[Numpy-discussion] Numeric 2 : Arrays and Floating Point in C#
frohne at gci.net
Thu Feb 15 14:22:08 EST 2001
----- Original Message -----
From: "Paul F. Dubois" <paul at pfdubois.com>
To: "Ivan Frohne" <frohne at gci.net>; <Numpy-discussion at lists.sourceforge.net>
Sent: Wednesday, February 14, 2001 19:22
Subject: RE: [Numpy-discussion] Numeric 2 : Arrays and Floating Point in C#
> Thank you for pointing this out. I have two questions.
> 1. Note that we could not reach a consensus about using C++ for future
> versions, even though C++ is quite aged by now, because of complaints that
> acceptable (ie, standard-conforming) compilers were not available (a) for
> free and (b) on all platforms. When would C# likely be able to meet these
> 2. Java flunked the Kindergarten test -- it did not like to play with
> others. Will C# pass it? If I want to use many of the available
> I have to be able to call C and Fortran. The fact that Python itself is
> implemented in a given language is of almost no value in and of itself.
> Nobody is going to rewrite Linpack and Spherepack in C# next month.
> My questions may sound rhetorical, but they are not. Although I have
> through the C# spec, and am somewhat pleased with it, I do not know the
> answers to these questions.
Microsoft has a long list of languages which they claim will
support C# and the .NET Framework, including C++, Python,
Perl, Eiffel, Oberon, Haskell, Smalltalk, and even COBOL.
Fortran is conspicuous by its absence on the list, but Fujitsu is
doing the COBOL port. Fujitsu and Lahey Fortran
are working partners. Or maybe Compaq/Digital has something
on the back burner?
What's encouraging about C# and the .NET Framework is that
they appear to have been designed to address some of the more
serious shortcomings of JAVA:
(0) Many languages will be supported.
(1) The C# language specification has been submitted to the
international standards body ECMA for standardization.
(2) Built-in types (ints, longs, doubles, arrays, etc.) are objects.
(3) Unsigned integer types are included.
(4) There is full IEEE 754 floating point support.
(5) There is native support for multidimensional arrays, not just
awkward ragged arrays.
(6) Most operators can be overloaded.
(7) If you must, pointers are supported.
Python supports complex arithmetic out of the box. But to invert
a matrix you have to twist yourself into a pretzel.
More information about the NumPy-Discussion