Feat / logfile analysis

[WilliamHPNielsen]

Changes proposed in this pull request:

• Add a minimodule for logfile analysis
• Add an example notebook with a crazy real-world example of an SR860 failing mid-run

@QCoDeS/core

[jenshnielsen]

Mypy is complaining. I think this is because you need an explicit import of dateutil.parser see https://stackoverflow.com/questions/23385003/attributeerror-when-using-import-dateutil-and-dateutil-parser-parse-but-no

It would be interesting to see if there are any recovering slowdowns. Could you do a plot of all time stamps larger than x where x is normaltime*1.1 or something like that

[codecov]

Codecov Report

Merging #1093 into master will not change coverage.
The diff coverage is n/a.

@@           Coverage Diff           @@
##           master    #1093   +/-   ##
=======================================
  Coverage   79.78%   79.78%           
=======================================
  Files          48       48           
  Lines        6664     6664           
=======================================
  Hits         5317     5317           
  Misses       1347     1347

[sohailc]

consider rewriting the above as

ntimes = np.zeros((2, len(firsttimes)).astype("datetime64[ns]")

for count, times in enumerate([firsttimes, secondtimes]): 
	
	if "," in times.iloc[0]:
		ntimes[count] = times.str.replace(",", ".")
	else:
		ntimes[count] = times 

timedeltas = np.diff(ntimes, axis=1).astype(float) * 1E-9

[WilliamHPNielsen]

I'm not sure... that snippet will not work as is. I modified it to work (spot three differences 😛 ):

    ntimes = np.zeros((2, len(firsttimes))).astype("datetime64[ns]")

    for count, times in enumerate([firsttimes, secondtimes]):
        if "," in times.iloc[0]:
            ntimes[count] = times.str.replace(",", ".")
        else:
            ntimes[count] = times 

    timedeltas = np.squeeze(np.diff(ntimes, axis=0).astype(float) * 1E-9)

which is actually slightly (2.5%) slower than the original. But I get your dissatisfaction with the two identical if statements.

[WilliamHPNielsen]

Should we put this in? It's not very great, but it's also not harmful in any way, and it does have some utility.

[astafan8]

agree, it's a nice util.