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internal.py
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internal.py
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"""
internal.py: Internal coordinate systems
Copyright 2016-2020 Regents of the University of California and the Authors
Authors: Lee-Ping Wang, Chenchen Song
Contributors:
Redistribution and use in source and binary forms, with or without modification,
are permitted provided that the following conditions are met:
1. Redistributions of source code must retain the above copyright notice,
this list of conditions and the following disclaimer.
2. Redistributions in binary form must reproduce the above copyright notice,
this list of conditions and the following disclaimer in the documentation
and/or other materials provided with the distribution.
3. Neither the name of the copyright holder nor the names of its contributors
may be used to endorse or promote products derived from this software
without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED.
IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT,
INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT
NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
POSSIBILITY OF SUCH DAMAGE.
"""
from __future__ import division
import itertools
import time, sys
from collections import OrderedDict, defaultdict
from copy import deepcopy
import networkx as nx
import numpy as np
from numpy.linalg import multi_dot
from geometric.molecule import Molecule, Elements, Radii
from geometric.nifty import click, commadash, ang2bohr, bohr2ang, logger, pvec1d, pmat2d
from geometric.rotate import get_expmap, get_expmap_der, calc_rot_vec_diff, get_quat, build_F, sorted_eigh
## Some vector calculus functions
def unit_vector(a):
"""
Vector function: Given a vector a, return the unit vector
"""
return a / np.linalg.norm(a)
def d_unit_vector(a, ndim=3):
term1 = np.eye(ndim)/np.linalg.norm(a)
term2 = np.outer(a, a)/(np.linalg.norm(a)**3)
answer = term1-term2
return answer
def d_cross(a, b):
"""
Given two vectors a and b, return the gradient of the cross product axb w/r.t. a.
(Note that the answer is independent of a.)
Derivative is on the first axis.
"""
d_cross = np.zeros((3, 3), dtype=float)
for i in range(3):
ei = np.zeros(3, dtype=float)
ei[i] = 1.0
d_cross[i] = np.cross(ei, b)
return d_cross
def d_cross_ab(a, b, da, db):
"""
Given two vectors a, b and their derivatives w/r.t. a parameter, return the derivative
of the cross product
"""
answer = np.zeros((da.shape[0], 3), dtype=float)
for i in range(da.shape[0]):
answer[i] = np.cross(a, db[i]) + np.cross(da[i], b)
return answer
def ncross(a, b):
"""
Scalar function: Given vectors a and b, return the norm of the cross product
"""
cross = np.cross(a, b)
return np.linalg.norm(cross)
def d_ncross(a, b):
"""
Return the gradient of the norm of the cross product w/r.t. a
"""
ncross = np.linalg.norm(np.cross(a, b))
term1 = a * np.dot(b, b)
term2 = -b * np.dot(a, b)
answer = (term1+term2)/ncross
return answer
def nudot(a, b):
r"""
Given two vectors a and b, return the dot product (\hat{a}).b.
"""
ev = a / np.linalg.norm(a)
return np.dot(ev, b)
def d_nudot(a, b):
r"""
Given two vectors a and b, return the gradient of
the norm of the dot product (\hat{a}).b w/r.t. a.
"""
return np.dot(d_unit_vector(a), b)
def ucross(a, b):
r"""
Given two vectors a and b, return the cross product (\hat{a})xb.
"""
ev = a / np.linalg.norm(a)
return np.cross(ev, b)
def d_ucross(a, b):
r"""
Given two vectors a and b, return the gradient of
the cross product (\hat{a})xb w/r.t. a.
"""
ev = a / np.linalg.norm(a)
return np.dot(d_unit_vector(a), d_cross(ev, b))
def nucross(a, b):
r"""
Given two vectors a and b, return the norm of the cross product (\hat{a})xb.
"""
ev = a / np.linalg.norm(a)
return np.linalg.norm(np.cross(ev, b))
def d_nucross(a, b):
r"""
Given two vectors a and b, return the gradient of
the norm of the cross product (\hat{a})xb w/r.t. a.
"""
ev = a / np.linalg.norm(a)
return np.dot(d_unit_vector(a), d_ncross(ev, b))
## End vector calculus functions
class PrimitiveCoordinate(object):
"""
Parent class for primitive internal coordinate objects with common methods.
"""
def calcDiff(self, xyz1, xyz2=None, val2=None):
"""
Return the difference of the internal coordinate
calculated for c(xyz1) - c(xyz2) or c(xyz1) - val2.
Parameters
----------
xyz1 : np.ndarray
xyz coordinates of first structure in Bohr
xyz2 : np.ndarray
If provided, xyz coordinates of second structure in Bohr
val2 : float
If provided, this is the value to subtract
"""
if xyz2 is None and val2 is None:
raise RuntimeError("Provide exactly one of xyz2 and val2")
elif xyz2 is not None and val2 is not None:
raise RuntimeError("Provide exactly one of xyz2 and val2")
if xyz2 is not None:
val2 = self.value(xyz2)
diff = self.value(xyz1) - val2
if hasattr(self, 'w'):
w = self.w
else:
w = 1.0
# Divide by the weight, if exists, to get the "base" number
diff /= w
# Subtract out any differences of 2*pi for periodic degrees of freedom
# (rotation ICs handled separately)
if hasattr(self, 'isPeriodic') and self.isPeriodic:
Plus2Pi = diff + 2*np.pi
Minus2Pi = diff - 2*np.pi
if np.abs(diff) > np.abs(Plus2Pi):
diff = Plus2Pi
if np.abs(diff) > np.abs(Minus2Pi):
diff = Minus2Pi
diff *= w
return diff
class CartesianX(PrimitiveCoordinate):
def __init__(self, a, w=1.0):
self.a = a
self.w = w
self.isAngular = False
self.isPeriodic = False
def __repr__(self):
#return "Cartesian-X %i : Weight %.3f" % (self.a+1, self.w)
return "Cartesian-X %i" % (self.a+1)
def __eq__(self, other):
if type(self) is not type(other): return False
eq = self.a == other.a
if eq and self.w != other.w:
logger.warning("Warning: CartesianX same atoms, different weights (%.4f %.4f)\n" % (self.w, other.w))
return eq
def __ne__(self, other):
return not self.__eq__(other)
def value(self, xyz):
xyz = xyz.reshape(-1,3)
a = self.a
return xyz[a][0]*self.w
def derivative(self, xyz):
xyz = xyz.reshape(-1,3)
derivatives = np.zeros_like(xyz)
derivatives[self.a][0] = self.w
return derivatives
def second_derivative(self, xyz):
xyz = xyz.reshape(-1,3)
deriv2 = np.zeros((xyz.shape[0], xyz.shape[1], xyz.shape[0], xyz.shape[1]))
return deriv2
class CartesianY(PrimitiveCoordinate):
def __init__(self, a, w=1.0):
self.a = a
self.w = w
self.isAngular = False
self.isPeriodic = False
def __repr__(self):
# return "Cartesian-Y %i : Weight %.3f" % (self.a+1, self.w)
return "Cartesian-Y %i" % (self.a+1)
def __eq__(self, other):
if type(self) is not type(other): return False
eq = self.a == other.a
if eq and self.w != other.w:
logger.warning("Warning: CartesianY same atoms, different weights (%.4f %.4f)\n" % (self.w, other.w))
return eq
def __ne__(self, other):
return not self.__eq__(other)
def value(self, xyz):
xyz = xyz.reshape(-1,3)
a = self.a
return xyz[a][1]*self.w
def derivative(self, xyz):
xyz = xyz.reshape(-1,3)
derivatives = np.zeros_like(xyz)
derivatives[self.a][1] = self.w
return derivatives
def second_derivative(self, xyz):
xyz = xyz.reshape(-1,3)
deriv2 = np.zeros((xyz.shape[0], xyz.shape[1], xyz.shape[0], xyz.shape[1]))
return deriv2
class CartesianZ(PrimitiveCoordinate):
def __init__(self, a, w=1.0):
self.a = a
self.w = w
self.isAngular = False
self.isPeriodic = False
def __repr__(self):
# return "Cartesian-Z %i : Weight %.3f" % (self.a+1, self.w)
return "Cartesian-Z %i" % (self.a+1)
def __eq__(self, other):
if type(self) is not type(other): return False
eq = self.a == other.a
if eq and self.w != other.w:
logger.warning("Warning: CartesianZ same atoms, different weights (%.4f %.4f)\n" % (self.w, other.w))
return eq
def __ne__(self, other):
return not self.__eq__(other)
def value(self, xyz):
xyz = xyz.reshape(-1,3)
a = self.a
return xyz[a][2]*self.w
def derivative(self, xyz):
xyz = xyz.reshape(-1,3)
derivatives = np.zeros_like(xyz)
derivatives[self.a][2] = self.w
return derivatives
def second_derivative(self, xyz):
xyz = xyz.reshape(-1,3)
deriv2 = np.zeros((xyz.shape[0], xyz.shape[1], xyz.shape[0], xyz.shape[1]))
return deriv2
class TranslationX(PrimitiveCoordinate):
def __init__(self, a, w):
self.a = a
self.w = w
assert len(a) == len(w)
self.isAngular = False
self.isPeriodic = False
def __repr__(self):
# return "Translation-X %s : Weights %s" % (' '.join([str(i+1) for i in self.a]), ' '.join(['%.2e' % i for i in self.w]))
return "Translation-X %s" % (commadash(self.a))
def __eq__(self, other):
if type(self) is not type(other): return False
eq = set(self.a) == set(other.a)
if eq and np.sum((self.w-other.w)**2) > 1e-6:
logger.warning("Warning: TranslationX same atoms, different weights\n")
eq = False
return eq
def __ne__(self, other):
return not self.__eq__(other)
def value(self, xyz):
xyz = xyz.reshape(-1,3)
a = np.array(self.a)
return np.sum(xyz[a,0]*self.w)
def calcDiff(self, xyz1, xyz2=None, val2=None):
# Translation ICs require an explicit implementation of calcDiff
# because self.w is not a float but an array
if xyz2 is None and val2 is None:
raise RuntimeError("Provide exactly one of xyz2 and val2")
elif xyz2 is not None and val2 is not None:
raise RuntimeError("Provide exactly one of xyz2 and val2")
if xyz2 is not None:
val2 = self.value(xyz2)
diff = self.value(xyz1) - val2
return diff
def derivative(self, xyz):
xyz = xyz.reshape(-1,3)
derivatives = np.zeros_like(xyz)
for i, a in enumerate(self.a):
derivatives[a][0] = self.w[i]
return derivatives
def second_derivative(self, xyz):
xyz = xyz.reshape(-1,3)
deriv2 = np.zeros((xyz.shape[0], xyz.shape[1], xyz.shape[0], xyz.shape[1]))
return deriv2
class TranslationY(object):
def __init__(self, a, w):
self.a = a
self.w = w
assert len(a) == len(w)
self.isAngular = False
self.isPeriodic = False
def __repr__(self):
# return "Translation-Y %s : Weights %s" % (' '.join([str(i+1) for i in self.a]), ' '.join(['%.2e' % i for i in self.w]))
return "Translation-Y %s" % (commadash(self.a))
def __eq__(self, other):
if type(self) is not type(other): return False
eq = set(self.a) == set(other.a)
if eq and np.sum((self.w-other.w)**2) > 1e-6:
logger.warning("Warning: TranslationY same atoms, different weights\n")
eq = False
return eq
def __ne__(self, other):
return not self.__eq__(other)
def value(self, xyz):
xyz = xyz.reshape(-1,3)
a = np.array(self.a)
return np.sum(xyz[a,1]*self.w)
def calcDiff(self, xyz1, xyz2=None, val2=None):
# Translation ICs require an explicit implementation of calcDiff
# because self.w is not a float but an array
if xyz2 is None and val2 is None:
raise RuntimeError("Provide exactly one of xyz2 and val2")
elif xyz2 is not None and val2 is not None:
raise RuntimeError("Provide exactly one of xyz2 and val2")
if xyz2 is not None:
val2 = self.value(xyz2)
diff = self.value(xyz1) - val2
return diff
def derivative(self, xyz):
xyz = xyz.reshape(-1,3)
derivatives = np.zeros_like(xyz)
for i, a in enumerate(self.a):
derivatives[a][1] = self.w[i]
return derivatives
def second_derivative(self, xyz):
xyz = xyz.reshape(-1,3)
deriv2 = np.zeros((xyz.shape[0], xyz.shape[1], xyz.shape[0], xyz.shape[1]))
return deriv2
class TranslationZ(PrimitiveCoordinate):
def __init__(self, a, w):
self.a = a
self.w = w
assert len(a) == len(w)
self.isAngular = False
self.isPeriodic = False
def __repr__(self):
# return "Translation-Z %s : Weights %s" % (' '.join([str(i+1) for i in self.a]), ' '.join(['%.2e' % i for i in self.w]))
return "Translation-Z %s" % (commadash(self.a))
def __eq__(self, other):
if type(self) is not type(other): return False
eq = set(self.a) == set(other.a)
if eq and np.sum((self.w-other.w)**2) > 1e-6:
logger.warning("Warning: TranslationZ same atoms, different weights\n")
eq = False
return eq
def __ne__(self, other):
return not self.__eq__(other)
def value(self, xyz):
xyz = xyz.reshape(-1,3)
a = np.array(self.a)
return np.sum(xyz[a,2]*self.w)
def calcDiff(self, xyz1, xyz2=None, val2=None):
# Translation ICs require an explicit implementation of calcDiff
# because self.w is not a float but an array
if xyz2 is None and val2 is None:
raise RuntimeError("Provide exactly one of xyz2 and val2")
elif xyz2 is not None and val2 is not None:
raise RuntimeError("Provide exactly one of xyz2 and val2")
if xyz2 is not None:
val2 = self.value(xyz2)
diff = self.value(xyz1) - val2
return diff
def derivative(self, xyz):
xyz = xyz.reshape(-1,3)
derivatives = np.zeros_like(xyz)
for i, a in enumerate(self.a):
derivatives[a][2] = self.w[i]
return derivatives
def second_derivative(self, xyz):
xyz = xyz.reshape(-1,3)
deriv2 = np.zeros((xyz.shape[0], xyz.shape[1], xyz.shape[0], xyz.shape[1]))
return deriv2
class Rotator(object):
def __init__(self, a, x0):
self.a = list(tuple(sorted(a)))
x0 = x0.reshape(-1, 3)
self.x0 = x0.copy()
# Information about the regularization quaternion
self.rquat = np.array([1.0, 0.0, 0.0, 0.0])
self.rmode = 0
self.set_regularization(x0)
self.clear_cache(x0)
def clear_cache(self, xyz):
xyz = xyz.reshape(-1, 3)
self.stored_valxyz = np.zeros_like(xyz)
self.stored_value = None
# A second set of xyz coordinates used only when computing
# differences in rotation coordinates
self.stored_valxyz2 = np.zeros_like(xyz)
self.stored_value2 = None
self.stored_derxyz = np.zeros_like(xyz)
self.stored_deriv = None
self.stored_deriv2xyz = np.zeros_like(xyz)
self.stored_deriv2 = None
self.stored_norm = 0.0
def reset(self, x0):
x0 = x0.reshape(-1, 3)
self.x0 = x0.copy()
self.rquat = np.array([1.0, 0.0, 0.0, 0.0])
self.rmode = 0
self.set_regularization(x0)
self.clear_cache(x0)
def __eq__(self, other):
if type(self) is not type(other): return False
eq = set(self.a) == set(other.a)
if eq and np.sum((self.x0-other.x0)**2) > 1e-6:
logger.warning("Warning: Rotator same atoms, different reference positions\n")
return eq
def __repr__(self):
return "Rotator %s" % commadash(self.a)
def __ne__(self, other):
return not self.__eq__(other)
def set_regularization(self, xyz):
self.clear_cache(xyz)
x = xyz.reshape(-1, 3)[self.a, :].copy()
x = x - np.mean(x,axis=0)
L, Q = sorted_eigh(build_F(x, x))
# The switch for the regularization is 'sticky'.
thre_lo = 1.01
thre_mid = 1.03
thre_hi = 1.1
regularization_changed = False
if L[0]/L[1] < thre_lo and L[0]/L[1] > 0.0 and self.rmode in (-1, 0):
self.rnorm = 1e-1*L[0]
self.rmode = 1
# Uncomment the below four logging messages to check whether regularization is on or off
# logger.info(" >>> %-18s L[0] = %.3f, L[0]/L[1] = %.3f (linear), turning regularization on.\n" % (str(self), L[0], L[0]/L[1]))
regularization_changed = True
elif L[0]/L[1] > thre_hi and self.rmode in (1, 0):
self.rnorm = 0.0
self.rmode = -1
# logger.info(" >>> %s L[0] = %.3f, L[0]/L[1] = %.3f (nonlin), turning regularization off.\n" % (str(self), L[0], L[0]/L[1]))
regularization_changed = True
elif self.rmode == 0:
if L[0]/L[1] < thre_mid and L[0]/L[1] > 0.0:
# logger.info(" >>> %s L[0] = %.3f, L[0]/L[1] = %.3f (linear), turning regularization on.\n" % (str(self), L[0], L[0]/L[1]))
self.rnorm = 1e-1*L[0]
self.rmode = 1
regularization_changed = True
else:
#
# logger.info(" >>> %s L[0] = %.3f, L[0]/L[1] = %.3f (nonlin), turning regularization off.\n" % (str(self), L[0], L[0]/L[1]))
self.rnorm = 0.0
self.rmode = -1
regularization_changed = True
if self.rmode > 0:
y = self.x0[self.a, :].copy()
y = y - np.mean(y,axis=0)
q = get_quat(x, y, r=self.rnorm*self.rquat)
ang = 2*np.arccos(np.dot(self.rquat, q))
# self.qsav = q.copy()
if ang > 0.9*np.pi:
logger.info("%s angle %.3f\n" % (str(self), ang))
# logger.info("setting regularization quaternion to %s\n", str(q))
# self.rquat = q.copy()
return regularization_changed
# else:
# self.rquat = np.array([1.0, 0.0, 0.0, 0.0])
def value(self, xyz, store=True):
xyz = xyz.reshape(-1, 3)
if np.max(np.abs(xyz-self.stored_valxyz)) < 1e-12:
return self.stored_value
else:
xsel = xyz[self.a, :]
ysel = self.x0[self.a, :]
answer = get_expmap(xsel, ysel, r=self.rnorm*self.rquat)
if store:
self.stored_norm = np.linalg.norm(answer)
self.stored_valxyz = xyz.copy()
self.stored_value = answer.copy()
return answer
def visualize(self, xyz):
xyz = xyz.reshape(-1, 3)
xsel = xyz[self.a, :]
ysel = self.x0[self.a, :]
xmean = np.mean(xsel,axis=0)
ymean = np.mean(ysel,axis=0)
answer = np.zeros((2, 3), dtype=float)
answer[0, :] = xmean
answer[1, :] = xmean + get_expmap(xsel, ysel, r=self.rnorm*self.rquat)*ang2bohr
return answer
def calcDiff(self, xyz1, xyz2=None, val2=None):
"""
Return the difference of the internal coordinate
calculated for (xyz1 - xyz2).
"""
if xyz2 is None and val2 is None:
raise RuntimeError("Provide exactly one of xyz2 and val2")
elif xyz2 is not None and val2 is not None:
raise RuntimeError("Provide exactly one of xyz2 and val2")
val1 = self.value(xyz1)
if xyz2 is not None:
# The "second" coordinate set is cached separately
xyz2 = xyz2.reshape(-1, 3)
if np.max(np.abs(xyz2-self.stored_valxyz2)) < 1e-12:
val2 = self.stored_value2.copy()
else:
val2 = self.value(xyz2, store=False)
self.stored_valxyz2 = xyz2.copy()
self.stored_value2 = val2.copy()
# Calculate difference in rotation vectors, modulo n*2pi displacement vectors
return calc_rot_vec_diff(val1, val2)
def derivative(self, xyz):
xyz = xyz.reshape(-1, 3)
if np.max(np.abs(xyz-self.stored_derxyz)) < 1e-12:
return self.stored_deriv
else:
xsel = xyz[self.a, :]
ysel = self.x0[self.a, :]
xmean = np.mean(xsel,axis=0)
ymean = np.mean(ysel,axis=0)
deriv_raw = get_expmap_der(xsel, ysel, r=self.rnorm*self.rquat)
derivatives = np.zeros((xyz.shape[0], 3, 3), dtype=float)
for i, a in enumerate(self.a):
derivatives[a, :, :] = deriv_raw[i, :, :]
self.stored_derxyz = xyz.copy()
self.stored_deriv = derivatives.copy()
return derivatives
def second_derivative(self, xyz):
xyz = xyz.reshape(-1, 3)
if np.max(np.abs(xyz-self.stored_deriv2xyz)) < 1e-12:
return self.stored_deriv2
else:
xsel = xyz[self.a, :]
ysel = self.x0[self.a, :]
xmean = np.mean(xsel,axis=0)
ymean = np.mean(ysel,axis=0)
deriv_raw, deriv2_raw = get_expmap_der(xsel, ysel, second=True, r=self.rnorm*self.rquat)
second_derivatives = np.zeros((xyz.shape[0], 3, xyz.shape[0], 3, 3), dtype=float)
for i, a in enumerate(self.a):
for j, b in enumerate(self.a):
second_derivatives[a, :, b, :, :] = deriv2_raw[i, :, j, :, :]
# derivatives, second_derivatives = get_expmap_der(xsel, ysel, second=True, r=self.rnorm*self.rquat)
return second_derivatives
class RotationA(PrimitiveCoordinate):
def __init__(self, a, x0, Rotators, w=1.0):
self.a = tuple(sorted(a))
self.x0 = x0
self.w = w
if self.a not in Rotators:
Rotators[self.a] = Rotator(self.a, x0)
self.Rotator = Rotators[self.a]
self.isAngular = True
self.isPeriodic = False
def __repr__(self):
# return "Rotation-A %s : Weight %.3f" % (' '.join([str(i+1) for i in self.a]), self.w)
return "Rotation-A %s" % (commadash(self.a))
def __eq__(self, other):
if type(self) is not type(other): return False
eq = set(self.a) == set(other.a)
# if eq and np.sum((self.w-other.w)**2) > 1e-6:
# print "Warning: RotationA same atoms, different weights"
# if eq and np.sum((self.x0-other.x0)**2) > 1e-6:
# print "Warning: RotationA same atoms, different reference positions"
return eq
def __ne__(self, other):
return not self.__eq__(other)
def value(self, xyz):
return self.Rotator.value(xyz)[0]*self.w
def calcDiff(self, xyz1, xyz2=None, val2=None):
return self.Rotator.calcDiff(xyz1, xyz2, val2)[0]*self.w
def derivative(self, xyz):
der_all = self.Rotator.derivative(xyz)
derivatives = der_all[:, :, 0]*self.w
return derivatives
def second_derivative(self, xyz):
deriv2_all = self.Rotator.second_derivative(xyz)
second_derivatives = deriv2_all[:, :, :, :, 0]*self.w
return second_derivatives
class RotationB(PrimitiveCoordinate):
def __init__(self, a, x0, Rotators, w=1.0):
self.a = tuple(sorted(a))
self.x0 = x0
self.w = w
if self.a not in Rotators:
Rotators[self.a] = Rotator(self.a, x0)
self.Rotator = Rotators[self.a]
self.isAngular = True
self.isPeriodic = False
def __repr__(self):
# return "Rotation-B %s : Weight %.3f" % (' '.join([str(i+1) for i in self.a]), self.w)
return "Rotation-B %s" % (commadash(self.a))
def __eq__(self, other):
if type(self) is not type(other): return False
eq = set(self.a) == set(other.a)
# if eq and np.sum((self.w-other.w)**2) > 1e-6:
# print "Warning: RotationB same atoms, different weights"
# if eq and np.sum((self.x0-other.x0)**2) > 1e-6:
# print "Warning: RotationB same atoms, different reference positions"
return eq
def __ne__(self, other):
return not self.__eq__(other)
def value(self, xyz):
return self.Rotator.value(xyz)[1]*self.w
def calcDiff(self, xyz1, xyz2=None, val2=None):
return self.Rotator.calcDiff(xyz1, xyz2, val2)[1]*self.w
def derivative(self, xyz):
der_all = self.Rotator.derivative(xyz)
derivatives = der_all[:, :, 1]*self.w
return derivatives
def second_derivative(self, xyz):
deriv2_all = self.Rotator.second_derivative(xyz)
second_derivatives = deriv2_all[:, :, :, :, 1]*self.w
return second_derivatives
class RotationC(PrimitiveCoordinate):
def __init__(self, a, x0, Rotators, w=1.0):
self.a = tuple(sorted(a))
self.x0 = x0
self.w = w
if self.a not in Rotators:
Rotators[self.a] = Rotator(self.a, x0)
self.Rotator = Rotators[self.a]
self.isAngular = True
self.isPeriodic = False
def __repr__(self):
# return "Rotation-C %s : Weight %.3f" % (' '.join([str(i+1) for i in self.a]), self.w)
return "Rotation-C %s" % (commadash(self.a))
def __eq__(self, other):
if type(self) is not type(other): return False
eq = set(self.a) == set(other.a)
# if eq and np.sum((self.w-other.w)**2) > 1e-6:
# print "Warning: RotationC same atoms, different weights"
# if eq and np.sum((self.x0-other.x0)**2) > 1e-6:
# print "Warning: RotationC same atoms, different reference positions"
return eq
def __ne__(self, other):
return not self.__eq__(other)
def value(self, xyz):
return self.Rotator.value(xyz)[2]*self.w
def calcDiff(self, xyz1, xyz2=None, val2=None):
return self.Rotator.calcDiff(xyz1, xyz2, val2)[2]*self.w
def derivative(self, xyz):
der_all = self.Rotator.derivative(xyz)
derivatives = der_all[:, :, 2]*self.w
return derivatives
def second_derivative(self, xyz):
deriv2_all = self.Rotator.second_derivative(xyz)
second_derivatives = deriv2_all[:, :, :, :, 2]*self.w
return second_derivatives
class Distance(PrimitiveCoordinate):
def __init__(self, a, b):
self.a = a
self.b = b
if a == b:
raise RuntimeError('a and b must be different')
self.isAngular = False
self.isPeriodic = False
def __repr__(self):
return "Distance %i-%i" % (self.a+1, self.b+1)
def __eq__(self, other):
if type(self) is not type(other): return False
if self.a == other.a:
if self.b == other.b:
return True
if self.a == other.b:
if self.b == other.a:
return True
return False
def __ne__(self, other):
return not self.__eq__(other)
def value(self, xyz):
xyz = xyz.reshape(-1,3)
a = self.a
b = self.b
return np.sqrt(np.sum((xyz[a]-xyz[b])**2))
def derivative(self, xyz):
xyz = xyz.reshape(-1,3)
derivatives = np.zeros_like(xyz)
m = self.a
n = self.b
u = (xyz[m] - xyz[n]) / np.linalg.norm(xyz[m] - xyz[n])
derivatives[m, :] = u
derivatives[n, :] = -u
return derivatives
def second_derivative(self, xyz):
xyz = xyz.reshape(-1,3)
deriv2 = np.zeros((xyz.shape[0], xyz.shape[1], xyz.shape[0], xyz.shape[1]))
m = self.a
n = self.b
l = np.linalg.norm(xyz[m] - xyz[n])
u = (xyz[m] - xyz[n]) / l
mtx = (np.outer(u, u) - np.eye(3))/l
deriv2[m, :, m, :] = -mtx
deriv2[n, :, n, :] = -mtx
deriv2[m, :, n, :] = mtx
deriv2[n, :, m, :] = mtx
return deriv2
class Angle(PrimitiveCoordinate):
def __init__(self, a, b, c):
self.a = a
self.b = b
self.c = c
self.isAngular = True
self.isPeriodic = False
if len({a, b, c}) != 3:
raise RuntimeError('a, b, and c must be different')
def __repr__(self):
return "Angle %i-%i-%i" % (self.a+1, self.b+1, self.c+1)
def __eq__(self, other):
if type(self) is not type(other): return False
if self.b == other.b:
if self.a == other.a:
if self.c == other.c:
return True
if self.a == other.c:
if self.c == other.a:
return True
return False
def __ne__(self, other):
return not self.__eq__(other)
def value(self, xyz):
xyz = xyz.reshape(-1,3)
a = self.a
b = self.b
c = self.c
# vector from first atom to central atom
vector1 = xyz[a] - xyz[b]
# vector from last atom to central atom
vector2 = xyz[c] - xyz[b]
# norm of the two vectors
norm1 = np.sqrt(np.sum(vector1**2))
norm2 = np.sqrt(np.sum(vector2**2))
dot = np.dot(vector1, vector2)
# Catch the edge case that very rarely this number is -1.
if dot / (norm1 * norm2) <= -1.0:
if (np.abs(dot / (norm1 * norm2)) + 1.0) < -1e-6:
raise RuntimeError('Encountered invalid value in angle')
return np.pi
if dot / (norm1 * norm2) >= 1.0:
if (np.abs(dot / (norm1 * norm2)) - 1.0) > 1e-6:
raise RuntimeError('Encountered invalid value in angle')
return 0.0
return np.arccos(dot / (norm1 * norm2))
def normal_vector(self, xyz):
xyz = xyz.reshape(-1,3)
a = self.a
b = self.b
c = self.c
# vector from first atom to central atom
vector1 = xyz[a] - xyz[b]
# vector from last atom to central atom
vector2 = xyz[c] - xyz[b]
# norm of the two vectors
norm1 = np.sqrt(np.sum(vector1**2))
norm2 = np.sqrt(np.sum(vector2**2))
crs = np.cross(vector1, vector2)
crs /= np.linalg.norm(crs)
return crs
def derivative(self, xyz):
xyz = xyz.reshape(-1,3)
derivatives = np.zeros_like(xyz)
m = self.a
o = self.b
n = self.c
# Unit displacement vectors
u_prime = (xyz[m] - xyz[o])
u_norm = np.linalg.norm(u_prime)
v_prime = (xyz[n] - xyz[o])
v_norm = np.linalg.norm(v_prime)
u = u_prime / u_norm
v = v_prime / v_norm
VECTOR1 = np.array([1, -1, 1]) / np.sqrt(3)
VECTOR2 = np.array([-1, 1, 1]) / np.sqrt(3)
if np.linalg.norm(u + v) < 1e-10 or np.linalg.norm(u - v) < 1e-10:
# if they're parallel
if ((np.linalg.norm(u + VECTOR1) < 1e-10) or
(np.linalg.norm(u - VECTOR2) < 1e-10)):
# and they're parallel o [1, -1, 1]
w_prime = np.cross(u, VECTOR2)
else:
w_prime = np.cross(u, VECTOR1)
else:
w_prime = np.cross(u, v)
w = w_prime / np.linalg.norm(w_prime)
term1 = np.cross(u, w) / u_norm
term2 = np.cross(w, v) / v_norm
derivatives[m, :] = term1
derivatives[n, :] = term2
derivatives[o, :] = -(term1 + term2)
return derivatives
def second_derivative(self, xyz):
xyz = xyz.reshape(-1,3)
deriv2 = np.zeros((xyz.shape[0], xyz.shape[1], xyz.shape[0], xyz.shape[1]))
m = self.a
o = self.b
n = self.c
# Unit displacement vectors
u_prime = (xyz[m] - xyz[o])
u_norm = np.linalg.norm(u_prime)
v_prime = (xyz[n] - xyz[o])
v_norm = np.linalg.norm(v_prime)
u = u_prime / u_norm
v = v_prime / v_norm
# Deriv2 derivatives are set to zero in the case of parallel or antiparallel vectors
if np.linalg.norm(u + v) < 1e-10 or np.linalg.norm(u - v) < 1e-10:
return deriv2
# cosine and sine of the bond angle
cq = np.dot(u, v)
sq = np.sqrt(1-cq**2)
uu = np.outer(u, u)
uv = np.outer(u, v)
vv = np.outer(v, v)
de = np.eye(3)
term1 = (uv + uv.T - (3*uu - de)*cq)/(u_norm**2*sq)
term2 = (uv + uv.T - (3*vv - de)*cq)/(v_norm**2*sq)
term3 = (uu + vv - uv*cq - de)/(u_norm*v_norm*sq)
term4 = (uu + vv - uv.T*cq - de)/(u_norm*v_norm*sq)
der1 = self.derivative(xyz)
def zeta(a_, m_, n_):
return (int(a_==m_) - int(a_==n_))
for a in [m, n, o]:
for b in [m, n, o]:
deriv2[a, :, b, :] = (zeta(a, m, o)*zeta(b, m, o)*term1
+ zeta(a, n, o)*zeta(b, n, o)*term2
+ zeta(a, m, o)*zeta(b, n, o)*term3
+ zeta(a, n, o)*zeta(b, m, o)*term4
- (cq/sq) * np.outer(der1[a], der1[b]))
return deriv2
class LinearAngle(PrimitiveCoordinate):
def __init__(self, a, b, c, axis):
self.a = a
self.b = b
self.c = c
self.axis = axis
self.isAngular = False
self.isPeriodic = False
if len({a, b, c}) != 3:
raise RuntimeError('a, b, and c must be different')
self.e0 = None
self.stored_dot2 = 0.0
def reset(self, xyz):
xyz = xyz.reshape(-1,3)
a = self.a
b = self.b
c = self.c
# Unit vector pointing from a to c.
v = xyz[c] - xyz[a]
ev = v / np.linalg.norm(v)
# Cartesian axes.
ex = np.array([1.0,0.0,0.0])
ey = np.array([0.0,1.0,0.0])
ez = np.array([0.0,0.0,1.0])
self.e0 = [ex, ey, ez][np.argmin([np.dot(i, ev)**2 for i in [ex, ey, ez]])]
self.stored_dot2 = 0.0
def reposition_e0(self, xyz):
"""
Project out the component of e0 that is parallel to ev.
This prevents linear angles from becoming parallel to e0,
which requires resetting the coordinate system.
This function should be called at the end of each accepted step.
"""
xyz = xyz.reshape(-1,3)
a = self.a
b = self.b
c = self.c
v = xyz[c] - xyz[a]
ev = v / np.linalg.norm(v)
dot = np.dot(ev, self.e0)
self.e0 -= dot*ev