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+<h1>Maneage tutorial</h1>
+
+<p>Copyright (C) 2020 Raul Infante-Sainz <a href="&#x6D;&#x61;&#105;&#x6C;&#116;&#111;:&#x69;&#110;&#102;&#97;&#x6E;t&#x65;&#115;&#x61;&#105;&#x6E;&#122;&#64;&#103;&#109;&#97;&#x69;&#x6C;&#46;&#x63;&#111;m">&#x69;&#110;&#102;&#97;&#x6E;t&#x65;&#115;&#x61;&#105;&#x6E;&#122;&#64;&#103;&#109;&#97;&#x69;&#x6C;&#46;&#x63;&#111;m</a>\
+Copyright (C) 2020 Mohammad Akhlaghi <a href="&#x6D;a&#x69;&#x6C;&#116;&#x6F;:&#109;&#x6F;&#x68;&#x61;&#109;&#x6D;&#97;&#100;&#64;&#97;&#x6B;&#104;&#108;a&#103;&#x68;&#105;&#46;o&#x72;&#103;">&#109;&#x6F;&#x68;&#x61;&#109;&#x6D;&#97;&#100;&#64;&#97;&#x6B;&#104;&#108;a&#103;&#x68;&#105;&#46;o&#x72;&#103;</a>\
+See the end of the file for license conditions.</p>
+
+<p>This document is a tutorial in which it is described how <code>Maneage</code>
+(management + lineage) works in practice. It is highly recommended to read
+the <code>README-hacking.md</code> in order to have a clear idea of what is this
+project about. Actually, in this tutorial it is assumed you have the project
+already set up and working properly. In order to do it, please, read and
+follow all the steps described in the sections <code>Customization checklist</code> up
+to the section <code>Title, short description and author</code> (including the last
+one).</p>
+
+<p>With the current tutorial, the reader will be able to have a fully
+reproducible paper describing a small research example carried out step by
+step. The research example is very simple: it will consist in analyse a
+dataset with two columns (time and population). The analysis will be just to
+make a linear fitting of the data, and then, write the results in a small
+paragraph into the final paper.</p>
+
+<p>In the following, the tutorial assume you have three different directories.
+You had to set up them in the configure step:</p>
+
+<ul>
+<li><p><code>input-directory</code>: Necessary input data for the project is in this
+directory.</p></li>
+<li><p><code>project-directory</code>: This directory contains the project itself (source
+codes), it is under <code>Git</code> control.</p></li>
+<li><p><code>build-directory</code>: Output directory of the project, it is where all the
+necessary software and the results of the project are saved.</p></li>
+</ul>
+
+<p><strong><em>IMPORTANT NOTE</em></strong>: the tutorial assume you are always in
+<code>project-directory</code> when considering command lines.</p>
+
+<p><strong>In short:</strong> this hands on tutorial will guide you through a simple
+research example in order to show the workflow in <code>Maneage</code>. The tutorial
+describes by step how to download a small file containg data, analyse the
+data (by making a linear fitting), and finally write a small paragraph with
+the fitting parameters into the final paper. All of this will be done in the
+same Makefile.</p>
+
+<h2>Installing available software: Matplotlib</h2>
+
+<p>If all steps above have been done successfully, you are ready to start
+including your own analysis scripts. But, before that, let's install
+<code>Matplotlib</code> Python package, which will be used later in the analysis of the
+data when obtaining the linear fit figure. This Python package will be used
+as an example on how to install programs that are already available in
+<code>Maneage</code>. Just open the Makefile
+<code>reproduce/software/config/installation/TARGETS.mk</code> and add to the
+<code>top-level-python</code> line, the word <code>matplotlib</code>.</p>
+
+<p><code>shell
+ # Python libraries/modules.
+ top-level-python = astropy matplotlib
+</code></p>
+
+<p>After that, run the configure step again with the option <code>-e</code> to continue
+using the same configuration options given before (input and build
+directories). Also, run the prepare and make steps:</p>
+
+<p>```shell
+$ ./project configure -e
+$ ./project prepare
+$ ./project make</p>
+
+<h1>Open 'paper.pdf' and see if everything is fine. Note that now, <code>Matplotlib</code></h1>
+
+<p>is appearing in the software appendix at the end of the document.
+```</p>
+
+<p>Once you have verified that <code>Matplotlib</code> has been properly installed and it
+appears into the final <code>paper.pdf</code>, you are ready to make the first commit
+of the project. With the next commands, you will see which files have been
+modified, what are the modifications, prepare them to be commited, and make
+the commit. In the commit process, <code>Git</code> will open the text editor for
+writting the commit message. Take into account that all changes commited
+will be preserved in the history of your project. So, it is a good practice
+to take some time to describe properly what have been done/changed/added.
+Finally, as this is the very first commit of the project, tag this as the
+zero-th version.</p>
+
+<p><code>shell
+$ git status # See which files have been changed.
+$ git diff # See the lines you have modified.
+$ git add -u # Put all tracked changes in staging area.
+$ git status # Make sure everything is fine.
+$ git commit # Your first commit, add a nice description.
+$ git tag -a v0.0 # Tag this as the zero-th version of your project.
+</code></p>
+
+<p>Now, have a look at the <code>Git</code> history of the project. Note that the local
+master branch is one commit above than the remote origin/master branch.
+After that, push your first commit and its tag to your remote repository
+with the next commands. Since you had setup your <code>master</code> branch to follow
+<code>origin/master</code>, you can just use <code>git push</code>.</p>
+
+<p><code>shell
+$ git log --oneline --decorate --all --graph # Have a look at the Git history.
+$ git push # Push the commit to the remote/origin.
+$ git push --tags # Push all tags to the remote/origin.
+</code></p>
+
+<p>Now it is time to start including your own scripts to download and make the
+analysis of the data. It is important to bear in mind that the goal of this
+tutorial is to give a general view of the workflow in <code>Maneage</code>. In this
+sense, only a few basic concepts about <code>Make</code> and how it is used into this
+project will be given. <code>Maneage</code> is much more powerfull and much more things
+than the ones showed in this tutorial can be done. So, read carefully all
+the documentation and comments already available into each file, be creative
+and experiment making your own research.</p>
+
+<p>In the following, the tutorial will be focused in download the data, analyse
+the data, and finally write the results into the final paper. As a
+consequence, there are a lot of things already done that are not necessary.
+For example, all the text of the final paper already written into the
+<code>paper.tex</code> file, some Makefiles to download images from the Hubble Space
+Telescope and analyse them, etc. In your own research, all of this work
+would be removed. However, in this tutorial they are not removed because we
+will only show how to do a simple analysis and include a small paragraph
+with the result of the linear fitting.</p>
+
+<p><strong>In short:</strong> in this section you have learnt how to install available
+software in <code>Maneage</code>. In this particular case, you installed <code>Matplotlib</code></p>
+
+<h2>Including Python script to make the analysis</h2>
+
+<p>You are going to use a small Python script to make the analysis of the data.
+This Python script will be invoked from a Makefile that will be set up
+later. For now, we are going to just create the Python script and put it in
+an appropiate location. All analysis scripts are kept into a subfolder with
+the name of the same file type in <code>reproduce/analysis</code>. For example, the
+Makefiles are saved into the <code>make</code> directory, and bash scripts are saved
+into the <code>bash</code> directory. Since there is any <code>python</code> directory, create it
+with the following command.</p>
+
+<p><code>shell
+$ mkdir reproduce/analysis/python
+</code></p>
+
+<p>After that, you need the Python script itself. The code is very simple: it
+will take an input file containing two columns (year and population), the
+name of the output file in which the parameters of the linear fit will be
+saved, and the name of the figure showing the original data and the fitted
+curve. Paste the next Python script into a new file named <code>linear-fit.py</code>
+into the directory generated in the above step
+(<code>reproduce/analysis/python</code>).</p>
+
+<p>```</p>
+
+<h1>Make a linear fit of an input data set</h1>
+
+<p>#</p>
+
+<h1>This Python script makes a linear fitting of a data consisting in time and</h1>
+
+<h1>population. It generates a figure in which the original data and the</h1>
+
+<h1>fitted curve is plotted. Finally, it saves the fitting parameters.</h1>
+
+<h1>Original author:</h1>
+
+<h1>Copyright (C) 2020, Raul Infante-Sainz <a href="&#109;&#97;&#x69;&#108;&#x74;o:i&#110;&#102;&#x61;&#110;&#x74;&#101;&#x73;&#97;i&#x6E;&#122;&#64;&#103;&#109;&#97;&#105;&#108;&#46;&#x63;&#111;&#109;">i&#110;&#102;&#x61;&#110;&#x74;&#101;&#x73;&#97;i&#x6E;&#122;&#64;&#103;&#109;&#97;&#105;&#108;&#46;&#x63;&#111;&#109;</a></h1>
+
+<h1>Contributing author(s):</h1>
+
+<h1>Copyright (C) YEAR, YourName YourSurname.</h1>
+
+<p>#</p>
+
+<h1>This Python script is free software: you can redistribute it and/or modify it</h1>
+
+<h1>under the terms of the GNU General Public License as published by the</h1>
+
+<h1>Free Software Foundation, either version 3 of the License, or (at your</h1>
+
+<h1>option) any later version.</h1>
+
+<p>#</p>
+
+<h1>This Python script is distributed in the hope that it will be useful, but</h1>
+
+<h1>WITHOUT ANY WARRANTY; without even the implied warranty of</h1>
+
+<h1>MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General</h1>
+
+<h1>Public License for more details. See <a href="http://www.gnu.org/licenses/">http://www.gnu.org/licenses/</a>.</h1>
+
+<h1>Necessary packages</h1>
+
+<p>import sys
+import numpy as np
+import matplotlib.pyplot as plt
+from scipy.optimize import curve_fit</p>
+
+<h1>Fitting function (linear fit)</h1>
+
+<p>def func(x, a, b):
+ return a * x + b</p>
+
+<h1>Define input and output arguments</h1>
+
+<p>ifile = sys.argv[1] # Input file
+ofile = sys.argv[2] # Output file
+ofig = sys.argv[3] # Output figure</p>
+
+<h1>Read the data from the input file.</h1>
+
+<p>data = np.loadtxt(ifile)</p>
+
+<h1>Time and population:</h1>
+
+<h1>time ---------- x</h1>
+
+<h1>population ---- y</h1>
+
+<p>x = data[:, 0]
+y = data[:, 1]</p>
+
+<h1>Make the linear fit</h1>
+
+<p>params, pcov = curve_fit(func, x, y)</p>
+
+<h1>Make and save the figure</h1>
+
+<p>plt.clf()
+plt.figure()</p>
+
+<p>plt.plot(x, y, 'bo', label="Original data")
+plt.plot(x, func(x, *params), 'r-', label="Fitted curve")</p>
+
+<p>plt.title('Population along time')
+plt.xlabel('Time (year)')
+plt.ylabel('Population (million people)')
+plt.legend()
+plt.grid()</p>
+
+<p>plt.savefig(ofig, format='PDF', bbox_inches='tight')</p>
+
+<h1>Save the fitting parameters</h1>
+
+<p>np.savetxt(ofile, params, fmt='%.3f')
+```</p>
+
+<p>Have a look at this Python script. At the very beginning, it has a block of
+commented lines with a descriptive title, a small paragraph describing the
+the script, and the copyright with the contact information. For each file,
+it is very important to have such kind of meta-data. Below these lines,
+there is the source code itself.</p>
+
+<p>As it can be seen, this Python script (<code>linear-fit.py</code>) is designed to be
+invoked from the command line in the following way.</p>
+
+<p><code>shell
+$ python /path/to/linear-fit.py /path/to/input.dat /path/to/output.dat /path/to/figure.pdf
+</code></p>
+
+<p><code>/path/to/input.dat</code> is the input data file, <code>/path/to/output.dat</code> is the
+output data file (with the fitted parameters), and <code>/path/to/figure.pdf</code> is
+the plotted figure.</p>
+
+<p>You will do this invokation inside of a Make rule (that will be set up
+later). Now that you have included this Python script, make a commit in
+order to save this work. With the first command you will see the files with
+modifications. With the second command, you can check what are the changes.
+Correct, add and modify whatever you want in order to include more
+information, comments or clarify any step. After that, add the files and
+commit the work. Finally, push the commit to the remote/origin.</p>
+
+<p><code>shell
+$ git status # See which files you have changed.
+$ git diff # See the lines you have added/changed.
+$ git add reproduce/analysis/python/linear-fit.py # Put all tracked changes in staging area.
+$ git commit # Commit, add a nice descriptions.
+$ git push # Push the commit to the remote/origin.
+</code></p>
+
+<p>Check that everything is fine having a look at the <code>Git</code> history of the
+project. Note that the <code>master</code> branch has been increased in one commit,
+while the <code>template</code> branch is behind.</p>
+
+<p><code>shell
+$ git log --oneline --decorate --all --graph # See the `Git` history.
+</code></p>
+
+<p><strong>In short</strong>: in this section you have included a <code>Python</code> script that will
+be used for making the linear fitting.</p>
+
+<h2>Downloading data</h2>
+
+<p>As it was said before, there are multiple things that are already included
+into the project. One of them is to use a dedicated Makefile to manage all
+necessary download of the input data
+(<code>reproduce/analysis/make/download.mk</code>). By appropiate modifications of this
+file, you would be able to download the necessary data. However, in order to
+keep this tutorial as simple as possible, we will describe how to download
+the data you need more explicity.</p>
+
+<p>The data needed by this tutorial consist in a simple plain text file
+containing two rows: time (year) and population (in million of people). This
+data correspond to Spain, and it can be downloaded from this URL:
+<code>http://akhlaghi.org/data/template-tutorial/ESP.dat</code>. But don't do that
+using your browser, you have to do it into <code>Maneage</code>!</p>
+
+<p>Let's create a Makefile for downloading the data. Later, you will also
+include (in the same Makefile) the necessary work in order to make the
+analysis. Save this Makefile in the dedicated directory
+(<code>reproduce/analysis/make</code>) with the name <code>getdata-analysis.mk</code>. In that
+Makefile, paste the following code.</p>
+
+<p>```</p>
+
+<h1>Download data for the tutorial</h1>
+
+<p>#</p>
+
+<h1>In this Makefile, data for the tutorial is downloaded.</h1>
+
+<p>#</p>
+
+<h1>Copyright (C) 2020 Raul Infante-Sainz <a href="&#x6D;&#x61;&#x69;&#108;&#116;&#111;:&#x69;n&#x66;&#x61;&#x6E;&#116;&#x65;&#x73;a&#x69;n&#122;&#64;&#103;&#x6D;&#97;&#105;&#108;.&#x63;&#111;&#x6D;">&#x69;n&#x66;&#x61;&#x6E;&#116;&#x65;&#x73;a&#x69;n&#122;&#64;&#103;&#x6D;&#97;&#105;&#108;.&#x63;&#111;&#x6D;</a></h1>
+
+<h1>Copyright (C) YYYY Your Name <a href="&#109;&#x61;&#105;&#108;&#x74;&#x6F;:&#x79;&#x6F;&#x75;&#114;&#x2D;&#x65;&#109;&#x61;&#105;&#x6C;&#64;&#101;&#x78;&#x61;&#x6D;&#x70;&#108;&#101;&#x2E;&#120;&#x78;&#120;">&#x79;&#x6F;&#x75;&#114;&#x2D;&#x65;&#109;&#x61;&#105;&#x6C;&#64;&#101;&#x78;&#x61;&#x6D;&#x70;&#108;&#101;&#x2E;&#120;&#x78;&#120;</a></h1>
+
+<p>#</p>
+
+<h1>This Makefile is free software: you can redistribute it and/or modify it</h1>
+
+<h1>under the terms of the GNU General Public License as published by the</h1>
+
+<h1>Free Software Foundation, either version 3 of the License, or (at your</h1>
+
+<h1>option) any later version.</h1>
+
+<p>#</p>
+
+<h1>This Makefile is distributed in the hope that it will be useful, but</h1>
+
+<h1>WITHOUT ANY WARRANTY; without even the implied warranty of</h1>
+
+<h1>MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General</h1>
+
+<h1>Public License for more details. See <a href="http://www.gnu.org/licenses/">http://www.gnu.org/licenses/</a>.</h1>
+
+<h1>Download data for the tutorial</h1>
+
+<h1>------------------------------</h1>
+
+<p>#
+pop-data = $(indir)/ESP.dat
+$(pop-data): | $(indir)
+ wget http://akhlaghi.org/data/template-tutorial/ESP.dat -O $@</p>
+
+<h1>Final TeX macro</h1>
+
+<h1>---------------</h1>
+
+<p>#</p>
+
+<h1>It is very important to mention the address where the data were</h1>
+
+<h1>downloaded in the final report.</h1>
+
+<p>$(mtexdir)/getdata-analysis.tex: $(pop-data) | $(mtexdir)
+ echo "\newcommand{\popurl}{http://akhlaghi.org/data/template-tutorial}" > $@
+```</p>
+
+<p>Have a look at this Makefile and see the different parts. The first line is
+a descriptive title. Below, include your name, contact email, and finally,
+the copyright. Please, take your time in order to add all relevant
+information in each Makefile you modify. As you can see, these lines start
+with <code>#</code> because they are comments.</p>
+
+<p>After that information, there are five white lines in order to separate the
+different parts. Then, you have the Make rule to download the data. Remember
+the general structure of a Make rule:</p>
+
+<p><code>
+TARGETS: PREREQUISITES
+ RECIPE
+</code></p>
+
+<p>In a rule, it is said how to construct the <code>TARGETS</code> from the
+<code>PREREQUISITES</code>, following the <code>RECIPE</code>. <strong>Note that the white space at the
+beginning of the <code>RECIPE</code> are not spaces but a single <code>TAB</code>. Take into
+account this if you copy/paste the code.</strong></p>
+
+<p>Now you can see this structure in our particular case:</p>
+
+<p><code>
+$(pop-data): | $(indir)
+ wget http://akhlaghi.org/data/template-tutorial/ESP.dat -O $@
+</code></p>
+
+<p>Here we have:</p>
+
+<ul>
+<li><p><code>$(pop-data)</code> is the TARGET. It is previously defined just one line above:
+<code>pop-data = $(indir)/ESP.dat</code>. As it can be seen, the target is just one
+file named <code>ESP.dat</code> into the <code>indir</code> directory.</p></li>
+<li><p><code>$(indir)</code> is the PREREQUISITE. In this case, nothing is needed for
+obtaining the TARGET, just the output directory in which it is going to be
+saved. This is the reason of having the pipe <code>|</code> at the beginning of the
+prerequisite (it indicates an order-only-prerequisite).</p></li>
+<li><p><code>wget http://akhlaghi.org/data/template-tutorial/ESP.dat -O $@</code> is the
+RECIPE. It states how to construct the <code>TARGET</code> from the <code>PREREQUISITE</code>.
+In this case, it is just the use of <code>wget</code> to download the file specified
+in the <code>URL</code> (<code>http://akhlaghi.org/data/template-tutorial/ESP.dat</code>) and
+save it as the target: <code>-O $@</code>. Inisde of a Make rule, <code>$@</code> is the target.
+So, in this case: <code>$@</code> is <code>$(pop-data)</code>.</p></li>
+</ul>
+
+<p>With this, you have included the rule that will download the data. Now, to
+finish, you have to specify what is the final purpose of the Makefile:
+download that data! This is done by setting <code>$(pop-data)</code> as a prerequisite
+of the final rule. Remember that each Makefile will build a final target
+with the same name as the Makefile, but with the extension <code>.tex</code>. As a
+consequence, they will be <code>TeX</code> macros in which relevant information to be
+included into the final paper are saved . Here, you are saving the <code>URL</code>.</p>
+
+<p><code>
+$(mtexdir)/getdata-analysis.tex: $(pop-data) | $(mtexdir)
+ echo "\\newcommand{\\popurl}{http://akhlaghi.org/data/template-tutorial}" &gt; $@
+</code></p>
+
+<p>In this final rule we have:</p>
+
+<ul>
+<li><p><code>$(mtexdir)/getdata-analysis.tex</code> is the TARGET. It is the <code>TeX</code> macro.
+Note that it has the same name as the Makefile itself, but it will be
+saved into the <code>$(mtexdir)</code> directory. What do I need for constructing
+this target? The prerequisites.</p></li>
+<li><p><code>$(pop-data) | $(mtexdir)</code> are the PREREQUISITES. In this case you have
+two prerequisites. First, <code>$(pop-data)</code>, which indicates that the final
+<code>TeX</code> macro has to be generated after this file has been obtained. The
+second prerequisite is order-only-prerequisite, and it is the directory in
+which the target is saved: <code>$(mtexdir)</code>.</p></li>
+<li><p><code>echo "\\newcommand{\\popurl}{http://akhlaghi.org/data/template-tutorial}" &gt; $@</code>
+is the RECIPE. Basically, it writes the text
+<code>\\newcommand{\\popurl}{http://akhlaghi.org/data/template-tutorial}</code> into
+the TARGET (<code>$@</code>). As you can see, this is the definition of a new
+command in <code>TeX</code>. The definition of this new command <code>\popurl</code> will be used
+for writting the final paper.</p></li>
+</ul>
+
+<p>Only one step is remaining to finally make the download of the data. You
+have to add the name (without the extension .mk) of this Makefile into the
+<code>reproduce/analysis/make/top-make.mk</code> Makefile. There it is defined which
+Makefiles have to be executed. You have to end up having:</p>
+
+<p><code>
+makesrc = initialize \
+ download \
+ getdata-analyse \
+ delete-me \
+ paper
+</code></p>
+
+<p>As allways, read carefully all comments and information in order to know
+what is going ong. Also, add your own comments and information in order to
+be clear and explain each step with enough level of detail. If everything is
+fine, now the project is ready to download the data in the make step. Try
+it!</p>
+
+<p><code>shell
+$ ./project make
+</code></p>
+
+<p>Hopefully, it will download and save the file into the folder called
+<code>inputs</code> under the <code>build-directory</code>. Check that it is there, and also have
+a look at the <code>TeX</code> macro in order to see that the new command has been
+included, it is into the top-build directory:
+<code>build-directory/tex/macros/getdata-analysis.tex</code>.</p>
+
+<p>Now that all of this changes have been included and it works fine, it is
+time to check little by little everything and make a commit order to save
+this work. Remember to put a good commit title and a nice commit message
+describing what you have done and why. Then, push the commit to the
+remote/origin.</p>
+
+<p>Congratulations! You have included you first Makefile and the data is now
+ready to be analysed!</p>
+
+<p><strong>In short</strong>, to download the data you did the following:</p>
+
+<ul>
+<li>Create a Makefile: <code>reproduce/analysis/make/getdata-analysis.mk</code></li>
+<li>Write meta-data at the beginning: title, your name, email, copyright, etc.</li>
+<li>Define the file you want to download, and the rule to do it.</li>
+<li>Write the rule to generate the <code>TeX</code> macro, putting as prerequisite, the
+file you are downloading.</li>
+<li>Add the name of the Makefile (without the <code>.tex</code>) into
+<code>reproduce/analysis/make/top-make.mk</code></li>
+<li><code>$ ./project make</code> in order to execute the project and download
+the data.</li>
+<li>Check that everything worked fine by loking at the downloaded file and the
+<code>TeX</code> macro.</li>
+<li>Commit and push all the work included.</li>
+</ul>
+
+<h2>Adding the analysis rule</h2>
+
+<p>Until this point, you have included the Python script that will do the
+linear fitting, and the rule for downloading the data. Now, it is necessary
+to construct the Make rule in which this Python script is invoked to do the
+analysis. This rule will be put in the same Makefile you have already
+generated for downloading the data. But, before this, define the directory
+in which the target is going to be saved.</p>
+
+<p><code>
+odir = $(BDIR)/fit-parameters
+</code></p>
+
+<p>This is a folder under the <code>build-directory</code> called <code>fit-parameters</code>. After
+that, define the target: a plain text file in which the linear fit
+parameters are saved (by the Python script). Put it into the previously
+defined directory. As the data is from Spain, name it <code>ESP.txt</code>.</p>
+
+<p><code>
+param-file = $(odir)/ESP.txt
+</code></p>
+
+<p>Now, include a rule to construct the output directory <code>odir</code>. This is
+necessary because this directory is needed for saving the file <code>ESP.txt</code>.</p>
+
+<p><code>
+$(odir):
+ mkdir $@
+</code></p>
+
+<p>With all the previous definitions, now it is possible to set the rule for
+making the analysis:</p>
+
+<p><code>
+$(param-file): $(indir)/ESP.dat | $(odir)
+ python reproduce/analysis/python/linear-fit.py $&lt; $@ $(odir)/ESP.pdf
+</code></p>
+
+<p>In this rule you have:</p>
+
+<ul>
+<li><p><code>$(param-file)</code> is the TARGET. It is the file previously defined in which
+the fitting parameters will be saved.</p></li>
+<li><p><code>$(indir)/ESP.dat | $(odir)</code> are the PREREQUISITES. In this case you have
+two prerequisites. First, <code>$(indir)/ESP.dat</code>, which is the input file
+previously downloaded by the rule above. In this file there is the input
+data that the Python script will use for making the linear fit. <code>$(odir)</code>
+is the second prerequisite. It is order-only-prerequisite (indicated by
+the pipe <code>|</code>), and it is the directory where the target is saved.</p></li>
+<li><p><code>python reproduce/analysis/python/linear-fit.py $&lt; $@ $(odir)/ESP.pdf</code> is
+the RECIPE. Basically, it call <code>python</code> to run the script
+<code>reproduce/analysis/python/linear-fit.py</code> with the necessary arguments:
+the input file <code>$&lt;</code>, the target <code>$@</code>, and the name of the figure
+<code>$(odir)/ESP.pdf</code> (a PDF figure saved into the same directory than the
+target.</p></li>
+</ul>
+
+<p>Finally, in order to indicate you want to obtain the target you have just
+included (<code>$(param-file)</code>), it is necessary to add it as a prerequisite of
+the final TARGET <code>$(mtexdir)/linear-fit.tex</code>. So, in the last rule (which
+creates the <code>TeX</code> macro), remove <code>$(pop-data)</code> and put <code>$(param-file)</code>
+instead. By doing this, you are telling to the Makefile that you want to
+obtain the file in which it is saved the fitted parameters. Inside of the
+rule, define a couple of bash variables (<code>a</code> and <code>b</code>) that are the fitted
+parameters extracted from the prerequisite. For <code>a</code>:</p>
+
+<p><code>
+a=$$(cat $&lt; | awk 'NR==1{print $1}')
+</code></p>
+
+<p>Similarly, for obtaining the parameter <code>b</code> (which is in the second row):</p>
+
+<p><code>
+b=$$(cat $&lt; | awk 'NR==2{print $1}')
+</code></p>
+
+<p>Then you have to specify the new <code>TeX</code> commands for these two parameters,
+just write them as it was done before for the <code>URL</code>:</p>
+
+<p>```
+echo "\newcommand{\afitparam}{$$a}" >> $@
+echo "\newcommand{\bfitparam}{$$b}" >> $@</p>
+
+<p>```</p>
+
+<p>So, at the end you will have the final rule like this:</p>
+
+<p>```
+$(mtexdir)/getdata-analysis.tex: $(param-file) | $(mtexdir)</p>
+
+<pre><code> echo "\\newcommand{\\popurl}{http://akhlaghi.org/data/template-tutorial}" &gt; $@
+
+ a=$$(cat $&lt; | awk 'NR==1{print $1}')
+ b=$$(cat $&lt; | awk 'NR==2{print $1}')
+
+ echo "\newcommand{\afitparam}{$$a}" &gt;&gt; $@
+ echo "\newcommand{\bfitparam}{$$b}" &gt;&gt; $@
+</code></pre>
+
+<p>```</p>
+
+<p><strong>Important notes: you have to use two <code>$</code> in order to use the bash <code>$</code>
+character inside of a Make rule. Also, note that you have to put <code>&gt;&gt;</code> in
+order to not create a new target each time you write someting into the
+target. With the double <code>&gt;</code> it will only add the line at the end of the file
+without generating a new file.</strong></p>
+
+<p>With all the above modifications, you are ready to obtain the fitting
+parameters. If you add the necessary comments and information, the final
+Makefile would look similar to:</p>
+
+<p>```</p>
+
+<h1>Download data and linear fitting for the tutorial</h1>
+
+<p>#</p>
+
+<h1>In this Makefile, data for the tutorial is downloaded. Then, a Python</h1>
+
+<h1>script is used to make a linear fitting. Finally, fitted parameters as</h1>
+
+<h1>well as the URL is saved into a TeX macro.</h1>
+
+<p>#</p>
+
+<h1>Copyright (C) 2020 Raul Infante-Sainz <a href="&#x6D;&#97;i&#x6C;t&#x6F;:&#105;&#110;&#x66;&#97;&#110;&#116;&#101;&#x73;&#x61;&#105;&#110;&#122;&#64;&#x67;&#109;&#97;i&#108;&#x2E;&#x63;&#111;&#109;">&#105;&#110;&#x66;&#97;&#110;&#116;&#101;&#x73;&#x61;&#105;&#110;&#122;&#64;&#x67;&#109;&#97;i&#108;&#x2E;&#x63;&#111;&#109;</a></h1>
+
+<h1>Copyright (C) YYYY Your Name <a href="&#109;&#97;&#x69;&#108;&#x74;o:&#121;&#x6F;&#117;&#x72;&#x2D;&#x65;m&#97;&#105;&#108;&#64;&#x65;&#120;&#97;&#x6D;&#112;&#x6C;&#x65;&#46;&#x78;&#x78;x">&#121;&#x6F;&#117;&#x72;&#x2D;&#x65;m&#97;&#105;&#108;&#64;&#x65;&#120;&#97;&#x6D;&#112;&#x6C;&#x65;&#46;&#x78;&#x78;x</a></h1>
+
+<p>#</p>
+
+<h1>This Makefile is free software: you can redistribute it and/or modify it</h1>
+
+<h1>under the terms of the GNU General Public License as published by the</h1>
+
+<h1>Free Software Foundation, either version 3 of the License, or (at your</h1>
+
+<h1>option) any later version.</h1>
+
+<p>#</p>
+
+<h1>This Makefile is distributed in the hope that it will be useful, but</h1>
+
+<h1>WITHOUT ANY WARRANTY; without even the implied warranty of</h1>
+
+<h1>MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General</h1>
+
+<h1>Public License for more details. See <a href="http://www.gnu.org/licenses/">http://www.gnu.org/licenses/</a>.</h1>
+
+<h1>Download data for the tutorial</h1>
+
+<h1>------------------------------</h1>
+
+<p>#</p>
+
+<h1>The input file is defined and downloaded using the following rule</h1>
+
+<p>pop-data = $(indir)/ESP.dat
+$(pop-data): | $(indir)
+ # Use wget to download the data
+ wget http://akhlaghi.org/data/template-tutorial/ESP.dat -O $@</p>
+
+<h1>Output directory</h1>
+
+<h1>----------------</h1>
+
+<p>#</p>
+
+<h1>Small rule for constructing the output directory, previously defined</h1>
+
+<p>odir = $(BDIR)/fit-parameters
+$(odir):
+ # Build the output directory
+ mkdir $@</p>
+
+<h1>Linear fitting of the data</h1>
+
+<h1>--------------------------</h1>
+
+<p>#</p>
+
+<h1>The output file is defined into the output directory. The fitted</h1>
+
+<h1>parameters will be saved into this directory by the Python script.</h1>
+
+<p>param-file = $(odir)/ESP.txt
+$(param-file): $(indir)/ESP.dat | $(odir)
+ # Invoke Python to run the script with the input data
+ python reproduce/analysis/python/linear-fit.py $&lt; $@ $(odir)/ESP.pdf</p>
+
+<h1>TeX macros final target</h1>
+
+<h1>-----------------------</h1>
+
+<p>#</p>
+
+<h1>This is how we write the necessary parameters in the final PDF. In this</h1>
+
+<h1>rule, new TeX parameters are defined from the URL, and the fitted</h1>
+
+<h1>parameters.</h1>
+
+<p>$(mtexdir)/getdata-analysis.tex: $(param-file) | $(mtexdir)</p>
+
+<pre><code> # Write the URL into the target
+ echo "\newcommand{\popurl}{http://akhlaghi.org/data/template-tutorial}" &gt; $@
+
+ # Read the fitted parameters and save them into the target
+ a=$$(cat $&lt; | awk 'NR==1{print $1}')
+ b=$$(cat $&lt; | awk 'NR==2{print $1}')
+
+ echo "\newcommand{\afitparam}{$$a}" &gt;&gt; $@
+ echo "\newcommand{\bfitparam}{$$b}" &gt;&gt; $@
+</code></pre>
+
+<p>```</p>
+
+<p>Have look at this Makefile and note that it is what it has been described
+above. Take your time for making useful comments and modifying whatever you
+think it is necessary. If everything is fine, now the project is ready to
+download the data <strong>and</strong> make the linear fitting. Try it!</p>
+
+<p><code>shell
+$ ./project make
+</code></p>
+
+<p>Hopefully, now you will have the fitted parameters into the
+<code>build-directory/fit-parameters/ESP.txt</code> file, and the figure in the same
+directory. Do not pay to much attention at the quality of the fitting. It is
+just an example. Also, check that the <code>TeX</code> macro has been created
+successfully by having a look at
+<code>build-directory/tex/macros/getdata-analyse.tex</code>. Finally, now that you have
+ensured that everything is fine, make a commit in order to keep the work
+safe. In the next step, you will see how to include this data into the final
+paper.</p>
+
+<p><strong>In short:</strong> with the work included in this section, the project is able to
+download and make the linear fitting of the data. The result is the fitted
+parameters that are also saved in a <code>TeX</code> macro, and the figure showing the
+data with the fitted curve.</p>
+
+<h2>Editing the final paper</h2>
+
+<p>With all the previous work, the project is able to download the file
+containing the data (two columns, year and population of Spain), and analyse
+them by making a linear fitting (y=ax+b). The result is a <code>TeX</code> macro in
+which there are the information about the <code>URL</code> of the data and the linear
+fitting parameters (<code>a</code> and <code>b</code>). Now, it is time to add a small paragraph
+into the paper, just to ilustrate how to write the relevant parameters from
+the analysis.</p>
+
+<p>Before all, make a copy of the current <code>paper.pdf</code> document you have into
+the <code>project-directory</code>. This paper is an example that <code>Maneage</code> constructs
+by default. Now, you will modify it by adding a small paragraph including
+the fitting parameters and the <code>URL</code>. So, open <code>project-directory/paper.tex</code>
+and add the following paragraph just at the beginning of the abstract
+section.</p>
+
+<p><code>
+By following the steps described in the tutorial, I have been able to obtain this reproducible paper!
+The project is very simple and it consists in download a file (from \popurl), and make an easy linear fit using a Python script.
+The linear fitting is $y=a*x+b$, with the following parameters: $a=\afitparam$ and $b=\bfitparam$
+</code></p>
+
+<p>As you can see, the <code>TeX</code> definitions done before in the Makefiles, are now
+included into the paper: <code>\popurl</code>, <code>\afitparam</code>, and <code>\bfitparam</code>. If you
+do again the make step <code>$ ./project make</code>, you will re-compile the paper
+including this paragraph. Check that it is true and compare with the
+previous version, of the paper. Contratulations! You have complete this
+tutorial and now you are able to use <code>Maneage</code> for making your exciting
+research in a reproducible way!</p>
+
+<h2>Copyright information</h2>
+
+<p>This file is part of the reproducible paper template
+ http://savannah.nongnu.org/projects/reproduce</p>
+
+<p>This template is free software: you can redistribute it and/or modify it
+under the terms of the GNU General Public License as published by the Free
+Software Foundation, either version 3 of the License, or (at your option)
+any later version.</p>
+
+<p>This template is distributed in the hope that it will be useful, but
+WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY
+or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for
+more details.</p>
+
+<p>You should have received a copy of the GNU General Public License along
+with Template. If not, see <a href="https://www.gnu.org/licenses/">https://www.gnu.org/licenses/</a>.</p>