A repository of analysis and computer control code for various experiments. Image above is an example of data collected and analyzed using this package.
See here for introdution videos
EKPy (formerly ekpmeasure) is a set of control and analysis code designed to help streamline experiments. The basic idea is that in experimental work we often take data from many different sources, store it in different places, have varying degrees meta data associated with the data (even for a single type of data) and somehow(!) we are supposed to make sense of it all. We like to compare across trials, days, experimental conditions, etc. and it is very difficult to keep track of what data is where, and quickly access it when we need it. Often I find that folks end up copying and pasting raw data between excel spreadsheets and if you're not careful you will quickly lose track of which data came from where. This package's goal is to make this all easier.
You may not find the experimental control code as helpful as it is relatively specific to my research in condensed matter physics (though electrical engineers or similar may find it very useful) but the analysis code is for everyone.
At the heart of the analysis is the Dataset class which is a means of manipulating meta data alone in order to locate which actual data you want to analyze. Datasets don't care about what the real data looks like, and they keep track of where different data is stored so it is easy to select which data you want to look at - only then do you retrieve the data. The real data is returned in a Data class which allows you to group by parameters, perform calculations and much more.
I am always improving this repository and if you have suggestions, I appreciate any feedback and or issues (https://github.com/eparsonnet93/ekpmeasure/issues)
See examples for more.
If you plan to use EKPy to control your experiments. You will need to install NI-VISA first.
Find the latest build here.
pip install ekpyor to upgrade to the latest version
pip install -U ekpyYou can also access .whl or .tar.gz files in the dist/ directory directly for installation.
For installation issues, please see Issue Tracker
There are also specific experiments that can be installed following installation of ekpy. Please see the accompanying readme (e.g., here) for such cases.
We welcome new contributors of all experience levels. Please reach out directly (e.parsonnet@berkeley.edu) to inqure about getting involved.
- Official source code repo: https://github.com/eparsonnet93/ekpmeasure
- Issue tracker: https://github.com/eparsonnet93/ekpmeasure/issues
With help form Geo!
- Updates to utils to make to improve the function
get_number_and_suffix+ other updates to include additional instruments and fixes.
- Can now group Data.
data.groupby - Can now remove nans from data.
data.dropna - Improvements to file management in control, saving, and more appropriate trial incrementing in
control.experiment - Functions used in
data.applyshould no longer require the use of iterable data arrays. Please raise an issue if one occurs.
- Added functionality to
analysis.radiant - Speed increase for
data.get_data() - Minor bugs and other fixes
experiment.print_run_function_argsis gone. It has been replaced withexperiment.show_run_function_help- Added a header of meta data to the default save function for
control.experimentand started the process of doing away with meta_data.pklfiles in favor of.csv(why did I ever think that was a good idea?)
- minor bug fixes and documentation updates
- minor bug fixes
2/18/22
- bug fixes from 0.1.7 and changed install name to
ekpy.
1/23/22
- added
Data.to_DataFrame()which allows one to convertDatatopandas.DataFrame. Each index ofDatawill be a single row in the resulting DataFrame.
1/12/22
-
merge_Dataswas replaced. The older version is nowconcat_Datasas it was really just concatenation, not merging. Merging now has real meaning, to merge a set of similar data objects on a specified definition key. Please report errors as they arise. -
similary
merge_Datasetsis deprecated. One must useconcat_Datasets.
12/2/21
- Added experiments module with
ferroelectricexperiments. This contains both relaxation (_relaxation) and switching (_switching) experiments. These consist of self contained jupyter notebooks that can be installed bypython -m ekpy.experiments.ferroelectric.<experiment_name>. For more see the experiment specific README for relaxation or switching - Bug fix on
Data.sort
11/16/21
Data.applynow allows for dropping data. This can be executed by having the function in.applyreturn'None'.data_array_builder.buildnow allows one to fix lengths on 1D data by appending nans to make all data arrays the same length.analysis.plotting.add_legend_elementnow allows kwarg fontsize
11/19/21
Datacan now be saved. Usedata.to_ekpdat.- Can be loaded as
analysis.read_ekpdat
- Can be loaded as
11/11/21
- Minor fixes for deprecations in
control.misc
11/7/21
- Speed improvements to
Dataset.remove_nonexistent_files Dataobjects can now be sorted by a definition parameter
11/2/21
- Updates to plotting during experimental control. Now one can simply override the
control.experimentmethod_plotto define how plotting will take place. Here is a brief example of such an override:
from ekpy.control import plotting
from ekpy.control import experiment
import matplotlib.pyplot as plt
class exp(experiment):
...
def _plot(self, data, scan_params):
if hasattr(self, 'fig') and hasattr(self, 'ax'):
pass
else:
fig, ax = plt.subplots()
self.fig = fig
self.ax = ax
self.ax.scatter(scan_params['frequency'], np.mean(data['R']), color = 'blue')
plt.show(self.fig)
plotting.update_plot(self.fig)
...10/24/21
- Dataset class is no longer subclass of
pandas.DataFrame. This is to limit usage of unsupported functions. - Data class updates including sorting and collapsing.
- One can access data or definition directly as an attribute now
Data.definition, for example. One can also access pieces of information such as the real data corresponding top1asData.p1or definition keys, e.g.high_voltageasData.high_voltage - Experiment class now saves a backup
.csvmeta data file in addition to the pickle file in order to help with errors related to different pandas versions on various machines.
Code related issues (e.g. bugs, feature requests) can be created in the issue tracker
Maintainer: Eric Parsonnet
Please cite this work following the CITATION.cff (see here for more details on how to cite.)
- E. Parsonnet et. al. NonVolatile Electric Field Control of Thermal Magnons in the Absence of an Applied Magnetic Field, Phys. Rev. Lett 129, 087601 (2022).