update to use latest healpix math functions

src/lsdb/dask/merge_catalog_functions.py

@@ -86,7 +86,7 @@ def align_catalogs(left: Catalog, right: Catalog, add_right_margin: bool = True)
         else right.hc_structure.pixel_tree.to_moc()
     )
     if right_added_radius is not None:
-        right_moc_depth_resol = hp.nside2resol(hp.order2nside(right_moc.max_order), arcmin=True) * 60
+        right_moc_depth_resol = hp.order2resol(right_moc.max_order, arcmin=True) * 60
         if right_added_radius < right_moc_depth_resol:
             right_moc = copy_moc(right_moc).add_neighbours()
         else:

src/lsdb/loaders/dataframe/margin_catalog_generator.py

@@ -169,12 +169,10 @@ def _create_margins(self, margin_pairs_df: pd.DataFrame) -> Dict[HealpixPixel, p
             A dictionary mapping each margin pixel to the respective DataFrame.
         """
         margin_pixel_df_map: Dict[HealpixPixel, npd.NestedFrame] = {}
-        self.dataframe["margin_pixel"] = hp.ang2pix(
-            2**self.margin_order,
+        self.dataframe["margin_pixel"] = hp.radec2pix(
+            self.margin_order,
             self.dataframe[self.hc_structure.catalog_info.ra_column].to_numpy(),
             self.dataframe[self.hc_structure.catalog_info.dec_column].to_numpy(),
-            lonlat=True,
-            nest=True,
         )
         constrained_data = self.dataframe.reset_index().merge(margin_pairs_df, on="margin_pixel")
         if len(constrained_data):

tests/lsdb/catalog/test_catalog.py

@@ -324,7 +324,7 @@ def test_prune_empty_partitions_all_are_removed(small_sky_order1_catalog):
 
 def test_skymap_data(small_sky_order1_catalog):
     def func(df, healpix):
-        return len(df) / hp.nside2pixarea(hp.order2nside(healpix.order), degrees=True)
+        return len(df) / hp.order2pixarea(healpix.order, degrees=True)
 
     skymap = small_sky_order1_catalog.skymap_data(func)
     for pixel in skymap.keys():
@@ -335,7 +335,7 @@ def func(df, healpix):
 
 def test_skymap_data_order(small_sky_order1_catalog):
     def func(df, healpix):
-        return len(df) / hp.nside2pixarea(hp.order2nside(healpix.order), degrees=True)
+        return len(df) / hp.order2pixarea(healpix.order, degrees=True)
 
     order = 3
 
@@ -357,7 +357,7 @@ def func(df, healpix):
 
 def test_skymap_data_wrong_order(small_sky_order1_catalog):
     def func(df, healpix):
-        return len(df) / hp.nside2pixarea(hp.order2nside(healpix.order), degrees=True)
+        return len(df) / hp.order2pixarea(healpix.order, degrees=True)
 
     order = 0
 
@@ -367,7 +367,7 @@ def func(df, healpix):
 
 def test_skymap_histogram(small_sky_order1_catalog):
     def func(df, healpix):
-        return len(df) / hp.nside2pixarea(hp.order2nside(healpix.order), degrees=True)
+        return len(df) / hp.order2pixarea(healpix.order, degrees=True)
 
     pixel_map = small_sky_order1_catalog.skymap_data(func)
     pixel_map = {pixel: value.compute() for pixel, value in pixel_map.items()}
@@ -384,7 +384,7 @@ def func(df, healpix):
 
 def test_skymap_histogram_empty(small_sky_order1_catalog):
     def func(df, healpix):
-        return len(df) / hp.nside2pixarea(hp.order2nside(healpix.order), degrees=True)
+        return len(df) / hp.order2pixarea(healpix.order, degrees=True)
 
     expected_img = np.full(12, 1)
     img = small_sky_order1_catalog.cone_search(0, 0, 1).skymap_histogram(func, default_value=1)
@@ -396,7 +396,7 @@ def test_skymap_histogram_order_default(small_sky_order1_catalog):
     default = -1.0
 
     def func(df, _):
-        return len(df) / hp.nside2pixarea(hp.order2nside(order), degrees=True)
+        return len(df) / hp.order2pixarea(order, degrees=True)
 
     computed_catalog = small_sky_order1_catalog.compute()
     order_3_pixels = spatial_index_to_healpix(computed_catalog.index.to_numpy(), order)
@@ -412,7 +412,7 @@ def test_skymap_histogram_null_values_order_default(small_sky_order1_catalog):
     default = -1.0
 
     def func(df, healpix):
-        density = len(df) / hp.nside2pixarea(hp.order2nside(healpix.order), degrees=True)
+        density = len(df) / hp.order2pixarea(healpix.order, degrees=True)
         return density if healpix.pixel % 2 == 0 else None
 
     pixels = list(small_sky_order1_catalog._ddf_pixel_map.keys())
@@ -438,7 +438,7 @@ def test_skymap_histogram_null_values_order(small_sky_order1_catalog):
     default = -1.0
 
     def func(df, healpix):
-        density = len(df) / hp.nside2pixarea(hp.order2nside(healpix.order), degrees=True)
+        density = len(df) / hp.order2pixarea(healpix.order, degrees=True)
         return density if healpix.pixel % 2 == 0 else None
 
     pixels = list(small_sky_order1_catalog._ddf_pixel_map.keys())
@@ -462,7 +462,7 @@ def test_skymap_histogram_order_empty(small_sky_order1_catalog):
     order = 3
 
     def func(df, healpix):
-        return len(df) / hp.nside2pixarea(hp.order2nside(healpix.order), degrees=True)
+        return len(df) / hp.order2pixarea(healpix.order, degrees=True)
 
     catalog = small_sky_order1_catalog.cone_search(0, 0, 1)
     _, non_empty_partitions = catalog._get_non_empty_partitions()
@@ -477,7 +477,7 @@ def test_skymap_histogram_order_some_partitions_empty(small_sky_order1_catalog):
     order = 3
 
     def func(df, healpix):
-        return len(df) / hp.nside2pixarea(hp.order2nside(healpix.order), degrees=True)
+        return len(df) / hp.order2pixarea(healpix.order, degrees=True)
 
     catalog = small_sky_order1_catalog.query("ra > 350 and dec < -50")
     _, non_empty_partitions = catalog._get_non_empty_partitions()
@@ -502,7 +502,7 @@ def test_skymap_plot(small_sky_order1_catalog, mocker):
     mocker.patch("lsdb.catalog.dataset.healpix_dataset.plot_healpix_map")
 
     def func(df, healpix):
-        return len(df) / hp.nside2pixarea(hp.order2nside(healpix.order), degrees=True)
+        return len(df) / hp.order2pixarea(healpix.order, degrees=True)
 
     small_sky_order1_catalog.skymap(func)
     pixel_map = small_sky_order1_catalog.skymap_data(func)
@@ -600,9 +600,7 @@ def add_col(df, pixel):
     assert isinstance(mapped, Catalog)
     assert "pix" in mapped.columns
     mapcomp = mapped.compute()
-    pix_col = hp.ang2pix(
-        hp.order2nside(1), mapcomp["ra"].to_numpy(), mapcomp["dec"].to_numpy(), lonlat=True, nest=True
-    )
+    pix_col = hp.radec2pix(1, mapcomp["ra"].to_numpy(), mapcomp["dec"].to_numpy())
     assert np.all(mapcomp["pix"] == pix_col)
 
 

tests/lsdb/loaders/dataframe/test_from_dataframe.py

@@ -95,7 +95,7 @@ def test_partitions_on_map_equal_partitions_in_df(small_sky_order1_df, small_sky
         partition_df = catalog._ddf.partitions[partition_index].compute()
         assert isinstance(partition_df, pd.DataFrame)
         for _, row in partition_df.iterrows():
-            ipix = hp.ang2pix(2**hp_pixel.order, row["ra"], row["dec"], nest=True, lonlat=True)
+            ipix = hp.radec2pix(hp_pixel.order, row["ra"], row["dec"])
             assert ipix == hp_pixel.pixel