JorgeVB/code_unlearning_dataset · Datasets at Hugging Face

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Given a solution of the dual problem, it returns the SOS decomposition. :param sdp: The SDP relaxation to be solved. :type sdp: :class:`ncpol2sdpa.sdp`. :param y_mat: Optional parameter providing the dual solution of the moment matrix. If not provided, the solution is extracted ...
Given a solution of the dual problem and a monomial, it returns the inner product of the corresponding coefficient matrix and the dual solution. It can be restricted to certain blocks. :param sdp: The SDP relaxation. :type sdp: :class:`ncpol2sdpa.sdp`. :param monomial: The monomial for which the va...
'prefix' is the start of the CC number as a string, any number of digits. 'length' is the length of the CC number to generate. Typically 13 or 16 def completed_number(prefix, length): """ 'prefix' is the start of the CC number as a string, any number of digits. 'length' is the length of the CC number t...
load_module is always called with the same argument as finder's find_module, see "How Import Works" def load_module(self, fullname): """ load_module is always called with the same argument as finder's find_module, see "How Import Works" """ mod = super(JsonLoader, self)....
Returns a message from tick() to be displayed if game is over def process_event(self, c): """Returns a message from tick() to be displayed if game is over""" if c == "": sys.exit() elif c in key_directions: self.move_entity(self.player, *vscale(self.player.speed, key_di...
Returns a message to be displayed if game is over, else None def tick(self): """Returns a message to be displayed if game is over, else None""" for npc in self.npcs: self.move_entity(npc, *npc.towards(self.player)) for entity1, entity2 in itertools.combinations(self.entities, 2): ...
Returns a FSArray of the size of the window containing msg def array_from_text(self, msg): """Returns a FSArray of the size of the window containing msg""" rows, columns = self.t.height, self.t.width return self.array_from_text_rc(msg, rows, columns)
Renders array to terminal and places (0-indexed) cursor Args: array (FSArray): Grid of styled characters to be rendered. * If array received is of width too small, render it anyway * If array received is of width too large, * render the renderable portion * If array...
Returns the terminal (row, column) of the cursor 0-indexed, like blessings cursor positions def get_cursor_position(self): """Returns the terminal (row, column) of the cursor 0-indexed, like blessings cursor positions""" # TODO would this be cleaner as a parameter? in_stream =...
Returns the how far down the cursor moved since last render. Note: If another get_cursor_vertical_diff call is already in progress, immediately returns zero. (This situation is likely if get_cursor_vertical_diff is called from a SIGWINCH signal handler, since sig...
Returns the how far down the cursor moved. def _get_cursor_vertical_diff_once(self): """Returns the how far down the cursor moved.""" old_top_usable_row = self.top_usable_row row, col = self.get_cursor_position() if self._last_cursor_row is None: cursor_dy = 0 else: ...
Renders array to terminal, returns the number of lines scrolled offscreen Returns: Number of times scrolled Args: array (FSArray): Grid of styled characters to be rendered. If array received is of width too small, render it anyway if array received is of...
Call a solver on the SDP relaxation. Upon successful solution, it returns the primal and dual objective values along with the solution matrices. It also sets these values in the `sdpRelaxation` object, along with some status information. :param sdpRelaxation: The SDP relaxation to be so...
Process a single monomial when building the moment matrix. def _process_monomial(self, monomial, n_vars): """Process a single monomial when building the moment matrix. """ processed_monomial, coeff = separate_scalar_factor(monomial) # Are we substituting this moment? try: ...
Generate the moment matrix of monomials. Arguments: n_vars -- current number of variables block_index -- current block index in the SDP matrix monomials -- \|W_d\| set of words of length up to the relaxation level def _generate_moment_matrix(self, n_vars, block_index, processed_entries, ...
Returns the index of a monomial. def _get_index_of_monomial(self, element, enablesubstitution=True, daggered=False): """Returns the index of a monomial. """ result = [] processed_element, coeff1 = separate_scalar_factor(element) if processed_elemen...
Calculate the sparse vector representation of a polynomial and pushes it to the F structure. def __push_facvar_sparse(self, polynomial, block_index, row_offset, i, j): """Calculate the sparse vector representation of a polynomial and pushes it to the F structure. """ width = sel...
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. def _get_facvar(self, polynomial): """Return dense vector representation of a polyn...
Generate localizing matrices Arguments: inequalities -- list of inequality constraints monomials -- localizing monomials block_index -- the current block index in constraint matrices of the SDP relaxation def __process_inequalities(self, block_index): ...
Generate localizing matrices Arguments: equalities -- list of equality constraints equalities -- list of moment equality constraints def __process_equalities(self, equalities, momentequalities): """Generate localizing matrices Arguments: equalities -- list of equality ...
Attempt to remove equalities by solving the linear equations. def __remove_equalities(self, equalities, momentequalities): """Attempt to remove equalities by solving the linear equations. """ A = self.__process_equalities(equalities, momentequalities) if min(A.shape != np.linalg.matrix_...
Calculates the block_struct array for the output file. def _calculate_block_structure(self, inequalities, equalities, momentinequalities, momentequalities, extramomentmatrix, removeequalities, block_struct=None): ...
Process the constraints and generate localizing matrices. Useful only if the moment matrix already exists. Call it if you want to replace your constraints. The number of the respective types of constraints and the maximum degree of each constraint must remain the same. :param in...
Set or change the objective function of the polynomial optimization problem. :param objective: Describes the objective function. :type objective: :class:`sympy.core.expr.Expr` :param extraobjexpr: Optional parameter of a string expression of a linear combina...
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 ...
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...
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...
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...
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. def flatten(lol): """Flatten a list of lists to a list. :param lol: A list of lists in arbitrary depth. :type lol: list of list. :returns: flat li...
Simplify a polynomial for uniform handling later. 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, ...
Separate the constant factor from a monomial. 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_...
Gets the support of a polynomial. def get_support(variables, polynomial): """Gets the support of a polynomial. """ support = [] if is_number_type(polynomial): support.append([0] * len(variables)) return support for monomial in polynomial.expand().as_coefficients_dict(): tmp_...
Gets the support of a polynomial. def get_support_variables(polynomial): """Gets the support of a polynomial. """ support = [] if is_number_type(polynomial): return support for monomial in polynomial.expand().as_coefficients_dict(): mon, _ = __separate_scalar_factor(monomial) ...
Construct a monomial with the coefficient separated from an element in a polynomial. def separate_scalar_factor(element): """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)): ...
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). :param degre...
Helper function to remove monomials from the basis. 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 if not pure: ...
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. :param old_sub: The part to be replaced. :param new_su...
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 if n_vars > 1. :type name: str. :param n_vars: The number of variables. ...
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. ...
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`. :...
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. def ncdegree(polynomial): """Returns the degree of a noncommutative polynomial. :param polyn...
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. def iscomplex(polynomial): """Returns whether the polynomial has complex coeffici...
Return the monomials of a certain degree. 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: monomia...
Collect monomials up to a given degree. 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_...
Collect all monomials up of a given degree. 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...
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): ...
Helper function to include only unique monomials in a basis. 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(it...
Build a permutation matrix for a permutation. 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 m...
Convert all inequalities to >=0 form. 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 ['<=', '<']: return relational.rhs-relational.lhs else: ...
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', ' '], [' ', ' ', '...
Returns best next board >>> b = Board(); b._rows = [['x', 'o', ' '], ['x', 'o', ' '], [' ', ' ', ' ']] >>> ai(b) < Board \|xo.xo.x..\| > def ai(board, who='x'): """ Returns best next board >>> b = Board(); b._rows = [['x', 'o', ' '], ['x', 'o', ' '], [' ', ' ', ' ']] >>> ai(b) < Board \|...
Returns either x or o if one of them won, otherwise 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 c...
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 Bob. :type B_configuration: list of list of int. :param I: T...
Returns list of users track has been shared with. Either track or url need to be provided. 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 = cl...
Helper function to convert the SDP problem to PICOS and call CVXOPT solver, and parse the output. :param sdp: The SDP relaxation to be solved. :type sdp: :class:`ncpol2sdpa.sdp`. def solve_with_cvxopt(sdp, solverparameters=None): """Helper function to convert the SDP problem to PICOS and call CVXO...
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 the moment matrix, such as partial transpose. :param sdp: T...
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`. def solve_with_cvxpy(sdp, solverparameters=None): """Helper function to convert the SDP problem to CVXPY and call the solv...
Convert an SDP relaxation to a CVXPY problem. :param sdp: The SDP relaxation to convert. :type sdp: :class:`ncpol2sdpa.sdp`. :returns: :class:`cvxpy.Problem`. def convert_to_cvxpy(sdp): """Convert an SDP relaxation to a CVXPY problem. :param sdp: The SDP relaxation to convert. :type sdp: :cl...
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...
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 lattice in either dimension :type lattice_length: int. :param width: Optional parameter to define width. ...
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. def bosonic_constraints(a): """Return a set of constraints that define fermionic ladder ope...
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. def fermionic_constraints(a): """Return a set of constraints that define fermionic ladder o...
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`...
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...
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 ...
Define a polynomial using measurements and an I matrix describing a Bell inequality. :param I: The I matrix of a Bell inequality in the Collins-Gisin notation. :type I: list of list of int. :param args: Either the measurements of Alice and Bob or a `Probability` class describing their ...
Correlators between the probabilities of two parties. :param A: Measurements of Alice. :type A: list of list of :class:`sympy.physics.quantum.operator.HermitianOperator`. :param B: Measurements of Bob. :type B: list of list of :class:`sympy.physics.quantum.operator.HermitianOp...
Get the maximum violation of a two-party Bell inequality. :param A_configuration: Measurement settings of Alice. :type A_configuration: list of int. :param B_configuration: Measurement settings of Bob. :type B_configuration: list of int. :param I: The I matrix of a Bell inequality in the Collins-Gi...
A sorted, python2/3 stable formatting of a dictionary. Does not work for dicts with unicode strings as values. def stable_format_dict(d): """A sorted, python2/3 stable formatting of a dictionary. Does not work for dicts with unicode strings as values.""" inner = ', '.join('{}: {}'.format(repr(k)[1:] ...
Returns by how much two intervals overlap assumed that a <= b and x <= y def interval_overlap(a, b, x, y): """Returns by how much two intervals overlap assumed that a <= b and x <= y""" if b <= x or a >= y: return 0 elif x <= a <= y: return min(b, y) - a elif x <= b <= y: ...
>>> width_aware_slice(u'a\uff25iou', 0, 2)[1] == u' ' True def width_aware_slice(s, start, end, replacement_char=u' '): # type: (Text, int, int, Text) """ >>> width_aware_slice(u'a\uff25iou', 0, 2)[1] == u' ' True """ divides = [0] for c in s: divides.append(divides[-1] + wcswid...
Returns a list of lines, split on the last possible space of each line. Split spaces will be removed. Whitespaces will be normalized to one space. Spaces will be the color of the first whitespace character of the normalized whitespace. If a word extends beyond the line, wrap it anyway. >>> linespl...
Fill in the Nones in a slice. def normalize_slice(length, index): "Fill in the Nones in a slice." is_int = False if isinstance(index, int): is_int = True index = slice(index, index+1) if index.start is None: index = slice(0, index.stop, index.step) if index.stop is None: ...
Returns a kwargs dictionary by turning args into kwargs def parse_args(args, kwargs): """Returns a kwargs dictionary by turning args into kwargs""" if 'style' in kwargs: args += (kwargs['style'],) del kwargs['style'] for arg in args: if not isinstance(arg, (bytes, unicode)): ...
Convenience function for creating a FmtStr >>> fmtstr('asdf', 'blue', 'on_red', 'bold') on_red(bold(blue('asdf'))) >>> fmtstr('blarg', fg='blue', bg='red', bold=True) on_red(bold(blue('blarg'))) def fmtstr(string, args, kwargs): # type: (Union[Text, bytes, FmtStr], Any, **Any) -> FmtStr ""...
Return an escape-coded string to write to the terminal. def color_str(self): "Return an escape-coded string to write to the terminal." s = self.s for k, v in sorted(self.atts.items()): # (self.atts sorted for the sake of always acting the same.) if k not in xforms: ...
FmtStr repr is build by concatenating these. def repr_part(self): """FmtStr repr is build by concatenating these.""" def pp_att(att): if att == 'fg': return FG_NUMBER_TO_COLOR[self.atts[att]] elif att == 'bg': return 'on_' + BG_NUMBER_TO_COLOR[self.atts[att]] else: r...
Requests a sub-chunk of max_width or shorter. Returns None if no chunks left. def request(self, max_width): # type: (int) -> Optional[Tuple[int, Chunk]] """Requests a sub-chunk of max_width or shorter. Returns None if no chunks left.""" if max_width < 1: raise ValueError('requires p...
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. >>> fmtstr("\|"+fmtstr("hey", fg='red', bg='blue')+"\|") '\|'+on_blue(red('hey'))+'\|' >>> fmtstr('\|\x1b[31m\x1b...
Copies the current FmtStr's attributes while changing its string. def copy_with_new_str(self, new_str): """Copies the current FmtStr's attributes while changing its string.""" # What to do when there are multiple Chunks with conflicting atts? old_atts = dict((att, value) for bfs in self.chunks ...
Shim for easily converting old __setitem__ calls def setitem(self, startindex, fs): """Shim for easily converting old __setitem__ calls""" return self.setslice_with_length(startindex, startindex+1, fs, len(self))
Shim for easily converting old __setitem__ calls def setslice_with_length(self, startindex, endindex, fs, length): """Shim for easily converting old __setitem__ calls""" if len(self) < startindex: fs = ' '*(startindex - len(self)) + fs if len(self) > endindex: fs = fs + ...
Returns a new FmtStr with the input string spliced into the the original FmtStr at start and end. If end is provided, new_str will replace the substring self.s[start:end-1]. def splice(self, new_str, start, end=None): """Returns a new FmtStr with the input string spliced into the the or...
Returns a new FmtStr with the same content but new formatting def copy_with_new_atts(self, *attributes): """Returns a new FmtStr with the same content but new formatting""" return FmtStr([Chunk(bfs.s, bfs.atts.extend(attributes)) for bfs in self.chunks])
Joins an iterable yielding strings or FmtStrs with self as separator def join(self, iterable): """Joins an iterable yielding strings or FmtStrs with self as separator""" before = [] chunks = [] for i, s in enumerate(iterable): chunks.extend(before) before = self....
Split based on seperator, optionally using a regex Capture groups are ignored in regex, the whole pattern is matched and used to split the original FmtStr. def split(self, sep=None, maxsplit=None, regex=False): """Split based on seperator, optionally using a regex Capture groups are i...
Return a list of lines, split on newline characters, include line boundaries, if keepends is true. def splitlines(self, keepends=False): """Return a list of lines, split on newline characters, include line boundaries, if keepends is true.""" lines = self.split('\n') return [line...
S.ljust(width[, fillchar]) -> string If a fillchar is provided, less formatting information will be preserved def ljust(self, width, fillchar=None): """S.ljust(width[, fillchar]) -> string If a fillchar is provided, less formatting information will be preserved """ if fillchar...
The number of columns it would take to display this string def width(self): """The number of columns it would take to display this string""" if self._width is not None: return self._width self._width = sum(fs.width for fs in self.chunks) return self._width
Returns the horizontal position of character n of the string def width_at_offset(self, n): """Returns the horizontal position of character n of the string""" #TODO make more efficient? width = wcswidth(self.s[:n]) assert width != -1 return width
Gets atts shared among all nonzero length component Chunk def shared_atts(self): """Gets atts shared among all nonzero length component Chunk""" #TODO cache this, could get ugly for large FmtStrs atts = {} first = self.chunks[0] for att in sorted(first.atts): #TODO h...
Returns a new FmtStr with the same content but some attributes removed def new_with_atts_removed(self, attributes): """Returns a new FmtStr with the same content but some attributes removed""" return FmtStr([Chunk(bfs.s, bfs.atts.remove(*attributes)) for bfs in self.chunks])
List of indices of divisions between the constituent chunks. def divides(self): """List of indices of divisions between the constituent chunks.""" acc = [0] for s in self.chunks: acc.append(acc[-1] + len(s)) return acc
Slice based on the number of columns it would take to display the substring. def width_aware_slice(self, index): """Slice based on the number of columns it would take to display the substring.""" if wcswidth(self.s) == -1: raise ValueError('bad values for width aware slicing') index...
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. def width_aware_splitlines(self, columns): # type: (int) -> Iterator[FmtStr] """Split into lines, pushing doub...
Builds the more compact fmtstrs by using fromstr( of the control sequences) def _getitem_normalized(self, index): """Builds the more compact fmtstrs by using fromstr( of the control sequences)""" index = normalize_slice(len(self), index) counter = 0 output = '' for fs in self.ch...
Calculates the block_struct array for the output file. def _calculate_block_structure(self, inequalities, equalities, momentinequalities, momentequalities, extramomentmatrix, removeequalities, block_struct=None): ...
Ideally we shouldn't lose the first second of events def main(): """Ideally we shouldn't lose the first second of events""" time.sleep(1) with Input() as input_generator: for e in input_generator: print(repr(e))
Process a single monomial when building the moment matrix. 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 = Fa...
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. def __get_trace_facvar(self, polynomial): """Return dense vector representation of ...

Given a solution of the dual problem, it returns the SOS decomposition. :param sdp: The SDP relaxation to be solved. :type sdp: :class:`ncpol2sdpa.sdp`. :param y_mat: Optional parameter providing the dual solution of the moment matrix. If not provided, the solution is extracted ...

Given a solution of the dual problem and a monomial, it returns the inner product of the corresponding coefficient matrix and the dual solution. It can be restricted to certain blocks. :param sdp: The SDP relaxation. :type sdp: :class:`ncpol2sdpa.sdp`. :param monomial: The monomial for which the va...

'prefix' is the start of the CC number as a string, any number of digits. 'length' is the length of the CC number to generate. Typically 13 or 16 def completed_number(prefix, length): """ 'prefix' is the start of the CC number as a string, any number of digits. 'length' is the length of the CC number t...

load_module is always called with the same argument as finder's find_module, see "How Import Works" def load_module(self, fullname): """ load_module is always called with the same argument as finder's find_module, see "How Import Works" """ mod = super(JsonLoader, self)....

Returns a message from tick() to be displayed if game is over def process_event(self, c): """Returns a message from tick() to be displayed if game is over""" if c == "": sys.exit() elif c in key_directions: self.move_entity(self.player, *vscale(self.player.speed, key_di...

Returns a message to be displayed if game is over, else None def tick(self): """Returns a message to be displayed if game is over, else None""" for npc in self.npcs: self.move_entity(npc, *npc.towards(self.player)) for entity1, entity2 in itertools.combinations(self.entities, 2): ...

Returns a FSArray of the size of the window containing msg def array_from_text(self, msg): """Returns a FSArray of the size of the window containing msg""" rows, columns = self.t.height, self.t.width return self.array_from_text_rc(msg, rows, columns)

Renders array to terminal and places (0-indexed) cursor Args: array (FSArray): Grid of styled characters to be rendered. * If array received is of width too small, render it anyway * If array received is of width too large, * render the renderable portion * If array...

Returns the terminal (row, column) of the cursor 0-indexed, like blessings cursor positions def get_cursor_position(self): """Returns the terminal (row, column) of the cursor 0-indexed, like blessings cursor positions""" # TODO would this be cleaner as a parameter? in_stream =...

Returns the how far down the cursor moved since last render. Note: If another get_cursor_vertical_diff call is already in progress, immediately returns zero. (This situation is likely if get_cursor_vertical_diff is called from a SIGWINCH signal handler, since sig...

Returns the how far down the cursor moved. def _get_cursor_vertical_diff_once(self): """Returns the how far down the cursor moved.""" old_top_usable_row = self.top_usable_row row, col = self.get_cursor_position() if self._last_cursor_row is None: cursor_dy = 0 else: ...

Renders array to terminal, returns the number of lines scrolled offscreen Returns: Number of times scrolled Args: array (FSArray): Grid of styled characters to be rendered. If array received is of width too small, render it anyway if array received is of...

Call a solver on the SDP relaxation. Upon successful solution, it returns the primal and dual objective values along with the solution matrices. It also sets these values in the `sdpRelaxation` object, along with some status information. :param sdpRelaxation: The SDP relaxation to be so...

Process a single monomial when building the moment matrix. def _process_monomial(self, monomial, n_vars): """Process a single monomial when building the moment matrix. """ processed_monomial, coeff = separate_scalar_factor(monomial) # Are we substituting this moment? try: ...

Generate the moment matrix of monomials. Arguments: n_vars -- current number of variables block_index -- current block index in the SDP matrix monomials -- |W_d| set of words of length up to the relaxation level def _generate_moment_matrix(self, n_vars, block_index, processed_entries, ...

Returns the index of a monomial. def _get_index_of_monomial(self, element, enablesubstitution=True, daggered=False): """Returns the index of a monomial. """ result = [] processed_element, coeff1 = separate_scalar_factor(element) if processed_elemen...

Calculate the sparse vector representation of a polynomial and pushes it to the F structure. def __push_facvar_sparse(self, polynomial, block_index, row_offset, i, j): """Calculate the sparse vector representation of a polynomial and pushes it to the F structure. """ width = sel...

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. def _get_facvar(self, polynomial): """Return dense vector representation of a polyn...

Generate localizing matrices Arguments: inequalities -- list of inequality constraints monomials -- localizing monomials block_index -- the current block index in constraint matrices of the SDP relaxation def __process_inequalities(self, block_index): ...

Generate localizing matrices Arguments: equalities -- list of equality constraints equalities -- list of moment equality constraints def __process_equalities(self, equalities, momentequalities): """Generate localizing matrices Arguments: equalities -- list of equality ...

Attempt to remove equalities by solving the linear equations. def __remove_equalities(self, equalities, momentequalities): """Attempt to remove equalities by solving the linear equations. """ A = self.__process_equalities(equalities, momentequalities) if min(A.shape != np.linalg.matrix_...

Calculates the block_struct array for the output file. def _calculate_block_structure(self, inequalities, equalities, momentinequalities, momentequalities, extramomentmatrix, removeequalities, block_struct=None): ...

Process the constraints and generate localizing matrices. Useful only if the moment matrix already exists. Call it if you want to replace your constraints. The number of the respective types of constraints and the maximum degree of each constraint must remain the same. :param in...

Set or change the objective function of the polynomial optimization problem. :param objective: Describes the objective function. :type objective: :class:`sympy.core.expr.Expr` :param extraobjexpr: Optional parameter of a string expression of a linear combina...

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 ...

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...

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...

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...

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. def flatten(lol): """Flatten a list of lists to a list. :param lol: A list of lists in arbitrary depth. :type lol: list of list. :returns: flat li...

Simplify a polynomial for uniform handling later. 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, ...

Separate the constant factor from a monomial. 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_...

Gets the support of a polynomial. def get_support(variables, polynomial): """Gets the support of a polynomial. """ support = [] if is_number_type(polynomial): support.append([0] * len(variables)) return support for monomial in polynomial.expand().as_coefficients_dict(): tmp_...

Gets the support of a polynomial. def get_support_variables(polynomial): """Gets the support of a polynomial. """ support = [] if is_number_type(polynomial): return support for monomial in polynomial.expand().as_coefficients_dict(): mon, _ = __separate_scalar_factor(monomial) ...

Construct a monomial with the coefficient separated from an element in a polynomial. def separate_scalar_factor(element): """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)): ...

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). :param degre...

Helper function to remove monomials from the basis. 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 if not pure: ...

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. :param old_sub: The part to be replaced. :param new_su...

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 if n_vars > 1. :type name: str. :param n_vars: The number of variables. ...

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. ...

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`. :...

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. def ncdegree(polynomial): """Returns the degree of a noncommutative polynomial. :param polyn...

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. def iscomplex(polynomial): """Returns whether the polynomial has complex coeffici...

Return the monomials of a certain degree. 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: monomia...

Collect monomials up to a given degree. 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_...

Collect all monomials up of a given degree. 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...

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): ...

Helper function to include only unique monomials in a basis. 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(it...

Build a permutation matrix for a permutation. 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 m...

Convert all inequalities to >=0 form. 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 ['<=', '<']: return relational.rhs-relational.lhs else: ...

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', ' '], [' ', ' ', '...

Returns best next board >>> b = Board(); b._rows = [['x', 'o', ' '], ['x', 'o', ' '], [' ', ' ', ' ']] >>> ai(b) < Board |xo.xo.x..| > def ai(board, who='x'): """ Returns best next board >>> b = Board(); b._rows = [['x', 'o', ' '], ['x', 'o', ' '], [' ', ' ', ' ']] >>> ai(b) < Board |...

Returns either x or o if one of them won, otherwise 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 c...

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 Bob. :type B_configuration: list of list of int. :param I: T...

Returns list of users track has been shared with. Either track or url need to be provided. 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 = cl...

Helper function to convert the SDP problem to PICOS and call CVXOPT solver, and parse the output. :param sdp: The SDP relaxation to be solved. :type sdp: :class:`ncpol2sdpa.sdp`. def solve_with_cvxopt(sdp, solverparameters=None): """Helper function to convert the SDP problem to PICOS and call CVXO...

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 the moment matrix, such as partial transpose. :param sdp: T...

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`. def solve_with_cvxpy(sdp, solverparameters=None): """Helper function to convert the SDP problem to CVXPY and call the solv...

Convert an SDP relaxation to a CVXPY problem. :param sdp: The SDP relaxation to convert. :type sdp: :class:`ncpol2sdpa.sdp`. :returns: :class:`cvxpy.Problem`. def convert_to_cvxpy(sdp): """Convert an SDP relaxation to a CVXPY problem. :param sdp: The SDP relaxation to convert. :type sdp: :cl...

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...

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 lattice in either dimension :type lattice_length: int. :param width: Optional parameter to define width. ...

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. def bosonic_constraints(a): """Return a set of constraints that define fermionic ladder ope...

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. def fermionic_constraints(a): """Return a set of constraints that define fermionic ladder o...

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`...

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...

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 ...

Define a polynomial using measurements and an I matrix describing a Bell inequality. :param I: The I matrix of a Bell inequality in the Collins-Gisin notation. :type I: list of list of int. :param args: Either the measurements of Alice and Bob or a `Probability` class describing their ...

Correlators between the probabilities of two parties. :param A: Measurements of Alice. :type A: list of list of :class:`sympy.physics.quantum.operator.HermitianOperator`. :param B: Measurements of Bob. :type B: list of list of :class:`sympy.physics.quantum.operator.HermitianOp...

Get the maximum violation of a two-party Bell inequality. :param A_configuration: Measurement settings of Alice. :type A_configuration: list of int. :param B_configuration: Measurement settings of Bob. :type B_configuration: list of int. :param I: The I matrix of a Bell inequality in the Collins-Gi...

A sorted, python2/3 stable formatting of a dictionary. Does not work for dicts with unicode strings as values. def stable_format_dict(d): """A sorted, python2/3 stable formatting of a dictionary. Does not work for dicts with unicode strings as values.""" inner = ', '.join('{}: {}'.format(repr(k)[1:] ...

Returns by how much two intervals overlap assumed that a <= b and x <= y def interval_overlap(a, b, x, y): """Returns by how much two intervals overlap assumed that a <= b and x <= y""" if b <= x or a >= y: return 0 elif x <= a <= y: return min(b, y) - a elif x <= b <= y: ...

>>> width_aware_slice(u'a\uff25iou', 0, 2)[1] == u' ' True def width_aware_slice(s, start, end, replacement_char=u' '): # type: (Text, int, int, Text) """ >>> width_aware_slice(u'a\uff25iou', 0, 2)[1] == u' ' True """ divides = [0] for c in s: divides.append(divides[-1] + wcswid...

Returns a list of lines, split on the last possible space of each line. Split spaces will be removed. Whitespaces will be normalized to one space. Spaces will be the color of the first whitespace character of the normalized whitespace. If a word extends beyond the line, wrap it anyway. >>> linespl...

Fill in the Nones in a slice. def normalize_slice(length, index): "Fill in the Nones in a slice." is_int = False if isinstance(index, int): is_int = True index = slice(index, index+1) if index.start is None: index = slice(0, index.stop, index.step) if index.stop is None: ...

Returns a kwargs dictionary by turning args into kwargs def parse_args(args, kwargs): """Returns a kwargs dictionary by turning args into kwargs""" if 'style' in kwargs: args += (kwargs['style'],) del kwargs['style'] for arg in args: if not isinstance(arg, (bytes, unicode)): ...

Convenience function for creating a FmtStr >>> fmtstr('asdf', 'blue', 'on_red', 'bold') on_red(bold(blue('asdf'))) >>> fmtstr('blarg', fg='blue', bg='red', bold=True) on_red(bold(blue('blarg'))) def fmtstr(string, *args, **kwargs): # type: (Union[Text, bytes, FmtStr], *Any, **Any) -> FmtStr ""...

Return an escape-coded string to write to the terminal. def color_str(self): "Return an escape-coded string to write to the terminal." s = self.s for k, v in sorted(self.atts.items()): # (self.atts sorted for the sake of always acting the same.) if k not in xforms: ...

FmtStr repr is build by concatenating these. def repr_part(self): """FmtStr repr is build by concatenating these.""" def pp_att(att): if att == 'fg': return FG_NUMBER_TO_COLOR[self.atts[att]] elif att == 'bg': return 'on_' + BG_NUMBER_TO_COLOR[self.atts[att]] else: r...

Requests a sub-chunk of max_width or shorter. Returns None if no chunks left. def request(self, max_width): # type: (int) -> Optional[Tuple[int, Chunk]] """Requests a sub-chunk of max_width or shorter. Returns None if no chunks left.""" if max_width < 1: raise ValueError('requires p...

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. >>> fmtstr("|"+fmtstr("hey", fg='red', bg='blue')+"|") '|'+on_blue(red('hey'))+'|' >>> fmtstr('|\x1b[31m\x1b...

Copies the current FmtStr's attributes while changing its string. def copy_with_new_str(self, new_str): """Copies the current FmtStr's attributes while changing its string.""" # What to do when there are multiple Chunks with conflicting atts? old_atts = dict((att, value) for bfs in self.chunks ...

Shim for easily converting old __setitem__ calls def setitem(self, startindex, fs): """Shim for easily converting old __setitem__ calls""" return self.setslice_with_length(startindex, startindex+1, fs, len(self))

Shim for easily converting old __setitem__ calls def setslice_with_length(self, startindex, endindex, fs, length): """Shim for easily converting old __setitem__ calls""" if len(self) < startindex: fs = ' '*(startindex - len(self)) + fs if len(self) > endindex: fs = fs + ...

Returns a new FmtStr with the input string spliced into the the original FmtStr at start and end. If end is provided, new_str will replace the substring self.s[start:end-1]. def splice(self, new_str, start, end=None): """Returns a new FmtStr with the input string spliced into the the or...

Returns a new FmtStr with the same content but new formatting def copy_with_new_atts(self, **attributes): """Returns a new FmtStr with the same content but new formatting""" return FmtStr(*[Chunk(bfs.s, bfs.atts.extend(attributes)) for bfs in self.chunks])

Joins an iterable yielding strings or FmtStrs with self as separator def join(self, iterable): """Joins an iterable yielding strings or FmtStrs with self as separator""" before = [] chunks = [] for i, s in enumerate(iterable): chunks.extend(before) before = self....

Split based on seperator, optionally using a regex Capture groups are ignored in regex, the whole pattern is matched and used to split the original FmtStr. def split(self, sep=None, maxsplit=None, regex=False): """Split based on seperator, optionally using a regex Capture groups are i...

Return a list of lines, split on newline characters, include line boundaries, if keepends is true. def splitlines(self, keepends=False): """Return a list of lines, split on newline characters, include line boundaries, if keepends is true.""" lines = self.split('\n') return [line...

S.ljust(width[, fillchar]) -> string If a fillchar is provided, less formatting information will be preserved def ljust(self, width, fillchar=None): """S.ljust(width[, fillchar]) -> string If a fillchar is provided, less formatting information will be preserved """ if fillchar...

The number of columns it would take to display this string def width(self): """The number of columns it would take to display this string""" if self._width is not None: return self._width self._width = sum(fs.width for fs in self.chunks) return self._width

Returns the horizontal position of character n of the string def width_at_offset(self, n): """Returns the horizontal position of character n of the string""" #TODO make more efficient? width = wcswidth(self.s[:n]) assert width != -1 return width

Gets atts shared among all nonzero length component Chunk def shared_atts(self): """Gets atts shared among all nonzero length component Chunk""" #TODO cache this, could get ugly for large FmtStrs atts = {} first = self.chunks[0] for att in sorted(first.atts): #TODO h...

Returns a new FmtStr with the same content but some attributes removed def new_with_atts_removed(self, *attributes): """Returns a new FmtStr with the same content but some attributes removed""" return FmtStr(*[Chunk(bfs.s, bfs.atts.remove(*attributes)) for bfs in self.chunks])

List of indices of divisions between the constituent chunks. def divides(self): """List of indices of divisions between the constituent chunks.""" acc = [0] for s in self.chunks: acc.append(acc[-1] + len(s)) return acc

Slice based on the number of columns it would take to display the substring. def width_aware_slice(self, index): """Slice based on the number of columns it would take to display the substring.""" if wcswidth(self.s) == -1: raise ValueError('bad values for width aware slicing') index...

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. def width_aware_splitlines(self, columns): # type: (int) -> Iterator[FmtStr] """Split into lines, pushing doub...

Builds the more compact fmtstrs by using fromstr( of the control sequences) def _getitem_normalized(self, index): """Builds the more compact fmtstrs by using fromstr( of the control sequences)""" index = normalize_slice(len(self), index) counter = 0 output = '' for fs in self.ch...

Calculates the block_struct array for the output file. def _calculate_block_structure(self, inequalities, equalities, momentinequalities, momentequalities, extramomentmatrix, removeequalities, block_struct=None): ...

Ideally we shouldn't lose the first second of events def main(): """Ideally we shouldn't lose the first second of events""" time.sleep(1) with Input() as input_generator: for e in input_generator: print(repr(e))

Process a single monomial when building the moment matrix. 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 = Fa...

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. def __get_trace_facvar(self, polynomial): """Return dense vector representation of ...