Hi, my name is Ade, I am a graduate student. In this channel, I share a tutorial video about what I've learned and used during my study. I hope my video could help you finish your homework, project, and your research. I upload videos every week, don't forget to subscribe, and let's study together.
Best, Made Python
1st Python Video 15 April 2022 100 Subscribers 19th November 2022 ........
Dear Made: Thank you for sharing your code on Github! However, without your data files, we cannot run your code. Is there any chance you can share your data files?
The first time I used this method it worked perfectly. I had a lovely smooth gif. Now when I do it the colours in my heatmap become less detailed. However the pngs that make the gif are much more detailed. I haven’t changed anything! If you have any experience with this issue please let me know.
@@madepython and yet the book shows that it does work in an example, your code is wrong, the image must be fftshifted and the blurring kernel must be sampled from -height/2:height/2 -width/2:width/2
Thanks for the video, friend. Could you help me with a plot of 2 roses in the same figure, but that have the same scale and the same graduated scale to facilitate analysis and relationship?
Thank you very much for your answer, I am sorry that my questions may be a little too much, I am a beginner college student, I tried to follow your steps, and also used your script, and removed the river part, but it showed FVCOM Fatal Error! CAN NOT UPDATE TIME FOR INVALID FLOATING POINT TIME VARIABLE Stopping FVCOM FVCOM Fatal Error! Can Not Read NameList NML_CASE from file: ./CX_run.nml Stopping FVCOM, in addition, I would like to ask where can I get the tide_component data, thank you very much!
No worries friend, I also faced the same problem when the first time I learned this FVCOM. I think from your error message you need to set the number of rive to 0 in the CX_run.nml file. For the tide_component data you could find it by estimation the the tidal component from sea water surface elevation data.
The "fvcom_river" is the file you get by compiling the fvcom source code. "casename_run.nml" or in this video, I named the casename "SE", which is the fvcom control file that is included in the fvcom example folder.
The '3 MATLAB scripts' shown in the tutorial video are not available in the fvcom-toolbox. I personally created those scripts as an example of how you can use the functions from the fvcom-toolbox. They serve as a demonstration of the toolbox's capabilities.
What if the image would be rgb? I splitted the channels and processed all steps for all channels. Then I merged sharpened channels again. But it didn't change. What should I do?
@@madepython I guess first we need to convert to YUV or HSV color space. Then apply laplacian to only intencity layer. But in my case I needed to multiply kernel with -1.
In your noisy image/array you now have values which are outside of the original range [0 ; 1], which is incorrect and unrealistic as a pixel on your real-world 8 bit camera sensor cannot have negative values or values above 255. This means that you need to implement => all negative values in my noisy array are 0, all positive values in my noisy array that are higher than 1 are 1. However, this introduces the problem that you are effectively truncating your Gaussian distribution, meaning that what you added to the image as noise (Gaussian) is not what you get in the end (some strange malformed/truncated Gaussian).
Hello, thank you for pointing this out. I still need to understand what we should do to the pixel where the values are outside of the original pixel range since the textbook did not explain this problem.
