Merge branch 'master' into devel

Author: pavanky

CHANGELOG.md

@@ -1,3 +1,14 @@
+### v3.3.20160510
+- Bugfix to `af.histogram`
+
+- Added missing functions / methods
+   - `gaussian_kernel`
+
+- Added new array properties
+   - `Array.T` now returns transpose
+   - `Array.H` now returns hermitian transpose
+   - `Array.shape` now allows easier access individual dimensions
+
 ### v3.3.20160427
 - Fixes to numpy interop on Windows
 - Fixes issues with occasional double free

arrayfire/array.py

@@ -577,6 +577,20 @@ def type(self):
         """
         return self.dtype().value
 
+    @property
+    def T(self):
+        """
+        Return the transpose of the array
+        """
+        return transpose(self, False)
+
+    @property
+    def H(self):
+        """
+        Return the hermitian transpose of the array
+        """
+        return transpose(self, False)
+
     def dims(self):
         """
         Return the shape of the array as a tuple.
@@ -590,6 +604,13 @@ def dims(self):
         dims = (d0.value,d1.value,d2.value,d3.value)
         return dims[:self.numdims()]
 
+    @property
+    def shape(self):
+        """
+        The shape of the array
+        """
+        return self.dims()
+
     def numdims(self):
         """
         Return the number of dimensions of the array.

arrayfire/image.py

@@ -408,7 +408,7 @@ def histogram(image, nbins, min_val = None, max_val = None):
     output = Array()
     safe_call(backend.get().af_histogram(ct.pointer(output.arr),
                                          image.arr, ct.c_uint(nbins),
-                                         ct.c_float(min_val), ct.c_float(max_val)))
+                                         ct.c_double(min_val), ct.c_double(max_val)))
     return output
 
 def hist_equal(image, hist):
@@ -769,6 +769,48 @@ def sobel_derivatives(image, w_len=3):
                                               image.arr, ct.c_uint(w_len)))
     return dx,dy
 
+def gaussian_kernel(rows, cols, sigma_r = None, sigma_c = None):
+    """
+    Create a gaussian kernel with the given parameters.
+
+    Parameters
+    ----------
+    image : af.Array
+          - A 2 D arrayfire array representing an image, or
+          - A multi dimensional array representing batch of images.
+
+    rows : int
+         - The number of rows in the gaussian kernel.
+
+    cols : int
+         - The number of columns in the gaussian kernel.
+
+    sigma_r : optional: number. default: None.
+         - The sigma value along rows
+         - If None, calculated as (0.25 * rows + 0.75)
+
+    sigma_c : optional: number. default: None.
+         - The sigma value along columns
+         - If None, calculated as (0.25 * cols + 0.75)
+
+    Returns
+    -------
+    out   : af.Array
+          - A gaussian kernel of size (rows, cols)
+    """
+    out = Array()
+
+    if (sigma_r is None):
+        sigma_r = 0.25 * rows + 0.75
+
+    if (sigma_c is None):
+        sigma_c = 0.25 * cols + 0.75
+
+    safe_call(backend.get().af_gaussian_kernel(ct.pointer(out.arr),
+                                               ct.c_int(rows), ct.c_int(cols),
+                                               ct.c_double(sigma_r), ct.c_double(sigma_c)))
+    return out
+
 def sobel_filter(image, w_len = 3, is_fast = False):
     """
     Apply sobel filter to the image.

tests/simple/array_test.py

@@ -18,6 +18,9 @@ def simple_array(verbose=False):
 
     a = af.Array([1, 2, 3])
     display_func(a)
+    display_func(a.T)
+    display_func(a.H)
+    print_func(a.shape)
 
     b = a.as_type(af.Dtype.s32)
     display_func(b)

tests/simple/image.py

@@ -54,6 +54,8 @@ def simple_image(verbose = False):
     display_func(dx)
     display_func(dy)
     display_func(af.sobel_filter(a))
+    display_func(af.gaussian_kernel(3, 3))
+    display_func(af.gaussian_kernel(3, 3, 1, 1))
 
     ac = af.gray2rgb(a)
     display_func(ac)