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These are questions asked by Britzel


I have a private license of Maple 2018, and am interested in advances in terms of tensor calculus in Maple 2019, in particular concerning applications in general relativity. Three questions:

(1) Is there a way for me to buy the package without having to buy Maple 2019 in full, or would I have to upgrade?

(2) I have seen in the preview video that the features can for instance calculate the Christoffel symbols, the Rieman tensor, etc., from a prescribed metric in a coordinate basis, correct? Can the formalism also handle Expressions expressed in a non-coordinate frame though? So a frame field, for which the commutaror of the basis vector fields does not vanish?

(3) Is there somewhere a nice documentation, with exaples, where I can read on what I can do with the package? The documentation in the "what's new" section on the website is mainly concerned with applications for quantum mechanics, which is not what I am interested in.



I am having trouble with the syntax for entering a limit of a multivariate function with direction specifiers.

For a single variate function f(x) the limit for x -> a from the right is specified by


A limit of a multivariate function f(x,y) for x -> a and y -> b can be entered by


However I do not know how to specify directions in this case. Say, I want x to approach a from the right, and y to approach b from the left. What is the syntax to do this?






I am trying to do a simple numerical calculation, and need to evaluate functions on a grid. I woult then like to build expression like finite differences, such as

Y[ i + 1 ] - Y[ i - 1 ]

where Y is my Array of function values. However I would then always get the "Error, bad index into Array", even though in the expressions I build i is specified as a summation index over a certain range. Interestingly, indexing with an i works though within the sequence command: seq( Y[ i ], i = 1..n) would produce an output.

I am not sure what is going on.

Thanks for Help!


I could solve my problem already. I edit in the solution at the end, in case some one ever runs into the same issue, and is happy finding this post when searching for a solution.



Hi there!

I am starting to learn how to use the Optimization package. The help page for the NLPSolve command contains the example

NLPSolve(sin(x)/x, x=1..30)

which would spit out the local minumum at x=23.519… with value -0.042… .

I tried to use the initialpoint option in order to solve for other local minima or maxima, but regardless which initial point choose, I get

Warning, initial point option ignored by solver

and again the same local minimum as before. I entered the option as follows:

NLPSolve(sin(x)/x, x=1..30,initialpoint={x=17})

I am not sure why it doesn't work, since the NLPSolve help page contains an example using the initialpoint option right underneath this example, and there everything works as intended.

Does anyone know what is going on here?




The problem was that NLPSolve uses the quadratic interpolation method by default if the function which should be extremised is univariate and unconstrained. This information can be found under the Optimization/General/Methods help page. This method however, is the only one which doesn't accept an initialpoint. Hence, the solution is to apply a different method, such as

NLPSolve(sin(x)/x, x=1..30,initialpoint={x=17},method=modifiednewton)


Hi there,

I am looking at the system of equations





Using the solve command with the assumption r >= 0 gives the solutions [r=0, theta=0], [r=1/2, theta=0] and [r=3/2, theta=pi].

However [r=0, theta=pi/2] is also a solution, which the solve command doesn't give me. Why not, and why doesn't if even give a warning that there are more solutions, which are not given?



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