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76 \title[]{Arrays \& Least Squares Fit} |
76 \title[]{Arrays \& Least Squares Fit} |
77 |
77 |
78 \author[FOSSEE] {FOSSEE} |
78 \author[FOSSEE] {FOSSEE} |
79 |
79 |
80 \institute[IIT Bombay] {Department of Aerospace Engineering\\IIT Bombay} |
80 \institute[IIT Bombay] {Department of Aerospace Engineering\\IIT Bombay} |
81 \date[] {31, October 2009} |
81 \date[] {31, October 2009\\Day 1, Session 3} |
82 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% |
82 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% |
83 |
83 |
84 %\pgfdeclareimage[height=0.75cm]{iitmlogo}{iitmlogo} |
84 %\pgfdeclareimage[height=0.75cm]{iitmlogo}{iitmlogo} |
85 %\logo{\pgfuseimage{iitmlogo}} |
85 %\logo{\pgfuseimage{iitmlogo}} |
86 |
86 |
228 \item Rank of matrix A |
228 \item Rank of matrix A |
229 \item Singular values of A |
229 \item Singular values of A |
230 \end{enumerate} |
230 \end{enumerate} |
231 \end{itemize} |
231 \end{itemize} |
232 \begin{lstlisting} |
232 \begin{lstlisting} |
233 coeffs, res, rank, sing = lstsq(A,Tsq) |
233 In []: coef, res, r, s = lstsq(A,Tsq) |
234 \end{lstlisting} |
234 \end{lstlisting} |
235 \end{frame} |
235 \end{frame} |
236 |
236 |
237 \begin{frame}[fragile] |
237 \begin{frame}[fragile] |
238 \frametitle{Least Square Fit Line \ldots} |
238 \frametitle{Least Square Fit Line \ldots} |
239 \begin{itemize} |
239 \begin{itemize} |
240 \item Use the poly1d function of pylab, to create a function for the line equation using the coefficients obtained |
240 \item Use the poly1d function of pylab, to create a function for the line equation using the coefficients obtained |
241 \begin{lstlisting} |
241 \begin{lstlisting} |
242 p=poly1d(coeffs) |
242 In []: p=poly1d(coef) |
243 \end{lstlisting} |
243 \end{lstlisting} |
244 \item Get new $T^2$ values using the function \typ{p} obtained |
244 \item Get new $T^2$ values using the function \typ{p} obtained |
245 \begin{lstlisting} |
245 \begin{lstlisting} |
246 Tline = p(L) |
246 In []: Tline = p(L) |
247 \end{lstlisting} |
247 \end{lstlisting} |
248 \item Now plot Tline vs. L, to get the Least squares fit line. |
248 \item Now plot Tline vs. L, to get the Least squares fit line. |
249 \begin{lstlisting} |
249 \begin{lstlisting} |
250 plot(L, Tline) |
250 In []: plot(L, Tline) |
251 \end{lstlisting} |
251 \end{lstlisting} |
252 \end{itemize} |
252 \end{itemize} |
253 \end{frame} |
253 \end{frame} |
254 |
254 |
255 \begin{frame} |
255 \begin{frame} |
415 \end{lstlisting} |
415 \end{lstlisting} |
416 \end{frame} |
416 \end{frame} |
417 |
417 |
418 \end{document} |
418 \end{document} |
419 |
419 |
420 Least squares: Smooth curve fit. |
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421 Array Operations: Mean, average (etc region wise like district wise and state wise from SSLC.txt) |
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422 Subject wise average. Introduce idea of dictionary. |
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423 |
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424 Session 3 |
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425 |
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426 import scipy |
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427 from scipy import linalg. |
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428 |
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429 choose some meaningful plot. ?? |
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430 Newton's law of cooling. |
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431 u, v, f - optics |
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432 hooke's law |
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433 Least fit curves. |
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434 |
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435 |
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436 Choose a named problem. |
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437 ODE - first order. Whatever. |
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438 |
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439 |
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440 arrays, etc etc. |
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441 sum, average, mean. whatever. statistical |
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442 sslc data |
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443 numpy load text?? |
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