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Merged
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Oct 10, 2021
Merged

added convolutional theorem implementation in python #869

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c8a0702
added convolutional theorem implementation in python
pillarxyz Oct 8, 2021
4ed3db9
fixed chapter linking
pillarxyz Oct 8, 2021
5372836
added comments to the code
pillarxyz Oct 8, 2021
e2ec833
changed random distribution to sawtooth
pillarxyz Oct 9, 2021
39eb8ff
corrected previous commit
pillarxyz Oct 9, 2021
bafdda7
fixed comments
pillarxyz Oct 9, 2021
4a1d761
Merge branch 'master' into python_implement
leios Oct 10, 2021
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19 changes: 19 additions & 0 deletions contents/convolutions/convolutional_theorem/code/python/convolutional_theorem.py
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@@ -0,0 +1,19 @@
from scipy.fft import fft, ifft
import numpy as np

# using the convolutional theorem
def convolve_fft(signal1, signal2):
return ifft(np.multiply(fft(signal1),fft(signal2)))

# Sawtooth functions
x = [float(i)/200 for i in range(1,101)]
y = [float(i)/200 for i in range(1,101)]

x /= np.linalg.norm(x)
y /= np.linalg.norm(y)

# Convolving the two signals
fft_output = convolve_fft(x, y)

np.savetxt("fft.dat", np.real(fft_output))

3 changes: 2 additions & 1 deletion contents/convolutions/convolutional_theorem/convolutional_theorem.md
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Expand Up @@ -44,6 +44,8 @@ For this example code, we will be using two sawtooth functions as we did in the
{% method %}
{% sample lang="jl" %}
[import, lang:"julia"](code/julia/convolutional_theorem.jl)
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@leios leios Oct 8, 2021

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Suggested change
[import, lang:"julia"](code/julia/convolutional_theorem.jl)
[import, lang:"julia"](code/julia/convolutional_theorem.jl)
{% sample lang="py" %}
[import, lang:"python"](code/python/convolutional_theorem.py)

{% sample lang="py" %}
[import, lang:"python"](code/python/convolutional_theorem.py)
{% endmethod %}

This should produce the following output:
Expand All @@ -52,7 +54,6 @@ This should produce the following output:
<img class="center" src="../res/cyclic.png" style="width:75%">
</p>


<script>
MathJax.Hub.Queue(["Typeset",MathJax.Hub]);
</script>
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