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train | SdpRelaxation.find_solution_ranks | Helper function to detect rank loop in the solution matrix.
:param sdpRelaxation: The SDP relaxation.
:type sdpRelaxation: :class:`ncpol2sdpa.SdpRelaxation`.
:param x_mat: Optional parameter providing the primal solution of the
moment matrix. If not provided, the solution ... | ncpol2sdpa/sdp_relaxation.py | def find_solution_ranks(self, xmat=None, baselevel=0):
"""Helper function to detect rank loop in the solution matrix.
:param sdpRelaxation: The SDP relaxation.
:type sdpRelaxation: :class:`ncpol2sdpa.SdpRelaxation`.
:param x_mat: Optional parameter providing the primal solution of the
... | def find_solution_ranks(self, xmat=None, baselevel=0):
"""Helper function to detect rank loop in the solution matrix.
:param sdpRelaxation: The SDP relaxation.
:type sdpRelaxation: :class:`ncpol2sdpa.SdpRelaxation`.
:param x_mat: Optional parameter providing the primal solution of the
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train | SdpRelaxation.get_dual | Given a solution of the dual problem and a constraint of any type,
it returns the corresponding block in the dual solution. If it is an
equality constraint that was converted to a pair of inequalities, it
returns a two-tuple of the matching dual blocks.
:param constraint: The constraint... | ncpol2sdpa/sdp_relaxation.py | def get_dual(self, constraint, ymat=None):
"""Given a solution of the dual problem and a constraint of any type,
it returns the corresponding block in the dual solution. If it is an
equality constraint that was converted to a pair of inequalities, it
returns a two-tuple of the matching d... | def get_dual(self, constraint, ymat=None):
"""Given a solution of the dual problem and a constraint of any type,
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train | SdpRelaxation.write_to_file | Write the relaxation to a file.
:param filename: The name of the file to write to. The type can be
autodetected from the extension: .dat-s for SDPA,
.task for mosek or .csv for human readable format.
:type filename: str.
:param filetype: Optiona... | ncpol2sdpa/sdp_relaxation.py | def write_to_file(self, filename, filetype=None):
"""Write the relaxation to a file.
:param filename: The name of the file to write to. The type can be
autodetected from the extension: .dat-s for SDPA,
.task for mosek or .csv for human readable format.
... | def write_to_file(self, filename, filetype=None):
"""Write the relaxation to a file.
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train | SdpRelaxation.get_relaxation | Get the SDP relaxation of a noncommutative polynomial optimization
problem.
:param level: The level of the relaxation. The value -1 will skip
automatic monomial generation and use only the monomials
supplied by the option `extramonomials`.
:type level... | ncpol2sdpa/sdp_relaxation.py | def get_relaxation(self, level, objective=None, inequalities=None,
equalities=None, substitutions=None,
momentinequalities=None, momentequalities=None,
momentsubstitutions=None,
removeequalities=False, extramonomials=None,
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equalities=None, substitutions=None,
momentinequalities=None, momentequalities=None,
momentsubstitutions=None,
removeequalities=False, extramonomials=None,
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train | flatten | Flatten a list of lists to a list.
:param lol: A list of lists in arbitrary depth.
:type lol: list of list.
:returns: flat list of elements. | ncpol2sdpa/nc_utils.py | def flatten(lol):
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train | simplify_polynomial | Simplify a polynomial for uniform handling later. | ncpol2sdpa/nc_utils.py | def simplify_polynomial(polynomial, monomial_substitutions):
"""Simplify a polynomial for uniform handling later.
"""
if isinstance(polynomial, (int, float, complex)):
return polynomial
polynomial = (1.0 * polynomial).expand(mul=True,
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... | def simplify_polynomial(polynomial, monomial_substitutions):
"""Simplify a polynomial for uniform handling later.
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if isinstance(polynomial, (int, float, complex)):
return polynomial
polynomial = (1.0 * polynomial).expand(mul=True,
multinomial=True)
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train | __separate_scalar_factor | Separate the constant factor from a monomial. | ncpol2sdpa/nc_utils.py | def __separate_scalar_factor(monomial):
"""Separate the constant factor from a monomial.
"""
scalar_factor = 1
if is_number_type(monomial):
return S.One, monomial
if monomial == 0:
return S.One, 0
comm_factors, _ = split_commutative_parts(monomial)
if len(comm_factors) > 0:
... | def __separate_scalar_factor(monomial):
"""Separate the constant factor from a monomial.
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scalar_factor = 1
if is_number_type(monomial):
return S.One, monomial
if monomial == 0:
return S.One, 0
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if len(comm_factors) > 0:
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train | get_support | Gets the support of a polynomial. | ncpol2sdpa/nc_utils.py | def get_support(variables, polynomial):
"""Gets the support of a polynomial.
"""
support = []
if is_number_type(polynomial):
support.append([0] * len(variables))
return support
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... | def get_support(variables, polynomial):
"""Gets the support of a polynomial.
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support = []
if is_number_type(polynomial):
support.append([0] * len(variables))
return support
for monomial in polynomial.expand().as_coefficients_dict():
tmp_support = [0] * len(variables)
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train | get_support_variables | Gets the support of a polynomial. | ncpol2sdpa/nc_utils.py | def get_support_variables(polynomial):
"""Gets the support of a polynomial.
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support = []
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support = []
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train | separate_scalar_factor | Construct a monomial with the coefficient separated
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"""Construct a monomial with the coefficient separated
from an element in a polynomial.
"""
coeff = 1.0
monomial = S.One
if isinstance(element, (int, float, complex)):
coeff *= element
return monomial, coeff
for var in element.as_coeff_mul... | def separate_scalar_factor(element):
"""Construct a monomial with the coefficient separated
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coeff = 1.0
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train | count_ncmonomials | Given a list of monomials, it counts those that have a certain degree,
or less. The function is useful when certain monomials were eliminated
from the basis.
:param variables: The noncommutative variables making up the monomials
:param monomials: List of monomials (the monomial basis).
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"""Given a list of monomials, it counts those that have a certain degree,
or less. The function is useful when certain monomials were eliminated
from the basis.
:param variables: The noncommutative variables making up the monomials
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train | apply_substitutions | Helper function to remove monomials from the basis. | ncpol2sdpa/nc_utils.py | def apply_substitutions(monomial, monomial_substitutions, pure=False):
"""Helper function to remove monomials from the basis."""
if is_number_type(monomial):
return monomial
original_monomial = monomial
changed = True
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else:
... | def apply_substitutions(monomial, monomial_substitutions, pure=False):
"""Helper function to remove monomials from the basis."""
if is_number_type(monomial):
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original_monomial = monomial
changed = True
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substitutions = monomial_substitutions
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train | fast_substitute | Experimental fast substitution routine that considers only restricted
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substitution. Use it with proper testing.
:param monomial: The monomial with parts need to be substituted.
:param old_sub: The part to be replaced.
:param new_su... | ncpol2sdpa/nc_utils.py | def fast_substitute(monomial, old_sub, new_sub):
"""Experimental fast substitution routine that considers only restricted
cases of noncommutative algebras. In rare cases, it fails to find a
substitution. Use it with proper testing.
:param monomial: The monomial with parts need to be substituted.
:p... | def fast_substitute(monomial, old_sub, new_sub):
"""Experimental fast substitution routine that considers only restricted
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:param monomial: The monomial with parts need to be substituted.
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train | generate_variables | Generates a number of commutative or noncommutative variables
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n_vars-1 if n_vars > 1.
:type name: str.
:param n_vars: The number of variables.
... | ncpol2sdpa/nc_utils.py | def generate_variables(name, n_vars=1, hermitian=None, commutative=True):
"""Generates a number of commutative or noncommutative variables
:param name: The prefix in the symbolic representation of the noncommuting
variables. This will be suffixed by a number from 0 to
n_vars-1... | def generate_variables(name, n_vars=1, hermitian=None, commutative=True):
"""Generates a number of commutative or noncommutative variables
:param name: The prefix in the symbolic representation of the noncommuting
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train | generate_operators | Generates a number of commutative or noncommutative operators
:param name: The prefix in the symbolic representation of the noncommuting
variables. This will be suffixed by a number from 0 to
n_vars-1 if n_vars > 1.
:type name: str.
:param n_vars: The number of variables.
... | ncpol2sdpa/nc_utils.py | def generate_operators(name, n_vars=1, hermitian=None, commutative=False):
"""Generates a number of commutative or noncommutative operators
:param name: The prefix in the symbolic representation of the noncommuting
variables. This will be suffixed by a number from 0 to
n_vars-... | def generate_operators(name, n_vars=1, hermitian=None, commutative=False):
"""Generates a number of commutative or noncommutative operators
:param name: The prefix in the symbolic representation of the noncommuting
variables. This will be suffixed by a number from 0 to
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train | get_monomials | Generates all noncommutative monomials up to a degree
:param variables: The noncommutative variables to generate monomials from
:type variables: list of :class:`sympy.physics.quantum.operator.Operator`
or
:class:`sympy.physics.quantum.operator.HermitianOperator`.
:... | ncpol2sdpa/nc_utils.py | def get_monomials(variables, degree):
"""Generates all noncommutative monomials up to a degree
:param variables: The noncommutative variables to generate monomials from
:type variables: list of :class:`sympy.physics.quantum.operator.Operator`
or
:class:`sympy.physi... | def get_monomials(variables, degree):
"""Generates all noncommutative monomials up to a degree
:param variables: The noncommutative variables to generate monomials from
:type variables: list of :class:`sympy.physics.quantum.operator.Operator`
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train | ncdegree | Returns the degree of a noncommutative polynomial.
:param polynomial: Polynomial of noncommutive variables.
:type polynomial: :class:`sympy.core.expr.Expr`.
:returns: int -- the degree of the polynomial. | ncpol2sdpa/nc_utils.py | def ncdegree(polynomial):
"""Returns the degree of a noncommutative polynomial.
:param polynomial: Polynomial of noncommutive variables.
:type polynomial: :class:`sympy.core.expr.Expr`.
:returns: int -- the degree of the polynomial.
"""
degree = 0
if is_number_type(polynomial):
ret... | def ncdegree(polynomial):
"""Returns the degree of a noncommutative polynomial.
:param polynomial: Polynomial of noncommutive variables.
:type polynomial: :class:`sympy.core.expr.Expr`.
:returns: int -- the degree of the polynomial.
"""
degree = 0
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train | iscomplex | Returns whether the polynomial has complex coefficients
:param polynomial: Polynomial of noncommutive variables.
:type polynomial: :class:`sympy.core.expr.Expr`.
:returns: bool -- whether there is a complex coefficient. | ncpol2sdpa/nc_utils.py | def iscomplex(polynomial):
"""Returns whether the polynomial has complex coefficients
:param polynomial: Polynomial of noncommutive variables.
:type polynomial: :class:`sympy.core.expr.Expr`.
:returns: bool -- whether there is a complex coefficient.
"""
if isinstance(polynomial, (int, float)):... | def iscomplex(polynomial):
"""Returns whether the polynomial has complex coefficients
:param polynomial: Polynomial of noncommutive variables.
:type polynomial: :class:`sympy.core.expr.Expr`.
:returns: bool -- whether there is a complex coefficient.
"""
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train | get_all_monomials | Return the monomials of a certain degree. | ncpol2sdpa/nc_utils.py | def get_all_monomials(variables, extramonomials, substitutions, degree,
removesubstitutions=True):
"""Return the monomials of a certain degree.
"""
monomials = get_monomials(variables, degree)
if extramonomials is not None:
monomials.extend(extramonomials)
if removesubs... | def get_all_monomials(variables, extramonomials, substitutions, degree,
removesubstitutions=True):
"""Return the monomials of a certain degree.
"""
monomials = get_monomials(variables, degree)
if extramonomials is not None:
monomials.extend(extramonomials)
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train | pick_monomials_up_to_degree | Collect monomials up to a given degree. | ncpol2sdpa/nc_utils.py | def pick_monomials_up_to_degree(monomials, degree):
"""Collect monomials up to a given degree.
"""
ordered_monomials = []
if degree >= 0:
ordered_monomials.append(S.One)
for deg in range(1, degree + 1):
ordered_monomials.extend(pick_monomials_of_degree(monomials, deg))
return ord... | def pick_monomials_up_to_degree(monomials, degree):
"""Collect monomials up to a given degree.
"""
ordered_monomials = []
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ordered_monomials.append(S.One)
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train | pick_monomials_of_degree | Collect all monomials up of a given degree. | ncpol2sdpa/nc_utils.py | def pick_monomials_of_degree(monomials, degree):
"""Collect all monomials up of a given degree.
"""
selected_monomials = []
for monomial in monomials:
if ncdegree(monomial) == degree:
selected_monomials.append(monomial)
return selected_monomials | def pick_monomials_of_degree(monomials, degree):
"""Collect all monomials up of a given degree.
"""
selected_monomials = []
for monomial in monomials:
if ncdegree(monomial) == degree:
selected_monomials.append(monomial)
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train | save_monomial_index | Save a monomial dictionary for debugging purposes.
:param filename: The name of the file to save to.
:type filename: str.
:param monomial_index: The monomial index of the SDP relaxation.
:type monomial_index: dict of :class:`sympy.core.expr.Expr`. | ncpol2sdpa/nc_utils.py | def save_monomial_index(filename, monomial_index):
"""Save a monomial dictionary for debugging purposes.
:param filename: The name of the file to save to.
:type filename: str.
:param monomial_index: The monomial index of the SDP relaxation.
:type monomial_index: dict of :class:`sympy.core.expr.Expr... | def save_monomial_index(filename, monomial_index):
"""Save a monomial dictionary for debugging purposes.
:param filename: The name of the file to save to.
:type filename: str.
:param monomial_index: The monomial index of the SDP relaxation.
:type monomial_index: dict of :class:`sympy.core.expr.Expr... | [
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train | unique | Helper function to include only unique monomials in a basis. | ncpol2sdpa/nc_utils.py | def unique(seq):
"""Helper function to include only unique monomials in a basis."""
seen = {}
result = []
for item in seq:
marker = item
if marker in seen:
continue
seen[marker] = 1
result.append(item)
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"""Helper function to include only unique monomials in a basis."""
seen = {}
result = []
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marker = item
if marker in seen:
continue
seen[marker] = 1
result.append(item)
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train | build_permutation_matrix | Build a permutation matrix for a permutation. | ncpol2sdpa/nc_utils.py | def build_permutation_matrix(permutation):
"""Build a permutation matrix for a permutation.
"""
matrix = lil_matrix((len(permutation), len(permutation)))
column = 0
for row in permutation:
matrix[row, column] = 1
column += 1
return matrix | def build_permutation_matrix(permutation):
"""Build a permutation matrix for a permutation.
"""
matrix = lil_matrix((len(permutation), len(permutation)))
column = 0
for row in permutation:
matrix[row, column] = 1
column += 1
return matrix | [
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train | convert_relational | Convert all inequalities to >=0 form. | ncpol2sdpa/nc_utils.py | def convert_relational(relational):
"""Convert all inequalities to >=0 form.
"""
rel = relational.rel_op
if rel in ['==', '>=', '>']:
return relational.lhs-relational.rhs
elif rel in ['<=', '<']:
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raise Exception("The relational o... | def convert_relational(relational):
"""Convert all inequalities to >=0 form.
"""
rel = relational.rel_op
if rel in ['==', '>=', '>']:
return relational.lhs-relational.rhs
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train | value | Returns the value of a board
>>> b = Board(); b._rows = [['x', 'x', 'x'], ['x', 'x', 'x'], ['x', 'x', 'x']]
>>> value(b)
1
>>> b = Board(); b._rows = [['o', 'o', 'o'], ['o', 'o', 'o'], ['o', 'o', 'o']]
>>> value(b)
-1
>>> b = Board(); b._rows = [['x', 'o', ' '], ['x', 'o', ' '], [' ', ' ', '... | examples/tictactoeexample.py | def value(board, who='x'):
"""Returns the value of a board
>>> b = Board(); b._rows = [['x', 'x', 'x'], ['x', 'x', 'x'], ['x', 'x', 'x']]
>>> value(b)
1
>>> b = Board(); b._rows = [['o', 'o', 'o'], ['o', 'o', 'o'], ['o', 'o', 'o']]
>>> value(b)
-1
>>> b = Board(); b._rows = [['x', 'o', '... | def value(board, who='x'):
"""Returns the value of a board
>>> b = Board(); b._rows = [['x', 'x', 'x'], ['x', 'x', 'x'], ['x', 'x', 'x']]
>>> value(b)
1
>>> b = Board(); b._rows = [['o', 'o', 'o'], ['o', 'o', 'o'], ['o', 'o', 'o']]
>>> value(b)
-1
>>> b = Board(); b._rows = [['x', 'o', '... | [
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train | ai | Returns best next board
>>> b = Board(); b._rows = [['x', 'o', ' '], ['x', 'o', ' '], [' ', ' ', ' ']]
>>> ai(b)
< Board |xo.xo.x..| > | examples/tictactoeexample.py | def ai(board, who='x'):
"""
Returns best next board
>>> b = Board(); b._rows = [['x', 'o', ' '], ['x', 'o', ' '], [' ', ' ', ' ']]
>>> ai(b)
< Board |xo.xo.x..| >
"""
return sorted(board.possible(), key=lambda b: value(b, who))[-1] | def ai(board, who='x'):
"""
Returns best next board
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>>> ai(b)
< Board |xo.xo.x..| >
"""
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train | Board.winner | Returns either x or o if one of them won, otherwise None | examples/tictactoeexample.py | def winner(self):
"""Returns either x or o if one of them won, otherwise None"""
for c in 'xo':
for comb in [(0,3,6), (1,4,7), (2,5,8), (0,1,2), (3,4,5), (6,7,8), (0,4,8), (2,4,6)]:
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return c
return None | def winner(self):
"""Returns either x or o if one of them won, otherwise None"""
for c in 'xo':
for comb in [(0,3,6), (1,4,7), (2,5,8), (0,1,2), (3,4,5), (6,7,8), (0,4,8), (2,4,6)]:
if all(self.spots[p] == c for p in comb):
return c
return None | [
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train | FaacetsRelaxation.get_relaxation | Get the sparse SDP relaxation of a Bell inequality.
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:param B_configuration: The definition of measurements of Bob.
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"""Get the sparse SDP relaxation of a Bell inequality.
:param A_configuration: The definition of measurements of Alice.
:type A_configuration: list of list of int.
:param B_configuration: The definition of measurements of Bo... | def get_relaxation(self, A_configuration, B_configuration, I):
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:type A_configuration: list of list of int.
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train | share | Returns list of users track has been shared with.
Either track or url need to be provided. | soundcloud_cli/api/share.py | def share(track_id=None, url=None, users=None):
"""
Returns list of users track has been shared with.
Either track or url need to be provided.
"""
client = get_client()
if url:
track_id = client.get('/resolve', url=url).id
if not users:
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"""
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client = get_client()
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train | solve_with_cvxopt | Helper function to convert the SDP problem to PICOS
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:param sdp: The SDP relaxation to be solved.
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"""Helper function to convert the SDP problem to PICOS
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:param sdp: The SDP relaxation to be solved.
:type sdp: :class:`ncpol2sdpa.sdp`.
"""
P = convert_to_picos(sdp)
P.set_option("solver", "cvxo... | def solve_with_cvxopt(sdp, solverparameters=None):
"""Helper function to convert the SDP problem to PICOS
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:param sdp: The SDP relaxation to be solved.
:type sdp: :class:`ncpol2sdpa.sdp`.
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train | convert_to_picos | Convert an SDP relaxation to a PICOS problem such that the exported
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SDP variables or number of constraints. This conversion can be used for
imposing extra constraints on the moment matrix, such as partial transpose.
:param sdp: T... | ncpol2sdpa/picos_utils.py | def convert_to_picos(sdp, duplicate_moment_matrix=False):
"""Convert an SDP relaxation to a PICOS problem such that the exported
.dat-s file is extremely sparse, there is not penalty imposed in terms of
SDP variables or number of constraints. This conversion can be used for
imposing extra constraints on... | def convert_to_picos(sdp, duplicate_moment_matrix=False):
"""Convert an SDP relaxation to a PICOS problem such that the exported
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train | solve_with_cvxpy | Helper function to convert the SDP problem to CVXPY
and call the solver, and parse the output.
:param sdp: The SDP relaxation to be solved.
:type sdp: :class:`ncpol2sdpa.sdp`. | ncpol2sdpa/cvxpy_utils.py | def solve_with_cvxpy(sdp, solverparameters=None):
"""Helper function to convert the SDP problem to CVXPY
and call the solver, and parse the output.
:param sdp: The SDP relaxation to be solved.
:type sdp: :class:`ncpol2sdpa.sdp`.
"""
problem = convert_to_cvxpy(sdp)
if solverparameters is not... | def solve_with_cvxpy(sdp, solverparameters=None):
"""Helper function to convert the SDP problem to CVXPY
and call the solver, and parse the output.
:param sdp: The SDP relaxation to be solved.
:type sdp: :class:`ncpol2sdpa.sdp`.
"""
problem = convert_to_cvxpy(sdp)
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train | convert_to_cvxpy | Convert an SDP relaxation to a CVXPY problem.
:param sdp: The SDP relaxation to convert.
:type sdp: :class:`ncpol2sdpa.sdp`.
:returns: :class:`cvxpy.Problem`. | ncpol2sdpa/cvxpy_utils.py | def convert_to_cvxpy(sdp):
"""Convert an SDP relaxation to a CVXPY problem.
:param sdp: The SDP relaxation to convert.
:type sdp: :class:`ncpol2sdpa.sdp`.
:returns: :class:`cvxpy.Problem`.
"""
from cvxpy import Minimize, Problem, Variable
row_offsets = [0]
cumulative_sum = 0
for bl... | def convert_to_cvxpy(sdp):
"""Convert an SDP relaxation to a CVXPY problem.
:param sdp: The SDP relaxation to convert.
:type sdp: :class:`ncpol2sdpa.sdp`.
:returns: :class:`cvxpy.Problem`.
"""
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train | get_neighbors | Get the forward neighbors of a site in a lattice.
:param index: Linear index of operator.
:type index: int.
:param lattice_length: The size of the 2D lattice in either dimension
:type lattice_length: int.
:param width: Optional parameter to define width.
:type width: int.
:param periodic: O... | ncpol2sdpa/physics_utils.py | def get_neighbors(index, lattice_length, width=0, periodic=False):
"""Get the forward neighbors of a site in a lattice.
:param index: Linear index of operator.
:type index: int.
:param lattice_length: The size of the 2D lattice in either dimension
:type lattice_length: int.
:param width: Option... | def get_neighbors(index, lattice_length, width=0, periodic=False):
"""Get the forward neighbors of a site in a lattice.
:param index: Linear index of operator.
:type index: int.
:param lattice_length: The size of the 2D lattice in either dimension
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train | get_next_neighbors | Get the forward neighbors at a given distance of a site or set of sites
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:param index: Linear index of operator.
:type index: int.
:param lattice_length: The size of the 2D lattice in either dimension
:type lattice_length: int.
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... | ncpol2sdpa/physics_utils.py | def get_next_neighbors(indices, lattice_length, width=0, distance=1,
periodic=False):
"""Get the forward neighbors at a given distance of a site or set of sites
in a lattice.
:param index: Linear index of operator.
:type index: int.
:param lattice_length: The size of the 2D l... | def get_next_neighbors(indices, lattice_length, width=0, distance=1,
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train | bosonic_constraints | Return a set of constraints that define fermionic ladder operators.
:param a: The non-Hermitian variables.
:type a: list of :class:`sympy.physics.quantum.operator.Operator`.
:returns: a dict of substitutions. | ncpol2sdpa/physics_utils.py | def bosonic_constraints(a):
"""Return a set of constraints that define fermionic ladder operators.
:param a: The non-Hermitian variables.
:type a: list of :class:`sympy.physics.quantum.operator.Operator`.
:returns: a dict of substitutions.
"""
substitutions = {}
for i, ai in enumerate(a):
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"""Return a set of constraints that define fermionic ladder operators.
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:returns: a dict of substitutions.
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train | fermionic_constraints | Return a set of constraints that define fermionic ladder operators.
:param a: The non-Hermitian variables.
:type a: list of :class:`sympy.physics.quantum.operator.Operator`.
:returns: a dict of substitutions. | ncpol2sdpa/physics_utils.py | def fermionic_constraints(a):
"""Return a set of constraints that define fermionic ladder operators.
:param a: The non-Hermitian variables.
:type a: list of :class:`sympy.physics.quantum.operator.Operator`.
:returns: a dict of substitutions.
"""
substitutions = {}
for i, ai in enumerate(a)... | def fermionic_constraints(a):
"""Return a set of constraints that define fermionic ladder operators.
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:type a: list of :class:`sympy.physics.quantum.operator.Operator`.
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train | pauli_constraints | Return a set of constraints that define Pauli spin operators.
:param X: List of Pauli X operator on sites.
:type X: list of :class:`sympy.physics.quantum.operator.HermitianOperator`.
:param Y: List of Pauli Y operator on sites.
:type Y: list of :class:`sympy.physics.quantum.operator.HermitianOperator`... | ncpol2sdpa/physics_utils.py | def pauli_constraints(X, Y, Z):
"""Return a set of constraints that define Pauli spin operators.
:param X: List of Pauli X operator on sites.
:type X: list of :class:`sympy.physics.quantum.operator.HermitianOperator`.
:param Y: List of Pauli Y operator on sites.
:type Y: list of :class:`sympy.phys... | def pauli_constraints(X, Y, Z):
"""Return a set of constraints that define Pauli spin operators.
:param X: List of Pauli X operator on sites.
:type X: list of :class:`sympy.physics.quantum.operator.HermitianOperator`.
:param Y: List of Pauli Y operator on sites.
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train | generate_measurements | Generate variables that behave like measurements.
:param party: The list of number of measurement outputs a party has.
:type party: list of int.
:param label: The label to be given to the symbolic variables.
:type label: str.
:returns: list of list of
:class:`sympy.physics.quantum.ope... | ncpol2sdpa/physics_utils.py | def generate_measurements(party, label):
"""Generate variables that behave like measurements.
:param party: The list of number of measurement outputs a party has.
:type party: list of int.
:param label: The label to be given to the symbolic variables.
:type label: str.
:returns: list of list o... | def generate_measurements(party, label):
"""Generate variables that behave like measurements.
:param party: The list of number of measurement outputs a party has.
:type party: list of int.
:param label: The label to be given to the symbolic variables.
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train | projective_measurement_constraints | Return a set of constraints that define projective measurements.
:param parties: Measurements of different parties.
:type A: list or tuple of list of list of
:class:`sympy.physics.quantum.operator.HermitianOperator`.
:returns: substitutions containing idempotency, orthogonality and
... | ncpol2sdpa/physics_utils.py | def projective_measurement_constraints(*parties):
"""Return a set of constraints that define projective measurements.
:param parties: Measurements of different parties.
:type A: list or tuple of list of list of
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:returns: substitut... | def projective_measurement_constraints(*parties):
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:type I: list of list of int.
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:type A: list of list of
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train | maximum_violation | Get the maximum violation of a two-party Bell inequality.
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"""Get the maximum violation of a two-party Bell inequality.
:param A_configuration: Measurement settings of Alice.
:type A_configuration: list of int.
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train | width_aware_slice | >>> width_aware_slice(u'a\uff25iou', 0, 2)[1] == u' '
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train | normalize_slice | Fill in the Nones in a slice. | curtsies/formatstring.py | def normalize_slice(length, index):
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train | parse_args | Returns a kwargs dictionary by turning args into kwargs | curtsies/formatstring.py | def parse_args(args, kwargs):
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Return a FmtStr representing input.
The str() of a FmtStr is guaranteed to produced the same FmtStr.
Other input with escape sequences may not be preserved.
>>> fmtstr("|"+fmtstr("hey", fg='red', bg='blue... | def from_str(cls, s):
# type: (Union[Text, bytes]) -> FmtStr
r"""
Return a FmtStr representing input.
The str() of a FmtStr is guaranteed to produced the same FmtStr.
Other input with escape sequences may not be preserved.
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train | FmtStr.setitem | Shim for easily converting old __setitem__ calls | curtsies/formatstring.py | def setitem(self, startindex, fs):
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train | FmtStr.setslice_with_length | Shim for easily converting old __setitem__ calls | curtsies/formatstring.py | def setslice_with_length(self, startindex, endindex, fs, length):
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train | FmtStr.join | Joins an iterable yielding strings or FmtStrs with self as separator | curtsies/formatstring.py | def join(self, iterable):
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train | FmtStr.width | The number of columns it would take to display this string | curtsies/formatstring.py | def width(self):
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train | FmtStr.width_at_offset | Returns the horizontal position of character n of the string | curtsies/formatstring.py | def width_at_offset(self, n):
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train | FmtStr.shared_atts | Gets atts shared among all nonzero length component Chunk | curtsies/formatstring.py | def shared_atts(self):
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#TODO how to write this without the '???'?
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train | FmtStr.new_with_atts_removed | Returns a new FmtStr with the same content but some attributes removed | curtsies/formatstring.py | def new_with_atts_removed(self, *attributes):
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train | FmtStr.divides | List of indices of divisions between the constituent chunks. | curtsies/formatstring.py | def divides(self):
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train | FmtStr.width_aware_slice | Slice based on the number of columns it would take to display the substring. | curtsies/formatstring.py | def width_aware_slice(self, index):
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train | FmtStr.width_aware_splitlines | Split into lines, pushing doublewidth characters at the end of a line to the next line.
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# type: (int) -> Iterator[FmtStr]
"""Split into lines, pushing doublewidth characters at the end of a line to the next line.
When a double-width character is pushed to the next line, a space is added to pad out the line.
"""
if columns ... | def width_aware_splitlines(self, columns):
# type: (int) -> Iterator[FmtStr]
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train | FmtStr._getitem_normalized | Builds the more compact fmtstrs by using fromstr( of the control sequences) | curtsies/formatstring.py | def _getitem_normalized(self, index):
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train | MoroderHierarchy._calculate_block_structure | Calculates the block_struct array for the output file. | ncpol2sdpa/moroder_hierarchy.py | def _calculate_block_structure(self, inequalities, equalities,
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train | main | Ideally we shouldn't lose the first second of events | examples/initial_input.py | def main():
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time.sleep(1)
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train | SteeringHierarchy._process_monomial | Process a single monomial when building the moment matrix. | ncpol2sdpa/steering_hierarchy.py | def _process_monomial(self, monomial, n_vars):
"""Process a single monomial when building the moment matrix.
"""
coeff, monomial = monomial.as_coeff_Mul()
k = 0
# Have we seen this monomial before?
conjugate = False
try:
# If yes, then we improve spars... | def _process_monomial(self, monomial, n_vars):
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coeff, monomial = monomial.as_coeff_Mul()
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train | SteeringHierarchy.__get_trace_facvar | Return dense vector representation of a polynomial. This function is
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sparse entries to the constraint matrices, it returns a dense
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"""Return dense vector representation of a polynomial. This function is
nearly identical to __push_facvar_sparse, but instead of pushing
sparse entries to the constraint matrices, it returns a dense
vector.
"""
facvar = [0] * (sel... | def __get_trace_facvar(self, polynomial):
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:param objective: Describes the objective function.
:type objective: :class:`sympy.core.expr.Expr`
:param extraobjexpr: Optional parameter of a string expression of a
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"""Set or change the objective function of the polynomial optimization
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:param objective: Describes the objective function.
:type objective: :class:`sympy.core.expr.Expr`
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train | BaseFinder.get_outerframe_skip_importlib_frame | There's a bug in Python3.4+, see http://bugs.python.org/issue23773,
remove this and use sys._getframe(3) when bug is fixed | ezcf/_base.py | def get_outerframe_skip_importlib_frame(level):
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There's a bug in Python3.4+, see http://bugs.python.org/issue23773,
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train | Market.public_api | template function of public api | coincheck/market.py | def public_api(self,url):
''' template function of public api'''
try :
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except Exception as e:
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''' template function of public api'''
try :
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train | parse | r"""
Returns a list of strings or format dictionaries to describe the strings.
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>>> parse(">>> []")
['>>> []']
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Returns a list of strings or format dictionaries to describe the strings.
May raise a ValueError if it can't be parsed.
>>> parse(">>> []")
['>>> []']
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['>>> []']
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train | get_key | Return key pressed from bytes_ or None
Return a key name or None meaning it's an incomplete sequence of bytes
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encoding is how the bytes should be translated to unicode - it should
match the terminal encoding.
keynames is a string describing how key... | curtsies/events.py | def get_key(bytes_, encoding, keynames='curtsies', full=False):
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Return a key name or None meaning it's an incomplete sequence of bytes
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encoding is how the bytes should be translated to unicode - it should
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train | could_be_unfinished_char | Whether seq bytes might create a char in encoding if more bytes were added | curtsies/events.py | def could_be_unfinished_char(seq, encoding):
"""Whether seq bytes might create a char in encoding if more bytes were added"""
if decodable(seq, encoding):
return False # any sensible encoding surely doesn't require lookahead (right?)
# (if seq bytes encoding a character, adding another byte shou... | def could_be_unfinished_char(seq, encoding):
"""Whether seq bytes might create a char in encoding if more bytes were added"""
if decodable(seq, encoding):
return False # any sensible encoding surely doesn't require lookahead (right?)
# (if seq bytes encoding a character, adding another byte shou... | [
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train | pp_event | Returns pretty representation of an Event or keypress | curtsies/events.py | def pp_event(seq):
"""Returns pretty representation of an Event or keypress"""
if isinstance(seq, Event):
return str(seq)
# Get the original sequence back if seq is a pretty name already
rev_curses = dict((v, k) for k, v in CURSES_NAMES.items())
rev_curtsies = dict((v, k) for k, v in CURTS... | def pp_event(seq):
"""Returns pretty representation of an Event or keypress"""
if isinstance(seq, Event):
return str(seq)
# Get the original sequence back if seq is a pretty name already
rev_curses = dict((v, k) for k, v in CURSES_NAMES.items())
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train | create_nouns | Return a string of random nouns up to max number | barnum/gen_data.py | def create_nouns(max=2):
"""
Return a string of random nouns up to max number
"""
nouns = []
for noun in range(0, max):
nouns.append(random.choice(noun_list))
return " ".join(nouns) | def create_nouns(max=2):
"""
Return a string of random nouns up to max number
"""
nouns = []
for noun in range(0, max):
nouns.append(random.choice(noun_list))
return " ".join(nouns) | [
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train | create_date | Create a random valid date
If past, then dates can be in the past
If into the future, then no more than max_years into the future
If it's not, then it can't be any older than max_years_past | barnum/gen_data.py | def create_date(past=False, max_years_future=10, max_years_past=10):
"""
Create a random valid date
If past, then dates can be in the past
If into the future, then no more than max_years into the future
If it's not, then it can't be any older than max_years_past
"""
if past:
start = ... | def create_date(past=False, max_years_future=10, max_years_past=10):
"""
Create a random valid date
If past, then dates can be in the past
If into the future, then no more than max_years into the future
If it's not, then it can't be any older than max_years_past
"""
if past:
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train | create_birthday | Create a random birthday fomr someone between the ages of min_age and max_age | barnum/gen_data.py | def create_birthday(min_age=18, max_age=80):
"""
Create a random birthday fomr someone between the ages of min_age and max_age
"""
age = random.randint(min_age, max_age)
start = datetime.date.today() - datetime.timedelta(days=random.randint(0, 365))
return start - datetime.timedelta(days=age * 3... | def create_birthday(min_age=18, max_age=80):
"""
Create a random birthday fomr someone between the ages of min_age and max_age
"""
age = random.randint(min_age, max_age)
start = datetime.date.today() - datetime.timedelta(days=random.randint(0, 365))
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train | create_pw | Create a random password
From Stackoverflow:
http://stackoverflow.com/questions/7479442/high-quality-simple-random-password-generator
Create a random password with the specified length and no. of
digit, upper and lower case letters.
:param length: Maximum no. of characters in the password
:typ... | barnum/gen_data.py | def create_pw(length=8, digits=2, upper=2, lower=2):
"""Create a random password
From Stackoverflow:
http://stackoverflow.com/questions/7479442/high-quality-simple-random-password-generator
Create a random password with the specified length and no. of
digit, upper and lower case letters.
:para... | def create_pw(length=8, digits=2, upper=2, lower=2):
"""Create a random password
From Stackoverflow:
http://stackoverflow.com/questions/7479442/high-quality-simple-random-password-generator
Create a random password with the specified length and no. of
digit, upper and lower case letters.
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train | show_examples | Run through some simple examples | barnum/gen_data.py | def show_examples():
""" Run through some simple examples
"""
first, last = create_name()
add = create_street()
zip, city, state = create_city_state_zip()
phone = create_phone(zip)
print(first, last)
print(add)
print("{0:s} {1:s} {2:s}".format(city, state, zip))
print(phone)
... | def show_examples():
""" Run through some simple examples
"""
first, last = create_name()
add = create_street()
zip, city, state = create_city_state_zip()
phone = create_phone(zip)
print(first, last)
print(add)
print("{0:s} {1:s} {2:s}".format(city, state, zip))
print(phone)
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train | convert_to_mosek_index | MOSEK requires a specific sparse format to define the lower-triangular
part of a symmetric matrix. This function does the conversion from the
sparse upper triangular matrix format of Ncpol2SDPA. | ncpol2sdpa/mosek_utils.py | def convert_to_mosek_index(block_struct, row_offsets, block_offsets, row):
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part of a symmetric matrix. This function does the conversion from the
sparse upper triangular matrix format of Ncpol2SDPA.
"""
block_index, i, j = con... | def convert_to_mosek_index(block_struct, row_offsets, block_offsets, row):
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train | convert_to_mosek_matrix | Converts the entire sparse representation of the Fi constraint matrices
to sparse MOSEK matrices. | ncpol2sdpa/mosek_utils.py | def convert_to_mosek_matrix(sdp):
"""Converts the entire sparse representation of the Fi constraint matrices
to sparse MOSEK matrices.
"""
barci = []
barcj = []
barcval = []
barai = []
baraj = []
baraval = []
for k in range(sdp.n_vars):
barai.append([])
baraj.appe... | def convert_to_mosek_matrix(sdp):
"""Converts the entire sparse representation of the Fi constraint matrices
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"""
barci = []
barcj = []
barcval = []
barai = []
baraj = []
baraval = []
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barai.append([])
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train | convert_to_mosek | Convert an SDP relaxation to a MOSEK task.
:param sdp: The SDP relaxation to convert.
:type sdp: :class:`ncpol2sdpa.sdp`.
:returns: :class:`mosek.Task`. | ncpol2sdpa/mosek_utils.py | def convert_to_mosek(sdp):
"""Convert an SDP relaxation to a MOSEK task.
:param sdp: The SDP relaxation to convert.
:type sdp: :class:`ncpol2sdpa.sdp`.
:returns: :class:`mosek.Task`.
"""
import mosek
# Cheat when variables are complex and convert with PICOS
if sdp.complex_matrix:
... | def convert_to_mosek(sdp):
"""Convert an SDP relaxation to a MOSEK task.
:param sdp: The SDP relaxation to convert.
:type sdp: :class:`ncpol2sdpa.sdp`.
:returns: :class:`mosek.Task`.
"""
import mosek
# Cheat when variables are complex and convert with PICOS
if sdp.complex_matrix:
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train | ANSIColorParser._add_text | If ``text`` is not empty, append a new Text node to the most recent
pending node, if there is any, or to the new nodes, if there are no
pending nodes. | docs/ansi.py | def _add_text(self, text):
"""
If ``text`` is not empty, append a new Text node to the most recent
pending node, if there is any, or to the new nodes, if there are no
pending nodes.
"""
if text:
if self.pending_nodes:
self.pending_nodes[-1].app... | def _add_text(self, text):
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If ``text`` is not empty, append a new Text node to the most recent
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"""
if text:
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train | version | Return version string. | setup.py | def version():
"""Return version string."""
with open(os.path.join('curtsies', '__init__.py')) as input_file:
for line in input_file:
if line.startswith('__version__'):
return ast.parse(line).body[0].value.s | def version():
"""Return version string."""
with open(os.path.join('curtsies', '__init__.py')) as input_file:
for line in input_file:
if line.startswith('__version__'):
return ast.parse(line).body[0].value.s | [
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train | fsarray | fsarray(list_of_FmtStrs_or_strings, width=None) -> FSArray
Returns a new FSArray of width of the maximum size of the provided
strings, or width provided, and height of the number of strings provided.
If a width is provided, raises a ValueError if any of the strings
are of length greater than this width | curtsies/formatstringarray.py | def fsarray(strings, *args, **kwargs):
"""fsarray(list_of_FmtStrs_or_strings, width=None) -> FSArray
Returns a new FSArray of width of the maximum size of the provided
strings, or width provided, and height of the number of strings provided.
If a width is provided, raises a ValueError if any of the str... | def fsarray(strings, *args, **kwargs):
"""fsarray(list_of_FmtStrs_or_strings, width=None) -> FSArray
Returns a new FSArray of width of the maximum size of the provided
strings, or width provided, and height of the number of strings provided.
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train | FSArray.diff | Returns two FSArrays with differences underlined | curtsies/formatstringarray.py | def diff(cls, a, b, ignore_formatting=False):
"""Returns two FSArrays with differences underlined"""
def underline(x): return u'\x1b[4m%s\x1b[0m' % (x,)
def blink(x): return u'\x1b[5m%s\x1b[0m' % (x,)
a_rows = []
b_rows = []
max_width = max([len(row) for row in a] + [len(... | def diff(cls, a, b, ignore_formatting=False):
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def underline(x): return u'\x1b[4m%s\x1b[0m' % (x,)
def blink(x): return u'\x1b[5m%s\x1b[0m' % (x,)
a_rows = []
b_rows = []
max_width = max([len(row) for row in a] + [len(... | [
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train | Order.create | create new order function
:param rate: float
:param amount: float
:param order_type: str; set 'buy' or 'sell'
:param pair: str; set 'btc_jpy' | coincheck/order.py | def create(self,rate, amount, order_type, pair):
''' create new order function
:param rate: float
:param amount: float
:param order_type: str; set 'buy' or 'sell'
:param pair: str; set 'btc_jpy'
'''
nonce = nounce()
payload = { 'rate': rate,
... | def create(self,rate, amount, order_type, pair):
''' create new order function
:param rate: float
:param amount: float
:param order_type: str; set 'buy' or 'sell'
:param pair: str; set 'btc_jpy'
'''
nonce = nounce()
payload = { 'rate': rate,
... | [
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... | 4e1062f1e564cddceec2f6fb4d70fe3a3ab645bc |
train | Order.cancel | cancel the specified order
:param order_id: order_id to be canceled | coincheck/order.py | def cancel(self,order_id):
''' cancel the specified order
:param order_id: order_id to be canceled
'''
url= 'https://coincheck.com/api/exchange/orders/' + order_id
headers = make_header(url,access_key=self.access_key,secret_key=self.secret_key)
r = requests.delete(url,hea... | def cancel(self,order_id):
''' cancel the specified order
:param order_id: order_id to be canceled
'''
url= 'https://coincheck.com/api/exchange/orders/' + order_id
headers = make_header(url,access_key=self.access_key,secret_key=self.secret_key)
r = requests.delete(url,hea... | [
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] | kmn/coincheck | python | https://github.com/kmn/coincheck/blob/4e1062f1e564cddceec2f6fb4d70fe3a3ab645bc/coincheck/order.py#L59-L66 | [
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... | 4e1062f1e564cddceec2f6fb4d70fe3a3ab645bc |
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