[](https://pypi.org/project/pyxdf/)
[](https://anaconda.org/conda-forge/pyxdf)
pyXDF
=====
pyXDF is a Python importer for [XDF](https://github.com/sccn/xdf) files.
## Sample usage
``` python
import pyxdf
import matplotlib.pyplot as plt
import numpy as np
data, header = pyxdf.load_xdf('test.xdf')
for stream in data:
y = stream['time_series']
if isinstance(y, list):
# list of strings, draw one vertical line for each marker
for timestamp, marker in zip(stream['time_stamps'], y):
plt.axvline(x=timestamp)
print(f'Marker "{marker[0]}" @ {timestamp:.2f}s')
elif isinstance(y, np.ndarray):
# numeric data, draw as lines
plt.plot(stream['time_stamps'], y)
else:
raise RuntimeError('Unknown stream format')
plt.show()
```
## CLI examples
`pyxdf` has an `examples` module. These can be run from the command line for basic functionality.
* `print_metadata` will enable a DEBUG logger to log read messages, then it will print basic metadata about each found stream.
* `python -m pyxdf.examples.print_metadata -f=/path/to/my.xdf`
* `playback_lsl` will open an XDF file then replay its data in an infinite loop, but using current timestamps. This is useful for prototyping online processing.
* `python -m pyxdf.examples.playback_lsl /path/to/my.xdf`
## Installation
The latest stable version can be installed with `pip install pyxdf`.
For the latest development version, use `pip install git+https://github.com/xdf-modules/pyxdf.git`.
## For maintainers
A new release is automatically uploaded to PyPI. Therefore, as soon as a new release is created on GitHub (using a tag labeled e.g. `v1.16.3`), a PyPI package is created with the version number matching the release tag.
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"description": "[](https://pypi.org/project/pyxdf/)\n[](https://anaconda.org/conda-forge/pyxdf)\n\n\n\npyXDF\n=====\n\npyXDF is a Python importer for [XDF](https://github.com/sccn/xdf) files.\n\n## Sample usage\n\n``` python\nimport pyxdf\nimport matplotlib.pyplot as plt\nimport numpy as np\n\ndata, header = pyxdf.load_xdf('test.xdf')\n\nfor stream in data:\n y = stream['time_series']\n\n if isinstance(y, list):\n # list of strings, draw one vertical line for each marker\n for timestamp, marker in zip(stream['time_stamps'], y):\n plt.axvline(x=timestamp)\n print(f'Marker \"{marker[0]}\" @ {timestamp:.2f}s')\n elif isinstance(y, np.ndarray):\n # numeric data, draw as lines\n plt.plot(stream['time_stamps'], y)\n else:\n raise RuntimeError('Unknown stream format')\n\nplt.show()\n```\n\n## CLI examples\n\n`pyxdf` has an `examples` module. These can be run from the command line for basic functionality.\n\n* `print_metadata` will enable a DEBUG logger to log read messages, then it will print basic metadata about each found stream.\n * `python -m pyxdf.examples.print_metadata -f=/path/to/my.xdf`\n* `playback_lsl` will open an XDF file then replay its data in an infinite loop, but using current timestamps. This is useful for prototyping online processing.\n * `python -m pyxdf.examples.playback_lsl /path/to/my.xdf` \n\n## Installation\n\nThe latest stable version can be installed with `pip install pyxdf`.\n\nFor the latest development version, use `pip install git+https://github.com/xdf-modules/pyxdf.git`.\n\n## For maintainers\n\nA new release is automatically uploaded to PyPI. Therefore, as soon as a new release is created on GitHub (using a tag labeled e.g. `v1.16.3`), a PyPI package is created with the version number matching the release tag.\n",
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