def plotfind(findata, ftype="pdf"):
"""
plot just the data from the stellar locations file
"""
outfile = findata + "." + ftype
#read the ascii table into an astropy.table
reader = ascii.Daophot()
photfile = reader.read(findata)
#remove the points that had issues
noerror = np.where(photfile[:]['PERROR'] == 'NoError')
goodphot = photfile[good[0][:]]
indef = np.where(goodphot["MAG"] != "INDEF")
phot = goodphot[indef[0][:]]
plt.figure(figsize=(8, 10)) #this is in inches
plt.title('Total Stars Detected %i' % (len(phot)))
mag = phot["MAG"].astype(np.float)
merr = phot["MERR"].astype(np.float)
#plots from the finder program
#sharpness histogram from the detection file
plt.subplot(222)
plt.xlabel('Sharpness')
plt.ylabel('Number')
hist, bins, p = plt.hist(sharp, 10, normed=False)
plt.title('Detection Types', {'fontsize': 10})
#plt.legend(['Stars','Blends','Blemish'],loc='upper left')
delta = max(hist) / len(bins)
yy = max(hist) - delta
plt.text(bins[0], yy, 'Stars at zero', {'color': 'black', 'fontsize': 10})
plt.text(bins[0], yy - delta * 1.5, 'Blends Positive', {
'color': 'black',
'fontsize': 10
})
plt.text(bins[0], yy - delta * 2.5, 'Blemish Negative', {
'color': 'black',
'fontsize': 10
})
#chi relation
plt.subplot(224)
plt.xlabel('chi')
plt.ylabel('mag')
#plt.hist(chi<2,10,normed=False)
u = np.where(sharp < 1.5)
uu = np.where(sharp[u] > 0.5)
schi = chi[uu]
smag = mag[uu]
plt.plot(schi, smag, 'bx')
plt.xlim(0, 2)
plt.title('CHI-ball for stars (0.5<sharp>1.5)', {'fontsize': 10})
plt.savefig(outfile)
return ofile
def plotphot(photdata, ftype="pdf"):
"""
neato phot plots from the output files
use the astropy library to read the input files
make sure you have astropy0.2 or later installed or it might fail to read correctly
"""
print photdata
outfile = photdata + "." + ftype
#read the ascii table into an astropy.table
reader = ascii.Daophot()
photfile = reader.read(photdata)
#remove the points that had issues
noerror = np.where(photfile[:]['PERROR'] == 'NoError')
goodphot = photfile[noerror[0][:]]
indef = np.where(goodphot["MAG"] != "INDEF")
phot = goodphot[indef[0][:]]
plt.ioff() #turn off interactive so plots dont pop up
plt.figure(figsize=(8, 10)) #this is in inches
mag = phot["MAG"].astype(np.float)
merr = phot["MERR"].astype(np.float)
#mag vs merr
plt.subplot(221)
plt.xlabel('MAG')
plt.ylabel('MERR')
plt.plot(mag, merr, 'bx')
plt.title(photdata, {'fontsize': 10})
#magnitude histogram
plt.subplot(222)
plt.xlabel('mag')
plt.ylabel('Number')
plt.hist(mag, 10)
plt.xlim(19, 29)
#overplot the cummulative curve
normHist, bins, patches = plt.hist(mag, bins=10, normed=False)
plt.title('Mag distribution', {'fontsize': 10})
xsh = phot["XSHIFT"].astype(np.float)
ysh = phot["YSHIFT"].astype(np.float)
#xshift and yshifts, just to see
plt.subplot(223)
plt.xlabel('XSHIFT')
plt.ylabel('YSHIFT')
plt.plot(xsh, ysh, 'bx')
plt.title('Xshift vs Yshift of centers', {'fontsize': 10})
#a quick reference plot of the image and starlocations
x = phot["XCENTER"].astype(np.float)
y = phot["YCENTER"].astype(np.float)
imname = phot["IMAGE"][0].split("[")[
0] #assume all from 1 image, and remove extension (careful here)
image = pyfits.getdata(imname)
plt.subplot(224)
plt.xlabel('X')
plt.ylabel('Y')
plt.plot(x, y, 'ko', mfc="None")
zero = np.where(image <= 0)
image[zero] = 0.999
plt.imshow(np.log10(image), cmap=plt.cm.gray)
plt.title('Total Non-error Stars: %i' % (len(phot)), {'fontsize': 10})
plt.tight_layout()
plt.savefig(outfile)
print "saved output figure to %s" % (outfile)