fft / inverse fft #12
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@ubsuny/cp1-24 Anyone interested to review this? |
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@zbpetersbuf please use the file names as requested in the homework description! |
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so I will be sure to do the following (rename the module preparation.py, and gives the freq in the useful values) only,
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also I am unsure what this pycache file is, I thought I didn't push this but it appeared regardless, should I delete this? |
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@zbpetersbuf so your PR should only contain 2 files:
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I will review this PR |
fft_folder/inv_fft.py
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| import math as m | ||
| import numpy as np | ||
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| def analyze_signal(signal, fs, use_filter, selec_filter): |
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please call this something like “fft”
also make sure this actually takes a pandas time series. in the moment you assume some fs as a time step. That is not how a pandas time series or the CO2 data is organized. Also you do not need any filters since this is another task
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im aware of this but since I dont know what that data will look like this is a placeholder
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also fft is already a function in numpy so I though I wasn't just making those functions, but I can if that's what's being asked of me this is no problem I just need to know
fft_folder/inv_fft.py
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| the modles in the function include liner polynomial cubic and exponential | ||
| """ | ||
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| def anze_revm_trnd(signal, fs, use_filter, selec_filter): |
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this is not part of your homework task. You can leave it but it has to work with the pandas time series
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so I am not removing the overall trend to this data before finding the inv fft?
fft_folder/test_inv_fft.py
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this is just something for myself I am not finished with my task
fft_folder/inv_fft.py
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| """ | ||
| inv_fft.py | ||
| inverse fast fourie transform | ||
| """ |
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this should be renamed to preparation.pycans should container at least three functions:
- fft
- inverse fft
- calculate frequencies
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so the task was to make my own fft function? and not use the numpy functions?
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ok to be clear I am not done with this I apologize for the inconvenience |
I know. I just wanted you to point you in the right direction. |
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So the task was to make my own fft, ifft and a function that finds the frequencies? and not use the numpy functions? |
No, use numpy fft and inverse fft inside a function that can use the pandas time series data format |
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Please note my comment in #3 (comment) to what your function should take as data |
fft_folder/preparation.py
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| return np.fft.ifft(matrx) | ||
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| def calc_freq(data): | ||
| n = len(data) |
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This only works if your time unit is seconds for returning Hz
fft_folder/preparation.py
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| def inv_fft(data): | ||
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| matrx = np.fft.fft(data) |
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you don’t need to take the fft first your fft function does that
fft_folder/preparation.py
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| matrx = np.fft.fft(data) | ||
| return np.abs(matrx) | ||
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| def inv_fft(data): |
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this will have to take a frequency as input
fft_folder/preparation.py
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| """ | ||
| import numpy as np | ||
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| def fft(data): |
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you rely on that data is the time data in equidistant time slots. This will fail e.g. for months which are not the same lengths.
fft_folder/test_preparation.py
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Needs a unit test function
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@SchrodingersStruggle merging this for now to have a starter file |
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