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Commit e1fd1b70 authored by Daniel Scheffler's avatar Daniel Scheffler
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Merge branch 'bugfix/fix_issue45_valueerror' into 'master' 

Bugfix/fix issue45 valueerror

Closes #45

See merge request !14
parents db908f4f 42a389e8
Pipeline #15565 passed with stages
in 8 minutes and 42 seconds
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Makefile
View file @ e1fd1b70
......@@ -43,13 +43,12 @@ clean-pyc: ## remove Python file artifacts
find . -name '__pycache__' -exec rm -fr {} +
clean-test: ## remove test and coverage artifacts
## don't include 'coverage erase' lib here because clean-test is also executed during package setup and coverage is
## only a test requirement
rm -fr .tox/
rm -f .coverage
rm -fr .coverage
rm -fr htmlcov/
rm -fr nosetests.html
rm -fr nosetests.xml
coverage erase
lint: ## check style with flake8
flake8 --max-line-length=120 arosics tests > ./tests/linting/flake8.log
......
arosics/Tie_Point_Grid.py
View file @ e1fd1b70
......@@ -562,10 +562,11 @@ class Tie_Point_Grid(object):
def dump_CoRegPoints_table(self, path_out=None):
path_out = path_out if path_out else \
get_generic_outpath(dir_out=self.dir_out, fName_out="CoRegPoints_table_grid%s_ws(%s_%s)__T_%s__R_%s.pkl"
% (self.grid_res, self.COREG_obj.win_size_XY[0],
self.COREG_obj.win_size_XY[1], self.shift.basename,
self.ref.basename))
get_generic_outpath(dir_out=self.dir_out,
fName_out="CoRegPoints_table_grid%s_ws(%s_%s)__T_%s__R_%s.pkl"
% (self.grid_res, self.COREG_obj.win_size_XY[0],
self.COREG_obj.win_size_XY[1], self.shift.basename,
self.ref.basename))
if not self.q:
print('Writing %s ...' % path_out)
self.CoRegPoints_table.to_pickle(path_out)
......@@ -599,8 +600,12 @@ class Tie_Point_Grid(object):
# calculate GCPs
GDF['X_UTM_new'] = GDF.X_UTM + GDF.X_SHIFT_M
GDF['Y_UTM_new'] = GDF.Y_UTM + GDF.Y_SHIFT_M
GDF['GCP'] = GDF.apply(lambda GDF_row: gdal.GCP(GDF_row.X_UTM_new, GDF_row.Y_UTM_new, 0,
GDF_row.X_IM, GDF_row.Y_IM), axis=1)
GDF['GCP'] = GDF.apply(lambda GDF_row: gdal.GCP(GDF_row.X_UTM_new,
GDF_row.Y_UTM_new,
0,
GDF_row.X_IM,
GDF_row.Y_IM),
axis=1)
self.GCPList = GDF.GCP.tolist()
return self.GCPList
......@@ -670,13 +675,21 @@ class Tie_Point_Grid(object):
"'_tiepoints_grid_to_PointShapefile' is deprecated." # TODO delete if other method validated
" 'tiepoints_grid_to_PointShapefile' is much faster."))
GDF = self.CoRegPoints_table
GDF2pass = GDF if not skip_nodata else GDF[GDF[skip_nodata_col] != self.outFillVal]
GDF2pass = \
GDF if not skip_nodata else \
GDF[GDF[skip_nodata_col] != self.outFillVal]
shapely_points = GDF2pass['geometry'].values.tolist()
attr_dicts = [collections.OrderedDict(zip(GDF2pass.columns, GDF2pass.loc[i].values)) for i in GDF2pass.index]
attr_dicts = [collections.OrderedDict(zip(GDF2pass.columns,
GDF2pass.loc[i].values))
for i in GDF2pass.index]
fName_out = "CoRegPoints_grid%s_ws%s.shp" % (self.grid_res, self.COREG_obj.win_size_XY)
fName_out = "CoRegPoints_grid%s_ws%s.shp" \
% (self.grid_res, self.COREG_obj.win_size_XY)
path_out = os.path.join(self.dir_out, fName_out)
write_shp(path_out, shapely_points, prj=self.COREG_obj.shift.prj, attrDict=attr_dicts)
write_shp(path_out,
shapely_points,
prj=self.COREG_obj.shift.prj,
attrDict=attr_dicts)
def to_vectorfield(self, path_out=None, fmt=None, mode='md'):
# type: (str, str, str) -> GeoArray
......@@ -773,7 +786,10 @@ class Tie_Point_Grid(object):
"Kriging__%s__grid%s_ws%s.tif" % (attrName, self.grid_res, self.COREG_obj.win_size_XY)
path_out = get_generic_outpath(dir_out=self.dir_out, fName_out=fName_out)
# add a half pixel grid points are centered on the output pixels
xmin, ymin, xmax, ymax = xmin - grid_res / 2, ymin - grid_res / 2, xmax + grid_res / 2, ymax + grid_res / 2
xmin = xmin - grid_res / 2
# ymin = ymin - grid_res / 2
# xmax = xmax + grid_res / 2
ymax = ymax + grid_res / 2
GeoArray(zvalues,
geotransform=(xmin, grid_res, 0, ymax, 0, -grid_res),
......@@ -944,7 +960,8 @@ class Tie_Point_Refiner(object):
if th_checked:
th_too_strict = count_inliers < ideal_count # True if too less inliers remaining
# calculate new theshold using old increment (but ensure th_new>0 by adjusting increment if needed)
# calculate new theshold using old increment
# (but ensure th_new>0 by adjusting increment if needed)
th_new = 0
while th_new <= 0:
th_new = th + th_substract if th_too_strict else th - th_substract
......@@ -955,27 +972,44 @@ class Tie_Point_Refiner(object):
th_already_checked = th_new in th_checked.keys()
# if yes, decrease increment and recalculate new threshold
th_substract = th_substract if not th_already_checked else th_substract / 2
th_substract = \
th_substract if not th_already_checked else \
th_substract / 2
th = th_new if not th_already_checked else \
(th + th_substract if th_too_strict else th - th_substract)
# RANSAC call
# model_robust, inliers = ransac((src, dst), PolynomialTransform, min_samples=3,
if src_coords.size and est_coords.size:
(th + th_substract if th_too_strict else
th - th_substract)
###############
# RANSAC call #
###############
# model_robust, inliers = ransac((src, dst),
# PolynomialTransform,
# min_samples=3)
if src_coords.size and \
est_coords.size and \
src_coords.shape[0] > 6:
# import here to avoid static TLS ImportError
from skimage.measure import ransac
from skimage.transform import AffineTransform
model_robust, inliers = \
ransac((src_coords, est_coords), AffineTransform,
ransac((src_coords, est_coords),
AffineTransform,
min_samples=6,
residual_threshold=th,
max_trials=2000,
stop_sample_num=int((min_inlier_percentage - self.rs_tolerance) / 100 * src_coords.shape[0]),
stop_sample_num=int(
(min_inlier_percentage - self.rs_tolerance) /
100 * src_coords.shape[0]
),
stop_residuals_sum=int(
(self.rs_max_outlier_percentage - self.rs_tolerance) / 100 * src_coords.shape[0])
(self.rs_max_outlier_percentage - self.rs_tolerance) /
100 * src_coords.shape[0])
)
else:
warnings.warn('RANSAC filtering could not be applied '
'because there were too few tie points to fit a model.')
inliers = np.array([])
break
......@@ -983,30 +1017,41 @@ class Tie_Point_Refiner(object):
th_checked[th] = count_inliers / src_coords.shape[0] * 100
# print(th,'\t', th_checked[th], )
if min_inlier_percentage - self.rs_tolerance < th_checked[th] < min_inlier_percentage + self.rs_tolerance:
if min_inlier_percentage - self.rs_tolerance <\
th_checked[th] <\
min_inlier_percentage + self.rs_tolerance:
# print('in tolerance')
break
if count_iter > self.rs_max_iter or time.time() - time_start > self.rs_timeout:
if count_iter > self.rs_max_iter or \
time.time() - time_start > self.rs_timeout:
break # keep last values and break while loop
count_iter += 1
outliers = inliers.__eq__(False) if inliers is not None and inliers.size else np.array([])
if inGDF.empty or outliers is None or (isinstance(outliers, list) and not outliers) or \
if inGDF.empty or outliers is None or \
(isinstance(outliers, list) and not outliers) or \
(isinstance(outliers, np.ndarray) and not outliers.size):
outseries = Series([False] * len(self.GDF))
elif len(inGDF) < len(self.GDF):
inGDF['outliers'] = outliers
fullGDF = GeoDataFrame(self.GDF['POINT_ID'])
fullGDF = fullGDF.merge(inGDF[['POINT_ID', 'outliers']], on='POINT_ID', how="outer")
fullGDF = fullGDF.merge(inGDF[['POINT_ID', 'outliers']],
on='POINT_ID',
how="outer")
# fullGDF.outliers.copy()[~fullGDF.POINT_ID.isin(GDF.POINT_ID)] = False
fullGDF = fullGDF.fillna(False) # NaNs are due to exclude_previous_outliers
outseries = fullGDF['outliers']
else:
outseries = Series(outliers)
assert len(outseries) == len(self.GDF), 'RANSAC output validation failed.'
assert len(outseries) == len(self.GDF), \
'RANSAC output validation failed.'
self.ransac_model_robust = model_robust
......
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