-----Original Message-----
From: Christopher Dean
<address@hidden>
To: Almohanad Fayez
<address@hidden>
Cc: discuss-gnuradio
<address@hidden>
Sent: Wed, Jul 13, 2011 3:37 pm
Subject: gr-dsp Library Block Parameters
Hi
Al,
We're trying to use your gr-dsp library and are
having difficulty verifying the output of your
DSP.fir_ccf blocks. To allow for easy comparison
to the standard filter type, gr.fir_filter_ccf, we
generated a very simple block diagram in GRC. This
consisted of a vector source, an fir_filter_ccf
block, and a file sink. All of the original data
and filter taps are the same, but the outputs are
not lining up with their expected values.
I have included the full script file at the bottom
of this email. The relevant calls to the filter
constructors are shown in the text.
For instance:
We have:
src = "">
0.02+0.22j,
0.03+0.33j,
0.04+0.44j,
0.05+0.55j,
0.06+0.66j,
0.07+0.77j,
0.08+0.88j,
0.09+0.99j)
src_coeff = (0.101, 0.102, 0.103, 0.104, 0.105)
Without scaling (scaling_factor = 0, so scaling by
2^0 = 1):
gr.fir_filter_ccf(1, src_coeff)
This produces output:
0.0010 + 0.0111i
0.0030 + 0.0334i
0.0061 + 0.0671i
0.0102 + 0.1122i
0.0154 + 0.1689i
0.0205 + 0.2255i
0.0257 + 0.2822i
0.0308 + 0.3388i
0.0360 + 0.3954i
What we thought would be the equivalent call
using the fir_ccf block is:
self.gr_fir_filter_xxx_0 = dsp.fir_ccf
(src_coeff, 0, 1, 0, 0, 0, 0)
This produces output:
0
0
0
0
0
0
0
0
0
With scaling (scaling_factor = 15, so scaling by
2^15):
gr.fir_filter_ccf(1, src_coeff)
The data was manually scaled by 2^15 in MATLAB,
producing output:
1.0e+04 *
0.0033 + 0.0364i
0.0100 + 0.1096i
0.0200 + 0.2199i
0.0334 + 0.3677i
0.0503 + 0.5533i
0.0672 + 0.7389i
0.0840 + 0.9245i
0.1009 + 1.1102i
0.1178 + 1.2958i
dsp.fir_ccf (src_coeff, 15, 1, 0, 1, 0, 0)
* output-signature = 1, so we want the output to
be have the same scale factor that it is on the
DSP.
This produces output:
1.0e+03 *
0.3350 + 0.3350i
0.3400 + 0.3390i
0.3430 + 0.3440i
0.3470 + 0.3470i
0.3500 - 0.0340i
-0.3650 - 0.1000i
-1.0960 - 0.2000i
-2.1990 - 0.3350i
-3.6770 - 0.5030i
In neither of these cases do the dsp
implementation and the gpp implementation give the
same output.
I'm pretty sure that the issue is in my
interpretation of your parameters. I've already
been using the online documentation to figure out
what the parameters do, so I know the basic jist
of it, but obviously I haven't got it figured out
yet. Could you please explain the use of the
scaling_factor, input_signature, and
output_signature parameters in more detail?
Also, for the input_signature parameter to be 0,
like it is in the examples qa_fir_ccf2.py and
qa_fir_ccf3.py, doesn't the input need to be
normalized? By my understanding, normalized
vectors are unit vectors, so they should have
length 1. But src (above) has length 9, so it's
not normalized and the input_signature parameter
should be 1. Is that correct?
Thanks,
Chris
-------------------------------------------------------------------------------
#!/usr/bin/env python
##################################################
# Gnuradio Python Flow Graph
# Title: Top Block
# Generated: Wed Jul 13 11:09:34 2011
##################################################
from gnuradio import eng_notation
from gnuradio import gr
from gnuradio.eng_option import eng_option
from gnuradio.gr import firdes
from optparse import OptionParser
from gnuradio import dsp
class top_block(gr.top_block):
def __init__(self):
gr.top_block.__init__(self, "Top Block")
##################################################
# Variables
##################################################
self.samp_rate = samp_rate = 32000
##################################################
# Blocks
##################################################
self.gr_vector_source_x_0 =
gr.vector_source_c((0.01+0.11j,0.02+0.22j,0.03+0.33j,0.04+0.44j,0.05+0.55j,
0.06+0.66j, .07+0.77j, 0.08+0.88j, 0.09+0.99j),
False, 1)
#self.gr_fir_filter_xxx_0 = gr.fir_filter_ccf(1,
(0.101, 0.102, 0.103, 0.104, 0.105))
# Uncomment the previous line, comment in the
next three lines to switch from dsp-based to
gpp-based filter.
src_coeff = (0.101, 0.102, 0.103, 0.104, 0.105)
dsp.init()
self.gr_fir_filter_xxx_0 = dsp.fir_ccf
(src_coeff, 15, 1, 0, 1, 0, 0)
self.gr_file_sink_0 =
gr.file_sink(gr.sizeof_gr_complex*1,
"filtertest-dsp2.dat")
self.gr_file_sink_0.set_unbuffered(False)
##################################################
# Connections
##################################################
self.connect((self.gr_vector_source_x_0, 0),
(self.gr_fir_filter_xxx_0, 0))
self.connect((self.gr_fir_filter_xxx_0, 0),
(self.gr_file_sink_0, 0))
def get_samp_rate(self):
return self.samp_rate
def set_samp_rate(self, samp_rate):
self.samp_rate = samp_rate
if __name__ == '__main__':
parser = OptionParser(option_class=eng_option,
usage="%prog: [options]")
(options, args) = parser.parse_args()
if gr.enable_realtime_scheduling() != gr.RT_OK:
print "Error: failed to enable realtime
scheduling."
tb = top_block()
tb.start()
raw_input('Press Enter to quit: ')
tb.stop()