Commit 6c393870 authored by Stelios Karozis's avatar Stelios Karozis

Use OrderedDict() when creating input

to keep order of input independent of the Python version
parent f6edc38e
.gitignore .gitignore
FORTRAN_vscode/
__pycache__/ __pycache__/
.venv/ .venv/
.vscode/ .vscode/
...@@ -12,4 +11,4 @@ __pycache__/ ...@@ -12,4 +11,4 @@ __pycache__/
*.code-workspace *.code-workspace
*.itp *.itp
system/ system/
20190322_10 Case4_20190909_5
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import os import os
from collections import OrderedDict
import pandas as pd import pandas as pd
import tooba_f as tbf import tooba_f as tbf
import tooba_gmx as tbgmx import tooba_gmx as tbgmx
...@@ -8,7 +9,7 @@ import tooba_gmx as tbgmx ...@@ -8,7 +9,7 @@ import tooba_gmx as tbgmx
# in case of tail is the one closest to the head, hence # in case of tail is the one closest to the head, hence
# the code is a good approximation # the code is a good approximation
################################################### ###################################################
SYSTEM_NAME='20190322_10' SYSTEM_NAME='Case4_20190909_5'
DISCET=[3.5, 3.5, 3.5] DISCET=[3.5, 3.5, 3.5]
NUM_FR=750 NUM_FR=750
TRAJ=SYSTEM_NAME+'/eq_traj.trr' TRAJ=SYSTEM_NAME+'/eq_traj.trr'
...@@ -39,6 +40,7 @@ TPR=SYSTEM_NAME+'/eq_run.tpr' ...@@ -39,6 +40,7 @@ TPR=SYSTEM_NAME+'/eq_run.tpr'
# [save, [TYPE], SAVE_NAME]: Save result of previous function, type: pkl, json # [save, [TYPE], SAVE_NAME]: Save result of previous function, type: pkl, json
# #
################################################### ###################################################
GROUPS=OrderedDict()
GROUPS={'ALL':['index+ALL_ndx',['save', ['pkl'],'index'],'density',['save', ['pkl'],'dens']], GROUPS={'ALL':['index+ALL_ndx',['save', ['pkl'],'index'],'density',['save', ['pkl'],'dens']],
'HD_GROUP':['surf',['save', ['pkl', 'json'],'surf'],'index+HD_ndx',['save', ['pkl'],'index'],'rdf',['save', ['pkl'],'rdf']], 'HD_GROUP':['surf',['save', ['pkl', 'json'],'surf'],'index+HD_ndx',['save', ['pkl'],'index'],'rdf',['save', ['pkl'],'rdf']],
'TL_GROUP':['vector',['save', ['pkl'],'vec']], 'TL_GROUP':['vector',['save', ['pkl'],'vec']],
...@@ -48,12 +50,19 @@ GROUPS={'ALL':['index+ALL_ndx',['save', ['pkl'],'index'],'density',['save', ['pk ...@@ -48,12 +50,19 @@ GROUPS={'ALL':['index+ALL_ndx',['save', ['pkl'],'index'],'density',['save', ['pk
'ORDER_CHOL':['index_order+ORDER_CHOL_ndx',['save', ['pkl'],'index'],'order',['save',['pkl'], 'order']], 'ORDER_CHOL':['index_order+ORDER_CHOL_ndx',['save', ['pkl'],'index'],'order',['save',['pkl'], 'order']],
'COMBINE':[['HD_GROUP','surf'],['TL_GROUP','vector'],['COMB','tilt'],['save', ['pkl'],'tilt']] 'COMBINE':[['HD_GROUP','surf'],['TL_GROUP','vector'],['COMB','tilt'],['save', ['pkl'],'tilt']]
} }
ALL=OrderedDict()
ALL={'NS':['C1', 'C2', 'C3', 'C4', 'C5','C6', 'Na', 'P4', 'P3', 'C7','C3', 'C4', 'C5', 'C8', 'C9', 'C10'], 'CHOL':['ROH','R1', 'R2', 'R3', 'R4', 'R5'], 'FFA':['AC','C1', 'C2', 'C3', 'C4']} ALL={'NS':['C1', 'C2', 'C3', 'C4', 'C5','C6', 'Na', 'P4', 'P3', 'C7','C3', 'C4', 'C5', 'C8', 'C9', 'C10'], 'CHOL':['ROH','R1', 'R2', 'R3', 'R4', 'R5'], 'FFA':['AC','C1', 'C2', 'C3', 'C4']}
HD_GROUP=OrderedDict()
HD_GROUP={'NS':['C6', 'Na', 'P4', 'P3', 'C7'], 'CHOL':['ROH'], 'FFA':['AC']} HD_GROUP={'NS':['C6', 'Na', 'P4', 'P3', 'C7'], 'CHOL':['ROH'], 'FFA':['AC']}
TL_GROUP=OrderedDict()
TL_GROUP={'NS':['C3', 'C4', 'C5', 'C8', 'C9', 'C10'], 'CHOL':['R1', 'R2', 'R3', 'R4', 'R5'], 'FFA':['C1', 'C2', 'C3', 'C4']} TL_GROUP={'NS':['C3', 'C4', 'C5', 'C8', 'C9', 'C10'], 'CHOL':['R1', 'R2', 'R3', 'R4', 'R5'], 'FFA':['C1', 'C2', 'C3', 'C4']}
ORDER_NS_SPH=OrderedDict()
ORDER_NS_SPH={'NS':['C1', 'C2', 'C3', 'C4', 'C5']} #propable problem with the same atomname of NS, FFA ORDER_NS_SPH={'NS':['C1', 'C2', 'C3', 'C4', 'C5']} #propable problem with the same atomname of NS, FFA
ORDER_NS_ACYL=OrderedDict()
ORDER_NS_ACYL={'NS':['C8', 'C9', 'C10']} ORDER_NS_ACYL={'NS':['C8', 'C9', 'C10']}
ORDER_FFA=OrderedDict()
ORDER_FFA={'FFA':['C1', 'C2', 'C3', 'C4']} ORDER_FFA={'FFA':['C1', 'C2', 'C3', 'C4']}
ORDER_CHOL=OrderedDict()
ORDER_CHOL={'CHOL':['R2', 'R3', 'R4', 'R5']} ORDER_CHOL={'CHOL':['R2', 'R3', 'R4', 'R5']}
################################################### ###################################################
################################################### ###################################################
......
numpy numpy
scipy scipy
mpl_toolkits #mpl_toolkits
matplotlib matplotlib
pytrr pytrr
pandas pandas
pickle #pickle
json #json
progress.bar progress.bar
subprocess #subprocess
hashlib #hashlib
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