lti#
- class scipy.signal.lti(*system)[source]#
- Continuous-time linear time invariant system base class. - Parameters:
- *systemarguments
- The - 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:- 2: - TransferFunction: (numerator, denominator)
- 3: - ZerosPolesGain: (zeros, poles, gain)
- 4: - StateSpace: (A, B, C, D)
 - Each argument can be an array or a sequence. 
 
 - See also - Notes - ltiinstances do not exist directly. Instead,- lticreates an instance of one of its subclasses:- StateSpace,- TransferFunctionor- ZerosPolesGain.- 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 - zerosof a- 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.- Examples - >>> from scipy import signal - >>> signal.lti(1, 2, 3, 4) StateSpaceContinuous( array([[1]]), array([[2]]), array([[3]]), array([[4]]), dt: None ) - Construct the transfer function \(H(s) = \frac{5(s - 1)(s - 2)}{(s - 3)(s - 4)}\): - >>> signal.lti([1, 2], [3, 4], 5) ZerosPolesGainContinuous( array([1, 2]), array([3, 4]), 5, dt: None ) - Construct the transfer function \(H(s) = \frac{3s + 4}{1s + 2}\): - >>> signal.lti([3, 4], [1, 2]) TransferFunctionContinuous( array([3., 4.]), array([1., 2.]), dt: None ) - Attributes:
 - Methods - bode([w, n])- Calculate Bode magnitude and phase data of a continuous-time system. - freqresp([w, n])- 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.