Datkit v0.1.1

This version adds two methods to quickly inspect the frequency content of a time series

import matplotlib.pyplot as plt
import numpy as np
import datkit

t = np.linspace(0, 10, 1000)
v = 3 * np.sin(t * (2 * np.pi * 2)) + 10 * np.cos(t * (2 * np.pi * 3))
fig = plt.figure(figsize=(7, 7))
ax = fig.add_subplot(3, 1, 1)
ax.plot(t, v)

ax = fig.add_subplot(3, 1, 2)
ax.set_xlim(0, 10)
f, a = datkit.amplitude_spectrum(t, v)
ax.stem(f, a)

ax = fig.add_subplot(3, 1, 3)
ax.set_xlim(0, 10)
ax.set_yscale('log')
f, psd = datkit.power_spectral_density(t, v)
ax.plot(f, psd)

plt.show()

Datkit v0.1.0

Added methods data_on, value_interpolated, index_crossing and time_crossing.

Datkit v0.0.3

Added methods imax_on, imin_on, iabs_max_on. Added smoothing functions haar_downsample, gaussian_smoothing, moving_average, window_size.

Datkit 0.0.2

First release via Github