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brick_queries.py

+import healpy as hp
+import numpy as np
+from .brick_core import generate_bricks
+from .brick_utils import angular_distance
+
+def bricks_in_disc(nside, ra_center, dec_center, radius_deg, overlap):
+    """
+    Find all bricks whose centers are within a circular region.
+    
+    Parameters
+    ----------
+    nside : int
+        HEALPix resolution parameter.
+    ra_center : float
+        Right Ascension of the circular region center (deg).
+    dec_center : float
+        Declination of the circular region center (deg).
+    radius_deg : float
+        Search radius of the circular region (deg).
+    overlap : float
+        Overlap factor to enlarge brick radius 
+        (1.0 = no overlap, >1.0 = enlarged).
+    
+    Returns
+    -------
+    list of Brick
+        A list of Brick objects whose centers fall within the given region.
+    """
+    theta = np.radians(90 - dec_center)
+    phi = np.radians(ra_center)
+    radius_rad = np.radians(radius_deg)
+    vec = hp.ang2vec(theta, phi)
+    pix_ids = hp.query_disc(nside, vec, radius_rad)
+    return [generate_bricks(nside, pid, overlap=overlap) for pid in pix_ids]
+
+
+def neighbor_bricks(nside, brick_id, overlap):
+    """
+    Get all neighboring bricks of a given brick.
+
+    Parameters
+    ----------
+    nside : int
+        HEALPix resolution parameter.
+    brick_id : int
+        The HEALPix pixel (brick) ID for which neighbors are to be found.
+    overlap : float
+        Overlap factor to enlarge brick radius 
+        (1.0 = no overlap, >1.0 = enlarged).
+
+    Returns
+    -------
+    list of Brick
+        A list of Brick objects corresponding to the neighboring pixels.
+    """
+    neighbors = hp.get_all_neighbours(nside, brick_id)
+    neighbors = [n for n in neighbors if n >= 0]
+    return [generate_bricks(nside, n, overlap=overlap) for n in neighbors]
+
+def nearest_brick_with_distance(nside, ra, dec, overlap):
+    """
+    Find the nearest brick to a given (RA, Dec) position and its angular distance.
+
+    Parameters
+    ----------
+    nside : int
+        HEALPix resolution parameter.
+    ra : float
+        Right Ascension of the target position (deg).
+    dec : float
+        Declination of the target position (deg).
+    overlap : float
+        Overlap factor to enlarge brick radius 
+        (1.0 = no overlap, >1.0 = enlarged).
+
+    Returns
+    -------
+    tuple
+        brick : Brick
+            The nearest Brick object to the given (RA, Dec) position.
+        dist_deg : float
+            The angular distance between the point and the brick center (deg).
+    """
+    theta = np.radians(90 - dec)
+    phi = np.radians(ra)
+    pix_id = hp.ang2pix(nside, theta, phi)
+    brick = generate_bricks(nside, pix_id, overlap=overlap)
+    ra1, dec1 = np.radians(ra), np.radians(dec)
+    ra2, dec2 = np.radians(brick.ra), np.radians(brick.dec)
+    dist_deg = np.degrees(angular_distance(ra1, dec1, ra2, dec2))
+    return brick, dist_deg
+
+def point_in_brick_with_distance(nside, ra, dec, brick_id, overlap):
+    """
+    Check if a given point (RA, Dec) lies within a specific brick and 
+    return its angular distance to the brick center.
+
+    Parameters
+    ----------
+    nside : int
+        HEALPix resolution parameter.
+    ra : float
+        Right Ascension of the target point (deg).
+    dec : float
+        Declination of the target point (deg).
+    brick_id : int
+        The HEALPix pixel (brick) ID to check.
+    overlap : float
+        Overlap factor to enlarge brick radius 
+        (1.0 = no overlap, >1.0 = enlarged).
+
+    Returns
+    -------
+    tuple
+        inside : bool
+            True if the point lies within the brick (distance <= brick.radius).
+        dist : float
+            Angular distance between the point and the brick center (deg).
+    """
+    brick = generate_bricks(nside, brick_id, overlap=overlap)
+    ra1, dec1 = np.radians(ra), np.radians(dec)
+    ra2, dec2 = np.radians(brick.ra), np.radians(brick.dec)
+    dist = np.degrees(angular_distance(ra1, dec1, ra2, dec2))
+    return dist <= brick.radius, dist
+
+def bricks_containing_point(nside, ra, dec, overlap, search_margin=5):
+    """
+    Find all bricks that contain a given point (RA, Dec).
+    
+    Parameters
+    ----------
+    nside : int
+        HEALPix resolution parameter.
+    ra : float
+        Right Ascension of the target point (deg).
+    dec : float
+        Declination of the target point (deg).
+    overlap : float
+        Overlap factor to enlarge brick radius 
+        (1.0 = no overlap, >1.0 = enlarged).
+    search_margin : float, optional
+        Search margin to expand the maximum search radius. Default is 5.
+
+    Returns
+    -------
+    list of Brick
+        A list of Brick objects whose radius contains the given point.
+    """
+    max_radius = (180 / (np.pi * np.sqrt(3) * nside)) * search_margin * overlap
+    theta = np.radians(90 - dec)
+    phi = np.radians(ra)
+    vec = hp.ang2vec(theta, phi)
+    pix_ids = hp.query_disc(nside, vec, np.radians(max_radius), inclusive=True)
+    result = []
+    for pid in pix_ids:
+        brick = generate_bricks(nside, pid, overlap=overlap)
+        ra1, dec1 = np.radians(ra), np.radians(dec)
+        ra2, dec2 = np.radians(brick.ra), np.radians(brick.dec)
+        dist = np.degrees(angular_distance(ra1, dec1, ra2, dec2))
+        if dist <= brick.radius:
+            result.append(brick)
+    return result
+
+
+class BrickQueries:
+    def __init__(self, nside, overlap=1.0):
+        self.nside = nside
+        self.overlap = overlap
+        self.methods = {
+            "disc_bricks": self.get_bricks_in_disc,
+            "neighbors": self.get_neighbor_bricks,
+            "nearest": self.get_nearest_brick_with_distance,
+            "contains_point": self.point_in_brick,
+            "find_bricks": self.get_bricks_containing_point
+        }
+
+    def __getattr__(self, name):
+        if name in self.methods:
+            return self.methods[name]
+        else:
+            raise AttributeError(f"'{self.__class__.__name__}' object has no attribute '{name}'")
+
+    def get_bricks_in_disc(self, ra_center, dec_center, radius_deg):
+        return bricks_in_disc(self.nside, ra_center, dec_center, radius_deg, self.overlap)
+
+    def get_neighbor_bricks(self, brick_id):
+        return neighbor_bricks(self.nside, brick_id, self.overlap)
+
+    def get_nearest_brick_with_distance(self, ra, dec):
+        return nearest_brick_with_distance(self.nside, ra, dec, self.overlap)
+
+    def point_in_brick(self, ra, dec, brick_id):
+        return point_in_brick_with_distance(self.nside, ra, dec, brick_id, self.overlap)
+
+    def get_bricks_containing_point(self, ra, dec, search_margin=5):
+        return bricks_containing_point(self.nside, ra, dec, self.overlap, search_margin)