/usr/lib/python2.7/dist-packages/FIAT/expansions.py is in python-fiat 1.3.0-1.
This file is owned by root:root, with mode 0o644.
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#
# This file is part of FIAT.
#
# FIAT is free software: you can redistribute it and/or modify
# it under the terms of the GNU Lesser General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# FIAT is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Lesser General Public License for more details.
#
# You should have received a copy of the GNU Lesser General Public License
# along with FIAT. If not, see <http://www.gnu.org/licenses/>.
"""Principal orthgonal expansion functions as defined by Karniadakis
and Sherwin. These are parametrized over a reference element so as
to allow users to get coordinates that they want."""
from . import reference_element
import numpy,math
from . import jacobi, reference_element
# Import AD modules from ScientificPython
try:
import Scientific.Functions.Derivatives as Derivatives
import Scientific.Functions.FirstDerivatives as FirstDerivatives
except:
raise Exception("""\
Unable to import the Python Scientific module required by FIAT.
Consider installing the package python-scientific.
""")
def xi_triangle( eta ):
"""Maps from [-1,1]^2 to the (-1,1) reference triangle."""
eta1,eta2 = eta
xi1 = 0.5 * ( 1.0 + eta1 ) * ( 1.0 - eta2 ) - 1.0
xi2 = eta2
return (xi1,xi2)
def xi_tetrahedron( eta ):
"""Maps from [-1,1]^3 to the -1/1 reference tetrahedron."""
eta1,eta2,eta3 = eta
xi1 = 0.25 * ( 1. + eta1 ) * ( 1. - eta2 ) * ( 1. - eta3 ) - 1.
xi2 = 0.5 * ( 1. + eta2 ) * ( 1. - eta3 ) - 1.
xi3 = eta3
return xi1,xi2,xi3
class LineExpansionSet:
"""Evaluates the Legendre basis on a line reference element."""
def __init__( self , ref_el ):
if ref_el.get_spatial_dimension() != 1:
raise Exception("Must have a line")
self.ref_el = ref_el
self.base_ref_el = reference_element.DefaultLine()
v1 = ref_el.get_vertices()
v2 = self.base_ref_el.get_vertices()
self.A,self.b = reference_element.make_affine_mapping( v1 , v2 )
self.mapping = lambda x: numpy.dot( self.A , x ) + self.b
self.scale = numpy.sqrt( numpy.linalg.det( self.A ) )
def get_num_members( self , n ):
return n+1
def tabulate( self , n , pts ):
"""Returns a numpy array A[i,j] = phi_i( pts[j] )"""
if len( pts ) > 0:
ref_pts = numpy.array([ self.mapping( pt ) for pt in pts ])
psitilde_as = jacobi.eval_jacobi_batch(0,0,n,ref_pts)
results = numpy.zeros( ( n+1 , len(pts) ) , type( pts[0][0] ) )
for k in range( n + 1 ):
results[k,:] = psitilde_as[k,:] * math.sqrt( k + 0.5 )
return results
else:
return []
def tabulate_derivatives( self , n , pts ):
"""Returns a tuple of length one (A,) such that
A[i,j] = D phi_i( pts[j] ). The tuple is returned for
compatibility with the interfaces of the triangle and
tetrahedron expansions."""
ref_pts = [ self.mapping( pt ) for pt in pts ]
psitilde_as_derivs = jacobi.eval_jacobi_deriv_batch(0,0,n,ref_pts)
results = numpy.zeros( ( n+1 , len(pts[0]) ) , "d" )
for k in range( 0 , n + 1 ):
results[k,:] = psitilde_as_derivs[k,:] * numpy.sqrt( k + 0.5 )
return (results,)
class TriangleExpansionSet:
"""Evaluates the orthonormal Dubiner basis on a triangular
reference element."""
def __init__( self , ref_el ):
if ref_el.get_spatial_dimension() != 2:
raise Exception("Must have a triangle")
self.ref_el = ref_el
self.base_ref_el = reference_element.DefaultTriangle( )
v1 = ref_el.get_vertices()
v2 = self.base_ref_el.get_vertices()
self.A,self.b = reference_element.make_affine_mapping( v1 , v2 )
self.mapping = lambda x: numpy.dot( self.A , x ) + self.b
# self.scale = numpy.sqrt( numpy.linalg.det( self.A ) )
def get_num_members( self , n ):
return (n+1)*(n+2)/2
def tabulate( self , n , pts ):
if len( pts ) == 0:
return numpy.array( [] )
ref_pts = [ self.mapping( pt ) for pt in pts ]
def idx(p,q):
return (p+q)*(p+q+1)/2 + q
def jrc( a , b , n ):
an = float( ( 2*n+1+a+b)*(2*n+2+a+b)) \
/ float( 2*(n+1)*(n+1+a+b))
bn = float( (a*a-b*b) * (2*n+1+a+b) ) \
/ float( 2*(n+1)*(2*n+a+b)*(n+1+a+b) )
cn = float( (n+a)*(n+b)*(2*n+2+a+b) ) \
/ float( (n+1)*(n+1+a+b)*(2*n+a+b) )
return an,bn,cn
pt_types = [ type(p) for p in pts[0] ]
ntype = type(0.0)
for pt in pt_types:
if type(pt) != type(0.0):
ntype = type(pt)
break
results = numpy.zeros( ( (n+1)*(n+2)/2,len(pts)),ntype )
apts = numpy.array( pts )
for ii in range( results.shape[1] ):
results[0,ii] = 1.0 + apts[ii,0]-apts[ii,0]+apts[ii,1]-apts[ii,1]
if n == 0:
return results
x = numpy.array( [ pt[0] for pt in ref_pts ] )
y = numpy.array( [ pt[1] for pt in ref_pts ] )
f1 = (1.0+2*x+y)/2.0
f2 = (1.0 - y) / 2.0
f3 = f2**2
results[idx(1,0),:] = f1
for p in range(1,n):
a = (2.0*p+1)/(1.0+p)
b = p / (p+1.0)
results[idx(p+1,0)] = a * f1 * results[idx(p,0),:] \
- p/(1.0+p) * f3 *results[idx(p-1,0),:]
for p in range(n):
results[idx(p,1),:] = 0.5 * (1+2.0*p+(3.0+2.0*p)*y) \
* results[idx(p,0)]
for p in range(n-1):
for q in range(1,n-p):
(a1,a2,a3) = jrc(2*p+1,0,q)
results[idx(p,q+1),:] \
= ( a1 * y + a2 ) * results[idx(p,q)] \
- a3 * results[idx(p,q-1)]
for p in range(n+1):
for q in range(n-p+1):
results[idx(p,q),:] *= math.sqrt((p+0.5)*(p+q+1.0))
return results
#return self.scale * results
def tabulate_jet( self , n , pts , order = 1 ):
import sys
from Derivatives import DerivVar
dpts = [ tuple( [ DerivVar( pt[i] , i , order ) \
for i in range( len( pt ) ) ] ) for pt in pts ]
dbfs = self.tabulate( n , dpts )
result = []
for d in range( order + 1 ):
result_d = [ [ foo[d] for foo in bar ] for bar in dbfs ]
result.append( numpy.array( result_d ) )
return result
class TetrahedronExpansionSet:
"""Collapsed orthonormal polynomial expanion on a tetrahedron."""
def __init__( self , ref_el ):
if ref_el.get_spatial_dimension() != 3:
raise Exception("Must be a tetrahedron")
self.ref_el = ref_el
self.base_ref_el = reference_element.DefaultTetrahedron( )
v1 = ref_el.get_vertices()
v2 = self.base_ref_el.get_vertices()
self.A,self.b = reference_element.make_affine_mapping( v1 , v2 )
self.mapping = lambda x: numpy.dot( self.A , x ) + self.b
self.scale = numpy.sqrt( numpy.linalg.det( self.A ) )
return
def get_num_members( self , n ):
return (n+1)*(n+2)*(n+3)/6
def tabulate( self , n , pts ):
if len( pts ) == 0:
return numpy.array( [] )
ref_pts = [ self.mapping( pt ) for pt in pts ]
def idx(p,q,r):
return (p+q+r)*(p+q+r+1)*(p+q+r+2)/6 + (q+r)*(q+r+1)/2 + r
def jrc( a , b , n ):
an = float( ( 2*n+1+a+b)*(2*n+2+a+b)) \
/ float( 2*(n+1)*(n+1+a+b))
bn = float( (a*a-b*b) * (2*n+1+a+b) ) \
/ float( 2*(n+1)*(2*n+a+b)*(n+1+a+b) )
cn = float( (n+a)*(n+b)*(2*n+2+a+b) ) \
/ float( (n+1)*(n+1+a+b)*(2*n+a+b) )
return an,bn,cn
apts = numpy.array( pts )
results = numpy.zeros( ( (n+1)*(n+2)*(n+3)/6,len(pts)), type(pts[0][0]))
results[0,:] = 1.0 + apts[:,0]-apts[:,0]+apts[:,1]-apts[:,1]+apts[:,2]-apts[:,2]
if n == 0:
return results
x = numpy.array( [ pt[0] for pt in ref_pts ] )
y = numpy.array( [ pt[1] for pt in ref_pts ] )
z = numpy.array( [ pt[2] for pt in ref_pts ] )
factor1 = 0.5 * ( 2.0 + 2.0*x + y + z )
factor2 = (0.5*(y+z))**2
factor3 = 0.5 * ( 1 + 2.0 * y + z )
factor4 = 0.5 * ( 1 - z )
factor5 = factor4 ** 2
results[idx(1,0,0)] = factor1
for p in range(1,n):
a1 = ( 2.0 * p + 1.0 ) / ( p + 1.0 )
a2 = p / (p + 1.0)
results[idx(p+1,0,0)] = a1 * factor1 * results[idx(p,0,0)] \
-a2 * factor2 * results[ idx(p-1,0,0) ]
# q = 1
for p in range(0,n):
results[idx(p,1,0)] = results[idx(p,0,0)] \
* ( p * (1.0 + y) + ( 2.0 + 3.0 * y + z ) / 2 )
for p in range(0,n-1):
for q in range(1,n-p):
(aq,bq,cq) = jrc(2*p+1,0,q)
qmcoeff = aq * factor3 + bq * factor4
qm1coeff = cq * factor5
results[idx(p,q+1,0)] = qmcoeff * results[idx(p,q,0)] \
- qm1coeff * results[idx(p,q-1,0)]
# now handle r=1
for p in range(n):
for q in range(n-p):
results[idx(p,q,1)] = results[idx(p,q,0)] \
* ( 1.0 + p + q + ( 2.0 + q + p ) * z )
# general r by recurrence
for p in range(n-1):
for q in range(0,n-p-1):
for r in range(1,n-p-q):
ar,br,cr = jrc(2*p+2*q+2,0,r)
results[idx(p,q,r+1)] = \
(ar * z + br) * results[idx(p,q,r) ] \
- cr * results[idx(p,q,r-1) ]
for p in range(n+1):
for q in range(n-p+1):
for r in range(n-p-q+1):
results[idx(p,q,r)] *= math.sqrt((p+0.5)*(p+q+1.0)*(p+q+r+1.5))
return results
def tabulate_jet( self , n , pts , order = 1 ):
from Derivatives import DerivVar
dpts = [ tuple( [ DerivVar( pt[i] , i , order ) \
for i in range( len( pt ) ) ] ) for pt in pts ]
dbfs = self.tabulate( n , dpts )
result = []
for d in range( order + 1 ):
result_d = [ [ foo[d] for foo in bar ] for bar in dbfs ]
result.append( numpy.array( result_d ) )
return result
def get_expansion_set( ref_el ):
"""Returns an ExpansionSet instance appopriate for the given
reference element."""
if ref_el.get_shape() == reference_element.LINE:
return LineExpansionSet( ref_el )
elif ref_el.get_shape() == reference_element.TRIANGLE:
return TriangleExpansionSet( ref_el )
elif ref_el.get_shape() == reference_element.TETRAHEDRON:
return TetrahedronExpansionSet( ref_el )
else:
raise Exception("Unknown reference element type.")
def polynomial_dimension( ref_el , degree ):
"""Returns the dimension of the space of polynomials of degree no
greater than degree on the reference element."""
if ref_el.get_shape() == reference_element.LINE:
return max( 0 , degree + 1 )
elif ref_el.get_shape() == reference_element.TRIANGLE:
return max( (degree+1)*(degree+2)/2 , 0 )
elif ref_el.get_shape() == reference_element.TETRAHEDRON:
return max( 0 , (degree+1)*(degree+2)*(degree+3)/6 )
else:
raise Exception("Unknown reference element type.")
if __name__=="__main__":
from . import reference_element, expansions
from FirstDerivatives import DerivVar
E = reference_element.DefaultTriangle( )
k = 3
pts = E.make_lattice( k )
dpts = [ [ DerivVar( pt[j] , j ) for j in range(len( pt )) ] for pt in pts ]
Phis = expansions.get_expansion_set( E )
phis = Phis.tabulate(k,pts)
dphis = Phis.tabulate(k,dpts)
# dphis_x = numpy.array( [ [ d[1][0] for d in dphi ] for dphi in dphis ] )
# dphis_y = numpy.array([[d[1][1] for d in dphi ] for dphi in dphis ] )
# dphis_z = numpy.array([[d[1][2] for d in dphi ] for dphi in dphis ] )
# print dphis_x
# for dmat in make_dmats( E , k ):
# print dmat
# print
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