def test_spectrum_set_measurement(self):
measurement1 = pd.Series([1, 2, 3, 4], index=pd.Index([1, 2, 3, 4], name='wavelength'),
name='pct_reflect')
measurement2 = pd.Series([3, 0, 1], index=pd.Index([2, 3, 4], name='wavelength'),
name='pct_reflect')
s1 = Spectrum(name='s1', measurement=measurement1)
s2 = Spectrum(name='s2', measurement=measurement2)
def test_collection_data_with_meta(self):
m1 = OrderedDict()
m2 = OrderedDict()
m3 = OrderedDict()
for i, meta in enumerate([m1, m2, m3]):
meta['file'] = 'f{}'.format(i)
meta['instrument_type'] = 'asd'
meta['integration_time'] = '15'
meta['measurement_type'] = 'pct_reflect'
meta['gps_time'] = (100 + i, 200 + i)
meta['wavelength_range'] = (1, 4)
s1 = Spectrum(name='s1',
measurement=pd.Series([1, 2, 3, 4],
index=pd.Index([1, 2, 3, 4],
name='wavelength'),
name='pct_reflect'),
metadata=m1)
s2 = Spectrum(name='s2',
measurement=pd.Series([10, 11, 12, 13],
index=pd.Index([1, 2, 3, 4],
name='wavelength'),
name='pct_reflect'),
metadata=m2)
s3 = Spectrum(name='s3',
measurement=pd.Series([100, 200, 300, 400],
index=pd.Index([1, 2, 3, 4],
name='wavelength'),
name='pct_reflect'),
metadata=m3)
c1 = Collection(name='c1', spectra=[s1, s2, s3])
c1.data_with_meta()
def test_spectrum_read(self):
s1 = Spectrum(name='s1',
filepath='../../../data/aidan_data2/ASD/ACPA_F_A_SU_20160617_00004.asd')
s2 = Spectrum(name='s2',
filepath='../../../data/aidan_data2/PSR/ACPA_F_A_SU_20160617_00002.sed')
s3 = Spectrum(name='s3',
filepath='../../../data/aidan_data2/SVC/ACPA_F_B_SU_20160617_003.sig')
def test_collection_assert_unique_name1(self):
s1 = Spectrum(name='s1',
measurement= pd.Series([1, 2, 3, 4],
index=pd.Index([1, 2, 3, 4],
name='wavelength'),
name='pct_reflect'))
s2 = Spectrum(name='s1',
measurement= pd.Series([1, 2, 3, 4],
index=pd.Index([1, 2, 3, 4],
name='wavelength'),
name='pct_reflect'))
self.assertRaises(AssertionError, Collection, name='c1', spectra=[s1, s2])
def test_collection_assert_unique_name1(self):
s1 = Spectrum(name='s1',
measurement= pd.Series([1, 2, 3, 4],
index=pd.Index([1, 2, 3, 4],
name='wavelength'),
name='pct_reflect'))
s2 = Spectrum(name='s1',
measurement= pd.Series([1, 2, 3, 4],
index=pd.Index([1, 2, 3, 4],
name='wavelength'),
name='pct_reflect'))
c1 = Collection(name='c1')
c1.append(s1)
self.assertRaises(AssertionError, c1.append, s2)
def setUp(self):
# total 36 spectra
self.c = Collection(name='For Groups')
for a in ('A', 'B', 'C'):
for b in ('a', 'b', 'c'):
for c in ('0', '1'):
for d in ('0001', '0002', '0003', '0004'):
self.c.append(Spectrum('_'.join([a, b, c, d])))
def test_collection_data_unstitched(self):
s1 = Spectrum(name='s1',
measurement=pd.Series([1, 2, 3, 4],
index=pd.Index([1, 2, 3, 4],
name='wavelength'),
name='pct_reflect'))
s2 = Spectrum(name='s2',
measurement=pd.Series([10, 11, 12, 13],
index=pd.Index([0.8, 2.2, 3.7, 5],
name='wavelength'),
name='pct_reflect'))
s3 = Spectrum(name='s3',
measurement=pd.Series([100, 200, 300, 400, 500],
index=pd.Index([1, 2, 3, 3, 4],
name='wavelength'),
name='pct_reflect'))
c1 = Collection(name='c1', spectra=[s1, s2, s3])
self.assertRaises(ValueError, lambda: c1.data)
c1.stitch()
def test_spectrum_stitcher_mean(self):
s1 = Spectrum(name='s1',
measurement= pd.Series([100, 200, 300, 400, 500],
index=pd.Index([1, 2, 3, 3, 4],
name='wavelength'),
name='pct_reflect'))
measurement_stitched = pd.Series([100, 200, 350, 500],
index=pd.Index([1, 2, 3, 4],
name='wavelength'),
name='pct_reflect')
s1.stitch()
pdt.assert_series_equal(s1.measurement, measurement_stitched)
def test_proximal_join(self):
s1 = Spectrum(name='s1',
measurement=pd.Series([1, 2, 3, 4],
index=pd.Index([1, 2, 3, 4],
name='wavelength'),
name='pct_reflect'),
metadata={'gps_time_tgt': 1})
s2 = Spectrum(name='s2',
measurement=pd.Series([10, 11, 12, 13],
index=pd.Index([1, 2, 3, 4],
name='wavelength'),
name='pct_reflect'),
metadata={'gps_time_tgt': 5})
s3 = Spectrum(name='s3',
measurement=pd.Series([100, 200, 300, 400],
index=pd.Index([1, 2, 3, 4],
name='wavelength'),
name='pct_reflect'),
metadata={'gps_time_tgt': 10})
base = Collection(name='base', spectra=[s1, s2, s3])
s4 = Spectrum(name='s4',
measurement=pd.Series([1, 2, 3, 4],
index=pd.Index([1, 2, 3, 4],
name='wavelength'),
name='pct_reflect'),
metadata={'gps_time_tgt': 2})
s5 = Spectrum(name='s5',
measurement=pd.Series([10, 11, 12, 13],
index=pd.Index([1, 2, 3, 4],
name='wavelength'),
name='pct_reflect'),
metadata={'gps_time_tgt': 5})
s6 = Spectrum(name='s6',
measurement=pd.Series([100, 200, 300, 400],
index=pd.Index([1, 2, 3, 4],
name='wavelength'),
name='pct_reflect'),
metadata={'gps_time_tgt': 9})
rover = Collection(name='rover', spectra=[s4, s5, s6])
proximal = proximal_join(base, rover)
proximal_df_correct = pd.DataFrame(
{
's4': [1.0, 1.0, 1.0, 1.0],
's5': [1.0, 1.0, 1.0, 1.0],
's6': [1.0, 1.0, 1.0, 1.0]
},
index=pd.Index([1, 2, 3, 4], name='wavelength'))
pdt.assert_frame_equal(proximal.data, proximal_df_correct)
def test_spectrum_read(self):
s1 = Spectrum(name='s1', filepath=ASD_FNAME)
s2 = Spectrum(name='s2', filepath=SED_PSM_FNAME)
s3 = Spectrum(name='s3', filepath=SIG_FNAME)
s4 = Spectrum(name='s4', filepath=PICO_FNAME)