arrayfire.signal module¶

Signal processing functions (fft, convolve, etc).

arrayfire.signal.approx1(signal,x,method=<INTERP.LINEAR:1>,off_grid=0.0,xp=None,output=None)[source]¶

Interpolate along a single dimension.Interpolation is performed along axis 0of the input array.

Parameters

signal: af.Array

Input signal array (signal = f(x))

x: af.Array

The x-coordinates of the interpolation points. The interpolation function is queried at these set of points.

method: optional: af.INTERP. default: af.INTERP.LINEAR.

Interpolation method.

off_grid: optional: scalar. default: 0.0.

The value used for positions outside the range.

xpaf.Array

The x-coordinates of the input data points

output: None or af.Array

Optional preallocated output array. If it is a sub-array of an existing af_array,only the corresponding portion of the af_array will be overwritten

Returns

output: af.Array

Values calculated at interpolation points.

arrayfire.signal.approx1_uniform(signal,x,interp_dim,idx_start,idx_step,method=<INTERP.LINEAR:1>,off_grid=0.0,output=None)[source]¶

Interpolation on one dimensional signals along specified dimension.

af_approx1_uniform() accepts the dimension to perform the interpolation along the input.It also accepts start and step values which define the uniform range of corresponding indices.

Parameters

signal: af.Array

Input signal array (signal = f(x))

x: af.Array

The x-coordinates of the interpolation points. The interpolation function is queried at these set of points.

interp_dim: scalar

is the dimension to perform interpolation across.

idx_start: scalar

is the first index value along interp_dim.

idx_step: scalar

is the uniform spacing value between subsequent indices along interp_dim.

method: optional: af.INTERP. default: af.INTERP.LINEAR.

Interpolation method.

off_grid: optional: scalar. default: 0.0.

The value used for positions outside the range.

output: None or af.Array

Optional preallocated output array. If it is a sub-array of an existing af_array,only the corresponding portion of the af_array will be overwritten

Returns

output: af.Array

Values calculated at interpolation points.

arrayfire.signal.approx2(signal,x,y,method=<INTERP.LINEAR:1>,off_grid=0.0,xp=None,yp=None,output=None)[source]¶

Interpolate along a two dimension.Interpolation is performed along axes 0 and 1of the input array.

Parameters

signal: af.Array

Input signal array (signal = f(x, y))

xaf.Array

The x-coordinates of the interpolation points. The interpolation function is queried at these set of points.

yaf.Array

The y-coordinates of the interpolation points. The interpolation function is queried at these set of points.

method: optional: af.INTERP. default: af.INTERP.LINEAR.

Interpolation method.

off_grid: optional: scalar. default: 0.0.

The value used for positions outside the range.

xpaf.Array

The x-coordinates of the input data points. The convention followed is thatthe x-coordinates vary along axis 0

ypaf.Array

The y-coordinates of the input data points. The convention followed is thatthe y-coordinates vary along axis 1

output: None or af.Array

Optional preallocated output array. If it is a sub-array of an existing af_array,only the corresponding portion of the af_array will be overwritten

Returns

output: af.Array

Values calculated at interpolation points.

arrayfire.signal.approx2_uniform(signal,pos0,interp_dim0,idx_start0,idx_step0,pos1,interp_dim1,idx_start1,idx_step1,method=<INTERP.LINEAR:1>,off_grid=0.0,output=None)[source]¶

Interpolate along two uniformly spaced dimensions of the input array.af_approx2_uniform() accepts two dimensions to perform the interpolation along the input.It also accepts start and step values which define the uniform range of corresponding indices.

Parameters

signal: af.Array

Input signal array (signal = f(x, y))

pos0af.Array

positions of the interpolation points along interp_dim0.

interp_dim0: scalar

is the first dimension to perform interpolation across.

idx_start0: scalar

is the first index value along interp_dim0.

idx_step0: scalar

is the uniform spacing value between subsequent indices along interp_dim0.

pos1af.Array

positions of the interpolation points along interp_dim1.

interp_dim1: scalar

is the second dimension to perform interpolation across.

idx_start1: scalar

is the first index value along interp_dim1.

idx_step1: scalar

is the uniform spacing value between subsequent indices along interp_dim1.

method: optional: af.INTERP. default: af.INTERP.LINEAR.

Interpolation method.

off_grid: optional: scalar. default: 0.0.

The value used for positions outside the range.

output: None or af.Array

Optional preallocated output array. If it is a sub-array of an existing af_array,only the corresponding portion of the af_array will be overwritten

Returns

output: af.Array

Values calculated at interpolation points.

arrayfire.signal.convolve(signal,kernel,conv_mode=<CONV_MODE.DEFAULT:0>,conv_domain=<CONV_DOMAIN.AUTO:0>)[source]¶

Non batched Convolution.

This function performs n-dimensional convolution based on input dimensionality.

Parameters

signal: af.Array

• An n-dimensional array.

kernel: af.Array

• A n-dimensional kernel.

conv_mode: optional: af.CONV_MODE. default: af.CONV_MODE.DEFAULT.

• Specifies if the output does full convolution (af.CONV_MODE.EXPAND) ormaintains the same size as input (af.CONV_MODE.DEFAULT).

conv_domain: optional: af.CONV_DOMAIN. default: af.CONV_DOMAIN.AUTO.

• Specifies the domain in which convolution is performed.

• af.CONV_DOMAIN.SPATIAL: Performs convolution in spatial domain.

• af.CONV_DOMAIN.FREQ: Performs convolution in frequency domain.

• af.CONV_DOMAIN.AUTO: Switches between spatial and frequency based on input size.

Returns

output: af.Array

• Output of n-dimensional convolution.

arrayfire.signal.convolve1(signal,kernel,conv_mode=<CONV_MODE.DEFAULT:0>,conv_domain=<CONV_DOMAIN.AUTO:0>)[source]¶

Convolution: 1D

Parameters

signal: af.Array

• A 1 dimensional signal or batch of 1 dimensional signals.

kernel: af.Array

• A 1 dimensional kernel or batch of 1 dimensional kernels.

conv_mode: optional: af.CONV_MODE. default: af.CONV_MODE.DEFAULT.

• Specifies if the output does full convolution (af.CONV_MODE.EXPAND) ormaintains the same size as input (af.CONV_MODE.DEFAULT).

conv_domain: optional: af.CONV_DOMAIN. default: af.CONV_DOMAIN.AUTO.

• Specifies the domain in which convolution is performed.

• af.CONV_DOMAIN.SPATIAL: Performs convolution in spatial domain.

• af.CONV_DOMAIN.FREQ: Performs convolution in frequency domain.

• af.CONV_DOMAIN.AUTO: Switches between spatial and frequency based on input size.

Returns

output: af.Array

• Output of 1D convolution.

arrayfire.signal.convolve2(signal,kernel,conv_mode=<CONV_MODE.DEFAULT:0>,conv_domain=<CONV_DOMAIN.AUTO:0>)[source]¶

Convolution: 2D

Parameters

signal: af.Array

• A 2 dimensional signal or batch of 2 dimensional signals.

kernel: af.Array

• A 2 dimensional kernel or batch of 2 dimensional kernels.

conv_mode: optional: af.CONV_MODE. default: af.CONV_MODE.DEFAULT.

• Specifies if the output does full convolution (af.CONV_MODE.EXPAND) ormaintains the same size as input (af.CONV_MODE.DEFAULT).

conv_domain: optional: af.CONV_DOMAIN. default: af.CONV_DOMAIN.AUTO.

• Specifies the domain in which convolution is performed.

• af.CONV_DOMAIN.SPATIAL: Performs convolution in spatial domain.

• af.CONV_DOMAIN.FREQ: Performs convolution in frequency domain.

• af.CONV_DOMAIN.AUTO: Switches between spatial and frequency based on input size.

Returns

output: af.Array

• Output of 2D convolution.

arrayfire.signal.convolve2NN(signal,kernel,stride=(1,1),padding=(0,0),dilation=(1,1))[source]¶

This version of convolution is consistent with the machine learningformulation that will spatially convolve a filter on 2-dimensions against asignal. Multiple signals and filters can be batched against each other.Furthermore, the signals and filters can be multi-dimensional however theirdimensions must match.

Example:

Signals with dimensions: d0 x d1 x d2 x NsFilters with dimensions: d0 x d1 x d2 x Nf

Resulting Convolution: d0 x d1 x Nf x Ns

Parameters

signal: af.Array

• A 2 dimensional signal or batch of 2 dimensional signals.

kernel: af.Array

• A 2 dimensional kernel or batch of 2 dimensional kernels.

stride: tuple of ints. default: (1, 1).

• Specifies how much to stride along each dimension

padding: tuple of ints. default: (0, 0).

• Specifies signal padding along each dimension

dilation: tuple of ints. default: (1, 1).

• Specifies how much to dilate kernel along each dimension before convolution

Returns

output: af.Array

• Convolved 2D array.

arrayfire.signal.convolve2_separable(col_kernel,row_kernel,signal,conv_mode=<CONV_MODE.DEFAULT:0>)[source]¶

Convolution: 2D separable convolution

Parameters

col_kernel: af.Array

• A column vector to be applied along each column ofsignal

row_kernel: af.Array

• A row vector to be applied along each row ofsignal

signal: af.Array

• A 2 dimensional signal or batch of 2 dimensional signals.

conv_mode: optional: af.CONV_MODE. default: af.CONV_MODE.DEFAULT.

• Specifies if the output does full convolution (af.CONV_MODE.EXPAND) ormaintains the same size as input (af.CONV_MODE.DEFAULT).

Returns

——–

output: af.Array

• Output of 2D sepearable convolution.

arrayfire.signal.convolve3(signal,kernel,conv_mode=<CONV_MODE.DEFAULT:0>,conv_domain=<CONV_DOMAIN.AUTO:0>)[source]¶

Convolution: 3D

Parameters

signal: af.Array

• A 3 dimensional signal or batch of 3 dimensional signals.

kernel: af.Array

• A 3 dimensional kernel or batch of 3 dimensional kernels.

conv_mode: optional: af.CONV_MODE. default: af.CONV_MODE.DEFAULT.

• Specifies if the output does full convolution (af.CONV_MODE.EXPAND) ormaintains the same size as input (af.CONV_MODE.DEFAULT).

conv_domain: optional: af.CONV_DOMAIN. default: af.CONV_DOMAIN.AUTO.

• Specifies the domain in which convolution is performed.

• af.CONV_DOMAIN.SPATIAL: Performs convolution in spatial domain.

• af.CONV_DOMAIN.FREQ: Performs convolution in frequency domain.

• af.CONV_DOMAIN.AUTO: Switches between spatial and frequency based on input size.

Returns

output: af.Array

• Output of 3D convolution.

arrayfire.signal.dft(signal,odims=(None,None,None,None),scale=None)[source]¶

Non batched Fourier transform.

This function performs n-dimensional fourier transform depending on the input dimensions.

Parameters

signal: af.Array

• A multi dimensional arrayfire array.

odims: optional: tuple of ints. default: (None, None, None, None).

• If None, calculated to besignal.dims()

scale: optional: scalar. default: None.

• Scale factor for the fourier transform.

• If none, calculated to be 1.0.

Returns

output: af.Array

• A complex array that is the ouput of n-dimensional fourier transform.

arrayfire.signal.fft(signal,dim0=None,scale=None)[source]¶

Fast Fourier Transform: 1D

Parameters

signal: af.Array

A 1 dimensional signal or a batch of 1 dimensional signals.

dim0: optional: int. default: None.

• Specifies the size of the output.

• If None, dim0 is calculated to be the first dimension ofsignal.

scale: optional: scalar. default: None.

• Specifies the scaling factor.

• If None, scale is set to 1.

Returns

output: af.Array

A complex af.Array containing the full output of the fft.

arrayfire.signal.fft2(signal,dim0=None,dim1=None,scale=None)[source]¶

Fast Fourier Transform: 2D

Parameters

signal: af.Array

A 2 dimensional signal or a batch of 2 dimensional signals.

dim0: optional: int. default: None.

• Specifies the size of the output.

• If None, dim0 is calculated to be the first dimension ofsignal.

dim1: optional: int. default: None.

• Specifies the size of the output.

• If None, dim1 is calculated to be the second dimension ofsignal.

scale: optional: scalar. default: None.

• Specifies the scaling factor.

• If None, scale is set to 1.

Returns

output: af.Array

A complex af.Array containing the full output of the fft.

arrayfire.signal.fft2_c2r(signal,is_odd=False,scale=None)[source]¶

Real to Complex Fast Fourier Transform: 2D

Parameters

signal: af.Array

A 2 dimensional signal or a batch of 2 dimensional signals.

is_odd: optional: Boolean. default: False.

• Specifies if the first dimension of output should be even or odd.

scale: optional: scalar. default: None.

• Specifies the scaling factor.

• If None, scale is set to 1 / (signal.dims()[0] * signal.dims()[1]).

Returns

output: af.Array

A real af.Array containing the full output of the fft.

arrayfire.signal.fft2_inplace(signal,scale=None)[source]¶

In-place Fast Fourier Transform: 2D

Parameters

signal: af.Array

A 2 dimensional signal or a batch of 2 dimensional signals.

scale: optional: scalar. default: None.

• Specifies the scaling factor.

• If None, scale is set to 1.

arrayfire.signal.fft2_r2c(signal,dim0=None,dim1=None,scale=None)[source]¶

Real to Complex Fast Fourier Transform: 2D

Parameters

signal: af.Array

A 2 dimensional signal or a batch of 2 dimensional signals.

dim0: optional: int. default: None.

• Specifies the size of the output.

• If None, dim0 is calculated to be the first dimension ofsignal.

dim1: optional: int. default: None.

• Specifies the size of the output.

• If None, dim1 is calculated to be the second dimension ofsignal.

scale: optional: scalar. default: None.

• Specifies the scaling factor.

• If None, scale is set to 1.

Returns

output: af.Array

A complex af.Array containing the non-redundant parts of the full FFT.

arrayfire.signal.fft3(signal,dim0=None,dim1=None,dim2=None,scale=None)[source]¶

Fast Fourier Transform: 3D

Parameters

signal: af.Array

A 3 dimensional signal or a batch of 3 dimensional signals.

dim0: optional: int. default: None.

• Specifies the size of the output.

• If None, dim0 is calculated to be the first dimension ofsignal.

dim1: optional: int. default: None.

• Specifies the size of the output.

• If None, dim1 is calculated to be the second dimension ofsignal.

dim2: optional: int. default: None.

• Specifies the size of the output.

• If None, dim2 is calculated to be the third dimension ofsignal.

scale: optional: scalar. default: None.

• Specifies the scaling factor.

• If None, scale is set to 1.

Returns

output: af.Array

A complex af.Array containing the full output of the fft.

arrayfire.signal.fft3_c2r(signal,is_odd=False,scale=None)[source]¶

Real to Complex Fast Fourier Transform: 3D

Parameters

signal: af.Array

A 3 dimensional signal or a batch of 3 dimensional signals.

is_odd: optional: Boolean. default: False.

• Specifies if the first dimension of output should be even or odd.

scale: optional: scalar. default: None.

• Specifies the scaling factor.

• If None, scale is set to 1 / (signal.dims()[0] * signal.dims()[1] * signal.dims()[2]).

Returns

output: af.Array

A real af.Array containing the full output of the fft.

arrayfire.signal.fft3_inplace(signal,scale=None)[source]¶

In-place Fast Fourier Transform: 3D

Parameters

signal: af.Array

A 3 dimensional signal or a batch of 3 dimensional signals.

scale: optional: scalar. default: None.

• Specifies the scaling factor.

• If None, scale is set to 1.

arrayfire.signal.fft3_r2c(signal,dim0=None,dim1=None,dim2=None,scale=None)[source]¶

Real to Complex Fast Fourier Transform: 3D

Parameters

signal: af.Array

A 3 dimensional signal or a batch of 3 dimensional signals.

dim0: optional: int. default: None.

• Specifies the size of the output.

• If None, dim0 is calculated to be the first dimension ofsignal.

dim1: optional: int. default: None.

• Specifies the size of the output.

• If None, dim1 is calculated to be the second dimension ofsignal.

dim2: optional: int. default: None.

• Specifies the size of the output.

• If None, dim2 is calculated to be the third dimension ofsignal.

scale: optional: scalar. default: None.

• Specifies the scaling factor.

• If None, scale is set to 1.

Returns

output: af.Array

A complex af.Array containing the non-redundant parts of the full FFT.

arrayfire.signal.fft_c2r(signal,is_odd=False,scale=None)[source]¶

Real to Complex Fast Fourier Transform: 1D

Parameters

signal: af.Array

A 1 dimensional signal or a batch of 1 dimensional signals.

is_odd: optional: Boolean. default: False.

• Specifies if the first dimension of output should be even or odd.

scale: optional: scalar. default: None.

• Specifies the scaling factor.

• If None, scale is set to 1 / (signal.dims()[0]).

Returns

output: af.Array

A real af.Array containing the full output of the fft.

arrayfire.signal.fft_convolve(signal,kernel,conv_mode=<CONV_MODE.DEFAULT:0>)[source]¶

Non batched FFT Convolution.

This function performs n-dimensional convolution based on input dimensionality.

Parameters

signal: af.Array

• An n-dimensional array.

kernel: af.Array

• A n-dimensional kernel.

conv_mode: optional: af.CONV_MODE. default: af.CONV_MODE.DEFAULT.

• Specifies if the output does full convolution (af.CONV_MODE.EXPAND) ormaintains the same size as input (af.CONV_MODE.DEFAULT).

Returns

output: af.Array

• Output of n-dimensional convolution.

arrayfire.signal.fft_convolve1(signal,kernel,conv_mode=<CONV_MODE.DEFAULT:0>)[source]¶

FFT based Convolution: 1D

Parameters

signal: af.Array

• A 1 dimensional signal or batch of 1 dimensional signals.

kernel: af.Array

• A 1 dimensional kernel or batch of 1 dimensional kernels.

conv_mode: optional: af.CONV_MODE. default: af.CONV_MODE.DEFAULT.

• Specifies if the output does full convolution (af.CONV_MODE.EXPAND) ormaintains the same size as input (af.CONV_MODE.DEFAULT).

Returns

output: af.Array

• Output of 1D convolution.

arrayfire.signal.fft_convolve2(signal,kernel,conv_mode=<CONV_MODE.DEFAULT:0>)[source]¶

FFT based Convolution: 2D

Parameters

signal: af.Array

• A 2 dimensional signal or batch of 2 dimensional signals.

kernel: af.Array

• A 2 dimensional kernel or batch of 2 dimensional kernels.

conv_mode: optional: af.CONV_MODE. default: af.CONV_MODE.DEFAULT.

• Specifies if the output does full convolution (af.CONV_MODE.EXPAND) ormaintains the same size as input (af.CONV_MODE.DEFAULT).

Returns

output: af.Array

• Output of 2D convolution.

arrayfire.signal.fft_convolve3(signal,kernel,conv_mode=<CONV_MODE.DEFAULT:0>)[source]¶

FFT based Convolution: 3D

Parameters

signal: af.Array

• A 3 dimensional signal or batch of 3 dimensional signals.

kernel: af.Array

• A 3 dimensional kernel or batch of 3 dimensional kernels.

conv_mode: optional: af.CONV_MODE. default: af.CONV_MODE.DEFAULT.

• Specifies if the output does full convolution (af.CONV_MODE.EXPAND) ormaintains the same size as input (af.CONV_MODE.DEFAULT).

Returns

output: af.Array

• Output of 3D convolution.

arrayfire.signal.fft_inplace(signal,scale=None)[source]¶

In-place Fast Fourier Transform: 1D

Parameters

signal: af.Array

A 1 dimensional signal or a batch of 1 dimensional signals.

scale: optional: scalar. default: None.

• Specifies the scaling factor.

• If None, scale is set to 1.

arrayfire.signal.fft_r2c(signal,dim0=None,scale=None)[source]¶

Real to Complex Fast Fourier Transform: 1D

Parameters

signal: af.Array

A 1 dimensional signal or a batch of 1 dimensional signals.

dim0: optional: int. default: None.

• Specifies the size of the output.

• If None, dim0 is calculated to be the first dimension ofsignal.

scale: optional: scalar. default: None.

• Specifies the scaling factor.

• If None, scale is set to 1.

Returns

output: af.Array

A complex af.Array containing the non-redundant parts of the full FFT.

arrayfire.signal.fir(B,X)[source]¶

Finite impulse response filter.

Parameters

Baf.Array

A 1 dimensional array containing the coefficients of the filter.

Xaf.Array

A 1 dimensional array containing the signal.

Returns

Yaf.Array

The output of the filter.

arrayfire.signal.idft(signal,scale=None,odims=(None,None,None,None))[source]¶

Non batched Inverse Fourier transform.

This function performs n-dimensional inverse fourier transform depending on the input dimensions.

Parameters

signal: af.Array

• A multi dimensional arrayfire array.

odims: optional: tuple of ints. default: (None, None, None, None).

• If None, calculated to besignal.dims()

scale: optional: scalar. default: None.

• Scale factor for the fourier transform.

• If none, calculated to be 1.0 / signal.elements()

Returns

output: af.Array

• A complex array that is the ouput of n-dimensional inverse fourier transform.

arrayfire.signal.ifft(signal,dim0=None,scale=None)[source]¶

Inverse Fast Fourier Transform: 1D

Parameters

signal: af.Array

A 1 dimensional signal or a batch of 1 dimensional signals.

dim0: optional: int. default: None.

• Specifies the size of the output.

• If None, dim0 is calculated to be the first dimension ofsignal.

scale: optional: scalar. default: None.

• Specifies the scaling factor.

• If None, scale is set to 1.0 / (dim0)

Returns

output: af.Array

A complex af.Array containing the full output of the inverse fft.

arrayfire.signal.ifft2(signal,dim0=None,dim1=None,scale=None)[source]¶

Inverse Fast Fourier Transform: 2D

Parameters

signal: af.Array

A 2 dimensional signal or a batch of 2 dimensional signals.

dim0: optional: int. default: None.

• Specifies the size of the output.

• If None, dim0 is calculated to be the first dimension ofsignal.

dim1: optional: int. default: None.

• Specifies the size of the output.

• If None, dim1 is calculated to be the second dimension ofsignal.

scale: optional: scalar. default: None.

• Specifies the scaling factor.

• If None, scale is set to 1.0 / (dim0 * dim1)

Returns

output: af.Array

A complex af.Array containing the full output of the inverse fft.

arrayfire.signal.ifft2_inplace(signal,scale=None)[source]¶

Inverse In-place Fast Fourier Transform: 2D

Parameters

signal: af.Array

A 2 dimensional signal or a batch of 2 dimensional signals.

scale: optional: scalar. default: None.

• Specifies the scaling factor.

• If None, scale is set to 1.0 / (signal.dims()[0] * signal.dims()[1])

arrayfire.signal.ifft3(signal,dim0=None,dim1=None,dim2=None,scale=None)[source]¶

Inverse Fast Fourier Transform: 3D

Parameters

signal: af.Array

A 3 dimensional signal or a batch of 3 dimensional signals.

dim0: optional: int. default: None.

• Specifies the size of the output.

• If None, dim0 is calculated to be the first dimension ofsignal.

dim1: optional: int. default: None.

• Specifies the size of the output.

• If None, dim1 is calculated to be the second dimension ofsignal.

dim2: optional: int. default: None.

• Specifies the size of the output.

• If None, dim2 is calculated to be the third dimension ofsignal.

scale: optional: scalar. default: None.

• Specifies the scaling factor.

• If None, scale is set to 1.0 / (dim0 * dim1 * dim2).

Returns

output: af.Array

A complex af.Array containing the full output of the inverse fft.

arrayfire.signal.ifft3_inplace(signal,scale=None)[source]¶

Inverse In-place Fast Fourier Transform: 3D

Parameters

signal: af.Array

A 3 dimensional signal or a batch of 3 dimensional signals.

scale: optional: scalar. default: None.

• Specifies the scaling factor.

• If None, scale is set to 1.0 / (signal.dims()[0] * signal.dims()[1] * signal.dims()[2]).

arrayfire.signal.ifft_inplace(signal,scale=None)[source]¶

Inverse In-place Fast Fourier Transform: 1D

Parameters

signal: af.Array

A 1 dimensional signal or a batch of 1 dimensional signals.

scale: optional: scalar. default: None.

• Specifies the scaling factor.

• If None, scale is set to 1.0 / (signal.dims()[0])

arrayfire.signal.iir(B,A,X)[source]¶

Infinite impulse response filter.

Parameters

Baf.Array

A 1 dimensional array containing the feed forward coefficients of the filter.

Aaf.Array

A 1 dimensional array containing the feed back coefficients of the filter.

Xaf.Array

A 1 dimensional array containing the signal.

Returns

Yaf.Array

The output of the filter.

arrayfire.signal.medfilt(signal,w0=3,w1=3,edge_pad=<PAD.ZERO:0>)[source]¶

Apply median filter for the signal.

Parameters

signalaf.Array

• A 2 D arrayfire array representing a signal, or

• A multi dimensional array representing batch of signals.

w0optional: int. default: 3.

• The length of the filter along the first dimension.

w1optional: int. default: 3.

• The length of the filter along the second dimension.

edge_padoptional: af.PAD. default: af.PAD.ZERO

• Flag specifying how the median at the edge should be treated.

Returns

outputaf.Array

• The signal after median filter is applied.

arrayfire.signal.medfilt1(signal,length=3,edge_pad=<PAD.ZERO:0>)[source]¶

Apply median filter for the signal.

Parameters

signalaf.Array

• A 1 D arrayfire array representing a signal, or

• A multi dimensional array representing batch of signals.

lengthoptional: int. default: 3.

• The length of the filter.

edge_padoptional: af.PAD. default: af.PAD.ZERO

• Flag specifying how the median at the edge should be treated.

Returns

outputaf.Array

• The signal after median filter is applied.

arrayfire.signal.medfilt2(signal,w0=3,w1=3,edge_pad=<PAD.ZERO:0>)[source]¶

Apply median filter for the signal.

Parameters

signalaf.Array

• A 2 D arrayfire array representing a signal, or

• A multi dimensional array representing batch of signals.

w0optional: int. default: 3.

• The length of the filter along the first dimension.

w1optional: int. default: 3.

• The length of the filter along the second dimension.

edge_padoptional: af.PAD. default: af.PAD.ZERO

• Flag specifying how the median at the edge should be treated.

Returns

outputaf.Array

• The signal after median filter is applied.

arrayfire.signal.set_fft_plan_cache_size(cache_size)[source]¶

Sets plan cache size.

Parameters

cache_sizescalar

the number of plans that shall be cached