Python Tutorial: Learn Scipy - Fast Fourier Transform (scipy.fftpack) in 17 Minutes

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  • Опубліковано 18 гру 2024

КОМЕНТАРІ • 35

  • @TimelyTimeSeries
    @TimelyTimeSeries 10 місяців тому +1

    Thanks a lot for this video. As someone with no engineering background, this demonstration makes the concept much easier to understand.

  • @syremusic_
    @syremusic_ Рік тому

    Excellent video, a practical introduction to how to use FFT to find the peak frequency in a noisy signal. You can take this a step further and find the n peak frequencies in a signal and attempt to reconstruct the original signal. Thank you!

  • @dhruv_195
    @dhruv_195 Рік тому +2

    great video man, you explained everything so well not only that those small boxes at top right corner telling what the function does is a really smart idea. for the first time I understood everything in a programming tutorial, thank you brother : )

  • @luisponce6594
    @luisponce6594 Рік тому +1

    Excellent video. keep it going, you helped me a lot on my mechanical dynamics class.

  • @kevinshao9148
    @kevinshao9148 3 роки тому +2

    Thanks for the great video! One question, 9:40 why sample freq goes symmetric around zero, why not go with one side of the x axis [0 .... n ] ? so mathematically, what are these generated frequencies? are they unique?

    • @Altekameraden79
      @Altekameraden79 2 роки тому

      The range of the Discrete Fourier Transform is -infinity to positive infinity to include all possible discrete signals. It is common practice to truncate spectrum from 0 Hz to Fmax (defined by sample rate, max resolution of sensor accuracy etc.)

  • @ushapedcurve3831
    @ushapedcurve3831 11 місяців тому

    Great tutorial! I think it-s recommended to build graph of each intermediate output in JPEG format, for better understanding. So that the student had some pyplot practice.

  • @kaewkt8987
    @kaewkt8987 4 роки тому +3

    Thank you, it's very clear explanation

  • @rajeshn2536
    @rajeshn2536 4 роки тому +2

    Thank you so much, it helped a lot in understanding FFT

  • @dman2633
    @dman2633 4 роки тому +1

    Thank you very much. Your video is very clear and functional.

  • @garrisonhustle3289
    @garrisonhustle3289 4 роки тому +1

    A pretty easy tool for filtering, nice intro!

  • @VanNguyen-yp7cd
    @VanNguyen-yp7cd 2 роки тому

    Thank you so much. It's very useful and your explain clearly.

  • @princecharlesmbedzi3832
    @princecharlesmbedzi3832 3 роки тому +1

    what arguments did you use to plot the amplitude vs frequency graph

  • @dsmith5272
    @dsmith5272 4 роки тому

    Nice explanation and tutorial; it helped me understand FFT a bit better.

  • @alierencelik2188
    @alierencelik2188 Рік тому

    Excellent video for a starter like me, thanks

  • @RUSSELL-s4h
    @RUSSELL-s4h 2 роки тому

    Thanks man, very good video. Very simple from the information i looked online

  • @jiehuang9740
    @jiehuang9740 3 роки тому +1

    Very helpful, perhaps can add more plotting when showing how the data is like.

  • @anwarparadis7997
    @anwarparadis7997 4 роки тому +2

    Amazing video I like it

  • @HarpreetKaur-bx1ej
    @HarpreetKaur-bx1ej 2 роки тому

    am getting both amplitude position and peak frequency 0, what should i do i am not getting valid result

  • @rio_agustian_
    @rio_agustian_ 2 роки тому +3

    Cool video, sir. Great explanation! But can you plot the bunch of numerical stuff instead of just print it? I think it'll be more intuitive for the viewers

  • @nickpenacl
    @nickpenacl Рік тому

    thanks for the video, just don't understand how the amplitude could be 100 in the spectrum when it's supposed to expect be 1

  • @supundasanthakuruppu3496
    @supundasanthakuruppu3496 2 роки тому

    Thanks. This helped a lot!

  • @nanoluisi
    @nanoluisi 4 роки тому

    Is it posible to generate a "clean" file out of fft?

  • @apoorvmodak3579
    @apoorvmodak3579 2 роки тому +2

    would have understood better with graphical representations

  • @fjlord407
    @fjlord407 4 роки тому +1

    Nice

  • @importantbiology7643
    @importantbiology7643 4 роки тому

    Please code seen clear or share PDF link .

  • @nyatoko8578
    @nyatoko8578 2 роки тому

    Where is the magnitude sir?

  • @aviadedell4826
    @aviadedell4826 4 роки тому +1

    The argument of sin should be omega*t, not 2*pi*t( i see now you divided by the period)