Check the effect of the bugs in the code

Load the libraries


In [61]:
import numpy as np
from astropy.table import Table, join
import matplotlib.pyplot as plt

In [62]:
%matplotlib inline

Load the data


In [2]:
idp = "idata/main_pdf_v0.8-b"

In [18]:
idp_old = "idata/main_pdf_v0.8"

In [6]:
lnew = Table.read(idp+"/lofar_m5.fits")

In [19]:
lold = Table.read(idp_old+"/lofar_m5.fits")

In [20]:
merged = join(lnew, lold, keys=["Source_Name"], table_names=["new", "old"])

Check the shape of the data


In [21]:
len(lnew)


Out[21]:
91332

In [22]:
len(lold)


Out[22]:
91332

Compute the difference between the LR


In [65]:
diff_lr = merged['lr_5_old']-merged['lr_5_new']

In [66]:
len(diff_lr)


Out[66]:
91332

Explore the differences

Plot of the difference in LR with respect to the new LR


In [67]:
plt.plot(merged['lr_5_new'], diff_lr, marker=",", ls="")
plt.xlabel("LR (new)")
plt.ylabel("LR diff")


Out[67]:
Text(0,0.5,'LR diff')

Plot of the absolute difference in LR with respect to the new LR in log space.


In [68]:
plt.loglog(merged['lr_5_new'], np.abs(diff_lr), marker=",", ls="")
plt.xlabel("log LR (new)")
plt.ylabel("log abs. LR diff")


Out[68]:
Text(0,0.5,'log abs. LR diff')

Thresholds


In [38]:
told = 0.69787
tnew = 0.71684

Plot of the percentage of absolute difference in LR with respect to the new LR with the y axis in log space. Sources always below the threshold are plotted in orange.


In [77]:
cond_sel = ((merged['lr_5_old'] >= told) | (merged['lr_5_new'] >= tnew))
cond_nosel = ((merged['lr_5_old'] < told) & (merged['lr_5_new'] < tnew))
plt.semilogy(merged['lr_5_new'][cond_sel], (np.abs(diff_lr)/merged['lr_5_new']*100)[cond_sel], marker=",", ls="")
plt.semilogy(merged['lr_5_new'][cond_nosel], (np.abs(diff_lr)/merged['lr_5_new']*100)[cond_nosel], marker=",", ls="")
plt.xlabel("LR (new)")
plt.ylabel("log percent abs. LR diff")


Out[77]:
Text(0,0.5,'log percent abs. LR diff')
/disk2/jsm/prog/anaconda3/lib/python3.6/site-packages/matplotlib/scale.py:111: RuntimeWarning: invalid value encountered in less_equal
  out[a <= 0] = -1000

Plot of the percentage of absolute difference in LR with respect to the new LR in log space. Sources always below the threshold are plotted in orange and the galaxies that are not matched now are plotted as green crosses.


In [118]:
cond_sel = ((merged['lr_5_old'] >= told) | (merged['lr_5_new'] >= tnew)) & (~np.isnan(merged['category_old']))
cond_nosel = ((merged['lr_5_old'] < told) & (merged['lr_5_new'] < tnew)) & (~np.isnan(merged['category_old']))
cond_change = ((merged['lr_5_old'] >= told) & (merged['lr_5_new'] < tnew)) & (~np.isnan(merged['category_old']))
plt.loglog(merged['lr_5_new'][cond_sel], (np.abs(diff_lr)/merged['lr_5_new']*100)[cond_sel], marker=",", ls="", label="Selected")
plt.loglog(merged['lr_5_new'][cond_nosel], (np.abs(diff_lr)/merged['lr_5_new']*100)[cond_nosel], marker=",", ls="", label="Rejected")
plt.loglog(merged['lr_5_new'][cond_change], (np.abs(diff_lr)/merged['lr_5_new']*100)[cond_change], marker="x", ls="", label="Changes")
plt.xlabel("log LR (new)")
plt.ylabel("log percent abs. LR diff")
plt.legend()


Out[118]:
<matplotlib.legend.Legend at 0x7f204c1d0860>

The same plot than before but using the new threshol


In [100]:
# Use new threshold for old data as well
cond_sel = ((merged['lr_5_old'] >= tnew) | (merged['lr_5_new'] >= tnew))
cond_nosel = ((merged['lr_5_old'] < tnew) & (merged['lr_5_new'] < tnew))
cond_change = ((merged['lr_5_old'] >= tnew) & (merged['lr_5_new'] < tnew))
plt.loglog(merged['lr_5_new'][cond_sel], (np.abs(diff_lr)/merged['lr_5_new']*100)[cond_sel], marker=",", ls="", label="Selected")
plt.loglog(merged['lr_5_new'][cond_nosel], (np.abs(diff_lr)/merged['lr_5_new']*100)[cond_nosel], marker=",", ls="", label="Rejected")
plt.loglog(merged['lr_5_new'][cond_change], (np.abs(diff_lr)/merged['lr_5_new']*100)[cond_change], marker="x", ls="", label="Changes")
plt.xlabel("log LR (new)")
plt.ylabel("log percent abs. LR diff")
plt.legend()


Out[100]:
<matplotlib.legend.Legend at 0x7f204c26ae80>
/disk2/jsm/prog/anaconda3/lib/python3.6/site-packages/matplotlib/scale.py:111: RuntimeWarning: invalid value encountered in less_equal
  out[a <= 0] = -1000

Direct comparison of the LR of the sources that changed. Most of them are close to the threshold change but in 4 cases there are big differences.


In [99]:
cond_change = ((merged['lr_5_old'] >= told) & (merged['lr_5_new'] < tnew))
plt.subplot(1,2,1)
plt.semilogx(merged['lr_5_new'][cond_change], merged['lr_5_old'][cond_change], marker="x", ls="")
plt.xlabel("log LR (new)")
plt.ylabel("LR (old)")
plt.subplot(1,2,2)
plt.plot(merged['lr_5_new'][cond_change], merged['lr_5_old'][cond_change], marker="x", ls="")
plt.xlabel("LR (new)")
plt.ylabel("LR (old)")


Out[99]:
Text(0,0.5,'LR (old)')

Number of sources with respect to the thresholds


In [50]:
np.sum((merged['lr_5_old'] >= told) & (merged['lr_5_new'] >= tnew))


Out[50]:
67188

In [87]:
np.sum((merged['lr_5_old'] >= told) & (merged['lr_5_new'] < tnew))


Out[87]:
29

In [52]:
np.sum((merged['lr_5_old'] < told) & (merged['lr_5_new'] >= tnew))


Out[52]:
0

In [53]:
np.sum((merged['lr_5_old'] < told) & (merged['lr_5_new'] < tnew))


Out[53]:
24115

The percentage of changes due to the bug


In [102]:
4/91332*100


Out[102]:
0.004379625979941313

In [105]:
cond_change = ((merged['lr_5_old'] >= told) & (merged['lr_5_new'] < tnew) & (np.abs(diff_lr)/merged['lr_5_new']*100 > 10))

In [106]:
merged[cond_change]


Out[106]:
<Table masked=True length=4>
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In [129]:
cond = (np.abs(diff_lr)/merged['lr_5_new']*100 > 10)

In [130]:
merged[cond]
# ['Source_Name','ML_LR_new','AllWISE_new',
#  'objID_new','category_new','W1mag_new','i_new','lr_index_5_new',
#  'lr_dist_5_new','lr_5_new','lr_index_sel_5_new','ML_LR_old','AllWISE_old',
#  'objID_old','category_old','W1mag_old','i_old','lr_index_5_old',
#  'lr_dist_5_old','lr_5_old','lr_index_sel_5_old']


Out[130]:
<Table masked=True length=62>
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ILTJ113141.95+492751.7172.92480911263240.594190720579336249.464372260152250.41293189389594530.413697474341384260.066114393147501170.48385830517596730.111457216889961918.0188733288446751.55749903566474655.2518865493474320.69060098464563495.3186849912822631.55749903566474650.00.6906009846456349118.0155816094212317.32622884118737118.0155816094219317.326228841187370.06601797940675169SP14Hetdex040.01nannannannannannannannannan--nannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannanFalsenannannannannannannannannannannannannannannannannan0.04.915840896960747433812.0nan0.0nannannannannannan0nannannan433812.04.9158408969607473.201571947139515e-13nan433812.04.9158408969607471.0787729161198615e-11nan433812.04.9158408969607473.595184070922353e-11nan433812.04.9158408969607476.410450193837766e-11nan172.92480911263240.594190720579336249.464372260152250.41293189389594530.413697474341384260.066114393147501170.48385830517596730.111457216889961918.0188733288446751.55749903566474655.2518865493474320.69060098464563495.3186849912822631.55749903566474650.00.6906009846456349118.0155816094212317.32622884118737118.0155816094219317.326228841187370.06601797940675169SP14Hetdex040.01nannannannannannannannannan--nannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannanFalsenannannannannannannannannannannannannannannannannan1.2100536132110481e-084.915840896960747433812.0nan0.0nannannannannannan0nannannan433812.04.9158408969607478.932808776740174e-10nan433812.04.9158408969607475.440198799814542e-10nan433812.04.9158408969607472.600694875728209e-10nan433812.04.9158408969607477.656632384190046e-11nan
.....................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................
ILTJ122457.12+500558.6186.237994437765020.593477411769482850.099621138990120.6021482100685580.345817095295450740.06437912281252160.50140663994880310.099853564228055298.1399751778914771.67062549637285756.413109940288571.08295361178187065.5007667490883151.67062549637285752.26300079696855061.0829536117818706135.126628880521235.17128540009035135.1266288805223635.171285400090350.06082066101953387SP26Hetdex030.01nannannannannannannannannan--nannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannanFalsenannannannannannannannannannannannannannannannannan5.964445504847836e-169.5823938507205752105614.0nan0.0nannannannannannan0nannannan2105614.09.5823938507205751.2737823325070743e-16nan2105614.09.5823938507205751.1945277155040809e-16nan2105614.09.5823938507205751.1857538840960523e-16nan2105614.09.5823938507205751.1857113180282023e-16nan186.237994437765020.593477411769482850.099621138990120.6021482100685580.345817095295450740.06437912281252160.50140663994880310.099853564228055298.1399751778914771.67062549637285756.413109940288571.08295361178187065.5007667490883151.67062549637285752.26300079696855061.0829536117818706135.126628880521235.17128540009035135.1266288805223635.171285400090350.06082066101953387SP26Hetdex030.01nannannannannannannannannan--nannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannanFalsenannannannannannannannannannannannannannannannannan1.100168985814171e-118.688933455052672062972.0nan0.0nannannannannannan0nannannan2062972.08.688933455052671.3943844352394215e-12nan2062972.08.688933455052671.0656127037963843e-12nan2062972.08.688933455052671.0585875790945938e-12nan2062972.08.688933455052671.0290247499580389e-12nan
ILTJ122458.51+482655.7186.243796686605780.529667059775106248.4488206959697150.28525486644387970.316066800810473060.051879998454432760.2599172752479180.098415754381008976.43558408873243251.26967372233060854.6010662918306150.62834255685623420.01.26967372233060850.00.6283425568562342103.1267146964553123.3520587700041130.023.3520587700041130.05602557212114334SP23Hetdex200.01nannannannannannannannannan--nannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannanFalsenannannannannannannannannannannannannannannannannan3.862448507718518e-5412.0232058790667281835606.0nan2.6015448382969307e-5312.0232058790667281835606.0nannannannan0nannannan1835853.09.2443329857625492.423003668736005e-35nan1835853.09.2443329857625493.625585826537212e-31nan1835853.09.2443329857625497.293775266283799e-30nan1835853.09.2443329857625494.3522189076828753e-29nan186.243796686605780.529667059775106248.4488206959697150.28525486644387970.316066800810473060.051879998454432760.2599172752479180.098415754381008976.43558408873243251.26967372233060854.6010662918306150.62834255685623420.01.26967372233060850.00.6283425568562342103.1267146964553123.3520587700041130.023.3520587700041130.05602557212114334SP23Hetdex200.01nannannannannannannannannan--nannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannanFalsenannannannannannannannannannannannannannannannannan2.0903594127526636e-199.2443329857625491835853.0nan2.499303113325556e-5312.0232058790667281835606.0nannannannan0nannannan1835853.09.2443329857625493.2800081116621207e-20nan1835853.09.2443329857625493.2411434095939e-20nan1835853.09.2443329857625493.2411320093648386e-20nan1835853.09.2443329857625493.240955161368489e-20nan
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ILTJ122603.92+485545.1186.516351999327920.346329744455627548.929215495635870.23142318109907610.486889724984783940.054640794287747450.47717145585967690.09593769730023826.5670596354031860.81557324993386755.3733114936854960.54490750880533010.00.81557324993386750.00.544907508805330189.6875540140970224.1849964097559140.024.1849964097559140.05533658622880466SP26Hetdex030.591nannannannannannannannannan--nannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannanFalsenannannannannannannannannannannannannannannannannan1.534020591502206e-5912.468676081546771897077.0nan2.8239507399695072e-5912.468676081546771897077.0nannannannan0nannannan1897184.07.88027542576066151.1411829554220124e-38nan1897184.07.88027542576066155.619628101288247e-35nan1897184.07.88027542576066158.31474651250763e-34nan1897184.07.88027542576066153.9677659849396246e-33nan186.516351999327920.346329744455627548.929215495635870.23142318109907610.486889724984783940.054640794287747450.47717145585967690.09593769730023826.5670596354031860.81557324993386755.3733114936854960.54490750880533010.00.81557324993386750.00.544907508805330189.6875540140970224.1849964097559140.024.1849964097559140.05533658622880466SP26Hetdex030.591nannannannannannannannannan--nannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannanFalsenannannannannannannannannannannannannannannannannan2.313080799842532e-257.88027542576066151897184.0nan2.6724138992103496e-5912.468676081546771897077.0nannannannan0nannannan1897184.07.88027542576066153.947696232834154e-26nan1897184.07.88027542576066153.743339796910367e-26nan1897184.07.88027542576066153.7430131171314537e-26nan1897184.07.88027542576066153.7399404016599675e-26nan
ILTJ122806.71+474427.5187.02794247613650.3563237549644723347.740993094292130.283234167711319150.445456868246358160.058441478480178510.398955070066058740.105414410336780176.0551945494927240.84981975429862325.3258390799711010.65316122858061760.00.84981975429862320.00.6531612285806176105.6643056728651145.242168553064090.045.242168553064090.060396640037652105SP23Hetdex200.01nannannannannannannannannan--nannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannanFalsenannannannannannannannannannannannannannannannannan0.013.5234113519883331658801.0nan0.0nannannannannannan0nannannan1658801.013.5234113519883331.36525655998337e-76nan1658801.013.5234113519883334.403654268360265e-75nan1658801.013.5234113519883331.4444517105772218e-74nan1658801.013.5234113519883332.5518045514525142e-74nan187.02794247613650.3563237549644723347.740993094292130.283234167711319150.445456868246358160.058441478480178510.398955070066058740.105414410336780176.0551945494927240.84981975429862325.3258390799711010.65316122858061760.00.84981975429862320.00.6531612285806176105.6643056728651145.242168553064090.045.242168553064090.060396640037652105SP23Hetdex200.01nannannannannannannannannan--nannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannanFalsenannannannannannannannannannannannannannannannannan4.4964190980885443e-7213.5234113519883331658801.0nan0.0nannannannannannan0nannannan1658801.013.5234113519883333.3394179314769016e-73nan1658801.013.5234113519883332.041141276292504e-73nan1658801.013.5234113519883339.689543709748526e-74nan1658801.013.5234113519883332.968853071710144e-74nan
ILTJ122856.93+482611.3187.23720127350290.1651397549553493348.43647171329330.185300652950943450.8030191117875270.0559754815977575660.77830961432235210.098033304802725966.0869355822788850.437249812281970635.7338314701045550.38784475540158990.00.437249812281970630.00.38784475540158998.17691575307302248.698971348254860.048.698971348254860.05646237696055323SP26Hetdex031.01nannannannannannannannannan--nannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannanFalsenannannannannannannannannannannannannannannannannan1.7589653244281253e-10314.4792969607175871821077.0nan5.200012714544903e-10314.4792969607175871821077.0nannannannan0nannannan1821043.06.7502584015604214.814439119912543e-31nan1821043.06.7502584015604212.587871625148471e-28nan1821043.06.7502584015604212.0595323447878427e-27nan1821043.06.7502584015604216.341085663050734e-27nan187.23720127350290.1651397549553493348.43647171329330.185300652950943450.8030191117875270.0559754815977575660.77830961432235210.098033304802725966.0869355822788850.437249812281970635.7338314701045550.38784475540158990.00.437249812281970630.00.38784475540158998.17691575307302248.698971348254860.048.698971348254860.05646237696055323SP26Hetdex031.01nannannannannannannannannan--nannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannanFalsenannannannannannannannannannannannannannannannannan3.4223324601356416e-226.7502584015604211821043.0nan5.360852413435648e-10314.4792969607175871821077.0nannannannan0nannannan1821043.06.7502584015604213.64180445874232e-23nan1821043.06.7502584015604212.496131920995703e-23nan1821043.06.7502584015604212.4438116145424056e-23nan1821043.06.7502584015604212.2732150107541296e-23nan
ILTJ123025.53+551006.9187.606393938212020.712719085356479855.168604286493290.462889716916020160.454581643601129740.081651100905644150.53063231198688240.138844634741198858.2794236546565081.86441901008374015.0757411689274640.72720415469938480.01.86441901008374010.00.7272041546993848118.6708046212424819.0450224574403180.019.0450224574403180.082471473433543SP187+551.01nannannannannannannannannan--nannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannanFalsenannannannannannannannannannannannannannannannannan0.09.6583641476561762790574.0nan0.0nannannannannannan0nannannan2790574.09.6583641476561763.0284628124665625e-20nan2790574.09.6583641476561769.317305687310864e-18nan2790574.09.6583641476561766.301873181691462e-17nan2790574.09.6583641476561761.7392844167088866e-16nan187.606393938212020.712719085356479855.168604286493290.462889716916020160.454581643601129740.081651100905644150.53063231198688240.138844634741198858.2794236546565081.86441901008374015.0757411689274640.72720415469938480.01.86441901008374010.00.7272041546993848118.6708046212424819.0450224574403180.019.0450224574403180.082471473433543SP187+551.01nannannannannannannannannan--nannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannanFalsenannannannannannannannannannannannannannannannannan2.270957431860298e-129.6583641476561762790574.0nan0.0nannannannannannan0nannannan2790574.09.6583641476561761.9644266881826352e-13nan2790574.09.6583641476561761.1847011918828074e-13nan2790574.09.6583641476561761.1043873867839741e-13nan2790574.09.6583641476561769.091057190231567e-14nan
ILTJ123313.65+500715.8188.30688403340220.442087769536141650.121054597526980.37846667649050280.32262458563657040.0537279893348625650.284297906037039860.097746590723241856.1532218338699791.12557463819477075.1559361189133810.78170350361549530.01.12557463819477070.00.7817035036154953122.5960869286934441.942568037707530.041.942568037707530.05594531467068009SP26Hetdex030.01nannannannannannannannannan--nannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannanFalsenannannannannannannannannannannannannannannannannan1.98540326696389e-5414.0384845789409452089950.0nan2.0054100850573144e-148.3675662138238723261536.0nannannannan0nannannan2090346.02.83237443007943369.998834690369575e-07nan2090346.02.83237443007943365.6922707644724104e-05nan2090346.02.83237443007943360.00022708774148264604nan2090346.02.83237443007943360.00044979959365673376nan188.30688403340220.442087769536141650.121054597526980.37846667649050280.32262458563657040.0537279893348625650.284297906037039860.097746590723241856.1532218338699791.12557463819477075.1559361189133810.78170350361549530.01.12557463819477070.00.7817035036154953122.5960869286934441.942568037707530.041.942568037707530.05594531467068009SP26Hetdex030.01nannannannannannannannannan--nannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannanFalsenannannannannannannannannannannannannannannannannan0.191114918415942972.83237443007943362090346.0nan2.675056851494045e-148.3675662138238723261536.0nannannannan0nannannan2090346.02.83237443007943360.01330853427385871nan2090346.02.83237443007943360.007757128984946877nan2090346.02.83237443007943360.004223814401760173nan2090346.02.83237443007943360.0010414013131104477nan
ILTJ123506.25+494857.4188.776057659040930.263084907279764449.815950396161910.292074532450741050.57766013148757840.056529541899544440.71082482237678620.091655865057949866.9056003379862310.69852256776037376.4156882328658570.60739385558165913.41857901338360830.69852256776037372.27003683983493240.607393855581659121.69027361631141257.0309331224144621.6902736163083757.030933122414460.054161173466127366SP26Hetdex030.831nannannannannannannannannan--nannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannanFalsenannannannannannannannannannannannannannannannannan7.053896029855569e-258.1360495799318522036988.0nan8.223118988162485e-3512.5281966778313533382711.0nannannannan0nannannan2037077.06.2018500339755067.691698351585467e-21nan2037077.06.2018500339755064.712938727318505e-19nan2037077.06.2018500339755061.9262171073812702e-18nan2037077.06.2018500339755063.8703845505061035e-18nan188.776057659040930.263084907279764449.815950396161910.292074532450741050.57766013148757840.056529541899544440.71082482237678620.091655865057949866.9056003379862310.69852256776037376.4156882328658570.60739385558165913.41857901338360830.69852256776037372.27003683983493240.607393855581659121.69027361631141257.0309331224144621.6902736163083757.030933122414460.054161173466127366SP26Hetdex030.831nannannannannannannannannan--nannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannanFalsenannannannannannannannannannannannannannannannannan1.8503863466181304e-156.2018500339755062037077.0nan1.110012555816419e-3412.5281966778313533382711.0nannannannan0nannannan2037077.06.2018500339755061.280854935365038e-16nan2037077.06.2018500339755067.417114758748095e-17nan2037077.06.2018500339755064.1355930553235685e-17nan2037077.06.2018500339755061.0454595746875863e-17nan
ILTJ123656.85+492215.0189.236878737380070.692225911626974149.370851829534120.82249484989879550.244836309602639220.061545410737977580.33794069450498010.096434122990372217.4454961301577791.95979536888809146.6753823429514421.60250265482288934.4080149744203261.95979536888809142.9237870529430071.602502654822889316.602343433894024100.4765137179659416.60234343389262100.476513717965940.058019391872221604SP26Hetdex030.01nannannannannannannannannan--nannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannanFalsenannannannannannannannannannannannannannannannannan0.07.9640440149972461947918.0nan0.0nannannannannannan0nannannan1947918.07.9640440149972461.9022807926647778e-14nan1947918.07.9640440149972462.3688216581132465e-12nan1947918.07.9640440149972461.2175800316600596e-11nan1947918.07.9640440149972462.815356805108469e-11nan189.236878737380070.692225911626974149.370851829534120.82249484989879550.244836309602639220.061545410737977580.33794069450498010.096434122990372217.4454961301577791.95979536888809146.6753823429514421.60250265482288934.4080149744203261.95979536888809142.9237870529430071.602502654822889316.602343433894024100.4765137179659416.60234343389262100.476513717965940.058019391872221604SP26Hetdex030.01nannannannannannannannannan--nannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannannanFalsenannannannannannannannannannannannannannannannannan4.9988573961243314e-087.9640440149972461947918.0nan0.0nannannannannannan0nannannan1947918.07.9640440149972463.4644686989373994e-09nan1947918.07.9640440149972461.903980584596411e-09nan1947918.07.9640440149972461.3970104092798935e-09nan1947918.07.9640440149972466.567335287065512e-10nan

In [136]:
cond = (np.abs(diff_lr)/merged['lr_5_new']*100 > 1)
merged[cond & (merged['lr_5_old'] >= told)]['Source_Name','ML_LR_new','AllWISE_new',
  'objID_new','category_new','W1mag_new','i_new','lr_index_5_new',
  'lr_dist_5_new','lr_5_new','lr_index_sel_5_new','ML_LR_old','AllWISE_old', 
  'objID_old','category_old','W1mag_old','i_old','lr_index_5_old',
  'lr_dist_5_old','lr_5_old','lr_index_sel_5_old']


Out[136]:
<Table masked=True length=165>
Source_NameML_LR_newAllWISE_newobjID_newcategory_newW1mag_newi_newlr_index_5_newlr_dist_5_newlr_5_newlr_index_sel_5_newML_LR_oldAllWISE_oldobjID_oldcategory_oldW1mag_oldi_oldlr_index_5_oldlr_dist_5_oldlr_5_oldlr_index_sel_5_old
str22float64str19int64float64float64float64float64float64float64float64float64str19int64float64float64float64float64float64float64float64
ILTJ112016.73+525526.1nan--2.014.37030261311520513.5223434127720151008170.01.5632381792519651.21439729195597111008170.0nan--2.014.37030261311520513.5223434127720151008170.01.5632381792519651.19201817030967061008170.0
ILTJ112021.43+554135.418.712744116837648J112021.43+554136.11748317008955027293.020.50482851881369220.999441621514891372193.00.66737350591498515.3411999291098591372193.018.712744116837648J112021.43+554136.11748317008955027293.020.50482851881369220.999441621514891372193.00.66737350591498515.6293741903113851372193.0
ILTJ112141.49+535249.4nan--2.015.78360550182698915.6894785573557561119593.02.07384782536835250.95914833027007111119593.0nan--2.015.78360550182698915.6894785573557561119593.02.07384782536835251.0263899083490051119593.0
ILTJ112234.48+492305.39.949187804478631J112234.44+492306.11672617064361425362.019.7901888121939419.753938108930445434969.00.256681869990647359.1180466041256434969.09.949187804478631J112234.44+492306.11672617064361425362.019.7901888121939419.753938108930445434969.00.256681869990647358.90432464264227434969.0
ILTJ112244.04+524817.04.449101983104592J112243.93+524815.71713617068299859203.020.31431010213407620.724413669317432977423.01.61751202028189336.06540552509655977423.04.449101983104592J112243.93+524815.71713617068299859203.020.31431010213407620.724413669317432977423.01.61751202028189336.147968694289568977423.0
ILTJ112249.37+533312.52.32587743394617J112249.25+533311.51722617070532544293.017.0024470423890717.279942812813671073080.01.541925265971359110.2849008406640771073080.02.32587743394617J112249.25+533311.51722617070532544293.017.0024470423890717.279942812813671073080.01.541925265971359110.4474429031430221073080.0
ILTJ112251.22+512601.44.820976155770548J112251.16+512601.01697217071316310783.020.71386177573276321.05036419190562797699.00.74526477627678796.369486152957047797699.04.820976155770548J112251.16+512601.01697217071316310783.020.71386177573276321.05036419190562797699.00.74526477627678796.494068032057322797699.0
ILTJ112308.82+492150.99.289887691940335J112308.81+492151.31672317078663277622.019.66630618955536419.549675942638018464940.00.33042756545136528.898929305167043464940.09.289887691940335J112308.81+492151.31672317078663277622.019.66630618955536419.549675942638018464940.00.33042756545136528.690343331797264464940.0
ILTJ112350.77+465114.13.5945271838763024J112350.73+465115.21642217096139656802.017.27272321532696617.13072282231277325384.00.96148775889374442.102655143731181625384.03.5945271838763024J112350.73+465115.21642217096139656802.017.27272321532696617.13072282231277325384.00.96148775889374442.066284480365048625384.0
ILTJ112437.64+504333.35.920054482528448J112437.61+504333.01688717115677816252.018.7697095213014718.72538906232106659914.00.46627438679698057.332298950173795659914.05.920054482528448J112437.61+504333.01688717115677816252.018.7697095213014718.72538906232106659914.00.46627438679698057.160434011306427659914.0
...............................................................
ILTJ123458.23+522246.8nan--2.019.1172341429877118.088279249959442467062.01.6352796046639871.05834526425207142467062.0nan--2.019.1172341429877118.088279249959442467062.01.6352796046639871.03354496345378262467062.0
ILTJ123539.02+521742.36.179274803115211J123539.12+521741.41707518891285646663.020.3087564722460420.7855443947786972417120.00.88592505168677458.6733790568293262417120.06.179274803115211J123539.12+521741.41707518891285646663.020.3087564722460420.7855443947786972417120.00.88592505168677458.8021753113736422417120.0
ILTJ123604.64+521224.32.569103848687789J123604.71+521224.41706418901972789822.018.53945911626376718.402041752595142394001.01.11753975551561123.07570167055122172394001.02.569103848687789J123604.71+521224.41706418901972789822.018.53945911626376718.402041752595142394001.01.11753975551561123.0036099731595662394001.0
ILTJ123639.80+524843.111.640610733994187J123639.80+524843.41713718916586551973.016.3602967442471316.848186575560512489701.00.3982870064569525339.739627767780952489701.011.640610733994187J123639.80+524843.41713718916586551973.016.3602967442471316.848186575560512489701.00.3982870064569525340.2553217627217142489701.0
ILTJ123716.84+505730.712.053328787327686N/A1691518932065611531.0nan24.7028662995982882231847.00.40675972714353583.84336696819267452231847.012.053328787327686N/A1691518932065611531.0nan24.7028662995982882231847.00.40675972714353583.95423832276270962231847.0
ILTJ123720.04+535303.11.7535082268131719J123719.88+535304.31726618933338521512.017.2659289618480117.2080194058793232622610.01.21932420362565330.99203611600274222622610.01.7535082268131719J123719.88+535304.31726618933338521512.017.2659289618480117.2080194058793232622610.01.21932420362565330.97276758059134862622610.0
ILTJ123847.90+544435.62.3199577730709224N/A1736918969977629331.0nan24.6483504447037522740242.01.34740128532019150.78154811715957212740242.02.3199577730709224N/A1736918969977629331.0nan24.6483504447037522740242.01.34740128532019150.80174979850918062740242.0
ILTJ123859.40+480308.311.392217119148832J123859.39+480308.21656618974747734192.018.06667822067175417.825486440169941742856.00.0778337428936558611.0179086670825261742856.011.392217119148832J123859.39+480308.21656618974747734192.018.06667822067175417.825486440169941742856.00.0778337428936558610.7602893985529191742856.0
ILTJ123919.92+491558.823.70394819237619J123919.94+491558.91671218983309702573.017.3632103313768717.654047233780011955889.00.09741628569698692100.802238624952761955889.023.70394819237619J123919.94+491558.91671218983309702573.017.3632103313768717.654047233780011955889.00.09741628569698692101.885618543564061955889.0
ILTJ123940.46+505008.2nan--2.019.51134335905314618.6467370728380432252693.01.61816232077529841.0806899771802842252693.0nan--2.019.51134335905314618.6467370728380432252693.01.61816232077529841.05535923326173542252693.0

In [138]:
cond = (np.abs(diff_lr)/merged['lr_5_new']*100 > 1)
merged[cond & (merged['lr_5_old'] >= told) & (merged['lr_index_5_old'] != merged['lr_index_5_new'])]['Source_Name','ML_LR_new','AllWISE_new',
  'objID_new','category_new','W1mag_new','i_new','lr_index_5_new',
  'lr_dist_5_new','lr_5_new','lr_index_sel_5_new','ML_LR_old','AllWISE_old', 
  'objID_old','category_old','W1mag_old','i_old','lr_index_5_old',
  'lr_dist_5_old','lr_5_old','lr_index_sel_5_old']


Out[138]:
<Table masked=True length=1>
Source_NameML_LR_newAllWISE_newobjID_newcategory_newW1mag_newi_newlr_index_5_newlr_dist_5_newlr_5_newlr_index_sel_5_newML_LR_oldAllWISE_oldobjID_oldcategory_oldW1mag_oldi_oldlr_index_5_oldlr_dist_5_oldlr_5_oldlr_index_sel_5_old
str22float64str19int64float64float64float64float64float64float64float64float64str19int64float64float64float64float64float64float64float64
ILTJ114909.78+494632.8nan--nannannan491914.07.2246091032680760.0010002481805411474nannan--0.012.810946568452223nan3391544.03.54706658943994053.44574380692324363391544.0

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