added step parameter

metobs/data/filter.py

@@ -7,7 +7,7 @@ __docformat__ = 'Epytext'
 __author__ = 'David Hoese'
 __version__ = '$Revision: 1.0 $'
 
-def filter_arr(arr, threshold, fill_value=None):
+def filter_arr(arr, threshold, fill_value=None, step=10):
     """Filter array arr of values that have a difference from the trend of
     threshold.  If fill_value is None(default) then a numpy.ma.masked_array will
     be returned with the filtered values being masked.
@@ -18,12 +18,13 @@ def filter_arr(arr, threshold, fill_value=None):
     @type threshold: int or float
     @param fill_value: Value to replace the filtered values with (ex. NaN)
     @type fill_value: anything
+    @param step: filters step points at a time
+    @type step: int
     """
     if type(arr) != ndarray and type(arr) != MaskedArray:
         if fill_value != None: arr = array(arr)
         if fill_value == None: arr = masked_array(arr)
 
-    step = 10
     m = zeros(arr.shape[0])
     for i in range(0, arr.shape[0], step):
         if arr.shape[0] - i < step: step = arr.shape[0] - i
@@ -32,10 +33,6 @@ def filter_arr(arr, threshold, fill_value=None):
             df = abs(mean - arr[i+j])
             if df > threshold: m[i+j] = 1
 
-    #if fill_value != None: diff_arr = zeros(arr.shape[0])
-    #if fill_value == None: diff_arr = mzeros(arr.shape[0])
-    #diff_arr[1:] = diff(arr, n=1)
-
     arr = masked_array(data = arr, mask = m)
     if fill_value != None:
         arr.fill_value = fill_value