DR12Q catalog prep creation

First import all the modules such as healpy and astropy needed for analyzing the structure



In [98]:

    
import healpix_util as hu
import astropy as ap
import numpy as np
from astropy.io import fits
from astropy.table import Table
import astropy.io.ascii as ascii
from astropy.io import fits
from astropy.constants import c
import matplotlib.pyplot as plt
import math
import scipy.special as sp
from astroML.decorators import pickle_results
from scipy import integrate
import pymangle
from scipy.optimize import curve_fit
from scipy.constants import pi
import pickle
import pymangle
#from astroML.datasets import fetch_sdss_specgals
#from astroML.correlation import bootstrap_two_point_angular
%matplotlib inline

Read the ply data file mangle polygons

Ref: https://pypi.python.org/pypi/pymangle/



In [2]:

    
dat=fits.open("./input/DR12Q.fits")



In [3]:

    
dat=dat[1].data



In [4]:

    
z=dat['Z_PIPE']



In [5]:

    
z









    Out[5]:





array([ 2.30909729,  2.49794078,  1.61884606, ...,  2.45101476,
        3.11339068,  2.39766693], dtype=float32)



In [6]:

    
len(z)









    Out[6]:





297301



In [7]:

    
np.histogram(z)









    Out[7]:





(array([ 14382,  48309,  42650, 139641,  42945,   7698,   1116,    271,
           175,    114]),
 array([ -4.94136522e-03,   6.96677249e-01,   1.39829586e+00,
          2.09991448e+00,   2.80153309e+00,   3.50315170e+00,
          4.20477032e+00,   4.90638893e+00,   5.60800755e+00,
          6.30962616e+00,   7.01124477e+00]))



In [8]:

    
plt.hist(z)









    Out[8]:





(array([  1.43820000e+04,   4.83090000e+04,   4.26500000e+04,
          1.39641000e+05,   4.29450000e+04,   7.69800000e+03,
          1.11600000e+03,   2.71000000e+02,   1.75000000e+02,
          1.14000000e+02]),
 array([ -4.94136522e-03,   6.96677249e-01,   1.39829586e+00,
          2.09991448e+00,   2.80153309e+00,   3.50315170e+00,
          4.20477032e+00,   4.90638893e+00,   5.60800755e+00,
          6.30962616e+00,   7.01124477e+00]),
 <a list of 10 Patch objects>)



In [10]:

    
print min(z)
print max(z)









    



-0.00494137
7.01124



In [16]:

    
bin1=dat[(dat['Z_PIPE']<1.39829586) & (dat['Z_PIPE']>=6.96677249e-01)]



In [15]:

    
len(dat)









    Out[15]:





297301



In [17]:

    
len(bin1)









    Out[17]:





48309



In [18]:

    
z=bin1['Z_PIPE']



In [19]:

    
ra=bin1['RA']



In [20]:

    
dec=bin1['DEC']



In [22]:

    
from scipy.constants import pi



In [23]:

    
dr12Qz1f = open("./output/DR12Qbin1.dat",'w')
dr12Qz1f.write("z\t rar\t decr \n")

for i in range(0,len(z)):
    dr12Qz1f.write("%f\t " %z[i])
    dr12Qz1f.write("%f\t %f\n " %(ra[i]*pi/180.0,dec[i]*pi/180.0))
dr12Qz1f.close()



In [122]:

    
bin1=ascii.read("./output/DR12Qbin1.dat")



In [123]:

    
z=bin1['z']
rar=bin1['rar']
decr=bin1['decr']



In [124]:

    
dat1=np.array([z,rar,decr])



In [125]:

    
dat1









    Out[125]:





array([[  1.36035800e+00,   1.13454400e+00,   8.35325000e-01, ...,
          7.86509000e-01,   8.35873000e-01,   1.19725300e+00],
       [  9.30000000e-05,   6.82000000e-04,   7.58000000e-04, ...,
          6.28274400e+00,   6.28277000e+00,   6.28307200e+00],
       [ -3.54870000e-02,   2.43272000e-01,  -1.42169000e-01, ...,
          2.60439000e-01,   1.59740000e-01,   3.69546000e-01]])



In [126]:

    
dat1=dat1.transpose()



In [127]:

    
dat1









    Out[127]:





array([[  1.36035800e+00,   9.30000000e-05,  -3.54870000e-02],
       [  1.13454400e+00,   6.82000000e-04,   2.43272000e-01],
       [  8.35325000e-01,   7.58000000e-04,  -1.42169000e-01],
       ..., 
       [  7.86509000e-01,   6.28274400e+00,   2.60439000e-01],
       [  8.35873000e-01,   6.28277000e+00,   1.59740000e-01],
       [  1.19725300e+00,   6.28307200e+00,   3.69546000e-01]])



In [128]:

    
# Getting back the objects:
with open('./output/DR12Qbin1.pkl','w') as f:  # Python 3: open(..., 'rb')
    pickle.dump(dat1,f)
dat1









    Out[128]:





array([[  1.36035800e+00,   9.30000000e-05,  -3.54870000e-02],
       [  1.13454400e+00,   6.82000000e-04,   2.43272000e-01],
       [  8.35325000e-01,   7.58000000e-04,  -1.42169000e-01],
       ..., 
       [  7.86509000e-01,   6.28274400e+00,   2.60439000e-01],
       [  8.35873000e-01,   6.28277000e+00,   1.59740000e-01],
       [  1.19725300e+00,   6.28307200e+00,   3.69546000e-01]])



In [129]:

    
# Getting back the objects:
with open('./output/DR12Qbin1.pkl') as f:  # Python 3: open(..., 'rb')
    dat1 = pickle.load(f)
dat1









    Out[129]:





array([[  1.36035800e+00,   9.30000000e-05,  -3.54870000e-02],
       [  1.13454400e+00,   6.82000000e-04,   2.43272000e-01],
       [  8.35325000e-01,   7.58000000e-04,  -1.42169000e-01],
       ..., 
       [  7.86509000e-01,   6.28274400e+00,   2.60439000e-01],
       [  8.35873000e-01,   6.28277000e+00,   1.59740000e-01],
       [  1.19725300e+00,   6.28307200e+00,   3.69546000e-01]])



In [130]:

    
len(dat1)









    Out[130]:





48309



In [131]:

    
len(dat1)









    Out[131]:





48309



In [ ]:



In [132]:

    
bin1









    Out[132]:




<Table length=48309>

z rar decr
float64 float64 float64
1.360358 9.3e-05 -0.035487
1.134544 0.000682 0.243272
0.835325 0.000758 -0.142169
0.752729 0.000782 -0.099872
0.896221 0.000918 -0.082249
0.882033 0.001199 0.042834
0.702284 0.001299 0.240805
1.301611 0.001425 0.021841
0.704229 0.001539 0.236405
0.840221 0.001691 0.339623
... ... ...
0.761227 6.281947 0.510654
0.864865 6.282053 -0.055125
0.854921 6.282082 0.454166
0.752217 6.282573 0.223546
0.813033 6.282579 -0.087908
1.172096 6.282584 -0.027623
0.979325 6.282665 0.288813
0.786509 6.282744 0.260439
0.835873 6.28277 0.15974
1.197253 6.283072 0.369546



In [ ]:



In [26]:

    
bin2=dat[(dat['Z_PIPE']<2.09991448) & (dat['Z_PIPE']>=1.39829586)]



In [27]:

    
len(bin2)









    Out[27]:





42650



In [28]:

    
z=bin2['Z_PIPE']



In [29]:

    
ra=bin2['RA']



In [30]:

    
dec=bin2['DEC']



In [31]:

    
dr12Qz2f = open("./output/DR12Qbin2.dat",'w')
dr12Qz2f.write("z\t rar\t decr \n")

for i in range(0,len(z)):
    dr12Qz2f.write("%f\t " %z[i])
    dr12Qz2f.write("%f\t %f\n " %(ra[i]*pi/180.0,dec[i]*pi/180.0))
dr12Qz2f.close()



In [34]:

    
bin2=ascii.read("./output/DR12Qbin2.dat")



In [35]:

    
bin2









    Out[35]:




<Table length=42650>

z rar decr
float64 float64 float64
1.618846 7.1e-05 0.084296
1.576134 0.000149 0.605257
1.710103 0.000157 0.266244
1.833563 0.000239 0.19133
2.001412 0.000373 0.150584
2.0892 0.000401 -0.096075
1.640517 0.00042 -0.075666
2.004653 0.000488 0.529287
1.545614 0.000513 0.105756
1.615499 0.000626 -0.178954
... ... ...
1.869809 6.282173 0.574029
1.605174 6.282174 0.534793
2.078732 6.282216 0.587197
1.852452 6.282393 0.301937
1.700308 6.282434 0.289916
1.762858 6.282488 0.189745
1.639977 6.282548 0.424658
1.621909 6.282646 -0.073565
1.569409 6.282703 -0.077083
1.849221 6.28282 0.033848



In [ ]:



In [73]:

    
bin2=ascii.read("./output/DR12Qbin2.dat")



In [74]:

    
z=bin2['z']
rar=bin2['rar']
decr=bin2['decr']



In [75]:

    
dat2=np.array([z,rar,decr])



In [76]:

    
dat2









    Out[76]:





array([[  1.61884600e+00,   1.57613400e+00,   1.71010300e+00, ...,
          1.62190900e+00,   1.56940900e+00,   1.84922100e+00],
       [  7.10000000e-05,   1.49000000e-04,   1.57000000e-04, ...,
          6.28264600e+00,   6.28270300e+00,   6.28282000e+00],
       [  8.42960000e-02,   6.05257000e-01,   2.66244000e-01, ...,
         -7.35650000e-02,  -7.70830000e-02,   3.38480000e-02]])



In [77]:

    
dat2=dat2.transpose()



In [78]:

    
dat2









    Out[78]:





array([[  1.61884600e+00,   7.10000000e-05,   8.42960000e-02],
       [  1.57613400e+00,   1.49000000e-04,   6.05257000e-01],
       [  1.71010300e+00,   1.57000000e-04,   2.66244000e-01],
       ..., 
       [  1.62190900e+00,   6.28264600e+00,  -7.35650000e-02],
       [  1.56940900e+00,   6.28270300e+00,  -7.70830000e-02],
       [  1.84922100e+00,   6.28282000e+00,   3.38480000e-02]])



In [120]:

    
len(dat2)









    Out[120]:





42650



In [79]:

    
# Getting back the objects:
with open('./output/DR12Qbin2.pkl','w') as f:  # Python 3: open(..., 'rb')
    pickle.dump(dat2,f)
dat2









    Out[79]:





array([[  1.61884600e+00,   7.10000000e-05,   8.42960000e-02],
       [  1.57613400e+00,   1.49000000e-04,   6.05257000e-01],
       [  1.71010300e+00,   1.57000000e-04,   2.66244000e-01],
       ..., 
       [  1.62190900e+00,   6.28264600e+00,  -7.35650000e-02],
       [  1.56940900e+00,   6.28270300e+00,  -7.70830000e-02],
       [  1.84922100e+00,   6.28282000e+00,   3.38480000e-02]])



In [80]:

    
# Getting back the objects:
with open('./output/DR12Qbin2.pkl') as f:  # Python 3: open(..., 'rb')
    dat = pickle.load(f)
dat









    Out[80]:





array([[  1.61884600e+00,   7.10000000e-05,   8.42960000e-02],
       [  1.57613400e+00,   1.49000000e-04,   6.05257000e-01],
       [  1.71010300e+00,   1.57000000e-04,   2.66244000e-01],
       ..., 
       [  1.62190900e+00,   6.28264600e+00,  -7.35650000e-02],
       [  1.56940900e+00,   6.28270300e+00,  -7.70830000e-02],
       [  1.84922100e+00,   6.28282000e+00,   3.38480000e-02]])



In [36]:

    
bin3=dat[(dat['Z_PIPE']<2.80153309) & (dat['Z_PIPE']>=2.09991448)]



In [37]:

    
len(bin3)









    Out[37]:





139641



In [38]:

    
z=bin3['Z_PIPE']



In [39]:

    
ra=bin3['RA']



In [40]:

    
dec=bin3['DEC']



In [41]:

    
dr12Qz3f = open("./output/DR12Qbin3.dat",'w')
dr12Qz3f.write("z\t rar\t decr \n")

for i in range(0,len(z)):
    dr12Qz3f.write("%f\t " %z[i])
    dr12Qz3f.write("%f\t %f\n " %(ra[i]*pi/180.0,dec[i]*pi/180.0))
dr12Qz3f.close()



In [42]:

    
bin3=ascii.read("./output/DR12Qbin3.dat")



In [43]:

    
bin3









    Out[43]:




<Table length=139641>

z rar decr
float64 float64 float64
2.309097 3.3e-05 0.31021
2.497941 4.8e-05 0.261357
2.332655 0.0001 -0.023126
2.373299 0.000119 0.532663
2.542303 0.000128 -0.130654
2.164559 0.000141 -0.004206
2.543471 0.00016 0.204148
2.651057 0.000171 0.385902
2.354148 0.000231 0.021868
2.164761 0.000257 0.533554
... ... ...
2.759595 6.283047 0.565462
2.733773 6.283068 0.087709
2.552077 6.283114 -0.147293
2.398304 6.28312 0.049193
2.181301 6.28314 0.519839
2.439179 6.283143 -0.171497
2.187777 6.283164 0.152742
2.415508 6.283166 0.176571
2.451015 6.28317 0.505355
2.397667 6.283184 0.606452



In [81]:

    
bin3=ascii.read("./output/DR12Qbin3.dat")



In [82]:

    
z=bin3['z']
rar=bin3['rar']
decr=bin3['decr']



In [83]:

    
dat3=np.array([z,rar,decr])



In [84]:

    
dat3









    Out[84]:





array([[  2.30909700e+00,   2.49794100e+00,   2.33265500e+00, ...,
          2.41550800e+00,   2.45101500e+00,   2.39766700e+00],
       [  3.30000000e-05,   4.80000000e-05,   1.00000000e-04, ...,
          6.28316600e+00,   6.28317000e+00,   6.28318400e+00],
       [  3.10210000e-01,   2.61357000e-01,  -2.31260000e-02, ...,
          1.76571000e-01,   5.05355000e-01,   6.06452000e-01]])



In [85]:

    
dat3=dat3.transpose()



In [86]:

    
dat3









    Out[86]:





array([[  2.30909700e+00,   3.30000000e-05,   3.10210000e-01],
       [  2.49794100e+00,   4.80000000e-05,   2.61357000e-01],
       [  2.33265500e+00,   1.00000000e-04,  -2.31260000e-02],
       ..., 
       [  2.41550800e+00,   6.28316600e+00,   1.76571000e-01],
       [  2.45101500e+00,   6.28317000e+00,   5.05355000e-01],
       [  2.39766700e+00,   6.28318400e+00,   6.06452000e-01]])



In [87]:

    
# Getting back the objects:
with open('./output/DR12Qbin3.pkl','w') as f:  # Python 3: open(..., 'rb')
    pickle.dump(dat3,f)
dat3









    Out[87]:





array([[  2.30909700e+00,   3.30000000e-05,   3.10210000e-01],
       [  2.49794100e+00,   4.80000000e-05,   2.61357000e-01],
       [  2.33265500e+00,   1.00000000e-04,  -2.31260000e-02],
       ..., 
       [  2.41550800e+00,   6.28316600e+00,   1.76571000e-01],
       [  2.45101500e+00,   6.28317000e+00,   5.05355000e-01],
       [  2.39766700e+00,   6.28318400e+00,   6.06452000e-01]])



In [88]:

    
# Getting back the objects:
with open('./output/DR12Qbin3.pkl') as f:  # Python 3: open(..., 'rb')
    dat = pickle.load(f)
dat









    Out[88]:





array([[  2.30909700e+00,   3.30000000e-05,   3.10210000e-01],
       [  2.49794100e+00,   4.80000000e-05,   2.61357000e-01],
       [  2.33265500e+00,   1.00000000e-04,  -2.31260000e-02],
       ..., 
       [  2.41550800e+00,   6.28316600e+00,   1.76571000e-01],
       [  2.45101500e+00,   6.28317000e+00,   5.05355000e-01],
       [  2.39766700e+00,   6.28318400e+00,   6.06452000e-01]])



In [44]:

    
bin4=dat[(dat['Z_PIPE']<3.50315170) & (dat['Z_PIPE']>=2.80153309)]



In [45]:

    
len(bin4)









    Out[45]:





42945



In [46]:

    
z=bin4['Z_PIPE']



In [47]:

    
ra=bin4['RA']



In [48]:

    
dec=bin4['DEC']



In [49]:

    
dr12Qz4f = open("./output/DR12Qbin4.dat",'w')
dr12Qz4f.write("z\t rar\t decr \n")

for i in range(0,len(z)):
    dr12Qz4f.write("%f\t " %z[i])
    dr12Qz4f.write("%f\t %f\n " %(ra[i]*pi/180.0,dec[i]*pi/180.0))
dr12Qz4f.close()



In [50]:

    
bin4=ascii.read("./output/DR12Qbin4.dat")



In [51]:

    
bin4









    Out[51]:




<Table length=42945>

z rar decr
float64 float64 float64
3.088839 0.000103 0.34928
2.906448 0.000252 0.280095
2.879372 0.000361 -0.004858
3.009077 0.000378 0.239244
3.123795 0.000428 0.594248
3.250361 0.000465 -0.120452
2.828129 0.000544 0.204236
3.089968 0.000897 0.398611
3.278693 0.000911 0.556924
3.22843 0.001024 0.026139
... ... ...
2.974564 6.282025 0.069631
3.128922 6.282221 0.212078
3.18261 6.282488 0.390924
2.81591 6.282607 -0.061368
2.976977 6.282751 0.199639
3.421283 6.282824 0.528812
3.128951 6.282996 -0.02931
3.166911 6.283033 0.624115
3.064749 6.283085 0.007521
3.113391 6.283173 0.605993



In [90]:

    
bin4=ascii.read("./output/DR12Qbin4.dat")



In [91]:

    
z=bin4['z']
rar=bin4['rar']
decr=bin4['decr']



In [92]:

    
dat4=np.array([z,rar,decr])



In [93]:

    
dat4









    Out[93]:





array([[  3.08883900e+00,   2.90644800e+00,   2.87937200e+00, ...,
          3.16691100e+00,   3.06474900e+00,   3.11339100e+00],
       [  1.03000000e-04,   2.52000000e-04,   3.61000000e-04, ...,
          6.28303300e+00,   6.28308500e+00,   6.28317300e+00],
       [  3.49280000e-01,   2.80095000e-01,  -4.85800000e-03, ...,
          6.24115000e-01,   7.52100000e-03,   6.05993000e-01]])



In [94]:

    
dat4=dat4.transpose()



In [95]:

    
dat4









    Out[95]:





array([[  3.08883900e+00,   1.03000000e-04,   3.49280000e-01],
       [  2.90644800e+00,   2.52000000e-04,   2.80095000e-01],
       [  2.87937200e+00,   3.61000000e-04,  -4.85800000e-03],
       ..., 
       [  3.16691100e+00,   6.28303300e+00,   6.24115000e-01],
       [  3.06474900e+00,   6.28308500e+00,   7.52100000e-03],
       [  3.11339100e+00,   6.28317300e+00,   6.05993000e-01]])



In [96]:

    
# Getting back the objects:
with open('./output/DR12Qbin4.pkl','w') as f:  # Python 3: open(..., 'rb')
    pickle.dump(dat4,f)
dat4









    Out[96]:





array([[  3.08883900e+00,   1.03000000e-04,   3.49280000e-01],
       [  2.90644800e+00,   2.52000000e-04,   2.80095000e-01],
       [  2.87937200e+00,   3.61000000e-04,  -4.85800000e-03],
       ..., 
       [  3.16691100e+00,   6.28303300e+00,   6.24115000e-01],
       [  3.06474900e+00,   6.28308500e+00,   7.52100000e-03],
       [  3.11339100e+00,   6.28317300e+00,   6.05993000e-01]])



In [97]:

    
# Getting back the objects:
with open('./output/DR12Qbin4.pkl') as f:  # Python 3: open(..., 'rb')
    dat = pickle.load(f)
dat









    Out[97]:





array([[  3.08883900e+00,   1.03000000e-04,   3.49280000e-01],
       [  2.90644800e+00,   2.52000000e-04,   2.80095000e-01],
       [  2.87937200e+00,   3.61000000e-04,  -4.85800000e-03],
       ..., 
       [  3.16691100e+00,   6.28303300e+00,   6.24115000e-01],
       [  3.06474900e+00,   6.28308500e+00,   7.52100000e-03],
       [  3.11339100e+00,   6.28317300e+00,   6.05993000e-01]])



In [99]:

    
mangle=pymangle.Mangle("./input/boss_geometry_2014_05_28.ply")



In [133]:

    
%%time
rar,decr=mangle.genrand(len(dat1))









    



CPU times: user 146 ms, sys: 1.5 ms, total: 148 ms
Wall time: 147 ms



In [134]:

    
rar









    Out[134]:





array([ 244.60063,  3.4907028,  340.43799, ...,  170.79402,  29.954694,
        197.62726], dtype=float128)



In [135]:

    
decr









    Out[135]:





array([ 29.496631,  35.246276,  10.567022, ...,  27.517911, -7.0798175,
        35.490503], dtype=float128)



In [136]:

    
len(rar)









    Out[136]:





48309



In [137]:

    
z=bin1['z']



In [138]:

    
len(z)









    Out[138]:





48309



In [139]:

    
z









    Out[139]:




<Column name='z' dtype='float64' length=48309>

1.360358
1.134544
0.835325
0.752729
0.896221
0.882033
0.702284
1.301611
0.704229
0.840221
0.908785
0.793805
...
0.865574
0.738804
0.761227
0.864865
0.854921
0.752217
0.813033
1.172096
0.979325
0.786509
0.835873
1.197253



In [148]:

    
fdata = open("./output/randDR12Qbin1.dat",'w')
fdata.write("z\t rar\t decr \n")
for i in range(0,len(rar)):
    fdata.write("%f\t" %z[i])
    fdata.write(("%f\t %f\n " %(rar[i]*pi/180.0,decr[i]*pi/180.0)))
fdata.close()



In [149]:

    
fd=ascii.read("./output/randDR12Qbin1.dat")



In [150]:

    
fd









    Out[150]:




<Table length=48309>

z rar decr
float64 float64 float64
1.360358 4.269086 0.514813
1.134544 0.060924 0.615164
0.835325 5.941764 0.184429
0.752729 2.044495 0.732866
0.896221 0.732539 -0.028812
0.882033 3.17327 1.120221
0.702284 6.09082 0.118695
1.301611 3.200835 0.256571
0.704229 3.333406 0.297478
0.840221 3.868056 0.296897
... ... ...
0.761227 3.92202 1.062586
0.864865 0.197829 0.517763
0.854921 3.300742 0.360668
0.752217 2.720828 0.202376
0.813033 3.414145 0.918999
1.172096 2.868106 0.627862
0.979325 6.263083 0.42093
0.786509 2.980918 0.480278
0.835873 0.522808 -0.123566
1.197253 3.449246 0.619426



In [151]:

    
bin1=ascii.read("./output/randDR12Qbin1.dat")



In [152]:

    
z=bin1['z']
rar=bin1['rar']
decr=bin1['decr']



In [153]:

    
dat1=np.array([z,rar,decr])



In [154]:

    
dat1









    Out[154]:





array([[ 1.360358,  1.134544,  0.835325, ...,  0.786509,  0.835873,
         1.197253],
       [ 4.269086,  0.060924,  5.941764, ...,  2.980918,  0.522808,
         3.449246],
       [ 0.514813,  0.615164,  0.184429, ...,  0.480278, -0.123566,
         0.619426]])



In [155]:

    
dat1=dat1.transpose()



In [156]:

    
dat1









    Out[156]:





array([[ 1.360358,  4.269086,  0.514813],
       [ 1.134544,  0.060924,  0.615164],
       [ 0.835325,  5.941764,  0.184429],
       ..., 
       [ 0.786509,  2.980918,  0.480278],
       [ 0.835873,  0.522808, -0.123566],
       [ 1.197253,  3.449246,  0.619426]])



In [157]:

    
# Getting back the objects:
with open('./output/randDR12Qbin1.pkl','w') as f:  # Python 3: open(..., 'rb')
    pickle.dump(dat1,f)
dat1









    Out[157]:





array([[ 1.360358,  4.269086,  0.514813],
       [ 1.134544,  0.060924,  0.615164],
       [ 0.835325,  5.941764,  0.184429],
       ..., 
       [ 0.786509,  2.980918,  0.480278],
       [ 0.835873,  0.522808, -0.123566],
       [ 1.197253,  3.449246,  0.619426]])



In [158]:

    
# Getting back the objects:
with open('./output/randDR12Qbin1.pkl') as f:  # Python 3: open(..., 'rb')
    dat1 = pickle.load(f)
dat1









    Out[158]:





array([[ 1.360358,  4.269086,  0.514813],
       [ 1.134544,  0.060924,  0.615164],
       [ 0.835325,  5.941764,  0.184429],
       ..., 
       [ 0.786509,  2.980918,  0.480278],
       [ 0.835873,  0.522808, -0.123566],
       [ 1.197253,  3.449246,  0.619426]])



In [159]:

    
len(dat1)









    Out[159]:





48309



In [235]:

    
dat1[:,0]









    Out[235]:





array([ 1.360358,  1.134544,  0.835325, ...,  0.786509,  0.835873,
        1.197253])



In [236]:

    
z1=np.mean(dat1[:,0])
print z1









    



0.957640720611



In [160]:

    
%%time
rar,decr=mangle.genrand(len(dat2))









    



CPU times: user 146 ms, sys: 1.57 ms, total: 147 ms
Wall time: 147 ms



In [161]:

    
rar









    Out[161]:





array([ 187.54879,  174.8315,  226.52937, ...,  199.90006,  24.570883,
        152.36008], dtype=float128)



In [162]:

    
decr









    Out[162]:





array([ 17.03004,  54.236363,  6.3119358, ...,  9.8931565,  2.0275094,
        15.830989], dtype=float128)



In [163]:

    
len(rar)









    Out[163]:





42650



In [164]:

    
z=bin2['z']



In [165]:

    
len(z)









    Out[165]:





42650



In [166]:

    
z









    Out[166]:




<Column name='z' dtype='float64' length=42650>

1.618846
1.576134
1.710103
1.833563
2.001412
2.0892
1.640517
2.004653
1.545614
1.615499
1.435563
1.976213
...
1.717248
1.758497
1.869809
1.605174
2.078732
1.852452
1.700308
1.762858
1.639977
1.621909
1.569409
1.849221



In [167]:

    
fdata = open("./output/randDR12Qbin2.dat",'w')
fdata.write("z\t rar\t decr \n")
for i in range(0,len(rar)):
    fdata.write("%f\t" %z[i])
    fdata.write(("%f\t %f\n " %(rar[i]*pi/180.0,decr[i]*pi/180.0)))
fdata.close()



In [168]:

    
fd=ascii.read("./output/randDR12Qbin2.dat")



In [169]:

    
fd









    Out[169]:




<Table length=42650>

z rar decr
float64 float64 float64
1.618846 3.273344 0.29723
1.576134 3.051385 0.946603
1.710103 3.953683 0.110164
1.833563 2.764983 0.255697
2.001412 3.702457 0.504963
2.0892 2.758408 0.674666
1.640517 3.091823 0.245293
2.004653 3.151295 0.708954
1.545614 3.789285 0.980275
1.615499 3.657412 0.825689
... ... ...
1.869809 2.717011 1.082111
1.605174 3.695028 0.021013
2.078732 6.253493 0.266181
1.852452 0.570581 0.452779
1.700308 3.682407 0.599498
1.762858 3.849029 0.210922
1.639977 3.186802 0.135185
1.621909 3.488914 0.172668
1.569409 0.428843 0.035387
1.849221 2.659185 0.276303



In [170]:

    
bin2=ascii.read("./output/randDR12Qbin2.dat")



In [171]:

    
z=bin2['z']
rar=bin2['rar']
decr=bin2['decr']



In [172]:

    
dat2=np.array([z,rar,decr])



In [173]:

    
dat2









    Out[173]:





array([[ 1.618846,  1.576134,  1.710103, ...,  1.621909,  1.569409,
         1.849221],
       [ 3.273344,  3.051385,  3.953683, ...,  3.488914,  0.428843,
         2.659185],
       [ 0.29723 ,  0.946603,  0.110164, ...,  0.172668,  0.035387,
         0.276303]])



In [174]:

    
dat2=dat2.transpose()



In [175]:

    
dat2









    Out[175]:





array([[ 1.618846,  3.273344,  0.29723 ],
       [ 1.576134,  3.051385,  0.946603],
       [ 1.710103,  3.953683,  0.110164],
       ..., 
       [ 1.621909,  3.488914,  0.172668],
       [ 1.569409,  0.428843,  0.035387],
       [ 1.849221,  2.659185,  0.276303]])



In [176]:

    
# Getting back the objects:
with open('./output/randDR12Qbin2.pkl','w') as f:  # Python 3: open(..., 'rb')
    pickle.dump(dat2,f)
dat2









    Out[176]:





array([[ 1.618846,  3.273344,  0.29723 ],
       [ 1.576134,  3.051385,  0.946603],
       [ 1.710103,  3.953683,  0.110164],
       ..., 
       [ 1.621909,  3.488914,  0.172668],
       [ 1.569409,  0.428843,  0.035387],
       [ 1.849221,  2.659185,  0.276303]])



In [177]:

    
# Getting back the objects:
with open('./output/randDR12Qbin2.pkl') as f:  # Python 3: open(..., 'rb')
    dat2 = pickle.load(f)
dat2









    Out[177]:





array([[ 1.618846,  3.273344,  0.29723 ],
       [ 1.576134,  3.051385,  0.946603],
       [ 1.710103,  3.953683,  0.110164],
       ..., 
       [ 1.621909,  3.488914,  0.172668],
       [ 1.569409,  0.428843,  0.035387],
       [ 1.849221,  2.659185,  0.276303]])



In [178]:

    
len(dat2)









    Out[178]:





42650



In [233]:

    
dat2[:,0]









    Out[233]:





array([ 1.618846,  1.576134,  1.710103, ...,  1.621909,  1.569409,
        1.849221])



In [234]:

    
z2=np.mean(dat2[:,0])
print z2









    



1.76960169147



In [179]:

    
%%time
rar,decr=mangle.genrand(len(dat3))









    



CPU times: user 415 ms, sys: 2.8 ms, total: 418 ms
Wall time: 418 ms



In [180]:

    
rar









    Out[180]:





array([ 219.16857,  247.39444,  228.08203, ...,  348.78554,  8.0626544,
        209.37297], dtype=float128)



In [181]:

    
decr









    Out[181]:





array([ 51.972382,  49.430065,  43.056694, ...,  18.618568,  22.657612,
        17.468624], dtype=float128)



In [182]:

    
len(rar)









    Out[182]:





139641



In [183]:

    
z=bin3['z']



In [184]:

    
len(z)









    Out[184]:





139641



In [185]:

    
z









    Out[185]:




<Column name='z' dtype='float64' length=139641>

2.309097
2.497941
2.332655
2.373299
2.542303
2.164559
2.543471
2.651057
2.354148
2.164761
2.271441
2.180127
...
2.3247
2.272273
2.759595
2.733773
2.552077
2.398304
2.181301
2.439179
2.187777
2.415508
2.451015
2.397667



In [ ]:



In [186]:

    
fdata = open("./output/randDR12Qbin3.dat",'w')
fdata.write("z\t rar\t decr \n")
for i in range(0,len(rar)):
    fdata.write("%f\t" %z[i])
    fdata.write(("%f\t %f\n " %(rar[i]*pi/180.0,decr[i]*pi/180.0)))
fdata.close()



In [187]:

    
fd=ascii.read("./output/randDR12Qbin3.dat")



In [188]:

    
fd









    Out[188]:




<Table length=139641>

z rar decr
float64 float64 float64
2.309097 3.825213 0.907089
2.497941 4.317847 0.862717
2.332655 3.980782 0.751481
2.373299 3.047116 0.402239
2.542303 0.250559 0.403021
2.164559 5.902057 0.208055
2.543471 6.17996 0.373863
2.651057 2.733107 1.114213
2.354148 2.894348 0.150544
2.164761 0.163354 0.34185
... ... ...
2.759595 4.24207 1.029525
2.733773 3.498952 0.152141
2.552077 2.137045 0.646528
2.398304 2.914508 0.615876
2.181301 0.119995 0.286168
2.439179 3.28874 -0.03044
2.187777 0.166733 -0.138122
2.415508 6.087456 0.324955
2.451015 0.14072 0.39545
2.397667 3.654248 0.304885



In [170]:

    
bin3=ascii.read("./output/randDR12Qbin3.dat")



In [189]:

    
z=bin3['z']
rar=bin3['rar']
decr=bin3['decr']



In [190]:

    
dat3=np.array([z,rar,decr])



In [191]:

    
dat3









    Out[191]:





array([[  2.30909700e+00,   2.49794100e+00,   2.33265500e+00, ...,
          2.41550800e+00,   2.45101500e+00,   2.39766700e+00],
       [  3.30000000e-05,   4.80000000e-05,   1.00000000e-04, ...,
          6.28316600e+00,   6.28317000e+00,   6.28318400e+00],
       [  3.10210000e-01,   2.61357000e-01,  -2.31260000e-02, ...,
          1.76571000e-01,   5.05355000e-01,   6.06452000e-01]])



In [192]:

    
dat3=dat3.transpose()



In [193]:

    
dat3









    Out[193]:





array([[  2.30909700e+00,   3.30000000e-05,   3.10210000e-01],
       [  2.49794100e+00,   4.80000000e-05,   2.61357000e-01],
       [  2.33265500e+00,   1.00000000e-04,  -2.31260000e-02],
       ..., 
       [  2.41550800e+00,   6.28316600e+00,   1.76571000e-01],
       [  2.45101500e+00,   6.28317000e+00,   5.05355000e-01],
       [  2.39766700e+00,   6.28318400e+00,   6.06452000e-01]])



In [194]:

    
# Getting back the objects:
with open('./output/randDR12Qbin3.pkl','w') as f:  # Python 3: open(..., 'rb')
    pickle.dump(dat3,f)
dat3









    Out[194]:





array([[  2.30909700e+00,   3.30000000e-05,   3.10210000e-01],
       [  2.49794100e+00,   4.80000000e-05,   2.61357000e-01],
       [  2.33265500e+00,   1.00000000e-04,  -2.31260000e-02],
       ..., 
       [  2.41550800e+00,   6.28316600e+00,   1.76571000e-01],
       [  2.45101500e+00,   6.28317000e+00,   5.05355000e-01],
       [  2.39766700e+00,   6.28318400e+00,   6.06452000e-01]])



In [195]:

    
# Getting back the objects:
with open('./output/randDR12Qbin3.pkl') as f:  # Python 3: open(..., 'rb')
    dat3 = pickle.load(f)
dat3









    Out[195]:





array([[  2.30909700e+00,   3.30000000e-05,   3.10210000e-01],
       [  2.49794100e+00,   4.80000000e-05,   2.61357000e-01],
       [  2.33265500e+00,   1.00000000e-04,  -2.31260000e-02],
       ..., 
       [  2.41550800e+00,   6.28316600e+00,   1.76571000e-01],
       [  2.45101500e+00,   6.28317000e+00,   5.05355000e-01],
       [  2.39766700e+00,   6.28318400e+00,   6.06452000e-01]])



In [196]:

    
len(dat3)









    Out[196]:





139641



In [231]:

    
dat3[:,0]









    Out[231]:





array([ 2.309097,  2.497941,  2.332655, ...,  2.415508,  2.451015,
        2.397667])



In [232]:

    
z3=np.mean(dat3[:,0])
print z3









    



2.41105691717



In [200]:

    
%%time
rar,decr=mangle.genrand(len(dat4))









    



CPU times: user 138 ms, sys: 1.54 ms, total: 140 ms
Wall time: 140 ms



In [201]:

    
rar









    Out[201]:





array([ 201.08922,  329.24997,  131.66923, ...,  5.6569609,  356.88081,
        328.56472], dtype=float128)



In [202]:

    
decr









    Out[202]:





array([ 30.181739,  1.4083831,  11.099657, ...,  4.9097444,  22.540363,
        2.4910029], dtype=float128)



In [203]:

    
len(rar)









    Out[203]:





42945



In [206]:

    
z=bin4['z']



In [207]:

    
len(z)









    Out[207]:





42945



In [208]:

    
z









    Out[208]:




<Column name='z' dtype='float64' length=42945>

3.088839
2.906448
2.879372
3.009077
3.123795
3.250361
2.828129
3.089968
3.278693
3.22843
3.48995
3.027761
...
3.058009
3.340463
2.974564
3.128922
3.18261
2.81591
2.976977
3.421283
3.128951
3.166911
3.064749
3.113391



In [ ]:



In [209]:

    
fdata = open("./output/randDR12Qbin4.dat",'w')
fdata.write("z\t rar\t decr \n")
for i in range(0,len(rar)):
    fdata.write("%f\t" %z[i])
    fdata.write(("%f\t %f\n " %(rar[i]*pi/180.0,decr[i]*pi/180.0)))
fdata.close()



In [210]:

    
fd=ascii.read("./output/randDR12Qbin4.dat")



In [211]:

    
fd









    Out[211]:




<Table length=42945>

z rar decr
float64 float64 float64
3.088839 3.509669 0.526771
2.906448 5.746496 0.024581
2.879372 2.298062 0.193726
3.009077 4.133702 0.273621
3.123795 2.831509 0.48065
3.250361 2.938304 0.510374
2.828129 5.630599 -0.059139
3.089968 3.048257 0.673365
3.278693 3.246362 0.259751
3.22843 3.273315 0.911471
... ... ...
2.974564 2.513916 0.219169
3.128922 2.850464 0.704095
3.18261 2.835107 0.564101
2.81591 6.233126 0.127182
2.976977 2.157878 0.067073
3.421283 3.056451 0.485489
3.128951 3.215674 0.730304
3.166911 0.098733 0.085691
3.064749 6.228745 0.393404
3.113391 5.734536 0.043476



In [212]:

    
bin4=ascii.read("./output/randDR12Qbin4.dat")



In [214]:

    
z=bin4['z']
rar=bin4['rar']
decr=bin4['decr']



In [215]:

    
dat4=np.array([z,rar,decr])



In [216]:

    
dat4









    Out[216]:





array([[ 3.088839,  2.906448,  2.879372, ...,  3.166911,  3.064749,
         3.113391],
       [ 3.509669,  5.746496,  2.298062, ...,  0.098733,  6.228745,
         5.734536],
       [ 0.526771,  0.024581,  0.193726, ...,  0.085691,  0.393404,
         0.043476]])



In [217]:

    
dat4=dat4.transpose()



In [218]:

    
dat4









    Out[218]:





array([[ 3.088839,  3.509669,  0.526771],
       [ 2.906448,  5.746496,  0.024581],
       [ 2.879372,  2.298062,  0.193726],
       ..., 
       [ 3.166911,  0.098733,  0.085691],
       [ 3.064749,  6.228745,  0.393404],
       [ 3.113391,  5.734536,  0.043476]])



In [219]:

    
# Getting back the objects:
with open('./output/randDR12Qbin4.pkl','w') as f:  # Python 3: open(..., 'rb')
    pickle.dump(dat4,f)
dat4









    Out[219]:





array([[ 3.088839,  3.509669,  0.526771],
       [ 2.906448,  5.746496,  0.024581],
       [ 2.879372,  2.298062,  0.193726],
       ..., 
       [ 3.166911,  0.098733,  0.085691],
       [ 3.064749,  6.228745,  0.393404],
       [ 3.113391,  5.734536,  0.043476]])



In [220]:

    
# Getting back the objects:
with open('./output/randDR12Qbin4.pkl') as f:  # Python 3: open(..., 'rb')
    dat4 = pickle.load(f)
dat4









    Out[220]:





array([[ 3.088839,  3.509669,  0.526771],
       [ 2.906448,  5.746496,  0.024581],
       [ 2.879372,  2.298062,  0.193726],
       ..., 
       [ 3.166911,  0.098733,  0.085691],
       [ 3.064749,  6.228745,  0.393404],
       [ 3.113391,  5.734536,  0.043476]])



In [221]:

    
len(dat4)









    Out[221]:





42945



In [225]:

    
np.mean(dat4[0:])









    Out[225]:





2.1992691680521599



In [228]:

    
dat4[:,0]









    Out[228]:





array([ 3.088839,  2.906448,  2.879372, ...,  3.166911,  3.064749,
        3.113391])



In [230]:

    
z4=np.mean(dat4[:,0])
print z4









    



3.07002500165



In [ ]:



In [ ]:



In [ ]:



In [ ]:



In [ ]:



In [ ]:



In [ ]:



In [46]:

    
z>=6.96677249e-01 and z<1.39829586









    



---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-46-fd2ee321d7c4> in <module>()
----> 1 z>=6.96677249e-01 and z<1.39829586

ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()



In [51]:

    
np.argwhere(z>=6.96677249e-01)









    Out[51]:





array([[     0],
       [     1],
       [     2],
       ..., 
       [297298],
       [297299],
       [297300]])



In [52]:

    
z11=np.argwhere(z<1.39829586)
z12=np.argwhere(z>=6.96677249e-01)



In [62]:

    
len(z11)









    Out[62]:





62691



In [64]:

    
z11v=z[z11]



In [65]:

    
z11v









    Out[65]:





array([[ 1.36035752],
       [ 0.67536956],
       [ 1.13454401],
       ..., 
       [ 0.78650928],
       [ 0.83587337],
       [ 1.19725287]], dtype=float32)



In [66]:

    
len(z11v)









    Out[66]:





62691



In [70]:

    
z1ind=np.argwhere(z11v>=6.96677249e-01)
z1=z11v[z1ind]



In [71]:

    
len(z[z1ind])









    Out[71]:





48309



In [72]:

    
z1









    Out[72]:





array([[[ 1.36035752],
        [ 1.36035752]],

       [[ 1.13454401],
        [ 1.36035752]],

       [[ 0.8353247 ],
        [ 1.36035752]],

       ..., 
       [[ 0.78650928],
        [ 1.36035752]],

       [[ 0.83587337],
        [ 1.36035752]],

       [[ 1.19725287],
        [ 1.36035752]]], dtype=float32)



In [41]:

    
plt.plot(np.histogram(z)[1][1:],np.histogram(z)[0])









    Out[41]:





[<matplotlib.lines.Line2D at 0x13781ad90>]



In [42]:

    
plt.hist(z)









    Out[42]:





(array([  1.43820000e+04,   4.83090000e+04,   4.26500000e+04,
          1.39641000e+05,   4.29450000e+04,   7.69800000e+03,
          1.11600000e+03,   2.71000000e+02,   1.75000000e+02,
          1.14000000e+02]),
 array([ -4.94136522e-03,   6.96677249e-01,   1.39829586e+00,
          2.09991448e+00,   2.80153309e+00,   3.50315170e+00,
          4.20477032e+00,   4.90638893e+00,   5.60800755e+00,
          6.30962616e+00,   7.01124477e+00]),
 <a list of 10 Patch objects>)



In [ ]:



In [7]:

    
mangle=pymangle.Mangle("./input/boss_geometry_2014_05_28.ply")



In [8]:

    
%%time
rar,decr=mangle.genrand(len(z))









    



CPU times: user 1.12 s, sys: 4.41 ms, total: 1.13 s
Wall time: 1.14 s



In [9]:

    
rar









    Out[9]:





array([ 200.46421,  16.276615,  217.50623, ...,  140.52798,  5.9646122,
        152.62438], dtype=float128)



In [10]:

    
decr









    Out[10]:





array([ 38.475609,  6.1485714,  27.729229, ...,  43.966504,  29.114936,
        40.696016], dtype=float128)



In [11]:

    
len(rar)









    Out[11]:





297301



In [12]:

    
print len(z)
print len(decr)



In [13]:

    
fdata = open("./output/randDR12Q.dat",'w')
fdata.write("z\t ra\t dec \n")
for i in range(0,len(rar)-1):
    fdata.write("%f\t" %z[i])
    fdata.write("%f\t" %rar[i])
    fdata.write("%f\n" %decr[i])
fdata.close()



In [14]:

    
fd=ascii.read("./output/randDR12Q.dat")



In [15]:

    
fd









    Out[15]:




<Table length=297300>

z ra dec
float64 float64 float64
2.309097 200.464211 38.475609
2.497941 16.276615 6.148571
1.618846 217.506234 27.729229
1.360358 209.750006 9.125118
2.332655 23.819124 15.051518
3.088839 245.171651 57.761975
2.373299 173.354973 4.91245
2.542303 137.507004 39.254526
3.711993 158.203712 19.110721
2.164559 241.60335 20.833734
... ... ...
1.197253 343.659044 12.314154
3.064749 26.382062 -0.859049
2.552077 317.561653 1.809564
2.398304 155.412601 29.174921
2.181301 206.356903 6.363123
2.439179 30.744467 28.764067
2.187777 133.625298 54.045642
2.415508 182.175292 26.12546
2.451015 140.52798 43.966504
3.113391 5.964612 29.114936



In [16]:

    
NSIDE=512
rdr12qhpix=hu.HealPix("ring",NSIDE)



In [18]:

    
pixdata = open("./output/pixranddr12Q.dat",'w')
pixdata.write("z\t pix \n")
for i in range(0,len(rar)-1):
    pixdata.write("%f\t" %z[i])
    pixdata.write("%d\n" %rdr12qhpix.eq2pix(rar[i],decr[i]))
pixdata.close()



In [19]:

    
pixdata = ascii.read("./output/pixranddr12Q.dat")
hpixdata=np.array(np.zeros(hu.nside2npix(NSIDE)))
for j in range(len(pixdata)):
    hpixdata[pixdata[j]['pix']]+=1



In [20]:

    
hpixdata









    Out[20]:





array([ 0.,  0.,  0., ...,  0.,  0.,  0.])



In [21]:

    
hu.mollview(hpixdata,rot=180)
plt.savefig("randDR12Qm.pdf")



In [22]:

    
hu.orthview(hpixdata)
plt.savefig("rand12Q.pdf")



In [23]:

    
print min(rar)
print max(rar)
print min(decr)
print max(decr)









    



0.000188855808432
359.996729426
-10.9989631307
68.7228354106



In [24]:

    
NSIDE=512
dr12qhpix=hu.HealPix("ring",NSIDE)



In [25]:

    
ra=dat['RA']
dec=dat['DEC']



In [27]:

    
pixdata = open("./output/pixdr12Q.dat",'w')
pixdata.write("z\t pix \n")
for i in range(0,len(ra)-1):
    pixdata.write("%f\t" %z[i])
    pixdata.write("%d\n" %dr12qhpix.eq2pix(ra[i],dec[i]))
pixdata.close()



In [26]:

    
pixdata = ascii.read("./output/pixdr12Q.dat")
hpixdata=np.array(np.zeros(hu.nside2npix(NSIDE)))
for j in range(len(pixdata)):
    hpixdata[pixdata[j]['pix']]+=1



In [27]:

    
hpixdata









    Out[27]:





array([ 0.,  0.,  0., ...,  0.,  0.,  0.])



In [28]:

    
hu.mollview(hpixdata,rot=180)
plt.savefig("DR12Qmollview.pdf")



In [29]:

    
hu.orthview(hpixdata)
plt.savefig("DR12Qorth.pdf")

z	rar	decr
float64	float64	float64
1.360358	9.3e-05	-0.035487
1.134544	0.000682	0.243272
0.835325	0.000758	-0.142169
0.752729	0.000782	-0.099872
0.896221	0.000918	-0.082249
0.882033	0.001199	0.042834
0.702284	0.001299	0.240805
1.301611	0.001425	0.021841
0.704229	0.001539	0.236405
0.840221	0.001691	0.339623
...	...	...
0.761227	6.281947	0.510654
0.864865	6.282053	-0.055125
0.854921	6.282082	0.454166
0.752217	6.282573	0.223546
0.813033	6.282579	-0.087908
1.172096	6.282584	-0.027623
0.979325	6.282665	0.288813
0.786509	6.282744	0.260439
0.835873	6.28277	0.15974
1.197253	6.283072	0.369546