Better handled Spectrum1D images across classes

Author: ojustino

specreduce/background.py

@@ -27,7 +27,7 @@ class Background:
 
     Parameters
     ----------
-    image : `~astropy.nddata.NDData` or array-like
+    image : `~astropy.nddata.NDData`-like or array-like
         image with 2-D spectral image data
     traces : List
         list of trace objects (or integers to define FlatTraces) to
@@ -60,7 +60,7 @@ def __post_init__(self):
 
         Parameters
         ----------
-        image : `~astropy.nddata.NDData` or array-like
+        image : `~astropy.nddata.NDData`-like or array-like
             image with 2-D spectral image data
         traces : List
             list of trace objects (or integers to define FlatTraces) to
@@ -86,6 +86,11 @@ def _to_trace(trace):
                     raise ValueError('trace_object.trace_pos must be >= 1')
             return trace
 
+        if isinstance(self.image, NDData):
+            # NOTE: should the NDData structure instead be preserved?
+            # (NDData includes Spectrum1D under its umbrella)
+            self.image = self.image.data
+
         bkg_wimage = np.zeros_like(self.image, dtype=np.float64)
         for trace in self.traces:
             trace = _to_trace(trace)
@@ -133,7 +138,7 @@ def two_sided(cls, image, trace_object, separation, **kwargs):
 
         Parameters
         ----------
-        image : nddata-compatible image
+        image : `~astropy.nddata.NDData`-like or array-like
             image with 2-D spectral image data
         trace_object: Trace
             estimated trace of the spectrum to center the background traces
@@ -166,7 +171,7 @@ def one_sided(cls, image, trace_object, separation, **kwargs):
 
         Parameters
         ----------
-        image : nddata-compatible image
+        image : `~astropy.nddata.NDData`-like or array-like
             image with 2-D spectral image data
         trace_object: Trace
             estimated trace of the spectrum to center the background traces

specreduce/extract.py

@@ -122,15 +122,15 @@ class BoxcarExtract(SpecreduceOperation):
 
     Parameters
     ----------
-    image : nddata-compatible image
+    image : `~astropy.nddata.NDData`-like or array-like, required
         image with 2-D spectral image data
-    trace_object : Trace
+    trace_object : Trace, required
         trace object
-    width : float
+    width : float, optional
         width of extraction aperture in pixels
-    disp_axis : int
+    disp_axis : int, optional
         dispersion axis
-    crossdisp_axis : int
+    crossdisp_axis : int, optional
         cross-dispersion axis
 
     Returns
@@ -156,15 +156,15 @@ def __call__(self, image=None, trace_object=None, width=None,
 
         Parameters
         ----------
-        image : nddata-compatible image
+        image : `~astropy.nddata.NDData`-like or array-like, required
             image with 2-D spectral image data
-        trace_object : Trace
+        trace_object : Trace, required
             trace object
-        width : float
+        width : float, optional
             width of extraction aperture in pixels [default: 5]
-        disp_axis : int
+        disp_axis : int, optional
             dispersion axis [default: 1]
-        crossdisp_axis : int
+        crossdisp_axis : int, optional
             cross-dispersion axis [default: 0]
 
 
@@ -180,22 +180,30 @@ def __call__(self, image=None, trace_object=None, width=None,
         disp_axis = disp_axis if disp_axis is not None else self.disp_axis
         crossdisp_axis = crossdisp_axis if crossdisp_axis is not None else self.crossdisp_axis
 
+        # handle image processing based on its type
+        if isinstance(image, Spectrum1D):
+            img = image.data
+            unit = image.unit
+        else:
+            img = image
+            unit = getattr(image, 'unit', u.DN)
+
         # TODO: this check can be removed if/when implemented as a check in FlatTrace
         if isinstance(trace_object, FlatTrace):
             if trace_object.trace_pos < 1:
                 raise ValueError('trace_object.trace_pos must be >= 1')
 
         # weight image to use for extraction
-        wimage = _ap_weight_image(
+        wimg = _ap_weight_image(
             trace_object,
             width,
             disp_axis,
             crossdisp_axis,
-            image.shape)
+            img.shape)
 
         # extract
         ext1d = np.sum(image * wimage, axis=crossdisp_axis)
-        return _to_spectrum1d_pixels(ext1d * getattr(image, 'unit', u.DN))
+        return _to_spectrum1d_pixels(ext1d * unit)
 
 
 @dataclass
@@ -207,7 +215,7 @@ class HorneExtract(SpecreduceOperation):
     Parameters
     ----------
 
-    image : `~astropy.nddata.NDData` or array-like, required
+    image : `~astropy.nddata.NDData`-like or array-like, required
         The input 2D spectrum from which to extract a source. An
         NDData object must specify uncertainty and a mask. An array
         requires use of the ``variance``, ``mask``, & ``unit`` arguments.
@@ -270,7 +278,7 @@ def __call__(self, image=None, trace_object=None,
         Parameters
         ----------
 
-        image : `~astropy.nddata.NDData` or array-like, required
+        image : `~astropy.nddata.NDData`-like or array-like, required
             The input 2D spectrum from which to extract a source. An
             NDData object must specify uncertainty and a mask. An array
             requires use of the ``variance``, ``mask``, & ``unit`` arguments.
@@ -323,6 +331,7 @@ def __call__(self, image=None, trace_object=None,
 
         # handle image and associated data based on image's type
         if isinstance(image, NDData):
+            # (NDData includes Spectrum1D under its umbrella)
             img = np.ma.array(image.data, mask=image.mask)
             unit = image.unit if image.unit is not None else u.Unit()
 

specreduce/tracing.py

@@ -5,9 +5,10 @@
 import warnings
 
 from astropy.modeling import fitting, models
-from astropy.nddata import CCDData, NDData
+from astropy.nddata import NDData
 from astropy.stats import gaussian_sigma_to_fwhm
 from scipy.interpolate import UnivariateSpline
+from specutils import Spectrum1D
 import numpy as np
 
 __all__ = ['Trace', 'FlatTrace', 'ArrayTrace', 'KosmosTrace']
@@ -20,15 +21,15 @@ class Trace:
 
     Parameters
     ----------
-    image : `~astropy.nddata.CCDData`
+    image : `~astropy.nddata.NDData`-like or array-like, required
         Image to be traced
 
     Properties
     ----------
     shape : tuple
         Shape of the array describing the trace
     """
-    image: CCDData
+    image: NDData
 
     def __post_init__(self):
         self.trace_pos = self.image.shape[0] / 2
@@ -37,6 +38,11 @@ def __post_init__(self):
     def __getitem__(self, i):
         return self.trace[i]
 
+    def _parse_image(self):
+        if isinstance(self.image, Spectrum1D):
+            # NOTE: should the Spectrum1D structure instead be preserved?
+            self.image = self.image.data
+
     @property
     def shape(self):
         return self.trace.shape
@@ -95,6 +101,8 @@ class FlatTrace(Trace):
     trace_pos: float
 
     def __post_init__(self):
+        super()._parse_image()
+
         self.set_position(self.trace_pos)
 
     def set_position(self, trace_pos):
@@ -124,6 +132,8 @@ class ArrayTrace(Trace):
     trace: np.ndarray
 
     def __post_init__(self):
+        super()._parse_image()
+
         nx = self.image.shape[1]
         nt = len(self.trace)
         if nt != nx:
@@ -158,7 +168,7 @@ class KosmosTrace(Trace):
 
     Parameters
     ----------
-    image : `~astropy.nddata.NDData` or array-like, required
+    image : `~astropy.nddata.NDData`-like or array-like, required
         The image over which to run the trace. Assumes cross-dispersion
         (spatial) direction is axis 0 and dispersion (wavelength)
         direction is axis 1.
@@ -200,6 +210,8 @@ class KosmosTrace(Trace):
     _disp_axis = 1
 
     def __post_init__(self):
+        super()._parse_image()
+
         # handle multiple image types and mask uncaught invalid values
         if isinstance(self.image, NDData):
             img = np.ma.masked_invalid(np.ma.masked_array(self.image.data,