inputed Z is not already an elemental symbol) Inputs: - `Z` = atomic number of nuclide (int, float, or string) or elemental symbol (string) - `A` = atomic mass of nuclide (int, float, or string) or string to go in place of A (ex. 'nat') - `m` = metastable state (D='', ground state); this will be appended to the end of A if not a string already, it will be converted into one and appended to 'm' (ex. 1 -> 'm1') Outputs: - LaTeX-formatted raw string of a nuclide, excellent for plot titles, labels, and auto-generated LaTeX documents ''' if isinstance(A,(int,float)): A = str(int(A)) if not isinstance(Z,str): symbol = Element_Z_to_Sym(int(Z)) if isinstance(m,float): m = int(m) if isinstance(m,int): m = 'm' + str(m) latex_str = r"$^{{{}{}}}$".format(A,m) + "{}".format(symbol) return latex_str def nuclide_plain_str_to_latex_str(nuc_str, include_Z=False)-
Description
Converts a plaintext string of a nuclide to a LaTeX-formatted raw string Note: if you already have the Z, A, and isomeric state information determined, the "nuclide_to_Latex_form" function can be used instead
Dependencies
Element_Z_to_Sym()(only required ifinclude_Z = True)
Inputs
(required)
nuc_str= string to be converted; a huge variety of formats are supported, but they all must follow the following rules:- Isomeric/metastable state characters must always immediately follow the atomic mass characters.
Isomeric state labels MUST either:
- (1) be a single lower-case character OR
- (2) begin with any non-numeric character and end with a number
- Atomic mass numbers must be nonnegative integers OR the string
"nat"(in which case no metastable states can be written) - Elemental symbols MUST begin with an upper-case character
- Isomeric/metastable state characters must always immediately follow the atomic mass characters.
Isomeric state labels MUST either:
Inputs
(optional)
include_Z=True/Falsedetermining whether the nuclide's atomic number Z will be printed as a subscript beneath the atomic mass
Outputs
- LaTeX-formatted raw string of nuclide
Expand source code
def nuclide_plain_str_to_latex_str(nuc_str,include_Z=False): ''' Description: Converts a plaintext string of a nuclide to a LaTeX-formatted raw string Note: if you already have the Z, A, and isomeric state information determined, the "nuclide_to_Latex_form" function can be used instead Dependencies: - `Element_Z_to_Sym` (only required if `include_Z = True`) Inputs: (required) - `nuc_str` = string to be converted; a huge variety of formats are supported, but they all must follow the following rules: + Isomeric/metastable state characters must always immediately follow the atomic mass characters. Isomeric state labels MUST either: - (1) be a single lower-case character OR - (2) begin with any non-numeric character and end with a number + Atomic mass numbers must be nonnegative integers OR the string `"nat"` (in which case no metastable states can be written) + Elemental symbols MUST begin with an upper-case character Inputs: (optional) - `include_Z` = `True`/`False` determining whether the nuclide's atomic number Z will be printed as a subscript beneath the atomic mass Outputs: - LaTeX-formatted raw string of nuclide ''' tex_str = r'' # remove unwanted characters from provided string delete_characters_list = [' ', '-', '_'] for dc in delete_characters_list: nuc_str = nuc_str.replace(dc,'') # determine which characters are letters versus numbers isalpha_list = [] isdigit_list = [] for c in nuc_str: isalpha_list.append(c.isalpha()) isdigit_list.append(c.isdigit()) symbol = '' mass = '' isost = '' # string MUST begin with either mass number or elemental symbol if isdigit_list[0] or nuc_str[0:3]=='nat': # mass first mass_first = True else: mass_first = False if mass_first: if nuc_str[0:3]=='nat': mass = 'nat' ci = 3 else: ci = 0 while isdigit_list[ci]: mass += nuc_str[ci] ci += 1 mass = str(int(mass)) # eliminate any extra leading zeros # encountered a non-numeric character, end of mass # now, determine if metastable state is listed or if element is listed next # first, check to see if any other numerals are in string lni = 0 # last numeral index for i in range(ci,len(nuc_str)): if isdigit_list[i]: lni = i if lni != 0: # grab all characters between ci and last numeral as metastable state isost = nuc_str[ci:lni+1] ci = lni + 1 else: # no more numerals in string, now check for single lower-case letter if isalpha_list[ci] and nuc_str[ci].islower(): isost = nuc_str[ci] ci += 1 # Now extract elemental symbol for i in range(ci,len(nuc_str)): if isalpha_list[i]: symbol += nuc_str[i] else: # if elemental symbol is listed first if 'nat' in nuc_str: mass = 'nat' nuc_str = nuc_str.replace('nat','') ci = 0 # Extract all characters before first number as the elemental symbol while nuc_str[ci].isalpha(): symbol += nuc_str[ci] ci += 1 # now, extract mass if mass != 'nat': while nuc_str[ci].isdigit(): mass += nuc_str[ci] ci += 1 if ci == len(nuc_str): break # lastly, extract isomeric state, if present if ci != len(nuc_str): isost = nuc_str[ci:] # treating the cases of lowercase-specified particles (n, d, t, etc.) if symbol == '' and isost != '': symbol = isost isost = '' # Now assemble LaTeX string for nuclides if include_Z: if symbol == 'n': Z = 0 elif symbol == 'p' or symbol == 'd' or symbol == 't': Z = 1 else: Z = Element_Sym_to_Z(symbol) Z = str(int(Z)) tex_str = r"$^{{{}{}}}_{{{}}}$".format(mass,isost,Z) + "{}".format(symbol) else: tex_str = r"$^{{{}{}}}$".format(mass,isost) + "{}".format(symbol) return tex_str def nuclide_plain_str_ZZZAAAM(nuc_str)-
Description
Converts a plaintext string of a nuclide to an integer ZZZAAAM = 10000*Z + 10*A + M
Dependencies
Inputs
nuc_str= string to be converted; a huge variety of formats are supported, but they all must follow the following rules:- Isomeric/metastable state characters must always immediately follow the atomic mass characters.
Isomeric state labels MUST either:
- (1) be a single lower-case character OR
- (2) begin with any non-numeric character and end with a number
- Atomic mass numbers must be nonnegative integers OR the string "nat" (in which case no metastable states can be written)
- Elemental symbols MUST begin with an upper-case character
- Isomeric/metastable state characters must always immediately follow the atomic mass characters.
Isomeric state labels MUST either:
Outputs
- ZZZAAAM integer
Expand source code
def nuclide_plain_str_ZZZAAAM(nuc_str): ''' Description: Converts a plaintext string of a nuclide to an integer ZZZAAAM = 10000\*Z + 10\*A + M Dependencies: `Element_Z_to_Sym` Inputs: - `nuc_str` = string to be converted; a huge variety of formats are supported, but they all must follow the following rules: + Isomeric/metastable state characters must always immediately follow the atomic mass characters. Isomeric state labels MUST either: - (1) be a single lower-case character OR - (2) begin with any non-numeric character and end with a number + Atomic mass numbers must be nonnegative integers OR the string "nat" (in which case no metastable states can be written) + Elemental symbols MUST begin with an upper-case character Outputs: - ZZZAAAM integer ''' # remove unwanted characters from provided string delete_characters_list = [' ', '-', '_'] for dc in delete_characters_list: nuc_str = nuc_str.replace(dc,'') # determine which characters are letters versus numbers isalpha_list = [] isdigit_list = [] for c in nuc_str: isalpha_list.append(c.isalpha()) isdigit_list.append(c.isdigit()) symbol = '' mass = '' isost = '' if 'nat' in nuc_str: print('Must specify a specific nuclide, not natural abundances') return None # string MUST begin with either mass number or elemental symbol if isdigit_list[0]: # mass first mass_first = True else: mass_first = False if mass_first: ci = 0 while isdigit_list[ci]: mass += nuc_str[ci] ci += 1 mass = str(int(mass)) # eliminate any extra leading zeros # encountered a non-numeric character, end of mass # now, determine if metastable state is listed or if element is listed next # first, check to see if any other numerals are in string lni = 0 # last numeral index for i in range(ci,len(nuc_str)): if isdigit_list[i]: lni = i if lni != 0: # grab all characters between ci and last numeral as metastable state isost = nuc_str[ci:lni+1] ci = lni + 1 else: # no more numerals in string, now check for single lower-case letter if isalpha_list[ci] and nuc_str[ci].islower(): isost = nuc_str[ci] ci += 1 # Now extract elemental symbol for i in range(ci,len(nuc_str)): if isalpha_list[i]: symbol += nuc_str[i] else: # if elemental symbol is listed first ci = 0 # Extract all characters before first number as the elemental symbol while nuc_str[ci].isalpha(): symbol += nuc_str[ci] ci += 1 # now, extract mass while nuc_str[ci].isdigit(): mass += nuc_str[ci] ci += 1 if ci == len(nuc_str): break # lastly, extract isomeric state, if present if ci != len(nuc_str): isost = nuc_str[ci:] # treating the cases of lowercase-specified particles (n, d, t, etc.) if symbol == '' and isost != '': symbol = isost isost = '' if symbol == 'n': Z = 0 elif symbol == 'p' or symbol == 'd' or symbol == 't': Z = 1 else: Z = Element_Sym_to_Z(symbol) A = int(mass) if isost.strip()=='' or isost=='g': M = 0 elif isost=='m' or isost=='m1': M = 1 elif isost=='n' or isost=='m2': M = 2 elif isost=='o' or isost=='m3': M = 3 elif isost=='p' or isost=='m4': M = 4 elif isost=='q' or isost=='m5': M = 5 else: print("Unknown isomeric state {}, assumed ground state".format(isost)) M = 0 ZZZAAAM = 10000*Z + 10*A + M return ZZZAAAM def time_str_to_sec_multiplier(time_str)-
Description
Provide a time unit and this function provides what those time units need to be multiplied by to obtain seconds.
Inputs
time_str= string containing time units character(s) [s,m,h,d,y,ms,us,ns,ps,fs]
Outputs
m= multiplier to convert a time of the supplied units to seconds
Expand source code
def time_str_to_sec_multiplier(time_str): ''' Description: Provide a time unit and this function provides what those time units need to be multiplied by to obtain seconds. Inputs: - `time_str` = string containing time units character(s) [s,m,h,d,y,ms,us,ns,ps,fs] Outputs: - `m` = multiplier to convert a time of the supplied units to seconds ''' try: if time_str == 's': m = 1 elif time_str == 'm': m = 60 elif time_str == 'h': m = 60*60 elif time_str == 'd': m = 60*60*24 elif time_str == 'y': m = 60*60*24*365.25 elif time_str == 'ms': m = 1e-3 elif time_str == 'us': m = 1e-6 elif time_str == 'ns': m = 1e-9 elif time_str == 'ps': m = 1e-12 elif time_str == 'fs': m = 1e-15 return m except: print('"{}" is not a valid time unit; please use one of the following: [s,m,h,d,y,ms,us,ns,ps,fs]'.format(time_str)) return None def seconds_to_dhms(t_sec)-
Description
Provide a time in seconds and obtain a string with the time in days, hours, minutes, and seconds
Inputs
t_sec= a time in seconds (float or int)
Outputs
time_str= string containing the time prettily formatted in d/h/m/s format
Expand source code
def seconds_to_dhms(t_sec): ''' Description: Provide a time in seconds and obtain a string with the time in days, hours, minutes, and seconds Inputs: - `t_sec` = a time in seconds (float or int) Outputs: - `time_str` = string containing the time prettily formatted in d/h/m/s format ''' m, s = divmod(t_sec, 60) h, m = divmod(m, 60) d, h = divmod(h, 24) if d != 0: time_str = "{:0.0f}d {:0.0f}h {:0.0f}m {:0.2f}s".format(d,h,m,s) elif h != 0: time_str = "{:0.0f}h {:0.0f}m {:0.2f}s".format(h,m,s) elif m != 0: time_str = "{:0.0f}m {:0.2f}s".format(m,s) elif s != 0: time_str = "{:0.2f}s".format(s) else: time_str = "" return time_str def seconds_to_ydhms(t_sec)-
Description
Provide a time in seconds and obtain a string with the time in years, days, hours, minutes, and seconds
Inputs
t_sec= a time in seconds (float or int)
Outputs
time_str= string containing the time prettily formatted in y/d/h/m/s format
Expand source code
def seconds_to_ydhms(t_sec): ''' Description: Provide a time in seconds and obtain a string with the time in years, days, hours, minutes, and seconds Inputs: - `t_sec` = a time in seconds (float or int) Outputs: - `time_str` = string containing the time prettily formatted in y/d/h/m/s format ''' m, s = divmod(t_sec, 60) h, m = divmod(m, 60) d, h = divmod(h, 24) y, d = divmod(d, 365) if y>=4 : # if leap year occurred n_leap_years = int(y/4) d = d-n_leap_years if y != 0: time_str = "{:0.0f}y {:0.0f}d {:0.0f}h {:0.0f}m {:0.2f}s".format(y,d,h,m,s) elif d != 0: time_str = "{:0.0f}d {:0.0f}h {:0.0f}m {:0.2f}s".format(d,h,m,s) elif h != 0: time_str = "{:0.0f}h {:0.0f}m {:0.2f}s".format(h,m,s) elif m != 0: time_str = "{:0.0f}m {:0.2f}s".format(m,s) elif s != 0: time_str = "{:0.2f}s".format(s) else: time_str = "" return time_str