def ast_diff_plot(ast, Rinds1s, Rinds2s, inds, **kwargs):
ast_file_ext = kwargs.get('ast_file_ext', '')
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])
mag1in = ast['mag1in']
mag1out = ast['mag1out']
mag2in = ast['mag2in']
mag2out = ast['mag2out']
for j in range(len(Rinds1s)):
ax1s[j].plot(mag1out[inds[j]],
mag1out[inds[j]] - mag1in[inds[j]],
'.',
color='black')
ax1s[j].plot(mag1out[Rinds1s[j]],
mag1out[Rinds1s[j]] - mag1in[Rinds1s[j]],
'.',
color='blue')
ax1s[j].xaxis.set_major_locator(MultipleLocator(2))
ax1s[j].set_xlim(19, 27)
ax1s[j].set_ylim(-2, 2)
plt.savefig('ast_diff_mag1%s%s' % EXT % (ast_file_ext))
plt.close()
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])
for j in range(len(Rinds2s)):
ax2s[j].plot(mag2out[inds[j]],
mag2out[inds[j]] - mag2in[inds[j]],
'.',
color='black')
ax2s[j].plot(mag2out[Rinds2s[j]],
mag2out[Rinds2s[j]] - mag2in[Rinds2s[j]],
'.',
color='blue')
ax2s[j].xaxis.set_major_locator(MultipleLocator(2))
ax2s[j].set_xlim(19, 27)
ax2s[j].set_ylim(-2, 2)
plt.savefig('ast_diff_mag2%s%s' % EXT % (ast_file_ext))
plt.close()
return
def red_star(phot, rad_inds, cut_inds, **kwargs):
axs = graphics.setup_five_panel_plot()
flux1, flux2 = [], []
Filter1 = kwargs.get('Filter1')
Filter2 = kwargs.get('Filter2')
for i in range(len(rad_inds)):
inds = list(set(rad_inds[i]) & set(cut_inds))
mag1 = phot['mag1'][inds]
mag2 = phot['mag2'][inds]
color = mag1 - mag2
red = np.nonzero((color > 0.8) & (mag2 < 19))[0]
flux2.append(
np.sum(Astronomy.vegamag2flux(mag2[red], Filter2, 'wfc3uvis')))
flux1.append(
np.sum(Astronomy.vegamag2flux(mag1[red], Filter1, 'wfc3uvis')))
ax = axs[i]
ax.plot(color, mag2, ',', color='black')
ax.plot(mag1[red] - mag2[red], mag2[red], ',', color='red')
return flux1, flux2
def main():
# /astro/users/ben/ad2/ben/WFC3/12058_M31-B01-F040510111617-UVIS/proc/
fits_file = os.path.join(
PHAT_DATA_BASE, '12058_M31-B01-F040510111617-UVIS_F275W_F336W.st.fits')
exposure_reg = os.path.join(
PHAT_DATA_BASE,
'12058_exposure_coverage_UVIS_F336W_chipswap_bulge.reg')
v3_contours = PHAT_DIR_EXTRA3 + 'contours_v3.reg'
f = pyfits.open(fits_file)
f_data = f[1].data
f.close()
Filter1 = 'F275W'
Filter2 = 'F336W'
mag1 = f_data.field('MAG1_UVIS')
mag2 = f_data.field('MAG2_UVIS')
color = mag1 - mag2
ra = f_data.field('RA')
dec = f_data.field('DEC')
contour_dict = reg_to_array(v3_contours)
verts, verts2, verts2 = get_overlap_regions()
radec = np.column_stack((ra, dec))
ind = np.nonzero(nxutils.points_inside_poly(radec, verts))[0]
ind2 = np.nonzero(nxutils.points_inside_poly(radec, verts2))[0]
ind3 = np.nonzero(nxutils.points_inside_poly(radec, verts3))[0]
inds = calcs.points_inside_ds9_polygon(v3_contours, ra, dec)
axs = graphics.setup_five_panel_plot(fig=2)
for i in range(len(inds)):
bam = list(set(inds[i]) & set(ind3))
axs[i].plot(color[bam], mag2[bam], '.')
axs[i].set_ylim(27, 19.5)
def lf_bin_comparison(phot, inds_cut1, inds_cut2, rad_inds, **kwargs):
lf_data = load_saved_lf(
'/Users/phil/research/PHAT/code/UVBrights/diy_final/lf_data.dat')
sup_phot = kwargs.get('sup_phot')
rif_36 = sup_phot['rif_36']
comp_file = kwargs.get('comp_file')
comp_data = kwargs.get('comp_data')
frac1s, frac2s, magbins = file_io.load_completeness_corrections(comp_file)
comp50mag1, comp50mag2 = file_io.get_comp50mags(comp_data)
ylab = r'$\rm{Number}/10^7 M_\odot$'
xlab1 = '$%s$' % kwargs.get('Filter1')
xlab2 = '$%s$' % kwargs.get('Filter2')
cols = kwargs.get('cols')
filter1 = kwargs.get('Filter1')
filter2 = kwargs.get('Filter2')
ax1s = graphics.setup_five_panel_plot(fig=2)
for i in range(len(rad_inds)):
ax1 = ax1s[i]
ax1.set_xlim(26, 19)
ax1.xaxis.set_major_locator(MultipleLocator(2))
if i == 0: ax1.set_ylabel(ylab)
ax1.set_xlabel(xlab1)
# M/L ratio 1e7 scaling is for AXIS
norm = rif_36[i + 1] / 2.315e-9 * 0.95 * 1e-7
inds1 = list(set(inds_cut1) & set(rad_inds[i]))
hist1, bins = np.histogram(phot['mag1'][inds1], bins=magbins)
known = np.nonzero(bins[1:] <= comp50mag1[i])[0]
poor = np.nonzero(bins[1:] >= comp50mag1[i])[0]
vals = hist1[known] * frac1s[i][known] / norm
errlow, errhigh = np.transpose([cdf_bitches(v) for v in vals])
ax1.fill_between(bins[1:][known],
errlow,
errhigh,
color=cols[i],
alpha=0.2)
ax1.plot(bins[1:],
hist1 * frac1s[i] / norm,
drawstyle='steps',
color=cols[i],
lw=1)
ax1.plot(bins[1:][known],
hist1[known] * frac1s[i][known] / norm,
drawstyle='steps',
color=cols[i],
lw=2)
lf_hist, lf_bins = lf_data[filter1][str(i)].values()
ax1.plot(lf_bins, lf_hist, drawstyle='steps', color='black', lw=2)
ax1.set_yscale('log')
ax1.set_ylim(.01, 10)
plt.savefig('radialLF_cdf_%s%s' % EXT % kwargs.get('Filter1'))
plt.close()
ax2s = graphics.setup_five_panel_plot(fig=1)
#ax1,ax2 = graphics.two_panel_plot(11,5,xlab1,xlab2,ylab)
for i in range(len(rad_inds)):
ax2 = ax2s[i]
ax2.set_xlim(26, 19)
#ax2.set_ylim(0,8)
ax2.xaxis.set_major_locator(MultipleLocator(2))
if i == 0: ax2.set_ylabel(ylab)
ax2.set_xlabel(xlab2)
# M/L ratio 1e7 scaling is for AXIS
norm = rif_36[i + 1] / 2.315e-9 * 0.95 * 1e-7
inds2 = list(set(inds_cut2) & set(rad_inds[i]))
hist2, bins = np.histogram(phot['mag2'][inds2], bins=magbins)
known = np.nonzero(bins[1:] <= comp50mag2[i])[0]
poor = np.nonzero(bins[1:] >= comp50mag2[i])[0]
vals = hist2[known] * frac2s[i][known] / norm
errlow, errhigh = np.transpose([cdf_bitches(v) for v in vals])
ax2.fill_between(bins[1:][known],
errlow,
errhigh,
color=cols[i],
alpha=0.2)
ax2.plot(bins[1:],
hist2 * frac2s[i] / norm,
drawstyle='steps',
color=cols[i],
lw=1)
ax2.plot(bins[1:][known],
hist2[known] * frac2s[i][known] / norm,
drawstyle='steps',
color=cols[i],
lw=2)
lf_hist, lf_bins = lf_data[filter2][str(i)].values()
ax2.plot(lf_bins, lf_hist, drawstyle='steps', color='black', lw=2)
ax2.set_yscale('log')
ax2.set_ylim(.01, 10)
plt.savefig('radialLF_cdf_%s%s' % EXT % kwargs.get('Filter2'))
plt.close()
return
def disk_cont(phot, rad_inds, cut_inds, **kwargs):
ftsize = kwargs.get('ftsize')
disk_fit = kwargs.get('disk_fit')
mag1_cut = kwargs.get('mag1_cut')
mag2_cut = kwargs.get('mag2_cut')
# exculding innermost region
areas = kwargs.get('areas')[1:]
distances = kwargs.get('distances')[1:]
d1 = pyfits.open(disk_fit)[1].data
dmag1 = d1.field('mag1')
dmag2 = d1.field('mag2')
dqc_inds = np.nonzero((dmag1 < mag1_cut) & (dmag2 < mag2_cut))
dmag = dmag2[dqc_inds]
dcolor = dmag1[dqc_inds] - dmag
mag_bot = 23.
mag_top = 22.
# outline of MS between 22-23 - done roughly by eye/plot
col_bl = 0.013
col_tl = -0.13
col_br = col_bl + 0.15
col_tr = col_tl + 0.15
test_col = [col_tl, col_tr, col_tr, col_tl, col_tl]
test_mag = [mag_top, mag_top, mag_bot, mag_bot, mag_top]
test_verts = np.column_stack((test_col, test_mag))
# outline of NOT MS between 22-23
col_r = -0.35
col_l = -0.50
control_col = [col_l, col_r, col_r, col_l, col_l]
control_mag = test_mag # just to be clear, same mag range...
control_verts = np.column_stack((control_col, control_mag))
axs = graphics.setup_five_panel_plot()
Ncontrol, Ntest = [], []
control, test = [], []
for i in range(len(rad_inds)):
inds = list(set(rad_inds[i]) & set(cut_inds))
mag1 = phot['mag1'][inds]
mag2 = phot['mag2'][inds]
color = mag1 - mag2
colmag = np.column_stack((color, mag2))
control = np.nonzero(nxutils.points_inside_poly(colmag,
control_verts))[0]
test = np.nonzero(nxutils.points_inside_poly(colmag, test_verts))[0]
Ncontrol.append(float(len(control)))
Ntest.append(float(len(test)))
ax = axs[i]
ax.plot(dcolor, dmag, ',', color='grey', mec='grey')
ax.plot(color[control], mag2[control], '.', color='black')
ax.plot(control_verts[:, 0], control_verts[:, 1], lw=2, color='blue')
ax.plot(test_verts[:, 0], test_verts[:, 1], lw=2, color='white')
ax.plot(color[test], mag2[test], '.', color='red')
Ncfit = np.polyfit(distances, Ncontrol, 1)
Ntfit = np.polyfit(distances, Ntest, 1)
plt.savefig('disk_cont.png')
print 'wrote disk_cont.png'
plt.close()
rel_errorNt = np.sqrt(Ntest) / Ntest
rel_errorNc = np.sqrt(Ncontrol) / Ncontrol
pct_err = [
rt**2 + rc**2 + 2 * rt * rc for rt, rc in zip(rel_errorNt, rel_errorNc)
]
ratio = np.array(Ntest) / np.array(Ncontrol)
ax1, ax2, ax3 = graphics.set_up_three_panel_plot()
ax3.errorbar(distances, ratio, yerr=ratio * pct_err, color='black', lw=2)
ax2.plot(dcolor, dmag, ',', color='grey')
for i in range(len(rad_inds)):
inds = list(set(rad_inds[i]) & set(cut_inds))
mag1 = phot['mag1'][inds]
mag2 = phot['mag2'][inds]
color = mag1 - mag2
ax1.plot(color, mag2, ',', color='black')
for ax in [ax1, ax2]:
ax.plot(control_verts[:, 0],
control_verts[:, 1],
'--',
lw=2,
color='red')
ax.plot(test_verts[:, 0], test_verts[:, 1], lw=2, color='darkblue')
ax.set_ylim(24.1, 19)
ax.set_xlim(-0.75, 2)
ax.set_xlabel(r'$F275W-F336W$', fontsize=ftsize)
ax2.yaxis.set_major_formatter(nullfmt)
ax1.set_ylabel(r'$F336W$', fontsize=ftsize)
ax3.set_xlabel(r'$\rm{Radius\ (pc)}$', fontsize=ftsize)
ax3.set_ylabel(r'$\rm{Number\ Ratio Bluer/Redder}$', fontsize=ftsize)
plt.savefig('nratio_cont.png')
print 'wrote nratio_cont.png'
plt.close()
plt.errorbar(distances,
Ntest / areas,
yerr=np.sqrt(np.array(Ntest / areas)),
color='red',
lw=2,
label='Possible cont')
plt.errorbar(distances,
Ncontrol / areas,
np.sqrt(np.array(Ncontrol / areas)),
color='black',
lw=2,
label='No cont')
plt.xlabel('Region pc')
plt.ylabel('Number in box/arcsec$^2$')
plt.legend(loc=2)
plt.savefig('density_cont.png')
print 'wrote density_cont.png'
plt.close()
plt.figure()
plt.plot(distances, Ntest, color='red', lw=2, label='Possible cont')
plt.plot(distances, Ncontrol, color='black', lw=2, label='No cont')
plt.xlabel('Region Out -- to -- In')
plt.ylabel('Number in box')
plt.legend(loc=0)
plt.savefig('number_cont.png')
print 'wrote number_cont.png'
return
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 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