Common All-Sky Bitmap Images (ligo.skymap.plot.backdrop)

Backdrops for astronomical plots.

ligo.skymap.plot.backdrop.blackmarble(t, resolution='low')[source] [edit on github]

Get the “Black Marble” image.

Get the NASA/NOAO/NPP image showing city lights, at the sidereal time given by t. See https://visibleearth.nasa.gov/view.php?id=79765.

Parameters:
tastropy.time.Time

Time to embed in the WCS header.

resolution{‘low’, ‘mid’, ‘high’}

Specify which version to use: the “low” resolution version (3600x1800 pixels, the default), the “mid” resolution version (13500x6750 pixels), or the “high” resolution version (54000x27000 pixels).

Returns:
astropy.io.fits.ImageHDU

A FITS WCS image in ICRS coordinates.

Examples

from matplotlib import pyplot as plt
from ligo.skymap.plot import blackmarble, reproject_interp_rgb

obstime = '2017-08-17 12:41:04'
ax = plt.axes(projection='geo degrees aitoff', obstime=obstime)
ax.imshow(reproject_interp_rgb(blackmarble(obstime), ax.header))

(Source code, png, hires.png, pdf)

../_images/backdrop-1.png
ligo.skymap.plot.backdrop.bluemarble(t, resolution='low')[source] [edit on github]

Get the “Blue Marble” image.

Retrieve, cache, and return the NASA/NOAO/NPP “Blue Marble” image showing landforms and oceans.

See https://visibleearth.nasa.gov/view.php?id=74117.

Parameters:
tastropy.time.Time

Time to embed in the WCS header.

resolution{‘low’, ‘high’}

Specify which version to use: the “low” resolution version (5400x2700 pixels, the default) or the “high” resolution version (21600x10800 pixels).

Returns:
astropy.io.fits.ImageHDU

A FITS WCS image in ICRS coordinates.

Examples

from matplotlib import pyplot as plt
from ligo.skymap.plot import bluemarble, reproject_interp_rgb

obstime = '2017-08-17 12:41:04'
ax = plt.axes(projection='geo degrees aitoff', obstime=obstime)
ax.imshow(reproject_interp_rgb(bluemarble(obstime), ax.header))

(Source code, png, hires.png, pdf)

../_images/backdrop-2.png
ligo.skymap.plot.backdrop.mellinger()[source] [edit on github]

Get the Mellinger Milky Way panorama.

Retrieve, cache, and return the Mellinger Milky Way panorama. See http://www.milkywaysky.com.

Returns:
astropy.io.fits.ImageHDU

A FITS WCS image in ICRS coordinates.

Examples

from astropy.visualization import (ImageNormalize,
                                   AsymmetricPercentileInterval)
from astropy.wcs import WCS
from matplotlib import pyplot as plt
from ligo.skymap.plot import mellinger
from reproject import reproject_interp

ax = plt.axes(projection='astro hours aitoff')
backdrop = mellinger()
backdrop_wcs = WCS(backdrop.header).dropaxis(-1)
interval = AsymmetricPercentileInterval(45, 98)
norm = ImageNormalize(backdrop.data, interval)
backdrop_reprojected = np.asarray([
    reproject_interp((layer, backdrop_wcs), ax.header)[0]
    for layer in norm(backdrop.data)])
backdrop_reprojected = np.rollaxis(backdrop_reprojected, 0, 3)
ax.imshow(backdrop_reprojected)

(Source code, png, hires.png, pdf)

../_images/backdrop-3.png