time-series

Hi,

first thanks for this awesome software. But I have some trouble and I don't know how to proceed. First I try to find out what else I could provide for this report to be a good bug report.

First, I use the latest version (v1.14.0) from openSUSE build Service. I know, I should compile it by my self to avoid any other causes for this behavior. But for now I still use this package from there

https://github.com/taosdata/TDengine/blob/develop/src/client/src/tscParseLineProtocol.c

val_s <= 9223372036854775807L is always true regardless of the values of its operands. This occurs as the logical second operand of "&&".

Relevant telegraf.conf:

[[inputs.openweathermap]]
  app_id = "xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
  

Is your feature request related to a problem?

I like to use the chart tab in the console. However, the chart scale is not customisable and starts at 0. This makes it hard to visualise data where the changes are relatively small.

Describe the solution you'd like.

Either

• Dynamic scaling of the charts based on results values
• Manual scaling by adding a range min/max input in the con

it's becoming more time-consuming and error-prone to manually re-test all the demos following internal refactorings and API adjustments.

now that the API is fleshed out a bit, it's possible to test a large amount of code (non-granularly) without having to simulate all interactions via Puppeteer or similar.

a lot of code can already be regression-tested by simply running all the demos and val

Please add LinkedIn Greykite time series model as a part of sktime.

Describe the bug

• W-THU is not supported right now. It only works if user specifies seasonal_period in setup

To Reproduce

Expected behavior
Would have expected it to automatically infer the freq = 52 from there.

提问题？
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提建议？
请写明白建议原因，即为何有此建议。

提修复PR？
请说明为何做此修改，需要做好测试。

提Feature？
建议先将想法提出，不着急写代码，与社区同道沟通，大家觉得OK再做代码实现

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另外，我们是在做开源软件，不是服务于您的企业，做您的乙方，您一分钱没付，就不要颐指气使了，认同我们这个社区，则参与进来，不认同，就不参与，谢谢理解

Use case:
Selecting a subset of array elements of an existing array inside the database without the need to unnest the array first or use a user-defined function.

CREATE TABLE t1 (id INTEGER, tags ARRAY(TEXT));
INSERT INTO t1 (id, tags) VALUES (1, ['database','search engine','document store']);

SELECT array_slice(tags,2,3) FROM t1;
--> ['search engine','document s

Recently found your library and it is really great and handy!
The evaluation of the forecasting performance is best done using a cross-validation approach. The backtest_forecasting()-function does that - although it currently iterates and re-trains the model on every single time step. In my application, I am training ten-thousands of different time series and it becomes computationally unfeasib

Description

(A clear and concise description of what the feature is.)

• util.cumsum implementation https://github.com/awslabs/gluon-ts/blob/master/src/gluonts/mx/util.py#L326 does not scale under mx.ndarray
• cumsum is 2-5 times slower than nd.cumsum under both mx.sym and mx.ndarray, and even fails for large 4-dim input

Sample test

Code

# import ...
def test_

Hi, Thanks for the awesome library!

So I am running a Kmeans on lots of different datasets, which all have roughly four shapes, so I initialize with those shapes and it works well, except for just a few times. There are a few datasets that look different enough that I end up with empty clusters and the algorithm just hangs ("Resumed because of empty cluster" again and again).

I conceptually