From cc8b9ab3d75bb7436242d47b0478aa35798332b0 Mon Sep 17 00:00:00 2001
From: Andreas Kloeckner <inform@tiker.net>
Date: Sun, 23 Sep 2012 10:54:43 -0500
Subject: [PATCH] Make image_from_array() support vector types.

---
 doc/source/array.rst   |  2 ++
 doc/source/runtime.rst |  9 +++++++--
 pyopencl/__init__.py   | 23 +++++++++++++++++------
 pyopencl/array.py      |  4 ++++
 4 files changed, 30 insertions(+), 8 deletions(-)

diff --git a/doc/source/array.rst b/doc/source/array.rst
index d747369c..cf0f080c 100644
--- a/doc/source/array.rst
+++ b/doc/source/array.rst
@@ -14,6 +14,8 @@ type system, as represented by :class:`numpy.dtype`, and the types
 available in OpenCL. All the simple scalar types map straightforwardly
 to their CL counterparts.
 
+.. _vector-types:
+
 Vector Types
 ^^^^^^^^^^^^
 
diff --git a/doc/source/runtime.rst b/doc/source/runtime.rst
index a872fc19..f3f84867 100644
--- a/doc/source/runtime.rst
+++ b/doc/source/runtime.rst
@@ -480,11 +480,13 @@ Images
 
     |comparable|
 
-.. function:: image_from_array(ctx, ary, num_channels, mode="r", norm_int=False)
+.. function:: image_from_array(ctx, ary, num_channels=None, mode="r", norm_int=False)
 
     Build a 2D or 3D :class:`Image` from the :class:`numpy.ndarray` *ary*.  If
     *num_channels* is greater than one, the last dimension of *ary* must be
-    identical to *num_channels*. *ary* must be in C order.
+    identical to *num_channels*. *ary* must be in C order. If *num_channels* is
+    not given, it defaults to 1 for scalar types and the number of entries
+    for :ref:`vector-types`.
 
     The :class:`ImageFormat` is chosen as the first *num_channels* components
     of "RGBA".
@@ -497,6 +499,9 @@ Images
         in the reverse order from what they would be when accessing *ary* from
         Python.
 
+    If *norm_int* is `True`, then the integer values are normalized to a floating
+    point scale of 0..1 when read.
+
     .. versionadded:: 2011.2
 
 .. function:: enqueue_fill_image(queue, mem, color, origin, region, wait_for=None)
diff --git a/pyopencl/__init__.py b/pyopencl/__init__.py
index 95e9283c..70c56409 100644
--- a/pyopencl/__init__.py
+++ b/pyopencl/__init__.py
@@ -882,13 +882,24 @@ DTYPE_TO_CHANNEL_TYPE_NORM = {
     np.dtype(np.uint8): channel_type.UNORM_INT8,
     }
 
-def image_from_array(ctx, ary, num_channels, mode="r", norm_int=False):
-    # FIXME what about vector types?
-
+def image_from_array(ctx, ary, num_channels=None, mode="r", norm_int=False):
     if not ary.flags.c_contiguous:
         raise ValueError("array must be C-contiguous")
 
-    if num_channels == 1:
+    dtype = ary.dtype
+    if num_channels is None:
+
+        from pyopencl.array import vec
+        try:
+            dtype, num_channels = vec.type_to_scalar_and_count[dtype]
+        except KeyError:
+            # It must be a scalar type then.
+            pass
+
+        shape = ary.shape
+        strides = ary.strides
+
+    elif num_channels == 1:
         shape = ary.shape
         strides = ary.strides
     else:
@@ -915,9 +926,9 @@ def image_from_array(ctx, ary, num_channels, mode="r", norm_int=False):
     assert ary.strides[-1] == ary.dtype.itemsize
 
     if norm_int:
-        channel_type = DTYPE_TO_CHANNEL_TYPE_NORM[ary.dtype]
+        channel_type = DTYPE_TO_CHANNEL_TYPE_NORM[dtype]
     else:
-        channel_type = DTYPE_TO_CHANNEL_TYPE[ary.dtype]
+        channel_type = DTYPE_TO_CHANNEL_TYPE[dtype]
 
     return Image(ctx, mode_flags | mem_flags.COPY_HOST_PTR,
             ImageFormat(img_format, channel_type),
diff --git a/pyopencl/array.py b/pyopencl/array.py
index 9e487988..fd40e16c 100644
--- a/pyopencl/array.py
+++ b/pyopencl/array.py
@@ -62,7 +62,10 @@ def _create_vector_types():
     from pyopencl.tools import get_or_register_dtype
 
     vec.types = {}
+    vec.type_to_scalar_and_count = {}
+
     counts = [2, 3, 4, 8, 16]
+
     for base_name, base_type in [
         ('char', np.int8),
         ('uchar', np.uint8),
@@ -101,6 +104,7 @@ def _create_vector_types():
                         dict(array=np.array, my_dtype=dtype))))
 
             vec.types[np.dtype(base_type), count] = dtype
+            vec.type_to_scalar_and_count[dtype] = np.dtype(base_type), count
 
 _create_vector_types()
 
-- 
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