'mytype', which spans the same period of time as the input frame, and has 1 data value
'input_type'that contains the value of the
typeof the input frame.
print()statements to print debug messages to our in-app terminal. More information on our in-app terminal can be found below.
search_forsetting, which we will be using later.
data, with 3 fields:
address. The serial data we are looking at will not be configured to produce frames with the
addressfield, so we can ignore that.
decode(frame)function in our HLA will be called once for each frame from the Async Serial analyzer, where:
frame.typewill always be
frame.data['data']will be a `bytes` object with the data for that frame
frame.data['error']will be set if there was an error
Reload Source Filesto reload your HLA:
search_forsetting that we added earlier comes in.
'Hl', let's replace that with the value of
result_typesvariable will need to be updated.
'mytype'will also be updated to
'match'to better represent that the frame represents a matched character.
decode(): we need to update the data in
'char', and update the frame
AnalyzerFrames include a
end_time. These get passed as the second and third parameter of
AnalyzerFrame, and can be used to control the time span of a frame. Let's use it to fill in the gaps between the matching frames.
__init__()to initialize the 2 time variables we will use to track the span of time that doesn't have a match:
decode()to track these variables:
result_typesfor our new