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util_test.py
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# -*- coding: utf-8 -*-
"""
Created on Fri May 22 15:29:38 2015
@author: Richard Sheridan
"""
import numpy as np
from util import schultz_zimm, sumkd, meankd, lattice_parameters
def lattice_parameters_test():
result = lattice_parameters(.0282, 104, .25, 2.33333333333333)
data = 1.4177993142857144, 589.8045147428572
assert np.allclose(result, data)
def sumkd_test():
result = sumkd(np.arange(4,dtype=float).reshape(2,2))
data = np.array([[6.]])
assert np.allclose(result, data, atol=1e-14)
result = sumkd(np.arange(4,dtype=float).reshape(2,2), 1)
data = np.array([[1.],
[5.]])
assert np.allclose(result, data, atol=1e-14)
result = sumkd(np.arange(4,dtype=float).reshape(2,2), 0)
data = np.array([[2., 4.]])
assert np.allclose(result, data, atol=1e-14)
def meankd_test():
result = meankd(np.arange(4,dtype=float).reshape(2,2))
data = np.array([[1.5]])
assert np.allclose(result, data, atol=1e-14)
result = meankd(np.arange(4,dtype=float).reshape(2,2), 1)
data = np.array([[ 0.5],
[ 2.5]])
assert np.allclose(result, data, atol=1e-14)
result = meankd(np.arange(4,dtype=float).reshape(2,2), 0)
data = np.array([[ 1., 2.]])
assert np.allclose(result, data, atol=1e-14)
def schultz_zimm_test():
# uniform
pdi=1
nn=100
data = np.array(((
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 0., 1.)))
assert np.allclose(schultz_zimm(pdi,nn), data, atol=1e-14)
# too narrow
pdi=1.0000000001
nn=100
assert np.allclose(schultz_zimm(pdi,nn), data, atol=1e-14)
# broad
pdi=2
nn=30
data = np.array([ 3.27848972e-02, 3.17100805e-02, 3.06705004e-02,
2.96650018e-02, 2.86924673e-02, 2.77518164e-02,
2.68420036e-02, 2.59620181e-02, 2.51108819e-02,
2.42876492e-02, 2.34914054e-02, 2.27212655e-02,
2.19763738e-02, 2.12559026e-02, 2.05590512e-02,
1.98850454e-02, 1.92331360e-02, 1.86025988e-02,
1.79927331e-02, 1.74028611e-02, 1.68323275e-02,
1.62804982e-02, 1.57467599e-02, 1.52305197e-02,
1.47312039e-02, 1.42482576e-02, 1.37811442e-02,
1.33293445e-02, 1.28923566e-02, 1.24696949e-02,
1.20608897e-02, 1.16654867e-02, 1.12830465e-02,
1.09131443e-02, 1.05553688e-02, 1.02093227e-02,
9.87462129e-03, 9.55089270e-03, 9.23777719e-03,
8.93492683e-03, 8.64200509e-03, 8.35868646e-03,
8.08465612e-03, 7.81960957e-03, 7.56325228e-03,
7.31529937e-03, 7.07547533e-03, 6.84351366e-03,
6.61915660e-03, 6.40215483e-03, 6.19226723e-03,
5.98926056e-03, 5.79290925e-03, 5.60299509e-03,
5.41930706e-03, 5.24164105e-03, 5.06979961e-03,
4.90359181e-03, 4.74283295e-03, 4.58734439e-03,
4.43695335e-03, 4.29149272e-03, 4.15080086e-03,
4.01472142e-03, 3.88310319e-03, 3.75579993e-03,
3.63267016e-03, 3.51357707e-03, 3.39838831e-03,
3.28697589e-03, 3.17921600e-03, 3.07498890e-03,
2.97417878e-03, 2.87667360e-03, 2.78236502e-03,
2.69114825e-03, 2.60292191e-03, 2.51758798e-03,
2.43505163e-03, 2.35522114e-03, 2.27800781e-03,
2.20332583e-03, 2.13109222e-03, 2.06122670e-03,
1.99365165e-03, 1.92829198e-03, 1.86507505e-03,
1.80393062e-03, 1.74479074e-03, 1.68758969e-03,
1.63226392e-03, 1.57875194e-03, 1.52699430e-03,
1.47693347e-03, 1.42851383e-03, 1.38168158e-03,
1.33638467e-03, 1.29257277e-03, 1.25019719e-03,
1.20921085e-03, 1.16956821e-03, 1.13122520e-03,
1.09413923e-03, 1.05826908e-03, 1.02357489e-03,
9.90018113e-04, 9.57561458e-04, 9.26168860e-04,
8.95805433e-04, 8.66437437e-04, 8.38032240e-04,
8.10558275e-04, 7.83985014e-04, 7.58282928e-04,
7.33423457e-04, 7.09378976e-04, 6.86122767e-04,
6.63628987e-04, 6.41872641e-04, 6.20829553e-04,
6.00476339e-04, 5.80790383e-04, 5.61749809e-04,
5.43333460e-04, 5.25520871e-04, 5.08292247e-04,
4.91628445e-04, 4.75510948e-04, 4.59921844e-04,
4.44843813e-04, 4.30260098e-04, 4.16154494e-04,
4.02511327e-04, 3.89315436e-04, 3.76552158e-04,
3.64207310e-04, 3.52267174e-04, 3.40718482e-04,
3.29548402e-04, 3.18744520e-04, 3.08294832e-04,
2.98187725e-04, 2.88411969e-04, 2.78956700e-04,
2.69811411e-04, 2.60965941e-04, 2.52410460e-04,
2.44135461e-04, 2.36131748e-04, 2.28390429e-04,
2.20902900e-04, 2.13660842e-04, 2.06656206e-04,
1.99881210e-04, 1.93328324e-04, 1.86990268e-04,
1.80859998e-04, 1.74930702e-04, 1.69195791e-04,
1.63648893e-04, 1.58283844e-04, 1.53094683e-04,
1.48075642e-04, 1.43221145e-04, 1.38525797e-04,
1.33984382e-04, 1.29591851e-04, 1.25343325e-04,
1.21234082e-04, 1.17259556e-04, 1.13415331e-04,
1.09697134e-04, 1.06100834e-04, 1.02622435e-04,
9.92580712e-05, 9.60040046e-05, 9.28566190e-05,
8.98124169e-05, 8.68680156e-05, 8.40201433e-05,
8.12656354e-05, 7.86014310e-05, 7.60245696e-05,
7.35321877e-05, 7.11215159e-05, 6.87898752e-05,
6.65346749e-05, 6.43534088e-05, 6.22436531e-05,
6.02030634e-05, 5.82293722e-05, 5.63203864e-05,
5.44739845e-05, 5.26881148e-05, 5.09607930e-05,
4.92900995e-05, 4.76741778e-05, 4.61112323e-05,
4.45995263e-05, 4.31373799e-05, 4.17231684e-05,
4.03553202e-05, 3.90323155e-05, 3.77526840e-05,
3.65150038e-05, 3.53178996e-05, 3.41600411e-05,
3.30401417e-05, 3.19569570e-05, 3.09092834e-05,
2.98959565e-05, 2.89158505e-05, 2.79678762e-05,
2.70509801e-05, 2.61641435e-05, 2.53063809e-05,
2.44767390e-05, 2.36742961e-05, 2.28981603e-05,
2.21474693e-05, 2.14213889e-05, 2.07191123e-05,
2.00398590e-05, 1.93828742e-05, 1.87474280e-05,
1.81328142e-05, 1.75383499e-05, 1.69633744e-05,
1.64072488e-05, 1.58693552e-05, 1.53490959e-05,
1.48458927e-05, 1.43591864e-05, 1.38884363e-05,
1.34331192e-05, 1.29927292e-05, 1.25667768e-05,
1.21547889e-05, 1.17563075e-05, 1.13708899e-05,
1.09981078e-05, 1.06375469e-05, 1.02888067e-05,
9.95149945e-06, 9.62525049e-06, 9.30969725e-06,
9.00448907e-06, 8.70928680e-06, 8.42376242e-06,
8.14759864e-06, 7.88048858e-06, 7.62213544e-06,
7.37225212e-06, 7.13056094e-06, 6.89679335e-06,
6.67068957e-06, 6.45199835e-06, 6.24047669e-06,
6.03588953e-06, 5.83800953e-06, 5.64661681e-06,
5.46149870e-06, 5.28244947e-06, 5.10927018e-06,
4.94176838e-06, 4.77975794e-06, 4.62305884e-06,
4.47149694e-06, 4.32490383e-06, 4.18311662e-06,
4.04597775e-06, 3.91333482e-06, 3.78504044e-06,
3.66095206e-06, 3.54093177e-06, 3.42484622e-06,
3.31256641e-06, 3.20396756e-06, 3.09892901e-06,
2.99733403e-06, 2.89906974e-06, 2.80402693e-06,
2.71209999e-06, 2.62318678e-06, 2.53718848e-06,
2.45400955e-06, 2.37355755e-06, 2.29574308e-06,
2.22047967e-06, 2.14768368e-06, 2.07727424e-06,
2.00917309e-06, 1.94330456e-06, 1.87959546e-06,
1.81797499e-06, 1.75837468e-06, 1.70072830e-06,
1.64497180e-06, 1.59104321e-06, 1.53888260e-06,
1.48843203e-06, 1.43963543e-06, 1.39243856e-06,
1.34678900e-06, 1.30263600e-06, 1.25993051e-06,
1.21862508e-06, 1.17867380e-06, 1.14003227e-06,
1.10265757e-06, 1.06650815e-06, 1.03154386e-06])
result = schultz_zimm(pdi,nn)
assert np.allclose(result, data, atol=1e-14)
def main():
schultz_zimm_test()
sumkd_test()
meankd_test()
print('all tests passed')
if __name__ == '__main__':
main()