move reproject to top-level dask class

Author: keflavich

spectral_cube/dask_spectral_cube.py

@@ -1447,6 +1447,98 @@ def convfunc(img, **kwargs):
                                                     accepts_chunks=True,
                                                     **kwargs).with_beam(beam, raise_error_jybm=False)
 
+    def reproject(self, header, order='bilinear', use_memmap=False,
+                  filled=True, **kwargs):
+        """
+        Spatially reproject the cube into a new header.  Fills the data with
+        the cube's ``fill_value`` to replace bad values before reprojection.
+
+        If you want to reproject a cube both spatially and spectrally, you need
+        to use `spectral_interpolate` as well.
+
+        .. warning::
+            The current implementation of ``reproject`` requires that the whole
+            cube be loaded into memory.  Issue #506 notes that this is a
+            problem, and it is on our to-do list to fix.
+
+        Parameters
+        ----------
+        header : `astropy.io.fits.Header`
+            A header specifying a cube in valid WCS
+        order : int or str, optional
+            The order of the interpolation (if ``mode`` is set to
+            ``'interpolation'``). This can be either one of the following
+            strings:
+
+                * 'nearest-neighbor'
+                * 'bilinear'
+                * 'biquadratic'
+                * 'bicubic'
+
+            or an integer. A value of ``0`` indicates nearest neighbor
+            interpolation.
+        use_memmap : bool
+            If specified, a memory mapped temporary file on disk will be
+            written to rather than storing the intermediate spectra in memory.
+        filled : bool
+            Fill the masked values with the cube's fill value before
+            reprojection?  Note that setting ``filled=False`` will use the raw
+            data array, which can be a workaround that prevents loading large
+            data into memory.
+        kwargs : dict
+            Passed to `reproject.reproject_interp`.
+        """
+
+        try:
+            from reproject.version import version
+        except ImportError:
+            raise ImportError("Requires the reproject package to be"
+                              " installed.")
+
+        reproj_kwargs = kwargs
+        # Need version > 0.2 to work with cubes, >= 0.5 for memmap
+        from distutils.version import LooseVersion
+        if LooseVersion(version) < "0.5":
+            raise Warning("Requires version >=0.5 of reproject. The current "
+                          "version is: {}".format(version))
+        elif LooseVersion(version) >= "0.6":
+            pass # no additional kwargs, no warning either
+        else:
+            reproj_kwargs['independent_celestial_slices'] = True
+
+        from reproject import reproject_interp
+
+        # TODO: Find the minimal subcube that contains the header and only reproject that
+        # (see FITS_tools.regrid_cube for a guide on how to do this)
+
+        newwcs = wcs.WCS(header)
+        shape_out = tuple([header['NAXIS{0}'.format(i + 1)] for i in
+                           range(header['NAXIS'])][::-1])
+
+        def reproject_interp_wrapper(img_slice):
+            # What exactly is the wrapper getting here?
+            # I think it is given a _cube_ that is a cutout?
+            if filled:
+                data = img_slice.filled_data[:]
+            else:
+                data = img_slice._data
+            return reproject_interp((data, img_slice.header),
+                                    newwcs, shape_out=shape_out, **kwargs)
+
+        newcube, newcube_valid = self.apply_function_parallel_spatial(
+            reproject_interp_wrapper,
+            accepts_chunks=True,
+            order=order,
+            **reproj_kwargs)
+
+        return self._new_cube_with(data=newcube,
+                                   wcs=newwcs,
+                                   mask=BooleanArrayMask(newcube_valid.astype('bool'),
+                                                         newwcs),
+                                   meta=self.meta,
+                                  )
+
+
 
 class DaskVaryingResolutionSpectralCube(DaskSpectralCubeMixin, VaryingResolutionSpectralCube):
 
@@ -1632,90 +1724,3 @@ def _mask_include(self):
                                               chunks=self._data.chunksize),
                                 wcs=self.wcs,
                                 shape=self.shape)
-
-    def reproject(self, header, order='bilinear', use_memmap=False,
-                  filled=True, **kwargs):
-        """
-        Spatially reproject the cube into a new header.  Fills the data with
-        the cube's ``fill_value`` to replace bad values before reprojection.
-
-        If you want to reproject a cube both spatially and spectrally, you need
-        to use `spectral_interpolate` as well.
-
-        Parameters
-        ----------
-        header : `astropy.io.fits.Header`
-            A header specifying a cube in valid WCS
-        order : int or str, optional
-            The order of the interpolation (if ``mode`` is set to
-            ``'interpolation'``). This can be either one of the following
-            strings:
-
-                * 'nearest-neighbor'
-                * 'bilinear'
-                * 'biquadratic'
-                * 'bicubic'
-
-            or an integer. A value of ``0`` indicates nearest neighbor
-            interpolation.
-        use_memmap : bool
-            If specified, a memory mapped temporary file on disk will be
-            written to rather than storing the intermediate spectra in memory.
-        filled : bool
-            Fill the masked values with the cube's fill value before
-            reprojection?  Note that setting ``filled=False`` will use the raw
-            data array, which can be a workaround that prevents loading large
-            data into memory.
-        kwargs : dict
-            Passed to `reproject.reproject_interp`.
-        """
-
-        try:
-            from reproject.version import version
-        except ImportError:
-            raise ImportError("Requires the reproject package to be"
-                              " installed.")
-
-        reproj_kwargs = kwargs
-        # Need version > 0.2 to work with cubes, >= 0.5 for memmap
-        from distutils.version import LooseVersion
-        if LooseVersion(version) < "0.5":
-            raise Warning("Requires version >=0.5 of reproject. The current "
-                          "version is: {}".format(version))
-        elif LooseVersion(version) >= "0.6":
-            pass # no additional kwargs, no warning either
-        else:
-            reproj_kwargs['independent_celestial_slices'] = True
-
-        from reproject import reproject_interp
-
-        # TODO: Find the minimal subcube that contains the header and only reproject that
-        # (see FITS_tools.regrid_cube for a guide on how to do this)
-
-        newwcs = wcs.WCS(header)
-        shape_out = tuple([header['NAXIS{0}'.format(i + 1)] for i in
-                           range(header['NAXIS'])][::-1])
-
-        def reproject_interp_wrapper(img_slice):
-            # What exactly is the wrapper getting here?
-            # I think it is given a _cube_ that is a cutout?
-            if filled:
-                data = img_slice.filled_data[:]
-            else:
-                data = img_slice._data
-            return reproject_interp((data, img_slice.header),
-                                    newwcs, shape_out=shape_out, **kwargs)
-
-        newcube, newcube_valid = self.apply_function_parallel_spatial(
-            reproject_interp_wrapper,
-            accepts_chunks=True,
-            order=order,
-            **reproj_kwargs)
-
-        return self._new_cube_with(data=newcube,
-                                   wcs=newwcs,
-                                   mask=BooleanArrayMask(newcube_valid.astype('bool'),
-                                                         newwcs),
-                                   meta=self.meta,
-                                  )
-