def testRasterScaling(self):
"""Raster layers can be scaled when resampled
This is a test for ticket #52
Native test .asc data has
Population_Jakarta_geographic.asc
ncols 638
nrows 649
cellsize 0.00045228819716044
Population_2010.asc
ncols 5525
nrows 2050
cellsize 0.0083333333333333
Scaling is necessary for raster data that represents density
such as population per km^2
"""
for test_filename in ['Population_Jakarta_geographic.asc',
'Population_2010.asc']:
myRasterPath = ('%s/%s' % (TESTDATA, test_filename))
# Get reference values
R = readSafeLayer(myRasterPath)
R_min_ref, R_max_ref = R.get_extrema()
del R_max_ref
del R_min_ref
native_resolution = R.get_resolution()
# Get the Hazard extents as an array in EPSG:4326
bounding_box = R.get_bounding_box()
# Test for a range of resolutions
for res in [0.02, 0.01, 0.005, 0.002, 0.001, 0.0005, # Coarser
0.0002]: # Finer
# To save time only do two resolutions for the
# large population set
if test_filename.startswith('Population_2010'):
if res > 0.01 or res < 0.005:
break
# Clip the raster to the bbox
extraKeywords = {'resolution': native_resolution}
myRasterLayer = QgsRasterLayer(myRasterPath, 'xxx')
myResult = clipLayer(myRasterLayer, bounding_box, res,
theExtraKeywords=extraKeywords)
R = readSafeLayer(myResult)
A_native = R.get_data(scaling=False)
A_scaled = R.get_data(scaling=True)
sigma = (R.get_resolution()[0] / native_resolution[0]) ** 2
# Compare extrema
expected_scaled_max = sigma * numpy.nanmax(A_native)
msg = ('Resampled raster was not rescaled correctly: '
'max(A_scaled) was %f but expected %f'
% (numpy.nanmax(A_scaled), expected_scaled_max))
# FIXME (Ole): The rtol used to be 1.0e-8 -
# now it has to be 1.0e-6, otherwise we get
# max(A_scaled) was 12083021.000000 but
# expected 12083020.414316
# Is something being rounded to the nearest
# integer?
assert numpy.allclose(expected_scaled_max,
numpy.nanmax(A_scaled),
rtol=1.0e-6, atol=1.0e-8), msg
expected_scaled_min = sigma * numpy.nanmin(A_native)
msg = ('Resampled raster was not rescaled correctly: '
'min(A_scaled) was %f but expected %f'
% (numpy.nanmin(A_scaled), expected_scaled_min))
assert numpy.allclose(expected_scaled_min,
numpy.nanmin(A_scaled),
rtol=1.0e-8, atol=1.0e-12), msg
# Compare elementwise
msg = 'Resampled raster was not rescaled correctly'
assert nanallclose(A_native * sigma, A_scaled,
rtol=1.0e-8, atol=1.0e-8), msg
# Check that it also works with manual scaling
A_manual = R.get_data(scaling=sigma)
msg = 'Resampled raster was not rescaled correctly'
assert nanallclose(A_manual, A_scaled,
rtol=1.0e-8, atol=1.0e-8), msg
# Check that an exception is raised for bad arguments
try:
R.get_data(scaling='bad')
except:
pass
else:
msg = 'String argument should have raised exception'
raise Exception(msg)
try:
R.get_data(scaling='(1, 3)')
except:
pass
else:
msg = 'Tuple argument should have raised exception'
raise Exception(msg)
# Check None option without keyword datatype == 'density'
R.keywords['datatype'] = 'undefined'
A_none = R.get_data(scaling=None)
msg = 'Data should not have changed'
assert nanallclose(A_native, A_none,
rtol=1.0e-12, atol=1.0e-12), msg
# Try with None and density keyword
R.keywords['datatype'] = 'density'
A_none = R.get_data(scaling=None)
msg = 'Resampled raster was not rescaled correctly'
assert nanallclose(A_scaled, A_none,
rtol=1.0e-12, atol=1.0e-12), msg
R.keywords['datatype'] = 'counts'
A_none = R.get_data(scaling=None)
msg = 'Data should not have changed'
assert nanallclose(A_native, A_none,
rtol=1.0e-12, atol=1.0e-12), msg
def testRasterScaling(self):
"""Raster layers can be scaled when resampled
This is a test for ticket #52
Native test .asc data has
Population_Jakarta_geographic.asc
ncols 638
nrows 649
cellsize 0.00045228819716044
Population_2010.asc
ncols 5525
nrows 2050
cellsize 0.0083333333333333
Scaling is necessary for raster data that represents density
such as population per km^2
"""
for myFilename in ['Population_Jakarta_geographic.asc',
'Population_2010.asc']:
myRasterPath = ('%s/%s' % (TESTDATA, myFilename))
# Get reference values
mySafeLayer = readSafeLayer(myRasterPath)
myMinimum, myMaximum = mySafeLayer.get_extrema()
del myMaximum
del myMinimum
myNativeResolution = mySafeLayer.get_resolution()
# Get the Hazard extents as an array in EPSG:4326
myBoundingBox = mySafeLayer.get_bounding_box()
# Test for a range of resolutions
for myResolution in [0.02,
0.01,
0.005,
0.002,
0.001,
0.0005, # Coarser
0.0002]: # Finer
# To save time only do two resolutions for the
# large population set
if myFilename.startswith('Population_2010'):
if myResolution > 0.01 or myResolution < 0.005:
break
# Clip the raster to the bbox
myExtraKeywords = {'resolution': myNativeResolution}
myRasterLayer = QgsRasterLayer(myRasterPath, 'xxx')
myResult = clipLayer(myRasterLayer,
myBoundingBox,
myResolution,
theExtraKeywords=myExtraKeywords)
mySafeLayer = readSafeLayer(myResult)
myNativeData = mySafeLayer.get_data(scaling=False)
myScaledData = mySafeLayer.get_data(scaling=True)
mySigma = (mySafeLayer.get_resolution()[0] /
myNativeResolution[0]) ** 2
# Compare extrema
myExpectedScaledMax = mySigma * numpy.nanmax(myNativeData)
myMessage = ('Resampled raster was not rescaled correctly: '
'max(myScaledData) was %f but expected %f'
% (numpy.nanmax(myScaledData), myExpectedScaledMax))
# FIXME (Ole): The rtol used to be 1.0e-8 -
# now it has to be 1.0e-6, otherwise we get
# max(myScaledData) was 12083021.000000 but
# expected 12083020.414316
# Is something being rounded to the nearest
# integer?
assert numpy.allclose(myExpectedScaledMax,
numpy.nanmax(myScaledData),
rtol=1.0e-6, atol=1.0e-8), myMessage
myExpectedScaledMin = mySigma * numpy.nanmin(myNativeData)
myMessage = ('Resampled raster was not rescaled correctly: '
'min(myScaledData) was %f but expected %f'
% (numpy.nanmin(myScaledData), myExpectedScaledMin))
assert numpy.allclose(myExpectedScaledMin,
numpy.nanmin(myScaledData),
rtol=1.0e-8, atol=1.0e-12), myMessage
# Compare elementwise
myMessage = 'Resampled raster was not rescaled correctly'
assert nanallclose(myNativeData * mySigma, myScaledData,
rtol=1.0e-8, atol=1.0e-8), myMessage
# Check that it also works with manual scaling
myManualData = mySafeLayer.get_data(scaling=mySigma)
myMessage = 'Resampled raster was not rescaled correctly'
assert nanallclose(myManualData, myScaledData,
rtol=1.0e-8, atol=1.0e-8), myMessage
# Check that an exception is raised for bad arguments
try:
mySafeLayer.get_data(scaling='bad')
except:
pass
else:
myMessage = 'String argument should have raised exception'
raise Exception(myMessage)
try:
mySafeLayer.get_data(scaling='(1, 3)')
except:
pass
else:
myMessage = 'Tuple argument should have raised exception'
raise Exception(myMessage)
# Check None option without keyword datatype == 'density'
mySafeLayer.keywords['datatype'] = 'undefined'
myUnscaledData = mySafeLayer.get_data(scaling=None)
myMessage = 'Data should not have changed'
assert nanallclose(myNativeData, myUnscaledData,
rtol=1.0e-12, atol=1.0e-12), myMessage
# Try with None and density keyword
mySafeLayer.keywords['datatype'] = 'density'
myUnscaledData = mySafeLayer.get_data(scaling=None)
myMessage = 'Resampled raster was not rescaled correctly'
assert nanallclose(myScaledData, myUnscaledData,
rtol=1.0e-12, atol=1.0e-12), myMessage
mySafeLayer.keywords['datatype'] = 'counts'
myUnscaledData = mySafeLayer.get_data(scaling=None)
myMessage = 'Data should not have changed'
assert nanallclose(myNativeData, myUnscaledData,
rtol=1.0e-12, atol=1.0e-12), myMessage
