Responding to some recent messages about sample-at-a-time
processing and
filters, it's a common misconception that the proper way to
filter a
signal is to take FFTs, manipulate the signal in the
frequency domain,
and inverse FFT back to a signal. This often leads to
artifacts and poor
quality. Nyquist has a lot of built-in IIR filters that can
be used
individually or in combination.
You can also process samples in XLISP. I tried to give some
helpful
guidance in the manual at the end of the "More
Examples" chapter in the
section "DSP in Lisp". If anyone wants to offer
better text or tell me
what was confusing, I'd be happy to expand or correct the
text.
NEXT TOPIC:
I agree the XLISP backtrace is kind of confusing, but it's
really pretty
simple: the backtrace is just info from the runtime stack,
starting with
the most recently called function and working backward. Each
function is
printed in two parts: The heading "Function: "
precedes the name of the
function, and the heading "Arguments:" heads a
list of arguments passed
to the function. The function is usually something like
#<Closure-REVERB-MONO: #45ba50>, but you can probably
guess that this
means a call to the function declared as REVERB-MONO. The
arguments are
printed one per line, but in many cases, lines wrap, so it
takes some
careful reading to parse them.
The backtrace is made uglier by the fact that functions like
COND, LET,
and SETF all appear. The arguments to these functions are
lists that get
interpreted as code. So often, you'll see lots of code in
the backtrace.
This can actually help figure out exactly how you reached
the error, but
again, it can take some careful reading to interpret this.
I find the backtrace facility indispensable, so if you are
ignoring it
because it looks too ugly, probably you should take a closer
look.
In any case, you'll be happy to hear that SAL has much
prettier
backtraces with line numbers and argument names; maybe we'll
get that
into Audacity before too long.
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