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NumPy is like a small array DSL on top of Python Numpy is small? Is there anything missing in Numpy that could be found in those esoteric languages you mentio

by p1esk 4y ago

NumPy is like a small array DSL on top of Python Numpy is small? Is there anything missing in Numpy that could be found in those esoteric languages you mentioned? I'm baffled GPU acceleration wasn't ubiquitous the second GPGPUs came out. At least in Python ecosystem, GPU acceleration has been available for a decade, provided cupy, numba, and all the ML frameworks.

juliangoldsmith 4y ago
>Numpy is small? Small might not be the right word. I mainly had broadcasting in mind when I wrote that. >Is there anything missing...? Not sure I'd call APL esoteric, given it was originally developed at IBM. My knowledge of both array languages and NumPy is limited, but one thing missing might be partitioning using a mask. An example of that would be the following snippet of J, from a WIP implementation of MTF encoding: mask <@(_1&|.)`<;.1 dict The line noise in the middle partitions dict by mask and uses a cyclic gerund to apply a different function to each partition. The ;.1 is the partition modifier; before it are the two functions separated by a tick. The second function just boxes its argument (due to different sizes). The first function rotates its argument by -1 places and then boxes it
- p1esk 4y ago
  mask <@(_1&|.)`<;.1 dict Honestly, I'd really prefer to unpack that statement into 20 lines of clear code. Not because I'm not familiar with and not used to this syntax: my preference equally applies to similar terse Numpy statements which I can understand (but which are error prone and require mental effort).
  - juliangoldsmith 4y ago
    Tacit expressions like that are interesting and very rewarding to write, but I'd agree that it's way too terse. The Iversonian array languages tend to be like that, since they're derived from mathematical notation. (Though I have heard that tacit expressions are pretty much absent from production APL code.) The aspect I find most interesting is the way primitives can be combined to build up functionality. It's closer to a declarative syntax, where the focus is on the end result instead of the steps to get there.

by p1esk 4y ago

juliangoldsmith 4y ago

>Numpy is small? Small might not be the right word. I mainly had broadcasting in mind when I wrote that. >Is there anything missing...? Not sure I'd call APL esoteric, given it was originally developed at IBM. My knowledge of both array languages and NumPy is limited, but one thing missing might be partitioning using a mask. An example of that would be the following snippet of J, from a WIP implementation of MTF encoding: mask <@(_1&|.)`<;.1 dict The line noise in the middle partitions dict by mask and uses a cyclic gerund to apply a different function to each partition. The ;.1 is the partition modifier; before it are the two functions separated by a tick. The second function just boxes its argument (due to different sizes). The first function rotates its argument by -1 places and then boxes it

p1esk 4y ago
mask <@(_1&|.)`<;.1 dict Honestly, I'd really prefer to unpack that statement into 20 lines of clear code. Not because I'm not familiar with and not used to this syntax: my preference equally applies to similar terse Numpy statements which I can understand (but which are error prone and require mental effort).
- juliangoldsmith 4y ago
  Tacit expressions like that are interesting and very rewarding to write, but I'd agree that it's way too terse. The Iversonian array languages tend to be like that, since they're derived from mathematical notation. (Though I have heard that tacit expressions are pretty much absent from production APL code.) The aspect I find most interesting is the way primitives can be combined to build up functionality. It's closer to a declarative syntax, where the focus is on the end result instead of the steps to get there.