The repository is still under developments and not ready to use. It made public to share the progress between collaborators. No documents are available yet.
There is prepared reaction index database in Python pickle format in pickles/reactions.pickle. You can load and manipulate Pandas DataFrame for instance:
import pandas as pd
df = pd.read_pickle("pickles/reactions.pickle")
target = "79-AU-197"
process = "N,G"
quantity = "SIG"
df = df[
(df_reaction.target == target.upper())
& (df_reaction.process == process.upper())
& (df_reaction.sf5.isnull())
& (df_reaction.sf6 == quantity.upper())
]
print(df)
This pickle contains 499,023 records that looks like:
id entry subentry pointer year author min_inc_en max_inc_en points target process sf4 residual sf5 sf6 sf7 sf8 sf9
C0290009XX C0290 009 XX 1981 R.A.Cecil 3.370e-04 3.370e-04 1 13-AL-27 10-NE-20,X 0-NN-1 0-NN-1 None DA/DE None None None
E1773008XX E1773 008 XX 2002 T.Wakasa 3.450e+02 3.450e+02 1 20-CA-40 P,X 0-NN-1 0-NN-1 None DA/DE None None None
411280022 41128 002 2 1993 V.A.Anufriev NaN NaN 0 98-CF-250 N,TOT None None None WID None None None
E2617012XX E2617 012 XX 2019 T.Murata 3.270e+01 5.040e+01 15 39-Y-89 A,X 39-Y-87 39-Y-87 None SIG None None None
G0018003XX G0018 003 XX 2010 Md.S.Rahman 5.000e+01 7.000e+01 3 49-IN-0 G,X 49-IN-111-G/M 49-IN-111-G/M None SIG/RAT None BRA None
21909005XX 21909 005 XX 1979 H.Yamamoto 1.450e+01 1.450e+01 1 92-U-238 N,F MASS A=110 SEC FY None None None
E1434007XX E1434 007 XX 1983 M.Takahashi 5.190e+01 5.190e+01 1 82-PB-208 P,T 82-PB-206 82-PB-206 PAR DA None None None
D6158002XX D6158 002 XX 2008 R.Tripathi 7.000e+01 1.000e+02 169 39-Y-89 9-F-19,X ELEM C None DA None None None
120970097 12097 009 7 1960 H.B.Moller NaN NaN 0 64-GD-155 N,TOT None None None WID None SQ/S0 None
O0920008XX O0920 008 XX 2001 J.Kuhnhenn 6.660e+01 6.660e+01 1 82-PB-0 P,F 47-AG-110-M 47-AG-110-M IND SIG None None None
D0635002XX D0635 002 XX 2003 W.Krolas 3.500e+02 3.500e+02 1 82-PB-208 28-NI-64,X ELEM/MASS 47-Ag-110 None SIG None None None
D0635002XX D0635 002 XX 2003 W.Krolas 3.500e+02 3.500e+02 1 82-PB-208 28-NI-64,X ELEM/MASS 82-Pb-199 None SIG None None None
M06350212 M0635 021 2 2003 V.V.Varlamov 1.980e+01 2.760e+01 27 23-V-51 G,2N 23-V-49 23-V-49 None SIG None None EVAL
There are three ways to run the conversion. All converted JSON files are in IAEA-NDS/exfor_json repository.
-
First, you need to download EXFOR master files from IAEA-NDS/exfor_master repository.
-
Change the EXFOR master file path (
EXFOR_ALL_PATH) and output path (OUT_PATH) inconfig.py. -
Convert from EXFOR to JSON, for instance, for EXFOR entry number 12898 and 40467:
import json
from exparser import convert_exfor_to_json
entries = ["12898", "40467"]
for entry in entries:
entry_json = convert_exfor_to_json(entry)
print(json.dumps(entry_json, indent = 1))
More functions will come soon.