Coverage for python/lsst/sims/maf/slicers/healpixSubsetSlicer.py : 10%

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1"""A HealpixSubsetSlicer - define the subset of healpixels to use to calculate metrics."""
3from functools import wraps
4import numpy as np
5import healpy as hp
7import lsst.sims.utils as simsUtils
9from lsst.sims.maf.plots.spatialPlotters import HealpixSkyMap, HealpixHistogram, HealpixPowerSpectrum
11from .baseSpatialSlicer import BaseSpatialSlicer
14__all__ = ['HealpixSubsetSlicer']
17class HealpixSubsetSlicer(BaseSpatialSlicer):
18 """
19 A spatial slicer that evaluates pointings on a subset of a healpix-based grid.
20 The advantage of using this healpixSubsetSlicer (rather than just putting the RA/Dec values into
21 the UserPointsSlicer, which is another valid approach) is that you preserve the full healpix array.
22 This means you could do things like calculate the power spectrum and plot without remapping into
23 healpixels first. The downside is that you must first (externally) define the healpixels that you
24 wish to use - the lsst.sims.featureScheduler.footprints is a useful add-on here.
26 When plotting with RA/Dec, the default HealpixSkyMap can be used, corresponding to
27 {'rot': (0, 0, 0), 'flip': 'astro'}.
29 Parameters
30 ----------
31 nside : int
32 The nside parameter of the healpix grid. Must be a power of 2.
33 hpid : np.ndarray
34 The subset of healpix id's to use to calculate the metric.
35 Because the hpid should be defined based on a particular nside, these first two
36 arguments are not optional for this slicer.
37 lonCol : str, optional
38 Name of the longitude (RA equivalent) column to use from the input data.
39 Default fieldRA
40 latCol : str, optional
41 Name of the latitude (Dec equivalent) column to use from the input data.
42 Default fieldDec
43 latLonDeg : boolean, optional
44 Flag indicating whether the lat and lon values in the input data are in
45 degrees (True) or radians (False).
46 Default True.
47 verbose : boolean, optional
48 Flag to indicate whether or not to write additional information to stdout during runtime.
49 Default True.
50 badval : float, optional
51 Bad value flag, relevant for plotting. Default the hp.UNSEEN value (in order to properly flag
52 bad data points for plotting with the healpix plotting routines). This should not be changed.
53 useCache : boolean
54 Flag allowing the user to indicate whether or not to cache (and reuse) metric results
55 calculated with the same set of simulated data pointings.
56 This can be safely set to True for slicers not using maps and will result in increased speed.
57 When calculating metric results using maps, the metadata at each individual ra/dec point may
58 influence the metric results and so useCache should be set to False.
59 Default True.
60 leafsize : int, optional
61 Leafsize value for kdtree. Default 100.
62 radius : float, optional
63 Radius for matching in the kdtree. Equivalent to the radius of the FOV. Degrees.
64 Default 1.75.
65 useCamera : boolean, optional
66 Flag to indicate whether to use the LSST camera footprint or not.
67 Default False.
68 rotSkyPosColName : str, optional
69 Name of the rotSkyPos column in the input data. Only used if useCamera is True.
70 Describes the orientation of the camera orientation compared to the sky.
71 Default rotSkyPos.
72 mjdColName : str, optional
73 Name of the exposure time column. Only used if useCamera is True.
74 Default observationStartMJD.
75 chipNames : array-like, optional
76 List of chips to accept, if useCamera is True. This lets users turn 'on' only a subset of chips.
77 Default 'all' - this uses all chips in the camera.
78 """
79 def __init__(self, nside, hpid, lonCol ='fieldRA',
80 latCol='fieldDec', latLonDeg=True, verbose=True, badval=hp.UNSEEN,
81 useCache=True, leafsize=100, radius=1.75,
82 useCamera=False, rotSkyPosColName='rotSkyPos',
83 mjdColName='observationStartMJD', chipNames='all'):
84 """Instantiate and set up healpix slicer object."""
85 super().__init__(verbose=verbose,
86 lonCol=lonCol, latCol=latCol,
87 badval=badval, radius=radius, leafsize=leafsize,
88 useCamera=useCamera, rotSkyPosColName=rotSkyPosColName,
89 mjdColName=mjdColName, chipNames=chipNames, latLonDeg=latLonDeg)
90 # Valid values of nside are powers of 2.
91 # nside=64 gives about 1 deg resolution
92 # nside=256 gives about 13' resolution (~1 CCD)
93 # nside=1024 gives about 3' resolution
94 # Check validity of nside:
95 if not(hp.isnsideok(nside)):
96 raise ValueError('Valid values of nside are powers of 2.')
97 if len(hpid) > hp.nside2npix(nside):
98 raise ValueError('Nside (%d) and length of hpid (%d) seem incompatible.' % (nside,
99 hp.nside2npix(nside)))
100 self.nside = int(nside)
101 self.hpid = hpid
102 self.pixArea = hp.nside2pixarea(self.nside)
103 self.nslice = hp.nside2npix(self.nside)
104 self.spatialExtent = [0, self.nslice-1]
105 self.shape = self.nslice
106 if self.verbose:
107 print('HealpixSubsetSlicer using NSIDE=%d, ' % (self.nside) + \
108 'approximate resolution %f arcminutes' % (hp.nside2resol(self.nside, arcmin=True)))
109 # Set variables so slicer can be re-constructed
110 self.slicer_init = {'nside': nside, 'hpid': hpid, 'lonCol': lonCol, 'latCol': latCol,
111 'radius': radius}
112 if useCache:
113 # useCache set the size of the cache for the memoize function in sliceMetric.
114 binRes = hp.nside2resol(nside) # Pixel size in radians
115 # Set the cache size to be ~2x the circumference
116 self.cacheSize = int(np.round(4.*np.pi/binRes))
117 # Set up slicePoint metadata.
118 self.slicePoints['nside'] = nside
119 self.slicePoints['sid'] = np.arange(self.nslice)
120 self.slicePoints['ra'], self.slicePoints['dec'] = self._pix2radec(self.slicePoints['sid'])
121 # Set the default plotting functions.
122 self.plotFuncs = [HealpixSkyMap, HealpixHistogram, HealpixPowerSpectrum]
124 def __eq__(self, otherSlicer):
125 """Evaluate if two slicers are equivalent."""
126 # If the two slicers are both healpix slicers, check nsides value.
127 result = False
128 if isinstance(otherSlicer, HealpixSubsetSlicer):
129 if otherSlicer.nside == self.nside:
130 if np.all(otherSlicer.hpid == self.hpid):
131 if (otherSlicer.lonCol == self.lonCol and otherSlicer.latCol == self.latCol):
132 if otherSlicer.radius == self.radius:
133 if otherSlicer.useCamera == self.useCamera:
134 if otherSlicer.chipsToUse == self.chipsToUse:
135 if otherSlicer.rotSkyPosColName == self.rotSkyPosColName:
136 if np.all(otherSlicer.shape == self.shape):
137 result = True
138 return result
140 def _pix2radec(self, islice):
141 """Given the pixel number / sliceID, return the RA/Dec of the pointing, in radians."""
142 # Calculate RA/Dec in RADIANS of pixel in this healpix slicer.
143 # Note that ipix could be an array,
144 # in which case RA/Dec values will be an array also.
145 lat, ra = hp.pix2ang(self.nside, islice)
146 # Move dec to +/- 90 degrees
147 dec = np.pi/2.0 - lat
148 return ra, dec
150 # This slicer does iterate over all of the slicepoints - mainly so it can return a masked value for
151 # non-calculated healpixels.
152 def setupSlicer(self, simData, maps=None):
153 """Use simData[self.lonCol] and simData[self.latCol] (in radians) to set up KDTree.
155 Parameters
156 -----------
157 simData : numpy.recarray
158 The simulated data, including the location of each pointing.
159 maps : list of lsst.sims.maf.maps objects, optional
160 List of maps (such as dust extinction) that will run to build up additional metadata at each
161 slicePoint. This additional metadata is available to metrics via the slicePoint dictionary.
162 Default None.
163 """
164 if maps is not None:
165 if self.cacheSize != 0 and len(maps) > 0:
166 warnings.warn('Warning: Loading maps but cache on.'
167 'Should probably set useCache=False in slicer.')
168 self._runMaps(maps)
169 self._setRad(self.radius)
170 if self.useCamera:
171 self._setupLSSTCamera()
172 self._presliceFootprint(simData)
173 else:
174 if self.latLonDeg:
175 self._buildTree(np.radians(simData[self.lonCol]),
176 np.radians(simData[self.latCol]), self.leafsize)
177 else:
178 self._buildTree(simData[self.lonCol], simData[self.latCol], self.leafsize)
180 @wraps(self._sliceSimData)
181 def _sliceSimData(islice):
182 """Return indexes for relevant opsim data at slicepoint
183 (slicepoint=lonCol/latCol value .. usually ra/dec)."""
184 if islice not in self.hpid:
185 return {'idxs': [], 'slicePoint': {self.slicePoints['sid'][islice],
186 self.slicePoints['ra'][islice],
187 self.slicePoints['dec'][islice]}}
188 # Build dict for slicePoint info
189 slicePoint = {}
190 if self.useCamera:
191 indices = self.sliceLookup[islice]
192 slicePoint['chipNames'] = self.chipNames[islice]
193 else:
194 sx, sy, sz = simsUtils._xyz_from_ra_dec(self.slicePoints['ra'][islice],
195 self.slicePoints['dec'][islice])
196 # Query against tree.
197 indices = self.opsimtree.query_ball_point((sx, sy, sz), self.rad)
199 # Loop through all the slicePoint keys. If the first dimension of slicepoint[key] has
200 # the same shape as the slicer, assume it is information per slicepoint.
201 # Otherwise, pass the whole slicePoint[key] information. Useful for stellar LF maps
202 # where we want to pass only the relevant LF and the bins that go with it.
203 for key in self.slicePoints:
204 if len(np.shape(self.slicePoints[key])) == 0:
205 keyShape = 0
206 else:
207 keyShape = np.shape(self.slicePoints[key])[0]
208 if (keyShape == self.nslice):
209 slicePoint[key] = self.slicePoints[key][islice]
210 else:
211 slicePoint[key] = self.slicePoints[key]
212 return {'idxs': indices, 'slicePoint': slicePoint}
213 setattr(self, '_sliceSimData', _sliceSimData)