semvec/pypi-packages huggingface dataset:
deconvoluted 0.1.1
Deconvoluted makes performing integral transforms simple and pythonic!
License: MIT license
Keywords: deconvoluted

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Deconvoluted
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Deconvoluted makes performing numerical integral transforms simple and pythonic!


* Free software: MIT license
* Documentation: https://deconvoluted.readthedocs.io.


Features
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Fourier Transforms
~~~~~~~~~~~~~~~~~~

As a first example, let's perform a Fourier transform:

.. code-block:: python

    t = np.linspace(0, 10, 201)
    f = np.sin(3 * 2 * np.pi * t)
    F, nu = fourier_transform(f, t)

By default, Fourier transforms use Fourier coefficients `a=0`,
`b=-2\pi`. Using another convention is simple:

.. code-block:: python

    F, omega = fourier_transform(f, t, convention=(-1, 1))

As a physicist myself, I therefore switch the labelling of the output from
`\nu` for frequency, to `\omega` for angular frequency.

Performing multidimensional transforms is just as easy. For example:

.. code-block:: python

    F_pq, p, q = fourier_transform(f_xy, x, y)

transforms both `x` and `y` at the same time.
Transforming only one of the two variables can be done simply by setting those
that shouldn't transform to ``None``:

.. code-block:: python

    F_py, p = fourier_transform(f_xy, x, None)
    F_xq, q = fourier_transform(f_xy, None, y)

See the documentation for more examples!


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History
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0.1.1 (2019-06-05)
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* Implemented support for different FT conventions.

0.1.0 (2019-06-03)
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* First release on PyPI.