multirate_helper

sk_dsp_comm.multirate_helper.freqz_resp(b, a=[1], mode='dB', fs=1.0, Npts=1024, fsize=(6, 4))[source]

A method for displaying digital filter frequency response magnitude, phase, and group delay. A plot is produced using matplotlib

freq_resp(self,mode = ‘dB’,Npts = 1024)

A method for displaying the filter frequency response magnitude, phase, and group delay. A plot is produced using matplotlib

freqz_resp(b,a=[1],mode = ‘dB’,Npts = 1024,fsize=(6,4))

b = ndarray of numerator coefficients a = ndarray of denominator coefficents
mode = display mode: ‘dB’ magnitude, ‘phase’ in radians, or
‘groupdelay_s’ in samples and ‘groupdelay_t’ in sec, all versus frequency in Hz

Npts = number of points to plot; defult is 1024

fsize = figure size; defult is (6,4) inches

Mark Wickert, January 2015

class sk_dsp_comm.multirate_helper.multirate_FIR(b)[source]

A simple class for encapsulating FIR filtering, or FIR upsample/ filter, or FIR filter/downsample operations used in modeling a comm system. Objects of this class will hold the required filter coefficients once an object is instantiated. Frequency response and the pole zero plot can also be plotted using supplied class methods.

Mark Wickert March 2017

Methods

dn(x[, M_change]) Downsample and filter the signal
filter(x) Filter the signal
up(x[, L_change]) Upsample and filter the signal
zplane([auto_scale, size, detect_mult, tol]) Plot the poles and zeros of the FIR filter in the z-plane
freq_resp  
dn(x, M_change=12)[source]

Downsample and filter the signal

filter(x)[source]

Filter the signal

freq_resp(mode='dB', fs=8000, ylim=[-100, 2])[source]
up(x, L_change=12)[source]

Upsample and filter the signal

zplane(auto_scale=True, size=2, detect_mult=True, tol=0.001)[source]

Plot the poles and zeros of the FIR filter in the z-plane

class sk_dsp_comm.multirate_helper.multirate_IIR(sos)[source]

A simple class for encapsulating IIR filtering, or IIR upsample/ filter, or IIR filter/downsample operations used in modeling a comm system. Objects of this class will hold the required filter coefficients once an object is instantiated. Frequency response and the pole zero plot can also be plotted using supplied class methods. For added robustness to floating point quantization all filtering is done using the scipy.signal cascade of second-order sections filter method y = sosfilter(sos,x).

Mark Wickert March 2017

Methods

dn(x[, M_change]) Downsample and filter the signal
filter(x) Filter the signal using second-order sections
freq_resp([mode, fs, ylim]) Frequency response plot
up(x[, L_change]) Upsample and filter the signal
zplane([auto_scale, size, detect_mult, tol]) Plot the poles and zeros of the FIR filter in the z-plane
dn(x, M_change=12)[source]

Downsample and filter the signal

filter(x)[source]

Filter the signal using second-order sections

freq_resp(mode='dB', fs=8000, ylim=[-100, 2])[source]

Frequency response plot

up(x, L_change=12)[source]

Upsample and filter the signal

zplane(auto_scale=True, size=2, detect_mult=True, tol=0.001)[source]

Plot the poles and zeros of the FIR filter in the z-plane

class sk_dsp_comm.multirate_helper.rate_change(M_change=12, fcutoff=0.9, N_filt_order=8, ftype='butter')[source]

A simple class for encapsulating the upsample/filter and filter/downsample operations used in modeling a comm system. Objects of this class will hold the required filter coefficients once an object is instantiated.

Mark Wickert February 2015

Methods

dn(x) Downsample and filter the signal
up(x) Upsample and filter the signal
dn(x)[source]

Downsample and filter the signal

up(x)[source]

Upsample and filter the signal