reorganize

specreduce/tracing.py

@@ -209,6 +209,8 @@ class FitTrace(Trace, _ImageParser):
     _disp_axis = 1
 
     def __post_init__(self):
+
+        # parse image
         self.image = self._parse_image(self.image)
 
         # mask any previously uncaught invalid values
@@ -262,14 +264,20 @@ def __post_init__(self):
             warnings.warn('TRACE: Converting window to int')
             self.window = int(self.window)
 
+        # fit the trace
+        self._fit_trace(img)
+
+    def _fit_trace(self, img):
+
+        yy = np.arange(img.shape[self._crossdisp_axis])
+
         # set max peak location by user choice or wavelength with max avg flux
         ztot = img.sum(axis=self._disp_axis) / img.shape[self._disp_axis]
         peak_y = self.guess if self.guess is not None else ztot.argmax()
         # NOTE: peak finder can be bad if multiple objects are on slit
 
-        yy = np.arange(img.shape[self._crossdisp_axis])
-
         if self.peak_method == 'gaussian':
+
             # guess the peak width as the FWHM, roughly converted to gaussian sigma
             yy_above_half_max = np.sum(ztot > (ztot.max() / 2))
             width_guess = yy_above_half_max / gaussian_sigma_to_fwhm
@@ -292,6 +300,8 @@ def __post_init__(self):
         ilum2 = (yy if self.window is None
                  else yy[np.arange(peak_y - self.window,
                                    peak_y + self.window, dtype=int)])
+
+        # check if everything in window region is masked
         if img[ilum2].mask.all():
             raise ValueError('All pixels in window region are masked. Check '
                              'for invalid values or use a larger window value.')
@@ -303,11 +313,10 @@ def __post_init__(self):
         warn_bins = []
         for i in range(self.bins):
 
-            # binned column
+            # binned column (sum) if bins < ncols. otherwise, just columns.
             z_i = img[ilum2, x_bins[i]:x_bins[i+1]].sum(axis=self._disp_axis)
 
             if self.peak_method == 'gaussian':
-
                 # if binned column is fully masked for peak_method='gaussian',
                 # the fit value for this bin should be nan, then continue to next
                 warn_msg = 'nan'
@@ -363,9 +372,8 @@ def __post_init__(self):
                 y_bins[i] = ilum2[z_i.argmax()]
 
                 # warning message for fully masked bin
-                # NOTE this reflects current behavior, should eventually be changed
-                # to set to nan by default (or zero fill / interpoate option once
-                # available) and warn accordingly.
+                # NOTE: should eventually be changed to set to nan by default
+                # (or zero fill / interpoate option onceavailable) and warn.
                 warn_msg = 'zero'
 
         # warn about fully-masked bins