Skip to content
Projects
Groups
Snippets
Help
Loading...
Help
Support
Keyboard shortcuts
?
Submit feedback
Sign in
Toggle navigation
T
TooBBA
Project overview
Project overview
Details
Activity
Releases
Repository
Repository
Files
Commits
Branches
Tags
Contributors
Graph
Compare
Issues
0
Issues
0
List
Boards
Labels
Milestones
Merge Requests
0
Merge Requests
0
CI / CD
CI / CD
Pipelines
Jobs
Schedules
Analytics
Analytics
CI / CD
Repository
Value Stream
Members
Members
Collapse sidebar
Close sidebar
Activity
Graph
Create a new issue
Jobs
Commits
Issue Boards
Open sidebar
Stelios Karozis
TooBBA
Commits
37c53192
Commit
37c53192
authored
Jun 04, 2021
by
Stelios Karozis
Browse files
Options
Browse Files
Download
Email Patches
Plain Diff
Debugging - Real case use
parent
87b2b8d9
Changes
4
Show whitespace changes
Inline
Side-by-side
Showing
4 changed files
with
154 additions
and
36 deletions
+154
-36
CHANGELOG
CHANGELOG
+11
-1
main.py
main.py
+86
-24
tooba_f.py
tooba_f.py
+44
-3
tooba_gmx.py
tooba_gmx.py
+13
-8
No files found.
CHANGELOG
View file @
37c53192
...
...
@@ -6,6 +6,16 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
## [Unreleased]
## [0.2.0] - 2021-06-04
### Added
- None
### Changed
- Use pickle5 to save data
### Removed
- None
## [0.1.2] - 2020-10-29
### Added
- add OrderedDict() function to keep input ordered independent to Python version
...
...
main.py
View file @
37c53192
...
...
@@ -3,13 +3,14 @@ from collections import OrderedDict
import
pandas
as
pd
import
tooba_f
as
tbf
import
tooba_gmx
as
tbgmx
import
gc
###################################################
#NOTICE: resids of head in each subdomain may differ in tail case
# keep all atoms of group in the first occurent subdomain
# in case of tail is the one closest to the head, hence
# the code is a good approximation
###################################################
SYSTEM_NAME
=
'Case4_20190909_5'
SYSTEM_NAME
=
"20190322_2"
DISCET
=
[
3.5
,
3.5
,
3.5
]
NUM_FR
=
750
TRAJ
=
SYSTEM_NAME
+
'/eq_traj.trr'
...
...
@@ -41,29 +42,41 @@ TPR=SYSTEM_NAME+'/eq_run.tpr'
#
###################################################
GROUPS
=
OrderedDict
()
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'
]],
'TL_GROUP'
:[
'vector'
,[
'save'
,
[
'pkl'
],
'vec'
]],
'ORDER_NS_SPH'
:[
'index_order+ORDER_NS_SPH_ndx'
,[
'save'
,
[
'pkl'
],
'index'
],
'order'
,[
'save'
,[
'pkl'
],
'order'
]],
'ORDER_NS_ACYL'
:[
'index_order+ORDER_NS_ACYL_ndx'
,[
'save'
,
[
'pkl'
],
'index'
],
'order'
,[
'save'
,[
'pkl'
],
'order'
]],
'ORDER_FFA'
:[
'index_order+ORDER_FFA_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'
]]
}
GROUPS
[
'ALL'
]
=
[
'index+ALL_ndx'
,[
'save'
,
[
'pkl'
],
'index'
],
'density'
,[
'save'
,
[
'pkl'
],
'dens'
]]
GROUPS
[
'HD_GROUP'
]
=
[
'surf'
,[
'save'
,
[
'pkl'
],
'surf'
],
'index+HD_ndx'
,[
'save'
,
[
'pkl'
],
'index'
],
'rdf'
,[
'save'
,
[
'pkl'
],
'rdf'
]]
GROUPS
[
'TL_GROUP'
]
=
[
'vector'
,[
'save'
,
[
'pkl'
],
'vec'
]]
GROUPS
[
'ORDER_NS_SPH'
]
=
[
'index_order+ORDER_NS_SPH_ndx'
,[
'save'
,
[
'pkl'
],
'index'
],
'order'
,[
'save'
,[
'pkl'
],
'order'
]]
GROUPS
[
'ORDER_NS_ACYL'
]
=
[
'index_order+ORDER_NS_ACYL_ndx'
,[
'save'
,
[
'pkl'
],
'index'
],
'order'
,[
'save'
,[
'pkl'
],
'order'
]]
GROUPS
[
'ORDER_FFA'
]
=
[
'index_order+ORDER_FFA_ndx'
,[
'save'
,
[
'pkl'
],
'index'
],
'order'
,[
'save'
,[
'pkl'
],
'order'
]]
GROUPS
[
'ORDER_CHOL'
]
=
[
'index_order+ORDER_CHOL_ndx'
,[
'save'
,
[
'pkl'
],
'index'
],
'order'
,[
'save'
,[
'pkl'
],
'order'
]]
GROUPS
[
'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'
]
ALL
[
'CHOL'
]
=
[
'ROH'
,
'R1'
,
'R2'
,
'R3'
,
'R4'
,
'R5'
]
ALL
[
'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'
]
HD_GROUP
[
'CHOL'
]
=
[
'ROH'
]
HD_GROUP
[
'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'
]
TL_GROUP
[
'CHOL'
]
=
[
'R1'
,
'R2'
,
'R3'
,
'R4'
,
'R5'
]
TL_GROUP
[
'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'
]
###################################################
###################################################
print
(
' '
)
...
...
@@ -95,12 +108,15 @@ ST_FR=MAX_FR-NUM_FR
###################################################
#--------------------------------------------------
if
os
.
path
.
isfile
(
'./'
+
SYSTEM_NAME
+
'/'
+
SYSTEM_NAME
+
'_data.pkl'
):
print
(
'_data.pkl exist !'
)
pass
else
:
#Read .trr file
data_all
=
tbf
.
fr_export
(
trajfile
=
TRAJ
,
num_frames
=
NUM_FR
)
#tbf.tojson(fl=data_all, sv_name='./'+SYSTEM_NAME+'/'+SYSTEM_NAME+'_data')
tbf
.
topickle
(
fl
=
data_all
,
sv_name
=
'./'
+
SYSTEM_NAME
+
'/'
+
SYSTEM_NAME
+
'_data'
)
del
data_all
gc
.
collect
()
###################################################
#--------------------------------------------------
#Check save files if exist in order to skip functions
...
...
@@ -161,13 +177,17 @@ for i in GROUPS.keys():
print
(
'++++++++++++++++++++++++'
)
group_ndx
=
tbf
.
atomid_data
(
res_num
,
res_type
,
atom_type
,
atom_num
,
group
=
locals
()[
i
])
tbf
.
topickle
(
fl
=
group_ndx
,
sv_name
=
'./'
+
SYSTEM_NAME
+
'/'
+
SYSTEM_NAME
+
'_'
+
i
+
'_ndx'
)
#tbf.tojson(fl=group_ndx, sv_name='./'+SYSTEM_NAME+'/'+SYSTEM_NAME+'_'+i+'_ndx')
del
group_ndx
gc
.
collect
()
#--------------------------------------------------
if
os
.
path
.
isfile
(
'./'
+
SYSTEM_NAME
+
'/'
+
SYSTEM_NAME
+
'_'
+
i
+
'_box.pkl'
):
pass
else
:
data_all
=
tbf
.
frompickle
(
'./'
+
SYSTEM_NAME
+
'/'
+
SYSTEM_NAME
+
'_data.pkl'
)
#data_all=tbf.fromjson('./'+SYSTEM_NAME+'/'+SYSTEM_NAME+'_data.json')
group_ndx
=
tbf
.
frompickle
(
'./'
+
SYSTEM_NAME
+
'/'
+
SYSTEM_NAME
+
'_'
+
i
+
'_ndx.pkl'
)
#group_ndx=tbf.fromjson('./'+SYSTEM_NAME+'/'+SYSTEM_NAME+'_'+i+'_ndx.json')
#Create subdomains coordinates
box_p
=
tbf
.
domain_decomposition
(
data
=
data_all
,
dx
=
DISCET
[
0
],
dy
=
DISCET
[
1
],
dz
=
DISCET
[
2
])
#Assign desired atoms (from above function) to subdomains
...
...
@@ -175,23 +195,31 @@ for i in GROUPS.keys():
##result2: {step:{res:{atom_type:{(subX,subYsubZ):[atom_num]}}}}
#todo keep fixed the initial domain name and the molecules that are grouped for all the steps
_
,
box_res
=
tbf
.
atom2group
(
data_all
,
box_p
,
group_ndx
)
tbf
.
topickle
(
fl
=
box_res
,
sv_name
=
'./'
+
SYSTEM_NAME
+
'/'
+
SYSTEM_NAME
+
'_'
+
i
+
'_box'
)
del
data_all
del
group_ndx
del
box_p
gc
.
collect
()
tbf
.
topickle
(
fl
=
box_res
,
sv_name
=
'./'
+
SYSTEM_NAME
+
'/'
+
SYSTEM_NAME
+
'_'
+
i
+
'_box'
)
#tbf.tojson(fl=box_res, sv_name='./'+SYSTEM_NAME+'/'+SYSTEM_NAME+'_'+i+'_box')
del
box_res
gc
.
collect
()
###################################################
if
os
.
path
.
isfile
(
'./'
+
SYSTEM_NAME
+
'/'
+
SYSTEM_NAME
+
'_'
+
i
+
'_FR'
+
str
(
NUM_FR
)
+
'.pkl'
):
pass
else
:
#Creates dictionary with coordinates per subdomain for each frame
data_all
=
tbf
.
frompickle
(
'./'
+
SYSTEM_NAME
+
'/'
+
SYSTEM_NAME
+
'_data.pkl'
)
#data_all=tbf.fromjson('./'+SYSTEM_NAME+'/'+SYSTEM_NAME+'_data.json')
box_res
=
tbf
.
frompickle
(
'./'
+
SYSTEM_NAME
+
'/'
+
SYSTEM_NAME
+
'_'
+
i
+
'_box.pkl'
)
#box_res=tbf.fromjson('./'+SYSTEM_NAME+'/'+SYSTEM_NAME+'_'+i+'_box.json')
_
,
coord_vector
=
tbf
.
sub_coord
(
box
=
box_res
,
data
=
data_all
,
res_num
=
res_num
)
tbf
.
topickle
(
fl
=
coord_vector
,
sv_name
=
'./'
+
SYSTEM_NAME
+
'/'
+
SYSTEM_NAME
+
'_'
+
i
+
'_FR'
+
str
(
NUM_FR
))
del
data_all
del
box_res
gc
.
collect
()
tbf
.
topickle
(
fl
=
coord_vector
,
sv_name
=
'./'
+
SYSTEM_NAME
+
'/'
+
SYSTEM_NAME
+
'_'
+
i
+
'_FR'
+
str
(
NUM_FR
))
#tbf.tojson(fl=coord_vector, sv_name='./'+SYSTEM_NAME+'/'+SYSTEM_NAME+'_'+i+'_FR'+str(NUM_FR))
del
coord_vector
gc
.
collect
()
###################################################
for
j
in
GROUPS
[
i
]:
if
len
(
j
)
>
1
:
...
...
@@ -200,57 +228,73 @@ for i in GROUPS.keys():
surf
=
{}
#Creates dictionary with c, normal per subdomain for each frame
coord_vector
=
tbf
.
frompickle
(
'./'
+
SYSTEM_NAME
+
'/'
+
SYSTEM_NAME
+
'_'
+
i
+
'_FR'
+
str
(
NUM_FR
)
+
'.pkl'
)
#coord_vector=tbf.fromjson('./'+SYSTEM_NAME+'/'+SYSTEM_NAME+'_'+i+'_FR'+str(NUM_FR)+'.json')
surf
[
i
]
=
tbf
.
coord2norm2cg
(
coord_vector
,
img
=
False
)
del
coord_vector
gc
.
collect
()
sv_data
=
surf
[
i
]
elif
j
==
'surf'
and
sv_index
[
i
][
j
][
'status'
]
==
'exist'
:
if
j
not
in
locals
():
surf
=
{}
surf
[
i
]
=
tbf
.
frompickle
(
sv_index
[
i
][
j
][
'name'
])
#surf[i]=tbf.fromjson(sv_index[i][j]['name'])
#--------------------------------------------------
if
j
==
'vector'
and
sv_index
[
i
][
j
][
'status'
]
==
'not exist'
:
if
j
not
in
locals
():
vector
=
{}
coord_vector
=
tbf
.
frompickle
(
'./'
+
SYSTEM_NAME
+
'/'
+
SYSTEM_NAME
+
'_'
+
i
+
'_FR'
+
str
(
NUM_FR
)
+
'.pkl'
)
#coord_vector=tbf.fromjson('./'+SYSTEM_NAME+'/'+SYSTEM_NAME+'_'+i+'_FR'+str(NUM_FR)+'.json')
vector
[
i
]
=
tbf
.
coord2vector
(
coord_vector
)
del
coord_vector
gc
.
collect
()
sv_data
=
vector
[
i
]
elif
j
==
'vector'
and
sv_index
[
i
][
j
][
'status'
]
==
'exist'
:
if
j
not
in
locals
():
vector
=
{}
vector
[
i
]
=
tbf
.
frompickle
(
sv_index
[
i
][
j
][
'name'
])
#vector[i]=tbf.fromjson(sv_index[i][j]['name'])
#--------------------------------------------------
#ToDo: make more generic file with ndx files and ndx for order parameter
#As for now the hash value is generic (system+domain coord), but needs to run for every input group
if
j
==
'index'
and
sv_index
[
i
][
j
][
'status'
]
==
'not exist'
:
box_res
=
tbf
.
frompickle
(
'./'
+
SYSTEM_NAME
+
'/'
+
SYSTEM_NAME
+
'_'
+
i
+
'_box.pkl'
)
#box_res=tbf.fromjson('./'+SYSTEM_NAME+'/'+SYSTEM_NAME+'_'+i+'_box.json')
tbf
.
togmxndx
(
box_res
,
fld
=
'./'
+
SYSTEM_NAME
+
'/'
+
ndx_fl
[
i
][
j
],
sv_name
=
SYSTEM_NAME
+
'_'
+
i
)
del
box_res
gc
.
collect
()
uniq_id
=
tbgmx
.
ndx_index
(
SYSTEM_NAME
,
ndx_fl
[
i
][
j
])
sv_data
=
uniq_id
elif
j
==
'index'
and
sv_index
[
i
][
j
][
'status'
]
==
'exist'
:
box_res
=
tbf
.
frompickle
(
'./'
+
SYSTEM_NAME
+
'/'
+
SYSTEM_NAME
+
'_'
+
i
+
'_box.pkl'
)
#box_res=tbf.fromjson('./'+SYSTEM_NAME+'/'+SYSTEM_NAME+'_'+i+'_box.json')
tbf
.
togmxndx
(
box_res
,
fld
=
'./'
+
SYSTEM_NAME
+
'/'
+
ndx_fl
[
i
][
j
],
sv_name
=
SYSTEM_NAME
+
'_'
+
i
)
del
box_res
gc
.
collect
()
uniq_id
=
tbf
.
frompickle
(
sv_index
[
i
][
j
][
'name'
])
#uniq_id=tbf.fromjson(sv_index[i][j]['name'])
#--------------------------------------------------
if
j
==
'index_order'
and
sv_index
[
i
][
j
][
'status'
]
==
'not exist'
:
box_res
=
tbf
.
frompickle
(
'./'
+
SYSTEM_NAME
+
'/'
+
SYSTEM_NAME
+
'_'
+
i
+
'_box.pkl'
)
#box_res=tbf.fromjson('./'+SYSTEM_NAME+'/'+SYSTEM_NAME+'_'+i+'_box.json')
for
mol
,
atoms
in
locals
()[
i
]
.
items
():
tbgmx
.
order_ndx
(
box_res
,
fld
=
'./'
+
SYSTEM_NAME
+
'/'
+
ndx_fl
[
i
][
j
],
atoms
=
atoms
,
sv_name
=
SYSTEM_NAME
+
'_'
+
i
)
del
box_res
gc
.
collect
()
uniq_id
=
tbgmx
.
ndx_index
(
SYSTEM_NAME
,
ndx_fl
[
i
][
j
])
sv_data
=
uniq_id
elif
j
==
'index_order'
and
sv_index
[
i
][
j
][
'status'
]
==
'exist'
:
box_res
=
tbf
.
frompickle
(
'./'
+
SYSTEM_NAME
+
'/'
+
SYSTEM_NAME
+
'_'
+
i
+
'_box.pkl'
)
#box_res=tbf.fromjson('./'+SYSTEM_NAME+'/'+SYSTEM_NAME+'_'+i+'_box.json')
for
mol
,
atoms
in
locals
()[
i
]
.
items
():
tbgmx
.
order_ndx
(
box_res
,
fld
=
'./'
+
SYSTEM_NAME
+
'/'
+
ndx_fl
[
i
][
j
],
atoms
=
atoms
,
sv_name
=
SYSTEM_NAME
+
'_'
+
i
)
del
box_res
gc
.
collect
()
uniq_id
=
tbf
.
frompickle
(
sv_index
[
i
][
j
][
'name'
])
#uniq_id=tbf.fromjson(sv_index[i][j]['name'])
#--------------------------------------------------
if
j
==
'density'
and
sv_index
[
i
][
j
][
'status'
]
==
'not exist'
:
dens_dict
=
{}
...
...
@@ -277,10 +321,13 @@ for i in GROUPS.keys():
sv_data
=
dens_dict
mrg_data
[
i
][
j
]
=
[
dens_dict
,[]]
del
dens_dict
gc
.
collect
()
elif
j
==
'density'
and
sv_index
[
i
][
j
][
'status'
]
==
'exist'
:
dens_dict
=
tbf
.
frompickle
(
sv_index
[
i
][
j
][
'name'
])
#dens_dict=tbf.fromjson(sv_index[i][j]['name'])
mrg_data
[
i
][
j
]
=
[
dens_dict
,[]]
del
dens_dict
gc
.
collect
()
#--------------------------------------------------
if
j
==
'rdf'
and
sv_index
[
i
][
j
][
'status'
]
==
'not exist'
:
rdf_dict
=
{}
...
...
@@ -301,17 +348,22 @@ for i in GROUPS.keys():
cnt2
=
cnt2
+
1
peaks
=
tbgmx
.
rdf_peaks
(
TRR
=
TRAJ
,
TPR
=
TPR
,
IND
=
fl
,
ST
=
time_index
[
ST_FR
],
EN
=-
1
,
fld
=
'./'
+
uniq_id
[
iidd
][
'system'
],
arg1
=
cnt1
,
arg2
=
cnt2
,
dist_pk
=
20
)
rdf_nm
=
mol1
+
'-'
+
mol2
+
'_rdf_'
+
uniq_id
[
iidd
][
'fld'
]
if
len
(
peaks
)
==
0
:
peaks
.
append
(
0
)
#if len(peaks)==0:
# print(peaks)
# print(type(peaks))
# peaks=np.ndarray((0))
rdf_dict
[
iidd
][
rdf_nm
]
=
peaks
sv_data
=
rdf_dict
mrg_data
[
i
][
j
]
=
[
rdf_dict
,[]]
del
rdf_dict
gc
.
collect
()
elif
j
==
'rdf'
and
sv_index
[
i
][
j
][
'status'
]
==
'exist'
:
rdf_dict
=
tbf
.
frompickle
(
sv_index
[
i
][
j
][
'name'
])
#rdf_dict=tbf.fromjson(sv_index[i][j]['name'])
mrg_data
[
i
][
j
]
=
[
rdf_dict
,[]]
del
rdf_dict
gc
.
collect
()
#--------------------------------------------------
if
j
==
'order'
and
sv_index
[
i
][
j
][
'status'
]
==
'not exist'
:
order_dict
=
{}
...
...
@@ -335,8 +387,10 @@ for i in GROUPS.keys():
sv_data
=
order_dict
mrg_data
[
i
][
j
]
=
[
order_dict
,[]]
del
order_dict
gc
.
collect
()
elif
j
==
'order'
and
sv_index
[
i
][
j
][
'status'
]
==
'exist'
:
order_dict
=
tbf
.
frompickle
(
sv_index
[
i
][
j
][
'name'
])
#order_dict=tbf.fromjson(sv_index[i][j]['name'])
mrg_data
[
i
][
j
]
=
[
order_dict
,[]]
del
order_dict
#--------------------------------------------------
...
...
@@ -354,6 +408,7 @@ for i in GROUPS.keys():
if
k
==
'json'
:
tbf
.
tojson
(
fl
=
sv_data
,
sv_name
=
'./'
+
SYSTEM_NAME
+
'/'
+
SYSTEM_NAME
+
'_'
+
i
+
'_'
+
j
[
2
])
del
sv_data
gc
.
collect
()
###################################################
#COMBINE section
else
:
...
...
@@ -373,6 +428,7 @@ for i in GROUPS.keys():
#ToDo: check "if str(value['domain']).strip() == str(sub).strip():"
del
surf_inuse
del
vector_inuse
gc
.
collect
()
#Loop over timesteps and keep avgs tilts for each step
avg
=
{}
for
step
in
tilt
.
keys
():
...
...
@@ -399,10 +455,13 @@ for i in GROUPS.keys():
sv_data
=
tot_avg
mrg_data
[
i
][
j
[
1
]]
=
[
tot_avg
,[
'Tilt[degrees]'
]]
del
tot_avg
gc
.
collect
()
elif
j
[
1
]
==
'tilt'
and
sv_index
[
i
][
str
(
j
)][
'status'
]
==
'exist'
:
tot_avg
=
tbf
.
frompickle
(
sv_index
[
i
][
str
(
j
)][
'name'
])
#tot_avg=tbf.fromjson(sv_index[i][str(j)]['name'])
mrg_data
[
i
][
j
[
1
]]
=
[
tot_avg
,[
'Tilt[degrees]'
]]
del
tot_avg
gc
.
collect
()
#--------------------------------------------------
# Save module
if
len
(
j
)
==
3
:
...
...
@@ -418,9 +477,11 @@ for i in GROUPS.keys():
if
k
==
'json'
:
tbf
.
tojson
(
fl
=
sv_data
,
sv_name
=
'./'
+
SYSTEM_NAME
+
'/'
+
SYSTEM_NAME
+
'_'
+
i
+
'_'
+
j
[
2
])
del
sv_data
gc
.
collect
()
###################################################
#Merge data
tbf
.
topickle
(
fl
=
mrg_data
,
sv_name
=
'./'
+
SYSTEM_NAME
+
'/'
+
SYSTEM_NAME
+
'_merge'
)
#tbf.tojson(fl=mrg_data, sv_name='./'+SYSTEM_NAME+'/'+SYSTEM_NAME+'_merge')
print
(
' '
)
print
(
'Merging data of:'
)
print
(
'=============================='
)
...
...
@@ -436,6 +497,7 @@ for grp in mrg_data.keys():
data_df
=
df
.
copy
()
continue
tbf
.
topickle
(
fl
=
data_df
,
sv_name
=
'./'
+
SYSTEM_NAME
+
'/'
+
SYSTEM_NAME
+
'_dataset'
)
#tbf.tojson(fl=data_df, sv_name='./'+SYSTEM_NAME+'/'+SYSTEM_NAME+'_dataset')
print
(
data_df
.
head
())
###################################################
###################################################
tooba_f.py
View file @
37c53192
...
...
@@ -3,11 +3,12 @@ import numpy as np
#from mpl_toolkits.mplot3d import Axes3D
import
matplotlib.pyplot
as
plt
import
scipy.optimize
import
pickle
as
pkl
import
pickle
5
as
pkl
import
json
import
re
import
pandas
as
pd
from
progress.bar
import
Bar
import
joblib
from
pytrr
import
(
read_trr_header
,
...
...
@@ -66,15 +67,47 @@ def center_gravity(a):
cg
=
np
.
sum
(
a
)
/
m
return
cg
class
StreamFile
(
object
):
def
__init__
(
self
,
f
):
self
.
f
=
f
def
__getattr__
(
self
,
item
):
return
getattr
(
self
.
f
,
item
)
def
read
(
self
,
n
):
# print("reading total_bytes=%s" % n, flush=True)
if
n
>=
(
1
<<
31
):
buffer
=
bytearray
(
n
)
idx
=
0
while
idx
<
n
:
batch_size
=
min
(
n
-
idx
,
1
<<
31
-
1
)
# print("reading bytes [%s,%s)..." % (idx, idx + batch_size), end="", flush=True)
buffer
[
idx
:
idx
+
batch_size
]
=
self
.
f
.
read
(
batch_size
)
# print("done.", flush=True)
idx
+=
batch_size
return
buffer
return
self
.
f
.
read
(
n
)
def
write
(
self
,
buffer
):
n
=
len
(
buffer
)
print
(
"writing total_bytes=
%
s..."
%
n
,
flush
=
True
)
idx
=
0
while
idx
<
n
:
batch_size
=
min
(
n
-
idx
,
1
<<
31
-
1
)
print
(
"writing bytes [
%
s,
%
s)... "
%
(
idx
,
idx
+
batch_size
),
end
=
""
,
flush
=
True
)
self
.
f
.
write
(
buffer
[
idx
:
idx
+
batch_size
])
print
(
"done."
,
flush
=
True
)
idx
+=
batch_size
def
topickle
(
fl
,
sv_name
):
print
(
' '
)
print
(
'Save to pickle |################################| 1/1'
)
with
open
(
sv_name
+
'.pkl'
,
'wb'
)
as
handle
:
pkl
.
dump
(
fl
,
handle
,
protocol
=
pkl
.
HIGHEST_PROTOCOL
)
#joblib.dump(fl, handle)
def
frompickle
(
fl
):
with
open
(
fl
,
'rb'
)
as
handle
:
b
=
pkl
.
load
(
handle
)
#b = joblib.load(handle)
return
b
...
...
@@ -83,6 +116,14 @@ def tojson(fl, sv_name):
print
(
'Save to json |################################| 1/1'
)
with
open
(
sv_name
+
'.json'
,
'w'
)
as
file
:
file
.
write
(
json
.
dumps
(
str
(
fl
)))
#file.write(json.dumps(fl))
def
fromjson
(
fl
):
print
(
' '
)
print
(
'Load to json |################################| 1/1'
)
with
open
(
fl
,
'r'
)
as
file
:
data
=
file
.
read
()
b
=
json
.
dumps
(
data
)
return
b
def
plot_surf
(
data
,
normal
,
c
,
save_name
):
#Plot surface
...
...
tooba_gmx.py
View file @
37c53192
...
...
@@ -97,13 +97,18 @@ def rdf_peaks(TRR,TPR,IND,ST,EN,fld,arg1,arg2,dist_pk):
p
.
communicate
(
cmd
.
encode
(
'UTF-8'
))
p
.
send_signal
(
'<Ctrl>-D'
)
p
.
wait
()
try
:
f
=
open
(
fld
+
'/tmp.xvg'
)
f
.
close
()
# Do something with the file
x
,
y
=
read_xvg
(
XVG
=
fld
+
'/tmp.xvg'
)
yhat
=
savgol_filter
(
y
,
15
,
4
)
# window size 15, polynomial order 4
peaks
,
_
=
find_peaks
(
yhat
,
distance
=
dist_pk
)
pathname
=
os
.
path
.
abspath
(
os
.
path
.
join
(
fld
,
'tmp.xvg'
))
os
.
remove
(
pathname
)
except
IOError
:
peaks
=
np
.
ndarray
((
0
))
return
peaks
...
...
Write
Preview
Markdown
is supported
0%
Try again
or
attach a new file
Attach a file
Cancel
You are about to add
0
people
to the discussion. Proceed with caution.
Finish editing this message first!
Cancel
Please
register
or
sign in
to comment