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fast linear transforms in Python

Project Description
# fastmat

## Description
Scientific computing requires handling large composed or structured matrices.
Fastmat is a framework for handling large composed or structured matrices.
It allows expressing and using them in a mathematically intuitive way while
storing and handling them internally in an efficient way. This approach allows
huge savings in computational time and memory requirements compared to using
dense matrix representations.

### Languages
- Python
- Cython

### Dependencies
- Python >= 2.7 or >=3.0
- Numpy >= 1.07
- Scipy >= 1.08
- Cython >= 1.18

### Authors
- Sebastian Semper - Technische Universität Ilmenau, Institute for Mathematics
- Christoph Wagner - Technische Universität Ilmenau,
Institute for Information Technology, EMS Group

### Contact
- sebastian.semper@tu-ilmenau.de
- christoph.wagner@tu-ilmenau.de
- https://www.tu-ilmenau.de/ems/

## Documentation / HELP !
Please have a look at the documentation, which is included in the source
distribution at github or may be built locally on your machine by running
`make doc`

If you experience any trouble please do not hesitate to contact us or to open
an issue on our github projectpage: https://github.com/EMS-TU-Ilmenau/fastmat

### FAQ

#### Installation fails with *ImportError: No module named Cython.Build*
Something went wrong with resolving the dependencies of fastmat during setup.
Unfortunately one or more of the required packages numpy, scipy or cython were
not installed automatically. Please do this manually by running
`pip install cython numpy scipy matplotlib`
and try the installation of fastmat again.

#### Issue not resolved?
Please contact us or leave your bug report in the *issue* section. Thank You!


## Citation / Acknowledgements
If you want to use fastmat or parts of it in your private, scientific or
commercial project or work you are required to acknowledge visibly to all users
that fastmat was used for your work and put a reference to the project and the
EMS Group at TU Ilmenau.

If you use fastmat for your scientific work you are further required to cite
the following publication affiliated with the project:
- `to be announced soon. Please tune back in regularly to check on updates.`

## Installation
fastmat currently **supports both Linux and Windows**. Building the
documentation and running benchmarks is currently only supported under linux
with windows support underway. You may choose one of these installation methods:

### installation with pip: the fast and easy way

fastmat is included in the Python Package Index (PyPI) and can be installed
from the commandline by running one easy and straightforward command:
`pip install fastmat`

When installing with pip all dependencies of the package will be installed
along.

### installation from source: doing it manually
- download the source distribution from our github repository:
https://github.com/EMS-TU-Ilmenau/fastmat/archive/master.zip
- unpack its contents and navigate to the project root directory
- make sure you have installed all listed dependencies with at least the
specified version
- type `make install` to install fastmat on your computer
* If you intend to install the package locally for your user
type `make install MODE=--user` instead.
* If you only would like to compile the package to use it from this local
directory without installing it, type `make compile`


## Demos
Feel free to have a look at the demos in the `demo/` directory of the source
distribution. Please make sure to have fastmat already installed when running
these.

Please note that the edgeDetect demo requires the Python Imaging Library (PIL)
installed and the SAFT demos do compile a cython-core of a user defined matrix
class beforehand thus having a delaying the first time they're executed.
Release History

Release History

This version
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0.1

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0.1b4

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0.1b3

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0.1b2

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0.1b1

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0.1b0

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