2016-12-21 04:39:51 +08:00
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from math import floor
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2016-12-08 02:14:23 +08:00
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from operator import add
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from functools import reduce
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2016-12-21 04:39:51 +08:00
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from collections import namedtuple
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2016-12-08 02:14:23 +08:00
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import numpy as np
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2016-12-21 04:39:51 +08:00
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2016-12-08 02:14:23 +08:00
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from migen import *
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2016-12-18 04:19:46 +08:00
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def halfgen4(width, n, df=1e-3):
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2016-12-08 02:14:23 +08:00
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"""
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http://recycle.lbl.gov/~ldoolitt/halfband
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params:
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2016-12-08 22:30:26 +08:00
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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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2016-12-08 02:14:23 +08:00
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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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implement wisely.
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"""
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npt = n*40
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2016-12-08 22:30:26 +08:00
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wmax = 2*np.pi*width
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2016-12-08 02:14:23 +08:00
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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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basis = np.cos(wfit*np.arange(1, 2*n, 2))
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weight = np.ones_like(wfit)
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2016-12-18 04:19:46 +08:00
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f0 = None
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2016-12-08 02:14:23 +08:00
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for i in range(40):
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l = np.linalg.pinv(basis*weight)@(target*weight)
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2016-12-18 04:19:46 +08:00
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err = np.fabs(basis@l - .5)
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f = np.max(err)/np.mean(err)
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if f0 and (f0 - f)/(f0 + f) < df/2:
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break
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f0 = f
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weight[err > (1 - df)*np.max(err)] *= 1 + 1.5/(i + 11)
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2016-12-08 02:14:23 +08:00
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a = np.c_[l, np.zeros_like(l)].ravel()[:-1]
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a = np.r_[a[::-1], 1, a]/2
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return a
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2016-12-21 04:39:51 +08:00
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_Widths = namedtuple("_Widths", "A B P")
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2016-12-08 02:14:23 +08:00
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2016-12-21 04:39:51 +08:00
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_widths = {
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"DSP48E1": _Widths(25, 18, 48),
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}
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2016-12-08 20:05:13 +08:00
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class ParallelFIR(Module):
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"""Full-rate parallelized finite impulse response filter.
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2016-12-15 02:15:50 +08:00
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Tries to use transposed form as much as possible.
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2016-12-21 04:39:51 +08:00
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:param coefficients: tap coefficients (normalized to 1.),
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increasing delay.
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2016-12-08 20:05:13 +08:00
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:param parallelism: number of samples per cycle.
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:param width: bit width of input and output.
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2016-12-21 04:39:51 +08:00
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:param arch: architecture (default: "DSP48E1").
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2016-12-08 20:05:13 +08:00
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"""
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2016-12-21 04:39:51 +08:00
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def __init__(self, coefficients, parallelism, width=16,
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2017-06-29 17:24:56 +08:00
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arch="DSP48E1", cull_delays=()):
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2016-12-08 20:05:13 +08:00
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self.width = width
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self.parallelism = p = parallelism
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n = len(coefficients)
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2016-12-15 02:15:50 +08:00
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# input and output: old to new, decreasing delay
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2016-12-08 20:05:13 +08:00
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self.i = [Signal((width, True)) for i in range(p)]
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self.o = [Signal((width, True)) for i in range(p)]
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2017-06-29 17:33:19 +08:00
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self.latency = (n + 1)//2//p + 2
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2016-12-21 04:39:51 +08:00
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w = _widths[arch]
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2016-12-08 20:05:13 +08:00
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2016-12-21 04:39:51 +08:00
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c_max = max(abs(c) for c in coefficients)
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c_shift = bits_for(floor((1 << w.B - 2) / c_max))
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self.coefficients = cs = [int(round(c*(1 << c_shift)))
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for c in coefficients]
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2017-06-13 02:07:23 +08:00
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assert max(bits_for(c) for c in cs) <= w.B
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2017-06-29 18:08:43 +08:00
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max_out = sum(abs(c)*(1 << w.A - 1) for c in cs)
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assert max_out <= (1 << w.P - 1) - 1, (bits_for(max_out), w)
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2016-12-08 20:05:13 +08:00
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2016-12-21 04:39:51 +08:00
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###
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2016-12-15 02:15:50 +08:00
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# Delay line: increasing delay
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2017-06-29 01:09:21 +08:00
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x = [Signal((w.A, True), reset_less=True) for _ in range(n + p - 1)]
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2017-06-13 02:07:23 +08:00
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2016-12-21 04:39:51 +08:00
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for xi, xj in zip(x, self.i[::-1]):
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2017-06-29 01:55:15 +08:00
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self.comb += xi.eq(xj)
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2016-12-21 04:39:51 +08:00
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for xi, xj in zip(x[len(self.i):], x):
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self.sync += xi.eq(xj)
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2016-12-08 20:05:13 +08:00
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2016-12-15 02:15:50 +08:00
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for delay in range(p):
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2017-06-29 01:09:21 +08:00
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o = Signal((w.P, True), reset_less=True)
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2017-06-29 17:33:19 +08:00
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self.sync += self.o[delay].eq(o >> c_shift)
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2016-12-09 00:00:39 +08:00
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# Make products
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tap = delay
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2016-12-21 04:39:51 +08:00
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for i, c in enumerate(cs):
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2016-12-08 20:05:13 +08:00
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# simplify for halfband and symmetric filters
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2016-12-21 04:39:51 +08:00
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if not c or c in cs[:i]:
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2016-12-08 20:05:13 +08:00
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continue
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2016-12-21 04:39:51 +08:00
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js = [j + p - 1 for j, cj in enumerate(cs) if cj == c]
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2016-12-15 02:15:50 +08:00
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m = Signal.like(o)
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o0, o = o, Signal.like(o)
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2016-12-21 04:39:51 +08:00
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q = Signal.like(x[0])
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2017-06-29 17:24:56 +08:00
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if tap + p <= js[0]:
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2016-12-15 02:15:50 +08:00
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self.sync += o0.eq(o + m)
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2017-06-29 17:24:56 +08:00
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tap += p
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2016-12-15 02:15:50 +08:00
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else:
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self.comb += o0.eq(o + m)
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2017-06-29 17:24:56 +08:00
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assert min(js) - tap >= 0
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2017-06-29 18:08:43 +08:00
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js = [j for j in js
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if (p - 1 - j - tap) % p not in cull_delays]
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2017-06-29 17:24:56 +08:00
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if not js:
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continue
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self.comb += q.eq(reduce(add, [x[j - tap] for j in js]))
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2016-12-21 04:39:51 +08:00
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self.sync += m.eq(c*q)
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2016-12-15 02:15:50 +08:00
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# symmetric rounding
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2017-06-29 17:24:56 +08:00
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if c_shift > 1 and delay not in cull_delays:
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2017-06-29 01:55:15 +08:00
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self.comb += o.eq((1 << c_shift - 1) - 1)
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2016-12-21 04:39:51 +08:00
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class FIR(ParallelFIR):
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def __init__(self, *args, **kwargs):
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super().__init__(self, *args, parallelism=1, **kwargs)
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self.i = self.i[0]
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self.o = self.o[0]
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2016-12-08 22:30:26 +08:00
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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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2017-06-29 18:08:43 +08:00
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2016-12-21 04:39:51 +08:00
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Coefficients are normalized to a gain of two per stage to compensate for
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the zero stuffing.
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2016-12-08 22:30:26 +08:00
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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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2016-12-21 04:39:51 +08:00
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coeff.append(2*halfgen4(width*p/rate/2, order*p//rate))
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2016-12-08 22:30:26 +08:00
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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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2016-12-21 04:39:51 +08:00
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self.parallelism = 1 # accumulate
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self.latency = 0 # accumulate
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2016-12-08 22:30:26 +08:00
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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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2017-06-29 17:24:56 +08:00
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hbf = ParallelFIR(coeff, self.parallelism, width=width,
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cull_delays={0}, **kwargs)
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2016-12-08 22:30:26 +08:00
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self.submodules += hbf
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2017-06-29 01:13:43 +08:00
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self.comb += [a.eq(b) for a, b in zip(hbf.i[1::2], i)]
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2016-12-08 22:30:26 +08:00
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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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