notebook.community

Edit and run



In [2]:

    
import sys, os
import matplotlib.pyplot as plt
import pynoddy.history
import pynoddy.output
import copy
import pickle
import scipy.stats



In [3]:

    
# os.chdir(r"/Users/Florian/Documents/10_Geomodels/Noddy/GBasin/GBasin")
# os.chdir(r"/Users/flow/Documents/02_work/10_Geomodels/06_Noddy/GBasin")
os.chdir(r'/Users/Florian/git/pynoddy/examples/')



In [4]:

    
print pynoddy.__file__









    



/Users/Florian/git/pynoddy/pynoddy/__init__.pyc



In [5]:

    
reload(pynoddy.history)
reload(pynoddy.events)
his = "GBasi123.his"
PH = pynoddy.history.NoddyHistory(his)
out = 'GBasin_out'
pynoddy.compute_model(his, out)
print os.getcwd()
PO = pynoddy.output.NoddyOutput(out)









    



 STRATIGRAPHY
 UNCONFORMITY
 UNCONFORMITY
 UNCONFORMITY
 FOLD
 FAULT
 FAULT
 FAULT
 UNCONFORMITY
/Users/Florian/git/pynoddy/examples



In [6]:

    
import gipps_uncertainty



In [34]:

    
reload(gipps_uncertainty)
GU = gipps_uncertainty.GUncert(PH, 10, compute=False)









    



Sampling step 0



In [35]:

    
GU.load_all_models()



In [36]:

    
print GU.all_blocks.nbytes / 1E6
# pickle.dump(GU.all_blocks, open("all_blocks.pkl", "w"))

Information Entropy

As a first step, let's have a look at probabilities and then calculate information entropy for the entire block model!



In [37]:

    
GU.calculate_entropy()

Save results and create VTK file for visualisations



In [38]:

    
pickle.dump(GU.entropy, open("GB_entropy.pkl", "w"))
GU.export_to_vtk(GU.entropy, "entropy")

Stratigraphic Variability

The modes can simply be calculated using the scipy stats mode method:



In [40]:

    
modes, bins = scipy.stats.mode(GU.all_blocks)
bins = bins[0,:,:,:]
strat_var_1 = modes[0,:,:,:]

Thankfully, the second return value from the mode function is actually the bin count of the modal value, so exactly what we need for the second part of the stratigraphic variability function:



In [44]:

    
strat_var_2 = 1. - bins / GU.n
strat_combined = strat_var_1 + strat_var_2

Save results and create VTK visualisations:



In [45]:

    
pickle.dump(strat_var_1, open("strat_modes.pkl", "w"))
pickle.dump(strat_var_2, open("strat_differs.pkl", "w"))
pickle.dump(strat_combined, open("strat_combined.pkl", "w"))



In [46]:

    
GU.export_to_vtk(strat_var_1, "strat_modes")
GU.export_to_vtk(strat_var_2, "strat_bins")
GU.export_to_vtk(strat_combined, "strat_combined")



In [84]:



In [146]:

    
a = np.array([1,3,1,2,3,5,1,2,5,12,3])



In [125]:

    
print a
print np.sort(a)
print np.argsort(a)
print "----"
print np.unique(a)
print np.argmax(np.unique(np.sort(a)))









    



[ 1  3  1  2  3  5  1  2  5 12  3]
[ 1  1  1  2  2  3  3  3  5  5 12]
[ 0  2  6  3  7  1  4 10  5  8  9]
----
[ 1  2  3  5 12]
4



In [187]:

    
a_sort = np.sort(a)
print a_sort



In [160]:

    
np.where(a_sort[:-1] != a_sort[1:])
n = float(len(a))



In [197]:

    
a = np.random.randint(0,3,size=(300,4))
b = [np.sum(a == id_a, axis=0) / 300. for id_a in np.unique(a)]



In [198]:

    
b









    Out[198]:





[array([ 0.31666667,  0.30666667,  0.32666667,  0.29333333]),
 array([ 0.35666667,  0.32333333,  0.35333333,  0.32666667]),
 array([ 0.32666667,  0.37      ,  0.32      ,  0.38      ])]



In [190]:

    
b









    Out[190]:





[array([ 0.25 ,  0.25 ,  0.125,  0.375]),
 array([ 0.625,  0.5  ,  0.5  ,  0.375]),
 array([ 0.125,  0.25 ,  0.375,  0.25 ])]



In [165]:









    



  File "<ipython-input-165-2ed524e762bc>", line 1
    np.unique(a, [:,:,:])
                  ^
SyntaxError: invalid syntax



In [53]:

    
2**2 + 2**1 + 2**(-2) + 2**(-3)









    Out[53]:





6.375



In [62]:

    
def own_sqrt(x):
    s = 1.
    for k in range(4):
        s = 0.5 * (s + x/s)
        print s
    return s



In [63]:

    
own_sqrt(2.)









    



1.5
1.41666666667
1.41421568627
1.41421356237






    Out[63]:





1.4142135623746899



In [64]:

    
pynoddy?



In [70]:

    
cd ~/git/pynoddy/examples/









    



/Users/flow/git/pynoddy/examples



In [71]:

    
NH = pynoddy.NoddyHistory("GBasi123.his")









    



 STRATIGRAPHY
 UNCONFORMITY
 UNCONFORMITY
 UNCONFORMITY
 FOLD
 FAULT
 FAULT
 FAULT
 UNCONFORMITY



In [118]:

    
run gipps_uncertainty









    



 STRATIGRAPHY
 UNCONFORMITY
 UNCONFORMITY
 UNCONFORMITY
 FOLD
 FAULT
 FAULT
 FAULT
 UNCONFORMITY
Sampling step 0
Sampling step 100
Sampling step 200
Sampling step 300
Sampling step 400
Sampling step 500
Sampling step 600
Sampling step 700
Sampling step 800
Sampling step 900
9



In [89]:

    
for event in NH.events:
    print NH.events[event]









    



<pynoddy.events.Stratigraphy instance at 0x1073de3b0>
<pynoddy.events.Unconformity instance at 0x1073de518>
<pynoddy.events.Unconformity instance at 0x1073de4d0>
<pynoddy.events.Unconformity instance at 0x1073de368>
<pynoddy.events.Fold instance at 0x1073de758>
<pynoddy.events.Fault instance at 0x1073de950>
<pynoddy.events.Fault instance at 0x1073de998>
<pynoddy.events.Fault instance at 0x1073de3f8>
<pynoddy.events.Unconformity instance at 0x1073de908>



In [97]:

    
NH.events[2].event_type









    Out[97]:





'UNCONFORMITY'



In [93]:

    
type(NH.events)









    Out[93]:





dict



In [116]:

    
NH.events









    Out[116]:





{1: <pynoddy.events.Stratigraphy instance at 0x10761c710>,
 2: <pynoddy.events.Unconformity instance at 0x10761c758>,
 3: <pynoddy.events.Unconformity instance at 0x10761c7a0>,
 4: <pynoddy.events.Unconformity instance at 0x10761c7e8>,
 5: <pynoddy.events.Fold instance at 0x10761c830>,
 6: <pynoddy.events.Fault instance at 0x10761c908>,
 7: <pynoddy.events.Fault instance at 0x10761c950>,
 8: <pynoddy.events.Fault instance at 0x10761c878>,
 9: <pynoddy.events.Unconformity instance at 0x10761c8c0>}



In [107]:

    
np.mod(101,10)









    Out[107]:





1



In [115]:

    
a = (1,2,3)
print np.random.choice(a, size = 3, replace=False)



In [ ]: