def plot_wise(cat_path):
for catfile in find_files(cat_path, "*merged+wise.csv"):
print("\nreading catalog: {}".format(catfile))
df = pd.read_csv(catfile)
# convert to magnitudes
nbadflux = (df.flux <= 0).sum()
try:
assert nbadflux == 0
except:
print("warning: {} negative flux source(s)".format(nbadflux))
ch = catfile.split('/')[-1].split('_')[1]
mags = spz_jy_to_mags(df.flux * 1e-3, float(ch))
if ch == '1':
plt.scatter(df.W1mag, mags)
plt.xlabel('W1 [mag]')
plt.ylabel('I1 [mag]')
elif ch == '2':
plt.scatter(df.W2mag, mags)
plt.xlabel('W2 [mag]')
plt.ylabel('I2 [mag]')
ax = plt.gca()
xlim, ylim = ax.get_xlim(), ax.get_ylim()
plt.plot([-5, ylim[1] * 2], [-5, ylim[1] * 2], 'r-')
ax.set_xlim(xlim)
ax.set_ylim(ylim)
reg = catfile.split('/')[-1].split('_')[0]
name = '{}_{}_IRAC_vs_WISE.png'.format(reg, ch)
outpath = '/'.join(catfile.split('/')[:-1] + [name])
plt.savefig(outpath, dpi=120)
plt.close()
def plot_wise(cat_path):
for catfile in find_files(cat_path, "*merged+wise.csv"):
print("\nreading catalog: {}".format(catfile))
df = pd.read_csv(catfile)
# convert to magnitudes
nbadflux = (df.flux <= 0).sum()
try:
assert nbadflux == 0
except:
print("warning: {} negative flux source(s)".format(nbadflux))
ch = catfile.split('/')[-1].split('_')[1]
mags = spz_jy_to_mags(df.flux*1e-3, float(ch))
if ch == '1':
plt.scatter(df.W1mag, mags)
plt.xlabel('W1 [mag]')
plt.ylabel('I1 [mag]')
elif ch == '2':
plt.scatter(df.W2mag, mags)
plt.xlabel('W2 [mag]')
plt.ylabel('I2 [mag]')
ax = plt.gca()
xlim, ylim = ax.get_xlim(), ax.get_ylim()
plt.plot([-5, ylim[1]*2], [-5, ylim[1]*2], 'r-')
ax.set_xlim(xlim) ; ax.set_ylim(ylim)
reg = catfile.split('/')[-1].split('_')[0]
name = '{}_{}_IRAC_vs_WISE.png'.format(reg, ch)
outpath = '/'.join(catfile.split('/')[:-1]+[name])
plt.savefig(outpath, dpi=120)
plt.close()
def plot_sdss(cat_path):
for catfile in find_files(cat_path, "*merged+sdss.txt"):
# for now ignore the channel 2 files
if catfile.split('/')[-1].split('_')[1] != '1':
continue
print("\nreading catalog: {}".format(catfile))
df = pd.read_table(catfile, sep=' ')
# get rid of negative flux sources, if any
df = df[df.flux > 0]
# convert to magnitudes
mags = spz_jy_to_mags(df.flux * 1e-3, 1)
# print counts per magnitude bin
for i in range(10, 15):
sc = ((df.cl == 3) & (mags > i) & (mags < i + 1)).sum()
xc = ((df.xsc == 1) & (mags > i) & (mags < i + 1)).sum()
msg = "{}th to {}th mag: {} SDSS galaxy sources, {} 2MASS XSC sources"
print(msg.format(i, i + 1, sc, xc))
# print number of sources agreed upon
agree = ((df.xsc == 1) & (df.cl == 3)).sum()
disagree = ((df.xsc == 1) & (df.cl == 6)).sum()
na = ((df.xsc == 1) & (df.cl == 0)).sum()
msg = "{} 2MASS XSC sources classified as galaxies by SDSS"
print(msg.format(agree))
msg = "{} 2MASS XSC sources classified as stars by SDSS"
print(msg.format(disagree))
msg = "{} 2MASS XSC sources not matched to SDSS"
print(msg.format(na))
# plot normed histograms of 2MASS XSC and SDSS galaxy magnitudes
xsc_gals = (mags > 10) & (mags < 15) & (df.xsc == 1)
sdss_gals = (mags > 10) & (mags < 15) & (df.cl == 3)
# mags[xsc_gals].hist(label='2MASS XSC', normed=True)
# mags[sdss_gals].hist(label='SDSS galaxies', normed=True)
plt.hist([mags[xsc_gals].values, mags[sdss_gals].values],
bins=5,
label=['2MASS', 'SDSS'])
plt.xlabel('IRAC1 [mag]')
plt.ylabel('Number Count')
reg = catfile.split('/')[-1].split('_')[0]
plt.title('{} Extended Sources / Galaxies'.format(reg))
plt.legend(loc=2)
name = '{}_2mass_xsc_vs_sdss_hist.png'.format(reg)
outpath = '/'.join(catfile.split('/')[:-1] + [name])
plt.savefig(outpath, dpi=100)
plt.close()
print("created file: {}".format(outpath))
def plot_sdss(cat_path):
for catfile in find_files(cat_path, "*merged+sdss.txt"):
# for now ignore the channel 2 files
if catfile.split('/')[-1].split('_')[1] != '1':
continue
print("\nreading catalog: {}".format(catfile))
df = pd.read_table(catfile, sep=' ')
# get rid of negative flux sources, if any
df = df[df.flux > 0]
# convert to magnitudes
mags = spz_jy_to_mags(df.flux*1e-3, 1)
# print counts per magnitude bin
for i in range(10,15):
sc = ((df.cl == 3) & (mags > i) & (mags < i+1)).sum()
xc = ((df.xsc == 1) & (mags > i) & (mags < i+1)).sum()
msg = "{}th to {}th mag: {} SDSS galaxy sources, {} 2MASS XSC sources"
print(msg.format(i, i+1, sc, xc))
# print number of sources agreed upon
agree = ((df.xsc == 1) & (df.cl == 3)).sum()
disagree = ((df.xsc == 1) & (df.cl == 6)).sum()
na = ((df.xsc == 1) & (df.cl == 0)).sum()
msg = "{} 2MASS XSC sources classified as galaxies by SDSS"
print(msg.format(agree))
msg = "{} 2MASS XSC sources classified as stars by SDSS"
print(msg.format(disagree))
msg = "{} 2MASS XSC sources not matched to SDSS"
print(msg.format(na))
# plot normed histograms of 2MASS XSC and SDSS galaxy magnitudes
xsc_gals = (mags > 10) & (mags < 15) & (df.xsc == 1)
sdss_gals = (mags > 10) & (mags < 15) & (df.cl == 3)
# mags[xsc_gals].hist(label='2MASS XSC', normed=True)
# mags[sdss_gals].hist(label='SDSS galaxies', normed=True)
plt.hist([mags[xsc_gals].values, mags[sdss_gals].values],
bins=5, label=['2MASS', 'SDSS'])
plt.xlabel('IRAC1 [mag]')
plt.ylabel('Number Count')
reg = catfile.split('/')[-1].split('_')[0]
plt.title('{} Extended Sources / Galaxies'.format(reg))
plt.legend(loc=2)
name = '{}_2mass_xsc_vs_sdss_hist.png'.format(reg)
outpath = '/'.join(catfile.split('/')[:-1]+[name])
plt.savefig(outpath, dpi=100)
plt.close()
print("created file: {}".format(outpath))
def plot_spz_vs_wise_sdss_class(cat_path, plot_style='scatter'):
ch1 = list(find_files(cat_path, "*merged+sdss+wise.csv"))[::2]
ch2 = list(find_files(cat_path, "*merged+sdss+wise.csv"))[1::2]
for ch1, ch2 in zip(ch1, ch2):
reg1 = ch1.split('/')[-1].split('_')[0]
reg2 = ch2.split('/')[-1].split('_')[0]
assert reg1 == reg2
print("\nreading catalog: {}".format(ch1))
print("reading catalog: {}".format(ch2))
df1 = pd.read_csv(ch1)
df2 = pd.read_csv(ch2)
# convert to magnitudes
mags1 = spz_jy_to_mags(df1.flux * 1e-3, 1)
mags2 = spz_jy_to_mags(df2.flux * 1e-3, 2)
# match ch1 / ch2
idx1, idx2 = match_cats(df1, df2, tol=2 / 3600.)
# save matched catalogs
matched1 = df1.loc[idx1]
matched2 = df2.loc[idx2]
ch1_cols = [i + '_1' for i in df1.columns.tolist()]
ch2_cols = [i + '_2' for i in df2.columns.tolist()]
# matched1.columns = ch1_cols
# matched2.columns = ch2_cols
# matched = pd.concat([matched1, matched2], 1, ignore_index=True) # weird error
matched = np.concatenate([matched1.values, matched2.values], 1)
df_matched = pd.DataFrame(matched, columns=ch1_cols + ch2_cols)
df_matched['I1'] = mags1[idx1].values
df_matched['I2'] = mags2[idx2].values
outpath = '/'.join(
ch1.split('/')[:-1]) + '/{}_2ch_matched+sdss.csv'.format(reg1)
df_matched.to_csv(outpath, index=False, float_format='%.8f')
print("created file: {}".format(outpath))
# identify SDSS galaxies and stars
galaxies = (df1.cl[idx1].values == 3) & (df2.cl[idx2].values == 3)
stars = (df1.cl[idx1].values == 6) & (df2.cl[idx2].values == 6)
# plot I1-I2 vs. W1-W2
color1 = df1.W1mag[idx1].values - df2.W2mag[idx2].values
color2 = mags1[idx1].values - mags2[idx2].values
# galaxies
name = '{}_I1-I2_vs_W1-W2_galaxies_plot_style.png'.format(reg1)
name = name.replace('plot_style', plot_style)
outpath = '/'.join(ch1.split('/')[:-1] + [name])
plot(color1[galaxies],
color2[galaxies],
outpath,
'W1-W2 [mag]',
'I1-I2 [mag]',
plot_style=plot_style,
plot_type='color-color')
# stars
outpath = '/'.join(ch1.split('/')[:-1] + [name]).replace(
'galaxies', 'stars')
plot(color1[stars],
color2[stars],
outpath,
'W1-W2 [mag]',
'I1-I2 [mag]',
plot_style=plot_style,
plot_type='color-color')
# plot I1-W1 vs. I2-W2
color1 = mags1[idx1].values - df1.W1mag[idx1].values
color2 = mags2[idx2].values - df2.W2mag[idx2].values
# galaxies
name = '{}_I1-W1_vs_I2-W2_galaxies_plot_style.png'.format(reg1)
name = name.replace('plot_style', plot_style)
outpath = '/'.join(ch1.split('/')[:-1] + [name])
plot(color1[galaxies],
color2[galaxies],
outpath,
'I1-W1 [mag]',
'I2-W2 [mag]',
plot_style=plot_style,
plot_type='color-color')
# stars
outpath = '/'.join(ch1.split('/')[:-1] + [name]).replace(
'galaxies', 'stars')
plot(color1[stars],
color2[stars],
outpath,
'I1-W1 [mag]',
'I2-W2 [mag]',
plot_style=plot_style,
plot_type='color-color')
# plot spz color-magnitude diagrams
color = mags1[idx1].values - mags2[idx2].values
mags = mags1[idx1].values
# galaxies
name = '{}_I1_vs_I1-I2_galaxies_plot_style.png'.format(reg1)
name = name.replace('plot_style', plot_style)
outpath = '/'.join(ch1.split('/')[:-1] + [name])
plot(mags[galaxies],
color[galaxies],
outpath,
'I1 [mag]',
'I1-I2 [mag]',
plot_style=plot_style,
plot_type='color-mag')
# stars
outpath = '/'.join(ch1.split('/')[:-1] + [name]).replace(
'galaxies', 'stars')
plot(mags[stars],
color[stars],
outpath,
'I1 [mag]',
'I1-I2 [mag]',
plot_style=plot_style,
plot_type='color-mag')
# plot wise color-magnitude diagrams
color = df1.W1mag[idx1].values - df2.W2mag[idx2].values
mags = df1.W1mag[idx1].values
# galaxies
name = '{}_W1_vs_W1-W2_galaxies_plot_style.png'.format(reg1)
name = name.replace('plot_style', plot_style)
outpath = '/'.join(ch1.split('/')[:-1] + [name])
plot(mags[galaxies],
color[galaxies],
outpath,
'W1 [mag]',
'W1-W2 [mag]',
plot_style=plot_style,
plot_type='color-mag')
# stars
outpath = '/'.join(ch1.split('/')[:-1] + [name]).replace(
'galaxies', 'stars')
plot(mags[stars],
color[stars],
outpath,
'W1 [mag]',
'W1-W2 [mag]',
plot_style=plot_style,
plot_type='color-mag')
# plot I1 vs I2
mags1_matched = mags1[idx1].values
mags2_matched = mags2[idx2].values
# galaxies
name = '{}_I1_vs_I2_galaxies_plot_style.png'.format(reg1)
name = name.replace('plot_style', plot_style)
outpath = '/'.join(ch1.split('/')[:-1] + [name])
plot(mags1_matched[galaxies],
mags2_matched[galaxies],
outpath,
'I1 [mag]',
'I2 [mag]',
plot_style=plot_style,
plot_type='mag-mag')
# stars
outpath = '/'.join(ch1.split('/')[:-1] + [name]).replace(
'galaxies', 'stars')
plot(mags1_matched[stars],
mags2_matched[stars],
outpath,
'I1 [mag]',
'I2 [mag]',
plot_style=plot_style,
plot_type='mag-mag')
def plot_spz_vs_wise_sdss_class(cat_path, plot_style='scatter'):
ch1 = list(find_files(cat_path, "*merged+sdss+wise.csv"))[::2]
ch2 = list(find_files(cat_path, "*merged+sdss+wise.csv"))[1::2]
for ch1, ch2 in zip(ch1, ch2):
reg1 = ch1.split('/')[-1].split('_')[0]
reg2 = ch2.split('/')[-1].split('_')[0]
assert reg1 == reg2
print("\nreading catalog: {}".format(ch1))
print("reading catalog: {}".format(ch2))
df1 = pd.read_csv(ch1)
df2 = pd.read_csv(ch2)
# convert to magnitudes
mags1 = spz_jy_to_mags(df1.flux*1e-3, 1)
mags2 = spz_jy_to_mags(df2.flux*1e-3, 2)
# match ch1 / ch2
idx1, idx2 = match_cats(df1, df2, tol=2/3600.)
# save matched catalogs
matched1 = df1.loc[idx1]
matched2 = df2.loc[idx2]
ch1_cols = [i+'_1' for i in df1.columns.tolist()]
ch2_cols = [i+'_2' for i in df2.columns.tolist()]
# matched1.columns = ch1_cols
# matched2.columns = ch2_cols
# matched = pd.concat([matched1, matched2], 1, ignore_index=True) # weird error
matched = np.concatenate([matched1.values, matched2.values], 1)
df_matched = pd.DataFrame(matched, columns=ch1_cols+ch2_cols)
df_matched['I1'] = mags1[idx1].values
df_matched['I2'] = mags2[idx2].values
outpath = '/'.join(ch1.split('/')[:-1])+'/{}_2ch_matched+sdss.csv'.format(reg1)
df_matched.to_csv(outpath, index=False, float_format='%.8f')
print("created file: {}".format(outpath))
# identify SDSS galaxies and stars
galaxies = (df1.cl[idx1].values == 3) & (df2.cl[idx2].values == 3)
stars = (df1.cl[idx1].values == 6) & (df2.cl[idx2].values == 6)
# plot I1-I2 vs. W1-W2
color1 = df1.W1mag[idx1].values - df2.W2mag[idx2].values
color2 = mags1[idx1].values - mags2[idx2].values
# galaxies
name = '{}_I1-I2_vs_W1-W2_galaxies_plot_style.png'.format(reg1)
name = name.replace('plot_style', plot_style)
outpath = '/'.join(ch1.split('/')[:-1]+[name])
plot(color1[galaxies], color2[galaxies], outpath, 'W1-W2 [mag]', 'I1-I2 [mag]',
plot_style=plot_style, plot_type='color-color')
# stars
outpath = '/'.join(ch1.split('/')[:-1]+[name]).replace('galaxies', 'stars')
plot(color1[stars], color2[stars], outpath, 'W1-W2 [mag]', 'I1-I2 [mag]',
plot_style=plot_style, plot_type='color-color')
# plot I1-W1 vs. I2-W2
color1 = mags1[idx1].values - df1.W1mag[idx1].values
color2 = mags2[idx2].values - df2.W2mag[idx2].values
# galaxies
name = '{}_I1-W1_vs_I2-W2_galaxies_plot_style.png'.format(reg1)
name = name.replace('plot_style', plot_style)
outpath = '/'.join(ch1.split('/')[:-1]+[name])
plot(color1[galaxies], color2[galaxies], outpath, 'I1-W1 [mag]', 'I2-W2 [mag]',
plot_style=plot_style, plot_type='color-color')
# stars
outpath = '/'.join(ch1.split('/')[:-1]+[name]).replace('galaxies', 'stars')
plot(color1[stars], color2[stars], outpath, 'I1-W1 [mag]', 'I2-W2 [mag]',
plot_style=plot_style, plot_type='color-color')
# plot spz color-magnitude diagrams
color = mags1[idx1].values - mags2[idx2].values
mags = mags1[idx1].values
# galaxies
name = '{}_I1_vs_I1-I2_galaxies_plot_style.png'.format(reg1)
name = name.replace('plot_style', plot_style)
outpath = '/'.join(ch1.split('/')[:-1]+[name])
plot(mags[galaxies], color[galaxies], outpath, 'I1 [mag]', 'I1-I2 [mag]',
plot_style=plot_style, plot_type='color-mag')
# stars
outpath = '/'.join(ch1.split('/')[:-1]+[name]).replace('galaxies', 'stars')
plot(mags[stars], color[stars], outpath, 'I1 [mag]', 'I1-I2 [mag]',
plot_style=plot_style, plot_type='color-mag')
# plot wise color-magnitude diagrams
color = df1.W1mag[idx1].values - df2.W2mag[idx2].values
mags = df1.W1mag[idx1].values
# galaxies
name = '{}_W1_vs_W1-W2_galaxies_plot_style.png'.format(reg1)
name = name.replace('plot_style', plot_style)
outpath = '/'.join(ch1.split('/')[:-1]+[name])
plot(mags[galaxies], color[galaxies], outpath, 'W1 [mag]', 'W1-W2 [mag]',
plot_style=plot_style, plot_type='color-mag')
# stars
outpath = '/'.join(ch1.split('/')[:-1]+[name]).replace('galaxies', 'stars')
plot(mags[stars], color[stars], outpath, 'W1 [mag]', 'W1-W2 [mag]',
plot_style=plot_style, plot_type='color-mag')
# plot I1 vs I2
mags1_matched = mags1[idx1].values
mags2_matched = mags2[idx2].values
# galaxies
name = '{}_I1_vs_I2_galaxies_plot_style.png'.format(reg1)
name = name.replace('plot_style', plot_style)
outpath = '/'.join(ch1.split('/')[:-1]+[name])
plot(mags1_matched[galaxies], mags2_matched[galaxies], outpath, 'I1 [mag]', 'I2 [mag]',
plot_style=plot_style, plot_type='mag-mag')
# stars
outpath = '/'.join(ch1.split('/')[:-1]+[name]).replace('galaxies', 'stars')
plot(mags1_matched[stars], mags2_matched[stars], outpath, 'I1 [mag]', 'I2 [mag]',
plot_style=plot_style, plot_type='mag-mag')