Python sympy.Eq方法代碼示例

# 需要導入模塊: import sympy [as 別名]
# 或者: from sympy import Eq [as 別名]
def __new__(cls, *args, **kwargs):
        if len(args) == 1:
            # origin: ClusterizedEq(expr, **kwargs)
            input_expr = args[0]
            expr = sympy.Eq.__new__(cls, *input_expr.args, evaluate=False)
            for i in cls._state:
                v = kwargs[i] if i in kwargs else getattr(input_expr, i, None)
                setattr(expr, '_%s' % i, v)
        elif len(args) == 2:
            # origin: ClusterizedEq(lhs, rhs, **kwargs)
            expr = sympy.Eq.__new__(cls, *args, evaluate=False)
            for i in cls._state:
                setattr(expr, '_%s' % i, kwargs.pop(i))
        else:
            raise ValueError("Cannot construct ClusterizedEq from args=%s "
                             "and kwargs=%s" % (str(args), str(kwargs)))
        return expr 

# 需要導入模塊: import sympy [as 別名]
# 或者: from sympy import Eq [as 別名]
def test_get_most_simple_representation(self):
        cpl = get_most_simple_representation(qc_sympify('1 + 1j'))
        self.assertIsInstance(cpl, str)
        self.assertTrue(bool(sympy.Eq(sympy.sympify(cpl), 1 + 1j)))

        integer = get_most_simple_representation(qc_sympify('3'))
        self.assertIsInstance(integer, int)
        self.assertEqual(integer, 3)

        flt = get_most_simple_representation(qc_sympify('3.1'))
        self.assertIsInstance(flt, float)
        self.assertEqual(flt, 3.1)

        st = get_most_simple_representation(qc_sympify('a + b'))
        self.assertIsInstance(st, str)
        self.assertEqual(st, 'a + b') 

# 需要導入模塊: import sympy [as 別名]
# 或者: from sympy import Eq [as 別名]
def convert_relation(rel):
    if rel.expr():
        return convert_expr(rel.expr())

    lh = convert_relation(rel.relation(0))
    rh = convert_relation(rel.relation(1))
    if rel.LT():
        return sympy.StrictLessThan(lh, rh)
    elif rel.LTE():
        return sympy.LessThan(lh, rh)
    elif rel.GT():
        return sympy.StrictGreaterThan(lh, rh) 
    elif rel.GTE():
        return sympy.GreaterThan(lh, rh)
    elif rel.EQUAL():
        return sympy.Eq(lh, rh) 

# 需要導入模塊: import sympy [as 別名]
# 或者: from sympy import Eq [as 別名]
def __init__(self, left, right):
    super(Eq, self).__init__({'left': left, 'right': right}) 

# 需要導入模塊: import sympy [as 別名]
# 或者: from sympy import Eq [as 別名]
def sympy(self):
    return sympy.Eq(self.children['left'], self.children['right']) 

# 需要導入模塊: import sympy [as 別名]
# 或者: from sympy import Eq [as 別名]
def get_episode_equations():
    """Get the score equations for a :class:`~subliminal.video.Episode`

    The equations are the following:

    1. hash = resolution + video_codec + audio_codec + series + season + episode + release_group
    2. series = resolution + video_codec + audio_codec + season + episode + 1
    3. tvdb_id = series
    4. season = resolution + video_codec + audio_codec + 1
    5. imdb_id = series + season + episode
    6. resolution = video_codec
    7. video_codec = 2 * audio_codec
    8. title = season + episode
    9. season = episode
    10. release_group = season
    11. audio_codec = 1

    :return: the score equations for an episode
    :rtype: list of :class:`sympy.Eq`

    """
    equations = []
    equations.append(Eq(hash, resolution + video_codec + audio_codec + series + season + episode + release_group))
    equations.append(Eq(series, resolution + video_codec + audio_codec + season + episode + release_group))
    equations.append(Eq(tvdb_id, series))
    equations.append(Eq(season, resolution + video_codec + audio_codec + 1))
    equations.append(Eq(imdb_id, series + season + episode))
    equations.append(Eq(resolution, video_codec))
    equations.append(Eq(video_codec, 2 * audio_codec))
    equations.append(Eq(title, season + episode))
    equations.append(Eq(season, episode))
    equations.append(Eq(release_group, season))
    equations.append(Eq(audio_codec, 1))
    return equations 

# 需要導入模塊: import sympy [as 別名]
# 或者: from sympy import Eq [as 別名]
def get_movie_equations():
    """Get the score equations for a :class:`~subliminal.video.Movie`

    The equations are the following:

    1. hash = resolution + video_codec + audio_codec + title + year + release_group
    2. imdb_id = hash
    3. resolution = video_codec
    4. video_codec = 2 * audio_codec
    5. title = resolution + video_codec + audio_codec + year + 1
    6. release_group = resolution + video_codec + audio_codec + 1
    7. year = release_group + 1
    8. audio_codec = 1

    :return: the score equations for a movie
    :rtype: list of :class:`sympy.Eq`

    """
    equations = []
    equations.append(Eq(hash, resolution + video_codec + audio_codec + title + year + release_group))
    equations.append(Eq(imdb_id, hash))
    equations.append(Eq(resolution, video_codec))
    equations.append(Eq(video_codec, 2 * audio_codec))
    equations.append(Eq(title, resolution + video_codec + audio_codec + year + 1))
    equations.append(Eq(video_codec, 2 * audio_codec))
    equations.append(Eq(release_group, resolution + video_codec + audio_codec + 1))
    equations.append(Eq(year, release_group + 1))
    equations.append(Eq(audio_codec, 1))
    return equations 

# 需要導入模塊: import sympy [as 別名]
# 或者: from sympy import Eq [as 別名]
def block4(exprs, iters, dims):
    # Non-perfect loop nest due to conditional
    # for i
    #   if i % 2 == 0
    #   for j
    return iters[0](Conditional(Eq(Mod(dims['i'], 2), 0), iters[1](exprs[0]))) 

# 需要導入模塊: import sympy [as 別名]
# 或者: from sympy import Eq [as 別名]
def test_printAST(block1, block2, block3, block4):
    str1 = printAST(block1)
    assert str1 in """
<Iteration i::i::(0, 3, 1)>
  <Iteration j::j::(0, 5, 1)>
    <Iteration k::k::(0, 7, 1)>
      <Expression a[i] = a[i] + b[i] + 5.0>
"""

    str2 = printAST(block2)
    assert str2 in """
<Iteration i::i::(0, 3, 1)>
  <Expression a[i] = a[i] + b[i] + 5.0>
  <Iteration j::j::(0, 5, 1)>
    <Iteration k::k::(0, 7, 1)>
      <Expression a[i] = -a[i] + b[i]>
"""

    str3 = printAST(block3)
    assert str3 in """
<Iteration i::i::(0, 3, 1)>
  <Iteration s::s::(0, 4, 1)>
    <Expression a[i] = a[i] + b[i] + 5.0>
  <Iteration j::j::(0, 5, 1)>
    <Iteration k::k::(0, 7, 1)>
      <Expression a[i] = -a[i] + b[i]>
      <Expression a[i] = 4*a[i]*b[i]>
  <Iteration q::q::(0, 4, 1)>
    <Expression a[i] = 8.0*a[i] + 6.0/b[i]>
"""

    str4 = printAST(block4)
    assert str4 in """
<Iteration i::i::(0, 3, 1)>
  <If Eq(Mod(i, 2), 0)>
    <Iteration j::j::(0, 5, 1)>
      <Expression a[i] = a[i] + b[i] + 5.0>
""" 

# 需要導入模塊: import sympy [as 別名]
# 或者: from sympy import Eq [as 別名]
def __new__(cls, *args, **kwargs):
        return sympy.Eq.__new__(cls, *args, evaluate=False) 

# 需要導入模塊: import sympy [as 別名]
# 或者: from sympy import Eq [as 別名]
def q_affine(expr, vars):
    """
    Return True if ``expr`` is (separately) affine in the variables ``vars``,
    False otherwise.

    Notes
    -----
    Exploits:

        https://stackoverflow.com/questions/36283548\
        /check-if-an-equation-is-linear-for-a-specific-set-of-variables/
    """
    vars = as_tuple(vars)
    free_symbols = expr.free_symbols

    # At this point, `expr` is (separately) affine in the `vars` variables
    # if all non-mixed second order derivatives are identically zero.
    for x in vars:
        if expr is x:
            continue

        if x not in free_symbols:
            # At this point the only hope is that `expr` is constant
            return q_constant(expr)

        # The vast majority of calls here are incredibly simple tests
        # like q_affine(x+1, [x]).  Catch these quickly and
        # explicitly, instead of calling the very slow function `diff`.
        if expr.is_Add and len(expr.args) == 2:
            if expr.args[1] is x and expr.args[0].is_Number:
                continue
            if expr.args[0] is x and expr.args[1].is_Number:
                continue

        try:
            if diff(expr, x) is nan or not Eq(diff(expr, x, x), 0):
                return False
        except TypeError:
            return False

    return True 

# 需要導入模塊: import sympy [as 別名]
# 或者: from sympy import Eq [as 別名]
def __new__(cls, lhs, rhs=0, subdomain=None, coefficients=None, implicit_dims=None,
                **kwargs):
        kwargs['evaluate'] = False
        obj = sympy.Eq.__new__(cls, lhs, rhs, **kwargs)
        obj._subdomain = subdomain
        obj._substitutions = coefficients
        obj._implicit_dims = as_tuple(implicit_dims)

        return obj 

# 需要導入模塊: import sympy [as 別名]
# 或者: from sympy import Eq [as 別名]
def solve(eq, target, **kwargs):
    """
    Algebraically rearrange an Eq w.r.t. a given symbol.

    This is a wrapper around ``sympy.solve``.

    Parameters
    ----------
    eq : expr-like
        The equation to be rearranged.
    target : symbol
        The symbol w.r.t. which the equation is rearranged. May be a `Function`
        or any other symbolic object.
    **kwargs
        Symbolic optimizations applied while rearranging the equation. For more
        information. refer to ``sympy.solve.__doc__``.
    """
    if isinstance(eq, Eq):
        eq = eq.lhs - eq.rhs if eq.rhs != 0 else eq.lhs
    sols = []
    for e, t in zip(as_tuple(eq), as_tuple(target)):
        # Try first linear solver
        try:
            cc = linear_coeffs(e.evaluate, t)
            sols.append(-cc[1]/cc[0])
        except ValueError:
            warning("Equation is not affine w.r.t the target, falling back to standard"
                    "sympy.solve that may be slow")
            kwargs['rational'] = False  # Avoid float indices
            kwargs['simplify'] = False  # Do not attempt premature optimisation
            sols.append(sympy.solve(e.evaluate, t, **kwargs)[0])
    # We need to rebuild the vector/tensor as sympy.solve outputs a tuple of solutions
    if len(sols) > 1:
        return target.new_from_mat(sols)
    else:
        return sols[0] 

# 需要導入模塊: import sympy [as 別名]
# 或者: from sympy import Eq [as 別名]
def scipy_constraints(self, constraints):
        """
        Returns all constraints in a scipy compatible format.

        :param constraints: List of either MinimizeModel instances (this is what
          is provided by :class:`~symfit.core.fit.Fit`),
          :class:`~symfit.core.models.BaseModel`, or
          :class:`sympy.core.relational.Relational`.
        :return: dict of scipy compatible statements.
        """
        cons = []
        types = {  # scipy only distinguishes two types of constraint.
            sympy.Eq: 'eq', sympy.Ge: 'ineq',
        }

        for constraint in constraints:
            if isinstance(constraint, MinimizeModel):
                # Typically the case when called by `Fit
                constraint_type = constraint.model.constraint_type
            elif hasattr(constraint, 'constraint_type'):
                # Model object, not provided by `Fit`. Do the best we can.
                if self.parameters != constraint.params:
                    raise AssertionError('The constraint should accept the same'
                                         ' parameters as used for the fit.')
                constraint_type = constraint.constraint_type
                constraint = MinimizeModel(constraint, data=self.objective.data)
            elif isinstance(constraint, sympy.Rel):
                constraint_type = constraint.__class__
                constraint = self.objective.model.__class__.as_constraint(
                    constraint, self.objective.model
                )
                constraint = MinimizeModel(constraint, data=self.objective.data)
            else:
                raise TypeError('Unknown type for a constraint.')
            con = {
                'type': types[constraint_type],
                'fun': constraint,
                }
            cons.append(con)
        cons = tuple(cons)
        return cons 

# 需要導入模塊: import sympy [as 別名]
# 或者: from sympy import Eq [as 別名]
def __init__(self, relation: Union[str, sympy.Expr]):
        super().__init__()
        if isinstance(relation, str) and '==' in relation:
            # The '==' operator is interpreted by sympy as exactly, however we need a symbolical evaluation
            self._expression = sympy.Eq(*sympy.sympify(relation.split('==')))
        else:
            self._expression = sympy.sympify(relation)
        if not isinstance(self._expression, sympy.boolalg.Boolean):
            raise ValueError('Constraint is not boolean')
        self._expression = Expression(self._expression)