def CompareSum( fname1, fname2, referenceSum_fname, minValue=0.0 ): """Sum the first two images and compare the result with the third; if the maximum relative deviation is >= 1e-6, return False, else return True. """ # kludge to avoid division by zero or very small numbers problem when one or # more input image has values equal to or very close to zero: add 1 to each # input image (and 2 to the reference image) imdata1 = fits_open(fname1)[0].data + 1.0 imdata2 = fits_open(fname2)[0].data + 1.0 imSum = imdata1 + imdata2 refSum_imdata = fits_open(referenceSum_fname)[0].data + 2.0 devianceImdata = np.abs((imSum / refSum_imdata) - 1.0) if np.max(devianceImdata) >= TOLERANCE: # i,j = np.unravel_index(devianceImdata.argmax(), devianceImdata.shape) # print() # print(np.max(devianceImdata)) # print(imSum[i,j], refSum_imdata[i,j], devianceImdata[i,j]) # print() return False else: return True
def open_kepler(filename):
""" Opens a Kepler filename and retrieves corrected flux """
if os.path.exists(filename)==False:
print "{} not found".format(filename)
return [-1],[-1],[-1]
hdu = fits_open(filename)
#print hdu[1].data.dtype.names
time = hdu[1].data.field("TIME")
## Use the corrected flux, not raw
flux = hdu[1].data.field("PDCSAP_FLUX")
flux_err = hdu[1].data.field("PDCSAP_FLUX_ERR")
hdu.close()
return time,flux,flux_err
def paths_to_fits(paths):
"""
paths (tuple): list of paths to a astronomical image which can be opened with
casacore
returns:
tuple: of HDUlist objects
"""
for path in paths:
try:
i = casacore_image(path)
except RuntimeError:
logging.error("can't open image {}".format(path))
yield
else:
with NamedTemporaryFile() as temp_file:
i.tofits(temp_file.name)
fits = fits_open(temp_file.name)
yield cPickle.dumps(fits[0].data), str(fits[0].header)
def get_stamps(self, oid, candid=None):
"""Download Stamps for an specific alert.
Parameters
----------
oid : :py:class:`str`
object ID in ALeRCE DBs.
candid : :py:class:`int`
Candid of the stamp to be displayed.
Returns
-------
:class:`astropy.io.fits.HDUList`
Science, Template and Difference stamps for an specific alert.
"""
if candid is None:
candid = self._get_first_detection(oid)
try:
hdulist = HDUList()
for stamp_type in ["science", "template", "difference"]:
tmp_hdulist = fits_open(
"%s?oid=%s&candid=%s&type=%s&format=fits"
% (
self.config["AVRO_URL"]
+ self.config["AVRO_ROUTES"]["get_stamp"],
oid,
candid,
stamp_type,
)
)
hdu = tmp_hdulist[0]
hdu.header["STAMP_TYPE"] = stamp_type
hdulist.append(hdu)
return hdulist
except HTTPError:
warnings.warn("AVRO File not found.", RuntimeWarning)
return None
def get_stamp(self, oid='', candid=0, stamp='science', output='png'):
"""
:param oid: str, case-sensitive, ZTF identifier
:param candid: int, candidate identifier (0 for earliest)
:param stamp: str, stamp from ['science', 'difference', 'template']
:param output: str, output format from ['fits', 'jpg', 'png']
:return: thumbnail in given format or None
"""
# check input(s)
if not isinstance(oid, str) or oid.strip() == '':
return
if not isinstance(candid, int) or candid < 0:
return
if not isinstance(stamp, str) or stamp.strip().lower() not in self.__alerce_stamps:
return
if not isinstance(output, str) or output.strip().lower() not in self.__alerce_outputs:
return
if self.__log:
self.__log.debug(f"get_stamp(oid='{oid}', candid={candid}, stamp='{stamp}', output='{output}')")
# execute
self.__reinit__()
self.__oid = oid
self.__stamp = stamp.strip().lower()
self.__output = output.strip().lower()
if candid > 0:
self.__candid = candid
else:
self.__url = 'https://ztf.alerce.online/get_detections'
self.__json = {'oid': f'{self.__oid}'}
self.__detections = self.__http_post__()
if self.__detections is None:
return
_tmp = {_i['mjd']: _i['candid'] for _i in self.__detections['result']['detections']}
_min = min(_tmp.keys())
self.__candid = _tmp[_min]
self.__url = f'https://avro.alerce.online/get_stamp?' \
f'oid={self.__oid}&candid={self.__candid}&type={self.__stamp}&format=fits'
# get data
try:
self.__image = fits_open(self.__url)[0]
self.__image.header['STAMP'] = self.__stamp
except Exception as _e:
if self.__log:
self.__log.error(f"failed to get_stamp(oid='{oid}', candid={candid}, stamp='{stamp}'), error={_e}")
return
# create output file
self.__output = os.path.join(os.getcwd(), f'{self.__oid}_{self.__candid}_{self.__stamp}.{self.__output}')
try:
if 'fits' in self.__output:
self.__image.writeto(self.__output)
else:
self.__image = Image.fromarray(self.__image.data)
self.__image.convert('RGB').save(self.__output)
except:
pass
return self.__output
def CompareImagesEqual( fname1, fname2, minValue=0.0 ): imdata1 = fits_open(fname1)[0].data imdata2 = fits_open(fname2)[0].data validPix = imdata2 > minValue return np.array_equal(imdata1[validPix], imdata2[validPix])
def CompareImagesNew( fname1, fname2, tol=TOERLANCE_ALLCLOSE ): imdata1 = fits_open(fname1)[0].data imdata2 = fits_open(fname2)[0].data return np.allclose(imdata1, imdata2, rtol=0, atol=tol)
