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Diffstat (limited to 'doc/pyrex/numpyx.pyx')
| -rw-r--r-- | doc/pyrex/numpyx.pyx | 101 |
1 files changed, 0 insertions, 101 deletions
diff --git a/doc/pyrex/numpyx.pyx b/doc/pyrex/numpyx.pyx deleted file mode 100644 index 068d251f6..000000000 --- a/doc/pyrex/numpyx.pyx +++ /dev/null @@ -1,101 +0,0 @@ -# -*- Mode: Python -*- Not really, but close enough -"""WARNING: this code is deprecated and slated for removal soon. See the -doc/cython directory for the replacement, which uses Cython (the actively -maintained version of Pyrex). -""" - -cimport c_python -cimport c_numpy -import numpy - -# Numpy must be initialized -c_numpy.import_array() - -def print_array_info(c_numpy.ndarray arr): - cdef int i - - print '-='*10 - print 'printing array info for ndarray at 0x%0lx'%(<c_python.Py_intptr_t>arr,) - print 'print number of dimensions:',arr.nd - print 'address of strides: 0x%0lx'%(<c_python.Py_intptr_t>arr.strides,) - print 'strides:' - for i from 0<=i<arr.nd: - # print each stride - print ' stride %d:'%i,<c_python.Py_intptr_t>arr.strides[i] - print 'memory dump:' - print_elements( arr.data, arr.strides, arr.dimensions, - arr.nd, sizeof(double), arr.dtype ) - print '-='*10 - print - -cdef print_elements(char *data, - c_python.Py_intptr_t* strides, - c_python.Py_intptr_t* dimensions, - int nd, - int elsize, - object dtype): - cdef c_python.Py_intptr_t i,j - cdef void* elptr - - if dtype not in [numpy.dtype(numpy.object_), - numpy.dtype(numpy.float64)]: - print ' print_elements() not (yet) implemented for dtype %s'%dtype.name - return - - if nd ==0: - if dtype==numpy.dtype(numpy.object_): - elptr = (<void**>data)[0] #[0] dereferences pointer in Pyrex - print ' ',<object>elptr - elif dtype==numpy.dtype(numpy.float64): - print ' ',(<double*>data)[0] - elif nd == 1: - for i from 0<=i<dimensions[0]: - if dtype==numpy.dtype(numpy.object_): - elptr = (<void**>data)[0] - print ' ',<object>elptr - elif dtype==numpy.dtype(numpy.float64): - print ' ',(<double*>data)[0] - data = data + strides[0] - else: - for i from 0<=i<dimensions[0]: - print_elements(data, strides+1, dimensions+1, nd-1, elsize, dtype) - data = data + strides[0] - -def test_methods(c_numpy.ndarray arr): - """Test a few attribute accesses for an array. - - This illustrates how the pyrex-visible object is in practice a strange - hybrid of the C PyArrayObject struct and the python object. Some - properties (like .nd) are visible here but not in python, while others - like flags behave very differently: in python flags appears as a separate, - object while here we see the raw int holding the bit pattern. - - This makes sense when we think of how pyrex resolves arr.foo: if foo is - listed as a field in the c_numpy.ndarray struct description, it will be - directly accessed as a C variable without going through Python at all. - This is why for arr.flags, we see the actual int which holds all the flags - as bit fields. However, for any other attribute not listed in the struct, - it simply forwards the attribute lookup to python at runtime, just like - python would (which means that AttributeError can be raised for - non-existent attributes, for example).""" - - print 'arr.any() :',arr.any() - print 'arr.nd :',arr.nd - print 'arr.flags :',arr.flags - -def test(): - """this function is pure Python""" - arr1 = numpy.array(-1e-30,dtype=numpy.float64) - arr2 = numpy.array([1.0,2.0,3.0],dtype=numpy.float64) - - arr3 = numpy.arange(9,dtype=numpy.float64) - arr3.shape = 3,3 - - four = 4 - arr4 = numpy.array(['one','two',3,four],dtype=numpy.object_) - - arr5 = numpy.array([1,2,3]) # int types not (yet) supported by print_elements - - for arr in [arr1,arr2,arr3,arr4,arr5]: - print_array_info(arr) - |