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numpy.html
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<!DOCTYPE html>
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<title>Configurable runtimes</title>
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<py-config>
{
"runtime": "micropython",
"files": {
"arrr.py": "/arrr.py"
}
}
</py-config>
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<h2>Native Modules</h2>
<p>There are numerous pure-Python modules that work with MicroPython.
However, some of the most interesting involve C-based extensions, with the
most well known being data science tools like
<a href="https://numpy.org/">numpy</a> and
<a href="https://scipy.org/">scipy</a>.</p>
<p>These C-based extensions can be compiled to WASM, in exactly the same
way that Python runtimes (written in C) are compiled to WASM.</p>
<p>The version of MicroPython emebedded in the following REPL also
includes a WASM compiled tool called
<a href="https://micropython-ulab.readthedocs.io/en/latest/index.html">uLab</a> ("micro lab").
This is a small reimplementation of the core functions, for effieciently
working with numeric arrays found, in the numpy
and scipy modules. It is clearly not a complete re-implementation, but
serves to prove that such bespoke C-based extensions can be used with the
MicroPython runtime.</p>
<py-repl></py-repl>
<p>Why not try:</p>
<pre><code>>>> import ulab
>>> dir(ulab)
['__class__', '__name__', '__dict__', '__version__', 'dtype', 'numpy', 'scipy', 'utils']
>>> dir(ulab.numpy)
['__class__', '__name__', 'all', 'any', 'bool', 'sort', 'sum', '__dict__', 'acos', 'acosh',
'arange', 'arctan2', 'argmax', 'argmin', 'argsort', 'around', 'array', 'asarray', 'asin',
'asinh', 'atan', 'atanh', 'ceil', 'clip', 'complex', 'compress', 'concatenate', 'conjugate',
'convolve', 'cos', 'cosh', 'cross', 'degrees', 'delete', 'diag', 'diff', 'dot', 'e', 'empty',
'equal', 'exp', 'expm1', 'eye', 'fft', 'flip', 'float', 'floor', 'frombuffer', 'full',
'get_printoptions', 'imag', 'inf', 'int16', 'int8', 'interp', 'isfinite', 'isinf', 'linalg',
'linspace', 'load', 'loadtxt', 'log', 'log10', 'log2', 'logspace', 'max', 'maximum', 'mean',
'median', 'min', 'minimum', 'nan', 'ndarray', 'ndinfo', 'nonzero', 'not_equal', 'ones', 'pi',
'polyfit', 'polyval', 'radians', 'real', 'roll', 'save', 'savetxt', 'set_printoptions', 'sin',
'sinh', 'size', 'sort_complex', 'sqrt', 'std', 'tan', 'tanh', 'trace', 'trapz', 'uint16',
'uint8', 'vectorize', 'where', 'zeros']
>>> a=ulab.numpy.ndarray([1,2,3])
>>> a
array([1.0, 2.0, 3.0], dtype=float64)
>>> ulab.numpy.sqrt(a)
array([1.0, 1.414213562373095, 1.732050807568877], dtype=float64)</code></pre>
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<p>Made with ❤️ by folks at <a href="https://anaconda.com" rel="noopener">Anaconda Inc</a>.<br>
💡Inspired by the great work at <a href="https://micropython.org/" rel="noopener">MicroPython</a>.<br><br>
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