reliability | Reliability engineering toolkit for Python - https | Analytics library
kandi X-RAY | reliability Summary
kandi X-RAY | reliability Summary
reliability is a Python library for reliability engineering and survival analysis. It significantly extends the functionality of scipy.stats and also includes many specialist tools that are otherwise only available in proprietary software.
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Top functions reviewed by kandi - BETA
- Calculate the least squares
- Color a string
- Generate a pandas DataFrame containing plot positions
- Linear regression
- Plots exponential probability plot
- Evaluate the Exponential distribution
- Compute the quantile of the distribution
- Generates a QQQ Q Q QQ Q Q Q Q
- Downsampling of x and y
- Calculate the HF distribution
- Plot points
- Calculate the least squares least squares
- Plot the probability density function
- Plot the probability density
- Plot the Gamma distribution
- Plot the Normal distribution
- Plot the Gaussian distribution
- Plot the beta distribution
- Generate a PSD plot of the distribution
- Plot the model
- Generate a plot of life stress plots
- Plot the distribution
- Generate a networkx diagram from stress and cycles
- Generate a QQ - Q Q Q - Q plot
- Plots the probability distribution of a distribution
- Plot the exponential distribution
reliability Key Features
reliability Examples and Code Snippets
|--timestamp-|------date time----|-resource-|p |block|s |e|rt |occupied
1529998904000|2018-06-26 15:41:44|HelloWorld|20|0 |20|0|0 |0
1529998905000|2018-06-26 15:41:45|HelloWorld|20|5579 |20|0|728 |0
1529998906000|2018-06-26 15:41:46|HelloWorld|
try (Entry entry = SphU.entry("HelloWorld")) {
// Your business logic here.
System.out.println("hello world");
} catch (BlockException e) {
// Handle rejected request.
e.printStackTrace();
}
// try-with-resources auto exit
List rules = new ArrayList<>();
FlowRule rule = new FlowRule();
rule.setResource("HelloWorld");
// set limit qps to 20
rule.setCount(20);
rule.setGrade(RuleConstant.FLOW_GRADE_QPS);
rules.add(rule);
FlowRuleManager.loadRules(rules);
d.update(dict(s.stripped_strings for s in e.select('dl')))
...
d.update({s.dt.text:float(s.dd.text.split()[0]) for s in e.select('dl')})
data.append(d)
...
{'Safety': 5.0, 'Technology': 5.
out = df.explode(df.columns.tolist()).reindex(['Reviewer_name','Review_date','Review_overall_rating','Review_title','Review_content'], axis=1)
Reviewer_name Review_date R
# User's table row is locked until session is commited or rolled back.
user = session.query(User).filter(User.id == current_user_id).with_for_update().first()
# Or session.query(User).get(current_user_id, with_for_update=True)
# Manipulat
os.popen("/usr/bin/nvm use v14.2.0")
subprocess.Popen(['bash', '-c', '. ~/nvm/nvm.sh; nvm'])
subprocess.Popen(['bash', '-c', '. ~/nvm/nvm.sh; nvm use v14.2.0; nvm list'],
s
PRE = "https://www.",
DOMAIN = "ebay-kleinanzeigen.de",
PRE = "https://www."
DOMAIN = "ebay-kleinanzeigen.de"
chrome_options.add_argument('--remote-debugging-port=9222')
chrome_options.binary_location = "/usr/bin/google-chrome"
executable_path="/usr/local/bin/chromedriver"
inp = """header1, it is 1a.4
blahblahblah1
header2, it is 2esd3
hlahblahblah2
header3, it is unf3d
blahblahblah3"""
matches = re.findall(r'\S+,.*?\n.*?(?=\n|$)', inp, flags=re.S)
print(matches)
['header1, it is 1a.
Community Discussions
Trending Discussions on reliability
QUESTION
hopefull someone can shed some light on this topic and here are some of my questions:
- How do big ecommerce websites manage their images for their websites?
- Is there any Best Practices should be consider when deciding where to keep websites images?
- I have heard to keep the images in multiple folder structure on the same server where the website is hosted so websites can render them easily and fast since they are all on same server - Is this the idea solution?
- How do professionals or big ecommerce handle images storage and maintain website images reliability and stability?
- Is Azure or AWS etc best place to store images for websites rendering?
Thanks in advance!
...ANSWER
Answered 2021-Jun-15 at 02:52Keeping the files in the same server comes with more risk, if your server crashes or region goes down your application stopped as well as your files not gonna render if you are using those files separately for different applications like mobile applications.
In this case, users will also face a high loading time for those media files if the users are not in the same zone as your application hosted.
The best practice to store the image/media files on some cloud storage like S3 or Azure Blob then connect it with some CDN like CloudFront or Azure CDN.
Now you can serve your media files via CDN which will act as a global caching system for your media files.
QUESTION
I have a dataframe on which I use psych::alpha. In the output there are general confidence boundaries around a general cronbach's alpha value. I want to access those but they don't appear in the results when I save the output as a variable. In the documentation they're called itemboot.ci but that doesn't exist in the alpha object.enter code here
...ANSWER
Answered 2021-Jun-13 at 13:26When you print an object, either by using print
or by sending it to the R console, some extra processing may happen. Every object (almost always) has its own print
and in this case you can see that the print.psych
method (called behind the scenes instead of print
on any psych package object) is doing the following with your object of (sub)class alpha
:
QUESTION
I am trying to create a class for calibrating a classifier. I have been reading resources on probability calibration and I am a bit confused on which dataset should we calibrate the classifier. I created a class that split the training set to further train and validation the set. Then, the classifier is first fitted to the train set and predicts the uncalibrated probability on the validation set.
Then, I create a cal_model instance of the CalibrationCV class and then fit it to the validation set and predict calibrated probabilities of the validation set again.
Could someone take a look at the code below and correct the code for me?
...ANSWER
Answered 2021-Jun-11 at 14:06the calibration_curve code is correct. I am comparing the logistic regression calibration versus the xgboost calibration. the dataframes hold predict_proba[:,1] values or the probability of happening. see (https://github.com/dnishimoto/python-deep-learning/blob/master/Credit%20Loan%20Risk%20.ipynb)
QUESTION
library(mirt) #this contains a dataset called deAyala.
library(psych) #this contains the alpha() function.
alpha(deAyala)
...ANSWER
Answered 2021-Jun-05 at 09:41You can get rid of the warning bit by wrapping it with suppressWarnings()
but the first bit of the message looks like just a print statement in the alpha()
function. This will work though
QUESTION
So i have this nodejs that was originaly used as api to crawl data using puppeteer from a website based on a schedule, now to check if there is a schedule i used a function that link to a model query and check if there are any schedule at the moment.
It seems to work and i get the data, but when i was crawling the second article and the next there is always this error UnhandledPromiseRejectionWarning: Error: Request is already handled!
and followed by UnhandledPromiseRejectionWarning: Unhandled promise rejection. This error originated either by throwing inside of an async function without a catch block, or by rejecting a promise which was not handled with .catch().
and it seems to take a lot of resource from the cpu and memory.
So my question is, is there any blocking in my code or anything that could have done better.
this is my server.js
...ANSWER
Answered 2021-Jun-05 at 16:26I figured it out, i just used puppeteer cluster.
QUESTION
I have a use case for which QLDB makes the most sense. I also think the Outbox pattern makes sense for data reliability. However, I am worried about polluting the Journal with the outbox entries.
My understanding is that while I can have my 'outbox' table separate from my main data table, the journal is shared across the entire ledger. It seems that the outbox pattern traditionally uses a relational DB where the concept of an immutable journal just isn't a concern.
Is this going to be a problem as the data set grows? More so, is there an alternate pattern that would make more sense to use?
...ANSWER
Answered 2021-Jun-01 at 22:03Since the journal is an immutable history of every transaction ever committed to the ledger, if you use the Outbox pattern with QLDB, your ledger will contain a permanent history of messages that passed through your Outbox table. This is great if you need an unfalsifiable audit history of the messages queued for sending and a record of them being sent ("deleted" from the table). However, if you don't need that, then you'll be paying storage for those messages for the life of the ledger and not getting much value from it.
The typical event-driven approach would be to use QLDB's streaming feature, which associates a Kinesis Data Stream to your ledger. Every time you commit a transaction, QLDB will publish the transaction to the Kinesis Data Stream. This enables you to drive events from transactions occurring in your ledger. With this approach, you commit your business data to the ledger without worrying about the Outbox table. The document should contain the information you would need in your messaging. Upon commit, QLDB pushes the document(s) from the transaction into Kinesis where you process it using a Lambda function that sends the message onward.
One thing to note is that QLDB offers an at-least-once guarantee of delivering data into Kinesis. This means that you'll need to identify and handle (or just tolerate) potential duplicate messaging. You should always be thinking about idempotence in distributed systems anyway, though.
If you don't want to pay for Kinesis and don't need a real-time approach, there are things you can do with scheduled QLDB exports into S3 and some batch processing of the export files, but I'd start with streaming. DM me if you want to hear more about the export approach.
See also:
QUESTION
I'm working on a small project to learn puppeteer and discord bots, thought it would be interesting to combine the two and make a weird cyborg bot thing that is essentially a bot but a normal user. I've set up the command handlers, etc, and I've created an 'invite' command that takes one of the arguments that the person provides (the code of the server invite) and uses it to auto-invite itself.
for example typing in discord: invite 78uHjkaf
This semi-works. Not really. It'll work the first time, but never again and I'll have to restart the thing. I keep trying to add a page.close();
hoping that it will solve the problem but then it won't work at all. How can I make this work consistently and reusably? - Note that my command handler works fine. The entire issue is located within the following code. (I hope)
Semi reliable.
...ANSWER
Answered 2021-Jan-06 at 11:49Why are you using Puppeteer? It's easier to use the Discord private API instead.
QUESTION
I have my own FIFO class that works OK, but I'd like to extend its flexibility.
Right now, the data struct that goes in the FIFO is defined in the FIFO class, so every FIFO object has the same data struct.
It would be nice if every object could define its own FIFO struct and pass it to the FIFO class. The FIFO class shouldn't care what the structure looks like, it just queues and enqueues whatever struct got passed to the FIFO constructor. This is actually well beyond my current skill set, but I thought with a little help, maybe I could pull it off.
Here's a simple example of what I'm trying to do that I haven't been able to compile:
...ANSWER
Answered 2021-May-26 at 00:32Is there a way to pass different structs to a single class constructor
No, it isn't possible to pass a type as a function argument (and constructors are (special member-) functions).
However, it is possible to pass types as template arguments, and a constructor can be an instance of a function template... Or the class itself can be instance of a class template. For example:
QUESTION
When trying to send my app to app store, I'm receiving the following message: ITMS-90809: Deprecated API Usage - New apps that use UIWebView are no longer accepted. Instead, use WKWebView for improved security and reliability. Learn more (https://developer.apple.com/documentation/uikit/uiwebview).
But my simulator log shows
...ANSWER
Answered 2021-May-23 at 18:23Cordova has already deprecated the WKWebView usage. So in order to fix those and future issues update cordova version to 10 and android/ios projects to newest.
Android 9.1 Ios 6.2
Here is the deprecation message: https://cordova.apache.org/2021/02/07/deprecate-wkwebview-engine.html
QUESTION
I'm trying to create a matrix to eventually run inter-rater reliability. I am trying to populate a matrix with TRUE and FALSE (or 1/0) based on whether a string is present in a row with a matching ID in a second or third matrix. I've included what that should look like at the bottom.
Below is my reproducible example, including the two existing matrices and what I've tried so far to produce the final matrix I want. I was able to get it to the point where I can confirm I'm selecting the correct columns that match the matrix I'm wanting to match (see output with "m1" in all columns that have "m1" in the column name). I haven't figured out how to get to the next stage of properly matching the id column between m1.mat
and the final matrix, reliability.ex
. In excel this would be something like a VLOOKUP, but when I search for VLOOKUP equivalents in R, I just get join/merge functions, which I don't think will work for what I need, but maybe I'm wrong. I tried doing all this in excel but ultimately got stuck and would rather have it in R if possible anyway.
ANSWER
Answered 2021-May-21 at 06:15library(dplyr)
library(tidyr)
make_rmat <- function(mat) {
mat %>%
data.frame() %>%
pivot_longer(!id) %>%
pivot_wider(!name, names_from=value, values_fn = list) %>%
select(!`NA`) %>%
unnest(!id) %>%
mutate(across(!id, ~ifelse(is.na(.x), 0, 1)))
}
reliability.desired <- merge(make_rmat(m1.mat), make_rmat(m2.mat), by="id",suffixes=c("_m1","_m2"))
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