In [5]:

    

%matplotlib inline


    

In [1]:

    

h = np.load('/lustre/ki/pfs/mwillia1/LG_project/Consuelo_Boxes/4001/4001hlist.npy')


    

In [3]:

    

h['vmax']


    

    
Out[3]:





array([ 1230.37,  1180.23,  1068.14, ...,    27.67,    28.33,    24.95])

In [7]:

    

scatter(np.log10(h['mvir']), h['vmax'])


    

    
Out[7]:





<matplotlib.collections.PathCollection at 0x3b03450>






    

In [25]:

    

hal = h[np.log10(h['mvir'])>11.3]


    

In [26]:

    

hal.shape


    

    
Out[26]:





(1178747,)

In [29]:

    

hist(hal['vmax'])


    

    
Out[29]:





(array([  1.10440400e+06,   6.22570000e+04,   9.11300000e+03,
          2.13200000e+03,   5.89000000e+02,   1.71000000e+02,
          5.10000000e+01,   2.10000000e+01,   6.00000000e+00,
          3.00000000e+00]),
 array([   83.97 ,   261.746,   439.522,   617.298,   795.074,   972.85 ,
         1150.626,  1328.402,  1506.178,  1683.954,  1861.73 ]),
 <a list of 10 Patch objects>)






    

In [32]:

    

print np.mean(hal['vmax'])
print np.std(hal['vmax'])
hal['vmax'].min()


    

    




154.57024336
70.4488375839






    
Out[32]:





83.969999999999999

In [22]:

    

v = h[np.abs(h['vmax'])>80]


    

In [23]:

    

hist(np.log10(v['mvir']))


    

    
Out[23]:





(array([  3.10920000e+04,   9.78800000e+05,   7.43493000e+05,
          2.74583000e+05,   9.70070000e+04,   3.21220000e+04,
          9.66500000e+03,   2.36800000e+03,   3.56000000e+02,
          2.70000000e+01]),
 array([ 10.31407799,  10.81022436,  11.30637073,  11.8025171 ,
         12.29866347,  12.79480984,  13.29095621,  13.78710258,
         14.28324895,  14.77939532,  15.27554169]),
 <a list of 10 Patch objects>)






    

In [ ]: