# RecreateWhiteNoiseStimuliWithPython
[](https://github.com/gollischlab/RecreateWhiteNoiseStimuliWithPython/deployments/PyPI)
[](https://pypi.python.org/pypi/retinawhitenoise)
Code for regenerating the random-number-based contrast values applied in experiments with white-noise stimulation in the Gollisch Lab.
Used for both temporal and spatiotemporal stimuli, and for both binary and Gaussian white noise.
The random-number sequences are needed for analyzing the spike responses of recorded cells under white-noise stimulation.
### Installation
A full installation of the package is done from command-line using `pip` with
```
pip install retinawhitenoise
```
#### Manual installation
If the `pip` package is not available for a given operating system or Python version, the package and Cython code can be compiled manually instead.
```
pip install https://github.com/gollischlab/RecreateWhiteNoiseStimuliWithPython/archive/main.tar.gz
```
Windows might require the [Microsoft C++ Build Tools](https://visualstudio.microsoft.com/visual-cpp-build-tools) to be installed (including *"Windows SDK"* and *"MSVC ... C++ x64/x86 build tools"*). For details, see [here](https://www.scivision.dev/python-windows-visual-c-14-required).
### Usage
The Python package `retinawhitenoise` offers two modules `binarystimulus` and `gaussianstimulus`,
each offering routines to `recreate`, `save` (to disk), and `load` stimulus sequences.
Instructions on how to use them with example code and explanations is included in the jupyter notebook `examples.ipynb`.
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"description": "# RecreateWhiteNoiseStimuliWithPython\n\n[](https://github.com/gollischlab/RecreateWhiteNoiseStimuliWithPython/deployments/PyPI)\n[](https://pypi.python.org/pypi/retinawhitenoise)\n\nCode for regenerating the random-number-based contrast values applied in experiments with white-noise stimulation in the Gollisch Lab.\nUsed for both temporal and spatiotemporal stimuli, and for both binary and Gaussian white noise.\n\nThe random-number sequences are needed for analyzing the spike responses of recorded cells under white-noise stimulation.\n\n### Installation\nA full installation of the package is done from command-line using `pip` with\n```\npip install retinawhitenoise\n```\n\n#### Manual installation\nIf the `pip` package is not available for a given operating system or Python version, the package and Cython code can be compiled manually instead.\n```\npip install https://github.com/gollischlab/RecreateWhiteNoiseStimuliWithPython/archive/main.tar.gz\n```\n\nWindows might require the [Microsoft C++ Build Tools](https://visualstudio.microsoft.com/visual-cpp-build-tools) to be installed (including *\"Windows SDK\"* and *\"MSVC ... C++ x64/x86 build tools\"*). For details, see [here](https://www.scivision.dev/python-windows-visual-c-14-required).\n\n### Usage\nThe Python package `retinawhitenoise` offers two modules `binarystimulus` and `gaussianstimulus`,\neach offering routines to `recreate`, `save` (to disk), and `load` stimulus sequences.\n\nInstructions on how to use them with example code and explanations is included in the jupyter notebook `examples.ipynb`.\n",
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