SubColVector¶

class SubColVector(*args, **kwargs)¶

Bases: ColVector

This class provides a mask on a vpColVector . It has internally a pointer to the parent vpColVector . All properties of vpColVector are available with a vpSubColVector .

Note

See vpMatrix vpColVector vpRowVector

Overloaded function.

__init__(self: visp._visp.core.SubColVector) -> None

Default constructor that creates an empty vector.

__init__(self: visp._visp.core.SubColVector, v: visp._visp.core.ColVector, offset: int, nrows: int) -> None

Construct a sub-column vector from a parent column vector.

Parameters:

v: parent column vector.
offset: offset where the sub-column vector starts in the parent column vector.
nrows: size of the sub-column vector.

Methods

`__init__`	Overloaded function.
`checkParentStatus`	This method can be used to detect if the parent column vector always exits or its size have not changed.
`init`	Overloaded function.

Inherited Methods

`sum`	Return the sum of all the elements \(v_{i}\) of the column vector \(\bf v\) that is of dimension \(m\) .
`strCppCode`	Returns a C++ code representation of this data array (see cppPrint in the C++ documentation)
`insert`	Overloaded function.
`getCols`	Return the number of columns of the 2D array.
`crossProd`	Compute and return the cross product of two vectors \(a \times b\) .
`stdev`	Compute the standard deviation value of all the elements of the vector.
`toStdVector`	return: The corresponding std::vector<double>.
`infinityNorm`	Compute and return the infinity norm \({\|\|v\|\|}_{\infty} = max\left({\mid v_{i} \mid}\right)\) with \(i \in \{0, ..., m-1\}\) where m is the vector size and \(v_i\) an element of the vector.
`getRows`	Return the number of rows of the 2D array.
`dotProd`	Compute end return the dot product of two column vectors:
`strCsv`	Returns the CSV representation of this data array (see csvPrint in the C++ documentation)
`rad2deg`	Note See deg2rad()
`sumSquare`	Return the sum of squares of all the elements \(v_{i}\) of the column vector \(\bf v\) that is of dimension \(m\) .
`frobeniusNorm`	Compute and return the Frobenius norm \(\|\|v\|\| = \sqrt{ \sum_{v_{i}^2}}\) of all the elements \(v_{i}\) of the column vector \(\bf v\) that is of dimension \(m\) .
`cppPrint`	Print to be used as part of a C++ code later.
`t`	Overloaded function.
`invSort`	Return a column vector with elements of v that are reverse sorted with values going from greatest to lowest.
`sort`	Return a column vector with elements of v that are sorted with values going from lowest to greatest.
`strMaple`	Returns the CSV representation of this data array (see maplePrint in the C++ documentation)
`numpy`	Numpy view of the underlying array data.
`median`	Compute the median value of all the elements of the vector.
`resize`	Overloaded function.
`csvPrint`	Print/save a column vector in csv format.
`deg2rad`	Converts a column vector containing angles in degrees into radians and returns a reference to the vector.
`normalize`	Overloaded function.
`skew`	Compute the skew symmetric matrix \([{\bf v}]_\times\) of vector v.
`insertStatic`	Insert array B in array A at the given position.
`strMatlab`	Returns the Matlab representation of this data array (see matlabPrint in the C++ documentation)
`extract`	Extract a sub-column vector from a column vector.
`save`	Overloaded function.
`reshape`	Overloaded function.
`size`	Return the number of elements of the 2D array.
`getMinValue`	Return the array min value.
`clear`	Removes all elements from the vector (which are destroyed), leaving the container with a size of 0.
`transpose`	Overloaded function.
`getMaxValue`	Return the array max value.
`hadamard`	Overloaded function.
`mean`	Compute the mean value of all the elements of the vector.
`stackVectors`	Overloaded function.
`saveYAML`	Save an array in a YAML-formatted file.
`cross`	Compute and return the cross product of two 3-dimension vectors: \(a \times b\) .
`conv2`	Overloaded function.
`stack`	Overloaded function.
`print`	Pretty print a column vector.

Operators

`__doc__`
`__init__`	Overloaded function.
`__module__`

Attributes

`__annotations__`
`__hash__`

__add__(*args, **kwargs)¶

Overloaded function.

__add__(self: visp._visp.core.ColVector, v: visp._visp.core.ColVector) -> visp._visp.core.ColVector

Operator that allows to add two column vectors.

__add__(self: visp._visp.core.ColVector, t: visp._visp.core.TranslationVector) -> visp._visp.core.TranslationVector

Operator that allows to add a column vector to a translation vector.

Parameters:

t: 3-dimension translation vector to add.

Returns:

The sum of the current column vector (*this) and the translation vector to add.

vpTranslationVector t1(1,2,3);
vpColVector v(3);
v[0] = 4;
v[1] = 5;
v[2] = 6;
vpTranslationVector t2;

t2 = v + t1;
// t1 and v leave unchanged
// t2 is now equal to : 5, 7, 9

__eq__(*args, **kwargs)¶

Overloaded function.

__eq__(self: visp._visp.core.ColVector, v: visp._visp.core.ColVector) -> bool

Compare two column vectors.

Parameters:

v: Vector to compare with.

Returns:

true when their respective size and their respective values are the same, false when their size or values differ.

__eq__(self: visp._visp.core.ColVector, v: float) -> bool

Compare a column vector to a floating point value.

Parameters:

v: Floating point value to compare with.

Returns:

true when all the values of the vector are equal to the floating point value v , false otherwise.

__getitem__(*args, **kwargs)¶

Overloaded function.

__getitem__(self: visp._visp.core.ColVector, arg0: int) -> float
__getitem__(self: visp._visp.core.ColVector, arg0: slice) -> numpy.ndarray[numpy.float64]

__iadd__(self, v: visp._visp.core.ColVector) → visp._visp.core.ColVector¶: Operator that allows to add two column vectors.

__imul__(self, x: float) → visp._visp.core.ColVector¶

Operator that allows to multiply each element of a column vector by a scalar.

vpColVector v(3);
v[0] = 1;
v[1] = 2;
v[2] = 3;

v *= 3;
// v is now equal to : [3, 6, 9]

Parameters:

x: float¶: The scalar.

Returns:

The column vector multiplied by the scalar.

__init__(*args, **kwargs)¶

Overloaded function.

__init__(self: visp._visp.core.SubColVector) -> None

Default constructor that creates an empty vector.

__init__(self: visp._visp.core.SubColVector, v: visp._visp.core.ColVector, offset: int, nrows: int) -> None

Construct a sub-column vector from a parent column vector.

Parameters:

v: parent column vector.
offset: offset where the sub-column vector starts in the parent column vector.
nrows: size of the sub-column vector.

__isub__(self, v: visp._visp.core.ColVector) → visp._visp.core.ColVector¶: Operator that allows to subtract two column vectors.

__itruediv__(self, x: float) → visp._visp.core.ColVector¶

Operator that allows to divide each element of a column vector by a scalar.

vpColVector v(3);
v[0] = 8;
v[1] = 4;
v[2] = 2;

v /= 2;
// v is now equal to : [4, 2, 1]

Parameters:

x: float¶: The scalar.

Returns:

The column vector divided by the scalar.

__mul__(*args, **kwargs)¶

Overloaded function.

__mul__(self: visp._visp.core.ColVector, v: visp._visp.core.ColVector) -> float

Operator that performs the dot product between two column vectors.

Note

See dotProd()

__mul__(self: visp._visp.core.ColVector, v: visp._visp.core.RowVector) -> visp._visp.core.Matrix

Multiply a column vector by a row vector.

Parameters:

v: Row vector.

Returns:

The resulting matrix.

__mul__(self: visp._visp.core.ColVector, x: float) -> visp._visp.core.ColVector

Operator that allows to multiply each element of a column vector by a scalar.

vpColVector v(3);
v[0] = 1;
v[1] = 2;
v[2] = 3;

vpColVector w = v * 3;
// v is unchanged
// w is now equal to : [3, 6, 9]

Parameters:

x: The scalar.

Returns:

The column vector multiplied by the scalar. The current column vector (*this) is unchanged.

__ne__(*args, **kwargs)¶

Overloaded function.

__ne__(self: visp._visp.core.ColVector, v: visp._visp.core.ColVector) -> bool

Compare two column vectors.

Parameters:

v: Vector to compare with.

Returns:

true when their respective size or their values differ, false when their size and values are the same.

__ne__(self: visp._visp.core.ColVector, v: float) -> bool

Compare a column vector to a floating point value.

Parameters:

v: Floating point value to compare with.

Returns:

true when at least one value of the vector differ from the floating point value v . false when all the vector values are equal to v .

__neg__(self) → visp._visp.core.ColVector¶

Operator that allows to negate all the column vector elements.

vpColVector r(3, 1);
// r contains [1 1 1]^T
vpColVector v = -r;
// v contains [-1 -1 -1]^T

__sub__(self, v: visp._visp.core.ColVector) → visp._visp.core.ColVector¶: Operator subtraction of two vectors this = this - v

__truediv__(self, x: float) → visp._visp.core.ColVector¶

Operator that allows to divide each element of a column vector by a scalar.

vpColVector v(3);
v[0] = 8;
v[1] = 4;
v[2] = 2;

vpColVector w = v / 2;
// v is unchanged
// w is now equal to : [4, 2, 1]

Parameters:

x: float¶: The scalar.

Returns:

The column vector divided by the scalar. The current column vector (*this) is unchanged.

checkParentStatus(self) → None¶: This method can be used to detect if the parent column vector always exits or its size have not changed. If this not the case an exception is thrown.

clear(self) → None¶: Removes all elements from the vector (which are destroyed), leaving the container with a size of 0.

static conv2(*args, **kwargs)¶

Overloaded function.

conv2(M: visp._visp.core.ArrayDouble2D, kernel: visp._visp.core.ArrayDouble2D, mode: str) -> visp._visp.core.ArrayDouble2D

Perform a 2D convolution similar to Matlab conv2 function: \(M \star kernel\) .

Note

This is a very basic implementation that does not use FFT.

Parameters:

M: First matrix.
kernel: Second matrix.
mode: Convolution mode: “full” (default), “same”, “valid”.

conv2(M: visp._visp.core.ArrayDouble2D, kernel: visp._visp.core.ArrayDouble2D, res: visp._visp.core.ArrayDouble2D, mode: str) -> None

Perform a 2D convolution similar to Matlab conv2 function: \(M \star kernel\) .

Note

This is a very basic implementation that does not use FFT.

Parameters:

M: First array.
kernel: Second array.
res: Result.
mode: Convolution mode: “full” (default), “same”, “valid”.

cppPrint(self: visp._visp.core.ColVector, os: std::ostream, matrixName: str = A, octet: bool = false) → std::ostream¶

Print to be used as part of a C++ code later.

The following code shows how to use this function:

#include <visp3/core/vpColVector.h>

int main()
{
  vpColVector v(3);
  for (unsigned int i=0; i<v.size(); ++i)
    v[i] = i;
  v.cppPrint(std::cout, "v");
}

It produces the following output that could be copy/paste in a C++ code:

vpColVector v (3);
v[0] = 0;
v[1] = 1;
v[2] = 2;

Note

See print() , matlabPrint() , maplePrint()

Parameters:

os: the stream to be printed in.
matrixName: name of the column vector, “A” by default.
octet: if false, print using double, if true, print byte per byte each bytes of the double array.

static cross(a: visp._visp.core.ColVector, b: visp._visp.core.ColVector) → visp._visp.core.ColVector¶

Compute and return the cross product of two 3-dimension vectors: \(a \times b\) .

Note

See crossProd() , dotProd() , operator*(const vpColVector &)

Parameters:

a: visp._visp.core.ColVector¶: 3-dimension column vector.
b: visp._visp.core.ColVector¶: 3-dimension column vector.

Returns:

The cross product \(a \times b\) .

static crossProd(a: visp._visp.core.ColVector, b: visp._visp.core.ColVector) → visp._visp.core.ColVector¶

Compute and return the cross product of two vectors \(a \times b\) .

Note

See dotProd()

Parameters:

a: visp._visp.core.ColVector¶: 3-dimension column vector.
b: visp._visp.core.ColVector¶: 3-dimension column vector.

Returns:

The cross product \(a \times b\) .

csvPrint(self: visp._visp.core.ColVector, os: std::ostream) → std::ostream¶

Print/save a column vector in csv format.

The following code

#include <visp3/core/vpColVector.h>

int main()
{
  std::ofstream ofs("log.csv", std::ofstream::out);
  vpColVector v(3);
  for (unsigned int i=0; i<v.size(); ++i)
    v[i] = i;

  v.csvPrint(ofs);

  ofs.close();
}

produces log.csv file that contains:

0
1
2

deg2rad(self) → visp._visp.core.ColVector¶

Converts a column vector containing angles in degrees into radians and returns a reference to the vector.

Note

See rad2deg()

Returns:: A reference to the vector with values expressed in [rad].

static dotProd(a: visp._visp.core.ColVector, b: visp._visp.core.ColVector) → float¶

Compute end return the dot product of two column vectors:

\[a \cdot b = \sum_{i=0}^n a_i * b_i\]

where n is the dimension of both vectors.

Note

See cross() , crossProd()

extract(self, r: int, colsize: int) → visp._visp.core.ColVector¶

Extract a sub-column vector from a column vector.

vpColVector v1;
for (unsigned int i=0; i<4; ++i)
  v1.stack(i);
// v1 is equal to [0 1 2 3]^T
vpColVector v2 = v1.extract(1, 3);
// v2 is equal to [1 2 3]^T

Parameters:

r: int¶: Index of the row corresponding to the first element of the vector to extract.
colsize: int¶: Size of the vector to extract.

frobeniusNorm(self) → float¶

Compute and return the Frobenius norm \(||v|| = \sqrt{ \sum_{v_{i}^2}}\) of all the elements \(v_{i}\) of the column vector \(\bf v\) that is of dimension \(m\) .

Note

See infinityNorm()

Returns:: The Frobenius norm if the vector is initialized, 0 otherwise.

getCols(self) → int¶: Return the number of columns of the 2D array.

Note

See getRows() , size()

getMaxValue(self) → float¶: Return the array max value.

getMinValue(self) → float¶: Return the array min value.

getRows(self) → int¶: Return the number of rows of the 2D array.

Note

See getCols() , size()

hadamard(*args, **kwargs)¶

Overloaded function.

hadamard(self: visp._visp.core.ColVector, v: visp._visp.core.ColVector) -> visp._visp.core.ColVector

Compute the Hadamard product (element wise vector multiplication).

Parameters:

v: Second vector;

Returns:

v1.hadamard(v2) The kronecker product : \(v1 \circ v2 = (v1 \circ v2)_{i} = (v1)_{i} (v2)_{i}\)

hadamard(self: visp._visp.core.ArrayDouble2D, m: visp._visp.core.ArrayDouble2D) -> visp._visp.core.ArrayDouble2D

Parameters:

m: Second matrix;

Returns:

m1.hadamard(m2) The Hadamard product : \(m1 \circ m2 = (m1 \circ m2)_{i,j} = (m1)_{i,j} (m2)_{i,j}\)

infinityNorm(self) → float¶

Compute and return the infinity norm \({||v||}_{\infty} = max\left({\mid v_{i} \mid}\right)\) with \(i \in \{0, ..., m-1\}\) where m is the vector size and \(v_i\) an element of the vector.

Note

See frobeniusNorm()

Returns:: The infinity norm if the matrix is initialized, 0 otherwise.

init(*args, **kwargs)¶

Overloaded function.

init(self: visp._visp.core.SubColVector, v: visp._visp.core.ColVector, offset: int, nrows: int) -> None

Initialize a sub-column vector from a parent column vector.

Parameters:

v: parent column vector.
offset: offset where the sub-column vector starts in the parent column vector.
nrows: size of the sub-column vector.

init(self: visp._visp.core.ColVector, v: visp._visp.core.ColVector, r: int, nrows: int) -> None

Initialize the column vector from a part of an input column vector v .

The sub-vector starting from v[r] element and ending on v[r+nrows-1] element is used to initialize the constructed column vector.

The following code shows how to use this function:

#include <visp3/core/vpColVector.h>

int main()
{
  vpColVector v(4);
  int val = 0;
  for(size_t i=0; i<v.getRows(); ++i) {
    v[i] = val++;
  }
  std::cout << "v: " << v.t() << std::endl;

  vpColVector w;
  w.init(v, 0, 2);
  std::cout << "w: " << w.t() << std::endl;
}

It produces the following output:

v: 0 1 2 3
w: 1 2

Parameters:

v: Input column vector used for initialization.
r: row index in v that corresponds to the first element of the column vector to construct.
nrows: Number of rows of the constructed column vector.

insert(*args, **kwargs)¶

Overloaded function.

insert(self: visp._visp.core.ColVector, i: int, v: visp._visp.core.ColVector) -> None

Insert a column vector.The following example shows how to use this function:

#include <visp3/core/vpColVector.h>

int main()
{
  vpColVector v(4);
  for (unsigned int i=0; i < v.size(); ++i)
    v[i] = i;
  std::cout << "v: " << v.t() << std::endl;

  vpColVector w(2);
  for (unsigned int i=0; i < w.size(); ++i)
    w[i] = i+10;
  std::cout << "w: " << w.t() << std::endl;

  v.insert(1, w);
  std::cout << "v: " << v.t() << std::endl;
}

It produces the following output:

v: 0 1 2 3
w: 10 11
v: 0 10 11 3

Parameters:

i: Index of the first element to introduce. This index starts from 0.
v: Column vector to insert.

insert(self: visp._visp.core.ArrayDouble2D, A: visp._visp.core.ArrayDouble2D, r: int, c: int) -> None

Insert array A at the given position in the current array.

Warning

Throw vpException::dimensionError if the dimensions of the matrices do not allow the operation.

Parameters:

A: The array to insert.
r: The index of the row to begin to insert data.
c: The index of the column to begin to insert data.

insert(self: visp._visp.core.ArrayDouble2D, A: visp._visp.core.ArrayDouble2D, B: visp._visp.core.ArrayDouble2D, r: int, c: int) -> visp._visp.core.ArrayDouble2D

Insert array B in array A at the given position.

Warning

Throw exception if the sizes of the arrays do not allow the insertion.

Parameters:

A: Main array.
B: Array to insert.
r: Index of the row where to add the array.
c: Index of the column where to add the array.

Returns:

Array with B insert in A.

static insertStatic(A: visp._visp.core.ArrayDouble2D, B: visp._visp.core.ArrayDouble2D, C: visp._visp.core.ArrayDouble2D, r: int, c: int) → None¶

Insert array B in array A at the given position.

Warning

Throw exception if the sizes of the arrays do not allow the insertion.

Parameters:

A: visp._visp.core.ArrayDouble2D¶: Main array.
B: visp._visp.core.ArrayDouble2D¶: Array to insert.
C: visp._visp.core.ArrayDouble2D¶: Result array.
r: int¶: Index of the row where to insert array B.
c: int¶: Index of the column where to insert array B.

static invSort(v: visp._visp.core.ColVector) → visp._visp.core.ColVector¶

Return a column vector with elements of v that are reverse sorted with values going from greatest to lowest.

Example:

#include <visp3/core/vpColVector.h>

int main()
{
  vpColVector v(10);
  v[0] = 5; v[1] = 7; v[2] = 4; v[3] = 2; v[4] = 8;
  v[5] = 6; v[6] = 1; v[7] = 9; v[8] = 0; v[9] = 3;

  std::cout << "v: " << v.t() << std::endl;

  vpColVector s = vpColVector::invSort(v);
  std::cout << "s: " << s.t() << std::endl;
}

Output:

v: 5  7  4  2  8  6  1  9  0  3
s: 9  8  7  6  5  4  3  2  1  0

Note

See sort()

static mean(v: visp._visp.core.ColVector) → float¶: Compute the mean value of all the elements of the vector.

static median(v: visp._visp.core.ColVector) → float¶: Compute the median value of all the elements of the vector.

normalize(*args, **kwargs)¶

Overloaded function.

normalize(self: visp._visp.core.ColVector) -> visp._visp.core.ColVector

Normalize the column vector.

Considering the n-dim column vector \({\bf x} = (x_0, x_1, \ldots, n_{n-1})\) normalize each vector element \(i\) :

\[x_i = \frac{x_i}{\sqrt{\sum_{i=0}^{n-1}x^2_i}} \]

Returns:: A reference to the normalized vector.

normalize(self: visp._visp.core.ColVector, x: visp._visp.core.ColVector) -> visp._visp.core.ColVector

Normalize a column vector.

Considering the n-dim column vector \({\bf x} = (x_0, x_1, \ldots, n_{n-1})\) normalize each vector element \(i\) :

\[x_i = \frac{x_i}{\sqrt{\sum_{i=0}^{n-1} x^2_i}} \]

Parameters:

x: As input, the vector to normalize, as output the normalized vector.

Returns:

A reference to the normalized vector.

numpy(self) → numpy.ndarray[numpy.float64]¶: Numpy view of the underlying array data. This numpy view can be used to directly modify the array.

print(self: visp._visp.core.ColVector, s: std::ostream, length: int, intro: str = 0) → int¶

Pretty print a column vector. The data are tabulated. The common widths before and after the decimal point are set with respect to the parameter maxlen.

Note

See std::ostream & operator<<(std::ostream &s, const vpArray2D<Type> &A)

Parameters:

s: Stream used for the printing.
length: The suggested width of each vector element. The actual width grows in order to accommodate the whole integral part, and shrinks if the whole extent is not needed for all the numbers.
intro: The introduction which is printed before the vector. Can be set to zero (or omitted), in which case the introduction is not printed.

Returns:

Returns the common total width for all vector elements.

rad2deg(self) → visp._visp.core.ColVector¶

Note

See deg2rad()

Returns:: A reference to the vector with values expressed in [deg].

reshape(*args, **kwargs)¶

Overloaded function.

reshape(self: visp._visp.core.ColVector, M: visp._visp.core.Matrix, nrows: int, ncols: int) -> None

Reshape the column vector in a matrix.

The following example shows how to use this method.

#include <visp3/core/vpColVector.h>

int main()
{
  int var=0;
  vpMatrix mat(3, 4);
  for (int i = 0; i < 3; ++i)
    for (int j = 0; j < 4; ++j)
      mat[i][j] = ++var;
  std::cout << "mat: \n" << mat << std::endl;

  vpColVector col = mat.stackColumns();
  std::cout << "column vector: \n" << col << std::endl;

  vpMatrix remat = col.reshape(3, 4);
  std::cout << "remat: \n" << remat << std::endl;
}

If you run the previous example, you get:

mat:
1  2  3  4
5  6  7  8
9  10  11  12
column vector:
1
5
9
2
6
10
3
7
11
4
8
12
remat:
1  2  3  4
5  6  7  8
9  10  11  12

Parameters:

M: the reshaped matrix.
nrows: number of rows of the matrix.
ncols: number of columns of the matrix.

reshape(self: visp._visp.core.ColVector, nrows: int, ncols: int) -> visp._visp.core.Matrix

Reshape the column vector in a matrix.

Note

See reshape(vpMatrix &, const unsigned int &, const unsigned int &)

Parameters:

nrows: number of rows of the matrix
ncols: number of columns of the matrix

Returns:

The reshaped matrix.

reshape(self: visp._visp.core.ArrayDouble2D, nrows: int, ncols: int) -> None

resize(*args, **kwargs)¶

Overloaded function.

resize(self: visp._visp.core.ColVector, i: int, flagNullify: bool = true) -> None

Modify the size of the column vector.

Parameters:

i: Size of the vector. This value corresponds to the vector number of rows.
flagNullify: If true, set the data to zero.

resize(self: visp._visp.core.ColVector, nrows: int, ncols: int, flagNullify: bool) -> None

Resize the column vector to a nrows-dimension vector. This function can only be used with ncols = 1.

Parameters:

nrows: Vector number of rows. This value corresponds to the size of the vector.
ncols: Vector number of columns. This value should be set to 1.
flagNullify: If true, set the data to zero.

resize(self: visp._visp.core.ArrayDouble2D, nrows: int, ncols: int, flagNullify: bool = true, recopy_: bool = true) -> None

Set the size of the array and initialize all the values to zero.

Parameters:

nrows: number of rows.
ncols: number of column.
flagNullify: if true, then the array is re-initialized to 0 after resize. If false, the initial values from the common part of the array (common part between old and new version of the array) are kept. Default value is true.
recopy_: if true, will perform an explicit recopy of the old data.

static save(*args, **kwargs)¶

Overloaded function.

save(filename: str, A: visp._visp.core.ArrayDouble2D, binary: bool = false, header: str = ) -> bool

Save a matrix to a file.

Warning : If you save the matrix as in a text file the precision is less than if you save it in a binary file.

Note

See load()

Parameters:

filename: Absolute file name.
A: Array to be saved.
binary: If true the matrix is saved in a binary file, else a text file.
header: Optional line that will be saved at the beginning of the file.

Returns:

Returns true if success.

save(filename: str, A: visp._visp.core.ArrayDouble2D, binary: bool = false, header: str = ) -> bool

Save a matrix to a file.

Warning : If you save the matrix as in a text file the precision is less than if you save it in a binary file.

Note

See load()

Parameters:

filename: Absolute file name.
A: Array to be saved.
binary: If true the matrix is saved in a binary file, else a text file.
header: Optional line that will be saved at the beginning of the file.

Returns:

Returns true if success.

save(filename: str, A: visp._visp.core.ArrayDouble2D, binary: bool = false, header: str = ) -> bool

Save a matrix to a file.

Warning : If you save the matrix as in a text file the precision is less than if you save it in a binary file.

Note

See load()

Parameters:

filename: Absolute file name.
A: Array to be saved.
binary: If true the matrix is saved in a binary file, else a text file.
header: Optional line that will be saved at the beginning of the file.

Returns:

Returns true if success.

static saveYAML(filename: str, A: visp._visp.core.ArrayDouble2D, header: str =) → bool¶

Save an array in a YAML-formatted file.

Here is an example of outputs.

vpArray2D<double> M(3,4);
vpArray2D::saveYAML("matrix.yml", M, "example: a YAML-formatted header");
vpArray2D::saveYAML("matrixIndent.yml", M, "example:\n    - a YAML-formatted \
header\n    - with inner indentation");

Content of matrix.yml:

example: a YAML-formatted header
rows: 3
cols: 4
data:
  - [0, 0, 0, 0]
  - [0, 0, 0, 0]
  - [0, 0, 0, 0]

Content of matrixIndent.yml:

example:
    - a YAML-formatted header
    - with inner indentation
rows: 3
cols: 4
data:
    - [0, 0, 0, 0]
    - [0, 0, 0, 0]
    - [0, 0, 0, 0]

Note

See loadYAML()

Parameters:

filename: absolute file name.
A: array to be saved in the file.
header: optional lines that will be saved at the beginning of the file. Should be YAML-formatted and will adapt to the indentation if any.

Returns:

Returns true if success.

size(self) → int¶: Return the number of elements of the 2D array.

static skew(v: visp._visp.core.ColVector) → visp._visp.core.Matrix¶

Compute the skew symmetric matrix \([{\bf v}]_\times\) of vector v.

\[\begin{split}\mbox{if} \quad {\bf v} = \left( \begin{array}{c} x \\y \\z \end{array}\right), \quad \mbox{then} \qquad [{\bf v}]_\times = \left( \begin{array}{ccc} 0 & -z & y \\z & 0 & -x \\-y & x & 0 \end{array}\right) \end{split}\]

Parameters:

v: visp._visp.core.ColVector¶: Input vector used to compute the skew symmetric matrix.

static sort(v: visp._visp.core.ColVector) → visp._visp.core.ColVector¶

Return a column vector with elements of v that are sorted with values going from lowest to greatest.

Example:

#include <visp3/core/vpColVector.h>

int main()
{
  vpColVector v(10);
  v[0] = 5; v[1] = 7; v[2] = 4; v[3] = 2; v[4] = 8;
  v[5] = 6; v[6] = 1; v[7] = 9; v[8] = 0; v[9] = 3;

  std::cout << "v: " << v.t() << std::endl;

  vpColVector s = vpColVector::sort(v);
  std::cout << "s: " << s.t() << std::endl;
}

Output:

v: 5  7  4  2  8  6  1  9  0  3
s: 0  1  2  3  4  5  6  7  8  9

Note

See invSort()

stack(*args, **kwargs)¶

Overloaded function.

stack(self: visp._visp.core.ColVector, d: float) -> None

Stack column vector with a new element at the end of the vector.

vpColVector v(3, 1);
// v is equal to [1 1 1]^T
v.stack(-2);
// v is equal to [1 1 1 -2]^T

Note

See stack(const vpColVector &, const vpColVector &)

Note

See stack(const vpColVector &, const vpColVector &, vpColVector &)

Parameters:

d: Element to stack to the existing vector.

stack(self: visp._visp.core.ColVector, v: visp._visp.core.ColVector) -> None

Stack column vectors.

vpColVector v1(3, 1);
// v1 is equal to [1 1 1]^T
vpColVector v2(2, 3);
// v2 is equal to [3 3]^T
v1.stack(v2);
// v1 is equal to [1 1 1 3 3]^T

Note

See stack(const vpColVector &, const double &)

Note

See stack(const vpColVector &, const vpColVector &)

Note

See stack(const vpColVector &, const vpColVector &, vpColVector &)

Parameters:

v: Vector to stack to the existing one.

static stackVectors(*args, **kwargs)¶

Overloaded function.

stackVectors(A: visp._visp.core.ColVector, B: visp._visp.core.ColVector) -> visp._visp.core.ColVector

Stack column vectors.

vpColVector A(3);
vpColVector B(5);
vpColVector C;
C = vpColVector::stack(A, B); // C = [A B]T
// C is now an 8 dimension column vector

Note

See stack(const vpColVector &)

Note

See stack(const vpColVector &, const vpColVector &, vpColVector &)

Parameters:

A: Initial vector.
B: Vector to stack at the end of A.

Returns:

Stacked vector \([A B]^T\) .

stackVectors(A: visp._visp.core.ColVector, B: visp._visp.core.ColVector, C: visp._visp.core.ColVector) -> None

Stack column vectors.

vpColVector  A(3);
vpColVector  B(5);
vpColVector  C;
vpColVector::stack (A, B, C); // C = [A B]T
// C is now an 8 dimension column vector

Note

See stack(const vpColVector &)

Note

See stack(const vpColVector &, const vpColVector &)

Parameters:

A: Initial vector.
B: Vector to stack at the end of A.
C: Resulting stacked vector \(C = [A B]^T\) .

static stdev(v: visp._visp.core.ColVector, useBesselCorrection: bool = false) → float¶: Compute the standard deviation value of all the elements of the vector.

strCppCode(self, name: str, byte_per_byte: bool = False) → str¶

Returns a C++ code representation of this data array (see cppPrint in the C++ documentation)

Parameters:

name: str¶: variable name of the matrix.
byte_per_byte: bool = False¶: Whether to print byte per byte defaults to false.

strCsv(self) → str¶: Returns the CSV representation of this data array (see csvPrint in the C++ documentation)

strMaple(self) → str¶: Returns the CSV representation of this data array (see maplePrint in the C++ documentation)

strMatlab(self) → str¶: Returns the Matlab representation of this data array (see matlabPrint in the C++ documentation)

sum(self) → float¶

Return the sum of all the elements \(v_{i}\) of the column vector \(\bf v\) that is of dimension \(m\) .

Returns:: The value

\[\sum_{i=0}^{m-1} v_i \]

sumSquare(self) → float¶

Return the sum of squares of all the elements \(v_{i}\) of the column vector \(\bf v\) that is of dimension \(m\) .

Returns:: The value

\[\sum_{i=0}^{m-1} v_i^{2}\]

t(*args, **kwargs)¶

Overloaded function.

t(self: visp._visp.core.ColVector) -> visp._visp.core.RowVector

Transpose the column vector. The resulting vector becomes a row vector.

t(self: visp._visp.core.ArrayDouble2D) -> visp._visp.core.ArrayDouble2D

Compute the transpose of the array.

Returns:: vpArray2D<Type> C = A^T

toStdVector(self) → list[float]¶

Returns:: The corresponding std::vector<double>.

transpose(*args, **kwargs)¶

Overloaded function.

transpose(self: visp._visp.core.ColVector) -> visp._visp.core.RowVector

Transpose the column vector. The resulting vector becomes a row vector.

Note

See t()

transpose(self: visp._visp.core.ColVector, v: visp._visp.core.RowVector) -> None

Transpose the column vector. The resulting vector v becomes a row vector.

Note

See t()

__hash__ = None¶