scipy.signal.

# ZerosPolesGain#

class scipy.signal.ZerosPolesGain(*system, **kwargs)[source]#

Linear Time Invariant system class in zeros, poles, gain form.

Represents the system as the continuous- or discrete-time transfer function $$H(s)=k \prod_i (s - z[i]) / \prod_j (s - p[j])$$, where $$k$$ is the gain, $$z$$ are the zeros and $$p$$ are the poles. ZerosPolesGain systems inherit additional functionality from the lti, respectively the dlti classes, depending on which system representation is used.

Parameters:
*systemarguments

The ZerosPolesGain class can be instantiated with 1 or 3 arguments. The following gives the number of input arguments and their interpretation:

• 3: array_like: (zeros, poles, gain)

dt: float, optional

Sampling time [s] of the discrete-time systems. Defaults to None (continuous-time). Must be specified as a keyword argument, for example, dt=0.1.

Attributes:
dt

Return the sampling time of the system, None for lti systems.

gain

Gain of the ZerosPolesGain system.

poles

Poles of the ZerosPolesGain system.

zeros

Zeros of the ZerosPolesGain system.

Methods

 Convert system representation to StateSpace. Convert system representation to TransferFunction. Return a copy of the current 'ZerosPolesGain' system.

Notes

Changing the value of properties that are not part of the ZerosPolesGain system representation (such as the A, B, C, D state-space matrices) 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_ss() before accessing/changing the A, B, C, D system matrices.

Examples

Construct the transfer function $$H(s) = \frac{5(s - 1)(s - 2)}{(s - 3)(s - 4)}$$:

>>> from scipy import signal

>>> signal.ZerosPolesGain([1, 2], [3, 4], 5)
ZerosPolesGainContinuous(
array([1, 2]),
array([3, 4]),
5,
dt: None
)


Construct the transfer function $$H(z) = \frac{5(z - 1)(z - 2)}{(z - 3)(z - 4)}$$ with a sampling time of 0.1 seconds:

>>> signal.ZerosPolesGain([1, 2], [3, 4], 5, dt=0.1)
ZerosPolesGainDiscrete(
array([1, 2]),
array([3, 4]),
5,
dt: 0.1
)