tests etc

CHANGES.rst

@@ -30,6 +30,8 @@ Specviz
 Specviz2d
 ^^^^^^^^^
 
+- Add option to use self-derived spatial profile for Horne extract in spectral extraction plugin. [#2845]
+
 API Changes
 -----------
 

jdaviz/configs/specviz2d/plugins/spectral_extraction/spectral_extraction.py

@@ -329,7 +329,7 @@ def __init__(self, *args, **kwargs):
         self.horne_ext_profile = SelectPluginComponent(self,
                                                        items='horne_ext_profile_items',
                                                        selected='horne_ext_profile_selected',
-                                                       manual_options=['Gaussian', 'Self (interpolated)'])
+                                                       manual_options=['Gaussian', 'Self (interpolated)'])  # noqa
 
         self.ext_add_results = AddResults(self, 'ext_results_label',
                                           'ext_results_label_default',
@@ -969,14 +969,15 @@ def export_extract(self, **kwargs):
                 # setup dict of interpolation options
                 n_bins_interpolated_profile = self.self_prof_n_bins
                 interp_degree = (self.self_prof_interp_degree_x, self.self_prof_interp_degree_y)
-                spatial_profile = {'n_bins_interpolated_profile': n_bins_interpolated_profile,
+                spatial_profile = {'name': 'interpolated_profile',
+                                   'n_bins_interpolated_profile': n_bins_interpolated_profile,
                                    'interp_degree': interp_degree}
             elif self.horne_ext_profile_selected == 'Gaussian':
-                spaital_profile = 'gaussian'
+                spatial_profile = 'gaussian'
             else:
-                raise ValueError("Horne extraction profile must either be 'Gaussian' or 'Self (interpolated)'")
+                raise ValueError("Horne extraction profile must either be 'Gaussian' or 'Self (interpolated)'")  # noqa
 
-            ext = extract.HorneExtract(inp_sp2d, trace)  # , spatial_profile=spatial_profile)
+            ext = extract.HorneExtract(inp_sp2d, trace, spatial_profile=spatial_profile)
         else:
             raise NotImplementedError(f"extraction type '{self.ext_type_selected}' not supported")  # noqa
 

jdaviz/configs/specviz2d/plugins/spectral_extraction/tests/test_spectral_extraction.py

@@ -1,6 +1,10 @@
 import gwcs
 import pytest
+from astropy.modeling import models
+from astropy.nddata import VarianceUncertainty
+import astropy.units as u
 from astropy.utils.data import download_file
+import numpy as np
 from packaging.version import Version
 from specreduce import tracing, background, extract
 from specutils import Spectrum1D
@@ -185,3 +189,63 @@ def test_spectrum_on_top(specviz2d_helper):
     pext = specviz2d_helper.app.get_tray_item_from_name('spectral-extraction')
     assert pext.bg_type_selected == 'OneSided'
     assert pext.bg_separation < 0
+
+
+@pytest.mark.filterwarnings('ignore')
+def test_horne_extract_self_profile(specviz2d_helper):
+
+    spec2d = np.zeros((40, 100))
+    spec2dvar = np.ones((40, 100))
+
+    for ii in range(spec2d.shape[1]):
+        mgaus = models.Gaussian1D(amplitude=10,
+                                  mean=(9.+(20/spec2d.shape[1])*ii),
+                                  stddev=2)
+        rg = np.arange(0, spec2d.shape[0], 1)
+        gaus = mgaus(rg)
+        spec2d[:, ii] = gaus
+
+    wave = np.arange(0, spec2d.shape[1], 1)
+    objectspec = Spectrum1D(spectral_axis=wave*u.m,
+                            flux=spec2d*u.Jy,
+                            uncertainty=VarianceUncertainty(spec2dvar*u.Jy*u.Jy))
+
+    specviz2d_helper.load_data(objectspec)
+    pext = specviz2d_helper.app.get_tray_item_from_name('spectral-extraction')
+
+    trace_fit = tracing.FitTrace(objectspec,
+                                 trace_model=models.Polynomial1D(degree=1),
+                                 window=13, peak_method='gaussian', guess=20)
+    pext.import_trace(trace_fit)
+
+    pext.ext_type_selected = "Horne"
+    pext.horne_ext_profile_selected = "Self (interpolated)"
+
+    # check that correct defaults are set
+    assert pext.self_prof_n_bins == 10
+    assert pext.self_prof_interp_degree_x == 1
+    assert pext.self_prof_interp_degree_y == 1
+
+    sp_ext = pext.export_extract_spectrum()
+
+    bg_sub = pext.export_bg_sub()
+
+    extract_horne_interp = extract.HorneExtract(bg_sub, trace_fit,
+                                                spatial_profile='interpolated_profile')
+
+    assert np.all(extract_horne_interp.spectrum.flux == sp_ext.flux)
+
+    # now try changing from defaults
+    pext.self_prof_n_bins = 5
+    pext.self_prof_interp_degree_x = 2
+    pext.self_prof_interp_degree_y = 2
+
+    sp_ext = pext.export_extract_spectrum()
+    bg_sub = pext.export_bg_sub()
+
+    extract_horne_interp = extract.HorneExtract(bg_sub, trace_fit,
+                                                spatial_profile={'name': 'interpolated_profile',
+                                                                 'n_bins_interpolated_profile': 5,
+                                                                 'interp_degree': (2, 2)})
+
+    assert np.all(extract_horne_interp.spectrum.flux == sp_ext.flux)