Create module perovskites_tolerance_factor

data/perovskites_tolerance_factor/electronegativities.csv

+H,2.2
+He,0
+Li,0.98
+Be,1.57
+B,2.04
+C,2.55
+N,3.04
+O,3.44
+F,3.98
+Ne,0
+Na,0.93
+Mg,1.31
+Al,1.61
+Si,1.9
+P,2.19
+S,2.58
+Cl,3.16
+Ar,0
+K,0.82
+Ca,1
+Sc,1.36
+Ti,1.54
+V,1.63
+Cr,1.66
+Mn,1.55
+Fe,1.83
+Co,1.88
+Ni,1.91
+Cu,1.9
+Zn,1.65
+Ga,1.81
+Ge,2.01
+As,2.18
+Se,2.55
+Br,2.96
+Kr,3
+Rb,0.82
+Sr,0.95
+Y,1.22
+Zr,1.33
+Nb,1.6
+Mo,2.16
+Tc,1.9
+Ru,2.2
+Rh,2.28
+Pd,2.2
+Ag,1.93
+Cd,1.69
+In,1.78
+Sn,1.96
+Sb,2.05
+Te,2.1
+I,2.66
+Xe,2.6
+Cs,0.79
+Ba,0.89
+La,1.1
+Ce,1.12
+Pr,1.13
+Nd,1.14
+Pm,1.13
+Sm,1.17
+Eu,1.2
+Gd,1.2
+Tb,1.1
+Dy,1.22
+Ho,1.23
+Er,1.24
+Tm,1.25
+Yb,1.1
+Lu,1.27
+Hf,1.3
+Ta,1.5
+W,2.36
+Re,1.9
+Os,2.2
+Ir,2.2
+Pt,2.28
+Au,2.54
+Hg,2
+Tl,1.62
+Pb,2.33
+Bi,2.02
+Po,2
+At,2.2
+Rn,0
+Fr,0.7
+Ra,0.9
+Ac,1.1
+Th,1.3
+Pa,1.5
+U,1.38
+Np,1.36
+Pu,1.28
+Am,1.3
+Cm,1.3
+Bk,1.3
+Cf,1.3
+Es,1.3
+Fm,1.3
+Md,1.3
+No,1.3
+Lr,1.3
+Rf,nan
+Db,nan
+Sg,nan
+Bh,nan
+Hs,nan
+Mt,nan

PredictPerovskites.py → perovskites_tolerance_factor/PredictPerovskites.py

@@ -3,7 +3,7 @@ import pandas as pd
 import os, json
 fjson = 'Shannon_radii_dict.json'
 if not os.path.exists(fjson):
-    from make_radii_dict import ionic_radii_dict as Shannon_dict    
+    from perovskites_tolerance_factor.make_radii_dict import ionic_radii_dict as Shannon_dict    
 else:
     with open(fjson) as f:
         Shannon_dict = json.load(f)
@@ -138,7 +138,7 @@ class PredictABX3(object):
         """
         cations = self.cations
         chi_dict = {}
-        with open('electronegativities.csv') as f:
+        with open('./electronegativities.csv') as f:
             for line in f:
                 line = line.split(',')
                 if line[0] in cations:

perovskites_tolerance_factor/electronegativities.csv

+H,2.2
+He,0
+Li,0.98
+Be,1.57
+B,2.04
+C,2.55
+N,3.04
+O,3.44
+F,3.98
+Ne,0
+Na,0.93
+Mg,1.31
+Al,1.61
+Si,1.9
+P,2.19
+S,2.58
+Cl,3.16
+Ar,0
+K,0.82
+Ca,1
+Sc,1.36
+Ti,1.54
+V,1.63
+Cr,1.66
+Mn,1.55
+Fe,1.83
+Co,1.88
+Ni,1.91
+Cu,1.9
+Zn,1.65
+Ga,1.81
+Ge,2.01
+As,2.18
+Se,2.55
+Br,2.96
+Kr,3
+Rb,0.82
+Sr,0.95
+Y,1.22
+Zr,1.33
+Nb,1.6
+Mo,2.16
+Tc,1.9
+Ru,2.2
+Rh,2.28
+Pd,2.2
+Ag,1.93
+Cd,1.69
+In,1.78
+Sn,1.96
+Sb,2.05
+Te,2.1
+I,2.66
+Xe,2.6
+Cs,0.79
+Ba,0.89
+La,1.1
+Ce,1.12
+Pr,1.13
+Nd,1.14
+Pm,1.13
+Sm,1.17
+Eu,1.2
+Gd,1.2
+Tb,1.1
+Dy,1.22
+Ho,1.23
+Er,1.24
+Tm,1.25
+Yb,1.1
+Lu,1.27
+Hf,1.3
+Ta,1.5
+W,2.36
+Re,1.9
+Os,2.2
+Ir,2.2
+Pt,2.28
+Au,2.54
+Hg,2
+Tl,1.62
+Pb,2.33
+Bi,2.02
+Po,2
+At,2.2
+Rn,0
+Fr,0.7
+Ra,0.9
+Ac,1.1
+Th,1.3
+Pa,1.5
+U,1.38
+Np,1.36
+Pu,1.28
+Am,1.3
+Cm,1.3
+Bk,1.3
+Cf,1.3
+Es,1.3
+Fm,1.3
+Md,1.3
+No,1.3
+Lr,1.3
+Rf,nan
+Db,nan
+Sg,nan
+Bh,nan
+Hs,nan
+Mt,nan

perovskites_tolerance_factor/make_radii_dict.py

+import numpy as np
+import pandas as pd
+import json
+
+df = pd.read_csv('./perovskites_tolerance_factor/Shannon_Effective_Ionic_Radii.csv')
+
+df = df.rename(columns = {'OX. State': 'ox',
+                          'Coord. #': 'coord',
+                          'Crystal Radius': 'rcryst',
+                          'Ionic Radius': 'rion',
+                          'Spin State' : 'spin'})
+    
+df['spin'] = [spin if spin in ['HS', 'LS'] else 'only_spin' for spin in df.spin.values]
+
+def get_el(row):
+    ION = row['ION']
+    if ' ' in ION:
+        return ION.split(' ')[0]
+    elif '+' in ION:
+        return ION.split('+')[0]
+    elif '-' in ION:
+        return ION.split('-')[0]
+
+df['el'] = df.apply(lambda row: get_el(row), axis = 1)
+
+el_to_ox = {}
+for el in df.el.values:
+    el_to_ox[el] = list(set(df.ox.get((df['el'] == el)).tolist()))
+ 
+ionic_radii_dict = {}
+for el in el_to_ox:
+    oxs = el_to_ox[el]
+    ox_to_coord = {}
+    for ox in oxs:
+        coords = df.coord.get((df['el'] == el) & (df['ox'] == ox)).tolist()
+        ox_to_coord[ox] = coords
+        coord_to_spin = {}
+        for coord in ox_to_coord[ox]:
+            spin = df.spin.get((df['el'] == el) & (df['ox'] == ox) & (df['coord'] == coord)).tolist()
+            coord_to_spin[coord] = spin
+            spin_to_rad = {}
+            for spin in coord_to_spin[coord]:
+                rad = df.rion.get((df['el'] == el) & (df['ox'] == ox) & (df['coord'] == coord) & (df['spin'] == spin)).tolist()[0]
+                spin_to_rad[spin] = rad  
+                coord_to_spin[coord] = spin_to_rad
+                ox_to_coord[ox] = coord_to_spin
+    ionic_radii_dict[el] = ox_to_coord
+
+spin_els = ['Cr', 'Mn', 'Fe', 'Co', 'Ni', 'Cu']
+starting_d = [4, 5, 6, 7, 8, 9]
+d_dict = dict(zip(spin_els, starting_d))
+for el in spin_els:
+    for ox in ionic_radii_dict[el].keys():
+        for coord in ionic_radii_dict[el][ox].keys():
+            if len(ionic_radii_dict[el][ox][coord].keys()) > 1:
+                num_d = d_dict[el] + 2 - ox
+                if num_d in [4, 5, 6, 7]:
+                    ionic_radii_dict[el][ox][coord]['only_spin'] = ionic_radii_dict[el][ox][coord]['HS']
+                else:
+                    ionic_radii_dict[el][ox][coord]['only_spin'] = ionic_radii_dict[el][ox][coord]['LS']
+            elif 'HS' in ionic_radii_dict[el][ox][coord].keys():
+                ionic_radii_dict[el][ox][coord]['only_spin'] = ionic_radii_dict[el][ox][coord]['HS']
+            elif 'LS' in ionic_radii_dict[el][ox][coord].keys():
+                ionic_radii_dict[el][ox][coord]['only_spin'] = ionic_radii_dict[el][ox][coord]['LS']
+                
+with open('Shannon_radii_dict.json', 'w') as f:
+    json.dump(ionic_radii_dict, f)    
\ No newline at end of file