Page Menu
Home
c4science
Search
Configure Global Search
Log In
Files
F62699729
random_sampler.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
Tue, May 14, 23:43
Size
2 KB
Mime Type
text/x-python
Expires
Thu, May 16, 23:43 (2 d)
Engine
blob
Format
Raw Data
Handle
17679131
Attached To
R6746 RationalROMPy
random_sampler.py
View Options
# Copyright (C) 2018 by the RROMPy authors
#
# This file is part of RROMPy.
#
# RROMPy is free software: you can redistribute it and/or modify
# it under the terms of the GNU Lesser General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# RROMPy is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Lesser General Public License for more details.
#
# You should have received a copy of the GNU Lesser General Public License
# along with RROMPy. If not, see <http://www.gnu.org/licenses/>.
#
import
numpy
as
np
from
rrompy.utilities.base.sobol
import
sobolGenerate
from
rrompy.utilities.parameter_sampling.generic_sampler
import
GenericSampler
from
rrompy.utilities.base.types
import
Np1D
,
Tuple
,
List
__all__
=
[
'RandomSampler'
]
class
RandomSampler
(
GenericSampler
):
"""Generator of quadrature sample points."""
allowedKinds
=
[
"UNIFORM"
,
"SOBOL"
]
def
__init__
(
self
,
lims
:
Tuple
[
Np1D
,
Np1D
],
kind
:
str
=
"UNIFORM"
,
scaling
:
callable
=
None
,
scalingInv
:
callable
=
None
):
super
()
.
__init__
(
lims
=
lims
,
scaling
=
scaling
,
scalingInv
=
scalingInv
)
self
.
kind
=
kind
def
__str__
(
self
)
->
str
:
return
"{}_{}"
.
format
(
super
()
.
__str__
(),
self
.
kind
)
def
__repr__
(
self
)
->
str
:
return
self
.
__str__
()
+
" at "
+
hex
(
id
(
self
))
@property
def
kind
(
self
):
"""Value of kind."""
return
self
.
_kind
@kind.setter
def
kind
(
self
,
kind
):
if
kind
.
upper
()
not
in
self
.
allowedKinds
:
raise
Exception
(
"Generator kind not recognized."
)
self
.
_kind
=
kind
.
upper
()
def
generatePoints
(
self
,
n
:
int
,
seed
:
int
=
0
)
->
Tuple
[
List
[
Np1D
],
Np1D
]:
"""Array of quadrature points and array of weights."""
super
()
.
generatePoints
(
n
)
d
=
len
(
self
.
lims
[
0
])
if
self
.
kind
==
"UNIFORM"
:
np
.
random
.
seed
(
seed
)
x
=
np
.
random
.
uniform
(
size
=
(
n
,
d
))
else
:
x
=
sobolGenerate
(
d
,
n
,
seed
)
for
j
in
range
(
d
):
a
,
b
=
self
.
lims
[
0
][
j
],
self
.
lims
[
1
][
j
]
if
self
.
scaling
is
not
None
:
a
,
b
=
self
.
scaling
[
j
](
a
),
self
.
scaling
[
j
](
b
)
x
[:,
j
]
=
a
+
(
b
-
a
)
*
x
[:,
j
]
if
self
.
scalingInv
is
not
None
:
x
[:,
j
]
=
self
.
scalingInv
[
j
](
x
[:,
j
])
return
[
y
.
flatten
()
for
y
in
np
.
split
(
x
,
n
)],
np
.
ones
(
n
)
def
refine
(
self
,
n
:
int
,
seed
:
int
=
420
)
->
Tuple
[
List
[
Np1D
],
Np1D
]:
"""
Apply refinement. If points are not nested, equivalent to
generatePoints([2 * x - 1 for x in n]).
"""
try
:
len
(
n
)
except
:
n
=
np
.
array
([
n
])
return
self
.
generatePoints
([
nj
-
1
for
nj
in
n
],
seed
)
Event Timeline
Log In to Comment