Comments (2)
TL;DR
This kinda works as intended. I get that this can be confusing and I will explicitly report skipped values in the future (soon).
Long version
Using no --entries
option and --entries 0
yields the same results, because a value of 0 is the default for entries. In either case only the fields from which valid measurements can be parsed are counted - meaning only those, that contain data for SYS, DIA and Pulse.
So if you parse this line 144/82/86, 137/81/75, -, 143/80/68
, you get three values, because three valid ones can be parsed.
If entries is set to a value > 0 though, it is guarantied to yield that much measurements per line, even if there are not enough (or more). So None
measurements are created for skipped measurements to keep things aligned.
This is the case for both explicitly skipped (i.g. marked by -
) or implicitly skipped (i.g. not enough values on the line) ones. Such a None
measurement means, here should be one but it was missing.
Since skipped measurements are important in a context where entires is set to some value > 0, they are counted and reported as values too. In a context where entries is not set or < 1, implicitly skipped values can't be detected anyway and so are completely ignored.
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I wrote a quick fix. If you run it against the example file like this :
./bpdiag.py ../examples/bp_values.txt
You should get the following output:
Parsed 24 values (4 skipped)...
Statistics (min, max, avg):
:: SYS...: 119, 144, 135
:: DIA...: 75, 87, 80
:: PULSE.: 60, 99, 71
Only those values explicitly marked are skipped are reported. If you run it with --entries
set, like this:
./bpdiag.py --entries 4 ../examples/bp_values.txt
Parsed 28 values (8 skipped)...
Statistics (min, max, avg):
:: SYS...: 119, 144, 135
:: DIA...: 75, 87, 80
:: PULSE.: 60, 99, 71
You should also get the implicitly skipped ones.
As I said, just a quick fix (I hope). A complete refactoring is due for next month or so. Just comment if you got something else in mind.
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