Hi all.I'm getting this error when trying to use the AMC block. I generated
the graph with tensorflow 0.12.1
Loading: "/home/dandrspc/default/src/gr-inspector/examples/amc_cnn.grc"
>>> Done
Generating: '/home/dandrspc/default/src/gr-inspector/examples/top_block.py'
Executing: /usr/bin/python2 -
Please stay on the mailing list.
Running make without successfully running CMake is meaningless.
Also errors pertaining to third party libraries are in 99% of cases
simply caused by the user having competing versions of the same library
installed, and that will likely be the case here for UHD.
Ne
Seems you didn't quite install things into a place CMake looks into by
default; quite possibly, there will be needs to tell CMake about
/usr/local/include/volk (which is what I guess is the default
installation prefix if you build from source manually).
Anyway, this wouldn't have helped you! Pleas
Folks,
I am trying to install GNUradio from source:
1. I downloaded a copy of the gnuradio master repository into my local
folder /home/xroot/GNUradio2/,
2. I created a subdirectory called "build",
3. within that sub-directory, I can execute "cmake ../".
When I execute "make", I ke
You can't actually control it, but you can set a minimum number, yes.
However, for tagging in invervals, you wouldn't even need that, just
look for the thing that initiates your tagging, and add new tags every
so and so many items. You can just keep the count between calls to
work. A function has n
Hmm ok, I feel like perhaps I've misunderstood some fundamental mechanic of
GNURadio.. is it within my power to define the exact number of samples that
should be available on the next call to the work function of e.g. a sync
block?
Den tis 28 maj 2019 kl 16:28 skrev Müller, Marcus (CEL) :
> But y
But you're free to do that in any block you desire, so you can write a
normal sync block and just always consume all input :)
On Tue, 2019-05-28 at 16:26 +0200, Sebastian Sahlin wrote:
> Hi,
>
> I suppose not - I just figured that using a tagged stream block would be
> useful since then I'd be ab
Hi,
I suppose not - I just figured that using a tagged stream block would be
useful since then I'd be able to iterate over the entire packet in one work
function call.
Den tis 28 maj 2019 kl 16:22 skrev Müller, Marcus (CEL) :
> But that block doesn't have to be a Tagged Stream Block itself, righ
But that block doesn't have to be a Tagged Stream Block itself, right?
On Tue, 2019-05-28 at 16:14 +0200, Sebastian Sahlin wrote:
> Hi Marcus,
>
> Aha, that explains it.. bummer! Perhaps you could advise me on an alternative
> solution to my problem. What I am trying to achieve with the tagged st
Hi Marcus,
Aha, that explains it.. bummer! Perhaps you could advise me on an
alternative solution to my problem. What I am trying to achieve with the
tagged stream block is to apply tags at an interval on a packet; the values
are taken from an array that I want to iterate over. However, since the
Hi Sebastian,
I must admit that I don't remember whether the TSB block base was
correctly wrapped for Python (darn it, first I write something, and
then you find a glaring counterexample); in fact, there's not a single
test case for that in the main GNU Radio tree, which probably means
"no".
Best
Hi Florian - My initial thoughts are: why 5e6 points (so many!), and how are
you accumulating that many points inside GR? In order to get that many points
accumulated, you'll need to set the I/O buffering on the FFT block to at least
that number of items, and probably more -- not impossible, but
GNU C++ version 8.2.0; Boost_106501; UHD_3.14.0.HEAD-0-g6875d061
GNUradio version: 3.7.13.4
USRP hardware: B210
Dear all,
for my flowgraph I need an FFT with 5e6 or more points. My problem is that my
flow graph is not executing, more precisely it seems to block when allocating
the memory fo
Hi,
I'm attempting to create a tagged stream block in Python using the
following constructor:
class test_tagged_stream(gr.tagged_stream_block):
def __init__(self, test_param):
gr.tagged_stream_block.__init__(self,
name="test_tagged_stream",
in_sig=[numpy.compl
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