def test_implemented_function_evalf():
f = Function('f')
f = implemented_function(f, lambda x: x + 1)
assert str(f(x)) == "f(x)"
assert str(f(2)) == "f(2)"
assert f(2).evalf(strict=False) == 3
assert f(x).evalf(strict=False) == f(x)
f = implemented_function(Function('sin'), lambda x: x + 1)
assert f(2).evalf() != sin(2)
del f._imp_ # XXX: due to caching _imp_ would influence all other tests
def test_implemented_function_evalf():
f = Function('f')
f = implemented_function(f, lambda x: x + 1)
assert str(f(x)) == "f(x)"
assert str(f(2)) == "f(2)"
assert f(2).evalf(strict=False) == 3
assert f(x).evalf(strict=False) == f(x)
f = implemented_function(Function('sin'), lambda x: x + 1)
assert f(2).evalf() != sin(2)
del f._imp_ # XXX: due to caching _imp_ would influence all other tests
def test_ccode_inline_function():
g = implemented_function('g', Lambda(x, 2 * x))
assert ccode(g(x)) == '2*x'
g = implemented_function('g', Lambda(x, 2 * x / Catalan))
assert ccode(
g(x)) == 'double const Catalan = %s;\n2*x/Catalan' % Catalan.evalf()
A = IndexedBase('A')
i = Idx('i', symbols('n', integer=True))
g = implemented_function('g', Lambda(x, x * (1 + x) * (2 + x)))
assert ccode(g(A[i]),
assign_to=A[i]) == ('for (int i=0; i<n; i++){\n'
' A[i] = (A[i] + 1)*(A[i] + 2)*A[i];\n'
'}')
def test_jscode_inline_function():
x = symbols('x')
g = implemented_function('g', Lambda(x, 2*x))
assert jscode(g(x)) == "2*x"
g = implemented_function('g', Lambda(x, 2*x/Catalan))
assert jscode(g(x)) == "var Catalan = %s;\n2*x/Catalan" % Catalan.n()
A = IndexedBase('A')
i = Idx('i', symbols('n', integer=True))
g = implemented_function('g', Lambda(x, x*(1 + x)*(2 + x)))
assert jscode(g(A[i]), assign_to=A[i]) == (
"for (var i=0; i<n; i++){\n"
" A[i] = (A[i] + 1)*(A[i] + 2)*A[i];\n"
"}"
)
def test_inline_function():
g = implemented_function('g', Lambda(x, 2 * x))
assert fcode(g(x)) == ' 2*x'
g = implemented_function('g', Lambda(x, 2 * pi / x))
assert fcode(g(x)) == (' parameter (pi = 3.14159265358979d0)\n'
' 2*pi/x')
A = IndexedBase('A')
i = Idx('i', symbols('n', integer=True))
g = implemented_function('g', Lambda(x, x * (1 + x) * (2 + x)))
assert fcode(
g(A[i]),
assign_to=A[i]) == (' do i = 1, n\n'
' A(i) = (A(i) + 1)*(A(i) + 2)*A(i)\n'
' end do')
def test_ccode_inline_function():
x = symbols('x')
g = implemented_function('g', Lambda(x, 2*x))
assert ccode(g(x)) == "2*x"
g = implemented_function('g', Lambda(x, 2*x/Catalan))
assert ccode(
g(x)) == "double const Catalan = %s;\n2*x/Catalan" % Catalan.evalf()
A = IndexedBase('A')
i = Idx('i', symbols('n', integer=True))
g = implemented_function('g', Lambda(x, x*(1 + x)*(2 + x)))
assert ccode(g(A[i]), assign_to=A[i]) == (
"for (int i=0; i<n; i++){\n"
" A[i] = (A[i] + 1)*(A[i] + 2)*A[i];\n"
"}"
)
def test_jscode_Pow():
g = implemented_function('g', Lambda(x, 2*x))
assert jscode(x**3) == "Math.pow(x, 3)"
assert jscode(x**(y**3)) == "Math.pow(x, Math.pow(y, 3))"
assert jscode(1/(g(x)*3.5)**(x - y**x)/(x**2 + y)) == \
"Math.pow(3.5*2*x, -x + Math.pow(y, x))/(Math.pow(x, 2) + y)"
assert jscode(x**-1.0) == '1/x'
def test_inline_function():
g = implemented_function('g', Lambda(x, 2*x))
assert fcode(g(x)) == " 2*x"
g = implemented_function('g', Lambda(x, 2*pi/x))
assert fcode(g(x)) == (
" parameter (pi = 3.14159265358979d0)\n"
" 2*pi/x"
)
A = IndexedBase('A')
i = Idx('i', symbols('n', integer=True))
g = implemented_function('g', Lambda(x, x*(1 + x)*(2 + x)))
assert fcode(g(A[i]), assign_to=A[i]) == (
" do i = 1, n\n"
" A(i) = (A(i) + 1)*(A(i) + 2)*A(i)\n"
" end do"
)
def test_lambdify_imps():
# Test lambdify with implemented functions
# first test basic (diofant) lambdify
f = diofant.cos
assert lambdify(x, f(x))(0) == 1
assert lambdify(x, 1 + f(x))(0) == 2
assert lambdify((x, y), y + f(x))(0, 1) == 2
# make an implemented function and test
f = implemented_function("f", lambda x: x + 100)
assert lambdify(x, f(x))(0) == 100
assert lambdify(x, 1 + f(x))(0) == 101
assert lambdify((x, y), y + f(x))(0, 1) == 101
# Can also handle tuples, lists, dicts as expressions
lam = lambdify(x, (f(x), x))
assert lam(3) == (103, 3)
lam = lambdify(x, [f(x), x])
assert lam(3) == [103, 3]
lam = lambdify(x, [f(x), (f(x), x)])
assert lam(3) == [103, (103, 3)]
lam = lambdify(x, {f(x): x})
assert lam(3) == {103: 3}
lam = lambdify(x, {f(x): x})
assert lam(3) == {103: 3}
lam = lambdify(x, {x: f(x)})
assert lam(3) == {3: 103}
# Check that imp preferred to other namespaces by default
d = {'f': lambda x: x + 99}
lam = lambdify(x, f(x), d)
assert lam(3) == 103
# Unless flag passed
lam = lambdify(x, f(x), d, use_imps=False)
assert lam(3) == 102
def test_lambdify_imps():
# Test lambdify with implemented functions
# first test basic (diofant) lambdify
f = diofant.cos
assert lambdify(x, f(x))(0) == 1
assert lambdify(x, 1 + f(x))(0) == 2
assert lambdify((x, y), y + f(x))(0, 1) == 2
# make an implemented function and test
f = implemented_function("f", lambda x: x + 100)
assert lambdify(x, f(x))(0) == 100
assert lambdify(x, 1 + f(x))(0) == 101
assert lambdify((x, y), y + f(x))(0, 1) == 101
# Can also handle tuples, lists, dicts as expressions
lam = lambdify(x, (f(x), x))
assert lam(3) == (103, 3)
lam = lambdify(x, [f(x), x])
assert lam(3) == [103, 3]
lam = lambdify(x, [f(x), (f(x), x)])
assert lam(3) == [103, (103, 3)]
lam = lambdify(x, {f(x): x})
assert lam(3) == {103: 3}
lam = lambdify(x, {f(x): x})
assert lam(3) == {103: 3}
lam = lambdify(x, {x: f(x)})
assert lam(3) == {3: 103}
# Check that imp preferred to other namespaces by default
d = {'f': lambda x: x + 99}
lam = lambdify(x, f(x), d)
assert lam(3) == 103
# Unless flag passed
lam = lambdify(x, f(x), d, use_imps=False)
assert lam(3) == 102
def test_Pow():
assert octave_code(x**3) == 'x.^3'
assert octave_code(x**(y**3)) == 'x.^(y.^3)'
assert octave_code(x**Rational(2, 3)) == 'x.^(2/3)'
g = implemented_function('g', Lambda(x, 2 * x))
assert octave_code(1/(g(x)*3.5)**(x - y**x)/(x**2 + y)) == \
'(3.5*2*x).^(-x + y.^x)./(x.^2 + y)'
def test_Pow():
assert mcode(x**3) == "x.^3"
assert mcode(x**(y**3)) == "x.^(y.^3)"
assert mcode(x**Rational(2, 3)) == 'x.^(2/3)'
g = implemented_function('g', Lambda(x, 2*x))
assert mcode(1/(g(x)*3.5)**(x - y**x)/(x**2 + y)) == \
"(3.5*2*x).^(-x + y.^x)./(x.^2 + y)"
def test_imps():
# Here we check if the default returned functions are anonymous - in
# the sense that we can have more than one function with the same name
f = implemented_function('f', lambda x: 2*x)
g = implemented_function('f', lambda x: math.sqrt(x))
l1 = lambdify(x, f(x))
l2 = lambdify(x, g(x))
assert str(f(x)) == str(g(x))
assert l1(3) == 6
assert l2(3) == math.sqrt(3)
# check that we can pass in a Function as input
func = diofant.Function('myfunc')
assert not hasattr(func, '_imp_')
my_f = implemented_function(func, lambda x: 2*x)
assert hasattr(func, '_imp_') and hasattr(my_f, '_imp_')
# Error for functions with same name and different implementation
f2 = implemented_function("f", lambda x: x + 101)
pytest.raises(ValueError, lambda: lambdify(x, f(f2(x))))
def test_implemented_function_evalf():
from diofant.utilities.lambdify import implemented_function
f = Function('f')
f = implemented_function(f, lambda x: x + 1)
assert str(f(x)) == "f(x)"
assert str(f(2)) == "f(2)"
assert f(2).evalf() == 3
assert f(x).evalf() == f(x)
del f._imp_ # XXX: due to caching _imp_ would influence all other tests
def test_numexpr_userfunctions():
a, b = numpy.random.randn(2, 10)
uf = type('uf', (Function, ), {'eval': classmethod(lambda x, y: y**2 + 1)})
func = lambdify(x, 1 - uf(x), modules='numexpr')
assert numpy.allclose(func(a), -(a**2))
uf = implemented_function(Function('uf'), lambda x, y: 2 * x * y + 1)
func = lambdify((x, y), uf(x, y), modules='numexpr')
assert numpy.allclose(func(a, b), 2 * a * b + 1)
def test_imps():
# Here we check if the default returned functions are anonymous - in
# the sense that we can have more than one function with the same name
f = implemented_function('f', lambda x: 2*x)
g = implemented_function('f', lambda x: math.sqrt(x))
l1 = lambdify(x, f(x))
l2 = lambdify(x, g(x))
assert str(f(x)) == str(g(x))
assert l1(3) == 6
assert l2(3) == math.sqrt(3)
# check that we can pass in a Function as input
func = diofant.Function('myfunc')
assert not hasattr(func, '_imp_')
my_f = implemented_function(func, lambda x: 2*x)
assert hasattr(func, '_imp_')
# Error for functions with same name and different implementation
f2 = implemented_function("f", lambda x: x + 101)
pytest.raises(ValueError, lambda: lambdify(x, f(f2(x))))
def test_numexpr_userfunctions():
a, b = numpy.random.randn(2, 10)
uf = type('uf', (Function, ),
{'eval': classmethod(lambda x, y: y**2+1)})
func = lambdify(x, 1-uf(x), modules='numexpr')
assert numpy.allclose(func(a), -(a**2))
uf = implemented_function(Function('uf'), lambda x, y: 2*x*y+1)
func = lambdify((x, y), uf(x, y), modules='numexpr')
assert numpy.allclose(func(a, b), 2*a*b+1)
def test_ccode_Pow():
assert ccode(x**3) == "pow(x, 3)"
assert ccode(x**(y**3)) == "pow(x, pow(y, 3))"
g = implemented_function('g', Lambda(x, 2 * x))
assert ccode(1/(g(x)*3.5)**(x - y**x)/(x**2 + y)) == \
"pow(3.5*2*x, -x + pow(y, x))/(pow(x, 2) + y)"
assert ccode(x**-1.0) == '1.0/x'
assert ccode(x**Rational(2, 3)) == 'pow(x, 2.0L/3.0L)'
_cond_cfunc = [(lambda base, exp: exp.is_integer, "dpowi"),
(lambda base, exp: not exp.is_integer, "pow")]
assert ccode(x**3, user_functions={'Pow': _cond_cfunc}) == 'dpowi(x, 3)'
assert ccode(x**3.2, user_functions={'Pow': _cond_cfunc}) == 'pow(x, 3.2)'
def test_imps_errors():
# Test errors that implemented functions can return, and still be
# able to form expressions. See issue sympy/sympy#10810.
for val, error_class in product((0, 0., 2, 2.0),
(AttributeError, TypeError, ValueError)):
def myfunc(a):
if a == 0:
raise error_class
return 1
f = implemented_function('f', myfunc)
expr = f(val)
assert expr == f(val)
def test_imps_errors():
# Test errors that implemented functions can return, and still be
# able to form expressions. See issue sympy/sympy#10810.
for val, error_class in product((0, 0., 2, 2.0),
(AttributeError, TypeError, ValueError)):
def myfunc(a):
if a == 0:
raise error_class
return 1
f = implemented_function('f', myfunc)
expr = f(val)
assert expr == f(val)
def test_numexprprinter():
p = NumExprPrinter()
M = MatrixSymbol('M', 1, 2)
pytest.raises(TypeError, lambda: p.doprint(M))
pytest.raises(TypeError, lambda: p.doprint([x, y]))
assert p.doprint(I) == "evaluate('1j')"
assert p.doprint(sin(x)) == "evaluate('sin(x)')"
assert p.doprint(asinh(x)) == "evaluate('arcsinh(x)')"
f = implemented_function('f', lambda x: 2 * x)
assert p.doprint(f(x)) == "evaluate('(2*x)')"
g = Function('g')
pytest.raises(TypeError, lambda: p.doprint(g(x)))
def test_numexprprinter():
p = NumExprPrinter()
M = MatrixSymbol('M', 1, 2)
pytest.raises(TypeError, lambda: p.doprint(M))
pytest.raises(TypeError, lambda: p.doprint([x, y]))
assert p.doprint(I) == "evaluate('1j')"
assert p.doprint(sin(x)) == "evaluate('sin(x)')"
assert p.doprint(asinh(x)) == "evaluate('arcsinh(x)')"
f = implemented_function('f', lambda x: 2*x)
assert p.doprint(f(x)) == "evaluate('(2*x)')"
g = Function('g')
pytest.raises(TypeError, lambda: p.doprint(g(x)))
def test_ccode_Pow():
assert ccode(x**3) == 'pow(x, 3)'
assert ccode(x**(y**3)) == 'pow(x, pow(y, 3))'
g = implemented_function('g', Lambda(x, 2*x))
assert ccode(1/(g(x)*3.5)**(x - y**x)/(x**2 + y)) == \
'pow(3.5*2*x, -x + pow(y, x))/(pow(x, 2) + y)'
assert ccode(x**-1.0) == '1.0/x'
assert ccode(x**Rational(2, 3)) == 'pow(x, 2.0L/3.0L)'
_cond_cfunc = [(lambda base, exp: exp.is_integer, 'dpowi'),
(lambda base, exp: not exp.is_integer, 'pow')]
assert ccode(x**3, user_functions={'Pow': _cond_cfunc}) == 'dpowi(x, 3)'
assert ccode(x**3.2, user_functions={'Pow': _cond_cfunc}) == 'pow(x, 3.2)'
_cond_cfunc2 = [(lambda base, exp: base == 2, lambda base, exp: f'exp2({exp})'),
(lambda base, exp: base != 2, 'pow')]
# Related to sympy/sympy#11353
assert ccode(2**x, user_functions={'Pow': _cond_cfunc2}) == 'exp2(x)'
assert ccode(x**2, user_functions={'Pow': _cond_cfunc2}) == 'pow(x, 2)'
def test_ccode_Pow():
assert ccode(x**3) == "pow(x, 3)"
assert ccode(x**(y**3)) == "pow(x, pow(y, 3))"
g = implemented_function('g', Lambda(x, 2*x))
assert ccode(1/(g(x)*3.5)**(x - y**x)/(x**2 + y)) == \
"pow(3.5*2*x, -x + pow(y, x))/(pow(x, 2) + y)"
assert ccode(x**-1.0) == '1.0/x'
assert ccode(x**Rational(2, 3)) == 'pow(x, 2.0L/3.0L)'
_cond_cfunc = [(lambda base, exp: exp.is_integer, "dpowi"),
(lambda base, exp: not exp.is_integer, "pow")]
assert ccode(x**3, user_functions={'Pow': _cond_cfunc}) == 'dpowi(x, 3)'
assert ccode(x**3.2, user_functions={'Pow': _cond_cfunc}) == 'pow(x, 3.2)'
_cond_cfunc2 = [(lambda base, exp: base == 2, lambda base, exp: 'exp2(%s)' % exp),
(lambda base, exp: base != 2, 'pow')]
# Related to sympy/sympy#11353
assert ccode(2**x, user_functions={'Pow': _cond_cfunc2}) == 'exp2(x)'
assert ccode(x**2, user_functions={'Pow': _cond_cfunc2}) == 'pow(x, 2)'
def binary_function(symfunc, expr, **kwargs):
"""Returns a diofant function with expr as binary implementation
This is a convenience function that automates the steps needed to
autowrap the Diofant expression and attaching it to a Function object
with implemented_function().
>>> from diofant.abc import x, y
>>> from diofant.utilities.autowrap import binary_function
>>> expr = ((x - y)**(25)).expand()
>>> f = binary_function('f', expr)
>>> type(f)
<class 'diofant.core.function.UndefinedFunction'>
>>> 2*f(x, y)
2*f(x, y)
>>> f(x, y).evalf(2, subs={x: 1, y: 2})
-1.0
"""
binary = autowrap(expr, **kwargs)
return implemented_function(symfunc, binary)
def test_inline_function():
n, m = symbols('n m', integer=True)
A, x, y = map(IndexedBase, 'Axy')
i = Idx('i', m)
p = FCodeGen()
func = implemented_function('func', Lambda(n, n*(n + 1)))
routine = make_routine('test_inline', Eq(y[i], func(x[i])))
code = get_string(p.dump_f95, [routine])
expected = (
'subroutine test_inline(m, x, y)\n'
'implicit none\n'
'INTEGER*4, intent(in) :: m\n'
'REAL*8, intent(in), dimension(1:m) :: x\n'
'REAL*8, intent(out), dimension(1:m) :: y\n'
'INTEGER*4 :: i\n'
'do i = 1, m\n'
' y(i) = %s*%s\n'
'end do\n'
'end subroutine\n'
)
args = ('x(i)', '(x(i) + 1)')
assert code == expected % args or\
code == expected % args[::-1]
def test_imps_wrong_args():
pytest.raises(ValueError, lambda: implemented_function(sin, lambda x: x))
def test_imps_wrong_args():
pytest.raises(ValueError, lambda: implemented_function(sin, lambda x: x))
def ufuncify(args,
expr,
language=None,
backend='numpy',
tempdir=None,
flags=None,
verbose=False,
helpers=None):
"""
Generates a binary function that supports broadcasting on numpy arrays.
Parameters
----------
args : iterable
Either a Symbol or an iterable of symbols. Specifies the argument
sequence for the function.
expr
A Diofant expression that defines the element wise operation.
language : string, optional
If supplied, (options: 'C' or 'F95'), specifies the language of the
generated code. If ``None`` [default], the language is inferred based
upon the specified backend.
backend : string, optional
Backend used to wrap the generated code. Either 'numpy' [default],
'cython', or 'f2py'.
tempdir : string, optional
Path to directory for temporary files. If this argument is supplied,
the generated code and the wrapper input files are left intact in the
specified path.
flags : iterable, optional
Additional option flags that will be passed to the backend
verbose : bool, optional
If True, autowrap will not mute the command line backends. This can be
helpful for debugging.
helpers : iterable, optional
Used to define auxillary expressions needed for the main expr. If the
main expression needs to call a specialized function it should be put
in the ``helpers`` iterable. Autowrap will then make sure that the
compiled main expression can link to the helper routine. Items should
be tuples with (<funtion_name>, <diofant_expression>, <arguments>). It
is mandatory to supply an argument sequence to helper routines.
Notes
-----
The default backend ('numpy') will create actual instances of
``numpy.ufunc``. These support ndimensional broadcasting, and implicit type
conversion. Use of the other backends will result in a "ufunc-like"
function, which requires equal length 1-dimensional arrays for all
arguments, and will not perform any type conversions.
References
----------
.. [1] http://docs.scipy.org/doc/numpy/reference/ufuncs.html
Examples
--------
>>> from diofant.utilities.autowrap import ufuncify
>>> from diofant.abc import x, y
>>> import numpy as np
>>> f = ufuncify((x, y), y + x**2)
>>> type(f) is np.ufunc
True
>>> f([1, 2, 3], 2)
array([ 3., 6., 11.])
>>> f(np.arange(5), 3)
array([ 3., 4., 7., 12., 19.])
For the F2Py and Cython backends, inputs are required to be equal length
1-dimensional arrays. The F2Py backend will perform type conversion, but
the Cython backend will error if the inputs are not of the expected type.
>>> f_fortran = ufuncify((x, y), y + x**2, backend='F2Py')
>>> f_fortran(1, 2)
3
>>> f_fortran(numpy.array([1, 2, 3]), numpy.array([1.0, 2.0, 3.0]))
array([2., 6., 12.])
>>> f_cython = ufuncify((x, y), y + x**2, backend='Cython')
>>> f_cython(1, 2)
Traceback (most recent call last):
...
TypeError: Argument '_x' has incorrect type (expected numpy.ndarray, got int)
>>> f_cython(numpy.array([1.0]), numpy.array([2.0]))
array([ 3.])
"""
if isinstance(args, (Dummy, Symbol)):
args = (args, )
else:
args = tuple(args)
if language:
_validate_backend_language(backend, language)
else:
language = _infer_language(backend)
helpers = helpers if helpers else ()
flags = flags if flags else ()
if backend.upper() == 'NUMPY':
routine = make_routine('autofunc', expr, args)
helps = []
for name, expr, args in helpers:
helps.append(make_routine(name, expr, args))
code_wrapper = UfuncifyCodeWrapper(CCodeGen("ufuncify"), tempdir,
flags, verbose)
return code_wrapper.wrap_code(routine, helpers=helps)
else:
# Dummies are used for all added expressions to prevent name clashes
# within the original expression.
y = IndexedBase(Dummy())
m = Dummy(integer=True)
i = Idx(Dummy(integer=True), m)
f = implemented_function(Dummy().name, Lambda(args, expr))
# For each of the args create an indexed version.
indexed_args = [IndexedBase(Dummy(str(a))) for a in args]
# Order the arguments (out, args, dim)
args = [y] + indexed_args + [m]
args_with_indices = [a[i] for a in indexed_args]
return autowrap(Eq(y[i], f(*args_with_indices)), language, backend,
tempdir, tuple(args), flags, verbose, helpers)
def test_sympyissue_12092():
f = implemented_function('f', lambda x: x**2)
assert f(f(2)).evalf() == Float(16)
