Crate basic_dsp_vector

Basic digital signal processing (DSP) operations

Digital signal processing based on real or complex vectors in time or frequency domain. Vectors are expected to typically have a size which is at least in the order of magnitude of a couple of thousand elements. This crate tries to balance between a clear API and performance in terms of processing speed. This project started as small pet project to learn more about DSP, CPU architecture and Rust. Since learning involves making mistakes, don't expect things to be flawless or even close to flawless.

This library isn't suited - from my point of view - for game programming. If you are looking for vector types to do 2D or 3D graphics calculations then you unfortunately have to continue with your search. However there seem to be a lot of suitable crates on crates.io for you.

The vector types don't distinguish between 1xN or Nx1. This is a difference to other conventions such as in MATLAB or GNU Octave. The reason for this decision is that it seems to be more practical to ignore the shape of the vector.

Right now the library uses pretty aggressive parallelization. So this means that it will keep all CPU cores busy even if the performance gain is minimal e.g. because the multi core overhead is nearly as large as the performance boost of multiple cores. In future there will be likely an option which tells the library how it should balance between processing time and CPU utilization. The library also avoids to allocate and free memory so it allocates all of the required temporary memory when a new vector is constructed. Therefore the library is likely not suitable for devices which are tight on memory. On normal desktop computers there is usually plenty of memory available so that the optimization focus is on decreasing the processing time for every (common) operation and to spent little time with memory allocations.

Modules

combined_ops	This module allows to combine certain operations into one operation. Since one many machines the speed of many DSP operations is limited by the memory bus speed this approach may result in better register and cache usage and thus decrease the pressure on the memory bus. As with all performance hints remember rule number 1: Benchmark your code. This is especially true at this very early state of the library.
conv_types	Types around a convolution, see also https://en.wikipedia.org/wiki/Convolution.
window_functions	This mod contains a definition for window functions and provides implementations for a few standard windows. See the WindowFunction type for more information.

Structs

ComplexData	Marker for types containing complex data.
DspVec	A 1xN (one times N elements) or Nx1 data vector as used for most digital signal processing (DSP) operations. All data vector operations consume the vector they operate on and return a new vector. A consumed vector must not be accessed again.
FrequencyData	Marker for types containing frequency data.
MultiCoreSettings	Holds parameters which specify how multiple cores are used to execute an operation.
RealData	Marker for types containing real data.
RealOrComplexData	Marker for types containing real or complex data.
SingleBuffer	A buffer which stores a single vector and never shrinks.
Statistics	Statistics about numeric data
TimeData	Marker for types containing time data.
TimeOrFrequencyData	Marker for types containing time or frequency data.
TypeMetaData	Holds meta data about a type.

Enums

DataDomain	The domain of a data vector
ErrorReason	Enumeration of all error reasons
PaddingOption	An option which defines how a vector should be padded

Traits

Buffer	A buffer which can be used by other types. Types will call buffers to create new arrays. A buffer may can implement any buffering strategy.
ComplexIndex	Like std::ops::Index but with a different method name so that it can be used to implement an additional range accessor for complex data.
ComplexIndexMut	Like std::ops::IndexMut but with a different method name so that it can be used to implement a additional range accessor for complex data.
ComplexNumberSpace	Trait for types containing complex data.
ComplexOps	Operations on complex types.
ComplexToRealGetterOps	Defines getters to get real data from complex types.
ComplexToRealSetterOps	Defines setters to create complex data from real data.
ComplexToRealTransformsOps	Defines transformations from complex to real number space.
ComplexToRealTransformsOpsBuffered	Defines transformations from complex to real number space.
Convolution	Provides a convolution operations.
ConvolutionOps	Provides a convolution operation for types which at some point are slice based.
CrossCorrelationArgumentOps	Cross-correlation of data vectors. See also https://en.wikipedia.org/wiki/Cross-correlation
CrossCorrelationOps	A trait to calculate the cross correlation.
DiffSumOps	A trait to calculate the diff (1st derivative in a discrete number space) or cumulative sum (integral in a discrete number space).
Domain	Domain (time or frequency) information.
DotProductOps	An operation which multiplies each vector element with a constant
ElementaryOps	Elementary algebra on types: addition, subtraction, multiplication and division
ElementaryWrapAroundOps	Elementary algebra on types where the argument might contain less data points than self.
FrequencyDomain	Trait for types containing frequency domain data.
FrequencyDomainOperations	Defines all operations which are valid on DataVecs containing frequency domain data.
FrequencyMultiplication	Provides a frequency response multiplication operations.
FrequencyToTimeDomainOperations	Defines all operations which are valid on DataVecs containing frequency domain data.
FromVector	Retrieves the underlying storage from a vector.
GetMetaData	Gets the meta data of a type. This can be used to create a new type with the same meta data.
InsertZerosOps	A trait to insert zeros into the data at some specified positions.
InsertZerosOpsBuffered	A trait to insert zeros into the data at some specified positions. A buffer is used for types which can't be resized and/or to speed up the calculation.
InterleaveToVector	Conversion from two instances of a generic data type into a dsp vector with complex data.
InterpolationOps	Provides interpolation operations for real and complex data vectors.
MapAggregateOps	Operations which allow to iterate over the vector and to derive results.
MapInplaceNoArgsOps	Operations which allow to iterate over the vector change the vector contents.
MapInplaceOps	Operations which allow to iterate over the vector and to derive results or to change the vector.
MergeOps	Merges several pieces of equal size into one data chunk.
MetaData	A trait which provides information about number space and domain.
ModuloOps	Operations on real types.
NumberSpace	Number space (real or complex) information.
OffsetOps	An operation which adds a constant to each vector element
Owner	A marker trait which states the the type owns its storage.
PowerOps	Roots, powers, exponentials and logarithms.
PreciseDotProductOps	An operation which multiplies each vector element with a constant
PreciseStatisticsOps	Offers the same functionality as the StatisticsOps trait but the statistics are calculated in a more precise (and slower) way.
PreciseStats	A trait for statistics which allows to add new values in a way so that the numerical uncertainty has less impact on the final results.
PreciseSumOps	Offers the same functionality as the SumOps trait but the sums are calculated in a more precise (and slower) way.
RealInterpolationOps	Provides interpolation operations which are only applicable for real data vectors.
RealNumber	A real floating pointer number intended to abstract over f32 and f64.
RealNumberSpace	Trait for types containing real data.
RealOps	Operations on real types.
RealToComplexTransformsOps	Defines transformations from real to complex number space.
RealToComplexTransformsOpsBuffered	Defines transformations from real to complex number space.
RededicateForceOps	This trait allows to change a data type and performs the Conversion without any checks. RededicateOps provides the same functionality but performs runtime checks to avoid that data is interpreted the wrong way.
RededicateOps	This trait allows to change a data type. The operations will convert a type to a different one and set self.len() to zero. However self.allocated_len() will remain unchanged. The use case for this is to allow to reuse the memory of a vector for different operations.
RededicateToOps	This trait allows to change a data type. The operations will convert a type to a different one and set self.len() to zero. However self.allocated_len() will remain unchanged. The use case for this is to allow to reuse the memory of a vector for different operations.
ReorganizeDataOps	This trait allows to reorganize the data by changing positions of the individual elements.
ReorganizeDataOpsBuffered	[Deprecated] This trait allows to reorganize the data by changing positions of the individual elements. Deprecated since it requires a buffer which is never used since there would be no beneifit in using it.
Resize	A trait for storage types which are known to have the capability to increase their capacity.
ResizeOps	Operations to resize a data type.
ScaleOps	An operation which multiplies each vector element with a constant
SplitOps	Splits the data into several smaller pieces of equal size.
StatisticsOps	This trait offers operations to calculate statistics about the data in a type.
Stats	Operations on statistics.
SumOps	Offers operations to calculate the sum or the sum of squares.
SymmetricFrequencyToTimeDomainOperations	Defines all operations which are valid on DataVecs containing frequency domain data and the data is assumed to half of complex conjugate symmetric spectrum round 0 Hz where the 0 Hz element itself is real.
SymmetricTimeToFrequencyDomainOperations	Defines all operations which are valid on DataVecs containing real time domain data.
TimeDomain	Trait for types containing time domain data.
TimeDomainOperations	Defines all operations which are valid on DataVecs containing time domain data.
TimeToFrequencyDomainOperations	Defines all operations which are valid on DataVecs containing time domain data.
ToComplexResult	Specifies what the the result is if a type is transformed to complex numbers.
ToComplexVector	Conversion from a generic data type into a dsp vector with complex data.
ToDspVector	Conversion from a generic data type into a dsp vector which tracks its meta information (domain and number space) only at runtime. See ToRealVector and ToComplexVector for alternatives which track most of the meta data with the type system and therefore avoid runtime errors.
ToFreqResult	Specifies what the the result is if a type is transformed to frequency domain.
ToRealResult	Specifies what the the result is if a type is transformed to real numbers.
ToRealTimeResult	Specifies what the the result is if a type is transformed to real numbers in time domain.
ToRealVector	Conversion from a generic data type into a dsp vector with real data.
ToSimd	Associates a number type with a SIMD register type.
ToSlice	A trait to convert a type into a slice.
ToSliceMut	A trait to convert a type into a mutable slice.
ToTimeResult	Specifies what the the result is if a type is transformed to time domain.
TrigOps	Trigonometry methods.
Vector	A trait for vector types.
Zero	This trait is necessary so that we can define zero for types outside this crate. It calls the num::Zero trait where possible.

Type Definitions

ComplexFreqVec	A vector with complex numbers in frequency domain.
ComplexFreqVec32	A vector with complex numbers in frequency domain.
ComplexFreqVec64	A vector with complex numbers in frequency domain.
ComplexFreqVecSlice32	A vector with complex numbers in frequency domain.
ComplexFreqVecSlice64	A vector with complex numbers in frequency domain.
ComplexTimeVec	A vector with complex numbers in time domain.
ComplexTimeVec32	A vector with complex numbers in time domain.
ComplexTimeVec64	A vector with complex numbers in time domain.
ComplexTimeVecSlice32	A vector with complex numbers in time domain.
ComplexTimeVecSlice64	A vector with complex numbers in time domain.
GenDspVec	A vector with no information about number space or domain at compile time.
GenDspVec32	A vector with no information about number space or domain at compile time.
GenDspVec64	A vector with no information about number space or domain at compile time.
GenDspVecSlice32	A vector with no information about number space or domain at compile time.
GenDspVecSlice64	A vector with no information about number space or domain at compile time.
RealFreqVec	A vector with real numbers in frequency domain.
RealFreqVec32	A vector with real numbers in frequency domain.
RealFreqVec64	A vector with real numbers in frequency domain.
RealFreqVecSlice32	A vector with real numbers in frequency domain.
RealFreqVecSlice64	A vector with real numbers in frequency domain.
RealTimeVec	A vector with real numbers in time domain.
RealTimeVec32	A vector with real numbers in time domain.
RealTimeVec64	A vector with real numbers in time domain.
RealTimeVecSlice32	A vector with real numbers in time domain.
RealTimeVecSlice64	A vector with real numbers in time domain.
ScalarResult	Scalar result or a reason in case of an error.
TransRes	Result for operations which transform a type (most commonly the type is a vector). On success the transformed type is returned. On failure it contains an error reason and the original type with with invalid data which still can be used in order to avoid memory allocation.
VoidResult	Void/nothing in case of success or a reason in case of an error.