Python API¶
This section includes information for using the pure Python API of bob.sp
.

bob.sp.
extrapolate_zero
(src, dst)[source]¶ Extrapolates the values in
src
todst
with zeros.Input
src
(anddst
) arrays can be 1 or 2dimensional. For more details, read the help forextrapolate()
.Parameters:
 src
 (array) A 1 or 2D array that is going to be extrapolated
 dst
 (array) A preallocated array, with the same number of dimensions
as in
src
, where the extrapolation results will be placed.
Returns
None
, raises in case of errors.

bob.sp.
extrapolate_mirror
(src, dst)[source]¶ Extrapolates the values in
src
todst
, mirroringsrc
.Input
src
(anddst
) arrays can be 1 or 2dimensional. For more details, read the help forextrapolate()
.Parameters:
 src
 (array) A 1 or 2D array that is going to be extrapolated
 dst
 (array) A preallocated array, with the same number of dimensions
as in
src
, where the extrapolation results will be placed.
Returns
None
, raises in case of errors.

bob.sp.
extrapolate_nearest
(src, dst)[source]¶ Extrapolates the values in
src
todst
, with nearest values.Input
src
(anddst
) arrays can be 1 or 2dimensional. For more details, read the help forextrapolate()
.Parameters:
 src
 (array) A 1 or 2D array that is going to be extrapolated
 dst
 (array) A preallocated array, with the same number of dimensions
as in
src
, where the extrapolation results will be placed.
Returns
None
, raises in case of errors.

bob.sp.
extrapolate_constant
(src, dst, constant)[source]¶ Extrapolates the values in
src
todst
, with a constant value.Input
src
(anddst
) arrays can be 1 or 2dimensional. For more details, read the help forextrapolate()
.Parameters:
 src
 (array) A 1 or 2D array that is going to be extrapolated
 dst
 (array) A preallocated array, with the same number of dimensions
as in
src
, where the extrapolation results will be placed.  constant
 (scalar) A scalar with matching type of
src
anddst
, containing the value that will be used to extrapolatesrc
intodst
.
Returns
None
, raises in case of errors.

bob.sp.
extrapolate_circular
(src, dst)[source]¶ Extrapolates the values in
src
todst
, using circular extrapolation.Input
src
(anddst
) arrays can be 1 or 2dimensional. For more details, read the help forextrapolate()
.Parameters:
 src
 (array) A 1 or 2D array that is going to be extrapolated
 dst
 (array) A preallocated array, with the same number of dimensions
as in
src
, where the extrapolation results will be placed.
Returns
None
, raises in case of errors.

class
bob.sp.
BorderType
¶ Bases:
object
BorderType (C++ enumeration)  cannot be instantiated from Python
Use of the values available in this class as input for
BorderType
when required: Zero
 Constant
 NearestNeighbour
 Circular
 Mirror
A dictionary containing all names and values available for this enumeration is available through the attribute
entries
.
Circular
= 3¶

Constant
= 1¶

Mirror
= 4¶

NearestNeighbour
= 2¶

Zero
= 0¶

entries
= {'Mirror': 4, 'Zero': 0, 'Circular': 3, 'Constant': 1, 'NearestNeighbour': 2}¶

class
bob.sp.
DCT1D
(shape) → new DCT1D operator¶ Bases:
object
Calculates the direct DCT of a 1D array/signal. Input and output arrays are 1D NumPy arrays of type
float64
.
length
¶ The length of the output vector

shape
¶ A tuple that represents the size of the output vector


class
bob.sp.
DCT2D
(shape) → new DCT2D operator¶ Bases:
object
Calculates the direct DCT of a 2D array/signal. Input and output arrays are 2D NumPy arrays of type
float64
.
height
¶ The height of the output vector

shape
¶ A tuple that represents the size of the output vector

width
¶ The width of the output vector


class
bob.sp.
FFT1D
(shape) → new FFT1D operator¶ Bases:
object
Calculates the direct FFT of a 1D array/signal. Input and output arrays are 1D NumPy arrays of type
complex128
.
length
¶ The length of the output vector

shape
¶ A tuple that represents the size of the output vector


class
bob.sp.
FFT2D
(shape) → new FFT2D operator¶ Bases:
object
Calculates the direct FFT of a 2D array/signal. Input and output arrays are 2D NumPy arrays of type
complex128
.
height
¶ The height of the output vector

shape
¶ A tuple that represents the size of the output vector

width
¶ The width of the output vector


class
bob.sp.
IDCT1D
(shape) → new IDCT1D operator¶ Bases:
object
Calculates the inverse DCT of a 1D array/signal. Input and output arrays are 1D NumPy arrays of type
float64
.
length
¶ The length of the output vector

shape
¶ A tuple that represents the size of the output vector


class
bob.sp.
IDCT2D
(shape) → new IDCT2D operator¶ Bases:
object
Calculates the inverse DCT of a 2D array/signal. Input and output arrays are 2D NumPy arrays of type
float64
.
height
¶ The height of the output vector

shape
¶ A tuple that represents the size of the output vector

width
¶ The width of the output vector


class
bob.sp.
IFFT1D
(shape) → new IFFT1D operator¶ Bases:
object
Calculates the inverse FFT of a 1D array/signal. Input and output arrays are 1D NumPy arrays of type
complex128
.
length
¶ The length of the output vector

shape
¶ A tuple that represents the size of the output vector


class
bob.sp.
IFFT2D
(shape) → new IFFT2D operator¶ Bases:
object
Calculates the inverse FFT of a 2D array/signal. Input and output arrays are 2D NumPy arrays of type
complex128
.
height
¶ The height of the output vector

shape
¶ A tuple that represents the size of the output vector

width
¶ The width of the output vector


class
bob.sp.
Quantization
(dtype[, rounding=False[, num_levels=1[, min_level=None[, max_level=None]]]])¶ Bases:
object
Quantization(quantization_table) Quantization(other)
Functor to quantize 1D or 2D signals into different number of levels. At the moment, only
uint8
anduint16
data types are supported. The output array returned by this functor will always have auint32
data type.Parameters:
 dtype
 (numpy.dtype) The data type of arrays that are going to be input
by this functor. Currently supported values are
uint8
anduint16
.  rounding
 (bool) If set to
True
(defaults toFalse
), performs Matlablike uniform quantization with rounding (see http://www.mathworks.com/matlabcentral/newsreader/view_thread/275291).  num_levels
 (int) the number of quantization levels. The default is the total
number of discrete values permitted by the data type. For example,
uint8
allows for 256 levels.  min_level
 (scalar) Input values smaller than or equal to this value are scaled to this value prior to quantization. As a result, they will be scaled in the lowest quantization level. The data type of this scalar should be coercible to the datatype of the input.
 max_level
 (scalar) Input values higher than this value are scaled to this value prior to quantization. As a result, they will be scaled in the highest qunatization level. The data type of this scalar should be coercible to the datatype of the input.
 quantization_table
 (array) A 1dimensional array matching the data type of
input
containing userspecified thresholds for the quantization. If Each element corresponds to the lower boundary of the particular quantization level. Eg.array([ 0, 5, 10])
means quantization in 3 levels. Input values in the range will be quantized to level 0, input values in the range will be quantized to level 1 and input values in the range will be quantized to level 2.  other
 (Quantization) You can also initialize a Quantization object by passing another Quantization object as constructor parameter. This will create a deepcopy of this Quantization object.
Once this object has been created, it can be used through its
()
operator, by passinginput
andoutput
parameters: input
 (array) a 1 or 2dimensional
uint8
oruint16
array of any size.  output
 (array) The array where to store the output. This array should
have the same dimensions of the input array, but have data type
uint32
. If this array is not provided, a new one is allocated internally and returned.

dtype
¶ (numpy.dtype) The data type of arrays that are going to be input by this functor. Currently supported values are
uint8
anduint16
.

max_level
¶ (scalar) Input values higher than this value are scaled to this value prior to quantization. As a result, they will be scaled in the highest qunatization level. The data type of this scalar should be coercible to the datatype of the input.

min_level
¶ Input values smaller than or equal to this value are scaled to this value prior to quantization. As a result, they will be scaled in the lowest quantization level. The data type of this scalar should be coercible to the datatype of the input.

num_levels
¶ (int) the number of quantization levels. The default is the total number of discrete values permitted by the data type. For example,
uint8
allows for 256 levels.

quantization_level
()¶ Calculates the quantization level for a single input value, given the current threshold table.

quantization_table
¶ (array) A 1dimensional array matching the data type of
input
containing userspecified thresholds for the quantization. If Each element corresponds to the lower boundary of the particular quantization level. Eg.array([ 0, 5, 10])
means quantization in 3 levels. Input values in the range will be quantized to level 0, input values in the range will be quantized to level 1 and input values in the range will be quantized to level 2.

quantization_type
¶ (str) Possible values of this parameter –
 uniform
 uniform quantization of the input signal within the range
between
min_level
andmax_level
 uniform_rounding
 same as
uniform
above, but implemented in a similar way to Matlab quantization (see http://www.mathworks.com/matlabcentral/newsreader/view_thread/275291);  user_spec
 quantization according to userspecified quantization table of thresholds.

bob.sp.
dct
(src[, dst]) → array¶ Computes the direct Discrete Cosine Transform of a 1D or 2D array/signal of type
float64
. Allocates a new output array ifdst
is not provided. If it is, then it must be of the same type and shape assrc
.Parameters:
 src
 [array] A 1 or 2dimensional array of type
float64
in which the DCT operation will be performed.  dst
 [array, optional] A 1 or 2dimensional array of type
float64
and matching dimensions tosrc
in which the result of the operation will be stored.
Returns a 1 or 2dimensional array, of the same dimension as
src
, of typefloat64
, containing the DCT of the input signal.

bob.sp.
extrapolate
(src, dst[[, border=bob.sp.BorderType.Zero], value=0.]) → None¶ Extrapolates values in the given array using the specified border type. Works for 1 or 2D input arrays. The parameter
value
is only used if the border type is set tobob.sp.BorderType.Constant
. It is, by default, set to0.
, or the equivalent on the datatype passed as input. For example,False
, if the input is boolean and 0+0j, if it is complex.

bob.sp.
fft
(src[, dst]) → array¶ Computes the direct Fast Fourier Transform of a 1D or 2D array/signal of type
complex128
. Allocates a new output array ifdst
is not provided. If it is, then it must be of the same type and shape assrc
.Parameters:
 src
 [array] A 1 or 2dimensional array of type
complex128
in which the FFT operation will be performed.  dst
 [array, optional] A 1 or 2dimensional array of type
complex128
and matching dimensions tosrc
in which the result of the operation will be stored.
Returns a 1 or 2dimensional array, of the same dimension as
src
, of typecomplex128
, containing the FFT of the input signal.

bob.sp.
fftshift
(src[, dst]) → array¶ If a 1D complex128 array is passed, inverses the two halves of that array and returns the result as a new array. If a 2D
complex128
array is passed, swaps the four quadrants of the array and returns the result as a new array.Parameters:
src [array] A 1 or 2dimensional array of type
complex128
with the signal to be shifted.dst [array, optional] A 1 or 2dimensional array of type
complex128
and matching dimensions tosrc
in which the result of the operation will be stored.Returns a 1 or 2dimensional array, of the same dimension as
src
, of typecomplex128
, containing the shifted version of theinput.

bob.sp.
idct
(src[, dst]) → array¶ Computes the inverse Discrete Cosinte Transform of a 1D or 2D transform of type
float64
. Allocates a new output array ifdst
is not provided. If it is, then it must be of the same type and shape assrc
.Parameters:
 src
 [array] A 1 or 2dimensional array of type
float64
in which the inverse DCT operation will be performed.  dst
 [array, optional] A 1 or 2dimensional array of type
float64
and matching dimensions tosrc
in which the result of the operation will be stored.
Returns a 1 or 2dimensional array, of the same dimension as
src
, of typefloat64
, containing the inverse DCT of the input transform.

bob.sp.
ifft
(src[, dst]) → array¶ Computes the inverse Fast Fourier Transform of a 1D or 2D transform of type
complex128
. Allocates a new output array ifdst
is not provided. If it is, then it must be of the same type and shape assrc
.Parameters:
 src
 [array] A 1 or 2dimensional array of type
complex128
in which the inverse FFT operation will be performed.  dst
 [array, optional] A 1 or 2dimensional array of type
complex128
and matching dimensions tosrc
in which the result of the operation will be stored.
Returns a 1 or 2dimensional array, of the same dimension as
src
, of typecomplex128
, containing the inverse FFT of the input transform.

bob.sp.
ifftshift
(src[, dst]) → array¶ This method undoes what
fftshift()
does. It accepts 1 or 2dimensional arrays of typecomplex128
.Parameters:
src [array] A 1 or 2dimensional array of type
complex128
with the signal to be shifted.dst [array, optional] A 1 or 2dimensional array of type
complex128
and matching dimensions tosrc
in which the result of the operation will be stored.Returns a 1 or 2dimensional array, of the same dimension as
src
, of typecomplex128
, containing the shifted version of theinput.