climate-dev mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From "ASF GitHub Bot (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (CLIMATE-791) temporal_subset does not work for month_start > month_end
Date Mon, 13 Jun 2016 17:40:21 GMT

    [ https://issues.apache.org/jira/browse/CLIMATE-791?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15327812#comment-15327812
] 

ASF GitHub Bot commented on CLIMATE-791:
----------------------------------------

Github user lewismc commented on a diff in the pull request:

    https://github.com/apache/climate/pull/341#discussion_r66834575
  
    --- Diff: ocw/dataset_processor.py ---
    @@ -68,8 +68,6 @@ def temporal_subset(month_start, month_end, target_dataset, average_each_year=Fa
     
         time_index = np.sort(time_index)
     
    -    time_index = time_index[np.where((time_index >= time_index_first) & (time_index
<= time_index_last))]
    --- End diff --
    
    Did you determine that this is not used?


> temporal_subset does not work for month_start > month_end
> ---------------------------------------------------------
>
>                 Key: CLIMATE-791
>                 URL: https://issues.apache.org/jira/browse/CLIMATE-791
>             Project: Apache Open Climate Workbench
>          Issue Type: Bug
>            Reporter: Ibrahim Jarif
>            Assignee: Ibrahim Jarif
>            Priority: Minor
>
> The following function does not work as expected when the *month_start* is *greater*
than *month_end*. The problem occurs with the last year in the *target_dataset*.
> {code}
> def temporal_subset(month_start, month_end, target_dataset, average_each_year=False):
>     """ Temporally subset data given month_index.
>     :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 target_dataset: Dataset object that needs temporal subsetting
>     :type target_dataset: Open Climate Workbench Dataset Object
>     :param average_each_year: If True, output dataset is averaged for each year
>     :type average_each_year: :class:'boolean'
>     :returns: A temporal subset OCW Dataset
>     :rtype: Open Climate Workbench Dataset Object
>     """
>     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)
>     dates = target_dataset.times
>     months = np.array([d.month for d in dates])
>     time_index = []
>     for m_value in month_index:
>         time_index = np.append(time_index, np.where(months == m_value)[0])
>         if m_value == month_index[0]:
>             time_index_first = np.min(np.where(months == m_value)[0])
>         if m_value == month_index[-1]:
>             time_index_last = np.max(np.where(months == m_value)[0])
>     time_index = np.sort(time_index)
>     time_index = time_index[np.where((time_index >= time_index_first) & (time_index
<= time_index_last))]
>     time_index = list(time_index)
>     new_dataset = ds.Dataset(target_dataset.lats,
>                              target_dataset.lons,
>                              target_dataset.times[time_index],
>                              target_dataset.values[time_index,:],
>                              variable=target_dataset.variable,
>                              units=target_dataset.units,
>                              name=target_dataset.name)
>     if average_each_year:
>         nmonth = len(month_index)
>         ntime  = new_dataset.times.size
>         nyear = ntime/nmonth
>         averaged_time = []              
>         ny, nx = target_dataset.values.shape[1:]
>         averaged_values =ma.zeros([nyear, ny, nx])
>         for iyear in np.arange(nyear):
>             # centered time index of the season between month_start and month_end in
each year
>             center_index = int(nmonth/2)+iyear*nmonth   
>             if nmonth == 1:
>                 center_index = iyear
>             averaged_time.append(new_dataset.times[center_index]) 
>             averaged_values[iyear,:] = ma.average(new_dataset.values[nmonth*iyear:nmonth*iyear+nmonth,:],
axis=0)
>         new_dataset = ds.Dataset(target_dataset.lats,
>                                  target_dataset.lons,
>                                  np.array(averaged_time),
>                                  averaged_values,
>                                  variable=target_dataset.variable,
>                                  units=target_dataset.units,
>                                  name=target_dataset.name)
>     
>     return new_dataset
> {code}
> Example: 
> {code}
> month_start = 8
> month_end = 1
> time = [2000,1,1,0,0,
>             2000,2,1,0,0,
>             2000,3,1,0,0,
>             2000,4,1,0,0,
>             2000,5,1,0,0,
>             2000,6,1,0,0,
>             2000,7,1,0,0,
>             2000,8,1,0,0,
>             2000,9,1,0,0,
>             2000,10,1,0,0,
>             2000,11,1,0,0,
>             2000,12,1,0,0]
> {code}
> The returned dataset should have 
> {code} 
> time = [2000,1,1,0,0,
>             2000,8,1,0,0,
>             2000,9,1,0,0,
>             2000,10,1,0,0
>             2000,11,1,0,0
>             2000,12,1,0,0] 
> {code} But it has {code} time = [2000,1,1,0,0] {code} All the other time values are removed.



--
This message was sent by Atlassian JIRA
(v6.3.4#6332)

Mime
View raw message