Add string inputs for range parameters of rescale_intensity

doc/source/user_guide/data_types.txt

@@ -134,7 +134,11 @@ dtype range::
 
 Here, the ``in_range`` argument is set to the maximum range for a 10-bit image.
 By default, ``rescale_intensity`` stretches the values of ``in_range`` to match
-the range of the dtype.
+the range of the dtype. ``rescale_intensity`` also accepts strings as inputs
+to ``in_range`` and ``out_range``, so the example above could also be written
+as::
+
+   >>> image = exposure.rescale_intensity(img10bit, in_range='uint10')
 
 
 Note about negative values

skimage/exposure/exposure.py

@@ -7,8 +7,16 @@ from skimage._shared.utils import deprecated
 
 
 __all__ = ['histogram', 'cumulative_distribution', 'equalize',
-           'rescale_intensity', 'adjust_gamma',
-           'adjust_log', 'adjust_sigmoid']
+           'rescale_intensity', 'adjust_gamma', 'adjust_log', 'adjust_sigmoid']
+
+
+DTYPE_RANGE = dtype_range.copy()
+DTYPE_RANGE.update((d.__name__, limits) for d, limits in dtype_range.items())
+DTYPE_RANGE.update({'uint10': (0, 2**10 - 1),
+                    'uint12': (0, 2**12 - 1),
+                    'uint14': (0, 2**14 - 1),
+                    'bool': dtype_range[np.bool_],
+                    'float': dtype_range[np.float64]})
 
 
 def histogram(image, nbins=256):
@@ -143,14 +151,15 @@ def rescale_intensity(image, in_range=None, out_range=None):
     ----------
     image : array
         Image array.
-    in_range : 2-tuple (float, float)
+    in_range : 2-tuple (float, float) or str
         Min and max *allowed* intensity values of input image. If None, the
         *allowed* min/max values are set to the *actual* min/max values in the
-        input image.
-    out_range : 2-tuple (float, float)
+        input image. Intensity values outside this range are clipped.
+        If string, use data limits of dtype specified by the string.
+    out_range : 2-tuple (float, float) or str
         Min and max intensity values of output image. If None, use the min/max
         intensities of the image data type. See `skimage.util.dtype` for
-        details.
+        details. If string, use data limits of dtype specified by the string.
 
     Returns
     -------
@@ -201,11 +210,16 @@ def rescale_intensity(image, in_range=None, out_range=None):
     if in_range is None:
         imin = np.min(image)
         imax = np.max(image)
+    elif in_range in DTYPE_RANGE:
+        imin, imax = DTYPE_RANGE[in_range]
     else:
         imin, imax = in_range
 
-    if out_range is None:
-        omin, omax = dtype_range[dtype]
+    if out_range is None or out_range in DTYPE_RANGE:
+        out_range = dtype if out_range is None else out_range
+        if out_range is None:
+            out_range
+        omin, omax = DTYPE_RANGE[out_range]
         if imin >= 0:
             omin = 0
     else:

skimage/exposure/tests/test_exposure.py

@@ -44,6 +44,11 @@ def check_cdf_slope(cdf):
 # Test rescale intensity
 # ======================
 
+
+uint10_max = 2**10 - 1
+uint16_max = 2**16 - 1
+
+
 def test_rescale_stretch():
     image = np.array([51, 102, 153], dtype=np.uint8)
     out = exposure.rescale_intensity(image)
@@ -76,6 +81,18 @@ def test_rescale_out_range():
     assert_close(out, [0, 63, 127])
 
 
+def test_rescale_named_in_range():
+    image = np.array([0, uint10_max, uint10_max + 100], dtype=np.uint16)
+    out = exposure.rescale_intensity(image, in_range='uint10')
+    assert_close(out, [0, uint16_max, uint16_max])
+
+
+def test_rescale_named_out_range():
+    image = np.array([0, uint16_max], dtype=np.uint16)
+    out = exposure.rescale_intensity(image, out_range='uint10')
+    assert_close(out, [0, uint10_max])
+
+
 # Test adaptive histogram equalization
 # ====================================