Sharing Data#

PyProBE makes sharing data simple and straightforward. This is a simple example to demonstrate the process.

First we will import some sample data:

[1]:

%%capture
%pip install matplotlib

[2]:

import pyprobe
import os
import shutil
from pprint import pprint

%matplotlib inline

# Describe the cell. Required fields are 'Name'.
info_dictionary = {
    "Name": "Sample cell",
    "Chemistry": "NMC622",
    "Nominal Capacity [Ah]": 0.04,
    "Cycler number": 1,
    "Channel number": 1,
}

# Create a cell object
cell = pyprobe.Cell(info=info_dictionary)

data_directory = "../../../tests/sample_data/neware"

cell.add_procedure(
    procedure_name="Sample",
    folder_path=data_directory,
    filename="sample_data_neware.parquet",
)

We can then use the archive() method of the cell object. This stores all attributes of the cell object into a single folder. The data is stored as .parquet files and the metadata is stored in .json files.

[3]:

cell.archive(path="sample_archive")
os.listdir(".")

[3]:

['working-with-pybamm-models.ipynb',
 'filtering-data.ipynb',
 'providing-valid-inputs.ipynb',
 'sample_archive',
 'comparing-pyprobe-performance.ipynb',
 'differentiating-voltage-data.ipynb',
 'examples.rst',
 'ocv-fitting.ipynb',
 'sharing-data.ipynb',
 'getting-started.ipynb',
 'analysing-GITT-data.ipynb',
 'plotting.ipynb']

You can choose to compress the folder by adding .zip to the path:

[4]:

cell.archive(path="sample_archive.zip")
os.listdir(".")

[4]:

['working-with-pybamm-models.ipynb',
 'filtering-data.ipynb',
 'providing-valid-inputs.ipynb',
 'comparing-pyprobe-performance.ipynb',
 'differentiating-voltage-data.ipynb',
 'examples.rst',
 'ocv-fitting.ipynb',
 'sample_archive.zip',
 'sharing-data.ipynb',
 'getting-started.ipynb',
 'analysing-GITT-data.ipynb',
 'plotting.ipynb']

You can then retrieve the archived object with the pyprobe.load_archive() method:

[5]:

saved_cell = pyprobe.load_archive("sample_archive.zip")
pprint(saved_cell.info)

{'Channel number': 1,
 'Chemistry': 'NMC622',
 'Cycler number': 1,
 'Name': 'Sample cell',
 'Nominal Capacity [Ah]': 0.04}

[6]:

saved_cell.procedure["Sample"].plot(x="Time [hr]", y="Voltage [V]")

[6]:

<Axes: xlabel='Time [hr]'>
../_images/examples_sharing-data_9_1.png

Clean up after example

[7]:

shutil.rmtree("sample_archive")

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