From e09bde2cbd8f3bd8de9efe60ce89c5de63366653 Mon Sep 17 00:00:00 2001 From: Gaspard Jankowiak Date: Wed, 24 Apr 2024 11:17:52 +0200 Subject: [PATCH] [numerics] markdownify a bit --- en/numerics/FJMT.2024/index.md | 47 +++++++++++++++++++++++----------- 1 file changed, 32 insertions(+), 15 deletions(-) diff --git a/en/numerics/FJMT.2024/index.md b/en/numerics/FJMT.2024/index.md index 29d67f1..102c72e 100644 --- a/en/numerics/FJMT.2024/index.md +++ b/en/numerics/FJMT.2024/index.md @@ -9,38 +9,55 @@ math: true {% assign sigma_array = "0.001, 0.002, 0.004, 0.012" | split: ", " %} {% assign mu_array = "0.001, 0.005, 0.01, 0.05, 0.20833333333333334, 0.36666666666666664, 0.525, 0.6833333333333333, 0.8416666666666667, 1.0" | split: ", " %} {% assign prefix = "/s/numerics/FJMT.2024/plots_23_04_2024/results/LFR_separated/N_micro=1000,N_mfl=301" %} +{% assign prefix = "https://gaspard.janko.fr/s/numerics/FJMT.2024/plots_23_04_2024/results/LFR_separated/N_micro=1000,N_mfl=301" %} {% for sigma in sigma_array %} - +

$β$ distribution with $σ² = {{sigma}}$

-

Movies (ensemble averages)

-{% for mu in mu_array -%} -μ={{ mu | round: 4 }}{% unless forloop.last %} · {% endunless -%} +

Movies (ensemble averages)

+ +|----------| +| R1 {% for mu in mu_array -%} +| [μ={{ mu | round: 4 }}]({{ prefix }}/σ²={{ sigma }}/μ={{ mu }}/movie_without_g.mp4){% if forloop.last -%} | {% endif -%} {% endfor %}

Graphs

+ +|----------| {% for run in (1..5) -%} -

- Run {{ run }}: - {% for mu in mu_array -%} - μ={{ mu | round: 4 }}{% unless forloop.last %} · {% endunless -%} +| R{{ run }} {% for mu in mu_array -%} +| [μ={{ mu | round: 4 }}]({{ prefix }}/σ²={{ sigma }}/μ={{ mu }}/micro-{{ run }}/graph_LFR.png){% if forloop.last -%} | {% endif -%} {% endfor %} -

{% endfor %} -

Dynamics

-{:.manual_center_1500} +

Dynamics

-

Graph properties

-{:.manual_center_1500} +Convergence rates are computed over the time span marked in blue in the first plot. -

g(t=0), 1 row per run, p increasing →

+**Parameters:** + +- $\mu$: LFR mixing parameter +- $T^*$: time to consensus = $-1/\log(\vert\lambda_2\vert) \cdot \delta t$, where $\lambda_2$ is the second largest eigenvalue of the transition matrix for the associated time discrete model. See [here](https://doi.org/10.1016/j.ins.2019.02.028). +- [assortativity](https://en.wikipedia.org/wiki/Assortativity) +- [clustering coeff.](https://en.wikipedia.org/wiki/Clustering_coefficient) + + +![convergence]({{ prefix }}/σ²={{ sigma }}/comparison.svg){:.manual_center_1500} + +

Graph properties

+![graph metrics]({{ prefix }}/σ²={{ sigma }}/graph_analysis.svg){:.manual_center_1500} + +

g(t=0), 1 row per run, p increasing →

1
-{:.manual_center_1500} +{:.manual_center_1500} {% endfor %}