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Magpie data updates #289

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merged 4 commits into from
Jul 12, 2024
Merged

Magpie data updates #289

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78a9356
Add magpie data to data_loader
Jul 12, 2024
edbb91a
Add magpie properties
Jul 12, 2024
0f3355f
Add magpie data
Jul 12, 2024
b563be1
Update smact/data_loader.py
AntObi Jul 12, 2024
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26 changes: 26 additions & 0 deletions smact/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -73,6 +73,16 @@ class Element:

Element.HHI_r (float) : Hirfindahl-Hirschman Index for elemental reserves

Element.mendeleev (int): Mendeleev number

Element.AtomicWeight (float): Atomic weight

Element.MeltingT (float): Melting temperature in K

Element.num_valence (int): Number of valence electrons



Raises:
NameError: Element not found in element.txt
Warning: Element not found in Eigenvalues.csv
Expand Down Expand Up @@ -140,6 +150,18 @@ def __init__(
else:
sse_Pauling = None

magpie_data = data_loader.lookup_element_magpie_data(symbol)
if magpie_data:
mendeleev = magpie_data["MendeleevNumber"]
AtomicWeight = magpie_data["AtomicWeight"]
MeltingT = magpie_data["MeltingT"]
num_valence = magpie_data["NValence"]
else:
mendeleev = None
AtomicWeight = None
MeltingT = None
num_valence = None

for attribute, value in (
("coord_envs", coord_envs),
("covalent_radius", dataset["r_cov"]),
Expand Down Expand Up @@ -174,6 +196,10 @@ def __init__(
("SSE", sse),
("SSEPauling", sse_Pauling),
("symbol", symbol),
("mendeleev", mendeleev),
("AtomicWeight", AtomicWeight),
("MeltingT", MeltingT),
("num_valence", num_valence),
# ('vdw_radius', dataset['RVdW']),
):
setattr(self, attribute, value)
Expand Down
98 changes: 98 additions & 0 deletions smact/data/magpie.csv
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Open in desktop
Original file line number Diff line number Diff line change
@@ -0,0 +1,98 @@
element,Number,MendeleevNumber,AtomicWeight,MeltingT,Column,Row,CovalentRadius,Electronegativity,NsValence,NpValence,NdValence,NfValence,NValence,NsUnfilled,NpUnfilled,NdUnfilled,NfUnfilled,NUnfilled,GSvolume_pa,GSbandgap,GSmagmom,SpaceGroupNumber
H,1.0,92.0,1.00794,14.01,1.0,1.0,31.0,2.2,1.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,1.0,6.615,7.853,0.0,194.0
He,2.0,98.0,4.002602,1211.4,18.0,1.0,28.0,1.63,2.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,12.305,18.098,0.0,225.0
Li,3.0,1.0,6.941,453.69,1.0,2.0,128.0,0.98,1.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,1.0,16.5933333333,0.0,0.0,229.0
Be,4.0,67.0,9.012182,1560.0,2.0,2.0,96.0,1.57,2.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,7.89,0.0,0.0,194.0
B,5.0,72.0,10.811,2348.0,13.0,2.0,84.0,2.04,2.0,1.0,0.0,0.0,3.0,0.0,5.0,0.0,0.0,5.0,7.1725,1.524,0.0,166.0
C,6.0,77.0,12.0107,3823.0,14.0,2.0,76.0,2.55,2.0,2.0,0.0,0.0,4.0,0.0,4.0,0.0,0.0,4.0,5.64,4.496,0.0,194.0
N,7.0,82.0,14.0067,63.05,15.0,2.0,71.0,3.04,2.0,3.0,0.0,0.0,5.0,0.0,3.0,0.0,0.0,3.0,14.76875,6.437,0.0,194.0
O,8.0,87.0,15.9994,54.8,16.0,2.0,66.0,3.44,2.0,4.0,0.0,0.0,6.0,0.0,2.0,0.0,0.0,2.0,9.105,0.0,0.0,12.0
F,9.0,93.0,18.9984032,53.5,17.0,2.0,57.0,3.98,2.0,5.0,0.0,0.0,7.0,0.0,1.0,0.0,0.0,1.0,9.7075,1.97,0.0,15.0
Ne,10.0,99.0,20.1791,24.56,18.0,2.0,58.0,1.63,2.0,6.0,0.0,0.0,8.0,0.0,0.0,0.0,0.0,0.0,12.64,13.088,0.0,225.0
Na,11.0,2.0,22.98976928,370.87,1.0,3.0,166.0,0.93,1.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,1.0,29.2433333333,0.0,0.0,229.0
Mg,12.0,68.0,24.305,923.0,2.0,3.0,141.0,1.31,2.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,22.89,0.0,0.0,194.0
Al,13.0,73.0,26.9815386,933.47,13.0,3.0,121.0,1.61,2.0,1.0,0.0,0.0,3.0,0.0,5.0,0.0,0.0,5.0,16.48,0.0,0.0,225.0
Si,14.0,78.0,28.0855,1687.0,14.0,3.0,111.0,1.9,2.0,2.0,0.0,0.0,4.0,0.0,4.0,0.0,0.0,4.0,20.44,0.773,0.0,227.0
P,15.0,83.0,30.973762,317.3,15.0,3.0,107.0,2.19,2.0,3.0,0.0,0.0,5.0,0.0,3.0,0.0,0.0,3.0,22.5702380952,1.625,0.0,2.0
S,16.0,88.0,32.065,388.36,16.0,3.0,105.0,2.58,2.0,4.0,0.0,0.0,6.0,0.0,2.0,0.0,0.0,2.0,25.786875,2.202,0.0,70.0
Cl,17.0,94.0,35.453,171.6,17.0,3.0,102.0,3.16,2.0,5.0,0.0,0.0,7.0,0.0,1.0,0.0,0.0,1.0,24.4975,2.493,0.0,64.0
Ar,18.0,100.0,39.948,83.8,18.0,3.0,106.0,1.63,2.0,6.0,0.0,0.0,8.0,0.0,0.0,0.0,0.0,0.0,28.54,9.26,0.0,225.0
K,19.0,3.0,39.0983,336.53,1.0,4.0,203.0,0.82,1.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,1.0,73.1066666667,0.0,0.0,229.0
Ca,20.0,7.0,40.078,1115.0,2.0,4.0,176.0,1.0,2.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,37.77,0.0,0.0,225.0
Sc,21.0,11.0,44.955912,1814.0,3.0,4.0,170.0,1.36,2.0,0.0,1.0,0.0,3.0,0.0,0.0,9.0,0.0,9.0,22.235,0.0,6.35e-06,194.0
Ti,22.0,43.0,47.867,1941.0,4.0,4.0,160.0,1.54,2.0,0.0,2.0,0.0,4.0,0.0,0.0,8.0,0.0,8.0,16.69,0.0,2.25333333333e-05,194.0
V,23.0,46.0,50.9415,2183.0,5.0,4.0,153.0,1.63,2.0,0.0,3.0,0.0,5.0,0.0,0.0,7.0,0.0,7.0,13.01,0.0,0.0,229.0
Cr,24.0,49.0,51.9961,2180.0,6.0,4.0,139.0,1.66,1.0,0.0,5.0,0.0,6.0,1.0,0.0,5.0,0.0,6.0,11.19,0.0,0.0,229.0
Mn,25.0,52.0,54.938045,1519.0,7.0,4.0,139.0,1.55,2.0,0.0,5.0,0.0,7.0,0.0,0.0,5.0,0.0,5.0,10.4875862069,0.0,0.000310120689655,217.0
Fe,26.0,55.0,55.845,1811.0,8.0,4.0,132.0,1.83,2.0,0.0,6.0,0.0,8.0,0.0,0.0,4.0,0.0,4.0,10.73,0.0,2.1106628,229.0
Co,27.0,58.0,58.933195,1768.0,9.0,4.0,126.0,1.88,2.0,0.0,7.0,0.0,9.0,0.0,0.0,3.0,0.0,3.0,10.245,0.0,1.5484712,194.0
Ni,28.0,61.0,58.6934,1728.0,10.0,4.0,124.0,1.91,2.0,0.0,8.0,0.0,10.0,0.0,0.0,2.0,0.0,2.0,10.32,0.0,0.5953947,225.0
Cu,29.0,64.0,63.546,1357.77,11.0,4.0,132.0,1.9,1.0,0.0,10.0,0.0,11.0,1.0,0.0,0.0,0.0,1.0,11.07,0.0,0.0,225.0
Zn,30.0,69.0,65.38,692.68,12.0,4.0,122.0,1.65,2.0,0.0,10.0,0.0,12.0,0.0,0.0,0.0,0.0,0.0,13.96,0.0,0.0,194.0
Ga,31.0,74.0,69.723,302.91,13.0,4.0,122.0,1.81,2.0,1.0,10.0,0.0,13.0,0.0,5.0,0.0,0.0,5.0,18.8575,0.0,0.0,64.0
Ge,32.0,79.0,72.64,1211.4,14.0,4.0,120.0,2.01,2.0,2.0,10.0,0.0,14.0,0.0,4.0,0.0,0.0,4.0,23.005,0.383,0.0,225.0
As,33.0,84.0,74.9216,1090.0,15.0,4.0,119.0,2.18,2.0,3.0,10.0,0.0,15.0,0.0,3.0,0.0,0.0,3.0,22.175,0.0,0.0,166.0
Se,34.0,89.0,78.96,494.0,16.0,4.0,120.0,2.55,2.0,4.0,10.0,0.0,16.0,0.0,2.0,0.0,0.0,2.0,25.92,0.799,0.0,14.0
Br,35.0,95.0,79.904,265.8,17.0,4.0,120.0,2.96,2.0,5.0,10.0,0.0,17.0,0.0,1.0,0.0,0.0,1.0,29.48,1.457,0.0,64.0
Kr,36.0,101.0,83.798,115.79,18.0,4.0,116.0,3.0,2.0,6.0,10.0,0.0,18.0,0.0,0.0,0.0,0.0,0.0,36.06,7.535,0.0,225.0
Rb,37.0,4.0,85.4678,312.46,1.0,5.0,220.0,0.82,1.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,1.0,90.7225,0.0,0.0,229.0
Sr,38.0,8.0,87.62,1050.0,2.0,5.0,195.0,0.95,2.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,54.23,0.0,0.0,225.0
Y,39.0,12.0,88.90585,1799.0,3.0,5.0,190.0,1.22,2.0,0.0,1.0,0.0,3.0,0.0,0.0,9.0,0.0,9.0,32.365,0.0,0.0,194.0
Zr,40.0,44.0,91.224,2128.0,4.0,5.0,175.0,1.33,2.0,0.0,2.0,0.0,4.0,0.0,0.0,8.0,0.0,8.0,23.195,0.0,0.0,194.0
Nb,41.0,47.0,92.90638,2750.0,5.0,5.0,164.0,1.6,1.0,0.0,4.0,0.0,5.0,1.0,0.0,6.0,0.0,7.0,18.18,0.0,0.0,229.0
Mo,42.0,50.0,95.96,2896.0,6.0,5.0,154.0,2.16,1.0,0.0,5.0,0.0,6.0,1.0,0.0,5.0,0.0,6.0,15.69,0.0,0.0,229.0
Tc,43.0,53.0,98.0,2430.0,7.0,5.0,147.0,1.9,2.0,0.0,5.0,0.0,7.0,0.0,0.0,5.0,0.0,5.0,14.285,0.0,0.0,194.0
Ru,44.0,56.0,101.07,2607.0,8.0,5.0,146.0,2.2,1.0,0.0,7.0,0.0,8.0,1.0,0.0,3.0,0.0,4.0,13.51,0.0,0.0,194.0
Rh,45.0,59.0,102.9055,2237.0,9.0,5.0,142.0,2.28,1.0,0.0,8.0,0.0,9.0,1.0,0.0,2.0,0.0,3.0,13.64,0.0,0.0,225.0
Pd,46.0,62.0,106.42,1828.05,10.0,5.0,139.0,2.2,0.0,0.0,10.0,0.0,10.0,0.0,0.0,0.0,0.0,0.0,14.41,0.0,0.0,225.0
Ag,47.0,65.0,107.8682,1234.93,11.0,5.0,145.0,1.93,1.0,0.0,10.0,0.0,11.0,1.0,0.0,0.0,0.0,1.0,16.33,0.0,0.0,225.0
Cd,48.0,70.0,112.411,594.22,12.0,5.0,144.0,1.69,2.0,0.0,10.0,0.0,12.0,0.0,0.0,0.0,0.0,0.0,19.495,0.0,0.0,194.0
In,49.0,75.0,114.818,429.75,13.0,5.0,142.0,1.78,2.0,1.0,10.0,0.0,13.0,0.0,5.0,0.0,0.0,5.0,24.26,0.0,0.0,139.0
Sn,50.0,80.0,118.71,505.08,14.0,5.0,139.0,1.96,2.0,2.0,10.0,0.0,14.0,0.0,4.0,0.0,0.0,4.0,33.285,0.0,0.0,141.0
Sb,51.0,85.0,121.76,903.78,15.0,5.0,139.0,2.05,2.0,3.0,10.0,0.0,15.0,0.0,3.0,0.0,0.0,3.0,31.56,0.0,0.0,166.0
Te,52.0,90.0,127.6,722.66,16.0,5.0,138.0,2.1,2.0,4.0,10.0,0.0,16.0,0.0,2.0,0.0,0.0,2.0,34.7633333333,0.464,0.0,152.0
I,53.0,96.0,126.90447,386.85,17.0,5.0,139.0,2.66,2.0,5.0,10.0,0.0,17.0,0.0,1.0,0.0,0.0,1.0,43.015,1.062,0.0,64.0
Xe,54.0,102.0,131.293,161.3,18.0,5.0,140.0,2.6,2.0,6.0,10.0,0.0,18.0,0.0,0.0,0.0,0.0,0.0,53.65,6.456,0.0,225.0
Cs,55.0,5.0,132.9054519,301.59,1.0,6.0,244.0,0.79,1.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,1.0,115.765,0.0,0.0,229.0
Ba,56.0,9.0,137.327,1000.0,2.0,6.0,215.0,0.89,2.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,63.59,0.0,0.0,229.0
La,57.0,13.0,138.90547,1193.0,3.0,6.0,207.0,1.1,2.0,0.0,1.0,0.0,3.0,0.0,0.0,9.0,0.0,9.0,36.8975,0.0,0.0,194.0
Ce,58.0,15.0,140.116,1071.0,3.0,6.0,204.0,1.12,2.0,0.0,1.0,1.0,4.0,0.0,0.0,9.0,13.0,22.0,37.24,0.0,0.0,194.0
Pr,59.0,17.0,140.90765,1204.0,3.0,6.0,203.0,1.13,2.0,0.0,0.0,3.0,5.0,0.0,0.0,0.0,11.0,11.0,35.675,0.0,0.0,194.0
Nd,60.0,19.0,144.242,1294.0,3.0,6.0,201.0,1.14,2.0,0.0,0.0,4.0,6.0,0.0,0.0,0.0,10.0,10.0,34.81,0.0,0.0,194.0
Pm,61.0,21.0,145.0,1373.0,3.0,6.0,199.0,1.155,2.0,0.0,0.0,5.0,7.0,0.0,0.0,0.0,9.0,9.0,33.8425,0.0,0.0,194.0
Sm,62.0,23.0,150.36,1345.0,3.0,6.0,198.0,1.17,2.0,0.0,0.0,6.0,8.0,0.0,0.0,0.0,8.0,8.0,33.23,0.0,0.0,166.0
Eu,63.0,25.0,151.964,1095.0,3.0,6.0,198.0,1.185,2.0,0.0,0.0,7.0,9.0,0.0,0.0,0.0,7.0,7.0,36.46,0.0,0.0,229.0
Gd,64.0,27.0,157.25,1586.0,3.0,6.0,196.0,1.2,2.0,0.0,1.0,7.0,10.0,0.0,0.0,9.0,7.0,16.0,32.05,0.0,0.0,194.0
Tb,65.0,29.0,158.92535,1629.0,3.0,6.0,194.0,1.21,2.0,0.0,0.0,9.0,11.0,0.0,0.0,0.0,5.0,5.0,31.7366666667,0.0,0.0,194.0
Dy,66.0,31.0,162.5,1685.0,3.0,6.0,192.0,1.22,2.0,0.0,0.0,10.0,12.0,0.0,0.0,0.0,4.0,4.0,31.24,0.0,0.0,194.0
Ho,67.0,33.0,164.93032,1747.0,3.0,6.0,192.0,1.23,2.0,0.0,0.0,11.0,13.0,0.0,0.0,0.0,3.0,3.0,30.7333333333,0.0,0.0,194.0
Er,68.0,35.0,167.259,1770.0,3.0,6.0,189.0,1.24,2.0,0.0,0.0,12.0,14.0,0.0,0.0,0.0,2.0,2.0,30.585,0.0,0.0,194.0
Tm,69.0,37.0,168.93421,1818.0,3.0,6.0,190.0,1.25,2.0,0.0,0.0,13.0,15.0,0.0,0.0,0.0,1.0,1.0,29.78,0.0,0.0,194.0
Yb,70.0,39.0,173.054,1092.0,3.0,6.0,187.0,1.26,2.0,0.0,0.0,14.0,16.0,0.0,0.0,0.0,0.0,0.0,34.12,0.0,0.0,225.0
Lu,71.0,41.0,174.9668,1936.0,3.0,6.0,187.0,1.27,2.0,0.0,1.0,14.0,17.0,0.0,0.0,9.0,0.0,9.0,28.865,0.0,0.0022471,194.0
Hf,72.0,45.0,178.49,2506.0,4.0,6.0,175.0,1.3,2.0,0.0,2.0,14.0,18.0,0.0,0.0,8.0,0.0,8.0,22.2,0.0,0.0,194.0
Ta,73.0,48.0,180.94788,3290.0,5.0,6.0,170.0,1.5,2.0,0.0,3.0,14.0,19.0,0.0,0.0,7.0,0.0,7.0,18.12,0.0,0.0,229.0
W,74.0,51.0,183.84,3695.0,6.0,6.0,162.0,2.36,2.0,0.0,4.0,14.0,20.0,0.0,0.0,6.0,0.0,6.0,16.05,0.0,0.0,229.0
Re,75.0,54.0,186.207,3459.0,7.0,6.0,151.0,1.9,2.0,0.0,5.0,14.0,21.0,0.0,0.0,5.0,0.0,5.0,14.655,0.0,0.0,194.0
Os,76.0,57.0,190.23,3306.0,8.0,6.0,144.0,2.2,2.0,0.0,6.0,14.0,22.0,0.0,0.0,4.0,0.0,4.0,14.09,0.0,0.0,194.0
Ir,77.0,60.0,192.217,2739.0,9.0,6.0,141.0,2.2,2.0,0.0,7.0,14.0,23.0,0.0,0.0,3.0,0.0,3.0,14.21,0.0,0.0,225.0
Pt,78.0,63.0,195.084,2041.4,10.0,6.0,136.0,2.28,1.0,0.0,9.0,14.0,24.0,1.0,0.0,1.0,0.0,2.0,15.02,0.0,0.0,225.0
Au,79.0,66.0,196.966569,1337.33,11.0,6.0,136.0,2.54,1.0,0.0,10.0,14.0,25.0,1.0,0.0,0.0,0.0,1.0,16.7,0.0,0.0,225.0
Hg,80.0,71.0,200.59,234.32,12.0,6.0,132.0,2.0,2.0,0.0,10.0,14.0,26.0,0.0,0.0,0.0,0.0,0.0,25.2375862069,0.0,0.0,166.0
Tl,81.0,76.0,204.3833,577.0,13.0,6.0,145.0,1.62,2.0,1.0,10.0,14.0,27.0,0.0,5.0,0.0,0.0,5.0,26.91,0.0,0.0,194.0
Pb,82.0,81.0,207.2,600.61,14.0,6.0,146.0,2.33,2.0,2.0,10.0,14.0,28.0,0.0,4.0,0.0,0.0,4.0,28.11,0.0,0.0,225.0
Bi,83.0,86.0,208.9804,544.4,15.0,6.0,148.0,2.02,2.0,3.0,10.0,14.0,29.0,0.0,3.0,0.0,0.0,3.0,32.95,0.0,0.0,12.0
Po,84.0,91.0,209.0,527.0,16.0,6.0,140.0,2.0,2.0,4.0,10.0,14.0,30.0,0.0,2.0,0.0,0.0,2.0,38.73125,0.0,0.0,221.0
At,85.0,97.0,210.0,575.0,17.0,6.0,150.0,2.2,2.0,5.0,10.0,14.0,31.0,0.0,1.0,0.0,0.0,1.0,38.73125,0.0,0.0,194.0
Rn,86.0,103.0,222.0,202.0,18.0,6.0,150.0,1.63,2.0,6.0,10.0,14.0,32.0,0.0,0.0,0.0,0.0,0.0,38.73125,0.0,0.0,194.0
Fr,87.0,6.0,223.0,1211.4,1.0,7.0,260.0,0.7,1.0,0.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0,1.0,38.73125,0.0,0.0,194.0
Ra,88.0,10.0,226.0,973.0,2.0,7.0,221.0,0.9,2.0,0.0,0.0,0.0,2.0,0.0,0.0,0.0,0.0,0.0,38.73125,0.0,0.0,229.0
Ac,89.0,14.0,227.0,1323.0,3.0,7.0,215.0,1.1,2.0,0.0,1.0,0.0,3.0,0.0,0.0,9.0,0.0,9.0,44.5125,0.0,0.0,225.0
Th,90.0,16.0,232.03806,2023.0,3.0,7.0,206.0,1.3,2.0,0.0,2.0,0.0,4.0,0.0,0.0,8.0,0.0,8.0,32.37,0.0,0.0,225.0
Pa,91.0,18.0,231.03586,1845.0,3.0,7.0,200.0,1.5,2.0,0.0,1.0,2.0,5.0,0.0,0.0,9.0,12.0,21.0,25.18,0.0,0.0,139.0
U,92.0,20.0,238.02891,1408.0,3.0,7.0,196.0,1.38,2.0,0.0,1.0,3.0,6.0,0.0,0.0,9.0,11.0,20.0,20.025,0.0,0.0,63.0
Np,93.0,22.0,237.0,917.0,3.0,7.0,190.0,1.36,2.0,0.0,1.0,4.0,7.0,0.0,0.0,9.0,10.0,19.0,18.45375,0.0,0.0,62.0
Pu,94.0,24.0,244.0,913.0,3.0,7.0,187.0,1.28,2.0,0.0,0.0,6.0,8.0,0.0,0.0,0.0,8.0,8.0,18.08,0.0,0.3180036375,11.0
Am,95.0,26.0,243.0,1449.0,3.0,7.0,180.0,1.3,2.0,0.0,0.0,7.0,9.0,0.0,0.0,0.0,7.0,7.0,18.08,0.0,0.3180036375,194.0
Cm,96.0,28.0,247.0,1618.0,3.0,7.0,169.0,1.3,2.0,0.0,1.0,7.0,10.0,0.0,0.0,9.0,7.0,16.0,18.08,0.0,0.3180036375,194.0
Bk,97.0,30.0,247.0,1323.0,3.0,7.0,146.0,1.3,2.0,0.0,0.0,9.0,11.0,0.0,0.0,0.0,5.0,5.0,18.08,0.0,0.3180036375,194.0
82 changes: 82 additions & 0 deletions smact/data_loader.py
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Original file line number Diff line number Diff line change
Expand Up @@ -13,6 +13,8 @@
import csv
import os

import pandas as pd

from smact import data_directory

# Module-level switch: print "verbose" warning messages
Expand Down Expand Up @@ -822,3 +824,83 @@
)

return None


_element_magpie_data = None


def lookup_element_magpie_data(symbol: str, copy: bool = True):
"""
Retrieve element data contained in the Magpie representation.

Taken from Ward, L., Agrawal, A., Choudhary, A. et al.
A general-purpose machine learning framework for
predicting properties of inorganic materials.
npj Comput Mater 2, 16028 (2016).
https://doi.org/10.1038/npjcompumats.2016.28

Args:
symbol : the atomic symbol of the element to look up.
copy: if True (default), return a copy of the data dictionary,
rather than a reference to a cached object -- only use
copy=False in performance-sensitive code and where you are
certain the dictionary will not be modified!

Returns:
list:
Magpie features.
Returns None if the element was not found among the external
data.

Magpie features are dictionaries with the keys:




"""

global _element_magpie_data

if _element_magpie_data is None:
_element_magpie_data = {}

df = pd.read_csv(os.path.join(data_directory, "magpie.csv"))
for index, row in df.iterrows():
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key = row.iloc[0]

dataset = {
"Number": int(row.iloc[1]),
"MendeleevNumber": int(row.iloc[2]),
"AtomicWeight": float(row.iloc[3]),
"MeltingT": float(row.iloc[4]),
"Column": int(row.iloc[5]),
"Row": int(row.iloc[6]),
"CovalentRadius": float(row.iloc[7]),
"Electronegativity": float(row.iloc[8]),
"NsValence": int(row.iloc[9]),
"NpValence": int(row.iloc[10]),
"NdValence": int(row.iloc[11]),
"NfValence": int(row.iloc[12]),
"NValence": int(row.iloc[13]),
"NsUnfilled": int(row.iloc[14]),
"NpUnfilled": int(row.iloc[15]),
"NdUnfilled": int(row.iloc[16]),
"NfUnfilled": int(row.iloc[17]),
"NUnfilled": int(row.iloc[18]),
"GSvolume_pa": float(row.iloc[19]),
"GSbandgap": float(row.iloc[20]),
"GSmagmom": float(row.iloc[21]),
"SpaceGroupNumber": int(row.iloc[22]),
}
_element_magpie_data[key] = dataset

if symbol in _element_magpie_data:
return _element_magpie_data[symbol]
else:
if _print_warnings:
print(

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"WARNING: Magpie data for element {} not "
"found.".format(symbol)
)

return None