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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Copyright © 2014 - 2021 German Neuroinformatics Node (G-Node)
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted under the terms of the BSD License. See
LICENSE file in the root of the Project.
Author: Jan Grewe <jan.grewe@g-node.org>
See https://github.com/G-node/nix/wiki for more information.
"""
import nixio
import numpy as np
import matplotlib.pyplot as plt
import docutils
def create_sinewave(duration=1, freq=10, stepsize=0.01):
x = np.arange(0, duration * 2 * np.pi, stepsize)
y = np.sin(freq * x)
return x, y
def plot_data(data_array):
x_axis = data_array.dimensions[0]
x = x_axis.axis(data_array.shape[0])
y = data_array[:]
plt.plot(x, y, marker=".", markersize=5, label=data_array.name)
plt.xlabel(x_axis.label + " [" + x_axis.unit + "]")
plt.ylabel(data_array.label + " [" + data_array.unit + "]")
plt.xlim(0, np.max(x))
plt.ylim((1.1 * np.min(y), 1.1 * np.max(y)))
plt.legend()
if docutils.is_running_under_pytest():
plt.close()
else:
plt.show()
def main():
# fake some data
duration = 10.
frequency = 5
stepsize = 0.002
_, y = create_sinewave(duration, frequency, stepsize)
# create a new file overwriting any existing content
file_name = 'regular_data_example.nix'
file = nixio.File.open(file_name, nixio.FileMode.Overwrite)
# create a 'Block' that represents a grouping object. Here, the recording session.
block = file.create_block("block name", "nix.session")
# create a 'DataArray' to take the sinewave, add some information about the signal
data = block.create_data_array("sinewave", "nix.regular_sampled", data=y,
label="voltage", unit="mV")
# add a descriptor for the xaxis
data.append_sampled_dimension(stepsize, label="time", unit="s", offset=0.0)
# let's plot the data from the stored information
plot_data(data)
file.close()
if __name__ == "__main__":
main()
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