When logscale is set on an axis only, its ylogscale ends up at NaN and the graph goes invisible. Docs should mention that logscale must be set globally as well.

It's a fairly common request to get the size of data for each symbol in VersionStore and currently I just use a Mongo js script to get it, but it would be nice to have a util in VersionStore or otherwise to do the same.

It claims that the response shape is {"results": [...]"} but it's actually wrapped in {"queries": [{"results": [...]}, ...]}":

~/D/k/bin $ ./kairosdb.sh run >/dev/null 2>&1 &
[1] 42911
~/D/k/bin $ 
~/D/k/bin $ curl --silent http://localhost:8080/api/v1/datapoints/query/tags -XPOST --data-binary '{"start_r

Currently tslearn/tests/test_estimators.py redefine a custom check_estimator and then monkeypatch some of the tests in sklearn.utils.estimator_checks to work with time series data.

In the latest version scikit-learn introduced parametrize_with_checks which should allow to simplify this quite a bit https://scikit-learn.org/stable/developers/develop.html#rolling-your-own-estimator (e.g. a

ES - v6.5.4
Kibana - v6.5.4
Search guard - v6.5.4
sentinl plugin - v6.5.4

Configure sentinl with some test watcher and action , but when i deleted the watcher from kibana GUI , but still alarm get fired at the regular interval , as i already given required permission at search guard , subsequent index get created at elastic search , manually deleted watcher index but it will auto recr

Today, the administration panel UI lacks some documentation.

To ease initial setup, it would be convenient to have a wizard-like UI when setuping new providers.

Hi,

Would it be possible to update the documentation + other meta data for ts-flint published in PyPI.

https://pypi.org/project/ts-flint/

There are tools which parse this information from PyPI for ex. automated license checkers.

Thanks,
Rohan

It's possible that I'm simply missing it in the documentation, but it doesn't appear as if there is any support for bind parameters in this client.

Could this be added?
https://docs.influxdata.com/influxdb/v1.4/tools/api/#bind-parameters

Hello

doing empirical tests + looking at go-carbon code looks like that you indeed follow the priority value in the storage-schemas.conf definitions.

For example

[should_apply_first]
pattern = ^stats\..*
priority = 1
retentions = 10s:1h

[should_not_apply_to_stats]
pattern = ^.*
priority = 10
retentions = 60s:1d

will apply a retention of 1 minute for 1 day to **ev

Description

Steps/Code to Reproduce

<< your code here >>

Versions

🐛Bug report

ValueList ignores the style parameters provided by its parent component (LabelAxis).

I'm setting the property "style" in LabelAxis to this, as specified in the LabelAxis docs:

            style={{
              axis: {
                fill: 'black',
                stroke: 'black',
                background: 'black',
                color: 'black',
              

Increase code coverage by:

• Adding tests for quandl API and alphavantager API. Include encrypted API key to pass Travis.
• Review code cov and add tests as appropriate.

nowadays, docs with rarely interpretation is difficult to understand the algorithm,
Such as bayes rule sets and other Underdogs have little references.
If can provide a common introduce in interface level may be good for programmers
who have little information of algorithm to start

While working with the source code, I was wondering what the workflow is. Could you please document that somewhere in the README.md file?

E.g. how are the makefiles generated?

E.g. What is the connection between src, Release/src and Debug/src (and if they need syncing, how is that done)? Why isn't the delta between Release and Debug not just a configure option/make variable?

NTP
RedisTimeSeries/RedisTimeSeries#195

According to the documentation, when this flag is set to True only means that distance function use precompiled functions in C.
But when I check both values they are so different as we can check in the image bellow.

I assume that this is a wrong behavior, I´m wrong?
Could you te

Hello,

I haven't tested append() yet, and I was wondering if duplicates are removed when an append is managed.
I had a look in collection.py script and following pandas function are used:
combined = dd.concat([current.data, new]).drop_duplicates(keep="last")

After a look into pandas documentation, I understand that duplicate lines are removed, only the last occurence is kept.