Continuous-time linear time invariant system base class.
*system : arguments
lticlass can be instantiated with either 2, 3 or 4 arguments. The following gives the number of arguments and the corresponding continuous-time subclass that is created:
Each argument can be an array or a sequence.
If (numerator, denominator) is passed in for
*system, coefficients for both the numerator and denominator should be specified in descending exponent order (e.g.,
s^2 + 3s + 5would be represented as
[1, 3, 5]).
Changing the value of properties that are not directly part of the current system representation (such as the
StateSpacesystem) is very inefficient and may lead to numerical inaccuracies. It is better to convert to the specific system representation first. For example, call
sys = sys.to_zpk()before accessing/changing the zeros, poles or gain.
>>> from scipy import signal
>>> signal.lti(1, 2, 3, 4) StateSpaceContinuous( array([]), array([]), array([]), array([]), dt: None )
>>> signal.lti([1, 2], [3, 4], 5) ZerosPolesGainContinuous( array([1, 2]), array([3, 4]), 5, dt: None )
>>> signal.lti([3, 4], [1, 2]) TransferFunctionContinuous( array([ 3., 4.]), array([ 1., 2.]), dt: None )
Return the sampling time of the system, None for
Poles of the system.
Zeros of the system.
Calculate Bode magnitude and phase data of a continuous-time system.
Calculate the frequency response of a continuous-time system.
impulse([X0, T, N])
Return the impulse response of a continuous-time system.
output(U, T[, X0])
Return the response of a continuous-time system to input U.
step([X0, T, N])
Return the step response of a continuous-time system.
to_discrete(dt[, method, alpha])
Return a discretized version of the current system.