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@syvb syvb commented Sep 27, 2022

Description

Updates documentation for the addition of integral/interpolated_integral in Toolkit 1.11. I based the content for these based on average/interpolated_average, since the functions are very similar.

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Allow 10 minutes from last push for the staging site to build. If the link doesn't work, try using incognito mode instead. For internal reviewers, check web-documentation repo actions for staging build status. Link to build for this PR: http://docs-dev.timescale.com/docs-sv-toolkit-1-11

@syvb syvb requested a review from charislam September 27, 2022 15:19
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Looks great! Some minor nits, mostly non-blocking

|-|-|-|
|`prev`|`TimeWeightSummary`|The TimeWeightSummary from the prior interval, used to interpolate the value at `start`. If `NULL`, the first timestamp in `tws` will be used as the start of the interval.|
|`next`|`TimeWeightSummary`|The TimeWeightSummary from the following interval, used to interpolate the value at `start` + `interval`. If `NULL`, the last timestamp in `tws` will be used as the end of the interval.|
|`prev`|`TimeWeightSummary`|The TimeWeightSummary from the prior interval, used to interpolate the value at `start`. If `NULL`, the first timestamp in `tws` is used as the start of the interval.|
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I really, really appreciate that you're following the linter guidelines! 🙌🏼

Comment on lines +26 to +30
Time weighted integrals are useful when you need a time-weighted sum of
irregularly sampled data. For example, if you bill your users based on
irregularly sampled CPU usage, you need to find the total area under the graph
of their CPU usage. You can use a time-weighted integral to find the total
CPU-hours used by a user over a given time period.
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This is great! Love the real-world example

@syvb syvb merged commit f5246c7 into latest Sep 28, 2022
@syvb syvb deleted the sv/toolkit-1-11 branch September 28, 2022 01:08
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4 participants