pycode.py

from collections import defaultdict
from functools import wraps
from itertools import chain
from sympy.core import sympify, S
from .precedence import precedence
from .codeprinter import CodePrinter

_kw_py2and3 = {
    'and', 'as', 'assert', 'break', 'class', 'continue', 'def', 'del', 'elif',
    'else', 'except', 'finally', 'for', 'from', 'global', 'if', 'import', 'in',
    'is', 'lambda', 'not', 'or', 'pass', 'raise', 'return', 'try', 'while',
    'with', 'yield', 'None'  # 'None' is actually not in Python 2's keyword.kwlist
}
_kw_only_py2 = {'exec', 'print'}
_kw_only_py3 = {'False', 'nonlocal', 'True'}

_known_functions = {
    'Abs': 'abs',
}
_known_functions_math = {
    'acos': 'acos',
    'acosh': 'acosh',
    'asin': 'asin',
    'asinh': 'asinh',
    'atan': 'atan',
    'atan2': 'atan2',
    'atanh': 'atanh',
    'ceiling': 'ceil',
    'cos': 'cos',
    'cosh': 'cosh',
    'erf': 'erf',
    'erfc': 'erfc',
    'exp': 'exp',
    'expm1': 'expm1',
    'factorial': 'factorial',
    'floor': 'floor',
    'gamma': 'gamma',
    'hypot': 'hypot',
    'loggamma': 'lgamma',
    'log': 'log',
    'log10': 'log10',
    'log1p': 'log1p',
    'log2': 'log2',
    'sin': 'sin',
    'sinh': 'sinh',
    'Sqrt': 'sqrt',
    'tan': 'tan',
    'tanh': 'tanh'
}  # Not used from ``math``: [copysign isclose isfinite isinf isnan ldexp frexp pow modf
# radians trunc fmod fsum gcd degrees fabs]
_known_constants_math = {
    'Exp1': 'e',
    'Pi': 'pi',
    # Only in python >= 3.5:
    # 'Infinity': 'inf',
    # 'NaN': 'nan'
}

def _print_known_func(self, expr):
    known = self.known_functions[expr.__class__.__name__]
    return '{name}({args})'.format(name=self._module_format(known),
                                   args=', '.join(map(self._print, expr.args)))


def _print_known_const(self, expr):
    known = self.known_constants[expr.__class__.__name__]
    return self._module_format(known)


class PythonCodePrinter(CodePrinter):
    printmethod = "_pythoncode"
    language = "Python"
    standard = "python3"
    reserved_words = _kw_py2and3.union(_kw_only_py3)
    modules = None  # initialized to a set in __init__
    tab = '    '
    _kf = dict(chain(
        _known_functions.items(),
        [(k, 'math.' + v) for k, v in _known_functions_math.items()]
    ))
    _kc = {k: 'math.'+v for k, v in _known_constants_math.items()}
    _operators = {'and': 'and', 'or': 'or', 'not': 'not'}
    _default_settings = dict(
        CodePrinter._default_settings,
        user_functions={},
        precision=17,
        inline=True,
        fully_qualified_modules=True
    )

    def __init__(self, settings=None):
        super(PythonCodePrinter, self).__init__(settings)
        self.module_imports = defaultdict(set)
        self.known_functions = dict(self._kf, **(settings or {}).get(
            'user_functions', {}))
        self.known_constants = dict(self._kc, **(settings or {}).get(
            'user_constants', {}))

    def _declare_number_const(self, name, value):
        return "%s = %s" % (name, value)

    def _module_format(self, fqn, register=True):
        parts = fqn.split('.')
        if register and len(parts) > 1:
            self.module_imports['.'.join(parts[:-1])].add(parts[-1])

        if self._settings['fully_qualified_modules']:
            return fqn
        else:
            return fqn.split('(')[0].split('[')[0].split('.')[-1]

    def _format_code(self, lines):
        return lines

    def _get_statement(self, codestring):
        return "%s" % codestring

    def _get_comment(self, text):
        return "  # {0}".format(text)

    def _print_NaN(self, expr):
        return "float('nan')"

    def _print_Infinity(self, expr):
        return "float('inf')"

    def _print_sign(self, e):
        return '(0.0 if {e} == 0 else {f}(1, {e}))'.format(
            f=self._module_format('math.copysign'), e=self._print(e.args[0]))

    def _print_NegativeInfinity(self, expr):
        return "float('-inf')"

    def _print_ComplexInfinity(self, expr):
        return self._print_NaN(expr)

    def _print_Mod(self, expr):
        PREC = precedence(expr)
        return ('{0} % {1}'.format(*map(lambda x: self.parenthesize(x, PREC), expr.args)))

    def _print_Piecewise(self, expr):
        result = []
        i = 0
        for arg in expr.args:
            e = arg.expr
            c = arg.cond
            if i == 0:
                result.append('(')
            result.append('(')
            result.append(self._print(e))
            result.append(')')
            result.append(' if ')
            result.append(self._print(c))
            result.append(' else ')
            i += 1
        result = result[:-1]
        if result[-1] == 'True':
            result = result[:-2]
            result.append(')')
        else:
            result.append(' else None)')
        return ''.join(result)

    def _print_Relational(self, expr):
        "Relational printer for Equality and Unequality"
        op = {
            '==' :'equal',
            '!=' :'not_equal',
            '<'  :'less',
            '<=' :'less_equal',
            '>'  :'greater',
            '>=' :'greater_equal',
        }
        if expr.rel_op in op:
            lhs = self._print(expr.lhs)
            rhs = self._print(expr.rhs)
            return '({lhs} {op} {rhs})'.format(op=expr.rel_op, lhs=lhs, rhs=rhs)
        return super(PythonCodePrinter, self)._print_Relational(expr)

    def _print_ITE(self, expr):
        from sympy.functions.elementary.piecewise import Piecewise
        return self._print(expr.rewrite(Piecewise))

    def _print_Sum(self, expr):
        loops = (
            'for {i} in range({a}, {b}+1)'.format(
                i=self._print(i),
                a=self._print(a),
                b=self._print(b))
            for i, a, b in expr.limits)
        return '(builtins.sum({function} {loops}))'.format(
            function=self._print(expr.function),
            loops=' '.join(loops))

    def _print_ImaginaryUnit(self, expr):
        return '1j'

    def _print_MatrixBase(self, expr):
        name = expr.__class__.__name__
        func = self.known_functions.get(name, name)
        return "%s(%s)" % (func, self._print(expr.tolist()))

    _print_SparseMatrix = \
        _print_MutableSparseMatrix = \
        _print_ImmutableSparseMatrix = \
        _print_Matrix = \
        _print_DenseMatrix = \
        _print_MutableDenseMatrix = \
        _print_ImmutableMatrix = \
        _print_ImmutableDenseMatrix = \
        lambda self, expr: self._print_MatrixBase(expr)


for k in PythonCodePrinter._kf:
    setattr(PythonCodePrinter, '_print_%s' % k, _print_known_func)

for k in _known_constants_math:
    setattr(PythonCodePrinter, '_print_%s' % k, _print_known_const)


def pycode(expr, **settings):
    return PythonCodePrinter(settings).doprint(expr)


_not_in_mpmath = 'log1p log2'.split()
_in_mpmath = [(k, v) for k, v in _known_functions_math.items() if k not in _not_in_mpmath]
_known_functions_mpmath = dict(_in_mpmath, **{
    'sign': 'sign',
})
_known_constants_mpmath = {
    'Pi': 'pi'
}


class MpmathPrinter(PythonCodePrinter):
    """
    Lambda printer for mpmath which maintains precision for floats
    """
    printmethod = "_mpmathcode"

    _kf = dict(chain(
        _known_functions.items(),
        [(k, 'mpmath.' + v) for k, v in _known_functions_mpmath.items()]
    ))

    def _print_Float(self, e):
        # XXX: This does not handle setting mpmath.mp.dps. It is assumed that
        # the caller of the lambdified function will have set it to sufficient
        # precision to match the Floats in the expression.

        # Remove 'mpz' if gmpy is installed.
        args = str(tuple(map(int, e._mpf_)))
        return '{func}({args})'.format(func=self._module_format('mpmath.mpf'), args=args)


    def _print_uppergamma(self,e): #printer for the uppergamma function
        return "{0}({1}, {2}, {3})".format(
            self._module_format('mpmath.gammainc'), self._print(e.args[0]), self._print(e.args[1]),
            self._module_format('mpmath.inf'))

    def _print_lowergamma(self,e): #printer for the lowergamma functioin
        return "{0}({1}, 0, {2})".format(
            self._module_format('mpmath.gammainc'), self._print(e.args[0]), self._print(e.args[1]))

    def _print_log2(self, e):
        return '{0}({1})/{0}(2)'.format(
            self._module_format('mpmath.log'), self._print(e.args[0]))

    def _print_log1p(self, e):
        return '{0}({1}+1)'.format(
            self._module_format('mpmath.log'), self._print(e.args[0]))

for k in MpmathPrinter._kf:
    setattr(MpmathPrinter, '_print_%s' % k, _print_known_func)

for k in _known_constants_mpmath:
    setattr(MpmathPrinter, '_print_%s' % k, _print_known_const)


_not_in_numpy = 'erf erfc factorial gamma lgamma'.split()
_in_numpy = [(k, v) for k, v in _known_functions_math.items() if k not in _not_in_numpy]
_known_functions_numpy = dict(_in_numpy, **{
    'acos': 'arccos',
    'acosh': 'arccosh',
    'asin': 'arcsin',
    'asinh': 'arcsinh',
    'atan': 'arctan',
    'atan2': 'arctan2',
    'atanh': 'arctanh',
    'exp2': 'exp2',
    'sign': 'sign',
})


class NumPyPrinter(PythonCodePrinter):
    """
    Numpy printer which handles vectorized piecewise functions,
    logical operators, etc.
    """
    printmethod = "_numpycode"

    _kf = dict(chain(
        PythonCodePrinter._kf.items(),
        [(k, 'numpy.' + v) for k, v in _known_functions_numpy.items()]
    ))
    _kc = {k: 'numpy.'+v for k, v in _known_constants_math.items()}


    def _print_seq(self, seq, delimiter=', '):
        "General sequence printer: converts to tuple"
        # Print tuples here instead of lists because numba supports
        #     tuples in nopython mode.
        return '({},)'.format(delimiter.join(self._print(item) for item in seq))

    def _print_MatMul(self, expr):
        "Matrix multiplication printer"
        return '({0})'.format(').dot('.join(self._print(i) for i in expr.args))

    def _print_DotProduct(self, expr):
        # DotProduct allows any shape order, but numpy.dot does matrix
        # multiplication, so we have to make sure it gets 1 x n by n x 1.
        arg1, arg2 = expr.args
        if arg1.shape[0] != 1:
            arg1 = arg1.T
        if arg2.shape[1] != 1:
            arg2 = arg2.T

        return "%s(%s, %s)" % (self._module_format('numpy.dot'), self._print(arg1), self._print(arg2))

    def _print_Piecewise(self, expr):
        "Piecewise function printer"
        exprs = '[{0}]'.format(','.join(self._print(arg.expr) for arg in expr.args))
        conds = '[{0}]'.format(','.join(self._print(arg.cond) for arg in expr.args))
        # If [default_value, True] is a (expr, cond) sequence in a Piecewise object
        #     it will behave the same as passing the 'default' kwarg to select()
        #     *as long as* it is the last element in expr.args.
        # If this is not the case, it may be triggered prematurely.
        return '{0}({1}, {2}, default=numpy.nan)'.format(self._module_format('numpy.select'), conds, exprs)

    def _print_Relational(self, expr):
        "Relational printer for Equality and Unequality"
        op = {
            '==' :'equal',
            '!=' :'not_equal',
            '<'  :'less',
            '<=' :'less_equal',
            '>'  :'greater',
            '>=' :'greater_equal',
        }
        if expr.rel_op in op:
            lhs = self._print(expr.lhs)
            rhs = self._print(expr.rhs)
            return '{op}({lhs}, {rhs})'.format(op=self._module_format('numpy.'+op[expr.rel_op]),
                                               lhs=lhs, rhs=rhs)
        return super(NumPyPrinter, self)._print_Relational(expr)

    def _print_And(self, expr):
        "Logical And printer"
        # We have to override LambdaPrinter because it uses Python 'and' keyword.
        # If LambdaPrinter didn't define it, we could use StrPrinter's
        # version of the function and add 'logical_and' to NUMPY_TRANSLATIONS.
        return '{0}.reduce(({1}))'.format(self._module_format('numpy.logical_and'), ','.join(self._print(i) for i in expr.args))

    def _print_Or(self, expr):
        "Logical Or printer"
        # We have to override LambdaPrinter because it uses Python 'or' keyword.
        # If LambdaPrinter didn't define it, we could use StrPrinter's
        # version of the function and add 'logical_or' to NUMPY_TRANSLATIONS.
        return '{0}.reduce(({1}))'.format(self._module_format('numpy.logical_or'), ','.join(self._print(i) for i in expr.args))

    def _print_Not(self, expr):
        "Logical Not printer"
        # We have to override LambdaPrinter because it uses Python 'not' keyword.
        # If LambdaPrinter didn't define it, we would still have to define our
        #     own because StrPrinter doesn't define it.
        return '{0}({1})'.format(self._module_format('numpy.logical_not'), ','.join(self._print(i) for i in expr.args))

    def _print_Min(self, expr):
        return '{0}(({1}))'.format(self._module_format('numpy.amin'), ','.join(self._print(i) for i in expr.args))

    def _print_Max(self, expr):
        return '{0}(({1}))'.format(self._module_format('numpy.amax'), ','.join(self._print(i) for i in expr.args))

    def _print_Pow(self, expr):
        if expr.exp == 0.5:
            return '{0}({1})'.format(self._module_format('numpy.sqrt'), self._print(expr.base))
        else:
            return super(NumPyPrinter, self)._print_Pow(expr)

    def _print_arg(self, expr):
        return "%s(%s)" % (self._module_format('numpy.angle'), self._print(expr.args[0]))

    def _print_im(self, expr):
        return "%s(%s)" % (self._module_format('numpy.imag', self._print(expr.args[0])))

    def _print_Mod(self, expr):
        return "%s(%s)" % (self._module_format('numpy.mod'), ', '.join(map(self._print, expr.args)))

    def _print_re(self, expr):
        return "%s(%s)" % (self._module_format('numpy.real'), self._print(expr.args[0]))

    def _print_sinc(self, expr):
        return "%s(%s)" % (self._module_format('numpy.sinc'), self._print(expr.args[0]/S.Pi))

    def _print_MatrixBase(self, expr):
        func = self.known_functions.get(expr.__class__.__name__, None)
        if func is None:
            func = self._module_format('numpy.array')
        return "%s(%s)" % (func, self._print(expr.tolist()))


for k in NumPyPrinter._kf:
    setattr(NumPyPrinter, '_print_%s' % k, _print_known_func)

for k in NumPyPrinter._kc:
    setattr(NumPyPrinter, '_print_%s' % k, _print_known_const)


_known_functions_scipy_special = {
    'erf': 'erf',
    'erfc': 'erfc',
    'gamma': 'gamma',
    'loggamma': 'gammaln'
}
_known_constants_scipy_constants = {
    'GoldenRatio': 'golden_ratio'
}

class SciPyPrinter(NumPyPrinter):

    _kf = dict(chain(
        NumPyPrinter._kf.items(),
        [(k, 'scipy.special.' + v) for k, v in _known_functions_scipy_special.items()]
    ))
    _kc = {k: 'scipy.constants.' + v for k, v in _known_constants_scipy_constants.items()}

    def _print_SparseMatrix(self, expr):
        i, j, data = [], [], []
        for (r, c), v in expr._smat.items():
            i.append(r)
            j.append(c)
            data.append(v)

        return "{name}({data}, ({i}, {j}), shape={shape})".format(
            name=self._module_format('scipy.sparse.coo_matrix'),
            data=data, i=i, j=j, shape=expr.shape
        )

    _print_ImmutableSparseMatrix = _print_SparseMatrix


for k in SciPyPrinter._kf:
    setattr(SciPyPrinter, '_print_%s' % k, _print_known_func)

for k in SciPyPrinter._kc:
    setattr(SciPyPrinter, '_print_%s' % k, _print_known_const)


class SymPyPrinter(PythonCodePrinter):

    _kf = dict([(k, 'sympy.' + v) for k, v in chain(
        _known_functions.items(),
        _known_functions_math.items()
    )])

    def _print_Function(self, expr):
        mod = expr.func.__module__ or ''
        return '%s(%s)' % (self._module_format(mod + ('.' if mod else '') + expr.func.__name__),
                           ', '.join(map(self._print, expr.args)))