def main():
# objects = ['AGC174540', 'AGC226067', 'AGC227987', 'AGC229326', 'AGC238713', 'AGC249282', 'AGC249323', 'AGC258242', 'AGC258459', 'AGC268074', 'HI1037+21', 'HI1050+23']
objects = OrderedDict([('AGC174540', 25.19), ('AGC226067', 24.72),
('AGC227987', 24.46), ('AGC229326', 22.14),
('AGC238713', 26.73), ('AGC249282', 24.14),
('AGC249323', 26.42), ('AGC258242', 26.00),
('AGC258459', 23.00), ('AGC268074', 23.12),
('HI1037+21', 22.02), ('HI1050+23', 22.86)])
filter_file = os.path.dirname(os.path.abspath(__file__)) + '/filter.txt'
# plt.clf()
fig = plt.figure(figsize=(10, 7))
outer = gridspec.GridSpec(4, 3, wspace=0.1, hspace=0.1)
for i, obj in enumerate(objects.keys()):
print obj
inner = gridspec.GridSpecFromSubplotSpec(1,
1,
subplot_spec=outer[i],
wspace=0.1,
hspace=0.1)
# set up some filenames
folder = '/Volumes/galileo/uchvc/targets/' + obj.lower() + '/'
mag_file = folder + 'calibrated_mags.dat'
fits_file_i = folder + obj + '_i.fits'
fits_i = fits.open(fits_file_i)
dm = objects[obj]
# read in magnitudes, colors, and positions(x,y)
# gxr,gyr,g_magr,g_ierrr,ixr,iyr,i_magr,i_ierrr,gmir,fwhm_sr= np.loadtxt(mag_file,usecols=(0,1,2,3,4,5,6,7,8,11),unpack=True)
gxr, gyr, g_magr, g_ierrr, ixr, iyr, i_magr, i_ierrr, gmir = np.loadtxt(
mag_file, usecols=(0, 1, 2, 3, 4, 5, 6, 7, 8), unpack=True)
# print len(gxr), "total stars"
fwhm_sr = np.ones_like(gxr)
# filter out the things with crappy color errors
color_error_cut = np.sqrt(2.0) * 0.2
mag_error_cut = 0.2
gmi_errr = [
np.sqrt(g_ierrr[i]**2 + i_ierrr[i]**2) for i in range(len(gxr))
]
gx = [
gxr[i] for i in range(len(gxr)) if (abs(
gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
]
gy = [
gyr[i] for i in range(len(gxr)) if (abs(
gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
]
g_mag = [
g_magr[i] for i in range(len(gxr)) if (abs(
gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
]
g_ierr = [
g_ierrr[i] for i in range(len(gxr)) if (abs(
gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
]
ix = [
ixr[i] for i in range(len(gxr)) if (abs(
gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
]
iy = [
iyr[i] for i in range(len(gxr)) if (abs(
gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
]
i_mag = [
i_magr[i] for i in range(len(gxr)) if (abs(
gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
]
i_ierr = np.array([
i_ierrr[i] for i in range(len(gxr)) if (abs(
gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
])
gmi = [
gmir[i] for i in range(len(gxr)) if (abs(
gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
]
fwhm_s = [
fwhm_sr[i] for i in range(len(gxr)) if (abs(
gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
]
gmi_err = np.array([
np.sqrt(g_ierrr[i]**2 + i_ierrr[i]**2) for i in range(len(gxr)) if
(abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
])
i_ierrAVG, bedges, binid = ss.binned_statistic(i_mag,
i_ierr,
statistic='median',
bins=10,
range=[15, 25])
gmi_errAVG, bedges, binid = ss.binned_statistic(i_mag,
gmi_err,
statistic='median',
bins=10,
range=[15, 25])
bcenters = (bedges[:-1] + bedges[1:]) / 2
bxvals = [3.75, 3.75, 3.75, 3.75, 3.75, 3.75, 3.75, 3.75, 3.75, 3.75]
# print bcenters
# print i_ierrAVG
# print gmi_errAVG
# print len(gx), "after color+mag error cut"
# nid = np.loadtxt(mag_file,usecols=(0,),dtype=int,unpack=True)
pixcrd = zip(ix, iy)
# print "Reading WCS info from image header..."
# Parse the WCS keywords in the primary HDU
warnings.filterwarnings('ignore', category=UserWarning, append=True)
w = wcs.WCS(fits_i[0].header)
# print fits_i[0].header['naxis1'], fits_i[0].header['naxis2']
footprint = w.calc_footprint()
se_corner = footprint[0]
ne_corner = footprint[1]
nw_corner = footprint[2]
sw_corner = footprint[3]
# print se_corner, ne_corner, nw_corner, sw_corner
width = (ne_corner[0] - nw_corner[0]) * 60.
height = (ne_corner[1] - se_corner[1]) * 60.
# print width, height
# Print out the "name" of the WCS, as defined in the FITS header
# print w.wcs.name
# Print out all of the settings that were parsed from the header
# w.wcs.print_contents()
# Convert pixel coordinates to world coordinates
# The second argument is "origin" -- in this case we're declaring we
# have 1-based (Fortran-like) coordinates.
world = w.all_pix2world(pixcrd, 1)
ra_corner, dec_corner = w.all_pix2world(0, 0, 1)
ra_c_d, dec_c_d = deg2HMS(ra=ra_corner, dec=dec_corner, round=True)
# print 'Corner RA:',ra_c_d,':: Corner Dec:',dec_c_d
fits_i.close()
# split the ra and dec out into individual arrays and transform to arcmin from the corner
i_ra = [
abs((world[i, 0] - ra_corner) * 60)
for i in range(len(world[:, 0]))
]
i_dec = [
abs((world[i, 1] - dec_corner) * 60)
for i in range(len(world[:, 1]))
]
# also preserve the decimal degrees for reference
i_rad = [world[i, 0] for i in range(len(world[:, 0]))]
i_decd = [world[i, 1] for i in range(len(world[:, 1]))]
search = open(obj + '_search.txt', 'w+')
sig_bins = []
sig_cens = []
sig_max = []
dms = np.arange(22.0, 26.99, 0.01)
for dm in dms:
mpc = pow(10, ((dm + 5.) / 5.)) / 1000000.
dm_string = '{:5.2f}'.format(dm).replace('.', '_')
cm_filter, gi_iso, i_m_iso = make_filter(dm, filter_file)
stars_f = filter_sources(i_mag,
i_ierr,
gmi,
gmi_err,
cm_filter,
filter_sig=1)
xy_points = zip(i_ra, i_dec)
# make new vectors containing only the filtered points
i_mag_f = [i_mag[i] for i in range(len(i_mag)) if (stars_f[i])]
g_mag_f = [g_mag[i] for i in range(len(i_mag)) if (stars_f[i])]
gmi_f = [gmi[i] for i in range(len(i_mag)) if (stars_f[i])]
i_ra_f = [i_ra[i] for i in range(len(i_mag)) if (stars_f[i])]
i_dec_f = [i_dec[i] for i in range(len(i_mag)) if (stars_f[i])]
i_rad_f = [i_rad[i] for i in range(len(i_mag)) if (stars_f[i])]
i_decd_f = [i_decd[i] for i in range(len(i_mag)) if (stars_f[i])]
i_x_f = [ix[i] for i in range(len(i_mag)) if (stars_f[i])]
i_y_f = [iy[i] for i in range(len(i_mag)) if (stars_f[i])]
fwhm_sf = [fwhm_s[i] for i in range(len(i_mag)) if (stars_f[i])]
n_in_filter = len(i_mag_f)
xedges, x_cent, yedges, y_cent, S, x_cent_S, y_cent_S, pltsig, tbl = grid_smooth(
i_ra_f, i_dec_f, 2.0, width, height)
pct, d_bins, d_cens = distfit(n_in_filter, S[x_cent_S][y_cent_S],
obj, width, height, 2.0, dm)
sig_bins.append(d_bins)
sig_cens.append(d_cens)
sig_max.append(S[x_cent_S][y_cent_S])
hi_c_ra, hi_c_dec = getHIellipse(obj,
ra_corner,
dec_corner,
centroid=True)
sep = dist2HIcentroid(ra_c_d, dec_c_d, hi_c_ra, hi_c_dec)
print 'm-M = {:5.2f} | d = {:4.2f} Mpc | α = {:s}, δ = {:s}, Δʜɪ = {:5.1f}" | N = {:4d} | σ = {:6.3f} | ξ = {:6.3f}%'.format(
dm, mpc, ra_c_d, dec_c_d, sep, n_in_filter,
S[x_cent_S][y_cent_S], pct)
print >> search, '{:5.2f} {:4.2f} {:s} {:s} {:5.1f} {:4d} {:6.3f} {:6.3f}'.format(
dm, mpc, ra_c_d, dec_c_d, sep, n_in_filter,
S[x_cent_S][y_cent_S], pct)
ax1 = plt.Subplot(fig, inner[0])
ax1.imshow(np.transpose(sig_bins),
cmap=plt.cm.Reds,
extent=(22, 27, 22, 2)) #, origin=origin)
ax1.plot(dms, sig_max, linestyle='-', color='black', lw=0.5)
ax1.set_ylabel('$\sigma$')
ax1.set_xlabel('distance modulus')
ax1.set_xlim(22, 27)
ax1.set_ylim(2, 6.5)
if obj.startswith('HI1151'):
ax1.set_title('AGC219656', size='small')
else:
ax1.set_title(obj, size='small')
ax1.set_aspect(0.4)
fig.add_subplot(ax1)
outer.tight_layout(fig)
plt.savefig('non-detections_significance.pdf')
pass
def main():
objects = OrderedDict([('AGC198511',22.91), ('AGC198606',24.72), ('AGC215417',22.69), ('HI1151+20',24.76), ('AGC249525',26.78), ('AGC268069',24.24)])
smooths = OrderedDict([('AGC198511',3.0), ('AGC198606',2.0), ('AGC215417',3.0), ('HI1151+20',2.0), ('AGC249525',3.0), ('AGC268069',3.0)])
filter_file = os.path.dirname(os.path.abspath(__file__))+'/filter.txt'
for file_ in os.listdir("./"):
if file_.endswith("i.fits"):
fits_file_i = file_
for file_ in os.listdir("./"):
if file_.endswith("g.fits"):
fits_file_g = file_
# downloadSDSSgal(fits_file_g, fits_file_i)
fits_i = fits.open(fits_file_i)
# fits_g = fits.open(fits_file_g)
# print "Opened fits files:",fits_file_g,"&",fits_file_i
# objid = fits_i[0].header['OBJECT']
title_string = fits_file_i.split('_')[0] # get the name part of the filename.
# set up some filenames
mag_file = 'calibrated_mags.dat'
# read in magnitudes, colors, and positions(x,y)
# gxr,gyr,g_magr,g_ierrr,ixr,iyr,i_magr,i_ierrr,gmir,fwhm_sr= np.loadtxt(mag_file,usecols=(0,1,2,3,4,5,6,7,8,11),unpack=True)
gxr,gyr,g_magr,g_ierrr,ixr,iyr,i_magr,i_ierrr,gmir= np.loadtxt(mag_file,usecols=(0,1,2,3,4,5,6,7,8),unpack=True)
# print len(gxr), "total stars"
fwhm_sr = np.ones_like(gxr)
# filter out the things with crappy color errors
color_error_cut = np.sqrt(2.0)*0.2
mag_error_cut = 0.2
gmi_errr = [np.sqrt(g_ierrr[i]**2 + i_ierrr[i]**2) for i in range(len(gxr))]
gx = [gxr[i] for i in range(len(gxr)) if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))]
gy = [gyr[i] for i in range(len(gxr)) if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))]
g_mag = [g_magr[i] for i in range(len(gxr)) if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))]
g_ierr = [g_ierrr[i] for i in range(len(gxr)) if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))]
ix = [ixr[i] for i in range(len(gxr)) if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))]
iy = [iyr[i] for i in range(len(gxr)) if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))]
i_mag = [i_magr[i] for i in range(len(gxr)) if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))]
i_ierr = np.array([i_ierrr[i] for i in range(len(gxr)) if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))])
gmi = [gmir[i] for i in range(len(gxr)) if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))]
fwhm_s = [fwhm_sr[i] for i in range(len(gxr)) if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))]
gmi_err = np.array([np.sqrt(g_ierrr[i]**2 + i_ierrr[i]**2) for i in range(len(gxr)) if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))])
cutleft = [i for i in range(len(gxr)) if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))]
with open('cutleft.txt', 'w+') as spud:
for i,item in enumerate(cutleft):
print(item, file=spud)
i_ierrAVG, bedges, binid = ss.binned_statistic(i_mag,i_ierr,statistic='median',bins=10,range=[15,25])
gmi_errAVG, bedges, binid = ss.binned_statistic(i_mag,gmi_err,statistic='median',bins=10,range=[15,25])
bcenters = (bedges[:-1] + bedges[1:]) / 2
bxvals = [3.75,3.75,3.75,3.75,3.75,3.75,3.75,3.75,3.75,3.75]
# print bcenters
# print i_ierrAVG
# print gmi_errAVG
# print len(gx), "after color+mag error cut"
# nid = np.loadtxt(mag_file,usecols=(0,),dtype=int,unpack=True)
pixcrd = list(zip(ix,iy))
# print "Reading WCS info from image header..."
# Parse the WCS keywords in the primary HDU
warnings.filterwarnings('ignore', category=UserWarning, append=True)
w = wcs.WCS(fits_i[0].header)
# print fits_i[0].header['naxis1'], fits_i[0].header['naxis2']
footprint = w.calc_footprint()
se_corner = footprint[0]
ne_corner = footprint[1]
nw_corner = footprint[2]
sw_corner = footprint[3]
# print se_corner, ne_corner, nw_corner, sw_corner
width = (ne_corner[0]-nw_corner[0])*60.
height = (ne_corner[1]-se_corner[1])*60.
# print width, height
# Print out the "name" of the WCS, as defined in the FITS header
# print w.wcs.name
# Print out all of the settings that were parsed from the header
# w.wcs.print_contents()
# Convert pixel coordinates to world coordinates
# The second argument is "origin" -- in this case we're declaring we
# have 1-based (Fortran-like) coordinates.
world = w.all_pix2world(pixcrd, 1)
ra_corner, dec_corner = w.all_pix2world(0,0,1)
ra_c_d,dec_c_d = deg2HMS(ra=ra_corner, dec=dec_corner, round=True)
# print 'Corner RA:',ra_c_d,':: Corner Dec:',dec_c_d
fwhm_i = 12.0 #fits_i[0].header['FWHMPSF']
fwhm_g = 9.0 # fits_g[0].header['FWHMPSF']
# print 'Image FWHM :: g = {0:5.3f} : i = {1:5.3f}'.format(fwhm_g,fwhm_i)
fits_i.close()
# fits_g.close()
# split the ra and dec out into individual arrays and transform to arcmin from the corner
i_ra = [abs((world[i,0]-ra_corner)*60) for i in range(len(world[:,0]))]
i_dec = [abs((world[i,1]-dec_corner)*60) for i in range(len(world[:,1]))]
# also preserve the decimal degrees for reference
i_rad = [world[i,0] for i in range(len(world[:,0]))]
i_decd = [world[i,1] for i in range(len(world[:,1]))]
i_magBright = [i_mag[i] for i in range(len(i_mag)) if (i_mag[i] < 22.75)]
g_magBright = [g_mag[i] for i in range(len(i_mag)) if (i_mag[i] < 22.75)]
ixBright = [ix[i] for i in range(len(i_mag)) if (i_mag[i] < 22.75)]
iyBright = [iy[i] for i in range(len(i_mag)) if (i_mag[i] < 22.75)]
i_radBright = [i_rad[i] for i in range(len(i_mag)) if (i_mag[i] < 22.75)]
i_decdBright = [i_decd[i] for i in range(len(i_mag)) if (i_mag[i] < 22.75)]
if not os.path.isfile('brightStars2275.reg'):
f1 = open('brightStars2275.reg', 'w+')
for i in range(len(i_magBright)) :
print('{0:12.4f} {1:12.4f} {2:10.5f} {3:9.5f} {4:8.2f} {5:8.2f} {6:8.2f}'.format(ixBright[i],iyBright[i], i_radBright[i], i_decdBright[i], g_magBright[i], i_magBright[i], g_magBright[i]-i_magBright[i]), file=f1)
f1.close()
i_magRed = [i_mag[i] for i in range(len(i_mag)) if (gmi[i] > 1.75)]
g_magRed = [g_mag[i] for i in range(len(i_mag)) if (gmi[i] > 1.75)]
ixRed = [ix[i] for i in range(len(i_mag)) if (gmi[i] > 1.75)]
iyRed = [iy[i] for i in range(len(i_mag)) if (gmi[i] > 1.75)]
i_radRed = [i_rad[i] for i in range(len(i_mag)) if (gmi[i] > 1.75)]
i_decdRed = [i_decd[i] for i in range(len(i_mag)) if (gmi[i] > 1.75)]
if not os.path.isfile('redStars175.reg'):
f1 = open('redStars175.reg', 'w+')
for i in range(len(i_magRed)) :
print('{0:12.4f} {1:12.4f} {2:10.5f} {3:9.5f} {4:8.2f} {5:8.2f} {6:8.2f}'.format(ixRed[i],iyRed[i], i_radRed[i], i_decdRed[i], g_magRed[i], i_magRed[i], g_magRed[i]-i_magRed[i]), file=f1)
f1.close()
dm = 22.0
dm2 = 27.0
fwhm = 2.0
# if dm2 > 0.0 and filter_string != 'none':
dms = np.arange(dm,dm2,0.01)
# search = open('search_{:3.1f}.txt'.format(fwhm),'w+')
# else:
# dms = [dm]
# search = open('spud.txt'.format(fwhm),'w+')
# sig_bins = []
# sig_cens = []
# sig_max = []
for dm in dms:
mpc = pow(10,((dm + 5.)/5.))/1000000.
dm_string = '{:5.2f}'.format(dm).replace('.','_')
out_file = 'anim/anim_' + dm_string + '_' + title_string + '.png'
# mark_file = 'f_list_' + filter_string + '_' + fwhm_string + '_' + dm_string + '_' + title_string + '.reg'
# filter_reg = 'f_reg_' + filter_string + '_' + fwhm_string + '_' + dm_string + '_' + title_string + '.reg'
# circ_file = 'c_list_' + filter_string + '_' + fwhm_string + '_' + dm_string + '_' + title_string + '.reg'
# fcirc_file = 'fc_list_' + filter_string + '_' + fwhm_string + '_' + dm_string + '_' + title_string + '.reg'
# ds9_file = 'circles_' + filter_string + '_' + fwhm_string + '_' + dm_string + '_' + title_string + '.reg'
circles_file = 'region_coords.dat'
cm_filter, gi_iso, i_m_iso = make_filter(dm, filter_file)
stars_f = filter_sources(i_mag, i_ierr, gmi, gmi_err, cm_filter, filter_sig = 1)
xy_points = list(zip(i_ra,i_dec))
# make new vectors containing only the filtered points
i_mag_f = [i_mag[i] for i in range(len(i_mag)) if (stars_f[i])]
g_mag_f = [g_mag[i] for i in range(len(i_mag)) if (stars_f[i])]
gmi_f = [gmi[i] for i in range(len(i_mag)) if (stars_f[i])]
i_ra_f = [i_ra[i] for i in range(len(i_mag)) if (stars_f[i])]
i_dec_f = [i_dec[i] for i in range(len(i_mag)) if (stars_f[i])]
i_rad_f = [i_rad[i] for i in range(len(i_mag)) if (stars_f[i])]
i_decd_f = [i_decd[i] for i in range(len(i_mag)) if (stars_f[i])]
i_x_f = [ix[i] for i in range(len(i_mag)) if (stars_f[i])]
i_y_f = [iy[i] for i in range(len(i_mag)) if (stars_f[i])]
fwhm_sf = [fwhm_s[i] for i in range(len(i_mag)) if (stars_f[i])]
n_in_filter = len(i_mag_f)
# xedgesg, x_centg, yedgesg, y_centg, Sg, x_cent_Sg, y_cent_Sg, pltsigg, tblg = galaxyMap(fits_file_i, fwhm, dm, filter_file)
xedges, x_cent, yedges, y_cent, S, x_cent_S, y_cent_S, pltsig, tbl = grid_smooth(i_ra_f, i_dec_f, fwhm, width, height)
# corr = signal.correlate2d(S, Sg, boundary='fill', mode='full')
# print corr
# pct, d_bins, d_cens = distfit(n_in_filter,S[x_cent_S][y_cent_S],title_string,width,height,fwhm,dm)
# pct_hi = 0.0 #getHIcoincidence(x_cent_S, y_cent_S, title_string, ra_corner, dec_corner, width, height, dm)
# sig_bins.append(d_bins)
# sig_cens.append(d_cens)
# sig_max.append(S[x_cent_S][y_cent_S])
# if pct > 90 :
# pct, bj,cj = distfit(n_in_filter,S[x_cent_S][y_cent_S],title_string,width,height,fwhm,dm, samples=25000)
# make a circle to highlight a certain region
cosd = lambda x : np.cos(np.deg2rad(x))
sind = lambda x : np.sin(np.deg2rad(x))
x_circ = [yedges[y_cent] + 3.0*cosd(t) for t in range(0,359,1)]
y_circ = [xedges[x_cent] + 3.0*sind(t) for t in range(0,359,1)]
verts_circ = list(zip(x_circ,y_circ))
circ_filter = Path(verts_circ)
stars_circ = circ_filter.contains_points(xy_points)
i_mag_c = [i_mag[i] for i in range(len(i_mag)) if (stars_circ[i])]
gmi_c = [gmi[i] for i in range(len(i_mag)) if (stars_circ[i])]
i_ra_c = [i_ra[i] for i in range(len(i_mag)) if (stars_circ[i])]
i_dec_c = [i_dec[i] for i in range(len(i_mag)) if (stars_circ[i])]
i_rad_c = [i_rad[i] for i in range(len(i_mag)) if (stars_circ[i])]
i_decd_c = [i_decd[i] for i in range(len(i_mag)) if (stars_circ[i])]
i_x_c = [ix[i] for i in range(len(i_mag)) if (stars_circ[i])]
i_y_c = [iy[i] for i in range(len(i_mag)) if (stars_circ[i])]
fwhm_sc = [fwhm_s[i] for i in range(len(i_mag)) if (stars_circ[i])]
# make a random reference cmd to compare to
if not os.path.isfile('refCircle.center'):
rCentx = 16.0*np.random.random()+2.0
rCenty = 16.0*np.random.random()+2.0
with open('refCircle.center','w+') as rc:
print('{:8.4f} {:8.4f}'.format(rCentx, rCenty), file=rc)
else :
rCentx, rCenty = np.loadtxt('refCircle.center', usecols=(0,1), unpack=True)
x_circr = [rCentx + 3.0*cosd(t) for t in range(0,359,1)]
y_circr = [rCenty + 3.0*sind(t) for t in range(0,359,1)]
verts_circr = list(zip(x_circr,y_circr))
rcirc_filter = Path(verts_circr)
stars_circr = rcirc_filter.contains_points(xy_points)
i_mag_cr = [i_mag[i] for i in range(len(i_mag)) if (stars_circr[i])]
gmi_cr = [gmi[i] for i in range(len(i_mag)) if (stars_circr[i])]
i_ra_cr = [i_ra[i] for i in range(len(i_mag)) if (stars_circr[i])]
i_dec_cr = [i_dec[i] for i in range(len(i_mag)) if (stars_circr[i])]
i_rad_cr = [i_rad[i] for i in range(len(i_mag)) if (stars_circr[i])]
i_decd_cr = [i_decd[i] for i in range(len(i_mag)) if (stars_circr[i])]
i_x_cr = [ix[i] for i in range(len(i_mag)) if (stars_circr[i])]
i_y_cr = [iy[i] for i in range(len(i_mag)) if (stars_circr[i])]
fwhm_scr = [fwhm_s[i] for i in range(len(i_mag)) if (stars_circr[i])]
i_mag_fc = [i_mag[i] for i in range(len(i_mag)) if (stars_circ[i] and stars_f[i])]
i_ierr_fc = [i_ierr[i] for i in range(len(i_mag)) if (stars_circ[i] and stars_f[i])]
g_ierr_fc = [g_ierr[i] for i in range(len(i_mag)) if (stars_circ[i] and stars_f[i])]
g_mag_fc = [i_mag[i] for i in range(len(i_mag)) if (stars_circ[i] and stars_f[i])]
gmi_fc = [gmi[i] for i in range(len(i_mag)) if (stars_circ[i] and stars_f[i])]
i_ra_fc = [i_ra[i] for i in range(len(i_mag)) if (stars_circ[i] and stars_f[i])]
i_dec_fc = [i_dec[i] for i in range(len(i_mag)) if (stars_circ[i] and stars_f[i])]
i_rad_fc = [i_rad[i] for i in range(len(i_mag)) if (stars_circ[i] and stars_f[i])]
i_decd_fc = [i_decd[i] for i in range(len(i_mag)) if (stars_circ[i] and stars_f[i])]
i_x_fc = [ix[i] for i in range(len(i_mag)) if (stars_circ[i] and stars_f[i])]
i_y_fc = [iy[i] for i in range(len(i_mag)) if (stars_circ[i] and stars_f[i])]
fwhm_sfc = [fwhm_s[i] for i in range(len(i_mag)) if (stars_circ[i] and stars_f[i])]
index_fc = [i for i in range(len(i_mag)) if (stars_circ[i] and stars_f[i])]
# with open('index_fc.txt', 'w+') as spud1:
# for i,item in enumerate(index_fc):
# print >> spud1, item
# print len(i_mag_fc), 'filter stars in circle'
# print 'max i mag in circle = ', min(i_mag_fc)
rs = np.array([51, 77, 90, 180])
for r in rs:
x_circ = [yedges[y_cent] + r/60.*cosd(t) for t in range(0,359,1)]
y_circ = [xedges[x_cent] + r/60.*sind(t) for t in range(0,359,1)]
verts_circ = list(zip(x_circ,y_circ))
circ_filter = Path(verts_circ)
stars_circ = circ_filter.contains_points(xy_points)
i_x_fc = [ix[i] for i in range(len(i_mag)) if (stars_circ[i] and stars_f[i])]
i_y_fc = [iy[i] for i in range(len(i_mag)) if (stars_circ[i] and stars_f[i])]
# fcirc_file = 'circle'+repr(r)+'.txt'
# with open(fcirc_file,'w+') as f3:
# for i,x in enumerate(i_x_fc):
# print >> f3, i_x_fc[i], i_y_fc[i]
i_mag_fcr = [i_mag[i] for i in range(len(i_mag)) if (stars_circr[i] and stars_f[i])]
i_ierr_fcr = [i_ierr[i] for i in range(len(i_mag)) if (stars_circr[i] and stars_f[i])]
g_ierr_fcr = [g_ierr[i] for i in range(len(i_mag)) if (stars_circr[i] and stars_f[i])]
g_mag_fcr = [i_mag[i] for i in range(len(i_mag)) if (stars_circr[i] and stars_f[i])]
gmi_fcr = [gmi[i] for i in range(len(i_mag)) if (stars_circr[i] and stars_f[i])]
i_ra_fcr = [i_ra[i] for i in range(len(i_mag)) if (stars_circr[i] and stars_f[i])]
i_dec_fcr = [i_dec[i] for i in range(len(i_mag)) if (stars_circr[i] and stars_f[i])]
i_rad_fcr = [i_rad[i] for i in range(len(i_mag)) if (stars_circr[i] and stars_f[i])]
i_decd_fcr = [i_decd[i] for i in range(len(i_mag)) if (stars_circr[i] and stars_f[i])]
i_x_fcr = [ix[i] for i in range(len(i_mag)) if (stars_circr[i] and stars_f[i])]
i_y_fcr = [iy[i] for i in range(len(i_mag)) if (stars_circr[i] and stars_f[i])]
fwhm_sfcr = [fwhm_s[i] for i in range(len(i_mag)) if (stars_circr[i] and stars_f[i])]
rcirc_c_x = ra_corner-(rCentx/60.)
rcirc_c_y = (rCenty/60.)+dec_corner
rcirc_pix_x, rcirc_pix_y = w.wcs_world2pix(rcirc_c_x,rcirc_c_y,1)
ra_cr, dec_cr = w.all_pix2world(rcirc_pix_x, rcirc_pix_y,1)
ra_cr_d,dec_cr_d = deg2HMS(ra=ra_cr, dec=dec_cr, round=False)
circ_c_x = ra_corner-(yedges[y_cent]/60.)
circ_c_y = (xedges[x_cent]/60.)+dec_corner
circ_pix_x, circ_pix_y = w.wcs_world2pix(circ_c_x,circ_c_y,1)
ra_c, dec_c = w.all_pix2world(circ_pix_x, circ_pix_y,1)
ra_c_d,dec_c_d = deg2HMS(ra=ra_c, dec=dec_c, round=False)
# print 'Peak RA:',ra_c_d,':: Peak Dec:',dec_c_d
hi_x_circ, hi_y_circ = getHIellipse(title_string, ra_corner, dec_corner)
hi_c_ra, hi_c_dec = getHIellipse(title_string, ra_corner, dec_corner, centroid=True)
hi_pix_x,hi_pix_y = w.wcs_world2pix(hi_c_ra,hi_c_dec,1)
sep = dist2HIcentroid(ra_c_d, dec_c_d, hi_c_ra, hi_c_dec)
# print "m-M = {:5.2f} | d = {:4.2f} Mpc | α = {:s}, δ = {:s}, Δʜɪ = {:5.1f}' | N = {:4d} | σ = {:6.3f} | ξ = {:6.3f}% | η = {:6.3f}%".format(dm, mpc, ra_c_d, dec_c_d, sep/60., n_in_filter, S[x_cent_S][y_cent_S], pct, pct_hi*100.)
fig = plt.figure(figsize=(8,6))
# plot
# print "Plotting for m-M = ",dm
ax0 = plt.subplot(2,2,1)
plt.scatter(i_ra, i_dec, color='black', marker='o', s=1, edgecolors='none')
plt.plot(x_circ,y_circ,linestyle='-', color='magenta')
plt.plot(x_circr,y_circr,linestyle='-', color='gold')
plt.plot(hi_x_circ,hi_y_circ,linestyle='-', color='limegreen')
# plt.scatter(i_ra_c, i_dec_c, color='red', marker='o', s=3, edgecolors='none')
plt.scatter(i_ra_f, i_dec_f, c='red', marker='o', s=10, edgecolors='none')
# plt.clim(0,2)
# plt.colorbar()
plt.ylabel('Dec (arcmin)')
plt.xlim(0,max(i_ra))
plt.ylim(0,max(i_dec))
plt.title('sky positions')
ax0.set_aspect('equal')
ax1 = plt.subplot(2,2,2)
if os.path.isfile('i_gmi_compl.gr.out'):
gmiCompl, iCompl = np.loadtxt('i_gmi_compl.gr.out',usecols=(0,1),unpack=True)
plt.plot(gmiCompl,iCompl, linestyle='--', color='green')
if os.path.isfile('i_gmi_compl.gr2.out'):
gmiCompl, iCompl = np.loadtxt('i_gmi_compl.gr2.out',usecols=(0,1),unpack=True)
plt.plot(gmiCompl,iCompl, linestyle='--', color='red')
if os.path.isfile('i_gmi_compl2.out'):
iCompl,gmiCompl = np.loadtxt('i_gmi_compl2.out',usecols=(0,1),unpack=True)
plt.plot(gmiCompl,iCompl, linestyle='--', color='blue')
plt.plot(gi_iso,i_m_iso,linestyle='-', color='blue')
plt.scatter(gmi, i_mag, color='black', marker='o', s=1, edgecolors='none')
plt.scatter(gmi_f, i_mag_f, color='red', marker='o', s=15, edgecolors='none')
# plt.scatter(gmi_c, i_mag_c, color='red', marker='o', s=3, edgecolors='none')
plt.errorbar(bxvals, bcenters, xerr=i_ierrAVG, yerr=gmi_errAVG, linestyle='None', color='black', capsize=0, ms=0)
plt.tick_params(axis='y',left='on',right='off',labelleft='on',labelright='off')
ax1.yaxis.set_label_position('left')
plt.ylabel('$i_0$')
plt.xlabel('$(g-i)_0$')
plt.ylim(25,15)
plt.xlim(-1,4)
plt.title('m-M = ' + '{:5.2f}'.format(dm) + ' (' + '{0:4.2f}'.format(mpc) + ' Mpc)')
ax1.set_aspect(0.5)
ax2 = plt.subplot(2,2,3)
extent = [yedges[0], yedges[-1], xedges[-1], xedges[0]]
plt.imshow(S, extent=extent, interpolation='nearest',cmap=cm.gray)
# plt.imshow(segm, extent=extent, cmap=rand_cmap, alpha=0.5)
cbar_S = plt.colorbar()
cbar_S.set_label('$\sigma$ from local mean')
# cbar_S.tick_params(labelsize=10)
plt.plot(x_circ,y_circ,linestyle='-', color='magenta')
plt.plot(x_circr,y_circr,linestyle='-', color='gold')
plt.plot(hi_x_circ,hi_y_circ,linestyle='-', color='limegreen')
# X, Y = np.meshgrid(xedges,yedges)
# ax3.pcolormesh(X,Y,grid_gaus)
plt.xlabel('RA (arcmin)')
plt.ylabel('Dec (arcmin)')
plt.title('smoothed stellar density')
# plt.ylabel('Dec (arcmin)')
plt.xlim(0,max(i_ra))
plt.ylim(0,max(i_dec))
ax2.set_aspect('equal')
# ax3 = plt.subplot(2,2,4)
ax3 = plt.subplot2grid((2,4), (1,2))
plt.scatter(gmi_c, i_mag_c, color='black', marker='o', s=3, edgecolors='none')
plt.scatter(gmi_fc, i_mag_fc, color='red', marker='o', s=15, edgecolors='none')
plt.tick_params(axis='y',left='on',right='on',labelleft='off',labelright='off')
ax0.yaxis.set_label_position('left')
plt.title('detection')
plt.xlabel('$(g-i)_0$')
plt.ylabel('$i_0$')
plt.ylim(25,15)
plt.xlim(-1,4)
# ax3.set_aspect(0.5)
ax4 = plt.subplot2grid((2,4), (1,3), sharey=ax3)
plt.scatter(gmi_cr, i_mag_cr, color='black', marker='o', s=3, edgecolors='none')
plt.scatter(gmi_fcr, i_mag_fcr, color='red', marker='o', s=15, edgecolors='none')
plt.tick_params(axis='y',left='on',right='on',labelleft='off',labelright='on')
plt.title('reference')
ax0.yaxis.set_label_position('left')
plt.xlabel('$(g-i)_0$')
plt.ylim(25,15)
plt.xlim(-1,4)
# ax3.set _aspect(0.5)
plt.tight_layout()
plt.savefig(out_file)
fig.clf()
pass
def main():
fwhm_sm = float(sys.argv[1])
objects = [
'AGC174540', 'AGC198511', 'AGC198606', 'AGC215417', 'AGC226067',
'AGC227987', 'AGC229326', 'AGC238626', 'AGC238713', 'AGC249000',
'AGC249282', 'AGC249320'
]
objects2 = [
'AGC249323', 'AGC249525', 'AGC258237', 'AGC258242', 'AGC258459',
'AGC268069', 'AGC268074', 'HI0932+24', 'HI0959+19', 'HI1037+21',
'HI1050+23', 'HI1151+20'
]
filter_file = os.path.dirname(os.path.abspath(__file__)) + '/filter.txt'
# plt.clf()
fig = plt.figure(figsize=(10, 7))
outer = gridspec.GridSpec(4, 3, wspace=0.1, hspace=0.1)
for i, obj in enumerate(objects2):
print obj
inner = gridspec.GridSpecFromSubplotSpec(1,
2,
subplot_spec=outer[i],
wspace=0.1,
hspace=0.1)
# set up some filenames
folder = '/Volumes/galileo/uchvc/targets/' + obj.lower() + '/'
mag_file = folder + 'calibrated_mags.dat'
fits_file_i = folder + obj + '_i.fits'
dmr, mpcr, sepr, nr, sr, pctr, pct_hir = np.loadtxt(
folder + 'search_{:3.1f}.txt'.format(fwhm_sm),
usecols=(0, 1, 4, 5, 6, 7, 8),
unpack=True)
close = np.where(sepr < 480.)
maxloc = np.argmax(pctr)
maxclose = np.argmax(pctr[close])
fits_i = fits.open(fits_file_i)
# dm = dmr[maxloc]
dm = (dmr[close])[maxclose]
# read in magnitudes, colors, and positions(x,y)
# gxr,gyr,g_magr,g_ierrr,ixr,iyr,i_magr,i_ierrr,gmir,fwhm_sr= np.loadtxt(mag_file,usecols=(0,1,2,3,4,5,6,7,8,11),unpack=True)
gxr, gyr, g_magr, g_ierrr, ixr, iyr, i_magr, i_ierrr, gmir = np.loadtxt(
mag_file, usecols=(0, 1, 2, 3, 4, 5, 6, 7, 8), unpack=True)
# print len(gxr), "total stars"
fwhm_sr = np.ones_like(gxr)
# filter out the things with crappy color errors
color_error_cut = np.sqrt(2.0) * 0.2
mag_error_cut = 0.2
gmi_errr = [
np.sqrt(g_ierrr[i]**2 + i_ierrr[i]**2) for i in range(len(gxr))
]
gx = [
gxr[i] for i in range(len(gxr)) if (abs(
gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
]
gy = [
gyr[i] for i in range(len(gxr)) if (abs(
gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
]
g_mag = [
g_magr[i] for i in range(len(gxr)) if (abs(
gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
]
g_ierr = [
g_ierrr[i] for i in range(len(gxr)) if (abs(
gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
]
ix = [
ixr[i] for i in range(len(gxr)) if (abs(
gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
]
iy = [
iyr[i] for i in range(len(gxr)) if (abs(
gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
]
i_mag = [
i_magr[i] for i in range(len(gxr)) if (abs(
gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
]
i_ierr = np.array([
i_ierrr[i] for i in range(len(gxr)) if (abs(
gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
])
gmi = [
gmir[i] for i in range(len(gxr)) if (abs(
gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
]
fwhm_s = [
fwhm_sr[i] for i in range(len(gxr)) if (abs(
gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
]
gmi_err = np.array([
np.sqrt(g_ierrr[i]**2 + i_ierrr[i]**2) for i in range(len(gxr)) if
(abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
])
i_ierrAVG, bedges, binid = ss.binned_statistic(i_mag,
i_ierr,
statistic='median',
bins=10,
range=[15, 25])
gmi_errAVG, bedges, binid = ss.binned_statistic(i_mag,
gmi_err,
statistic='median',
bins=10,
range=[15, 25])
bcenters = (bedges[:-1] + bedges[1:]) / 2
bxvals = [3.75, 3.75, 3.75, 3.75, 3.75, 3.75, 3.75, 3.75, 3.75, 3.75]
# print bcenters
# print i_ierrAVG
# print gmi_errAVG
# print len(gx), "after color+mag error cut"
# nid = np.loadtxt(mag_file,usecols=(0,),dtype=int,unpack=True)
pixcrd = zip(ix, iy)
# print "Reading WCS info from image header..."
# Parse the WCS keywords in the primary HDU
warnings.filterwarnings('ignore', category=UserWarning, append=True)
w = wcs.WCS(fits_i[0].header)
# print fits_i[0].header['naxis1'], fits_i[0].header['naxis2']
footprint = w.calc_footprint()
se_corner = footprint[0]
ne_corner = footprint[1]
nw_corner = footprint[2]
sw_corner = footprint[3]
# print se_corner, ne_corner, nw_corner, sw_corner
width = (ne_corner[0] - nw_corner[0]) * 60.
height = (ne_corner[1] - se_corner[1]) * 60.
# print width, height
# Print out the "name" of the WCS, as defined in the FITS header
# print w.wcs.name
# Print out all of the settings that were parsed from the header
# w.wcs.print_contents()
# Convert pixel coordinates to world coordinates
# The second argument is "origin" -- in this case we're declaring we
# have 1-based (Fortran-like) coordinates.
world = w.all_pix2world(pixcrd, 1)
ra_corner, dec_corner = w.all_pix2world(0, 0, 1)
ra_c_d, dec_c_d = deg2HMS(ra=ra_corner, dec=dec_corner, round=True)
# print 'Corner RA:',ra_c_d,':: Corner Dec:',dec_c_d
fits_i.close()
# split the ra and dec out into individual arrays and transform to arcmin from the corner
i_ra = [
abs((world[i, 0] - ra_corner) * 60)
for i in range(len(world[:, 0]))
]
i_dec = [
abs((world[i, 1] - dec_corner) * 60)
for i in range(len(world[:, 1]))
]
# also preserve the decimal degrees for reference
i_rad = [world[i, 0] for i in range(len(world[:, 0]))]
i_decd = [world[i, 1] for i in range(len(world[:, 1]))]
cm_filter, gi_iso, i_m_iso = make_filter(dm, filter_file)
stars_f = filter_sources(i_mag,
i_ierr,
gmi,
gmi_err,
cm_filter,
filter_sig=1)
xy_points = zip(i_ra, i_dec)
# make new vectors containing only the filtered points
i_mag_f = [i_mag[i] for i in range(len(i_mag)) if (stars_f[i])]
g_mag_f = [g_mag[i] for i in range(len(i_mag)) if (stars_f[i])]
gmi_f = [gmi[i] for i in range(len(i_mag)) if (stars_f[i])]
i_ra_f = [i_ra[i] for i in range(len(i_mag)) if (stars_f[i])]
i_dec_f = [i_dec[i] for i in range(len(i_mag)) if (stars_f[i])]
i_rad_f = [i_rad[i] for i in range(len(i_mag)) if (stars_f[i])]
i_decd_f = [i_decd[i] for i in range(len(i_mag)) if (stars_f[i])]
i_x_f = [ix[i] for i in range(len(i_mag)) if (stars_f[i])]
i_y_f = [iy[i] for i in range(len(i_mag)) if (stars_f[i])]
fwhm_sf = [fwhm_s[i] for i in range(len(i_mag)) if (stars_f[i])]
n_in_filter = len(i_mag_f)
xedges, x_cent, yedges, y_cent, S, x_cent_S, y_cent_S, pltsig, tbl = grid_smooth(
i_ra_f, i_dec_f, fwhm_sm, width, height)
# xedges, x_cent, yedges, y_cent, S, x_cent_S, y_cent_S, pltsig, tbl = grid_smooth(i_ra, i_dec, 2.0, width, height)
cosd = lambda x: np.cos(np.deg2rad(x))
sind = lambda x: np.sin(np.deg2rad(x))
hi_x_circ, hi_y_circ = getHIellipse(obj, ra_corner, dec_corner)
# hi_c_x, hi_c_y = abs((hi_c_ra-ra_corner)*60), abs((hi_c_dec-dec_corner)*60)
#
# t = np.array(range(0,359,1))
# ell = np.array([a*cosd(t) , b*sind(t)])
# rot = np.array([[cosd(pa) , -sind(pa)],[sind(pa) , cosd(pa)]])
# ell_rot = np.zeros((2,ell.shape[1]))
# for i in range(ell.shape[1]):
# ell_rot[:,i] = np.dot(rot,ell[:,i])
# hi_x_circ, hi_y_circ = hi_c_x+ell_rot[0,:], hi_c_y+ell_rot[1,:]
# hi_x_circ = [hi_c_x + a*cosd(t) for t in range(0,359,1)]
# hi_y_circ = [hi_c_y + b*sind(t) for t in range(0,359,1)]
x_circ = [yedges[y_cent] + 3.0 * cosd(t) for t in range(0, 359, 1)]
y_circ = [xedges[x_cent] + 3.0 * sind(t) for t in range(0, 359, 1)]
ax1 = plt.Subplot(fig, inner[0])
if os.path.isfile(folder + 'i_gmi_compl.gr.out'):
gmiCompl, iCompl = np.loadtxt(folder + 'i_gmi_compl.gr.out',
usecols=(0, 1),
unpack=True)
ax1.plot(gmiCompl, iCompl, linestyle='--', color='green')
# if os.path.isfile(folder+'i_gmi_compl.gr2.out'):
# gmiCompl, iCompl = np.loadtxt(folder+'i_gmi_compl.gr2.out',usecols=(0,1),unpack=True)
# ax1.plot(gmiCompl,iCompl, linestyle='--', color='red')
# if os.path.isfile(folder+'i_gmi_compl2.out'):
# iCompl,gmiCompl = np.loadtxt(folder+'i_gmi_compl2.out',usecols=(0,1),unpack=True)
# ax1.plot(gmiCompl,iCompl, linestyle='--', color='blue')
ax1.plot(gi_iso, i_m_iso, linestyle='-', color='blue')
ax1.scatter(gmi,
i_mag,
color='black',
marker='o',
s=1,
edgecolors='none')
ax1.scatter(gmi_f,
i_mag_f,
color='red',
marker='o',
s=15,
edgecolors='none')
ax1.errorbar(bxvals,
bcenters,
xerr=i_ierrAVG,
yerr=gmi_errAVG,
linestyle='None',
color='black',
capsize=0,
ms=0)
ax1.tick_params(axis='y',
left='on',
right='off',
labelleft='on',
labelright='off')
ax1.yaxis.set_label_position('left')
ax1.set_xticks([-1, 0, 1, 2, 3, 4])
ax1.set_yticks([15, 17, 19, 21, 23, 25])
ax1.set_ylabel('$i_0$')
ax1.set_xlabel('$(g-i)_0$')
ax1.set_ylim(25, 15)
ax1.set_xlim(-1, 4)
ax1.set_aspect(0.5)
ax1.set_title('$m-M = ${:5.2f}'.format(dm), size='small')
fig.add_subplot(ax1)
ax2 = plt.Subplot(fig, inner[1])
extent = [yedges[0], yedges[-1], xedges[-1], xedges[0]]
ax2.imshow(S, extent=extent, interpolation='nearest', cmap=cm.gray)
# cbar_S = plt.colorbar()
# cbar_S.set_label('$\sigma$ from local mean')
ax2.plot(hi_x_circ, hi_y_circ, linestyle='-', color='limegreen')
ax2.plot(x_circ, y_circ, linestyle='-', color='magenta')
ax2.tick_params(axis='y',
left='off',
right='on',
labelleft='off',
labelright='on')
ax2.yaxis.set_label_position('right')
ax2.set_xticks([0, 5, 10, 15, 20])
ax2.set_yticks([0, 5, 10, 15, 20])
ax2.set_xlabel('RA (arcmin)')
ax2.set_ylabel('Dec (arcmin)')
# if obj.startswith('HI1151'):
# ax2.set_title('AGC219656', size='small')
# else:
ax2.set_title(obj, size='small')
ax2.set_xlim(0, max(i_ra))
ax2.set_ylim(0, max(i_dec))
ax2.set_aspect('equal')
fig.add_subplot(ax2)
outer.tight_layout(fig)
plt.savefig('detections_close_{:3.1f}.pdf'.format(fwhm_sm))
pass
def main():
objects = OrderedDict([('AGC198606', 24.72), ('AGC215417', 22.69),
('HI1151+20', 24.76), ('AGC249525', 26.07),
('AGC268069', 24.24)])
smooths = OrderedDict([('AGC198606', 2.0), ('AGC215417', 3.0),
('HI1151+20', 2.0), ('AGC249525', 3.0),
('AGC268069', 3.0)])
filter_file = os.path.dirname(os.path.abspath(__file__)) + '/filter.txt'
# plt.clf()
for i, obj in enumerate(objects.keys()):
# set up some filenames
folder = '/Volumes/discovery1/uchvc/targets/' + obj.lower() + '/'
mag_file = folder + 'calibrated_mags.dat'
fits_file_i = folder + obj + '_i.fits'
fits_i = fits.open(fits_file_i)
dm = objects[obj]
mpc = pow(10, ((dm + 5.) / 5.)) / 1000000.
# read in magnitudes, colors, and positions(x,y)
# gxr,gyr,g_magr,g_ierrr,ixr,iyr,i_magr,i_ierrr,gmir,fwhm_sr= np.loadtxt(mag_file,usecols=(0,1,2,3,4,5,6,7,8,11),unpack=True)
gxr, gyr, g_magr, g_ierrr, ixr, iyr, i_magr, i_ierrr, gmir = np.loadtxt(
mag_file, usecols=(0, 1, 2, 3, 4, 5, 6, 7, 8), unpack=True)
# print len(gxr), "total stars"
fwhm_sr = np.ones_like(gxr)
# filter out the things with crappy color errors
color_error_cut = np.sqrt(2.0) * 0.2
mag_error_cut = 0.2
gmi_errr = [
np.sqrt(g_ierrr[i]**2 + i_ierrr[i]**2) for i in range(len(gxr))
]
gx = [
gxr[i] for i in range(len(gxr)) if (abs(
gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
]
gy = [
gyr[i] for i in range(len(gxr)) if (abs(
gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
]
g_mag = [
g_magr[i] for i in range(len(gxr)) if (abs(
gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
]
g_ierr = [
g_ierrr[i] for i in range(len(gxr)) if (abs(
gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
]
ix = [
ixr[i] for i in range(len(gxr)) if (abs(
gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
]
iy = [
iyr[i] for i in range(len(gxr)) if (abs(
gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
]
i_mag = np.array([
i_magr[i] for i in range(len(gxr)) if (abs(
gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
])
i_ierr = np.array([
i_ierrr[i] for i in range(len(gxr)) if (abs(
gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
])
gmi = [
gmir[i] for i in range(len(gxr)) if (abs(
gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
]
fwhm_s = [
fwhm_sr[i] for i in range(len(gxr)) if (abs(
gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
]
gmi_err = np.array([
np.sqrt(g_ierrr[i]**2 + i_ierrr[i]**2) for i in range(len(gxr)) if
(abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
])
i_ierrAVG, bedges, binid = ss.binned_statistic(i_mag,
i_ierr,
statistic='median',
bins=10,
range=[15, 25])
gmi_errAVG, bedges, binid = ss.binned_statistic(i_mag,
gmi_err,
statistic='median',
bins=10,
range=[15, 25])
bcenters = (bedges[:-1] + bedges[1:]) / 2
bxvals = [3.75, 3.75, 3.75, 3.75, 3.75, 3.75, 3.75, 3.75, 3.75, 3.75]
# print bcenters
# print i_ierrAVG
# print gmi_errAVG
# print len(gx), "after color+mag error cut"
# nid = np.loadtxt(mag_file,usecols=(0,),dtype=int,unpack=True)
pixcrd = list(zip(ix, iy))
# print "Reading WCS info from image header..."
# Parse the WCS keywords in the primary HDU
warnings.filterwarnings('ignore', category=UserWarning, append=True)
w = wcs.WCS(fits_i[0].header)
# print fits_i[0].header['naxis1'], fits_i[0].header['naxis2']
footprint = w.calc_footprint()
se_corner = footprint[0]
ne_corner = footprint[1]
nw_corner = footprint[2]
sw_corner = footprint[3]
# print se_corner, ne_corner, nw_corner, sw_corner
width = (ne_corner[0] - nw_corner[0]) * 60.
height = (ne_corner[1] - se_corner[1]) * 60.
# print width, height
# Print out the "name" of the WCS, as defined in the FITS header
# print w.wcs.name
# Print out all of the settings that were parsed from the header
# w.wcs.print_contents()
# Convert pixel coordinates to world coordinates
# The second argument is "origin" -- in this case we're declaring we
# have 1-based (Fortran-like) coordinates.
world = w.all_pix2world(pixcrd, 1)
ra_corner, dec_corner = w.all_pix2world(0, 0, 1)
ra_c_d, dec_c_d = deg2HMS(ra=ra_corner, dec=dec_corner, round=True)
# print 'Corner RA:',ra_c_d,':: Corner Dec:',dec_c_d
fits_i.close()
# split the ra and dec out into individual arrays and transform to arcmin from the corner
i_ra = [
abs((world[i, 0] - ra_corner) * 60)
for i in range(len(world[:, 0]))
]
i_dec = [
abs((world[i, 1] - dec_corner) * 60)
for i in range(len(world[:, 1]))
]
# also preserve the decimal degrees for reference
i_rad = [world[i, 0] for i in range(len(world[:, 0]))]
i_decd = [world[i, 1] for i in range(len(world[:, 1]))]
cm_filter, gi_iso, i_m_iso = make_filter(dm, filter_file)
stars_f = filter_sources(i_mag,
i_ierr,
gmi,
gmi_err,
cm_filter,
filter_sig=1)
xy_points = list(zip(i_ra, i_dec))
# make new vectors containing only the filtered points
i_mag_f = [i_mag[i] for i in range(len(i_mag)) if (stars_f[i])]
g_mag_f = [g_mag[i] for i in range(len(i_mag)) if (stars_f[i])]
gmi_f = [gmi[i] for i in range(len(i_mag)) if (stars_f[i])]
i_ra_f = [i_ra[i] for i in range(len(i_mag)) if (stars_f[i])]
i_dec_f = [i_dec[i] for i in range(len(i_mag)) if (stars_f[i])]
i_rad_f = [i_rad[i] for i in range(len(i_mag)) if (stars_f[i])]
i_decd_f = [i_decd[i] for i in range(len(i_mag)) if (stars_f[i])]
i_x_f = [ix[i] for i in range(len(i_mag)) if (stars_f[i])]
i_y_f = [iy[i] for i in range(len(i_mag)) if (stars_f[i])]
fwhm_sf = [fwhm_s[i] for i in range(len(i_mag)) if (stars_f[i])]
n_in_filter = len(i_mag_f)
fwhm = smooths[obj]
xedges, x_cent, yedges, y_cent, S, x_cent_S, y_cent_S, pltsig, tbl = grid_smooth(
i_ra_f, i_dec_f, fwhm, width, height)
# xedges, x_cent, yedges, y_cent, S, x_cent_S, y_cent_S, pltsig, tbl = grid_smooth(i_ra, i_dec, 2.0, width, height)
cosd = lambda x: np.cos(np.deg2rad(x))
sind = lambda x: np.sin(np.deg2rad(x))
hi_x_circ, hi_y_circ = getHIellipse(obj, ra_corner, dec_corner)
# hi_c_x, hi_c_y = abs((hi_c_ra-ra_corner)*60), abs((hi_c_dec-dec_corner)*60)
#
# t = np.array(range(0,359,1))
# ell = np.array([a*cosd(t) , b*sind(t)])
# rot = np.array([[cosd(pa) , -sind(pa)],[sind(pa) , cosd(pa)]])
# ell_rot = np.zeros((2,ell.shape[1]))
# for i in range(ell.shape[1]):
# ell_rot[:,i] = np.dot(rot,ell[:,i])
# hi_x_circ, hi_y_circ = hi_c_x+ell_rot[0,:], hi_c_y+ell_rot[1,:]
# hi_x_circ = [hi_c_x + a*cosd(t) for t in range(0,359,1)]
# hi_y_circ = [hi_c_y + b*sind(t) for t in range(0,359,1)]
x_circ = [yedges[y_cent] + 3.0 * cosd(t) for t in range(0, 359, 1)]
y_circ = [xedges[x_cent] + 3.0 * sind(t) for t in range(0, 359, 1)]
verts_circ = list(zip(x_circ, y_circ))
circ_filter = Path(verts_circ)
stars_circ = circ_filter.contains_points(xy_points)
i_mag_c = [i_mag[i] for i in range(len(i_mag)) if (stars_circ[i])]
gmi_c = [gmi[i] for i in range(len(i_mag)) if (stars_circ[i])]
i_ra_c = [i_ra[i] for i in range(len(i_mag)) if (stars_circ[i])]
i_dec_c = [i_dec[i] for i in range(len(i_mag)) if (stars_circ[i])]
i_rad_c = [i_rad[i] for i in range(len(i_mag)) if (stars_circ[i])]
i_decd_c = [i_decd[i] for i in range(len(i_mag)) if (stars_circ[i])]
i_x_c = [ix[i] for i in range(len(i_mag)) if (stars_circ[i])]
i_y_c = [iy[i] for i in range(len(i_mag)) if (stars_circ[i])]
fwhm_sc = [fwhm_s[i] for i in range(len(i_mag)) if (stars_circ[i])]
# make a random reference cmd to compare to
if not os.path.isfile(folder + 'refCircle.center'):
rCentx = 16.0 * np.random.random() + 2.0
rCenty = 16.0 * np.random.random() + 2.0
with open('refCircle.center', 'w+') as rc:
print('{:8.4f} {:8.4f}'.format(rCentx, rCenty), file=rc)
else:
rCentx, rCenty = np.loadtxt(folder + 'refCircle.center',
usecols=(0, 1),
unpack=True)
x_circr = [rCentx + 3.0 * cosd(t) for t in range(0, 359, 1)]
y_circr = [rCenty + 3.0 * sind(t) for t in range(0, 359, 1)]
verts_circr = list(zip(x_circr, y_circr))
rcirc_filter = Path(verts_circr)
stars_circr = rcirc_filter.contains_points(xy_points)
i_mag_cr = [i_mag[i] for i in range(len(i_mag)) if (stars_circr[i])]
gmi_cr = [gmi[i] for i in range(len(i_mag)) if (stars_circr[i])]
i_ra_cr = [i_ra[i] for i in range(len(i_mag)) if (stars_circr[i])]
i_dec_cr = [i_dec[i] for i in range(len(i_mag)) if (stars_circr[i])]
i_rad_cr = [i_rad[i] for i in range(len(i_mag)) if (stars_circr[i])]
i_decd_cr = [i_decd[i] for i in range(len(i_mag)) if (stars_circr[i])]
i_x_cr = [ix[i] for i in range(len(i_mag)) if (stars_circr[i])]
i_y_cr = [iy[i] for i in range(len(i_mag)) if (stars_circr[i])]
fwhm_scr = [fwhm_s[i] for i in range(len(i_mag)) if (stars_circr[i])]
i_mag_fc = [
i_mag[i] for i in range(len(i_mag))
if (stars_circ[i] and stars_f[i])
]
i_ierr_fc = [
i_ierr[i] for i in range(len(i_mag))
if (stars_circ[i] and stars_f[i])
]
g_ierr_fc = [
g_ierr[i] for i in range(len(i_mag))
if (stars_circ[i] and stars_f[i])
]
g_mag_fc = [
i_mag[i] for i in range(len(i_mag))
if (stars_circ[i] and stars_f[i])
]
gmi_fc = [
gmi[i] for i in range(len(i_mag)) if (stars_circ[i] and stars_f[i])
]
i_ra_fc = [
i_ra[i] for i in range(len(i_mag))
if (stars_circ[i] and stars_f[i])
]
i_dec_fc = [
i_dec[i] for i in range(len(i_mag))
if (stars_circ[i] and stars_f[i])
]
i_rad_fc = [
i_rad[i] for i in range(len(i_mag))
if (stars_circ[i] and stars_f[i])
]
i_decd_fc = [
i_decd[i] for i in range(len(i_mag))
if (stars_circ[i] and stars_f[i])
]
i_x_fc = [
ix[i] for i in range(len(i_mag)) if (stars_circ[i] and stars_f[i])
]
i_y_fc = [
iy[i] for i in range(len(i_mag)) if (stars_circ[i] and stars_f[i])
]
fwhm_sfc = [
fwhm_s[i] for i in range(len(i_mag))
if (stars_circ[i] and stars_f[i])
]
index_fc = [
i for i in range(len(i_mag)) if (stars_circ[i] and stars_f[i])
]
i_mag_fcr = [
i_mag[i] for i in range(len(i_mag))
if (stars_circr[i] and stars_f[i])
]
i_ierr_fcr = [
i_ierr[i] for i in range(len(i_mag))
if (stars_circr[i] and stars_f[i])
]
g_ierr_fcr = [
g_ierr[i] for i in range(len(i_mag))
if (stars_circr[i] and stars_f[i])
]
g_mag_fcr = [
i_mag[i] for i in range(len(i_mag))
if (stars_circr[i] and stars_f[i])
]
gmi_fcr = [
gmi[i] for i in range(len(i_mag))
if (stars_circr[i] and stars_f[i])
]
i_ra_fcr = [
i_ra[i] for i in range(len(i_mag))
if (stars_circr[i] and stars_f[i])
]
i_dec_fcr = [
i_dec[i] for i in range(len(i_mag))
if (stars_circr[i] and stars_f[i])
]
i_rad_fcr = [
i_rad[i] for i in range(len(i_mag))
if (stars_circr[i] and stars_f[i])
]
i_decd_fcr = [
i_decd[i] for i in range(len(i_mag))
if (stars_circr[i] and stars_f[i])
]
i_x_fcr = [
ix[i] for i in range(len(i_mag)) if (stars_circr[i] and stars_f[i])
]
i_y_fcr = [
iy[i] for i in range(len(i_mag)) if (stars_circr[i] and stars_f[i])
]
fwhm_sfcr = [
fwhm_s[i] for i in range(len(i_mag))
if (stars_circr[i] and stars_f[i])
]
# fig = plt.figure(figsize=(8.5,8.5))
fig = plt.figure(figsize=(8.5, 8.5))
outer = gridspec.GridSpec(2, 2, wspace=0.1, hspace=0.1)
# inner = gridspec.GridSpecFromSubplotSpec(1, 4, subplot_spec=outer[i], wspace=0.1, hspace=0.1)
ax1 = plt.Subplot(fig, outer[1])
if os.path.isfile(folder + 'i_gmi_compl.gr.out'):
gmiCompl, iCompl = np.loadtxt(folder + 'i_gmi_compl.gr.out',
usecols=(0, 1),
unpack=True)
ax1.plot(gmiCompl, iCompl, linestyle='--', color='green')
# if os.path.isfile(folder+'i_gmi_compl.gr2.out'):
# gmiCompl, iCompl = np.loadtxt(folder+'i_gmi_compl.gr2.out',usecols=(0,1),unpack=True)
# ax1.plot(gmiCompl,iCompl, linestyle='--', color='red')
# if os.path.isfile(folder+'i_gmi_compl2.out'):
# iCompl,gmiCompl = np.loadtxt(folder+'i_gmi_compl2.out',usecols=(0,1),unpack=True)
# ax1.plot(gmiCompl,iCompl, linestyle='--', color='blue')
ax1.plot(gi_iso, i_m_iso, linestyle='-', color='blue')
ax1.scatter(gmi,
i_mag,
color='black',
marker='o',
s=1,
edgecolors='none')
ax1.scatter(gmi_f,
i_mag_f,
color='red',
marker='o',
s=10,
edgecolors='none')
ax1.errorbar(bxvals,
bcenters,
xerr=i_ierrAVG,
yerr=gmi_errAVG,
linestyle='None',
color='black',
capsize=0,
ms=0)
ax1.tick_params(axis='y',
left='on',
right='off',
labelleft='on',
labelright='off')
ax1.yaxis.set_label_position('left')
ax1.set_xticks([-1, 0, 1, 2, 3, 4])
ax1.set_yticks([15, 17, 19, 21, 23, 25])
ax1.set_ylabel('$i_0$')
ax1.set_xlabel('$(g-i)_0$')
ax1.set_ylim(25, 15)
ax1.set_xlim(-1, 4)
ax1.set_aspect(0.5)
ax1.set_title('$m-M = ${:5.2f} | $d = ${:4.2f} Mpc'.format(dm, mpc),
size='small')
fig.add_subplot(ax1)
ax2 = plt.Subplot(fig, outer[0])
extent = [yedges[0], yedges[-1], xedges[-1], xedges[0]]
im = ax2.imshow(S,
extent=extent,
interpolation='nearest',
cmap=cm.gray)
# cbar_S = plt.colorbar()
# cbar_S.set_label('$\sigma$ from local mean')
ax2.plot(hi_x_circ, hi_y_circ, linestyle='-', color='limegreen')
ax2.plot(x_circ, y_circ, linestyle='-', color='magenta')
ax2.plot(x_circr, y_circr, linestyle='-', color='gold')
ax2.tick_params(axis='y',
left='on',
right='off',
labelleft='on',
labelright='off')
ax2.yaxis.set_label_position('left')
ax2.set_xticks([0, 5, 10, 15, 20])
ax2.set_yticks([0, 5, 10, 15, 20])
ax2.set_xlabel('RA (arcmin)')
ax2.set_ylabel('Dec (arcmin)')
if obj.startswith('HI1151'):
ax2.set_title('AGC219656', size='small')
else:
ax2.set_title(obj, size='small')
ax2.set_xlim(0, max(i_ra))
ax2.set_ylim(0, max(i_dec))
# im.set_clim(-3, 3)
ax2.set_aspect('equal')
fig.add_subplot(ax2)
ax3 = plt.Subplot(fig, outer[2])
if os.path.isfile(folder + 'i_gmi_compl.gr.out'):
gmiCompl, iCompl = np.loadtxt(folder + 'i_gmi_compl.gr.out',
usecols=(0, 1),
unpack=True)
ax3.plot(gmiCompl, iCompl, linestyle='--', color='green')
ax3.plot(gi_iso, i_m_iso, linestyle='-', lw=0.5, color='blue')
ax3.scatter(gmi_c,
i_mag_c,
color='black',
marker='o',
s=1,
edgecolors='none')
ax3.scatter(gmi_fc,
i_mag_fc,
color='red',
marker='o',
s=10,
edgecolors='none')
ax3.errorbar(bxvals,
bcenters,
xerr=i_ierrAVG,
yerr=gmi_errAVG,
linestyle='None',
color='black',
capsize=0,
ms=0)
ax3.tick_params(axis='y',
left='on',
right='off',
labelleft='on',
labelright='off')
ax3.yaxis.set_label_position('left')
ax3.set_xticks([-1, 0, 1, 2, 3, 4])
ax3.set_yticks([15, 17, 19, 21, 23, 25])
ax3.set_ylabel('$i_0$')
ax3.set_xlabel('$(g-i)_0$')
ax3.set_ylim(25, 15)
ax3.set_xlim(-1, 4)
ax3.set_aspect(0.5)
ax3.set_title('detection', size='small')
fig.add_subplot(ax3)
ax4 = plt.Subplot(fig, outer[3])
if os.path.isfile(folder + 'i_gmi_compl.gr.out'):
gmiCompl, iCompl = np.loadtxt(folder + 'i_gmi_compl.gr.out',
usecols=(0, 1),
unpack=True)
ax4.plot(gmiCompl, iCompl, linestyle='--', color='green')
ax4.plot(gi_iso, i_m_iso, linestyle='-', lw=0.5, color='blue')
ax4.scatter(gmi_cr,
i_mag_cr,
color='black',
marker='o',
s=1,
edgecolors='none')
ax4.scatter(gmi_fcr,
i_mag_fcr,
color='red',
marker='o',
s=10,
edgecolors='none')
ax4.errorbar(bxvals,
bcenters,
xerr=i_ierrAVG,
yerr=gmi_errAVG,
linestyle='None',
color='black',
capsize=0,
ms=0)
ax4.tick_params(axis='y',
left='on',
right='off',
labelleft='on',
labelright='off')
ax4.yaxis.set_label_position('left')
ax4.set_xticks([-1, 0, 1, 2, 3, 4])
ax4.set_yticks([15, 17, 19, 21, 23, 25])
ax4.set_ylabel('$i_0$')
ax4.set_xlabel('$(g-i)_0$')
ax4.set_ylim(25, 15)
ax4.set_xlim(-1, 4)
ax4.set_aspect(0.5)
ax4.set_title('reference', size='small')
fig.add_subplot(ax4)
outer.tight_layout(fig)
# plt.savefig('detections.pdf')
plt.savefig('{:s}.pdf'.format(obj))
pass
def main():
objects = OrderedDict([('AGC249525',26.78)])
filter_file = os.path.dirname(os.path.abspath(__file__))+'/filter.txt'
fwhm_sm = 3.0
fwhm_sm_string = '3.0'
# plt.clf()
fig = plt.figure(figsize=(9,4))
outer = gridspec.GridSpec(1,1, wspace=0.1, hspace=0.1)
for i, obj in enumerate(objects.keys()):
print obj
inner = gridspec.GridSpecFromSubplotSpec(1, 1, subplot_spec=outer[i], wspace=0.1, hspace=0.1)
# set up some filenames
folder = '/Volumes/galileo/uchvc/targets/'+obj.lower()+'/'
mag_file = folder+'calibrated_mags.dat'
fits_file_i = folder+obj+'_i.fits'
fits_i = fits.open(fits_file_i)
dm = objects[obj]
# read in magnitudes, colors, and positions(x,y)
# gxr,gyr,g_magr,g_ierrr,ixr,iyr,i_magr,i_ierrr,gmir,fwhm_sr= np.loadtxt(mag_file,usecols=(0,1,2,3,4,5,6,7,8,11),unpack=True)
gxr,gyr,g_magr,g_ierrr,ixr,iyr,i_magr,i_ierrr,gmir= np.loadtxt(mag_file,usecols=(0,1,2,3,4,5,6,7,8),unpack=True)
# print len(gxr), "total stars"
fwhm_sr = np.ones_like(gxr)
# filter out the things with crappy color errors
color_error_cut = np.sqrt(2.0)*0.2
mag_error_cut = 0.2
gmi_errr = [np.sqrt(g_ierrr[i]**2 + i_ierrr[i]**2) for i in range(len(gxr))]
gx = [gxr[i] for i in range(len(gxr)) if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))]
gy = [gyr[i] for i in range(len(gxr)) if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))]
g_mag = [g_magr[i] for i in range(len(gxr)) if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))]
g_ierr = [g_ierrr[i] for i in range(len(gxr)) if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))]
ix = [ixr[i] for i in range(len(gxr)) if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))]
iy = [iyr[i] for i in range(len(gxr)) if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))]
i_mag = [i_magr[i] for i in range(len(gxr)) if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))]
i_ierr = np.array([i_ierrr[i] for i in range(len(gxr)) if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))])
gmi = [gmir[i] for i in range(len(gxr)) if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))]
fwhm_s = [fwhm_sr[i] for i in range(len(gxr)) if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))]
gmi_err = np.array([np.sqrt(g_ierrr[i]**2 + i_ierrr[i]**2) for i in range(len(gxr)) if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))])
i_ierrAVG, bedges, binid = ss.binned_statistic(i_mag,i_ierr,statistic='median',bins=10,range=[15,25])
gmi_errAVG, bedges, binid = ss.binned_statistic(i_mag,gmi_err,statistic='median',bins=10,range=[15,25])
bcenters = (bedges[:-1] + bedges[1:]) / 2
bxvals = [3.75,3.75,3.75,3.75,3.75,3.75,3.75,3.75,3.75,3.75]
# print bcenters
# print i_ierrAVG
# print gmi_errAVG
# print len(gx), "after color+mag error cut"
# nid = np.loadtxt(mag_file,usecols=(0,),dtype=int,unpack=True)
pixcrd = zip(ix,iy)
# print "Reading WCS info from image header..."
# Parse the WCS keywords in the primary HDU
warnings.filterwarnings('ignore', category=UserWarning, append=True)
w = wcs.WCS(fits_i[0].header)
# print fits_i[0].header['naxis1'], fits_i[0].header['naxis2']
footprint = w.calc_footprint()
se_corner = footprint[0]
ne_corner = footprint[1]
nw_corner = footprint[2]
sw_corner = footprint[3]
# print se_corner, ne_corner, nw_corner, sw_corner
width = (ne_corner[0]-nw_corner[0])*60.
height = (ne_corner[1]-se_corner[1])*60.
# print width, height
# Print out the "name" of the WCS, as defined in the FITS header
# print w.wcs.name
# Print out all of the settings that were parsed from the header
# w.wcs.print_contents()
# Convert pixel coordinates to world coordinates
# The second argument is "origin" -- in this case we're declaring we
# have 1-based (Fortran-like) coordinates.
world = w.all_pix2world(pixcrd, 1)
ra_corner, dec_corner = w.all_pix2world(0,0,1)
ra_c_d,dec_c_d = deg2HMS(ra=ra_corner, dec=dec_corner, round=True)
# print 'Corner RA:',ra_c_d,':: Corner Dec:',dec_c_d
fits_i.close()
# split the ra and dec out into individual arrays and transform to arcmin from the corner
i_ra = [abs((world[i,0]-ra_corner)*60) for i in range(len(world[:,0]))]
i_dec = [abs((world[i,1]-dec_corner)*60) for i in range(len(world[:,1]))]
# also preserve the decimal degrees for reference
i_rad = [world[i,0] for i in range(len(world[:,0]))]
i_decd = [world[i,1] for i in range(len(world[:,1]))]
search = open(obj+'_search'+fwhm_sm_string+'.txt','w+')
sig_bins = []
sig_cens = []
sig_max = []
pcts = []
dms = np.arange(22.0,27.0,0.01)
for dm in dms:
mpc = pow(10,((dm + 5.)/5.))/1000000.
dm_string = '{:5.2f}'.format(dm).replace('.','_')
cm_filter, gi_iso, i_m_iso = make_filter(dm, filter_file)
stars_f = filter_sources(i_mag, i_ierr, gmi, gmi_err, cm_filter, filter_sig = 1)
xy_points = zip(i_ra,i_dec)
# make new vectors containing only the filtered points
i_mag_f = [i_mag[i] for i in range(len(i_mag)) if (stars_f[i])]
g_mag_f = [g_mag[i] for i in range(len(i_mag)) if (stars_f[i])]
gmi_f = [gmi[i] for i in range(len(i_mag)) if (stars_f[i])]
i_ra_f = [i_ra[i] for i in range(len(i_mag)) if (stars_f[i])]
i_dec_f = [i_dec[i] for i in range(len(i_mag)) if (stars_f[i])]
i_rad_f = [i_rad[i] for i in range(len(i_mag)) if (stars_f[i])]
i_decd_f = [i_decd[i] for i in range(len(i_mag)) if (stars_f[i])]
i_x_f = [ix[i] for i in range(len(i_mag)) if (stars_f[i])]
i_y_f = [iy[i] for i in range(len(i_mag)) if (stars_f[i])]
fwhm_sf = [fwhm_s[i] for i in range(len(i_mag)) if (stars_f[i])]
n_in_filter = len(i_mag_f)
xedges, x_cent, yedges, y_cent, S, x_cent_S, y_cent_S, pltsig, tbl = grid_smooth(i_ra_f, i_dec_f, fwhm_sm, width, height)
pct, d_bins, d_cens = distfit(n_in_filter,S[x_cent_S][y_cent_S],obj,width,height,fwhm_sm,dm, samples=1000)
sig_bins.append(d_bins)
sig_cens.append(d_cens)
sig_max.append(S[x_cent_S][y_cent_S])
pcts.append(pct)
circ_c_x = ra_corner-(yedges[y_cent]/60.)
circ_c_y = (xedges[x_cent]/60.)+dec_corner
circ_pix_x, circ_pix_y = w.wcs_world2pix(circ_c_x,circ_c_y,1)
ra_c, dec_c = w.all_pix2world(circ_pix_x, circ_pix_y,1)
ra_c_d,dec_c_d = deg2HMS(ra=ra_c, dec=dec_c, round=False)
hi_c_ra, hi_c_dec = getHIellipse(obj, ra_corner, dec_corner, centroid=True)
sep = dist2HIcentroid(ra_c_d, dec_c_d, hi_c_ra, hi_c_dec)
print 'm-M = {:5.2f} | d = {:4.2f} Mpc | α = {:s}, δ = {:s}, Δʜɪ = {:5.1f}" | N = {:4d} | σ = {:6.3f} | ξ = {:6.3f}%'.format(dm, mpc, ra_c_d, dec_c_d, sep, n_in_filter, S[x_cent_S][y_cent_S], pct)
print >> search, '{:5.2f} {:4.2f} {:s} {:s} {:5.1f} {:4d} {:6.3f} {:6.3f}'.format(dm, mpc, ra_c_d, dec_c_d, sep, n_in_filter, S[x_cent_S][y_cent_S], pct)
ax1 = plt.Subplot(fig, inner[0])
ax1.imshow(np.transpose(sig_bins), cmap=plt.cm.Reds, extent=(22, 27, 22, 2))#, origin=origin)
ax1.scatter(dms, sig_max, linestyle='-', c=pcts, cmap=plt.cm.Blues)
ax1.set_ylabel('$\sigma$')
ax1.set_xlabel('distance modulus')
ax1.set_xlim(22,27)
ax1.set_ylim(2,6.5)
ax1.vlines([26.07, 26.78], 2, 6.5, linestyles='dashed', lw=0.5)
if obj.startswith('HI1151'):
ax1.set_title('AGC219656', size='small')
else:
ax1.set_title(obj, size='small')
ax1.set_aspect(0.4)
fig.add_subplot(ax1)
outer.tight_layout(fig)
plt.savefig('detections_significance.pdf')
pass
def main():
objects = OrderedDict([('AGC249320',25.28), ('AGC258242',25.05), ('AGC268074',22.10), ('HI0959+19',23.08)])
smooths = OrderedDict([('AGC249320',2.0), ('AGC258242',3.0), ('AGC268074',2.0), ('HI0959+19',2.0)])
filter_file = os.path.dirname(os.path.abspath(__file__))+'/filter.txt'
young_file = os.path.dirname(os.path.abspath(__file__))+'/filter_young.txt'
# plt.clf()
fig = plt.figure(figsize=(8.75,8.75))
outer = gridspec.GridSpec(4, 1, wspace=0.05, hspace=0.01)
for i, obj in enumerate(objects.keys()):
inner = gridspec.GridSpecFromSubplotSpec(1, 4, subplot_spec=outer[i], wspace=0.05, hspace=0.05)
# set up some filenames
# if os.path.isfile('/data/uchvc/targets/'+obj.lower()+'/'):
folder = '/data/uchvc/targets/'+obj.lower()+'/'
# else:
# folder = '/Volumes/discovery1/uchvc/targets/'+obj.lower()+'/'
mag_file = folder+'calibrated_mags.dat'
fits_file_i = folder+obj+'_i.fits'
fits_i = fits.open(fits_file_i)
dm = objects[obj]
mpc = pow(10,((dm + 5.)/5.))/1000000.
# read in magnitudes, colors, and positions(x,y)
# gxr,gyr,g_magr,g_ierrr,ixr,iyr,i_magr,i_ierrr,gmir,fwhm_sr= np.loadtxt(mag_file,usecols=(0,1,2,3,4,5,6,7,8,11),unpack=True)
gxr,gyr,g_magr,g_ierrr,ixr,iyr,i_magr,i_ierrr,gmir= np.loadtxt(mag_file,usecols=(0,1,2,3,4,5,6,7,8),unpack=True)
# print len(gxr), "total stars"
fwhm_sr = np.ones_like(gxr)
# filter out the things with crappy color errors
color_error_cut = np.sqrt(2.0)*0.2
mag_error_cut = 0.2
gmi_errr = [np.sqrt(g_ierrr[i]**2 + i_ierrr[i]**2) for i in range(len(gxr))]
gx = [gxr[i] for i in range(len(gxr)) if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))]
gy = [gyr[i] for i in range(len(gxr)) if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))]
g_mag = [g_magr[i] for i in range(len(gxr)) if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))]
g_ierr = [g_ierrr[i] for i in range(len(gxr)) if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))]
ix = [ixr[i] for i in range(len(gxr)) if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))]
iy = [iyr[i] for i in range(len(gxr)) if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))]
i_mag = np.array([i_magr[i] for i in range(len(gxr)) if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))])
i_ierr = np.array([i_ierrr[i] for i in range(len(gxr)) if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))])
gmi = [gmir[i] for i in range(len(gxr)) if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))]
fwhm_s = [fwhm_sr[i] for i in range(len(gxr)) if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))]
gmi_err = np.array([np.sqrt(g_ierrr[i]**2 + i_ierrr[i]**2) for i in range(len(gxr)) if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))])
i_ierrAVG, bedges, binid = ss.binned_statistic(i_mag,i_ierr,statistic='median',bins=10,range=[15,25])
gmi_errAVG, bedges, binid = ss.binned_statistic(i_mag,gmi_err,statistic='median',bins=10,range=[15,25])
bcenters = (bedges[:-1] + bedges[1:]) / 2
bxvals = [3.75,3.75,3.75,3.75,3.75,3.75,3.75,3.75,3.75,3.75]
# print bcenters
# print i_ierrAVG
# print gmi_errAVG
# print len(gx), "after color+mag error cut"
# nid = np.loadtxt(mag_file,usecols=(0,),dtype=int,unpack=True)
pixcrd = list(zip(ix,iy))
# print "Reading WCS info from image header..."
# Parse the WCS keywords in the primary HDU
warnings.filterwarnings('ignore', category=UserWarning, append=True)
w = wcs.WCS(fits_i[0].header)
# print fits_i[0].header['naxis1'], fits_i[0].header['naxis2']
footprint = w.calc_footprint()
se_corner = footprint[0]
ne_corner = footprint[1]
nw_corner = footprint[2]
sw_corner = footprint[3]
# print se_corner, ne_corner, nw_corner, sw_corner
width = (ne_corner[0]-nw_corner[0])*60.
height = (ne_corner[1]-se_corner[1])*60.
# print width, height
# Print out the "name" of the WCS, as defined in the FITS header
# print w.wcs.name
# Print out all of the settings that were parsed from the header
# w.wcs.print_contents()
# Convert pixel coordinates to world coordinates
# The second argument is "origin" -- in this case we're declaring we
# have 1-based (Fortran-like) coordinates.
world = w.all_pix2world(pixcrd, 1)
ra_corner, dec_corner = w.all_pix2world(0,0,1)
ra_c_d,dec_c_d = deg2HMS(ra=ra_corner, dec=dec_corner, round=True)
# print 'Corner RA:',ra_c_d,':: Corner Dec:',dec_c_d
fits_i.close()
# split the ra and dec out into individual arrays and transform to arcmin from the corner
i_ra = [abs((world[i,0]-ra_corner)*60) for i in range(len(world[:,0]))]
i_dec = [abs((world[i,1]-dec_corner)*60) for i in range(len(world[:,1]))]
# also preserve the decimal degrees for reference
i_rad = [world[i,0] for i in range(len(world[:,0]))]
i_decd = [world[i,1] for i in range(len(world[:,1]))]
cm_filter, gi_iso, i_m_iso = make_filter(dm, filter_file)
gi_young, i_m_young = make_youngpop(dm, young_file)
stars_f = filter_sources(i_mag, i_ierr, gmi, gmi_err, cm_filter, filter_sig = 1)
xy_points = list(zip(i_ra,i_dec))
# make new vectors containing only the filtered points
i_mag_f = [i_mag[i] for i in range(len(i_mag)) if (stars_f[i])]
g_mag_f = [g_mag[i] for i in range(len(i_mag)) if (stars_f[i])]
gmi_f = [gmi[i] for i in range(len(i_mag)) if (stars_f[i])]
i_ra_f = [i_ra[i] for i in range(len(i_mag)) if (stars_f[i])]
i_dec_f = [i_dec[i] for i in range(len(i_mag)) if (stars_f[i])]
i_rad_f = [i_rad[i] for i in range(len(i_mag)) if (stars_f[i])]
i_decd_f = [i_decd[i] for i in range(len(i_mag)) if (stars_f[i])]
i_x_f = [ix[i] for i in range(len(i_mag)) if (stars_f[i])]
i_y_f = [iy[i] for i in range(len(i_mag)) if (stars_f[i])]
fwhm_sf = [fwhm_s[i] for i in range(len(i_mag)) if (stars_f[i])]
n_in_filter = len(i_mag_f)
fwhm = smooths[obj]
xedges, x_cent, yedges, y_cent, S, x_cent_S, y_cent_S, pltsig, tbl = grid_smooth(i_ra_f, i_dec_f, fwhm, width, height)
# xedges, x_cent, yedges, y_cent, S, x_cent_S, y_cent_S, pltsig, tbl = grid_smooth(i_ra, i_dec, 2.0, width, height)
cosd = lambda x : np.cos(np.deg2rad(x))
sind = lambda x : np.sin(np.deg2rad(x))
# hi_c_x, hi_c_y = abs((hi_c_ra-ra_corner)*60), abs((hi_c_dec-dec_corner)*60)
#
# t = np.array(range(0,359,1))
# ell = np.array([a*cosd(t) , b*sind(t)])
# rot = np.array([[cosd(pa) , -sind(pa)],[sind(pa) , cosd(pa)]])
# ell_rot = np.zeros((2,ell.shape[1]))
# for i in range(ell.shape[1]):
# ell_rot[:,i] = np.dot(rot,ell[:,i])
# hi_x_circ, hi_y_circ = hi_c_x+ell_rot[0,:], hi_c_y+ell_rot[1,:]
# hi_x_circ = [hi_c_x + a*cosd(t) for t in range(0,359,1)]
# hi_y_circ = [hi_c_y + b*sind(t) for t in range(0,359,1)]
x_circ = [yedges[y_cent] + 3.0*cosd(t) for t in range(0,359,1)]
y_circ = [xedges[x_cent] + 3.0*sind(t) for t in range(0,359,1)]
circ_c_x = ra_corner-(yedges[y_cent]/60.)
circ_c_y = (xedges[x_cent]/60.)+dec_corner
circ_pix_x, circ_pix_y = w.wcs_world2pix(circ_c_x,circ_c_y,1)
ra_c, dec_c = w.all_pix2world(circ_pix_x, circ_pix_y,1)
ra_c_d,dec_c_d = deg2HMS(ra=ra_c, dec=dec_c, round=False)
hi_x_circ, hi_y_circ = getHIellipse(obj, ra_corner, dec_corner)
hi_c_ra, hi_c_dec = getHIellipse(obj, ra_corner, dec_corner, centroid=True)
sep, sep3d = dist2HIcentroid(ra_c_d, dec_c_d, hi_c_ra, hi_c_dec, mpc)
print(obj, sep, sep3d)
verts_circ = list(zip(x_circ,y_circ))
circ_filter = Path(verts_circ)
stars_circ = circ_filter.contains_points(xy_points)
i_mag_c = [i_mag[i] for i in range(len(i_mag)) if (stars_circ[i])]
gmi_c = [gmi[i] for i in range(len(i_mag)) if (stars_circ[i])]
i_ra_c = [i_ra[i] for i in range(len(i_mag)) if (stars_circ[i])]
i_dec_c = [i_dec[i] for i in range(len(i_mag)) if (stars_circ[i])]
i_rad_c = [i_rad[i] for i in range(len(i_mag)) if (stars_circ[i])]
i_decd_c = [i_decd[i] for i in range(len(i_mag)) if (stars_circ[i])]
i_x_c = [ix[i] for i in range(len(i_mag)) if (stars_circ[i])]
i_y_c = [iy[i] for i in range(len(i_mag)) if (stars_circ[i])]
fwhm_sc = [fwhm_s[i] for i in range(len(i_mag)) if (stars_circ[i])]
# make a random reference cmd to compare to
if not os.path.isfile(folder+'refCircle.center'):
rCentx = 16.0*np.random.random()+2.0
rCenty = 16.0*np.random.random()+2.0
with open('refCircle.center','w+') as rc:
print('{:8.4f} {:8.4f}'.format(rCentx, rCenty), file=rc)
else :
rCentx, rCenty = np.loadtxt(folder+'refCircle.center', usecols=(0,1), unpack=True)
x_circr = [rCentx + 3.0*cosd(t) for t in range(0,359,1)]
y_circr = [rCenty + 3.0*sind(t) for t in range(0,359,1)]
verts_circr = list(zip(x_circr,y_circr))
rcirc_filter = Path(verts_circr)
stars_circr = rcirc_filter.contains_points(xy_points)
i_mag_cr = [i_mag[i] for i in range(len(i_mag)) if (stars_circr[i])]
gmi_cr = [gmi[i] for i in range(len(i_mag)) if (stars_circr[i])]
i_ra_cr = [i_ra[i] for i in range(len(i_mag)) if (stars_circr[i])]
i_dec_cr = [i_dec[i] for i in range(len(i_mag)) if (stars_circr[i])]
i_rad_cr = [i_rad[i] for i in range(len(i_mag)) if (stars_circr[i])]
i_decd_cr = [i_decd[i] for i in range(len(i_mag)) if (stars_circr[i])]
i_x_cr = [ix[i] for i in range(len(i_mag)) if (stars_circr[i])]
i_y_cr = [iy[i] for i in range(len(i_mag)) if (stars_circr[i])]
fwhm_scr = [fwhm_s[i] for i in range(len(i_mag)) if (stars_circr[i])]
i_mag_fc = [i_mag[i] for i in range(len(i_mag)) if (stars_circ[i] and stars_f[i])]
i_ierr_fc = [i_ierr[i] for i in range(len(i_mag)) if (stars_circ[i] and stars_f[i])]
g_ierr_fc = [g_ierr[i] for i in range(len(i_mag)) if (stars_circ[i] and stars_f[i])]
g_mag_fc = [i_mag[i] for i in range(len(i_mag)) if (stars_circ[i] and stars_f[i])]
gmi_fc = [gmi[i] for i in range(len(i_mag)) if (stars_circ[i] and stars_f[i])]
i_ra_fc = [i_ra[i] for i in range(len(i_mag)) if (stars_circ[i] and stars_f[i])]
i_dec_fc = [i_dec[i] for i in range(len(i_mag)) if (stars_circ[i] and stars_f[i])]
i_rad_fc = [i_rad[i] for i in range(len(i_mag)) if (stars_circ[i] and stars_f[i])]
i_decd_fc = [i_decd[i] for i in range(len(i_mag)) if (stars_circ[i] and stars_f[i])]
i_x_fc = [ix[i] for i in range(len(i_mag)) if (stars_circ[i] and stars_f[i])]
i_y_fc = [iy[i] for i in range(len(i_mag)) if (stars_circ[i] and stars_f[i])]
fwhm_sfc = [fwhm_s[i] for i in range(len(i_mag)) if (stars_circ[i] and stars_f[i])]
index_fc = [i for i in range(len(i_mag)) if (stars_circ[i] and stars_f[i])]
i_mag_fcr = [i_mag[i] for i in range(len(i_mag)) if (stars_circr[i] and stars_f[i])]
i_ierr_fcr = [i_ierr[i] for i in range(len(i_mag)) if (stars_circr[i] and stars_f[i])]
g_ierr_fcr = [g_ierr[i] for i in range(len(i_mag)) if (stars_circr[i] and stars_f[i])]
g_mag_fcr = [i_mag[i] for i in range(len(i_mag)) if (stars_circr[i] and stars_f[i])]
gmi_fcr = [gmi[i] for i in range(len(i_mag)) if (stars_circr[i] and stars_f[i])]
i_ra_fcr = [i_ra[i] for i in range(len(i_mag)) if (stars_circr[i] and stars_f[i])]
i_dec_fcr = [i_dec[i] for i in range(len(i_mag)) if (stars_circr[i] and stars_f[i])]
i_rad_fcr = [i_rad[i] for i in range(len(i_mag)) if (stars_circr[i] and stars_f[i])]
i_decd_fcr = [i_decd[i] for i in range(len(i_mag)) if (stars_circr[i] and stars_f[i])]
i_x_fcr = [ix[i] for i in range(len(i_mag)) if (stars_circr[i] and stars_f[i])]
i_y_fcr = [iy[i] for i in range(len(i_mag)) if (stars_circr[i] and stars_f[i])]
fwhm_sfcr = [fwhm_s[i] for i in range(len(i_mag)) if (stars_circr[i] and stars_f[i])]
# fig = plt.figure(figsize=(8.5,8.5))
ax1 = plt.Subplot(fig, inner[0])
if os.path.isfile(folder+'i_gmi_compl.gr.out'):
gmiCompl, iCompl = np.loadtxt(folder+'i_gmi_compl.gr.out',usecols=(0,1),unpack=True)
ax1.plot(gmiCompl,iCompl, linestyle='--', color='green')
# if os.path.isfile(folder+'i_gmi_compl.gr2.out'):
# gmiCompl, iCompl = np.loadtxt(folder+'i_gmi_compl.gr2.out',usecols=(0,1),unpack=True)
# ax1.plot(gmiCompl,iCompl, linestyle='--', color='red')
# if os.path.isfile(folder+'i_gmi_compl2.out'):
# iCompl,gmiCompl = np.loadtxt(folder+'i_gmi_compl2.out',usecols=(0,1),unpack=True)
# ax1.plot(gmiCompl,iCompl, linestyle='--', color='blue')
ax1.plot(gi_iso,i_m_iso,linestyle='-', lw=0.5, color='blue')
ax1.plot(gi_young,i_m_young,linestyle='--', lw=0.5, color='blue')
ax1.scatter(gmi, i_mag, color='black', marker='o', s=1, edgecolors='none')
ax1.scatter(gmi_f, i_mag_f, color='red', marker='o', s=5, edgecolors='none')
ax1.errorbar(bxvals, bcenters, xerr=i_ierrAVG, yerr=gmi_errAVG, linestyle='None', color='black', capsize=0, ms=0)
ax1.tick_params(labelsize='small')
ax1.yaxis.set_label_position('left')
ax1.set_xticks([-1,0,1,2,3,4])
ax1.set_yticks([15, 17, 19, 21, 23, 25])
ax1.set_ylabel('$i_0$', size='small')
ax1.set_xlabel('$(g-i)_0$', size='small')
ax1.set_ylim(25,15)
ax1.set_xlim(-1,4)
ax1.set_aspect(0.5)
ax1.set_title('$m-M = ${:5.2f} | $d = ${:4.2f} Mpc'.format(dm, mpc), size='small')
if obj.startswith('HI1151'):
ax1.text(-0.4, 0.75, 'AGC219656', size='small', weight='bold', rotation=90, transform=ax1.transAxes)
else:
ax1.text(-0.4, 0.75, obj, size='small', weight='bold', rotation=90, transform=ax1.transAxes)
fig.add_subplot(ax1)
ax2 = plt.Subplot(fig, inner[1])
extent = [yedges[0], yedges[-1], xedges[-1], xedges[0]]
im = ax2.imshow(S, extent=extent, interpolation='nearest',cmap=cm.gray)
# cbar_S = plt.colorbar()
# cbar_S.set_label('$\sigma$ from local mean')
ax2.plot(hi_x_circ,hi_y_circ,linestyle='-', color='limegreen')
ax2.plot(x_circ,y_circ,linestyle='-', color='magenta')
ax2.plot(x_circr,y_circr,linestyle='-', color='gold')
ax2.tick_params(labelsize='small')
ax2.yaxis.set_label_position('left')
ax2.set_xticks([0,5,10,15,20])
ax2.set_yticks([0,5,10,15,20])
ax2.set_xlabel('RA (arcmin)', size='small')
ax2.set_ylabel('Dec (arcmin)', size='small')
ax2.set_title("stellar density map", weight='bold', size='small')
ax2.set_xlim(0,max(i_ra))
ax2.set_ylim(0,max(i_dec))
# im.set_clim(-3, 3)
ax2.set_aspect('equal')
fig.add_subplot(ax2)
ax3 = plt.Subplot(fig, inner[2])
if os.path.isfile(folder+'i_gmi_compl.gr.out'):
gmiCompl, iCompl = np.loadtxt(folder+'i_gmi_compl.gr.out',usecols=(0,1),unpack=True)
ax3.plot(gmiCompl,iCompl, linestyle='--', color='green')
ax3.plot(gi_iso,i_m_iso,linestyle='-', lw=0.5, color='blue')
ax3.plot(gi_young,i_m_young,linestyle='--', lw=0.5, color='blue')
ax3.scatter(gmi_c, i_mag_c, color='black', marker='o', s=1, edgecolors='none')
ax3.scatter(gmi_fc, i_mag_fc, color='red', marker='o', s=5, edgecolors='none')
ax3.errorbar(bxvals, bcenters, xerr=i_ierrAVG, yerr=gmi_errAVG, linestyle='None', color='black', capsize=0, ms=0)
ax3.tick_params(labelsize='small')
ax3.yaxis.set_label_position('left')
ax3.set_xticks([-1,0,1,2,3,4])
ax3.set_yticks([15, 17, 19, 21, 23, 25])
ax3.set_ylabel('$i_0$', size='small')
ax3.set_xlabel('$(g-i)_0$', size='small')
ax3.set_ylim(25,15)
ax3.set_xlim(-1,4)
ax3.set_aspect(0.5)
ax3.set_title('object circle', color='magenta', weight='bold', size='small')
fig.add_subplot(ax3)
ax4 = plt.Subplot(fig, inner[3])
if os.path.isfile(folder+'i_gmi_compl.gr.out'):
gmiCompl, iCompl = np.loadtxt(folder+'i_gmi_compl.gr.out',usecols=(0,1),unpack=True)
ax4.plot(gmiCompl,iCompl, linestyle='--', color='green')
ax4.plot(gi_iso,i_m_iso,linestyle='-', lw=0.5, color='blue')
ax4.plot(gi_young,i_m_young,linestyle='--', lw=0.5, color='blue')
ax4.scatter(gmi_cr, i_mag_cr, color='black', marker='o', s=1, edgecolors='none')
ax4.scatter(gmi_fcr, i_mag_fcr, color='red', marker='o', s=5, edgecolors='none')
ax4.errorbar(bxvals, bcenters, xerr=i_ierrAVG, yerr=gmi_errAVG, linestyle='None', color='black', capsize=0, ms=0)
ax4.tick_params(labelsize='small')
ax4.yaxis.set_label_position('left')
ax4.set_xticks([-1,0,1,2,3,4])
ax4.set_yticks([15, 17, 19, 21, 23, 25])
ax4.set_ylabel('$i_0$', size='small')
ax4.set_xlabel('$(g-i)_0$', size='small')
ax4.set_ylim(25,15)
ax4.set_xlim(-1,4)
ax4.set_aspect(0.5)
ax4.set_title('reference circle', color='gold', weight='bold', size='small')
fig.add_subplot(ax4)
fig.tight_layout()
outer.tight_layout(fig)
plt.savefig('marginals.pdf')
# plt.savefig('{:s}.pdf'.format(obj))
pass
def main():
fwhm_sm = float(sys.argv[1])
objects = ['AGC174540', 'AGC198511', 'AGC198606', 'AGC215417', 'AGC226067', 'AGC227987', 'AGC229326', 'AGC238626', 'AGC238713', 'AGC249000', 'AGC249282', 'AGC249320']
objects2 = ['AGC249323', 'AGC249525', 'AGC258237', 'AGC258242', 'AGC258459', 'AGC268069', 'AGC268074', 'HI0932+24', 'HI0959+19', 'HI1037+21', 'HI1050+23', 'HI1151+20']
filter_file = os.path.dirname(os.path.abspath(__file__))+'/filter.txt'
# plt.clf()
fig = plt.figure(figsize=(10,7))
outer = gridspec.GridSpec(4,3, wspace=0.1, hspace=0.1)
for i, obj in enumerate(objects2):
print obj
inner = gridspec.GridSpecFromSubplotSpec(1, 2, subplot_spec=outer[i], wspace=0.1, hspace=0.1)
# set up some filenames
folder = '/Volumes/galileo/uchvc/targets/'+obj.lower()+'/'
mag_file = folder+'calibrated_mags.dat'
fits_file_i = folder+obj+'_i.fits'
dmr, mpcr, sepr, nr, sr, pctr, pct_hir = np.loadtxt(folder+'search_{:3.1f}.txt'.format(fwhm_sm), usecols=(0,1,4,5,6,7,8), unpack=True)
close = np.where(sepr < 480.)
maxloc = np.argmax(pctr)
maxclose = np.argmax(pctr[close])
fits_i = fits.open(fits_file_i)
# dm = dmr[maxloc]
dm = (dmr[close])[maxclose]
# read in magnitudes, colors, and positions(x,y)
# gxr,gyr,g_magr,g_ierrr,ixr,iyr,i_magr,i_ierrr,gmir,fwhm_sr= np.loadtxt(mag_file,usecols=(0,1,2,3,4,5,6,7,8,11),unpack=True)
gxr,gyr,g_magr,g_ierrr,ixr,iyr,i_magr,i_ierrr,gmir= np.loadtxt(mag_file,usecols=(0,1,2,3,4,5,6,7,8),unpack=True)
# print len(gxr), "total stars"
fwhm_sr = np.ones_like(gxr)
# filter out the things with crappy color errors
color_error_cut = np.sqrt(2.0)*0.2
mag_error_cut = 0.2
gmi_errr = [np.sqrt(g_ierrr[i]**2 + i_ierrr[i]**2) for i in range(len(gxr))]
gx = [gxr[i] for i in range(len(gxr)) if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))]
gy = [gyr[i] for i in range(len(gxr)) if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))]
g_mag = [g_magr[i] for i in range(len(gxr)) if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))]
g_ierr = [g_ierrr[i] for i in range(len(gxr)) if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))]
ix = [ixr[i] for i in range(len(gxr)) if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))]
iy = [iyr[i] for i in range(len(gxr)) if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))]
i_mag = [i_magr[i] for i in range(len(gxr)) if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))]
i_ierr = np.array([i_ierrr[i] for i in range(len(gxr)) if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))])
gmi = [gmir[i] for i in range(len(gxr)) if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))]
fwhm_s = [fwhm_sr[i] for i in range(len(gxr)) if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))]
gmi_err = np.array([np.sqrt(g_ierrr[i]**2 + i_ierrr[i]**2) for i in range(len(gxr)) if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))])
i_ierrAVG, bedges, binid = ss.binned_statistic(i_mag,i_ierr,statistic='median',bins=10,range=[15,25])
gmi_errAVG, bedges, binid = ss.binned_statistic(i_mag,gmi_err,statistic='median',bins=10,range=[15,25])
bcenters = (bedges[:-1] + bedges[1:]) / 2
bxvals = [3.75,3.75,3.75,3.75,3.75,3.75,3.75,3.75,3.75,3.75]
# print bcenters
# print i_ierrAVG
# print gmi_errAVG
# print len(gx), "after color+mag error cut"
# nid = np.loadtxt(mag_file,usecols=(0,),dtype=int,unpack=True)
pixcrd = zip(ix,iy)
# print "Reading WCS info from image header..."
# Parse the WCS keywords in the primary HDU
warnings.filterwarnings('ignore', category=UserWarning, append=True)
w = wcs.WCS(fits_i[0].header)
# print fits_i[0].header['naxis1'], fits_i[0].header['naxis2']
footprint = w.calc_footprint()
se_corner = footprint[0]
ne_corner = footprint[1]
nw_corner = footprint[2]
sw_corner = footprint[3]
# print se_corner, ne_corner, nw_corner, sw_corner
width = (ne_corner[0]-nw_corner[0])*60.
height = (ne_corner[1]-se_corner[1])*60.
# print width, height
# Print out the "name" of the WCS, as defined in the FITS header
# print w.wcs.name
# Print out all of the settings that were parsed from the header
# w.wcs.print_contents()
# Convert pixel coordinates to world coordinates
# The second argument is "origin" -- in this case we're declaring we
# have 1-based (Fortran-like) coordinates.
world = w.all_pix2world(pixcrd, 1)
ra_corner, dec_corner = w.all_pix2world(0,0,1)
ra_c_d,dec_c_d = deg2HMS(ra=ra_corner, dec=dec_corner, round=True)
# print 'Corner RA:',ra_c_d,':: Corner Dec:',dec_c_d
fits_i.close()
# split the ra and dec out into individual arrays and transform to arcmin from the corner
i_ra = [abs((world[i,0]-ra_corner)*60) for i in range(len(world[:,0]))]
i_dec = [abs((world[i,1]-dec_corner)*60) for i in range(len(world[:,1]))]
# also preserve the decimal degrees for reference
i_rad = [world[i,0] for i in range(len(world[:,0]))]
i_decd = [world[i,1] for i in range(len(world[:,1]))]
cm_filter, gi_iso, i_m_iso = make_filter(dm, filter_file)
stars_f = filter_sources(i_mag, i_ierr, gmi, gmi_err, cm_filter, filter_sig = 1)
xy_points = zip(i_ra,i_dec)
# make new vectors containing only the filtered points
i_mag_f = [i_mag[i] for i in range(len(i_mag)) if (stars_f[i])]
g_mag_f = [g_mag[i] for i in range(len(i_mag)) if (stars_f[i])]
gmi_f = [gmi[i] for i in range(len(i_mag)) if (stars_f[i])]
i_ra_f = [i_ra[i] for i in range(len(i_mag)) if (stars_f[i])]
i_dec_f = [i_dec[i] for i in range(len(i_mag)) if (stars_f[i])]
i_rad_f = [i_rad[i] for i in range(len(i_mag)) if (stars_f[i])]
i_decd_f = [i_decd[i] for i in range(len(i_mag)) if (stars_f[i])]
i_x_f = [ix[i] for i in range(len(i_mag)) if (stars_f[i])]
i_y_f = [iy[i] for i in range(len(i_mag)) if (stars_f[i])]
fwhm_sf = [fwhm_s[i] for i in range(len(i_mag)) if (stars_f[i])]
n_in_filter = len(i_mag_f)
xedges, x_cent, yedges, y_cent, S, x_cent_S, y_cent_S, pltsig, tbl = grid_smooth(i_ra_f, i_dec_f, fwhm_sm, width, height)
# xedges, x_cent, yedges, y_cent, S, x_cent_S, y_cent_S, pltsig, tbl = grid_smooth(i_ra, i_dec, 2.0, width, height)
cosd = lambda x : np.cos(np.deg2rad(x))
sind = lambda x : np.sin(np.deg2rad(x))
hi_x_circ, hi_y_circ = getHIellipse(obj, ra_corner, dec_corner)
# hi_c_x, hi_c_y = abs((hi_c_ra-ra_corner)*60), abs((hi_c_dec-dec_corner)*60)
#
# t = np.array(range(0,359,1))
# ell = np.array([a*cosd(t) , b*sind(t)])
# rot = np.array([[cosd(pa) , -sind(pa)],[sind(pa) , cosd(pa)]])
# ell_rot = np.zeros((2,ell.shape[1]))
# for i in range(ell.shape[1]):
# ell_rot[:,i] = np.dot(rot,ell[:,i])
# hi_x_circ, hi_y_circ = hi_c_x+ell_rot[0,:], hi_c_y+ell_rot[1,:]
# hi_x_circ = [hi_c_x + a*cosd(t) for t in range(0,359,1)]
# hi_y_circ = [hi_c_y + b*sind(t) for t in range(0,359,1)]
x_circ = [yedges[y_cent] + 3.0*cosd(t) for t in range(0,359,1)]
y_circ = [xedges[x_cent] + 3.0*sind(t) for t in range(0,359,1)]
ax1 = plt.Subplot(fig, inner[0])
if os.path.isfile(folder+'i_gmi_compl.gr.out'):
gmiCompl, iCompl = np.loadtxt(folder+'i_gmi_compl.gr.out',usecols=(0,1),unpack=True)
ax1.plot(gmiCompl,iCompl, linestyle='--', color='green')
# if os.path.isfile(folder+'i_gmi_compl.gr2.out'):
# gmiCompl, iCompl = np.loadtxt(folder+'i_gmi_compl.gr2.out',usecols=(0,1),unpack=True)
# ax1.plot(gmiCompl,iCompl, linestyle='--', color='red')
# if os.path.isfile(folder+'i_gmi_compl2.out'):
# iCompl,gmiCompl = np.loadtxt(folder+'i_gmi_compl2.out',usecols=(0,1),unpack=True)
# ax1.plot(gmiCompl,iCompl, linestyle='--', color='blue')
ax1.plot(gi_iso,i_m_iso,linestyle='-', color='blue')
ax1.scatter(gmi, i_mag, color='black', marker='o', s=1, edgecolors='none')
ax1.scatter(gmi_f, i_mag_f, color='red', marker='o', s=15, edgecolors='none')
ax1.errorbar(bxvals, bcenters, xerr=i_ierrAVG, yerr=gmi_errAVG, linestyle='None', color='black', capsize=0, ms=0)
ax1.tick_params(axis='y',left='on',right='off',labelleft='on',labelright='off')
ax1.yaxis.set_label_position('left')
ax1.set_xticks([-1,0,1,2,3,4])
ax1.set_yticks([15, 17, 19, 21, 23, 25])
ax1.set_ylabel('$i_0$')
ax1.set_xlabel('$(g-i)_0$')
ax1.set_ylim(25,15)
ax1.set_xlim(-1,4)
ax1.set_aspect(0.5)
ax1.set_title('$m-M = ${:5.2f}'.format(dm), size='small')
fig.add_subplot(ax1)
ax2 = plt.Subplot(fig, inner[1])
extent = [yedges[0], yedges[-1], xedges[-1], xedges[0]]
ax2.imshow(S, extent=extent, interpolation='nearest',cmap=cm.gray)
# cbar_S = plt.colorbar()
# cbar_S.set_label('$\sigma$ from local mean')
ax2.plot(hi_x_circ,hi_y_circ,linestyle='-', color='limegreen')
ax2.plot(x_circ,y_circ,linestyle='-', color='magenta')
ax2.tick_params(axis='y',left='off',right='on',labelleft='off',labelright='on')
ax2.yaxis.set_label_position('right')
ax2.set_xticks([0,5,10,15,20])
ax2.set_yticks([0,5,10,15,20])
ax2.set_xlabel('RA (arcmin)')
ax2.set_ylabel('Dec (arcmin)')
# if obj.startswith('HI1151'):
# ax2.set_title('AGC219656', size='small')
# else:
ax2.set_title(obj, size='small')
ax2.set_xlim(0,max(i_ra))
ax2.set_ylim(0,max(i_dec))
ax2.set_aspect('equal')
fig.add_subplot(ax2)
outer.tight_layout(fig)
plt.savefig('detections_close_{:3.1f}.pdf'.format(fwhm_sm))
pass
def main():
objects = OrderedDict([('new', 22.89), ('old', 22.89)])
smooths = OrderedDict([('new', 2.0), ('old', 2.0)])
filter_file = os.path.dirname(os.path.abspath(__file__)) + '/filter.txt'
# plt.clf()
fig = plt.figure(figsize=(4, 4))
outer = gridspec.GridSpec(2, 1, wspace=0.1, hspace=0.1)
for i, obj in enumerate(objects.keys()):
inner = gridspec.GridSpecFromSubplotSpec(1,
2,
subplot_spec=outer[i],
wspace=0.1,
hspace=0.1)
# set up some filenames
if i == 0:
folder = '/Volumes/galileo/uchvc/targets/agc198606/'
if i == 1:
folder = '/Volumes/galileo/uchvc/targets/agc198606_correct_old/'
mag_file = folder + 'calibrated_mags.dat'
fits_file_i = folder + 'AGC198606_i.fits'
fits_i = fits.open(fits_file_i)
dm = objects[obj]
mpc = pow(10, ((dm + 5.) / 5.)) / 1000000.
# read in magnitudes, colors, and positions(x,y)
# gxr,gyr,g_magr,g_ierrr,ixr,iyr,i_magr,i_ierrr,gmir,fwhm_sr= np.loadtxt(mag_file,usecols=(0,1,2,3,4,5,6,7,8,11),unpack=True)
gxr, gyr, g_magr, g_ierrr, ixr, iyr, i_magr, i_ierrr, gmir = np.loadtxt(
mag_file, usecols=(0, 1, 2, 3, 4, 5, 6, 7, 8), unpack=True)
print len(gxr), "total stars"
fwhm_sr = np.ones_like(gxr)
# filter out the things with crappy color errors
color_error_cut = np.sqrt(2.0) * 0.2
mag_error_cut = 0.2
gmi_errr = [
np.sqrt(g_ierrr[i]**2 + i_ierrr[i]**2) for i in range(len(gxr))
]
gx = [
gxr[i] for i in range(len(gxr)) if (abs(
gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
]
gy = [
gyr[i] for i in range(len(gxr)) if (abs(
gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
]
g_mag = [
g_magr[i] for i in range(len(gxr)) if (abs(
gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
]
g_ierr = [
g_ierrr[i] for i in range(len(gxr)) if (abs(
gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
]
ix = [
ixr[i] for i in range(len(gxr)) if (abs(
gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
]
iy = [
iyr[i] for i in range(len(gxr)) if (abs(
gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
]
i_mag = [
i_magr[i] for i in range(len(gxr)) if (abs(
gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
]
i_ierr = np.array([
i_ierrr[i] for i in range(len(gxr)) if (abs(
gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
])
gmi = [
gmir[i] for i in range(len(gxr)) if (abs(
gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
]
fwhm_s = [
fwhm_sr[i] for i in range(len(gxr)) if (abs(
gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
]
kept_stars = [
i for i in range(len(gxr)) if (abs(gmi_errr[i] < color_error_cut
and i_ierrr[i] < mag_error_cut))
]
gmi_err = np.array([
np.sqrt(g_ierrr[i]**2 + i_ierrr[i]**2) for i in range(len(gxr)) if
(abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
])
i_ierrAVG, bedges, binid = ss.binned_statistic(i_mag,
i_ierr,
statistic='median',
bins=10,
range=[15, 25])
gmi_errAVG, bedges, binid = ss.binned_statistic(i_mag,
gmi_err,
statistic='median',
bins=10,
range=[15, 25])
bcenters = (bedges[:-1] + bedges[1:]) / 2
bxvals = [3.75, 3.75, 3.75, 3.75, 3.75, 3.75, 3.75, 3.75, 3.75, 3.75]
# print bcenters
# print i_ierrAVG
# print gmi_errAVG
# print len(gx), "after color+mag error cut"
# nid = np.loadtxt(mag_file,usecols=(0,),dtype=int,unpack=True)
pixcrd = zip(ix, iy)
# print "Reading WCS info from image header..."
# Parse the WCS keywords in the primary HDU
warnings.filterwarnings('ignore', category=UserWarning, append=True)
w = wcs.WCS(fits_i[0].header)
# print fits_i[0].header['naxis1'], fits_i[0].header['naxis2']
footprint = w.calc_footprint()
se_corner = footprint[0]
ne_corner = footprint[1]
nw_corner = footprint[2]
sw_corner = footprint[3]
# print se_corner, ne_corner, nw_corner, sw_corner
width = (ne_corner[0] - nw_corner[0]) * 60.
height = (ne_corner[1] - se_corner[1]) * 60.
# print width, height
# Print out the "name" of the WCS, as defined in the FITS header
# print w.wcs.name
# Print out all of the settings that were parsed from the header
# w.wcs.print_contents()
# Convert pixel coordinates to world coordinates
# The second argument is "origin" -- in this case we're declaring we
# have 1-based (Fortran-like) coordinates.
world = w.all_pix2world(pixcrd, 1)
ra_corner, dec_corner = w.all_pix2world(0, 0, 1)
ra_c_d, dec_c_d = deg2HMS(ra=ra_corner, dec=dec_corner, round=True)
# print 'Corner RA:',ra_c_d,':: Corner Dec:',dec_c_d
fits_i.close()
# split the ra and dec out into individual arrays and transform to arcmin from the corner
i_ra = [
abs((world[i, 0] - ra_corner) * 60)
for i in range(len(world[:, 0]))
]
i_dec = [
abs((world[i, 1] - dec_corner) * 60)
for i in range(len(world[:, 1]))
]
# also preserve the decimal degrees for reference
i_rad = [world[i, 0] for i in range(len(world[:, 0]))]
i_decd = [world[i, 1] for i in range(len(world[:, 1]))]
cm_filter, gi_iso, i_m_iso = make_filter(dm, filter_file)
stars_f = filter_sources(i_mag,
i_ierr,
gmi,
gmi_err,
cm_filter,
filter_sig=1)
xy_points = zip(i_ra, i_dec)
# make new vectors containing only the filtered points
i_mag_f = [i_mag[i] for i in range(len(i_mag)) if (stars_f[i])]
g_mag_f = [g_mag[i] for i in range(len(i_mag)) if (stars_f[i])]
gmi_f = [gmi[i] for i in range(len(i_mag)) if (stars_f[i])]
i_ra_f = [i_ra[i] for i in range(len(i_mag)) if (stars_f[i])]
i_dec_f = [i_dec[i] for i in range(len(i_mag)) if (stars_f[i])]
i_rad_f = [i_rad[i] for i in range(len(i_mag)) if (stars_f[i])]
i_decd_f = [i_decd[i] for i in range(len(i_mag)) if (stars_f[i])]
i_x_f = [ix[i] for i in range(len(i_mag)) if (stars_f[i])]
i_y_f = [iy[i] for i in range(len(i_mag)) if (stars_f[i])]
fwhm_sf = [fwhm_s[i] for i in range(len(i_mag)) if (stars_f[i])]
filtered = [i for i in range(len(i_mag)) if (stars_f[i])]
# print filtered
n_in_filter = len(i_mag_f)
if 'new' in obj:
kept1 = kept_stars
filtered1 = np.array(filtered)
i_ra1 = np.array(i_ra)
i_dec1 = np.array(i_dec)
xmin1, ymin1 = np.absolute(
w.all_world2pix((8.2 / 60) + ra_corner,
(8.1 / 60) + dec_corner, 1))
xmax1, ymax1 = np.absolute(
w.all_world2pix((14.2 / 60) + ra_corner,
(14.1 / 60) + dec_corner, 1))
# print xmin1, xmax1, ymin1, ymax1
if 'old' in obj:
kept2 = kept_stars
filtered2 = np.array(filtered)
i_ra2 = np.array(i_ra)
i_dec2 = np.array(i_dec)
xmin2, ymin2 = np.absolute(
w.all_world2pix((8.2 / 60) + ra_corner,
(8.1 / 60) + dec_corner, 1))
xmax2, ymax2 = np.absolute(
w.all_world2pix((14.2 / 60) + ra_corner,
(14.1 / 60) + dec_corner, 1))
# print xmin2, xmax2, ymin2, ymax2
fwhm = smooths[obj]
xedges, x_cent, yedges, y_cent, S, x_cent_S, y_cent_S, pltsig, tbl = grid_smooth(
i_ra_f, i_dec_f, fwhm, width, height)
print yedges[y_cent], xedges[x_cent]
# xedges, x_cent, yedges, y_cent, S, x_cent_S, y_cent_S, pltsig, tbl = grid_smooth(i_ra, i_dec, 2.0, width, height)
cosd = lambda x: np.cos(np.deg2rad(x))
sind = lambda x: np.sin(np.deg2rad(x))
hi_x_circ, hi_y_circ = getHIellipse('AGC198606', ra_corner, dec_corner)
# hi_c_x, hi_c_y = abs((hi_c_ra-ra_corner)*60), abs((hi_c_dec-dec_corner)*60)
#
# t = np.array(range(0,359,1))
# ell = np.array([a*cosd(t) , b*sind(t)])
# rot = np.array([[cosd(pa) , -sind(pa)],[sind(pa) , cosd(pa)]])
# ell_rot = np.zeros((2,ell.shape[1]))
# for i in range(ell.shape[1]):
# ell_rot[:,i] = np.dot(rot,ell[:,i])
# hi_x_circ, hi_y_circ = hi_c_x+ell_rot[0,:], hi_c_y+ell_rot[1,:]
# hi_x_circ = [hi_c_x + a*cosd(t) for t in range(0,359,1)]
# hi_y_circ = [hi_c_y + b*sind(t) for t in range(0,359,1)]
x_circ = [yedges[y_cent] + 3.0 * cosd(t) for t in range(0, 359, 1)]
y_circ = [xedges[x_cent] + 3.0 * sind(t) for t in range(0, 359, 1)]
ax1 = plt.Subplot(fig, inner[0])
if os.path.isfile(folder + 'i_gmi_compl.gr.out'):
gmiCompl, iCompl = np.loadtxt(folder + 'i_gmi_compl.gr.out',
usecols=(0, 1),
unpack=True)
ax1.plot(gmiCompl, iCompl, linestyle='--', color='green')
# if os.path.isfile(folder+'i_gmi_compl.gr2.out'):
# gmiCompl, iCompl = np.loadtxt(folder+'i_gmi_compl.gr2.out',usecols=(0,1),unpack=True)
# ax1.plot(gmiCompl,iCompl, linestyle='--', color='red')
# if os.path.isfile(folder+'i_gmi_compl2.out'):
# iCompl,gmiCompl = np.loadtxt(folder+'i_gmi_compl2.out',usecols=(0,1),unpack=True)
# ax1.plot(gmiCompl,iCompl, linestyle='--', color='blue')
ax1.plot(gi_iso, i_m_iso, linestyle='-', color='blue')
ax1.scatter(gmi,
i_mag,
color='black',
marker='o',
s=1,
edgecolors='none')
ax1.scatter(gmi_f,
i_mag_f,
color='red',
marker='o',
s=15,
edgecolors='none')
ax1.errorbar(bxvals,
bcenters,
xerr=i_ierrAVG,
yerr=gmi_errAVG,
linestyle='None',
color='black',
capsize=0,
ms=0)
ax1.tick_params(axis='y',
left='on',
right='off',
labelleft='on',
labelright='off')
ax1.yaxis.set_label_position('left')
ax1.set_xticks([-1, 0, 1, 2, 3, 4])
ax1.set_yticks([15, 17, 19, 21, 23, 25])
ax1.set_ylabel('$i_0$')
ax1.set_xlabel('$(g-i)_0$')
ax1.set_ylim(25, 15)
ax1.set_xlim(-1, 4)
ax1.set_aspect(0.5)
ax1.set_title('$m-M = ${:5.2f} | $d = ${:4.2f} Mpc'.format(dm, mpc),
size='small')
fig.add_subplot(ax1)
ax2 = plt.Subplot(fig, inner[1])
extent = [yedges[0], yedges[-1], xedges[-1], xedges[0]]
im = ax2.imshow(S, extent=extent, interpolation='none', cmap=cm.gray)
ax2.scatter(i_ra,
i_dec,
color='black',
marker='o',
s=1,
edgecolors='none')
ax2.scatter(i_ra_f,
i_dec_f,
c='red',
marker='o',
s=10,
edgecolors='none')
# cbar_S = plt.colorbar()
# cbar_S.set_label('$\sigma$ from local mean')
ax2.plot(hi_x_circ, hi_y_circ, linestyle='-', color='limegreen')
ax2.plot(x_circ, y_circ, linestyle='-', color='magenta')
ax2.tick_params(axis='y',
left='off',
right='on',
labelleft='off',
labelright='on')
ax2.yaxis.set_label_position('right')
ax2.set_xticks([0, 5, 10, 15, 20])
ax2.set_yticks([0, 5, 10, 15, 20])
ax2.set_xlabel('RA (arcmin)')
ax2.set_ylabel('Dec (arcmin)')
if obj.startswith('HI1151'):
ax2.set_title('AGC219656', size='small')
else:
ax2.set_title(obj, size='small')
ax2.set_xlim(8.2, 14.2)
ax2.set_ylim(8.1, 14.1)
# im.set_clim(-3, 3)
ax2.set_aspect('equal')
fig.add_subplot(ax2)
outer.tight_layout(fig)
plt.savefig('friend_comp.pdf')
x1, y1, mag2x1, fwhm1, mag1x1 = np.loadtxt(
'/Volumes/galileo/uchvc/targets/agc198606/escut_i.pos',
usecols=(0, 1, 2, 3, 4),
unpack=True)
x1, y1, mag2x1, fwhm1 = x1[kept1], y1[kept1], mag2x1[kept1], fwhm1[kept1]
box1 = [
j for j, f in enumerate(x1)
if (x1[j] > xmin1 and x1[j] < xmax1 and y1[j] > ymin1 and y1[j] < ymax1
)
]
keep1 = [
j for j, f in enumerate(x1)
if (j in filtered1 and x1[j] > xmin1 and x1[j] < xmax1
and y1[j] > ymin1 and y1[j] < ymax1)
]
# mag2x1 = mag2x1[keep1]
# fwhm1 = fwhm1[keep1]
x2, y2, mag2x2, fwhm2, fi = np.loadtxt(
'/Volumes/galileo/uchvc/targets/agc198606_correct_old/point_source_info',
usecols=(0, 1, 4, 8, 10),
dtype=str,
unpack=True)
istars = [j for j, f in enumerate(fi) if (f.endswith('i'))]
x2, y2, mag2x2, fwhm2 = x2[istars].astype(float), y2[istars].astype(
float), mag2x2[istars].astype(float), fwhm2[istars].astype(float)
x2, y2, mag2x2, fwhm2 = x2[kept2], y2[kept2], mag2x2[kept2], fwhm2[kept2]
box2 = [
j for j, f in enumerate(x2)
if (x2[j] > xmin2 and x2[j] < xmax2 and y2[j] > ymin2 and y2[j] < ymax2
)
]
keep2 = [
j for j, f in enumerate(x2)
if (j in filtered2 and x2[j] > xmin2 and x2[j] < xmax2
and y2[j] > ymin2 and y2[j] < ymax2)
]
# mag2x2 = mag2x2[keep2]
# fwhm2 = fwhm2[keep2]
fig2 = plt.figure(figsize=(8, 4))
ax3 = plt.subplot(121)
ax3.scatter(i_ra1,
i_dec1,
c='none',
marker='o',
s=20,
lw=0.5,
edgecolors='black')
ax3.scatter(i_ra2,
i_dec2,
c='black',
marker='x',
s=10,
lw=0.5,
edgecolors='none')
ax3.scatter(i_ra1[filtered1],
i_dec1[filtered1],
c='none',
marker='o',
s=20,
lw=1.0,
edgecolors='red',
label='this work')
ax3.scatter(i_ra2[filtered2],
i_dec2[filtered2],
c='blue',
marker='x',
s=10,
lw=1.0,
edgecolors='none',
label='J15')
ax3.set_xlim(8.2, 14.2)
ax3.set_ylim(8.1, 14.1)
ax3.set_ylabel('Dec (arcmin)')
ax3.set_xlabel('RA (arcmin)')
ax1.set_title('$m-M = ${:5.2f} | $d = ${:4.2f} Mpc'.format(22.89, 0.38),
size='small')
ax3.set_aspect('equal')
plt.legend(loc='upper left')
# plt.savefig('star_overlap.pdf')
# fig3 = plt.figure(figsize=(6,3))
ax4 = plt.subplot(122)
ax4.scatter(mag2x1[box1],
fwhm1[box1],
c='none',
marker='o',
s=20,
lw=0.5,
edgecolors='black')
ax4.scatter(mag2x2[box2],
fwhm2[box2],
c='black',
marker='x',
s=10,
lw=0.5,
edgecolors='none')
ax4.scatter(mag2x1[keep1],
fwhm1[keep1],
c='none',
marker='o',
s=20,
lw=1.0,
edgecolors='red')
ax4.scatter(mag2x2[keep2],
fwhm2[keep2],
c='blue',
marker='x',
s=10,
lw=1.0,
edgecolors='none')
ax4.set_xlim(-11, 1)
ax4.set_ylim(0, 14)
ax4.set_ylabel('FWHM (pixels)')
ax4.set_xlabel('inst. mag')
plt.tight_layout()
plt.savefig('escut_comp.pdf')
pass
def main():
objects = OrderedDict([('AGC198511', 22.91), ('AGC198606', 24.72),
('AGC215417', 22.69), ('HI1151+20', 24.76),
('AGC249525', 26.78), ('AGC268069', 24.24)])
smooths = OrderedDict([('AGC198511', 3.0), ('AGC198606', 2.0),
('AGC215417', 3.0), ('HI1151+20', 2.0),
('AGC249525', 3.0), ('AGC268069', 3.0)])
filter_file = os.path.dirname(os.path.abspath(__file__)) + '/filter.txt'
for file_ in os.listdir("./"):
if file_.endswith("i.fits"):
fits_file_i = file_
for file_ in os.listdir("./"):
if file_.endswith("g.fits"):
fits_file_g = file_
# downloadSDSSgal(fits_file_g, fits_file_i)
fits_i = fits.open(fits_file_i)
# fits_g = fits.open(fits_file_g)
# print "Opened fits files:",fits_file_g,"&",fits_file_i
# objid = fits_i[0].header['OBJECT']
title_string = fits_file_i.split('_')[
0] # get the name part of the filename.
# set up some filenames
mag_file = 'calibrated_mags.dat'
# read in magnitudes, colors, and positions(x,y)
# gxr,gyr,g_magr,g_ierrr,ixr,iyr,i_magr,i_ierrr,gmir,fwhm_sr= np.loadtxt(mag_file,usecols=(0,1,2,3,4,5,6,7,8,11),unpack=True)
gxr, gyr, g_magr, g_ierrr, ixr, iyr, i_magr, i_ierrr, gmir = np.loadtxt(
mag_file, usecols=(0, 1, 2, 3, 4, 5, 6, 7, 8), unpack=True)
# print len(gxr), "total stars"
fwhm_sr = np.ones_like(gxr)
# filter out the things with crappy color errors
color_error_cut = np.sqrt(2.0) * 0.2
mag_error_cut = 0.2
gmi_errr = [
np.sqrt(g_ierrr[i]**2 + i_ierrr[i]**2) for i in range(len(gxr))
]
gx = [
gxr[i] for i in range(len(gxr))
if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
]
gy = [
gyr[i] for i in range(len(gxr))
if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
]
g_mag = [
g_magr[i] for i in range(len(gxr))
if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
]
g_ierr = [
g_ierrr[i] for i in range(len(gxr))
if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
]
ix = [
ixr[i] for i in range(len(gxr))
if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
]
iy = [
iyr[i] for i in range(len(gxr))
if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
]
i_mag = [
i_magr[i] for i in range(len(gxr))
if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
]
i_ierr = np.array([
i_ierrr[i] for i in range(len(gxr))
if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
])
gmi = [
gmir[i] for i in range(len(gxr))
if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
]
fwhm_s = [
fwhm_sr[i] for i in range(len(gxr))
if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
]
gmi_err = np.array([
np.sqrt(g_ierrr[i]**2 + i_ierrr[i]**2) for i in range(len(gxr))
if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
])
cutleft = [
i for i in range(len(gxr))
if (abs(gmi_errr[i] < color_error_cut and i_ierrr[i] < mag_error_cut))
]
with open('cutleft.txt', 'w+') as spud:
for i, item in enumerate(cutleft):
print(item, file=spud)
i_ierrAVG, bedges, binid = ss.binned_statistic(i_mag,
i_ierr,
statistic='median',
bins=10,
range=[15, 25])
gmi_errAVG, bedges, binid = ss.binned_statistic(i_mag,
gmi_err,
statistic='median',
bins=10,
range=[15, 25])
bcenters = (bedges[:-1] + bedges[1:]) / 2
bxvals = [3.75, 3.75, 3.75, 3.75, 3.75, 3.75, 3.75, 3.75, 3.75, 3.75]
# print bcenters
# print i_ierrAVG
# print gmi_errAVG
# print len(gx), "after color+mag error cut"
# nid = np.loadtxt(mag_file,usecols=(0,),dtype=int,unpack=True)
pixcrd = list(zip(ix, iy))
# print "Reading WCS info from image header..."
# Parse the WCS keywords in the primary HDU
warnings.filterwarnings('ignore', category=UserWarning, append=True)
w = wcs.WCS(fits_i[0].header)
# print fits_i[0].header['naxis1'], fits_i[0].header['naxis2']
footprint = w.calc_footprint()
se_corner = footprint[0]
ne_corner = footprint[1]
nw_corner = footprint[2]
sw_corner = footprint[3]
# print se_corner, ne_corner, nw_corner, sw_corner
width = (ne_corner[0] - nw_corner[0]) * 60.
height = (ne_corner[1] - se_corner[1]) * 60.
# print width, height
# Print out the "name" of the WCS, as defined in the FITS header
# print w.wcs.name
# Print out all of the settings that were parsed from the header
# w.wcs.print_contents()
# Convert pixel coordinates to world coordinates
# The second argument is "origin" -- in this case we're declaring we
# have 1-based (Fortran-like) coordinates.
world = w.all_pix2world(pixcrd, 1)
ra_corner, dec_corner = w.all_pix2world(0, 0, 1)
ra_c_d, dec_c_d = deg2HMS(ra=ra_corner, dec=dec_corner, round=True)
# print 'Corner RA:',ra_c_d,':: Corner Dec:',dec_c_d
fwhm_i = 12.0 #fits_i[0].header['FWHMPSF']
fwhm_g = 9.0 # fits_g[0].header['FWHMPSF']
# print 'Image FWHM :: g = {0:5.3f} : i = {1:5.3f}'.format(fwhm_g,fwhm_i)
fits_i.close()
# fits_g.close()
# split the ra and dec out into individual arrays and transform to arcmin from the corner
i_ra = [
abs((world[i, 0] - ra_corner) * 60) for i in range(len(world[:, 0]))
]
i_dec = [
abs((world[i, 1] - dec_corner) * 60) for i in range(len(world[:, 1]))
]
# also preserve the decimal degrees for reference
i_rad = [world[i, 0] for i in range(len(world[:, 0]))]
i_decd = [world[i, 1] for i in range(len(world[:, 1]))]
i_magBright = [i_mag[i] for i in range(len(i_mag)) if (i_mag[i] < 22.75)]
g_magBright = [g_mag[i] for i in range(len(i_mag)) if (i_mag[i] < 22.75)]
ixBright = [ix[i] for i in range(len(i_mag)) if (i_mag[i] < 22.75)]
iyBright = [iy[i] for i in range(len(i_mag)) if (i_mag[i] < 22.75)]
i_radBright = [i_rad[i] for i in range(len(i_mag)) if (i_mag[i] < 22.75)]
i_decdBright = [i_decd[i] for i in range(len(i_mag)) if (i_mag[i] < 22.75)]
if not os.path.isfile('brightStars2275.reg'):
f1 = open('brightStars2275.reg', 'w+')
for i in range(len(i_magBright)):
print(
'{0:12.4f} {1:12.4f} {2:10.5f} {3:9.5f} {4:8.2f} {5:8.2f} {6:8.2f}'
.format(ixBright[i], iyBright[i], i_radBright[i],
i_decdBright[i], g_magBright[i], i_magBright[i],
g_magBright[i] - i_magBright[i]),
file=f1)
f1.close()
i_magRed = [i_mag[i] for i in range(len(i_mag)) if (gmi[i] > 1.75)]
g_magRed = [g_mag[i] for i in range(len(i_mag)) if (gmi[i] > 1.75)]
ixRed = [ix[i] for i in range(len(i_mag)) if (gmi[i] > 1.75)]
iyRed = [iy[i] for i in range(len(i_mag)) if (gmi[i] > 1.75)]
i_radRed = [i_rad[i] for i in range(len(i_mag)) if (gmi[i] > 1.75)]
i_decdRed = [i_decd[i] for i in range(len(i_mag)) if (gmi[i] > 1.75)]
if not os.path.isfile('redStars175.reg'):
f1 = open('redStars175.reg', 'w+')
for i in range(len(i_magRed)):
print(
'{0:12.4f} {1:12.4f} {2:10.5f} {3:9.5f} {4:8.2f} {5:8.2f} {6:8.2f}'
.format(ixRed[i], iyRed[i], i_radRed[i], i_decdRed[i],
g_magRed[i], i_magRed[i], g_magRed[i] - i_magRed[i]),
file=f1)
f1.close()
dm = 22.0
dm2 = 27.0
fwhm = 2.0
# if dm2 > 0.0 and filter_string != 'none':
dms = np.arange(dm, dm2, 0.01)
# search = open('search_{:3.1f}.txt'.format(fwhm),'w+')
# else:
# dms = [dm]
# search = open('spud.txt'.format(fwhm),'w+')
# sig_bins = []
# sig_cens = []
# sig_max = []
for dm in dms:
mpc = pow(10, ((dm + 5.) / 5.)) / 1000000.
dm_string = '{:5.2f}'.format(dm).replace('.', '_')
out_file = 'anim/anim_' + dm_string + '_' + title_string + '.png'
# mark_file = 'f_list_' + filter_string + '_' + fwhm_string + '_' + dm_string + '_' + title_string + '.reg'
# filter_reg = 'f_reg_' + filter_string + '_' + fwhm_string + '_' + dm_string + '_' + title_string + '.reg'
# circ_file = 'c_list_' + filter_string + '_' + fwhm_string + '_' + dm_string + '_' + title_string + '.reg'
# fcirc_file = 'fc_list_' + filter_string + '_' + fwhm_string + '_' + dm_string + '_' + title_string + '.reg'
# ds9_file = 'circles_' + filter_string + '_' + fwhm_string + '_' + dm_string + '_' + title_string + '.reg'
circles_file = 'region_coords.dat'
cm_filter, gi_iso, i_m_iso = make_filter(dm, filter_file)
stars_f = filter_sources(i_mag,
i_ierr,
gmi,
gmi_err,
cm_filter,
filter_sig=1)
xy_points = list(zip(i_ra, i_dec))
# make new vectors containing only the filtered points
i_mag_f = [i_mag[i] for i in range(len(i_mag)) if (stars_f[i])]
g_mag_f = [g_mag[i] for i in range(len(i_mag)) if (stars_f[i])]
gmi_f = [gmi[i] for i in range(len(i_mag)) if (stars_f[i])]
i_ra_f = [i_ra[i] for i in range(len(i_mag)) if (stars_f[i])]
i_dec_f = [i_dec[i] for i in range(len(i_mag)) if (stars_f[i])]
i_rad_f = [i_rad[i] for i in range(len(i_mag)) if (stars_f[i])]
i_decd_f = [i_decd[i] for i in range(len(i_mag)) if (stars_f[i])]
i_x_f = [ix[i] for i in range(len(i_mag)) if (stars_f[i])]
i_y_f = [iy[i] for i in range(len(i_mag)) if (stars_f[i])]
fwhm_sf = [fwhm_s[i] for i in range(len(i_mag)) if (stars_f[i])]
n_in_filter = len(i_mag_f)
# xedgesg, x_centg, yedgesg, y_centg, Sg, x_cent_Sg, y_cent_Sg, pltsigg, tblg = galaxyMap(fits_file_i, fwhm, dm, filter_file)
xedges, x_cent, yedges, y_cent, S, x_cent_S, y_cent_S, pltsig, tbl = grid_smooth(
i_ra_f, i_dec_f, fwhm, width, height)
# corr = signal.correlate2d(S, Sg, boundary='fill', mode='full')
# print corr
# pct, d_bins, d_cens = distfit(n_in_filter,S[x_cent_S][y_cent_S],title_string,width,height,fwhm,dm)
# pct_hi = 0.0 #getHIcoincidence(x_cent_S, y_cent_S, title_string, ra_corner, dec_corner, width, height, dm)
# sig_bins.append(d_bins)
# sig_cens.append(d_cens)
# sig_max.append(S[x_cent_S][y_cent_S])
# if pct > 90 :
# pct, bj,cj = distfit(n_in_filter,S[x_cent_S][y_cent_S],title_string,width,height,fwhm,dm, samples=25000)
# make a circle to highlight a certain region
cosd = lambda x: np.cos(np.deg2rad(x))
sind = lambda x: np.sin(np.deg2rad(x))
x_circ = [yedges[y_cent] + 3.0 * cosd(t) for t in range(0, 359, 1)]
y_circ = [xedges[x_cent] + 3.0 * sind(t) for t in range(0, 359, 1)]
verts_circ = list(zip(x_circ, y_circ))
circ_filter = Path(verts_circ)
stars_circ = circ_filter.contains_points(xy_points)
i_mag_c = [i_mag[i] for i in range(len(i_mag)) if (stars_circ[i])]
gmi_c = [gmi[i] for i in range(len(i_mag)) if (stars_circ[i])]
i_ra_c = [i_ra[i] for i in range(len(i_mag)) if (stars_circ[i])]
i_dec_c = [i_dec[i] for i in range(len(i_mag)) if (stars_circ[i])]
i_rad_c = [i_rad[i] for i in range(len(i_mag)) if (stars_circ[i])]
i_decd_c = [i_decd[i] for i in range(len(i_mag)) if (stars_circ[i])]
i_x_c = [ix[i] for i in range(len(i_mag)) if (stars_circ[i])]
i_y_c = [iy[i] for i in range(len(i_mag)) if (stars_circ[i])]
fwhm_sc = [fwhm_s[i] for i in range(len(i_mag)) if (stars_circ[i])]
# make a random reference cmd to compare to
if not os.path.isfile('refCircle.center'):
rCentx = 16.0 * np.random.random() + 2.0
rCenty = 16.0 * np.random.random() + 2.0
with open('refCircle.center', 'w+') as rc:
print('{:8.4f} {:8.4f}'.format(rCentx, rCenty), file=rc)
else:
rCentx, rCenty = np.loadtxt('refCircle.center',
usecols=(0, 1),
unpack=True)
x_circr = [rCentx + 3.0 * cosd(t) for t in range(0, 359, 1)]
y_circr = [rCenty + 3.0 * sind(t) for t in range(0, 359, 1)]
verts_circr = list(zip(x_circr, y_circr))
rcirc_filter = Path(verts_circr)
stars_circr = rcirc_filter.contains_points(xy_points)
i_mag_cr = [i_mag[i] for i in range(len(i_mag)) if (stars_circr[i])]
gmi_cr = [gmi[i] for i in range(len(i_mag)) if (stars_circr[i])]
i_ra_cr = [i_ra[i] for i in range(len(i_mag)) if (stars_circr[i])]
i_dec_cr = [i_dec[i] for i in range(len(i_mag)) if (stars_circr[i])]
i_rad_cr = [i_rad[i] for i in range(len(i_mag)) if (stars_circr[i])]
i_decd_cr = [i_decd[i] for i in range(len(i_mag)) if (stars_circr[i])]
i_x_cr = [ix[i] for i in range(len(i_mag)) if (stars_circr[i])]
i_y_cr = [iy[i] for i in range(len(i_mag)) if (stars_circr[i])]
fwhm_scr = [fwhm_s[i] for i in range(len(i_mag)) if (stars_circr[i])]
i_mag_fc = [
i_mag[i] for i in range(len(i_mag))
if (stars_circ[i] and stars_f[i])
]
i_ierr_fc = [
i_ierr[i] for i in range(len(i_mag))
if (stars_circ[i] and stars_f[i])
]
g_ierr_fc = [
g_ierr[i] for i in range(len(i_mag))
if (stars_circ[i] and stars_f[i])
]
g_mag_fc = [
i_mag[i] for i in range(len(i_mag))
if (stars_circ[i] and stars_f[i])
]
gmi_fc = [
gmi[i] for i in range(len(i_mag)) if (stars_circ[i] and stars_f[i])
]
i_ra_fc = [
i_ra[i] for i in range(len(i_mag))
if (stars_circ[i] and stars_f[i])
]
i_dec_fc = [
i_dec[i] for i in range(len(i_mag))
if (stars_circ[i] and stars_f[i])
]
i_rad_fc = [
i_rad[i] for i in range(len(i_mag))
if (stars_circ[i] and stars_f[i])
]
i_decd_fc = [
i_decd[i] for i in range(len(i_mag))
if (stars_circ[i] and stars_f[i])
]
i_x_fc = [
ix[i] for i in range(len(i_mag)) if (stars_circ[i] and stars_f[i])
]
i_y_fc = [
iy[i] for i in range(len(i_mag)) if (stars_circ[i] and stars_f[i])
]
fwhm_sfc = [
fwhm_s[i] for i in range(len(i_mag))
if (stars_circ[i] and stars_f[i])
]
index_fc = [
i for i in range(len(i_mag)) if (stars_circ[i] and stars_f[i])
]
# with open('index_fc.txt', 'w+') as spud1:
# for i,item in enumerate(index_fc):
# print >> spud1, item
# print len(i_mag_fc), 'filter stars in circle'
# print 'max i mag in circle = ', min(i_mag_fc)
rs = np.array([51, 77, 90, 180])
for r in rs:
x_circ = [
yedges[y_cent] + r / 60. * cosd(t) for t in range(0, 359, 1)
]
y_circ = [
xedges[x_cent] + r / 60. * sind(t) for t in range(0, 359, 1)
]
verts_circ = list(zip(x_circ, y_circ))
circ_filter = Path(verts_circ)
stars_circ = circ_filter.contains_points(xy_points)
i_x_fc = [
ix[i] for i in range(len(i_mag))
if (stars_circ[i] and stars_f[i])
]
i_y_fc = [
iy[i] for i in range(len(i_mag))
if (stars_circ[i] and stars_f[i])
]
# fcirc_file = 'circle'+repr(r)+'.txt'
# with open(fcirc_file,'w+') as f3:
# for i,x in enumerate(i_x_fc):
# print >> f3, i_x_fc[i], i_y_fc[i]
i_mag_fcr = [
i_mag[i] for i in range(len(i_mag))
if (stars_circr[i] and stars_f[i])
]
i_ierr_fcr = [
i_ierr[i] for i in range(len(i_mag))
if (stars_circr[i] and stars_f[i])
]
g_ierr_fcr = [
g_ierr[i] for i in range(len(i_mag))
if (stars_circr[i] and stars_f[i])
]
g_mag_fcr = [
i_mag[i] for i in range(len(i_mag))
if (stars_circr[i] and stars_f[i])
]
gmi_fcr = [
gmi[i] for i in range(len(i_mag))
if (stars_circr[i] and stars_f[i])
]
i_ra_fcr = [
i_ra[i] for i in range(len(i_mag))
if (stars_circr[i] and stars_f[i])
]
i_dec_fcr = [
i_dec[i] for i in range(len(i_mag))
if (stars_circr[i] and stars_f[i])
]
i_rad_fcr = [
i_rad[i] for i in range(len(i_mag))
if (stars_circr[i] and stars_f[i])
]
i_decd_fcr = [
i_decd[i] for i in range(len(i_mag))
if (stars_circr[i] and stars_f[i])
]
i_x_fcr = [
ix[i] for i in range(len(i_mag)) if (stars_circr[i] and stars_f[i])
]
i_y_fcr = [
iy[i] for i in range(len(i_mag)) if (stars_circr[i] and stars_f[i])
]
fwhm_sfcr = [
fwhm_s[i] for i in range(len(i_mag))
if (stars_circr[i] and stars_f[i])
]
rcirc_c_x = ra_corner - (rCentx / 60.)
rcirc_c_y = (rCenty / 60.) + dec_corner
rcirc_pix_x, rcirc_pix_y = w.wcs_world2pix(rcirc_c_x, rcirc_c_y, 1)
ra_cr, dec_cr = w.all_pix2world(rcirc_pix_x, rcirc_pix_y, 1)
ra_cr_d, dec_cr_d = deg2HMS(ra=ra_cr, dec=dec_cr, round=False)
circ_c_x = ra_corner - (yedges[y_cent] / 60.)
circ_c_y = (xedges[x_cent] / 60.) + dec_corner
circ_pix_x, circ_pix_y = w.wcs_world2pix(circ_c_x, circ_c_y, 1)
ra_c, dec_c = w.all_pix2world(circ_pix_x, circ_pix_y, 1)
ra_c_d, dec_c_d = deg2HMS(ra=ra_c, dec=dec_c, round=False)
# print 'Peak RA:',ra_c_d,':: Peak Dec:',dec_c_d
hi_x_circ, hi_y_circ = getHIellipse(title_string, ra_corner,
dec_corner)
hi_c_ra, hi_c_dec = getHIellipse(title_string,
ra_corner,
dec_corner,
centroid=True)
hi_pix_x, hi_pix_y = w.wcs_world2pix(hi_c_ra, hi_c_dec, 1)
sep = dist2HIcentroid(ra_c_d, dec_c_d, hi_c_ra, hi_c_dec)
# print "m-M = {:5.2f} | d = {:4.2f} Mpc | α = {:s}, δ = {:s}, Δʜɪ = {:5.1f}' | N = {:4d} | σ = {:6.3f} | ξ = {:6.3f}% | η = {:6.3f}%".format(dm, mpc, ra_c_d, dec_c_d, sep/60., n_in_filter, S[x_cent_S][y_cent_S], pct, pct_hi*100.)
fig = plt.figure(figsize=(8, 6))
# plot
# print "Plotting for m-M = ",dm
ax0 = plt.subplot(2, 2, 1)
plt.scatter(i_ra,
i_dec,
color='black',
marker='o',
s=1,
edgecolors='none')
plt.plot(x_circ, y_circ, linestyle='-', color='magenta')
plt.plot(x_circr, y_circr, linestyle='-', color='gold')
plt.plot(hi_x_circ, hi_y_circ, linestyle='-', color='limegreen')
# plt.scatter(i_ra_c, i_dec_c, color='red', marker='o', s=3, edgecolors='none')
plt.scatter(i_ra_f,
i_dec_f,
c='red',
marker='o',
s=10,
edgecolors='none')
# plt.clim(0,2)
# plt.colorbar()
plt.ylabel('Dec (arcmin)')
plt.xlim(0, max(i_ra))
plt.ylim(0, max(i_dec))
plt.title('sky positions')
ax0.set_aspect('equal')
ax1 = plt.subplot(2, 2, 2)
if os.path.isfile('i_gmi_compl.gr.out'):
gmiCompl, iCompl = np.loadtxt('i_gmi_compl.gr.out',
usecols=(0, 1),
unpack=True)
plt.plot(gmiCompl, iCompl, linestyle='--', color='green')
if os.path.isfile('i_gmi_compl.gr2.out'):
gmiCompl, iCompl = np.loadtxt('i_gmi_compl.gr2.out',
usecols=(0, 1),
unpack=True)
plt.plot(gmiCompl, iCompl, linestyle='--', color='red')
if os.path.isfile('i_gmi_compl2.out'):
iCompl, gmiCompl = np.loadtxt('i_gmi_compl2.out',
usecols=(0, 1),
unpack=True)
plt.plot(gmiCompl, iCompl, linestyle='--', color='blue')
plt.plot(gi_iso, i_m_iso, linestyle='-', color='blue')
plt.scatter(gmi,
i_mag,
color='black',
marker='o',
s=1,
edgecolors='none')
plt.scatter(gmi_f,
i_mag_f,
color='red',
marker='o',
s=15,
edgecolors='none')
# plt.scatter(gmi_c, i_mag_c, color='red', marker='o', s=3, edgecolors='none')
plt.errorbar(bxvals,
bcenters,
xerr=i_ierrAVG,
yerr=gmi_errAVG,
linestyle='None',
color='black',
capsize=0,
ms=0)
plt.tick_params(axis='y',
left='on',
right='off',
labelleft='on',
labelright='off')
ax1.yaxis.set_label_position('left')
plt.ylabel('$i_0$')
plt.xlabel('$(g-i)_0$')
plt.ylim(25, 15)
plt.xlim(-1, 4)
plt.title('m-M = ' + '{:5.2f}'.format(dm) + ' (' +
'{0:4.2f}'.format(mpc) + ' Mpc)')
ax1.set_aspect(0.5)
ax2 = plt.subplot(2, 2, 3)
extent = [yedges[0], yedges[-1], xedges[-1], xedges[0]]
plt.imshow(S, extent=extent, interpolation='nearest', cmap=cm.gray)
# plt.imshow(segm, extent=extent, cmap=rand_cmap, alpha=0.5)
cbar_S = plt.colorbar()
cbar_S.set_label('$\sigma$ from local mean')
# cbar_S.tick_params(labelsize=10)
plt.plot(x_circ, y_circ, linestyle='-', color='magenta')
plt.plot(x_circr, y_circr, linestyle='-', color='gold')
plt.plot(hi_x_circ, hi_y_circ, linestyle='-', color='limegreen')
# X, Y = np.meshgrid(xedges,yedges)
# ax3.pcolormesh(X,Y,grid_gaus)
plt.xlabel('RA (arcmin)')
plt.ylabel('Dec (arcmin)')
plt.title('smoothed stellar density')
# plt.ylabel('Dec (arcmin)')
plt.xlim(0, max(i_ra))
plt.ylim(0, max(i_dec))
ax2.set_aspect('equal')
# ax3 = plt.subplot(2,2,4)
ax3 = plt.subplot2grid((2, 4), (1, 2))
plt.scatter(gmi_c,
i_mag_c,
color='black',
marker='o',
s=3,
edgecolors='none')
plt.scatter(gmi_fc,
i_mag_fc,
color='red',
marker='o',
s=15,
edgecolors='none')
plt.tick_params(axis='y',
left='on',
right='on',
labelleft='off',
labelright='off')
ax0.yaxis.set_label_position('left')
plt.title('detection')
plt.xlabel('$(g-i)_0$')
plt.ylabel('$i_0$')
plt.ylim(25, 15)
plt.xlim(-1, 4)
# ax3.set_aspect(0.5)
ax4 = plt.subplot2grid((2, 4), (1, 3), sharey=ax3)
plt.scatter(gmi_cr,
i_mag_cr,
color='black',
marker='o',
s=3,
edgecolors='none')
plt.scatter(gmi_fcr,
i_mag_fcr,
color='red',
marker='o',
s=15,
edgecolors='none')
plt.tick_params(axis='y',
left='on',
right='on',
labelleft='off',
labelright='on')
plt.title('reference')
ax0.yaxis.set_label_position('left')
plt.xlabel('$(g-i)_0$')
plt.ylim(25, 15)
plt.xlim(-1, 4)
# ax3.set _aspect(0.5)
plt.tight_layout()
plt.savefig(out_file)
fig.clf()
pass