axographio 0.3.2

Getting axographio

axographio is compatible with both Python 2 and Python 3.

The easiest way to get axographio is to install the latest stable version using pip, but you can alternatively build it from the source code.

pip install axographio

pip install git+https://github.com/CWRUChielLab/axographio

pip install C:\wherever-you-put-the-source-code

Usage

Try out the Binder demo for an interactive Python session that requires no installation or fuss. You can start hacking right now!

Loading a data file is as easy as calling read:

>>> import axographio
>>>
>>> f = axographio.read('AxoGraph X File.axgx')

At this point the variable f will contain a file_contents object with the column names and data from the file. For example, you could now plot the first two columns using Matplotlib:

>>> import matplotlib.pyplot as plt
>>>
>>> plt.plot(f.data[0], f.data[1])
>>> plt.xlabel(f.names[0])
>>> plt.ylabel(f.names[1])
>>> plt.show()  # may be optional depending on your OS

Of course, you probably have grander plans than just plotting the data. The column data supports the standard sequence interfaces (i.e., indexing, iteration, etc.) and can be converted to a NumPy or SciPy array using the asarray functions in these packages, e.g.:

>>> import numpy as np
>>>
>>> times = np.asarray(f.data[0])

Writing files is also relatively easy. You simply create a new file_contents object (or use one you loaded earlier), and then call write. For example, the following code creates a file in the current directory called ‘my60Hz.axgx’ with two channels with 60 Hz sine waves:

>>> import axographio
>>> import numpy as np
>>>
>>> times = np.arange(0, 10, 0.0001)
>>> column1 = np.sin(2*np.pi * 60 * times)
>>> column2 = np.cos(2*np.pi * 60 * times)
>>> f = axographio.file_contents(
...    ['time (s)', 'my recording (V)', 'your recording (V)'],
...    [times, column1, column2])
>>> f.write('my60Hz.axgx') # created in the current directory

Questions and Support

Please post any questions, problems, comments, or suggestions in the GitHub issue tracker.

Changes

Acknowledgments

This initial version of this project was written in the Chiel Laboratory at Case Western Reserve University, with support from NIH grant NS047073, an Ohio Innovation Incentive Award Fellowship, and the Case Western Reserve MSTP (NIH T32 GM007250). This project builds on a number of other open source projects, including Python, C++ AxoGraph file input/output code from AxoGraph Scientific (placed in the public domain; a modified version is included with the project source code), Cython, and many others. Thanks also to Dr. Hillel Chiel for providing testing and helpful suggestions.