Exemplo n.º 1
0
def test(testsdir, verbose = False):
    idir = os.path.join(testsdir, "input")
    edir = os.path.join(testsdir, "expect")
    statuses = []
    
    ifs = ["input_sed_test1.sed", 
           "input_sed_test2.csv",
           "input_sed_test3.sed"]
    ifs = [os.path.join(idir, f) for f in ifs]
    efs = ["expect_sed_test1.sed", 
           "expect_sed_test2.csv",
           "expect_sed_test3.sed"]
    efs = [os.path.join(edir, f) for f in efs]
    
    
    ins = [SdalReader().read_spectrum(f) for f in ifs]
    expuns = [SdalReader().read_spectrum(f) for f in efs]
    uniquifier = WaveUniquifier()
    prouns = [uniquifier.uniquify(s) for s in ins]
    testcount = 0
    for (e, p) in zip(expuns, prouns):
        testcount = testcount + 1
        statuses.append(np.allclose(e.data, p.data, atol = 0.0001))
        statuses.append(e.idstr == p.idstr)
        statuses.append(e.company == p.company)
        statuses.append(e.instrument == p.instrument)
        if not all(statuses):
            print("Failed TEST 1-{}".format(testcount))
    
    #status message
    if all(statuses):
        print("{}: PASSED".format(__file__))
    else:
        print("{}: FAILED".format(__file__))
Exemplo n.º 2
0
def test(testsdir, verbose=False):
    idir = os.path.join(testsdir, "input")
    edir = os.path.join(testsdir, "expect")
    statuses = []

    ifs = ["input_sed_test1.sed", "input_sed_test2.csv", "input_sed_test3.sed"]
    ifs = [os.path.join(idir, f) for f in ifs]
    efs = [
        "expect_sed_test1.sed", "expect_sed_test2.csv", "expect_sed_test3.sed"
    ]
    efs = [os.path.join(edir, f) for f in efs]

    ins = [SdalReader().read_spectrum(f) for f in ifs]
    expuns = [SdalReader().read_spectrum(f) for f in efs]
    uniquifier = WaveUniquifier()
    prouns = [uniquifier.uniquify(s) for s in ins]
    testcount = 0
    for (e, p) in zip(expuns, prouns):
        testcount = testcount + 1
        statuses.append(np.allclose(e.data, p.data, atol=0.0001))
        statuses.append(e.idstr == p.idstr)
        statuses.append(e.company == p.company)
        statuses.append(e.instrument == p.instrument)
        if not all(statuses):
            print("Failed TEST 1-{}".format(testcount))

    #status message
    if all(statuses):
        print("{}: PASSED".format(__file__))
    else:
        print("{}: FAILED".format(__file__))
Exemplo n.º 3
0
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)
Exemplo n.º 4
0
    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]
Exemplo n.º 5
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__))
Exemplo n.º 6
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__))