def __init__(
self,
freq=888,
plot_hpx_order=7,
gridsep=30,
cmap=matplotlib.pyplot.get_cmap("Dark2"),
projection="Mollweide",
**kwargs,
):
if projection not in skymapper.projection_register.keys():
raise ValueError(
f"Projection {projection} not valid for skymapper")
self.freq = freq
self.plot_hpx_order = plot_hpx_order
self.nside = 2**self.plot_hpx_order
self.gridsep = gridsep
if isinstance(cmap, matplotlib.colors.ListedColormap):
self.cmap = cmap.colors
else:
self.cmap = cmap
# make the background map
gsm_nside = 512 # pygsm outputs nside=512
npix = healpy.nside2npix(gsm_nside)
ra, dec = healpy.pix2ang(gsm_nside, np.arange(npix), lonlat=True)
coords = SkyCoord(ra, dec, unit="deg")
gsm = pygsm.GlobalSkyModel()
# this is in Galactic coords - convert back to equatorial
bg_gsm = gsm.generate(self.freq)
coords_gal = coords.galactic
bg_gsm_equatorial = healpy.pixelfunc.get_interp_val(bg_gsm,
coords_gal.l.value,
coords_gal.b.value,
lonlat=True)
bg_gsm_equatorial_o7 = healpy.ud_grade(
bg_gsm_equatorial, self.nside) # degrade the resolution
# self.projection = skymapper.Mollweide(lon_0=RA0)
self.projection = getattr(skymapper, projection)(**kwargs)
self.ax = skymapper.Map(self.projection, interactive=False)
self.ax.grid(sep=self.gridsep)
self.color_cycle = cycler(facecolors=self.cmap)
self.color_cycle_it = iter(self.color_cycle)
# and plot the background map
self.ax.healpix(
bg_gsm_equatorial_o7,
color_percentiles=[0, 99],
cmap="Greys",
norm=matplotlib.colors.LogNorm(),
)
self.plotted_surveys = []
self.labels = []
import skymapper as skm
if __name__ == "__main__":
# cycle through all defined projections and show the full sky
# with default graticules
args = {"lon_0": 0}
conic_args = {"lon_0": 0, "lat_0": -10, "lat_1": -40, "lat_2": 10}
for name, proj_cls in skm.projection_register.items():
proj = None
try:
proj = proj_cls(**args)
except TypeError:
try:
proj = proj_cls(**conic_args)
except TypeError:
pass
if proj is not None:
map = skm.Map(proj, interactive=False)
map.grid()
map.title(name)
map.show()
def plot_hp_skymapper(obs, mask, projection=None, filename=None, vmax=None, cmap=None, cb_label=None, nside_out=True):
"""
Plot a healpix masked map using skymapper.
Parameters
----------
obs : array
Healpix map.
mask : array
Mask map.
projection : type
- 'DESY3', in which case it uses precomputed best projection for the Y3 footprint,
- a predefined skymapper projection objectself,
- or None, if which case the projection is infered from the mask.
filename : string
If not None, the name of the file to save the figure (the default is None).
vmax : type
- a float, in which case the color scale goes from -vmax to +vmax
- 'best', in which case skymapper uses the 10-90 percentiles
- None, in which case the min/max values of `obs` are used.
cmap : type
Color map (the default is None).
cb_label : string
Label of the color bar (the default is None).
nside_out : bool or int
Whether to degrade obs to make if faster or the nside to use (the default
is True, in which case nside=256 is used).
Returns
-------
type
Description of returned object.
Raises
-------
ExceptionName
Why the exception is raised.
"""
import skymapper as skm
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import make_axes_locatable
assert obs.shape == mask.shape, "[plot_hp_skymapper] `obs` and `mask` don't have the same shape."
fig = plt.figure(figsize=(10,6))
ax = fig.add_subplot(111)
nside_in = hp.npix2nside(len(mask))
theta, phi = hp.pix2ang(nside_in, np.arange(len(mask))[mask.astype(bool)])
ra, dec = thetaphi2radec(theta, phi)
if projection == 'DESY3':
# define the best Albers projection for the footprint
# minimizing the variation in distortion
# crit = skm.meanDistortion
# proj = skm.Albers.optimize(a['ra'], a['dec'], crit=crit)
proj = skm.Albers( 28.51234891, -43.90175288, -55.63596295, -32.39570739)
else :
if projection is None:
crit = skm.meanDistortion
proj = skm.Albers.optimize(ra, dec, crit=crit)
# construct map: will hold figure and projection
# the outline of the sphere can be styled with kwargs for matplotlib Polygon
map = skm.Map(proj, ax=ax)
# add graticules, separated by 15 deg
# the lines can be styled with kwargs for matplotlib Line2D
# additional arguments for formatting the graticule labels
# sep = 15
map.grid()
map.focus(ra, dec)
obs_plot = np.copy(obs)
maskmap(obs_plot, mask, fill_UNSEEN=False)
if nside_out:
if type(nside_out) is int:
obs_plot = hp.ud_grade(obs_plot, nside_out=nside_out)
else:
obs_plot = hp.ud_grade(obs_plot, nside_out=256)
if type(vmax) is float:
mappable = map.healpix(obs_plot, cmap=cmap, vmin=-vmax, vmax=vmax)
if vmax == 'best' : # skymapper uses 10-90 percentiles
mappable = map.healpix(obs_plot, cmap=cmap)
if vmax is None :
mappable = map.healpix(obs_plot, cmap=cmap, vmin=np.min(obs_plot), vmax=np.max(obs_plot))
map.colorbar(mappable, cb_label=cb_label)
plt.tight_layout()
if filename is not None:
plt.savefig(filename, dpi=300)
import numpy as np
import skymapper as skm
import matplotlib.pyplot as plt
from astropy.table import Table, vstack
from astropy.coordinates import SkyCoord
from astropy import units as u
fig = plt.figure(figsize=(7, 3.5))
proj = skm.Hammer()
footprint = skm.Map(skm.Hammer(), facecolor='white', ax=fig.gca())
sep = 30
footprint.grid(sep=sep)
nside = 1024
des = skm.survey.DES()
vertex = footprint.footprint(des, nside, facecolor='red', alpha=0.4)
footprint.ax.text(0,
np.deg2rad(-70),
'DES',
color='red',
horizontalalignment='center',
verticalalignment='bottom')
pixels, rap, decp, vertices = skm.healpix.getGrid(nside, return_vertices=True)
# http://kids.strw.leidenuniv.nl/overview.php
ra_min_list = [0, 329.5, 156, 225, 128.5]
ra_max_list = [53.5, 360, 225, 238, 141.5]
dec_min_list = [-35.6, -35.6, -5, -3, -2]
dec_max_list = [-25.7, -25.7, +4, +4, +3]
inside = np.zeros(len(pixels), dtype=bool)
dec = dec[inside]
return ra, dec
if __name__ == "__main__":
# load RA/Dec from catalog
size = 10000
des = skm.survey.DES()
ra, dec = getCatalog(size, survey=des)
# define the best WagnerIV projection for the footprint
# minimizing the variation in distortion, aka ellipticity
for crit in [skm.meanDistortion, skm.maxDistortion, skm.stdDistortion]:
proj = skm.WagnerIV.optimize(ra, dec, crit)
map = skm.Map(proj)
map.grid()
#map.labelMeridianAtParallel(-90, meridians=[])
map.footprint(des, nside=64, zorder=20, facecolor='w', alpha=0.3)
a, b = proj.distortion(ra, dec)
c = map.extrapolate(ra,
dec,
1 - np.abs(b / a),
vmin=0,
vmax=0.3,
resolution=72)
cb = map.colorbar(c, cb_label='distortion')
map.focus(ra, dec)
map.title(proj.__class__.__name__ + ": " + crit.__name__)
if __name__ == "__main__":
# load RA/Dec from catalog
size = 100000
des = skm.survey.DES()
ra, dec = getCatalog(size, survey=des)
# define the best Albers projection for the footprint
# minimizing the variation in distortion
crit = skm.stdDistortion
proj = skm.Albers.optimize(ra, dec, crit=crit)
# construct map: will hold figure and projection
# the outline of the sphere can be styled with kwargs for matplotlib Polygon
map = skm.Map(proj)
# add graticules, separated by 15 deg
# the lines can be styled with kwargs for matplotlib Line2D
# additional arguments for formatting the graticule labels
sep = 15
map.grid(sep=sep)
# # add footprint, retain the polygon for clipping
# footprint = map.footprint("DES", zorder=20, edgecolor='#2222B2', facecolor='None', lw=1)
#
#### 1. plot density in healpix cells ####
nside = 32
mappable = map.density(ra, dec, nside=nside)
cb = map.colorbar(mappable, cb_label="$n$ [arcmin$^{-2}$]")