Update docs

docs/_helpers/bandpass_page.py

@@ -10,8 +10,8 @@
 ASCII_LETTERS = 'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ'
 
 bandpass_meta = _BANDPASSES.get_loaders_metadata()
-table_delim = "  ".join([15 * '=', 80 * '=', 24 * '=', 8 * '=', 12 * '='])
-table_colnames = ("{0:15}  {1:80}  {2:24}  {3:8}  {4:12}"
+table_delim = "  ".join([15 * '=', 120 * '=', 24 * '=', 8 * '=', 12 * '='])
+table_colnames = ("{0:15}  {1:120}  {2:24}  {3:8}  {4:12}"
                   .format('Name', 'Description', 'Reference', 'Data URL',
                           'Retrieved'))
 urlnums = {}
@@ -50,7 +50,7 @@ def bandpass_table(setname):
         if 'retrieved' in m:
             retrieved = m['retrieved']
 
-        lines.append("{0!r:15}  {1:80}  {2:24}  {3:8}  {4:12}".format(
+        lines.append("{0!r:15}  {1:120}  {2:24}  {3:8}  {4:12}".format(
             m['name'], m['description'], reflink, urllink, retrieved))
 
     lines.append(table_delim)

docs/_helpers/source_page.py

@@ -9,8 +9,8 @@
 
 lines = [
     '',
-    '  '.join([20*'=', 7*'=', 10*'=', 27*'=', 30*'=', 7*'=', 20*'=']),
-    '{0:20}  {1:7}  {2:10}  {3:27}  {4:30}  {5:7}  {6:50}'.format(
+    '  '.join([30*'=', 7*'=', 10*'=', 27*'=', 30*'=', 7*'=', 20*'=']),
+    '{0:30}  {1:7}  {2:10}  {3:27}  {4:30}  {5:7}  {6:50}'.format(
         'Name', 'Version', 'Type', 'Subclass', 'Reference', 'Website', 'Notes')
     ]
 lines.append(lines[1])
@@ -44,7 +44,7 @@
                 urlnums[url] = max(urlnums.values()) + 1
         urllink = '`{0}`_'.format(string.ascii_letters[urlnums[url]])
 
-    lines.append("{0!r:20}  {1!r:7}  {2:10}  {3:27}  {4:30}  {5:7}  {6:50}"
+    lines.append("{0!r:30}  {1!r:7}  {2:10}  {3:27}  {4:30}  {5:7}  {6:50}"
                  .format(m['name'], m['version'], m['type'], m['subclass'],
                          reflink, urllink, notelink))
 

docs/reference.rst

@@ -61,6 +61,7 @@ maps, and more.*
    write_lc
    read_bandpass
    load_example_data
+   load_example_spectrum_data
    read_snana_ascii
    read_snana_fits
    read_snana_simlib
@@ -69,6 +70,16 @@ maps, and more.*
    write_griddata_ascii
    write_griddata_fits
 
+Spectra
+=======
+
+.. autosummary::
+   :toctree: api
+
+   Spectrum
+
+
+
 .. _fitting-api:
 
 Fitting Photometric Data

docs/spectrum.rst

@@ -2,21 +2,17 @@
 Spectra
 *******
 
-Spectroscopic observations are supported in `sncosmo` with the `~sncosmo.Spectrum`
-class. A spectrum object can be created from a list of wavelengths and flux values:
+Spectroscopic observations are supported in `sncosmo` with the
+`~sncosmo.Spectrum` class. A spectrum object can be created from a list of
+wavelengths and flux values:
 
 .. code:: python
 
-    >>> wave = np.arange(3000, 9000)
-    >>> model = sncosmo.Model(source='hsiao-subsampled')
-    >>> model.set(z=0.1, amplitude=1e-5, t0=56000.)
-    >>> sample_time = model['t0'] + 2.
-    >>> flux = model.flux(time=sample_time, wave=wave)
-
-    >>> spectrum = sncosmo.Spectrum(wave, flux, time=sample_time)
+    >>> wave, flux, fluxerr = sncosmo.load_example_spectrum_data()
+    >>> spectrum = sncosmo.Spectrum(wave, flux)
 
-By default, the wavelengths are assumed to be in angstroms and the flux values as a
-spectral flux density (erg / s / cm^2 / A).
+By default, the wavelengths are assumed to be in angstroms and the flux
+values as a spectral flux density (erg / s / cm^2 / A).
 
 Uncertainties
 -------------
@@ -26,15 +22,14 @@ uncertainties for each spectral element:
 
 .. code:: python
 
-    >>> fluxerr = 0.1 * flux
-    >>> spectrum = sncosmo.Spectrum(wave, flux, fluxerr, time=sample_time)
+    >>> spectrum = sncosmo.Spectrum(wave, flux, fluxerr)
 
 or a full covariance matrix:
 
 .. code:: python
 
     >>> fluxcov = np.diag(fluxerr**2) + 1e-5 * np.max(flux)**2
-    >>> spectrum = sncosmo.Spectrum(wave, flux, fluxcov=fluxcov, time=sample_time)
+    >>> spectrum = sncosmo.Spectrum(wave, flux, fluxcov=fluxcov)
 
 All operations will take these uncertanties into account.
 
@@ -47,39 +42,40 @@ available in sncosmo:
 .. code:: python
 
     >>> spectrum.bandflux('sdssg')
-    6.336874516839506
+    6.417843339246818
 
 Synthetic photometry can be calculated on multiple bands simultaneously:
 
 .. code:: python
 
     >>> spectrum.bandflux(['sdssg', 'sdssr', 'sdssi'])
-    array([6.33687452, 5.33348909, 2.86301428])
+    array([6.41784334, 5.37683496, 2.8626649 ])
 
-If a zeropoint and magnitude system are specified, then the bandflux is returned in that
-system (otherwise it is in photons / s / cm^2 by default).
+If a zeropoint and magnitude system are specified, then the bandflux is
+returned in that system (otherwise it is in photons / s / cm^2 by default).
 
 .. code:: python
 
     >>> spectrum.bandflux(['sdssg', 'sdssr', 'sdssi'], zp=25., zpsys='ab')
-    array([115932.40764299, 108077.89453051,  79602.18806937])
+    array([117413.72315598, 108956.25581652,  79592.47424074])
 
-Optionally, the full covariance matrix between the bandfluxes can also be calculated:
+Optionally, the full covariance matrix between the bandfluxes can also be
+calculated:
 
 .. code:: python
 
     >>> spectrum.bandfluxcov(['sdssg', 'sdssr', 'sdssi'], zp=25., zpsys='ab')
-    (array([115932.40764299, 108077.89453051,  79602.18806937]),
-     array([[ 436626.04457069,  574161.2530974 ,  845566.99897734],
-            [ 574161.2530974 , 1088219.30397941, 1460106.55463119],
-            [ 845566.99897734, 1460106.55463119, 2203060.35600117]]))
+    (array([117413.72315598, 108956.25581652,  79592.47424074]),
+     array([[1546972.78077853,  874550.34470817, 1287550.14818921],
+             [ 874550.34470817, 2479812.26652077, 2226272.0481113 ],
+             [1287550.14818921, 2226272.0481113 , 3805168.84485814]]))
 
 A band magnitude can be evaluated in a specific magnitude system:
 
 .. code:: python
 
     >>> spectrum.bandmag(['sdssg', 'sdssr', 'sdssi'], magsys='ab')
-    array([12.33948786, 12.41565781, 12.74768749])
+    array([12.32570285, 12.40686957, 12.74781999])
 
 
 
@@ -93,38 +89,45 @@ A spectrum can be rebinned with arbitrary wavelength bins. This returns a new
 
     >>> binned_spectrum = spectrum.rebin(np.arange(3500, 6000, 100))
 
-Rebinning introduces covariance between adjacent spectral elements if the bin edges
-in the original spectrum don't line up with the bin edges in the rebinned spectrum. This
-covariance is properly propagated.
+Rebinning introduces covariance between adjacent spectral elements if the bin
+edges in the original spectrum don't line up with the bin edges in the
+rebinned spectrum. This covariance is properly propagated.
 
 
 Fitting with spectra
 --------------------
 
-Spectra can be used in fits. Any combination of spectra and photometry is allowed. For
-example, to fit a single spectrum:
+Spectra can be used in fits. Any combination of spectra and photometry is
+allowed. To fit spectra, the times at which the spectra were taken must be
+specified. For example, to fit a single spectrum:
 
 .. code:: python
 
-    >>> model.set(z=0., amplitude=1., t0=0.)
-    >>> sncosmo.fit_lc(model=model, spectra=binned_spectrum,
+    Create the spectrum object, and specify the time at which it was taken.
+    >>> spectrum = sncosmo.Spectrum(wave, flux, fluxerr, time=20.)
+
+    Fit a model to the spectrum.
+    >>> model = sncosmo.Model(source='hsiao-subsampled')
+    >>> sncosmo.fit_lc(model=model, spectra=spectrum,
     ...                vparam_names=['amplitude', 't0', 'z'],
     ...                bounds={'z': (0., 0.3)})
     (      success: True
            message: 'Minimization exited successfully.'
-             ncall: 86
-             chisq: 1.1072097164403554e-05
-              ndof: 22
+             ncall: 108
+             chisq: 576.7111360163605
+              ndof: 597
        param_names: ['z', 't0', 'amplitude']
-        parameters: array([9.99999822e-02, 5.60000000e+04, 9.99997056e-06])
+        parameters: array([9.96571945e-02, 1.80278503e+01, 1.00650322e-05])
       vparam_names: ['z', 't0', 'amplitude']
-        covariance: array([[ 4.60410999e-08,  7.84028630e-06, -1.39915254e-12],
-            [ 7.84028630e-06,  6.28193143e-03, -1.47231576e-09],
-            [-1.39915254e-12, -1.47231576e-09,  2.86156520e-15]])
-            errors: OrderedDict([('z', 0.0002145718167298541), ('t0', 0.07925860166142229), ('amplitude', 5.3493599593407034e-08)])
+        covariance: array([[ 1.17946556e-07,  1.64336679e-05, -5.21279026e-12],
+                           [ 1.64336679e-05,  1.70047614e-02, -4.60755668e-09],
+                           [-5.21279026e-12, -4.60755668e-09,  2.91915780e-15]])
+            errors: OrderedDict([('z', 0.00034343314287464677),
+                                 ('t0', 0.13040215158608248), 
+                                 ('amplitude', 5.4029230945864686e-08)])
               nfit: 1
          data_mask: None,
-     <sncosmo.models.Model at 0x7fb8d498c110>)
+    <sncosmo.models.Model at 0x7fa30159a6d0>)
 
 Other valid signatures are:
 

misc/gen_example_spectrum.py

@@ -0,0 +1,14 @@
+#!/usr/bin/env python
+import numpy as np
+import sncosmo
+
+wave = np.arange(3000, 9000, 10)
+model = sncosmo.Model(source='hsiao-subsampled')
+model.set(z=0.1, amplitude=1e-5, t0=0.)
+sample_time = model['t0'] + 2.
+flux = model.flux(time=sample_time, wave=wave)
+fluxerr = 0.1 * flux
+flux = flux + np.random.normal(scale=fluxerr)
+
+np.savetxt('example_spectrum.dat', np.array([wave, flux, fluxerr]).T,
+           header="wave flux fluxerr")

sncosmo/builtins.py

@@ -922,10 +922,10 @@ def load_2011fe(relpath, name=None, version=None):
     ('v19-iptf13bvn', '1.0', 'SN Ib', 'V19_iPTF13bvn_noHostExtCorr.SED')
 ]
 
-note = """Templates from Vincenzi et al. 19. Each template is extended in the
-ultraviolet (1600AA) and in the near infrared (10000AA). Each template can be
-used in its original version (v19-sn-name) or in its host dust extinction
-corrected version (v19-sn-name-corr)."""
+note = "Templates from Vincenzi et al. 19. Each template is extended in the " \
+    "ultraviolet (1600AA) and in the near infrared (10000AA). Each template " \
+    "can be used in its original version (v19-sn-name) or in its host dust " \
+    "extinction corrected version (v19-sn-name-corr)."
 
 for name, vrs, sntype, fn in V19_CC_models:
     relpath = os.path.join('models', 'vincenzi', fn)
@@ -1009,7 +1009,7 @@ def load_sugarmodel(relpath, name=None, version=None):
     meta = {'type': 'SN Ia', 'subclass': '`~sncosmo.SUGARSource`',
             'url': 'http://supernovae.in2p3.fr/sugar_template/',
             'reference': ('Leget20',
-                          'Leget et al. 2020',
+                          'Leget et al. 2020 '
                           '<https://doi.org/10.1051/0004-6361/201834954>')}
 
     _SOURCES.register_loader(name, load_sugarmodel,