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Specifying log with arbitrary base #4311
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The implementation reason for this is that the "the current void of capabilities" is maybe a bit dramatic :-D |
i know, i have even already attached the screenshot of it. but there has to be some way to specify the base in case of log, or say power in case of extension of
tick marks and grid - yeah, so, how can i do that?
yeah, i agree 😅 , but it is kinda essential for analysis - like say, u are dealing with something where the output which come to say powers of 7 is important. so, keeping track of that (i.e. both the tick marks and grid) becomes essential |
If you known your maths, you should be able to transform your data before plotting.
As you pointed out scaling is (most of the time) a feature of a specific backend (lower level than |
that's not a good suggestion at all... going by that, even the log scaling can be done before plotting, but the option to plot on log scale/log graph exist and that's for a reason... but anyways, thanks for the input. |
Yes, this is to say that log scaling is a convenience provided by Plots, not a necessity. Sorry, maybe the wording was too harsh, but I wanted to point out that nothing prevented you from transforming your data before plotting, achieving the end result. |
just for the records, the problem with that approach is that log scaling doesnt work directly/inline with 2D arrays (i.e. when an array has multiple "series" to be plotted) whereas with scaling it works direct: # Doesn't work on whole list, works only per index
plot( log.( list[ i ] ) ) plot( list, scale = :log ) |
how about `log( base = x )`
**for Fun only:**
& similarly, maybe for future: `pow( val = x , inverse = true )` 😆😆
|
aah, this is painful - what happened 5 days ago, this is third instance of some old email resent "5 days ago" please help me in this misterious auto resending of emails |
ln
,log10
,log2
are listed in there (the defaultgr
backend doesnt support base 2, e as can be seen in the attached image)e.g. from
python
:matplotlib.pyplot
:Originally posted by @yashpalgoyal1304 in #74 (comment)
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