Get image from the PS1 image server

Query the PS1 image server to get a list of images and retrieve some images. This sample script demonstrates the use of the PS1 image services. See the PS1 Image Cutout Service documentation for details of the services being used. This notebook is available for download.

In [1]:
%matplotlib inline
from __future__ import print_function
import numpy
from astropy.table import Table
import requests
from PIL import Image
from io import BytesIO
import pylab

Helper functions to query the list of images and to extract images

In [2]:
def getimages(ra,dec,size=240,filters="grizy"):
    
    """Query ps1filenames.py service to get a list of images
    
    ra, dec = position in degrees
    size = image size in pixels (0.25 arcsec/pixel)
    filters = string with filters to include
    Returns a table with the results
    """
    
    service = "https://ps1images.stsci.edu/cgi-bin/ps1filenames.py"
    url = ("{service}?ra={ra}&dec={dec}&size={size}&format=fits"
           "&filters={filters}").format(**locals())
    table = Table.read(url, format='ascii')
    return table


def geturl(ra, dec, size=240, output_size=None, filters="grizy", format="jpg", color=False):
    
    """Get URL for images in the table
    
    ra, dec = position in degrees
    size = extracted image size in pixels (0.25 arcsec/pixel)
    output_size = output (display) image size in pixels (default = size).
                  output_size has no effect for fits format images.
    filters = string with filters to include
    format = data format (options are "jpg", "png" or "fits")
    color = if True, creates a color image (only for jpg or png format).
            Default is return a list of URLs for single-filter grayscale images.
    Returns a string with the URL
    """
    
    if color and format == "fits":
        raise ValueError("color images are available only for jpg or png formats")
    if format not in ("jpg","png","fits"):
        raise ValueError("format must be one of jpg, png, fits")
    table = getimages(ra,dec,size=size,filters=filters)
    url = ("https://ps1images.stsci.edu/cgi-bin/fitscut.cgi?"
           "ra={ra}&dec={dec}&size={size}&format={format}").format(**locals())
    if output_size:
        url = url + "&output_size={}".format(output_size)
    # sort filters from red to blue
    flist = ["yzirg".find(x) for x in table['filter']]
    table = table[numpy.argsort(flist)]
    if color:
        if len(table) > 3:
            # pick 3 filters
            table = table[[0,len(table)//2,len(table)-1]]
        for i, param in enumerate(["red","green","blue"]):
            url = url + "&{}={}".format(param,table['filename'][i])
    else:
        urlbase = url + "&red="
        url = []
        for filename in table['filename']:
            url.append(urlbase+filename)
    return url


def getcolorim(ra, dec, size=240, output_size=None, filters="grizy", format="jpg"):
    
    """Get color image at a sky position
    
    ra, dec = position in degrees
    size = extracted image size in pixels (0.25 arcsec/pixel)
    output_size = output (display) image size in pixels (default = size).
                  output_size has no effect for fits format images.
    filters = string with filters to include
    format = data format (options are "jpg", "png")
    Returns the image
    """
    
    if format not in ("jpg","png"):
        raise ValueError("format must be jpg or png")
    url = geturl(ra,dec,size=size,filters=filters,output_size=output_size,format=format,color=True)
    r = requests.get(url)
    im = Image.open(BytesIO(r.content))
    return im


def getgrayim(ra, dec, size=240, output_size=None, filter="g", format="jpg"):
    
    """Get grayscale image at a sky position
    
    ra, dec = position in degrees
    size = extracted image size in pixels (0.25 arcsec/pixel)
    output_size = output (display) image size in pixels (default = size).
                  output_size has no effect for fits format images.
    filter = string with filter to extract (one of grizy)
    format = data format (options are "jpg", "png")
    Returns the image
    """
    
    if format not in ("jpg","png"):
        raise ValueError("format must be jpg or png")
    if filter not in list("grizy"):
        raise ValueError("filter must be one of grizy")
    url = geturl(ra,dec,size=size,filters=filter,output_size=output_size,format=format)
    r = requests.get(url[0])
    im = Image.open(BytesIO(r.content))
    return im

Sample JPEG images

This gets single-band grayscale and color JPEG images at the position of the Crab Nebula. The extracted region size is 1280 pixels = 320 arcsec.

In [3]:
# Crab Nebula position
ra = 83.633210
dec = 22.014460
size = 1280

# grayscale image
gim = getgrayim(ra,dec,size=size,filter="i")
# color image
cim = getcolorim(ra,dec,size=size,filters="grz")

pylab.rcParams.update({'font.size':12})
pylab.figure(1,(12,6))
pylab.subplot(121)
pylab.imshow(gim,origin="upper")
pylab.title('Crab Nebula PS1 i')
pylab.subplot(122)
pylab.title('Crab Nebula PS1 grz')
pylab.imshow(cim,origin="upper")
Downloading https://ps1images.stsci.edu/cgi-bin/ps1filenames.py?ra=83.63321&dec=22.01446&size=1280&format=fits&filters=i [Done]
Downloading https://ps1images.stsci.edu/cgi-bin/ps1filenames.py?ra=83.63321&dec=22.01446&size=1280&format=fits&filters=grz [Done]
Out[3]:
<matplotlib.image.AxesImage at 0x118c7e828>

Load and display a FITS image

Note that the $y$-axis is flipped in the JPEG image compared with the original FITS image.

In [4]:
from astropy.io import fits
from astropy.visualization import PercentileInterval, AsinhStretch

fitsurl = geturl(ra, dec, size=size, filters="i", format="fits")
fh = fits.open(fitsurl[0])
fim = fh[0].data
# replace NaN values with zero for display
fim[numpy.isnan(fim)] = 0.0
# set contrast to something reasonable
transform = AsinhStretch() + PercentileInterval(99.5)
bfim = transform(fim)

pylab.figure(1,(12,6))
pylab.subplot(121)
pylab.imshow(gim,origin="upper")
pylab.title('Crab Nebula PS1 i (jpeg)')

pylab.subplot(122)
pylab.title('Crab Nebula PS1 i (fits)')
pylab.imshow(bfim,cmap="gray",origin="lower")
Downloading https://ps1images.stsci.edu/cgi-bin/ps1filenames.py?ra=83.63321&dec=22.01446&size=1280&format=fits&filters=i [Done]
Out[4]:
<matplotlib.image.AxesImage at 0x825f6ecf8>