Fix 'min deviation' -> 'min deviations' typos.

In hooke.util.peak and hooke.plugin.convfilt/flatfilt.

Also:
  * Fix "std == data.std" typo in hooke.util.peak.above_noise
  * Pass mean and std from noise to above_noise in find_peaks.

diff --git a/hooke/plugin/convfilt.py b/hooke/plugin/convfilt.py
index 37794ad952e4b10d38b74c2b72a4f5d1c2c7a1a8..7400f22830f057b3468dc4fba45f025d36198ce8 100644 (file)
--- a/hooke/plugin/convfilt.py
+++ b/hooke/plugin/convfilt.py
@@ -72,7 +72,7 @@ Minimum number of peaks for curve acceptance.
         for key,value in [('cut side', 'positive'),
                           ('stable', 0.005),
                           ('max cut', 0.2),
-                          ('min deviation', 5.0),
+                          ('min deviations', 5.0),
                           ('min points', 1),
                           ('see double', 10e-9),
                           ]:

diff --git a/hooke/plugin/flatfilt.py b/hooke/plugin/flatfilt.py
index 25abf758d8e4008efd0e009f0d34ea1c61ade410..a1d5e8361257d25e5fb2500d165d6e8dfa1fd3ff 100644 (file)
--- a/hooke/plugin/flatfilt.py
+++ b/hooke/plugin/flatfilt.py
@@ -62,7 +62,7 @@ Median window filter size (in points).
         for key,value in [('cut side', 'both'),
                           ('stable', 0.005),
                           ('max cut', 0.2),
-                          ('min deviation', 9.0),
+                          ('min deviations', 9.0),
                           ('min points', 4),
                           ('see double', 10e-9),
                           ]:
@@ -163,7 +163,7 @@ Number of points to use in the initial rolling median filter.
             if value == None: # Use configured default value.
                 params[key] = self.plugin.config[key]
         # TODO: better option parser to do this automatically by Argument.type
-        for key in ['max cut', 'min deviation', 'min points', 'see double', 'stable']:
+        for key in ['max cut', 'min deviations', 'min points', 'see double', 'stable']:
             params[key] = float(params[key])
         # TODO: convert 'see double' from nm to points
         return z_data,d_data,params

diff --git a/hooke/util/peak.py b/hooke/util/peak.py
index 32ec79ff0058df469b72ce32f99488286f68ca44..f980267390d1d5211d5f63b4f69188bd368a6fb1 100644 (file)
--- a/hooke/util/peak.py
+++ b/hooke/util/peak.py
@@ -333,7 +333,7 @@ def above_noise(data, side='both', min_deviations=5.0, mean=None, std=None):
     if mean == None:
         mean = data.mean()
     if std == None:
-        std == data.std()
+        std = data.std()
     if side == 'negative':
         data = -data
         mean = -mean
@@ -348,7 +348,7 @@ above_noise_arguments = [
 Select the side of the curve that counts as "above".  `positive`,
 `negative`, or `both`.
 """.strip()),
-    Argument('min deviation', type='float', default=5.0, help="""
+    Argument('min deviations', type='float', default=5.0, help="""
 Number of standard deviations above the noise to define a peak.
 Increase to tighten the filter.
 """.strip()),
@@ -504,7 +504,8 @@ def find_peaks(data, **kwargs):
     The input parameters may be any accepted by the above functions.
     """
     mask,mean,std,converged = noise(data, **_kwargs(kwargs, noise_arguments))
-    mask = above_noise(data, **_kwargs(kwargs, above_noise_arguments))
+    mask = above_noise(data, mean=mean, std=std,
+                       **_kwargs(kwargs, above_noise_arguments))
     peaks = mask_to_peaks(data, mask)
     peaks = merge_double_peaks(
         data, peaks, **_kwargs(kwargs, merge_double_peaks_arguments))