Refactor and add test 2.

report/main.tex

@@ -1,25 +1,79 @@
-% !TeX program = pdflatex
-\documentclass{mathreport} % Uses our custom mathreport.cls
+\documentclass[11pt]{article}
+\usepackage[margin=1.2in]{geometry}
+\usepackage[utf8]{inputenc}
+\usepackage[T1]{fontenc}
+\usepackage[english]{babel}
+\usepackage{fourier}
+\usepackage{amsthm}
+\usepackage{amssymb}
+\usepackage{amsmath}
+\usepackage{amsfonts}
+\usepackage{latexsym}
+\usepackage{graphicx}
+\usepackage{float}
+\usepackage{etoolbox}
+\usepackage{hyperref}
+\usepackage{tikz}
+\usepackage{lipsum}
+\usepackage{algorithm}
+\usepackage{algpseudocode}
+\usepackage{mathtools}
+\usepackage{nccmath}
+\usepackage[most]{tcolorbox}
+\newtcolorbox[auto counter]{problem}[1][]{%
+    enhanced,
+    breakable,
+    colback=white,
+    colbacktitle=white,
+    coltitle=black,
+    fonttitle=\bfseries,
+    boxrule=.6pt,
+    titlerule=.2pt,
+    toptitle=3pt,
+    bottomtitle=3pt,
+    title=GitHub repository of this project}
+
+\RequirePackage[activate={true,nocompatibility},final,tracking=true,kerning=true,spacing=true]{microtype}
+\SetTracking{encoding={*}, shape=sc}{40} % Spacing for Small Caps
+
+
+\newcommand{\R}{\mathbb{R}}
+\newcommand{\N}{\mathbb{N}}
+\newcommand{\Z}{\mathbb{Z}}
+\newcommand{\Q}{\mathbb{Q}}
+\newcommand{\C}{\mathbb{C}}
+
+\newtheorem{theorem}{Theorem}[section]
+\newtheorem{lemma}[theorem]{Lemma}
+\newtheorem{proposition}[theorem]{Proposition}
+\newtheorem{corollary}[theorem]{Corollary}
+\theoremstyle{definition}
+\newtheorem{definition}[theorem]{Definition}
+\newtheorem{example}[theorem]{Example}
+\theoremstyle{remark}
+\newtheorem{remark}[theorem]{Remark}
 
-% Load bibliography
-\addbibresource{references.bib}
-
-% --- Document Metadata ---
 \title{%
     Accelerated filtering on graphs using Lanczos method
     \\ \large Relazione del progetto di Calcolo Scientifico}
 \author{Alberto Defendi}
-\date{\small\today}
 
-\begin{document}
+\date{}
 
+\setlength{\parskip}{1em}
+\setlength{\parindent}{0em}
+
+\begin{document}
 \maketitle
 
 \begin{abstract}
-    \noindent \small \textbf{\textit{Abstract.}}
+    \noindent The Lanczos algorithm \ldots 
 \end{abstract}
 
-\section{Introduction}
+{\setlength{\parskip}{0em}
+\tableofcontents}
+
+\section{Introduzione}
 
 Introduciamo alcuni concetti di teoria dei grafi e alcuni risultati del corso che verranno usati nel corso della sperimentazione.
 Scopo del progetto è verificare numericamente i risultati 
@@ -38,6 +92,11 @@ attraverso la valutazione $g(\mathcal{L})s$.
 test
 
 
-\printbibliography
+\clearpage
+\bibliographystyle{unsrt}
+\bibliography{ref}
+\nocite{*}
+
+
 
 \end{document}

report/ref.bib

@@ -0,0 +1,9 @@
+@article{susnjara2015,
+      title={Accelerated filtering on graphs using Lanczos method}, 
+      author={Ana Susnjara and Nathanael Perraudin and Daniel Kressner and Pierre Vandergheynst},
+      year={2015},
+      eprint={1509.04537},
+      archivePrefix={arXiv},
+      primaryClass={math.NA},
+      url={https://arxiv.org/abs/1509.04537}, 
+}

src/afgl/example_2.py

@@ -1,13 +0,0 @@
-def run() -> None:
-    """Genera i grafi di di Erdos-Reny di grandezza crescente (ad esempio 250,
-    500,1000, 2000, 4000) e parametro p = 0.04 e misura il tempo
-    computazionale del metodo di Lanczos utilizzando come soglia per il criterio
-    d'arresto epsilon = 10^-2 (o una soglia a scelta).
-
-     Args:
-         None
-
-     Returns:
-         None
-    """
-    pass

src/afgl/main.py

@@ -1,18 +1,13 @@
 import sys
 
-import scienceplots  # noqa: F401
-
-# Requires latex installed
-import afgl.example_1 as ex1
-import afgl.example_2 as ex2
+import afgl.test_2 as t_2
 from afgl.util.plot import plot_setup
 
 
 def run() -> None:
     plot_setup()
-    # example_1()
-    ex1.run()
-    ex2.run()
+    # t_1.run()
+    t_2.run()
 
 
 if __name__ == "__main__":

src/afgl/test_1.py

@@ -2,10 +2,10 @@ import matplotlib.pyplot as plt
 import matplotlib.ticker as ticker
 import numpy as np
 import numpy.linalg as LA
-import scienceplots  # noqa: F401
-import scipy
 
 # Requires latex installed
+import scienceplots  # noqa: F401
+import scipy
 from pygsp import graphs
 
 from afgl.util.build_T_matrix import build_T_matrix

src/afgl/test_2.py

@@ -0,0 +1,36 @@
+import numpy as np
+import numpy.linalg as LA
+from pygsp import graphs
+
+from afgl.util.lanczos import lanczos
+
+
+def run() -> None:
+    """Genera i grafi di di Erdos-Reny di grandezza crescente (ad esempio 250,
+    500,1000, 2000, 4000) e parametro p = 0.04 e misura il tempo
+    computazionale del metodo di Lanczos utilizzando come soglia per il criterio
+    d'arresto epsilon = 10^-2 (o una soglia a scelta).
+
+     Args:
+         None
+
+     Returns:
+         None
+    """
+    n = 6
+    p = 0.04
+
+    M = 200
+
+    N_VALUES = 250 * (2 ** np.arange(n))
+
+    for N in N_VALUES:
+        s = np.random.randint(1, 10000, N).astype(float)
+        # Normalize s as in request
+        s /= LA.norm(s)
+
+        G = graphs.ErdosRenyi(N, p)
+        G.compute_laplacian("combinatorial")
+        L = G.L
+
+        lanczos(L, s, M)