def test_normalize_at_point_seds(self):
sed1 = Sed(
x=numpy.arange(1000, 10001, 500),
y=numpy.arange(1000, 10001, 500),
yerr=numpy.arange(1000, 10001, 500) * 0.01,
)
sed2 = Sed(
x=numpy.arange(10500, 20501, 500),
y=numpy.arange(10500, 20501, 500),
yerr=numpy.arange(10500, 20501, 500) * 0.01,
)
sed3 = Sed(
x=numpy.arange(30000, 40001, 500),
y=numpy.arange(30000, 40001, 500),
yerr=numpy.arange(30000, 40001, 500) * 0.01,
)
aggsed = AggregateSed([sed1, sed2, sed3])
norm_aggsed = aggsed.normalize_at_point(10350, 1)
control_norm_constant = 9.523809523809524e-05 # 1./10500.
self.assertAlmostEqual(norm_aggsed.norm_constant, control_norm_constant)
# The AggregateSed should
# retain all Segments after the normalization, even though
# none of the Segments do not contain the point (10350).
self.assertEqual(len(norm_aggsed), len(aggsed))
norm_aggsed = aggsed.normalize_at_point(10251, 1)
self.assertAlmostEqual(norm_aggsed.norm_constant, 1.0 / 10500)
def test_normalize_at_point_spectra(self):
sed1 = Spectrum(x=numpy.arange(1000, 10001), y=numpy.arange(1000, 10001), yerr=numpy.arange(1000, 10001) * 0.01)
sed2 = Spectrum(
x=numpy.arange(10500, 20501), y=numpy.arange(10500, 20501), yerr=numpy.arange(10500, 20501) * 0.01
)
sed3 = Spectrum(
x=numpy.arange(30000, 40001), y=numpy.arange(30000, 40001), yerr=numpy.arange(30000, 40001) * 0.01
)
aggsed = AggregateSed([sed1, sed2, sed3])
norm_aggsed = aggsed.normalize_at_point(20000, 1, dx=50)
control_norm_constant = 1.0 / 20000.0
self.assertAlmostEqual(norm_aggsed.norm_constant, control_norm_constant)
# The AggregateSed should
# retain all Segments after the normalization, even though
# none of the Segments do not contain the point (10350).
self.assertEqual(len(norm_aggsed), len(aggsed))
def test_normalize_at_point_segments(self):
spec1 = Spectrum(
x=numpy.arange(1000, 10001), y=numpy.arange(1000, 10001), yerr=numpy.arange(1000, 10001) * 0.01
)
spec2 = Spectrum(
x=numpy.arange(10500, 20501), y=numpy.arange(10500, 20501), yerr=numpy.arange(10500, 20501) * 0.01
)
spec3 = Spectrum(
x=numpy.arange(30000, 40001), y=numpy.arange(30000, 40001), yerr=numpy.arange(30000, 40001) * 0.01
)
sed1 = Sed(x=numpy.arange(3000, 11001, 500), y=numpy.arange(300, 1101, 50), yerr=numpy.arange(300, 1101, 50))
sed2 = Sed(
x=numpy.arange(25000, 30001, 500), y=numpy.arange(2500, 3001, 50), yerr=numpy.arange(2500, 3001, 50) * 0.01
)
aggsed = AggregateSed([spec1, spec2, spec3, sed1, sed2])
norm_aggsed = aggsed.normalize_at_point(4505.0, 1000.0, dx=50)
avg = numpy.average(numpy.append(numpy.arange(4456, 4555), [450]))
control_norm_constant = 1000.0 / avg
self.assertAlmostEqual(norm_aggsed.norm_constant, control_norm_constant)
files = os.listdir(test_directory)
specs = []
counter = 0
while counter < 14:
spec = load_sed(test_directory+files[counter], sed_type="spectrum")
specs.append(spec)
counter += 1
#specs = [load_sed(test_directory+f, sed_type="spectrum") for f in files]
for spec in specs:
spec.z = np.random.random_sample()
aggsed = AggregateSed(specs)
norm_aggsed = aggsed.normalize_at_point(3500.0, 1.0)
stack_spectra = stack(norm_aggsed, 10.0, 'avg', fill='fill')
stack_spectra.write(test_directory+'stacked_spectra_maskcc10.dat')
stack_spectra = load_sed(test_directory+'stacked_spectra_maskcc10.dat')
end = time.clock()
plt.plot(stack_.x, stack_.y)
plt.show()
print ''
print 'time it took to do all of this: %.3g sec' % (end-start)
