Interpolation Using Prelookup
Using pre-calculated values of indices and fractions to speed up the approximation - dimensional function.
blockType: Interpolation_n-D
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Path in the library: |
Description
Block Interpolation Using Prelookup most effective when using a block Prelookup. Block Prelookup calculates the index and fraction of the interval, which determine how its input value is refers to a data set of reference points. The obtained index and fraction values are fed into the block Interpolation Using Prelookup for interpolation - dimensional table. Both blocks have integrated algorithms.
The block icon will change depending on the set parameters.
Supported block operations
To use the block Interpolation Using Prelookup You must specify a set of table data values directly in the dialog box. As a rule, these tabular values correspond to data sets of reference points specified in blocks Prelookup. Block Interpolation Using Prelookup generates output data by searching or evaluating tabular values based on index values and interval fractions obtained from the block Prelookup. The ports for the index and the interval fraction are displayed as k and f on the block icon Interpolation Using Prelookup.
| When entering the values of the index and the fraction of the interval… | Block Interpolation Using Prelookup… |
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Mapping to values in datasets with reference points |
Displays the table value at the intersection of rows, columns, and reference points of higher dimension |
Are not matched with the values in the data sets of the reference points, but are within the range |
Interpolates the corresponding table values using the selected interpolation method |
Are not matched with the values in the data sets of the reference points and are out of range |
Extrapolates the output value using the selected extrapolation method |
Ports
Output
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OUT_1
—
approximation of N-dimensional function
scalar | vector | matrix
Details
An approximation of an N-dimensional function calculated by interpolating (or extrapolating) tabular data from the values of the input index, k, and the fraction, f.
| Data types |
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| Complex numbers support |
No |
Input
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k1
—
index k for the first dimension of the table
scalar | vector | matrix
Details
Index with the first value specifying the interval containing the input value , for the first dimension of the table.
| Data types |
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| Complex numbers support |
No |
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f1
—
fraction f for the first dimension of the table
scalar | vector | matrix
Details
Fraction , representing the normalised position of the input in the interval for the first dimension of the table.
| Data types |
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| Complex numbers support |
No |
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kn
—
index k for the nth dimension of the table
scalar | vector | matrix
Details
Index with the first value , specifying the interval containing the input value for the nth dimension of the table.
| Data types |
|
| Complex numbers support |
No |
#
fn
—
fraction f for the nth dimension of the table
scalar | vector | matrix
Details
Fraction , representing the normalised position of the input in the interval for the nth dimension of the table.
| Data types |
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| Complex numbers support |
No |
Parameters
Table data
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Number of dimensions —
table data dimensionality
Real number
Details
Specify the dimensionality that the table data should have. The number of dimensions determines the number of independent variables for the table.
The maximum table dimensionality supported by this block is 30.
| Default value |
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| Program usage name |
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| Tunable |
No |
| Evaluatable |
Yes |
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Value —
tabular data values
Array of real numbers
Details
Setting the tabular data as an N-dimensional array, where is the value of the parameters. Number of dimensions.
| Default value |
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| Program usage name |
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| Tunable |
Yes |
| Evaluatable |
Yes |
Algorithm
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Interpolation method —
interpolation method
Flat | Nearest | Linear point-slope | Linear Lagrange
Details
The method by which the block interpolates the table data.
Read more about interpolation methods here: Methods for approximating function values
| Values |
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| Default value |
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| Program usage name |
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| Tunable |
No |
| Evaluatable |
No |
#
Extrapolation method —
a method of processing input values that are outside the range of the dataset of reference points
Clip | Linear
Details
The method that the block uses to extrapolate values for all inputs that fall outside the range of the reference point dataset.
Read more about extrapolation methods here: Methods for approximating function values
To make the blocks Prelookup and Interpolation Using Prelookup repeat the behaviour of block n-D Lookup Table, the extrapolation method for both blocks Prelookup and must be the same as when using only block . Interpolation Using Prelookup should be the same as for usage of only block n-D Lookup Table.
For example, to get the same behaviour for the n-D Lookup Table block with the Linear extrapolation method, set the extrapolation method to Linear for both the Prelookup block and the Interpolation Using Prelookup block.
The block Interpolation Using Prelookup block does not support linear extrapolation if the input or output signals are of fixed point data type.
| Values |
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| Default value |
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| Program usage name |
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| Tunable |
No |
| Evaluatable |
No |