From 9a4ba5945bb0ae09380c0b753329b3b087b912b2 Mon Sep 17 00:00:00 2001
From: Stefano Covino <stefano.covino@inaf.it>
Date: Wed, 19 Mar 2025 07:35:00 +0100
Subject: [PATCH] 190325 commit

---
 .../Lecture-Lomb-Scargle.jl                   |  22 +++++++++---------
 .../Science Case - FRBs/Lecture-FRBs.ipynb    |   4 ++--
 .../__pycache__/GL_algorithm.cpython-312.pyc  | Bin 0 -> 8943 bytes
 3 files changed, 13 insertions(+), 13 deletions(-)
 create mode 100644 Lectures/Science Case - FRBs/__pycache__/GL_algorithm.cpython-312.pyc

diff --git a/Lectures/Lecture - Lomb-Scargle/Lecture-Lomb-Scargle.jl b/Lectures/Lecture - Lomb-Scargle/Lecture-Lomb-Scargle.jl
index 9c828e8..cbdbf72 100644
--- a/Lectures/Lecture - Lomb-Scargle/Lecture-Lomb-Scargle.jl	
+++ b/Lectures/Lecture - Lomb-Scargle/Lecture-Lomb-Scargle.jl	
@@ -82,11 +82,11 @@ md"""
 
 # ╔═╡ 477704cc-f022-4cc5-a4a4-679387b819bd
 # ╠═╡ show_logs = false
-md"""
+cm"""
 ## A reminder of the CFT
 ***
 
-- Given a continuous signal g(t) the Fourier transform and its inverse are:
+- Given a continuous signal ``g(t)`` the Fourier transform and its inverse are:
 
 ```math
 \hat{g}(f) \equiv \int_{-\infty}^\infty g(t) e^{-2\pi i f t} dt \quad  g(t) \equiv \int_{-\infty}^\infty \hat{g}(f) e^{+2\pi i f t} df
@@ -98,7 +98,7 @@ md"""
 \mathcal{F}\{g\} = \hat{g} \quad    \mathcal{F}^{-1}\{\hat{g}\} = g
 ```
 
-- g and ĝ are know as a Fourier pair: $g \Longleftrightarrow \hat{g}$.
+- ``g`` and ``ĝ`` are know as a Fourier pair: ``g \Longleftrightarrow \hat{g}``.
 
 - The Fourier Transform (FT) is a linear operator:
 
@@ -107,22 +107,22 @@ md"""
        \mathcal{F}\{A f(t)\} = A\mathcal{F}\{f(t)\}
 ```
 
-- The FT of a sinusoid with frequency $f_0$ is a sum of delta functions at $\pm f_0$, where $\delta(f)\equiv\int_{-\infty}^\infty e^{-2\pi i x f}df$.
+- The FT of a sinusoid with frequency ``f_0`` is a sum of delta functions at ``\pm f_0``, where ``\delta(f)\equiv\int_{-\infty}^\infty e^{-2\pi i x f}df``.
 
-- We can write: $ \mathcal{F}\{e^{2\pi f_0 t}\} = \delta(f - f_0)$, and:
+- We can write: `` \mathcal{F}\{e^{2\pi f_0 t}\} = \delta(f - f_0)``, and:
 
 ```math
 \mathcal{F}\{\cos(2\pi f_0 t)\} = \frac{1}{2}\left[\delta(f - f_0) + \delta(f + f_0)\right] \quad
       \mathcal{F}\{\sin(2\pi f_0 t)\} = \frac{1}{2i}\left[\delta(f - f_0) - \delta(f + f_0)\right]
 ```
 
-- Relations that can be derived from Euler’s formula: $e^{ix} = \cos x + i\sin x$
+- Relations that can be derived from Euler’s formula: ``e^{ix} = \cos x + i\sin x``
 
-- A time shift imparts a phase in the FT:  $  \mathcal{F}\{g(t - t_0)\} = \mathcal{F}\{g(t)\} e^{-2\pi i ft_0}$.
+- A time shift imparts a phase in the FT:  ``  \mathcal{F}\{g(t - t_0)\} = \mathcal{F}\{g(t)\} e^{-2\pi i ft_0}``.
 
-- And, as we know, the squared amplitude of the FT of a continuous signal is known as the power spectral density (PSD):  $ \mathcal{P}_g \equiv \left|\mathcal{F}\{g\}\right|^2 $.
+- And, as we know, the squared amplitude of the FT of a continuous signal is known as the power spectral density (PSD):  `` \mathcal{P}_g \equiv \left|\mathcal{F}\{g\}\right|^2 ``.
 
-    - Note that if $g$ is real-valued, it follows that $P_g$ is an even function, {i.e.} $\mathcal{P}_g(f) = \mathcal{P}_g(-f)$.
+    - Note that if ``g`` is real-valued, it follows that ``P_g`` is an even function, {i.e.} ``\mathcal{P}_g(f) = \mathcal{P}_g(-f)``.
 
 $(LocalResource("Pics/FTpairs.png"))
 """
@@ -709,7 +709,7 @@ md"""
 # ╔═╡ 9d413d79-c9fb-4c30-ac02-92380510b607
 # ╠═╡ show_logs = false
 begin
-	fg6 = Figure(size=(2000,1000))
+	fg6 = Figure(size=(700,350))
 	
 	ax1fg6 = Axis(fg6[1, 1],
 	    title="Peak scaling with number of data points (fixed S/N=10)",
@@ -837,7 +837,7 @@ begin
 	p99 = LombScargle.fapinv(lsboot7,0.99)
 	
 	
-	fg7 = Figure(size=(1000,400))
+	fg7 = Figure(size=(700,350))
 	
 	ax1fg7 = Axis(fg7[1, 1],
 	    )
diff --git a/Lectures/Science Case - FRBs/Lecture-FRBs.ipynb b/Lectures/Science Case - FRBs/Lecture-FRBs.ipynb
index 6c2aa3f..866f993 100644
--- a/Lectures/Science Case - FRBs/Lecture-FRBs.ipynb	
+++ b/Lectures/Science Case - FRBs/Lecture-FRBs.ipynb	
@@ -451,7 +451,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -849,7 +849,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.11"
+   "version": "3.12.7"
   }
  },
  "nbformat": 4,
diff --git a/Lectures/Science Case - FRBs/__pycache__/GL_algorithm.cpython-312.pyc b/Lectures/Science Case - FRBs/__pycache__/GL_algorithm.cpython-312.pyc
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-- 
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