Struct basic_dsp_vector::DspVec[][src]

pub struct DspVec<S, T, N, D> where
    S: ToSlice<T>,
    T: RealNumber,
    N: NumberSpace,
    D: Domain
{ pub data: S, // some fields omitted }
Expand description

A 1xN (one times N elements) or Nx1 data vector as used for most digital signal processing (DSP) operations.

Vectors come in different flavors:

  1. Time or Frequency domain
  2. Real or Complex numbers
  3. 32bit or 64bit floating point numbers

The first two flavors define meta information about the vector and provide compile time information what operations are available with the given vector and how this will transform the vector. This makes sure that some invalid operations are already discovered at compile time. In case that this isn’t desired or the information about the vector isn’t known at compile time there are the generic DataVec32 and DataVec64 vectors available.

32bit and 64bit flavors trade performance and memory consumption against accuracy. 32bit vectors are roughly two times faster than 64bit vectors for most operations. But remember that you should benchmark first before you give away accuracy for performance unless however you are sure that 32bit accuracy is certainly good enough.

Fields

data: S

The underlying storage. self.len() should be called to find out how many elements in data contain valid data.

Implementations

Convolves a vector of vectors (in this lib also considered a matrix) with a vector of impulse responses and stores the result in target.

Indicates whether or not the operations on this vector have been successful. Consider using the statically typed vector versions so that this check doesn’t need to be performed.

Trait Implementations

Computes the principal value approximation of natural logarithm of every element in the vector. Read more

Calculates the natural exponential approximation for every vector element. Read more

Calculates the sine approximation of each element in radians. Read more

Calculates the cosine approximation of each element in radians Read more

Calculates the approximated logarithm to the given base for every vector element. Read more

Calculates the approximated exponential to the given base for every vector element. Read more

Raises every vector element to approximately a floating point power. Read more

Returns a copy of the value. Read more

Performs copy-assignment from source. Read more

The method for complex indexing

The method for complex indexing

The method for complex indexing

The method for complex indexing

The method for complex indexing

The method for complex indexing

The method for complex indexing

The method for complex indexing

The method for complex indexing

The method for complex indexing

Multiplies each vector element with exp(j*(a*idx*self.delta() + b)) where a and b are arguments and idx is the index of the data points in the vector ranging from 0 to self.points() - 1. j is the imaginary number and exp the exponential function. Read more

Calculates the complex conjugate of the vector. Read more

Copies all real elements into the given vector. Read more

Copies all imag elements into the given vector. Read more

Copies the absolute value or magnitude of all vector elements into the given target vector. Read more

Copies the absolute value squared or magnitude squared of all vector elements into the given target vector. Read more

Copies the phase of all elements in [rad] into the given vector. Read more

Gets the real and imaginary parts and stores them in the given vectors. See also get_phase and get_complex_abs for further information. Read more

Gets the magnitude and phase and stores them in the given vectors. See also get_real and get_imag for further information. Read more

Overrides the self vectors data with the real and imaginary data in the given vectors. real and imag must have the same size. Read more

Overrides the self vectors data with the magnitude and phase data in the given vectors. Note that self vector will immediately convert the data into a real and imaginary representation of the complex numbers which is its default format. mag and phase must have the same size. Read more

Gets the absolute value, magnitude or norm of all vector elements. Read more

Gets the square root of the absolute value of all vector elements. Read more

Gets all real elements. Read more

Gets all imag elements. Read more

Gets the phase of all elements in [rad]. Read more

Gets the absolute value, magnitude or norm of all vector elements. Read more

Gets the square root of the absolute value of all vector elements. Read more

Gets all real elements. Read more

Gets all imag elements. Read more

Gets the phase of all elements in [rad]. Read more

Convolves self with the convolution function impulse_response. For performance consider to to use FrequencyMultiplication instead of this operation depending on len. Read more

Convolves self with the convolution function impulse_response. For performance consider to to use FrequencyMultiplication instead of this operation depending on len. Read more

Convolves self with the convolution function impulse_response. For performance it’s recommended to use multiply both vectors in frequency domain instead of this operation. Read more

Prepares an argument to be used for convolution. Preparing an argument includes two steps: Read more

Prepares an argument to be used for convolution. The argument is zero padded to length of 2 * self.points() - 1 and then the same operations are performed as described for prepare_argument. Read more

Calculates the correlation between self and other. other needs to be a time vector which went through one of the prepare functions prepare_argument or prepare_argument_padded. See also the trait description for more details. Read more

Formats the value using the given formatter. Read more

Calculates the delta of each elements to its previous element. This will decrease the vector length by one point. Read more

Calculates the delta of each elements to its previous element. The first element will remain unchanged. Read more

Calculates the cumulative sum of all elements. This operation undoes the diff_with_startoperation. Read more

Calculates the dot product of self and factor. Self and factor remain unchanged. Read more

Calculates the dot product of self and factor. Self and factor remain unchanged. Read more

Calculates the sum of self + summand. It consumes self and returns the result. Read more

Calculates the difference of self - subtrahend. It consumes self and returns the result. Read more

Calculates the product of self * factor. It consumes self and returns the result. Read more

Calculates the quotient of self / summand. It consumes self and returns the result. Read more

Calculates the sum of self + summand. summand may be smaller than self as long as self.len() % summand.len() == 0. THe result is the same as it would be if you would repeat summand until it has the same length as self. It consumes self and returns the result. Read more

Calculates the sum of self - subtrahend. subtrahend may be smaller than self as long as self.len() % subtrahend.len() == 0. THe result is the same as it would be if you would repeat subtrahend until it has the same length as self. It consumes self and returns the result. Read more

Calculates the sum of self - factor. factor may be smaller than self as long as self.len() % factor.len() == 0. THe result is the same as it would be if you would repeat factor until it has the same length as self. It consumes self and returns the result. Read more

Calculates the sum of self - divisor. divisor may be smaller than self as long as self.len() % divisor.len() == 0. THe result is the same as it would be if you would repeat divisor until it has the same length as self. It consumes self and returns the result. Read more

The method for float indexing. If the vector is real valued then this function just returns the values

The method for float indexing. If the vector is real valued then this function just returns the values

The method for float indexing. If the vector is real valued then this function just returns the values

The method for float indexing. If the vector is real valued then this function just returns the values

The method for float indexing. If the vector is real valued then this function just returns the values

The method for real indexing

The method for real indexing

The method for real indexing

The method for real indexing

The method for real indexing

This function mirrors the spectrum vector to transform a symmetric spectrum into a full spectrum with the DC element at index 0 (no FFT shift/swap halves). Read more

Swaps vector halves after a Fourier Transformation.

Swaps vector halves before an Inverse Fourier Transformation.

Multiplies self with the frequency response function frequency_response. Read more

Multiplies self with the frequency response function frequency_response. Read more

Performs an Inverse Fast Fourier Transformation transforming a frequency domain vector into a time domain vector. Read more

Performs an Inverse Fast Fourier Transformation transforming a frequency domain vector into a time domain vector. Read more

Performs an Inverse Fast Fourier Transformation transforming a frequency domain vector into a time domain vector and removes the FFT window. Read more

Performs the conversion.

Performs the conversion.

Type of the underlying storage of a vector.

If you are working with std::vec::Vec then it’s recommended to use
Into instead of this one, as it’s more straightforward to use. Read more

Type of the underlying storage of a vector.

If you are working with std::vec::Vec then it’s recommended to use
Into instead of this one, as it’s more straightforward to use. Read more

Type of the underlying storage of a vector.

If you are working with std::vec::Vec then it’s recommended to use
Into instead of this one, as it’s more straightforward to use. Read more

Type of the underlying storage of a vector.

If you are working with std::vec::Vec then it’s recommended to use
Into instead of this one, as it’s more straightforward to use. Read more

Type of the underlying storage of a vector.

Gets the underlying storage and the number of elements which contain valid data. In case of complex vectors the values are returned real-imag pairs. Refer to Into or FromVector for a method which returns the data of complex vectors in a different manner. Read more

Gets a copy of the vector meta data. This can be used to create new types with the same meta data. Read more

The returned type after indexing.

Performs the indexing (container[index]) operation. Read more

The returned type after indexing.

Performs the indexing (container[index]) operation. Read more

The returned type after indexing.

Performs the indexing (container[index]) operation. Read more

The returned type after indexing.

Performs the indexing (container[index]) operation. Read more

The returned type after indexing.

Performs the indexing (container[index]) operation. Read more

The returned type after indexing.

Performs the indexing (container[index]) operation. Read more

The returned type after indexing.

Performs the indexing (container[index]) operation. Read more

The returned type after indexing.

Performs the indexing (container[index]) operation. Read more

The returned type after indexing.

Performs the indexing (container[index]) operation. Read more

The returned type after indexing.

Performs the indexing (container[index]) operation. Read more

Performs the mutable indexing (container[index]) operation. Read more

Performs the mutable indexing (container[index]) operation. Read more

Performs the mutable indexing (container[index]) operation. Read more

Performs the mutable indexing (container[index]) operation. Read more

Performs the mutable indexing (container[index]) operation. Read more

Performs the mutable indexing (container[index]) operation. Read more

Performs the mutable indexing (container[index]) operation. Read more

Performs the mutable indexing (container[index]) operation. Read more

Performs the mutable indexing (container[index]) operation. Read more

Performs the mutable indexing (container[index]) operation. Read more

Appends zeros add the end of the vector until the vector has the size given in the points argument. If points smaller than the self.len() then this operation won’t do anything, however in future it will raise an error. Read more

Interleaves zeros factor - 1times after every vector element, so that the resulting vector will have a length of self.len() * factor. Read more

Appends zeros add the end of the vector until the vector has the size given in the points argument. If points smaller than the self.len() then this operation will return an error. Read more

Interleaves zeros factor - 1times after every vector element, so that the resulting vector will have a length of self.len() * factor. Read more

Interpolates self with the convolution function function by the real value interpolation_factor. InterpolationOps is done in time domain and the argument conv_len can be used to balance accuracy and computational performance. A delay can be used to delay or phase shift the vector. The delay considers self.delta(). Read more

Interpolates self with the convolution function function by the integer value interpolation_factor. InterpolationOps is done in in frequency domain. Read more

Interpolates the signal in frequency domain by padding it with zeros. This function preserves the shape of the signal in frequency domain. Read more

Interpolates the signal in frequency domain by padding it with zeros.

Decimates or downsamples self. decimatei is the inverse function to interpolatei.

Transforms all vector elements using the function map and then aggregates all the results with aggregate. aggregate must be a commutativity and associativity; that’s because there is no guarantee that the numbers will be aggregated in any deterministic order. Read more

Transforms all vector elements using the function map and then aggregates all the results with aggregate. aggregate must be a commutativity and associativity; that’s because there is no guarantee that the numbers will be aggregated in any deterministic order. Read more

Transforms all vector elements using the function map.

Transforms all vector elements using the function map.

Merges several vectors into self. All vectors must have the same size and at least one vector must be provided. Read more

The domain in which the data vector resides. Basically specifies the x-axis and the type of operations which are valid on this vector. Read more

Indicates whether the vector contains complex data. This also specifies the type of operations which are valid on this vector. Read more

Each value in the vector is dividable by the divisor and the remainder is stored in the resulting vector. This the same a modulo operation or to phase wrapping. Read more

This function corrects the jumps in the given vector which occur due to wrap or modulo operations. This will undo a wrap operation only if the deltas are smaller than half the divisor. Read more

Adds a scalar to each vector element. Read more

Adds a scalar to each vector element. Read more

Gets the square root of all vector elements. Read more

Squares all vector elements. Read more

Calculates the n-th root of every vector element. Read more

Raises every vector element to a floating point power. Read more

Computes the principal value of natural logarithm of every element in the vector. Read more

Calculates the natural exponential for every vector element. Read more

Calculates the logarithm to the given base for every vector element. Read more

Calculates the exponential to the given base for every vector element. Read more

Calculates the dot product of self and factor using a more precise but slower algorithm. Self and factor remain unchanged. Read more

Calculates the dot product of self and factor using a more precise but slower algorithm. Self and factor remain unchanged. Read more

Calculates the statistics of the data contained in the vector using a more precise but slower algorithm. Read more

Calculates the statistics of the data contained in the vector using a more precise but slower algorithm. Read more

Calculates the statistics of the data contained in the vector using a more precise but slower algorithm. Read more

Calculates the statistics of the data contained in the vector using a more precise but slower algorithm. Read more

Calculates the statistics of the data contained in the vector as if the vector would have been split into len pieces using a more precise but slower algorithm. self.len should be dividable by len without a remainder, but this isn’t enforced by the implementation. For implementation reasons len <= 16 must be true. Read more

Calculates the statistics of the data contained in the vector as if the vector would have been split into len pieces using a more precise but slower algorithm. self.len should be dividable by len without a remainder, but this isn’t enforced by the implementation. For implementation reasons len <= 16 must be true. Read more

Calculates the statistics of the data contained in the vector as if the vector would have been split into len pieces using a more precise but slower algorithm. self.len should be dividable by len without a remainder, but this isn’t enforced by the implementation. For implementation reasons len <= 16 must be true. Read more

Calculates the statistics of the data contained in the vector as if the vector would have been split into len pieces using a more precise but slower algorithm. self.len should be dividable by len without a remainder, but this isn’t enforced by the implementation. For implementation reasons len <= 16 must be true. Read more

Calculates the sum of the data contained in the vector using a more precise but slower algorithm. Read more

Calculates the sum of the squared data contained in the vector using a more precise but slower algorithm. Read more

Calculates the sum of the data contained in the vector using a more precise but slower algorithm. Read more

Calculates the sum of the squared data contained in the vector using a more precise but slower algorithm. Read more

Calculates the sum of the data contained in the vector using a more precise but slower algorithm. Read more

Calculates the sum of the squared data contained in the vector using a more precise but slower algorithm. Read more

Calculates the sum of the data contained in the vector using a more precise but slower algorithm. Read more

Calculates the sum of the squared data contained in the vector using a more precise but slower algorithm. Read more

Linear interpolation between samples.

Piecewise cubic hermite interpolation between samples.

Gets the absolute value of all vector elements. Read more

Converts the real vector into a complex vector. Read more

Converts the real vector into a complex vector. The buffer allows this operation to succeed even if the storage type doesn’t allow resizing. Read more

Make Other a Self without performing any checks.

Make Other a Self without performing any checks. Read more

Make Other a Self without performing any checks.

Make Other a Self without performing any checks. Read more

Make Other a Self without performing any checks.

Make Other a Self without performing any checks. Read more

Make Other a Self without performing any checks.

Make Other a Self without performing any checks. Read more

Make Other a Self without performing any checks.

Make Other a Self without performing any checks. Read more

Make Other a Self. Read more

Converts Self inot Other.

Reverses the data inside the vector. Read more

This function swaps both halves of the vector. This operation is also called FFT shift Use it after a plain_fft to get a spectrum which is centered at 0 Hz. Read more

Changes self.len(). If self.is_complex() is true then len must be an even number. len > self.alloc_len() is only possible if the underlying storage or the buffer supports resizing. Read more

Changes self.len(). If self.is_complex() is true then len must be an even number. len > self.alloc_len() is only possible if the underlying storage supports resizing. Read more

Multiplies the vector element with a scalar. Read more

Multiplies the vector element with a scalar. Read more

Splits the vector into several smaller vectors. self.len() must be dividable by targets.len() without a remainder and this condition must be true too targets.len() > 0. Read more

Calculates the statistics of the data. Read more

Calculates the statistics of the data. Read more

Calculates the statistics of the data contained in the vector as if the vector would have been split into len pieces. self.len should be dividable by len without a remainder, but this isn’t enforced by the implementation. For implementation reasons len <= 16 must be true. Read more

Calculates the statistics of the data contained in the vector as if the vector would have been split into len pieces. self.len should be dividable by len without a remainder, but this isn’t enforced by the implementation. For implementation reasons len <= 16 must be true. Read more

Calculates the sum of the data contained in the vector. Read more

Calculates the sum of the squared data contained in the vector. Read more

Calculates the sum of the data contained in the vector. Read more

Calculates the sum of the squared data contained in the vector. Read more

Performs a Symmetric Inverse Fast Fourier Transformation under the assumption that self contains half of a symmetric spectrum starting from 0 Hz. This assumption isn’t verified and no error is raised if the spectrum isn’t symmetric. The reason for this is that there is no robust verification possible. Read more

Performs a Symmetric Inverse Fast Fourier Transformation under the assumption that self contains half of a symmetric spectrum starting from 0 Hz. This assumption isn’t verified and no error is raised if the spectrum isn’t symmetric. The reason for this is that there is no robust verification possible. Read more

Performs a Symmetric Inverse Fast Fourier Transformation (SIFFT) and removes the FFT window. The SIFFT is performed under the assumption that self contains half of a symmetric spectrum starting from 0 Hz. This assumption isn’t verified and no error is raised if the spectrum isn’t symmetric. The reason for this is that there is no robust verification possible. Read more

Performs a Symmetric Fast Fourier Transformation under the assumption that self is symmetric around the center. This assumption isn’t verified and no error is raised if the vector isn’t symmetric. Read more

Performs a Symmetric Fast Fourier Transformation under the assumption that self is symmetric around the center. This assumption isn’t verified and no error is raised if the vector isn’t symmetric. Read more

Performs a Symmetric Fast Fourier Transformation under the assumption that self is symmetric around the center. This assumption isn’t verified and no error is raised if the vector isn’t symmetric. Read more

Applies a window to the data vector.

Removes a window from the data vector.

Performs a Fast Fourier Transformation transforming a time domain vector into a frequency domain vector. Read more

Performs a Fast Fourier Transformation transforming a time domain vector into a frequency domain vector. Read more

Applies a FFT window and performs a Fast Fourier Transformation transforming a time domain vector into a frequency domain vector. Read more

Calculates the sine of each element in radians. Read more

Calculates the cosine of each element in radians. Read more

Calculates the tangent of each element in radians.

Calculates the principal value of the inverse sine of each element in radians.

Calculates the principal value of the inverse cosine of each element in radians.

Calculates the principal value of the inverse tangent of each element in radians.

Calculates the hyperbolic sine each element in radians.

Calculates the hyperbolic cosine each element in radians.

Calculates the hyperbolic tangent each element in radians.

Calculates the principal value of the inverse hyperbolic sine of each element in radians.

Calculates the principal value of the inverse hyperbolic cosine of each element in radians.

Calculates the principal value of the inverse hyperbolic tangent of each element in radians. Read more

The x-axis delta. If domain is time domain then delta is in [s], in frequency domain delta is in [Hz]. Read more

Sets the x-axis delta. If domain is time domain then delta is in [s], in frequency domain delta is in [Hz]. Read more

The number of valid elements in the vector. This can be changed with the Resize trait. Read more

Indicates whether or not the vector is empty.

The number of valid points. If the vector is complex then every valid point consists of two floating point numbers, while for real vectors every point only consists of one floating point number. Read more

Gets the multi core settings which determine how the work is split between several cores if the amount of data gets larger. Read more

Sets the multi core settings which determine how the work is split between several cores if the amount of data gets larger. Read more

Gets the number of allocated elements in the underlying vector. The allocated length may be larger than the length of valid points. In most cases you likely want to have lenor points instead. Read more

Auto Trait Implementations

Blanket Implementations

Gets the TypeId of self. Read more

Immutably borrows from an owned value. Read more

Mutably borrows from an owned value. Read more

Performs the conversion.

Performs the conversion.

Performs the conversion.

The alignment of pointer.

The type for initializers.

Initializes a with the given initializer. Read more

Dereferences the given pointer. Read more

Mutably dereferences the given pointer. Read more

Drops the object pointed to by the given pointer. Read more

The resulting type after obtaining ownership.

Creates owned data from borrowed data, usually by cloning. Read more

🔬 This is a nightly-only experimental API. (toowned_clone_into)

recently added

Uses borrowed data to replace owned data, usually by cloning. Read more

The type returned in the event of a conversion error.

Performs the conversion.

The type returned in the event of a conversion error.

Performs the conversion.