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renamed "None()" to "noArray()" to avoid conflicts with X11 (ticket #1122)

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Vadim Pisarevsky
2011-06-08 06:55:04 +00:00
parent aad9b3219c
commit 2d2b8a496e
21 changed files with 108 additions and 108 deletions
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modules/core/doc/clustering.rst
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@@ -10,7 +10,7 @@ Clustering
kmeans
------
.. cpp:function:: double kmeans( InputArray samples, int clusterCount, InputOutputArray labels, TermCriteria termcrit, int attempts, int flags, OutputArray centers=None() )
.. cpp:function:: double kmeans( InputArray samples, int clusterCount, InputOutputArray labels, TermCriteria termcrit, int attempts, int flags, OutputArray centers=noArray() )
Finds centers of clusters and groups input samples around the clusters.
modules/core/doc/intro.rst
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@@ -199,7 +199,7 @@ The subset of supported types for each function has been defined from practical
InputArray and OutputArray
--------------------------
Many OpenCV functions process dense 2-dimensional or multi-dimensional numerical arrays. Usually, such functions take cpp:class:`Mat` as parameters, but in some cases it's more convenient to use ``std::vector<>`` (for a point set, for example) or ``Matx<>`` (for 3x3 homography matrix and such). To avoid many duplicates in the API, special "proxy" classes have been introduced. The base "proxy" class is ``InputArray``. It is used for passing read-only arrays on a function input. The derived from ``InputArray`` class ``OutputArray`` is used to specify an output array for a function. Normally, you should not care of those intermediate types (and you should not declare variables of those types explicitly) - it will all just work automatically. You can assume that instead of ``InputArray``/``OutputArray`` you can always use ``Mat``, ``std::vector<>``, ``Matx<>``, ``Vec<>`` or ``Scalar``. When a function has an optional input or output array, and you do not have or do not want one, pass ``cv::None()``.
Many OpenCV functions process dense 2-dimensional or multi-dimensional numerical arrays. Usually, such functions take cpp:class:`Mat` as parameters, but in some cases it's more convenient to use ``std::vector<>`` (for a point set, for example) or ``Matx<>`` (for 3x3 homography matrix and such). To avoid many duplicates in the API, special "proxy" classes have been introduced. The base "proxy" class is ``InputArray``. It is used for passing read-only arrays on a function input. The derived from ``InputArray`` class ``OutputArray`` is used to specify an output array for a function. Normally, you should not care of those intermediate types (and you should not declare variables of those types explicitly) - it will all just work automatically. You can assume that instead of ``InputArray``/``OutputArray`` you can always use ``Mat``, ``std::vector<>``, ``Matx<>``, ``Vec<>`` or ``Scalar``. When a function has an optional input or output array, and you do not have or do not want one, pass ``cv::noArray()``.
Error Handling
--------------
modules/core/doc/operations_on_arrays.rst
+14 -14
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@@ -67,7 +67,7 @@ See Also: :cpp:func:`abs`
add
-------
.. cpp:function:: void add(InputArray src1, InputArray src2, OutputArray dst, InputArray mask=None(), int dtype=-1)
.. cpp:function:: void add(InputArray src1, InputArray src2, OutputArray dst, InputArray mask=noArray(), int dtype=-1)
Computes the per-element sum of two arrays or an array and a scalar.
@@ -166,7 +166,7 @@ See Also:
bitwise_and
-----------
.. cpp:function:: void bitwise_and(InputArray src1, InputArray src2, OutputArray dst, InputArray mask=None())
.. cpp:function:: void bitwise_and(InputArray src1, InputArray src2, OutputArray dst, InputArray mask=noArray())
Calculates the per-element bit-wise conjunction of two arrays or an array and a scalar.
@@ -208,7 +208,7 @@ In case of floating-point arrays, their machine-specific bit representations (us
bitwise_not
-----------
.. cpp:function:: void bitwise_not(InputArray src, OutputArray dst, InputArray mask=None())
.. cpp:function:: void bitwise_not(InputArray src, OutputArray dst, InputArray mask=noArray())
Inverts every bit of an array.
@@ -230,7 +230,7 @@ In case of a floating-point source array, its machine-specific bit representatio
bitwise_or
----------
.. cpp:function:: void bitwise_or(InputArray src1, InputArray src2, OutputArray dst, InputArray mask=None())
.. cpp:function:: void bitwise_or(InputArray src1, InputArray src2, OutputArray dst, InputArray mask=noArray())
Calculates the per-element bit-wise disjunction of two arrays or an array and a scalar.
@@ -273,7 +273,7 @@ The function computes the per-element bit-wise logical disjunction:
bitwise_xor
-----------
.. cpp:function:: void bitwise_xor(InputArray src1, InputArray src2, OutputArray dst, InputArray mask=None())
.. cpp:function:: void bitwise_xor(InputArray src1, InputArray src2, OutputArray dst, InputArray mask=noArray())
Calculates the per-element bit-wise "exclusive or" operation on two arrays or an array and a scalar.
@@ -1513,7 +1513,7 @@ See Also:
mean
----
.. cpp:function:: Scalar mean(InputArray mtx, InputArray mask=None())
.. cpp:function:: Scalar mean(InputArray mtx, InputArray mask=noArray())
Calculates an average (mean) of array elements.
@@ -1540,7 +1540,7 @@ See Also:
meanStdDev
----------
.. cpp:function:: void meanStdDev(InputArray mtx, OutputArray mean, OutputArray stddev, InputArray mask=None())
.. cpp:function:: void meanStdDev(InputArray mtx, OutputArray mean, OutputArray stddev, InputArray mask=noArray())
Calculates mean and standard deviation of array elements.
@@ -1656,7 +1656,7 @@ See Also:
minMaxLoc
---------
.. cpp:function:: void minMaxLoc(InputArray src, double* minVal, double* maxVal=0, Point* minLoc=0, Point* maxLoc=0, InputArray mask=None())
.. cpp:function:: void minMaxLoc(InputArray src, double* minVal, double* maxVal=0, Point* minLoc=0, Point* maxLoc=0, InputArray mask=noArray())
.. cpp:function:: void minMaxLoc(const SparseMat& src, double* minVal, double* maxVal, int* minIdx=0, int* maxIdx=0)
@@ -1824,7 +1824,7 @@ See Also:
mulTransposed
-------------
.. cpp:function:: void mulTransposed(InputArray src, OutputArray dst, bool aTa, InputArray delta=None(), double scale=1, int rtype=-1)
.. cpp:function:: void mulTransposed(InputArray src, OutputArray dst, bool aTa, InputArray delta=noArray(), double scale=1, int rtype=-1)
Calculates the product of a matrix and its transposition.
@@ -1834,7 +1834,7 @@ mulTransposed
:param aTa: Flag specifying the multiplication ordering. See the description below.
:param delta: Optional delta matrix subtracted from ``src`` before the multiplication. When the matrix is empty ( ``delta=None()`` ), it is assumed to be zero, that is, nothing is subtracted. If it has the same size as ``src`` , it is simply subtracted. Otherwise, it is "repeated" (see :cpp:func:`repeat` ) to cover the full ``src`` and then subtracted. Type of the delta matrix, when it is not empty, must be the same as the type of created destination matrix. See the ``rtype`` description.
:param delta: Optional delta matrix subtracted from ``src`` before the multiplication. When the matrix is empty ( ``delta=noArray()`` ), it is assumed to be zero, that is, nothing is subtracted. If it has the same size as ``src`` , it is simply subtracted. Otherwise, it is "repeated" (see :cpp:func:`repeat` ) to cover the full ``src`` and then subtracted. Type of the delta matrix, when it is not empty, must be the same as the type of created destination matrix. See the ``rtype`` description.
:param scale: Optional scale factor for the matrix product.
@@ -1867,9 +1867,9 @@ See Also:
norm
----
.. cpp:function:: double norm(InputArray src1, int normType=NORM_L2, InputArray mask=None())
.. cpp:function:: double norm(InputArray src1, int normType=NORM_L2, InputArray mask=noArray())
.. cpp:function:: double norm(InputArray src1, InputArray src2, int normType, InputArray mask=None())
.. cpp:function:: double norm(InputArray src1, InputArray src2, int normType, InputArray mask=noArray())
.. cpp:function:: double norm( const SparseMat& src, int normType )
@@ -1918,7 +1918,7 @@ A multi-channel source arrays are treated as a single-channel, that is, the resu
normalize
---------
.. cpp:function:: void normalize(const InputArray src, OutputArray dst, double alpha=1, double beta=0, int normType=NORM_L2, int rtype=-1, InputArray mask=None())
.. cpp:function:: void normalize(const InputArray src, OutputArray dst, double alpha=1, double beta=0, int normType=NORM_L2, int rtype=-1, InputArray mask=noArray())
.. cpp:function:: void normalize(const SparseMat& src, SparseMat& dst, double alpha, int normType)
@@ -2938,7 +2938,7 @@ See Also:
subtract
--------
.. cpp:function:: void subtract(InputArray src1, InputArray src2, OutputArray dst, InputArray mask=None(), int dtype=-1)
.. cpp:function:: void subtract(InputArray src1, InputArray src2, OutputArray dst, InputArray mask=noArray(), int dtype=-1)
Calculates the per-element difference between two arrays or array and a scalar.