def test_func_args():
class MyClass(Expr):
# A class with nontrivial .func
def __init__(self, *args):
self.my_member = ""
@property
def func(self):
def my_func(*args):
obj = MyClass(*args)
obj.my_member = self.my_member
return obj
return my_func
x = MyClass()
x.my_member = "A very important value"
assert x.my_member == refine(x).my_member
python类Expr()的实例源码
def output_equation(self, output_equation):
if isinstance(output_equation, sp.Expr):
output_equation = Array([output_equation])
if output_equation is None and self.dim_state == 0:
output_equation = empty_array()
else:
if output_equation is None:
output_equation = self.state
assert output_equation.atoms(sp.Symbol) <= (
set(self.constants_values.keys())
| set([dynamicsymbols._t])
)
if self.dim_state:
assert find_dynamicsymbols(output_equation) <= set(self.state)
else:
assert find_dynamicsymbols(output_equation) <= set(self.input)
self.dim_output = len(output_equation)
self._output_equation = output_equation
self.update_output_equation_function()
def update_bcs(self, sympy_params={}, bc=None):
if not sympy_params is {}:
for i in range(2):
if isinstance(self.bc[i], sympy.Expr):
self.bcs[i] = self.bc[i].evalf(subs=sympy_params)
self.bcs_final[:] = self.bcs
if bc is not None:
assert isinstance(bc, (list, tuple))
assert len(bc) == 2
self.bc = list(bc)
for i in range(2):
if isinstance(bc[i], (Number, sympy.Expr, np.ndarray)) :
self.bcs[i] = bc[i]
else:
raise NotImplementedError
self.bcs_final[:] = self.bcs
def resolve_expression(expression):
if not isinstance(expression, sympy.Expr):
return expression
substitution = []
for sym in expression.free_symbols:
register = getattr(REG, sym.name.upper())
value = getCurrentRegisterValue(register)
substitution.append((sym, value))
return int(expression.subs(substitution))
def sympy_to_numpy(m, **options):
"""Convert a sympy Matrix/complex number to a numpy matrix or scalar."""
if not np:
raise ImportError
dtype = options.get('dtype', 'complex')
if isinstance(m, Matrix):
return np.matrix(m.tolist(), dtype=dtype)
elif isinstance(m, Expr):
if m.is_Number or m.is_NumberSymbol or m == I:
return complex(m)
raise TypeError('Expected Matrix or complex scalar, got: %r' % m)
def sympy_to_scipy_sparse(m, **options):
"""Convert a sympy Matrix/complex number to a numpy matrix or scalar."""
if not np or not sparse:
raise ImportError
dtype = options.get('dtype', 'complex')
if isinstance(m, Matrix):
return sparse.csr_matrix(np.matrix(m.tolist(), dtype=dtype))
elif isinstance(m, Expr):
if m.is_Number or m.is_NumberSymbol or m == I:
return complex(m)
raise TypeError('Expected Matrix or complex scalar, got: %r' % m)
def to_sympy(m, **options):
"""Convert a numpy/scipy.sparse matrix to a sympy matrix."""
if isinstance(m, Matrix):
return m
elif isinstance(m, numpy_ndarray):
return numpy_to_sympy(m)
elif isinstance(m, scipy_sparse_matrix):
return scipy_sparse_to_sympy(m)
elif isinstance(m, Expr):
return m
raise TypeError('Expected sympy/numpy/scipy.sparse matrix, got: %r' % m)
def to_scipy_sparse(m, **options):
"""Convert a sympy/numpy matrix to a scipy.sparse matrix."""
dtype = options.get('dtype', 'complex')
if isinstance(m, (Matrix, Expr)):
return sympy_to_scipy_sparse(m, dtype=dtype)
elif isinstance(m, numpy_ndarray):
if not sparse:
raise ImportError
return sparse.csr_matrix(m)
elif isinstance(m, scipy_sparse_matrix):
return m
raise TypeError('Expected sympy/numpy/scipy.sparse matrix, got: %r' % m)
def _sympy_to_scalar(e):
"""Convert from a sympy scalar to a Python scalar."""
if isinstance(e, Expr):
if e.is_Integer:
return int(e)
elif e.is_Float:
return float(e)
elif e.is_Rational:
return float(e)
elif e.is_Number or e.is_NumberSymbol or e == I:
return complex(e)
raise TypeError('Expected number, got: %r' % e)
def test_styleof():
styles = [(Basic, {'color': 'blue', 'shape': 'ellipse'}),
(Expr, {'color': 'black'})]
assert styleof(Basic(1), styles) == {'color': 'blue', 'shape': 'ellipse'}
assert styleof(x + 1, styles) == {'color': 'black', 'shape': 'ellipse'}
def state(self, state):
if state is None: # or other checks?
state = empty_array()
if isinstance(state, sp.Expr):
state = Array([state])
self.dim_state = len(state)
self._state = state
def input(self, input_):
if input_ is None: # or other checks?
input_ = empty_array()
if isinstance(input_, sp.Expr): # check it's a single dynamicsymbol?
input_ = Array([input_])
self.dim_input = len(input_)
self._inputs = input_
def test_class_handler_registry():
my_handler_registry = ClassFactRegistry()
# The predicate doesn't matter here, so just use is_true
fact1 = Equivalent(Q.is_true, AllArgs(Q.is_true))
fact2 = Equivalent(Q.is_true, AnyArgs(Q.is_true))
my_handler_registry[Mul] = {fact1}
my_handler_registry[Expr] = {fact2}
assert my_handler_registry[Basic] == set()
assert my_handler_registry[Expr] == {fact2}
assert my_handler_registry[Mul] == {fact1, fact2}
def test_CheckOldAssump():
# TODO: Make these tests more complete
class Test1(Expr):
def _eval_is_positive(self):
return True
def _eval_is_negative(self):
return False
class Test2(Expr):
def _eval_is_finite(self):
return True
def _eval_is_positive(self):
return True
def _eval_is_negative(self):
return False
t1 = Test1()
t2 = Test2()
# We can't say if it's positive or negative in the old assumptions without
# bounded. Remember, True means "no new knowledge", and
# Q.positive(t2) means "t2 is positive."
assert CheckOldAssump(Q.positive(t1)) == True
assert CheckOldAssump(Q.negative(t1)) == ~Q.negative(t1)
assert CheckOldAssump(Q.positive(t2)) == Q.positive(t2)
assert CheckOldAssump(Q.negative(t2)) == ~Q.negative(t2)
def sympy_to_numpy(m, **options):
"""Convert a sympy Matrix/complex number to a numpy matrix or scalar."""
if not np:
raise ImportError
dtype = options.get('dtype', 'complex')
if isinstance(m, Matrix):
return np.matrix(m.tolist(), dtype=dtype)
elif isinstance(m, Expr):
if m.is_Number or m.is_NumberSymbol or m == I:
return complex(m)
raise TypeError('Expected Matrix or complex scalar, got: %r' % m)
def sympy_to_scipy_sparse(m, **options):
"""Convert a sympy Matrix/complex number to a numpy matrix or scalar."""
if not np or not sparse:
raise ImportError
dtype = options.get('dtype', 'complex')
if isinstance(m, Matrix):
return sparse.csr_matrix(np.matrix(m.tolist(), dtype=dtype))
elif isinstance(m, Expr):
if m.is_Number or m.is_NumberSymbol or m == I:
return complex(m)
raise TypeError('Expected Matrix or complex scalar, got: %r' % m)
def to_numpy(m, **options):
"""Convert a sympy/scipy.sparse matrix to a numpy matrix."""
dtype = options.get('dtype', 'complex')
if isinstance(m, (Matrix, Expr)):
return sympy_to_numpy(m, dtype=dtype)
elif isinstance(m, numpy_ndarray):
return m
elif isinstance(m, scipy_sparse_matrix):
return m.todense()
raise TypeError('Expected sympy/numpy/scipy.sparse matrix, got: %r' % m)
def to_scipy_sparse(m, **options):
"""Convert a sympy/numpy matrix to a scipy.sparse matrix."""
dtype = options.get('dtype', 'complex')
if isinstance(m, (Matrix, Expr)):
return sympy_to_scipy_sparse(m, dtype=dtype)
elif isinstance(m, numpy_ndarray):
if not sparse:
raise ImportError
return sparse.csr_matrix(m)
elif isinstance(m, scipy_sparse_matrix):
return m
raise TypeError('Expected sympy/numpy/scipy.sparse matrix, got: %r' % m)
def _sympy_to_scalar(e):
"""Convert from a sympy scalar to a Python scalar."""
if isinstance(e, Expr):
if e.is_Integer:
return int(e)
elif e.is_Float:
return float(e)
elif e.is_Rational:
return float(e)
elif e.is_Number or e.is_NumberSymbol or e == I:
return complex(e)
raise TypeError('Expected number, got: %r' % e)
def test_styleof():
styles = [(Basic, {'color': 'blue', 'shape': 'ellipse'}),
(Expr, {'color': 'black'})]
assert styleof(Basic(1), styles) == {'color': 'blue', 'shape': 'ellipse'}
assert styleof(x + 1, styles) == {'color': 'black', 'shape': 'ellipse'}
def serialize_value(value):
if isinstance(value, list):
return '[{}]'.format(', '.join(map(serialize_value, value)))
elif isinstance(value, expression):
return value
elif isinstance(value, Expr):
return str(float(value))
else:
return json.dumps(value)
def __init__(
self,
root,
outputs,
inputs=None,
name="unnamed_tree",
):
self.root = copy.deepcopy(root)
if not self.root.prototype.get("root"):
raise vadouvan.exceptions.WDFError(
"Attempted to use non-root node type '{}' as root of a "
"WDFTree."
.format(self.root.prototype["name"]))
self.name = name
if isinstance(outputs, numbers.Number):
outputs = sympy.sympify(outputs)
if isinstance(outputs, sympy.Expr):
outputs = [("out", outputs)]
self.outputs = collections.OrderedDict(outputs)
actual_inputs_set = self._normalize_parameters_and_get_inputs()
if inputs is None:
self.inputs = sorted(list(actual_inputs_set))
else:
if set(inputs) != actual_inputs_set:
raise vadouvan.exceptions.WDFError(
"Discrepancy between provided inputs list and tree"
" inputs.")
self.inputs = inputs
self._assign_names_to_unnamed_nodes()
def rewriterule(source, target, variables=(), condition=None, assume=None):
""" Rewrite rule
Transform expressions that match source into expressions that match target
treating all `variables` as wilds.
>>> from sympy.abc import w, x, y, z
>>> from sympy.unify.rewrite import rewriterule
>>> from sympy.utilities import default_sort_key
>>> rl = rewriterule(x + y, x**y, [x, y])
>>> sorted(rl(z + 3), key=default_sort_key)
[3**z, z**3]
Use ``condition`` to specify additional requirements. Inputs are taken in
the same order as is found in variables.
>>> rl = rewriterule(x + y, x**y, [x, y], lambda x, y: x.is_integer)
>>> list(rl(z + 3))
[3**z]
Use ``assume`` to specify additional requirements using new assumptions.
>>> from sympy.assumptions import Q
>>> rl = rewriterule(x + y, x**y, [x, y], assume=Q.integer(x))
>>> list(rl(z + 3))
[3**z]
Assumptions for the local context are provided at rule runtime
>>> list(rl(w + z, Q.integer(z)))
[z**w]
"""
def rewrite_rl(expr, assumptions=True):
for match in unify(source, expr, {}, variables=variables):
if (condition and
not condition(*[match.get(var, var) for var in variables])):
continue
if (assume and not ask(assume.xreplace(match), assumptions)):
continue
expr2 = subs(match)(target)
if isinstance(expr2, Expr):
expr2 = rebuild(expr2)
yield expr2
return rewrite_rl
def rewriterule(source, target, variables=(), condition=None, assume=None):
""" Rewrite rule
Transform expressions that match source into expressions that match target
treating all `variables` as wilds.
>>> from sympy.abc import w, x, y, z
>>> from sympy.unify.rewrite import rewriterule
>>> from sympy.utilities import default_sort_key
>>> rl = rewriterule(x + y, x**y, [x, y])
>>> sorted(rl(z + 3), key=default_sort_key)
[3**z, z**3]
Use ``condition`` to specify additional requirements. Inputs are taken in
the same order as is found in variables.
>>> rl = rewriterule(x + y, x**y, [x, y], lambda x, y: x.is_integer)
>>> list(rl(z + 3))
[3**z]
Use ``assume`` to specify additional requirements using new assumptions.
>>> from sympy.assumptions import Q
>>> rl = rewriterule(x + y, x**y, [x, y], assume=Q.integer(x))
>>> list(rl(z + 3))
[3**z]
Assumptions for the local context are provided at rule runtime
>>> list(rl(w + z, Q.integer(z)))
[z**w]
"""
def rewrite_rl(expr, assumptions=True):
for match in unify(source, expr, {}, variables=variables):
if (condition and
not condition(*[match.get(var, var) for var in variables])):
continue
if (assume and not ask(assume.xreplace(match), assumptions)):
continue
expr2 = subs(match)(target)
if isinstance(expr2, Expr):
expr2 = rebuild(expr2)
yield expr2
return rewrite_rl
