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I have two general functions Estability3 and Lstability3 where I would like to evaluate both two dimensional slices of arrays and one dimensional ranges of vectors. I have explored the error outside the functions in a jupyter notebook with some of the arguments to the functions.

These function compute energy and angular momentum. The position and velocity data needed to compute the energy and angular momentum is stored in a two dimensional matrix called xvec where the position and velocity are along a row and the three entries represent the three stars. xvec0 is the initial data for the simulation (timestep 0).

xvec0
array([[-5.00000000e+00, 0.00000000e+00, 0.00000000e+00, -0.00000000e+00, -2.23606798e+00, 0.00000000e+00],
 [ 5.00000000e+00, 0.00000000e+00, 0.00000000e+00, -0.00000000e+00, 2.23606798e+00, 0.00000000e+00], 
[ 9.95024876e+02, 0.00000000e+00, 0.00000000e+00, -0.00000000e+00, 4.46099737e-01, 0.00000000e+00]])

I select the first star of the zeroth timestep by selecting the first row of this matrix. If I were looping over thousands of timesteps like usual I would use thousands of matrices like these and append them to a list then convert to a numpy array with thousands of columns. (so xvec1_0 would have thousands of columns instead of one).

xvec1_0=xvec0[0]

Since xvec1_0 has only one column, here I am trying to force numpy to recognize it as a matrix. It doesn't work.

np.reshape(xvec1_0,(1,6))

array([[-5.        ,  0.        ,  0.        , -0.        , -2.23606798,
         0.        ]])

I see that it has two outer brackets, which implies that it is a matrix. But when I try to use the colon index over the one column like I normally do over the 1000s of columns, I get an error.

xvec1_0[:,0:3]
IndexError                                Traceback (most recent call last)
<ipython-input-115-79d26475ac10> in <module>
----> 1 xvec1_0[:,0:3]

IndexError: too many indices for array

Why can't I use the : operator to obtain the first row of this two dimensional array? How can I do that in this more general code that also applies to matrices?

Thanks, Steven

Ian Kemp
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StevenJD
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1 Answers1

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I think I misread the function definition for reshape. I thought it changed it in place. It doesn't, I needed to assign an output, like this

xvec0_1 = np.reshape(xvec1_0,(1,6))

xvec1_0[:,0:3]
array([[-5.,  0.,  0.]])

xvec1_0
array([[-5.        ,  0.        ,  0.        , -0.        , -2.23606798,
         0.        ]])

xvec1_0.shape
(1, 6)

Thanks to a friend's help, I discovered that the following works just fine.

import numpy as np
x = np.zeros((1,6))
print(x.shape)
print(x[:,0:3])
x[:,0:3]

(1, 6)
[[0. 0. 0.]]
array([[0., 0., 0.]])

x = np.zeros((6,))
print(x.shape)
x = np.reshape(x, (1,6))
print(x[:,0:3])
x[:,0:3]

(6,)
[[0. 0. 0.]]
array([[0., 0., 0.]])

Probably I should have thought of some of these tests, but I thought I already had found the most basic test when I saw the output from np.reshape. I really appreciate the help from my friend, and hope my question did not waste anyone's time too badly.

StevenJD
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