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diff --git a/book/module1/1_excel_to_python.tex b/book/module1/1_excel_to_python.tex
deleted file mode 100644
index 300c951..0000000
--- a/book/module1/1_excel_to_python.tex
+++ /dev/null
@@ -1,119 +0,0 @@
-\section{Excel to Python}\label{excel-to-python}
-
-\begin{itemize}
-\tightlist
-\item
-  Importing
-\item
-  Plotting
-\item
-  Statistical analysis
-\end{itemize}
-
-\subsection{\texorpdfstring{\textbf{How Excel Translates to
-Python}}{How Excel Translates to Python}}\label{how-excel-translates-to-python}
-
-Here's how common Excel functionalities map to Python:
-
-\begin{longtable}[]{@{}
-  >{\raggedright\arraybackslash}p{(\columnwidth - 2\tabcolsep) * \real{0.2911}}
-  >{\raggedright\arraybackslash}p{(\columnwidth - 2\tabcolsep) * \real{0.7089}}@{}}
-\toprule\noalign{}
-\begin{minipage}[b]{\linewidth}\raggedright
-\textbf{Excel Feature}
-\end{minipage} & \begin{minipage}[b]{\linewidth}\raggedright
-\textbf{Python Equivalent}
-\end{minipage} \\
-\midrule\noalign{}
-\endhead
-\bottomrule\noalign{}
-\endlastfoot
-Formulas (SUM, AVERAGE) & \texttt{numpy}, \texttt{pandas}
-(\texttt{df.sum()}, \texttt{df.mean()}) \\
-Sorting \& Filtering & \texttt{pandas.sort\_values()},
-\texttt{df{[}df{[}\textquotesingle{}col\textquotesingle{}{]}\ \textgreater{}\ value{]}} \\
-Conditional Formatting & \texttt{matplotlib} for highlighting \\
-Pivot Tables & \texttt{pandas.pivot\_table()} \\
-Charts \& Graphs & \texttt{matplotlib}, \texttt{seaborn},
-\texttt{plotly} \\
-Regression Analysis & \texttt{scipy.stats.linregress},
-\texttt{sklearn.linear\_model} \\
-Solver/Optimization & \texttt{scipy.optimize} \\
-VBA Macros & Python scripting with \texttt{openpyxl}, \texttt{pandas},
-or \texttt{xlwings} \\
-\end{longtable}
-
-\subsection{Statistical functions}\label{statistical-functions}
-
-\paragraph{SUM}\label{sum}
-
-Built-in:
-
-\begin{Shaded}
-\begin{Highlighting}[]
-\NormalTok{my\_array }\OperatorTok{=}\NormalTok{ [}\DecValTok{1}\NormalTok{, }\DecValTok{2}\NormalTok{, }\DecValTok{3}\NormalTok{, }\DecValTok{4}\NormalTok{, }\DecValTok{5}\NormalTok{]}
-\NormalTok{total }\OperatorTok{=} \BuiltInTok{sum}\NormalTok{(my\_array)}
-\BuiltInTok{print}\NormalTok{(total)  }\CommentTok{\# Output: 15}
-\end{Highlighting}
-\end{Shaded}
-
-Numpy:
-
-\begin{Shaded}
-\begin{Highlighting}[]
-\ImportTok{import}\NormalTok{ numpy }\ImportTok{as}\NormalTok{ np}
-
-\NormalTok{my\_array }\OperatorTok{=}\NormalTok{ np.array([}\DecValTok{1}\NormalTok{, }\DecValTok{2}\NormalTok{, }\DecValTok{3}\NormalTok{, }\DecValTok{4}\NormalTok{, }\DecValTok{5}\NormalTok{])}
-\NormalTok{total }\OperatorTok{=}\NormalTok{ np.}\BuiltInTok{sum}\NormalTok{(my\_array)}
-\BuiltInTok{print}\NormalTok{(total)  }\CommentTok{\# Output: 15}
-\end{Highlighting}
-\end{Shaded}
-
-\subsubsection{Average}\label{average}
-
-Built-in:
-
-\begin{Shaded}
-\begin{Highlighting}[]
-\NormalTok{my\_array }\OperatorTok{=}\NormalTok{ [}\DecValTok{1}\NormalTok{, }\DecValTok{2}\NormalTok{, }\DecValTok{3}\NormalTok{, }\DecValTok{4}\NormalTok{, }\DecValTok{5}\NormalTok{]}
-\NormalTok{average }\OperatorTok{=} \BuiltInTok{sum}\NormalTok{(my\_array) }\OperatorTok{/} \BuiltInTok{len}\NormalTok{(my\_array)}
-\BuiltInTok{print}\NormalTok{(average)  }\CommentTok{\# Output: 3.0}
-\end{Highlighting}
-\end{Shaded}
-
-Numpy:
-
-\begin{Shaded}
-\begin{Highlighting}[]
-\ImportTok{import}\NormalTok{ numpy }\ImportTok{as}\NormalTok{ np}
-
-\NormalTok{my\_array }\OperatorTok{=}\NormalTok{ np.array([}\DecValTok{1}\NormalTok{, }\DecValTok{2}\NormalTok{, }\DecValTok{3}\NormalTok{, }\DecValTok{4}\NormalTok{, }\DecValTok{5}\NormalTok{])}
-\NormalTok{average }\OperatorTok{=}\NormalTok{ np.mean(my\_array)}
-\BuiltInTok{print}\NormalTok{(average)  }\CommentTok{\# Output: 3.0}
-\end{Highlighting}
-\end{Shaded}
-
-\subsection{Plotting}\label{plotting}
-
-We can use the package \emph{matplotlib} to plot our graphs in python.
-Matplotlib provides data visualization tools for the Scientific Python
-Ecosystem. You can make very professional looking figures with this
-tool.
-
-Here is a section from the matplotlib documentation page that you can
-run in python.
-
-\begin{Shaded}
-\begin{Highlighting}[]
-\ImportTok{import}\NormalTok{ matplotlib.pyplot }\ImportTok{as}\NormalTok{ plt}
-
-\NormalTok{fig, ax }\OperatorTok{=}\NormalTok{ plt.subplots()             }\CommentTok{\# Create a figure containing a single Axes.}
-\NormalTok{ax.plot([}\DecValTok{1}\NormalTok{, }\DecValTok{2}\NormalTok{, }\DecValTok{3}\NormalTok{, }\DecValTok{4}\NormalTok{], [}\DecValTok{1}\NormalTok{, }\DecValTok{4}\NormalTok{, }\DecValTok{2}\NormalTok{, }\DecValTok{3}\NormalTok{])  }\CommentTok{\# Plot some data on the Axes.}
-\NormalTok{plt.show()                           }\CommentTok{\# Show the figure.}
-\end{Highlighting}
-\end{Shaded}
-
-Check out the documentation pages for a
-\href{https://matplotlib.org/stable/users/explain/quick_start.html\#a-simple-example}{simple
-example} or more information on the types of plots you came create
-\href{https://matplotlib.org/stable/plot_types/index.html}{here}.
diff --git a/book/module1/array.tex b/book/module1/array.tex
deleted file mode 100644
index e442ba6..0000000
--- a/book/module1/array.tex
+++ /dev/null
@@ -1,293 +0,0 @@
-\section{Arrays}\label{arrays}
-
-In computer programming, an array is a structure for storing and
-retrieving data. We often talk about an array as if it were a grid in
-space, with each cell storing one element of the data. For instance, if
-each element of the data were a number, we might visualize a
-``one-dimensional'' array like a list:
-
-\begin{longtable}[]{@{}llll@{}}
-\toprule\noalign{}
-1 & 5 & 2 & 0 \\
-\midrule\noalign{}
-\endhead
-\bottomrule\noalign{}
-\endlastfoot
-\end{longtable}
-
-A two-dimensional array would be like a table:
-
-\begin{longtable}[]{@{}llll@{}}
-\toprule\noalign{}
-1 & 5 & 2 & 0 \\
-\midrule\noalign{}
-\endhead
-\bottomrule\noalign{}
-\endlastfoot
-8 & 3 & 6 & 1 \\
-1 & 7 & 2 & 9 \\
-\end{longtable}
-
-A three-dimensional array would be like a set of tables, perhaps stacked
-as though they were printed on separate pages. If we visualize the
-position of each element as a position in space. Then we can represent
-the value of the element as a property. In other words, if we were to
-analyze the stress concentration of an aluminum block, the property
-would be stress.
-
-\begin{itemize}
-\tightlist
-\item
-  From
-  \href{https://numpy.org/doc/2.2/user/absolute_beginners.html}{Numpy
-  documentation}
-\end{itemize}
-
-\begin{figure}
-\centering
-\includegraphics{figures/multi-dimensional-array.png}
-\caption{Mathworks 3-D array}
-\end{figure}
-
-If the load on this block changes over time, then we may want to add a
-4th dimension i.e.~additional sets of 3-D arrays for each time
-increment. As you can see - the more dimensions we add, the more
-complicated of a problem we have to solve. It is possible to increase
-the number of dimensions to the n-th order. This course we will not be
-going beyond dimensional analysis.
-
-\subsection{Numpy - the python's array
-library}\label{numpy---the-pythons-array-library}
-
-In this tutorial we will be introducing arrays and we will be using the
-numpy library. Arrays, lists, vectors, matrices, sets - You might've
-heard of them before, they all store data. In programming, an array is a
-variable that can hold more than one value at a time. We will be using
-the Numpy python library to create arrays. Since we already have
-installed Numpy previously, we can start using the package.
-
-Before importing our first package, let's as ourselves \emph{what is a
-package?} A package can be thought of as pre-written python code that we
-can re-use. This means the for every script that we write in python we
-need to tell it to use a certain package. We call this importing a
-package.
-
-\subsubsection{Importing Numpy}\label{importing-numpy}
-
-When using packages in python, we need to let it know what package we
-will be using. This is called importing. To import numpy we need to
-declare it a the start of a script as follows:
-
-\begin{Shaded}
-\begin{Highlighting}[]
-\ImportTok{import}\NormalTok{ numpy }\ImportTok{as}\NormalTok{ np}
-\end{Highlighting}
-\end{Shaded}
-
-\begin{itemize}
-\tightlist
-\item
-  \texttt{import} - calls for a library to use, in our case it is Numpy.
-\item
-  \texttt{as} - gives the library an alias in your script. It's common
-  convention in Python programming to make the code shorter and more
-  readable. We will be using \emph{np} as it's a standard using in many
-  projects.
-\end{itemize}
-
-\subsection{Creating arrays}\label{creating-arrays}
-
-Now that we have imported the library we can create a one dimensional
-array or \emph{vector} with three elements.
-
-\begin{Shaded}
-\begin{Highlighting}[]
-\NormalTok{x }\OperatorTok{=}\NormalTok{ np.array([}\DecValTok{1}\NormalTok{,}\DecValTok{2}\NormalTok{,}\DecValTok{3}\NormalTok{])}
-\end{Highlighting}
-\end{Shaded}
-
-To create a \emph{matrix} we can nest the arrays to create a two
-dimensional array. This is done as follows.
-
-\begin{Shaded}
-\begin{Highlighting}[]
-\NormalTok{matrix }\OperatorTok{=}\NormalTok{ np.array([[}\DecValTok{1}\NormalTok{,}\DecValTok{2}\NormalTok{,}\DecValTok{3}\NormalTok{],}
-\NormalTok{                   [}\DecValTok{4}\NormalTok{,}\DecValTok{5}\NormalTok{,}\DecValTok{6}\NormalTok{],}
-\NormalTok{                   [}\DecValTok{7}\NormalTok{,}\DecValTok{8}\NormalTok{,}\DecValTok{9}\NormalTok{]])}
-\end{Highlighting}
-\end{Shaded}
-
-\emph{Note: for every array we nest, we get a new dimension in our data
-structure.}
-
-\subsubsection{Numpy array creation
-functions}\label{numpy-array-creation-functions}
-
-Numpy comes with some built-in function that we can use to create arrays
-quickly. Here are a couple of functions that are commonly used in
-python. \#\#\#\# np.arange The \texttt{np.arange()} function returns an
-array with evenly spaced values within a specified range. It is similar
-to the built-in \texttt{range()} function in Python but returns a Numpy
-array instead of a list. The parameters for this function are the start
-value (inclusive), the stop value (exclusive), and the step size. If the
-step size is not provided, it defaults to 1.
-
-\begin{Shaded}
-\begin{Highlighting}[]
-\OperatorTok{\textgreater{}\textgreater{}\textgreater{}}\NormalTok{ np.arange(}\DecValTok{4}\NormalTok{)}
-\NormalTok{array([}\FloatTok{0.}\NormalTok{ , }\FloatTok{1.}\NormalTok{, }\FloatTok{2.}\NormalTok{, }\FloatTok{3.}\NormalTok{ ])}
-\end{Highlighting}
-\end{Shaded}
-
-In this example, \texttt{np.arange(4)} generates an array starting from
-0 and ending before 4, with a step size of 1.
-
-\paragraph{np.linspace}\label{np.linspace}
-
-The \texttt{np.linspace()} function returns an array of evenly spaced
-values over a specified range. Unlike \texttt{np.arange()}, which uses a
-step size to define the spacing between elements, \texttt{np.linspace()}
-uses the number of values you want to generate and calculates the
-spacing automatically. It accepts three parameters: the start value, the
-stop value, and the number of samples.
-
-\begin{Shaded}
-\begin{Highlighting}[]
-\OperatorTok{\textgreater{}\textgreater{}\textgreater{}}\NormalTok{ np.linspace(}\FloatTok{1.}\NormalTok{, }\FloatTok{4.}\NormalTok{, }\DecValTok{6}\NormalTok{)}
-\NormalTok{array([}\FloatTok{1.}\NormalTok{ ,  }\FloatTok{1.6}\NormalTok{,  }\FloatTok{2.2}\NormalTok{,  }\FloatTok{2.8}\NormalTok{,  }\FloatTok{3.4}\NormalTok{,  }\FloatTok{4.}\NormalTok{ ])}
-\end{Highlighting}
-\end{Shaded}
-
-In this example, \texttt{np.linspace(1.,\ 4.,\ 6)} generates 6 evenly
-spaced values between 1. and 4., including both endpoints.
-
-Try this and see what happens:
-
-\begin{Shaded}
-\begin{Highlighting}[]
-\NormalTok{x }\OperatorTok{=}\NormalTok{ np.linspace(}\DecValTok{0}\NormalTok{,}\DecValTok{100}\NormalTok{,}\DecValTok{101}\NormalTok{)}
-\NormalTok{y }\OperatorTok{=}\NormalTok{ np.sin(x)}
-\end{Highlighting}
-\end{Shaded}
-
-\paragraph{Other useful functions}\label{other-useful-functions}
-
-\begin{itemize}
-\tightlist
-\item
-  \texttt{np.zeros()}
-\item
-  \texttt{np.ones()}
-\item
-  \texttt{np.eye()}
-\end{itemize}
-
-\subsubsection{Working with Arrays}\label{working-with-arrays}
-
-Now that we have been introduced to some ways to create arrays using the
-Numpy functions let's start using them. \#\#\#\# Indexing Indexing in
-Python allows you to access specific elements within an array based on
-their position. This means you can directly retrieve and manipulate
-individual items as needed.
-
-Python uses \textbf{zero-based indexing}, meaning the first element is
-at position \textbf{0} rather than \textbf{1}. This approach is common
-in many programming languages. For example, in a list with five
-elements, the first element is at index \texttt{0}, followed by elements
-at indices \texttt{1}, \texttt{2}, \texttt{3}, and \texttt{4}.
-
-Here's an example of data from a rocket test stand where thrust was
-recorded as a function of time.
-
-\begin{Shaded}
-\begin{Highlighting}[]
-\NormalTok{thrust\_lbf }\OperatorTok{=}\NormalTok{ np.array(}\FloatTok{0.603355}\NormalTok{, }\FloatTok{2.019083}\NormalTok{, }\FloatTok{2.808092}\NormalTok{, }\FloatTok{4.054973}\NormalTok{, }\FloatTok{1.136618}\NormalTok{, }\FloatTok{0.943668}\NormalTok{)}
-
-\BuiltInTok{print}\NormalTok{(thrust\_lbs[}\DecValTok{3}\NormalTok{])}
-\end{Highlighting}
-\end{Shaded}
-
-Due to the nature of zero-based indexing. If we want to call the value
-\texttt{4.054973} that will be the 3rd index. \#\#\#\# Operations on
-arrays - Arithmetic operations (\texttt{+}, \texttt{-}, \texttt{*},
-\texttt{/}, \texttt{**}) - \texttt{np.add()}, \texttt{np.subtract()},
-\texttt{np.multiply()}, \texttt{np.divide()} - \texttt{np.dot()} for dot
-product - \texttt{np.matmul()} for matrix multiplication -
-\texttt{np.linalg.inv()}, \texttt{np.linalg.det()} for linear algebra
-\#\#\#\#\# Statistics - \texttt{np.mean()}, \texttt{np.median()},
-\texttt{np.std()}, \texttt{np.var()} - \texttt{np.min()},
-\texttt{np.max()}, \texttt{np.argmin()}, \texttt{np.argmax()} -
-Summation along axes: \texttt{np.sum(arr,\ axis=0)}
-
-\subsection{Exercise}\label{exercise}
-
-Let's solve a statics problem given the following problem
-
-A simply supported bridge of length L = 20 m is subjected to three point
-loads:
-
-\begin{itemize}
-\tightlist
-\item
-  \(P_1 = 10 kN\) at \(x = 5 m\)
-\item
-  \(P_2 = 15 kN\) at \(x = 10 m\)
-\item
-  \(P_3 = 20 kN\) at \(x = 15 m\)
-\end{itemize}
-
-The bridge is supported by two reaction forces at points AAA (left
-support) and BBB (right support). We assume the bridge is in static
-equilibrium, meaning the sum of forces and sum of moments about any
-point must be zero.
-
-\subparagraph{Equilibrium Equations:}\label{equilibrium-equations}
-
-\begin{enumerate}
-\def\labelenumi{\arabic{enumi}.}
-\tightlist
-\item
-  \textbf{Sum of Forces in the Vertical Direction}:
-  \(R_A + R_B - P_1 - P_2 - P_3 = 0\)
-\item
-  \textbf{Sum of Moments About Point A}:
-  \(5 P_1 + 10 P_2 + 15 P_3 - 20 R_B = 0\)
-\item
-  \textbf{Sum of Moments About Point B}:
-  \(20 R_A - 15 P_3 - 10 P_2 - 5 P_1 = 0\)
-\end{enumerate}
-
-\subparagraph{System of Equations:}\label{system-of-equations}
-
-\[
-\begin{cases} R_A + R_B - 10 - 15 - 20 = 0 \\ 5(10) + 10(15) + 15(20) - 20 R_B = 0 \\ 20 R_A - 5(10) - 10(15) - 15(20) = 0 \end{cases}
-\]
-
-\subsubsection{Solution}\label{solution}
-
-\begin{Shaded}
-\begin{Highlighting}[]
-\ImportTok{import}\NormalTok{ numpy }\ImportTok{as}\NormalTok{ np}
-
-\CommentTok{\# Define the coefficient matrix A}
-\NormalTok{A }\OperatorTok{=}\NormalTok{ np.array([}
-\NormalTok{    [}\DecValTok{1}\NormalTok{, }\DecValTok{1}\NormalTok{],}
-\NormalTok{    [}\DecValTok{0}\NormalTok{, }\OperatorTok{{-}}\DecValTok{20}\NormalTok{],}
-\NormalTok{    [}\DecValTok{20}\NormalTok{, }\DecValTok{0}\NormalTok{]}
-\NormalTok{])}
-
-\CommentTok{\# Define the right{-}hand side vector b}
-\NormalTok{b }\OperatorTok{=}\NormalTok{ np.array([}
-    \DecValTok{45}\NormalTok{,}
-    \DecValTok{5}\OperatorTok{*}\DecValTok{10} \OperatorTok{+} \DecValTok{10}\OperatorTok{*}\DecValTok{15} \OperatorTok{+} \DecValTok{15}\OperatorTok{*}\DecValTok{20}\NormalTok{,}
-    \DecValTok{5}\OperatorTok{*}\DecValTok{10} \OperatorTok{+} \DecValTok{10}\OperatorTok{*}\DecValTok{15} \OperatorTok{+} \DecValTok{15}\OperatorTok{*}\DecValTok{20}
-\NormalTok{])}
-
-\CommentTok{\# Solve the system of equations Ax = b}
-\NormalTok{x }\OperatorTok{=}\NormalTok{ np.linalg.lstsq(A, b, rcond}\OperatorTok{=}\VariableTok{None}\NormalTok{)[}\DecValTok{0}\NormalTok{]  }\CommentTok{\# Using least squares to handle potential overdetermination}
-
-\CommentTok{\# Display the results}
-\BuiltInTok{print}\NormalTok{(}\SpecialStringTok{f"Reaction force at A (R\_A): }\SpecialCharTok{\{}\NormalTok{x[}\DecValTok{0}\NormalTok{]}\SpecialCharTok{:.2f\}}\SpecialStringTok{ kN"}\NormalTok{)}
-\BuiltInTok{print}\NormalTok{(}\SpecialStringTok{f"Reaction force at B (R\_B): }\SpecialCharTok{\{}\NormalTok{x[}\DecValTok{1}\NormalTok{]}\SpecialCharTok{:.2f\}}\SpecialStringTok{ kN"}\NormalTok{)}
-\end{Highlighting}
-\end{Shaded}
diff --git a/book/module1/arrays.tex b/book/module1/arrays.tex
deleted file mode 100644
index a5486d9..0000000
--- a/book/module1/arrays.tex
+++ /dev/null
@@ -1,411 +0,0 @@
-    \hypertarget{matrixarrays}{%
-\section{matrixArrays}\label{matrixarrays}}
-
-In computer programming, an array is a structure for storing and
-retrieving data. We often talk about an array as if it were a grid in
-space, with each cell storing one element of the data. For instance, if
-each element of the data were a number, we might visualize a
-``one-dimensional'' array like a list:
-
-\begin{longtable}[]{@{}llll@{}}
-\toprule
-1 & 5 & 2 & 0 \\
-\midrule
-\endhead
-\bottomrule
-\end{longtable}
-
-A two-dimensional array would be like a table:
-
-\begin{longtable}[]{@{}llll@{}}
-\toprule
-1 & 5 & 2 & 0 \\
-\midrule
-\endhead
-8 & 3 & 6 & 1 \\
-1 & 7 & 2 & 9 \\
-\bottomrule
-\end{longtable}
-
-A three-dimensional array would be like a set of tables, perhaps stacked
-as though they were printed on separate pages. If we visualize the
-position of each element as a position in space. Then we can represent
-the value of the element as a property. In other words, if we were to
-analyze the stress concentration of an aluminum block, the property
-would be stress.
-
-\begin{itemize}
-\tightlist
-\item
-  From
-  \href{https://numpy.org/doc/2.2/user/absolute_beginners.html}{Numpy
-  documentation}
-
-\end{itemize}
-
-If the load on this block changes over time, then we may want to add a
-4th dimension i.e.~additional sets of 3-D arrays for each time
-increment. As you can see - the more dimensions we add, the more
-complicated of a problem we have to solve. It is possible to increase
-the number of dimensions to the n-th order. This course we will not be
-going beyond dimensional analysis.
-
-\begin{center}\rule{0.5\linewidth}{0.5pt}\end{center}
-
-\hypertarget{numpy---the-pythons-array-library}{%
-\section{Numpy - the python's array
-library}\label{numpy---the-pythons-array-library}}
-
-In this tutorial we will be introducing arrays and we will be using the
-numpy library. Arrays, lists, vectors, matrices, sets - You might've
-heard of them before, they all store data. In programming, an array is a
-variable that can hold more than one value at a time. We will be using
-the Numpy python library to create arrays. Since we already have
-installed Numpy previously, we can start using the package.
-
-Before importing our first package, let's as ourselves \emph{what is a
-package?} A package can be thought of as pre-written python code that we
-can re-use. This means the for every script that we write in python we
-need to tell it to use a certain package. We call this importing a
-package.
-
-\hypertarget{importing-numpy}{%
-\subsection{Importing Numpy}\label{importing-numpy}}
-
-When using packages in python, we need to let it know what package we
-will be using. This is called importing. To import numpy we need to
-declare it a the start of a script as follows:
-
-\begin{Shaded}
-\begin{Highlighting}[]
-\ImportTok{import}\NormalTok{ numpy }\ImportTok{as}\NormalTok{ np}
-\end{Highlighting}
-\end{Shaded}
-
-\begin{itemize}
-\tightlist
-\item
-  \texttt{import} - calls for a library to use, in our case it is Numpy.
-\item
-  \texttt{as} - gives the library an alias in your script. It's common
-  convention in Python programming to make the code shorter and more
-  readable. We will be using \emph{np} as it's a standard using in many
-  projects.
-\end{itemize}
-
-\begin{center}\rule{0.5\linewidth}{0.5pt}\end{center}
-
-\hypertarget{creating-arrays}{%
-\section{Creating arrays}\label{creating-arrays}}
-
-Now that we have imported the library we can create a one dimensional
-array or \emph{vector} with three elements.
-
-\begin{Shaded}
-\begin{Highlighting}[]
-\NormalTok{x }\OperatorTok{=}\NormalTok{ np.array([}\DecValTok{1}\NormalTok{,}\DecValTok{2}\NormalTok{,}\DecValTok{3}\NormalTok{])}
-\end{Highlighting}
-\end{Shaded}
-
-To create a \emph{matrix} we can nest the arrays to create a two
-dimensional array. This is done as follows.
-
-\begin{Shaded}
-\begin{Highlighting}[]
-\NormalTok{matrix }\OperatorTok{=}\NormalTok{ np.array([[}\DecValTok{1}\NormalTok{,}\DecValTok{2}\NormalTok{,}\DecValTok{3}\NormalTok{],}
-\NormalTok{                   [}\DecValTok{4}\NormalTok{,}\DecValTok{5}\NormalTok{,}\DecValTok{6}\NormalTok{],}
-\NormalTok{                   [}\DecValTok{7}\NormalTok{,}\DecValTok{8}\NormalTok{,}\DecValTok{9}\NormalTok{]])}
-\end{Highlighting}
-\end{Shaded}
-
-\emph{Note: for every array we nest, we get a new dimension in our data
-structure.}
-
-    \hypertarget{display-arrays}{%
-\section{Display arrays}\label{display-arrays}}
-
-Using command print("") Accessing particular elements of an array
-\ldots..
-
-    \hypertarget{practice-problem}{%
-\section{Practice Problem}\label{practice-problem}}
-
-Problem statement
-
-    \begin{tcolorbox}[breakable, size=fbox, boxrule=1pt, pad at break*=1mm,colback=cellbackground, colframe=cellborder]
-\prompt{In}{incolor}{1}{\boxspacing}
-\begin{Verbatim}[commandchars=\\\{\}]
-\PY{k+kn}{import} \PY{n+nn}{numpy} \PY{k}{as} \PY{n+nn}{np}
-
-\PY{n}{x} \PY{o}{=} \PY{n}{np}\PY{o}{.}\PY{n}{array}\PY{p}{(}\PY{p}{[}\PY{l+m+mi}{7}\PY{p}{,} \PY{l+m+mi}{10} \PY{p}{,}\PY{l+m+mi}{12}\PY{p}{]}\PY{p}{)}
-
-\PY{n+nb}{print}\PY{p}{(}\PY{n}{x}\PY{p}{)}
-
-\PY{n+nb}{print}\PY{p}{(}\PY{n}{x}\PY{p}{[}\PY{l+m+mi}{1}\PY{p}{]}\PY{p}{)}
-\end{Verbatim}
-\end{tcolorbox}
-
-    \begin{Verbatim}[commandchars=\\\{\}]
-[ 7 10 12]
-10
-    \end{Verbatim}
-
-    \hypertarget{numpy-array-creation-functions}{%
-\subsection{Numpy array creation
-functions}\label{numpy-array-creation-functions}}
-
-Numpy comes with some built-in function that we can use to create arrays
-quickly. Here are a couple of functions that are commonly used in
-python.
-
-\hypertarget{np.arange}{%
-\subsubsection{np.arange}\label{np.arange}}
-
-The \texttt{np.arange()} function returns an array with evenly spaced
-values within a specified range. It is similar to the built-in
-\texttt{range()} function in Python but returns a Numpy array instead of
-a list. The parameters for this function are the start value
-(inclusive), the stop value (exclusive), and the step size. If the step
-size is not provided, it defaults to 1.
-
-\begin{Shaded}
-\begin{Highlighting}[]
-\OperatorTok{\textgreater{}\textgreater{}\textgreater{}}\NormalTok{ np.arange(}\DecValTok{4}\NormalTok{)}
-\NormalTok{array([}\FloatTok{0.}\NormalTok{ , }\FloatTok{1.}\NormalTok{, }\FloatTok{2.}\NormalTok{, }\FloatTok{3.}\NormalTok{ ])}
-\end{Highlighting}
-\end{Shaded}
-
-In this example, \texttt{np.arange(4)} generates an array starting from
-0 and ending before 4, with a step size of 1.
-
-\hypertarget{np.linspace}{%
-\subsubsection{np.linspace}\label{np.linspace}}
-
-The \texttt{np.linspace()} function returns an array of evenly spaced
-values over a specified range. Unlike \texttt{np.arange()}, which uses a
-step size to define the spacing between elements, \texttt{np.linspace()}
-uses the number of values you want to generate and calculates the
-spacing automatically. It accepts three parameters: the start value, the
-stop value, and the number of samples.
-
-\begin{Shaded}
-\begin{Highlighting}[]
-\OperatorTok{\textgreater{}\textgreater{}\textgreater{}}\NormalTok{ np.linspace(}\FloatTok{1.}\NormalTok{, }\FloatTok{4.}\NormalTok{, }\DecValTok{6}\NormalTok{)}
-\NormalTok{array([}\FloatTok{1.}\NormalTok{ ,  }\FloatTok{1.6}\NormalTok{,  }\FloatTok{2.2}\NormalTok{,  }\FloatTok{2.8}\NormalTok{,  }\FloatTok{3.4}\NormalTok{,  }\FloatTok{4.}\NormalTok{ ])}
-\end{Highlighting}
-\end{Shaded}
-
-In this example, \texttt{np.linspace(1.,\ 4.,\ 6)} generates 6 evenly
-spaced values between 1. and 4., including both endpoints.
-
-Try this and see what happens:
-
-\begin{Shaded}
-\begin{Highlighting}[]
-\NormalTok{x }\OperatorTok{=}\NormalTok{ np.linspace(}\DecValTok{0}\NormalTok{,}\DecValTok{100}\NormalTok{,}\DecValTok{101}\NormalTok{)}
-\NormalTok{y }\OperatorTok{=}\NormalTok{ np.sin(x)}
-\end{Highlighting}
-\end{Shaded}
-
-\hypertarget{other-useful-functions}{%
-\subsubsection{Other useful functions}\label{other-useful-functions}}
-
-\begin{itemize}
-\tightlist
-\item
-  \texttt{np.zeros()}
-\item
-  \texttt{np.ones()}
-\item
-  \texttt{np.eye()}
-\end{itemize}
-
-    \hypertarget{practice-problem}{%
-\subsection{Practice problem}\label{practice-problem}}
-
-Problem statement below
-
-    \begin{tcolorbox}[breakable, size=fbox, boxrule=1pt, pad at break*=1mm,colback=cellbackground, colframe=cellborder]
-\prompt{In}{incolor}{2}{\boxspacing}
-\begin{Verbatim}[commandchars=\\\{\}]
-\PY{n}{y}\PY{o}{=}\PY{n}{np}\PY{o}{.}\PY{n}{linspace}\PY{p}{(}\PY{l+m+mi}{10}\PY{p}{,}\PY{l+m+mi}{20}\PY{p}{,}\PY{l+m+mi}{5}\PY{p}{)}
-\PY{n+nb}{print}\PY{p}{(}\PY{n}{y}\PY{p}{)}
-\end{Verbatim}
-\end{tcolorbox}
-
-    \begin{Verbatim}[commandchars=\\\{\}]
-[10.  12.5 15.  17.5 20. ]
-    \end{Verbatim}
-
-    \hypertarget{working-with-arrays}{%
-\subsection{Working with Arrays}\label{working-with-arrays}}
-
-Now that we have been introduced to some ways to create arrays using the
-Numpy functions let's start using them.
-
-\hypertarget{indexing}{%
-\subsubsection{Indexing}\label{indexing}}
-
-Indexing in Python allows you to access specific elements within an
-array based on their position. This means you can directly retrieve and
-manipulate individual items as needed.
-
-Python uses \textbf{zero-based indexing}, meaning the first element is
-at position \textbf{0} rather than \textbf{1}. This approach is common
-in many programming languages. For example, in a list with five
-elements, the first element is at index \texttt{0}, followed by elements
-at indices \texttt{1}, \texttt{2}, \texttt{3}, and \texttt{4}.
-
-Here's an example of data from a rocket test stand where thrust was
-recorded as a function of time.
-
-\begin{Shaded}
-\begin{Highlighting}[]
-\NormalTok{thrust\_lbf }\OperatorTok{=}\NormalTok{ np.array(}\FloatTok{0.603355}\NormalTok{, }\FloatTok{2.019083}\NormalTok{, }\FloatTok{2.808092}\NormalTok{, }\FloatTok{4.054973}\NormalTok{, }\FloatTok{1.136618}\NormalTok{, }\FloatTok{0.943668}\NormalTok{)}
-
-\OperatorTok{\textgreater{}\textgreater{}\textgreater{}}\NormalTok{ thrust\_lbs[}\DecValTok{3}\NormalTok{]}
-\end{Highlighting}
-\end{Shaded}
-
-Due to the nature of zero-based indexing. If we want to call the value
-\texttt{4.054973} that will be the 3rd index.
-
-\hypertarget{operations-on-arrays}{%
-\subsubsection{Operations on arrays}\label{operations-on-arrays}}
-
-\begin{itemize}
-\tightlist
-\item
-  Arithmetic operations (\texttt{+}, \texttt{-}, \texttt{*}, \texttt{/},
-  \texttt{**})
-\item
-  \texttt{np.add()}, \texttt{np.subtract()}, \texttt{np.multiply()},
-  \texttt{np.divide()}
-\item
-  \texttt{np.dot()} for dot product
-\item
-  \texttt{np.matmul()} for matrix multiplication
-\item
-  \texttt{np.linalg.inv()}, \texttt{np.linalg.det()} for linear algebra
-\end{itemize}
-
-\hypertarget{statistics}{%
-\paragraph{Statistics}\label{statistics}}
-
-\begin{itemize}
-\tightlist
-\item
-  \texttt{np.mean()}, \texttt{np.median()}, \texttt{np.std()},
-  \texttt{np.var()}
-\item
-  \texttt{np.min()}, \texttt{np.max()}, \texttt{np.argmin()},
-  \texttt{np.argmax()}
-\item
-  Summation along axes: \texttt{np.sum(arr,\ axis=0)}
-\end{itemize}
-
-\hypertarget{combining-arrays}{%
-\paragraph{Combining arrays}\label{combining-arrays}}
-
-\begin{itemize}
-\tightlist
-\item
-  Concatenation: \texttt{np.concatenate((arr1,\ arr2),\ axis=0)}
-\item
-  Stacking: \texttt{np.vstack()}, \texttt{np.hstack()}
-\item
-  Splitting: \texttt{np.split()}
-\end{itemize}
-
-    \hypertarget{exercise}{%
-\section{Exercise}\label{exercise}}
-
-Let's solve a statics problem given the following problem
-
-A simply supported bridge of length L=20L = 20L=20 m is subjected to
-three point loads:
-
-\begin{itemize}
-\tightlist
-\item
-  \(P1=1010 kN\) at \(x=5m\)
-\item
-  \(P2=15 kN\) at \(x=10m\)
-\item
-  \(P3=20 kN\) at \(x=15m\)
-\end{itemize}
-
-The bridge is supported by two reaction forces at points AAA (left
-support) and BBB (right support). We assume the bridge is in static
-equilibrium, meaning the sum of forces and sum of moments about any
-point must be zero.
-
-\hypertarget{equilibrium-equations}{%
-\paragraph{Equilibrium Equations:}\label{equilibrium-equations}}
-
-\begin{enumerate}
-\def\labelenumi{\arabic{enumi}.}
-\item
-  \textbf{Sum of Forces in the Vertical Direction}:
-
-  \(R_A + R_B - P_1 - P_2 - P_3 = 0\)
-\item
-  \textbf{Sum of Moments About Point A}:
-
-  \(5 P_1 + 10 P_2 + 15 P_3 - 20 R_B = 0\)
-\item
-  \textbf{Sum of Moments About Point B}:
-
-  \(20 R_A - 15 P_3 - 10 P_2 - 5 P_1 = 0\)
-\end{enumerate}
-
-\hypertarget{system-of-equations}{%
-\paragraph{System of Equations:}\label{system-of-equations}}
-
-\[
-\begin{cases}
-R_A + R_B - 10 - 15 - 20 = 0 \\
-5 \cdot 10 + 10 \cdot 15 + 15 \cdot 20 - 20 R_B = 0 \\
-20 R_A - 5 \cdot 10 - 10 \cdot 15 - 15 \cdot 20 = 0
-\end{cases}
-\]
-
-    \hypertarget{solution}{%
-\subsubsection{Solution}\label{solution}}
-
-    \begin{tcolorbox}[breakable, size=fbox, boxrule=1pt, pad at break*=1mm,colback=cellbackground, colframe=cellborder]
-\prompt{In}{incolor}{3}{\boxspacing}
-\begin{Verbatim}[commandchars=\\\{\}]
-\PY{k+kn}{import} \PY{n+nn}{numpy} \PY{k}{as} \PY{n+nn}{np}
-
-\PY{c+c1}{\PYZsh{} Define the coefficient matrix A}
-\PY{n}{A} \PY{o}{=} \PY{n}{np}\PY{o}{.}\PY{n}{array}\PY{p}{(}\PY{p}{[}
-    \PY{p}{[}\PY{l+m+mi}{1}\PY{p}{,} \PY{l+m+mi}{1}\PY{p}{]}\PY{p}{,}
-    \PY{p}{[}\PY{l+m+mi}{0}\PY{p}{,} \PY{o}{\PYZhy{}}\PY{l+m+mi}{20}\PY{p}{]}\PY{p}{,}
-    \PY{p}{[}\PY{l+m+mi}{20}\PY{p}{,} \PY{l+m+mi}{0}\PY{p}{]}
-\PY{p}{]}\PY{p}{)}
-
-\PY{c+c1}{\PYZsh{} Define the right\PYZhy{}hand side vector b}
-\PY{n}{b} \PY{o}{=} \PY{n}{np}\PY{o}{.}\PY{n}{array}\PY{p}{(}\PY{p}{[}
-    \PY{l+m+mi}{45}\PY{p}{,}
-    \PY{l+m+mi}{5}\PY{o}{*}\PY{l+m+mi}{10} \PY{o}{+} \PY{l+m+mi}{10}\PY{o}{*}\PY{l+m+mi}{15} \PY{o}{+} \PY{l+m+mi}{15}\PY{o}{*}\PY{l+m+mi}{20}\PY{p}{,}
-    \PY{l+m+mi}{5}\PY{o}{*}\PY{l+m+mi}{10} \PY{o}{+} \PY{l+m+mi}{10}\PY{o}{*}\PY{l+m+mi}{15} \PY{o}{+} \PY{l+m+mi}{15}\PY{o}{*}\PY{l+m+mi}{20}
-\PY{p}{]}\PY{p}{)}
-
-\PY{c+c1}{\PYZsh{} Solve the system of equations Ax = b}
-\PY{c+c1}{\PYZsh{} Using least squares to handle potential overdetermination}
-\PY{n}{x} \PY{o}{=} \PY{n}{np}\PY{o}{.}\PY{n}{linalg}\PY{o}{.}\PY{n}{lstsq}\PY{p}{(}\PY{n}{A}\PY{p}{,} \PY{n}{b}\PY{p}{,} \PY{n}{rcond}\PY{o}{=}\PY{k+kc}{None}\PY{p}{)}\PY{p}{[}\PY{l+m+mi}{0}\PY{p}{]}
-
-\PY{c+c1}{\PYZsh{} Display the results}
-\PY{n+nb}{print}\PY{p}{(}\PY{l+s+sa}{f}\PY{l+s+s2}{\PYZdq{}}\PY{l+s+s2}{Reaction force at A (R\PYZus{}A): }\PY{l+s+si}{\PYZob{}}\PY{n}{x}\PY{p}{[}\PY{l+m+mi}{0}\PY{p}{]}\PY{l+s+si}{:}\PY{l+s+s2}{.2f}\PY{l+s+si}{\PYZcb{}}\PY{l+s+s2}{ kN}\PY{l+s+s2}{\PYZdq{}}\PY{p}{)}
-\PY{n+nb}{print}\PY{p}{(}\PY{l+s+sa}{f}\PY{l+s+s2}{\PYZdq{}}\PY{l+s+s2}{Reaction force at B (R\PYZus{}B): }\PY{l+s+si}{\PYZob{}}\PY{n}{x}\PY{p}{[}\PY{l+m+mi}{1}\PY{p}{]}\PY{l+s+si}{:}\PY{l+s+s2}{.2f}\PY{l+s+si}{\PYZcb{}}\PY{l+s+s2}{ kN}\PY{l+s+s2}{\PYZdq{}}\PY{p}{)}
-\end{Verbatim}
-\end{tcolorbox}
-
-    \begin{Verbatim}[commandchars=\\\{\}]
-Reaction force at A (R\_A): 25.11 kN
-Reaction force at B (R\_B): -24.89 kN
-    \end{Verbatim}
-
-
-    % Add a bibliography block to the postdoc
diff --git a/book/module1/basics_of_python.tex b/book/module1/basics_of_python.tex
deleted file mode 100644
index a68400e..0000000
--- a/book/module1/basics_of_python.tex
+++ /dev/null
@@ -1,248 +0,0 @@
-\section{Basics of Python}\label{basics-of-python}
-
-This page contains important fundamental concepts used in Python such as
-syntax, operators, order or precedence and more.
-
-\subsection{Syntax}\label{syntax}
-
-\subsubsection{Indentations and blocks}\label{indentations-and-blocks}
-
-In python \emph{indentations} or the space at the start of each line,
-signifies a block of code. This becomes important when we start working
-with function and loops. We will talk more about this in the controls
-structures tutorial.
-
-\subsubsection{Comments}\label{comments}
-
-Comments can be added to your code using the hash operator (\#). Any
-text behind the comment operator till the end of the line will be
-rendered as a comment. If you have an entire block of text or code that
-needs to be commented out, the triple quotation marks (``\,``\,``) can
-be used. Once used all the code after it will be considered a comment
-until the comment is ended with the triple quotation marks.f
-
-\subsection{Operators}\label{operators}
-
-In python, operators are special symbols or keywords that perform
-operations on values or variables. This section covers some of the most
-common operator that you will see in this course.
-
-\subsubsection{Arithmetic operators}\label{arithmetic-operators}
-
-\begin{longtable}[]{@{}ll@{}}
-\toprule\noalign{}
-Operator & Name \\
-\midrule\noalign{}
-\endhead
-\bottomrule\noalign{}
-\endlastfoot
-+ & Addition \\
-- & Subtraction \\
-* & Multiplication \\
-/ & Division \\
-\% & Modulus \\
-** & Exponentiation \\
-// & Floor division \\
-\end{longtable}
-
-\subsubsection{Comparison operators}\label{comparison-operators}
-
-Used in conditional statements such as \texttt{if} statements or
-\texttt{while} loops. Note that in the computer world a double equal
-sign (\texttt{==}) means \emph{is equal to}, where as the single equal
-sign assigns the variable or defines the variable to be something.
-
-\begin{longtable}[]{@{}ll@{}}
-\toprule\noalign{}
-Operator & Name \\
-\midrule\noalign{}
-\endhead
-\bottomrule\noalign{}
-\endlastfoot
-== & Equal \\
-!= & Not equal \\
-\textgreater{} & Greater than \\
-\textless{} & Less than \\
-\textgreater= & Greater than or equal to \\
-\textless= & Less than or equal to \\
-\end{longtable}
-
-\subsubsection{Logical operators}\label{logical-operators}
-
-\begin{longtable}[]{@{}ll@{}}
-\toprule\noalign{}
-Operator & Descrription \\
-\midrule\noalign{}
-\endhead
-\bottomrule\noalign{}
-\endlastfoot
-and & Returns True if both statemetns are true \\
-or & Returns True if one of the statements is true \\
-not & Reerse the result, returns False if the result is true \\
-\end{longtable}
-
-\subsubsection{Identity operators}\label{identity-operators}
-
-\begin{longtable}[]{@{}ll@{}}
-\toprule\noalign{}
-Operator & Description \\
-\midrule\noalign{}
-\endhead
-\bottomrule\noalign{}
-\endlastfoot
-is & Returns True if both variables are the same object \\
-is not & Returns True if both variables are not the same object \\
-\end{longtable}
-
-\subsection{Order of Operation}\label{order-of-operation}
-
-Similarly to the order or precedence in mathematics, different computer
-languages have their own set of rules. Here is a comprehensive table of
-the order of operation that python follows.
-
-\begin{longtable}[]{@{}
-  >{\raggedright\arraybackslash}p{(\columnwidth - 2\tabcolsep) * \real{0.5093}}
-  >{\raggedright\arraybackslash}p{(\columnwidth - 2\tabcolsep) * \real{0.4907}}@{}}
-\toprule\noalign{}
-\begin{minipage}[b]{\linewidth}\raggedright
-Operator
-\end{minipage} & \begin{minipage}[b]{\linewidth}\raggedright
-Description
-\end{minipage} \\
-\midrule\noalign{}
-\endhead
-\bottomrule\noalign{}
-\endlastfoot
-\texttt{()} & Parentheses \\
-\texttt{**} & Exponentiation \\
-\texttt{+x} \texttt{-x} \texttt{\textasciitilde{}x} & Unary plus, unary
-minus, and bitwise NOT \\
-\texttt{*} \texttt{/} \texttt{//} \texttt{\%} & Multiplication,
-Division, floor division, and modulus \\
-\texttt{+} \texttt{-} & Addition and subtraction \\
-\texttt{\textless{}\textless{}} \texttt{\textgreater{}\textgreater{}} &
-Bitwise left and right shifts \\
-\& & Bitwise AND \\
-\^{} & Bitwise XOR \\
-\textbar{} & Bitwise OR \\
-\texttt{==} \texttt{!=} \texttt{\textgreater{}} \texttt{\textgreater{}=}
-\texttt{\textless{}} \texttt{\textless{}=} \texttt{is} \texttt{is\ not}
-\texttt{in} \texttt{not\ in} & Comparision, identity and membership
-operators \\
-\texttt{not} & logical NOT \\
-\texttt{and} & AND \\
-\texttt{or} & OR \\
-\end{longtable}
-
-\subsection{Data types}\label{data-types}
-
-Data types are different ways a computer stores data. Other data types
-use fewer bits than others allowing you to better utilize your computer
-memory. This is important for engineers because The most common data
-types that an engineer encounters in python are numeric types. -
-\texttt{int} - integer - \texttt{float} - a decimal number -
-\texttt{complex} - imaginary number
-
-The comprehensive table below show all built-in data types available in
-python.
-
-\begin{longtable}[]{@{}ll@{}}
-\toprule\noalign{}
-Category & Data Type \\
-\midrule\noalign{}
-\endhead
-\bottomrule\noalign{}
-\endlastfoot
-Text & int, float, complex \\
-Sequance & list, tuple, range \\
-Mapping & dict \\
-Set & set, frozenset \\
-Boolean & bytes, bytearray, memoryview \\
-Binary & bytes, bytearray, memoryview \\
-None & NoneType \\
-\end{longtable}
-
-\subsection{Variables}\label{variables}
-
-A \textbf{variable} in Python is a name that stores a value, allowing
-you to use and manipulate data efficiently.
-
-\paragraph{Declaring and Assigning
-Variables}\label{declaring-and-assigning-variables}
-
-It is common in low-level computer languages to declare the datatype if
-the variable. In python, the datatype is set whilst you assign it. We
-assign values to variables using a single \texttt{=}.
-
-\begin{Shaded}
-\begin{Highlighting}[]
-\NormalTok{x }\OperatorTok{=} \DecValTok{10}          \CommentTok{\# Integer}
-\NormalTok{y }\OperatorTok{=} \FloatTok{3.14}        \CommentTok{\# Float}
-\NormalTok{name }\OperatorTok{=} \StringTok{"Joe"}    \CommentTok{\# String}
-\NormalTok{is\_valid }\OperatorTok{=} \VariableTok{True} \CommentTok{\# Boolean}
-\end{Highlighting}
-\end{Shaded}
-
-You can assign multiple variables at once:
-
-\begin{Shaded}
-\begin{Highlighting}[]
-\NormalTok{a, b, c }\OperatorTok{=} \DecValTok{1}\NormalTok{, }\DecValTok{2}\NormalTok{, }\DecValTok{3}
-\end{Highlighting}
-\end{Shaded}
-
-Similarly we can assign the same value to multiple variables:
-
-\begin{Shaded}
-\begin{Highlighting}[]
-\NormalTok{x }\OperatorTok{=}\NormalTok{ y }\OperatorTok{=}\NormalTok{ z }\OperatorTok{=} \DecValTok{100}
-\end{Highlighting}
-\end{Shaded}
-
-\subparagraph{Rules}\label{rules}
-
-\begin{itemize}
-\tightlist
-\item
-  Must start with a letter or \texttt{\_}
-\item
-  Cannot start with a number
-\item
-  Can only contain letters, numbers, and \texttt{\_}
-\item
-  Case-sensitive (\texttt{Name} and \texttt{name} are different)
-\end{itemize}
-
-\paragraph{Updating Variables}\label{updating-variables}
-
-You can change a variable's value at any time.
-
-\begin{Shaded}
-\begin{Highlighting}[]
-\NormalTok{x }\OperatorTok{=} \DecValTok{5}
-\NormalTok{x }\OperatorTok{=}\NormalTok{ x }\OperatorTok{+} \DecValTok{10}  \CommentTok{\# Now x is 15}
-\end{Highlighting}
-\end{Shaded}
-
-Or shorthand:
-
-\begin{Shaded}
-\begin{Highlighting}[]
-\NormalTok{x }\OperatorTok{+=} \DecValTok{10}  \CommentTok{\# Same as x = x + 10}
-\end{Highlighting}
-\end{Shaded}
-
-\paragraph{Variable Types \& Type
-Checking}\label{variable-types-type-checking}
-
-Use \texttt{type()} to check a variable's type.
-
-\begin{Shaded}
-\begin{Highlighting}[]
-\NormalTok{x }\OperatorTok{=} \DecValTok{10}
-\BuiltInTok{print}\NormalTok{(}\BuiltInTok{type}\NormalTok{(x))  }\CommentTok{\# Output: \textless{}class \textquotesingle{}int\textquotesingle{}\textgreater{}}
-
-\NormalTok{y }\OperatorTok{=} \StringTok{"Hello"}
-\BuiltInTok{print}\NormalTok{(}\BuiltInTok{type}\NormalTok{(y))  }\CommentTok{\# Output: \textless{}class \textquotesingle{}str\textquotesingle{}\textgreater{}}
-\end{Highlighting}
-\end{Shaded}
diff --git a/book/module1/classes_and_objects.tex b/book/module1/classes_and_objects.tex
deleted file mode 100644
index b783048..0000000
--- a/book/module1/classes_and_objects.tex
+++ /dev/null
@@ -1,120 +0,0 @@
-\section{Modular Programming}\label{modular-programming}
-
-\subsection{1. Introduction}\label{introduction}
-
-\begin{itemize}
-\tightlist
-\item
-  A. What is Object-Oriented Programming?
-\item
-  B. Why use OOP? (vs.~procedural)
-\item
-  C. Real-world analogies (e.g., modeling components like pumps, motors,
-  or vehicles)
-\end{itemize}
-
-\subsection{2. Core OOP Concepts}\label{core-oop-concepts}
-
-\begin{itemize}
-\tightlist
-\item
-  A. \textbf{Classes and Objects}
-
-  \begin{itemize}
-  \tightlist
-  \item
-    Definitions
-  \item
-    Syntax in Python
-  \end{itemize}
-\item
-  B. \textbf{Attributes and Methods}
-
-  \begin{itemize}
-  \tightlist
-  \item
-    Instance variables
-  \item
-    Functions inside classes
-  \end{itemize}
-\item
-  C. \textbf{Encapsulation}
-
-  \begin{itemize}
-  \tightlist
-  \item
-    Public vs private variables
-  \item
-    Using \texttt{\_\_init\_\_} and \texttt{self}
-  \end{itemize}
-\item
-  D. \textbf{Inheritance}
-
-  \begin{itemize}
-  \tightlist
-  \item
-    Parent and child classes
-  \item
-    Reuse and extension of code
-  \end{itemize}
-\item
-  E. \textbf{Polymorphism} \emph{(brief overview)}
-
-  \begin{itemize}
-  \tightlist
-  \item
-    Method overriding
-  \item
-    Flexibility in interfaces
-  \end{itemize}
-\end{itemize}
-
-\subsection{3. Python OOP Syntax and
-Examples}\label{python-oop-syntax-and-examples}
-
-\begin{itemize}
-\tightlist
-\item
-  A. Define a simple class (e.g., \texttt{Spring})
-\item
-  B. Instantiate objects and use methods
-\item
-  C. Show \texttt{\_\_init\_\_}, \texttt{\_\_str\_\_}, custom methods
-\item
-  D. Add a derived class (e.g., \texttt{DampedSpring} inherits from
-  \texttt{Spring})
-\end{itemize}
-
-\subsection{4. Engineering Applications of
-OOP}\label{engineering-applications-of-oop}
-
-\begin{itemize}
-\tightlist
-\item
-  A. Modeling a mechanical system using classes
-
-  \begin{itemize}
-  \tightlist
-  \item
-    Example: Mass-Spring-Damper system
-  \end{itemize}
-\item
-  B. Creating reusable components (e.g., \texttt{Material},
-  \texttt{Beam}, \texttt{Force})
-\item
-  C. Organizing simulation code with OOP
-\end{itemize}
-
-\subsection{5. Hands-On Coding Activity}\label{hands-on-coding-activity}
-
-\begin{itemize}
-\tightlist
-\item
-  A. Write a class for a basic physical component (e.g., \texttt{Motor})
-\item
-  B. Add behavior (e.g., \texttt{calculate\_torque})
-\item
-  C. Extend with inheritance (e.g., \texttt{ServoMotor})
-\item
-  D. Bonus: Integrate two objects to simulate interaction
-\end{itemize}
diff --git a/book/module1/computational_expense.tex b/book/module1/computational_expense.tex
deleted file mode 100644
index f315969..0000000
--- a/book/module1/computational_expense.tex
+++ /dev/null
@@ -1 +0,0 @@
-\section{Computational Expense}\label{computational-expense}
diff --git a/book/module1/computing_fundamentals.tex b/book/module1/computing_fundamentals.tex
deleted file mode 100644
index af38b93..0000000
--- a/book/module1/computing_fundamentals.tex
+++ /dev/null
@@ -1,19 +0,0 @@
-\section{Computing Fundamentals}\label{computing-fundamentals}
-
-\subsection{Using computers as a tool for
-engineers}\label{using-computers-as-a-tool-for-engineers}
-
-\subsection{How do computers work?}\label{how-do-computers-work}
-
-Globe analogy: Hardware, Kernel, Shell, Application, Software.
-
-\subsection{Interfaces}\label{interfaces}
-
-\subsubsection{Text editor for
-Scripting}\label{text-editor-for-scripting}
-
-\subsubsection{Command window}\label{command-window}
-
-Command window, terminal, console, command prompt you might've heard of
-theses terms before. They all essentially mean the same thing. The
-command window is used to control your system.
diff --git a/book/module1/control_structures.tex b/book/module1/control_structures.tex
deleted file mode 100644
index 4042e09..0000000
--- a/book/module1/control_structures.tex
+++ /dev/null
@@ -1,202 +0,0 @@
-\section{Control Structures}\label{control-structures}
-
-Control structures allow us to control the flow of execution in a Python
-program. The two main types are \textbf{conditional statements
-(\texttt{if} statements)} and \textbf{loops (\texttt{for} and
-\texttt{while} loops)}.
-
-\subsection{Conditional Statements}\label{conditional-statements}
-
-Conditional statements allow a program to execute different blocks of
-code depending on whether a given condition is \texttt{True} or
-\texttt{False}. These conditions are typically comparisons, such as
-checking if one number is greater than another.
-
-\subsubsection{\texorpdfstring{The \texttt{if}
-Statement}{The if Statement}}\label{the-if-statement}
-
-The simplest form of a conditional statement is the \texttt{if}
-statement. If the condition evaluates to \texttt{True}, the indented
-block of code runs. Otherwise, the program moves on without executing
-the statement.
-
-For example, consider a situation where we need to determine if a person
-is an adult based on their age. If the age is 18 or greater, we print a
-message saying they are an adult.
-
-\subsubsection{\texorpdfstring{The \texttt{if-else}
-Statement}{The if-else Statement}}\label{the-if-else-statement}
-
-Sometimes, we need to specify what should happen if the condition is
-\texttt{False}. The \texttt{else} clause allows us to handle this case.
-Instead of just skipping over the block, the program can execute an
-alternative action.
-
-For instance, if a person is younger than 18, they are considered a
-minor. If the condition of being an adult is not met, the program will
-print a message indicating that the person is a minor.
-
-\subsubsection{\texorpdfstring{The \texttt{if-elif-else}
-Statement}{The if-elif-else Statement}}\label{the-if-elif-else-statement}
-
-When dealing with multiple conditions, the \texttt{if-elif-else}
-structure is useful. The program evaluates conditions in order,
-executing the first one that is \texttt{True}. If none of the conditions
-are met, the \texttt{else} block runs.
-
-For example, in a grading system, different score ranges correspond to
-different letter grades. If a student's score is 90 or higher, they
-receive an ``A''. If it's between 80 and 89, they get a ``B'', and so
-on. If none of the conditions match, they receive an ``F''.
-
-\subsubsection{\texorpdfstring{Nested \texttt{if}
-Statements}{Nested if Statements}}\label{nested-if-statements}
-
-Sometimes, we need to check conditions within other conditions. This is
-known as \textbf{nesting}. For example, if we first determine that a
-person is an adult, we can then check if they are a student. Based on
-that information, we print different messages.
-
-\begin{Shaded}
-\begin{Highlighting}[]
-\CommentTok{\# Getting user input for the student\textquotesingle{}s score}
-\NormalTok{score }\OperatorTok{=} \BuiltInTok{int}\NormalTok{(}\BuiltInTok{input}\NormalTok{(}\StringTok{"Enter the student\textquotesingle{}s score (0{-}100): "}\NormalTok{))}
-
-\ControlFlowTok{if} \DecValTok{0} \OperatorTok{\textless{}=}\NormalTok{ score }\OperatorTok{\textless{}=} \DecValTok{100}\NormalTok{:}
-    \ControlFlowTok{if}\NormalTok{ score }\OperatorTok{\textgreater{}=} \DecValTok{90}\NormalTok{:}
-\NormalTok{        grade }\OperatorTok{=} \StringTok{"A"}
-    \ControlFlowTok{elif}\NormalTok{ score }\OperatorTok{\textgreater{}=} \DecValTok{80}\NormalTok{:}
-\NormalTok{        grade }\OperatorTok{=} \StringTok{"B"}
-    \ControlFlowTok{elif}\NormalTok{ score }\OperatorTok{\textgreater{}=} \DecValTok{70}\NormalTok{:}
-\NormalTok{        grade }\OperatorTok{=} \StringTok{"C"}
-    \ControlFlowTok{elif}\NormalTok{ score }\OperatorTok{\textgreater{}=} \DecValTok{60}\NormalTok{:}
-\NormalTok{        grade }\OperatorTok{=} \StringTok{"D"}
-    \ControlFlowTok{else}\NormalTok{:}
-\NormalTok{        grade }\OperatorTok{=} \StringTok{"F"}  \CommentTok{\# Score below 60 is a failing grade}
-
-
-    \ControlFlowTok{if}\NormalTok{ grade }\OperatorTok{==} \StringTok{"F"}\NormalTok{:}
-        \BuiltInTok{print}\NormalTok{(}\StringTok{"The student has failed."}\NormalTok{)}
-\NormalTok{        retake\_eligible }\OperatorTok{=} \BuiltInTok{input}\NormalTok{(}\StringTok{"Is the student eligible for a retest? (yes/no): "}\NormalTok{).strip().lower()}
-        
-        \ControlFlowTok{if}\NormalTok{ retake\_eligible }\OperatorTok{==} \StringTok{"yes"}\NormalTok{:}
-            \BuiltInTok{print}\NormalTok{(}\StringTok{"The student is eligible for a retest."}\NormalTok{)}
-        \ControlFlowTok{else}\NormalTok{:}
-            \BuiltInTok{print}\NormalTok{(}\StringTok{"The student has failed the course and must retake it next semester."}\NormalTok{)}
-
-    
-\end{Highlighting}
-\end{Shaded}
-
-\subsection{Loops in Python}\label{loops-in-python}
-
-Loops allow a program to execute a block of code multiple times. This is
-especially useful for tasks such as processing lists of data, performing
-repetitive calculations, or automating tasks.
-
-\subsubsection{\texorpdfstring{The \texttt{for}
-Loop}{The for Loop}}\label{the-for-loop}
-
-A \texttt{for} loop iterates over a sequence, such as a list, tuple,
-string, or a range of numbers. Each iteration assigns the next value in
-the sequence to a loop variable, which can then be used inside the loop.
-
-For instance, if we have a list of fruits and want to print each fruit's
-name, a \texttt{for} loop can iterate over the list and display each
-item.
-
-Another useful feature of \texttt{for} loops is the \texttt{range()}
-function, which generates a sequence of numbers. This is commonly used
-when we need to repeat an action a specific number of times. For
-example, iterating from 0 to 4 allows us to print a message five times.
-
-Additionally, the \texttt{enumerate()} function can be used to loop
-through a list while keeping track of the index of each item. This is
-useful when both the position and the value in a sequence are needed.
-
-\begin{Shaded}
-\begin{Highlighting}[]
-\NormalTok{fruits }\OperatorTok{=}\NormalTok{ [}\StringTok{"apple"}\NormalTok{, }\StringTok{"banana"}\NormalTok{, }\StringTok{"cherry"}\NormalTok{]  }
-\ControlFlowTok{for}\NormalTok{ x }\KeywordTok{in}\NormalTok{ fruits:  }
-  \BuiltInTok{print}\NormalTok{(x)}
-\end{Highlighting}
-\end{Shaded}
-
-\begin{Shaded}
-\begin{Highlighting}[]
-\ControlFlowTok{for}\NormalTok{ x }\KeywordTok{in} \BuiltInTok{range}\NormalTok{(}\DecValTok{6}\NormalTok{):  }
-  \BuiltInTok{print}\NormalTok{(x)  }
-\ControlFlowTok{else}\NormalTok{:  }
-  \BuiltInTok{print}\NormalTok{(}\StringTok{"Finally finished!"}\NormalTok{)}
-\end{Highlighting}
-\end{Shaded}
-
-\subsubsection{\texorpdfstring{The \texttt{while}
-Loop}{The while Loop}}\label{the-while-loop}
-
-Unlike \texttt{for} loops, which iterate over a sequence, \texttt{while}
-loops continue running as long as a specified condition remains
-\texttt{True}. This is useful when the number of iterations is not known
-in advance.
-
-For example, a countdown timer can be implemented using a \texttt{while}
-loop. The loop will continue decreasing the count until it reaches zero.
-
-It's important to be careful with \texttt{while} loops to avoid infinite
-loops, which occur when the condition never becomes \texttt{False}. To
-prevent this, ensure that the condition will eventually change during
-the execution of the loop.
-
-A \texttt{while} loop can also be used to wait for a certain event to
-occur. For example, in interactive programs, a \texttt{while\ True} loop
-can keep running until the user provides a valid input, at which point
-we break out of the loop.
-
-\begin{Shaded}
-\begin{Highlighting}[]
-\NormalTok{i }\OperatorTok{=} \DecValTok{1}  
-\ControlFlowTok{while}\NormalTok{ i }\OperatorTok{\textless{}} \DecValTok{6}\NormalTok{:  }
-\NormalTok{  print(i)  }
-\NormalTok{  i }\OperatorTok{+=} \DecValTok{1}
-\end{Highlighting}
-\end{Shaded}
-
-\subsection{Loop Control Statements}\label{loop-control-statements}
-
-Python provides special statements to control the behavior of loops.
-These can be used to break out of a loop, skip certain iterations, or
-simply include a placeholder for future code.
-
-\subsubsection{\texorpdfstring{The \texttt{break}
-Statement}{The break Statement}}\label{the-break-statement}
-
-The \texttt{break} statement is used to exit a loop before it has
-iterated through all its elements. When the \texttt{break} statement is
-encountered, the loop stops immediately, and the program continues
-executing the next statement outside the loop.
-
-For instance, if we are searching for a specific value in a list, we can
-use a \texttt{break} statement to stop the loop as soon as we find the
-item, instead of continuing unnecessary iterations.
-
-\subsubsection{\texorpdfstring{The \texttt{continue}
-Statement}{The continue Statement}}\label{the-continue-statement}
-
-The \texttt{continue} statement is used to skip the current iteration
-and proceed to the next one. Instead of exiting the loop entirely, it
-simply moves on to the next cycle.
-
-For example, if we are iterating over numbers and want to skip
-processing number 2, we can use \texttt{continue}. The loop will ignore
-that iteration and proceed with the next number.
-
-\subsubsection{\texorpdfstring{The \texttt{pass}
-Statement}{The pass Statement}}\label{the-pass-statement}
-
-The \texttt{pass} statement is a placeholder that does nothing. It is
-useful when a block of code is syntactically required but no action
-needs to be performed yet.
-
-For example, in a loop where a condition has not yet been implemented,
-using \texttt{pass} ensures that the code remains valid while avoiding
-errors.
diff --git a/book/module1/functions.tex b/book/module1/functions.tex
deleted file mode 100644
index 19a8a85..0000000
--- a/book/module1/functions.tex
+++ /dev/null
@@ -1,110 +0,0 @@
-\section{Functions}\label{functions}
-
-Like a traditional mathematical functions, python functions can take an
-input, process it, and give an output. In python, the input variables
-are referred to as \emph{arguments}. Functions are blocks of code that
-is run every time it's called. This allows us to re-use code.
-
-Functions are defined by using the def keyword. Reminder: it is
-important to keep track of indentations as it signifies the end of the
-function when the indentation returns back to the same level.
-
-\subsection{Defining Functions}\label{defining-functions}
-
-\subsubsection{Simple function}\label{simple-function}
-
-A simple function with no input variable can be useful if you need to
-re-use code multiple times without having to re-write it.
-
-\begin{Shaded}
-\begin{Highlighting}[]
-    \KeywordTok{def}\NormalTok{ function\_name():}
-        \BuiltInTok{print}\NormalTok{(}\StringTok{"This is from a function"}\NormalTok{)}
-\end{Highlighting}
-\end{Shaded}
-
-\subsubsection{Defining a function with one
-input}\label{defining-a-function-with-one-input}
-
-We can pass variables through to the function to be processed as
-follows:
-
-\begin{Shaded}
-\begin{Highlighting}[]
-    \KeywordTok{def}\NormalTok{ function(x):}
-        \BuiltInTok{print}\NormalTok{(x }\OperatorTok{+} \StringTok{" is best"}\NormalTok{)}
-\end{Highlighting}
-\end{Shaded}
-
-Note input variables can be of any data type (integer, float, string,
-etc.). \#\#\# Returning values from a function If we want to calculate a
-value and pass it back to the script for further use, we can use the
-\texttt{return} keyword. Let's define a linear function that takes two
-inputs, \texttt{x} and \texttt{b}, computes the corresponding \texttt{y}
-value, and returns it so it can be used elsewhere in the code.
-
-\begin{Shaded}
-\begin{Highlighting}[]
-    \KeywordTok{def}\NormalTok{ function(x, b):}
-\NormalTok{        y }\OperatorTok{=} \DecValTok{3}\OperatorTok{*}\NormalTok{x}\OperatorTok{+}\NormalTok{b}
-        \ControlFlowTok{return}\NormalTok{ y}
-\end{Highlighting}
-\end{Shaded}
-
-For multiple output variables we can add \#\# Calling functions Now that
-we've covered defining functions we want to call the function in order
-to execute the block inside the function. To do this, we simply re-call
-the function name as follows.
-
-\begin{Shaded}
-\begin{Highlighting}[]
-\NormalTok{function(}\DecValTok{2}\NormalTok{,}\OperatorTok{{-}}\DecValTok{1}\NormalTok{)}
-\end{Highlighting}
-\end{Shaded}
-
-Note that when running this code, nothing happens. This is because we
-haven't told the computer what to do with the output. Hence, if we wish
-to store the output then we need to use the assign operator \texttt{=}.
-
-\begin{Shaded}
-\begin{Highlighting}[]
-\NormalTok{output }\OperatorTok{=}\NormalTok{ function(}\DecValTok{2}\NormalTok{,}\OperatorTok{{-}}\DecValTok{1}\NormalTok{)}
-
-\BuiltInTok{print}\NormalTok{(output)}
-\end{Highlighting}
-\end{Shaded}
-
-In case you want to return multiple output variable from a single
-function we will have\ldots{}
-
-\subsection{Summary}\label{summary}
-
-\begin{Shaded}
-\begin{Highlighting}[]
-\KeywordTok{def}\NormalTok{ function\_name(argument1, argument2, argument3):}
-\NormalTok{    output1 }\OperatorTok{=}\NormalTok{ argument1 }\OperatorTok{*}\NormalTok{ argument2 }\OperatorTok{{-}}\NormalTok{ argument3}
-\NormalTok{    output2 }\OperatorTok{=}\NormalTok{ argument2 }\OperatorTok{+}\NormalTok{ argument3}
-    \ControlFlowTok{return}\NormalTok{ output1, output2}
-
-\NormalTok{[solution1, solution2] }\OperatorTok{=}\NormalTok{ function\_name(}\DecValTok{1}\NormalTok{,}\DecValTok{2}\NormalTok{,}\DecValTok{3}\NormalTok{)}
-\end{Highlighting}
-\end{Shaded}
-
-\begin{itemize}
-\tightlist
-\item
-  \texttt{def} - defines a function. All the code that is indented
-  underneath is considered inside the function block.
-\item
-  \texttt{function\_name} - this is used to call the function block.
-\item
-  \texttt{argument1} (optional) - input variable. This is data that can
-  be pass to the function. It is possible to have multiple variables
-  separated by a comma. As well as can be omitted if the function should
-  just give you an output such as.
-\item
-  \texttt{return} (optional) - if you wish to return something to your
-  script, the return keyword is used. The keyword can be followed by an
-  output variable or a constant. For multiple output variables, separate
-  them by a comma.
-\end{itemize}
diff --git a/book/module1/fundamentals_of_programming.tex b/book/module1/fundamentals_of_programming.tex
deleted file mode 100644
index 6a412d1..0000000
--- a/book/module1/fundamentals_of_programming.tex
+++ /dev/null
@@ -1,25 +0,0 @@
-\section{Fundamentals of programming}\label{fundamentals-of-programming}
-
-\subsection{Orientation of common
-interfaces}\label{orientation-of-common-interfaces}
-
-In this section we will cover the use and purpose of some common
-interfaces that you'll be using in this course.
-
-\subsubsection{Command window, terminal, console, command
-prompt.}\label{command-window-terminal-console-command-prompt.}
-
-This is a text based interface that allows the users to interact with
-the computer. It is used to execute commands, run scripts or programs.
-
-\subsubsection{Text Editor / Script}\label{text-editor-script}
-
-Your text editor is the program used to write a script which can be
-re-run every time you call it from the command window. This can be a
-built-in text editor such as Spyder and MATLAB provide or an external on
-such a notepad++.
-
-\begin{verbatim}
-  Globe analogy: Hardware, Kernel, shell, Application software.
-- Scripting
-\end{verbatim}
diff --git a/book/module1/installing_anaconda.tex b/book/module1/installing_anaconda.tex
deleted file mode 100644
index 0ff3d6f..0000000
--- a/book/module1/installing_anaconda.tex
+++ /dev/null
@@ -1,158 +0,0 @@
-\section{Installing Anaconda}\label{installing-anaconda}
-
-This tutorial will cover the steps on how to install Anaconda.
-
-\emph{Note for Advanced users: For those who wish to have a lightweight
-installation, can install miniconda or miniForge, however for this
-course we will show you how to use Anaconda Navigator. If you've never
-used the programs before then using Anaconda is recommended.}
-
-\subsubsection{What is Anaconda?}\label{what-is-anaconda}
-
-Anaconda Distribution is a popular open-source Python distribution
-specifically designed for scientific computing, data science, machine
-learning, and artificial intelligence applications. It simplifies the
-set up and use of Python for data science, machine learning, and
-scientific computing. It comes with all the important tools you need,
-like NumPy, Pandas, and JupyterLab, so you don't have to install
-everything separately. The Conda package manager helps you install and
-update software without worrying about breaking other programs. It also
-lets you create separate environments, so different projects don't
-interfere with each other. Additionally, Anaconda includes programs like
-JupyterLab for interactive coding, and Spyer a MATLAB-like IDE.
-
-\subsection{Instructions}\label{instructions}
-
-\begin{enumerate}
-\def\labelenumi{\arabic{enumi}.}
-\item
-  Find the latest version of Navigator from the official Anaconda
-  Inc.~website: \href{https://www.anaconda.com/download}{Download
-  Anaconda}
-\item
-  Press the \emph{Download Now} button.
-\item
-  Press the \emph{Skip registration} button below the submit button,
-  otherwise submit your email address to subscribe to the Anaconda email
-  list.
-\item
-  Under Anaconda Installers press \emph{Download} or find the
-  appropriate version for your operating system below.
-\end{enumerate}
-
-Proceed to next section for your respective operating system.
-
-\subsubsection{Windows}\label{windows}
-
-\begin{enumerate}
-\def\labelenumi{\arabic{enumi}.}
-\setcounter{enumi}{4}
-\tightlist
-\item
-  Once the download is complete, double click the executable (.exe) file
-  to start the installer. Proceed with the installation instructions.
-\end{enumerate}
-
-\begin{figure}
-\centering
-\includegraphics{figures/installingAnaconda_windows_installer_01_welcome.png}
-\caption{Welcome screen}
-\end{figure}
-
-\begin{figure}
-\centering
-\includegraphics{figures/installingAnaconda_windows_installer_02_terms.png}
-\caption{Terms and conditions}
-\end{figure}
-
-\begin{enumerate}
-\def\labelenumi{\arabic{enumi}.}
-\setcounter{enumi}{5}
-\tightlist
-\item
-  Select the \emph{Just Me} recommended option.
-\end{enumerate}
-
-\begin{figure}
-\centering
-\includegraphics{figures/installingAnaconda_windows_installer_03_for.png}
-\caption{Install for}
-\end{figure}
-
-\begin{enumerate}
-\def\labelenumi{\arabic{enumi}.}
-\setcounter{enumi}{6}
-\tightlist
-\item
-  You can leave the destination folder as is, just make sure you have a
-  minimum of \textasciitilde5 GB available storage space. Press
-  \emph{Next} to proceed.
-\end{enumerate}
-
-\begin{figure}
-\centering
-\includegraphics{figures/installingAnaconda_windows_installer_04_destination.png}
-\caption{Installation destination}
-\end{figure}
-
-\begin{enumerate}
-\def\labelenumi{\arabic{enumi}.}
-\setcounter{enumi}{7}
-\tightlist
-\item
-  It is recommended to register Anaconda3 as the default python version
-  if you already have an instance of python installed. Otherwise, you
-  can leave the checkboxes as defaults.
-\end{enumerate}
-
-\begin{figure}
-\centering
-\includegraphics{figures/installingAnaconda_windows_installer_05_advanced.png}
-\caption{Avanced Options}
-\end{figure}
-
-\begin{figure}
-\centering
-\includegraphics{figures/installingAnaconda_windows_installer_06_installing.png}
-\caption{Installing}
-\end{figure}
-
-\begin{figure}
-\centering
-\includegraphics{figures/installingAnaconda_windows_installer_07_installing2.png}
-\caption{Installing 2}
-\end{figure}
-
-\begin{figure}
-\centering
-\includegraphics{figures/installingAnaconda_windows_installer_08_installing_complete.png}
-\caption{Complete}
-\end{figure}
-
-\begin{figure}
-\centering
-\includegraphics{figures/installingAnaconda_windows_installer_09_cloud.png}
-\caption{Cloud}
-\end{figure}
-
-\begin{figure}
-\centering
-\includegraphics{figures/installingAnaconda_windows_installer_10_finish.png}
-\caption{Finish}
-\end{figure}
-
-\begin{enumerate}
-\def\labelenumi{\arabic{enumi}.}
-\setcounter{enumi}{8}
-\tightlist
-\item
-  You made it! Anaconda is now installed, you are ready for launch.
-  Assuming that you didn't add Anaconda to PATH environment variable you
-  will need to start navigator from the start menu.
-\end{enumerate}
-
-\subsubsection{Mac/Linux}\label{maclinux}
-
-Anaconda provides installation documentation for Mac and Linux users,
-please refer to the
-\href{https://docs.anaconda.com/anaconda/install/}{documentation page}.
diff --git a/book/module1/intro_to_anaconda.tex b/book/module1/intro_to_anaconda.tex
deleted file mode 100644
index 935b3f5..0000000
--- a/book/module1/intro_to_anaconda.tex
+++ /dev/null
@@ -1,191 +0,0 @@
-\section{Introduction to Anaconda
-Navigator}\label{introduction-to-anaconda-navigator}
-
-Anaconda Navigator is a program that we will be using in this course to
-manage Python environments, libraries and launch programs to help us
-write our python code.
-
-The Anaconda website nicely describes \emph{Navigator} as:
-
-\emph{a graphical user interface (GUI) that enables you to work with
-packages and environments without needing to type conda commands in a
-terminal window.Find the packages you want, install them in an
-environment, run the packages, and update them -- all inside Navigator.}
-
-To better understand how Navigator works and interacts with the anaconda
-ecosystem see the figure below.
-\includegraphics{figures/AnacondaSchematic.png} As you schematic
-indicated, Navigator is a tool in the Anaconda toolbox that allows the
-user to select and configure python environments and libraries. Let's
-see how we can do this.
-
-\subsection{Getting Started}\label{getting-started}
-
-Note to windows 10 users: Some installation instances do not allow users
-to search the start menu for \emph{Navigator}, instead, you'll have to
-find the program under the \emph{Anaconda (anaconda3)} folder. Expand
-the folder and click on \emph{Anaconda Navigator} to launch the program.
-
-\begin{figure}
-\centering
-\includegraphics{figures/installingAnaconda_windows_launched.png}
-\caption{Anaconda Navigator screen}
-\end{figure}
-
-Once Navigator starts, under \emph{Home}, you'll see tiles of programs
-that come with anaconda. The tab allows you to launch the programs we
-will be using in this course. Before jumping straight into the programs
-we will first need to configure our Python instance.
-
-The \emph{Environment} page allows us to install a variety of libraries
-and configure our environments for different project, more on this in
-the next section.
-
-\subsection{Environments}\label{environments}
-
-A Python environment can be thought of as a ``container'' where you can
-have all the tools, libraries, and dependencies your Python project
-needs without interfering with other projects. Think of it as a
-dedicated toolbox for your project.
-
-Although the base environment comes with many libraries and programs
-pre-installed, it's recommended to create a dedicated environment for
-your projects. This protects the base environment from breaking due to
-complex dependency conflicts. Let us go ahead and create a new
-environment for us to use Spyder with.
-
-\begin{enumerate}
-\def\labelenumi{\arabic{enumi}.}
-\tightlist
-\item
-  Click on the \emph{Environments} page located on the left hand side.
-\end{enumerate}
-
-\begin{figure}
-\centering
-\includegraphics{figures/anaconda_environment_page.png}
-\caption{Environment Page}
-\end{figure}
-
-\begin{enumerate}
-\def\labelenumi{\arabic{enumi}.}
-\setcounter{enumi}{1}
-\tightlist
-\item
-  At the bottom of the environments list, click \emph{Create}.
-\end{enumerate}
-
-\begin{figure}
-\centering
-\includegraphics{figures/anaconda_create_new_environment.png}
-\caption{Create new environment}
-\end{figure}
-
-\begin{enumerate}
-\def\labelenumi{\arabic{enumi}.}
-\setcounter{enumi}{2}
-\item
-  Select the python checkbox.
-\item
-  Select versions of python. At the time of making this tutorial the
-  latest version of Python is 3.xx.x. We will go ahead and use that one.
-\item
-  Choose an appropriate name for your project. We will be creating an
-  environment for the Spyder IDE so we'll call it ``Spyder-env''.
-\item
-  Click \emph{Create}.
-\end{enumerate}
-
-For more information see
-\href{https://docs.anaconda.com/working-with-conda/environments/}{Anaconda
-Environments} and
-\href{https://docs.anaconda.com/navigator/tutorials/manage-environments/}{Managing
-environment}.
-
-\subsection{Package Management}\label{package-management}
-
-Now that we have a clean environment configured, let us install some
-library we will be using for this class.
-
-\begin{enumerate}
-\def\labelenumi{\arabic{enumi}.}
-\tightlist
-\item
-  Navigate to the environment page and select the environment we just
-  created in the previous section.
-\end{enumerate}
-
-\begin{figure}
-\centering
-\includegraphics{figures/anaconda_select_package_to_manage.png}
-\caption{Select environment to manage}
-\end{figure}
-
-\begin{enumerate}
-\def\labelenumi{\arabic{enumi}.}
-\setcounter{enumi}{1}
-\tightlist
-\item
-  Use the search bar in the top right corner to search for the following
-  packages:
-\end{enumerate}
-
-\begin{longtable}[]{@{}ll@{}}
-\toprule\noalign{}
-Library & Usage \\
-\midrule\noalign{}
-\endhead
-\bottomrule\noalign{}
-\endlastfoot
-numpy & Numerical computation \\
-scipy & Scientific and techical computing \\
-pandas & Data manipulation and analysis \\
-matplotlib & Plots and visualizations \\
-sympy & Symbolic mathematics \\
-\end{longtable}
-
-\emph{Note: The libraries list may change throughout the development of
-this course}
-
-\begin{enumerate}
-\def\labelenumi{\arabic{enumi}.}
-\setcounter{enumi}{2}
-\tightlist
-\item
-  Check the boxes to install the selected packages to the current
-  environment.
-\end{enumerate}
-
-\subsection{Installing Applications}\label{installing-applications}
-
-From the \emph{Home} page you can install applications, to the current
-environment we created in the Environment section above. In this section
-we will install Spyder IDE, but the process is exactly the same for
-other applications.
-
-\begin{enumerate}
-\def\labelenumi{\arabic{enumi}.}
-\item
-  Go to the \emph{Home} page.
-\item
-  Select the desired environment. In our case, we select
-  \emph{Spyder-env}.
-\item
-  From the Home page find the Spyder IDE tile. Click the \emph{Install}
-  button to start the download.
-\end{enumerate}
-
-\begin{figure}
-\centering
-\includegraphics{figures/anaconda_homepage.png}
-\caption{Anaconda Home Page}
-\end{figure}
-
-\begin{enumerate}
-\def\labelenumi{\arabic{enumi}.}
-\setcounter{enumi}{3}
-\tightlist
-\item
-  Once the download is complete, press \emph{Launch} to start the
-  applications.
-\end{enumerate}
diff --git a/book/module1/intro_to_programming.tex b/book/module1/intro_to_programming.tex
deleted file mode 100644
index c73dcf4..0000000
--- a/book/module1/intro_to_programming.tex
+++ /dev/null
@@ -1,38 +0,0 @@
-\section{Introduction to Programming}\label{introduction-to-programming}
-
-\subsection{The Importance of Programming in
-Engineering}\label{the-importance-of-programming-in-engineering}
-
-Engineering is all about solving problems, designing innovative
-solutions, and making systems work efficiently. Whether you're designing
-cars, airplanes, rockets, or even everyday machines, programming plays a
-critical role in modern engineering.
-
-In mechanical engineering, programming helps us \textbf{analyze data,
-model complex systems, automate repetitive tasks, and simulate
-real-world physics.} For example, instead of spending hours solving
-equations by hand, engineers can write a program that does it in
-seconds. This saves time and therefore do more.
-
-With programming, mechanical engineers can:
-
-\begin{itemize}
-\tightlist
-\item
-  \textbf{Automate calculations:} Quickly solve equations for heat
-  transfer, fluid dynamics, and mechanical stresses.
-\item
-  \textbf{Simulate systems:} Model how a bridge bends under weight or
-  how an engine burns fuel efficiently.
-\item
-  \textbf{Analyze data:} Process thousands of test results to improve
-  designs.
-\item
-  \textbf{Control machines:} Program robots, 3D printers, and CNC's.
-\end{itemize}
-
-In this course, you'll see how computing and programming applies to
-mechanical engineering and how they can make you a better problem
-solver. By the end, you'll have the skills and understanding of how to
-write programs that help you \textbf{think like an engineer in the
-digital age.}
diff --git a/book/module1/jupyter_lab_notebook.tex b/book/module1/jupyter_lab_notebook.tex
deleted file mode 100644
index b7d9353..0000000
--- a/book/module1/jupyter_lab_notebook.tex
+++ /dev/null
@@ -1,146 +0,0 @@
-\subsection{Introduction}\label{introduction}
-
-Jupyter Notebooks are often used for data science and scientific
-computing such as machine learning as the interactive design allow you
-to experiment easily with your code. For our purpose, we will use
-Notebooks as it's a useful tool to learn how to code as well as writing
-reports.
-
-\emph{Note on the difference between Notebook and Lab: Jupyter Notebook
-offers a simplified, lightweight notebook authoring experience, where
-as, JupyterLab offers a feature-rich, tabbed multi-notebook editing
-environment with additional tools like a customizable interface layout
-and system console}
-
-\subsection{Setup and Installation}\label{setup-and-installation}
-
-Jupyter Notebooks can be installed either from the Anaconda Navigator
-home page or directly from your Conda terminal.
-
-Terminal: \texttt{conda\ install\ conda-forge::jupyterlab}
-
-\subsection{Notebook Basics}\label{notebook-basics}
-
-Jupyter Notebooks are files which allows you to combine \emph{Code} and
-\emph{Markdown} cells in one single document. The code cells, allow you
-to interactively run python code and print and plot data in your
-document. If you wish to update or change data your code you can re-run
-the cell to update the output. The markdown cells allows you to write
-text, titles and insert images in your documentation using the markup
-language \emph{Markdown}.
-
-To start a new notebook select
-\texttt{File\ \textgreater{}\ New\ \textgreater{}\ Notebook} or right
-click the file browser and select \texttt{New\ notebook}, this will
-prompt you to select a kernel (the Jupyter notebook ``engine''). For
-now, just select the default Kernel 3. This will start a new fresh
-kernel for us to use. Next, it's recommended to rename the file.
-
-Now that we have a blank notebook we can start to add cells. Add a cell
-and change the type to Markdown. Add a title with the hash symbol
-(\texttt{\#}). As shown below.
-
-\begin{Shaded}
-\begin{Highlighting}[]
-\FunctionTok{\# Title here}
-\end{Highlighting}
-\end{Shaded}
-
-Press \texttt{Shift\ +\ Enter} to run the cell. You just entered created
-your first markdown cell. Now let's do the same but instead select code
-as the cell type, we're going to add some python code to the document.
-
-\begin{Shaded}
-\begin{Highlighting}[]
-\NormalTok{x }\OperatorTok{=} \DecValTok{4}
-\NormalTok{y }\OperatorTok{=} \DecValTok{3}
-
-\NormalTok{x}\OperatorTok{**}\DecValTok{2}\OperatorTok{+}\DecValTok{2}\OperatorTok{*}\NormalTok{y}
-\end{Highlighting}
-\end{Shaded}
-
-Again, run the cell and see what happens. You should've gotten an output
-of \texttt{22}. You can now use the notebook as a calculator, but there
-is so much more we can do.
-
-The order of running code matters. Think of the code cells as code
-snippets. Every time you run a cell variable will be updated. This means
-that the current state of all variables, functions, and imports depends
-on the history of what cells have been executed and in what order. In
-other words, if you run a later cell before running an earlier one that
-defines a variable or function it needs, you will get an error. If you
-change a variable in one cell and rerun it, that new value immediately
-affects the results of any cells that use that variable afterward ---
-but not any previously run results unless you rerun them too. Variables
-and imports persist in memory between cells, but only based on the
-current session state --- if you restart the kernel, you lose all
-previous definitions unless you re-run the necessary cells. Therefore,
-let's press the \texttt{Restart\ the\ kernel} button on the top window.3
-
-Because of this, it's best practice to; Run cells in order, restart the
-kernel and run all cells
-(\texttt{Kernel\ -\textgreater{}\ Restart\ \&\ Run\ All}) to make sure
-everything works cleanly and predictably and lastly, initialize
-important variables or imports in early cells, so they are always
-defined before they are needed.
-
-\subsection{Making your document look good with
-Markdown}\label{making-your-document-look-good-with-markdown}
-
-Creating titles or headers is done with the hash symbol. The number of
-hashes determines whether it's a sub-title \texttt{\#}, \texttt{\#\#},
-\texttt{\#\#\#}
-
-\subsubsection{Lists}\label{lists}
-
-There are two types of list in - Bullet lists: \texttt{-\ item} -
-Numbered lists: \texttt{1.\ item} \#\#\# Style - Emphasis:
-\emph{italic}, \textbf{bold}, \texttt{monospace}
-
-\subsubsection{Mathematical Equation}\label{mathematical-equation}
-
-Markdown supports LaTeX format equations. Inline equation is opened and
-closed with a single \texttt{\$}. For a block math a double
-\texttt{\$\$} is used instead of single.
-
-\begin{itemize}
-\tightlist
-\item
-  Inline: This equation is inline \texttt{\$E\ =\ mc\^{}2\$} in with the
-  markdown text.
-\item
-  Block: Whilst this is a block:
-  \texttt{\$\$\textbackslash{}int\_0\^{}\textbackslash{}infty\ e\^{}\{-x\^{}2\}\ dx\ =\ \textbackslash{}frac\{\textbackslash{}sqrt\{\textbackslash{}pi\}\}\{2\}\$\$}
-\end{itemize}
-
-\subsubsection{Links and images}\label{links-and-images}
-
-You can insert links to a different local file or online urls like this:
-{[}Link{]}(file.md). I insert an image it's the same however start with
-an exclamation mark \texttt{!} like this: !{[}Image
-Caption{]}(picture.png)
-
-\subsection{Exporting and Sharing}\label{exporting-and-sharing}
-
-To export your notebook go to
-
-\texttt{File} \textgreater{} \texttt{Download\ As}
-
-You can then select these options.
-
-\begin{itemize}
-\tightlist
-\item
-  Notebook (\texttt{.ipynb})
-\item
-  HTML
-\item
-  PDF (requires LaTeX)
-\item
-  Markdown
-\end{itemize}
-
-For homework assignments, download an HTML version of your document,
-then from your browser, save or print as a PDF. Alternatively, you can
-install the LaTeX typesetting system and export your document directly
-as PDF from jupyter.
diff --git a/book/module1/module1.tex b/book/module1/module1.tex
deleted file mode 100644
index 27bf133..0000000
--- a/book/module1/module1.tex
+++ /dev/null
@@ -1,12 +0,0 @@
-\chapter{Module 1: Introductory Programming Concepts}
-\input{module1/intro_to_anaconda}
-\input{module1/jupyter_lab_notebook}
-\input{module1/spyder_getting_started}
-\input{module1/basics_of_python}
-\input{module1/array}
-\input{module1/control_structures}
-\input{module1/functions}
-\input{module1/classes_and_objects}
-\input{module1/open_source_software}
-\input{module1/1_excel_to_python}
-\input{module1/computational_expense}
diff --git a/book/module1/open_source_software.tex b/book/module1/open_source_software.tex
deleted file mode 100644
index 96de292..0000000
--- a/book/module1/open_source_software.tex
+++ /dev/null
@@ -1,104 +0,0 @@
-\section{Open Source Software}\label{open-source-software}
-
-Open-source software (OSS) is a type of software that allows users to
-access, modify, and distribute its source code freely. It is built on
-principles of collaboration, transparency, and community-driven
-development.
-
-You've probably heard of the saying ``Don't reinventing the wheel''.
-This
-
-\subsubsection{Key Principles of Open Source
-Software}\label{key-principles-of-open-source-software}
-
-\begin{itemize}
-\tightlist
-\item
-  \textbf{Free Distribution:} Anyone can download and use the software
-  without cost.
-\item
-  \textbf{Access to Source Code:} Users can view and modify the code to
-  suit their needs.
-\item
-  \textbf{Community Collaboration:} Developers from around the world
-  contribute to improvements and security fixes.
-\end{itemize}
-
-\subsubsection{Benefits of Open Source
-Software}\label{benefits-of-open-source-software}
-
-\begin{itemize}
-\tightlist
-\item
-  \textbf{Cost-effectiveness:} Open-source software is free to use,
-  making it accessible to individuals and organizations.
-\item
-  \textbf{Transparency and Security:} Open code allows for peer review,
-  reducing security vulnerabilities.
-\item
-  \textbf{Community Support:} Global developer communities provide
-  assistance, troubleshooting, and improvements.
-\item
-  \textbf{Customization and Flexibility:} Users can modify software to
-  fit their specific requirements.
-\end{itemize}
-
-\subsubsection{Challenges of Open Source
-Software}\label{challenges-of-open-source-software}
-
-\begin{itemize}
-\tightlist
-\item
-  \textbf{Usability Issues:} Some open-source software may have a
-  steeper learning curve.
-\item
-  \textbf{Compatibility Problems:} Integration with proprietary systems
-  may require additional effort.
-\item
-  \textbf{Support and Documentation:} The quality of documentation and
-  support varies.
-\item
-  \textbf{Sustainability:} Open-source projects often rely on
-  volunteers, which can lead to inconsistent updates.
-\end{itemize}
-
-\subsubsection{Popular Open Source
-Projects}\label{popular-open-source-projects}
-
-\begin{itemize}
-\tightlist
-\item
-  \textbf{Operating Systems:} Linux, Ubuntu
-\item
-  \textbf{Web Browsers:} Mozilla Firefox
-\item
-  \textbf{Programming Languages:} Python, JavaScript
-\item
-  \textbf{Office Suites:} LibreOffice
-\item
-  \textbf{Multimedia Tools:} Audacity, Blender
-\item
-  \textbf{Software Development:} Git, GitHub, Apache
-\end{itemize}
-
-\subsubsection{How to Contribute to Open
-Source}\label{how-to-contribute-to-open-source}
-
-\begin{itemize}
-\tightlist
-\item
-  \textbf{Finding Projects:} Platforms like GitHub, GitLab, and
-  SourceForge host many open-source projects.
-\item
-  \textbf{Understanding Licensing:} Common licenses include GPL, MIT,
-  and Apache.
-\item
-  \textbf{Ways to Contribute:} Developers can contribute code, test
-  software, write documentation, translate, or help with design.
-\item
-  \textbf{Best Practices for Contributions:} Using version control
-  (Git), writing clean code, and following community guidelines are
-  essential for successful collaboration.
-\end{itemize}
-
-\subsection{Licensing}\label{licensing}
diff --git a/book/module1/spyder_getting_started.tex b/book/module1/spyder_getting_started.tex
deleted file mode 100644
index 3133b15..0000000
--- a/book/module1/spyder_getting_started.tex
+++ /dev/null
@@ -1,107 +0,0 @@
-\section{Getting started with Spyder}\label{getting-started-with-spyder}
-
-In this tutorial we will cover the basics of using the Spyder IDE
-(Interactive Development Environment). If you've ever worked with MATLAB
-before, then this will feel familiar. Spyder is a program that allows
-you to write, run and de-bug code.
-
-\subsection{Launching Spyder}\label{launching-spyder}
-
-Using Anaconda we will select the environment we created earlier
-\emph{spyder-dev} and then we can launch spyder from the Home page.
-
-\subsection{Spyder Interface}\label{spyder-interface}
-
-\begin{figure}
-\centering
-\includegraphics{figures/spyder_interface.png}
-\caption{Spyder Interface}
-\end{figure}
-
-Once you open up Spyder in it's default configuration, you'll see three
-sections; the editor IPython Console, Help viewer. You can customize the
-interface to suit your prefference and needs some of which include,
-rearrange, undock, hide panes. Feel free to set up Spyder as you like.
-
-\subsubsection{Editor}\label{editor}
-
-This pane is used to write your scripts. The
-
-\begin{figure}
-\centering
-\includegraphics{figures/editor_key_components.png}
-\caption{Editor key components}
-\end{figure}
-
-\begin{enumerate}
-\def\labelenumi{\arabic{enumi}.}
-\tightlist
-\item
-  The left sidebar shows line numbers and displays any code analysis
-  warnings that exist in the current file. Clicking a line number
-  selects the text on that line, and clicking to the right of it sets a
-  \href{https://docs.spyder-ide.org/5/panes/debugging.html\#debugging-breakpoints}{breakpoint}.
-\item
-  The scrollbars allow vertical and horizontal navigation in a file.
-\item
-  The context (right-click) menu displays actions relevant to whatever
-  was clicked.
-\item
-  The options menu (``Hamburger'' icon at top right) includes useful
-  settings and actions relevant to the Editor.
-\item
-  The location bar at the top of the Editor pane shows the full path of
-  the current file.
-\item
-  The tab bar displays the names of all opened files. It also has a
-  Browse tabs button (at left) to show every open tab and switch between
-  them---which comes in handy if many are open.
-\end{enumerate}
-
-\subsubsection{IPython Console}\label{ipython-console}
-
-This pane allows you to interactively run functions, do math
-computations, assign and modify variables.
-
-\begin{figure}
-\centering
-\includegraphics{figures/spyder_ipython_console.png}
-\caption{IPython Console}
-\end{figure}
-
-\begin{itemize}
-\tightlist
-\item
-  Automatic code completion
-\item
-  Real-time function calltips
-\item
-  Full GUI integration with the enhanced Spyder
-  \href{https://docs.spyder-ide.org/5/panes/debugging.html}{Debugger}.
-\item
-  The
-  \href{https://docs.spyder-ide.org/5/panes/variableexplorer.html}{Variable
-  Explorer}, with GUI-based editors for many built-in and third-party
-  Python objects.
-\item
-  Display of Matplotlib graphics in Spyder's
-  \href{https://docs.spyder-ide.org/5/panes/plots.html}{Plots} pane, if
-  the Inline backend is selected under \texttt{Preferences}
-  \textgreater{} \texttt{IPython\ console} \textgreater{}
-  \texttt{Graphics} \textgreater{} \texttt{Graphics\ backend}, and
-  inline in the console if Mute inline plotting is unchecked under the
-  Plots pane's options menu.
-\end{itemize}
-
-\subsubsection{Variable Explorer}\label{variable-explorer}
-
-This pane shows all the defined variables (objects) stored. This can be
-used to identify the data type of variables, the size and inspect larger
-arrays. Double clicking the value cell opens up a window which allowing
-you to inspect the data in a spreadsheet like view.
-
-\begin{figure}
-\centering
-\includegraphics{figures/spyder_variable_explorer.png}
-\caption{Variable Explorer}
-\end{figure}