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| -rw-r--r-- | day1/session4.tex | 23 |
1 files changed, 19 insertions, 4 deletions
diff --git a/day1/session4.tex b/day1/session4.tex index 79da193..4b814c9 100644 --- a/day1/session4.tex +++ b/day1/session4.tex @@ -503,9 +503,24 @@ Out[]: array([-1., 8., -1.]) \end{frame} \begin{frame}[fragile] +\frametitle{Getting $L$ and $T^2$} +If you \alert{closed} IPython after session 2 +\begin{lstlisting} +In []: l = [] +In []: t = [] +In []: for line in open('pendulum.txt'): + .... point = line.split() + .... l.append(float(point[0])) + .... t.append(float(point[1])) + .... + .... +\end{lstlisting} +\end{frame} + +\begin{frame}[fragile] \frametitle{Generating $A$} \begin{lstlisting} -In []: A = array([L, ones_like(L)]) +In []: A = array([l, ones_like(l)]) In []: A = A.T \end{lstlisting} %% \begin{itemize} @@ -533,13 +548,13 @@ In []: coef = result[0] \frametitle{Least Square Fit Line \ldots} We get the points of the line from \typ{coef} \begin{lstlisting} -In []: Tline = coef[0]*L + coef[1] +In []: Tline = coef[0]*l + coef[1] \end{lstlisting} \begin{itemize} -\item Now plot Tline vs. L, to get the Least squares fit line. +\item Now plot \typ{Tline} vs. \typ{l}, to get the Least squares fit line. \end{itemize} \begin{lstlisting} -In []: plot(L, Tline) +In []: plot(l, Tline) \end{lstlisting} \end{frame} |