def get_upper_degree(self):
list_of_products = [self.variables[i] ** self.max_degrees[i]
for i in range(self.n)]
product = prod(list_of_products)
product = Poly(product).monoms()
return monomial_deg(*product)
def get_upper_degree(self):
list_of_products = [
self.variables[i]**self.max_degrees[i] for i in range(self.n)
]
product = prod(list_of_products)
product = Poly(product).monoms()
return monomial_deg(*product)
def get_upper_degree(self):
SymPyDeprecationWarning(feature="get_upper_degree",
useinstead="get_max_degrees",
issue=17763,
deprecated_since_version="1.5").warn()
list_of_products = [self.variables[i] ** self._max_degrees[i]
for i in range(self.n)]
product = prod(list_of_products)
product = Poly(product).monoms()
return monomial_deg(*product)
def sdm_monomial_deg(M):
"""
Return the total degree of ``M``.
Examples
========
For example, the total degree of `x^2 y f_5` is 3:
>>> from sympy.polys.distributedmodules import sdm_monomial_deg
>>> sdm_monomial_deg((5, 2, 1))
3
"""
return monomial_deg(M[1:])
def sdm_monomial_deg(M):
"""
Return the total degree of ``M``.
Examples
========
For example, the total degree of `x^2 y f_5` is 3:
>>> from sympy.polys.distributedmodules import sdm_monomial_deg
>>> sdm_monomial_deg((5, 2, 1))
3
"""
return monomial_deg(M[1:])
def get_upper_degree(self):
sympy_deprecation_warning(
"""
The get_upper_degree() method of DixonResultant is deprecated. Use
get_max_degrees() instead.
""",
deprecated_since_version="1.5",
active_deprecations_target="deprecated-dixonresultant-properties"
)
list_of_products = [self.variables[i] ** self._max_degrees[i]
for i in range(self.n)]
product = prod(list_of_products)
product = Poly(product).monoms()
return monomial_deg(*product)
def _compute_smd(sub, mlist: list):
return (monomial_deg(sub) - 1) * len(list(filter(lambda m: monomial_divides(sub, m), mlist)))
def _compute_aeqd(sub: Tuple[int], eq_degs):
mon_degs = map(lambda deg: deg + monomial_deg(sub) - 1, eq_degs)
quad_discrepancies = filter(lambda x: x > 0, map(lambda d: d - 2, mon_degs))
return sum(quad_discrepancies)
def default_strategy(system) -> int:
total_nonsquare = sum([monomial_deg(m) for m in system.nonsquares])
return total_nonsquare + system.dim * len(system.vars)
