added getting-started examples

Author: Chaluvadi

examples/getting_started/convolve.py

@@ -0,0 +1,50 @@
+#!/usr/bin/python
+
+#######################################################
+# Copyright (c) 2024, ArrayFire
+# All rights reserved.
+#
+# This file is distributed under 3-clause BSD license.
+# The complete license agreement can be obtained at:
+# http://arrayfire.com/licenses/BSD-3-Clause
+########################################################
+
+import sys
+from array import array
+
+# from time import time
+from timeit import timeit
+
+import arrayfire as af
+from arrayfire.library.signal_processing import convolve2, convolve2_separable
+
+
+def af_assert(left, right, eps=1e-6):
+    if af.max(af.abs(left - right)) > eps:
+        raise ValueError("Arrays not within dictated precision")
+    return
+
+
+if __name__ == "__main__":
+    if len(sys.argv) > 1:
+        af.set_device(int(sys.argv[1]))
+    af.info()
+
+    h_dx = array("f", (1.0 / 12, -8.0 / 12, 0, 8.0 / 12, 1.0 / 12))
+    h_spread = array("f", (1.0 / 5, 1.0 / 5, 1.0 / 5, 1.0 / 5, 1.0 / 5))
+
+    img = af.randu((640, 480))
+    dx = af.Array(obj=h_dx, shape=(5, 1))
+    spread = af.Array(obj=h_spread, shape=(1, 5))
+    kernel = af.matmul(dx, spread)
+
+    full_res = convolve2(img, kernel)
+    sep_res = convolve2_separable(dx, spread, img)
+
+    af_assert(full_res, sep_res)
+
+    time_convolve2 = timeit(lambda: convolve2(img, kernel), number=1000)
+    print(f"full 2D convolution time: {time_convolve2 * 1000:.5f} ms")
+
+    time_convolve2_sep = timeit(lambda: convolve2_separable(dx, spread, img), number=1000)
+    print(f"full separable 2D convolution time: {time_convolve2_sep * 1000:.5f} ms")

examples/getting_started/intro.py

@@ -0,0 +1,78 @@
+#!/usr/bin/python
+
+#######################################################
+# Copyright (c) 2024, ArrayFire
+# All rights reserved.
+#
+# This file is distributed under 3-clause BSD license.
+# The complete license agreement can be obtained at:
+# http://arrayfire.com/licenses/BSD-3-Clause
+########################################################
+
+import sys
+from array import array
+
+import arrayfire as af
+from arrayfire.array_object import _array_as_str
+
+if __name__ == "__main__":
+    if len(sys.argv) > 1:
+        af.set_device(int(sys.argv[1]))
+    af.info()
+
+    print("\n---- Intro to ArrayFire using unsigned(s32) arrays ----\n")
+
+    h_A = array("i", (1, 2, 4, -1, 2, 0, 4, 2, 3))
+    h_B = array("i", (2, 3, 5, 6, 0, 10, -12, 0, 1))
+
+    A = af.Array(obj=h_A, shape=(3, 3), dtype=af.int32)
+    B = af.Array(obj=h_B, shape=(3, 3), dtype=af.int32)
+
+    print("\n---- Sub referencing and sub assignment\n")
+    print(_array_as_str(A))
+    print(_array_as_str(A[0, :]))
+    print(_array_as_str(A[:, 0]))
+    A[0, 0] = 11
+    A[1] = 100
+    print(_array_as_str(A))
+    print(_array_as_str(B))
+    A[1, :] = B[2, :]
+    print(_array_as_str(A))
+
+    b_A = array("I", (1, 1, 1, 0, 1, 1, 0, 0, 0))
+    b_B = array("I", (1, 0, 1, 0, 1, 0, 1, 0, 1))
+
+    C = af.Array(obj=b_A, shape=(3, 3), dtype=af.uint32)
+    D = af.Array(obj=b_B, shape=(3, 3), dtype=af.uint32)
+    print(_array_as_str(C))
+    print(_array_as_str(D))
+
+    print("\n---- Bitwise operations\n")
+    print(_array_as_str(af.bitand(C, D)))
+    print(_array_as_str(af.bitor(C, D)))
+    print(_array_as_str(af.bitxor(C, D)))
+
+    print("\n---- Transpose\n")
+    print(_array_as_str(A))
+    print(_array_as_str(af.transpose(A)))
+
+    print("\n---- Flip Vertically / Horizontally\n")
+    print(_array_as_str(A))
+    print(_array_as_str(af.flip(A, axis=0)))
+    print(_array_as_str(af.flip(A, axis=1)))
+
+    print("\n---- Sum, Min, Max along row / columns\n")
+    print(_array_as_str(A))
+    print(_array_as_str(af.min(A, axis=0)))  # type: ignore[arg-type]
+    print(_array_as_str(af.max(A, axis=0)))  # type: ignore[arg-type]
+
+    print(_array_as_str(af.min(A, axis=1)))  # type: ignore[arg-type]
+    print(_array_as_str(af.max(A, axis=1)))  # type: ignore[arg-type]
+
+    print(_array_as_str(af.sum(A, axis=0)))  # type: ignore[arg-type]
+    print(_array_as_str(af.sum(A, axis=1)))  # type: ignore[arg-type]
+
+    print("\n---- Get minimum with index\n")
+    (min_val, min_idx) = af.imin(A, axis=0)
+    print(_array_as_str(min_val))  # type: ignore[arg-type]
+    print(_array_as_str(min_idx))  # type: ignore[arg-type]