Step response of a complex LTI system plotted with several parameter variations in Python.

moreStepResponse.py

# Step response graphs
# Python 2.7 with numpy, scipy, and matplotlib
# Based on https://gist.github.com/ofan666/1882562

from numpy import min as nmin
from scipy import linspace
from scipy.signal import lti, step
from matplotlib import pyplot as p

def create_tf(i):
    num = [i.kw*i.kd, i.kw*i.ks]
    den = [i.mc*i.mw, i.kd*(i.mc+i.mw), i.mc*(i.ks+i.kw)+i.ks*i.mw, i.kd*i.kw, i.kw*i.ks]
    print den
    return lti(num, den)

def plotLTI(i, n = 200):
    tf = create_tf(i)
    print tf
    t, s = step(tf)
    t, s = step(tf, T = linspace(nmin(t), t[-1], n))
    p.plot(t, s * i.h)
    p.xlabel('Time / s')
    p.ylabel('Displacement / m')
    p.show()

class Args(object):
    pass

def tf_args(d):
    a = Args()
    a.__dict__.update(d)
    return a

def d():
    plotLTI(tf_args({
        'h': 0.25,
        'mw': 25.0,
        'mc': 625.0,
        'kw': 220000.0,
        'kd': 8000.0,
        'ks': 25000.0,
    }))

def i():
    plotLTI(tf_args({
        'h': 0.25,
        'mw': 25.0,
        'mc': 625.0,
        'kw': 220000.0,
        'kd': 4000.0,
        'ks': 25000.0,
    }))

def ii():
    plotLTI(tf_args({
        'h': 0.25,
        'mw': 25.0,
        'mc': 625.0,
        'kw': 220000.0,
        'kd': 1000.0,
        'ks': 25000.0,
    }))

def iii():
    plotLTI(tf_args({
        'h': 0.25,
        'mw': 25.0,
        'mc': 625.0,
        'kw': 220000.0,
        'kd': 8000.0,
        'ks': 12000.0,
    }))

def iv():
    plotLTI(tf_args({
        'h': 0.25,
        'mw': 25.0,
        'mc': 625.0,
        'kw': 220000.0,
        'kd': 4000.0,
        'ks': 12000.0,
    }))

def v():
    plotLTI(tf_args({
        'h': 0.25,
        'mw': 25.0,
        'mc': 625.0,
        'kw': 220000.0,
        'kd': 1000.0,
        'ks': 12000.0,
    }))