def get_pt(pt_str):
xjs = []
for xj in pt_str.strip('()').split(','):
if '/' in xj:
n, d = xj.split('/')
xjf = FastFraction(int(n), int(d))
else:
xjf = FastFraction(int(xj), 1)
xjs.append(xjf)
return tuple(xjs)
def test_vertex_moments(self):
known_moments = [
{
'curve': get_haverkort_curve_A26(),
'moments': [FastFraction(k, 28) for k in [0, 5, 9, 12, 16, 19, 23, 28]],
},
{
'curve': get_haverkort_curve_2(),
'moments': [FastFraction(k, 28) for k in [1, 6, 8, 13, 15, 20, 22, 27]],
},
]
for d in known_moments:
moments = d['curve'].get_vertex_moments().values()
self.assertSetEqual(set(d['moments']), set(moments))
def test_55_ratio(self):
good_proto = Proto(dim=2,
div=5,
cubes=[
(0, 0),
(0, 1),
(1, 1),
(1, 0),
(2, 0),
(2, 1),
(2, 2),
(1, 2),
(0, 2),
(0, 3),
(0, 4),
(1, 4),
(1, 3),
(2, 3),
(2, 4),
(3, 4),
(4, 4),
(4, 3),
(3, 3),
(3, 2),
(4, 2),
(4, 1),
(3, 1),
(3, 0),
(4, 0),
])
# in new version we have (0,0)->(0,1) gate
good_proto = BaseMap.from_basis('ji') * good_proto
paths_gen = PathsGenerator(dim=2,
div=5,
hdist=1,
max_cdist=1,
verbose=1)
for paths in paths_gen.generate_paths():
if paths[0].proto == good_proto:
path0 = paths[0]
break
pcurve = PathFuzzyCurve.init_from_paths([path0])
estimator = Estimator(utils.ratio_l2_squared)
curve = estimator.estimate_ratio(pcurve,
rel_tol_inv=10000,
verbose=False)['curve']
ratio = estimator.estimate_ratio(curve,
rel_tol_inv=10000,
use_vertex_brkline=True,
verbose=False)
assert ratio['lo'] == (FastFraction(408, 73)**2)
def test_mul(self):
assert FastFraction(2, 3) * FastFraction(-1, 2) == FastFraction(-1, 3)
assert FastFraction(1, 5) * FastFraction(5, -1) == FastFraction(-1, 1)
def test_neg(self):
assert -FastFraction(3, 5) == FastFraction(-3, 5)
assert -FastFraction(0, 1) == FastFraction(0, -1)
def test_sub(self):
assert FastFraction(1, 2) - FastFraction(1, 6) == FastFraction(1, 3)
def test_add(self):
assert FastFraction(1, 3) + FastFraction(1, 6) == FastFraction(1, 2)
assert FastFraction(1, 5) + FastFraction(1, -5) == FastFraction(0, 1)
kwargs['ratio_func'] = funcs.get(kwargs.pop('metric'))
verbosity = kwargs.pop('verbose')
if verbosity == 1:
logging.basicConfig(level=logging.INFO)
elif verbosity == 2:
logging.basicConfig(level=logging.DEBUG)
if (not args.output_stats) and (not args.output_gates) and (args.metric is
None):
raise ValueError("Define metric to estimate ratio!")
gates_file = kwargs.pop('gates_file')
if gates_file is not None:
with open(gates_file) as fh:
for line in fh:
gates = [
Gate.parse(token) for token in line.strip().split('|')
]
gate_list.append(gates)
kwargs['gate_list'] = gate_list
gates_str = kwargs.pop('gates')
if gates_str is not None:
gates = [Gate.parse(token) for token in gates_str.strip().split('|')]
kwargs['gate_list'] = [gates]
if args.upper_bound is not None:
kwargs['upper_bound'] = FastFraction.parse(args.upper_bound)
run_estimator(**kwargs)
def cnt_bnd_coords(pt):
return len(
list(xj for xj in pt
if xj == FastFraction(0, 1) or xj == FastFraction(1, 1)))
def is_vertex(pt):
if any(FastFraction(0, 1) < xj < FastFraction(1, 1) for xj in pt):
return False
return True
for idx, gates in enumerate(gates_list):
pts = []
for g in gates:
pts += [g.entrance, g.exit]
vertex_count = len(list(pt for pt in pts if is_vertex(pt)))
if vertex_count != 0:
continue
total_bnd_coords = sum(
cnt_bnd_coords(gate.entrance) + cnt_bnd_coords(gate.exit)
for gate in gates)
add_bnd_coords = total_bnd_coords - 2 * pattern_count
if add_bnd_coords != 0:
continue
conf = {
'dim': 2,
'div': 2,
'ratio_func_name': 'linf',
#'ratio_func_name': 'l2',
'gates': gates,
'rel_tol_inv': 10000,
'upper_bound': FastFraction(5, 1),
#'upper_bound': FastFraction(51, 10),
}
print('GATE:', idx, [str(g) for g in gates])
perebor(conf)
print('===')
print('')