def test_numpy_matrix():
if not numpy:
skip("numpy not installed.")
A = Matrix([[x, x * y], [sin(z) + 4, x**z]])
sol_arr = numpy.array([[1, 2], [numpy.sin(3) + 4, 1]])
#Lambdify array first, to ensure return to array as default
f = lambdify((x, y, z), A, ['numpy'])
numpy.testing.assert_allclose(f(1, 2, 3), sol_arr)
#Check that the types are arrays and matrices
assert isinstance(f(1, 2, 3), numpy.ndarray)
# gh-15071
class dot(Function):
pass
x_dot_mtx = dot(x, Matrix([[2], [1], [0]]))
f_dot1 = lambdify(x, x_dot_mtx)
inp = numpy.zeros((17, 3))
assert numpy.all(f_dot1(inp) == 0)
strict_kw = dict(allow_unknown_functions=False,
inline=True,
fully_qualified_modules=False)
p2 = NumPyPrinter(dict(user_functions={'dot': 'dot'}, **strict_kw))
f_dot2 = lambdify(x, x_dot_mtx, printer=p2)
assert numpy.all(f_dot2(inp) == 0)
p3 = NumPyPrinter(strict_kw)
# The line below should probably fail upon construction (before calling with "(inp)"):
raises(Exception, lambda: lambdify(x, x_dot_mtx, printer=p3)(inp))
def test_numpy_piecewise_regression():
"""
NumPyPrinter needs to print Piecewise()'s choicelist as a list to avoid
breaking compatibility with numpy 1.8. This is not necessary in numpy 1.9+.
See gh-9747 and gh-9749 for details.
"""
printer = NumPyPrinter()
p = Piecewise((1, x < 0), (0, True))
assert printer.doprint(p) == \
'numpy.select([numpy.less(x, 0),True], [1,0], default=numpy.nan)'
assert printer.module_imports == {'numpy': {'select', 'less', 'nan'}}
def test_16857():
if not np:
skip("NumPy not installed")
a_1 = MatrixSymbol('a_1', 10, 3)
a_2 = MatrixSymbol('a_2', 10, 3)
a_3 = MatrixSymbol('a_3', 10, 3)
a_4 = MatrixSymbol('a_4', 10, 3)
A = BlockMatrix([[a_1, a_2], [a_3, a_4]])
assert A.shape == (20, 6)
printer = NumPyPrinter()
assert printer.doprint(A) == 'numpy.block([[a_1, a_2], [a_3, a_4]])'
def _append_code_rendering(
expr: NumPyPrintable,
use_cse: bool = False,
docstring_class: Optional[type] = None,
) -> None:
printer = NumPyPrinter()
if use_cse:
args = sorted(expr.free_symbols, key=str)
func = sp.lambdify(args, expr, cse=True, printer=printer)
numpy_code = inspect.getsource(func)
else:
numpy_code = expr._numpycode(printer)
import_statements = __print_imports(printer)
if docstring_class is None:
docstring_class = type(expr)
numpy_code = textwrap.dedent(numpy_code)
numpy_code = textwrap.indent(numpy_code, prefix=8 * " ").strip()
options = ""
if (
max(__get_text_width(import_statements), __get_text_width(numpy_code))
> 90
):
options += ":class: full-width\n"
appended_text = f"""\n
.. code-block:: python
{options}
{import_statements}
{numpy_code}
"""
_append_to_docstring(docstring_class, appended_text)
def test_sqrt():
prntr = PythonCodePrinter()
assert prntr._print_Pow(sqrt(x), rational=False) == 'math.sqrt(x)'
assert prntr._print_Pow(1/sqrt(x), rational=False) == '1/math.sqrt(x)'
prntr = PythonCodePrinter({'standard' : 'python2'})
assert prntr._print_Pow(sqrt(x), rational=True) == 'x**(1./2.)'
assert prntr._print_Pow(1/sqrt(x), rational=True) == 'x**(-1./2.)'
prntr = PythonCodePrinter({'standard' : 'python3'})
assert prntr._print_Pow(sqrt(x), rational=True) == 'x**(1/2)'
assert prntr._print_Pow(1/sqrt(x), rational=True) == 'x**(-1/2)'
prntr = MpmathPrinter()
assert prntr._print_Pow(sqrt(x), rational=False) == 'mpmath.sqrt(x)'
assert prntr._print_Pow(sqrt(x), rational=True) == \
"x**(mpmath.mpf(1)/mpmath.mpf(2))"
prntr = NumPyPrinter()
assert prntr._print_Pow(sqrt(x), rational=False) == 'numpy.sqrt(x)'
assert prntr._print_Pow(sqrt(x), rational=True) == 'x**(1/2)'
prntr = SciPyPrinter()
assert prntr._print_Pow(sqrt(x), rational=False) == 'numpy.sqrt(x)'
assert prntr._print_Pow(sqrt(x), rational=True) == 'x**(1/2)'
prntr = SymPyPrinter()
assert prntr._print_Pow(sqrt(x), rational=False) == 'sympy.sqrt(x)'
assert prntr._print_Pow(sqrt(x), rational=True) == 'x**(1/2)'
def test_airy_prime():
from sympy import airyaiprime, airybiprime
expr1 = airyaiprime(x)
expr2 = airybiprime(x)
prntr = SciPyPrinter()
assert prntr.doprint(expr1) == 'scipy.special.airy(x)[1]'
assert prntr.doprint(expr2) == 'scipy.special.airy(x)[3]'
prntr = NumPyPrinter()
assert "Not supported" in prntr.doprint(expr1)
assert "Not supported" in prntr.doprint(expr2)
prntr = PythonCodePrinter()
assert "Not supported" in prntr.doprint(expr1)
assert "Not supported" in prntr.doprint(expr2)
def test_airy():
from sympy.functions.special.bessel import (airyai, airybi)
expr1 = airyai(x)
expr2 = airybi(x)
prntr = SciPyPrinter()
assert prntr.doprint(expr1) == 'scipy.special.airy(x)[0]'
assert prntr.doprint(expr2) == 'scipy.special.airy(x)[2]'
prntr = NumPyPrinter()
assert "Not supported" in prntr.doprint(expr1)
assert "Not supported" in prntr.doprint(expr2)
prntr = PythonCodePrinter()
assert "Not supported" in prntr.doprint(expr1)
assert "Not supported" in prntr.doprint(expr2)
def test_issue_16535_16536():
from sympy import lowergamma, uppergamma
a = symbols('a')
expr1 = lowergamma(a, x)
expr2 = uppergamma(a, x)
prntr = SciPyPrinter()
assert prntr.doprint(expr1) == 'scipy.special.gamma(a)*scipy.special.gammainc(a, x)'
assert prntr.doprint(expr2) == 'scipy.special.gamma(a)*scipy.special.gammaincc(a, x)'
prntr = NumPyPrinter()
assert "Not supported" in prntr.doprint(expr1)
assert "Not supported" in prntr.doprint(expr2)
prntr = PythonCodePrinter()
assert "Not supported" in prntr.doprint(expr1)
assert "Not supported" in prntr.doprint(expr2)
def test_beta():
from sympy import beta
expr = beta(x, y)
prntr = SciPyPrinter()
assert prntr.doprint(expr) == 'scipy.special.beta(x, y)'
prntr = NumPyPrinter()
assert prntr.doprint(expr) == 'math.gamma(x)*math.gamma(y)/math.gamma(x + y)'
prntr = PythonCodePrinter()
assert prntr.doprint(expr) == 'math.gamma(x)*math.gamma(y)/math.gamma(x + y)'
prntr = PythonCodePrinter({'allow_unknown_functions': True})
assert prntr.doprint(expr) == 'math.gamma(x)*math.gamma(y)/math.gamma(x + y)'
prntr = MpmathPrinter()
assert prntr.doprint(expr) == 'mpmath.beta(x, y)'
def test_fresnel_integrals():
from sympy import fresnelc, fresnels
expr1 = fresnelc(x)
expr2 = fresnels(x)
prntr = SciPyPrinter()
assert prntr.doprint(expr1) == 'scipy.special.fresnel(x)[1]'
assert prntr.doprint(expr2) == 'scipy.special.fresnel(x)[0]'
prntr = NumPyPrinter()
assert "Not supported" in prntr.doprint(expr1)
assert "Not supported" in prntr.doprint(expr2)
prntr = PythonCodePrinter()
assert "Not supported" in prntr.doprint(expr1)
assert "Not supported" in prntr.doprint(expr2)
prntr = MpmathPrinter()
assert prntr.doprint(expr1) == 'mpmath.fresnelc(x)'
assert prntr.doprint(expr2) == 'mpmath.fresnels(x)'
def test_numpy_array():
assert NumPyPrinter().doprint(Array(
((1, 2), (3, 5)))) == 'numpy.array([[1, 2], [3, 5]])'
assert NumPyPrinter().doprint(Array((1, 2))) == 'numpy.array((1, 2))'
def test_NumPyPrinter():
from sympy import (Lambda, ZeroMatrix, OneMatrix, FunctionMatrix,
HadamardProduct, KroneckerProduct, Adjoint, DiagonalOf,
DiagMatrix, DiagonalMatrix)
from sympy.abc import a, b
p = NumPyPrinter()
assert p.doprint(sign(x)) == 'numpy.sign(x)'
A = MatrixSymbol("A", 2, 2)
B = MatrixSymbol("B", 2, 2)
C = MatrixSymbol("C", 1, 5)
D = MatrixSymbol("D", 3, 4)
assert p.doprint(A**(-1)) == "numpy.linalg.inv(A)"
assert p.doprint(A**5) == "numpy.linalg.matrix_power(A, 5)"
assert p.doprint(Identity(3)) == "numpy.eye(3)"
u = MatrixSymbol('x', 2, 1)
v = MatrixSymbol('y', 2, 1)
assert p.doprint(MatrixSolve(A, u)) == 'numpy.linalg.solve(A, x)'
assert p.doprint(MatrixSolve(A, u) + v) == 'numpy.linalg.solve(A, x) + y'
assert p.doprint(ZeroMatrix(2, 3)) == "numpy.zeros((2, 3))"
assert p.doprint(OneMatrix(2, 3)) == "numpy.ones((2, 3))"
assert p.doprint(FunctionMatrix(4, 5, Lambda((a, b), a + b))) == \
"numpy.fromfunction(lambda a, b: a + b, (4, 5))"
assert p.doprint(HadamardProduct(A, B)) == "numpy.multiply(A, B)"
assert p.doprint(KroneckerProduct(A, B)) == "numpy.kron(A, B)"
assert p.doprint(Adjoint(A)) == "numpy.conjugate(numpy.transpose(A))"
assert p.doprint(DiagonalOf(A)) == "numpy.reshape(numpy.diag(A), (-1, 1))"
assert p.doprint(DiagMatrix(C)) == "numpy.diagflat(C)"
assert p.doprint(DiagonalMatrix(D)) == "numpy.multiply(D, numpy.eye(3, 4))"
# Workaround for numpy negative integer power errors
assert p.doprint(x**-1) == 'x**(-1.0)'
assert p.doprint(x**-2) == 'x**(-2.0)'
expr = Pow(2, -1, evaluate=False)
assert p.doprint(expr) == "2**(-1.0)"
assert p.doprint(S.Exp1) == 'numpy.e'
assert p.doprint(S.Pi) == 'numpy.pi'
assert p.doprint(S.EulerGamma) == 'numpy.euler_gamma'
assert p.doprint(S.NaN) == 'numpy.nan'
assert p.doprint(S.Infinity) == 'numpy.PINF'
assert p.doprint(S.NegativeInfinity) == 'numpy.NINF'
def test_NumPyPrinter_print_seq():
n = NumPyPrinter()
assert n._print_seq(range(2)) == '(0, 1,)'
def _numpycode(self, printer: NumPyPrinter, *args: Any) -> str:
printer.module_imports[printer._module].add("zeros")
shape = printer._print(self.args[0])
return f"zeros({shape})"
def test_numpy_logaddexp():
lae = logaddexp(a, b)
assert NumPyPrinter().doprint(lae) == 'numpy.logaddexp(a, b)'
lae2 = logaddexp2(a, b)
assert NumPyPrinter().doprint(lae2) == 'numpy.logaddexp2(a, b)'
def _numpycode(self, printer: NumPyPrinter, *args: Any) -> str:
shape = printer._print(self.args[0])
return f"len({shape})"
def _numpycode(self, printer: NumPyPrinter, *args: Any) -> str:
printer.module_imports[printer._module].add("sum")
array = printer._print(self.array)
axis = printer._print(self.axis)
return f"sum({array}, axis={axis})"
def test_array_printer():
A = ArraySymbol('A', (4, 4, 6, 6, 6))
I = IndexedBase('I')
i, j, k = Idx('i', (0, 1)), Idx('j', (2, 3)), Idx('k', (4, 5))
prntr = NumPyPrinter()
assert prntr.doprint(ZeroArray(5)) == 'numpy.zeros((5,))'
assert prntr.doprint(OneArray(5)) == 'numpy.ones((5,))'
assert prntr.doprint(ArrayContraction(
A, [2, 3])) == 'numpy.einsum("abccd->abd", A)'
assert prntr.doprint(I) == 'I'
assert prntr.doprint(ArrayDiagonal(
A, [2, 3, 4])) == 'numpy.einsum("abccc->abc", A)'
assert prntr.doprint(ArrayDiagonal(
A, [0, 1], [2, 3])) == 'numpy.einsum("aabbc->cab", A)'
assert prntr.doprint(ArrayContraction(
A, [2], [3])) == 'numpy.einsum("abcde->abe", A)'
assert prntr.doprint(Assignment(I[i, j, k], I[i, j, k])) == 'I = I'
prntr = TensorflowPrinter()
assert prntr.doprint(ZeroArray(5)) == 'tensorflow.zeros((5,))'
assert prntr.doprint(OneArray(5)) == 'tensorflow.ones((5,))'
assert prntr.doprint(ArrayContraction(
A, [2, 3])) == 'tensorflow.linalg.einsum("abccd->abd", A)'
assert prntr.doprint(I) == 'I'
assert prntr.doprint(ArrayDiagonal(
A, [2, 3, 4])) == 'tensorflow.linalg.einsum("abccc->abc", A)'
assert prntr.doprint(ArrayDiagonal(
A, [0, 1], [2, 3])) == 'tensorflow.linalg.einsum("aabbc->cab", A)'
assert prntr.doprint(ArrayContraction(
A, [2], [3])) == 'tensorflow.linalg.einsum("abcde->abe", A)'
assert prntr.doprint(Assignment(I[i, j, k], I[i, j, k])) == 'I = I'
def _generate_numpy_code(expr: sp.Expr) -> str:
printer = NumPyPrinter()
return printer.doprint(expr)
def test_frac():
from sympy import frac
expr = frac(x)
prntr = NumPyPrinter()
assert prntr.doprint(expr) == 'numpy.mod(x, 1)'
prntr = SciPyPrinter()
assert prntr.doprint(expr) == 'numpy.mod(x, 1)'
prntr = PythonCodePrinter()
assert prntr.doprint(expr) == 'x % 1'
prntr = MpmathPrinter()
assert prntr.doprint(expr) == 'mpmath.frac(x)'
prntr = SymPyPrinter()
assert prntr.doprint(expr) == 'sympy.functions.elementary.integers.frac(x)'
def test_printmethod():
obj = CustomPrintedObject()
assert NumPyPrinter().doprint(obj) == 'numpy'
assert MpmathPrinter().doprint(obj) == 'mpmath'
def test_numpy_print_methods():
prntr = NumPyPrinter()
assert hasattr(prntr, '_print_acos')
assert hasattr(prntr, '_print_log')
def _numpycode(self, printer: NumPyPrinter, *args: Any) -> str:
return printer._print(self.evaluate())
