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this function is really usefull!

Very good video!

first thanks a lot for the excellent video and good description then I have a question how can you find the roots of this equation: R = ∑_(k=1)^(k=100)▒∑_(j=-100)^(j=100)▒(e^12 〖 (12)〗^k )/k! k/(2π(w^2+1/4)) √(1-〖(w/(LkR^2 ))〗^2 ) ∆w ∆k , ∆k=1,∆w=LkR^2/100

more important

Hello, how ca I do this with more columns and rows, that means with a dataset?

With this method, that is np.diff(y) / np.diff(x) will compute the gradient of the data points but the derivative will have one less data point, what can be done about that?

perfect video, thanks!

This is really helpful, but the link to the python code in the description no longer works.\

Great man, but i want something. Im trying to make a code with a table of the function f and its derivative valuated but i dont know how to print without any error

Thank you for explaining in such details

Hi Chuck, I am a student at Cambridge University looking to employ MCMC or HMC on TRPL and TA datasets. I have read your paper on this subject and would be interested to know if you have released your code to run this on a CPU?

Incredible video, nice and clear explanation. 10/10

Can you please use light mode?

Hi! I have a question: the plot of the bands are the same in both cases of epsilon > 1 and epsilon <1?

thanks a lot ! <3 lil cutie

it is not necessary to define the bounds most of the time, more often, p0, the initial guess is something you need to provide

where is download your code *.py and csv file sir ?

how do you solve a 3 order ODE, is it the same as this since we have 3 dimensions for y? and the boundary conditions also double.

I LOVE YOU SO MUCH THANK YOU THANK YOU THANK YOU THANK YOU THANK YOU

Thank you so much!!!!! You saved me!!!❤ subscribed 🥹

thank you for video. it was so easy to understand how to use this function. really perfect you know, I had a problem with code, and I didn't know what I need to do to solve. the problem was in boundary conditions. It really easy to solve my problem)

Very nice animation! What RNG are you using? How well do different RNG converge? How well would the actual digits of Pi used as a distribution source perform? I don't know why suddenly a lot more questions come to my mind. In any case: thank you very much for the inspiration!

Simple but outstanding. Deep gratitude! Thank you.

thanks a lot

Awesome! Thanks for the clear guide of how to use this matplotlib tool!

MERCI BEAUCOUP TRES INTERESSANT

Great lecture! Thank you very much!

This is a nice video. As usual, I am confused. I have never understood contourf and meshgrid. It seems to me that contourf should work with 1D arrays rlist and thetalist, and a function Z(r, theta). The function would be a 1D array of appropriate length = len(rlist)*len(thetalist). This seems completely defined, so I don't know what is accomplished with meshgrid. All I need to do is a nested loop that fills Z(r, theta) with each element of r and theta. I checked the documentation for contourf. It can accept 1D arrays, so why use meshgrid? Conceptually, I have trouble verifying that meshgrid is doing the right thing. A nested loop seems much easier to verify, because I explicitly pass in the r and theta values that I want to evaluate for Z. It's not always possible to generate a 2D array for Z, as done in the video. Sometimes, the function Z is complicated and cannot just take in 2D arrays directly. When that is the case, getting the correct Z function using meshgrid takes effort to understand exactly how meshgrid creates the grid. I basically have to reverse engineer meshgrid to fill Z. Very complicated. So, I try to work with 1D arrays and a nested loop. That always works and is simple conceptually, whereas the meshgrid technique might or might not work, depending on the function. What's really mind-bending for me is that meshgrid returns two 2D arrays, whereas conceptually a contour plot maps two numbers to a third number, not two 2D arrays to a third number. So, the meshgrid technique is much more confusing for me to validate and conceptualize.

Having programmed in Python for some time, I found the video confusing because python does not normally perform math operations on an entire list of floats which is what is done in function f here. And, this program would not work if you manually defined xlist with something like xlist = [-10.0, -9.9, ...., 9.9, 10.0]. However, using numpy to create the list does not create a list of floats but instead a class 'numpy.ndarray' object. Python then understands math operations like xlist **2.

I am using VSCODE as my IDE. I could not get the plot window to show up, unless I added plt.show() to thee end of your code. I enjoyed your video, but I wanted to know more about which function outputs the graph, and whether or not this issue is IDE specific (spyder vs vscode)

Thanks. Very important and useful How to find conduction quasi-fermi level for a known injected carrier concentration, effective mass, and conduction band minimum?

Your videos are amazing and really helpfull. Keep going bro

Thanks for excellent video. Flux is in W/m2.

is there a way to solve these type of problems when you also have boundary conditions for the first derivative? e.g. a function that starts at (T, T') = (T0, 0) and ends at (T, T') = (0, 0) . That would mean 4 boundary conditions for a 1D problem, is it possible?

That's an awesome tutorial. It was so easy to understand the codes. Great work!!

gracias maestro

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14:57

This is my favorite Minecraft lets play series, keep up the good content

Cool video. This I like a lot. Thanks for the helpful instructions.

How we can find Spectroscopic Limited Maximum Efficiency (SLME) of Perovskite materials by Using CASTEP code or Python?

Please include in your title "Spyder". It will help in the search! :)

thank you, this is an awesome primer.

You are just osm where can I connect to you

thanks, very clear explination and was also interesting to see spyder used for investigation rather than jupyter lab

i dont found de CSV ?

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Thank you