From 0b7df2626a8bdec47013d40c5f91088b8b391313 Mon Sep 17 00:00:00 2001
From: Stefan van der Walt <stefan@sun.ac.za>
Date: Tue, 27 Sep 2011 01:16:35 -0700
Subject: [PATCH] ENH: Add img_as_ubyte.

---
 scikits/image/util/__init__.py         |  2 ++
 scikits/image/util/dtype.py            | 24 +++++++++++++++++++++++-
 scikits/image/util/tests/test_dtype.py |  6 ++++--
 3 files changed, 29 insertions(+), 3 deletions(-)
 create mode 100644 scikits/image/util/__init__.py

diff --git a/scikits/image/util/__init__.py b/scikits/image/util/__init__.py
new file mode 100644
index 00000000..6eb4da1c
--- /dev/null
+++ b/scikits/image/util/__init__.py
@@ -0,0 +1,2 @@
+from dtype import *
+
diff --git a/scikits/image/util/dtype.py b/scikits/image/util/dtype.py
index 8a690689..7e86892a 100644
--- a/scikits/image/util/dtype.py
+++ b/scikits/image/util/dtype.py
@@ -1,7 +1,7 @@
 from __future__ import division
 import numpy as np
 
-__all__ = ['img_as_float', 'img_as_int', 'img_as_uint']
+__all__ = ['img_as_float', 'img_as_int', 'img_as_uint', 'img_as_ubyte']
 
 from .. import get_log
 log = get_log('dtype_converter')
@@ -146,3 +146,25 @@ def img_as_int(image):
     """
     prec_loss = (np.float32, np.float64, np.uint16)
     return _convert(image, np.int16, prec_loss)
+
+def img_as_ubyte(image):
+    """Convert an image to 8-bit unsigned integer format.
+
+    Parameters
+    ----------
+    image : ndarray
+        Input image.
+
+    Returns
+    -------
+    out : ndarray of ubyte (uint8)
+        Output image.
+
+    Notes
+    -----
+    If the input data-type is positive-only (e.g., uint16), then
+    the output image will still only have positive values.
+
+    """
+    prec_loss = (np.float32, np.float64, np.uint16, np.int16, np.int8)
+    return _convert(image, np.ubyte, prec_loss)
diff --git a/scikits/image/util/tests/test_dtype.py b/scikits/image/util/tests/test_dtype.py
index a3ef2377..d7cc3259 100644
--- a/scikits/image/util/tests/test_dtype.py
+++ b/scikits/image/util/tests/test_dtype.py
@@ -1,6 +1,7 @@
 import numpy as np
 from numpy.testing import assert_equal
-from scikits.image import img_as_int, img_as_float, img_as_uint
+from scikits.image import img_as_int, img_as_float, \
+                          img_as_uint, img_as_ubyte
 
 dtype_range = {np.uint8: (0, 255),
                np.uint16: (0, 65535),
@@ -20,7 +21,8 @@ def test_range():
 
         for (f, dt) in [(img_as_int, np.int16),
                         (img_as_float, np.float64),
-                        (img_as_uint, np.uint16)]:
+                        (img_as_uint, np.uint16),
+                        (img_as_ubyte, np.ubyte)]:
             y = f(x)
 
             omin, omax = dtype_range[dt]