NOTE from the future: As you can see in the comments, this file is no longer available to download, sourceforge removed the user spaces and did not respond my email about it. This was done at an office where I don’t work anymore, so there’s no means so far to recover
Doesn't Numpy already use a C inner loop to do the main data loading, since Numpy is wrapping around C data structures that the loading process loads into? Surely for a reasonably sized array, the overhead of parsing the header info in Python would not be the bottleneck?
I don't mean to write off the possibility (especially in 2014) that OP could have written (especially hardware-specific) faster C code for the loading process. But I would take that as more of a reason to contribute to the project than to do what's described here.
Comments
Doesn't Numpy already use a C inner loop to do the main data loading, since Numpy is wrapping around C data structures that the loading process loads into? Surely for a reasonably sized array, the overhead of parsing the header info in Python would not be the bottleneck?
I don't mean to write off the possibility (especially in 2014) that OP could have written (especially hardware-specific) faster C code for the loading process. But I would take that as more of a reason to contribute to the project than to do what's described here.