Updated the convolve benchmark

benchpress/benchmarks/convolve/python_numpy/convolve.py

@@ -1,59 +1,28 @@
 from __future__ import print_function
-from PIL import Image
 from benchpress import util
 import numpy as np
-from bohrium.stdviews import cartesian
-
-def apply_filter(size, weight):
-    """TODO: And what does this one do?"""
-
-    kernel      = np.zeros((size, size))
-    totalsum    = 0
-    kernelrad   = size/2
-    distance    = 0
-    caleuler    = 1.0 /(2.0 * np.pi * weight**2)
-
-    for filterY in range(-kernelrad, kernelrad+1, 1): 
-        for filterX in range(-kernelrad, kernelrad+1, 1): 
-            distance = ((filterX * filterX)+(filterY*filterY))/(2 * (weight * weight)) 
-            kernel[filterY + kernelrad,filterX + kernelrad] = caleuler * np.exp(-distance) 
-            totalsum += kernel[filterY + kernelrad, filterX + kernelrad] 
-    kernel *= (1.0/totalsum)
-
-    return kernel
-
-def convolve_init(fsize, photo='/tmp/Hell.jpg'):
-    """TODO: Describe the data loaded/generated by this function."""
-
-    img     = Image.open(photo)
-    rgb     = np.array(img)
-    tones   = np.array((0.3, 0.6, 0.11))
-    rgb     = np.add.reduce((rgb*tones[np.newaxis, np.newaxis, :]), axis=2)
-    kernel  = apply_filter(fsize, 13.0)
-
-    return (rgb, kernel)
-
-def convolve(image, image_filter):
-    """TODO: Describe the benchmark."""
-
-    views   = cartesian(image, len(image_filter))
-    result  = sum(d[0]*d[1] for d in zip(views, image_filter.flatten()))
-
-    return result
 
 def main():
     """
-    Example parameter: --size=25.
-    This will execute on a something related to 25....
+    Example parameter : --size=10000000*10*10
     """
     B = util.Benchmark()
-    (N,) = B.size
-    image, image_filter = convolve_init(N)
-
+    (image_size, filter_size, I) = B.size
+
+    image = B.random_array((image_size,))
+    image_filter = B.random_array((filter_size,))
+
     B.start()
-    result = convolve(image, image_filter)
+    for _ in range(I):
+        R = np.convolve(image, image_filter)
+        B.flush()
     B.stop()
     B.pprint()
+    if B.outputfn:
+        B.tofile(B.outputfn, {'res': R})
+
+    if B.verbose:
+        print (R)
 
 if __name__ == "__main__":
     main()