def test_SkyServer_getJpegImgCutout(self):
#image cutout
img = SkyServer.getJpegImgCutout(
ra=197.614455642896,
dec=18.438168853724,
width=512,
height=512,
scale=0.4,
dataRelease=SkyServer_DataRelease,
opt="OG",
query=
"SELECT TOP 100 p.objID, p.ra, p.dec, p.r FROM fGetObjFromRectEq(197.6,18.4,197.7,18.5) n, PhotoPrimary p WHERE n.objID=p.objID"
)
im = skimage.io.imread("./TestGalaxy.jpeg")
self.assertEqual(img.tobytes(), im.tobytes())
def get_images(df, width=424, height=424, scale=.02):
"""Get images for objects present in pandas dataframe.
Downloads JPEG images of objects from SDSS to disk storage, naming
images according to their :attr:`specobjid`. Filepaths are
additionally stored in the dataframe, such that the dataframe can
be used with :class:`keras.preprocessing.image.ImageDataGenerator`
"""
catalog_path = os.path.join(ARGS.DATA, ARGS.CATALOG + '.h5')
df = df.assign(imgpath=None)
with tqdm(total=len(df.index), unit='object') as pbar:
for index, obj in df.iterrows():
# allows for restarting incomplete downloads by
# checking for all entries if the path already exists
# XXX: tqdm includes better ways to approach this
if obj['imgpath'] is not None:
pbar.update(1)
continue
img = None
img = SkyServer.getJpegImgCutout(ra=obj['ra'],
dec=obj['dec'],
width=width,
height=height,
scale=(scale * obj['petroR90_r']),
dataRelease='DR15')
if img is not None:
imgpath = os.path.join(ARGS.IMG,
'{0}.jpeg'.format(obj['specobjid']))
Image.fromarray(img).save(imgpath)
df.at[index, 'imgpath'] = imgpath
df.to_hdf(catalog_path,
key=ARGS.CATALOG,
append=False,
mode='w')
pbar.update(1)
return df.dropna(axis=0, subset=['imgpath'], inplace=True)
imgName = str(galaxies.iloc[x][0]) + ".jpeg"
maxValue = 0
shapeIndex = ellipticIndex
for y in xrange(ellipticIndex,combinedIndex + 1):
if galaxies.iloc[x][y] > maxValue:
maxValue = galaxies.iloc[x][y]
shapeIndex = y
hd2 = galaxies.iloc[x][1] + " " + galaxies.iloc[x][2]
# Obtain decimal representation
ra1, dec1 = pyasl.coordsSexaToDeg(hd2)
img = SkyServer.getJpegImgCutout(ra=ra1, dec=dec1, width=512, height=512, scale=0.1,
dataRelease="DR13",opt="I",
query="SELECT TOP 1 g.objID, g.ra, g.dec, g.r FROM fGetObjFromRectEq(ra1-0.5,dec1-0.5,ra1+0.5,dec1+0.5) n, Galaxy g WHERE n.objID=g.objID")
im = Image.fromarray(img)
im.save(imgName)
with open('shapes.csv', 'a') as f:
writer = csv.writer(f)
writer.writerow([str(galaxies.iloc[x][0]), str(shapeIndex)])
# In[ ]:
#Exectute sql query
df = SkyServer.sqlSearch(sql=SkyServer_TestQuery, dataRelease=SkyServer_DataRelease)
print(df)
# In[ ]:
#get an image cutout
img = SkyServer.getJpegImgCutout(ra=197.614455642896, dec=18.438168853724, width=2, height=2, scale=0.4,
dataRelease=SkyServer_DataRelease,opt="OG",
query="SELECT TOP 100 p.objID, p.ra, p.dec, p.r FROM fGetObjFromRectEq(197.6,18.4,197.7,18.5) n, PhotoPrimary p WHERE n.objID=p.objID")
plt.imshow(img)
# In[ ]:
# do a radial search of objects:
df = SkyServer.radialSearch(ra=258.25, dec=64.05, radius=0.1, dataRelease=SkyServer_DataRelease)
print(df)
# In[ ]:
#do rectangular search of objects:
csv_reader = csv.reader(csv_file, delimiter=',')
line_count = 0
for x in range(0, num_lines):
row = next(csv_reader)
if line_count == 0:
line_count += 1
else:
ra_sx, dec_sx = row[1], row[2]
c = SkyCoord(ra_sx, dec_sx, unit=u.degree)
print(f'object {row[0]}', c)
line_count += 1
img = SkyServer.getJpegImgCutout(ra=c.ra.deg,
dec=c.dec.deg,
width=IMG_WIDTH,
height=IMG_HEIGHT,
scale=0.1,
dataRelease='DR13')
Image.fromarray(img).save(f"skyserver_fits/{row[0]}.png")
r, g, b = img[:, :, 0], img[:, :, 1], img[:, :, 2]
red = fits.PrimaryHDU(data=r)
red.writeto(f"skyserver_fits/{row[0]}r.fits")
green = fits.PrimaryHDU(data=g)
green.writeto(f"skyserver_fits/{row[0]}g.fits")
blue = fits.PrimaryHDU(data=b)
blue.writeto(f"skyserver_fits/{row[0]}b.fits")