updates to files

Author: jemorrison

jwst/cube_build/blot_cube_build.py

@@ -2,7 +2,6 @@
 import logging
 
 from jwst.datamodels import ModelContainer
-
 from ..assign_wcs import nirspec
 from gwcs import wcstools
 from jwst.assign_wcs.util import in_ifu_slice
@@ -64,13 +63,13 @@ def __init__(self, median_model, input_models):
             self.median_skycube.meta.wcs.bounding_box, step=(1, 1, 1)
         )
 
-        # using wcs of ifu cube determine ra,dec,lambda
+        # using wcs of ifu cube determine ra, dec, lambda
         self.cube_ra, self.cube_dec, self.cube_wave = self.median_skycube.meta.wcs(
             xcube + 1, ycube + 1, zcube + 1
         )
 
         # pull out flux from the median sky cube that matches with
-        # cube_ra,dec,wave
+        # cube_ra, dec, wave
         self.cube_flux = self.median_skycube.data
 
         # remove all the nan values - just in case
@@ -152,8 +151,8 @@ def blot_images_miri(self):
 
         This is the main routine for blotting the MIRI median sky cube back to
         the detector space and creating a blotting image for each input model
-        1. Loop over every data model to be blotted and find ra,dec,wavelength
-           for every pixel in a valid slice on the detector.
+        1. Loop over every data model to be blotted and find ra, dec and
+           wavelength for every pixel in a valid slice on the detector.
         2. Loop over every input model and using the inverse (backwards) transform
            convert the median sky cube values ra, dec, lambda to the blotted
            x, y detector value (x_cube, y_cube).

jwst/cube_build/coord.py

@@ -12,9 +12,9 @@ def radec2std(crval1, crval2, ra, dec, rot_angle=None):
     Parameters
     ----------
     crval1 : float
-      RA value of tangent point
+      Ra value of tangent point
     crval2 : float
-      DEC value of tangent point
+      Dec value of tangent point
     ra : numpy.ndarray or float
       A list (or single value) of ra points to convert
     dec : numpy.ndarray  or float
@@ -71,15 +71,15 @@ def std2radec(crval1, crval2, xi, eta):
 
     Compute the ra,dec values of  tangent plane rectangular coordinates using
     crval1, crval2(the tangent point). This routine takes the rectangular
-    plane and projects it to the spherical plane using crval1, crval2 as
+    plane and projects it onto the spherical plane using crval1, crval2 as
     the tangent plane.
 
     Parameters
     ----------
     crval1 : float
-      RA value of tangent point
+      Ra value of tangent point
     crval2 : float
-      DEC value of tangent point
+      Dec value of tangent point
     xi : float
       Xi rectangular coordinate of tangent plane projected ra,dec
     eta : float

jwst/cube_build/cube_build_step.py

@@ -17,21 +17,21 @@
 
 class CubeBuildStep(Step):
     """
-    Creates a 3-D spectral cube.
+    Creates a 3-D spectral cube from IFU data.
 
     This is the controlling routine for building IFU Spectral Cubes.
-    It loads and sets the various input data and parameters need by
+    It loads and sets the various input data and parameters needed by
     the cube_build_step.
 
     This routine does the following operations:
 
        1. Extracts the input parameters from the cubepars reference file and
        merges them with any user-provided values.
        2. Creates the output WCS from the input images and defines the mapping
-       between all the input arrays and the output array
+       between all the input arrays and the output array.
        3. Passes the input data to the function to map all their input data
        to the output array.
-       4. Updates the output data model with correct meta data
+       4. Updates the output data model with correct meta data.
     """
 
     class_alias = "cube_build"
@@ -433,13 +433,12 @@ def read_user_input(self):
         """
         Read user input options for channel, subchannel, filter, or grating.
 
-        # Determine if any of the input parameters channel, band, filter or
-        # grating have been set by the user.
-
-        # This routine updates the dictionary self.pars_input with any user
-        # provided inputs. In particular it sets pars_input['channel'],
-        # pars_input['sub_channel'], pars_input['grating'], and
-        # pars_input['filter'] with user provided values.
+        Determine if any of the input parameters channel, band, filter or
+        grating have been set by the user.
+        This routine updates the dictionary self.pars_input with any user
+        provided inputs. In particular it sets pars_input['channel'],
+        pars_input['sub_channel'], pars_input['grating'], and
+        pars_input['filter'] with user provided values.
         """
         valid_channel = ["1", "2", "3", "4", "all"]
         valid_subchannel = [
@@ -560,10 +559,9 @@ def check_offset_file(self):
         """
         Read in an optional ra and dec offset for each file.
 
-        Check that is file is asdf file.
-        Check the file has the correct format using an local schema file.
-        The schema file, ifuoffset.schema.yaml, is located in the jwst/cube_build directory.
-        For each file in the input  association check that there is a corresponding
+        Check that the offset file is an asdf file.
+        Check that the file has the correct format using an local schema file.
+        For each file in the input association check that there is a corresponding
         file in the offset file.
 
         Returns

jwst/cube_build/ifu_cube.py

@@ -176,7 +176,7 @@ def define_cubename(self):
         Usually the output name is defined by the association table. However in the case
         of cube_build several cubes can be created from a single call of cube_build. The
         user can override the type of data to combine to make a cube. It is left to cube_build
-        to determine with channels, bands, gratings or filters are used to make the IFUCube.
+        to determine which channels, bands, gratings or filters are used to make the IFUCube.
         The final name includes the channel/band (MIRI) or grating/filter (NIRSpec).
 
         Returns
@@ -261,13 +261,13 @@ def set_geometry(self, corner_a, corner_b, lambda_min, lambda_max):
         Parameters
         ----------
         corner_a : numpy array
-            Array of ra corners of the footprint of all input data
+            Array of ra corners of the footprint of all input data.
         corner_b : numpy array
-            Array of dec corners of the footprint of all input data
+            Array of dec corners of the footprint of all input data.
         lambda_min : float
-            Minimum wavelength value of the data
+            Minimum wavelength value of the data.
         lambda_max : float
-            Maximum wavelength value of the data
+            Maximum wavelength value of the data.
         """
         ra_min = np.min(corner_a)
         ra_max = np.max(corner_a)
@@ -406,20 +406,19 @@ def set_geometry_slicer(self, corner_a, corner_b, lambda_min, lambda_max):
         """
         Set up the size of the cube in the internal IFU plane.
 
-        This will be a single exposure cube - small FOV assume
-        rectangular coord system. The internal IFU Cube is in the slicer plane
-        and is defined by along slice and across slice coordinates.
+        This will be a single exposure cube. The internal IFU Cube is in the
+        slicer plane and is defined by along slice and across slice coordinates.
 
         Parameters
         ----------
         corner_a : numpy array
-            Array of along slice corners of the footprint of all input data
+            Array of along slice corners of the footprint of all input data.
         corner_b : numpy array
-            Array of across slice  corners of the footprint of all input data
+            Array of across slice  corners of the footprint of all input data.
         lambda_min : float
-            Minimum wavelength value of the data
+            Minimum wavelength value of the data.
         lambda_max : float
-            Maximum wavelength value of the data
+            Maximum wavelength value of the data.
         """
         self.a_min = np.min(corner_a)
         self.a_max = np.max(corner_a)
@@ -595,7 +594,7 @@ def print_cube_geometry(self):
 
     def build_ifucube(self):
         """
-        Create the IFU cube.
+        Create an IFU cube.
 
         1. Loop over every band contained in the IFU cube and read in the data
         associated with the band
@@ -1196,9 +1195,8 @@ def determine_cube_parameters(self):
         """
         Determine the spatial and wavelength roi size if IFU covers more than 1 band of data.
 
-        If the IFU cube covers more than 1 band - then use the rules to
+        If the IFU cube covers more than 1 band, then use the rules to
         define the spatial and wavelength roi size to use for the cube
-        Current Rule: using the minimum
         """
         # initialize
         wave_roi = None
@@ -1467,7 +1465,7 @@ def determine_cube_parameters(self):
 
     def setup_ifucube_wcs(self):
         """
-        Determine the min and max coordinates of the spectral cube.
+        Set up the wcs of the IFU cube.
 
         Loop over every datamodel contained in the cube and find the WCS
         of the output cube that contains all the data.
@@ -1758,9 +1756,9 @@ def map_detector_to_outputframe(self, this_par1, subtract_background, input_mode
         roiw_det: numpy.ndarray
            Spectral roi size associated with coord1,coord2
         weight_det : numpy.ndarray
-            Weighting parameter association with coord1,coord2
+            Weighting parameter associated with coord1,coord2
         softrad_det : numpy.ndarray
-            Weighting parameter association with coord1,coord2
+            Weighting parameter associated with coord1,coord2
         """
         # initialize alpha_det and beta_det to None. These are filled in
         # if the instrument is MIRI and the weighting is miripsf
@@ -1987,7 +1985,7 @@ def map_detector_to_outputframe(self, this_par1, subtract_background, input_mode
 
     def map_miri_pixel_to_sky(self, input_model, this_par1, subtract_background, offsets):
         """
-        Loop over a file and map the detector pixels to the output cube.
+        Loop over a MIRI model and map the detector pixels to the output cube.
 
         The output frame is on the SKY (ra-dec)
         Return the coordinates of all the detector pixel in the output frame.
@@ -2150,7 +2148,7 @@ def map_miri_pixel_to_sky(self, input_model, this_par1, subtract_background, off
     # ______________________________________________________________________
     def map_nirspec_pixel_to_sky(self, input_model, offsets):
         """
-        Loop over a file and map the detector pixels to the output cube.
+        Loop over a NIRSpec model and map the detector pixels to the output cube.
 
         The output frame is on the SKY (ra-dec)
         Return the coordinates of all the detector pixel in the output frame.
@@ -2334,7 +2332,6 @@ def map_nirspec_pixel_to_sky(self, input_model, offsets):
 
         valid_data = np.where(flag_det == 1)
         y, x = valid_data
-
         wave = lam_det[valid_data]
         slice_no = slice_det[valid_data]
         dwave = dwave_det[valid_data]

jwst/cube_build/instrument_defaults.py

@@ -1140,21 +1140,6 @@ def set_wave_max(self, value, parameter1, parameter2):
         """
         self.Info[parameter1][parameter2]["wavemax"] = value
 
-    # def set_spatial_roi(self, value, parameter1, parameter2):
-    #    self.Info[parameter1][parameter2]["sroi"] = value
-
-    # def set_wave_roi(self, value, parameter1, parameter2):
-    #    self.Info[parameter1][parameter2]["wroi"] = value
-
-    # def set_msm_power(self, value, parameter1, parameter2):
-    #    self.Info[parameter1][parameter2]["msm_power"] = value
-
-    # def set_soft_rad(self, value, parameter1, parameter2):
-    #    self.Info[parameter1][parameter2]["softrad"] = value
-
-    # def set_scale_rad(self, value, parameter1, parameter2):
-    #    self.Info[parameter1][parameter2]["scalerad"] = value
-
     # Get functions
 
     def get_wave_roi(self, parameter1, parameter2):