importmatplotlib.pyplotaspltimportnumpyasnpnp.random.seed(19680801)# Fixing random state for reproducibility.# create some data to use for the plotdt=0.001t=np.arange(0.0,10.0,dt)r=np.exp(-t[:1000]/0.05)# impulse responsex=np.random.randn(len(t))s=np.convolve(x,r)[:len(x)]*dt# colored noisefig,main_ax=plt.subplots()main_ax.plot(t,s)main_ax.set_xlim(0,1)main_ax.set_ylim(1.1*np.min(s),2*np.max(s))main_ax.set_xlabel('time (s)')main_ax.set_ylabel('current (nA)')main_ax.set_title('Gaussian colored noise')# this is an inset Axes over the main Axesright_inset_ax=fig.add_axes((.65,.6,.2,.2),facecolor='k')right_inset_ax.hist(s,400,density=True)right_inset_ax.set(title='Probability',xticks=[],yticks=[])# this is another inset Axes over the main Axesleft_inset_ax=fig.add_axes((.2,.6,.2,.2),facecolor='k')left_inset_ax.plot(t[:len(r)],r)left_inset_ax.set(title='Impulse response',xlim=(0,.2),xticks=[],yticks=[])plt.show()

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