Proper API for readthedocs

avocado/__init__.py

@@ -1 +1,2 @@
-from .astronomical_object import AstronomicalObject
+from .astronomical_object import *
+from .dataset import *

avocado/astronomical_object.py

@@ -1,6 +1,6 @@
 import pandas as pd
 
-class AstronomicalObject(object):
+class AstronomicalObject():
     """Class representing an astronomical object.
 
     An astronomical object has both metadata describing its global properties,
@@ -33,8 +33,72 @@ class AstronomicalObject(object):
         - flux: The measured flux value of the observation.
         - flux_err: The flux measurement uncertainty of the observation.
     """
-
     def __init__(self, metadata, observations):
         """Create a new AstronomicalObject"""
         self.metadata = metadata
         self.observations = observations
+
+    def _get_gp_data(self, object_meta, object_data, fix_background=True):
+        times = []
+        fluxes = []
+        bands = []
+        flux_errs = []
+        wavelengths = []
+
+        # The zeropoints were arbitrarily set from the first image. Pick the
+        # 20th percentile of all observations in each channel as a new
+        # zeropoint. This has good performance when there are supernova-like
+        # bursts in the image, even if they are quite wide.
+        # UPDATE: when picking the 20th percentile, observations with just
+        # noise get really messed up. Revert back to the median for now and see
+        # if that helps. It doesn't really matter if supernovae go slightly
+        # negative...
+        # UPDATE 2: most of the objects of interest are short-lived in time.
+        # The only issue with the background occurs when there was flux from
+        # the transient in the reference image. To deal with this, look at the
+        # last observations and see if they are negative (indicating that the
+        # reference has additional flux in it). If so, then update the
+        # background level. Otherwise, leave the background at the reference
+        # level.
+        for passband in range(num_passbands):
+            band_data = object_data[object_data['passband'] == passband]
+            if len(band_data) == 0:
+                # No observations in this band
+                continue
+
+            # Use a biweight location to estimate the background
+            ref_flux = biweight_location(band_data['flux'])
+
+            for idx, row in band_data.iterrows():
+                times.append(row['mjd'] - start_mjd)
+                flux = row['flux']
+                if fix_background:
+                    flux = flux - ref_flux
+                bands.append(passband)
+                wavelengths.append(band_wavelengths[passband])
+                fluxes.append(flux)
+                flux_errs.append(row['flux_err'])
+
+        times = np.array(times)
+        bands = np.array(bands)
+        wavelengths = np.array(wavelengths)
+        fluxes = np.array(fluxes)
+        flux_errs = np.array(flux_errs)
+
+        # Guess the scale based off of the highest signal-to-noise point.
+        # Sometimes the edge bands are pure noise and can have large
+        # insignificant points. Add epsilon to this calculation to avoid divide
+        # by zero errors for model fluxes that have 0 error.
+        scale = fluxes[np.argmax(fluxes / (flux_errs + 1e-5))]
+
+        gp_data = {
+            'meta': object_meta,
+            'times': times,
+            'bands': bands,
+            'scale': scale,
+            'wavelengths': wavelengths,
+            'fluxes': fluxes,
+            'flux_errs': flux_errs,
+        }
+
+        return gp_data

avocado/dataset.py

@@ -0,0 +1,3 @@
+
+class Dataset():
+    """Class representing a dataset of many astronomical objects."""

docs/conf.py

@@ -4,16 +4,14 @@
 # list see the documentation:
 # http://www.sphinx-doc.org/en/master/config
 
-# -- Path setup --------------------------------------------------------------
+import os
+import sys
 
-# If extensions (or modules to document with autodoc) are in another directory,
-# add these directories to sys.path here. If the directory is relative to the
-# documentation root, use os.path.abspath to make it absolute, like shown here.
-#
-# import os
-# import sys
-# sys.path.insert(0, os.path.abspath('.'))
+# -- Path setup --------------------------------------------------------------
 
+# Generate api directory if it doesn't already exist
+if not os.path.exists('api'):
+    os.mkdir('api')
 
 # -- Project information -----------------------------------------------------
 
@@ -24,7 +22,6 @@
 # The full version, including alpha/beta/rc tags
 release = '0.1'
 
-
 # -- General configuration ---------------------------------------------------
 
 # Add any Sphinx extension module names here, as strings. They can be
@@ -37,6 +34,11 @@
     'numpydoc',
 ]
 
+numpydoc_show_class_members = False
+autosummary_generate = ["reference.rst"]
+autoclass_content = "class"
+autodoc_default_flags = ["members", "no-special-members"]
+
 # Add any paths that contain templates here, relative to this directory.
 templates_path = ['_templates']
 

docs/index.rst

@@ -10,7 +10,7 @@ Welcome to avocado's documentation!
    :maxdepth: 2
    :caption: Contents:
 
-
+   reference
 
 Indices and tables
 ==================

docs/reference.rst

@@ -0,0 +1,20 @@
+Reference / API
+===============
+
+.. currentmodule:: avocado
+
+Dataset
+=======
+
+.. autosummary::
+   :toctree: api
+
+   Dataset
+
+AstronomicalObject
+==================
+
+.. autosummary::
+   :toctree: api
+
+   AstronomicalObject