Hi Al,
That really clears things up conceptually. Thanks for the insight.
Given that, I went back and modified the dsp test case to use a scaling
factor of 15, normalized input, and normalized output, so the block
invocation was "dsp.fir_ccf (src_coeff, 15, 1, 0, 0, 0, 0)". Running
the test provides:
-0.0102 - 0.0102i
-0.0104 - 0.0103i
-0.0105 - 0.0105i
-0.0106 - 0.0106i
-0.0107 + 0.0010i
0.0111 + 0.0031i
0.0334 + 0.0061i
0.0671 + 0.0102i
0.1122 + 0.0154i
However, this differs from the output of the gr.fir_filter_ccf block and
the result of direct computation in MATLAB:
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
I've checked the magnitude and phase of each of these results, and it
doesn't look like they're a simple rotation or multiple of each other.
I thought that it might just not work for decimal sources/coefficients,
so I adjusted the tests so that src = (1,1,1,1,1,1,1,1,1) and src_coeff
= (1,1,1,1,1).
Since we no longer needed to scale it before or after, our block
invocation is "dsp.fir_ccf (src_coeff, 15, 1, 1, 1, 0, 0)". This gives
the output:
1.0e+04 *
3.2748 + 3.2751i
3.2762 + 3.2752i
3.2762 + 3.2767i
3.2763 - 3.2768i
-3.2768 - 0.0001i
0 - 0.0002i
0 - 0.0003i
0 - 0.0004i
0 - 0.0005i
0
0
0
0
0
2.8678 - 3.2752i
-3.2757 - 3.2751i
-3.2757 + 0.0001i
0.0005 - 3.2768i
-3.2768
The output from the gr.fir_filter_ccf test is the first nine elements of
the MATLAB output:
1
2
3
4
5
5
5
5
5
Finally, I thought that the issue might be that I'm not normalizing my
source coefficients. So, I normalized them in MATLAB, yielding
src_coeff = (0.4472, 0.4472, 0.4472, 0.4472, 0.4472), which provided the
output:
1.0e+03 *
6.5440 + 6.5450i
6.5500 + 6.5460i
6.5500 + 6.5520i
6.5510 + 6.5530i
6.5530 - 0.0010i
0 - 0.0010i
0 - 0.0020i
0 - 0.0020i
0 - 0.0030i
What am I doing wrong?
Thanks,
Chris
On 7/13/2011 7:14 PM, Almohanad Fayez wrote:
Hey Chris, if you reached this far I'm assuming that the new packages
have solved your issues ... Since you're passing normalized values to
the DSP you will need to scale them or they will be converted to zeros
when moved to the DSP
float fixed
0.3333 = 0
3.3333 = 3
33.333 = 33
so your scaling factor should be 15. Regarding input/output signature
it allows you to define if the input is normalized (signature = 0)
meaning that the easycom-gpp library would need to scale it before
transferring it to the dsp and the same for the output you'll tell it
if it should scale it back to normalized numbers or should it keep it
as fixed point numbers. The motivation for this is the USRP1 with
non-uhd drivers would provide fixed point data during receive mode and
normalized data for transmit mode.
al
src_coeff, 0, 1, 0, 0, 0, 0)
-----Original Message-----
From: Christopher Dean <christopher.d...@ll.mit.edu>
To: Almohanad Fayez <alfa...@aol.com>
Cc: discuss-gnuradio <discuss-gnuradio@gnu.org>
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 = (0.01+0.11j,
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()
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