discipline | Flexible law checking for Scala | Testing library

I have a list of map, so I want to check If the value I type contains any of the key value before adding.

here is my code:

I want a circular convolution function where I can set the number N as I like.

All examples I looked at like here and here assume that full padding is required but that not what I want.

I want to have the result for different values of N

• so input would N and and two different arrays of values
• the output should be the N point convolved signal

Here is the formula for circular convolution. Sub N can be seen as the modulo operation.

taken from this basic introduction

This answer is a suitable solution when the array a is piled accordingly to the different cases of N.

When I find time I will post a complete answer, meanwhile feel free to do so.

Thanks to @André pointing this out in the comments!

I need help, how can I shorten this code. I have a response message which I need to deserialize based on code type. the deserialization is of different classes. Below code works if I write for each loop inside each "if"statement but I am looking for a better way to write this

I'd like to examine the Psychological Capital (a construct consisting of four dimensions, namely hope, optimism, efficacy and resiliency) of founders using computer-aided text analysis in R. So far I have pulled tweets from various users into R. The data frame contains of 2130 tweets from 5 different users in different periods. The dataframe is called before_failure. Picture of original data frame

I have then used the quanteda package to create a corpus, perfomed tokenization on it and removed redundant punctuatio/numbers/symbols:

I'm reviewing and experimenting with outlier flagging strategies, and keep running into references to Sn and Qn from Rousseeuw and Croux in Alternatives to the Median Absolute Deviation.

http://web.ipac.caltech.edu/staff/fmasci/home/astro_refs/BetterThanMAD.pdf

They sound quite excellent, and seem to be widely used in academic and applied stats across disciplines. I checked Google Scholar, and that paper has over 2,100 citations.

The appealing feature of this technique is that it isn't heavily impacted by asymmetric distributions. Which is what we've got, most of the time. Sometimes quite extremely.

This is of course available in R, but I'm not a stats person, we don't have server-side access to R (or Python), and would like to do some searches directly in Postgres. I haven't been able to find anything in any SQL idiom, and am hoping that some stats lover out there has some Postgres code up their sleeve.

I have two different data (students performance).

dict1 --- performance for the 1st semester
dict2 --- performance for the 2nd semester

I need to concatenate two df's so that sub-columns for semesters appear in the columns of disciplines.

I have recently started studying PostgreSQL and am having trouble creating triggers. In the specific case I should check that a male athlete cannot participate in a competition for women and vice versa; in the match_code attribute an 'M' or an 'F' is inserted as the third to last character to identify that the race is for males or females (for example: 'Q100x4M06'); only one character, 'M' or 'F', is stored in the gender attribute. I would therefore need to understand how to compare them and activate the trigger when they are not correctly entered in the participation table. This is what i have assumed but i know it is wrong, it is just an idea, can someone help me?

I have the following models:

The identical dataset of funding dates vs disciplines plotted differently using plotly.express (px) lines and plotly.graph_objects (go) scatter traces. The shape of the plots look identical, but dates are wrong in the go traces. Any suggestions on what may be wrong here? Thank you.

Using px.line: