diff options
Diffstat (limited to 'day2/session2.tex')
| -rw-r--r-- | day2/session2.tex | 38 |
1 files changed, 19 insertions, 19 deletions
diff --git a/day2/session2.tex b/day2/session2.tex index 67c2939..9a02146 100644 --- a/day2/session2.tex +++ b/day2/session2.tex @@ -324,7 +324,7 @@ \item Integrating Functions given fixed samples \item Numerical integrators of ODE systems \end{itemize} - Calculate $\int^1_0(sin(x) + x^2)dx$ + Calculate the area under $(sin(x) + x^2)$ in the range $(0,1)$ \begin{lstlisting} >>> def f(x): return np.sin(x)+x**2 @@ -340,11 +340,11 @@ x(0)&=2 \end{align*} \begin{lstlisting} - def dx_dt(x,t): +>>> def dx_dt(x,t): return -np.exp(-t)*x**2 - x=integrate.odeint(dx_dt, 2, t) - plt.plot(x,t) +>>> x=integrate.odeint(dx_dt, 2, t) +>>> plt.plot(x,t) \end{lstlisting} \inctime{10} \end{frame} @@ -369,15 +369,15 @@ \begin{frame}[fragile] \frametitle{Interpolation - Splines} - Cubic Spline of $sin(x)$ + Plot the Cubic Spline of $sin(x)$ \begin{lstlisting} - x = np.arange(0,2*np.pi,np.pi/4) - y = np.sin(x) - tck = interpolate.splrep(x,y) - X = np.arange(0,2*np.pi,np.pi/50) - Y = interpolate.splev(X,tck,der=0) - plt.plot(x,y,'o',x,y,X,Y) - plt.show() +>>> x = np.arange(0,2*np.pi,np.pi/4) +>>> y = np.sin(x) +>>> tck = interpolate.splrep(x,y) +>>> X = np.arange(0,2*np.pi,np.pi/50) +>>> Y = interpolate.splev(X,tck,der=0) +>>> plt.plot(x,y,'o',x,y,X,Y) +>>> plt.show() \end{lstlisting} \inctime{10} \end{frame} @@ -403,16 +403,16 @@ \frametitle{Signal \& Image Processing} Applying a simple median filter \begin{lstlisting} - from scipy import signal, ndimage - from scipy import lena - A=lena().astype('float32') - B=signal.medfilt2d(A) - imshow(B) +>>> from scipy import signal, ndimage +>>> from scipy import lena +>>> A=lena().astype('float32') +>>> B=signal.medfilt2d(A) +>>> imshow(B) \end{lstlisting} Zooming an array - uses spline interpolation \begin{lstlisting} - b=ndimage.zoom(A,0.5) - imshow(b) +>>> b=ndimage.zoom(A,0.5) +>>> imshow(b) \end{lstlisting} \inctime{5} \end{frame} |