rename histc2 to bhistc

5 files changed, 13 insertions, 13 deletions

diff --git a/TensorMath.lua b/TensorMath.lua
index e8cb97b..ec875b0 100644
--- a/TensorMath.lua
+++ b/TensorMath.lua
@@ -1089,8 +1089,8 @@ static void THTensor_random1__(THTensor *self, THGenerator *gen, long b)
             {name="double",default=0},
             {name="double",default=0}})
       
-      wrap("histc2",
-           cname("histc2"),
+      wrap("bhistc",
+           cname("bhistc"),
            {{name=Tensor, default=true, returned=true},
             {name=Tensor},
             {name="long",default=100},
diff --git a/doc/maths.md b/doc/maths.md
index 433bf52..b5b1395 100755
--- a/doc/maths.md
+++ b/doc/maths.md
@@ -150,11 +150,11 @@ By default the elements are sorted into 100 equally spaced bins between the mini
 `y = torch.histc(x, n, min, max)` same as above with `n` bins and `[min, max]` as elements range.
 
 
-<a name="torch.histc2"></a>
-### [res] torch.histc2([res,] x [,nbins, min_value, max_value]) ###
-<a name="torch.histc2"></a>
+<a name="torch.bhistc"></a>
+### [res] torch.bhistc([res,] x [,nbins, min_value, max_value]) ###
+<a name="torch.bhistc"></a>
 
-`y = torch.histc2(x)` returns the histogram of the elements in 2d tensor `x` along the last dimension.
+`y = torch.bhistc(x)` returns the histogram of the elements in 2d tensor `x` along the last dimension.
 By default the elements are sorted into 100 equally spaced bins between the minimum and maximum values of `x`.
 
 `y = torch.histc(x, n)` same as above with `n` bins.
@@ -174,7 +174,7 @@ x =torch.Tensor(3, 6)
  3  4  2  5  5  1
 [torch.DoubleTensor of size 3x6]
 
-> torch.histc2(x, 5, 1, 5)
+> torch.bhistc(x, 5, 1, 5)
  0  3  0  2  1
  1  0  2  0  3
  1  1  1  1  2
@@ -182,7 +182,7 @@ x =torch.Tensor(3, 6)
 
 > y = torch.Tensor(1, 6):copy(x[1])
 
-> torch.histc2(y, 5)
+> torch.bhistc(y, 5)
  3  0  2  0  1
 [torch.DoubleTensor of size 1x5]
 ```
diff --git a/lib/TH/generic/THTensorMath.c b/lib/TH/generic/THTensorMath.c
index 765f9c4..fff60a5 100644
--- a/lib/TH/generic/THTensorMath.c
+++ b/lib/TH/generic/THTensorMath.c
@@ -2538,7 +2538,7 @@ void THTensor_(histc)(THTensor *hist, THTensor *tensor, long nbins, real minvalu
   );
 }
 
-void THTensor_(histc2)(THTensor *hist, THTensor *tensor, long nbins, real minvalue, real maxvalue)
+void THTensor_(bhistc)(THTensor *hist, THTensor *tensor, long nbins, real minvalue, real maxvalue)
 {  
   THArgCheck(THTensor_(nDimension)(tensor) < 3, 2, "invalid dimension %d, the input must be a 2d tensor", THTensor_(nDimension)(tensor));
   
diff --git a/lib/TH/generic/THTensorMath.h b/lib/TH/generic/THTensorMath.h
index 3908c27..f5e5c1b 100644
--- a/lib/TH/generic/THTensorMath.h
+++ b/lib/TH/generic/THTensorMath.h
@@ -163,7 +163,7 @@ TH_API void THTensor_(norm)(THTensor *r_, THTensor *t, real value, int dimension
 TH_API void THTensor_(renorm)(THTensor *r_, THTensor *t, real value, int dimension, real maxnorm);
 TH_API accreal THTensor_(dist)(THTensor *a, THTensor *b, real value);
 TH_API void THTensor_(histc)(THTensor *hist, THTensor *tensor, long nbins, real minvalue, real maxvalue);
-TH_API void THTensor_(histc2)(THTensor *hist, THTensor *tensor, long nbins, real minvalue, real maxvalue);
+TH_API void THTensor_(bhistc)(THTensor *hist, THTensor *tensor, long nbins, real minvalue, real maxvalue);
 
 TH_API accreal THTensor_(meanall)(THTensor *self);
 TH_API accreal THTensor_(varall)(THTensor *self);
diff --git a/test/test.lua b/test/test.lua
index 4ab2f4a..f68835b 100644
--- a/test/test.lua
+++ b/test/test.lua
@@ -1355,17 +1355,17 @@ function torchtest.histc()
    local z = torch.Tensor{ 0, 3, 0, 2, 1 }
    mytester:assertTensorEq(y,z,precision,'error in torch.histc')
 end
-function torchtest.histc2()
+function torchtest.bhistc()
    local x = torch.Tensor(3, 6)
    x[1] = torch.Tensor{ 2, 4, 2, 2, 5, 4 }
    x[2] = torch.Tensor{ 3, 5, 1, 5, 3, 5 }
    x[3] = torch.Tensor{ 3, 4, 2, 5, 5, 1 }
-   local y = torch.histc2(x, 5, 1, 5) -- nbins, min, max
+   local y = torch.bhistc(x, 5, 1, 5) -- nbins, min, max
    local z = torch.Tensor(3, 5)
    z[1] = torch.Tensor{ 0, 3, 0, 2, 1 }
    z[2] = torch.Tensor{ 1, 0, 2, 0, 3 }
    z[3] = torch.Tensor{ 1, 1, 1, 1, 2 }
-   mytester:assertTensorEq(y,z,precision,'error in torch.histc2 in last dimension')
+   mytester:assertTensorEq(y,z,precision,'error in torch.bhistc in last dimension')
 end
 function torchtest.ones()
    local mx = torch.ones(msize,msize)