ArrayResample

ArrayResample[array,{n1,n2,}]

resamples array to have dimensions {n1,n2,}.

ArrayResample[array,dspec]

resamples array according to the dimension specification dspec.

ArrayResample[array,dspec,scheme]

specifies resampling scheme, either point or bin based.

ArrayResample[array,dspec,scheme,{{xmin,xmax},}]

resamples only the data in the specified subrange {{xmin,xmax},}.

Details and Options

• ArrayResample can be used for resampling data arrays based on a large selection of interpolation and approximation models.
• ArrayResample works with data arrays of any depth.
• The dimension specification dspec can be of the form:
•  n n samples Scaled[s] rescale sampling resolution by factor s All preserve dimension Automatic preserve dimension ratios {dspec1,…,dspeck} resample up to the dimension
• For a multidimensional array, the notation n is taken to be equivalent to {n,Automatic,} and {n} equivalent to {n,All,}.
• The dimension ratios for an array of dimensions is taken to be .
• The scheme determines the location of sample and resample positions and can be of the form:
•  "Point" point sampling (default) "Bin" bin sampling {"Bin",alignment} bin sampling with specified alignment
• For input data of length n the "Point" resampling scheme assumes a data range from 1 to n and the "Bin" scheme assumes a data range from 0 to n with the alignment indicating the sample location within each bin.
• Bin alignment alignment can be Left, Center, Right or any number between (Left) and 1 (Right).
• The data range can be modified using the DataRange option.
• By default, the data is resampled on the entire data domain, ranging from 1 to for the "Point" scheme and from 0 to for the "Bin" scheme. Use the DataRange option to modify the coordinates of the data domain.
• With a subrange {{xmin,xmax},} specified with respect to the DataRange, only the data values in the given interval are resampled. »
• The following options can be given:
•  Antialiasing False apply antialiasing when downsampling DataRange Automatic range of the input data Padding "Fixed" padding method Resampling Automatic resampling method
• For possible settings for Padding, see the reference page for ArrayPad.

Examples

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Basic Examples(2)

Subsample an array:

Downsample an array:

Resize a 2D array of data:

Scope(8)

Basic Uses(4)

Exact computation:

Precision of the input is preserved:

Resizing a symbolic array:

Resample a subdomain of the input signal:

Output Dimensions(1)

With size specified as a scalar, output dimension is selected such that dimension ratio is preserved:

Sampling Schemes(3)

By default, the "Point" sampling scheme is used:

Use the "Bin" scheme, which uses center alignment by default:

Specify the alignment of the bins:

Generate a "Point" resampling with three times the input resolution:

Compute the sampling positions:

Options(5)

Antialiasing(1)

When downsampling, by default no antialiasing is happening:

With antialiasing, all samples that fall in between new samples are averaged:

DataRange(1)

DataRange specifies the domain of resampling. Subrange specification is defined with respect to this domain:

Resample the whole data:

Resample the first half using default DataRange->{1,n}, where n is the length of data:

Resample the first half of the data using a {0,1} data range:

The default padding value is "Fixed":

By default, the same padding is used for all dimensions:

Use different paddings for different dimensions:

Resampling(1)

By default, "Linear" resampling is used:

Use a different resampling scheme:

"Nearest" resampling averages the samples if the sampling position is halfway between samples:

Use "NearestLeft" or "NearestRight" for a bias to left or right for half-integer sampling positions:

Applications(1)

Reduce the size of a dataset for faster visualization:

Properties & Relations(2)

Compare array resampling for a few different kernels:

Downsample can be used to downsample by an integer factor:

Possible Issues(1)

Exact computations are performed with integer data:

Apply N to integer data for faster computation:

Wolfram Research (2014), ArrayResample, Wolfram Language function, https://reference.wolfram.com/language/ref/ArrayResample.html (updated 2016).

Text

Wolfram Research (2014), ArrayResample, Wolfram Language function, https://reference.wolfram.com/language/ref/ArrayResample.html (updated 2016).

CMS

Wolfram Language. 2014. "ArrayResample." Wolfram Language & System Documentation Center. Wolfram Research. Last Modified 2016. https://reference.wolfram.com/language/ref/ArrayResample.html.

APA

Wolfram Language. (2014). ArrayResample. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/ArrayResample.html

BibTeX

@misc{reference.wolfram_2022_arrayresample, author="Wolfram Research", title="{ArrayResample}", year="2016", howpublished="\url{https://reference.wolfram.com/language/ref/ArrayResample.html}", note=[Accessed: 01-June-2023 ]}

BibLaTeX

@online{reference.wolfram_2022_arrayresample, organization={Wolfram Research}, title={ArrayResample}, year={2016}, url={https://reference.wolfram.com/language/ref/ArrayResample.html}, note=[Accessed: 01-June-2023 ]}