def get_fake(**kwargs):
fake = '/astro/net/angst2/philrose/PHAT/paper/referree/test.st'
d = np.loadtxt(fake, unpack=True)
x = d[2]
y = d[3]
Chi = d[4]
SNR = d[5]
Sharp = d[6]
Round = d[7]
Crowd = d[9]
Type = d[10]
mag_F275W = d[15]
chi_F275W = d[18]
snr_F275W = d[19]
sharp_F275W = d[20]
round_F275W = d[21]
crowd_F275W = d[22]
flag_F275W = d[23]
mag_F336W = d[28]
chi_F336W = d[31]
snr_F336W = d[32]
sharp_F336W = d[33]
round_F336W = d[34]
crowd_F336W = d[35]
flag_F336W = d[36]
cut_F336W = data.quality_cut(sharp_F336W, snr_F336W, crowd_F336W,
round_F336W, **kwargs)
cut_F275W = data.quality_cut(sharp_F275W, snr_F275W, crowd_F275W,
round_F275W, **kwargs)
cut_both = list(set(cut_F336W) & set(cut_F275W))
return mag_F336W[cut_both]
def new_mag_cut(**kwargs):
'''
this can run by a call to ASTs, not just by running main
set the magnitude cutoff to be the faintest recovered magnitude of a
star whose input magnitude was at the 50% completeness limit
'''
ast_file = kwargs.get('ast_file')
comp_data = kwargs.get('comp_data')
ast = load_ast_file(ast_file)
comp = file_io.load_comp_data(comp_data)
pm = 0.05
# within dmag range
rec1 = recovered_asts(ast['mag1in'], ast['mag1out'])
rec2 = recovered_asts(ast['mag2in'], ast['mag2out'])
# quality cut on all asts
qc1 = quality_cut(ast['sharp1'],
ast['snr1'],
ast['crowd1'],
ast['round1'],
loud=True,
**kwargs)
qc2 = quality_cut(ast['sharp2'],
ast['snr2'],
ast['crowd2'],
ast['round2'],
loud=True,
**kwargs)
# each radial bin
from params import PHAT_DIR_EXTRA3
contour = PHAT_DIR_EXTRA3 + 'contours_v3.reg'
inds = points_inside_ds9_polygon(contour, ast['ra'], ast['dec'])
filters = ('F275W', 'F336W')
ax1s = graphics.setup_five_panel_plot(fig=1)
[ax.set_xlabel('$%s$ Recovered' % filters[0]) for ax in ax1s]
ax1s[0].set_ylabel('$%s$ Recovered-Input' % filters[0])
cols = kwargs.get('cols')
axs = graphics.two_panel_plot_vert_bsquat()
axs[0].set_xlabel('F275W Recovered')
axs[1].set_ylabel('standard deviation')
axs[0].set_ylabel('residual')
for i in range(len(inds)):
Rinds1 = list(set(rec1) & set(qc1) & set(inds[i]))
#Rinds1 = list(set(rec1) & set(inds[i]))
#Rinds1 = list(set(rec1) & set(qc1) & set(qc2) & set(inds[i]))
within1 = np.nonzero(
(ast['mag1in'][Rinds1] <= comp['comp50mag1'][i] + pm)
& (ast['mag1in'][Rinds1] >= comp['comp50mag1'][i] - pm))[0]
mag1_cut = np.max(ast['mag1out'][Rinds1][within1])
print mag1_cut
ast_diff_test(ast['mag1out'][Rinds1],
ast['mag1in'][Rinds1],
axs=axs,
color=cols[i],
spacing=0.4)
axs[0].set_ylim(-0.01, 0.1)
ax1s[i].plot(ast['mag1out'][inds[i]],
ast['mag1out'][inds[i]] - ast['mag1in'][inds[i]],
'.',
color='black')
ax1s[i].plot(ast['mag1out'][Rinds1],
ast['mag1out'][Rinds1] - ast['mag1in'][Rinds1],
'.',
color='blue')
#ax1s[i].plot(ast['mag1in'][inds[i]],ast['mag1out'][inds[i]]-ast['mag1in'][inds[i]],'.',color='black')
#ax1s[i].plot(ast['mag1in'][Rinds1],ast['mag1out'][Rinds1]-ast['mag1in'][Rinds1],'.',color='blue')
ax1s[i].plot(np.zeros(100) + mag1_cut,
np.linspace(-2, 10, 100),
color='green')
ax1s[i].plot(np.zeros(100) + comp['comp50mag1'][i],
np.linspace(-2, 10, 100),
color='red')
ax1s[i].xaxis.set_major_locator(MultipleLocator(2))
ax1s[i].set_xlim(19, 27)
ax1s[i].set_ylim(-2, 2)
plt.savefig('ast_diff_mag1%s' % EXT)
ax2s = graphics.setup_five_panel_plot(fig=2)
[ax.set_xlabel('$%s$ Recovered' % filters[1]) for ax in ax2s]
ax2s[0].set_ylabel('$%s$ Recovered-Input' % filters[1])
axs = graphics.two_panel_plot_vert_bsquat()
axs[0].set_xlabel('F336W Recovered')
axs[1].set_ylabel('standard deviation')
axs[0].set_ylabel('residual')
for i in range(len(inds)):
Rinds2 = list(set(rec2) & set(qc2) & set(inds[i]))
#Rinds2 = list(set(rec2) & set(qc1) & set(qc2) & set(inds[i]))
within2 = np.nonzero(
(ast['mag2in'][Rinds2] <= comp['comp50mag2'][i] + pm)
& (ast['mag2in'][Rinds2] >= comp['comp50mag2'][i] - pm))[0]
mag2_cut = np.max(ast['mag2out'][Rinds2][within2])
print mag2_cut
ast_diff_test(ast['mag2out'][Rinds2],
ast['mag2in'][Rinds2],
axs=axs,
color=cols[i],
spacing=0.4)
axs[0].set_ylim(-0.01, 0.1)
ax2s[i].plot(ast['mag2out'][inds[i]],
ast['mag2out'][inds[i]] - ast['mag2in'][inds[i]],
'.',
color='black')
ax2s[i].plot(ast['mag2out'][Rinds2],
ast['mag2out'][Rinds2] - ast['mag2in'][Rinds2],
'.',
color='blue')
ax2s[i].plot(np.zeros(100) + mag2_cut,
np.linspace(-2, 10, 100),
color='green')
ax2s[i].plot(np.zeros(100) + comp['comp50mag2'][i],
np.linspace(-2, 10, 100),
color='red')
ax2s[i].xaxis.set_major_locator(MultipleLocator(2))
ax2s[i].set_xlim(19, 27)
ax2s[i].set_ylim(-2, 2)
plt.savefig('ast_diff_mag2%s' % EXT)
return
def main(**kwargs):
ast_file = kwargs.get('ast_file')
ast = load_ast_file(ast_file)
from params import PHAT_DIR_EXTRA3
contour = PHAT_DIR_EXTRA3 + 'contours_v3.reg'
cras, cdecs = file_io.read_reg(contour)
outverts = np.column_stack((cras[-1], cdecs[-1]))
rec1 = recovered_asts(ast['mag1in'], ast['mag1out'])
rec2 = recovered_asts(ast['mag2in'], ast['mag2out'])
# quality cut on all asts
qc1 = quality_cut(ast['sharp1'], ast['snr1'], ast['crowd1'], ast['round1'],
**kwargs)
qc2 = quality_cut(ast['sharp2'], ast['snr2'], ast['crowd2'], ast['round2'],
**kwargs)
qcd = list(set(qc1) & set(qc2))
inds = points_inside_ds9_polygon(contour, ast['ra'], ast['dec'])
comp_corr_file = open(kwargs.get('comp_file'), 'w')
comp_corr_file.write('# region (0=in) mags comp_frac \n')
comp_data_file = open(kwargs.get('comp_data'), 'w')
print 'comp correction file:', kwargs.get('comp_file')
print 'comp data file:', comp_data_file
single = kwargs.get('single')
kwargs['ast_file_ext'] = '_' + kwargs.get('comp_file').replace(
'.dat', '').split('_')[-1]
if single == False:
qc1 = qcd
qc2 = qcd
kwargs['ast_file_ext'] += '_dd'
color_range = (-0.7, 0.5)
ast_color = ast['mag1in'] - ast['mag2in']
color_inds = np.nonzero((ast_color > color_range[0])
& (ast_color < color_range[1]))[0]
Rinds1s, Rinds2s, Bins, Frac1s, Frac2s = [], [], [], [], []
Rhist1s, Rhist2s, Qhist1s, Qhist2s = [], [], [], []
comp_data_file.write(
'# Region comp50mag1 comp50mag2 comp90mag1 comp90mag2\n')
print '# Region comp50mag1 comp50mag2 comp90mag1 comp90mag2'
for i in range(len(inds)):
# in each annulus, passed qc, recovered
if single == False:
Rinds1 = list(
set(rec1) & set(qc1) & set(inds[i]) & set(color_inds))
Rinds2 = list(
set(rec2) & set(qc2) & set(inds[i]) & set(color_inds))
# REWRITING INDS OF I FOR THIS COLOR RANGE.
inds[i] = list(set(inds[i]) & set(color_inds))
else:
Rinds1 = list(set(rec1) & set(qc1) & set(inds[i]))
Rinds2 = list(set(rec2) & set(qc2) & set(inds[i]))
hist_range = (18.34, 28.)
# use hist_bin_optimization to get this value
#spacing = 0.04
spacing = 0.2
Rhist1, Rbins1 = np.histogram(ast['mag1in'][Rinds1],
bins=np.arange(hist_range[0],
hist_range[1], spacing))
Rhist2, Rbins2 = np.histogram(ast['mag2in'][Rinds2],
bins=np.arange(hist_range[0],
hist_range[1], spacing))
Qhist1, Qbins1 = np.histogram(ast['mag1in'][inds[i]],
bins=np.arange(hist_range[0],
hist_range[1], spacing))
Qhist2, Qbins2 = np.histogram(ast['mag2in'][inds[i]],
bins=np.arange(hist_range[0],
hist_range[1], spacing))
# need to be float...
frac1 = np.array(map(float, Qhist1)) / np.array(map(float, Rhist1))
frac2 = np.array(map(float, Qhist2)) / np.array(map(float, Rhist2))
c_lim1 = GenUtils.closest_match(0.5, 1 / frac1)
c_lim2 = GenUtils.closest_match(0.5, 1 / frac2)
c_lim1a = GenUtils.closest_match(0.90, 1 / frac1)
c_lim2a = GenUtils.closest_match(0.90, 1 / frac2)
if i == 0:
inmag1 = c_lim1
inmag2 = c_lim2
[comp_corr_file.write('%.2f ' % bin) for bin in Rbins1]
comp_corr_file.write('\n')
else:
print 1. / frac1[inmag1], 1. / frac2[inmag2]
comp_data_file.write(
'# inner mag limit corresponds to 50 percent completeness \n# 275: %.3f \n# 336: %.3f \n'
% (1. / frac1[inmag1], 1. / frac2[inmag2]))
comp_corr_file.write('F336W %i ' % i)
[comp_corr_file.write('%.8f ' % frac) for frac in frac1]
comp_corr_file.write('\nF275W %i ' % i)
[comp_corr_file.write('%.8f ' % frac) for frac in frac2]
comp_corr_file.write('\n')
# for Table1 need comp50,98 index 0 to be inner ring.
comp50mag1 = Rbins1[c_lim1]
comp50mag2 = Rbins1[c_lim2]
comp92mag1 = Rbins1[c_lim1a]
comp92mag2 = Rbins1[c_lim2a]
comp_data_file.write(
'%i %.1f %.1f %.1f %.1f\n' %
(i, comp50mag1, comp50mag2, comp92mag1, comp92mag2))
print '%i %.1f %.1f %.1f %.1f' % (i, comp50mag1, comp50mag2,
comp92mag1, comp92mag2)
Rinds1s.append(Rinds1)
Rinds2s.append(Rinds2)
Bins.append(Rbins1)
Frac1s.append(frac1)
Frac2s.append(frac2)
Rhist1s.append(Rhist1)
Rhist2s.append(Rhist2)
Qhist1s.append(Qhist1)
Qhist2s.append(Qhist2)
ax1, ax2 = ast_completeness_plot(Bins, Frac1s, Frac2s, **kwargs)
ast_diff_plot(ast, Rinds1s, Rinds2s, inds, **kwargs)
ast_hist_plot(Bins, Rhist1s, Qhist1s, Rhist2s, Qhist2s, **kwargs)
comp_corr_file.close()
comp_data_file.close()
def ast_LF(ast, **kwargs):
cont_file = kwargs.get('cont_file')
one_plot = kwargs.get('one_plot', True)
powerlaw = lambda x, amp, index: amp * (x**index)
import CrowdTest
cols = kwargs.get('cols')
double_plot = kwargs.get('double_plot', False)
two_panel = kwargs.get('two_panel', True)
lf_o = CrowdTest.load_saved_lf(
filename=
'/Users/phil/research/PHAT/code/UVBrights/diy_final/lf_data.dat')
comp_data = kwargs['comp_data']
mag1_cut = file_io.get_comp90mags(comp_data)[0][0]
mag2_cut = file_io.get_comp90mags(comp_data)[1][0]
print '# mag1_cut, mag2_cut', mag1_cut, mag2_cut
if cont_file != None:
cf = open(cont_file, 'w')
cf.write('# mag1_cut, mag2_cut %.1f %.1f\n' % (mag1_cut, mag2_cut))
from params import PHAT_DIR_EXTRA3
contour = PHAT_DIR_EXTRA3 + 'contours_v3.reg'
inds = calcs.points_inside_ds9_polygon(contour, ast['ra'], ast['dec'])
filters = ('F275W', 'F336W')
rec1 = recovered_asts(ast['mag1in'], ast['mag1out'])
rec2 = recovered_asts(ast['mag2in'], ast['mag2out'])
# quality cut on all asts
qc1 = quality_cut(ast['sharp1'],
ast['snr1'],
ast['crowd1'],
ast['round1'],
loud=True,
**kwargs)
qc2 = quality_cut(ast['sharp2'],
ast['snr2'],
ast['crowd2'],
ast['round2'],
loud=True,
**kwargs)
spacing = .05
if two_panel == True:
ax1, ax2 = graphics.two_panel_plot(11, 5, 'x', 'x', '$\#$')
axs = [ax1, ax2, ax1, ax2, ax1]
for j, filter in enumerate(filters):
fcolor = 'blue'
if double_plot == True:
axs, baxs = graphics.setup_ten_panel_plot(fig=j + 1, noy=True)
elif two_panel == False:
fig = j + 1
if one_plot == True: fig = 1
axs = graphics.setup_five_panel_plot(fig=fig, noy=True)
if j != 0: fcolor = 'green'
sortkeys = np.sort(lf_o[filter].keys())
for k, region in enumerate(sortkeys):
if filter == 'F336W':
qc = qc2
ast_mag_in = ast['mag2in']
ast_mag_out = ast['mag2out']
mag = mag2_cut
if two_panel == True: axs[k] = ax2
axs[k].set_xlim(26.1, 16)
index = 16.943523372280001
amp = 1e-17
if filter == 'F275W':
qc = qc1
ast_mag_in = ast['mag1in']
ast_mag_out = ast['mag1out']
mag = mag1_cut
if two_panel == True: axs[k] = ax1
axs[k].set_xlim(25.9, 16)
index = 19.246755161139998
amp = 1e-20
Rinds = list(set(rec1) & set(qc) & set(inds[k]))
bins = np.arange(np.min(ast_mag_in[Rinds]),
np.max(ast_mag_in[Rinds]), spacing)
hist = powerlaw(bins, 1e-17, 15)
#hist = powerlaw(bins,amp,index)
# paste tests here
axs[k].plot(bins, hist, ls='steps', color='black')
hist_o, bins_o = lf_o[filter][region].values()
#axs[k].plot(bins_o,np.array(hist_o)*1e2,ls='steps',color=cols[k])
# bin up input mag
in1s = np.digitize(ast_mag_in[Rinds], bins)
new_mags = np.array([])
for i in range(len(bins)):
if hist[i] == 0: continue
if len(np.array(in1s == i).nonzero()[0]) <= 1: continue
# output mag corresponding to the input mag bin
ast_mag = ast_mag_out[Rinds][np.array(in1s == i).nonzero()[0]]
# make cumulative distribution
sort_ast = np.sort(ast_mag)
yvals = np.arange(len(sort_ast)) / float(len(sort_ast))
# interpolate it from 0,1
f = scipy.interpolate.interp1d(yvals,
sort_ast,
bounds_error=False)
# pick randomly from distribution the same number as in the current histogram
new_mags = np.append(new_mags, f(np.random.random(hist[i])))
# find new LF
new_hist, lixo = np.histogram(new_mags, bins=bins)
#print sum(new_hist), sum(hist)
axs[k].plot(bins[1:], new_hist, ls='steps', color=fcolor, lw=2)
ofst = 0.1
#mag = closest_match(bins[1:],(new_hist-hist[1:])/hist[1:],.2)
g = scipy.interpolate.interp1d(bins[1:],
(new_hist - hist[1:]) / hist[1:])
print filter, k, g(mag)
if cont_file != None:
cf.write('%s %i %f\n' % (filter, k, g(mag)))
if double_plot == True:
baxs[k].plot(np.zeros(10) + mag,
np.linspace(baxs[k].get_ylim()[0],
baxs[k].get_ylim()[1], 10),
'--',
color='black',
label='%.2f' % g(mag))
baxs[k].set_xlim(
np.max(ast_mag_in) - ofst,
np.min(ast_mag_in) + ofst)
baxs[k].legend(loc=0, frameon=False)
baxs[k].set_xlabel('$%s$' % filter)
baxs[k].plot(bins[1:], (new_hist - hist[1:]) / hist[1:],
color='black',
lw=2,
ls='steps')
else:
if one_plot == True:
axs[k].set_xlabel(r'$\rm{mag}$')
if k != 0: axs[k].yaxis.set_major_formatter(nullfmt)
else:
axs[k].set_xlabel('$%s$' % filter)
axs[k].xaxis.set_major_locator(MultipleLocator(2))
axs[k].xaxis.set_minor_locator(MultipleLocator(1))
axs[k].set_ylim(1e1, 1e5)
axs[k].plot(np.zeros(3) + mag,
np.logspace(1, 5, 3),
'--',
lw=2,
color=fcolor,
label='%.2f' % g(mag))
axs[k].set_yscale('log')
axs[0].set_ylabel('$\#$')
axs[k].annotate(r'$F275W$', xy=(22, 5e4), fontsize=20, color='blue')
axs[k].annotate(r'$F336W$', xy=(22, 3e4), fontsize=20, color='green')
[ax.set_ylim(1e2, 1e5) for ax in axs]
[ax.set_xlim(26, 19) for ax in axs]
if double_plot == True: baxs[0].set_ylabel('(input-obs)/input')
if one_plot != True:
plt.figure(j + 1)
plt.savefig('ast_lf_test_%s%s' % EXT % filter)
else:
plt.savefig('ast_lf_test%s' % EXT)
if cont_file != None: cf.close()
return axs