2.1.2.5. Periodic Functions
2.1.2.5.1. Main Functions
- teaspoon.MakeData.DynSysLib.periodic_functions.sine(omega=6.283185307179586, L=40, fs=50, SampleSize=2000)[source]
The sinusoidal function is defined as
\[x(t) = \sin(2\pi t)\]This was solved for 40 seconds with a sampling rate of 50 Hz.
- Parameters:
omega (Optional[float]) – frequency of the sine wave.
L (Optional[int]) – amount of time to solve simulation for.
fs (Optional[int]) – sampling rate for simulation.
SampleSize (Optional[int]) – length of sample at end of entire time series
- Returns:
Array of the time indices as t and the simulation time series ts
- Return type:
array
- teaspoon.MakeData.DynSysLib.periodic_functions.incommensurate_sine(omega1=3.141592653589793, omega2=1, L=100, fs=50, SampleSize=5000)[source]
This function is generated using two incommensurate periodic functions as
\[x(t) = \sin(\omega_1 t) + \sin(\omega_2 t)\]This was sampled such that \(t \in [0, 100]\) at a rate of 50 Hz.
- Parameters:
omega1 (Optional[float]) – frequency of the first sine wave.
omega2 (Optional[float]) – frequency of the second sine wave.
L (Optional[int]) – amount of time to solve simulation for.
fs (Optional[int]) – sampling rate for simulation.
SampleSize (Optional[int]) – length of sample at end of entire time series
- Returns:
Array of the time indices as t and the simulation time series ts
- Return type:
array