In [75]:

    

import numpy as np
import h5py


    

In [76]:

    

from matplotlib import pyplot as plt
%matplotlib inline
import seaborn as sns
sns.set()


    

In [77]:

    

#f= h5py.File('/home/users/swmclau2/scratch/Darksky/ds14_a_1.0000_0.010_downsample.hdf5')
f = h5py.File('/home/users/swmclau2/scratch/Darksky/ds14_a_halos_1.0000_fixed_boundaries_v2.hdf5')


    

In [78]:

    

#f['halos'].keys()


    

In [79]:

    

parts = f['halos']


    

In [80]:

    

h = 0.6880620000000001


    

In [81]:

    

R0 = 5.81342950e6


    

In [82]:

    

2*R0*h/1000


    

    
Out[82]:





7999.999857258001

In [93]:

    

x = (parts['subbox_444'].value[:100000])# + R0)*h/1000


    

In [94]:

    

non_nan_idxs = ~np.isnan(x[:,7])


    

In [95]:

    

np.max(x[x[:,3]>0,3])


    

    
Out[95]:





1.8480616e+15

In [96]:

    

bins = np.logspace(10.5, 15.5, 20)
plt.hist(x[:, 3],bins=bins )
plt.hist(x[non_nan_idxs, 3],bins = bins )
plt.hist(x[~non_nan_idxs, 3],bins = bins , alpha = 0.1)

plt.yscale('log')
plt.xscale('log')


    

In [108]:

    

nan_hist, _ = np.histogram(x[~non_nan_idxs,3], bins = bins)
non_nan_hist, _  = np.histogram(x[non_nan_idxs, 3], bins = bins)

plt.plot((bins[:1]+bins[:-1])/2.0, nan_hist/non_nan_hist)
plt.xscale('log')


    

    




/share/software/user/open/py-jupyter/1.0.0_py27/lib/python2.7/site-packages/ipykernel_launcher.py:4: RuntimeWarning: divide by zero encountered in divide
  after removing the cwd from sys.path.






    

In [97]:

    

np.sum(non_nan_idxs)*1.0/non_nan_idxs.shape[0]


    

    
Out[97]:





0.036420000000000001

In [98]:

    

plt.scatter(x[:, 0], x[:, 2], alpha = 0.2)
plt.scatter(x[non_nan_idxs, 0], x[non_nan_idxs, 2], alpha = 1.0)


    

    
Out[98]:





<matplotlib.collections.PathCollection at 0x7f91b84470d0>






    

In [ ]: