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Commit 5015902e authored by Malthe Kjær Bisbo's avatar Malthe Kjær Bisbo
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slight changes to descriptors and prior

parent dd3edadb
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Showing with 3341 additions and 5896 deletions
surrogate/#test_gpr.py# deleted 100644 → 0
View file @ dd3edadb
import numpy as np
import unittest
from gpr import gpr
class test_kernel(unittest.TestCase):
@classmethod
def setUpClass(cls):
print('setupClass')
@classmethod
def tearDownClass(cls):
print('teardownClass')
def setUp(self):
print('setUp')
#self.kernel = gauss_kernel()
self.gpr = gpr()
def tearDown(self):
print('tearDown\n')
def test_jac(self):
x1 = np.array([1.,2.,3.])
x2 = np.array([1.5,2.,1.])
x3 = np.array([3.,1.,1.])
y = np.c_[x1,x2,x3].T
np.testing.assert_almost_equal(self.kernel.kernel_jacobian(x1,x2),
self.kernel.numerical_jacobian(x1,x2))
np.testing.assert_almost_equal(self.kernel.kernel_jacobian(x1,y),
self.kernel.numerical_jacobian(x1,y))
np.testing.assert_almost_equal(self.kernel.kernel_jacobian(x2,y),
self.kernel.numerical_jacobian(x2,y))
def test_hyper_jac(self):
x1 = np.array([1.,2.,3.])
x2 = np.array([1.5,2.,1.])
x3 = np.array([3.,1.,1.])
X = np.c_[x1,x2,x3].T
np.testing.assert_almost_equal(self.kernel.kernel_hyperparameter_gradient(X),
self.kernel.numerical_hyperparameter_gradient(X))
if __name__ == '__main__':
unittest.main()
surrogate/#test_kernel.py# deleted 100644 → 0
View file @ dd3edadb
import numpy as np
import unittest
from kernel import gauss_kernel, double_gauss_kernel
class test_kernel(unittest.TestCase):
@classmethod
def setUpClass(cls):
print('setupClass')
@classmethod
def tearDownClass(cls):
print('teardownClass')
def setUp(self):
print('setUp')
#self.kernel = gauss_kernel()
self.kernel = double_gauss_kernel()
def tearDown(self):
print('tearDown\n')
def test_jac(self):
x1 = np.array([1.,2.,3.])
x2 = np.array([1.5,2.,1.])
x3 = np.array([3.,1.,1.])
y = np.c_[x1,x2,x3].T
np.testing.assert_almost_equal(self.kernel.kernel_jacobian(x1,x2),
self.kernel.numerical_jacobian(x1,x2))
np.testing.assert_almost_equal(self.kernel.kernel_jacobian(x1,y),
self.kernel.numerical_jacobian(x1,y))
np.testing.assert_almost_equal(self.kernel.kernel_jacobian(x2,y),
self.kernel.numerical_jacobian(x2,y))
def test_hyper_jac(self):
x1 = np.array([1.,2.,3.])
x2 = np.array([1.5,2.,1.])
x3 = np.array([3.,1.,1.])
X = np.c_[x1,x2,x3].T
np.testing.assert_almost_equal(self.kernel.kernel_hyperparameter_gradient(X),
self.kernel.numerical_hyperparameter_gradient(X))
if __name__ == '__main__':
unittest.main()
surrogate/.#test_gpr.py deleted 120000 → 0
View file @ dd3edadb
mkb@s81n11.grendel.cscaa.dk.9244:1576483191
\ No newline at end of file
surrogate/.#test_kernel.py deleted 120000 → 0
View file @ dd3edadb
mkb@s81n11.grendel.cscaa.dk.9244:1576483191
\ No newline at end of file
surrogate/delta_functions_multi/delta.html deleted 100644 → 0
View file @ dd3edadb
This source diff could not be displayed because it is too large. You can view the blob instead.
surrogate/featureCalculators_multi/angular_fingerprintFeature_cy.pyx → surrogate/descriptor/fingerprint.pyx
View file @ 5015902e
......@@ -91,10 +91,10 @@ def convert_atom_types(num):
num_converted[i] = j
return num_converted
class Angular_Fingerprint(object):
class Fingerprint(object):
""" comparator for construction of angular fingerprints
"""
def __init__(self, atoms, Rc1=4.0, Rc2=4.0, binwidth1=0.1, Nbins2=30, sigma1=0.2, sigma2=0.10, nsigma=4, eta=1, gamma=3, use_angular=True):
def __init__(self, Rc1=6.0, Rc2=4.0, binwidth1=0.2, Nbins2=30, sigma1=0.2, sigma2=0.2, eta=20, gamma=2, use_angular=True):
""" Set a common cut of radius
"""
......@@ -105,11 +105,14 @@ class Angular_Fingerprint(object):
self.binwidth2 = np.pi / Nbins2
self.sigma1 = sigma1
self.sigma2 = sigma2
self.nsigma = nsigma
self.eta = eta
self.gamma = gamma
self.use_angular = use_angular
self.initialized = False
def initialize_from_atoms(self, atoms):
self.nsigma = 4
self.volume = atoms.get_volume()
self.pbc = atoms.get_pbc()
......@@ -123,7 +126,7 @@ class Angular_Fingerprint(object):
self.m2 = self.nsigma*self.sigma2/self.binwidth2 # number of neighbour bins included.
self.smearing_norm2 = erf(1/np.sqrt(2) * self.m2 * self.binwidth2/self.sigma2) # Integral of the included part of the gauss
self.binwidth2 = np.pi/Nbins2
self.binwidth2 = np.pi/self.Nbins2
# Prepare stuff to handle multiple species
self.num = atoms.get_atomic_numbers()
......@@ -184,7 +187,7 @@ class Angular_Fingerprint(object):
self.Nelements_2body = self.Nbondtypes_2body * self.Nbins1
self.Nelements_3body = self.Nbondtypes_3body * self.Nbins2
if use_angular:
if self.use_angular:
self.Nelements = self.Nelements_2body + self.Nelements_3body
else:
self.Nelements = self.Nelements_2body
......@@ -194,9 +197,15 @@ class Angular_Fingerprint(object):
self.cell = atoms.get_cell()
self.neighbourcells_disp = self.__get_neighbour_cells_displacement(self.pbc, self.cell)
self.initialized = True
def get_feature(self, atoms):
"""
"""
if not self.initialized:
self.initialize_from_atoms(atoms)
cdef double Rc1 = self.Rc1
cdef double Rc2 = self.Rc2
cdef double binwidth1 = self.binwidth1
......@@ -437,6 +446,9 @@ class Angular_Fingerprint(object):
def get_featureGradient(self, atoms):
if not self.initialized:
self.initialize_from_atoms(atoms)
cdef double Rc1 = self.Rc1
cdef double Rc2 = self.Rc2
cdef double binwidth1 = self.binwidth1
......
surrogate/featureCalculators_multi/setup.py → surrogate/descriptor/setup.py
View file @ 5015902e
......@@ -2,4 +2,4 @@ from distutils.core import setup
from Cython.Build import cythonize
import numpy
setup(ext_modules=cythonize('angular_fingerprintFeature_cy.pyx'), include_dirs=[numpy.get_include()])
setup(ext_modules=cythonize('fingerprint.pyx'), include_dirs=[numpy.get_include()])
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