Use different methods for healpix manipulation. (#436)

* Remove margin fine filtering.

* Use different methods for healpix manipulation.

* Optional dependency for older healpy fits files.

* Allow import of map types. (#437)

* Accomodate changes in cds-healpix.

pyproject.toml

@@ -42,6 +42,7 @@ full = [
     "fsspec[full]", # complete file system specs.
     "ipykernel", # Support for Jupyter notebooks
     "ipywidgets", # useful for tqdm in notebooks.
+    "healpy", # used only in hipscat conversion
 ]
 
 [build-system]

src/hats_import/catalog/arguments.py

@@ -105,8 +105,8 @@ def _check_arguments(self):
                 raise ValueError("pixel_threshold should be between 100 and 1,000,000,000")
             self.mapping_healpix_order = self.highest_healpix_order
 
-        if self.catalog_type not in ("source", "object"):
-            raise ValueError("catalog_type should be one of `source` or `object`")
+        if self.catalog_type not in ("source", "object", "map"):
+            raise ValueError("catalog_type should be one of `source`, `object`, or `map`")
 
         if self.file_reader is None:
             raise ValueError("file_reader is required")

src/hats_import/hipscat_conversion/run_conversion.py

@@ -4,7 +4,7 @@
 import tempfile
 from typing import no_type_check
 
-import hats.pixel_math.healpix_shim as hp
+import healpy as hp
 import numpy as np
 import pyarrow.parquet as pq
 from dask.distributed import as_completed, get_worker
@@ -169,11 +169,6 @@ def _write_nested_fits_map(input_dir, output_dir):
                 map_fits_image = hp.read_map(_tmp_file.name)
             else:
                 map_fits_image = map_fits_image[0]
+    map_fits_image = map_fits_image.astype(np.int32)
 
-    output_file = output_dir / "point_map.fits"
-    with tempfile.NamedTemporaryFile() as _tmp_file:
-        with output_file.open("wb") as _map_file:
-            hp.write_map(
-                _tmp_file.name, map_fits_image, overwrite=True, dtype=np.int32, nest=True, coord="CEL"
-            )
-            _map_file.write(_tmp_file.read())
+    file_io.write_fits_image(map_fits_image, output_dir / "point_map.fits")

src/hats_import/margin_cache/margin_cache_arguments.py

@@ -67,9 +67,7 @@ def _check_arguments(self):
                 "margin_order must be of a higher order than the highest order catalog partition pixel."
             )
 
-        margin_pixel_nside = hp.order2nside(self.margin_order)
-        margin_pixel_avgsize = hp.nside2resol(margin_pixel_nside, arcmin=True)
-        margin_pixel_mindist = hp.avgsize2mindist(margin_pixel_avgsize)
+        margin_pixel_mindist = hp.order2mindist(self.margin_order)
         if margin_pixel_mindist * 60.0 < self.margin_threshold:
             raise ValueError("margin pixels must be larger than margin_threshold")
 

src/hats_import/soap/resume_plan.py

@@ -7,7 +7,7 @@
 
 import hats.pixel_math.healpix_shim as hp
 import numpy as np
-from hats import read_hats
+from hats import pixel_math, read_hats
 from hats.catalog import Catalog
 from hats.io import file_io
 from hats.pixel_math.healpix_pixel import HealpixPixel
@@ -193,8 +193,7 @@ def source_to_object_map(object_catalog, source_catalog):
 
     for source, objects in source_to_object.items():
         # get all neighboring pixels
-        nside = hp.order2nside(source.order)
-        neighbors = hp.get_all_neighbours(nside, source.pixel, nest=True)
+        neighbors = pixel_math.get_margin(source.order, source.pixel, 0)
 
         ## get rid of -1s and normalize to max order
         explosion_factor = 4 ** (max_order - source.order)