Merge pull request #12 from cloudygoose/master

add matrix doc

2 files changed, 55 insertions, 8 deletions

diff --git a/doc/nerv_matrix.md b/doc/nerv_matrix.md
index c710ac8..00356c3 100644
--- a/doc/nerv_matrix.md
+++ b/doc/nerv_matrix.md
@@ -3,12 +3,12 @@ Part of the [Nerv](../README.md) toolkit.
 
 ##Description##
 ###Underlying structure###
-In the begining is could be useful to know something about the underlying structure of a __Nerv__ matrix.  
+In the begining is could be useful to know something about the underlying structure of a __Nerv__ matrix. Please keep in mind that matrice in __Nerv__ is row-major.  
 Every matrix object is a encapsulation of a C struct that describes the attributes of this matrix.  
 ```
 typedef struct Matrix {
     size_t stride;              /* size of a row */
-    long ncol, nrow, nmax;    /* dimension of the matrix */
+    long ncol, nrow, nmax;    /* dimension of the matrix, nmax is simply nrow * ncol */
     union {
         float *f;
         double *d;
@@ -17,16 +17,63 @@ typedef struct Matrix {
     long *data_ref;
 } Matrix;
 ```
-It is worth mentioning that that `data_ref` is a counter which counts the number of references to its memory space, mind that it will also be increased when a row of the matrix is referenced(`col = m[2]`). A __Nerv__ matrix will deallocate its space when this counter is decreased to zero.   
-Also note that all assigning operation in __Nerv__ is reference copy, you can use `copy_tod` or `copy_toh` method to copy value.
+It is worth mentioning that that `data_ref` is a counter which counts the number of references to its memory space, mind that it will also be increased when a row of the matrix is referenced(`col = m[2]`). A __Nerv__ matrix will deallocate its space when this counter is decreased to zero.
+Also note that all assigning operation in __Nerv__ is reference copy, you can use `copy_tod` or `copy_toh` method to copy value. Also, row assigning operations like `m1[2]=m2[3]` is forbidden in __Nerv__.
 
 ###Class hierarchy###
-The class hierarchy of the matrix classes can be clearly observed in `matrix/init.c`.   
+The class hierarchy of the matrix classes can be clearly observed in `matrix/init.c`.
 First there is a abstract base class __Nerv.Matrix__, which is inherited by __Nerv.CuMatrix__ and __Nerv.MMatrix__(also abstract).  
 Finally, there is __Nerv.CuMatrixFloat__, __Nerv.CuMatrixDouble__, inheriting __Nerv.CuMatrix__, and __Nerv.MMatrixFloat__, __Nerv.MMatrixDouble__, inheriting __Nerv.MMatrix__.
 
 ##Methods##
 Mind that usually a matrix object can only do calculation with matrix of its own type(a __Nerv.CuMatrixFloat__ matrix can only do add operation with a __Nerv.CuMatrixFloat__).  
-In the methods description below, __Matrix__ could be __Nerv.CuMatrixFloat__, __Nerv.CuMatrixDouble__, __Nerv.MMatrixFloat__ or __Nerv.MMatrixDouble__.   
+In the methods description below, __Matrix__ could be __Nerv.CuMatrixFloat__, __Nerv.CuMatrixDouble__, __Nerv.MMatrixFloat__ or __Nerv.MMatrixDouble__. __Element_type__ could be `float` or `double`, respectively.
 * __Matrix = Matrix(int nrow, int ncol)__  
-Returns a __Matrix__ object of `nrow` rows and `ncol` columns.
\ No newline at end of file
+Returns a __Matrix__ object of `nrow` rows and `ncol` columns.
+* __Element_type = Matrix.get_elem(Matrix self, int index)__  
+Returns the element value at the specific index(treating the matrix as a vector). The index should be less than `nmax` of the matrix.
+* __void Matrix.set_elem(Matrix self, int index, Element_type value)__  
+Set the value at `index` to be `value`.
+* __int Matrix.ncol(Matrix self)__  
+Get `ncol`, the number of columns.
+* __int Matrix.nrow(Matrix self)__  
+Get `nrow`, the number of rows.
+* __int Matrix.get_dataref_value(Matrix self)__  
+Returns the value(not a pointer) of space the `data_ref` pointer pointed to. This function is mainly for debugging.  
+* __Matrix/Element\_type, boolean Matrix.\_\_index\_\_(Matrix self, int index)__  
+If the matrix has more than one row, will return the row at `index` as a __Matrix__ . Otherwise it will return the value at `index`.
+* __void Matrix.\_\_newindex\_\_(Matrix self, int index, Element_type value)__  
+Set the element at `index` to be `value`.
+---
+* __Matrix Matrix.create(Matrix a)__  
+Return a new __Matrix__ of `a`'s size(of the same number of rows and columns).
+* __Matrix Matrix.colsum(Matrix self)__  
+Return a new __Matrix__ of size (1,`self.ncol`), which stores the sum of all columns of __Matrix__ `self`.
+* __Matrix Matrix.rowsum(Matrix self)__  
+Return a new __Matrix__ of size (`self.nrow`,1), which stores the sum of all rows of __Matrix__ `self`.
+* __Matrix Matrix.rowmax(Matrix self)__  
+Return a new __Matrix__ of size (`self.nrow`,1), which stores the max value of all rows of __Matrix__ `self`.
+* __Matrix Matrix.trans(Matrix self)__  
+Return a new __Matrix__ of size (`self.ncol`,`self.nrow`), which stores the transpose of __Matrix__ `self`.
+* __void Matrix.copy_fromh(Matrix self, MMatrix a)__  
+Copy the content of a __MMatrix__ `a` to __Matrix__ `self`, they should be of the same size.
+* __void Matrix.copy_fromd(Matrix self, CuMatrix a)__  
+Copy the content of a __CuMatrix__ `a` to __Matrix__ `self`, they should be of the same size.
+* __void Matrix.copy_toh(Matrix self, MMatrix a)__  
+Copy the content of the __Matrix__ `self` to a __MMatrix__ `a`.
+* __void Matrix.copy_tod(Matrix self, CuMatrix a)__  
+Copy the content of the __Matrix__ `self` to a __CuMatrix__ `a`.
+* __void Matrix.add(Matrix self, Matrix ma, Matrix mb, Element_type alpha, Element_type beta)__  
+It sets the content of __Matrix__ `self` to be `alpha * ma + beta * mb`.__Matrix__ `ma,mb,self` should be of the same size.
+* __void Matrix.mul(Matrix self, Matrix ma, Matrix mb, Element_type alpha, Element_type beta, [string ta, string tb])__  
+It sets the content of __Matrix__ `self` to be `beta * self + alpha * ma * mb`. `ta` and `tb` is optional, if `ta` is 'T', then `ma` will be transposed, also if `tb` is 'T', `mb` will be transposed.
+* __void Matrix.add_row(Matrix self, Matrix va, Element_type beta)__  
+It sets the content of __Matrix__ `self`(which should be row vector) to be `self + beta * va`.
+* __void Matrix.fill(Matrix self, Element_type value)__  
+Fill the content of __Matrix__ `self` to be `value`.
+* __void Matrix.sigmoid(Matrix self, Matrix ma)__  
+Set the element of __Matrix__ `self` to be elementwise-sigmoid of `ma`.
+* __void Matrix.sigmoid_grad(Matrix self, Matrix err, Matrix output)__  
+Set the element of __Matrix__ `self`, to be `self[i][j]=err[i][j]*output[i][j]*(1-output[i][j])`. This function is used to propagate sigmoid layer error.
+* __void Matrix.softmax(Matrix self, Matrix a)__  
+Calculate a row-by-row softmax of __Matrix__ `a` and save the result in `self`.
diff --git a/matrix/generic/cumatrix.c b/matrix/generic/cumatrix.c
index 58f3679..0df1bd7 100644
--- a/matrix/generic/cumatrix.c
+++ b/matrix/generic/cumatrix.c
@@ -74,7 +74,7 @@ static int nerv_matrix_(mul)(lua_State *L) {
     if (an != bm)
         nerv_error(L, "Wrong dimension of multipliers");
 /*    MATRIX_ELEM alpha = 1.0f, beta = 0.0f; */
-    CUBLAS_SAFE_CALL(
+    CUBLAS_SAFE_CALL( //Because matrix in Nerv is row-major, here b comes first
             NERV_CUBLAS_(gemm)(cublas_handle, tb, ta,
                 bn, am, bm,
                 &alpha,