# Source code for dustmaps.unstructured_map

#!/usr/bin/env python
#
# unstructured_map.py
# Implements a class for querying dust maps with unstructured pixels. Sky
# coordinates are assigned to the nearest pixel.
#
# Copyright (C) 2016  Gregory M. Green
#
# This program is free software; you can redistribute it and/or modify
# the Free Software Foundation; either version 2 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License along
# with this program; if not, write to the Free Software Foundation, Inc.,
# 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
#

from __future__ import print_function, division

import numpy as np
import astropy.coordinates as coordinates
import astropy.units as units
from scipy.spatial import cKDTree as KDTree

from .map_base import DustMap

[docs]class UnstructuredDustMap(DustMap): """ A class for querying dust maps with unstructured pixels. Sky coordinates are assigned to the nearest pixel. """
[docs] def __init__(self, pix_coords, max_pix_scale, metric_p=2, frame=None): """ Args: pix_coords (array-like astropy.coordinates.SkyCoord): The sky coordinates of the pixels. max_pix_scale (scalar astropy.units.Quantity): Maximum angular extent of a pixel. If no pixel is within this distance of a query point, NaN will be returned for that query point. metric_p (Optional[float]): The metric to use. Defaults to 2, which is the Euclidean metric. A value of 1 corresponds to the Manhattan metric, while a value approaching infinity yields the maximum component metric. frame (Optional[str]): The coordinate frame to use internally. Must be a frame understood by astropy.coordinates.SkyCoord. Defaults to None, meaning that the frame will be inferred from pix_coords. """ self._n_pix = pix_coords.shape[0] self._metric_p = metric_p if frame is None: self._frame = pix_coords.frame else: self._frame = frame # Tesselate the space self._pix_vec = self._coords2vec(pix_coords) self._kd = KDTree(self._pix_vec) # Don't query more than this distance from any point self._max_pix_scale = max_pix_scale.to('rad').value
def _coords2vec(self, coords): """ Converts from sky coordinates to unit vectors. Before conversion to unit vectors, the coordiantes are transformed to the coordinate system used internally by the UnstructuredDustMap, which can be set during initialization of the class. Args: coords (astropy.coordinates.SkyCoord): Input coordinates to convert to unit vectors. Returns: Cartesian unit vectors corresponding to the input coordinates, after transforming to the coordinate system used internally by the UnstructuredDustMap. """ # c = coords.transform_to(self._frame) # vec = np.empty((c.shape[0], 2), dtype='f8') # vec[:,0] = coordinates.Longitude(coords.l, wrap_angle=360.*units.deg).deg[:] # vec[:,1] = coords.b.deg[:] # return np.radians(vec) c = coords.transform_to(self._frame).represent_as('cartesian') vec_norm = np.sqrt(c.x**2 + c.y**2 + c.z**2) vec = np.empty((c.shape[0], 3), dtype=c.x.dtype) vec[:,0] = (c.x / vec_norm).value[:] vec[:,1] = (c.y / vec_norm).value[:] vec[:,2] = (c.z / vec_norm).value[:] return vec def _coords2idx(self, coords): """ Converts from sky coordinates to pixel indices. Args: coords (astropy.coordinates.SkyCoord): Sky coordinates. Returns: Pixel indices of the coordinates, with the same shape as the input coordinates. Pixels which are outside the map are given an index equal to the number of pixels in the map. """ x = self._coords2vec(coords) idx = self._kd.query(x, p=self._metric_p, distance_upper_bound=self._max_pix_scale) return idx[1]