Added an sg module to collect spectrographic analyses.

docs/index.rst

@@ -47,25 +47,11 @@ and display as a false-color movie.
     import iris
 
     # Download a 320-step raster sequence
-    obs = iris.SpectrographObservation.from_time_range(
-        time_start=astropy.time.Time("2021-09-23T02:00"),
-        time_stop=astropy.time.Time("2021-09-23T03:00"),
+    obs = iris.sg.SpectrographObservation.from_time_range(
+        time_start=astropy.time.Time("2017-02-11T04:50"),
+        time_stop=astropy.time.Time("2017-02-11T05:00"),
     )
 
-    # Crop the observation so readthedocs doesn't run out of memory.
-    # This is probably unnecessary on your machine
-    index = {obs.axis_wavelength: slice(75, 150)}
-    obs = dataclasses.replace(
-        obs,
-        inputs=na.TemporalSpectralPositionalVectorArray(
-            time=obs.inputs.time,
-            wavelength=obs.inputs.wavelength[index],
-            position=obs.inputs.position[index],
-        ),
-        outputs=obs.outputs[index],
-    )
-
-
     # Calculate the mean rest wavelength of the
     # brightest spectral line
     wavelength_center = obs.wavelength_center.ndarray.mean()

iris/__init__.py

@@ -4,10 +4,10 @@
 
 from . import planning
 from . import data
-from ._spectrograph import SpectrographObservation
+from . import sg
 
 __all__ = [
     "planning",
     "data",
-    "SpectrographObservation",
+    "sg",
 ]

iris/data.py

@@ -168,17 +168,21 @@ def urls_hek(
         for group in event["groups"]:
 
             url = group["comp_data_url"]
+            url = urlpath.URL(url)
+            url = urlpath.URL(*["data" if p == "data_lmsal" else p for p in url.parts])
+
+            url_str = str(url)
 
             if spectrograph:
-                if "raster" in url:
-                    result.append(urlpath.URL(url))
+                if "raster" in url_str:
+                    result.append(url)
             if sji:
-                if "SJI" in url:
-                    if "deconvolved" in url:
+                if "SJI" in url_str:
+                    if "deconvolved" in url_str:
                         if deconvolved:
-                            result.append(urlpath.URL(url))
+                            result.append(url)
                     else:
-                        result.append(urlpath.URL(url))
+                        result.append(url)
 
     return result
 

iris/_spectrograph/_spectrograph.py → iris/sg/_spectrograph.py

@@ -40,7 +40,7 @@ class SpectrographObservation(
         import iris
 
         # Load a 320-step raster
-        obs = iris.SpectrographObservation.from_time_range(
+        obs = iris.sg.SpectrographObservation.from_time_range(
             time_start=astropy.time.Time("2021-09-23T06:00"),
             time_stop=astropy.time.Time("2021-09-23T07:00"),
         )

iris/_spectrograph/_spectrograph_test.py → iris/sg/_spectrograph_test.py

@@ -6,22 +6,22 @@
 @pytest.mark.parametrize(
     argnames="array",
     argvalues=[
-        iris.SpectrographObservation.from_time_range(
+        iris.sg.SpectrographObservation.from_time_range(
             time_start=astropy.time.Time("2021-09-23T06:00"),
             time_stop=astropy.time.Time("2021-09-23T07:00"),
         )
     ],
 )
 class TestSpectrographObservation:
 
-    def test_axis_time(self, array: iris.SpectrographObservation):
+    def test_axis_time(self, array: iris.sg.SpectrographObservation):
         assert isinstance(array.axis_time, str)
 
-    def test_axis_wavelength(self, array: iris.SpectrographObservation):
+    def test_axis_wavelength(self, array: iris.sg.SpectrographObservation):
         assert isinstance(array.axis_wavelength, str)
 
-    def test_axis_detector_x(self, array: iris.SpectrographObservation):
+    def test_axis_detector_x(self, array: iris.sg.SpectrographObservation):
         assert isinstance(array.axis_detector_x, str)
 
-    def test_axis_detector_y(self, array: iris.SpectrographObservation):
+    def test_axis_detector_y(self, array: iris.sg.SpectrographObservation):
         assert isinstance(array.axis_detector_y, str)