#else:
# single_band_output = list()
# for band_sp in spectrum:
# raw = "\t".join([str(f) for f in band_sp['raw']])
# mean = str(band_sp['mean'])
# std_dev = str(band_sp['std_dev'])
# # putting it all together in output text for a single band
# single_band_output.append("\t".join((raw, mean, std_dev)))
# output.append("\t".join([str(x) for x in [plot_id, cp['x'], cp['y']]] + ["\t".join(single_band_output)]))
else:
# checking whether we operate in some nxn-neighborhood
if neighborhood > 1:
single_band_output = list()
for band in good_bands:
raw_output = list()
for suff in general_utils.letter_generator(len(spectrum[0]['raw'])):
raw_output.append("%d_raw_%s" % (band, suff))
single_band_output.append("%s\t%d_mean\t%d_std_dev" % ("\t".join(raw_output), band, band))
#single_band_output.append("%d_raw_a\t%d_raw_b\t%d_raw_c\t%d_raw_d\t%d_mean\t%d_std_dev" % tuple([band] * 6))
output.insert(0, "\t".join((id_field, "x", "y", "\t".join(single_band_output))))
# otherwise the header is much easier to build
#else:
# output.insert(0, "\t".join((id_field, "x", "y", "\t".join([str(k) for k in good_bands]))))
if neighborhood > 1:
tgt_file = tgt_file.replace(".txt", "_%dx%d.txt" % tuple([neighborhood] * 2))
tgt_path = os.path.join(tgt_dir, tgt_file)
open(tgt_path, 'wb').write("\n".join(output))
def dump_spectra(self, include_bad_bands=True, include_raw_data=True):
u"""
Prepare output of extracted spectra data to an external file.
"""
if not self.spectra:
return
# initializing output array
output = list()
# determining output bands
if include_bad_bands:
output_bands = sorted(self.bad_bands + self.good_bands)
else:
output_bands = self.good_bands
# if there is more than one source image, we'll include the origin of the
# current spectra
if len(self.image_data) > 1:
include_spectra_source = True
else:
include_spectra_source = False
# iterating over all spectra and adding them to output
for sp in sorted(self.spectra, key=attrgetter("id")):
output.append(sp.__str__(include_bad_bands, include_spectra_source, include_raw_data))
# finally adding a header line
header_items = [self.roi_id, "img_id", "x", "y"]
if len(self.image_data) == 1:
header_items.remove("img_id")
tmp_sp = self.spectra[0]
if len(tmp_sp.attributes) > 0:
for attr in sorted(tmp_sp.attributes.keys()):
header_items.append(attr)
if self.context_type == "circle":
header_items.append("count")
if self.context_range > 1:
single_band_output = list()
for band in output_bands:
if band in self.good_bands:
raw_output = list()
if self.context_type == "square":
for suff in general_utils.letter_generator(self.context_range * self.context_range):
raw_output.append("%d_raw_%s" % (band, suff))
elif self.context_type == "circle":
raw_output.append("\t".join(("%d_min" % band, "%d_max" % band)))
single_band_output.append("%s\t%d_mean\t%d_std_dev" % ("\t".join(raw_output), band, band))
else:
single_band_output.append(str(band))
header_items.append("\t".join(single_band_output))
# output.insert(0, "\t".join((self.loc_id_field, "img_id", "x", "y", "\t".join(single_band_output))))
else:
header_items.append("\t".join([str(k) for k in output_bands]))
# output.insert(0, "\t".join((self.loc_id_field, "img_id", "x", "y", "\t".join([str(k) for k in output_bands]))))
output.insert(0, "\t".join(header_items))
# defining target file path
self.tgt_path = os.path.join(self.tgt_dir, self.tgt_file)
print "+ Dumping spectra to external file '%s'..." % self.tgt_path
# writing result to specified output file path
open(self.tgt_path, "wb").write("\n".join(output))
def dump_spectra(self, include_bad_bands=True, include_raw_data=True):
u"""
Prepare output of extracted spectra data to an external file.
"""
# initializing output array
output = list()
# determining output bands
if include_bad_bands:
output_bands = sorted(self.bad_bands + self.good_bands)
else:
output_bands = self.good_bands
# if there is more than on source image, we'll include the origin of the
# current spectra
if len(self.image_data) > 1:
include_spectra_source = True
else:
include_spectra_source = False
# iterating over all spectra and adding them to output
for sp in sorted(self.spectra, key=attrgetter('id')):
output.append(
sp.__str__(include_bad_bands, include_spectra_source,
include_raw_data))
# finally adding a header line
header_items = [self.loc_id_field, "img_id", "x", "y"]
if len(self.image_data) == 1:
header_items.remove("img_id")
if self.spectra:
tmp_sp = self.spectra[0]
if len(tmp_sp.attributes) > 0:
for attr in sorted(tmp_sp.attributes.keys()):
header_items.append(attr)
if self.neighborhood_type == 'circle':
header_items.append("count")
if self.neighborhood > 1:
single_band_output = list()
for band in output_bands:
if band in self.good_bands:
raw_output = list()
if self.neighborhood_type == 'square':
for suff in general_utils.letter_generator(
self.neighborhood * self.neighborhood):
raw_output.append("%d_raw_%s" % (band, suff))
elif self.neighborhood_type == 'circle':
raw_output.append("\t".join(
("%d_min" % band, "%d_max" % band)))
single_band_output.append(
"%s\t%d_mean\t%d_std_dev" %
("\t".join(raw_output), band, band))
else:
single_band_output.append(str(band))
header_items.append("\t".join(single_band_output))
#output.insert(0, "\t".join((self.loc_id_field, "img_id", "x", "y", "\t".join(single_band_output))))
else:
header_items.append("\t".join([str(k) for k in output_bands]))
#output.insert(0, "\t".join((self.loc_id_field, "img_id", "x", "y", "\t".join([str(k) for k in output_bands]))))
output.insert(0, "\t".join(header_items))
# defining target file path
self.tgt_path = os.path.join(self.tgt_dir, self.tgt_file)
print "+ Dumping spectra to external file '%s'..." % self.tgt_path
# writing result to specified output file path
open(self.tgt_path, 'wb').write("\n".join(output))
