def test_progress_png(self, client, capsys):
"""
Tests if progress bars are disabled when running `download_png()`.
"""
msg = "\rFiles Downloaded:"
client = HelioviewerClient()
client.download_png('2012/07/16 10:08:00',
2.4,
"[SDO,AIA,AIA,171,1,100]",
x0=0,
y0=0,
width=1024,
height=1024,
progress=False)
_, err = capsys.readouterr()
assert msg not in err
client.download_png('2012/07/16 10:08:00',
2.4,
"[SDO,AIA,AIA,171,1,100]",
x0=0,
y0=0,
width=1024,
height=1024)
_, err = capsys.readouterr()
assert msg in err
year, month, day = get_date()
timelist = build_timelist(year, month, day)
hv = HelioviewerClient()
#file = hv.download_png('2015/01/01', 6, "[SDO,AIA,AIA,304,1,100],[SDO,AIA,AIA,193,1,50],[SOHO,LASCO,C2,white-light,1,100],[SOHO,LASCO,C3,white-light,1,100]", x0=0, y0=0, width=900, height=900)
minutes = []
for minute in xrange(0, 60, 12):
minutes.append(minute)
for time in timelist:
filenum = timelist.index(time) + 1
total = len(timelist)
print("DOWNLOADING: " + str(time) + " --- " + str(filenum) + "/" + str(total))
file = hv.download_png(time, 6,
"[SDO,AIA,AIA,193,1,100],"\
"[SOHO,LASCO,C2,white-light,1,100]",
directory="./downloaded",
x0=0, y0=0, width=2000, height=2000, watermark=False )
i = 0
for f in sorted(glob.glob("downloaded/*.png")):
os.rename(f, "downloaded/" + str(i) + ".png")
i = i + 1
outname = "LASCO_" + str(year) + str(month) + str(day) + ".mp4"
subprocess.call('ffmpeg -r 24 -i downloaded/%01d.png -vcodec libx264 -filter "minterpolate=mi_mode=blend" -b:v 4M -pix_fmt yuv420p -y ' + outname, shell = True)
backup = "archived/" + str(year) + str(month) + str(day)
subprocess.call("mkdir -p " + backup + " && mv downloaded/*.png " + backup, shell = True)
from sunpy.net.helioviewer import HelioviewerClient
from matplotlib.image import imread
import matplotlib.pyplot as plt
from matplotlib import patches
hv = HelioviewerClient()
DAT = input('Date yyyy/m/d: ')
#IMRES = input('Image Resolution in arcseconds/pixel: ')
SRCID = input('Data Source ID: ')
#VIS = input('Visibility: ')
#OP = input('Opacity: ')
XFOC = input('Specify x-coord: ')
YFOC = input('Specify y-coord: ')
##include image size in a function, make dict for source ids, make optional args for composite images
IN = [SRCID, XFOC, YFOC]
FLIN = list(map(float, IN))
imgfile = hv.download_png(DAT,
6.0, [FLIN[0], 1.0, 100.0],
x0=FLIN[1],
y0=FLIN[2],
width=512,
height=512)
im = imread(imgfile)
plt.imshow(im)
plt.show()
'stereocor1', 'sdoaia304', 'sdoaia193', 'sdoaia211', 'sdoaia4500',
'trace1550', 'trace195', 'stereohi1', 'yohkohsxtwh', 'irissji2796',
'sdoaia1600', 'sohoeit195'
]
print('List of available color maps: ')
pprint.pprint(cmap_list)
color = None
while color not in cmap_list:
color = input('Select a color map to display: ')
cmap = plt.get_cmap(color)
imgfile = hv.download_png(date,
6.0, [SRCID, 5.0, 100.0],
x0=0,
y0=0,
width=512,
height=512)
##Section 3 -- PNG image downloaded from Helioviewer is processed using Pillow. The image is first converted to a JPG file, then split into RGB components. From these component files, a FITS image is compiled that sunpy.maps can readily use for plotting.
im = Image.open(imgfile)
imRGB = im.convert('RGB')
imRGB.save('im.jpg')
image = Image.open('im.jpg')
xsize, ysize = image.size
r, g, b = image.split()
r_data = np.array(r.getdata())
g_data = np.array(g.getdata())
b_data = np.array(b.getdata())
from sunpy.net.helioviewer import HelioviewerClient
hv = HelioviewerClient()
hv.download_png("2099/01/01", 6,
"[SDO,AIA,AIA,304,1,100],[SDO,AIA,AIA,193,1,50],"+
"[SOHO,LASCO,C2,white-light,1,100]",
x0=0, y0=0, width=768, height=768)
def download_images(c1, c2, craft, c1_hvr, c2_hvr, cme_root):
"""Download the COR1 and COR2 fits files for the frame nearest tm, to get
coords and do distance calc. Download several pngs around the event.
"""
# Open up a VSO client and a Helioviewer Client
vsoclient = vso.VSOClient()
hv = HelioviewerClient()
# Loop over the events, make event directory, download closest fits file
# and several pngs.
for i in range(len(c1)):
print 'length of c1'
print len(c1)
print i
cme_dir = cme_root + r'\cme_' + '{0:02d}'.format(i + 1)
if not os.path.exists(cme_dir):
os.makedirs(cme_dir)
#######################################################################
# Search for COR1 data in +/- 30min window around event tm1
dt = pd.Timedelta(30, 'm')
tl = [(c1['tm'][i] - dt).isoformat(), (c1['tm'][i] + dt).isoformat()]
# Query VSO to find what files available
qr = vsoclient.query(vso.attrs.Time(tl[0], tl[1]),
vso.attrs.Instrument('cor1'),
vso.attrs.Source(craft))
# Take out values that are not 0deg polarised
q = 0
while q <= len(qr) - 1:
tpe = qr[q]['info'].split(';')[3].strip()
if tpe == '0deg.':
q = q + 1
else:
qr.pop(q)
# Find closest mathced in time
# Get datetimes of the query resutls
times = np.array([pd.to_datetime(x['time']['start']) for x in qr])
# Remove querys before the closest match
q = 0
while q < np.argmin(np.abs(times - c1['tm'][i])):
qr.pop(0)
q = q + 1
# Remove querys after the closest match
while len(qr) > 1:
qr.pop(1)
# Download best matched file
vsoclient.get(qr, path=cme_dir + r"\{file}").wait()
for t in times:
hv.download_png(t.isoformat(),
7.5,
c1_hvr,
x0=0,
y0=0,
width=1024,
height=1024,
directory=cme_dir,
watermark=True)
###################################################################
# Search for COR2 data around tm2
dt = pd.Timedelta(90, 'm')
tl = [(c2['tm'][i] - dt).isoformat(), (c2['tm'][i] + dt).isoformat()]
qr = vsoclient.query(vso.attrs.Time(tl[0], tl[1]),
vso.attrs.Instrument('cor2'),
vso.attrs.Source(craft))
# Take out values not 2048x2048 double exposures
q = 0
while q <= len(qr) - 1:
tpe = qr[q]['info'].split(';')[2].strip()
sze = qr[q]['info'].split(';')[-1].strip()
if tpe == 'DOUBLE' and sze == '2048x2048':
q = q + 1
else:
qr.pop(q)
# Find closest mathced in time
# Get datetimes of the query resutls
times = np.array([pd.to_datetime(x['time']['start']) for x in qr])
# Remove querys before the closest match
q = 0
while q < np.argmin(np.abs(times - c2['tm'][i])):
qr.pop(0)
q = q + 1
# Remove querys after the closest match
while len(qr) > 1:
qr.pop(1)
# Download best matched file
vsoclient.get(qr, path=cme_dir + r"\{file}").wait()
# Use the query times to download helioviewer PNGS
for t in times:
hv.download_png(t.isoformat(),
14.7,
c2_hvr,
x0=0,
y0=0,
width=2048,
height=2048,
directory=cme_dir,
watermark=True)
###################################################################
# Now use the fits files to work out the mid point distance and
# update the arrays
c1_file = glob.glob(cme_dir + r'\*c1*.fts')
rb, rm = calc_radial_distance(c1_file, cme_root)
c1['rb'][i] = rb
c1['rm'][i] = rm
# Repeat for COR2
c2_file = glob.glob(cme_dir + r'\*c2*.fts')
rb, rm = calc_radial_distance(c2_file, cme_root)
c2['rb'][i] = rb
c2['rm'][i] = rm
return c1, c2
from sunpy.net.helioviewer import HelioviewerClient
hv = HelioviewerClient()
hv.download_png("2099/01/01",
6,
"[SDO,AIA,AIA,304,1,100],[SDO,AIA,AIA,193,1,50]," +
"[SOHO,LASCO,C2,white-light,1,100]",
x0=0,
y0=0,
width=768,
height=768)