forked from M-Labs/artiq
fir: add ParallelHBFCascade
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@ -4,12 +4,13 @@ import numpy as np
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from migen import *
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def halfgen4(up, n):
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def halfgen4(width, n):
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"""
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http://recycle.lbl.gov/~ldoolitt/halfband
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params:
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* `up` is the stopband width, as a fraction of input sampling rate
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* `up` is the passband/stopband width, as a fraction of
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input sampling rate
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* `n is the order of half-band filter to generate
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returns:
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* `a` is the full set of FIR coefficients, `4*n-1` long.
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@ -17,7 +18,7 @@ def halfgen4(up, n):
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"""
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npt = n*40
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wmax = 2*np.pi*up
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wmax = 2*np.pi*width
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wfit = (1 - np.linspace(0, 1, npt)[:, None]**2)*wmax
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target = .5*np.ones_like(wfit)
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@ -106,3 +107,44 @@ class ParallelFIR(Module):
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xj for xj, cj in zip(x[-1 - j::-1], coefficients) if cj == c
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]))
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self.sync += self.o[j].eq(reduce(add, o) >> shift)
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def halfgen4_cascade(rate, width, order=None):
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"""Generate coefficients for cascaded half-band filters.
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:param rate: upsampling rate. power of two
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:param width: passband/stopband width in units of input sampling rate.
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:param order: highest order, defaults to :param:`rate`"""
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if order is None:
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order = rate
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coeff = []
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p = 1
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while p < rate:
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p *= 2
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coeff.append(halfgen4(width*p/rate/2, order*p//rate))
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return coeff
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class ParallelHBFUpsampler(Module):
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"""Parallel, power-of-two, half-band, cascading upsampler.
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Coefficients should be normalized to overall gain of 2
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(highest/center coefficient being 1)."""
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def __init__(self, coefficients, width=16, **kwargs):
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self.parallelism = 1
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self.latency = 0
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self.width = width
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self.i = Signal((width, True))
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###
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i = [self.i]
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for coeff in coefficients:
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self.parallelism *= 2
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# assert coeff[len(coeff)//2 + 1] == 1
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hbf = ParallelFIR(coeff, self.parallelism, width, **kwargs)
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self.submodules += hbf
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self.comb += [a.eq(b) for a, b in zip(hbf.i[::2], i)]
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i = hbf.o
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self.latency += hbf.latency
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self.o = i
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@ -81,13 +81,19 @@ def _main():
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coeff = fir.halfgen4(.4/2, 8)
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coeff_int = [int(round(c * (1 << 16 - 1))) for c in coeff]
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if False:
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dut = fir.FIR(coeff_int, width=16)
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# print(verilog.convert(dut, ios={dut.i, dut.o}))
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tb = Transfer(dut)
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else:
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coeff = [[int(round((1 << 26) * ci)) for ci in c]
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for c in fir.halfgen4_cascade(8, width=.4, order=8)]
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dut = fir.ParallelHBFUpsampler(coeff, width=16, shift=25)
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print(verilog.convert(dut, ios=set([dut.i] + dut.o)))
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elif True:
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dut = fir.ParallelFIR(coeff_int, parallelism=4, width=16)
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# print(verilog.convert(dut, ios=set(dut.i + dut.o)))
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tb = ParallelTransfer(dut)
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else:
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dut = fir.FIR(coeff_int, width=16)
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# print(verilog.convert(dut, ios={dut.i, dut.o}))
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tb = Transfer(dut)
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x, y = tb.run(samples=1 << 10, amplitude=.8)
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tb.analyze(x, y)
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plt.show()
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