Bring hooke.config and hooke.util.peak doctests up to speed

diff --git a/hooke/config.py b/hooke/config.py
index 5f9e91942cb48fccacd7392a35436f5992d382e5..6d9ccebaea40f448b018bbc1ef6eec54be317ba1 100644 (file)
--- a/hooke/config.py
+++ b/hooke/config.py
@@ -131,10 +131,18 @@ class HookeConfigParser (configparser.SafeConfigParser):
     >>> c = HookeConfigParser(paths=DEFAULT_PATHS,
     ...                       default_settings=DEFAULT_SETTINGS)
     >>> c.write(sys.stdout) # doctest: +ELLIPSIS
-    # Control display appearance: colour, ???, etc.
-    [display]
-    colour_ext = None
-    colour_ret = None
+    # Default environmental conditions in case they are not specified in
+    # the force curve data.
+    [conditions]
+    # Temperature in Kelvin
+    temperature = 301
+    <BLANKLINE>
+    # Configure loggers, see
+    # http://docs.python.org/library/logging.html#configuration-file-format
+    [loggers]
+    # Hooke only uses the hooke logger, but other included modules may
+    # also use logging and you can configure their loggers here as well.
+    keys = root, hooke
     ...
     """
     def __init__(self, paths=None, default_settings=None, defaults=None,

diff --git a/hooke/util/peak.py b/hooke/util/peak.py
index 185f04d760e2993a454996b28d45c422c78bfcfa..137763baaf21bfa0250aa308d7eccbce9e815b11 100644 (file)
--- a/hooke/util/peak.py
+++ b/hooke/util/peak.py
@@ -323,12 +323,12 @@ def above_noise(data, side='both', min_deviations=5.0, mean=None, std=None):
     --------
 
     >>> data = numpy.arange(-3, 4)
-    >>> above_noise(data, side='both', min_deviations=1.0, mean=0, std=1.0)
-    array([ True, False, False, False, False, False,  True], dtype=bool)
-    >>> above_noise(data, side='positive', min_deviations=1.0, mean=0, std=1.0)
-    array([False, False, False, False, False, False,  True], dtype=bool)
-    >>> above_noise(data, side='negative', min_deviations=1.0, mean=0, std=1.0)
-    array([ True, False, False, False, False, False, False], dtype=bool)
+    >>> above_noise(data, side='both', min_deviations=1.1, mean=0, std=1.0)
+    array([ True,  True, False, False, False,  True,  True], dtype=bool)
+    >>> above_noise(data, side='positive', min_deviations=1.1, mean=0, std=1.0)
+    array([False, False, False, False, False,  True,  True], dtype=bool)
+    >>> above_noise(data, side='negative', min_deviations=1.1, mean=0, std=1.0)
+    array([ True,  True, False, False, False, False, False], dtype=bool)
     """
     if mean == None:
         mean = data.mean()