1130 lines
40 KiB
Python
1130 lines
40 KiB
Python
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"""Module for compiling codegen output, and wrap the binary for use in
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python.
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.. note:: To use the autowrap module it must first be imported
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>>> from sympy.utilities.autowrap import autowrap
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This module provides a common interface for different external backends, such
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as f2py, fwrap, Cython, SWIG(?) etc. (Currently only f2py and Cython are
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implemented) The goal is to provide access to compiled binaries of acceptable
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performance with a one-button user interface, e.g.,
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>>> from sympy.abc import x,y
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>>> expr = (x - y)**25
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>>> flat = expr.expand()
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>>> binary_callable = autowrap(flat)
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>>> binary_callable(2, 3)
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-1.0
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Although a SymPy user might primarily be interested in working with
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mathematical expressions and not in the details of wrapping tools
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needed to evaluate such expressions efficiently in numerical form,
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the user cannot do so without some understanding of the
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limits in the target language. For example, the expanded expression
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contains large coefficients which result in loss of precision when
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computing the expression:
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>>> binary_callable(3, 2)
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0.0
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>>> binary_callable(4, 5), binary_callable(5, 4)
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(-22925376.0, 25165824.0)
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Wrapping the unexpanded expression gives the expected behavior:
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>>> e = autowrap(expr)
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>>> e(4, 5), e(5, 4)
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(-1.0, 1.0)
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The callable returned from autowrap() is a binary Python function, not a
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SymPy object. If it is desired to use the compiled function in symbolic
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expressions, it is better to use binary_function() which returns a SymPy
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Function object. The binary callable is attached as the _imp_ attribute and
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invoked when a numerical evaluation is requested with evalf(), or with
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lambdify().
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>>> from sympy.utilities.autowrap import binary_function
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>>> f = binary_function('f', expr)
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>>> 2*f(x, y) + y
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y + 2*f(x, y)
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>>> (2*f(x, y) + y).evalf(2, subs={x: 1, y:2})
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0.e-110
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When is this useful?
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1) For computations on large arrays, Python iterations may be too slow,
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and depending on the mathematical expression, it may be difficult to
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exploit the advanced index operations provided by NumPy.
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2) For *really* long expressions that will be called repeatedly, the
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compiled binary should be significantly faster than SymPy's .evalf()
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3) If you are generating code with the codegen utility in order to use
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it in another project, the automatic Python wrappers let you test the
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binaries immediately from within SymPy.
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4) To create customized ufuncs for use with numpy arrays.
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See *ufuncify*.
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When is this module NOT the best approach?
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1) If you are really concerned about speed or memory optimizations,
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you will probably get better results by working directly with the
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wrapper tools and the low level code. However, the files generated
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by this utility may provide a useful starting point and reference
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code. Temporary files will be left intact if you supply the keyword
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tempdir="path/to/files/".
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2) If the array computation can be handled easily by numpy, and you
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do not need the binaries for another project.
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"""
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import sys
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import os
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import shutil
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import tempfile
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from subprocess import STDOUT, CalledProcessError, check_output
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from string import Template
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from warnings import warn
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from sympy.core.cache import cacheit
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from sympy.core.function import Lambda
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from sympy.core.relational import Eq
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from sympy.core.symbol import Dummy, Symbol
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from sympy.tensor.indexed import Idx, IndexedBase
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from sympy.utilities.codegen import (make_routine, get_code_generator,
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OutputArgument, InOutArgument,
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InputArgument, CodeGenArgumentListError,
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Result, ResultBase, C99CodeGen)
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from sympy.utilities.iterables import iterable
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from sympy.utilities.lambdify import implemented_function
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from sympy.utilities.decorator import doctest_depends_on
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_doctest_depends_on = {'exe': ('f2py', 'gfortran', 'gcc'),
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'modules': ('numpy',)}
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class CodeWrapError(Exception):
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pass
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class CodeWrapper:
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"""Base Class for code wrappers"""
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_filename = "wrapped_code"
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_module_basename = "wrapper_module"
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_module_counter = 0
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@property
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def filename(self):
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return "%s_%s" % (self._filename, CodeWrapper._module_counter)
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@property
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def module_name(self):
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return "%s_%s" % (self._module_basename, CodeWrapper._module_counter)
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def __init__(self, generator, filepath=None, flags=[], verbose=False):
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"""
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generator -- the code generator to use
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"""
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self.generator = generator
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self.filepath = filepath
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self.flags = flags
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self.quiet = not verbose
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@property
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def include_header(self):
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return bool(self.filepath)
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@property
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def include_empty(self):
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return bool(self.filepath)
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def _generate_code(self, main_routine, routines):
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routines.append(main_routine)
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self.generator.write(
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routines, self.filename, True, self.include_header,
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self.include_empty)
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def wrap_code(self, routine, helpers=None):
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helpers = helpers or []
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if self.filepath:
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workdir = os.path.abspath(self.filepath)
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else:
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workdir = tempfile.mkdtemp("_sympy_compile")
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if not os.access(workdir, os.F_OK):
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os.mkdir(workdir)
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oldwork = os.getcwd()
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os.chdir(workdir)
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try:
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sys.path.append(workdir)
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self._generate_code(routine, helpers)
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self._prepare_files(routine)
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self._process_files(routine)
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mod = __import__(self.module_name)
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finally:
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sys.path.remove(workdir)
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CodeWrapper._module_counter += 1
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os.chdir(oldwork)
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if not self.filepath:
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try:
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shutil.rmtree(workdir)
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except OSError:
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# Could be some issues on Windows
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pass
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return self._get_wrapped_function(mod, routine.name)
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def _process_files(self, routine):
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command = self.command
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command.extend(self.flags)
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try:
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retoutput = check_output(command, stderr=STDOUT)
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except CalledProcessError as e:
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raise CodeWrapError(
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"Error while executing command: %s. Command output is:\n%s" % (
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" ".join(command), e.output.decode('utf-8')))
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if not self.quiet:
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print(retoutput)
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class DummyWrapper(CodeWrapper):
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"""Class used for testing independent of backends """
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template = """# dummy module for testing of SymPy
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def %(name)s():
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return "%(expr)s"
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%(name)s.args = "%(args)s"
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%(name)s.returns = "%(retvals)s"
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"""
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def _prepare_files(self, routine):
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return
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def _generate_code(self, routine, helpers):
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with open('%s.py' % self.module_name, 'w') as f:
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printed = ", ".join(
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[str(res.expr) for res in routine.result_variables])
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# convert OutputArguments to return value like f2py
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args = filter(lambda x: not isinstance(
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x, OutputArgument), routine.arguments)
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retvals = []
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for val in routine.result_variables:
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if isinstance(val, Result):
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retvals.append('nameless')
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else:
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retvals.append(val.result_var)
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print(DummyWrapper.template % {
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'name': routine.name,
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'expr': printed,
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'args': ", ".join([str(a.name) for a in args]),
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'retvals': ", ".join([str(val) for val in retvals])
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}, end="", file=f)
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def _process_files(self, routine):
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return
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@classmethod
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def _get_wrapped_function(cls, mod, name):
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return getattr(mod, name)
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class CythonCodeWrapper(CodeWrapper):
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"""Wrapper that uses Cython"""
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setup_template = """\
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from setuptools import setup
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from setuptools import Extension
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from Cython.Build import cythonize
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cy_opts = {cythonize_options}
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{np_import}
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ext_mods = [Extension(
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{ext_args},
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include_dirs={include_dirs},
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library_dirs={library_dirs},
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libraries={libraries},
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extra_compile_args={extra_compile_args},
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extra_link_args={extra_link_args}
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)]
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setup(ext_modules=cythonize(ext_mods, **cy_opts))
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"""
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_cythonize_options = {'compiler_directives':{'language_level' : "3"}}
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pyx_imports = (
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"import numpy as np\n"
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"cimport numpy as np\n\n")
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pyx_header = (
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"cdef extern from '{header_file}.h':\n"
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" {prototype}\n\n")
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pyx_func = (
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"def {name}_c({arg_string}):\n"
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"\n"
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"{declarations}"
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"{body}")
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std_compile_flag = '-std=c99'
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def __init__(self, *args, **kwargs):
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"""Instantiates a Cython code wrapper.
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The following optional parameters get passed to ``setuptools.Extension``
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for building the Python extension module. Read its documentation to
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learn more.
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Parameters
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==========
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include_dirs : [list of strings]
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A list of directories to search for C/C++ header files (in Unix
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form for portability).
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library_dirs : [list of strings]
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A list of directories to search for C/C++ libraries at link time.
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libraries : [list of strings]
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A list of library names (not filenames or paths) to link against.
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extra_compile_args : [list of strings]
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Any extra platform- and compiler-specific information to use when
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compiling the source files in 'sources'. For platforms and
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compilers where "command line" makes sense, this is typically a
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list of command-line arguments, but for other platforms it could be
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anything. Note that the attribute ``std_compile_flag`` will be
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appended to this list.
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extra_link_args : [list of strings]
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Any extra platform- and compiler-specific information to use when
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linking object files together to create the extension (or to create
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a new static Python interpreter). Similar interpretation as for
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'extra_compile_args'.
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cythonize_options : [dictionary]
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Keyword arguments passed on to cythonize.
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"""
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self._include_dirs = kwargs.pop('include_dirs', [])
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self._library_dirs = kwargs.pop('library_dirs', [])
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self._libraries = kwargs.pop('libraries', [])
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self._extra_compile_args = kwargs.pop('extra_compile_args', [])
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self._extra_compile_args.append(self.std_compile_flag)
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self._extra_link_args = kwargs.pop('extra_link_args', [])
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self._cythonize_options = kwargs.pop('cythonize_options', self._cythonize_options)
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self._need_numpy = False
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super().__init__(*args, **kwargs)
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@property
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def command(self):
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command = [sys.executable, "setup.py", "build_ext", "--inplace"]
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return command
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def _prepare_files(self, routine, build_dir=os.curdir):
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# NOTE : build_dir is used for testing purposes.
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pyxfilename = self.module_name + '.pyx'
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codefilename = "%s.%s" % (self.filename, self.generator.code_extension)
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# pyx
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with open(os.path.join(build_dir, pyxfilename), 'w') as f:
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self.dump_pyx([routine], f, self.filename)
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# setup.py
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ext_args = [repr(self.module_name), repr([pyxfilename, codefilename])]
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if self._need_numpy:
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np_import = 'import numpy as np\n'
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self._include_dirs.append('np.get_include()')
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else:
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np_import = ''
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with open(os.path.join(build_dir, 'setup.py'), 'w') as f:
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includes = str(self._include_dirs).replace("'np.get_include()'",
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'np.get_include()')
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f.write(self.setup_template.format(
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ext_args=", ".join(ext_args),
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np_import=np_import,
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include_dirs=includes,
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library_dirs=self._library_dirs,
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libraries=self._libraries,
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extra_compile_args=self._extra_compile_args,
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extra_link_args=self._extra_link_args,
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cythonize_options=self._cythonize_options
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))
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@classmethod
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def _get_wrapped_function(cls, mod, name):
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return getattr(mod, name + '_c')
|
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def dump_pyx(self, routines, f, prefix):
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"""Write a Cython file with Python wrappers
|
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This file contains all the definitions of the routines in c code and
|
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refers to the header file.
|
||
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Arguments
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---------
|
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routines
|
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List of Routine instances
|
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f
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File-like object to write the file to
|
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prefix
|
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The filename prefix, used to refer to the proper header file.
|
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Only the basename of the prefix is used.
|
||
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"""
|
||
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headers = []
|
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functions = []
|
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for routine in routines:
|
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prototype = self.generator.get_prototype(routine)
|
||
|
|
|
||
|
|
# C Function Header Import
|
||
|
|
headers.append(self.pyx_header.format(header_file=prefix,
|
||
|
|
prototype=prototype))
|
||
|
|
|
||
|
|
# Partition the C function arguments into categories
|
||
|
|
py_rets, py_args, py_loc, py_inf = self._partition_args(routine.arguments)
|
||
|
|
|
||
|
|
# Function prototype
|
||
|
|
name = routine.name
|
||
|
|
arg_string = ", ".join(self._prototype_arg(arg) for arg in py_args)
|
||
|
|
|
||
|
|
# Local Declarations
|
||
|
|
local_decs = []
|
||
|
|
for arg, val in py_inf.items():
|
||
|
|
proto = self._prototype_arg(arg)
|
||
|
|
mat, ind = [self._string_var(v) for v in val]
|
||
|
|
local_decs.append(" cdef {} = {}.shape[{}]".format(proto, mat, ind))
|
||
|
|
local_decs.extend([" cdef {}".format(self._declare_arg(a)) for a in py_loc])
|
||
|
|
declarations = "\n".join(local_decs)
|
||
|
|
if declarations:
|
||
|
|
declarations = declarations + "\n"
|
||
|
|
|
||
|
|
# Function Body
|
||
|
|
args_c = ", ".join([self._call_arg(a) for a in routine.arguments])
|
||
|
|
rets = ", ".join([self._string_var(r.name) for r in py_rets])
|
||
|
|
if routine.results:
|
||
|
|
body = ' return %s(%s)' % (routine.name, args_c)
|
||
|
|
if rets:
|
||
|
|
body = body + ', ' + rets
|
||
|
|
else:
|
||
|
|
body = ' %s(%s)\n' % (routine.name, args_c)
|
||
|
|
body = body + ' return ' + rets
|
||
|
|
|
||
|
|
functions.append(self.pyx_func.format(name=name, arg_string=arg_string,
|
||
|
|
declarations=declarations, body=body))
|
||
|
|
|
||
|
|
# Write text to file
|
||
|
|
if self._need_numpy:
|
||
|
|
# Only import numpy if required
|
||
|
|
f.write(self.pyx_imports)
|
||
|
|
f.write('\n'.join(headers))
|
||
|
|
f.write('\n'.join(functions))
|
||
|
|
|
||
|
|
def _partition_args(self, args):
|
||
|
|
"""Group function arguments into categories."""
|
||
|
|
py_args = []
|
||
|
|
py_returns = []
|
||
|
|
py_locals = []
|
||
|
|
py_inferred = {}
|
||
|
|
for arg in args:
|
||
|
|
if isinstance(arg, OutputArgument):
|
||
|
|
py_returns.append(arg)
|
||
|
|
py_locals.append(arg)
|
||
|
|
elif isinstance(arg, InOutArgument):
|
||
|
|
py_returns.append(arg)
|
||
|
|
py_args.append(arg)
|
||
|
|
else:
|
||
|
|
py_args.append(arg)
|
||
|
|
# Find arguments that are array dimensions. These can be inferred
|
||
|
|
# locally in the Cython code.
|
||
|
|
if isinstance(arg, (InputArgument, InOutArgument)) and arg.dimensions:
|
||
|
|
dims = [d[1] + 1 for d in arg.dimensions]
|
||
|
|
sym_dims = [(i, d) for (i, d) in enumerate(dims) if
|
||
|
|
isinstance(d, Symbol)]
|
||
|
|
for (i, d) in sym_dims:
|
||
|
|
py_inferred[d] = (arg.name, i)
|
||
|
|
for arg in args:
|
||
|
|
if arg.name in py_inferred:
|
||
|
|
py_inferred[arg] = py_inferred.pop(arg.name)
|
||
|
|
# Filter inferred arguments from py_args
|
||
|
|
py_args = [a for a in py_args if a not in py_inferred]
|
||
|
|
return py_returns, py_args, py_locals, py_inferred
|
||
|
|
|
||
|
|
def _prototype_arg(self, arg):
|
||
|
|
mat_dec = "np.ndarray[{mtype}, ndim={ndim}] {name}"
|
||
|
|
np_types = {'double': 'np.double_t',
|
||
|
|
'int': 'np.int_t'}
|
||
|
|
t = arg.get_datatype('c')
|
||
|
|
if arg.dimensions:
|
||
|
|
self._need_numpy = True
|
||
|
|
ndim = len(arg.dimensions)
|
||
|
|
mtype = np_types[t]
|
||
|
|
return mat_dec.format(mtype=mtype, ndim=ndim, name=self._string_var(arg.name))
|
||
|
|
else:
|
||
|
|
return "%s %s" % (t, self._string_var(arg.name))
|
||
|
|
|
||
|
|
def _declare_arg(self, arg):
|
||
|
|
proto = self._prototype_arg(arg)
|
||
|
|
if arg.dimensions:
|
||
|
|
shape = '(' + ','.join(self._string_var(i[1] + 1) for i in arg.dimensions) + ')'
|
||
|
|
return proto + " = np.empty({shape})".format(shape=shape)
|
||
|
|
else:
|
||
|
|
return proto + " = 0"
|
||
|
|
|
||
|
|
def _call_arg(self, arg):
|
||
|
|
if arg.dimensions:
|
||
|
|
t = arg.get_datatype('c')
|
||
|
|
return "<{}*> {}.data".format(t, self._string_var(arg.name))
|
||
|
|
elif isinstance(arg, ResultBase):
|
||
|
|
return "&{}".format(self._string_var(arg.name))
|
||
|
|
else:
|
||
|
|
return self._string_var(arg.name)
|
||
|
|
|
||
|
|
def _string_var(self, var):
|
||
|
|
printer = self.generator.printer.doprint
|
||
|
|
return printer(var)
|
||
|
|
|
||
|
|
|
||
|
|
class F2PyCodeWrapper(CodeWrapper):
|
||
|
|
"""Wrapper that uses f2py"""
|
||
|
|
|
||
|
|
def __init__(self, *args, **kwargs):
|
||
|
|
|
||
|
|
ext_keys = ['include_dirs', 'library_dirs', 'libraries',
|
||
|
|
'extra_compile_args', 'extra_link_args']
|
||
|
|
msg = ('The compilation option kwarg {} is not supported with the f2py '
|
||
|
|
'backend.')
|
||
|
|
|
||
|
|
for k in ext_keys:
|
||
|
|
if k in kwargs.keys():
|
||
|
|
warn(msg.format(k))
|
||
|
|
kwargs.pop(k, None)
|
||
|
|
|
||
|
|
super().__init__(*args, **kwargs)
|
||
|
|
|
||
|
|
@property
|
||
|
|
def command(self):
|
||
|
|
filename = self.filename + '.' + self.generator.code_extension
|
||
|
|
args = ['-c', '-m', self.module_name, filename]
|
||
|
|
command = [sys.executable, "-c", "import numpy.f2py as f2py2e;f2py2e.main()"]+args
|
||
|
|
return command
|
||
|
|
|
||
|
|
def _prepare_files(self, routine):
|
||
|
|
pass
|
||
|
|
|
||
|
|
@classmethod
|
||
|
|
def _get_wrapped_function(cls, mod, name):
|
||
|
|
return getattr(mod, name)
|
||
|
|
|
||
|
|
|
||
|
|
# Here we define a lookup of backends -> tuples of languages. For now, each
|
||
|
|
# tuple is of length 1, but if a backend supports more than one language,
|
||
|
|
# the most preferable language is listed first.
|
||
|
|
_lang_lookup = {'CYTHON': ('C99', 'C89', 'C'),
|
||
|
|
'F2PY': ('F95',),
|
||
|
|
'NUMPY': ('C99', 'C89', 'C'),
|
||
|
|
'DUMMY': ('F95',)} # Dummy here just for testing
|
||
|
|
|
||
|
|
|
||
|
|
def _infer_language(backend):
|
||
|
|
"""For a given backend, return the top choice of language"""
|
||
|
|
langs = _lang_lookup.get(backend.upper(), False)
|
||
|
|
if not langs:
|
||
|
|
raise ValueError("Unrecognized backend: " + backend)
|
||
|
|
return langs[0]
|
||
|
|
|
||
|
|
|
||
|
|
def _validate_backend_language(backend, language):
|
||
|
|
"""Throws error if backend and language are incompatible"""
|
||
|
|
langs = _lang_lookup.get(backend.upper(), False)
|
||
|
|
if not langs:
|
||
|
|
raise ValueError("Unrecognized backend: " + backend)
|
||
|
|
if language.upper() not in langs:
|
||
|
|
raise ValueError(("Backend {} and language {} are "
|
||
|
|
"incompatible").format(backend, language))
|
||
|
|
|
||
|
|
|
||
|
|
@cacheit
|
||
|
|
@doctest_depends_on(exe=('f2py', 'gfortran'), modules=('numpy',))
|
||
|
|
def autowrap(expr, language=None, backend='f2py', tempdir=None, args=None,
|
||
|
|
flags=None, verbose=False, helpers=None, code_gen=None, **kwargs):
|
||
|
|
"""Generates Python callable binaries based on the math expression.
|
||
|
|
|
||
|
|
Parameters
|
||
|
|
==========
|
||
|
|
|
||
|
|
expr
|
||
|
|
The SymPy expression that should be wrapped as a binary routine.
|
||
|
|
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 'f2py' [default],
|
||
|
|
or 'cython'.
|
||
|
|
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.
|
||
|
|
args : iterable, optional
|
||
|
|
An ordered iterable of symbols. Specifies the argument sequence for the
|
||
|
|
function.
|
||
|
|
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 : 3-tuple or iterable of 3-tuples, optional
|
||
|
|
Used to define auxiliary expressions needed for the main expr. If the
|
||
|
|
main expression needs to call a specialized function it should be
|
||
|
|
passed in via ``helpers``. Autowrap will then make sure that the
|
||
|
|
compiled main expression can link to the helper routine. Items should
|
||
|
|
be 3-tuples with (<function_name>, <sympy_expression>,
|
||
|
|
<argument_tuple>). It is mandatory to supply an argument sequence to
|
||
|
|
helper routines.
|
||
|
|
code_gen : CodeGen instance
|
||
|
|
An instance of a CodeGen subclass. Overrides ``language``.
|
||
|
|
include_dirs : [string]
|
||
|
|
A list of directories to search for C/C++ header files (in Unix form
|
||
|
|
for portability).
|
||
|
|
library_dirs : [string]
|
||
|
|
A list of directories to search for C/C++ libraries at link time.
|
||
|
|
libraries : [string]
|
||
|
|
A list of library names (not filenames or paths) to link against.
|
||
|
|
extra_compile_args : [string]
|
||
|
|
Any extra platform- and compiler-specific information to use when
|
||
|
|
compiling the source files in 'sources'. For platforms and compilers
|
||
|
|
where "command line" makes sense, this is typically a list of
|
||
|
|
command-line arguments, but for other platforms it could be anything.
|
||
|
|
extra_link_args : [string]
|
||
|
|
Any extra platform- and compiler-specific information to use when
|
||
|
|
linking object files together to create the extension (or to create a
|
||
|
|
new static Python interpreter). Similar interpretation as for
|
||
|
|
'extra_compile_args'.
|
||
|
|
|
||
|
|
Examples
|
||
|
|
========
|
||
|
|
|
||
|
|
>>> from sympy.abc import x, y, z
|
||
|
|
>>> from sympy.utilities.autowrap import autowrap
|
||
|
|
>>> expr = ((x - y + z)**(13)).expand()
|
||
|
|
>>> binary_func = autowrap(expr)
|
||
|
|
>>> binary_func(1, 4, 2)
|
||
|
|
-1.0
|
||
|
|
|
||
|
|
"""
|
||
|
|
if language:
|
||
|
|
if not isinstance(language, type):
|
||
|
|
_validate_backend_language(backend, language)
|
||
|
|
else:
|
||
|
|
language = _infer_language(backend)
|
||
|
|
|
||
|
|
# two cases 1) helpers is an iterable of 3-tuples and 2) helpers is a
|
||
|
|
# 3-tuple
|
||
|
|
if iterable(helpers) and len(helpers) != 0 and iterable(helpers[0]):
|
||
|
|
helpers = helpers if helpers else ()
|
||
|
|
else:
|
||
|
|
helpers = [helpers] if helpers else ()
|
||
|
|
args = list(args) if iterable(args, exclude=set) else args
|
||
|
|
|
||
|
|
if code_gen is None:
|
||
|
|
code_gen = get_code_generator(language, "autowrap")
|
||
|
|
|
||
|
|
CodeWrapperClass = {
|
||
|
|
'F2PY': F2PyCodeWrapper,
|
||
|
|
'CYTHON': CythonCodeWrapper,
|
||
|
|
'DUMMY': DummyWrapper
|
||
|
|
}[backend.upper()]
|
||
|
|
code_wrapper = CodeWrapperClass(code_gen, tempdir, flags if flags else (),
|
||
|
|
verbose, **kwargs)
|
||
|
|
|
||
|
|
helps = []
|
||
|
|
for name_h, expr_h, args_h in helpers:
|
||
|
|
helps.append(code_gen.routine(name_h, expr_h, args_h))
|
||
|
|
|
||
|
|
for name_h, expr_h, args_h in helpers:
|
||
|
|
if expr.has(expr_h):
|
||
|
|
name_h = binary_function(name_h, expr_h, backend='dummy')
|
||
|
|
expr = expr.subs(expr_h, name_h(*args_h))
|
||
|
|
try:
|
||
|
|
routine = code_gen.routine('autofunc', expr, args)
|
||
|
|
except CodeGenArgumentListError as e:
|
||
|
|
# if all missing arguments are for pure output, we simply attach them
|
||
|
|
# at the end and try again, because the wrappers will silently convert
|
||
|
|
# them to return values anyway.
|
||
|
|
new_args = []
|
||
|
|
for missing in e.missing_args:
|
||
|
|
if not isinstance(missing, OutputArgument):
|
||
|
|
raise
|
||
|
|
new_args.append(missing.name)
|
||
|
|
routine = code_gen.routine('autofunc', expr, args + new_args)
|
||
|
|
|
||
|
|
return code_wrapper.wrap_code(routine, helpers=helps)
|
||
|
|
|
||
|
|
|
||
|
|
@doctest_depends_on(exe=('f2py', 'gfortran'), modules=('numpy',))
|
||
|
|
def binary_function(symfunc, expr, **kwargs):
|
||
|
|
"""Returns a SymPy function with expr as binary implementation
|
||
|
|
|
||
|
|
This is a convenience function that automates the steps needed to
|
||
|
|
autowrap the SymPy expression and attaching it to a Function object
|
||
|
|
with implemented_function().
|
||
|
|
|
||
|
|
Parameters
|
||
|
|
==========
|
||
|
|
|
||
|
|
symfunc : SymPy Function
|
||
|
|
The function to bind the callable to.
|
||
|
|
expr : SymPy Expression
|
||
|
|
The expression used to generate the function.
|
||
|
|
kwargs : dict
|
||
|
|
Any kwargs accepted by autowrap.
|
||
|
|
|
||
|
|
Examples
|
||
|
|
========
|
||
|
|
|
||
|
|
>>> from sympy.abc import x, y
|
||
|
|
>>> from sympy.utilities.autowrap import binary_function
|
||
|
|
>>> expr = ((x - y)**(25)).expand()
|
||
|
|
>>> f = binary_function('f', expr)
|
||
|
|
>>> type(f)
|
||
|
|
<class 'sympy.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)
|
||
|
|
|
||
|
|
#################################################################
|
||
|
|
# UFUNCIFY #
|
||
|
|
#################################################################
|
||
|
|
|
||
|
|
_ufunc_top = Template("""\
|
||
|
|
#include "Python.h"
|
||
|
|
#include "math.h"
|
||
|
|
#include "numpy/ndarraytypes.h"
|
||
|
|
#include "numpy/ufuncobject.h"
|
||
|
|
#include "numpy/halffloat.h"
|
||
|
|
#include ${include_file}
|
||
|
|
|
||
|
|
static PyMethodDef ${module}Methods[] = {
|
||
|
|
{NULL, NULL, 0, NULL}
|
||
|
|
};""")
|
||
|
|
|
||
|
|
_ufunc_outcalls = Template("*((double *)out${outnum}) = ${funcname}(${call_args});")
|
||
|
|
|
||
|
|
_ufunc_body = Template("""\
|
||
|
|
static void ${funcname}_ufunc(char **args, npy_intp *dimensions, npy_intp* steps, void* data)
|
||
|
|
{
|
||
|
|
npy_intp i;
|
||
|
|
npy_intp n = dimensions[0];
|
||
|
|
${declare_args}
|
||
|
|
${declare_steps}
|
||
|
|
for (i = 0; i < n; i++) {
|
||
|
|
${outcalls}
|
||
|
|
${step_increments}
|
||
|
|
}
|
||
|
|
}
|
||
|
|
PyUFuncGenericFunction ${funcname}_funcs[1] = {&${funcname}_ufunc};
|
||
|
|
static char ${funcname}_types[${n_types}] = ${types}
|
||
|
|
static void *${funcname}_data[1] = {NULL};""")
|
||
|
|
|
||
|
|
_ufunc_bottom = Template("""\
|
||
|
|
#if PY_VERSION_HEX >= 0x03000000
|
||
|
|
static struct PyModuleDef moduledef = {
|
||
|
|
PyModuleDef_HEAD_INIT,
|
||
|
|
"${module}",
|
||
|
|
NULL,
|
||
|
|
-1,
|
||
|
|
${module}Methods,
|
||
|
|
NULL,
|
||
|
|
NULL,
|
||
|
|
NULL,
|
||
|
|
NULL
|
||
|
|
};
|
||
|
|
|
||
|
|
PyMODINIT_FUNC PyInit_${module}(void)
|
||
|
|
{
|
||
|
|
PyObject *m, *d;
|
||
|
|
${function_creation}
|
||
|
|
m = PyModule_Create(&moduledef);
|
||
|
|
if (!m) {
|
||
|
|
return NULL;
|
||
|
|
}
|
||
|
|
import_array();
|
||
|
|
import_umath();
|
||
|
|
d = PyModule_GetDict(m);
|
||
|
|
${ufunc_init}
|
||
|
|
return m;
|
||
|
|
}
|
||
|
|
#else
|
||
|
|
PyMODINIT_FUNC init${module}(void)
|
||
|
|
{
|
||
|
|
PyObject *m, *d;
|
||
|
|
${function_creation}
|
||
|
|
m = Py_InitModule("${module}", ${module}Methods);
|
||
|
|
if (m == NULL) {
|
||
|
|
return;
|
||
|
|
}
|
||
|
|
import_array();
|
||
|
|
import_umath();
|
||
|
|
d = PyModule_GetDict(m);
|
||
|
|
${ufunc_init}
|
||
|
|
}
|
||
|
|
#endif\
|
||
|
|
""")
|
||
|
|
|
||
|
|
_ufunc_init_form = Template("""\
|
||
|
|
ufunc${ind} = PyUFunc_FromFuncAndData(${funcname}_funcs, ${funcname}_data, ${funcname}_types, 1, ${n_in}, ${n_out},
|
||
|
|
PyUFunc_None, "${module}", ${docstring}, 0);
|
||
|
|
PyDict_SetItemString(d, "${funcname}", ufunc${ind});
|
||
|
|
Py_DECREF(ufunc${ind});""")
|
||
|
|
|
||
|
|
_ufunc_setup = Template("""\
|
||
|
|
from setuptools.extension import Extension
|
||
|
|
from setuptools import setup
|
||
|
|
|
||
|
|
from numpy import get_include
|
||
|
|
|
||
|
|
if __name__ == "__main__":
|
||
|
|
setup(ext_modules=[
|
||
|
|
Extension('${module}',
|
||
|
|
sources=['${module}.c', '${filename}.c'],
|
||
|
|
include_dirs=[get_include()])])
|
||
|
|
""")
|
||
|
|
|
||
|
|
|
||
|
|
class UfuncifyCodeWrapper(CodeWrapper):
|
||
|
|
"""Wrapper for Ufuncify"""
|
||
|
|
|
||
|
|
def __init__(self, *args, **kwargs):
|
||
|
|
|
||
|
|
ext_keys = ['include_dirs', 'library_dirs', 'libraries',
|
||
|
|
'extra_compile_args', 'extra_link_args']
|
||
|
|
msg = ('The compilation option kwarg {} is not supported with the numpy'
|
||
|
|
' backend.')
|
||
|
|
|
||
|
|
for k in ext_keys:
|
||
|
|
if k in kwargs.keys():
|
||
|
|
warn(msg.format(k))
|
||
|
|
kwargs.pop(k, None)
|
||
|
|
|
||
|
|
super().__init__(*args, **kwargs)
|
||
|
|
|
||
|
|
@property
|
||
|
|
def command(self):
|
||
|
|
command = [sys.executable, "setup.py", "build_ext", "--inplace"]
|
||
|
|
return command
|
||
|
|
|
||
|
|
def wrap_code(self, routines, helpers=None):
|
||
|
|
# This routine overrides CodeWrapper because we can't assume funcname == routines[0].name
|
||
|
|
# Therefore we have to break the CodeWrapper private API.
|
||
|
|
# There isn't an obvious way to extend multi-expr support to
|
||
|
|
# the other autowrap backends, so we limit this change to ufuncify.
|
||
|
|
helpers = helpers if helpers is not None else []
|
||
|
|
# We just need a consistent name
|
||
|
|
funcname = 'wrapped_' + str(id(routines) + id(helpers))
|
||
|
|
|
||
|
|
workdir = self.filepath or tempfile.mkdtemp("_sympy_compile")
|
||
|
|
if not os.access(workdir, os.F_OK):
|
||
|
|
os.mkdir(workdir)
|
||
|
|
oldwork = os.getcwd()
|
||
|
|
os.chdir(workdir)
|
||
|
|
try:
|
||
|
|
sys.path.append(workdir)
|
||
|
|
self._generate_code(routines, helpers)
|
||
|
|
self._prepare_files(routines, funcname)
|
||
|
|
self._process_files(routines)
|
||
|
|
mod = __import__(self.module_name)
|
||
|
|
finally:
|
||
|
|
sys.path.remove(workdir)
|
||
|
|
CodeWrapper._module_counter += 1
|
||
|
|
os.chdir(oldwork)
|
||
|
|
if not self.filepath:
|
||
|
|
try:
|
||
|
|
shutil.rmtree(workdir)
|
||
|
|
except OSError:
|
||
|
|
# Could be some issues on Windows
|
||
|
|
pass
|
||
|
|
|
||
|
|
return self._get_wrapped_function(mod, funcname)
|
||
|
|
|
||
|
|
def _generate_code(self, main_routines, helper_routines):
|
||
|
|
all_routines = main_routines + helper_routines
|
||
|
|
self.generator.write(
|
||
|
|
all_routines, self.filename, True, self.include_header,
|
||
|
|
self.include_empty)
|
||
|
|
|
||
|
|
def _prepare_files(self, routines, funcname):
|
||
|
|
|
||
|
|
# C
|
||
|
|
codefilename = self.module_name + '.c'
|
||
|
|
with open(codefilename, 'w') as f:
|
||
|
|
self.dump_c(routines, f, self.filename, funcname=funcname)
|
||
|
|
|
||
|
|
# setup.py
|
||
|
|
with open('setup.py', 'w') as f:
|
||
|
|
self.dump_setup(f)
|
||
|
|
|
||
|
|
@classmethod
|
||
|
|
def _get_wrapped_function(cls, mod, name):
|
||
|
|
return getattr(mod, name)
|
||
|
|
|
||
|
|
def dump_setup(self, f):
|
||
|
|
setup = _ufunc_setup.substitute(module=self.module_name,
|
||
|
|
filename=self.filename)
|
||
|
|
f.write(setup)
|
||
|
|
|
||
|
|
def dump_c(self, routines, f, prefix, funcname=None):
|
||
|
|
"""Write a C file with Python wrappers
|
||
|
|
|
||
|
|
This file contains all the definitions of the routines in c code.
|
||
|
|
|
||
|
|
Arguments
|
||
|
|
---------
|
||
|
|
routines
|
||
|
|
List of Routine instances
|
||
|
|
f
|
||
|
|
File-like object to write the file to
|
||
|
|
prefix
|
||
|
|
The filename prefix, used to name the imported module.
|
||
|
|
funcname
|
||
|
|
Name of the main function to be returned.
|
||
|
|
"""
|
||
|
|
if funcname is None:
|
||
|
|
if len(routines) == 1:
|
||
|
|
funcname = routines[0].name
|
||
|
|
else:
|
||
|
|
msg = 'funcname must be specified for multiple output routines'
|
||
|
|
raise ValueError(msg)
|
||
|
|
functions = []
|
||
|
|
function_creation = []
|
||
|
|
ufunc_init = []
|
||
|
|
module = self.module_name
|
||
|
|
include_file = "\"{}.h\"".format(prefix)
|
||
|
|
top = _ufunc_top.substitute(include_file=include_file, module=module)
|
||
|
|
|
||
|
|
name = funcname
|
||
|
|
|
||
|
|
# Partition the C function arguments into categories
|
||
|
|
# Here we assume all routines accept the same arguments
|
||
|
|
r_index = 0
|
||
|
|
py_in, _ = self._partition_args(routines[0].arguments)
|
||
|
|
n_in = len(py_in)
|
||
|
|
n_out = len(routines)
|
||
|
|
|
||
|
|
# Declare Args
|
||
|
|
form = "char *{0}{1} = args[{2}];"
|
||
|
|
arg_decs = [form.format('in', i, i) for i in range(n_in)]
|
||
|
|
arg_decs.extend([form.format('out', i, i+n_in) for i in range(n_out)])
|
||
|
|
declare_args = '\n '.join(arg_decs)
|
||
|
|
|
||
|
|
# Declare Steps
|
||
|
|
form = "npy_intp {0}{1}_step = steps[{2}];"
|
||
|
|
step_decs = [form.format('in', i, i) for i in range(n_in)]
|
||
|
|
step_decs.extend([form.format('out', i, i+n_in) for i in range(n_out)])
|
||
|
|
declare_steps = '\n '.join(step_decs)
|
||
|
|
|
||
|
|
# Call Args
|
||
|
|
form = "*(double *)in{0}"
|
||
|
|
call_args = ', '.join([form.format(a) for a in range(n_in)])
|
||
|
|
|
||
|
|
# Step Increments
|
||
|
|
form = "{0}{1} += {0}{1}_step;"
|
||
|
|
step_incs = [form.format('in', i) for i in range(n_in)]
|
||
|
|
step_incs.extend([form.format('out', i, i) for i in range(n_out)])
|
||
|
|
step_increments = '\n '.join(step_incs)
|
||
|
|
|
||
|
|
# Types
|
||
|
|
n_types = n_in + n_out
|
||
|
|
types = "{" + ', '.join(["NPY_DOUBLE"]*n_types) + "};"
|
||
|
|
|
||
|
|
# Docstring
|
||
|
|
docstring = '"Created in SymPy with Ufuncify"'
|
||
|
|
|
||
|
|
# Function Creation
|
||
|
|
function_creation.append("PyObject *ufunc{};".format(r_index))
|
||
|
|
|
||
|
|
# Ufunc initialization
|
||
|
|
init_form = _ufunc_init_form.substitute(module=module,
|
||
|
|
funcname=name,
|
||
|
|
docstring=docstring,
|
||
|
|
n_in=n_in, n_out=n_out,
|
||
|
|
ind=r_index)
|
||
|
|
ufunc_init.append(init_form)
|
||
|
|
|
||
|
|
outcalls = [_ufunc_outcalls.substitute(
|
||
|
|
outnum=i, call_args=call_args, funcname=routines[i].name) for i in
|
||
|
|
range(n_out)]
|
||
|
|
|
||
|
|
body = _ufunc_body.substitute(module=module, funcname=name,
|
||
|
|
declare_args=declare_args,
|
||
|
|
declare_steps=declare_steps,
|
||
|
|
call_args=call_args,
|
||
|
|
step_increments=step_increments,
|
||
|
|
n_types=n_types, types=types,
|
||
|
|
outcalls='\n '.join(outcalls))
|
||
|
|
functions.append(body)
|
||
|
|
|
||
|
|
body = '\n\n'.join(functions)
|
||
|
|
ufunc_init = '\n '.join(ufunc_init)
|
||
|
|
function_creation = '\n '.join(function_creation)
|
||
|
|
bottom = _ufunc_bottom.substitute(module=module,
|
||
|
|
ufunc_init=ufunc_init,
|
||
|
|
function_creation=function_creation)
|
||
|
|
text = [top, body, bottom]
|
||
|
|
f.write('\n\n'.join(text))
|
||
|
|
|
||
|
|
def _partition_args(self, args):
|
||
|
|
"""Group function arguments into categories."""
|
||
|
|
py_in = []
|
||
|
|
py_out = []
|
||
|
|
for arg in args:
|
||
|
|
if isinstance(arg, OutputArgument):
|
||
|
|
py_out.append(arg)
|
||
|
|
elif isinstance(arg, InOutArgument):
|
||
|
|
raise ValueError("Ufuncify doesn't support InOutArguments")
|
||
|
|
else:
|
||
|
|
py_in.append(arg)
|
||
|
|
return py_in, py_out
|
||
|
|
|
||
|
|
|
||
|
|
@cacheit
|
||
|
|
@doctest_depends_on(exe=('f2py', 'gfortran', 'gcc'), modules=('numpy',))
|
||
|
|
def ufuncify(args, expr, language=None, backend='numpy', tempdir=None,
|
||
|
|
flags=None, verbose=False, helpers=None, **kwargs):
|
||
|
|
"""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 SymPy 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 auxiliary 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>, <sympy_expression>,
|
||
|
|
<arguments>). It is mandatory to supply an argument sequence to
|
||
|
|
helper routines.
|
||
|
|
kwargs : dict
|
||
|
|
These kwargs will be passed to autowrap if the `f2py` or `cython`
|
||
|
|
backend is used and ignored if the `numpy` backend is used.
|
||
|
|
|
||
|
|
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] https://numpy.org/doc/stable/reference/ufuncs.html
|
||
|
|
|
||
|
|
Examples
|
||
|
|
========
|
||
|
|
|
||
|
|
>>> from sympy.utilities.autowrap import ufuncify
|
||
|
|
>>> from sympy.abc import x, y
|
||
|
|
>>> import numpy as np
|
||
|
|
>>> f = ufuncify((x, y), y + x**2)
|
||
|
|
>>> type(f)
|
||
|
|
<class 'numpy.ufunc'>
|
||
|
|
>>> 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)
|
||
|
|
array([ 3.])
|
||
|
|
>>> f_fortran(np.array([1, 2, 3]), np.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) # doctest: +ELLIPSIS
|
||
|
|
Traceback (most recent call last):
|
||
|
|
...
|
||
|
|
TypeError: Argument '_x' has incorrect type (expected numpy.ndarray, got int)
|
||
|
|
>>> f_cython(np.array([1.0]), np.array([2.0]))
|
||
|
|
array([ 3.])
|
||
|
|
|
||
|
|
"""
|
||
|
|
|
||
|
|
if isinstance(args, 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':
|
||
|
|
# maxargs is set by numpy compile-time constant NPY_MAXARGS
|
||
|
|
# If a future version of numpy modifies or removes this restriction
|
||
|
|
# this variable should be changed or removed
|
||
|
|
maxargs = 32
|
||
|
|
helps = []
|
||
|
|
for name, expr, args in helpers:
|
||
|
|
helps.append(make_routine(name, expr, args))
|
||
|
|
code_wrapper = UfuncifyCodeWrapper(C99CodeGen("ufuncify"), tempdir,
|
||
|
|
flags, verbose)
|
||
|
|
if not isinstance(expr, (list, tuple)):
|
||
|
|
expr = [expr]
|
||
|
|
if len(expr) == 0:
|
||
|
|
raise ValueError('Expression iterable has zero length')
|
||
|
|
if len(expr) + len(args) > maxargs:
|
||
|
|
msg = ('Cannot create ufunc with more than {0} total arguments: '
|
||
|
|
'got {1} in, {2} out')
|
||
|
|
raise ValueError(msg.format(maxargs, len(args), len(expr)))
|
||
|
|
routines = [make_routine('autofunc{}'.format(idx), exprx, args) for
|
||
|
|
idx, exprx in enumerate(expr)]
|
||
|
|
return code_wrapper.wrap_code(routines, helpers=helps)
|
||
|
|
else:
|
||
|
|
# Dummies are used for all added expressions to prevent name clashes
|
||
|
|
# within the original expression.
|
||
|
|
y = IndexedBase(Dummy('y'))
|
||
|
|
m = Dummy('m', integer=True)
|
||
|
|
i = Idx(Dummy('i', integer=True), m)
|
||
|
|
f_dummy = Dummy('f')
|
||
|
|
f = implemented_function('%s_%d' % (f_dummy.name, f_dummy.dummy_index), 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, args, flags, verbose, helpers, **kwargs)
|