You are really great at teaching, sir! I love the way you show examples, tracing back if something «went too fast». You dont assume we know all the small things you know so really well yourself, which is easy to forget about when explaining things in my opinion. Superb stuff!
you must have read my mind! Just starting an in-depth course in classical mechanics, those symbolic Lagrangians will save me a lot of time, thank you! :)
The default solution to `sols` on my system has turned out substantially more complex than shown in your video. Consequently, in order to obtain exactly the same results, smp.simplify() had to be added as such: sols[sp.diff(theta, t,t)].simplify() sols[sp.diff(z, t,t)].simplify() Frankly, I'm still awed by the fact that presumably, human engineers, had actually managed to create the SymPy algorithms capable of dealing with such complex expressions flawlessly.
Thanks, mate, this helps me a ton. I thought I'd need to completely switch to Mathematica for my project, but this gets me where I need to in Python. Much appreciated.
At 26:20, I understand what is happening but I don't understand how the code works. f and g are first instantiated as `UndefinedFunction` type. How is it that I can call them right away with arguments. My understanding is you call a certain method of an object defined within its class type. But here we're calling the object itself? That feels kinda funky to me. What is going on?
Hey Mr. P Solver, great contents on your channel ! new subscriber here. I have a small suggestion, you could flip your camera recording horizontally and it would look like you're looking towards the right area on the screen.
I don't get why you said that it's a good practice to use smp.Rational(1/2) instead of just writing 1/2 or 0.5 there. In larger problems, will the latter be not more time-saving in nature?
Looks like a typo has occurred in your part of the code (2*n*(sp.factorial(n+l)))) \ If you look at the formula above you will see that it should be (2*n*(sp.factorial(n+1)))) \ leaving us with differing numeric results after substitution further down. Consequently: Interpreting the above formula correctly with SymPy results in a linear relationship with plt.scatter(ns, ds) and not an exponential one. I strongly feel that the discrepancy in the interpretation of the original formula ought to be double-checked, before more students who are not entirely on par with quantum mechanics find themselves stranded.
thanks, very useful video! I tried to calculate the integral that is taken by residue (from the theory of a function by a complex variable) but sumpy give useless answer. Do you know how help program and give some advice that it is necessary to solve it residue? so my problem: integrated (dw/((w^2-1)^2+w^2) from -inf to +inf) I now answer, it very simple: pi
How is your menu on pressing tab totally different from mine (yours have them sorted in instanced, functions , etc.)? Can you let me know (or make a video) on all the settings and extensions you have on your setup? Thank you!
Excellent video, thank you very much! Not entirely related but do you have any book/course recommendation for an introduction to differential equations?
12 mins into, I got this error: multiple generators [y, sin(y**2)] No algorithms are implemented to solve equation y*sin(y**2) + z** It seems I cannot find x,y,z values that make he function F = 0. Any suggestions?
let's say i solve a differential equation using dsolve. Now i want to use the output say y(t) = .......(something). Is there any way to use the result to solve for t when y=2?
Idea - What is energy? - My guess - If you iterate y = model(X) and loss = mean((X-y)**2) that is let y -> X an image then using only one image X it will succeed. But y will not become X completely there is a residual y = X + dX. Its the dX that is the universe energy. Change something with dX and the approximation of the function restores the energy to its vibrant small state. Small compared to the entire universe. Its like hydro if you place something infront of the flow of water it will move it same with dX differences. Thats is energy. So it open ups new opportunities. Energy is dependent on squaring a function the error. So if the err0(t[123]) ^ 2 = err1(t[123]) ^ 4 then you got much stronger energy. So accumulate energy from timed extraction for that super power.
Dude as someone that's new to python but an experienced developer with a Physics undergrad... Python is the best and the worst of everything. The tools are incredible... but EVERYTHING. Literally everything apart from Numpy and Pandas and a few others use this insanely lazy and horribly put together auto-generated documentation. That will be the death of Python I promise.
Also... fun fact... when you highlighted those functions, you can run help(justAboutAnyPackage.thatMysteriousFunction) and it will print a **usually** more informative docstring than what's available on these $%#% autogenerated documentation sites. If you use an ide you'd have to run that in the terminal, but jupyter will print it out right in the output.
This video takes my math friends to ⇨ SymPy :) Some people use: import sympy as sy, and .n() instead of .evalf() . Application for atom -- thanks for answering my childhood curiosity!
There he goes SymPying for science.
Yeah right, I've always thought the SymPy package was for symps.
There also is a package called SimPy for discrete event simulation
You are really great at teaching, sir! I love the way you show examples, tracing back if something «went too fast». You dont assume we know all the small things you know so really well yourself, which is easy to forget about when explaining things in my opinion. Superb stuff!
you must have read my mind! Just starting an in-depth course in classical mechanics, those symbolic Lagrangians will save me a lot of time, thank you! :)
Swear to god, this dude creates the best fuckin content on this fuckin platform.
The default solution to `sols` on my system has turned out substantially more complex than shown in your video.
Consequently, in order to obtain exactly the same results, smp.simplify() had to be added as such:
sols[sp.diff(theta, t,t)].simplify()
sols[sp.diff(z, t,t)].simplify()
Frankly, I'm still awed by the fact that presumably, human engineers, had actually managed to create the SymPy algorithms capable of dealing with such complex expressions flawlessly.
as a CS student, there were only a only a few vids abt sympy on yt, it really healped
As one of my profs says, "Super-Excellent" video! Thanks for the easy to understand walk through
Thank you very much!!!
We need more of these videos!!
You’re the best!!
Thanks, mate, this helps me a ton. I thought I'd need to completely switch to Mathematica for my project, but this gets me where I need to in Python. Much appreciated.
Take this Mathematica subscription! Great videos!
Everything I see on your videos, "Everything you do is great and keep it simple .. also even if it is not related to someone's field".
The Symbol definition right at the beginning was exactly what I need to perform my lengthy calculations ❤
Thx
6:36 for anyone confused, make sure tyo write variable. [THEN PRESS THE TAB KEY]
This is great! Thank you for doing actual examples and not taking too long in basic functions!! (I did watch it in x1.5-x2, I think that's allowed 😁)
In segment 46 of the code the differential dh0dt is written wrong. It should be " -gt - v0" instead of "gt - v0"
The most helpful hour I've spent. Thanks sir. What's a gorgeous video!!! 🎉
Excellent lecture! You are a gem! Really appreciate your time and effort. Cheers!
I was literally wishing you would do this video last week. AWESOME!
Thanks for keeping my request bro !✌
Ohh my, what a treat! Let's go!!
Definitely educative! My first encounter with SymPy. 🙂
Hi. Thanks for the video. I have a doubt: min 20:10 in line [46] dh0dt = g*t - v0? ... or dh0dt = -g*t - v0? Thanks again and excuse my bad english.
Great work dude. Keep posting for us to learn. It really helped.
At 26:20, I understand what is happening but I don't understand how the code works. f and g are first instantiated as `UndefinedFunction` type. How is it that I can call them right away with arguments. My understanding is you call a certain method of an object defined within its class type. But here we're calling the object itself? That feels kinda funky to me. What is going on?
Aweasome! That was just what I needed to switch on Python
Wow, this looks like a great alternative for a licensed software like MAPLE. Again, the best video on SymPy on youtube, great job!
Excellent tutorial! Thank you very much. Please make one on Astropy also.
Best video ever! Appreciate!
Thank you very much! Can you make a tutorial on TenPy?
So helpful and really well explained I love SymPy but I learned tricks from this video that I had never used! Thank you
Thanks for your efforts. Highly appreciated.
Infact you are my online teacher.
Thank you Sir
Is this library can use with jupyter notebook only? Because I try run in vscode but it doesn't show the latex format in the vscode terminal
Can we use sympy to simulate the behaviour of quantum entanglement
20:19 how is it gt - (v0t) shouldnt it be -gt - v0t
Great job buddy. Thanks for the dedication.
In your example of falling object colliding with platform your dh0dt must be equal to -g*t - v0? Not g*t-v0.
Yes!! Thank you for spotting this
Hey Mr. P Solver, great contents on your channel ! new subscriber here. I have a small suggestion, you could flip your camera recording horizontally and it would look like you're looking towards the right area on the screen.
Thank you so much for the passionate courses! :)
Would be nice if you present about holomorphic maps and iterations to generate fractals!
I don't get why you said that it's a good practice to use smp.Rational(1/2) instead of just writing 1/2 or 0.5 there. In larger problems, will the latter be not more time-saving in nature?
Thanks for the video, is there a way to input a expression and then use it With sympy ?
Looks like a typo has occurred in your part of the code (2*n*(sp.factorial(n+l)))) \
If you look at the formula above you will see that it should be (2*n*(sp.factorial(n+1)))) \
leaving us with differing numeric results after substitution further down.
Consequently: Interpreting the above formula correctly with SymPy results in a linear relationship with plt.scatter(ns, ds)
and not an exponential one.
I strongly feel that the discrepancy in the interpretation of the original formula ought to be double-checked,
before more students who are not entirely on par with quantum mechanics find themselves stranded.
thanks, very useful video!
I tried to calculate the integral that is taken by residue (from the theory of a function by a complex variable) but sumpy give useless answer. Do you know how help program and give some advice that it is necessary to solve it residue?
so my problem:
integrated (dw/((w^2-1)^2+w^2) from -inf to +inf)
I now answer, it very simple: pi
How is your menu on pressing tab totally different from mine (yours have them sorted in instanced, functions , etc.)? Can you let me know (or make a video) on all the settings and extensions you have on your setup? Thank you!
How can u write a variable with subscript ?
Excellent video, thank you very much! Not entirely related but do you have any book/course recommendation for an introduction to differential equations?
If I have an array containing complex exponential functions then how can I Integrate it ?
Can Senpai be used by a visually impaired person that uses a screen reader notepad plus plus and python code?
12 mins into, I got this error:
multiple generators [y, sin(y**2)]
No algorithms are implemented to solve equation y*sin(y**2) + z**
It seems I cannot find x,y,z values that make he function F = 0. Any suggestions?
Is there any function in sympy that solves improper partial fractional decomposition function?
Thanks for SymPy tutorial. You are my Senpai.🥰
Perhaps not efficiently, but Is it even possible to use NumPy to solve SymPy problems , or SciPy?
How do i setup jupyter to get all those cmd icons on top. I want to use them on w11 64 bit.!
Awesome video! Thank you!
mr. p solver be like :)
perfect video
Muito obrigado pelo excelente vídeo
Yo how do you insert your pictures in the markdown cell?
Is the wavefunction psi_10 not yet normalized?
Great thanks for your work, is there some library to work with chemistry? Abilities of python are amazing!
Pychem
Incredible good content. Thx a ton from Germany
This is awesome!
please recommend best python book for such a scientific computing.......
Thank you, great tutorial!
hey guys who knows how to install jupyter notebook to your laptop? i couldn't do it without anaconda. is there any other methods to do that?
How import sympy as smp in my laptop
the r^3 thing was great :)
It's neither in case you've not been reading the bright red text :D
Does anyone know how to define symbol as a binary variable? (so that you have b**2=b)
Do you use jupyter
I think that there is a mistake in the first example.
dh0tdt should be -gt-v0 instead of gt-v0 as presented.
Yeahh.... U r right
Outstanding contents! Wow!
One small request of making one dedicated video on Interactive plotting of some of these beautiful equations. You contents are truly amazing.
Thanks
Great stuff, thanks.
thank you very much legend!!!!
Jupiter stuff has such a small font that its almost unreadable by my eyes.
Where are you from? Where are you currently located?
ask yr mom
Good job 👌
You are awesome.
let's say i solve a differential equation using dsolve. Now i want to use the output say y(t) = .......(something). Is there any way to use the result to solve for t when y=2?
Hydro wave equation: should be 2n[(n+l)!] in denominator and not 2n[(n+1)!].....
So nice, I liked it twice.
But you have to like it _thrice!_
Idea - What is energy? - My guess - If you iterate y = model(X) and loss = mean((X-y)**2) that is let y -> X an image then using only one image X it will succeed. But y will not become X completely there is a residual y = X + dX. Its the dX that is the universe energy. Change something with dX and the approximation of the function restores the energy to its vibrant small state. Small compared to the entire universe. Its like hydro if you place something infront of the flow of water it will move it same with dX differences. Thats is energy. So it open ups new opportunities. Energy is dependent on squaring a function the error. So if the err0(t[123]) ^ 2 = err1(t[123]) ^ 4 then you got much stronger energy. So accumulate energy from timed extraction for that super power.
thanks!
Thanks !!
Thank you 🙏🙏🙏
hi , can you make a movie teaching deep learning tensor algebra using numpy to construct??
Kudos to you.
Dude as someone that's new to python but an experienced developer with a Physics undergrad... Python is the best and the worst of everything. The tools are incredible... but EVERYTHING. Literally everything apart from Numpy and Pandas and a few others use this insanely lazy and horribly put together auto-generated documentation. That will be the death of Python I promise.
Also... fun fact... when you highlighted those functions, you can run help(justAboutAnyPackage.thatMysteriousFunction) and it will print a **usually** more informative docstring than what's available on these $%#% autogenerated documentation sites. If you use an ide you'd have to run that in the terminal, but jupyter will print it out right in the output.
I wish you get admitted so we can see some formal lectures!
Like a Boss.......................
Nice stuff
These free libraries will probably eventually make Matlab and Mathematica go bankrupt!
Thanks
Thank you
if u use ``` from sympy import *``` it imports all the functionality of sympy without using smp.()
mfw diff eq. class ain't so hard anymore :)
Call me a symp
nice tutorial, but pls don't call integrals antiderivatives xDD
the music is really annoying, ditch it or at least turn it down, just my two cents
This video takes my math friends to ⇨ SymPy :) Some people use: import sympy as sy, and .n() instead of .evalf() . Application for atom -- thanks for answering my childhood curiosity!
Is this genuine? @MrPSolver
This is a good tutorial for replacing www.wikipedia.org/wiki/Abramowitz_and_Stegun
Thank you
thanks