def test_sanity_check_stack(self):
# the average-stacked SED of 6 identical SEDs should just be
# one of the SEDs used in the stack.
seg1 = sed.Spectrum(x=self.x,y=self.y,yerr=self.yerr,z=self.z)
seg2 = sed.Spectrum(x=self.x,y=self.y,yerr=self.yerr,z=self.z)
seg3 = sed.Spectrum(x=self.x,y=self.y,yerr=self.yerr,z=self.z)
seg4 = sed.Spectrum(x=self.x,y=self.y,yerr=self.yerr,z=self.z)
seg5 = sed.Spectrum(x=self.x,y=self.y,yerr=self.yerr,z=self.z)
seg6 = sed.Spectrum(x=self.x,y=self.y,yerr=self.yerr,z=self.z)
segments = [seg1,seg2,seg3,seg4,seg5,seg6]
aggsed = sed.AggregateSed(segments)
bin = seg1.x[1] - seg1.x[0]
stacksed = sed.stack(aggsed, bin, 'avg')
numpy.testing.assert_array_almost_equal(stacksed.y,aggsed.y[0],decimal=6)
self.assertEqual(stacksed[3].y,aggsed.y[0][3])
self.assertEqual(len(stacksed.y), len(aggsed.y[0]))
self.assertEqual(stacksed.counts[0], 6)
stacksed = sed.stack(aggsed, bin, 'wavg')
numpy.testing.assert_array_almost_equal(stacksed.y,aggsed.y[0],decimal=6)
self.assertEqual(stacksed[3].y,aggsed.y[0][3])
stacksed = sed.stack(aggsed, bin, 'sum')
numpy.testing.assert_array_almost_equal(stacksed.y,aggsed.y[0]*6.,decimal=6)
self.assertEqual(stacksed[3].y,aggsed.y[0][3]*6.)
def test_log_binning(self):
aggsed = load_cat(sed_filename, column_map)
stacked_seds = sed.stack(aggsed, 0.2, 'avg', logbin=True)
control_x = 10**numpy.array([3.6,3.8,4.0,4.4,4.6,4.8,5.0,5.4])
control_y = numpy.array([23.63388888888888, 22.751176470588234,
21.614166666666, 20.295,
19.485, 19.0783333333,
18.88, 17.565])
numpy.testing.assert_allclose(stacked_seds.x, control_x)
numpy.testing.assert_allclose(stacked_seds.y, control_y)
def test_stack_one_segment(self):
seg1 = sed.Sed(x=numpy.linspace(1000,10000, num=100),
y=numpy.linspace(1000,10000, num=100)*0.001)
seg2 = sed.Sed(x=numpy.linspace(1000,10000, num=100),
y=numpy.linspace(1000,10000, num=100)*0.001)
seg1.add_segment(seg2)
bin = seg1.x[1] - seg1.x[0]
stackedsed = sed.stack([seg1], bin, 'avg')
self.assertEqual(stackedsed[3].y,seg1[3].y)
self.assertEqual(stackedsed.counts[0],2)
def test_stack_seds(self):
aggsed = load_cat(sed_filename, column_map)
stacked_seds = sed.stack(aggsed, 50, 'avg')
control_x = numpy.array([3823., 4473., 4773.,
5473., 6273., 7623.,
9023., 12473., 21573.,
36023., 45023., 58023.,
80023., 240023.])
control_y = numpy.array([23.9516667, 23.498333333,
23.45166667, 23.071666667,
22.71166667, 22.414,
21.97833333, 21.25,
20.295, 19.61,
19.36, 19.07833333,
18.88, 17.565])
numpy.testing.assert_allclose(stacked_seds.x, control_x)
numpy.testing.assert_allclose(stacked_seds.y, control_y)
stacked_seds = sed.stack(aggsed, 50, 'wavg')
control_x = numpy.array([3823., 4473., 4773.,
5473., 6273., 7623.,
9023., 12473., 21573.,
36023., 45023., 58023.,
80023., 240023.])
control_y = numpy.array([23.9516667, 23.498333333,
23.45166667, 23.071666667,
22.71166667, 22.414,
21.97833333, 21.25,
20.295, 19.61,
19.36, 19.07833333,
18.88, 17.565])
numpy.testing.assert_allclose(stacked_seds.x, control_x)
numpy.testing.assert_allclose(stacked_seds.y, control_y)
def test_stack_list_of_aggregateseds(self):
seg1 = sed.Sed(x=self.x,y=self.y,yerr=self.yerr,z=self.z)
seg2 = sed.Sed(x=self.x,y=self.y,yerr=self.yerr,z=self.z)
seg3 = sed.Sed(x=self.x,y=self.y,yerr=self.yerr,z=self.z)
seg4 = sed.Spectrum(x=self.x,y=self.y,yerr=self.yerr,z=self.z)
seg5 = sed.Spectrum(x=self.x,y=self.y,yerr=self.yerr,z=self.z)
seg6 = sed.Spectrum(x=self.x,y=self.y,yerr=self.yerr,z=self.z)
bin = seg1.x[1] - seg1.x[0]
aggsed = sed.AggregateSed([seg1,seg2,seg3,seg4,seg5,seg6])
stacked_seds = sed.stack([aggsed,aggsed], bin, 'avg')
self.assertEqual(stacked_seds.y[3],aggsed[0].y[3])
numpy.testing.assert_array_almost_equal(stacked_seds.y[0],aggsed[0].y[0],decimal=6)
self.assertEqual(stacked_seds.counts[0], 12)
def test_no_y_errors_avg(self):
seg1 = sed.Spectrum(x=self.x,y=self.y,z=self.z)
seg2 = sed.Spectrum(x=self.x,y=self.y,z=self.z)
seg3 = sed.Spectrum(x=self.x,y=self.y,z=self.z)
seg4 = sed.Spectrum(x=self.x,y=self.y,yerr=self.yerr,z=self.z)
seg5 = sed.Spectrum(x=self.x,y=self.y,yerr=self.yerr,z=self.z)
seg6 = sed.Spectrum(x=self.x,y=self.y,yerr=self.yerr,z=self.z)
segments = [seg1,seg2,seg3,seg4,seg5,seg6]
aggsed = sed.AggregateSed(segments)
bin = seg1.x[1] - seg1.x[0]
stacksed = sed.stack(aggsed, bin, 'avg')
self.assertEqual(stacksed[3].y,aggsed.y[0][3])
numpy.testing.assert_array_almost_equal(stacksed.y,aggsed.y[0],decimal=6)
def test_stack_segments(self):
seg1 = sed.Sed(x=self.x,y=self.y,yerr=self.yerr,z=self.z)
seg2 = sed.Sed(x=self.x,y=self.y,yerr=self.yerr,z=self.z)
seg3 = sed.Sed(x=self.x,y=self.y,yerr=self.yerr,z=self.z)
seg4 = sed.Spectrum(x=self.x,y=self.y,yerr=self.yerr,z=self.z)
seg5 = sed.Spectrum(x=self.x,y=self.y,yerr=self.yerr,z=self.z)
seg6 = sed.Spectrum(x=self.x,y=self.y,yerr=self.yerr,z=self.z)
bin = seg1.x[1] - seg1.x[0]
aggsed = [seg1,seg2,seg3,seg4,seg5,seg6]
stacked_seds = sed.stack(aggsed, bin, 'wavg')
self.assertEqual(stacked_seds.y[3],aggsed[0].y[3])
self.assertEqual(stacked_seds.yerr[3], 0.0) # variance of identical values is 0.0
numpy.testing.assert_array_almost_equal(stacked_seds.y[0],aggsed[0].y[0],decimal=6)
self.assertEqual(stacked_seds.counts[0], 6)
def test_no_y_errors_sum(self):
seg1 = sed.Spectrum(x=self.x,y=self.y,z=self.z)
seg2 = sed.Spectrum(x=self.x,y=self.y,z=self.z)
seg3 = sed.Spectrum(x=self.x,y=self.y,z=self.z)
seg4 = sed.Spectrum(x=self.x,y=self.y,yerr=self.yerr,z=self.z)
seg5 = sed.Spectrum(x=self.x,y=self.y,yerr=self.yerr,z=self.z)
seg6 = sed.Spectrum(x=self.x,y=self.y,yerr=self.yerr,z=self.z)
segments = [seg1,seg2,seg3,seg4,seg5,seg6]
aggsed = sed.AggregateSed(segments)
bin = seg1.x[1] - seg1.x[0]
stacksed = sed.stack(aggsed, bin, 'sum')
stack_sedarray = stacksed._toarray()
numpy.testing.assert_array_almost_equal(stacksed.y,aggsed.y[0]*6.,decimal=6)
self.assertEqual(stacksed[3].y,aggsed.y[0][3]*6.)
self.assertEqual(len(stacksed.xunit), len(stacksed.x))
def test_user_defined_function(self):
seg1 = sed.Spectrum(x=self.x,y=self.y,z=self.z)
seg2 = sed.Spectrum(x=self.x,y=self.y,z=self.z)
seg3 = sed.Spectrum(x=self.x,y=self.y,z=self.z)
segments = [seg1,seg2,seg3]
aggsed = sed.AggregateSed(segments)
bin = seg1.x[1] - seg1.x[0]
def my_average(yarr, yerrarr, nans):
yout = numpy.average(yarr)
yerrarr = numpy.average(yerrarr)
counts = len(yarr)
return yout, yerrarr, counts
stacksed = sed.stack(aggsed, bin, my_average)
self.assertEqual(stacksed.counts[0], 3)
self.assertEqual(stacksed[3].y,aggsed.y[0][3])
def test_no_y_errors_wavg(self):
seg1 = sed.Spectrum(x=self.x,y=self.y,z=self.z)
seg2 = sed.Spectrum(x=self.x,y=self.y,z=self.z)
seg3 = sed.Spectrum(x=self.x,y=self.y,z=self.z)
seg4 = sed.Spectrum(x=self.x,y=self.y,yerr=self.yerr,z=self.z)
seg5 = sed.Spectrum(x=self.x,y=self.y,yerr=self.yerr,z=self.z)
seg6 = sed.Spectrum(x=self.x,y=self.y,yerr=self.yerr,z=self.z)
segments = [seg1,seg2,seg3,seg4,seg5,seg6]
aggsed = sed.AggregateSed(segments)
bin = seg1.x[1] - seg1.x[0]
stacksed = sed.stack(aggsed, bin, 'wavg')
# because there are seds with no y-errors, stack() will
# use 'avg' instead of 'wavg'.
self.assertEqual(stacksed[3].y,aggsed.y[0][3])
self.assertEqual(stacksed[3].yerr,0.0)
numpy.testing.assert_array_almost_equal(stacksed.y,aggsed.y[0],decimal=6)
self.assertEqual(stacksed.counts[0], 6)
#plt.plot(aggsed.x,aggsed.y,'o')
#plt.show()
restframe_aggsed = aggsed.shift(0)
#plt.loglog(restframe_aggsed.x[0],restframe_aggsed.y[0],'o',restframe_aggsed.x[1],restframe_aggsed.y[1],'o',restframe_aggsed.x[2],restframe_aggsed.y[2],'o',restframe_aggsed.x[3],restframe_aggsed.y[3],'o',restframe_aggsed.x[4],restframe_aggsed.y[4],'o',restframe_aggsed.x[5],restframe_aggsed.y[5],'o')
#plt.show()
norm_point_aggsed = restframe_aggsed.normalize_at_point(5000.0, 1e-5, norm_operator=1)
print ''
norm_int_aggsed = restframe_aggsed.normalize_by_int()
plt.plot(restframe_aggsed.x[1],restframe_aggsed.y[1],'ko', norm_point_aggsed.x[1],norm_point_aggsed.y[1],'go', norm_int_aggsed.x[1],norm_int_aggsed.y[1],'ro')
plt.legend(('restframe','norm_at_point','norm_by_int'), fontsize='x-small', loc=2)
plt.show()
start = datetime.datetime.now()
stack_i = stack(norm_int_aggsed, 0.1, 'wavg', fill='remove', logbin=True)
stack_p = stack(norm_point_aggsed, 0.1, 'wavg', fill='remove', logbin=True)
stack_rf = stack(restframe_aggsed, 0.1, 'wavg', fill='remove', logbin=True)
end = datetime.datetime.now()
print(end - start)
plt.loglog(stack_rf.x,stack_rf.y,'ko',stack_p.x,stack_p.y,'go',stack_i.x,stack_i.y,'ro')
plt.legend(('restframe','norm_at_point','norm_by_int'),fontsize='x-small', loc=2)
plt.show()
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)
