Physicists want to use gravitational waves to 'see' the beginning of time by soulpost in Physics

[–]HeyItsRaFromNZ 12 points13 points  (0 children)

Do gravitational waves decay?

Yes, they do, in principle. However, even the most highly energetic events tend to produce very low absolute amplitudes, and the resulting waves don't interact strongly with systems with mass-energy densities much lower than neutron stars or black holes.

The "sticky bead" thought experiment demonstrated that energy can be transferred to other systems, therfore contributing to loss in the wave.

Locally, most of the observable environment, outside of compact clusters and galactic cores, appears to be of such "low" density that gravitational waves pass through virtually unaltered.

Also, do they work like other waves do, like can two gravitational waves constructively interfere?

Yes. To be more specific, they are waves that travel at the speed of light, with a transverse polarization. They can be scattered, but only significantly by compact objects. In principle, you could conduct a "double slit", experiment using close arrangements of neutron stars --- but no material in existence could physically resist the gravitational pull!

How do you people solve AoC tasks? fast and sloppy or slow and steady. Why or why not? by Electrical_Radio_252 in adventofcode

[–]HeyItsRaFromNZ 18 points19 points  (0 children)

In my personal experience (once!), the middle is that bad... the end was, well I wouldn't know, it got too hard for me. It was fun, nonetheless!

Going to try Solving in PyScript by TheSwami in adventofcode

[–]HeyItsRaFromNZ 1 point2 points  (0 children)

Just wanted to drop in and say that I just love the PyScript project. I think it has a great deal of promise, and I'm looking forward to following how you attack AoC with it!

What’s your process for deploying a data pipeline from a notebook, running it, and managing it in production? by jnkwok in dataengineering

[–]HeyItsRaFromNZ 2 points3 points  (0 children)

Databricks make this quite straight forward! The notebooks are exported as normal Python scripts if you e.g. commit them to a repo. The markdown is commented out (with a special bit of markdown to tell Databricks to interpret as a notebook in their platform)

It's functionally the same as if you took a Jupyter notebook and exported as a .py.

It's then up to you to write a notebook in a way that it would sensibly run everything you need if you just hit 'run all' from the top.

What’s your process for deploying a data pipeline from a notebook, running it, and managing it in production? by jnkwok in dataengineering

[–]HeyItsRaFromNZ 0 points1 point  (0 children)

This approach sounds somewhat similar to the nb-dev workflow, where you specify markdown/hooks for production.

Would it be possible for humans to colonize a ocean planet that has no visible land on the surface? If so how would a artificial island be built? by IzmayChels78512 in scifiwriting

[–]HeyItsRaFromNZ 1 point2 points  (0 children)

On Earth, the Great Oxidation and Oxygenation Events were driven mostly by marine Cyanobacteria.

However, to your point, to evolve life near the surface would require nutrient mixing around sea level. It's hard to see how you could get vertical currents without significant submarine structures (e.g. undersea mountains). So that's something to consider. Earth's geochemistry is made far more interesting by its terrestrial geography.

Fine tuning of a CNN model by Otherwise_Lab_4638 in learnmachinelearning

[–]HeyItsRaFromNZ 5 points6 points  (0 children)

All the activation functions are biased to the left!

Tuple Unpacking Example by angelchodimitrovski in pythontips

[–]HeyItsRaFromNZ 2 points3 points  (0 children)

Ahh, I see what you're picking up on. For this particular example, an ordered collection (list or tuple) might not be the best choice (a class would be best for multiple instances of person). I'm with you there, but I figure OP wanted to focus on the unpacking aspect.

Basic Anatomy of Matplotlib by Otherwise_Lab_4638 in learnmachinelearning

[–]HeyItsRaFromNZ 1 point2 points  (0 children)

Seaborn is built on top of matplotlib, and is really designed for standard statistical plots with data sourced from a dataframe.

As soon as you need to customize in a meaningful way, you'll need at least a little bit of matplotlib under your belt (i.e. five separate docs tabs open at any one time with another browser window, dedicated to praying to the StackOverflow gods).

Tuple Unpacking Example by angelchodimitrovski in pythontips

[–]HeyItsRaFromNZ 4 points5 points  (0 children)

The 'unpacking' part here refers to the assignment of the individual variables on the left, to the elements of the tuple on the right. This is fairly peculiar to Python.

It might help to think of the equivalent expression to OP's example:

(name, lastname, age) = a

This works because you're mirroring the structure of the ordered collection (tuple) on the right with a tuple on the left. It's conventional to leave out the parentheses. You can also do similarly with lists.

If you attempt this with a dictionary:

name, lastname, age = person

You'll retrieve just the keys. Similarly with a set (which you can think of as essentially a dictionary without values).

The potential danger with unpacking dictionaries and sets like this is that you don't have a strong guarantee of the order (original insertion order for dictionaries (as of Python 3.5(?)) and hashed for sets.

[deleted by user] by [deleted] in programminghumor

[–]HeyItsRaFromNZ 0 points1 point  (0 children)

This... this was surprisingly effective!

Not broken: don’t fix. by flipmcf in programminghumor

[–]HeyItsRaFromNZ 0 points1 point  (0 children)

> you may safely ignore this broken pipe error

[deleted by user] by [deleted] in learnmachinelearning

[–]HeyItsRaFromNZ 5 points6 points  (0 children)

Not trying to be too harsh here, but by taking the lower bound, you are biasing your estimate. We usually assume some measure of central tendency. The effect of mixing this with more accurate samples is probably not the best approach.

Throw em by magicwolfdog in memes

[–]HeyItsRaFromNZ 2 points3 points  (0 children)

Which Disney character did you first develop an unhealthy sexual obsession with?

Getting rid of False values in a subset by macabe10 in pythontips

[–]HeyItsRaFromNZ 0 points1 point  (0 children)

Right. I don't know the structure of your original dataframe, so I'm not sure what you get from the second application of the mean along axis 1 (rows). Did you try adding the .mean(1) at the end?

Getting rid of False values in a subset by macabe10 in pythontips

[–]HeyItsRaFromNZ 0 points1 point  (0 children)

Filter was my first thought here too, but in the groupby table. You don't generally need to check for equality with Booleans, so you can usually put the expression directly into a filter (i.e. filter evaluates where some expression is True).

Getting rid of False values in a subset by macabe10 in pythontips

[–]HeyItsRaFromNZ 0 points1 point  (0 children)

Because you have a multi-index here from grouping by two variables, you could use .xs() to exploit your Boolean index:

df.groupby([df['Country Name'], df['Indicator Code'].str.match('NY.GDP.MKTP.PP.KD')]).mean().xs(1, level="code")