In [1]:

    

import pymatgen_pars as pymt
import numpy as np
import pymatgen.analysis.bond_valence as bv
from collections import Counter


    

In [2]:

    

st=pymt.read_unique_data("unique_data.json")


    

In [3]:

    

import tqdm


    

In [4]:

    

st_masked=[i for i in st if np.all([a in bv.BV_PARAMS for a in i.composition.elements])]


    

In [5]:

    

BV=bv.BVAnalyzer()


    

In [6]:

    

valency1=[]
True_vals=[]
for i in tqdm.tqdm_notebook(st_masked[0:5000]):
    try:
        valency1.append(BV.get_valences(i))
        True_vals.append(i)
    except:
        pass


    

In [10]:

    

valency=[]
st_true=[]
valency=valency+valency1
st_true=st_true+True_vals


    

In [13]:

    

import pickle


    

In [16]:

    

val3=pickle.load(open('val3.pickle', 'rb'))
true3=pickle.load(open("True3.pickle",'rb'))


    

In [17]:

    

val4=pickle.load(open('val4.pickle', 'rb'))
true4=pickle.load(open("True4.pickle",'rb'))


    

In [18]:

    

import pickle

with open("val1.pickle","w") as f:
    pickle.dump(valency1,f)

with open("True1.pickle","w") as f:
    pickle.dump(True_vals,f)


    

In [19]:

    

valency=valency+val3
st_true=st_true+true3


    

In [20]:

    

valency=valency+val4
st_true=st_true+true4


    

In [22]:

    

val_types=[set(i) for i in valency]


    

In [24]:

    

vel_lens=[len(i) for i in val_types]


    

In [26]:

    

Counter(vel_lens)


    

    
Out[26]:





Counter({2: 1674, 3: 7471, 4: 1277, 5: 61, 6: 1})

In [27]:

    

val5=pickle.load(open('val5.pickle', 'rb'))
true5=pickle.load(open("True5.pickle",'rb'))


    

In [28]:

    

valency=valency+val5
st_true=st_true+true5


    

In [38]:

    

species=[[i.name for i in entry.species] for entry in st_true]


    

In [42]:

    

no_vals=[len(i) for i in valency]

no_spec=[len(i) for i in species]


    

In [44]:

    

np.all(np.array(no_spec)==np.array(no_vals))


    

    
Out[44]:





True

In [45]:

    

val2=pickle.load(open('val2.pickle', 'rb'))
true2=pickle.load(open("True2.pickle",'rb'))


    

In [46]:

    

valency=valency+val2
st_true=st_true+true2


    

In [47]:

    

val_types=[set(i) for i in valency]


    

In [48]:

    

species=[[i.name for i in entry.species] for entry in st_true]


    

In [49]:

    

val_lens=[len(i) for i in val_types]


    

In [50]:

    

no_vals=[len(i) for i in valency]

no_spec=[len(i) for i in species]


    

In [51]:

    

np.all(np.array(no_spec)==np.array(no_vals))


    

    
Out[51]:





True

In [52]:

    

with open("val_all.pickle","w") as f:
    pickle.dump(valency,f)

with open("struct_all.pickle","w") as f:
    pickle.dump(st_true,f)


    

In [53]:

    

len(valency)


    

    
Out[53]:





17311

In [64]:

    

st_true[0],st_true[0].species,valency[0]


    

    
Out[64]:





(Structure Summary
 Lattice
     abc : 4.0239864900000004 4.0239864900000004 4.0239864900000004
  angles : 90.0 90.0 90.0
  volume : 65.158269541098122
       A : 4.0239864900000004 0.0 2.4639810873953469e-16
       B : -2.4639810873953469e-16 4.0239864900000004 2.4639810873953469e-16
       C : 0.0 0.0 4.0239864900000004
 PeriodicSite: Nb (0.0000, 0.0000, 0.0000) [0.0000, 0.0000, 0.0000]
 PeriodicSite: Ag (2.0120, 2.0120, 2.0120) [0.5000, 0.5000, 0.5000]
 PeriodicSite: O (2.0120, 0.0000, 0.0000) [0.5000, 0.0000, 0.0000]
 PeriodicSite: O (-0.0000, 2.0120, 0.0000) [0.0000, 0.5000, 0.0000]
 PeriodicSite: O (0.0000, 0.0000, 2.0120) [0.0000, 0.0000, 0.5000],
 [Element Nb, Element Ag, Element O, Element O, Element O],
 [5, 1, -2, -2, -2])

In [57]:

    

Counter(val_lens)


    

    
Out[57]:





Counter({2: 2761, 3: 12499, 4: 1959, 5: 91, 6: 1})

In [61]:

    

len(st_masked),len(st)


    

    
Out[61]:





(24059, 26230)

In [ ]: