Struct basic_dsp_matrix::MatrixMxN
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pub struct MatrixMxN<V, S, T> where
T: RealNumber,
S: ToSlice<T>,
V: Vector<T>, { /* fields omitted */ }
A matrix which can hold 1 to N vectors.
Trait Implementations
impl<V, S, T> MetaData for MatrixMxN<V, S, T> where
T: RealNumber,
S: ToSlice<T>,
V: Vector<T>,
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T: RealNumber,
S: ToSlice<T>,
V: Vector<T>,
fn domain(&self) -> DataDomain
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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
fn is_complex(&self) -> bool
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Indicates whether the vector contains complex data. This also specifies the type of operations which are valid on this vector. Read more
impl<V, S, T> ResizeOps for MatrixMxN<V, S, T> where
T: RealNumber,
S: ToSlice<T>,
V: Vector<T>,
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T: RealNumber,
S: ToSlice<T>,
V: Vector<T>,
fn resize(&mut self, len: usize) -> VoidResult
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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
impl<V, S, T> Matrix<V, T> for MatrixMxN<V, S, T> where
T: RealNumber,
S: ToSlice<T>,
V: Vector<T>,
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T: RealNumber,
S: ToSlice<T>,
V: Vector<T>,
fn delta(&self) -> T
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The x-axis delta. If domain
is time domain then delta
is in [s]
, in frequency domain delta
is in [Hz]
. Read more
fn set_delta(&mut self, delta: T)
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Sets the x-axis delta. If domain
is time domain then delta
is in [s]
, in frequency domain delta
is in [Hz]
. Read more
fn row_len(&self) -> usize
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The number of valid elements in each row of the matrix. This can be changed with the Resize
trait. Read more
fn row_points(&self) -> usize
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The number of valid points in a row. If the matrix 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
fn col_len(&self) -> usize
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The number of columns in the matrix.
fn rows(&self) -> &[V]
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Gets the rows as vectors.
fn rows_mut(&mut self) -> &mut [V]
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Gets the rows as mutable vectors.
impl<V, S, T, N, D> GetMetaData<T, N, D> for MatrixMxN<V, S, T> where
T: RealNumber,
S: ToSlice<T>,
V: Vector<T> + GetMetaData<T, N, D>,
N: NumberSpace,
D: Domain,
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T: RealNumber,
S: ToSlice<T>,
V: Vector<T> + GetMetaData<T, N, D>,
N: NumberSpace,
D: Domain,
fn get_meta_data(&self) -> TypeMetaData<T, N, D>
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Gets a copy of the vector meta data. This can be used to create new types with the same meta data. Read more
impl<V, S, T> FromMatrix<T> for MatrixMxN<V, S, T> where
T: RealNumber,
V: Vector<T>,
S: ToSlice<T>,
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T: RealNumber,
V: Vector<T>,
S: ToSlice<T>,
type Output = Vec<V>
Type of the underlying storage of a matrix.
fn get(self) -> (Self::Output, usize)
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Gets the underlying matrix and the number of elements which contain valid. Read more
impl<V: Vector<T> + ScaleOps<T>, S: ToSlice<T>, T: RealNumber> ScaleOps<T> for MatrixMxN<V, S, T>
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impl<V: Vector<T>, S: ToSlice<T>, T: RealNumber> OffsetOps<T> for MatrixMxN<V, S, T> where
V: OffsetOps<T>,
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V: OffsetOps<T>,
impl<V: Vector<T>, S: ToSlice<T>, T: RealNumber> ScaleOps<Complex<T>> for MatrixMxN<V, S, T> where
V: ScaleOps<Complex<T>>,
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V: ScaleOps<Complex<T>>,
impl<V: Vector<T>, S: ToSlice<T>, T: RealNumber> OffsetOps<Complex<T>> for MatrixMxN<V, S, T> where
V: OffsetOps<Complex<T>>,
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V: OffsetOps<Complex<T>>,
impl<V: Vector<T>, S: ToSlice<T>, T: RealNumber, N: NumberSpace, D: Domain> ElementaryOps<MatrixMxN<V, S, T>, T, N, D> for MatrixMxN<V, S, T> where
V: ElementaryOps<V, T, N, D> + GetMetaData<T, N, D>,
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V: ElementaryOps<V, T, N, D> + GetMetaData<T, N, D>,
fn add(&mut self, summand: &Self) -> VoidResult
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Calculates the sum of self + summand
. It consumes self and returns the result. # Failures TransRes may report the following ErrorReason
members: Read more
fn sub(&mut self, summand: &Self) -> VoidResult
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Calculates the difference of self - subtrahend
. It consumes self and returns the result. # Failures TransRes may report the following ErrorReason
members: Read more
fn div(&mut self, summand: &Self) -> VoidResult
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Calculates the quotient of self / summand
. It consumes self and returns the result. # Failures TransRes may report the following ErrorReason
members: Read more
fn mul(&mut self, summand: &Self) -> VoidResult
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Calculates the product of self * factor
. It consumes self and returns the result. # Failures TransRes may report the following ErrorReason
members: Read more
impl<V: Vector<T>, S: ToSlice<T>, T: RealNumber, N: NumberSpace, D: Domain> ElementaryOps<V, T, N, D> for MatrixMxN<V, S, T> where
V: ElementaryOps<V, T, N, D> + GetMetaData<T, N, D>,
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V: ElementaryOps<V, T, N, D> + GetMetaData<T, N, D>,
fn add(&mut self, summand: &V) -> VoidResult
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Calculates the sum of self + summand
. It consumes self and returns the result. # Failures TransRes may report the following ErrorReason
members: Read more
fn sub(&mut self, summand: &V) -> VoidResult
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Calculates the difference of self - subtrahend
. It consumes self and returns the result. # Failures TransRes may report the following ErrorReason
members: Read more
fn div(&mut self, summand: &V) -> VoidResult
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Calculates the quotient of self / summand
. It consumes self and returns the result. # Failures TransRes may report the following ErrorReason
members: Read more
fn mul(&mut self, summand: &V) -> VoidResult
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Calculates the product of self * factor
. It consumes self and returns the result. # Failures TransRes may report the following ErrorReason
members: Read more
impl<V: Vector<T>, S: ToSlice<T>, T: RealNumber, N: NumberSpace, D: Domain> ElementaryWrapAroundOps<MatrixMxN<V, S, T>, T, N, D> for MatrixMxN<V, S, T> where
V: ElementaryWrapAroundOps<V, T, N, D> + GetMetaData<T, N, D>,
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V: ElementaryWrapAroundOps<V, T, N, D> + GetMetaData<T, N, D>,
fn add_smaller(&mut self, summand: &Self) -> VoidResult
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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. # Failures TransRes may report the following ErrorReason
members: Read more
fn sub_smaller(&mut self, summand: &Self) -> VoidResult
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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. # Failures TransRes may report the following ErrorReason
members: Read more
fn div_smaller(&mut self, summand: &Self) -> VoidResult
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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. # Failures TransRes may report the following ErrorReason
members: Read more
fn mul_smaller(&mut self, summand: &Self) -> VoidResult
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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. # Failures TransRes may report the following ErrorReason
members: Read more
impl<V: Vector<T>, S: ToSlice<T>, T: RealNumber, N: NumberSpace, D: Domain> ElementaryWrapAroundOps<V, T, N, D> for MatrixMxN<V, S, T> where
V: ElementaryWrapAroundOps<V, T, N, D> + GetMetaData<T, N, D>,
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V: ElementaryWrapAroundOps<V, T, N, D> + GetMetaData<T, N, D>,
fn add_smaller(&mut self, summand: &V) -> VoidResult
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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. # Failures TransRes may report the following ErrorReason
members: Read more
fn sub_smaller(&mut self, summand: &V) -> VoidResult
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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. # Failures TransRes may report the following ErrorReason
members: Read more
fn div_smaller(&mut self, summand: &V) -> VoidResult
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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. # Failures TransRes may report the following ErrorReason
members: Read more
fn mul_smaller(&mut self, summand: &V) -> VoidResult
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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. # Failures TransRes may report the following ErrorReason
members: Read more
impl<V: Vector<T>, S: ToSlice<T>, T: RealNumber> ReorganizeDataOps<T> for MatrixMxN<V, S, T> where
V: ReorganizeDataOps<T>,
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V: ReorganizeDataOps<T>,
fn reverse(&mut self)
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Reverses the data inside the vector. Read more
fn swap_halves(&mut self)
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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
impl<S: ToSlice<T>, V: Vector<T> + DiffSumOps, T: RealNumber> DiffSumOps for MatrixMxN<V, S, T>
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fn diff(&mut self)
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Calculates the delta of each elements to its previous element. This will decrease the vector length by one point. Read more
fn diff_with_start(&mut self)
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Calculates the delta of each elements to its previous element. The first element will remain unchanged. Read more
fn cum_sum(&mut self)
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Calculates the cumulative sum of all elements. This operation undoes the diff_with_start
operation. Read more
impl<S: ToSlice<T>, V: Vector<T> + TrigOps, T: RealNumber> TrigOps for MatrixMxN<V, S, T>
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fn sin(&mut self)
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Calculates the sine of each element in radians. Read more
fn cos(&mut self)
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Calculates the cosine of each element in radians. Read more
fn tan(&mut self)
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Calculates the tangent of each element in radians.
fn asin(&mut self)
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Calculates the principal value of the inverse sine of each element in radians.
fn acos(&mut self)
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Calculates the principal value of the inverse cosine of each element in radians.
fn atan(&mut self)
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Calculates the principal value of the inverse tangent of each element in radians.
fn sinh(&mut self)
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Calculates the hyperbolic sine each element in radians.
fn cosh(&mut self)
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Calculates the hyperbolic cosine each element in radians.
fn tanh(&mut self)
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Calculates the hyperbolic tangent each element in radians.
fn asinh(&mut self)
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Calculates the principal value of the inverse hyperbolic sine of each element in radians.
fn acosh(&mut self)
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Calculates the principal value of the inverse hyperbolic cosine of each element in radians.
fn atanh(&mut self)
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Calculates the principal value of the inverse hyperbolic tangent of each element in radians. Read more
impl<S: ToSlice<T>, V: Vector<T> + PowerOps<T>, T: RealNumber> PowerOps<T> for MatrixMxN<V, S, T>
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fn sqrt(&mut self)
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Gets the square root of all vector elements. Read more
fn square(&mut self)
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Squares all vector elements. Read more
fn root(&mut self, degree: T)
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Calculates the n-th root of every vector element. Read more
fn powf(&mut self, exponent: T)
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Raises every vector element to a floating point power. Read more
fn ln(&mut self)
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Computes the principal value of natural logarithm of every element in the vector. Read more
fn exp(&mut self)
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Calculates the natural exponential for every vector element. Read more
fn log(&mut self, base: T)
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Calculates the logarithm to the given base for every vector element. Read more
fn expf(&mut self, base: T)
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Calculates the exponential to the given base for every vector element. Read more
impl<S: ToSlice<T>, V: Vector<T> + MapInplaceOps<T>, T: RealNumber> MapInplaceOps<T> for MatrixMxN<V, S, T>
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fn map_inplace<'a, A, F>(&mut self, argument: A, map: &F) where
A: Sync + Copy + Send,
F: Fn(T, usize, A) -> T + 'a + Sync,
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A: Sync + Copy + Send,
F: Fn(T, usize, A) -> T + 'a + Sync,
Transforms all vector elements using the function map
.
impl<S: ToSlice<T>, V: Vector<T> + MapInplaceOps<Complex<T>>, T: RealNumber> MapInplaceOps<Complex<T>> for MatrixMxN<V, S, T>
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fn map_inplace<'a, A, F>(&mut self, argument: A, map: &F) where
A: Sync + Copy + Send,
F: Fn(Complex<T>, usize, A) -> Complex<T> + 'a + Sync,
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A: Sync + Copy + Send,
F: Fn(Complex<T>, usize, A) -> Complex<T> + 'a + Sync,
Transforms all vector elements using the function map
.
impl<S: ToSlice<T>, V: Vector<T>, T: RealNumber> StatisticsOps<T> for MatrixMxN<V, S, T> where
V: StatisticsOps<Statistics<T>, Result = Statistics<T>>,
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V: StatisticsOps<Statistics<T>, Result = Statistics<T>>,
type Result = Vec<Statistics<T>>
fn statistics(&self) -> Vec<Statistics<T>>
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Calculates the statistics of the data. Read more
impl<S: ToSlice<T>, V: Vector<T>, T: RealNumber> StatisticsSplitOps<T> for MatrixMxN<V, S, T> where
V: StatisticsSplitOps<Statistics<T>, Result = StatsVec<Statistics<T>>>,
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V: StatisticsSplitOps<Statistics<T>, Result = StatsVec<Statistics<T>>>,
type Result = Vec<StatsVec<Statistics<T>>>
fn statistics_split(
&self,
len: usize
) -> ScalarResult<Vec<StatsVec<Statistics<T>>>>
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&self,
len: usize
) -> ScalarResult<Vec<StatsVec<Statistics<T>>>>
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
impl<S: ToSlice<T>, V: Vector<T>, T: RealNumber> SumOps<Vec<T>> for MatrixMxN<V, S, T> where
V: SumOps<T>,
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V: SumOps<T>,
fn sum(&self) -> Vec<T>
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Calculates the sum of the data contained in the vector. # Example Read more
fn sum_sq(&self) -> Vec<T>
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Calculates the sum of the squared data contained in the vector. # Example Read more
impl<S: ToSlice<T>, V: Vector<T>, T: RealNumber> PreciseStatisticsOps<T> for MatrixMxN<V, S, T> where
V: PreciseStatisticsOps<Statistics<T>, Result = Statistics<T>>,
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V: PreciseStatisticsOps<Statistics<T>, Result = Statistics<T>>,
type Result = Vec<Statistics<T>>
fn statistics_prec(&self) -> Vec<Statistics<T>>
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Calculates the statistics of the data contained in the vector using a more precise but slower algorithm. Read more
impl<S: ToSlice<T>, V: Vector<T>, T: RealNumber> PreciseStatisticsSplitOps<T> for MatrixMxN<V, S, T> where
V: PreciseStatisticsSplitOps<Statistics<T>, Result = StatsVec<Statistics<T>>>,
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V: PreciseStatisticsSplitOps<Statistics<T>, Result = StatsVec<Statistics<T>>>,
type Result = Vec<StatsVec<Statistics<T>>>
fn statistics_split_prec(
&self,
len: usize
) -> ScalarResult<Vec<StatsVec<Statistics<T>>>>
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&self,
len: usize
) -> ScalarResult<Vec<StatsVec<Statistics<T>>>>
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
impl<S: ToSlice<T>, V: Vector<T>, T: RealNumber, O: RealNumber> PreciseSumOps<Vec<O>> for MatrixMxN<V, S, T> where
V: PreciseSumOps<O>,
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V: PreciseSumOps<O>,
fn sum_prec(&self) -> Vec<O>
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Calculates the sum of the data contained in the vector using a more precise but slower algorithm. # Example Read more
fn sum_sq_prec(&self) -> Vec<O>
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Calculates the sum of the squared data contained in the vector using a more precise but slower algorithm. # Example Read more
impl<S: ToSlice<T>, V: Vector<T>, T: RealNumber, N: NumberSpace, D: Domain> DotProductOps<MatrixMxN<V, S, T>, T, T, N, D> for MatrixMxN<V, S, T> where
V: DotProductOps<V, T, T, N, D, Output = ScalarResult<T>> + GetMetaData<T, N, D>,
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V: DotProductOps<V, T, T, N, D, Output = ScalarResult<T>> + GetMetaData<T, N, D>,
type Output = ScalarResult<Vec<T>>
fn dot_product(&self, factor: &MatrixMxN<V, S, T>) -> ScalarResult<Vec<T>>
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Calculates the dot product of self and factor. Self and factor remain unchanged. Read more
impl<S: ToSlice<T>, V: Vector<T>, T: RealNumber, N: NumberSpace, D: Domain> DotProductOps<V, T, T, N, D> for MatrixMxN<V, S, T> where
V: DotProductOps<V, T, T, N, D, Output = ScalarResult<T>> + GetMetaData<T, N, D>,
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V: DotProductOps<V, T, T, N, D, Output = ScalarResult<T>> + GetMetaData<T, N, D>,
type Output = ScalarResult<Vec<T>>
fn dot_product(&self, factor: &V) -> ScalarResult<Vec<T>>
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Calculates the dot product of self and factor. Self and factor remain unchanged. Read more
impl<S: ToSlice<T>, V: Vector<T>, T: RealNumber, N: NumberSpace, D: Domain> PreciseDotProductOps<MatrixMxN<V, S, T>, T, T, N, D> for MatrixMxN<V, S, T> where
V: PreciseDotProductOps<V, T, T, N, D, Output = ScalarResult<T>> + GetMetaData<T, N, D>,
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V: PreciseDotProductOps<V, T, T, N, D, Output = ScalarResult<T>> + GetMetaData<T, N, D>,
type Output = ScalarResult<Vec<T>>
fn dot_product_prec(&self, factor: &MatrixMxN<V, S, T>) -> ScalarResult<Vec<T>>
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Calculates the dot product of self and factor using a more precise but slower algorithm. Self and factor remain unchanged. Read more
impl<S: ToSlice<T>, V: Vector<T>, T: RealNumber, N: NumberSpace, D: Domain> PreciseDotProductOps<V, T, T, N, D> for MatrixMxN<V, S, T> where
V: PreciseDotProductOps<V, T, T, N, D, Output = ScalarResult<T>> + GetMetaData<T, N, D>,
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V: PreciseDotProductOps<V, T, T, N, D, Output = ScalarResult<T>> + GetMetaData<T, N, D>,
type Output = ScalarResult<Vec<T>>
fn dot_product_prec(&self, factor: &V) -> ScalarResult<Vec<T>>
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Calculates the dot product of self and factor using a more precise but slower algorithm. Self and factor remain unchanged. Read more
impl<S: ToSlice<T>, V: Vector<T>, T: RealNumber, R: Send> MapAggregateOps<T, R> for MatrixMxN<V, S, T> where
V: MapAggregateOps<T, R, Output = ScalarResult<R>>,
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V: MapAggregateOps<T, R, Output = ScalarResult<R>>,
type Output = ScalarResult<Vec<R>>
fn map_aggregate<'a, A, FMap, FAggr>(
&self,
argument: A,
map: &FMap,
aggregate: &FAggr
) -> ScalarResult<Vec<R>> where
A: Sync + Copy + Send,
FMap: Fn(T, usize, A) -> R + 'a + Sync,
FAggr: Fn(R, R) -> R + 'a + Sync + Send,
R: Send,
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&self,
argument: A,
map: &FMap,
aggregate: &FAggr
) -> ScalarResult<Vec<R>> where
A: Sync + Copy + Send,
FMap: Fn(T, usize, A) -> R + 'a + Sync,
FAggr: Fn(R, R) -> R + 'a + Sync + Send,
R: Send,
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
impl<V, O, S: ToSlice<T>, T: RealNumber> RededicateForceOps<MatrixMxN<O, S, T>> for MatrixMxN<V, S, T> where
V: RededicateForceOps<O> + Vector<T>,
T: RealNumber,
O: Vector<T>,
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V: RededicateForceOps<O> + Vector<T>,
T: RealNumber,
O: Vector<T>,
fn rededicate_from_force(origin: MatrixMxN<O, S, T>) -> Self
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Make Other
a Self
without performing any checks.
fn rededicate_with_runtime_data(
origin: MatrixMxN<O, S, T>,
is_complex: bool,
domain: DataDomain
) -> Self
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origin: MatrixMxN<O, S, T>,
is_complex: bool,
domain: DataDomain
) -> Self
Make Other
a Self
without performing any checks. Read more
impl<V: Vector<T> + ToRealResult, S: ToSlice<T>, T: RealNumber> ToRealResult for MatrixMxN<V, S, T> where
<V as ToRealResult>::RealResult: Vector<T>,
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<V as ToRealResult>::RealResult: Vector<T>,
type RealResult = MatrixMxN<V::RealResult, S, T>
impl<V: Vector<T>, S: ToSlice<T>, T: RealNumber> ComplexToRealTransformsOps<T> for MatrixMxN<V, S, T> where
<V as ToRealResult>::RealResult: Vector<T>,
V: ComplexToRealTransformsOps<T>,
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<V as ToRealResult>::RealResult: Vector<T>,
V: ComplexToRealTransformsOps<T>,
fn magnitude(self) -> Self::RealResult
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Gets the absolute value, magnitude or norm of all vector elements. # Example Read more
fn magnitude_squared(self) -> Self::RealResult
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Gets the square root of the absolute value of all vector elements. # Example Read more
fn to_real(self) -> Self::RealResult
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Gets all real elements. # Example Read more
fn to_imag(self) -> Self::RealResult
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Gets all imag elements. # Example Read more
fn phase(self) -> Self::RealResult
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Gets the phase of all elements in [rad]. # Example Read more
impl<V: Vector<T>, S: ToSliceMut<T>, T: RealNumber> ComplexToRealTransformsOpsBuffered<S, T> for MatrixMxN<V, S, T> where
<V as ToRealResult>::RealResult: Vector<T>,
V: ComplexToRealTransformsOpsBuffered<S, T>,
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<V as ToRealResult>::RealResult: Vector<T>,
V: ComplexToRealTransformsOpsBuffered<S, T>,
fn magnitude_b<B>(self, buffer: &mut B) -> Self::RealResult where
B: for<'b> Buffer<'b, S, T>,
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B: for<'b> Buffer<'b, S, T>,
Gets the absolute value, magnitude or norm of all vector elements. # Example Read more
fn magnitude_squared_b<B>(self, buffer: &mut B) -> Self::RealResult where
B: for<'b> Buffer<'b, S, T>,
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B: for<'b> Buffer<'b, S, T>,
Gets the square root of the absolute value of all vector elements. # Example Read more
fn to_real_b<B>(self, buffer: &mut B) -> Self::RealResult where
B: for<'b> Buffer<'b, S, T>,
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B: for<'b> Buffer<'b, S, T>,
Gets all real elements. # Example Read more
fn to_imag_b<B>(self, buffer: &mut B) -> Self::RealResult where
B: for<'b> Buffer<'b, S, T>,
[src]
B: for<'b> Buffer<'b, S, T>,
Gets all imag elements. # Example Read more
fn phase_b<B>(self, buffer: &mut B) -> Self::RealResult where
B: for<'b> Buffer<'b, S, T>,
[src]
B: for<'b> Buffer<'b, S, T>,
Gets the phase of all elements in [rad]. # Example Read more
impl<V: Vector<T>, S: ToSlice<T>, T: RealNumber, N: NumberSpace, D: Domain, O> ComplexToRealGetterOps<O, T, N, D> for MatrixMxN<V, S, T> where
O: Matrix<V, T> + GetMetaData<T, N, D>,
V: ComplexToRealGetterOps<V, T, N, D> + GetMetaData<T, N, D>,
[src]
O: Matrix<V, T> + GetMetaData<T, N, D>,
V: ComplexToRealGetterOps<V, T, N, D> + GetMetaData<T, N, D>,
fn get_real(&self, destination: &mut O)
[src]
Copies all real elements into the given vector. # Example Read more
fn get_imag(&self, destination: &mut O)
[src]
Copies all imag elements into the given vector. # Example Read more
fn get_magnitude(&self, destination: &mut O)
[src]
Copies the absolute value or magnitude of all vector elements into the given target vector. # Example Read more
fn get_magnitude_squared(&self, destination: &mut O)
[src]
Copies the absolute value squared or magnitude squared of all vector elements into the given target vector. # Example Read more
fn get_phase(&self, destination: &mut O)
[src]
Copies the phase of all elements in [rad] into the given vector. # Example Read more
fn get_real_imag(&self, real: &mut O, imag: &mut O)
[src]
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
fn get_mag_phase(&self, mag: &mut O, phase: &mut O)
[src]
Gets the magnitude and phase and stores them in the given vectors. See also get_real
and get_imag
for further information. Read more
impl<V: Vector<T>, S: ToSlice<T>, T: RealNumber, N: NumberSpace, D: Domain, O> ComplexToRealSetterOps<O, T, N, D> for MatrixMxN<V, S, T> where
O: Matrix<V, T> + GetMetaData<T, N, D>,
V: ComplexToRealSetterOps<V, T, N, D> + GetMetaData<T, N, D>,
[src]
O: Matrix<V, T> + GetMetaData<T, N, D>,
V: ComplexToRealSetterOps<V, T, N, D> + GetMetaData<T, N, D>,
fn set_real_imag(&mut self, real: &O, imag: &O) -> VoidResult
[src]
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
fn set_mag_phase(&mut self, mag: &O, phase: &O) -> VoidResult
[src]
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
impl<V: Vector<T>, S: ToSlice<T>, T: RealNumber> ComplexOps<T> for MatrixMxN<V, S, T> where
V: ComplexOps<T>,
[src]
V: ComplexOps<T>,
fn multiply_complex_exponential(&mut self, a: T, b: T)
[src]
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
fn conj(&mut self)
[src]
Calculates the complex conjugate of the vector. # Example Read more
impl<V: Vector<T> + ToComplexResult, S: ToSlice<T>, T: RealNumber> ToComplexResult for MatrixMxN<V, S, T> where
<V as ToComplexResult>::ComplexResult: Vector<T>,
[src]
<V as ToComplexResult>::ComplexResult: Vector<T>,
type ComplexResult = MatrixMxN<V::ComplexResult, S, T>
impl<V: Vector<T>, S: ToSlice<T>, T: RealNumber> RealToComplexTransformsOps<T> for MatrixMxN<V, S, T> where
<V as ToComplexResult>::ComplexResult: Vector<T>,
V: RealToComplexTransformsOps<T>,
[src]
<V as ToComplexResult>::ComplexResult: Vector<T>,
V: RealToComplexTransformsOps<T>,
fn to_complex(self) -> TransRes<Self::ComplexResult>
[src]
Converts the real vector into a complex vector. Read more
impl<V: Vector<T>, S: ToSliceMut<T>, T: RealNumber> RealToComplexTransformsOpsBuffered<S, T> for MatrixMxN<V, S, T> where
<V as ToComplexResult>::ComplexResult: Vector<T>,
V: RealToComplexTransformsOpsBuffered<S, T>,
[src]
<V as ToComplexResult>::ComplexResult: Vector<T>,
V: RealToComplexTransformsOpsBuffered<S, T>,
fn to_complex_b<B>(self, buffer: &mut B) -> Self::ComplexResult where
B: for<'b> Buffer<'b, S, T>,
[src]
B: for<'b> Buffer<'b, S, T>,
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
impl<V: Vector<T>, S: ToSlice<T>, T: RealNumber> RealOps for MatrixMxN<V, S, T> where
V: RealOps,
[src]
V: RealOps,
impl<V: Vector<T>, S: ToSlice<T>, T: RealNumber> ModuloOps<T> for MatrixMxN<V, S, T> where
V: ModuloOps<T>,
[src]
V: ModuloOps<T>,
fn wrap(&mut self, divisor: T)
[src]
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
fn unwrap(&mut self, divisor: T)
[src]
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
impl<S: ToSlice<T>, V: Vector<T> + ApproximatedOps<T>, T: RealNumber> ApproximatedOps<T> for MatrixMxN<V, S, T>
[src]
fn ln_approx(&mut self)
[src]
Computes the principal value approximation of natural logarithm of every element in the vector. Read more
fn exp_approx(&mut self)
[src]
Calculates the natural exponential approximation for every vector element. Read more
fn sin_approx(&mut self)
[src]
Calculates the sine approximation of each element in radians. Read more
fn cos_approx(&mut self)
[src]
Calculates the cosine approximation of each element in radians Read more
fn log_approx(&mut self, base: T)
[src]
Calculates the approximated logarithm to the given base for every vector element. Read more
fn expf_approx(&mut self, base: T)
[src]
Calculates the approximated exponential to the given base for every vector element. Read more
fn powf_approx(&mut self, exponent: T)
[src]
Raises every vector element to approximately a floating point power. Read more
impl<V: Vector<T> + ToTimeResult, S: ToSlice<T>, T: RealNumber> ToTimeResult for MatrixMxN<V, S, T> where
<V as ToTimeResult>::TimeResult: Vector<T>,
[src]
<V as ToTimeResult>::TimeResult: Vector<T>,
type TimeResult = MatrixMxN<V::TimeResult, S, T>
Specifies what the the result is if a type is transformed to time domain.
impl<V: Vector<T> + ToFreqResult, S: ToSlice<T>, T: RealNumber> ToFreqResult for MatrixMxN<V, S, T> where
<V as ToFreqResult>::FreqResult: Vector<T>,
[src]
<V as ToFreqResult>::FreqResult: Vector<T>,
type FreqResult = MatrixMxN<V::FreqResult, S, T>
impl<V: Vector<T> + ToRealTimeResult, S: ToSlice<T>, T: RealNumber> ToRealTimeResult for MatrixMxN<V, S, T> where
<V as ToRealTimeResult>::RealTimeResult: Vector<T>,
[src]
<V as ToRealTimeResult>::RealTimeResult: Vector<T>,
type RealTimeResult = MatrixMxN<V::RealTimeResult, S, T>
impl<V: Vector<T>, S: ToSliceMut<T>, T: RealNumber> TimeToFrequencyDomainOperations<S, T> for MatrixMxN<V, S, T> where
<V as ToFreqResult>::FreqResult: Vector<T>,
V: TimeToFrequencyDomainOperations<S, T>,
[src]
<V as ToFreqResult>::FreqResult: Vector<T>,
V: TimeToFrequencyDomainOperations<S, T>,
fn plain_fft<B>(self, buffer: &mut B) -> Self::FreqResult where
B: for<'b> Buffer<'b, S, T>,
[src]
B: for<'b> Buffer<'b, S, T>,
Performs a Fast Fourier Transformation transforming a time domain vector into a frequency domain vector. Read more
fn fft<B>(self, buffer: &mut B) -> Self::FreqResult where
B: for<'b> Buffer<'b, S, T>,
[src]
B: for<'b> Buffer<'b, S, T>,
Performs a Fast Fourier Transformation transforming a time domain vector into a frequency domain vector. # Unstable FFTs of real vectors are unstable. # Example Read more
fn windowed_fft<B>(
self,
buffer: &mut B,
window: &WindowFunction<T>
) -> Self::FreqResult where
B: for<'b> Buffer<'b, S, T>,
[src]
self,
buffer: &mut B,
window: &WindowFunction<T>
) -> Self::FreqResult where
B: for<'b> Buffer<'b, S, T>,
Applies a FFT window and performs a Fast Fourier Transformation transforming a time domain vector into a frequency domain vector. Read more
impl<V: Vector<T>, S: ToSliceMut<T>, T: RealNumber> SymmetricTimeToFrequencyDomainOperations<S, T> for MatrixMxN<V, S, T> where
<V as ToFreqResult>::FreqResult: Vector<T>,
V: SymmetricTimeToFrequencyDomainOperations<S, T>,
[src]
<V as ToFreqResult>::FreqResult: Vector<T>,
V: SymmetricTimeToFrequencyDomainOperations<S, T>,
fn plain_sfft<B>(self, buffer: &mut B) -> TransRes<Self::FreqResult> where
B: for<'b> Buffer<'b, S, T>,
[src]
B: for<'b> Buffer<'b, S, T>,
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
fn sfft<B>(self, buffer: &mut B) -> TransRes<Self::FreqResult> where
B: for<'b> Buffer<'b, S, T>,
[src]
B: for<'b> Buffer<'b, S, T>,
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. # Failures TransRes may report the following ErrorReason
members: Read more
fn windowed_sfft<B>(
self,
buffer: &mut B,
window: &WindowFunction<T>
) -> TransRes<Self::FreqResult> where
B: for<'b> Buffer<'b, S, T>,
[src]
self,
buffer: &mut B,
window: &WindowFunction<T>
) -> TransRes<Self::FreqResult> where
B: for<'b> Buffer<'b, S, T>,
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. # Failures TransRes may report the following ErrorReason
members: Read more
impl<V: Vector<T>, S: ToSliceMut<T>, T: RealNumber> FrequencyToTimeDomainOperations<S, T> for MatrixMxN<V, S, T> where
<V as ToTimeResult>::TimeResult: Vector<T>,
V: FrequencyToTimeDomainOperations<S, T>,
[src]
<V as ToTimeResult>::TimeResult: Vector<T>,
V: FrequencyToTimeDomainOperations<S, T>,
fn plain_ifft<B>(self, buffer: &mut B) -> Self::TimeResult where
B: for<'b> Buffer<'b, S, T>,
[src]
B: for<'b> Buffer<'b, S, T>,
Performs an Inverse Fast Fourier Transformation transforming a frequency domain vector into a time domain vector. Read more
fn ifft<B>(self, buffer: &mut B) -> Self::TimeResult where
B: for<'b> Buffer<'b, S, T>,
[src]
B: for<'b> Buffer<'b, S, T>,
Performs an Inverse Fast Fourier Transformation transforming a frequency domain vector into a time domain vector. # Example Read more
fn windowed_ifft<B>(
self,
buffer: &mut B,
window: &WindowFunction<T>
) -> Self::TimeResult where
B: for<'b> Buffer<'b, S, T>,
[src]
self,
buffer: &mut B,
window: &WindowFunction<T>
) -> Self::TimeResult where
B: for<'b> Buffer<'b, S, T>,
Performs an Inverse Fast Fourier Transformation transforming a frequency domain vector into a time domain vector and removes the FFT window. Read more
impl<V: Vector<T>, S: ToSliceMut<T>, T: RealNumber> SymmetricFrequencyToTimeDomainOperations<S, T> for MatrixMxN<V, S, T> where
<V as ToRealTimeResult>::RealTimeResult: Vector<T>,
V: SymmetricFrequencyToTimeDomainOperations<S, T>,
[src]
<V as ToRealTimeResult>::RealTimeResult: Vector<T>,
V: SymmetricFrequencyToTimeDomainOperations<S, T>,
fn plain_sifft<B>(self, buffer: &mut B) -> TransRes<Self::RealTimeResult> where
B: for<'b> Buffer<'b, S, T>,
[src]
B: for<'b> Buffer<'b, S, T>,
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
fn sifft<B>(self, buffer: &mut B) -> TransRes<Self::RealTimeResult> where
B: for<'b> Buffer<'b, S, T>,
[src]
B: for<'b> Buffer<'b, S, T>,
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
fn windowed_sifft<B>(
self,
buffer: &mut B,
window: &WindowFunction<T>
) -> TransRes<Self::RealTimeResult> where
B: for<'b> Buffer<'b, S, T>,
[src]
self,
buffer: &mut B,
window: &WindowFunction<T>
) -> TransRes<Self::RealTimeResult> where
B: for<'b> Buffer<'b, S, T>,
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
impl<V: Vector<T>, S: ToSliceMut<T>, T: RealNumber> FrequencyDomainOperations<S, T> for MatrixMxN<V, S, T> where
V: FrequencyDomainOperations<S, T>,
[src]
V: FrequencyDomainOperations<S, T>,
fn mirror<B>(&mut self, buffer: &mut B) where
B: for<'b> Buffer<'b, S, T>,
[src]
B: for<'b> Buffer<'b, S, T>,
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
fn fft_shift(&mut self)
[src]
Swaps vector halves after a Fourier Transformation.
fn ifft_shift(&mut self)
[src]
Swaps vector halves before an Inverse Fourier Transformation.
impl<V: Vector<T>, S: ToSliceMut<T>, T: RealNumber> TimeDomainOperations<S, T> for MatrixMxN<V, S, T> where
V: TimeDomainOperations<S, T>,
[src]
V: TimeDomainOperations<S, T>,
fn apply_window(&mut self, window: &WindowFunction<T>)
[src]
Applies a window to the data vector.
fn unapply_window(&mut self, window: &WindowFunction<T>)
[src]
Removes a window from the data vector.
impl<V: Vector<T>, S: ToSliceMut<T>, T: RealNumber> CrossCorrelationArgumentOps<S, T> for MatrixMxN<V, S, T> where
<V as ToFreqResult>::FreqResult: Vector<T>,
V: CrossCorrelationArgumentOps<S, T>,
[src]
<V as ToFreqResult>::FreqResult: Vector<T>,
V: CrossCorrelationArgumentOps<S, T>,
fn prepare_argument<B>(self, buffer: &mut B) -> Self::FreqResult where
B: for<'b> Buffer<'b, S, T>,
[src]
B: for<'b> Buffer<'b, S, T>,
Prepares an argument to be used for convolution. Preparing an argument includes two steps: Read more
fn prepare_argument_padded<B>(self, buffer: &mut B) -> Self::FreqResult where
B: for<'b> Buffer<'b, S, T>,
[src]
B: for<'b> Buffer<'b, S, T>,
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
impl<S: ToSliceMut<T>, T: RealNumber, N: NumberSpace, D: Domain, O, V> CrossCorrelationOps<O, S, T, N, D> for MatrixMxN<V, S, T> where
O: Matrix<V, T> + GetMetaData<T, N, D>,
V: CrossCorrelationOps<V, S, T, N, D> + GetMetaData<T, N, D> + Vector<T>,
[src]
O: Matrix<V, T> + GetMetaData<T, N, D>,
V: CrossCorrelationOps<V, S, T, N, D> + GetMetaData<T, N, D> + Vector<T>,
fn correlate<B>(&mut self, buffer: &mut B, other: &O) -> VoidResult where
B: for<'b> Buffer<'b, S, T>,
[src]
B: for<'b> Buffer<'b, S, T>,
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
impl<V: Vector<T>, S: ToSliceMut<T>, T: RealNumber> InterpolationOps<S, T> for MatrixMxN<V, S, T> where
V: InterpolationOps<S, T>,
[src]
V: InterpolationOps<S, T>,
fn interpolatef<B>(
&mut self,
buffer: &mut B,
function: &RealImpulseResponse<T>,
interpolation_factor: T,
delay: T,
conv_len: usize
) where
B: for<'b> Buffer<'b, S, T>,
[src]
&mut self,
buffer: &mut B,
function: &RealImpulseResponse<T>,
interpolation_factor: T,
delay: T,
conv_len: usize
) where
B: for<'b> Buffer<'b, S, T>,
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
fn interpolatei<B>(
&mut self,
buffer: &mut B,
function: &RealFrequencyResponse<T>,
interpolation_factor: u32
) -> VoidResult where
B: for<'b> Buffer<'b, S, T>,
[src]
&mut self,
buffer: &mut B,
function: &RealFrequencyResponse<T>,
interpolation_factor: u32
) -> VoidResult where
B: for<'b> Buffer<'b, S, T>,
Interpolates self
with the convolution function function
by the interger value interpolation_factor
. InterpolationOps is done in in frequency domain. Read more
fn interpolate<B>(
&mut self,
buffer: &mut B,
function: Option<&RealFrequencyResponse<T>>,
dest_points: usize,
delay: T
) -> VoidResult where
B: for<'b> Buffer<'b, S, T>,
[src]
&mut self,
buffer: &mut B,
function: Option<&RealFrequencyResponse<T>>,
dest_points: usize,
delay: T
) -> VoidResult where
B: for<'b> Buffer<'b, S, T>,
Interpolates the signal in frequency domain by padding it with zeros.
fn interpft<B>(&mut self, buffer: &mut B, dest_points: usize) where
B: for<'b> Buffer<'b, S, T>,
[src]
B: for<'b> Buffer<'b, S, T>,
Interpolates the signal in frequency domain by padding it with zeros. This function preserves the shape of the signal in frequency domain. Read more
fn decimatei(&mut self, decimation_factor: u32, delay: u32)
[src]
Decimates or downsamples self
. decimatei
is the inverse function to interpolatei
.
impl<V: Vector<T>, S: ToSliceMut<T>, T: RealNumber> RealInterpolationOps<S, T> for MatrixMxN<V, S, T> where
V: RealInterpolationOps<S, T>,
[src]
V: RealInterpolationOps<S, T>,
fn interpolate_hermite<B>(
&mut self,
buffer: &mut B,
interpolation_factor: T,
delay: T
) where
B: for<'b> Buffer<'b, S, T>,
[src]
&mut self,
buffer: &mut B,
interpolation_factor: T,
delay: T
) where
B: for<'b> Buffer<'b, S, T>,
Piecewise cubic hermite interpolation between samples. # Unstable Algorithm might need to be revised. This operation and interpolate_lin
might be merged into one function with an additional argument in future. Read more
fn interpolate_lin<B>(
&mut self,
buffer: &mut B,
interpolation_factor: T,
delay: T
) where
B: for<'b> Buffer<'b, S, T>,
[src]
&mut self,
buffer: &mut B,
interpolation_factor: T,
delay: T
) where
B: for<'b> Buffer<'b, S, T>,
Linear interpolation between samples. # Unstable This operation and interpolate_hermite
might be merged into one function with an additional argument in future. Read more
impl<'a, V: Vector<T>, S: ToSliceMut<T>, T: RealNumber> Convolution<'a, S, T, &'a RealImpulseResponse<T>> for MatrixMxN<V, S, T> where
V: Convolution<'a, S, T, &'a RealImpulseResponse<T>>,
[src]
V: Convolution<'a, S, T, &'a RealImpulseResponse<T>>,
fn convolve<B>(
&mut self,
buffer: &mut B,
impulse_response: &'a RealImpulseResponse<T>,
ratio: T,
len: usize
) where
B: for<'b> Buffer<'b, S, T>,
[src]
&mut self,
buffer: &mut B,
impulse_response: &'a RealImpulseResponse<T>,
ratio: T,
len: usize
) where
B: for<'b> Buffer<'b, S, T>,
Convolves self
with the convolution function impulse_response
. For performance consider to to use FrequencyMultiplication
instead of this operation depending on len
. Read more
impl<'a, V: Vector<T>, S: ToSliceMut<T>, T: RealNumber> Convolution<'a, S, T, &'a ComplexImpulseResponse<T>> for MatrixMxN<V, S, T> where
V: Convolution<'a, S, T, &'a ComplexImpulseResponse<T>>,
[src]
V: Convolution<'a, S, T, &'a ComplexImpulseResponse<T>>,
fn convolve<B>(
&mut self,
buffer: &mut B,
impulse_response: &'a ComplexImpulseResponse<T>,
ratio: T,
len: usize
) where
B: for<'b> Buffer<'b, S, T>,
[src]
&mut self,
buffer: &mut B,
impulse_response: &'a ComplexImpulseResponse<T>,
ratio: T,
len: usize
) where
B: for<'b> Buffer<'b, S, T>,
Convolves self
with the convolution function impulse_response
. For performance consider to to use FrequencyMultiplication
instead of this operation depending on len
. Read more
impl<'a, V: Vector<T>, S: ToSliceMut<T>, T: RealNumber> FrequencyMultiplication<'a, S, T, &'a RealFrequencyResponse<T>> for MatrixMxN<V, S, T> where
V: FrequencyMultiplication<'a, S, T, &'a RealFrequencyResponse<T>>,
[src]
V: FrequencyMultiplication<'a, S, T, &'a RealFrequencyResponse<T>>,
fn multiply_frequency_response(
&mut self,
frequency_response: &'a RealFrequencyResponse<T>,
ratio: T
)
[src]
&mut self,
frequency_response: &'a RealFrequencyResponse<T>,
ratio: T
)
Multiplies self
with the frequency response function frequency_response
. Read more
impl<'a, V: Vector<T>, S: ToSliceMut<T>, T: RealNumber> FrequencyMultiplication<'a, S, T, &'a ComplexFrequencyResponse<T>> for MatrixMxN<V, S, T> where
V: FrequencyMultiplication<'a, S, T, &'a ComplexFrequencyResponse<T>>,
[src]
V: FrequencyMultiplication<'a, S, T, &'a ComplexFrequencyResponse<T>>,
fn multiply_frequency_response(
&mut self,
frequency_response: &'a ComplexFrequencyResponse<T>,
ratio: T
)
[src]
&mut self,
frequency_response: &'a ComplexFrequencyResponse<T>,
ratio: T
)
Multiplies self
with the frequency response function frequency_response
. Read more
impl<S: ToSliceMut<T>, T: RealNumber, N: NumberSpace, D: Domain> ConvolutionOps<DspVec<S, T, N, D>, S, T, N, D> for MatrixMxN<DspVec<S, T, N, D>, S, T> where
DspVec<S, T, N, D>: ConvolutionOps<DspVec<S, T, N, D>, S, T, N, D>,
[src]
DspVec<S, T, N, D>: ConvolutionOps<DspVec<S, T, N, D>, S, T, N, D>,
fn convolve_signal<B>(
&mut self,
buffer: &mut B,
impulse_response: &DspVec<S, T, N, D>
) -> VoidResult where
B: for<'b> Buffer<'b, S, T>,
[src]
&mut self,
buffer: &mut B,
impulse_response: &DspVec<S, T, N, D>
) -> VoidResult where
B: for<'b> Buffer<'b, S, T>,
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
impl<'a, S: ToSliceMut<T>, T: RealNumber, N: NumberSpace, D: Domain> ConvolutionOps<Vec<&'a Vec<&'a DspVec<S, T, N, D>>>, S, T, N, D> for MatrixMxN<DspVec<S, T, N, D>, S, T>
[src]
fn convolve_signal<B>(
&mut self,
buffer: &mut B,
impulse_response: &Vec<&Vec<&DspVec<S, T, N, D>>>
) -> VoidResult where
B: for<'b> Buffer<'b, S, T>,
[src]
&mut self,
buffer: &mut B,
impulse_response: &Vec<&Vec<&DspVec<S, T, N, D>>>
) -> VoidResult where
B: for<'b> Buffer<'b, S, T>,
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