Merge pull request #68 from hover2pi/UBV

v1.2.0

README.md

@@ -200,7 +200,7 @@ A variety of evolutionary model grids can be used to infer fundamental parameter
 
 ```python
 trap1.evo_model = 'DUSTY00'
-trap1.mass_from_age()
+trap1.infer_mass()
 ```
 
 <img src="https://github.com/hover2pi/sedkit/blob/master/sedkit/data/figures/Lbol_v_mass.png" height="400">
@@ -222,7 +222,7 @@ trap1.fit_modelgrid(SpexPrismLibrary())
 Inspect the SED at any time with the interactive plotting method.
 
 ```python
-trap1.plot()
+trap1.plot(integral=True, best_fit=True)
 ```
 
 <img src="https://github.com/hover2pi/sedkit/blob/master/sedkit/data/figures/sed_plot.png" height="500">

env/environment-3.7.yml

@@ -5,11 +5,13 @@ channels:
   - defaults
 dependencies:
   - numpy>=1.18.1
-  - astropy>=4.0
+  - astropy>=4.3.1
+  - astroquery>=0.4.2
   - python>=3.7
   - bokeh>=1.4.0
   - scipy>=1.4.1
   - pandas>=0.23.4
+  - pickle5>=0.0.11
   - pip>=20.3.3
   - selenium>=2.49.2
   - sphinx>=3.4.3
@@ -19,8 +21,7 @@ dependencies:
   - jupyter>=1.0.0
   - ipython>=7.12.0
   - pip:
-    - svo-filters==0.4.0
+    - svo-filters==0.4.1
     - dustmaps==1.0.4
     - numpydoc==0.8.0
     - emcee>=3.0.2
-    - git+https://github.com/astropy/astroquery.git@ccc96185beeff86f3a12a31a00a801afcebe1dbe

env/environment-3.8.yml

@@ -5,7 +5,8 @@ channels:
   - defaults
 dependencies:
   - numpy>=1.18.1
-  - astropy>=4.0
+  - astropy>=4.3.1
+  - astroquery>=0.4.2
   - python>=3.8
   - bokeh>=1.4.0
   - scipy>=1.4.1
@@ -16,11 +17,11 @@ dependencies:
   - sphinx-automodapi>=0.13
   - pytest>=6.2.1
   - pygments>=2.7.4
+  - tqdm>=4.62.3
   - jupyter>=1.0.0
   - ipython>=7.12.0
   - pip:
-    - svo-filters==0.4.0
+    - svo-filters==0.4.1
     - dustmaps==1.0.4
     - numpydoc==0.8.0
     - emcee>=3.0.2
-    - git+https://github.com/astropy/astroquery.git@ccc96185beeff86f3a12a31a00a801afcebe1dbe

sedkit/__init__.py

@@ -17,7 +17,7 @@
 __version_commit__ = ''
 _regex_git_hash = re.compile(r'.*\+g(\w+)')
 
-__version__ = '1.1.3'
+__version__ = '1.2.0'
 
 # from pkg_resources import get_distribution, DistributionNotFound
 # try:

sedkit/catalog.py

@@ -9,6 +9,7 @@
 import os
 import pickle
 from copy import copy
+from pkg_resources import resource_filename
 import shutil
 
 from astropy.io import ascii
@@ -126,6 +127,12 @@ def add_SED(self, sed):
         sed: sedkit.sed.SED
             The SED object to add
         """
+        # Overwrite duplicate names
+        idx = None
+        if sed.name in self.results['name']:
+            self.message("{}: Target already in catalog. Overwriting with new SED...")
+            idx = np.where(self.results['name'] == sed.name)[0][0]
+
         # Turn off print statements
         sed.verbose = False
 
@@ -182,8 +189,13 @@ def add_SED(self, sed):
             # Add the absolute uncertainty
             new_row['M_' + row['band'] + '_unc'] = row['abs_magnitude_unc']
 
-        # Add the new row
-        self.results.add_row(new_row)
+        # Add the new row...
+        if idx is None:
+            self.results.add_row(new_row)
+
+        # ...or replace existing
+        else:
+            self.results[idx] = new_row
 
         self.message("Successfully added SED '{}'".format(sed.name))
 
@@ -298,7 +310,7 @@ def from_file(self, filepath, run_methods=['find_2MASS'], delimiter=','):
                 # Make the SED
                 s = SED(row['name'], verbose=False)
                 if 'ra' in row and 'dec' in row:
-                    s.sky_coords = row['ra']*q.deg, row['dec']*q.deg
+                    s.sky_coords = row['ra'] * q.deg, row['dec'] * q.deg
 
                 # Run the desired methods
                 s.run_methods(run_methods)
@@ -688,3 +700,15 @@ def source(self):
         results_dict = {key: val for key, val in dict(self.results).items() if key != 'SED'}
 
         return ColumnDataSource(data=results_dict)
+
+
+class MdwarfCatalog(Catalog):
+    """A catalog of M dwarf stars"""
+    def __init__(self, **kwargs):
+        """Initialize the catalog object"""
+        # Initialize object
+        super().__init__(name='M Dwarf Catalog', **kwargs)
+
+        # Read the names from the file
+        file = resource_filename('sedkit', 'data/sources.txt')
+        self.from_file(file, run_methods=['find_SDSS', 'find_2MASS', 'find_WISE'])

sedkit/isochrone.py

@@ -198,7 +198,7 @@ def evaluate(self, xval, age, xparam, yparam, plot=False):
         if np.isnan(nominal):
             raise ValueError("I got a nan from {} for some reason.".format(self.name))
 
-        return nominal, error
+        return nominal, error, self.name
 
     def interpolate(self, xval, age, xparam, yparam):
         """Interpolate a value between two isochrones
@@ -252,7 +252,7 @@ def interpolate(self, xval, age, xparam, yparam):
 
         return result * unit
 
-    def message(self, msg, pre='[sedkit.Isochrone]'):
+    def message(self, msg, pre='[sedkit]'):
         """
         Only print message if verbose=True
 

sedkit/mcmc.py

@@ -161,13 +161,13 @@ def mcmc_go(self, nwalk_mult=20, nstep_mult=50):
         sampler = emcee.EnsembleSampler(nwalkers, self.ndim, log_probability, args=(self.model_grid, self.spectrum))
 
         # Burn in the walkers
-        pos, prob, state = sampler.run_mcmc(p0, nsteps / 10, progress=True)
+        pos, prob, state = sampler.run_mcmc(p0, int(nsteps / 10), progress=True)
 
         # Reset the walkers, so the burn-in steps aren't included in analysis
         sampler.reset()
 
         # Run MCMC with the walkers starting at the end of the burn-in
-        pos, prob, state = sampler.run_mcmc(pos, nsteps, progress=True)
+        pos, prob, state = sampler.run_mcmc(pos, int(nsteps), progress=True)
 
         # Chains contains the positions for each parameter, for each walker
         self.chain = sampler.chain

sedkit/modelgrid.py

@@ -191,6 +191,7 @@ def __init__(self, name, parameters, wave_units=None, flux_units=None,
         self.ref = ref
         self.verbose = verbose
         self.phot = False
+        self.bandpasses = []
 
         # Make all args into attributes
         for key, val in kwargs.items():
@@ -262,7 +263,7 @@ def filter(self, **kwargs):
         # Get the relevant table rows
         return u.filter_table(self.index, **kwargs)
 
-    def get_spectrum(self, closest=False, snr=None, interp=True, spec_obj=True, trim=None, resolution=None, **kwargs):
+    def get_spectrum(self, closest=False, snr=None, interp=True, spec_obj=True, trim=None, resolution=None, const=1, **kwargs):
         """Retrieve the first model with the specified parameters
 
         Parameters
@@ -275,6 +276,8 @@ def get_spectrum(self, closest=False, snr=None, interp=True, spec_obj=True, trim
             Interpolate the model grid if not present
         spec_obj: bool
             Return a sedkit.spectrum.Spectrum object
+        const: float
+            Multiplicative factor fof the flux
 
         Returns
         -------
@@ -325,7 +328,7 @@ def get_spectrum(self, closest=False, snr=None, interp=True, spec_obj=True, trim
         spec = u.scrub(spec)
 
         # Convert to specobj
-        spec = Spectrum(spec[0] * self.wave_units, spec[1] * self.flux_units, name=name, snr=snr, ref=self.ref, phot=self.phot, **kwargs)
+        spec = Spectrum(spec[0] * self.wave_units, spec[1] * self.flux_units, name=name, snr=snr, ref=self.ref, phot=self.phot, const=const, **kwargs)
 
         if trim is not None:
             spec = spec.trim(include=trim, concat=True)
@@ -533,14 +536,12 @@ def photometry(self, bandpasses, weight=False):
             # Collect data
             data = []
             weights = []
+            bands = []
             for band in bandpasses:
 
                 # Get the bandpass
                 bp = svo.Filter(band)
 
-                # Weight the bands by the inverse of the band width
-                weights.append((bp.wave_max - bp.wave_min).to(q.um).value if weight else 1)
-
                 # Calculate the synthetic flux
                 flx, flx_unc = spec.synthetic_flux(bp)
                 wav = bp.wave_eff.astype(np.float16).value
@@ -552,11 +553,18 @@ def photometry(self, bandpasses, weight=False):
                         # data.append([bp.wave_eff.astype(np.float16).value, flx.to(self.flux_units).value])
                         data.append([wav, flx.value])
 
+                    # Store the band names
+                    bands.append(band)
+
+                    # Weight the bands by the inverse of the band width
+                    weights.append((bp.wave_max - bp.wave_min).to(q.um).value if weight else 1)
+
             # Unpack and save as new spectrum
             dataT = np.array(data).T
             phot.add_model(dataT if err else dataT[:2], weights=weights, label=row['label'], **params)
             phot.phot = True
             phot.native_wave_units = bp.wave_units
+            phot.bandpasses = bands
 
         return phot
 
@@ -722,9 +730,7 @@ def __init__(self):
         self.load(root)
 
         # Add numeric spectral type
-        self.index['SpT'] = [u.specType(i.split(',')[0].replace('Opt:','')\
-                              .replace('NIR:',''))[0] for i in\
-                              self.index['spty']]
+        self.index['SpT'] = [u.specType(i.split(',')[0].replace('Opt:','').replace('NIR:',''))[0] for i in self.index['spty']]
 
 
 def format_XML(modeldir):