# Deconvolution

The primary function for performing deconvolution is {func}`~pycudadecon.decon`.

This convenience function is capable of receiving a variety of input types (filenames, directory names, numpy arrays, or a list of any of those) and will handle setting up and breaking down the FFT plan on the GPU for all files being deconvolved. Keywords arguments will be passed internally to the {class}`~pycudadecon.RLContext` context manager or the {func}`~pycudadecon.make_otf` {func}`~pycudadecon.rl_decon` functions.

The setup and breakdown for the GPU-deconvolution can also be performed manually:

  1. call {func}`~pycudadecon.rl_init` with the shape of the raw data and path to OTF file.

  2. perform deconvolution(s) with {func}`~pycudadecon.rl_decon`.

  3. cleanup with {func}`~pycudadecon.rl_cleanup`

As a convenience, the {class}`~pycudadecon.RLContext` context manager will perform the setup and breakdown automatically:

```python data = tiffile.imread(‘some_file.tif’) otf = ‘path_to_otf.tif’ with RLContext(data.shape, otf) as ctx:

result = rl_decon(data, output_shape=ctx.out_shape)

```

## API

```{eval-rst} .. automodule:: pycudadecon

members

decon, rl_init, rl_decon, RLContext, rl_cleanup

```