Add some descriptor scripts for enrichment tests

This commit is contained in:
Florent Guiotte 2018-08-28 16:04:37 +02:00
parent 2370a79b21
commit eb6a39896c
6 changed files with 270 additions and 0 deletions

34
Descriptors/dfc_base.py Normal file
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#!/usr/bin/python
# -*- coding: utf-8 -*-
# \file dfc_base.py
# \brief TODO
# \author Florent Guiotte <florent.guiotte@gmail.com>
# \version 0.1
# \date 27 août 2018
#
# TODO details
import numpy as np
import sys
sys.path.append('..')
import ld2dap
def run(rasters, treshold=1e4):
# Parse parameters type
treshold = float(treshold)
# Pipelines
loader = ld2dap.LoadTIFF(rasters)
dfc_filter = ld2dap.Treshold(treshold)
dfc_filter.input = loader
out_vectors = ld2dap.RawOutput()
out_vectors.input = dfc_filter
# Compute vectors
out_vectors.run()
return out_vectors.data
def version():
return 'v0.0'

41
Descriptors/dfc_daps.py Normal file
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#!/usr/bin/python
# -*- coding: utf-8 -*-
# \file dfc_daps.py
# \brief TODO
# \author Florent Guiotte <florent.guiotte@gmail.com>
# \version 0.1
# \date 27 août 2018
#
# TODO details
import numpy as np
import sys
sys.path.append('..')
import ld2dap
def run(rasters, treshold=1e4, areas=None, sd=None, moi=None):
# Parse parameters type
treshold = float(treshold)
areas = None if areas is None else np.array(areas).astype(np.float).astype(np.int)
sd = None if sd is None else np.array(sd).astype(np.float)
moi = None if moi is None else np.array(moi).astype(np.float)
# Pipelines
loader = ld2dap.LoadTIFF(rasters)
dfc_filter = ld2dap.Treshold(treshold)
dfc_filter.input = loader
aps = ld2dap.AttributeProfiles(area=areas, sd=sd, moi=moi)
aps.input = dfc_filter
differential = ld2dap.Differential()
differential.input = aps
out_vectors = ld2dap.RawOutput()
out_vectors.input = differential
# Compute vectors
out_vectors.run()
return out_vectors.data
def version():
return 'v0.0'

41
Descriptors/dfc_dsdaps.py Normal file
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#!/usr/bin/python
# -*- coding: utf-8 -*-
# \file dfc_dsdaps.py
# \brief TODO
# \author Florent Guiotte <florent.guiotte@gmail.com>
# \version 0.1
# \date 28 août 2018
#
# TODO details
import numpy as np
import sys
sys.path.append('..')
import ld2dap
def run(rasters, treshold=1e4, areas=None, sd=None, moi=None):
# Parse parameters type
treshold = float(treshold)
areas = None if areas is None else np.array(areas).astype(np.float).astype(np.int)
sd = None if sd is None else np.array(sd).astype(np.float)
moi = None if moi is None else np.array(moi).astype(np.float)
# Pipelines
loader = ld2dap.LoadTIFF(rasters)
dfc_filter = ld2dap.Treshold(treshold)
dfc_filter.input = loader
sdaps = ld2dap.SelfDualAttributeProfiles(area=areas, sd=sd, moi=moi)
sdaps.input = dfc_filter
differential = ld2dap.Differential()
differential.input = sdaps
out_vectors = ld2dap.RawOutput()
out_vectors.input = differential
# Compute vectors
out_vectors.run()
return out_vectors.data
def version():
return 'v0.0'

57
Descriptors/dfc_lfaps.py Normal file
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#!/usr/bin/python
# -*- coding: utf-8 -*-
# \file dfc_lfaps.py
# \brief TODO
# \author Florent Guiotte <florent.guiotte@gmail.com>
# \version 0.1
# \date 27 août 2018
#
# TODO details
import numpy as np
import sys
sys.path.append('..')
import ld2dap
# TODO: Add param percentile?
dispatcher = {
'mean': np.mean, # Arithmetic mean
'median': np.median, # Median
'average': np.average, # Weighted average (=mean ?)
'std': np.std, # Standard deviation
'var': np.var, # Variance
'amax': np.amax, # Maximum
'amin': np.amin, # Minimum
'ptp': np.ptp, # Range of values (max - min)
}
def run(rasters, treshold=1e4, areas=None, sd=None, moi=None, features=['mean'], patch_size=3):
# Parse parameters type
treshold = float(treshold)
areas = None if areas is None else np.array(areas).astype(np.float).astype(np.int)
sd = None if sd is None else np.array(sd).astype(np.float)
moi = None if moi is None else np.array(moi).astype(np.float)
patch_size = int(patch_size)
features = [dispatcher[x] for x in features]
# Pipelines
loader = ld2dap.LoadTIFF(rasters)
dfc_filter = ld2dap.Treshold(treshold)
dfc_filter.input = loader
aps = ld2dap.AttributeProfiles(area=areas, sd=sd, moi=moi)
aps.input = dfc_filter
local_features = ld2dap.LocalFeatures(features, patch_size)
local_features.input = aps
out_vectors = ld2dap.RawOutput()
out_vectors.input = local_features
# Compute vectors
out_vectors.run()
return out_vectors.data
def version():
return 'v0.0'

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#!/usr/bin/python
# -*- coding: utf-8 -*-
# \file dfc_lfsdaps.py
# \brief TODO
# \author Florent Guiotte <florent.guiotte@gmail.com>
# \version 0.1
# \date 28 août 2018
#
# TODO details
import numpy as np
import sys
sys.path.append('..')
import ld2dap
# TODO: Add param percentile?
dispatcher = {
'mean': np.mean, # Arithmetic mean
'median': np.median, # Median
'average': np.average, # Weighted average (=mean ?)
'std': np.std, # Standard deviation
'var': np.var, # Variance
'amax': np.amax, # Maximum
'amin': np.amin, # Minimum
'ptp': np.ptp, # Range of values (max - min)
}
def run(rasters, treshold=1e4, areas=None, sd=None, moi=None, features=['mean'], patch_size=3):
# Parse parameters type
treshold = float(treshold)
areas = None if areas is None else np.array(areas).astype(np.float).astype(np.int)
sd = None if sd is None else np.array(sd).astype(np.float)
moi = None if moi is None else np.array(moi).astype(np.float)
patch_size = int(patch_size)
features = [dispatcher[x] for x in features]
# Pipelines
loader = ld2dap.LoadTIFF(rasters)
dfc_filter = ld2dap.Treshold(treshold)
dfc_filter.input = loader
sdaps = ld2dap.SelfDualAttributeProfiles(area=areas, sd=sd, moi=moi)
sdaps.input = dfc_filter
local_features = ld2dap.LocalFeatures(features, patch_size)
local_features.input = sdaps
out_vectors = ld2dap.RawOutput()
out_vectors.input = local_features
# Compute vectors
out_vectors.run()
return out_vectors.data
def version():
return 'v0.0'

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Descriptors/dfc_sdaps.py Normal file
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#!/usr/bin/python
# -*- coding: utf-8 -*-
# \file dfc_sdaps.py
# \brief TODO
# \author Florent Guiotte <florent.guiotte@gmail.com>
# \version 0.1
# \date 27 août 2018
#
# TODO details
import numpy as np
import sys
sys.path.append('..')
import ld2dap
def run(rasters, treshold=1e4, areas=None, sd=None, moi=None):
# Parse parameters type
treshold = float(treshold)
areas = None if areas is None else np.array(areas).astype(np.float).astype(np.int)
sd = None if sd is None else np.array(sd).astype(np.float)
moi = None if moi is None else np.array(moi).astype(np.float)
# Pipelines
loader = ld2dap.LoadTIFF(rasters)
dfc_filter = ld2dap.Treshold(treshold)
dfc_filter.input = loader
sdaps = ld2dap.SelfDualAttributeProfiles(area=areas, sd=sd, moi=moi)
sdaps.input = dfc_filter
out_vectors = ld2dap.RawOutput()
out_vectors.input = sdaps
# Compute vectors
out_vectors.run()
return out_vectors.data
def version():
return 'v0.0'