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% Most of the following are not required for the majority
% of cheat sheets but are needed for some symbol support.
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% Document Info
\author{gonz95alo}
\pdfinfo{
  /Title (numpy-scipy.pdf)
  /Creator (Cheatography)
  /Author (gonz95alo)
  /Subject (Numpy/Scipy Cheat Sheet)
}

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\noindent
\begin{multicols}{3}
\begin{tabulary}{5.8cm}{C}
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    \vspace{-7pt}
    {\parbox{\dimexpr\textwidth-2\fboxsep\relax}{\noindent
        \hspace*{-6pt}\includegraphics[width=5.8cm]{/web/www.cheatography.com/public/images/cheatography_logo.pdf}}
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\begin{tabulary}{11cm}{L}
    \vspace{-2pt}\large{\bf{\textcolor{DarkBackground}{\textrm{Numpy/Scipy Cheat Sheet}}}} \\
    \normalsize{by \textcolor{DarkBackground}{gonz95alo} via \textcolor{DarkBackground}{\uline{cheatography.com/152363/cs/33001/}}}
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\noindent
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\begin{tabulary}{5.8cm}{LL}
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  \mymulticolumn{2}{p{5.377cm}}{\bf\textcolor{white}{Cheatographer}}  \\
  \vspace{-2pt}gonz95alo \\
  \uline{cheatography.com/gonz95alo} \\
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\begin{tabulary}{5.8cm}{L}
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  \mymulticolumn{1}{p{5.377cm}}{\bf\textcolor{white}{Cheat Sheet}}  \\
   \vspace{-2pt}Not Yet Published.\\
   Updated 18th October, 2022.\\
   Page {\thepage} of \pageref{LastPage}.
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  \mymulticolumn{1}{p{5.377cm}}{\bf\textcolor{white}{Sponsor}}  \\
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  %\includegraphics[width=48px,height=48px]{dave.jpeg}
  Measure your website readability!\\
  www.readability-score.com
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\end{multicols}}




\begin{document}
\raggedright
\raggedcolumns

% Set font size to small. Switch to any value
% from this page to resize cheat sheet text:
% www.emerson.emory.edu/services/latex/latex_169.html
\footnotesize % Small font.

\begin{multicols*}{2}

\begin{tabularx}{8.4cm}{x{3.52 cm} x{4.48 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{8.4cm}}{\bf\textcolor{white}{Libraries}}  \tn
% Row 0
\SetRowColor{LightBackground}
Numpy & `import numpy as np` \tn 
% Row Count 1 (+ 1)
% Row 1
\SetRowColor{white}
Linear algebra (numpy) & `import numpy.linalg as LA` \tn 
% Row Count 3 (+ 2)
% Row 2
\SetRowColor{LightBackground}
Sparse operations (scipy) & `import scipy.sparse as ss` \tn 
% Row Count 5 (+ 2)
% Row 3
\SetRowColor{white}
Sparse normalizations (sklearn) & `from sklearn.preprocessing import normalize as sparse\_norm` \tn 
% Row Count 8 (+ 3)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{8.4cm}{x{3.68 cm} x{4.32 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{8.4cm}}{\bf\textcolor{white}{Array comparisons}}  \tn
% Row 0
\SetRowColor{LightBackground}
Locate indices based on condition & `index = np.where(array == 4)` \tn 
% Row Count 2 (+ 2)
% Row 1
\SetRowColor{white}
Check if all/any satisfy condition & `np.any(array == 1), np.all(array1 == array2)` \tn 
% Row Count 5 (+ 3)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{8.4cm}{x{3.68 cm} x{4.32 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{8.4cm}}{\bf\textcolor{white}{Matricial operations}}  \tn
% Row 0
\SetRowColor{LightBackground}
Dot product & `np.dot(v1, v2)` or `v1 @ v2` \tn 
% Row Count 2 (+ 2)
% Row 1
\SetRowColor{white}
Outer product & `np.outer(v1, v1)` \tn 
% Row Count 3 (+ 1)
% Row 2
\SetRowColor{LightBackground}
Sum rows (0), columns (1) & `np.sum(A, axis=0)` \tn 
% Row Count 5 (+ 2)
% Row 3
\SetRowColor{white}
Eigenvector, eigenvalues & `eigval, eigvec = LA.eig(A)` \tn 
% Row Count 7 (+ 2)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\SetRowColor{LightBackground}
\mymulticolumn{2}{x{8.4cm}}{The eigenvector output of the `eig()` function is a matrix containing the usual eigenvectors as its columns.}  \tn 
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{8.4cm}{x{5.2 cm} x{2.8 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{8.4cm}}{\bf\textcolor{white}{Numpy comparisons}}  \tn
% Row 0
\SetRowColor{LightBackground}
Check if any element satisfies a condition & `np.any(A == 1)` \tn 
% Row Count 2 (+ 2)
% Row 1
\SetRowColor{white}
Find which elements (their indices) satisfy a condition & `np.where(A == 1)` \tn 
% Row Count 5 (+ 3)
% Row 2
\SetRowColor{LightBackground}
Check if all elements satisfies a condition & `np.all(A == 1)` \tn 
% Row Count 7 (+ 2)
% Row 3
\SetRowColor{white}
Closeness up to tolerance & \seqsplit{`np.isclose(1.001}, 1)` \tn 
% Row Count 9 (+ 2)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{8.4cm}{x{5.84 cm} x{2.16 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{8.4cm}}{\bf\textcolor{white}{Numpy utilities}}  \tn
% Row 0
\SetRowColor{LightBackground}
Arrange all array elements in a list & \seqsplit{`np.ravel(A)`} \tn 
% Row Count 2 (+ 2)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\end{tabularx}
\par\addvspace{1.3em}

\begin{tabularx}{8.4cm}{x{3.52 cm} x{4.48 cm} }
\SetRowColor{DarkBackground}
\mymulticolumn{2}{x{8.4cm}}{\bf\textcolor{white}{Sparse matrices with scipy}}  \tn
% Row 0
\SetRowColor{LightBackground}
Convert numpy matrices to sparse & `A\_sparse = ss.csr\_matrix(A) \{\{nl\}\} A\_sparse = ss.csc\_matrix(A)` \tn 
% Row Count 3 (+ 3)
% Row 1
\SetRowColor{white}
Change CSC to CSR and viceversa & `A\_csr = A\_csc.tocsr() \{\{nl\}\} A\_csc = A\_csr.tocsc() ` \tn 
% Row Count 6 (+ 3)
% Row 2
\SetRowColor{LightBackground}
Row/col. normalization & `A\_norm = \seqsplit{sparse\_normalize(A\_csc}, norm='l1', axis=1)` \tn 
% Row Count 9 (+ 3)
% Row 3
\SetRowColor{white}
Sparse identity matrix & `sparse\_id = ss.identity(n)` \tn 
% Row Count 11 (+ 2)
% Row 4
\SetRowColor{LightBackground}
Invert a (CSC) sparse matrix & `sparse\_inv = ss.inv(A\_sparse)` \tn 
% Row Count 13 (+ 2)
% Row 5
\SetRowColor{white}
Dot product with vector & `A\_sparse.dot(v)` \tn 
% Row Count 15 (+ 2)
% Row 6
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Transpose sparse matrix & `At\_sparse = \seqsplit{A\_sparse.transpose()`} \tn 
% Row Count 17 (+ 2)
\hhline{>{\arrayrulecolor{DarkBackground}}--}
\SetRowColor{LightBackground}
\mymulticolumn{2}{x{8.4cm}}{CSC ({\emph{Compressed Sparse Column}}) are more suitable for column operations while CSR ({\emph{Compressed Sparse Row}}) are for row operations. For instance, row/col. normalizations.}  \tn 
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\end{tabularx}
\par\addvspace{1.3em}


% That's all folks
\end{multicols*}

\end{document}