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From huiky...@apache.org
Subject [2/6] climate git commit: Now the seasonal average calculation works for any OCW dataset objects
Date Tue, 14 Jul 2015 18:26:58 GMT
Now the seasonal average calculation works for any OCW dataset objects


Project: http://git-wip-us.apache.org/repos/asf/climate/repo
Commit: http://git-wip-us.apache.org/repos/asf/climate/commit/4d8fee64
Tree: http://git-wip-us.apache.org/repos/asf/climate/tree/4d8fee64
Diff: http://git-wip-us.apache.org/repos/asf/climate/diff/4d8fee64

Branch: refs/heads/master
Commit: 4d8fee64a2af4280ee90ba23566418703197fc34
Parents: 30d9ff4
Author: huikyole <huikyole.lee@jpl.nasa.gov>
Authored: Tue May 12 01:20:11 2015 -0700
Committer: huikyole <huikyole.lee@jpl.nasa.gov>
Committed: Tue May 12 01:20:11 2015 -0700

----------------------------------------------------------------------
 ocw/dataset_processor.py | 31 ++++++++++++++++++++++++++++++-
 ocw/utils.py             | 32 --------------------------------
 2 files changed, 30 insertions(+), 33 deletions(-)
----------------------------------------------------------------------


http://git-wip-us.apache.org/repos/asf/climate/blob/4d8fee64/ocw/dataset_processor.py
----------------------------------------------------------------------
diff --git a/ocw/dataset_processor.py b/ocw/dataset_processor.py
index 469eb76..a536794 100644
--- a/ocw/dataset_processor.py
+++ b/ocw/dataset_processor.py
@@ -64,7 +64,36 @@ def temporal_subset(target_dataset, month_index):
                              target_dataset.name)
     return new_dataset
 
-def temporal_rebin(target_dataset, temporal_resolution):
+def calc_climatology_season(month_start, month_end, dataset):
+    ''' Calculate seasonal mean and time series for given months.
+
+    :param month_start: An integer for beginning month (Jan=1)
+    :type month_start: :class:`int`
+
+    :param month_end: An integer for ending month (Jan=1)
+    :type month_end: :class:`int`
+
+    :param dataset: OCW dataset object with full-year format
+    :type dataset: :class:`dataset.Dataset`
+
+    :returns: t_series - monthly average over the given season
+              means - mean over the entire season
+
+    '''
+
+    if month_start > month_end:
+        month_index = range(month_start,13)
+        month_index.extend(range(1, month_end+1))
+    else:
+        month_index = range(month_start, month_end+1)
+
+    # t_series only includes data of months in month_index
+    t_series = temporal_subset(dataset, month_index)
+    means = ma.mean(t_series.values, axis=0)
+
+    return t_series, means
+
+def temporal_rebin(target_dataset, temporal_resolution):     
     """ Rebin a Dataset to a new temporal resolution
     
     :param target_dataset: Dataset object that needs temporal rebinned

http://git-wip-us.apache.org/repos/asf/climate/blob/4d8fee64/ocw/utils.py
----------------------------------------------------------------------
diff --git a/ocw/utils.py b/ocw/utils.py
index 607b218..536aa09 100644
--- a/ocw/utils.py
+++ b/ocw/utils.py
@@ -24,7 +24,6 @@ import datetime
 
 from mpl_toolkits.basemap import shiftgrid
 from dateutil.relativedelta import relativedelta
-import ocw.dataset_processor as dsp
 
 def decode_time_values(dataset, time_var_name):
     ''' Decode NetCDF time values into Python datetime objects.
@@ -284,37 +283,6 @@ def calc_climatology_year(dataset):
 
     return annually_mean, total_mean
 
-def calc_climatology_season(month_start, month_end, dataset):
-    ''' Calculate seasonal mean and time series for given months.
-    
-    :param month_start: An integer for beginning month (Jan=1)
-    :type month_start: :class:`int`
-
-    :param month_end: An integer for ending month (Jan=1)
-    :type month_end: :class:`int`
-
-    :param dataset: OCW dataset object with full-year format
-    :type dataset: :class:`dataset.Dataset`
-
-    :returns: t_series - monthly average over the given season
-        means - mean over the entire season
-        
-    '''
-
-    if month_start > month_end:
-        month_index = range(month_start,13)
-	month_index.extend(range(1, month_end+1))
-    else:
-        month_index = range(month_start, month_end+1)
-   
-    # t_series only includes data of months in month_index
-    t_series = dsp.temporal_subset(dataset, month_index).values  
-    print dsp.temporal_subset(dataset, month_index).times
-    means = t_series.mean(axis=0)
-    
-    return t_series, means
-
-
 def calc_climatology_monthly(dataset):
     ''' Calculate monthly mean values for a dataset.
     Follow COARDS climo stats calculation, the year can be given as 0 


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