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This library facilitates the clear division of data acquisition from analysis. It provides robust tools for efficient data management and includes features to ensure a further use of the saved data.
This library is based on the other library dh5 which is a wrapper around the h5py library.
pip install labmate
pip install -e .[dev]
or python setup.py develop
Setup:
from labmate.acquisition_notebook import AcquisitionAnalysisManager
aqm = AcquisitionAnalysisManager("path/to/database")
Example of an acquisition cell. The variables x and y, along with the acquisition cell code and additional parameters that can be set, will be saved inside an h5 file.
aqm.acquisition_cell("your_experiment_name")
...
aqm.save_acquisition(x=x, y=y)
Example of an analysis cell. You cannot directly use the x
or y
variables, as you would not be able to open them afterwards. Therefore, whenever you use variables inside an analysis cell, retrieve them from aqm.data
.
aqm.analysis_cell()
data = aqm.data
fig, ax = plt.subplots(1, 1)
ax.plot(data.x, data.y)
aqm.save_fig(fig)
You can find this example here.
To see more look at the documentation
FAQs
Data management library to save data and plots to hdf5 files
We found that labmate demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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