def process(self, spectrum_list):
proc_list = []
for s in spectrum_list:
wr = WaveResampler(rstype = self._interpolation,
wavestart = float(math.ceil(s.wavelengths[0])),
wavestop = float(math.floor(s.wavelengths[-1])),
spacing = 1.0)
proc_list.append(wr.resample(s))
return proc_list
def process(self, spectrum_list):
proc_list = []
for s in spectrum_list:
wr = WaveResampler(rstype=self._interpolation,
wavestart=float(math.ceil(s.wavelengths[0])),
wavestop=float(math.floor(s.wavelengths[-1])),
spacing=1.0)
proc_list.append(wr.resample(s))
return proc_list
def process(params):
# params.print_params()
#get the project params and verify
project = params.get_params("project")
if project:
verify_project(project)
else:
print("--project is required")
sys.exit(0)
#get the resampling params
resampling = params.get_params("resampling")
#get the jumpcorrection params and verify
jumpcorrection = params.get_params("jumpcorrection")
if jumpcorrection:
verify_jumpcorrection(jumpcorrection)
#get the groupings and verify them
groupings = {grp:params.get_params(grp) for grp in params.get_groups()}
verify_groupings(params.default_group, params.get_groups(), groupings)
tags = ["raw", params.default_group]
specs = defaultdict(list)
#specs["raw"] created
#get the filenames
allfiles = os.listdir(project["indir"])
extfiles = []
for f in allfiles:
ext = get_directory_filename_extension(f)[2]
if ext == project["fileext"]:
extfiles.append(os.path.join(project["indir"], f))
#read the raw spectrums
uniquifier = WaveUniquifier()
rawspecs = [SdalReader().read_spectrum(f) for f in extfiles]
uniqspecs = [uniquifier.uniquify(s) for s in rawspecs]
specs["raw"] = uniqspecs
#specs["preproc"] created
#do the pre-processing
prepspecs = specs["raw"]
if resampling:
resampler = WaveResampler(rstype = resampling["type"],
wavestart = resampling["range"][0],
wavestop = resampling["range"][1],
spacing = resampling["spacing"])
rsspecs = [resampler.resample(s) for s in prepspecs]
prepspecs = rsspecs
if jumpcorrection:
corrector = JumpCorrector(jumpcorrection["wavelengths"],
jumpcorrection["stablezone"])
jcspecs = [corrector.correct(s) for s in prepspecs]
prepspecs = jcspecs
#detect the references
refdet = ReferenceDetector(context = "gveg")
nonrefs = []
refs = []
for s in prepspecs:
if refdet.is_reference(s):
refs.append(s)
else:
nonrefs.append(s)
specs[params.default_group] = nonrefs
#specs[group_tag] created
#do the grouping
for t in groupings:
tags.append(t)
itag = groupings[t]["intag"]
patt = groupings[t]["pattern"]
regex = SpectrumRegex()
tgrps = regex.make_groups(specs[itag], patt)
for tg in tgrps:
sg = SpectrumGroup(spectrums = tgrps[tg])
ms = sg.mean_spectrum()
ms.idstr = tg
specs[t].append(ms)
# subsets = {grp:params.get_params(grp) for grp in params.get_subsets()}
# print(subsets)
# for t in subsets:
# itag = subsets[t]["intag"]
# otag = subsets[t]["outtag"]
# wavestart = subsets[t]["range"][0]
# wavestop = subsets[t]["range"][1]
# for s in specs[itag]:
# subspec = s.wavelength_subset(wavestart, wavestop)
# subspec.idstr = subspec.idstr + otag
# print("idstr = {}".format(subspec.idstr))
# specs[otag].append(subspec)
#create outputs
prjdir = os.path.join(project["outdir"], project["name"])
os.mkdir(prjdir)
for t in specs:
tdir = os.path.join(prjdir, t)
os.mkdir(tdir)
tgrpfn = "___{}___.csv".format(t)
for s in specs[t]:
s.write_csv(odir = tdir)
sg = SpectrumGroup(spectrums = specs[t])
sg.write_csv(tdir, tgrpfn)
def process_overlap(self, spec):
#find the forward difference for the wavelengths
diffs = np.diff(spec.wavelengths)
#find where the wavelength differences are negative
idxs = np.nonzero(diffs <= -0.05)[0]
idxs = idxs + 1
idxs = np.hstack((np.array([0]), idxs, np.size(spec.wavelengths)))
#create pieces os spectrums with increasing wavelengths
pcs = []
data = spec.data
uniquifier = WaveUniquifier()
for k in range(1, len(idxs)):
i1 = idxs[k - 1]
i2 = idxs[k]
s = Spectrum(data = data[i1:i2, :],
idstr = spec.idstr,
company = spec.company,
instrument = spec.instrument)
pcs.append(uniquifier.uniquify(s))
#resample the pieces into 1 nm wavelengths
rspcs = []
resampler = WaveResampler()
for s in pcs:
wr = s.wavelength_range()
start = math.ceil(wr[0])
stop = math.floor(wr[1])
resampler = WaveResampler(rstype = self._rstype,
wavestart = start,
wavestop = stop,
spacing = 1.0)
rspcs.append(resampler.resample(s))
# print(rspcs[-1].wavelengths[0], rspcs[-1].wavelengths[-1])
# print("------------------------")
#chop and stitch
if len(rspcs) > 1:
#find the wavelengths to chop at
critwaves = [rspcs[0].wavelengths[0]]
for i in range(1, len(rspcs)):
#find the overlapping indices
lstart, lstop, rstart, rstop = -1, -1, -1, -1
rstart = 0
lstart = closest_array_index(rspcs[i].wavelengths[0],
rspcs[i - 1].wavelengths)
lstop = len(rspcs[i - 1].wavelengths)
rstop = closest_array_index(rspcs[i - 1].wavelengths[-1],
rspcs[i].wavelengths) + 1
lrefls = rspcs[i - 1].reflectances[lstart:lstop]
rrefls = rspcs[i].reflectances[rstart:rstop]
lwaves = rspcs[i - 1].wavelengths[lstart:lstop]
critwaves.append(lwaves[np.argmin(np.abs(lrefls - rrefls))])
critwaves.append(rspcs[-1].wavelengths[-1])
# print("critwaves = {}".format(critwaves))
subdms = []
for i in range(len(rspcs)):
start = closest_array_index(critwaves[i],
rspcs[i].wavelengths)
stop = closest_array_index(critwaves[i + 1],
rspcs[i].wavelengths) + 1
subdms.append(rspcs[i].data[start:stop, :])
# print(rspcs[i].data[start:stop, :])
# print("========================")
return uniquifier.uniquify(Spectrum(data = np.vstack(tuple(subdms)),
idstr = spec.idstr,
company = spec.company,
instrument = spec.instrument))
else:
return rspcs[0]
def test(testsdir, verbose = False):
idir = os.path.join(testsdir, "input")
edir = os.path.join(testsdir, "expect")
statuses = []
#TEST 1:
#resampling sig data
#--create filenames
ifs = ["input_sig_test1.sig",
"input_sig_test2.sig",
"input_sig_test3.sig"]
ifs = [os.path.join(idir, f) for f in ifs]
efs = ["expect_sig_test1.sig",
"expect_sig_test2.sig",
"expect_sig_test3.sig"]
efs = [os.path.join(edir, f) for f in efs]
#--load the spectrums
ins = [SdalReader().read_spectrum(f) for f in ifs]
uniquifier = WaveUniquifier()
ins = [uniquifier.uniquify(s) for s in ins]
exs = [SdalReader().read_spectrum(f) for f in efs]
#--resample the input spectrums
wavestart = 350.0
wavestop = 2500.0
resampler = WaveResampler(rstype = "linear",
wavestart = wavestart,
wavestop = wavestop,
spacing = 1.0)
inrs = [resampler.resample(s) for s in ins]
#--subset input resampled and expect spectrums
subexs = [s.wavelength_subset(wavestart, wavestop) for s in exs]
#--do the comparisons
testcount = 0
for (si, se) in zip(inrs, subexs):
testcount = testcount + 1
statuses.append(np.allclose(si.data, se.data, atol = 0.001))
if not all(statuses):
print("Failed TEST 1-{}".format(testcount))
#TEST 2:
#resampling sed data
#--create filenames
ifs = ["input_sed_test1.sed",
"input_sed_test2.sed",
"input_sed_test3.sed"]
ifs = [os.path.join(idir, f) for f in ifs]
efs = ["expect_sed_test1.sed",
"expect_sed_test2.sed",
"expect_sed_test3.sed"]
efs = [os.path.join(edir, f) for f in efs]
#--load the spectrums
ins = [SdalReader().read_spectrum(f) for f in ifs]
uniquifier = WaveUniquifier()
ins = [uniquifier.uniquify(s) for s in ins]
exs = [SdalReader().read_spectrum(f) for f in efs]
#--resample the input spectrums
wavestart = 350.0
wavestop = 2500.0
resampler = WaveResampler(rstype = "cubic",
wavestart = wavestart,
wavestop = wavestop,
spacing = 1.0)
inrs = [resampler.resample(s) for s in ins]
#--subset input resampled and expect spectrums
subexs = [s.wavelength_subset(wavestart, wavestop) for s in exs]
#--do the comparisons
testcount = 0
for (si, se) in zip(inrs, subexs):
testcount = testcount + 1
statuses.append(np.allclose(si.data, se.data, atol = 0.01))
if not all(statuses):
print("Failed TEST 2-{}".format(testcount))
#TEST : 3
#resampling sig data
#--create filenames
ifs = ["input_sig_test1.sig",
"input_sig_test2.sig",
"input_sig_test3.sig"]
ifs = [os.path.join(idir, f) for f in ifs]
#--load the spectrums
ins = [SdalReader().read_spectrum(f) for f in ifs]
uniquifier = WaveUniquifier()
ins = [uniquifier.uniquify(s) for s in ins]
#--resample the input spectrums
resampler = WaveResampler(rstype = "linear",
wavestart = 338.0,
wavestop = 2500.0,
spacing = 2.0)
inrs = [resampler.resample(s) for s in ins]
#status message
if all(statuses):
print("{}: PASSED".format(__file__))
else:
print("{}: FAILED".format(__file__))
def test(testsdir, verbose=False):
idir = os.path.join(testsdir, "input")
edir = os.path.join(testsdir, "expect")
statuses = []
#TEST 1:
#resampling sig data
#--create filenames
ifs = ["input_sig_test1.sig", "input_sig_test2.sig", "input_sig_test3.sig"]
ifs = [os.path.join(idir, f) for f in ifs]
efs = [
"expect_sig_test1.sig", "expect_sig_test2.sig", "expect_sig_test3.sig"
]
efs = [os.path.join(edir, f) for f in efs]
#--load the spectrums
ins = [SdalReader().read_spectrum(f) for f in ifs]
uniquifier = WaveUniquifier()
ins = [uniquifier.uniquify(s) for s in ins]
exs = [SdalReader().read_spectrum(f) for f in efs]
#--resample the input spectrums
wavestart = 350.0
wavestop = 2500.0
resampler = WaveResampler(rstype="linear",
wavestart=wavestart,
wavestop=wavestop,
spacing=1.0)
inrs = [resampler.resample(s) for s in ins]
#--subset input resampled and expect spectrums
subexs = [s.wavelength_subset(wavestart, wavestop) for s in exs]
#--do the comparisons
testcount = 0
for (si, se) in zip(inrs, subexs):
testcount = testcount + 1
statuses.append(np.allclose(si.data, se.data, atol=0.001))
if not all(statuses):
print("Failed TEST 1-{}".format(testcount))
#TEST 2:
#resampling sed data
#--create filenames
ifs = ["input_sed_test1.sed", "input_sed_test2.sed", "input_sed_test3.sed"]
ifs = [os.path.join(idir, f) for f in ifs]
efs = [
"expect_sed_test1.sed", "expect_sed_test2.sed", "expect_sed_test3.sed"
]
efs = [os.path.join(edir, f) for f in efs]
#--load the spectrums
ins = [SdalReader().read_spectrum(f) for f in ifs]
uniquifier = WaveUniquifier()
ins = [uniquifier.uniquify(s) for s in ins]
exs = [SdalReader().read_spectrum(f) for f in efs]
#--resample the input spectrums
wavestart = 350.0
wavestop = 2500.0
resampler = WaveResampler(rstype="cubic",
wavestart=wavestart,
wavestop=wavestop,
spacing=1.0)
inrs = [resampler.resample(s) for s in ins]
#--subset input resampled and expect spectrums
subexs = [s.wavelength_subset(wavestart, wavestop) for s in exs]
#--do the comparisons
testcount = 0
for (si, se) in zip(inrs, subexs):
testcount = testcount + 1
statuses.append(np.allclose(si.data, se.data, atol=0.01))
if not all(statuses):
print("Failed TEST 2-{}".format(testcount))
#TEST : 3
#resampling sig data
#--create filenames
ifs = ["input_sig_test1.sig", "input_sig_test2.sig", "input_sig_test3.sig"]
ifs = [os.path.join(idir, f) for f in ifs]
#--load the spectrums
ins = [SdalReader().read_spectrum(f) for f in ifs]
uniquifier = WaveUniquifier()
ins = [uniquifier.uniquify(s) for s in ins]
#--resample the input spectrums
resampler = WaveResampler(rstype="linear",
wavestart=338.0,
wavestop=2500.0,
spacing=2.0)
inrs = [resampler.resample(s) for s in ins]
#status message
if all(statuses):
print("{}: PASSED".format(__file__))
else:
print("{}: FAILED".format(__file__))
