Taylor Series Expansion Example Report
This is a text report generated for the Taylor Series Expansion example. All objects, notes, formulas and formula inputs were turned on and the report was generated with tabs.
The order the objects are listed in is determined by their position on the diagram, with the leftmost objects first and in the case of a tie, from the top down.
: Taylor Series Expansion
Notes: Tap here first...
Series expansion is a common mathematical tool for approximating functions that cannot be directly
calculated. This example will show how Math Minion's matrix object can be used to easily implement
a series expansion, specifically a Taylor series to calculate e^x and sin(x).
See the notes for each of the objects.
Expression: Root.x
Notes: Just an arbitrary value for the functions to work on.
Formula: 2
Unit: Fraction
1
1 2.00000
Matrix: Root.taylorE
Notes: An exponential function e^x can be represented by the Taylor series:
e^x = sum from n=0 to infinity of:
x^n / n!
The terms of this summation, except for n=0, are represented in this matrix as a column calculated
by the formula
x^{row}/{factorial {row}}
which is assigned to the column header cell of column 1.
The function {row} will return the number of each row and thus represents n starting from 1 rather
than 0. This means we still have to add the n=0 term, which is just 1, when we sum the terms.
The number of terms is set by setting the number or rows in the matrix.
Input Sources: x
Cell Formulas:
0_0: x^{row}/{factorial {row}}
Unit: Fraction
1
1 2.00000
2 2.00000
3 1.33333
4 0.66667
5 0.26667
6 0.08889
7 0.02540
8 6.349206e-03
9 1.410935e-03
10 2.821869e-04
Expression: Root.sumE
Notes: Using the sum function with TaylorE as the argument will sum all the terms of the expansion
except for the n=0 term.
The value of this term is just 1, and it is added to the function for a formula:
1+{sum taylorE}
Input Sources: taylorE
Formula: 1+{sum taylorE}
Unit: Fraction
1
1 7.38899
Expression: Root.diffE
Notes: Math Minion has an e to the x function, so we can easily check the accuracy of our
approximation with the formula:
{exp x} - sumE
Try altering the number of terms in the expansion to see how that affects the accuracy. This is
done by just changing the number of rows in the TaylorE matrix object.
Input Sources: sumE x
Formula: {exp x} - sumE
Unit: Fraction
1
1 6.138994e-05
Matrix: Root.rowE
Notes: In order to plot the convergence as the number of terms increase, the formula for the column
in this matrix:
1+{sum taylorE[1:{row}]}
Is similar to the one for sumE, but it uses the range operator : and the index operators [] to sum
the first n rows of taylorE.
Note that the number of rows for this matrix is set to the formula:
{nrows taylorE}
so that it is always the same size as taylorE.
Input Sources: taylorE
Cell Formulas:
0_0: 0
0_1: 1+{sum taylorE[1:{row}]}
Unit: Fraction
1
1 3.00000
2 5.00000
3 6.33333
4 7.00000
5 7.26667
6 7.35556
7 7.38095
8 7.38730
9 7.38871
10 7.38899
Graph/Table: Root.Plot
Notes: This plots the sum to n of the taylorE terms, as calculated by rowE, versus n as calculated
by the formula:
1:{nrows taylorE}
Note that term 0, which would be 1, is not plotted.
Input Sources: rowE taylorE
1:{nrows taylo rowE
Fraction Fraction
1.00000 3.00000
2.00000 5.00000
3.00000 6.33333
4.00000 7.00000
5.00000 7.26667
6.00000 7.35556
7.00000 7.38095
8.00000 7.38730
9.00000 7.38871
10.00000 7.38899
Matrix: Root.taylorSine
Notes: This follows the same procedure as taylorE, but uses the formula:
x^(2*{row}+1) * -1^{row}/{factorial 2*{row}+1}
to calculate the Taylor expansion terms for sin(x), which are:
((-1)^n) * x^(2n+1)
-------------------------
(2n+1)!
Input Sources: x
Cell Formulas:
0_0: x^(2*{row}+1) * -1^{row}/{factorial 2*{row}+1}
Unit: Fraction
1
1 -1.33333
2 0.26667
3 -0.02540
4 1.410935e-03
5 -5.130672e-05
Expression: Root.sumSine
Notes: In this case the n=0 term is just x, which is added to the sum of their other terms
calculated by taylorSine.
Input Sources: taylorSine x
Formula: x+{sum taylorSine}
Unit: Fraction
1
1 0.90930
Expression: Root.diffSine
Notes: Calculates the difference between the approximation and the built in sine function.
Input Sources: sumSine x
Formula: {sin x}-sumSine
Unit: Fraction
1
1 1.290863e-06