aboutsummaryrefslogtreecommitdiffstats
path: root/fg21sim/sky.py
blob: a016cb67e19937cf9c6829606c502499d413c5bf (plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
# Copyright (c) 2017,2019 Weitian LI <wt@liwt.net>
# MIT License

"""
Generic simulation sky supporting both sky patch and HEALPix all-sky
maps.

References
----------
* Python - 3. Data Model
  https://docs.python.org/3/reference/datamodel.html#special-method-names
"""

import logging
import copy
from datetime import datetime

import numpy as np
from scipy import ndimage
from astropy.io import fits
import astropy.units as au
from astropy.coordinates import SkyCoord
from regions import PixCoord, RectanglePixelRegion
from reproject import reproject_interp, reproject_to_healpix
import healpy as hp

from .utils.wcs import make_wcs
from .utils.io import (read_fits_healpix,
                       write_fits_healpix,
                       write_fits_image)
from .utils.random import spherical_uniform
from .utils.units import UnitConversions as AUC


logger = logging.getLogger(__name__)


class SkyBase:
    """
    The base class for both the sky patch and HEALPix all-sky
    map classes.

    Attributes
    ----------
    type_ : str
        The type of the sky image
        Values: ``patch`` or ``healpix``
    data : `~numpy.ndarray`
        The data array read from input sky image, or to be written into
        output FITS file.
    frequency_ : float
        The frequency of the input/output sky image.
        Unit: [MHz]
    pixelsize_ : float
        The pixel size of the sky image.
        Unit: [arcsec]
    creator_ : str
        The creator of the (output) sky image.
        Default: ``__name__``
    header_ : `~astropy.io.fits.Header`
        The FITS header information of the input/output file.
    float32_ : bool
        Whether to use single/float32 data type to save the sky image?
        Default: True
    clobber_ : bool, optional
        Whether to overwrite the existing output file.
        Default: False
    checksum_ : bool, optional
        Whether to calculate the checksum data for the output
        FITS file, which may cost some time.
        Default: False
    """
    def __init__(self, float32=True, clobber=False, checksum=False):
        self.type_ = None
        self.data = None
        self.frequency_ = None  # [MHz]
        self.pixelsize_ = None  # [arcsec]
        self.creator_ = __name__
        self.header_ = fits.Header()
        self.float32_ = float32
        self.clobber_ = clobber
        self.checksum_ = checksum

    def __add__(self, other):
        """Binary arithmetic operation: ``+``."""
        if isinstance(other, self.__class__):
            return self.data + other.data
        elif isinstance(other, (int, float, np.ndarray)):
            return self.data + other
        else:
            raise NotImplementedError

    def __sub__(self, other):
        """Binary arithmetic operation: ``-``."""
        if isinstance(other, self.__class__):
            return self.data - other.data
        elif isinstance(other, (int, float, np.ndarray)):
            return self.data - other
        else:
            raise NotImplementedError

    def __mul__(self, other):
        """Binary arithmetic operation: ``*``."""
        if isinstance(other, self.__class__):
            return self.data * other.data
        elif isinstance(other, (int, float, np.ndarray)):
            return self.data * other
        else:
            raise NotImplementedError

    def __truediv__(self, other):
        """Binary arithmetic operation: ``/``."""
        if isinstance(other, self.__class__):
            return self.data / other.data
        elif isinstance(other, (int, float, np.ndarray)):
            return self.data / other
        else:
            raise NotImplementedError

    def __pow__(self, other):
        """Binary arithmetic operation: ``**``."""
        if isinstance(other, self.__class__):
            return self.data ** other.data
        elif isinstance(other, (int, float, np.ndarray)):
            return self.data ** other
        else:
            raise NotImplementedError

    def __iadd__(self, other):
        """
        Augmented arithmetic assignment: ``+=``.

        NOTE
        ----
        These augmented arithmetic assignment methods should attempt
        to do the operation in-place (modifying ``self``) and return
        the result (which could be, but does not have to be, ``self``).
        """
        if isinstance(other, self.__class__):
            self.data += other.data
            return self
        elif isinstance(other, (int, float, np.ndarray)):
            self.data += other
            return self
        else:
            raise NotImplementedError

    def __isub__(self, other):
        """Augmented arithmetic assignment: ``-=``."""
        if isinstance(other, self.__class__):
            self.data -= other.data
            return self
        elif isinstance(other, (int, float, np.ndarray)):
            self.data -= other
            return self
        else:
            raise NotImplementedError

    def __imul__(self, other):
        """Augmented arithmetic assignment: ``*=``."""
        if isinstance(other, self.__class__):
            self.data *= other.data
            return self
        elif isinstance(other, (int, float, np.ndarray)):
            self.data *= other
            return self
        else:
            raise NotImplementedError

    def __itruediv__(self, other):
        """Augmented arithmetic assignment: ``/=``."""
        if isinstance(other, self.__class__):
            self.data /= other.data
            return self
        elif isinstance(other, (int, float, np.ndarray)):
            self.data /= other
            return self
        else:
            raise NotImplementedError

    def __neg__(self):
        """Unary arithmetic operation: ``-``."""
        return -self.data

    def __abs__(self):
        """Unary arithmetic operation: ``abs()``."""
        return np.abs(self.data)

    def add(self, obj, *args, **kwargs):
        """
        Add/superimpose an object to the sky image.
        """
        raise NotImplementedError

    @property
    def shape(self):
        """
        Numpy array shape of the (current/output) sky data.
        """
        return self.data.shape

    @property
    def frequency(self):
        """
        The frequency of the sky image.
        Unit: [MHz]
        """
        if self.frequency_ is not None:
            return self.frequency_
        else:
            return self.header_.get("FREQ", None)

    @frequency.setter
    def frequency(self, value):
        """
        Set the frequency of the sky image.
        Unit: [MHz]
        """
        self.frequency_ = value

    @property
    def pixelsize(self):
        """
        Pixel size of the sky image.
        Unit: [arcsec]
        """
        return self.pixelsize_

    @property
    def creator(self):
        """
        The creator of the sky image.
        """
        if self.creator_ is not None:
            return self.creator_
        else:
            return self.header_.get("CREATOR", None)

    @creator.setter
    def creator(self, value):
        """
        Set the creator of the sky image.
        """
        self.creator_ = value

    @property
    def header(self):
        """
        The FITS header of the current sky.
        """
        hdr = self.header_.copy()
        hdr["SkyType"] = (self.type_, "Patch / HEALPix")
        hdr["PixSize"] = (self.pixelsize, "Pixel size [arcsec]")
        hdr["CREATOR"] = (self.creator, "Sky Creator")
        hdr["FREQ"] = (self.frequency, "Sky frequency [MHz]")
        hdr["DATE"] = (datetime.utcnow().isoformat()+"Z",
                       "File creation date")
        return hdr

    def merge_header(self, header, update=False):
        """
        Merge the supplied header to the instance's FITS header.
        Do not overwrite the original keywords by default (``update=False``).
        """
        self.header_.extend(header, update=update)

    def add_header(self, key, value, comment=None):
        """
        Add/update a key to the FITS header.
        """
        if comment is None:
            self.header_[key] = value
        else:
            self.header_[key] = (value, comment)

    def add_history(self, history):
        """
        Add history to the FITS header.
        """
        self.header_.add_history(history)

    def copy(self):
        """
        Return a (deep) copy of this instance.
        """
        return copy.deepcopy(self)

    def load(self, infile, frequency=None):
        """
        Load the given sky image into this instance.

        Parameters
        ----------
        infile : str
            The path to the given input sky image.
        frequency : float, optional
            The frequency of the  given sky image if applicable.
            Unit: [MHz]
        """
        raise NotImplementedError

    def open(self, infile, frequency=None):
        """
        Open the given input file as a *new* instance.

        The current instance is *copied*, load the given sky image,
        and then returned.

        Returns
        -------
        sky : a *new* instance with given sky image loaded.
        """
        sky = self.copy()
        sky.load(infile=infile, frequency=frequency)
        return sky

    def write(self, outfile, clobber=None):
        """
        Write the sky image (with current data) into a FITS file.

        Parameters
        ----------
        outfile : str
            The path/filename to the output FITS file.
        clobber : bool, optional
            If not ``None``, then overwrite the default ``self.clobber_``
            from the configuration file, to determine whether to overwrite
            the existing output file.
        """
        raise NotImplementedError

    @property
    def area(self):
        """
        Sky coverage of the sky.
        Unit: [deg^2]
        """
        raise NotImplementedError

    def random_points(self, n=1):
        """
        Generate uniformly distributed random points within the
        sky image (coverage).

        Parameters
        ----------
        n : int, optional
            The number of random points required.
            Default: 1

        Returns
        -------
        lon, lat : float, or 1D `~numpy.ndarray`
            The longitudes and latitudes (in world coordinate)
            generated.
            Unit: [deg]
        """
        raise NotImplementedError


class SkyPatch(SkyBase):
    """
    Support reading & writing FITS file of sky patches.

    NOTE/XXX
    --------
    Currently just use ``CAR`` (Cartesian) sky projection, i.e.,
    assuming a flat sky!!

    NOTE
    ----
    X: FITS width / sky R.A. <-> data array rows
    Y: FITS height / sky Dec. <-> data array columns

    Parameters
    ----------
    size : (xsize, ysize) tuple
        The (pixel) dimensions of the (output) sky patch.
        If the input sky has a different size, then it will be *scaled*
        to match this output size.
    pixelsize : float
        The pixel size of the sky patch, will be used to determine
        the sky coordinates.
        Unit: [arcsec]
    center : (ra, dec) tuple, optional
        The (R.A., Dec.) coordinate of the sky patch center.
        Unit: [deg]
    infile : str, optional
        The path to the input sky patch
    frequency : float, optional
        The frequency of the input sky path
        Unit: [MHz]

    Attributes
    ----------
    type_ : ``patch``
        This is a sky patch.
    data : 2D `~numpy.ndarray`
        The 2D data array of sky image, with shape (self.ysize, self.xsize).
        (HEALPix map stores data in an 1D array.)
    """
    def __init__(self, size, pixelsize, center=(0.0, 0.0),
                 infile=None, frequency=None, **kwargs):
        super().__init__(**kwargs)

        self.type_ = "patch"
        self.xsize, self.ysize = size
        # Initialize an empty image
        self.data = np.zeros(shape=(self.ysize, self.xsize))
        self.pixelsize_ = pixelsize
        self.xcenter, self.ycenter = center

        if infile is not None:
            self.load(infile, frequency)

    @property
    def area(self):
        """
        The sky coverage of this patch.
        Unit: [deg^2]

        XXX/FIXME
        ---------
        Assumed a flat sky, without WCS projection!!
        """
        lonsize, latsize = self.size
        return (lonsize * latsize)

    @property
    def size(self):
        """
        The sky patch size along X/longitude and Y/latitude axes.

        Returns
        -------
        (lonsize, latsize) : float tuple
            Longitudinal and latitudinal sizes
            Unit: [deg]
        """
        return (self.xsize * self.pixelsize * AUC.arcsec2deg,
                self.ysize * self.pixelsize * AUC.arcsec2deg)

    @property
    def center(self):
        return (self.xcenter, self.ycenter)

    @property
    def lon_limit(self):
        """
        The longitudinal (X axis) limits.

        Returns
        -------
        (lon_min, lon_max) : float tuple
            The minimum and maximum longitudes (X axis).
            Unit: [deg]
        """
        lonsize, latsize = self.size
        return (self.xcenter - 0.5*lonsize,
                self.xcenter + 0.5*lonsize)

    @property
    def lat_limit(self):
        """
        The latitudinal (Y axis) limits.

        Returns
        -------
        (lat_min, lat_max) : float tuple
            The minimum and maximum latitudes (Y axis).
            Unit: [deg]
        """
        lonsize, latsize = self.size
        return (self.ycenter - 0.5*latsize,
                self.ycenter + 0.5*latsize)

    def add(self, obj, center):
        """
        Add/superimpose the object image into this sky patch.

        XXX/FIXME
       ----------
        Assumed a flat sky!!

        Parameters
        ----------
        obj : 2D `~numpy.ndarray`
            The object image to be added into the sky.
            NOTE: Should have same pixel size as the sky patch.
        center : (ra, dec) tuple
            The central coordinate (R.A., Dec.) of the given object.
        """
        obj = np.asarray(obj)
        nrow, ncol = obj.shape
        xc, yc = center
        ric, cic = self.world2pix(xc, yc)

        # Index ranges (inclusive at both ends) for the supplied object
        # image on the sky array
        rimin0, rimax0 = ric - nrow//2, ric + (nrow-1)//2
        cimin0, cimax0 = cic - ncol//2, cic + (ncol-1)//2
        # Index ranges for the supplied object image
        rimin1, rimax1 = 0, nrow-1
        cimin1, cimax1 = 0, ncol-1

        # Check the object boundaries
        if ((rimin0 >= self.ysize) or (rimax0 < 0) or
                (cimin0 >= self.xsize) or (cimax0 < 0)):
            logger.warning("The given object is beyond the sky coverage")
            return

        if rimin0 < 0:
            rimin1 = -rimin0
            rimin0 = 0
        if rimax0 >= self.ysize:
            rimax1 = nrow - (rimax0-self.ysize) - 2
            rimax0 = self.ysize-1
        if cimin0 < 0:
            cimin1 = -cimin0
            cimin0 = 0
        if cimax0 >= self.xsize:
            cimax1 = nrow - (cimax0-self.xsize) - 2
            cimax0 = self.xsize-1

        self.data[rimin0:(rimax0+1),
                  cimin0:(cimax0+1)] += obj[rimin1:(rimax1+1),
                                            cimin1:(cimax1+1)]

    def world2pix(self, x, y):
        """
        Convert the world coordinates (R.A., Dec.) into the pixel
        coordinates (indexes) within the sky data array.

        Parameters
        ----------
        x, y : float, `~numpy.ndarray`
            The R.A., Dec. world coordinates
            Unit: [deg]

        Returns
        -------
        ri, ci : int, `~numpy.ndarray`
            The row, column indexes within the sky data array.
        """
        pixelsize = self.pixelsize * AUC.arcsec2deg  # [deg]
        x, y = np.asarray(x), np.asarray(y)  # [deg]
        ri0, ci0 = self.ysize//2, self.xsize//2
        ri = np.round((y - self.ycenter) / pixelsize + ri0).astype(int)
        ci = np.round((x - self.xcenter) / pixelsize + ci0).astype(int)
        return (ri, ci)

    def load(self, infile, frequency=None):
        """
        Load input sky image from file into this instance.

        Parameters
        ----------
        infile : str
            The path to the input sky patch
        frequency : float, optional
            The frequency of the sky patch;
            Unit: [MHz]
        """
        self.infile = infile
        if frequency is not None:
            self.frequency = frequency
        with fits.open(infile) as f:
            self.data = f[0].data
            header = f[0].header.copy(strip=True)
            self.header_.extend(header, update=True)
        self.ysize_in, self.xsize_in = self.data.shape
        logger.info("Loaded sky patch from: %s (%dx%d)" %
                    (infile, self.xsize_in, self.ysize_in))

        if (self.xsize_in != self.xsize) or (self.ysize_in != self.ysize):
            logger.warning("Scale input sky patch to size %dx%d" %
                           (self.xsize, self.ysize))
            zoom = ((self.ysize+0.1)/self.ysize_in,
                    (self.xsize+0.1)/self.xsize_in)
            self.data = ndimage.zoom(self.data, zoom=zoom, order=1)

    def write(self, outfile, clobber=None):
        """
        Write current data to file.
        """
        if clobber is None:
            clobber = self.clobber_
        write_fits_image(outfile, image=self.data, header=self.header,
                         float32=self.float32_,
                         clobber=clobber,
                         checksum=self.checksum_)

    @property
    def header(self):
        """
        FITS header of the sky for storing information in the output file.
        """
        hdr = super().header
        hdr.extend(self.wcs.to_header(), update=True)
        hdr["OBJECT"] = "Sky Patch"
        hdr["EXTNAME"] = "IMAGE"
        hdr["RA0"] = (self.center[0], "R.A. of patch center [deg]")
        hdr["DEC0"] = (self.center[1], "Dec. of patch center [deg]")
        return hdr

    @property
    def wcs(self):
        """
        The WCS header with sky projection information, for sky <->
        pixel coordinate(s) conversion.

        NOTE/XXX
        --------
        Currently just use the `CAR` (Cartesian) projection,
        i.e., assuming a flat sky.
        """
        w = make_wcs(center=(self.xcenter, self.ycenter),
                     size=(self.xsize, self.ysize),
                     pixelsize=self.pixelsize,
                     frame="ICRS", projection="CAR")
        return w

    def contains(self, skycoord):
        """
        Check whether the given (list of) sky coordinate(s) falls
        inside this sky patch (region).

        Parameters
        ----------
        skycoord : `~astropy.coordinate.SkyCoord` or (lon, lat) tuple
            The (list of) sky coordinate(s) to check, or the (list of)
            longitudes and latitudes of sky coordinates [ deg ]

        Returns
        -------
        inside : bool
            (list of) boolean values indicating whether the given
            sky coordinate(s) is inside this sky patch.
        """
        if not isinstance(skycoord, SkyCoord):
            lon, lat = skycoord
            skycoord = SkyCoord(lon, lat, unit=au.deg)
        wcs = self.wcs
        pixcoord = PixCoord.from_sky(skycoord, wcs=wcs)
        center = PixCoord(x=self.xcenter, y=self.ycenter)
        region = RectanglePixelRegion(center=center,
                                      width=self.xsize, height=self.ysize)
        return region.contains(pixcoord)

    def reproject_from(self, data, wcs, squeeze=False, eps=1e-5):
        """
        Reproject the given image/data together with WCS information
        onto the grid of this sky.

        Parameters
        ----------
        data : 2D float `~numpy.ndarray`
            The input data/image to be reprojected
        wcs : `~astropy.wcs.WCS`
            The WCS information of the input data/image (naxis=2)
        squeeze : bool, optional
            Whether to squeeze the reprojected data to only keep
            the pixels greater than a small positive value specified
            by parameter ``eps``.
            Default: False
        eps : float, optional
            The small positive value to specify the squeeze threshold.
            Default: 1e-5

        Returns
        -------
        If ``squeeze=True``, then returns tuple of ``(indexes, values)``,
        otherwise, returns the reprojected image/data array.

        indexes : 1D int `~numpy.ndarray`
            The indexes of the pixels with positive values.
        values : 1D float `~numpy.ndarray`
            The values of the above pixels.

        reprojected : 1D `~numpy.ndarray`
            The reprojected data/image with same shape of this sky,
            i.e., ``self.data``.
        """
        wcs_out = self.wcs
        shape_out = (self.ysize, self.xsize)
        reprojected, __ = reproject_interp(
            input_data=(data, wcs), output_projection=wcs_out,
            shape_out=shape_out)
        reprojected = reprojected.flatten()
        if squeeze:
            with np.errstate(invalid="ignore"):
                indexes = reprojected > eps
            values = reprojected[indexes]
            return (indexes, values)
        else:
            return reprojected

    def random_points(self, n=1):
        """
        Generate uniformly distributed random points within the sky patch.

        Returns
        -------
        lon : float, or 1D `~numpy.ndarray`
            Longitudes (Galactic/equatorial);
            Unit: [deg]
        lat : float, or 1D `~numpy.ndarray`
            Latitudes (Galactic/equatorial);
            Unit: [deg]
        """
        lon_min, lon_max = self.lon_limit
        lat_min, lat_max = self.lat_limit
        lon = np.random.uniform(low=lon_min, high=lon_max, size=n)
        lat = np.random.uniform(low=lat_min, high=lat_max, size=n)
        return (lon, lat)


class SkyHealpix(SkyBase):
    """
    Support the HEALPix all-sky map.

    Parameters
    ----------
    nside : int
        The pixel resolution of HEALPix (must be power of 2)
    infile : str, optional
        The path to the input sky patch
    frequency : float, optional
        The frequency of the input sky path
        Unit: [MHz]

    Attributes
    ----------
    shape : int tuple, (npix,)
        The shape (i.e., length) of the HEALPix array
    pixelsize : float
        The pixel size of the HEALPix map
        Unit: [arcsec]
    """
    def __init__(self, nside, infile=None, frequency=None, **kwargs):
        super().__init__(**kwargs)

        self.type_ = "healpix"
        self.nside = nside
        self.pixelsize_ = (hp.nside2resol(self.nside, arcmin=True) *
                           AUC.arcmin2arcsec)
        self.data = np.zeros(shape=hp.nside2npix(self.nside))

        if infile is not None:
            self.load(infile, frequency)

    @property
    def area(self):
        """
        The sky coverage of this HEALPix map, i.e., all sky = 4π,
        Unit: [deg^2]
        """
        return 4*np.pi * AUC.rad2deg**2

    def load(self, infile, frequency=None):
        """
        Load input HEALPix all-sky map into this instance.

        Parameters
        ----------
        infile : str
            The path to the input HEALPix all-sky map.
        frequency : float, optional
            The frequency of the sky patch;
            Unit: [MHz]
        """
        self.infile = infile
        if frequency is not None:
            self.frequency = frequency
        self.data, header = read_fits_healpix(infile)
        self.header_.extend(header, update=True)
        self.nside_in = header["NSIDE"]
        logger.info("Loaded HEALPix sky map from: {0} (Nside={1})".format(
            infile, self.nside_in))
        if self.nside_in != self.nside:
            self.data = hp.ud_grade(self.data, nside_out=self.nside)
            logger.warning("Upgrade/downgrade sky map from Nside " +
                           "{0} to {1}".format(self.nside_in, self.nside))

    def write(self, outfile, clobber=None):
        """
        Write current data to file.
        """
        if clobber is None:
            clobber = self.clobber_
        write_fits_healpix(outfile, hpmap=self.data, header=self.header,
                           float32=self.float32_,
                           clobber=self.clobber_,
                           checksum=self.checksum_)

    def contains(self, skycoord):
        """
        Shim method to be consistent with ``SkyPatch``.

        Always returns ``True``, since the HEALPix map covers all sky.
        """
        if skycoord.isscalar:
            return True
        else:
            return np.ones(shape=len(skycoord), dtype=np.bool)

    def reproject_from(self, data, wcs, squeeze=False):
        """
        Reproject the given image/data together with WCS information
        onto the grid of this sky.

        Parameters
        ----------
        data : 2D float `~numpy.ndarray`
            The input data/image to be reprojected
        wcs : `~astropy.wcs.WCS`
            The WCS information of the input data/image (naxis=2)
        squeeze : bool, optional
            Whether to squeeze the reprojected data to only keep
            the positive pixels.

        Returns
        -------
        If ``squeeze=True``, then returns tuple of ``(indexes, values)``,
        otherwise, returns the reprojected image/data array.

        indexes : 1D int `~numpy.ndarray`
            The indexes of the pixels with positive values.
        values : 1D float `~numpy.ndarray`
            The values of the above pixels.

        reprojected : 1D `~numpy.ndarray`
            The reprojected data/image with same shape of this sky,
            i.e., ``self.data.shape``.
        """
        eps = 1e-5
        reprojected, __ = reproject_to_healpix(
            input_data=(data, wcs), coord_system_out="galactic",
            nested=False, nside=self.nside)
        if squeeze:
            with np.errstate(invalid="ignore"):
                indexes = reprojected > eps
            values = reprojected[indexes]
            return (indexes, values)
        else:
            return reprojected

    def random_points(self, n=1):
        """
        Generate uniformly distributed random points within the sky
        (i.e., all sky; on an unit sphere).

        Returns
        -------
        lon : float, or 1D `~numpy.ndarray`
            Longitudes (Galactic/equatorial), [0, 360) [deg].
        lat : float, or 1D `~numpy.ndarray`
            Latitudes (Galactic/equatorial), [-90, 90] [deg].
        """
        theta, phi = spherical_uniform(n)
        lon = np.degrees(phi)
        lat = 90.0 - np.degrees(theta)
        return (lon, lat)


##########################################################################


def get_sky(configs):
    """
    Sky class factory function to support both the sky patch and
    HEALPix all-sky map.

    Parameters
    ----------
    configs : ConfigManager object
        An `ConfigManager` object contains default and user configurations.
        For more details, see the example config specification.
    """
    # Parameters for the base sky class
    kwargs = {
        "float32": configs.getn("output/float32"),
        "clobber": configs.getn("output/clobber"),
        "checksum": configs.getn("output/checksum"),
    }

    skytype = configs.getn("sky/type")
    if skytype == "patch":
        sec = "sky/patch"
        xsize = configs.getn(sec+"/xsize")
        ysize = configs.getn(sec+"/ysize")
        xcenter = configs.getn(sec+"/xcenter")
        ycenter = configs.getn(sec+"/ycenter")
        pixelsize = configs.getn(sec+"/pixelsize")
        return SkyPatch(size=(xsize, ysize), pixelsize=pixelsize,
                        center=(xcenter, ycenter), **kwargs)
    elif skytype == "healpix":
        sec = "sky/healpix"
        nside = configs.getn(sec+"/nside")
        return SkyHealpix(nside=nside, **kwargs)
    else:
        raise ValueError("unknown sky type: %s" % skytype)