[SciPy-User] [SciPy-user] ValueError: arrays must have same number of dimensions

surfcast23 surfcast23@gmail....
Thu Jun 28 10:32:47 CDT 2012


Hi I am trying to translate a Matlab code from Trefethen's Spectral Methods
in MATLAB to Python. I am running into a problem with numpy.concatenate
wanting the arrays to have the same number of dimensions.
Here is part of the Matlab code that I am rewriting 


N = 512; h = 2*pi/N; x = h*(1:N); t = 0; dt = h/4;
a = .1;
c = a + sin (x-1).^2;
v = exp(-100*(x-1).^2); vold = exp(-100*(x-a*dt-1).^2);

column = [0 .5*(-1).^(1:N-1).*cot((1:N-1)*h/2)];
D = toeplitz(column,-column);

% Time-stepping by leap frog formula:
tmax = 15; tplot = .15; clf, drawnow, set(gcf,'renderer','zbuffer')
plotgap = round(tplot/dt); dt = tplot/plotgap;
nplots = round(tmax/tplot);
data = [v; zeros(nplots,N)]; tdata = t;


What I am trying in Python

for j in range(1,N):
 tmax = 15;   
 tplot = .15;
 h = 2*pi/N;
 dt = h/4; 
 nplots = around(tmax/tplot);
 plotgap = around(tplot/dt);
 dt = tplot/plotgap;  
 x = h*arange(1,N);
 c = a+np.sin(x-1)**2;
 v = exp(-100*(x-1)**2);
 vold = exp(-100*(x-a*dt-1)**2);
 
 column = ((0.5*(-1)**arange(1,N-1))*cotdg(arange(1,N-1))*(h/2));
 D = toeplitz(column,-column);
 
 k = np.zeros(((nplots,N)));
 data = np.concatenate((v, k),axis = 0);
 tdata = t;


I have highlighted the vectors in question.
v.shape gives (511,)

k.shape gives (100, 512)

I would appreciate any help with this. Thank you!

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