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test_basistools.py
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test_basistools.py
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import numpy as np
import scipy
from functools import partial
from ..util import BaseCase
import pygsti.tools.basistools as bt
import pygsti.tools.lindbladtools as lindbladtools
from pygsti.objects.basis import Basis, ExplicitBasis, DirectSumBasis
class BasisToolsTester(BaseCase):
def test_basis_element_labels(self):
basisnames = ['gm', 'std', 'pp']
# One dimensional gm
self.assertEqual([''], bt.basis_element_labels('gm', 1))
# Two dimensional
expectedLabels = [
['I', 'X', 'Y', 'Z'],
['(0,0)', '(0,1)', '(1,0)', '(1,1)'],
['I', 'X', 'Y', 'Z']
]
labels = [bt.basis_element_labels(basisname, 4) for basisname in basisnames]
self.assertEqual(labels, expectedLabels)
with self.assertRaises(AssertionError):
bt.basis_element_labels('asdklfasdf', 4)
# Non power of two for pp labels:
with self.assertRaises(ValueError):
label = bt.basis_element_labels('pp', 9)
# TODO assert correctness
# Single list arg for pp labels
self.assertEqual(bt.basis_element_labels('pp', 4), ['I', 'X', 'Y', 'Z'])
# Four dimensional+
expectedLabels = [
['I', 'X_{0,1}', 'X_{0,2}', 'X_{0,3}', 'X_{1,2}', 'X_{1,3}', 'X_{2,3}', 'Y_{0,1}', 'Y_{0,2}', 'Y_{0,3}',
'Y_{1,2}', 'Y_{1,3}', 'Y_{2,3}', 'Z_{1}', 'Z_{2}', 'Z_{3}'],
['(0,0)', '(0,1)', '(0,2)', '(0,3)', '(1,0)', '(1,1)', '(1,2)', '(1,3)', '(2,0)', '(2,1)', '(2,2)', '(2,3)',
'(3,0)', '(3,1)', '(3,2)', '(3,3)'],
['II', 'IX', 'IY', 'IZ', 'XI', 'XX', 'XY', 'XZ', 'YI', 'YX', 'YY', 'YZ', 'ZI', 'ZX', 'ZY', 'ZZ']
]
labels = [bt.basis_element_labels(basisname, 16) for basisname in basisnames]
self.assertEqual(expectedLabels, labels)
def test_basis_longname(self):
longnames = {bt.basis_longname(b) for b in {'gm', 'std', 'pp', 'qt'}}
self.assertEqual(longnames, {'Gell-Mann basis', 'Matrix-unit basis', 'Pauli-Product basis', 'Qutrit basis'})
with self.assertRaises(KeyError):
bt.basis_longname('not a basis')
def test_expand_contract(self):
# matrix that operates on 2x2 density matrices, but only on the 0-th and 3-rd
# elements which correspond to the diagonals of the 2x2 density matrix.
mxInStdBasis = np.array([[1,0,0,2],
[0,0,0,0],
[0,0,0,0],
[3,0,0,4]], 'd')
# Reduce to a matrix operating on a density matrix space with 2 1x1 blocks (hence [1,1])
begin = Basis.cast('std', [1, 1])
end = Basis.cast('std', 4)
mxInReducedBasis = bt.resize_std_mx(mxInStdBasis, 'contract', end, begin)
#mxInReducedBasis = bt.change_basis(mxInStdBasis, begin, end)
notReallyContracted = bt.change_basis(mxInStdBasis, 'std', 'std') # 4
correctAnswer = np.array([[ 1.0, 2.0],
[ 3.0, 4.0]])
self.assertArraysAlmostEqual(mxInReducedBasis, correctAnswer)
self.assertArraysAlmostEqual(notReallyContracted, mxInStdBasis)
expandedMx = bt.resize_std_mx(mxInReducedBasis, 'expand', begin, end)
#expandedMx = bt.change_basis(mxInReducedBasis, end, begin)
expandedMxAgain = bt.change_basis(expandedMx, 'std', 'std') # , 4)
self.assertArraysAlmostEqual(expandedMx, mxInStdBasis)
self.assertArraysAlmostEqual(expandedMxAgain, mxInStdBasis)
def test_transforms(self):
mxStd = np.array([[1,0,0,0],
[0,1,0,0],
[0,0,1,0],
[0,0,0,1]], 'complex')
vecStd = np.array([1,0,0,0], 'complex')
change = bt.change_basis
mxGM = change(mxStd, 'std', 'gm')
mxStd2 = change(mxGM, 'gm', 'std')
self.assertArraysAlmostEqual(mxStd, mxStd2)
vecGM = change(vecStd, 'std', 'gm')
vecStd2 = change(vecGM, 'gm', 'std')
self.assertArraysAlmostEqual(vecStd, vecStd2)
mxPP = change(mxStd, 'std', 'pp')
mxStd2 = change(mxPP, 'pp', 'std')
self.assertArraysAlmostEqual(mxStd, mxStd2)
vecPP = change(vecStd, 'std', 'pp')
vecStd2 = change(vecPP, 'pp', 'std')
self.assertArraysAlmostEqual(vecStd, vecStd2)
mxPP2 = change(mxGM, 'gm', 'pp')
self.assertArraysAlmostEqual(mxPP, mxPP2)
vecPP2 = change(vecGM, 'gm', 'pp')
self.assertArraysAlmostEqual(vecPP, vecPP2)
mxGM2 = change(mxPP, 'pp', 'gm')
self.assertArraysAlmostEqual(mxGM, mxGM2)
vecGM2 = change(vecPP, 'pp', 'gm')
self.assertArraysAlmostEqual(vecGM, vecGM2)
non_herm_mxStd = np.array([[1,0,2,3j],
[0,1,0,2],
[0,0,1,0],
[0,0,0,1]], 'complex')
non_herm_vecStd = np.array([1,0,2,3j], 'complex') # ~ non-herm 2x2 density mx
rank3tensor = np.ones((4, 4, 4), 'd')
with self.assertRaises(ValueError):
change(non_herm_mxStd, 'std', 'gm') # will result in gm mx with *imag* part
with self.assertRaises(ValueError):
change(non_herm_vecStd, 'std', 'gm') # will result in gm vec with *imag* part
with self.assertRaises(ValueError):
change(non_herm_mxStd, 'std', 'pp') # will result in pp mx with *imag* part
with self.assertRaises(ValueError):
change(non_herm_vecStd, 'std', 'pp') # will result in pp vec with *imag* part
with self.assertRaises(ValueError):
change(rank3tensor, 'std', 'gm') # only convert rank 1 & 2 objects
with self.assertRaises(ValueError):
change(rank3tensor, 'gm', 'std') # only convert rank 1 & 2 objects
with self.assertRaises(ValueError):
change(rank3tensor, 'std', 'pp') # only convert rank 1 & 2 objects
with self.assertRaises(ValueError):
change(rank3tensor, 'pp', 'std') # only convert rank 1 & 2 objects
with self.assertRaises(ValueError):
change(rank3tensor, 'gm', 'pp') # only convert rank 1 & 2 objects
with self.assertRaises(ValueError):
change(rank3tensor, 'pp', 'gm') # only convert rank 1 & 2 objects
densityMx = np.array([[1, 0], [0, -1]], 'complex')
gmVec = bt.stdmx_to_gmvec(densityMx)
ppVec = bt.stdmx_to_ppvec(densityMx)
stdVec = bt.stdmx_to_stdvec(densityMx)
self.assertArraysAlmostEqual(gmVec, np.array([[0], [0], [0], [np.sqrt(2)]], 'd'))
self.assertArraysAlmostEqual(ppVec, np.array([[0], [0], [0], [np.sqrt(2)]], 'd'))
self.assertArraysAlmostEqual(stdVec, np.array([[1], [0], [0], [-1]], 'complex'))
mxFromGM = bt.gmvec_to_stdmx(gmVec)
mxFromPP = bt.ppvec_to_stdmx(ppVec)
mxFromStd = bt.stdvec_to_stdmx(stdVec)
self.assertArraysAlmostEqual(mxFromGM, densityMx)
self.assertArraysAlmostEqual(mxFromPP, densityMx)
self.assertArraysAlmostEqual(mxFromStd, densityMx)
def test_few_qubit_fns(self):
state_vec = np.array([1, 0], 'complex')
dmVec = bt.state_to_pauli_density_vec(state_vec)
self.assertArraysAlmostEqual(dmVec, np.array([[0.70710678], [0], [0], [0.70710678]], 'complex'))
stdMx = np.array([[1, 0], [0, 0]], 'complex') # density matrix
pauliVec = bt.stdmx_to_ppvec(stdMx)
self.assertArraysAlmostEqual(pauliVec, np.array([[0.70710678], [0], [0], [0.70710678]], 'complex'))
stdMx2 = bt.ppvec_to_stdmx(pauliVec)
self.assertArraysAlmostEqual(stdMx, stdMx2)
def test_vec_to_stdmx(self):
vec = np.zeros(shape=(4,))
for b in {'gm', 'pp', 'std'}:
bt.vec_to_stdmx(vec, b)
with self.assertRaises(AssertionError):
bt.vec_to_stdmx(vec, 'akdfj;ladskf')
def test_auto_expand(self):
comp = Basis.cast([('std', 4,), ('std', 1)])
std = Basis.cast('std', 9)
mxStd = np.identity(5)
test = bt.resize_std_mx(mxStd, 'expand', comp, std)
# TODO assert intermediate correctness
test2 = bt.resize_std_mx(test, 'contract', std, comp)
self.assertArraysAlmostEqual(test2, mxStd)
def test_flexible_change_basis(self):
comp = Basis.cast([('gm', 4,), ('gm', 1)])
std = Basis.cast('std', 9)
mx = np.identity(5)
test = bt.flexible_change_basis(mx, comp, std)
self.assertEqual(test.shape[0], comp.elsize)
test2 = bt.flexible_change_basis(test, std, comp)
self.assertArraysAlmostEqual(test2, mx)
def test_change_between_composites(self):
a = Basis.cast('std', [4, 1])
b = Basis.cast('gm', [4, 1])
mxStd = np.identity(5)
test = bt.change_basis(mxStd, a, b)
self.assertEqual(test.shape, mxStd.shape)
test2 = bt.change_basis(test, b, a)
self.assertArraysAlmostEqual(test2, mxStd)
def test_general(self):
std = Basis.cast('std', 4)
std4 = Basis.cast('std', 16)
std2x2 = Basis.cast([('std', 4), ('std', 4)])
gm = Basis.cast('gm', 4)
from_basis, to_basis = bt.build_basis_pair(np.identity(4, 'd'), "std", "gm")
from_basis, to_basis = bt.build_basis_pair(np.identity(4, 'd'), std, "gm")
from_basis, to_basis = bt.build_basis_pair(np.identity(4, 'd'), "std", gm)
mx = np.array([
[1, 0, 0, 1],
[0, 1, 2, 0],
[0, 2, 1, 0],
[1, 0, 0, 1]
])
bt.change_basis(mx, 'std', 'gm') # shortname lookup
bt.change_basis(mx, std, gm) # object
bt.change_basis(mx, std, 'gm') # combination
bt.flexible_change_basis(mx, std, gm) # same dimension
I2x2 = np.identity(8, 'd')
I4 = bt.flexible_change_basis(I2x2, std2x2, std4)
self.assertArraysAlmostEqual(bt.flexible_change_basis(I4, std4, std2x2), I2x2)
with self.assertRaises(AssertionError):
bt.change_basis(mx, std, std4) # basis size mismatch
mxInStdBasis = np.array([[1,0,0,2],
[0,0,0,0],
[0,0,0,0],
[3,0,0,4]], 'd')
begin = Basis.cast('std', [1, 1])
end = Basis.cast('std', 4)
mxInReducedBasis = bt.resize_std_mx(mxInStdBasis, 'contract', end, begin)
original = bt.resize_std_mx(mxInReducedBasis, 'expand', begin, end)
# TODO assert correctness
def test_sparse_lindblad_bases(self):
sparsePP = Basis.cast("pp", 16, sparse=True)
mxs = sparsePP.elements
for lbl, mx in zip(sparsePP.labels, mxs):
print("{}: {} matrix with {} nonzero entries (of {} total)".format(
lbl, mx.shape, mx.nnz, mx.shape[0] * mx.shape[1]
))
print(mx.toarray())
print("{} basis elements".format(len(sparsePP)))
self.assertEqual(len(sparsePP), 16)
# TODO assert correctness
M = np.ones((16, 16), 'd')
v = np.ones(16, 'd')
S = scipy.sparse.identity(16, 'd', 'csr')
print("Test types after basis change by sparse basis:")
Mout = bt.change_basis(M, sparsePP, 'std')
vout = bt.change_basis(v, sparsePP, 'std')
Sout = bt.change_basis(S, sparsePP, 'std')
print("{} -> {}".format(type(M), type(Mout)))
print("{} -> {}".format(type(v), type(vout)))
print("{} -> {}".format(type(S), type(Sout)))
self.assertIsInstance(Mout, np.ndarray)
self.assertIsInstance(vout, np.ndarray)
self.assertIsInstance(Sout, scipy.sparse.csr_matrix)