fir: add ParallelHBFCascade

This commit is contained in:
Robert Jördens 2016-12-08 15:30:26 +01:00
parent d303225249
commit a629eb1665
2 changed files with 55 additions and 7 deletions

View File

@ -4,12 +4,13 @@ import numpy as np
from migen import *
def halfgen4(up, n):
def halfgen4(width, n):
"""
http://recycle.lbl.gov/~ldoolitt/halfband
params:
* `up` is the stopband width, as a fraction of input sampling rate
* `up` is the passband/stopband width, as a fraction of
input sampling rate
* `n is the order of half-band filter to generate
returns:
* `a` is the full set of FIR coefficients, `4*n-1` long.
@ -17,7 +18,7 @@ def halfgen4(up, n):
"""
npt = n*40
wmax = 2*np.pi*up
wmax = 2*np.pi*width
wfit = (1 - np.linspace(0, 1, npt)[:, None]**2)*wmax
target = .5*np.ones_like(wfit)
@ -106,3 +107,44 @@ class ParallelFIR(Module):
xj for xj, cj in zip(x[-1 - j::-1], coefficients) if cj == c
]))
self.sync += self.o[j].eq(reduce(add, o) >> shift)
def halfgen4_cascade(rate, width, order=None):
"""Generate coefficients for cascaded half-band filters.
:param rate: upsampling rate. power of two
:param width: passband/stopband width in units of input sampling rate.
:param order: highest order, defaults to :param:`rate`"""
if order is None:
order = rate
coeff = []
p = 1
while p < rate:
p *= 2
coeff.append(halfgen4(width*p/rate/2, order*p//rate))
return coeff
class ParallelHBFUpsampler(Module):
"""Parallel, power-of-two, half-band, cascading upsampler.
Coefficients should be normalized to overall gain of 2
(highest/center coefficient being 1)."""
def __init__(self, coefficients, width=16, **kwargs):
self.parallelism = 1
self.latency = 0
self.width = width
self.i = Signal((width, True))
###
i = [self.i]
for coeff in coefficients:
self.parallelism *= 2
# assert coeff[len(coeff)//2 + 1] == 1
hbf = ParallelFIR(coeff, self.parallelism, width, **kwargs)
self.submodules += hbf
self.comb += [a.eq(b) for a, b in zip(hbf.i[::2], i)]
i = hbf.o
self.latency += hbf.latency
self.o = i

View File

@ -81,13 +81,19 @@ def _main():
coeff = fir.halfgen4(.4/2, 8)
coeff_int = [int(round(c * (1 << 16 - 1))) for c in coeff]
if False:
dut = fir.FIR(coeff_int, width=16)
# print(verilog.convert(dut, ios={dut.i, dut.o}))
tb = Transfer(dut)
else:
coeff = [[int(round((1 << 26) * ci)) for ci in c]
for c in fir.halfgen4_cascade(8, width=.4, order=8)]
dut = fir.ParallelHBFUpsampler(coeff, width=16, shift=25)
print(verilog.convert(dut, ios=set([dut.i] + dut.o)))
elif True:
dut = fir.ParallelFIR(coeff_int, parallelism=4, width=16)
# print(verilog.convert(dut, ios=set(dut.i + dut.o)))
tb = ParallelTransfer(dut)
else:
dut = fir.FIR(coeff_int, width=16)
# print(verilog.convert(dut, ios={dut.i, dut.o}))
tb = Transfer(dut)
x, y = tb.run(samples=1 << 10, amplitude=.8)
tb.analyze(x, y)
plt.show()