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Josef Brandt
Subsampling
Commits
de30ddf1
Commit
de30ddf1
authored
Apr 09, 2020
by
Josef Brandt
Browse files
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RandomBoxSampling
parent
c070f4ab
Changes
8
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Showing
8 changed files
with
419 additions
and
111 deletions
+419
-111
evaluation.py
evaluation.py
+1
-0
geometricMethods.py
geometricMethods.py
+169
-49
gui/mainView.py
gui/mainView.py
+12
-7
gui/measureModes.py
gui/measureModes.py
+98
-40
methods.py
methods.py
+16
-0
tests/helpers_for_test.py
tests/helpers_for_test.py
+1
-0
tests/test_evaluation.py
tests/test_evaluation.py
+15
-4
tests/test_geometricMethods.py
tests/test_geometricMethods.py
+107
-11
No files found.
evaluation.py
View file @
de30ddf1
...
...
@@ -43,6 +43,7 @@ def get_methods_to_test(dataset: dataset.DataSet, fractions: list = []) -> list:
boxCreator
:
gmeth
.
BoxSelectionCreator
=
gmeth
.
BoxSelectionCreator
(
dataset
)
methods
+=
boxCreator
.
get_crossBoxSubsamplers_for_fraction
(
fraction
)
methods
+=
boxCreator
.
get_spiralBoxSubsamplers_for_fraction
(
fraction
)
methods
+=
boxCreator
.
get_randomBoxSubsamplers_for_fraction
(
fraction
)
# methods.append(cmeth.ChemometricSubsampling(particleContainer, fraction))
return
methods
...
...
geometricMethods.py
View file @
de30ddf1
import
numpy
as
np
from
itertools
import
combinations
from
methods
import
SubsamplingMethod
from
copy
import
deepcopy
import
sys
sys
.
path
.
append
(
"C://Users//xbrjos//Desktop//Python"
)
from
gepard
import
dataset
import
helpers
def
box_overlaps_other_box
(
topLeft1
:
list
,
topLeft2
:
list
,
boxSize
:
float
)
->
bool
:
"""
Returns true if the two specified boxes overlap
:param topLeft1:
:param topLeft2:
:param boxSize:
:return:
"""
return
abs
(
topLeft1
[
0
]
-
topLeft2
[
0
])
<
boxSize
and
abs
(
topLeft1
[
1
]
-
topLeft2
[
1
])
<
boxSize
class
BoxSelectionSubsamplingMethod
(
SubsamplingMethod
):
possibleBoxNumbers
:
list
=
[
7
,
10
,
15
]
def
__init__
(
self
,
*
args
):
super
(
BoxSelectionSubsamplingMethod
,
self
).
__init__
(
*
args
)
self
.
filterDiameter
:
float
=
500
self
.
offset
:
tuple
=
(
0
,
0
)
self
.
numBoxes
:
int
=
1
self
.
maxFractions
:
dict
=
{}
@
property
def
label
(
self
)
->
str
:
...
...
@@ -22,6 +37,16 @@ class BoxSelectionSubsamplingMethod(SubsamplingMethod):
def
filterArea
(
self
)
->
float
:
return
np
.
pi
*
(
self
.
filterDiameter
/
2
)
**
2
@
property
def
boxSize
(
self
)
->
float
:
totalBoxArea
:
float
=
self
.
filterArea
*
self
.
fraction
boxArea
:
float
=
totalBoxArea
/
self
.
numBoxes
return
boxArea
**
0.5
@
property
def
noBoxOverlap
(
self
)
->
bool
:
return
not
self
.
_boxes_are_overlapping
(
self
.
get_topLeft_of_boxes
())
def
apply_subsampling_method
(
self
)
->
list
:
def
distanceToCnt
(
topleft
:
tuple
):
return
abs
(
topleft
[
0
]
-
cntStart
[
0
])
+
abs
(
topleft
[
1
]
-
cntStart
[
1
])
...
...
@@ -55,8 +80,48 @@ class BoxSelectionSubsamplingMethod(SubsamplingMethod):
newTopLefts
.
append
((
topLeft
[
0
]
+
self
.
offset
[
0
],
topLeft
[
1
]
+
self
.
offset
[
1
]))
return
newTopLefts
def
equals
(
self
,
otherMethod
)
->
bool
:
raise
NotImplementedError
def
_boxes_are_overlapping
(
self
,
topLefts
:
list
)
->
bool
:
"""
Calculates if there is any overlap of the boxes
:return:
"""
overlaps
:
bool
=
False
boxSize
=
self
.
boxSize
for
topLeft1
,
topLeft2
in
combinations
(
topLefts
,
2
):
if
box_overlaps_other_box
(
topLeft1
,
topLeft2
,
boxSize
):
overlaps
=
True
break
return
overlaps
def
_get_max_distance_of_box_to_center
(
self
,
boxCenter
:
tuple
,
center
:
tuple
=
(
0
,
0
))
->
float
:
"""
Calculates the maximal distance of all point in a box to the given center
:param boxCenter:
:param center:
:return:
"""
center
=
np
.
array
(
center
)
boxSize
=
self
.
boxSize
coords
:
np
.
ndarray
=
np
.
array
([[
boxCenter
[
0
]
-
0.5
*
boxSize
,
boxCenter
[
1
]
-
0.5
*
boxSize
],
[
boxCenter
[
0
]
+
0.5
*
boxSize
,
boxCenter
[
1
]
-
0.5
*
boxSize
],
[
boxCenter
[
0
]
-
0.5
*
boxSize
,
boxCenter
[
1
]
+
0.5
*
boxSize
],
[
boxCenter
[
0
]
+
0.5
*
boxSize
,
boxCenter
[
1
]
+
0.5
*
boxSize
]])
distances
:
np
.
ndarray
=
np
.
linalg
.
norm
(
coords
-
center
,
axis
=
1
)
return
np
.
max
(
distances
)
def
get_maximum_achievable_fraction
(
self
)
->
float
:
if
len
(
self
.
maxFractions
)
==
0
:
self
.
update_max_fractions
()
if
self
.
numBoxes
not
in
self
.
maxFractions
.
keys
():
self
.
maxFractions
[
self
.
numBoxes
]
=
determine_max_achievable_frac
(
self
,
self
.
numBoxes
)
return
self
.
maxFractions
[
self
.
numBoxes
]
def
update_max_fractions
(
self
)
->
None
:
for
boxNum
in
self
.
possibleBoxNumbers
:
self
.
maxFractions
[
boxNum
]
=
determine_max_achievable_frac
(
self
,
boxNum
)
class
BoxSelectionCreator
(
object
):
...
...
@@ -82,8 +147,7 @@ class BoxSelectionCreator(object):
newBoxSelector
.
offset
=
offset
newBoxSelector
.
numBoxesAcross
=
numBoxesAcross
maxFraction
:
float
=
newBoxSelector
.
get_maximum_achievable_fraction
()
if
desiredFraction
<=
maxFraction
:
if
newBoxSelector
.
config_is_valid
():
crossBoxSubsamplers
.
append
(
newBoxSelector
)
return
crossBoxSubsamplers
...
...
@@ -106,11 +170,24 @@ class BoxSelectionCreator(object):
newBoxSelector
.
offset
=
offset
newBoxSelector
.
numBoxes
=
numBoxes
if
newBoxSelector
.
noBoxOverlap
:
if
newBoxSelector
.
config_is_valid
()
:
spiralBoxSubsamplers
.
append
(
newBoxSelector
)
return
spiralBoxSubsamplers
def
get_randomBoxSubsamplers_for_fraction
(
self
,
desiredFraction
:
float
)
->
list
:
randomBoxSamplers
:
list
=
[]
randomBoxSampler
:
RandomBoxSampling
=
RandomBoxSampling
(
None
,
desiredFraction
)
randomBoxSampler
.
update_max_fractions
()
for
numBoxes
in
randomBoxSampler
.
possibleBoxNumbers
:
randomBoxSampler
.
numBoxes
=
numBoxes
if
randomBoxSampler
.
config_is_valid
():
newSampler
:
RandomBoxSampling
=
deepcopy
(
randomBoxSampler
)
newSampler
.
particleContainer
=
self
.
dataset
.
particleContainer
randomBoxSamplers
.
append
(
newSampler
)
return
randomBoxSamplers
class
CrossBoxSubSampling
(
BoxSelectionSubsamplingMethod
):
def
__init__
(
self
,
particleContainer
,
desiredFraction
:
float
=
0.1
)
->
None
:
...
...
@@ -199,8 +276,6 @@ class CrossBoxSubSampling(BoxSelectionSubsamplingMethod):
class
SpiralBoxSubsampling
(
BoxSelectionSubsamplingMethod
):
possibleBoxNumbers
:
list
=
[
7
,
10
,
15
]
def
__init__
(
self
,
particleContainer
,
desiredFraction
:
float
=
0.1
)
->
None
:
super
(
SpiralBoxSubsampling
,
self
).
__init__
(
particleContainer
,
desiredFraction
)
self
.
numBoxes
=
10
...
...
@@ -209,16 +284,6 @@ class SpiralBoxSubsampling(BoxSelectionSubsamplingMethod):
def
label
(
self
)
->
str
:
return
f
'Boxes SpiralLayout (
{
self
.
numBoxes
}
boxes)'
@
property
def
noBoxOverlap
(
self
)
->
bool
:
return
not
self
.
_boxes_are_overlapping
(
self
.
get_topLeft_of_boxes
())
@
property
def
boxSize
(
self
)
->
float
:
totalBoxArea
:
float
=
self
.
filterArea
*
self
.
fraction
boxArea
:
float
=
totalBoxArea
/
self
.
numBoxes
return
boxArea
**
0.5
@
property
def
spiralSlope
(
self
)
->
float
:
return
self
.
armDistance
/
(
2
*
np
.
pi
)
...
...
@@ -243,8 +308,8 @@ class SpiralBoxSubsampling(BoxSelectionSubsamplingMethod):
topLefts
.
append
(
newPoint
)
theta
+=
boxDistance
/
(
slope
*
np
.
sqrt
(
1
+
theta
**
2
))
boxDistance
*=
1.05
topLefts
=
self
.
_move_and_scale_toplefts
(
topLefts
)
if
len
(
topLefts
)
>
1
:
topLefts
=
self
.
_move_and_scale_toplefts
(
topLefts
)
return
self
.
_apply_offset_to_toplefts
(
topLefts
)
def
equals
(
self
,
otherMethod
)
->
bool
:
...
...
@@ -268,7 +333,7 @@ class SpiralBoxSubsampling(BoxSelectionSubsamplingMethod):
lastBoxCenter
:
tuple
=
(
xCoordsBoxMiddles
[
-
1
],
yCoordsBoxMiddles
[
-
1
])
distanceLastCenter
:
float
=
np
.
linalg
.
norm
(
lastBoxCenter
)
maxDistanceInLastBox
:
float
=
self
.
_get_max_distance_of_box
Center
_to_center
(
lastBoxCenter
)
maxDistanceInLastBox
:
float
=
self
.
_get_max_distance_of_box_to_center
(
lastBoxCenter
)
halfBoxDistance
:
float
=
maxDistanceInLastBox
-
distanceLastCenter
desiredDistanceTotal
:
float
=
self
.
filterDiameter
/
2
desiredDistanceCenter
:
float
=
desiredDistanceTotal
-
halfBoxDistance
...
...
@@ -283,37 +348,92 @@ class SpiralBoxSubsampling(BoxSelectionSubsamplingMethod):
newTopLefts
=
zip
(
np
.
round
(
xCoords
),
np
.
round
(
yCoords
))
return
list
(
tuple
(
newTopLefts
))
def
_get_max_distance_of_boxCenter_to_center
(
self
,
boxCenter
:
tuple
,
center
:
tuple
=
(
0
,
0
))
->
float
:
"""
Calculates the maximal distance of a box to the given center
:param topLeft:
:param boxSize:
:return:
"""
center
=
np
.
array
(
center
)
boxSize
=
self
.
boxSize
coords
:
np
.
ndarray
=
np
.
array
([[
boxCenter
[
0
]
-
0.5
*
boxSize
,
boxCenter
[
1
]
-
0.5
*
boxSize
],
[
boxCenter
[
0
]
+
0.5
*
boxSize
,
boxCenter
[
1
]
-
0.5
*
boxSize
],
[
boxCenter
[
0
]
-
0.5
*
boxSize
,
boxCenter
[
1
]
+
0.5
*
boxSize
],
[
boxCenter
[
0
]
+
0.5
*
boxSize
,
boxCenter
[
1
]
+
0.5
*
boxSize
]])
distances
:
np
.
ndarray
=
np
.
linalg
.
norm
(
coords
-
center
,
axis
=
1
)
return
np
.
max
(
distances
)
def
_get_xy_at_angle
(
self
,
theta
:
float
,
centerXY
:
tuple
=
(
0
,
0
))
->
tuple
:
distance
:
float
=
self
.
spiralSlope
*
theta
return
distance
*
np
.
cos
(
theta
)
+
centerXY
[
0
],
distance
*
np
.
sin
(
theta
)
+
centerXY
[
1
]
def
_boxes_are_overlapping
(
self
,
topLefts
:
list
)
->
bool
:
"""
Calculates if there is any overlap of the boxes
:return:
"""
overlaps
:
bool
=
False
for
topLeft1
,
topLeft2
in
combinations
(
topLefts
,
2
):
if
abs
(
topLeft1
[
0
]
-
topLeft2
[
0
])
<
self
.
boxSize
and
abs
(
topLeft1
[
1
]
-
topLeft2
[
1
])
<
self
.
boxSize
:
overlaps
=
True
break
class
RandomBoxSampling
(
BoxSelectionSubsamplingMethod
):
def
__init__
(
self
,
particleContainer
,
desiredFraction
=
0.1
):
super
(
RandomBoxSampling
,
self
).
__init__
(
particleContainer
,
desiredFraction
)
self
.
numBoxes
:
int
=
10
self
.
maxTries
:
int
=
50
return
overlaps
@
property
def
label
(
self
)
->
str
:
return
f
'Boxes random layout (
{
self
.
numBoxes
}
boxes)'
def
get_topLeft_of_boxes
(
self
)
->
list
:
def
get_random_topleft
()
->
list
:
angle
=
np
.
random
.
rand
()
*
2
*
np
.
pi
dist
=
np
.
random
.
rand
()
*
maxDist
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
)
outerCounter
:
int
=
0
validSolutionFound
:
bool
=
False
while
not
validSolutionFound
and
outerCounter
<
self
.
maxTries
:
topLefts
=
[]
for
i
in
range
(
self
.
numBoxes
):
if
i
==
0
:
topLefts
.
append
(
get_random_topleft
())
else
:
counter
:
int
=
0
while
counter
<
50
:
newTopLeft
:
list
=
get_random_topleft
()
overlaps
:
list
=
[
box_overlaps_other_box
(
newTopLeft
,
topLeft2
,
boxSize
)
for
topLeft2
in
topLefts
]
if
not
True
in
overlaps
:
topLefts
.
append
(
newTopLeft
)
break
counter
+=
1
if
len
(
topLefts
)
==
self
.
numBoxes
:
validSolutionFound
=
True
else
:
outerCounter
+=
1
if
not
validSolutionFound
:
raise
AttributeError
return
topLefts
def
determine_max_achievable_frac
(
method
:
BoxSelectionSubsamplingMethod
,
numBoxes
:
int
)
->
float
:
"""
Takes a boxsampling method and iteratively increases the covered fraction for the given number of boxes.
If boxes start to overlap, the last valid fraction is returned
:param method:
:param numBoxes:
:return:
"""
assert
type
(
method
)
!=
CrossBoxSubSampling
# setting of numBoxes is not possible in that case..
origFrac
:
float
=
method
.
fraction
origBoxNum
:
int
=
method
.
numBoxes
method
.
numBoxes
=
numBoxes
frac
:
float
=
0.0
lastvalidFrac
:
float
=
0.0
for
frac
in
np
.
linspace
(
0.05
,
0.6
,
50
):
method
.
fraction
=
frac
valid
:
bool
=
False
try
:
valid
=
method
.
noBoxOverlap
except
AttributeError
:
valid
=
False
if
valid
:
lastvalidFrac
=
frac
else
:
break
method
.
fraction
=
origFrac
method
.
numBoxes
=
origBoxNum
return
lastvalidFrac
gui/mainView.py
View file @
de30ddf1
...
...
@@ -4,7 +4,7 @@ sys.path.append("C://Users//xbrjos//Desktop//Python")
import
gepard
from
gepard
import
dataset
from
gui.filterView
import
FilterView
from
gui.measureModes
import
MeasureMode
,
CrossBoxMode
,
CrossBoxesControls
,
SpiralBoxMode
from
gui.measureModes
import
*
import
helpers
from
evaluation
import
SubsamplingResult
...
...
@@ -55,10 +55,15 @@ class MainView(QtWidgets.QWidget):
self
.
_switch_to_default_mode
()
def
_add_measure_modes
(
self
)
->
None
:
self
.
measureModes
[
'spiralSelection'
]
=
SpiralBoxMode
(
self
.
filterView
)
self
.
measureModes
[
'crossSelection'
]
=
CrossBoxMode
(
self
.
filterView
)
self
.
modeSelector
.
addItem
(
'spiralSelection'
)
self
.
modeSelector
.
addItem
(
'crossSelection'
)
self
.
measureModes
[
'Spiral Box Selection'
]
=
SpiralBoxMode
(
self
.
filterView
)
self
.
measureModes
[
'Cross Box Selection'
]
=
CrossBoxMode
(
self
.
filterView
)
self
.
measureModes
[
'Random Box Selection'
]
=
RandomBoxMode
(
self
.
filterView
)
self
.
measureModes
[
'Random Particle Selection'
]
=
RandomMeasureMode
(
self
.
filterView
)
self
.
modeSelector
.
addItem
(
'Spiral Box Selection'
)
self
.
modeSelector
.
addItem
(
'Cross Box Selection'
)
self
.
modeSelector
.
addItem
(
'Random Box Selection'
)
self
.
modeSelector
.
addItem
(
'Random Particle Selection'
)
for
mode
in
self
.
measureModes
.
values
():
mode
.
updatedResult
.
connect
(
self
.
infoWidget
.
update_results
)
...
...
@@ -101,8 +106,8 @@ class MainView(QtWidgets.QWidget):
self
.
filterView
.
filter
.
update_filterSize
(
width
,
height
,
diameter
,
(
offsetx
,
offsety
))
for
mode
in
self
.
measureModes
.
values
():
mode
.
boxSelectionM
ethod
.
particleContainer
=
dset
.
particleContainer
mode
.
boxSelectionM
ethod
.
offset
=
(
offsetx
,
offsety
)
mode
.
m
ethod
.
particleContainer
=
dset
.
particleContainer
mode
.
m
ethod
.
offset
=
(
offsetx
,
offsety
)
self
.
filterView
.
update_from_dataset
(
dset
)
self
.
activeMode
.
update_measure_viewItems
()
...
...
gui/measureModes.py
View file @
de30ddf1
from
PyQt5
import
QtCore
,
QtWidgets
from
gui.filterView
import
FilterView
,
MeasureBoxGraphItem
from
geometricMethods
import
BoxSelectionSubsamplingMethod
,
CrossBoxSubSampling
,
SpiralBoxSubsampling
from
methods
import
*
from
geometricMethods
import
*
from
evaluation
import
SubsamplingResult
class
MeasureMode
(
QtCore
.
QObject
):
updatedResult
:
QtCore
.
pyqtSignal
=
QtCore
.
pyqtSignal
(
SubsamplingResult
)
def
__init__
(
self
,
relatedFilterView
:
FilterView
):
def
__init__
(
self
,
relatedFilterView
:
FilterView
)
->
None
:
super
(
MeasureMode
,
self
).
__init__
()
self
.
filterView
:
FilterView
=
relatedFilterView
self
.
uiControls
:
QtWidgets
.
QGroupBox
=
QtWidgets
.
QGroupBox
()
self
.
boxSelectionMethod
:
BoxSelection
SubsamplingMethod
=
None
self
.
subsamplingResult
:
SubsamplingResult
=
SubsamplingResult
(
self
.
boxSelectionM
ethod
)
self
.
method
:
SubsamplingMethod
=
None
self
.
subsamplingResult
:
SubsamplingResult
=
SubsamplingResult
(
self
.
m
ethod
)
self
.
subParticles
:
list
=
[]
def
get_control_groupBox
(
self
)
->
QtWidgets
.
QGroupBox
:
return
self
.
uiControls
def
update_measure_viewItems
(
self
)
->
None
:
raise
NotImplementedError
self
.
method
.
filterDiameter
=
self
.
filterView
.
filter
.
diameter
self
.
method
.
numBoxes
=
self
.
uiControls
.
numBoxesSpinbox
.
value
()
self
.
method
.
fraction
=
self
.
uiControls
.
coverageSpinbox
.
value
()
/
100
topLefts
:
list
=
self
.
method
.
get_topLeft_of_boxes
()
boxSize
=
self
.
method
.
boxSize
self
.
filterView
.
update_measure_boxes
(
topLefts
,
boxSize
)
self
.
send_measuredParticles_to_filterview
()
def
send_measuredParticles_to_filterview
(
self
)
->
None
:
if
self
.
boxSelectionM
ethod
.
particleContainer
is
not
None
:
subParticles
=
self
.
boxSelectionM
ethod
.
apply_subsampling_method
()
self
.
subsamplingResult
.
method
=
self
.
boxSelectionM
ethod
if
self
.
m
ethod
.
particleContainer
is
not
None
:
subParticles
=
self
.
m
ethod
.
apply_subsampling_method
()
self
.
subsamplingResult
.
method
=
self
.
m
ethod
self
.
subsamplingResult
.
reset_results
()
self
.
subsamplingResult
.
add_result
(
self
.
boxSelectionM
ethod
.
particleContainer
.
particles
,
subParticles
)
self
.
subsamplingResult
.
add_result
(
self
.
m
ethod
.
particleContainer
.
particles
,
subParticles
)
self
.
updatedResult
.
emit
(
self
.
subsamplingResult
)
self
.
filterView
.
update_measured_particles
(
subParticles
)
class
RandomMeasureMode
(
MeasureMode
):
updatedResult
:
QtCore
.
pyqtSignal
=
QtCore
.
pyqtSignal
(
SubsamplingResult
)
def
__init__
(
self
,
filterView
:
FilterView
):
super
(
RandomMeasureMode
,
self
).
__init__
(
filterView
)
self
.
method
:
RandomSampling
=
RandomSampling
(
None
)
self
.
uiControls
=
ParticleModeControlGroup
(
self
,
'Random Particle Measurement'
)
def
update_measure_viewItems
(
self
)
->
None
:
self
.
method
.
fraction
=
self
.
uiControls
.
coverageSpinbox
.
value
()
/
100
self
.
filterView
.
update_measure_boxes
([],
0.0
)
self
.
send_measuredParticles_to_filterview
()
class
ParticleModeControlGroup
(
QtWidgets
.
QGroupBox
):
def
__init__
(
self
,
measureModeParent
:
MeasureMode
,
title
:
str
)
->
None
:
super
(
ParticleModeControlGroup
,
self
).
__init__
()
self
.
measureModeParent
=
measureModeParent
self
.
setTitle
(
title
)
layout
=
QtWidgets
.
QHBoxLayout
()
self
.
setLayout
(
layout
)
layout
.
addWidget
(
QtWidgets
.
QLabel
(
'Desired Coverage (%)'
))
self
.
coverageSpinbox
=
QtWidgets
.
QSpinBox
()
self
.
coverageSpinbox
.
setFixedWidth
(
50
)
self
.
coverageSpinbox
.
setMinimum
(
0
)
self
.
coverageSpinbox
.
setMaximum
(
100
)
self
.
coverageSpinbox
.
setValue
(
10
)
self
.
coverageSpinbox
.
valueChanged
.
connect
(
self
.
_config_changed
)
layout
.
addWidget
(
self
.
coverageSpinbox
)
def
_config_changed
(
self
)
->
None
:
self
.
measureModeParent
.
update_measure_viewItems
()
class
CrossBoxMode
(
MeasureMode
):
def
__init__
(
self
,
*
args
):
super
(
CrossBoxMode
,
self
).
__init__
(
*
args
)
self
.
uiControls
=
CrossBoxesControls
(
self
)
self
.
boxSelectionM
ethod
:
CrossBoxSubSampling
=
CrossBoxSubSampling
(
None
)
self
.
m
ethod
:
CrossBoxSubSampling
=
CrossBoxSubSampling
(
None
)
self
.
update_measure_viewItems
()
def
update_measure_viewItems
(
self
)
->
None
:
self
.
boxSelectionM
ethod
.
filterDiameter
=
self
.
filterView
.
filter
.
diameter
self
.
boxSelectionM
ethod
.
numBoxesAcross
=
int
(
self
.
uiControls
.
numBoxesSelector
.
currentText
())
self
.
m
ethod
.
filterDiameter
=
self
.
filterView
.
filter
.
diameter
self
.
m
ethod
.
numBoxesAcross
=
int
(
self
.
uiControls
.
numBoxesSelector
.
currentText
())
desiredCoverage
:
int
=
self
.
uiControls
.
coverageSpinbox
.
value
()
maxCoverage
:
int
=
int
(
self
.
boxSelectionM
ethod
.
get_maximum_achievable_fraction
()
*
100
)
maxCoverage
:
int
=
int
(
self
.
m
ethod
.
get_maximum_achievable_fraction
()
*
100
)
self
.
uiControls
.
set_to_max_possible_coverage
(
maxCoverage
)
if
desiredCoverage
>
maxCoverage
:
desiredCoverage
=
maxCoverage
self
.
boxSelectionM
ethod
.
fraction
=
desiredCoverage
/
100
self
.
m
ethod
.
fraction
=
desiredCoverage
/
100
topLefts
:
list
=
self
.
boxSelectionM
ethod
.
get_topLeft_of_boxes
()
boxSize
=
self
.
boxSelectionM
ethod
.
boxSize
topLefts
:
list
=
self
.
m
ethod
.
get_topLeft_of_boxes
()
boxSize
=
self
.
m
ethod
.
boxSize
self
.
filterView
.
update_measure_boxes
(
topLefts
,
boxSize
)
self
.
send_measuredParticles_to_filterview
()
...
...
@@ -96,33 +141,14 @@ class CrossBoxesControls(QtWidgets.QGroupBox):
self
.
coverageSpinbox
.
valueChanged
.
connect
(
self
.
_config_changed
)
class
SpiralBoxMode
(
MeasureMode
):
def
__init__
(
self
,
*
args
):
super
(
SpiralBoxMode
,
self
).
__init__
(
*
args
)
self
.
uiControls
:
SpiralBoxControls
=
SpiralBoxControls
(
self
)
self
.
boxSelectionMethod
:
SpiralBoxSubsampling
=
SpiralBoxSubsampling
(
None
)
self
.
update_measure_viewItems
()
def
update_measure_viewItems
(
self
)
->
None
:
self
.
boxSelectionMethod
.
filterDiameter
=
self
.
filterView
.
filter
.
diameter
self
.
boxSelectionMethod
.
numBoxes
=
self
.
uiControls
.
numBoxesSpinbox
.
value
()
self
.
boxSelectionMethod
.
fraction
=
self
.
uiControls
.
coverageSpinbox
.
value
()
/
100
topLefts
:
list
=
self
.
boxSelectionMethod
.
get_topLeft_of_boxes
()
boxSize
=
self
.
boxSelectionMethod
.
boxSize
self
.
filterView
.
update_measure_boxes
(
topLefts
,
boxSize
)
self
.
send_measuredParticles_to_filterview
()
class
SpiralBoxControls
(
QtWidgets
.
QGroupBox
):
class
BoxControlGroup
(
QtWidgets
.
QGroupBox
):
"""
Gives a groupbox with the controls for setting up the cross boxes.
"""
def
__init__
(
self
,
measureModeParent
:
MeasureMode
)
:
super
(
SpiralBoxControls
,
self
).
__init__
()
self
.
setTitle
(
'Spiral Box Controls'
)
def
__init__
(
self
,
measureModeParent
:
MeasureMode
,
title
:
str
)
->
None
:
super
(
BoxControlGroup
,
self
).
__init__
()
self
.
setTitle
(
title
)
self
.
measureModeParent
=
measureModeParent
layout
=
QtWidgets
.
QHBoxLayout
()
self
.
setLayout
(
layout
)
...
...
@@ -144,6 +170,38 @@ class SpiralBoxControls(QtWidgets.QGroupBox):
self
.
coverageSpinbox
.
valueChanged
.
connect
(
self
.
_config_changed
)
layout
.
addWidget
(
self
.
coverageSpinbox
)
def
_config_changed
(
self
):
def
_config_changed
(
self
)
->
None
:
if
self
.
numBoxesSpinbox
.
value
()
>
0
:
numBoxes
:
int
=
self
.
numBoxesSpinbox
.
value
()
self
.
measureModeParent
.
method
.
numBoxes
=
numBoxes
maxCoverage
:
float
=
self
.
measureModeParent
.
method
.
get_maximum_achievable_fraction
()
self
.
set_to_max_possible_coverage
(
round
(
maxCoverage
*
100
))
self
.
measureModeParent
.
update_measure_viewItems
()
def
set_to_max_possible_coverage
(
self
,
maxCoverage
:
int
)
->
None
:
"""
Adjusts maximum of coverage spinbox and, if necessary, caps the current value.
:param maxCoverage: the maximum pssible converage IN PERCENT!!
:return:
"""
self
.
coverageSpinbox
.
setMaximum
(
maxCoverage
)
if
maxCoverage
<
self
.
coverageSpinbox
.
value
():
self
.
coverageSpinbox
.
valueChanged
.
disconnect
()
self
.
coverageSpinbox
.
setValue
(
maxCoverage
)
self
.
coverageSpinbox
.
valueChanged
.
connect
(
self
.
_config_changed
)
class
SpiralBoxMode
(
MeasureMode
):
def
__init__
(
self
,
*
args
):
super
(
SpiralBoxMode
,
self
).
__init__
(
*
args
)
self
.
uiControls
:
BoxControlGroup
=
BoxControlGroup
(
self
,
'Spiral Box Controls'
)
self
.
method
:
SpiralBoxSubsampling
=
SpiralBoxSubsampling
(
None
)
self
.
update_measure_viewItems
()
class
RandomBoxMode
(
MeasureMode
):
def
__init__
(
self
,
*
args
):
super
(
RandomBoxMode
,
self
).
__init__
(
*
args
)
self
.
uiControls
:
BoxControlGroup
=
BoxControlGroup
(
self
,
'Random Box Controls'
)
self
.
method
:
RandomBoxSampling
=
RandomBoxSampling
(
None
)
self
.
update_measure_viewItems
()
methods.py
View file @
de30ddf1
...
...
@@ -11,6 +11,8 @@ from helpers import ParticleBinSorter
class
SubsamplingMethod
(
object
):
randomSeed
=
15203018
def
__init__
(
self
,
particleConatainer
,
desiredFraction
:
float
=
0.2
):
super
(
SubsamplingMethod
,
self
).
__init__
()
self
.
particleContainer
=
particleConatainer
...
...
@@ -65,6 +67,14 @@ class SubsamplingMethod(object):
matches
=
(
self
.
label
.
lower
().
find
(
pattern
.
lower
())
!=
-
1
)
return
matches
def
config_is_valid
(
self
)
->
bool
:
isValid
:
bool
=
False
if
self
.
fraction
<=
self
.
get_maximum_achievable_fraction
():
isValid
=
True
return
isValid
def
get_maximum_achievable_fraction
(
self
)
->
float
:
raise
NotImplementedError
class
RandomSampling
(
SubsamplingMethod
):
@
property
...
...
@@ -82,6 +92,9 @@ class RandomSampling(SubsamplingMethod):
def
equals
(
self
,
otherMethod
)
->
bool
:
return
type
(
otherMethod
)
==
type
(
self
)
and
otherMethod
.
fraction
==
self
.
fraction
def
get_maximum_achievable_fraction
(
self
)
->
float
:
return
1.0
class
SizeBinFractioning
(
SubsamplingMethod
):
...
...
@@ -117,3 +130,6 @@ class SizeBinFractioning(SubsamplingMethod):
def
equals
(
self
,
otherMethod
)
->
bool
:
return
type
(
otherMethod
)
==
type
(
self
)
and
otherMethod
.
fraction
==
self
.
fraction
def
get_maximum_achievable_fraction
(
self
)
->
float
:
return
1.0
\ No newline at end of file
tests/helpers_for_test.py
View file @
de30ddf1
...
...
@@ -28,3 +28,4 @@ def get_default_ParticleContainer() -> ParticleContainer:
contours
.
append
(
np
.
array
([[[
x
,
0
]],
[[
x
+
10
,
0
]],
[[
x
+
10
,
10
]],
[[
x
,
10
]]],
dtype
=
np
.
int32
))
particleContainer
.
setParticleContours
(
contours
)
return
particleContainer
tests/test_evaluation.py
View file @
de30ddf1
...
...
@@ -258,14 +258,18 @@ class TestSampleResult(unittest.TestCase):
possibleRandomMethods
=
2
possibleCrossBoxMethods
=
2
possibleSpiralBoxMethods
=
3
possibleRandomBoxMethods
=
3
possibleChemometricMethods
=
0
totalPossible
=
possibleCrossBoxMethods
+
possibleRandomMethods
+
\
possibleSpiralBoxMethods
+
possibleChemometricMethods
possibleSpiralBoxMethods
+
possibleChemometricMethods
+
\
possibleRandomBoxMethods