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diff --git a/book/module1/arrays.tex b/book/module1/arrays.tex new file mode 100644 index 0000000..a5486d9 --- /dev/null +++ b/book/module1/arrays.tex @@ -0,0 +1,411 @@ + \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 |
