kandi X-RAY | ping.py Summary
kandi X-RAY | ping.py Summary
Network ping with delay, jitter and MOS. The original code was obtained from: The original code has been through a number of authors and iterations.
Top functions reviewed by kandi - BETA
- Create rrd file .
- Calculate the checksum of a source string .
- Send one ICMP messages to another process .
- Receive one ping packet .
- Send a single ping .
- Send a ping .
- Update an rrd file
ping.py Key Features
ping.py Examples and Code Snippets
Trending Discussions on ping.py
Question in short
To have a proper input for pycosat, is there a way to speed up calculation from dnf to cnf, or to circumvent it altogether?
Question in detail
Example Tower puzzle (solved):...
ANSWERAnswered 2022-Mar-19 at 22:23
First, it's good to note the difference between equivalence and equisatisfiability. In general, converting an arbitrary boolean formula (say, something in DNF) to CNF can result in a exponential blow-up in size.
This blow-up is the issue with your
from_dnf approach: whenever you handle another product term, each of the literals in that product demands a new copy of the current cnf clause set (to which it will add itself in every clause). If you have n product terms of size k, the growth is
In your case
n is actually a function of
k!. What's kept as a product term is filtered to those satisfying the view constraint, but overall the runtime of your program is roughly in the region of
O(k^f(k!)). Even if f grows logarithmically, this is still
O(k^(k lg k)) and not quite ideal!
Because you're asking "is this satisfiable?", you don't need an equivalent formula but merely an equisatisfiable one. This is some new formula that is satisfiable if and only if the original is, but which might not be satisfied by the same assignments.
(a ∨ b) and
(a ∨ c) ∧ (¬b) are each obviously satisfiable, so they are equisatisfiable. But setting
b true satisfies the first and falsifies the second, so they are not equivalent. Furthermore the first doesn't even have
c as a variable, again making it not equivalent to the second.
This relaxation is enough to replace this exponential blow-up with a linear-sized translation instead.
The critical idea is the use of extension variables. These are fresh variables (i.e., not already present in the formula) that allow us to abbreviate expressions, so we don't end up making multiple copies of them in the translation. Since the new variable is not present in the original, we'll no longer have an equivalent formula; but because the variable will be true if and only if the expression is, it will be equisatisfiable.
If we wanted to use
x as an abbreviation of
y, we'd state
x ≡ y. This is the same as
x → y and
y → x, which is the same as
(¬x ∨ y) ∧ (¬y ∨ x), which is already in CNF.
Consider the abbreviation for a product term:
x ≡ (a ∧ b). This is
x → (a ∧ b) and
(a ∧ b) → x, which works out to be three clauses:
(¬x ∨ a) ∧ (¬x ∨ b) ∧ (¬a ∨ ¬b ∨ x). In general, abbreviating a product term of k literals with
x will produce k binary clauses expressing that
x implies each of them, and one
(k+1)-clause expressing that all together they imply
x. This is linear in
To really see why this helps, try converting
(a ∧ b ∧ c) ∨ (d ∧ e ∧ f) ∨ (g ∧ h ∧ i) to an equivalent CNF with and without an extension variable for the first product term. Of course, we won't just stop with one term: if we abbreviate each term then the result is precisely a single CNF clause:
(x ∨ y ∨ z) where these each abbreviate a single product term. This is a lot smaller!
This approach can be used to turn any circuit into an equisatisfiable formula, linear in size and in CNF. This is called a Tseitin transformation. Your DNF formula is simply a circuit composed of a bunch of arbitrary fan-in AND gates, all feeding into a single arbitrary fan-in OR gate.
Best of all, although this formula is not equivalent due to additional variables, we can recover an assignment for the original formula by simply dropping the extension variables. It is sort of a 'best case' equisatisfiable formula, being a strict superset of the original.
To patch this into your code, I added:
I try to train Neural Network model in PyTorch Lightning and training fails on validation step where it executes EarlyStopping callback.
The relevant part of the model is below. See, in particular,
validation_step which must log the metrics necessary for Early stopping.
ANSWERAnswered 2022-Mar-16 at 15:39
if you use pytorch-lightning latest version you should want to log the val_accuracy or val_loss while you calling early stopping or similar functions. for more please check out the code below.i think this will definitely helpful for you...
I'm unable to install stackstac on Google Colab. This is reproducible with the code below....
ANSWERAnswered 2022-Mar-16 at 12:28
Protocol was introduced to
typing as of Python 3.8, as can be seen in the docs. You appear to be running Python 3.7, based on your file paths - upgrade to use Python 3.8 or later if you can.
I build the standalone spark cluster on Oracle linux. I add this line in spark-env.sh on Master:...
ANSWERAnswered 2022-Mar-04 at 11:04
I think it was because of network problem. Since when I added this part to spark-submit every thing worked fine.
I have the Python program that works without any issue locally. But when I want to run it in Spark cluster I receive the error about libclntsh.so, the cluster has two nodes.
To explain more, to run the program in the cluster, first I set Master IP Address in spark-env.sh like this:...
ANSWERAnswered 2022-Feb-21 at 14:34
Problem solved. According to the TroubleShooting link, first I create a file InstantClient.conf in /etc/ld.so.conf.d/ PATH and write the path to the Instant Client directory in it.
I have a code called
Trigger.py that works in looping by making a call to another code called
ANSWERAnswered 2022-Jan-28 at 13:38
sys.exit(1) will do exactly that, kill the process running the Python. If you want to stop just the function that is in an infinite loop,
return will work just fine.
We have a data pipeline built in Google Cloud Dataflow that consumes messages from a pubsub topic and streams them into BigQuery. In order to test that it works successfully we have some tests that run in a CI pipeline, these tests post messages onto the pubsub topic and verify that the messages are written to BigQuery successfully.
This is the code that posts to the pubsub topic:...
ANSWERAnswered 2022-Jan-27 at 17:18
We had the same error. Finally solved it by using a JSON Web Token for authentication per Google's Quckstart. Like so:
I am learning python and I came across with package in python. I made a directory containing
shipping.py the code is
ANSWERAnswered 2022-Jan-23 at 08:45
In Python everything is an object. classes, functions, methods, even modules, operators and etc. (except for language tokens and keywords which make statements like
Every class in Python inherits from a base object class.
Functions are not exceptions, They are from type
I'm using Pandas 1.3.2 in a Conda environment.
When importing pandas on a Jupyter Notebook:...
ANSWERAnswered 2021-Aug-25 at 16:53
According to the answer provided in this post it is a bug in
A possible solution is to downgrade it to some earlier version, e.g
pip install pandas==1.3.0
I have a selenium script that I execute in another python program. This program will only execute when I am logged into the server using ssh as root but not executable by the www-data user because it returns with the error:...
ANSWERAnswered 2022-Jan-09 at 18:27
Ideally you should have been able to execute the program as www-data user. However this error message...
No vulnerabilities reported
You can use ping.py like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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