def test_TVB_paper_example():
#Power form of the polys
p1 = MultiPower(np.array([[1, -4, 0], [0, 3, 0], [1, 0,
0]])) #y^2 + 3xy - 4x +1
p2 = MultiPower(np.array([[3, 0, -2], [6, -6, 0],
[0, 0, 0]])) #-6xy -2x^2 + 6y +3
#Cheb form of the polys
c1 = MultiCheb(np.array([[2, 0, -1], [6, -6, 0], [0, 0,
0]])) #p1 in Cheb form
c2 = MultiCheb(np.array([[1.5, -4, 0], [0, 3, 0], [.5, 0,
0]])) #p2 in Cheb form
#Homogenous power form
p1 = MultiPower(np.array([[1, -4, 0], [0, 3, 0], [1, 0,
0]])) #y^2 + 3xy - 4x +1
p2 = MultiPower(np.array([[3, 0, -2], [6, -6, 0],
[0, 0, 0]])) #-6xy -2x^2 + 6y +3
right_number_of_roots = 4
power_roots = tvb.solve([p1, p2], verbose=True)
assert len(power_roots) == right_number_of_roots
for root in power_roots:
assert np.isclose(0, p1(root), atol=1.e-8)
assert np.isclose(0, p2(root), atol=1.e-8)
cheb_roots = tvb.solve([c1, c2], verbose=True)
assert len(cheb_roots) == right_number_of_roots
for root in cheb_roots:
assert np.isclose(0, c1(root), atol=1.e-8)
assert np.isclose(0, c1(root), atol=1.e-8)
def testRoots_4():
f1 = MultiPower(np.array([[5, -1], [1, 0]]))
f2 = MultiPower(np.array([[1, -1], [-1, 0]]))
root = rf.roots([f1, f2], method='Macaulay')[0]
assert (all(np.isclose(root, [-2, 3])))
def Mxi_Matrix(i, basisDict, VB, dim, poly_type, verbose=False):
'''
Uses the reduced Macaulay matrix to construct the Moller-Stetter matrix M_xi, which
represents the linear map of multiplying by xi in the space C[x1, ..., xn]/I.
Parameters
----------
i : int
The index of the variable xi to make the Moller-Stetter matrix of, where variables
are indexed as x1, x2, ..., xn.
basisDict: dictionary
A dictionary which maps monomials not in the basis to linear combinations
of monomials in the basis. Generated using the TVB method.
VB: numpy array
Represents a vector basis for the space C[x1, ..., xn]/I created with the TVB method.
Each row represents a monomial in the basis as the degrees of each variable.
For example, x^2y^5 would be represented as [2,5].
dim: int
The dimension of the system (n)
verbose : bool
Prints information about how the roots are computed.
Returns
-------
Mxi : 2D numpy array
The Moller-Stetter matrix which represents multiplying by xi
'''
VB = VB.tolist() #convert to list bc numpy's __contains__() function is broken
#Construct the polynomial to create the MS Matrix of (xi)
xi_ind = np.zeros(dim, dtype=int)
xi_ind[i-1] = 1
coef = np.zeros((2,)*dim)
coef[tuple(xi_ind)] = 1
if poly_type == "MultiPower":
xi = MultiPower(np.array(coef))
elif poly_type == "MultiCheb":
xi = MultiCheb(np.array(coef))
if verbose:
print("\nCoefficients of polynomial whose Moller-Stetter matrix we construt\n", xi.coeff)
# Build multiplication matrix M_xi
Mxi = np.zeros((len(VB), len(VB)))
for j in range(len(VB)): #multiply each monomial in the basis by xi
product_coef = xi.mon_mult(VB[j], returnType = 'Matrix')
for monomial in zip(*np.where(product_coef != 0)):
if list(monomial) in VB: #convert to list to test if list of lists
Mxi[VB.index(list(monomial))][j] += product_coef[monomial]
else:
Mxi[:,j] -= product_coef[monomial]*basisDict[monomial]
# Construct var_dict
var_dict = {}
for i in range(len(VB)):
mon = VB[i]
if np.sum(mon) == 1 or np.sum(mon) == 0:
var_dict[tuple(mon)] = i
return Mxi
def test_mon_mult_random():
np.random.seed(988)
#test with random matrices
possible_dim = np.random.randint(1,5, (1,10))
dim = possible_dim[0, np.random.randint(1,9)]
shape = list()
for i in range(dim):
shape.append(np.random.randint(2,4))
matrix1 = np.random.randint(1,11,(shape))
M1 = MultiPower(matrix1)
shape2 = list()
for i in range(dim):
shape2.append(np.random.randint(2,4))
matrix2 = np.ones(shape2)
M2 = MultiPower(matrix2)
M3 = M1*M2
for index, i in np.ndenumerate(M2.coeff):
if sum(index) == 0:
M4 = MultiPower.mon_mult(M1, index)
else:
M4 = M4 + MultiPower.mon_mult(M1, index)
if M3.shape != M4.shape:
new_M3_coeff, new_M4_coeff = utils.match_size(M3.coeff,M4.coeff)
else:
new_M3_coeff, new_M4_coeff = M3.coeff, M4.coeff
assert np.allclose(new_M3_coeff, new_M4_coeff)
def test_add():
a1 = np.arange(27).reshape((3,3,3))
Test2 = MultiPower(a1)
a2 = np.ones((3,3,3))
Test3 = MultiPower(a2)
addTest = Test2 + Test3
assert (addTest.coeff == (Test2.coeff + Test3.coeff)).all()
def testReducePoly():
poly = MultiPower(np.array([[-3], [2], [-4], [1]]))
g = MultiPower(np.array([[2], [1]]))
basisSet = set()
basisSet.add((0, 0))
reduced = rf.reduce_poly(poly, [g], basisSet)
assert (MultiPower(reduced).coeff == np.array([[-31.]]))
def test_mult():
test1 = np.array([[0,1],[2,1]])
test2 = np.array([[2,2],[3,0]])
p1 = MultiPower(test1)
p2 = MultiPower(test2)
new_poly = p1*p2
truth = MultiPower(np.array([[0, 2, 2],[4,9,2],[6,3,0]]))
assert np.allclose(new_poly.coeff, truth.coeff)
def testRoots_5():
f1 = MultiPower(np.array([[0, -1], [0, 0], [1, 0]]))
f2 = MultiPower(np.array([[1, -1], [1, 0]]))
roots = rf.roots([f1, f2], method='Macaulay')
assert (all(np.isclose(roots[0], [-0.61803399, 0.38196601])))
assert (all(np.isclose(roots[1], [1.61803399, 2.61803399])))
def testReducePoly_2():
poly = MultiPower(np.array([[-7], [2], [-13], [4]]))
g = MultiPower(np.array([[-2], [3], [1]]))
basisSet = set()
basisSet.add((0, 0))
basisSet.add((1, 0))
reduced = rf.reduce_poly(poly, [g], basisSet)
assert (np.all(MultiPower(reduced).coeff == np.array([[-57.], [85.]])))
def test_vectorSpaceBasis():
f1 = MultiPower(np.array([[0, -1.5, .5], [-1.5, 1.5, 0], [1, 0, 0]]))
f2 = MultiPower(np.array([[0, 0, 0], [-1, 0, 1], [0, 0, 0]]))
f3 = MultiPower(
np.array([[0, -1, 0, 1], [0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0]]))
G = [f1, f2, f3]
basis = rf.vectorSpaceBasis(G)[0]
trueBasis = [(0, 0), (1, 0), (0, 1), (1, 1), (0, 2)]
assert ((len(basis) == len(trueBasis)) and (m in basis for m in trueBasis))
def testRoots_3():
# roots of [x^2-y, x^3-y+1]
f1 = MultiPower(np.array([[0, -1], [0, 0], [1, 0]]))
f2 = MultiPower(np.array([[1, -1], [0, 0], [0, 0], [1, 0]]))
roots = rf.roots([f1, f2], method='Groebner')
values_at_roots = np.array([[f1(root) for root in roots],
[f2(root) for root in roots]])
assert (np.all(np.isclose(values_at_roots, 0)))
def test_roots_at_inf():
g = MultiPower(np.array([[0, 0, 1], [-1, 0, 0]]).T) #f(x,y) = x^2 - y
assert roots_at_inf(g) == [(0, 1)]
f = MultiPower(np.array([[0, 1]])) #f(x,y) = y
g = MultiPower(np.array([[0, 0, -1], [1, 0, 0]])) #f(x,y) = x - y^2
assert roots_at_inf(f) == [(1, 0)]
assert roots_at_inf(g) == [(1, 0)]
f = MultiPower(np.array([[5, 6, 2], [9, 3, 0], [1, 0, 0]]))
assert roots_at_inf(f) == [(-2, 1), (-1, 1)]
def test_evaluate_grid1():
#Evaluate 2 + yx^2 + 3y^2 - xy on grid (0,0), (0,1), (0,2), (1,0), (1,1), (1,2), (2,0), (2,1), (2,2)
poly = MultiPower(np.array([[2,0,3],
[0,-1,0],
[0,1,0]]))
x = np.arange(3)
xy = np.column_stack([x,x])
sol = np.array([[2,5,14],
[2,5,14],
[2,7,18]])
assert(np.all(poly.evaluate_grid(xy) == sol))
def test_find_degree():
#Test Case #1 - 2,3,4, and 5 2D Polynomials of degree 3
degree3Coeff = np.array([[1, 1, 1, 1], [1, 1, 1, 0], [1, 1, 0, 0],
[1, 0, 0, 0]])
A = MultiPower(degree3Coeff)
B = MultiPower(degree3Coeff)
C = MultiPower(degree3Coeff)
D = MultiPower(degree3Coeff)
E = MultiPower(degree3Coeff)
assert (find_degree([A, B]) == 5)
assert (find_degree([A, B, C]) == 7)
assert (find_degree([A, B, C, D]) == 9)
assert (find_degree([A, B, C, D, E]) == 11)
#Test Case #2 - A 2D polynomials of degree 3 and one of degree 5
degree5Coeff = np.array([[1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 0],
[1, 1, 1, 1, 0, 0], [1, 1, 1, 0, 0, 0],
[1, 1, 0, 0, 0, 0], [1, 0, 0, 0, 0, 0]])
F = MultiPower(degree5Coeff)
assert (find_degree([A, F]) == 7)
#Test Case #3 - Two 3D polynomials of degree 15
G = MultiPower(np.random.rand(6, 6, 6))
H = MultiPower(np.random.rand(6, 6, 6))
assert (find_degree([G, H]) == 29)
def test_find_degree():
'''Test Case #1 - 2,3,4, and 5 2D Polynomials of degree 3'''
degree3Coeff = np.array([
[1,1,1,1],
[1,1,1,0],
[1,1,0,0],
[1,0,0,0]])
A = MultiPower(degree3Coeff)
B = MultiPower(degree3Coeff)
C = MultiPower(degree3Coeff)
D = MultiPower(degree3Coeff)
E = MultiPower(degree3Coeff)
assert(find_degree([A,B]) == 5)
assert(find_degree([A,B,C]) == 7)
assert(find_degree([A,B,C,D]) == 9)
assert(find_degree([A,B,C,D,E]) == 11)
'''Test Case #2 - A 2D polynomials of degree 3 and one of degree 5'''
degree5Coeff = np.array([
[1,1,1,1,1,1],
[1,1,1,1,1,0],
[1,1,1,1,0,0],
[1,1,1,0,0,0],
[1,1,0,0,0,0],
[1,0,0,0,0,0]])
F = MultiPower(degree5Coeff)
assert(find_degree([A,F]) == 7)
''' Test Case #3 - Two 3D polynomials of degree 15'''
G = MultiPower(np.random.rand(6,6,6))
H = MultiPower(np.random.rand(6,6,6))
assert(find_degree([G,H]) == 29)
#Test 3 - Simple Example in 2D
poly1 = MultiPower(np.array([[3,0,1],[0,0,0],[0,0,1]]))
poly2 = MultiPower(np.array([[3,0],[1,1],[0,1]]))
found_degree = find_degree([poly1,poly2])
correct_degree = 6
assert found_degree == correct_degree
#Test 4 - Simple Example in 3D
a = np.zeros((4,4,4))
a[3,3,3] = 1
poly1 = MultiCheb(a)
poly2 = MultiCheb(np.ones((3,5,4)))
poly3 = MultiCheb(np.ones((2,4,5)))
found_degree1 = find_degree([poly1,poly2,poly3])
correct_degree1 = 24
assert found_degree1 == correct_degree1
def test_sorted_polys_coeff():
A = MultiPower(
np.array([[2, 0, -3, 0, 0], [0, 1, 0, 0, 0], [-2, 0, 0, 0, 0],
[0, 0, 4, 0, 0], [0, 0, 0, 0, -2]]))
B = MultiPower(
np.array([[3, 0, -5, 0, 0, 4, 2, -6, 3, -6],
[-2, 0, -1, 1, -1, 4, 2, -6, -5, -2],
[-1, 3, 2, -2, 0, 4, -1, -2, -4, 6],
[4, 2, 5, 9, 0, 3, 2, -1, -3, -3],
[3, -3, -5, -2, 0, 4, -2, 2, 1, -6]]))
assert ([A, B] == ut.sorted_polys_coeff([A, B]))
C = MultiPower(np.array([[1]]))
assert ([C, A, B] == ut.sorted_polys_coeff([A, B, C]))
def testRoots():
f1 = MultiPower(np.array([[0, -1.5, .5], [-1.5, 1.5, 0], [1, 0, 0]]),
clean_zeros=False)
f2 = MultiPower(np.array([[0, 0, 0], [-1, 0, 1], [0, 0, 0]]),
clean_zeros=False)
f3 = MultiPower(np.array([[0, -1, 0, 1], [0, 0, 0, 0], [0, 0, 0, 0],
[0, 0, 0, 0]]),
clean_zeros=False)
roots = rf.roots([f1, f2, f3], method='Groebner')
values_at_roots = np.array([[f1(root) for root in roots],
[f2(root) for root in roots],
[f3(root) for root in roots]])
assert (np.all(np.isclose(values_at_roots, 0)))
def roots_at_inf(f):
'''
Finds the roots at infinity of a homogenous, bivarite power-basis polynomial.
Parameters
----------
poly: a bivariate power-basis polynomial
returns
-------
the roots at infinity of the polynomial (list of tuples). In the form (x,y). Since at infinity, z = 0
'''
#get the coefficients of the homogenous part of f: [y^d ... x^d]
f_d_coefs = np.diag(np.fliplr(pad_with_zeros(f.coeff)))
#find all x s.t. f_d(x,1) == 0
#essentially, set y = 1 and solve a 1D polynomial with coefficients from f_d
#if there is only 1 nonzero coefficient in this 1D polynomial have to handle separately
if sum(f_d_coefs != 0) == 1:
if np.where(f_d_coefs != 0) == np.array([0]): #if the nonzero coef in the 1D poly is the constant, only root at inf is (1,0)
return [(1,0)]
else: #f_d(x,y) = x^a y^b, so 0 = f_d(x,1) == x^a implies x = 0
x_coords = np.array([0])
else:
x_coords = solve(MultiPower(f_d_coefs))
inf_roots_f_d = list(zip(x_coords, np.ones(len(x_coords))))
#check if f_d(1,0) == 0
#f_d(1,0) = the coef of x^d
if np.isclose(f_d_coefs[-1],0):
inf_roots_f_d.append((1,0))
return inf_roots_f_d
def _random_poly(_type, dim):
'''
Generates a random polynomial that has the form
c_1x_1 + c_2x_2 + ... + c_nx_n where n = dim and each c_i is a randomly
chosen integer between 0 and 1000.
Parameters
----------
_type : string
Type of Polynomial to generate. "MultiCheb" or "MultiPower".
dim : int
Degree of polynomial to generate (?).
Returns
-------
Polynomial
Randomly generated Polynomial.
'''
_vars = get_var_list(dim)
random_poly_shape = [2 for i in range(dim)]
random_poly_coeff = np.zeros(tuple(random_poly_shape), dtype=int)
for var in _vars:
random_poly_coeff[var] = np.random.randint(1000)
if _type == 'MultiCheb':
return MultiCheb(random_poly_coeff), _vars
else:
return MultiPower(random_poly_coeff), _vars
def testReducePoly_4():
poly = MultiPower(
np.array([[[-1, 2, 0], [0, 0, 0], [-3, 0, 0]],
[[0, 0, 0], [2, 0, 0], [0, 0, 0]],
[[0, 0, 0], [0, 0, 1], [0, 0, 0]]]))
d1 = MultiPower(np.array([[[0, -3, 0], [0, 0, 0], [1, 0, 0]]]))
d2 = MultiPower(np.array([[[0, 0, 0, 1], [4, 0, 0, 0]]]))
d3 = MultiPower(np.array([[[-1]], [[1]]]))
basisSet = set()
for i in range(2):
for j in range(3):
for k in range(1):
basisSet.add((k, i, j))
reduced = rf.reduce_poly(poly, [d1, d2, d3], basisSet)
assert (np.all(
MultiPower(reduced).coeff == np.array([[[-1, -7, 0], [2, 0, 1]]])))
def test_evaluate():
# Evaluate .5xyz + 2x + y + z at (4,2,1)
poly = MultiPower(np.array([[[0,1,0],
[1,0,0],
[0,0,0]],
[[2,0,0],
[0,.5,0],
[0,0,0]]]))
assert(poly((4,2,1)) == 15)
def getPoly(deg, power):
'''
A helper function for testing. Returns a random 1D polynomial of the given degree.
power is a boolean indicating whether or not the polynomial should be MultiPower.
'''
coeff = np.random.random_sample(deg+1)
if power:
return MultiPower(coeff)
else:
return MultiCheb(coeff)
def test_common_root_at_inf():
f = MultiPower(np.array([[0, 1]])) #f(x,y) = y
g = MultiPower(np.array([[0, 0, -1], [1, 0, 0]])) #f(x,y) = x - y^2
#assert common_root_at_inf([f,g]) == True
f = MultiPower(np.array([[0, 1]])) #f(x,y) = y
g = MultiPower(np.array([[0, 0, -1], [1, 0, 0]]).T) #f(x,y) = x^2 - y
#assert common_root_at_inf([f,g]) == False
#from ./Easy/dpdx-dpdy_ex016.mat, which is a dupliate of ./Easy/dpdx-dpdy_ex007.mat and almost the same as ./Easy/dpdx-dpdy_ex008.mat
f = MultiPower(
np.array([[-0.21875, 0., 1.3125, 0., -1.09375, 0., 0.21875],
[0., -2.625, 0., 4.375, 0., -1.3125, 0.],
[1.3125, 0., -6.5625, 0., 3.28125, 0., 0.],
[0., 4.375, 0., -4.375, 0., 0., 0.],
[-1.09375, 0., 3.28125, 0., 0., 0., 0.],
[0., -1.3125, 0., 0., 0., 0., 0.],
[0.21875, 0., 0., 0., 0., 0., 0.]]))
g = MultiPower(
np.array([[0., -0.65625, 0., 1.09375, 0., -0.328125],
[0.65625, 0., -3.28125, 0., 1.640625, 0.],
[0., 3.28125, 0., -3.28125, 0., 0.],
[-1.09375, 0., 3.28125, 0., 0., 0.],
[0., -1.640625, 0., 0., 0., 0.],
[0.328125, 0., 0., 0., 0., 0.]]))
assert common_root_at_inf([f, g]) == True
#from ./Easy/dpdx-dpdy_C1.mat
f = MultiPower(
np.array([[0., 1., -1.5, -0.5, -1.875, 0., 0.875],
[0., -3., 1.5, 1.5, -0.625, 0., 0.],
[-0.125, 2.5, 0.375, -1.5, 1.25, 0., 0.],
[0.125, 0.5, -0.75, 0.5, 0., 0., 0.],
[0.125, -1.5, 0.375, 0., 0., 0., 0.],
[-0.125, 0.5, 0., 0., 0., 0., 0.]]))
g = MultiPower(
np.array([[0., 0.25, 9.], [0., 0., 0.], [-0.75, -1., 0.], [0, 0, 0]]))
assert common_root_at_inf([f, g]) == False
f = MultiPower(np.array([[0., 0., 0., 1.]]))
g = MultiPower(np.array([[0., 0., 0., 0., 1.25]]))
assert common_root_at_inf([f, g]) == True
def testMultMatrix_2():
f1 = MultiPower(np.array([[0, -1.5, .5], [-1.5, 1.5, 0], [1, 0, 0]]))
f2 = MultiPower(np.array([[0, 0, 0], [-1, 0, 1], [0, 0, 0]]))
f3 = MultiPower(
np.array([[0, -1, 0, 1], [0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0]]))
GB = [f1, f2, f3]
VB = rf.vectorSpaceBasis(GB)[0]
x = MultiPower(np.array([[0], [1]]))
y = MultiPower(np.array([[0, 1]]))
mx_Eig = np.linalg.eigvals(rf.multMatrix(x, GB, VB))
my_Eig = np.linalg.eigvals(rf.multMatrix(y, GB, VB))
assert (len(mx_Eig) == 5)
assert (len(my_Eig) == 5)
assert (np.allclose(mx_Eig, [-1., 2., 1., 1., 0.]))
assert (np.allclose(my_Eig, [1., -1., 1., -1., 0.]))
def testReducePoly_3():
poly = MultiPower(
np.array([[0, -1, 0, 1], [0, 2, 0, 0], [0, 0, 1, 0], [1, 0, 0, 0]]))
g1 = MultiPower(np.array([[0, 0, 0], [-2, 0, 0], [1, 0, 0]]))
g2 = MultiPower(
np.array([[0, -1, 0, 1], [3, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0]]))
basisSet = set()
basisSet.add((0, 0))
basisSet.add((0, 1))
basisSet.add((0, 2))
basisSet.add((1, 0))
basisSet.add((1, 1))
basisSet.add((1, 2))
reduced = rf.reduce_poly(poly, [g1, g2], basisSet)
assert (np.all(
MultiPower(reduced).coeff == np.array([[0, 0, 0], [1, 2, 2]])))
def test_mon_mult():
"""
Tests monomial multiplication using normal polynomial multiplication.
"""
np.random.seed(4)
#Simple 2D test cases
cheb1 = MultiCheb(np.array([[0, 0, 0], [0, 0, 0], [0, 0, 1]]))
mon1 = (1, 1)
result1 = cheb1.mon_mult(mon1)
truth1 = np.array([[0, 0, 0, 0], [0, 0.25, 0, 0.25], [0, 0, 0, 0],
[0, 0.25, 0, 0.25]])
assert np.allclose(result1.coeff, truth1)
#test with random matrices
cheb2 = np.random.randint(-9, 9, (4, 4))
C1 = MultiCheb(cheb2)
C2 = cheb2poly(C1)
C3 = MultiCheb.mon_mult(C1, (1, 1))
C4 = MultiPower.mon_mult(C2, (1, 1))
C5 = poly2cheb(C4)
assert np.allclose(C3.coeff, C5.coeff)
# test results of chebyshev mult compared to power multiplication
cheb3 = np.random.randn(5, 4)
c1 = MultiCheb(cheb3)
c2 = MultiCheb(np.ones((4, 2)))
for index, i in np.ndenumerate(c2.coeff):
if sum(index) == 0:
c3 = c1.mon_mult(index)
else:
c3 = c3 + c1.mon_mult(index)
p1 = cheb2poly(c1)
p2 = cheb2poly(c2)
p3 = p1 * p2
p4 = cheb2poly(c3)
assert np.allclose(p3.coeff, p4.coeff)
# test results of chebyshev mult compared to power multiplication in 3D
cheb4 = np.random.randn(3, 3, 3)
a1 = MultiCheb(cheb4)
a2 = MultiCheb(np.ones((3, 3, 3)))
for index, i in np.ndenumerate(a2.coeff):
if sum(index) == 0:
a3 = a1.mon_mult(index)
else:
a3 = a3 + a1.mon_mult(index)
q1 = cheb2poly(a1)
q2 = cheb2poly(a2)
q3 = q1 * q2
q4 = cheb2poly(a3)
assert np.allclose(q3.coeff, q4.coeff)
def getPoly(deg, dim):
'''
A helper function for testing. Returns a random upper triangular polynomial of the given dimension and degree.
power is a boolean indicating whether or not the polynomial should be MultiPower.
'''
deg += 1
ACoeff = np.random.random_sample(deg * np.ones(dim, dtype=int))
for i, j in np.ndenumerate(ACoeff):
if np.sum(i) >= deg:
ACoeff[i] = 0
return MultiPower(ACoeff)
def test_evaluate2():
# Evaluate -.5x^2y + 2xy^2 - 3z^2 + yz at (7.4,2.33,.25)
poly = MultiPower(np.array([[[0,0,-3],
[0,1,0],
[0,0,0]],
[[0,0,0],
[0,0,0],
[2,0,0]],
[[0,0,0],
[-.5,0,0],
[0,0,0]]]))
assert(np.isclose(poly((7.4, 2.33, .25)), 16.94732))
def test_evaluate_grid2():
#Evaluate zy^2 + 3z^2 + 3x + zx^2y^2 on grid {0, 1, 2}X{0, 1, 2}X{0, 1, 2}
poly = MultiPower(np.array([[[0,0,3],
[0,0,0],
[0,1,0]],
[[3,0,0],
[0,0,0],
[0,0,0]],
[[0,0,0],
[0,0,0],
[0,1,0]]]))
x = np.arange(3)
xyz = np.column_stack([x,x,x])
sol = np.array([[[0,3,12],
[0,4,14],
[0,7,20]],
[[3,6,15],
[3,8,19],
[3,14,31]],
[[6,9,18],
[6,14,28],
[6,29,58]]])
assert(np.all(poly.evaluate_grid(xyz) == sol))
def testRoots_2():
f1 = MultiPower(
np.array([[[5, 0, 0], [0, 0, 0], [0, 0, 0]],
[[0, -2, 0], [0, 0, 0], [0, 0, 0]],
[[1, 0, 0], [0, 0, 0], [0, 0, 0]]]))
f2 = MultiPower(
np.array([[[1, 0, 0], [0, 1, 0], [0, 0, 0]],
[[0, 0, 0], [0, 0, 0], [1, 0, 0]],
[[0, 0, 0], [0, 0, 0], [0, 0, 0]]]))
f3 = MultiPower(
np.array([[[0, 0, 0], [0, 0, 0], [3, 0, 0]],
[[0, -8, 0], [0, 0, 0], [0, 0, 0]],
[[0, 0, 0], [0, 0, 0], [0, 0, 0]]]))
roots = rf.roots([f1, f2, f3], method='Groebner')
values_at_roots = np.array([[f1(root) for root in roots],
[f2(root) for root in roots],
[f3(root) for root in roots]])
assert (np.all(np.isclose(values_at_roots, 0)))
