def process_directory(params):
#parameters for processing
input_dir = params["input_directory"]
ws = params["subset_wavelength_range"][0]
we = params["subset_wavelength_range"][1]
pattern = params["grouping_pattern"]
patt_name = params['grouping_output_name']
#read the spectrums
extension = {'asd': 1, 'ASD': 1}
spec_files = [
os.path.join(input_dir, f) for f in os.listdir(input_dir)
if get_extension(f) in extension
]
raw_specs = [SdalReader().read_spectrum(f) for f in spec_files]
if len(raw_specs) == 0: return
print("Data directory: {}".format(input_dir))
print(" Read {} {} files".format(len(raw_specs), extension))
#perform jump correction
jumpcorrector = JumpCorrector(params["jumpcorrection_wavelengths"],
params["jumpcorrection_stablezone"])
jc_specs = [jumpcorrector.correct(s) for s in raw_specs]
print(" Jump corrected {} spectrums(s)".format(len(jc_specs)))
#separate into green vegetation and non-green vegetation spectra
gvd = GreenVegDetector()
raw_white_specs, raw_target_specs = [], []
jc_white_specs, jc_target_specs = [], []
ndvis, reflectance_ranges = [], []
for (raw, jc) in zip(raw_specs, jc_specs):
(status, ndvi, reflectance_range) = gvd.is_green_vegetation(jc)
ndvis.append(ndvi)
reflectance_ranges.append(reflectance_range)
if status:
raw_target_specs.append(raw)
jc_target_specs.append(jc)
else:
raw_white_specs.append(raw)
jc_white_specs.append(jc)
print(" # white spectra: {}".format(len(jc_white_specs)))
print(" # target spectra: {}".format(len(jc_target_specs)))
#subset to desired wavelength range
#do this for the jc_target_specs only
proc_target_specs = [s.wavelength_subset(ws, we) for s in jc_target_specs]
print(" Subsetted spectra to range: {}, {}".format(ws, we))
#identify groups using SpectrumRegex and create SpectrumGroup objects
patt_groups = []
grps_dict = SpectrumRegex().make_groups(proc_target_specs, pattern)
patt_groups = [SpectrumGroup().group(grps_dict[k], k) for k in grps_dict]
print(" Grouped spectrums: {} groups".format(len(patt_groups)))
#create output directories and save data
save_data(input_dir, raw_white_specs, raw_target_specs, proc_target_specs,
patt_name, patt_groups)
def process_directory(params):
#parameters for processing
input_dir = params["input_directory"]
ws = params["subset_wavelength_range"][0]
we = params["subset_wavelength_range"][1]
pattern = params["grouping_pattern"]
patt_name = params['grouping_output_name']
#read the spectrums
extension = 'sed'
spec_files = [
os.path.join(input_dir, f) for f in os.listdir(input_dir)
if get_extension(f) == extension
]
raw_specs = [SdalReader().read_spectrum(f) for f in spec_files]
if len(raw_specs) == 0: return
print("Data directory: {}".format(input_dir))
print(" Read {} {} files".format(len(raw_specs), extension))
#uniquify wavelengths, monotone them and interpolate to 1nm
ohr = OverlapHandler(rstype='cubic')
rs_specs = []
for s in raw_specs:
if ohr.is_1nm(s):
rs_specs.append(s)
else:
rs_specs.append(ohr.process_overlap(s))
print(" Uniquified and monotoned spectrums")
#separate into green vegetation and non-green vegetation spectra
gvd = GreenVegDetector()
raw_white_specs, raw_target_specs = [], []
rs_white_specs, rs_target_specs = [], []
ndvis, reflectance_ranges = [], []
for (raw, rs) in zip(raw_specs, rs_specs):
(status, ndvi, reflectance_range) = gvd.is_green_vegetation(rs)
ndvis.append(ndvi)
reflectance_ranges.append(reflectance_range)
if status:
raw_target_specs.append(raw)
rs_target_specs.append(rs)
else:
raw_white_specs.append(raw)
rs_white_specs.append(rs)
print(" # white spectra: {}".format(len(rs_white_specs)))
print(" # target spectra: {}".format(len(rs_target_specs)))
#subset to desired wavelength range
#do this for the jc_target_specs only
proc_target_specs = [s.wavelength_subset(ws, we) for s in rs_target_specs]
print(" Subsetted spectra to range: {}, {}".format(ws, we))
#identify groups using SpectrumRegex and create SpectrumGroup objects
grps_dict = SpectrumRegex().make_groups(proc_target_specs, pattern)
patt_groups = [SpectrumGroup().group(grps_dict[k], k) for k in grps_dict]
print(" Grouped spectrums: {} groups".format(len(patt_groups)))
#create output directories and save data
save_data(input_dir, raw_white_specs, raw_target_specs, proc_target_specs,
patt_name, patt_groups)
def process_directory(params):
#parameters for processing
input_dir = params["input_directory"]
ws = params["subset_wavelength_range"][0]
we = params["subset_wavelength_range"][1]
pattern = params["grouping_pattern"]
patt_name = params['grouping_output_name']
#read the spectrums
extension = 'sig'
spec_files = [os.path.join(input_dir, f) for f in os.listdir(input_dir)
if get_extension(f) == extension]
# for f in spec_files:
# print(f)
raw_specs = [SdalReader().read_spectrum(f) for f in spec_files]
if len(raw_specs) == 0:
return
# print("Data directory: {}".format(input_dir))
# print(" Read {} {} files".format(len(raw_specs), extension))
# for s in raw_specs:
# print(s.idstr)
#uniquify wavelengths and interpolate to 1nm
ohr = OverlapHandler(rstype = 'linear')
rs_specs = []
for s in raw_specs:
if ohr.is_1nm(s):
rs_specs.append(s)
else:
rs_specs.append(ohr.process_overlap(s))
print(" Uniquified and monotoned spectrums")
# for w in rs_specs[0].wavelengths:
# print(w)
#separate into green vegetation and non-green vegetation spectra
gvd = GreenVegDetector()
raw_white_specs, raw_target_specs = [], []
rs_white_specs, rs_target_specs = [], []
ndvis, reflectance_ranges = [], []
for (raw, rs) in zip(raw_specs, rs_specs):
(status, ndvi, reflectance_range) = gvd.is_green_vegetation(rs)
ndvis.append(ndvi)
reflectance_ranges.append(reflectance_range)
if status:
raw_target_specs.append(raw)
rs_target_specs.append(rs)
else:
raw_white_specs.append(raw)
rs_white_specs.append(rs)
print(" # white spectra: {}".format(len(rs_white_specs)))
print(" # target spectra: {}".format(len(rs_target_specs)))
#subset to desired wavelength range
#do this for the jc_target_specs only
proc_target_specs = [s.wavelength_subset(ws, we) for s in rs_target_specs]
print(" Subsetted spectra to range: {}, {}".format(ws, we))
#identify groups using SpectrumRegex and create SpectrumGroup objects
grps_dict = SpectrumRegex().make_groups(proc_target_specs, pattern)
# for k in grps_dict:
# print(k, len(grps_dict[k]))
# SpectrumGroup().group(grps_dict[k], k)
patt_groups = [SpectrumGroup().group(grps_dict[k], k) for k in grps_dict]
print(" Grouped spectrums: {} groups".format(len(patt_groups)))
#create output directories and save data
save_data(input_dir,
raw_white_specs,
raw_target_specs,
proc_target_specs,
patt_name,
patt_groups)
def process_directory(params):
#parameters for processing
input_dir = params["input_directory"]
ws = params["subset_wavelength_range"][0]
we = params["subset_wavelength_range"][1]
pattern = params["grouping_pattern"]
patt_name = params['grouping_output_name']
#read the spectrums
extension = {'asd': 1, 'ASD': 1}
spec_files = [os.path.join(input_dir, f) for f in os.listdir(input_dir)
if get_extension(f) in extension]
raw_specs = [SdalReader().read_spectrum(f) for f in spec_files]
if len(raw_specs) == 0: return
print("Data directory: {}".format(input_dir))
print(" Read {} {} files".format(len(raw_specs), extension))
#perform jump correction
jumpcorrector = JumpCorrector(params["jumpcorrection_wavelengths"],
params["jumpcorrection_stablezone"])
jc_specs = [jumpcorrector.correct(s) for s in raw_specs]
print(" Jump corrected {} spectrums(s)".format(len(jc_specs)))
#separate into green vegetation and non-green vegetation spectra
gvd = GreenVegDetector()
raw_white_specs, raw_target_specs = [], []
jc_white_specs, jc_target_specs = [], []
ndvis, reflectance_ranges = [], []
for (raw, jc) in zip(raw_specs, jc_specs):
(status, ndvi, reflectance_range) = gvd.is_green_vegetation(jc)
ndvis.append(ndvi)
reflectance_ranges.append(reflectance_range)
if status:
raw_target_specs.append(raw)
jc_target_specs.append(jc)
else:
raw_white_specs.append(raw)
jc_white_specs.append(jc)
print(" # white spectra: {}".format(len(jc_white_specs)))
print(" # target spectra: {}".format(len(jc_target_specs)))
#subset to desired wavelength range
#do this for the jc_target_specs only
proc_target_specs = [s.wavelength_subset(ws, we) for s in jc_target_specs]
print(" Subsetted spectra to range: {}, {}".format(ws, we))
#identify groups using SpectrumRegex and create SpectrumGroup objects
patt_groups = []
grps_dict = SpectrumRegex().make_groups(proc_target_specs, pattern)
patt_groups = [SpectrumGroup().group(grps_dict[k], k) for k in grps_dict]
print(" Grouped spectrums: {} groups".format(len(patt_groups)))
#create output directories and save data
save_data(input_dir,
raw_white_specs,
raw_target_specs,
proc_target_specs,
patt_name,
patt_groups)
