Remove margin fine filtering, and healpy dependency. (#434)

* Remove margin fine filtering.

* Remove unused unseen.

* Remove margin fine filtering. (#421)

* Remove margin fine filtering.

* Remove unused unseen.

* Use cdshealpix for margin pixel finding.

* Unused import.

* add color_by_order option and plot on existing axes

* reset matplotlib after tests

* pylint

* Migrate ang2vec (#426)

* Use astropy for ang2vec conversion

* Allow for kwargs in ang2vec

* use mindist instead of resol for margin filter

* Replace healpy in healpix_shim pixel math operations

* isort

* support np arrays

* use order instead of nside

* remove unused variable

* Return int64 from radec2pix (#432)

* Migrate box filtering to use MOCpy (#428)

* Use mocpy in box filtering

* Update tests

* Ensure moc is correct in box filter test

* Remove unused healpy methods

* Pin mocpy

* Remove healpy references. (#433)

* Address merge conflicts

---------

Co-authored-by: Sean McGuire <123987820+smcguire-cmu@users.noreply.github.com>
Co-authored-by: Sean McGuire <seanmcgu@andrew.cmu.edu>
Co-authored-by: Sandro Campos <scampos@andrew.cmu.edu>

docs/guide/contributing.rst

@@ -58,19 +58,7 @@ Notes:
 
 .. tip::
     Installing on Mac
-
-    Native prebuilt binaries for healpy on Apple Silicon Macs 
-    `do not yet exist <https://healpy.readthedocs.io/en/latest/install.html#binary-installation-with-pip-recommended-for-most-other-python-users>`_, 
-    so it's recommended to install via conda before proceeding to hats.
-
-    .. code-block:: bash
-
-        $ conda config --add channels conda-forge
-        $ conda install healpy
-        $ git clone https://github.com/astronomy-commons/hats
-        $ cd hats
-        $ pip install -e .
-        
+
     When installing dev dependencies, make sure to include the single quotes.
 
     .. code-block:: bash

docs/index.rst

@@ -36,7 +36,6 @@ operations on top of these utilities. Some known extensions:
    :caption: Developers
 
    guide/contributing
-   Pixel math <guide/pixel_math>
    API Reference <autoapi/index>
 
 Getting Started

pyproject.toml

@@ -22,10 +22,9 @@ dependencies = [
     "aiohttp", # http filesystem support
     "astropy",
     "fsspec>=2023.10.0", # Used for abstract filesystems
-    "healpy",
     "jproperties",
     "matplotlib>=3.3,<3.9",
-    "mocpy",
+    "mocpy>=0.17.1",
     "numba>=0.58",
     "numpy<3", 
     "pandas",

src/hats/catalog/healpix_dataset/healpix_dataset.py

@@ -155,12 +155,10 @@ def filter_by_cone(self, ra: float, dec: float, radius_arcsec: float) -> Self:
         )
         return self.filter_by_moc(cone_moc)
 
-    def filter_by_box(
-        self, ra: Tuple[float, float] | None = None, dec: Tuple[float, float] | None = None
-    ) -> Self:
+    def filter_by_box(self, ra: Tuple[float, float], dec: Tuple[float, float]) -> Self:
         """Filter the pixels in the catalog to only include the pixels that overlap with a
-        right ascension or declination range. In case both ranges are provided, filtering
-        is performed using a polygon.
+        zone, defined by right ascension and declination ranges. The right ascension edges follow
+        great arc circles and the declination edges follow small arc circles.
 
         Args:
             ra (Tuple[float, float]): Right ascension range, in degrees

src/hats/catalog/margin_cache/margin_catalog.py

@@ -33,8 +33,8 @@ def filter_by_moc(self, moc: MOC) -> Self:
             pixel sizes.
         """
         max_order = moc.max_order
-        max_order_size = hp.nside2resol(2**max_order, arcmin=True)
-        if self.catalog_info.margin_threshold > max_order_size * 60:
+        max_order_size_arcsec = hp.order2mindist(max_order) * 60
+        if self.catalog_info.margin_threshold > max_order_size_arcsec:
             raise ValueError(
                 f"Cannot Filter Margin: Margin size {self.catalog_info.margin_threshold} is "
                 f"greater than the size of a pixel at the highest order {max_order}."

src/hats/catalog/partition_info.py

@@ -274,7 +274,7 @@ def calculate_fractional_coverage(self):
         """Calculate what fraction of the sky is covered by partition tiles."""
         pixel_orders = [p.order for p in self.pixel_list]
         cov_order, cov_count = np.unique(pixel_orders, return_counts=True)
-        area_by_order = [hp.nside2pixarea(hp.order2nside(order), degrees=True) for order in cov_order]
+        area_by_order = [hp.order2pixarea(order, degrees=True) for order in cov_order]
         # 41253 is the number of square degrees in a sphere
         # https://en.wikipedia.org/wiki/Square_degree
         return (area_by_order * cov_count).sum() / (360**2 / np.pi)