# Lazylinop’s documentation

## Lazylinop philosophy – what is a LazyLinOp object?

A LazyLinOp is a high-level linear operator based on an arbitrary underlying implementation, such as:

custom Python functions,

a NumPy array,

a SciPy matrix,

a Faust object,

any Python linear operator.

**lazy paradigm**: their evaluation is delayed until the resulting LazyLinOp is actually applied to a vector (or to a collection of vectors, seen as a matrix).

## Main benefits of Lazylinop

Lazylinop aims at providing:

a unified NumPy/SciPy-like API for any underlying implementation (including transparent use of efficient third-party libraries for advanced linear operators such as wavelets, etc.),

an easy way to combine existing operators into more complex operators with all the LazyLinOp operations at your fingertips (and in particular the adjoint),

potential performance gains & memory sparing offered by the lazy paradigm,

many pre-built operators and related APIs, delivered in specialized Lazylinop sub-packages (polynomials of operators, signal-processing oriented operators, etc.).

Compatibility with SciPy algorithms implemented for LinearOperator-s: svds, eigsh, etc.

Lazylinop is also an alternative or a complement to other related libraries that harness the power of the lazy paradigm. See the section Related lazy libraries for more details.

Beta stage

Lazylinop is currently in a beta stage of development. It is thus intensively evolving and we invite you to consult this documentation regularly. We welcome all beta testers and any feedback.

## Getting started with lazylinop

**Quick install using Anaconda**

```
conda config --add channels conda-forge
conda config --add channels lazylinop
conda install lazylinop
```

**Quick install using PIP**

```
pip install lazylinop
```

Python beginners willing to safely install Lazylinop with a virtual environment can consult this guide.

**Installing all extra/optional dependencies**

```
pip install -r lz_requirements.txt
```

Download the dependency file lz_requirements.txt

**Quick introduction**

For a quick introduction to the use of Lazylinop go to this notebook. The raw notebook is available here.