def make_2ch_catalogs(cat_tuple, tol=2 / 3600.0):
ch1, ch2 = cat_tuple
reg1 = ch1.split("/")[-1].split("_")[0]
reg2 = ch2.split("/")[-1].split("_")[0]
assert reg1 == reg2
df1 = pd.read_csv(ch1, sep=" ")
df2 = pd.read_csv(ch2, sep=" ")
idx1, idx2 = match_cats(df1, df2, tol=tol)
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 = np.concatenate([matched1.values, matched2.values], 1)
# df_matched = pd.DataFrame(matched, columns=ch1_cols+ch2_cols)
# df_matched[['n_obs_1', 'n_obs_2']] = df_matched[['n_obs_1', 'n_obs_2']].astype(int)
matched1.index = pd.Index(np.arange(matched1.shape[0]))
matched2.index = pd.Index(np.arange(matched2.shape[0]))
df_matched = pd.concat([matched1, matched2], 1)
out_path = "/".join(ch1.split("/")[:-2]) + "/{}_2ch_matched.csv".format(reg1)
df_matched.to_csv(out_path, index=False, float_format="%.8f")
print("created file: " + out_path)
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')
