diff --git a/.idea/IMAT.iml b/.idea/IMAT.iml
new file mode 100644
index 0000000..6711606
--- /dev/null
+++ b/.idea/IMAT.iml
@@ -0,0 +1,11 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<module type="PYTHON_MODULE" version="4">
+  <component name="NewModuleRootManager">
+    <content url="file://$MODULE_DIR$" />
+    <orderEntry type="inheritedJdk" />
+    <orderEntry type="sourceFolder" forTests="false" />
+  </component>
+  <component name="TestRunnerService">
+    <option name="PROJECT_TEST_RUNNER" value="Unittests" />
+  </component>
+</module>
\ No newline at end of file
diff --git a/.idea/encodings.xml b/.idea/encodings.xml
new file mode 100644
index 0000000..0ccdc5c
--- /dev/null
+++ b/.idea/encodings.xml
@@ -0,0 +1,7 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="Encoding">
+    <file url="file://$PROJECT_DIR$/IterMethodsTool.m" charset="windows-1252" />
+    <file url="file://$PROJECT_DIR$/MatrixCreator.m" charset="windows-1252" />
+  </component>
+</project>
\ No newline at end of file
diff --git a/.idea/inspectionProfiles/profiles_settings.xml b/.idea/inspectionProfiles/profiles_settings.xml
new file mode 100644
index 0000000..105ce2d
--- /dev/null
+++ b/.idea/inspectionProfiles/profiles_settings.xml
@@ -0,0 +1,6 @@
+<component name="InspectionProjectProfileManager">
+  <settings>
+    <option name="USE_PROJECT_PROFILE" value="false" />
+    <version value="1.0" />
+  </settings>
+</component>
\ No newline at end of file
diff --git a/.idea/misc.xml b/.idea/misc.xml
new file mode 100644
index 0000000..3999087
--- /dev/null
+++ b/.idea/misc.xml
@@ -0,0 +1,7 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="JavaScriptSettings">
+    <option name="languageLevel" value="ES6" />
+  </component>
+  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.6" project-jdk-type="Python SDK" />
+</project>
\ No newline at end of file
diff --git a/.idea/modules.xml b/.idea/modules.xml
new file mode 100644
index 0000000..a78cd8b
--- /dev/null
+++ b/.idea/modules.xml
@@ -0,0 +1,8 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectModuleManager">
+    <modules>
+      <module fileurl="file://$PROJECT_DIR$/.idea/IMAT.iml" filepath="$PROJECT_DIR$/.idea/IMAT.iml" />
+    </modules>
+  </component>
+</project>
\ No newline at end of file
diff --git a/.idea/vcs.xml b/.idea/vcs.xml
new file mode 100644
index 0000000..94a25f7
--- /dev/null
+++ b/.idea/vcs.xml
@@ -0,0 +1,6 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="VcsDirectoryMappings">
+    <mapping directory="$PROJECT_DIR$" vcs="Git" />
+  </component>
+</project>
\ No newline at end of file
diff --git a/.idea/workspace.xml b/.idea/workspace.xml
new file mode 100644
index 0000000..7e0363a
--- /dev/null
+++ b/.idea/workspace.xml
@@ -0,0 +1,295 @@
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+<project version="4">
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+    </list>
+    <option name="EXCLUDED_CONVERTED_TO_IGNORED" value="true" />
+    <option name="SHOW_DIALOG" value="false" />
+    <option name="HIGHLIGHT_CONFLICTS" value="true" />
+    <option name="HIGHLIGHT_NON_ACTIVE_CHANGELIST" value="false" />
+    <option name="LAST_RESOLUTION" value="IGNORE" />
+  </component>
+  <component name="FileEditorManager">
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+        </entry>
+      </file>
+      <file pinned="false" current-in-tab="false">
+        <entry file="file://$PROJECT_DIR$/Jacobi.m">
+          <provider selected="true" editor-type-id="text-editor" />
+        </entry>
+      </file>
+      <file pinned="false" current-in-tab="false">
+        <entry file="file://$PROJECT_DIR$/MatrixCreator.m">
+          <provider selected="true" editor-type-id="text-editor" />
+        </entry>
+      </file>
+      <file pinned="false" current-in-tab="true">
+        <entry file="file://$PROJECT_DIR$/IterMethodsTool.m">
+          <provider selected="true" editor-type-id="text-editor">
+            <state relative-caret-position="138">
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+          <entry type="REMOTE">
+            <value>
+              <list>
+                <branch-info repo="$PROJECT_DIR$" source="upstream/master" />
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+            </value>
+          </entry>
+        </map>
+      </branch-storage>
+    </favorite-branches>
+  </component>
+  <component name="IgnoredFileRootStore">
+    <option name="generatedRoots">
+      <set>
+        <option value="$PROJECT_DIR$/.idea" />
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+  </component>
+  <component name="ProjectFrameBounds">
+    <option name="x" value="85" />
+    <option name="y" value="25" />
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+  <component name="ProjectLevelVcsManager" settingsEditedManually="true">
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+    <panes>
+      <pane id="Scope" />
+      <pane id="ProjectPane">
+        <subPane>
+          <expand>
+            <path>
+              <item name="IMAT" type="b2602c69:ProjectViewProjectNode" />
+              <item name="IMAT" type="462c0819:PsiDirectoryNode" />
+            </path>
+          </expand>
+          <select />
+        </subPane>
+      </pane>
+    </panes>
+  </component>
+  <component name="PropertiesComponent">
+    <property name="ASKED_ADD_EXTERNAL_FILES" value="true" />
+    <property name="SHARE_PROJECT_CONFIGURATION_FILES" value="true" />
+    <property name="WebServerToolWindowFactoryState" value="false" />
+    <property name="ignore_missing_gitignore" value="true" />
+    <property name="last_opened_file_path" value="$PROJECT_DIR$" />
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+  <component name="RunDashboard">
+    <option name="ruleStates">
+      <list>
+        <RuleState>
+          <option name="name" value="ConfigurationTypeDashboardGroupingRule" />
+        </RuleState>
+        <RuleState>
+          <option name="name" value="StatusDashboardGroupingRule" />
+        </RuleState>
+      </list>
+    </option>
+  </component>
+  <component name="SvnConfiguration">
+    <configuration />
+  </component>
+  <component name="TaskManager">
+    <task active="true" id="Default" summary="Default task">
+      <changelist id="9499bc9a-90f7-43f9-8cd0-00401f3d35c0" name="Default Changelist" comment="boh" />
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+      <option name="project" value="LOCAL" />
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+      <option name="project" value="LOCAL" />
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+      <option name="project" value="LOCAL" />
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+      <option name="project" value="LOCAL" />
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+        <entry key="MAIN">
+          <value>
+            <State>
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+          <value>
+            <list />
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+    </option>
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+  <component name="VcsManagerConfiguration">
+    <option name="ADD_EXTERNAL_FILES_SILENTLY" value="true" />
+    <MESSAGE value="add gui matlab" />
+    <MESSAGE value="boh" />
+    <MESSAGE value="first graph ok!" />
+    <MESSAGE value="second graph ok!" />
+    <MESSAGE value="third graph ok!" />
+    <MESSAGE value="add stupid logo" />
+    <MESSAGE value="gui 0.1&#10;- graph complete (with sparse!)" />
+    <MESSAGE value="gui 0.3 - add sound, github link" />
+    <MESSAGE value="gui 0.31 - add xscale/yscale plot" />
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+    <option name="LAST_COMMIT_MESSAGE" value="gui 0.32 - add knob example" />
+  </component>
+</project>
\ No newline at end of file
diff --git a/Cute-cat-meowing-on-the-street.mp3 b/Cute-cat-meowing-on-the-street.mp3
new file mode 100644
index 0000000..a753836
Binary files /dev/null and b/Cute-cat-meowing-on-the-street.mp3 differ
diff --git a/IterMethodsTool.m b/IterMethodsTool.m
index a9b1ce1..01dc3e2 100644
--- a/IterMethodsTool.m
+++ b/IterMethodsTool.m
@@ -1,318 +1,318 @@
-fprintf('---IMAT (Iterative methods analysis tool)---\n');
-fprintf('Press space to start\n');
-pause
-clear
-
-% List of matrices
-mat1 = '[1] - Diagonally dominant matrix sparse';
-mat2 = '[2] - Positive symmetric definite matrix';
-mat3 = '[3] - Positive and sparse symmetric definite matrix';
-mat4 = '[4] - Poisson''s matrix';
-
-% Choice of matrix type
-matrix_str = sprintf('%s\n%s\n%s\n%s\n%s\n',mat1,mat2,mat3,mat4);
-fprintf(matrix_str);
-choice_str = 'Choose the matrix to use ';
-mtype = input(choice_str);
-
-steps_str = input('Enter the dimension steps you want to test separated by spaces or commas: ', 's');
-dimens = str2num(steps_str);
-steps = size(dimens,2);
-
-% Parameters for performing the analysis
-tol = 1e-12;
-nmax = 200;
-omega = 0.5;
-
-fprintf('List of settings used for performing the test:\n')
-fprintf('%d - Tolerance\n', tol);
-fprintf('%d - Maximum number of iterations\n', nmax);
-fprintf('%d - Relaxation parameter\n', omega);
-prompt_3 = sprintf('Do you want to change these values? [Y][N]');
-
-r = input(prompt_3, 's');
-if isempty(r)
-    r = 'N';
-end
-if strcmp(r,'y') || strcmp(r,'Y')
-    prompt_n = 'Enter the tolerance value: ';
-    tol = input(prompt_n);
-    prompt_n = 'Enter the maximum number of iterations: ';
-    nmax = input(prompt_n);
-    prompt_n = 'Enter the omega value for relaxation operations: ';
-    omega = input(prompt_n);
-end
-
-% We use an incomplete preconditioner - Cholesky
-% Required parameters:
-opts.type = 'ict'; % Select Cholesky with threshold dropping (ICT)
-opts.droptol = 1e-3; % Below which threshold values must be set to zero (small numbers become zero)
-% If you increase this value becomes more sparse preconditioner
-opts.shape = 'upper'; % choose the upper (RT)(R) format
-% opts is actually a struct that contains the parameters
-
-% Initialization of variables
-time1 = zeros(steps,1);
-time1p = zeros(steps,1);
-time2 = zeros(steps,1);
-time2p = zeros(steps,1);
-time3 = zeros(steps,1);
-time3p = zeros(steps,1);
-time4 = zeros(steps,1);
-time5 = zeros(steps,1);
-time6 = zeros(steps,1);
-
-x1 = cell(1,steps);
-iter1 = zeros(steps,1);
-resvec1 = cell(1,steps);
-error1 = zeros(steps,1);
-
-x1p = cell(1,steps);
-iter1p = zeros(steps,1);
-resvec1p = cell(1,steps);
-error1p = zeros(steps,1);
-
-x2 = cell(1,steps);
-iter2 = zeros(steps,1);
-resvec2 = cell(1,steps);
-error2 = zeros(steps,1);
-
-x2p = cell(1,steps);
-iter2p = zeros(steps,1);
-resvec2p = cell(1,steps);
-error2p = zeros(steps,1);
-
-x3 = cell(1,steps);
-iter3 = zeros(steps,1);
-resvec3 = cell(1,steps);
-error3 = zeros(steps,1);
-
-x3p = cell(1,steps);
-iter3p = zeros(steps,1);
-resvec3p = cell(1,steps);
-error3p = zeros(steps,1);
-
-x4 = cell(1,steps);
-iter4 = zeros(steps,1);
-resvec4 = cell(1,steps);
-error4 = zeros(steps,1);
-
-x5 = cell(1,steps);
-iter5 = zeros(steps,1);
-resvec5 = cell(1,steps);
-error5 = zeros(steps,1);
-
-x6 = cell(1,steps);
-iter6 = zeros(steps,1);
-resvec6 = cell(1,steps);
-error6 = zeros(steps,1);
-
-for i=1:steps
-    
-    fprintf ('Iteration [%d] with dimensioning [%d]\n', i, dimens(i));
-    A = MatrixCreator(mtype,dimens(i));
-    figure(i);
-    spy(A); % In blue the non-zero elements of the selected matrix
-    titleTimeBar = sprintf('Sparsity pattern of the matrix with dim= %d', dimens(i));
-    title(titleTimeBar)   
-    
-    % Construction of the linear system to be solved
-    n = size (A, 1);
-    % System setting, with solution equal to a vector of 1:
-    sol = ones (n, 1);
-    b = A * sol;
-    % Alternatively we choose the known term with a random vector of size n:
-    % b = rand (n, 1);
-    x0 = zeros (n, 1);
-    
-    % Matlab gradient conjugate
-    tic
-    [x, flag, relres, iter, resvec] = pcg (A, b, tol, nmax, [], [], x0); % we can also not insert tol and nmax because they are set by default
-    time1(i) = toc;
-    error1(i) = norm(sol-x)/norm(sol); % relative error
-    x1(i) = {x};
-    iter1(i) = iter;
-    resvec1(i) = {resvec};
-    
-    % Evaluate whether to perform the incomplete LU according to the matrices chosen
-    % setup.type = 'crout';
-    % setup.milu = 'row';
-    % setup.droptol = 1e-3;
-    % setup.udiag = 1;
-    % [L,U] = ilu(A,setup);
-    
-    % Matlab conjugate gradient preconditioned
-    R = ichol(A, opts);
-    tic
-    [x, flag, relres, iter, resvec] = pcg(A,b,tol,nmax,R',R,x0);
-    time1p(i) = toc;
-    error1p(i) = norm(sol-x)/norm(sol); % relative error
-    x1p(i) = {x};
-    iter1p(i) = iter;
-    resvec1p(i) = {resvec};
-    
-    % Method of steepest descent or stationary-phase method or saddle-point method
-    tic
-    [x, iter, resvec] = SelfGradient(A,b,tol,nmax,x0);
-    time2(i) = toc;
-    error2(i) = norm(sol-x)/norm(sol); % relative error
-    x2(i) = {x};
-    iter2(i) = iter;
-    resvec2(i) = {resvec};
-    
-    % Classic preconditioned gradient
-    tic
-    [x, iter, resvec] = SelfPreGradient(A,b,tol,nmax,R',R,x0);
-    time2p(i) = toc;
-    error2p(i) = norm(sol-x)/norm(sol); % relative error
-    x2p(i) = {x};
-    iter2p(i) = iter;
-    resvec2p(i) = {resvec};
-    
-    % Conjugate gradient
-    tic
-    [x, iter, resvec] = SelfConiugGradient(A,b,tol,nmax,x0); % we can also not insert tol and nmax because they are set by default
-    time3(i) = toc;
-    error3(i) = norm(sol-x)/norm(sol); % relative error
-    x3(i) = {x};
-    iter3(i) = iter;
-    resvec3(i) = {resvec};
-    
-    % Preconditioned conjugate gradient
-    tic
-    [x, iter, resvec] = SelfPreConiugGradient(A,b,tol,nmax,R',R,x0);
-    time3p(i) = toc;
-    error3p(i) = norm(sol-x)/norm(sol); % relative error
-    x3p(i) = {x};
-    iter3p(i) = iter;
-    resvec3p(i) = {resvec};
-    
-    % Jacobi method
-    tic
-    [x, iter, resvec] = Jacobi(A,b,tol,nmax,x0);
-    time4(i) = toc;
-    error4(i) = norm(sol-x)/norm(sol); % relative error
-    x4(i) = {x};
-    iter4(i) = iter;
-    resvec4(i) = {resvec};
-    
-    % Gauss Seidel method
-    tic
-    [x, iter, resvec] = GaussSeidel(A,b,tol,nmax,x0);
-    time5(i) = toc;
-    error5(i) = norm(sol-x)/norm(sol); % relative error
-    x5(i) = {x};
-    iter5(i) = iter;
-    resvec5(i) = {resvec};   
-
-end
-
-timeMatrix = [time1 time1p time2 time2p time3 time3p time4 time5];
-minTime = min(min(timeMatrix));
-maxTime = max(max(timeMatrix));
-
-T.Dimensione = dimens';
-T.MCG = time1;
-T.MPCG = time1p;
-T.SG = time2;
-T.SPG = time2p;
-T.SCG = time3;
-T.SPCG = time3p;
-T.Jacobi = time4;
-T.GaussSeidel = time5;
-
-% Time table
-timeTable = struct2table(T)
-
-I.Dimensione = dimens';
-I.MCG = iter1;
-I.MPCG = iter1p;
-I.SG = iter2;
-I.SPG = iter2p;
-I.SCG = iter3;
-I.SPCG = iter3p;
-I.Jacobi = iter4;
-I.GaussSeidel = iter5;
-
-% Iteration table
-iterTable = struct2table(I)
-
-E.Dimensione = (dimens)';
-E.MCG = error1;
-E.MPCG = error1p;
-E.SG = error2;
-E.SPG = error2p;
-E.SCG = error3;
-E.SPCG = error3p;
-E.Jacobi = error4;
-E.GaussSeidel = error5;
-
-% Tabella errori
-errorTable = struct2table(E)
-
-% Residual charts
-figure(steps+1)
-for i=1:steps
-
-subplot(1,steps,i)
-semilogy(resvec1{i}, '--g', 'LineWidth',5)
-hold on
-semilogy(resvec1p{i}, '-g', 'LineWidth',5)
-hold on
-semilogy(resvec2{i}, '--r', 'LineWidth',3)
-hold on
-semilogy(resvec2p{i}, '-r', 'LineWidth',3)
-hold on
-semilogy(resvec3{i}, '--b', 'LineWidth',2)
-hold on
-semilogy(resvec3p{i}, '-b', 'LineWidth',2)
-hold on
-semilogy(resvec4{i}, '-y', 'LineWidth',2)
-hold on
-semilogy(resvec5{i}, '-m', 'LineWidth',2)
-hold off
-legend('MCG','MPCG','SG','SPG','SCG','SPCG','Jacobi','GaussSeidel')
-titleGradPlot = sprintf('Residual Iterative Methods, DIM = %d', dimens(i));
-title(titleGradPlot)
-end
-
-% Bar charts (iterations and times)
-figure(steps+2)
-for i=1:steps
-    iterData = [iter1(i) iter1p(i) iter2(i) iter2p(i) iter3(i) iter3p(i) iter4(i) iter5(i)];
-    ax1 = subplot(2,steps,i);
-    c = categorical({'MCG','MPCG','SG','SPG','SCG','SPCG','Jacobi','GaussSeidel'});
-    c = reordercats(c,{'MCG','MPCG','SG','SPG','SCG','SPCG','Jacobi','GaussSeidel'});
-    b=bar(ax1,c,iterData);
-    b.FaceColor = 'flat';
-    b.CData(1,:) = [0,1,0];
-    b.CData(2,:) = [0,1,0];
-    b.CData(3,:) = [1,0,0];
-    b.CData(4,:) = [1,0,0];
-    b.CData(5,:) = [0,0,1];
-    b.CData(6,:) = [0,0,1];
-    b.CData(7,:) = [1,1,0];
-    b.CData(8,:) = [1,0,1];
-    ylim([0 nmax])
-    titleIterBar = sprintf('Iteraction, DIM = %d', dimens(i));
-    title(titleIterBar)
-    
-    timeData = [time1(i) time1p(i) time2(i) time2p(i) time3(i) time3p(i) time4(i) time5(i)];
-    ax1 = subplot(2,steps,i+steps);
-    c = categorical({'MCG','MPCG','SG','SPG','SCG','SPCG','Jacobi','GaussSeidel'});
-    c = reordercats(c,{'MCG','MPCG','SG','SPG','SCG','SPCG','Jacobi','GaussSeidel'});
-    b=bar(ax1,c,timeData);
-    % ylim([minTime maxTime])
-    ylim([0.0001 0.4])
-    b.FaceColor = 'flat';
-    b.CData(1,:) = [0,1,0];
-    b.CData(2,:) = [0,1,0];
-    b.CData(3,:) = [1,0,0];
-    b.CData(4,:) = [1,0,0];
-    b.CData(5,:) = [0,0,1];
-    b.CData(6,:) = [0,0,1];
-    b.CData(7,:) = [1,1,0];
-    b.CData(8,:) = [1,0,1];
-    titleTimeBar = sprintf('Time, DIM = %d', dimens(i));
-    title(titleTimeBar)   
-end
+fprintf('---IMAT (Iterative methods analysis tool)---\n');
+fprintf('Press space to start\n');
+pause
+clear
+
+% List of matrices
+mat1 = '[1] - Diagonally dominant matrix sparse';
+mat2 = '[2] - Positive symmetric definite matrix';
+mat3 = '[3] - Positive and sparse symmetric definite matrix';
+mat4 = '[4] - Poisson''s matrix';
+
+% Choice of matrix type
+matrix_str = sprintf('%s\n%s\n%s\n%s\n%s\n',mat1,mat2,mat3,mat4);
+fprintf(matrix_str);
+choice_str = 'Choose the matrix to use ';
+mtype = input(choice_str);
+
+steps_str = input('Enter the dimension steps you want to test separated by spaces or commas: ', 's');
+dimens = str2num(steps_str);
+steps = size(dimens,2);
+
+% Parameters for performing the analysis
+tol = 1e-12;
+nmax = 200;
+omega = 0.5;
+
+fprintf('List of settings used for performing the test:\n')
+fprintf('%d - Tolerance\n', tol);
+fprintf('%d - Maximum number of iterations\n', nmax);
+fprintf('%d - Relaxation parameter\n', omega);
+prompt_3 = sprintf('Do you want to change these values? [Y][N]');
+
+r = input(prompt_3, 's');
+if isempty(r)
+    r = 'N';
+end
+if strcmp(r,'y') || strcmp(r,'Y')
+    prompt_n = 'Enter the tolerance value: ';
+    tol = input(prompt_n);
+    prompt_n = 'Enter the maximum number of iterations: ';
+    nmax = input(prompt_n);
+    prompt_n = 'Enter the omega value for relaxation operations: ';
+    omega = input(prompt_n);
+end
+
+% We use an incomplete preconditioner - Cholesky
+% Required parameters:
+opts.type = 'ict'; % Select Cholesky with threshold dropping (ICT)
+opts.droptol = 1e-3; % Below which threshold values must be set to zero (small numbers become zero)
+% If you increase this value becomes more sparse preconditioner
+opts.shape = 'upper'; % choose the upper (RT)(R) format
+% opts is actually a struct that contains the parameters
+
+% Initialization of variables
+time1 = zeros(steps,1);
+time1p = zeros(steps,1);
+time2 = zeros(steps,1);
+time2p = zeros(steps,1);
+time3 = zeros(steps,1);
+time3p = zeros(steps,1);
+time4 = zeros(steps,1);
+time5 = zeros(steps,1);
+time6 = zeros(steps,1);
+
+x1 = cell(1,steps);
+iter1 = zeros(steps,1);
+resvec1 = cell(1,steps);
+error1 = zeros(steps,1);
+
+x1p = cell(1,steps);
+iter1p = zeros(steps,1);
+resvec1p = cell(1,steps);
+error1p = zeros(steps,1);
+
+x2 = cell(1,steps);
+iter2 = zeros(steps,1);
+resvec2 = cell(1,steps);
+error2 = zeros(steps,1);
+
+x2p = cell(1,steps);
+iter2p = zeros(steps,1);
+resvec2p = cell(1,steps);
+error2p = zeros(steps,1);
+
+x3 = cell(1,steps);
+iter3 = zeros(steps,1);
+resvec3 = cell(1,steps);
+error3 = zeros(steps,1);
+
+x3p = cell(1,steps);
+iter3p = zeros(steps,1);
+resvec3p = cell(1,steps);
+error3p = zeros(steps,1);
+
+x4 = cell(1,steps);
+iter4 = zeros(steps,1);
+resvec4 = cell(1,steps);
+error4 = zeros(steps,1);
+
+x5 = cell(1,steps);
+iter5 = zeros(steps,1);
+resvec5 = cell(1,steps);
+error5 = zeros(steps,1);
+
+x6 = cell(1,steps);
+iter6 = zeros(steps,1);
+resvec6 = cell(1,steps);
+error6 = zeros(steps,1);
+
+for i=1:steps
+    
+    fprintf ('Iteration [%d] with dimensioning [%d]\n', i, dimens(i));
+    A = MatrixCreator(mtype,dimens(i));
+    figure(i);
+    spy(A); % In blue the non-zero elements of the selected matrix
+    titleTimeBar = sprintf('Sparsity pattern of the matrix with dim= %d', dimens(i));
+    title(titleTimeBar)   
+    
+    % Construction of the linear system to be solved
+    n = size (A, 1);
+    % System setting, with solution equal to a vector of 1:
+    sol = ones (n, 1);
+    b = A * sol;
+    % Alternatively we choose the known term with a random vector of size n:
+    % b = rand (n, 1);
+    x0 = zeros (n, 1);
+    
+    % Matlab gradient conjugate
+    tic
+    [x, flag, relres, iter, resvec] = pcg (A, b, tol, nmax, [], [], x0); % we can also not insert tol and nmax because they are set by default
+    time1(i) = toc;
+    error1(i) = norm(sol-x)/norm(sol); % relative error
+    x1(i) = {x};
+    iter1(i) = iter;
+    resvec1(i) = {resvec};
+    
+    % Evaluate whether to perform the incomplete LU according to the matrices chosen
+    % setup.type = 'crout';
+    % setup.milu = 'row';
+    % setup.droptol = 1e-3;
+    % setup.udiag = 1;
+    % [L,U] = ilu(A,setup);
+    
+    % Matlab conjugate gradient preconditioned
+    R = ichol(A, opts);
+    tic
+    [x, flag, relres, iter, resvec] = pcg(A,b,tol,nmax,R',R,x0);
+    time1p(i) = toc;
+    error1p(i) = norm(sol-x)/norm(sol); % relative error
+    x1p(i) = {x};
+    iter1p(i) = iter;
+    resvec1p(i) = {resvec};
+    
+    % Method of steepest descent or stationary-phase method or saddle-point method
+    tic
+    [x, iter, resvec] = SelfGradient(A,b,tol,nmax,x0);
+    time2(i) = toc;
+    error2(i) = norm(sol-x)/norm(sol); % relative error
+    x2(i) = {x};
+    iter2(i) = iter;
+    resvec2(i) = {resvec};
+    
+    % Classic preconditioned gradient
+    tic
+    [x, iter, resvec] = SelfPreGradient(A,b,tol,nmax,R',R,x0);
+    time2p(i) = toc;
+    error2p(i) = norm(sol-x)/norm(sol); % relative error
+    x2p(i) = {x};
+    iter2p(i) = iter;
+    resvec2p(i) = {resvec};
+    
+    % Conjugate gradient
+    tic
+    [x, iter, resvec] = SelfConiugGradient(A,b,tol,nmax,x0); % we can also not insert tol and nmax because they are set by default
+    time3(i) = toc;
+    error3(i) = norm(sol-x)/norm(sol); % relative error
+    x3(i) = {x};
+    iter3(i) = iter;
+    resvec3(i) = {resvec};
+    
+    % Preconditioned conjugate gradient
+    tic
+    [x, iter, resvec] = SelfPreConiugGradient(A,b,tol,nmax,R',R,x0);
+    time3p(i) = toc;
+    error3p(i) = norm(sol-x)/norm(sol); % relative error
+    x3p(i) = {x};
+    iter3p(i) = iter;
+    resvec3p(i) = {resvec};
+    
+    % Jacobi method
+    tic
+    [x, iter, resvec] = Jacobi(A,b,tol,nmax,x0);
+    time4(i) = toc;
+    error4(i) = norm(sol-x)/norm(sol); % relative error
+    x4(i) = {x};
+    iter4(i) = iter;
+    resvec4(i) = {resvec};
+    
+    % Gauss Seidel method
+    tic
+    [x, iter, resvec] = GaussSeidel(A,b,tol,nmax,x0);
+    time5(i) = toc;
+    error5(i) = norm(sol-x)/norm(sol); % relative error
+    x5(i) = {x};
+    iter5(i) = iter;
+    resvec5(i) = {resvec};   
+
+end
+
+timeMatrix = [time1 time1p time2 time2p time3 time3p time4 time5];
+minTime = min(min(timeMatrix));
+maxTime = max(max(timeMatrix));
+
+T.Dimensione = dimens';
+T.MCG = time1;
+T.MPCG = time1p;
+T.SG = time2;
+T.SPG = time2p;
+T.SCG = time3;
+T.SPCG = time3p;
+T.Jacobi = time4;
+T.GaussSeidel = time5;
+
+% Time table
+timeTable = struct2table(T)
+
+I.Dimensione = dimens';
+I.MCG = iter1;
+I.MPCG = iter1p;
+I.SG = iter2;
+I.SPG = iter2p;
+I.SCG = iter3;
+I.SPCG = iter3p;
+I.Jacobi = iter4;
+I.GaussSeidel = iter5;
+
+% Iteration table
+iterTable = struct2table(I)
+
+E.Dimensione = (dimens)';
+E.MCG = error1;
+E.MPCG = error1p;
+E.SG = error2;
+E.SPG = error2p;
+E.SCG = error3;
+E.SPCG = error3p;
+E.Jacobi = error4;
+E.GaussSeidel = error5;
+
+% Errors table
+errorTable = struct2table(E)
+
+% Residual charts
+figure(steps+1)
+for i=1:steps
+
+subplot(1,steps,i)
+semilogy(resvec1{i}, '--g', 'LineWidth',5)
+hold on
+semilogy(resvec1p{i}, '-g', 'LineWidth',5)
+hold on
+semilogy(resvec2{i}, '--r', 'LineWidth',3)
+hold on
+semilogy(resvec2p{i}, '-r', 'LineWidth',3)
+hold on
+semilogy(resvec3{i}, '--b', 'LineWidth',2)
+hold on
+semilogy(resvec3p{i}, '-b', 'LineWidth',2)
+hold on
+semilogy(resvec4{i}, '-y', 'LineWidth',2)
+hold on
+semilogy(resvec5{i}, '-m', 'LineWidth',2)
+hold off
+legend('MCG','MPCG','SG','SPG','SCG','SPCG','Jacobi','GaussSeidel')
+titleGradPlot = sprintf('Residual Iterative Methods, DIM = %d', dimens(i));
+title(titleGradPlot)
+end
+
+% Bar charts (iterations and times)
+figure(steps+2)
+for i=1:steps
+    iterData = [iter1(i) iter1p(i) iter2(i) iter2p(i) iter3(i) iter3p(i) iter4(i) iter5(i)];
+    ax1 = subplot(2,steps,i);
+    c = categorical({'MCG','MPCG','SG','SPG','SCG','SPCG','Jacobi','GaussSeidel'});
+    c = reordercats(c,{'MCG','MPCG','SG','SPG','SCG','SPCG','Jacobi','GaussSeidel'});
+    b = bar(ax1,c,iterData);
+    b.FaceColor = 'flat';
+    b.CData(1,:) = [0,1,0];
+    b.CData(2,:) = [0,1,0];
+    b.CData(3,:) = [1,0,0];
+    b.CData(4,:) = [1,0,0];
+    b.CData(5,:) = [0,0,1];
+    b.CData(6,:) = [0,0,1];
+    b.CData(7,:) = [1,1,0];
+    b.CData(8,:) = [1,0,1];
+    ylim([0 nmax])
+    titleIterBar = sprintf('Iteractions, DIM = %d', dimens(i));
+    title(titleIterBar)
+    
+    timeData = [time1(i) time1p(i) time2(i) time2p(i) time3(i) time3p(i) time4(i) time5(i)];
+    ax1 = subplot(2,steps,i+steps);
+    c = categorical({'MCG','MPCG','SG','SPG','SCG','SPCG','Jacobi','GaussSeidel'});
+    c = reordercats(c,{'MCG','MPCG','SG','SPG','SCG','SPCG','Jacobi','GaussSeidel'});
+    b = bar(ax1,c,timeData);
+    % ylim([minTime maxTime])
+    ylim([0.0001 0.4])
+    b.FaceColor = 'flat';
+    b.CData(1,:) = [0,1,0];
+    b.CData(2,:) = [0,1,0];
+    b.CData(3,:) = [1,0,0];
+    b.CData(4,:) = [1,0,0];
+    b.CData(5,:) = [0,0,1];
+    b.CData(6,:) = [0,0,1];
+    b.CData(7,:) = [1,1,0];
+    b.CData(8,:) = [1,0,1];
+    titleTimeBar = sprintf('Time, DIM = %d', dimens(i));
+    title(titleTimeBar)   
+end
\ No newline at end of file
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