def solve(fn):
p = Dispatch('PinPoint.Plate')
p.Catalog = 4 # Tycho2 catalog
p.CatalogPath = filepath.catalog
if 'B' in fn:
p.colorband = 1 # B band
else:
p.colorband = 2 # V band
fn_orig = fn
m = int(fn_orig[-7:-4])
if m in range(0, 50, 5):
print 'Solving images %i/45' % m
# Masking the area near the horizon in image 0-15
if m < 16:
f = fits.open(fn, uint=False)[0]
f.data[630:] = 0.
fn = fn[:-4] + 'c.fit'
f.writeto(fn, overwrite=True)
p.attachFits(fn)
p.ArcsecPerPixelHoriz = 96
p.ArcsecPerPixelVert = 96
p.SigmaAboveMean = 3
p.Minimumbrightness = 2500
p.FindImageStars()
p.RightAscension = p.TargetRightAscension
p.Declination = p.TargetDeclination
p.CatalogMaximumMagnitude = 7.
p.CatalogMinimumMagnitude = 2.
p.CatalogExpansion = 0.1
p.Maxsolvetime = 60
p.FindCatalogStars()
try:
p.Solve()
p.UpdateFITS()
message = ['normal', fn_orig] # files that have been solved normally
except:
# trying to just solve the cropped (200x200 pix) image
f = fits.open(fn, uint=False)[0]
l = len(f.data) / 2
f.data = f.data[l - 100:l + 100, l - 100:l + 100]
fn = fn[:-4] + 's.fit'
f.writeto(fn, overwrite=True)
p.DetachFITS()
p.attachFits(fn)
p.ArcsecPerPixelHoriz = 96
p.ArcsecPerPixelVert = 96
p.SigmaAboveMean = 2
p.Minimumbrightness = 2000
p.FindImageStars()
p.RightAscension = p.TargetRightAscension
p.Declination = p.TargetDeclination
p.CatalogMaximumMagnitude = 9.
p.CatalogMinimumMagnitude = 2.
p.CatalogExpansion = 0.3
p.Maxsolvetime = 40
p.FindCatalogStars()
try:
p.Solve()
p.UpdateFITS()
message = ['cropped',
fn_orig] #files that have been cropped & solved
except:
message = ['failed',
fn_orig] #files that haven been failed to solve
p.DetachFITS()
#save the updated fits header to the first row horizon images
if (m < 16) & (p.solved == True):
f = fits.open(fn_orig, uint=False)
data = f[0].data.copy()
f.close()
header = fits.open(fn)[0].header
fits.writeto(fn_orig, data, header=header, overwrite=True)
return message
