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Josef Brandt
Subsampling
Commits
fc238b30
Commit
fc238b30
authored
Apr 15, 2020
by
Josef Brandt
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Cython RandomBoxGeneration
parent
d23662e8
Changes
5
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5 changed files
with
105 additions
and
13 deletions
+105
-13
cythonModules/randoms.pyx
cythonModules/randoms.pyx
+69
-0
cythonModules/setup_cython.py
cythonModules/setup_cython.py
+12
-4
evaluation.py
evaluation.py
+2
-2
geometricMethods.py
geometricMethods.py
+19
-5
subsampling.py
subsampling.py
+3
-2
No files found.
cythonModules/randoms.pyx
0 → 100644
View file @
fc238b30
import
numpy
as
np
cimport
numpy
as
np
cimport
numpy.random
cimport
cython
DTYPE
=
np
.
float
ctypedef
np
.
int32_t
INT32_t
cdef
get_random_topleft
(
double
maxDist
,
double
maxAngle
,
double
radius
,
double
boxSize
):
cdef
double
angle
,
dist
,
x
,
y
cdef
np
.
ndarray
[
INT32_t
,
ndim
=
1
]
newTopLeft
dist
=
np
.
random
.
rand
()
*
maxDist
angle
=
np
.
random
.
rand
()
*
maxAngle
newTopLeft
=
np
.
empty
(
2
,
dtype
=
np
.
int32
)
x
=
dist
*
np
.
cos
(
angle
)
+
radius
-
boxSize
/
2
y
=
dist
*
np
.
sin
(
angle
)
+
radius
-
boxSize
/
2
newTopLeft
[
0
]
=
np
.
int32
(
np
.
round
(
x
))
newTopLeft
[
1
]
=
np
.
int32
(
np
.
round
(
y
))
return
newTopLeft
def
get_random_topLefts
(
int
numBoxes
,
double
boxSize
,
double
radius
,
double
maxAngle
,
int
seed
=
1337
,
int
maxTries
=
50
):
cdef
np
.
ndarray
[
INT32_t
,
ndim
=
2
]
topLefts
cdef
np
.
ndarray
[
INT32_t
,
ndim
=
1
]
newTopLeft
cdef
double
maxDist
cdef
int
outerCounter
,
counter
,
x
,
y
,
i
,
j
,
diffX
,
diffY
,
successfullyAdded
cdef
bint
validSolutionFound
,
boxOverlaps
np
.
random
.
seed
(
seed
)
maxDist
=
radius
-
np
.
sqrt
((
boxSize
/
2
)
**
2
+
(
boxSize
/
2
)
**
2
)
outerCounter
=
0
validSolutionFound
=
False
while
not
validSolutionFound
and
outerCounter
<
maxTries
:
successfullyAdded
=
0
topLefts
=
np
.
empty
((
numBoxes
,
2
),
dtype
=
np
.
int32
)
for
i
in
range
(
numBoxes
):
if
i
==
0
:
topLefts
[
0
,
:]
=
get_random_topleft
(
maxDist
,
maxAngle
,
radius
,
boxSize
)
successfullyAdded
+=
1
else
:
counter
=
0
while
counter
<
50
:
newTopLeft
=
get_random_topleft
(
maxDist
,
maxAngle
,
radius
,
boxSize
)
boxOverlaps
=
False
for
j
in
range
(
i
):
diffX
=
abs
(
np
.
float
(
newTopLeft
[
0
]
-
np
.
float
(
topLefts
[
j
,
0
])))
diffY
=
abs
(
np
.
float
(
newTopLeft
[
1
]
-
np
.
float
(
topLefts
[
j
,
1
])))
if
diffX
<
boxSize
and
diffY
<
boxSize
:
boxOverlaps
=
True
break
if
boxOverlaps
:
counter
+=
1
else
:
topLefts
[
i
,
:]
=
newTopLeft
successfullyAdded
+=
1
break
if
successfullyAdded
==
numBoxes
:
validSolutionFound
=
True
else
:
outerCounter
+=
1
return
validSolutionFound
,
topLefts
\ No newline at end of file
cythonModules/setup_cython.py
View file @
fc238b30
...
...
@@ -9,10 +9,18 @@ if len(sys.argv) == 1:
sys
.
argv
.
append
(
"build_ext"
)
sys
.
argv
.
append
(
"--inplace"
)
ext
=
Extension
(
"rotateContour"
,
[
"rotateContour.pyx"
],
extra_compile_args
=
[
'-O3'
],)
# ext = Extension("rotateContour", ["rotateContour.pyx"], extra_compile_args=['-O3'],)
# setup(
# name="rotate contour around reference point",
# ext_modules=cythonize([ext], annotate=True), # accepts a glob pattern
# include_dirs=[np.get_include()]
# )
# ext = Extension("getRandomTopLefts", ["getRandomTopLefts.pyx"], extra_compile_args=['-O3'],)
setup
(
name
=
"
rotate contour around reference point
"
,
ext_modules
=
cythonize
(
[
ext
]
,
annotate
=
True
),
# accepts a glob pattern
name
=
"
get a given number of random topLefts
"
,
ext_modules
=
cythonize
(
"randoms.pyx"
,
annotate
=
True
),
# accepts a glob pattern
include_dirs
=
[
np
.
get_include
()]
)
\ No newline at end of file
)
evaluation.py
View file @
fc238b30
...
...
@@ -32,7 +32,7 @@ def get_methods_to_test(dataset: dataset.DataSet, fractions: list = []) -> list:
:return: list of measurement Objects that are applicable
"""
if
len
(
fractions
)
==
0
:
fractions
:
list
=
[
0.0
5
,
0.1
]
fractions
:
list
=
[
0.0
2
,
0.05
,
0.1
,
0.2
,
0.3
,
0.5
,
0.7
,
0.9
]
methods
:
list
=
[]
particleContainer
=
dataset
.
particleContainer
...
...
@@ -247,7 +247,7 @@ class SampleResult(object):
"""
An object the stores all generated results per sample and can update and report on them.
"""
def
__init__
(
self
,
filepath
:
str
,
numVariations
:
int
=
1
):
def
__init__
(
self
,
filepath
:
str
,
numVariations
:
int
=
1
0
):
super
(
SampleResult
,
self
).
__init__
()
self
.
filepath
:
str
=
filepath
self
.
dataset
:
dataset
.
DataSet
=
None
...
...
geometricMethods.py
View file @
fc238b30
...
...
@@ -6,6 +6,7 @@ import sys
sys
.
path
.
append
(
"C://Users//xbrjos//Desktop//Python"
)
from
gepard
import
dataset
import
helpers
from
cythonModules
import
randoms
def
box_overlaps_other_box
(
topLeft1
:
list
,
topLeft2
:
list
,
boxSize
:
float
)
->
bool
:
...
...
@@ -190,6 +191,7 @@ class BoxSelectionCreator(object):
diameter
,
offset
=
self
.
_get_diameter_and_offset
()
randomBoxSampler
:
RandomQuarterBoxes
=
RandomQuarterBoxes
(
None
,
desiredFraction
)
randomBoxSampler
.
update_max_fractions
()
for
numBoxes
in
randomBoxSampler
.
possibleBoxNumbers
:
randomBoxSampler
.
numBoxes
=
numBoxes
if
randomBoxSampler
.
config_is_valid
():
...
...
@@ -392,18 +394,29 @@ class RandomBoxSampling(BoxSelectionSubsamplingMethod):
return
equals
def
get_topLeft_of_boxes
(
self
)
->
list
:
#
# valid, topLefts = randoms.get_random_topLefts(self.numBoxes, self.boxSize,
# self.filterDiameter/2, self.__maxAngle,
# seed=self.randomSeed, maxTries=self.maxTries)
#
# if not valid:
# raise AttributeError
#
# topLefts: list = [[topLefts[i, 0], topLefts[i, 1]] for i in range(topLefts.shape[0])]
#
def
get_random_topleft
()
->
list
:
angle
=
np
.
random
.
rand
()
*
self
.
__maxAngle
dist
=
np
.
random
.
rand
()
*
maxDist
x
:
float
=
dist
*
np
.
cos
(
angle
)
+
radius
-
boxSize
/
2
y
:
float
=
dist
*
np
.
sin
(
angle
)
+
radius
-
boxSize
/
2
x
:
float
=
dist
*
np
.
cos
(
angle
)
+
radius
-
boxSize
/
2
y
:
float
=
dist
*
np
.
sin
(
angle
)
+
radius
-
boxSize
/
2
return
[
x
,
y
]
np
.
random
.
seed
(
self
.
randomSeed
)
topLefts
:
list
=
[]
boxSize
:
float
=
self
.
boxSize
radius
:
float
=
self
.
filterDiameter
/
2
maxDist
:
float
=
radius
-
np
.
sqrt
((
boxSize
/
2
)
**
2
+
(
boxSize
/
2
)
**
2
)
radius
:
float
=
self
.
filterDiameter
/
2
maxDist
:
float
=
radius
-
np
.
sqrt
((
boxSize
/
2
)
**
2
+
(
boxSize
/
2
)
**
2
)
outerCounter
:
int
=
0
validSolutionFound
:
bool
=
False
...
...
@@ -459,7 +472,7 @@ def determine_max_achievable_frac(method: BoxSelectionSubsamplingMethod, numBoxe
method
.
numBoxes
=
numBoxes
frac
:
float
=
0.0
lastvalidFrac
:
float
=
0.0
for
frac
in
np
.
linspace
(
0.0
5
,
0.6
,
50
):
for
frac
in
np
.
linspace
(
0.0
1
,
0.6
,
50
):
method
.
fraction
=
frac
valid
:
bool
=
False
...
...
@@ -475,4 +488,5 @@ def determine_max_achievable_frac(method: BoxSelectionSubsamplingMethod, numBoxe
method
.
fraction
=
origFrac
method
.
numBoxes
=
origBoxNum
# print(method.label, numBoxes, lastvalidFrac)
return
lastvalidFrac
subsampling.py
View file @
fc238b30
...
...
@@ -12,7 +12,8 @@ SET GEPARD TO EVALUATION BRANCH (WITHOUT THE TILING STUFF), OTHERWISE SOME OF TH
"""
if
__name__
==
'__main__'
:
results
:
TotalResults
=
TotalResults
()
# results: TotalResults = TotalResults()
results
:
TotalResults
=
load_results
(
'results1.res'
)
pklsInFolders
=
get_pkls_from_directory
(
r
'C:\Users\xbrjos\Desktop\temp MP\NewDatasets'
)
for
folder
in
pklsInFolders
.
keys
():
...
...
@@ -26,7 +27,7 @@ if __name__ == '__main__':
print
(
'updating all took'
,
time
.
time
()
-
t0
,
'seconds'
)
save_results
(
'results1.res'
,
results
)
#
results: TotalResults = load_results('results1.res')
results
:
TotalResults
=
load_results
(
'results1.res'
)
plot
:
Figure
=
get_error_vs_frac_plot
(
results
,
attributes
=
[[
'air'
,
'water'
],
[
'sediment'
,
'soil'
,
'beach'
,
'slush'
]],
methods
=
[])
...
...
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