be8ed228-7b9f-4d88-9521-f6039e697cd5 50 4 5 decimal
&[DATE] &[TIME] - &[FILENAME]
&[PAGENUM] / &[COUNT]

Rechnen mit Listen

List operations

Listen

Lists (systems)

Mathematik

Mathematics

Inhalt

Contents

Ansprechen von Listenelementen

Indexing of list elements

Listenelemente können wie bei Vektoren durch einen Adressindex angesprochen werden. Das funktioniert bei Anzeige und Zuweisung. Wird ein nicht existierendes Listenelement zugewiesen, dann wird die Liste dynamisch erweitert.

List elements can be adressed by indices just like vector elements. This works for display and assignment of individual elements. If a non-existent element is assigned to, then the list is extended to the required size.

1 2.5 0 3 4 1 sys 2.5

Bei Adressierung einer noch nicht existierenden Variable wird standardmäßig ein Vektor erzeugt:

If elements of non-existing variables are assigned to, then a vector variable is generated by default.

0 2 2 1 mat

Wollen Sie eine Liste durch dynamisch erzeugte Elemente aufbauen, müssen Sie vorher die Variable mit einer Liste belegen:

If you want to dynamically build up a list, then first a variable of type list must be created by just assigning any list to it.

0 0 3 3 1 sys

SMath kennt den Plus/Minus-Operator und den Minus/Plus-Operator, die beide Listen als Ergebnis liefern. Die Operatoren sind zugänglich über das Menü

SMath provides the plus/minus and minus/plus operators, which both return lists. They are accessed via menu:

Einfügen> Operator

Insert> Operator

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

Plus/Minus-Operator

operator plus/minus

a b + a b - 2 1 sys 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

Minus/Plus-Operator

operator minus/plus

Tastaturkürzel

Hot key

%

a b - a b + 2 1 sys

Die Beispiele oben wurden mit symbolischer Optimierung angezeigt.

The examples above are given with symbolic evaluation in order to emphasize the difference between the two operators.

Listen als Operanden in Formeln

Lists as operands in expressions

Rechenoperationen können gleichzeitig auf alle Elemente einer Liste angewendet werden:

Operations can be applied to all elements of a list at a time:

3 4.5 2 1 sys 1 6.25 2 1 sys 0.5403 0.8011 - 2 1 sys

Treten in einem Ausdruck zwei oder mehrere Listen auf, so wird der Ausdruck für alle möglichen Elementkombinationen ausgewertet:

If two or more lists appear in an expression, then the expression is evaluated for all possible combinations of list elements:

2 3.5 3.5 5 4 1 sys 1 2.5 2.5 6.25 4 1 sys 1 2.5 1 9.8821 4 1 sys 2 3.5 2 10.8821 3.5 5 3.5 12.3821 8 1 sys

Beispiel

Example

Das kann man beispielsweise benutzen, um Toleranzanalysen durchzuführen. In welchen Grenzen schwankt das Volumen eines Quaders, wenn die Kantenlängen mit ihren Toleranzen bekannt sind? Zunächst werden die Abmessungen mit ihren Toleranzen definiert:

This can be used, for example, in tolerance analysis. What is the range of the volume of a brick, if the tolerances of the edge lengths are known? First, we define the dimensions along with their relative or absolute tolerances:

absolute Toleranz

absolute tolerance

relative Toleranz, ±10%

relative tolerance, ±10%

Die Listen enthalten nun die extremal möglichen Abmessungswerte:

The lists now contain the extreme values of the dimensions:

mm 100 100.5 2 1 sys mm 50.2 49.8 2 1 sys mm 27 33 2 1 sys

Das Volumen ist das Produkt der drei Kantenlängen. Berechnet wird das Volumen jeder möglichen Kombination von Einzelwerten.

The volume is the product of the three dimensions. The result is the volume for each possible combination of extreme values:

cm 3 ^ 135.54 136.2177 134.46 135.1323 165.66 166.4883 164.34 165.1617 8 1 sys cm 3 ^ 134.46 cm 3 ^ 166.4883

Num sind noch Maximum und Minimum zu berechnen. Die internen Funktionen min() und max() können nicht mit Listen umgehen. Das Plugin CustomFunctions stellt allerdings die verbesserten Versionen Min() und Max() bereit:

Now we have to determine minimum and maximum. The internal functions min() and max() cannot handle lists. The plugin CustomFunctions provides improved versions Min() and Max():

cm 3 ^ 134.46 cm 3 ^ 166.4883

Listen

Lists (systems)

Mathematik

Mathematics

Inhalt

Contents

$Author: mkraska $ $Date: 2013-08-17 23:58:19 +0200 (Sa, 17. Aug 2013) $