thanks for all the developmenters.
i can't access to intetent all the time, is there any pleace where i can download the offline tutorials ?

I became quite confused by the Algorithms to perform MCMC section.

The issue is that steps 3-4:
"3. Accept/Reject the new position based on the position's adherence to the data and prior distributions (ask if the pebble likely came from the mountain).
4.A If you accept: Move to the new position. Return to Step 1.
4.B Else: Do not move to new position. Return to Step 1."
imply that

理论上，所有的 G2 版本都有这个问题， 带来的问题：

每次 resize 触发的时候，因为 canvas 大小有父容器大小决定，所以 resize 都会导致图形比之前的高度大 5px。

解决办法：

对 canvas 设置 css 样式。

1. 设置 display: inline;
2. 设置 vertical-align: center (只要不是 baseline 即可)

可以在 G 层解决掉，也可以在 G2 层创建 G.Canvas 之后，再设置样式。

I don't know if this is worth documenting, but I was playing with the CLI referenced using pageres and came up with a fun little ("little" 😜 ) one-liner:

TMP=$(mktemp)".html";OUT=gitstats-"$(date '+%Y-%m-%d')".png;rm $OUT && git-stats --raw | git-stats-html -o $TMP && pageres $TMP 775x250 --filename="gitstats-<%=date%>" && imgcat $OUT

Aside from a little tempfile and date manipulation to

The documentation of the boltons.timeutils.daterange function only mention date objects as input, but I discovered that it works with datetime objects as well. Explicitly stating so would be great. Thanks!

Need to do some better handling of low-observation models in plot_diagnostics. These are models that shouldn't really be estimated, and we can't really make the plots work, but we shouldn't raise exceptions.

• Any dataset with less than 10 observations will raise an error computing the error autocorrelations:

mod = sm.tsa.statespace.SARIMAX(np.random.normal(size=10), order=(10, 

I think there is a little typo which gives the following error:
TypeError: init() got an unexpected keyword argument 'mu'

I checked the "mixture_gaussian_gibbs.py" example and I suggest the following suggestion
params = {'loc': tf.zeros(5), 'scale': tf.ones(5)}

https://github.com/blei-lab/edward/blob/352596c3bc77e1cb5c01f77ac3283a53c74dbf21/edward/models/param_mixture.py#L36

Description

Calling fit method of Pipeline object throws an expection: UnboundLocalError: local variable 'cloned_transformer' referenced before assignment, when the memory argument is passed an argument. Therfore I am unable to cache any transformers (especially during hyperparameter tuning using a Pipeline object.

Steps/Code to Reproduce

Example:

from imblearn.pipel

Please add an example for FourierTransform.FFT Method.

TODO (optional): Describe a specific scenario you would like to see addressed.

I would like to use this functionality on a 1 dimensional array of floating point values for the purpose of audio analysis.

Help Topic: http://accord-framework.net/docs/html/M_Accord_Math_FourierTransform_FFT.htm

See:
gonum/gonum#845 (comment)

Hey there @JonnyWong16 , wanted to provide some content for the Wiki, and can't for the life of me figure out how to do a PR for Wiki content.

Below is an Nginx reverse proxy example that will allow users to access Tautulli via tautulli.url.com, and redirects HTTP requests to HTTPS. This configuration passes SSL Labs' test with an "A" grade.

DH Params creation vi

The file ~/.tokeirc is ignored when tokei is not run in ~. tokei should use three sources of configuration: defaults < ~/.tokeirc < ./.tokeirc

The current behavior is not convenient for me. Most of my command line tools such as Bash and Vim conveniently read their config from ~. I move around directories and run tokei. I also use tokei to calculate the number of lines of code in Git

SeparableConv enables a much greater range of low power, low latency models. MobileNet and other low cost high performance networks generally utilizes SeparableConv for it's efficiency. I am building a real probabilistic inference version of a MobileNet which uses SeparableConv. I am using regular tfp convolution ops for now for initial validation but it is much less efficient and will not be fit

If my training samples very large than system memory, XLearn will terminate without nothing print。 That's not the point， I strongly suggest that you can supply a function for us to config log print/

Hi,
I have prepared these two example input files:

• example.csv https://gist.github.com/a2768e81ef94802079df8acb21b3c2eb
• loop.txt https://gist.github.com/d10c542f5f9b796388ca158b513c4619

If I run

parallel --colsep "\t" 'mlr --csv filter -S '$comune=="{1}"' example.csv>{1}.csv' :::: ./loop.txt

I have always

mlr DSL: syntax error at "=="
mlr filter: syntax error o

From the docs for https://simplestatistics.org/docs/#standardnormaltable:

The table used is the cumulative, and not cumulative from 0 to mean.

I'm having trouble understanding this sentence. What is meant by cumulative and not cumulative?

Checklist

Please ensure the following tasks are completed before filing a bug report.

• Read and understood the [Code of Conduct][code-of-conduct].
• Searched for existing issues and pull requests.

Description

Description of the issue.

The following code produces an array whose shape does not match what I'd expect:

The help currently reads:
Vector S get; set;
Gets the singular values (Σ) of matrix in ascending value.

It should be:
descending order of magnitude.

Use mvn release:prepare to build the docs and copy them to the /docs directory

I found several useful applications of pseudo-random number sampling in the past. In particular:

• Inverse transform sampling
• Gibbs sampling

(This issue serves a reminder to add the respective methods. Pull requests always welcome.)

When trying to show any of the listed example outputs in the Readme.md, I'm forwarded to a weird site:

Example link:

• http://githubproxy.ejwa.se/wiki/ejwa/gitinspector/examples/django_output.html

The figures in index.rst have URLs that don't work. I looked for them in the source tree, but I don't find them there.