ufunc | --- Lib | --- Src
For a real extension, the top level directory should probably be named after the extension rather than as it is named here, i.e. foo rather than ufunc.
""" This setup demonstrates how to use the numarray code generation facilities to define additional ufuncs at the user level. Universal functions apply operators or C-functions elementwise to all of the elements of an array or pair of arrays. This setup generates code defining three universal functions which are installed as the numarray.foo package: Cos, bessel, and bar. The ufuncs are used like this: >>> import numarray as na >>> import numarray.foo as foo >>> a = na.array([1,2,3,4], type='Int32') >>> foo.Cos(a) array([ 0.54030228, -0.41614684, -0.9899925 , -0.65364361 ], type=Float32) Note that since a is an Int32 array, Cos(a) first does blockwise conversion of a to Float32 before calling the cosine library function. """ import distutils, os from distutils.core import setup from numarray.numarrayext import NumarrayExtension from numarray.codegenerator import UfuncModule, make_stub # ====================================================================== # # Generate the C-code for the numarray.foo._foo extension: # m = UfuncModule("_foo") # Inline the code for a couple C functions to be turned into ufuncs. # This method lets you define your function here in the setup.py. An # alternate approach would be to link with a libarary or additional C # module. m.add_code(""" static double c_bessel(double x, double y) { double x2=x*x, y2=y*y, diff=x2-y2; return diff*diff/(x2+y2); } static UInt8 c_bar(UInt32 x ) { return (x >> 24) & 0xFF; } """)
# Method add_ufunc() defines the name of a ufunc, it's corresponding C # function which is applied element-wise to all elements of an array, # The arity of the ufunc (unary or binary only), and the I/O type # signatures which are directly supported by the ufunc. Binary Ufunc # "bessel" is implemented by the inline function "c_bessel" from the # add_code() call above. m.add_ufunc("bessel", "c_bessel", 2, [('Float32', 'Float32'), ('Float64', 'Float64')]) # Unary Ufunc "bar" only supports one builtin type signature: # UInt32-->UInt8. Other types are blockwise converted by the ufunc # machinery to UInt32 before "c_bar" is called. m.add_ufunc("bar", "c_bar", 1, [('UInt32','UInt8')]) # Unary Ufunc "cos" is implemented by the C standard library function # "cos". Given a Float32 array, it returns a Float32 array. Given a # Float64 array, it returns a Float64 array. For other arrays, # transparent conversion to one of the supported input types is performed # by the ufunc machinery. m.add_ufunc("cos", "cos", 1, [('Float32', 'Float32'), ('Float64', 'Float64')]) # The generate() method writes out the complete extension module to the # specified C file. m.generate("Src/_foo.c") # ====================================================================== # Create foo's __init__.py for defining UFuncs corresponding to CFuncs # in _foo. make_stub() emits boiler-plate which makes your extension # a package. The __init__ file imports all the public symbols from # C extension _foo making them visible as numarray.foo. make_stub("Lib/__init__", "_foo") # ====================================================================== # # Standard distutils setup for the generated code. # setup(name = "foo", version = "0.1", maintainer = "Todd Miller", maintainer_email = "jmiller@stsci.edu", description = "foo universal functions for numarray", url = "http://www.stsci.edu/projects/foo/", packages = ["numarray.foo"], package_dir = { "numarray.foo":"Lib" }, ext_modules = [ NumarrayExtension( 'numarray.foo._foo', ['Src/_foo.c'], # libraries = ['ttf'], # include_dirs = ['include'], # library_dirs = ['lib'] ) ] )
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