Move model classes from ccsn.py to base.py

doc/source/nb/AnalyticFluence.ipynb

@@ -27,7 +27,7 @@
     "\n",
     "from snewpy import snowglobes, model_path\n",
     "from snewpy.flavor import ThreeFlavor\n",
-    "from snewpy.models.ccsn import Analytic3Species\n",
+    "from snewpy.models.base import Analytic3Species\n",
     "\n",
     "mpl.rc('font', size=14)\n",
     "\n",

doc/source/nb/README.md

@@ -8,15 +8,15 @@ These directories contain notebooks demonstrating how to use the core-collapse a
 
 ## AnalyticFluence
 
-This notebook demonstrates how to use the `Analytic3Species` class from `snewpy.models` to create an analytic supernova model by specifying the luminosity, mean energy and mean squared energy for three neutrino flavors.
+This notebook demonstrates how to use the `Analytic3Species` class from `snewpy.models.base` to create an analytic supernova model by specifying the luminosity, mean energy and mean squared energy for three neutrino flavors.
 
 ## FlavorTransformation
 
 This notebook demonstrates the flavor transformations available in `snewpy.flavor_transformation`. It was used to produce many of the figures in the SNEWPY ApJ paper.
 
 ## SNOwGLoBES_models
 
-This notebook demonstrates how to use the `SNOwGLoBES` class in `snewpy.models`, which can be used with the `Type_Ia` and `PISN` model files that are available for download through SNEWPY.
+This notebook demonstrates how to use the `SNOwGLoBES` class in `snewpy.models.base`, which can be used with the `Type_Ia` and `PISN` model files that are available for download through SNEWPY.
 
 ## SNOwGLoBES_usage
 
@@ -25,4 +25,4 @@ This notebook demonstrates how to use SNEWPY’s `snewpy.snowglobes` module to i
 ## `dev` Directory
 
 This directory contains notebooks which may be under development or illustrate usage of internal/undocumented APIs.
-They are not recommended for general users.
+They are not recommended for general users.

doc/source/nb/SNOwGLoBES_models.ipynb

@@ -19,7 +19,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from snewpy.models.ccsn import SNOwGLoBES\n",
+    "from snewpy.models.base import SNOwGLoBES\n",
     "\n",
     "import matplotlib as mpl\n",
     "import matplotlib.pyplot as plt\n",

python/snewpy/models/base.py

@@ -204,6 +204,86 @@ def get_value(x):
         return x.value
     return x
 
+
+class SNOwGLoBES:
+    """A model that does not inherit from SupernovaModel (yet) and imports a group of SNOwGLoBES files."""
+
+    def __init__(self, tarfilename):
+        """
+        Parameters
+        ----------
+        tarfilename: str
+            Absolute or relative path to tar archive with SNOwGLoBES files.
+        """
+        self.tfname = tarfilename
+        tf = tarfile.open(self.tfname)
+
+        # For now just pull out the "NoOsc" files.
+        datafiles = sorted([f.name for f in tf if '.dat' in f.name])
+        noosc = [df for df in datafiles if 'NoOsc' in df]
+        noosc.sort(key=len)
+
+        # Loop through the noosc files and pull out the number fluxes.
+        self.time = []
+        self.energy = None
+        self.flux = {}
+        self.fmin = 1e99
+        self.fmax = -1e99
+
+        for nooscfile in noosc:
+            with tf.extractfile(nooscfile) as f:
+                logging.debug('Reading {}'.format(nooscfile))
+                meta = f.readline()
+                metatext = meta.decode('utf-8')
+                t = float(metatext.split('TBinMid=')[-1].split('sec')[0])
+                dt = float(metatext.split('tBinWidth=')[-1].split('s')[0])
+                dE = float(metatext.split('eBinWidth=')[-1].split('MeV')[0])
+
+                data = Table.read(f, format='ascii.commented_header', header_start=-1)
+                data.meta['t'] = t
+                data.meta['dt'] = dt
+                data.meta['dE'] = dE
+
+                self.time.append(t)
+                if self.energy is None:
+                    self.energy = (data['E(GeV)'].data*1000).tolist()
+
+            for flavor in ['NuE', 'NuMu', 'NuTau', 'aNuE', 'aNuMu', 'aNuTau']:
+                if flavor in self.flux:
+                    self.flux[flavor].append(data[flavor].data.tolist())
+                else:
+                    self.flux[flavor] = [data[flavor].data.tolist()]
+
+        # We now have a table with rows=times and columns=energies. Transpose
+        # so that rows=energy and cols=time.
+        for k, v in self.flux.items():
+            self.flux[k] = np.transpose(self.flux[k])
+            self.fmin = np.minimum(self.fmin, np.min(self.flux[k]))
+            self.fmax = np.maximum(self.fmax, np.max(self.flux[k]))
+
+    def get_fluence(self, t):
+        """Return the fluence at a given time t.
+
+        Parameters
+        ----------
+        t : float
+            Time in seconds.
+
+        Returns
+        -------
+        fluence : dict
+            A dictionary giving fluence at time t, keyed by flavor.
+        """
+        # Get index of closest element in the array
+        idx = np.abs(np.asarray(self.time) - t).argmin()
+
+        fluence = {}
+        for k, fl in self.flux.items():
+            fluence[k] = fl[:,idx]
+
+        return fluence
+
+
 class PinchedModel(SupernovaModel):
     """Subclass that contains spectra/luminosity pinches"""
     def __init__(self, simtab, metadata):
@@ -286,3 +366,27 @@ def _get_initial_spectra_dict(self, t, E, flavors=ThreeFlavor):
             initialspectra[flavor] = result
 
         return initialspectra
+
+
+class Analytic3Species(PinchedModel):
+    """An analytical model calculating spectra given total luminosity,
+    average energy, and rms or pinch, for each species.
+    """
+
+    param = "There are no input files available for this class. Use `doc/scripts/Analytic.py` in the SNEWPY GitHub repo to create a custom input file."
+
+    def get_param_combinations(cls):
+        print(cls.param)
+        return []
+
+    def __init__(self, filename):
+        """
+        Parameters
+        ----------
+        filename : str
+            Absolute or relative path to file with model data.
+        """
+
+        simtab = Table.read(filename,format='ascii')
+        self.filename = filename
+        super().__init__(simtab, metadata={})

python/snewpy/models/ccsn.py

@@ -35,7 +35,6 @@ class method to get a list of all valid combinations and filter it:
 from astropy.table import Table
 
 from snewpy.models import ccsn_loaders as loaders
-from .base import PinchedModel
 
 from snewpy.models.registry_model import RegistryModel, Parameter
 from snewpy.models.registry_model import all_models
@@ -392,103 +391,3 @@ def __init__(self, *, Bfield:str, direction:str, rotation:int=None, grav:str=Non
             filename = f'{Bfield}_b12_3d_{rotation}deg_snewpy_{direction}.dat'
         return super().__init__(filename=filename, metadata=self.metadata)
 
-class SNOwGLoBES:
-    """A model that does not inherit from SupernovaModel (yet) and imports a group of SNOwGLoBES files."""
-
-    def __init__(self, tarfilename):
-        """
-        Parameters
-        ----------
-        tarfilename: str
-            Absolute or relative path to tar archive with SNOwGLoBES files.
-        """
-        self.tfname = tarfilename
-        tf = tarfile.open(self.tfname)
-
-        # For now just pull out the "NoOsc" files.
-        datafiles = sorted([f.name for f in tf if '.dat' in f.name])
-        noosc = [df for df in datafiles if 'NoOsc' in df]
-        noosc.sort(key=len)
-
-        # Loop through the noosc files and pull out the number fluxes.
-        self.time = []
-        self.energy = None
-        self.flux = {}
-        self.fmin = 1e99
-        self.fmax = -1e99
-
-        for nooscfile in noosc:
-            with tf.extractfile(nooscfile) as f:
-                logging.debug('Reading {}'.format(nooscfile))
-                meta = f.readline()
-                metatext = meta.decode('utf-8')
-                t = float(metatext.split('TBinMid=')[-1].split('sec')[0])
-                dt = float(metatext.split('tBinWidth=')[-1].split('s')[0])
-                dE = float(metatext.split('eBinWidth=')[-1].split('MeV')[0])
-
-                data = Table.read(f, format='ascii.commented_header', header_start=-1)
-                data.meta['t'] = t
-                data.meta['dt'] = dt
-                data.meta['dE'] = dE
-
-                self.time.append(t)
-                if self.energy is None:
-                    self.energy = (data['E(GeV)'].data*1000).tolist()
-
-            for flavor in ['NuE', 'NuMu', 'NuTau', 'aNuE', 'aNuMu', 'aNuTau']:
-                if flavor in self.flux:
-                    self.flux[flavor].append(data[flavor].data.tolist())
-                else:
-                    self.flux[flavor] = [data[flavor].data.tolist()]
-
-        # We now have a table with rows=times and columns=energies. Transpose
-        # so that rows=energy and cols=time.
-        for k, v in self.flux.items():
-            self.flux[k] = np.transpose(self.flux[k])
-            self.fmin = np.minimum(self.fmin, np.min(self.flux[k]))
-            self.fmax = np.maximum(self.fmax, np.max(self.flux[k]))
-
-    def get_fluence(self, t):
-        """Return the fluence at a given time t.
-
-        Parameters
-        ----------
-        t : float
-            Time in seconds.
-
-        Returns
-        -------
-        fluence : dict
-            A dictionary giving fluence at time t, keyed by flavor.
-        """
-        # Get index of closest element in the array
-        idx = np.abs(np.asarray(self.time) - t).argmin()
-
-        fluence = {}
-        for k, fl in self.flux.items():
-            fluence[k] = fl[:,idx]
-
-        return fluence
-
-class Analytic3Species(PinchedModel):
-    """An analytical model calculating spectra given total luminosity,
-    average energy, and rms or pinch, for each species.
-    """
-
-    param = "There are no input files available for this class. Use `doc/scripts/Analytic.py` in the SNEWPY GitHub repo to create a custom input file."
-
-    def get_param_combinations(cls):
-        print(cls.param)
-        return []
-
-    def __init__(self, filename):
-        """
-        Parameters
-        ----------
-        filename : str
-            Absolute or relative path to file with model data.
-        """
-
-        simtab = Table.read(filename,format='ascii')
-        self.filename = filename
-        super().__init__(simtab, metadata={})

python/snewpy/models/model_files.yml

@@ -6,6 +6,7 @@ config:
     - &snewpy "https://github.com/SNEWS2/snewpy/raw/v{snewpy_version}/models/{model}/{filename}"
     - &ccsn_repository "https://github.com/SNEWS2/snewpy-models-ccsn/raw/v0.3/models/{model}/{filename}"
     - &presn_repository "https://github.com/SNEWS2/snewpy-models-presn/raw/v0.2/models/{model}/{filename}"
+    - &pisn_typeIa_repository "https://github.com/SNEWS2/snewpy-models-pisn_typeIa/raw/v0.1/models/{model}/{filename}"
 
 models:
     ccsn:
@@ -73,3 +74,10 @@ models:
 
         Yoshida_2016:
             repository: *presn_repository
+
+    pisn_typeIa:
+        TypeIa:
+            repository: *pisn_typeIa_repository  
+
+        Wright_2017:
+            repository: *pisn_typeIa_repository

python/snewpy/scripts/Analytic.py

@@ -1,5 +1,5 @@
 """This model stub allows one to generate simple analytic models and then 
-read them into the Analytic3Species model found in model.py which is part of SNEWPY.
+read them into the Analytic3Species model found in models.base.py which is part of SNEWPY.
 """
 
 from astropy.table import Table