tachymeter | Go library for timing things | Time Series Database library

by jamiealquiza Go Version: v2.0.0 License: MIT

X-Ray Key Features Code Snippets Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | tachymeter Summary

tachymeter is a Go library typically used in Database, Time Series Database applications. tachymeter has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

Tachymeter captures event timings and returns latency and rate statistics: "In a loop with 1,000 database calls, what was the 95%ile and lowest observed latency? What was the per-second rate?". Tachymeter stores data in a lossless sliding window. This means it's accurate but take o(n) space in relation to the desired sample size.

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Support

tachymeter has a low active ecosystem.

It has 99 star(s) with 6 fork(s). There are 2 watchers for this library.

It had no major release in the last 12 months.

There are 6 open issues and 26 have been closed. On average issues are closed in 92 days. There are 4 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of tachymeter is v2.0.0

Quality

tachymeter has no bugs reported.

Security

tachymeter has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

tachymeter is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

tachymeter releases are available to install and integrate.

Installation instructions are not available. Examples and code snippets are available.

Top functions reviewed by kandi - BETA

kandi has reviewed tachymeter and discovered the below as its top functions. This is intended to give you an instant insight into tachymeter implemented functionality, and help decide if they suit your requirements.

Main entry point .
genGraphHTML returns a HTML representation of the timeline event .
New returns a Tachymeter .
scale returns the scale of x
SetWallTime sets the wall time

Get all kandi verified functions for this library.

tachymeter Key Features

No Key Features are available at this moment for tachymeter.

tachymeter Examples and Code Snippets

No Code Snippets are available at this moment for tachymeter.

Community Discussions

Trending Discussions on tachymeter

Get Pivot values on specific condition

Curve fitting with SciPy's least_squares()

QUESTION

Get Pivot values on specific condition

Asked 2020-Oct-13 at 08:15

I have query in SQL SEVRER -

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ANSWER

Answered 2020-Oct-13 at 08:15

First make UNPIVOT, then exclude the N values. After that make a PIVOT. You may want to make it dynamic.

It should be something like this:

Source https://stackoverflow.com/questions/64329845

QUESTION

Curve fitting with SciPy's least_squares()

Asked 2018-Mar-17 at 17:52

I'm doing least squares curve fitting with Python and getting decent results, but would like it to be a bit more robust.

I have data from a first order LTI system, more specifically the speed of a motor that is read by a tachymeter. I'm trying to fit the step response of the motors so I can deduce its transfer function.

The speed (v(t)) has the following form: v(t) = K * (1 - exp(-t/T))

I'm having some outliers in the data I use though, and would like to mitigate them. This mostly happens when the speeds becomes constant. Say the speed is 10000 units, I sometimes get outliers that are 10000 +/- 400. I wonder how to set my f_scale parameter given I want my data points to stay within +/- 400 of the "actual" speed (mean). Should I set f_scale to 400 or 800? I'm not sure what exactly I should set there.

Thanks

EDIT: Some data.

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ANSWER

Answered 2018-Mar-17 at 17:52

I have constructed a minimal example which is for a curve similar to yours. If you had posted actual data instead of a picture, this would have gone a bit faster. The two key things to understand about robust fitting with least_squares is that you have to use a different value for the loss parameter than linear and that f_scale is used as a scaling parameter for the loss function.

Basically, from the docs, least_squares tries to

Source https://stackoverflow.com/questions/49339079

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install tachymeter

You can download it from GitHub.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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