updated document, which is generated now

site/doxygen.sh → site/_doxygen.sh

@@ -1,5 +1,5 @@
 #!/bin/sh
 
 for f in `find _doxygen/xml -name "group__*.xml"` ; do
-	./doxygen.rb $f _posts/
+	./_doxygen.rb $f _posts/
 done

site/_posts/0000-01-01-ccv-algebra.markdown

@@ -9,94 +9,131 @@ categories:
 - lib
 ---
 
-ccv_normalize
--------------
+ccv\_normalize
+--------------
 
-	double ccv_normalize(ccv_matrix_t* a, ccv_matrix_t** b, int btype, int flag)
+	double ccv_normalize(ccv_matrix_t *a, ccv_matrix_t **b, int btype, int flag)
 
 Normalize a matrix and return the normalize factor.
 
- * **a**: the input matrix.
- * **b**: the output matrix.
- * **btype**: the type of output matrix, if 0, ccv will try to match the input matrix for appropriate type.
+ * **a**: The input matrix.
+ * **b**: The output matrix.
+ * **btype**: The type of output matrix, if 0, ccv will try to match the input matrix for appropriate type.
  * **flag**: CCV\_L1 or CCV\_L2, for L1 or L2 normalization.
 
-ccv_sat
--------
+**return**: L1 or L2 sum.
+
+ccv\_sat
+--------
+
+	void ccv_sat(ccv_dense_matrix_t *a, ccv_dense_matrix_t **b, int type, int padding_pattern)
+
+Generate the [Summed Area Table](https://en.wikipedia.org/wiki/Summed\_area\_table).
+
+ * **a**: The input matrix.
+ * **b**: The output matrix.
+ * **type**: The type of output matrix, if 0, ccv will try to match the input matrix for appropriate type.
+ * **padding\_pattern**: CCV\_NO\_PADDING - the first row and the first column in the output matrix is the same as the input matrix. CCV\_PADDING\_ZERO - the first row and the first column in the output matrix is zero, thus, the output matrix size is 1 larger than the input matrix.
+
+ccv\_dot
+--------
+
+	double ccv_dot(ccv_matrix_t *a, ccv_matrix_t *b)
 
-	void ccv_sat(ccv_dense_matrix_t* a, ccv_dense_matrix_t** b, int type, int padding_pattern)
+Dot product of two matrix.
 
-Generate the [Summed Area Table](https://en.wikipedia.org/wiki/Summed_area_table).
+ * **a**: The input matrix.
+ * **b**: The other input matrix.
 
- * **a**: the input matrix.
- * **b**: the output matrix.
- * **type**: the type of output matrix, if 0, ccv will try to match the input matrix for appropriate type.
- * **padding_pattern**: CCV\_NO\_PADDING - the first row and the first column in the output matrix is the same as the input matrix. CCV\_PADDING\_ZERO - the first row and the first column in the output matrix is zero, thus, the output matrix size is 1 larger than the input matrix.
+**return**: Dot product.
 
-ccv_sum
--------
+ccv\_sum
+--------
 
-	double ccv_sum(ccv_matrix_t* mat, int flag)
+	double ccv_sum(ccv_matrix_t *mat, int flag)
 
 Return the sum of all elements in the matrix.
 
- * **mat**: the input matrix.
+ * **mat**: The input matrix.
  * **flag**: CCV\_UNSIGNED - compute fabs(x) of the elements first and then sum up. CCV\_SIGNED - compute the sum normally.
 
-ccv_multiply
-------------
+ccv\_variance
+-------------
+
+	double ccv_variance(ccv_matrix_t *mat)
+
+Return the sum of all elements in the matrix.
 
-	void ccv_multiply(ccv_matrix_t* a, ccv_matrix_t* b, ccv_matrix_t** c, int type)
+ * **mat**: The input matrix.
+
+**return**: Element variance of the input matrix.
+
+ccv\_multiply
+-------------
+
+	void ccv_multiply(ccv_matrix_t *a, ccv_matrix_t *b, ccv_matrix_t **c, int type)
 
 Do element-wise matrix multiplication.
 
- * **a**: the input matrix.
- * **b**: the input matrix.
- * **c**: the output matrix.
- * **type**: the type of output matrix, if 0, ccv will try to match the input matrix for appropriate type.
+ * **a**: The input matrix.
+ * **b**: The input matrix.
+ * **c**: The output matrix.
+ * **type**: The type of output matrix, if 0, ccv will try to match the input matrix for appropriate type.
+
+ccv\_add
+--------
+
+	void ccv_add(ccv_matrix_t *a, ccv_matrix_t *b, ccv_matrix_t **c, int type)
 
-ccv_subtract
-------------
+Matrix addition.
 
-	void ccv_subtract(ccv_matrix_t* a, ccv_matrix_t* b, ccv_matrix_t** c, int type)
+ * **a**: The input matrix.
+ * **b**: The input matrix.
+ * **c**: The output matrix.
+ * **type**: The type of output matrix, if 0, ccv will try to match the input matrix for appropriate type.
+
+ccv\_subtract
+-------------
+
+	void ccv_subtract(ccv_matrix_t *a, ccv_matrix_t *b, ccv_matrix_t **c, int type)
 
 Matrix subtraction.
 
- * **a**: the input matrix.
- * **b**: the input matrix.
- * **c**: the output matrix.
- * **type**: the type of output matrix, if 0, ccv will try to match the input matrix for appropriate type.
+ * **a**: The input matrix.
+ * **b**: The input matrix.
+ * **c**: The output matrix.
+ * **type**: The type of output matrix, if 0, ccv will try to match the input matrix for appropriate type.
 
-ccv_scale
----------
+ccv\_scale
+----------
 
-	void ccv_scale(ccv_matrix_t* a, ccv_matrix_t** b, int type, double ds)
+	void ccv_scale(ccv_matrix_t *a, ccv_matrix_t **b, int type, double ds)
 
 Scale given matrix by factor of **ds**.
 
- * **a**: the input matrix.
- * **b**: the output matrix.
- * **type**: the type of output matrix, if 0, ccv will try to match the input matrix for appropriate type.
- * **ds**: the scale factor, `b = a * ds`
+ * **a**: The input matrix.
+ * **b**: The output matrix.
+ * **type**: The type of output matrix, if 0, ccv will try to match the input matrix for appropriate type.
+ * **ds**: The scale factor, `b = a * ds`
 
-ccv_gemm
---------
+ccv\_gemm
+---------
 
-	void ccv_gemm(ccv_matrix_t* a, ccv_matrix_t* b, double alpha, ccv_matrix_t* c, double beta, int transpose, ccv_matrix_t** d, int type)
+	void ccv_gemm(ccv_matrix_t *a, ccv_matrix_t *b, double alpha, ccv_matrix_t *c, double beta, int transpose, ccv_matrix_t **d, int type)
 
 General purpose matrix multiplication. This function has a hard dependency on [cblas](http://www.netlib.org/blas/) library.
 
 As general as it is, it computes:
 
-	alpha * A * B + beta * C
+alpha * A * B + beta * C
 
 whereas A, B, C are matrix, and alpha, beta are scalar.
 
- * **a**: the input matrix.
- * **b**: the input matrix.
- * **alpha**: the multiplication factor.
- * **c**: the input matrix.
- * **beta**: the multiplication factor.
+ * **a**: The input matrix.
+ * **b**: The input matrix.
+ * **alpha**: The multiplication factor.
+ * **c**: The input matrix.
+ * **beta**: The multiplication factor.
  * **transpose**: CCV\_A\_TRANSPOSE, CCV\_B\_TRANSPOSE to indicate if matrix A or B need to be transposed first before multiplication.
- * **d**: the output matrix.
- * **type**: the type of output matrix, if 0, ccv will try to match the input matrix for appropriate type.
+ * **d**: The output matrix.
+ * **type**: The type of output matrix, if 0, ccv will try to match the input matrix for appropriate type.

site/_posts/0000-01-01-ccv-basic.markdown

@@ -11,54 +11,54 @@ categories:
 
 The utilities in this file provides basic pre-processing which, most-likely, are the first steps for computer vision algorithms.
 
-ccv_sobel
----------
+ccv\_sobel
+----------
 
-	void ccv_sobel(ccv_dense_matrix_t* a, ccv_dense_matrix_t** b, int type, int dx, int dy)
+	void ccv_sobel(ccv_dense_matrix_t *a, ccv_dense_matrix_t **b, int type, int dx, int dy)
 
-Compute image with [Sobel operator](https://en.wikipedia.org/wiki/Sobel_operator).
+Compute image with [Sobel operator](https://en.wikipedia.org/wiki/Sobel\_operator).
 
- * **a**: the input matrix.
- * **b**: the output matrix.
- * **type**: the type of output matrix, if 0, ccv will try to match the input matrix for appropriate type.
- * **dx**: the window size of Sobel operator on x-axis, specially optimized for 1, 3
- * **dy**: the window size of Sobel operator on y-axis, specially optimized for 1, 3
+ * **a**: The input matrix.
+ * **b**: The output matrix.
+ * **type**: The type of output matrix, if 0, ccv will try to match the input matrix for appropriate type.
+ * **dx**: The window size of Sobel operator on x-axis, specially optimized for 1, 3
+ * **dy**: The window size of Sobel operator on y-axis, specially optimized for 1, 3
 
-ccv_gradient
-------------
+ccv\_gradient
+-------------
 
-	void ccv_gradient(ccv_dense_matrix_t* a, ccv_dense_matrix_t** theta, int ttype, ccv_dense_matrix_t** m, int mtype, int dx, int dy)
+	void ccv_gradient(ccv_dense_matrix_t *a, ccv_dense_matrix_t **theta, int ttype, ccv_dense_matrix_t **m, int mtype, int dx, int dy)
 
 Compute the gradient (angle and magnitude) at each pixel.
 
- * **a**: the input matrix.
- * **theta**: the output matrix of angle at each pixel.
- * **ttype**: the type of output matrix, if 0, ccv will defaults to CCV\_32F.
- * **m**: the output matrix of magnitude at each pixel.
- * **mtype**: the type of output matrix, if 0, ccv will defaults to CCV\_32F.
- * **dx**: the window size of the underlying Sobel operator used on x-axis, specially optimized for 1, 3
- * **dy**: the window size of the underlying Sobel operator used on y-axis, specially optimized for 1, 3
+ * **a**: The input matrix.
+ * **theta**: The output matrix of angle at each pixel.
+ * **ttype**: The type of output matrix, if 0, ccv will defaults to CCV\_32F.
+ * **m**: The output matrix of magnitude at each pixel.
+ * **mtype**: The type of output matrix, if 0, ccv will defaults to CCV\_32F.
+ * **dx**: The window size of the underlying Sobel operator used on x-axis, specially optimized for 1, 3
+ * **dy**: The window size of the underlying Sobel operator used on y-axis, specially optimized for 1, 3
 
-ccv_flip
---------
+ccv\_flip
+---------
 
-	void ccv_flip(ccv_dense_matrix_t* a, ccv_dense_matrix_t** b, int btype, int type)
+	void ccv_flip(ccv_dense_matrix_t *a, ccv_dense_matrix_t **b, int btype, int type)
 
 Flip the matrix by x-axis, y-axis or both.
 
- * **a**: the input matrix.
- * **b**: the output matrix (it is in-place safe).
- * **btype**: the type of output matrix, if 0, ccv will use the sample type as the input matrix.
+ * **a**: The input matrix.
+ * **b**: The output matrix (it is in-place safe).
+ * **btype**: The type of output matrix, if 0, ccv will use the sample type as the input matrix.
  * **type**: CCV\_FLIP\_X - flip around x-axis, CCV\_FLIP\_Y - flip around y-axis.
 
-ccv_blur
---------
+ccv\_blur
+---------
 
-	void ccv_blur(ccv_dense_matrix_t* a, ccv_dense_matrix_t** b, int type, double sigma)
+	void ccv_blur(ccv_dense_matrix_t *a, ccv_dense_matrix_t **b, int type, double sigma)
 
-Using [Gaussian blur](https://en.wikipedia.org/wiki/Gaussian_blur) on a given matrix. It implements a O(n * sqrt(m)) algorithm, n is the size of input matrix, m is the size of Gaussian filtering kernel.
+Using [Gaussian blur](https://en.wikipedia.org/wiki/Gaussian\_blur) on a given matrix. It implements a O(n * sqrt(m)) algorithm, n is the size of input matrix, m is the size of Gaussian filtering kernel.
 
- * **a**: the input matrix.
- * **b**: the output matrix.
- * **type**: the type of output matrix, if 0, ccv will try to match the input matrix for appropriate type.
- * **sigma**: the sigma factor in Gaussian filtering kernel.
+ * **a**: The input matrix.
+ * **b**: The output matrix.
+ * **type**: The type of output matrix, if 0, ccv will try to match the input matrix for appropriate type.
+ * **sigma**: The sigma factor in Gaussian filtering kernel.