def retrieve_sample_locations(self, loc_id_field, additional_attributes = []):
u"""
Retrieve sampling locations by using the specified attribute in the
previously defined location data source.
"""
self.loc_id_field = loc_id_field
# handling location data source
self.loc_ds = ogr.Open(self.loc_src)
self.loc_ly = self.loc_ds.GetLayer(0)
# caching locations
self.cached_locations = ogr_utils.cache_locations(self.loc_ly, [self.loc_id_field] + additional_attributes)
self.cached_locations = sorted(self.cached_locations, key = itemgetter('attributes'))
def retrieve_sample_locations(self,
loc_id_field,
additional_attributes=[]):
u"""
Retrieve sampling locations by using the specified attribute in the
previously defined location data source.
"""
self.loc_id_field = loc_id_field
# handling location data source
self.loc_ds = ogr.Open(self.loc_src)
self.loc_ly = self.loc_ds.GetLayer(0)
# caching locations
self.cached_locations = ogr_utils.cache_locations(
self.loc_ly, [self.loc_id_field] + additional_attributes)
self.cached_locations = sorted(self.cached_locations,
key=itemgetter('attributes'))
except:
bad_bands = list()
# building an image data dictionary using strip ids as keys
image_data = dict()
# list of all available strip ids
available_strips = list()
for f in image_data_files:
strip_id = int(re.search("_(\d)_", f).group(1))
available_strips.append(strip_id)
image_data[strip_id] = f
# retrieving plots
plt_ds = ogr.Open(plt_shp_src)
plt_ly = plt_ds.GetLayer(0)
# caching plots
cached_plots = ogr_utils.cache_locations(plt_ly, ['plot_id'])
# setting up output
output = list()
# iterating over a selection of strip ids
for strip_id in available_strips:
# retrieving band count
band_count = gdal_utils.get_band_count(image_data[strip_id])
# retrieving good bands by calculating the difference between all
# bands and those that have been declared bad
good_bands = list(set(range(1, band_count + 1)).difference(bad_bands))
tgt_file = "".join(
(re.search("(.+)_\d_",
os.path.basename(image_data[strip_id])).group(1),
except:
bad_bands = list()
# building an image data dictionary using strip ids as keys
image_data = dict()
# list of all available strip ids
available_strips = list()
for f in image_data_files:
strip_id = int(re.search("_(\d)_", f).group(1))
available_strips.append(strip_id)
image_data[strip_id] = f
# retrieving plots
plt_ds = ogr.Open(plt_shp_src)
plt_ly = plt_ds.GetLayer(0)
# caching plots
cached_plots = ogr_utils.cache_locations(plt_ly, ['plot_id'])
# setting up output
output = list()
# iterating over a selection of strip ids
for strip_id in available_strips:
# retrieving band count
band_count = gdal_utils.get_band_count(image_data[strip_id])
# retrieving good bands by calculating the difference between all
# bands and those that have been declared bad
good_bands = list(set(range(1, band_count + 1)).difference(bad_bands))
tgt_file = "".join((re.search("(.+)_\d_", os.path.basename(image_data[strip_id])).group(1), '_spectra.txt'))
# setting up a list of plots that are linked with the current strip
cov_dir = r"D:\work\ms.monina\wp5\wahner_heide\2011-09-14_apex\coverage"
#cov_dir = r"D:\work\ms.monina\wp5\wahner_heide\2009-08-06_hymap\coverage"
#cov_dir = r"D:\work\ms.monina\wp5\wahner_heide\2011-08-02_worldview\coverage"
plot_id_name = 'plot_id'
plot_id_name = 'pnt_id'
#plot_id_name = 'ID'
#plot_id_name = 'NUMMER'
img_extension = '*.tif'
# reading plots from vector dataset
plt_ds = ogr.Open(plt_src)
plt_ly = plt_ds.GetLayer(0)
# caching plots to prepare raster data extraction
cached_plots = ogr_utils.cache_locations(plt_ly, [plot_id_name])
coverages = dict()
# iterating over all images in coverage directory
for img in glob.glob(os.path.join(cov_dir, img_extension)):
print "+ Checking for plot availability in dataset '%s'..." % os.path.basename(img),
# checking plot coverage for current GeoTiff
cov = check_coverage(img, cached_plots, 2, plot_id_name)
coverages[os.path.basename(img)] = cov
print "Done"
# iterating over all plot ids
for cp in sorted(cached_plots, key = itemgetter('attributes')):
plot_id = cp['attributes'][plot_id_name]
line = list()