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https://github.com/vmchale/apple

Apple array system
https://github.com/vmchale/apple

array haskell

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Apple array system

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# Apple Array System

This is an experimental compiler for an array domain-specific language (DSL) targeting Aarch64.

See [Apple by Example](https://vmchale.github.io/apple/) for a tour of the
language.

The compiler will bail out with arcane error messages rather than
produce an incorrect result (some cases are not implemented), except that the Python/R extension modules do not
enforce type safety and thus may mysteriously segfault or produce unpredictable corrupt results.

## Compiler-As-a-Library

Rather than an environment-based interpreter or a compiler invoked on the
command line and generating object files, one calls a library function which
returns assembly or machine code from a source string.

Thus the same implementation can be used interpreted, compiled, or called from
another language.

```
> [(+)/x%ℝ(:x)]\`7 (frange 1 10 10)
Arr (4) [4.0, 5.0, 6.0, 7.0]
```

```python
>>> import apple
>>> import numpy as np
>>> sliding_mean=apple.jit('([(+)/x%ℝ(:x)]\`7)')
>>> sliding_mean(np.arange(0,10,dtype=np.float64))
array([3., 4., 5., 6.])
```

```janet
repl:1:> (import apple)
@{_ @{:value } apple/jit @{:private true} apple/tyof @{:private true}}
repl:2:> (def sliding-mean (apple/jit ``([(+)/x%ℝ(:x)]\`7)``))

repl:3:> (sliding-mean @[0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0])
@[3 4 5 6 7]
```

```R
> source("R/apple.R")
> sliding_mean<-jit("([(+)/x%ℝ(:x)]\\`7)")
> run(sliding_mean,seq(0,10,1.0))
[1] 3 4 5 6 7
```

Apple [tends to be faster than R](http://blog.vmchale.com/article/r-perf) but
lags NumPy.

### JIT'ed Calculator

There are no imports.

Recursive functions are not allowed. The DSL is still useful in that it compiles array
constructs for the host languages.

## Dimension As a Functor

This is based on J (and APL?). Looping is replaced by functoriality (rerank).

To supply a zero-cells (scalars) as the first argument to `⊲` (cons) and 1-cells as the second:

```
(⊲)`{0,1}
```

We can further specify that the cells should be selected along some axis, e.g.
to get vector-matrix multiplication:

```
λA.λx.
{
λA.λx. (x⋅)`{1∘[2]} (A::Arr (i × j) float)
}
```

The `2` means "iterate over the second axis" i.e. columns.

## Array QuickCheck

```
> :qc \x. [(+)/(*)`x y] x x >= 0.0
Passed, 100.
> :qc \x. [(+)/(*)`x y] x x > 2.0
Proposition failed!
[ Arr (5) [ 0.6213045301664751
, 0.6599381241699802
, 0.762478867048601
, 6.026206825450409e-3
, 0.5633419282435523 ] ]
```

## Installation

Use [ghcup](https://www.haskell.org/ghcup/) to install [cabal](https://www.haskell.org/cabal/) and GHC. Then:

```
make install
```

to install `arepl` (the REPL).

Run

```
make
sudo make install-lib
```

To install the shared library (requires [jq](https://jqlang.github.io/jq/)).

### Python

To install the Python module:

```
make install-py
```

### R

Install `libappler.so` on your system like so:

```
make -C Rc
sudo make install-r
```

Then:

```
source("R/apple.R")
```

to access the functions.

### Janet

Uses [jpm](https://janet-lang.org/docs/jpm.html).

```
make -C janet install
```

## Documentation

Type `\l` in the REPL to show the reference card:

```
> \l
Λ scan √ sqrt
⋉ max ⋊ min
⍳ integer range ⌊, ⌈ floor, ceiling
e: exp ⨳ {m,n} convolve
\~ successive application \`n infix
_. log ' map
` zip `{i,j∘[k,l]} rank
𝒻 range (real) 𝜋 pi
_ negate : size
𝓉 dimension {x⟜y;z} no inline
->n select ** power
⊂ scatter }. last
⊲ cons ⊳ snoc
^: iterate %. matmul
⊗ outer product ⍉, |: transpose
{. head }: typesafe init
⟨z,w⟩ array literal ?p,.e1,.e2 conditional
...
```

Enter `:help` in REPL:

```
> :help
:help, :h Show this help
:yank, :y Read file
:store, :st Display the type of an expression
:ann Annotate with types
...
```

### Vim Plugin

`:h apple` lists potentially useful digraphs, viz.

```
← <-
⟜ o-
𝒻 ff
⊲ <\
⊳ \>

```

### Python Module

To display module documentation:

```python
>>> import apple
>>> help(apple)
```

```
CLASSES
builtins.object
AppleJIT

class AppleJIT(builtins.object)
| JIT-compiled function in-memory
|
| Methods defined here:
|
| __call__(self, /, *args, **kwargs)
| Call self as a function.
|
| ----------------------------------------------------------------------

FUNCTIONS
asm(...)
Dump assembly

ir(...)
Dump IR (debug)

jit(...)
Compile an expressoin into a callable object

typeof(...)
Display type of expression
```

### Janet

```janet
repl:2:> (import apple)
@{_ @{:value } apple/jit @{:private true} apple/tyof @{:private true}}
repl:4:> (doc apple/jit)

cfunction

Compile source string into Janet callable

nil
repl:5:> (doc apple/tyof)

cfunction

type of expression

nil
```