> Hi, > > Is it possible to have a view of a float64 array that is itself float32? > So that: > >>>> A = np.arange(5, dtype='d') >>>> A.view(dtype='f') > > would return a size 5 float32 array looking at A's data?
I think not. The memory layout of a 32-bit IEEE float is not a subset of that of a 64-bit float -- see e.g. the first table in: http://steve.hollasch.net/cgindex/coding/ieeefloat.html This would work for int8/int16 or other int types (so long as the number doesn't exceed the range of the smaller type), but AFAIK not floats. Note how the subset relationship works for the int8/int16 case, but not float32/float64: str(numpy.array(100,dtype=numpy.int8).data) 'd' str(numpy.array(100,dtype=numpy.int16).data) 'd\x00' str(numpy.array(-100,dtype=numpy.int16).data) '\x9c\xff' str(numpy.array(-100,dtype=numpy.int8).data) '\x9c' str(numpy.array(100,dtype=numpy.float32).data) '\x00\x00\xc8B' str(numpy.array(100,dtype=numpy.float64).data) '\x00\x00\x00\x00\x00\x00Y@' Zach _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
