Page Menu
Home
c4science
Search
Configure Global Search
Log In
Files
F88595218
gurobi.py
No One
Temporary
Actions
Download File
Edit File
Delete File
View Transforms
Subscribe
Mute Notifications
Award Token
Subscribers
None
File Metadata
Details
File Info
Storage
Attached
Created
Sat, Oct 19, 16:00
Size
4 KB
Mime Type
text/x-python
Expires
Mon, Oct 21, 16:00 (1 d, 21 h)
Engine
blob
Format
Raw Data
Handle
21710263
Attached To
R11301 MOLEKUEHL
gurobi.py
View Options
import
numpy
as
np
import
timeit
import
gurobipy
as
gp
from
gurobipy
import
GRB
# This function places the molecule M optimally within the target T such that
# the charges of the molecule CM and the charges of the target CT are
# compatible
def
OptimalPlacement
(
M
,
CM
,
T
,
CT
):
try
:
#Dimemsion of the Molecule and Target
m
=
len
(
M
)
n
=
len
(
T
)
print
(
"-----------------------------------"
)
print
(
"Sizes of Matrices to match: "
,
m
,
n
)
print
(
"-----------------------------------"
)
# Create a new model
Z
=
gp
.
Model
(
"QP"
)
Z
.
setParam
(
'OutputFlag'
,
0
)
start
=
timeit
.
default_timer
()
#Create Variables
x
=
Z
.
addVars
(
m
,
n
,
name
=
'X'
,
vtype
=
GRB
.
BINARY
)
Z
.
addConstrs
(
x
.
sum
(
i
,
'*'
)
==
1
for
i
in
range
(
m
))
Z
.
addConstrs
(
x
.
sum
(
'*'
,
j
)
<=
1
for
j
in
range
(
n
))
# if the charges of atom i in molecule and atom j in target do not
# match, then we forbid the assignment i-> j
for
i
in
range
(
m
):
for
j
in
range
(
n
):
if
(
CM
[
i
]
!=
CT
[
j
]):
Z
.
addConstr
(
x
[
i
,
j
]
==
0
)
# Set objective by building a long expression
# this takes the most time by far, to optimize?
expr
=
2
*
x
[
1
,
1
]
*
x
[
1
,
2
]
expr
.
clear
()
for
i
in
range
(
m
):
for
j
in
range
(
m
):
for
k
in
range
(
n
):
for
l
in
range
(
n
):
expr
.
add
(
x
[
i
,
k
]
*
x
[
j
,
l
],
(
T
[
k
,
l
]
-
M
[
i
,
j
])
**
2
)
expr
.
addConstant
(
-
m
)
Z
.
setObjective
(
expr
,
GRB
.
MINIMIZE
)
stop
=
timeit
.
default_timer
()
print
(
"Time to define objective function:"
,
stop
-
start
,
"s"
)
# Optimize model
print
(
"
\n
----------------
\n
Optimisation...
\n
----------------
\n
"
)
Z
.
optimize
()
assert
Z
.
status
==
2
print
(
"
\n
------------------
\n
Best match...
\n
------------------
\n
"
)
matched_target
=
[]
for
v
in
Z
.
getVars
():
if
v
.
x
==
1
:
i
,
j
=
v
.
varName
.
split
(
"["
)[
-
1
]
.
split
(
"]"
)[
0
]
.
split
(
","
)
j
=
int
(
j
)
matched_target
.
append
(
j
)
print
(
"Indices of the target:"
)
print
(
matched_target
)
print
(
"Objective value:"
)
print
(
Z
.
ObjVal
)
print
(
"Runtime:"
)
print
(
Z
.
Runtime
,
"s"
)
return
[
matched_target
,
Z
.
ObjVal
]
except
gp
.
GurobiError
as
e
:
print
(
'Error code '
+
str
(
e
.
errno
)
+
': '
+
str
(
e
))
return
[[],
-
1
]
except
AttributeError
:
print
(
'Encountered an attribute error'
)
return
[[],
-
1
]
except
AssertionError
:
print
(
"No optimal solution has been found"
)
return
[[],
-
1
]
#A shortcut to call the OptimalPlacement function
def
Assignment
(
database_index
,
target_index
):
target_CM
=
data
[
'target_CMs'
][
target_index
]
target_ncharges
=
data
[
'target_ncharges'
][
target_index
]
target_label
=
data
[
'target_labels'
][
target_index
]
assert
len
(
target_CM
)
==
len
(
target_ncharges
)
database_CM
=
data
[
'database_CMs'
][
database_index
]
database_ncharges
=
data
[
'database_ncharges'
][
database_index
]
database_label
=
data
[
'database_labels'
][
database_index
]
assert
len
(
database_CM
)
==
len
(
database_ncharges
)
print
(
"----------------------------------------"
)
print
(
"Trying to place"
,
database_label
,
"inside"
,
target_label
,
"..."
)
print
(
"----------------------------------------"
)
[
target_indices
,
objval
]
=
OptimalPlacement
(
database_CM
,
database_ncharges
,
target_CM
,
target_ncharges
)
return
[
target_indices
,
objval
]
if
__name__
==
"__main__"
:
data
=
np
.
load
(
"data.npz"
,
allow_pickle
=
True
)
#fixed target index (value in {0, 1, 2})
target_index
=
2
# loops over all candidates M, looking for minimal objective value
size_database
=
len
(
data
[
'database_ncharges'
])
m_index
=
0
[
target_indices
,
objval
]
=
[[],
-
1
]
#for database_index in range(size_database):
for
database_index
in
[
0
,
1
]:
print
(
database_index
,
" / "
,
size_database
)
[
tempindices
,
tempobjval
]
=
Assignment
(
database_index
,
target_index
)
if
objval
==-
1
or
(
tempobjval
!=-
1
and
tempobjval
<
objval
):
objval
=
tempobjval
target_indices
=
tempindices
molecule_index
=
database_index
print
(
"Best molecule M found:"
)
print
(
"Name:"
,
data
[
'database_labels'
][
m_index
])
print
(
"Target indices:"
,
target_indices
)
print
(
"Objective value:"
,
objval
)
Event Timeline
Log In to Comment