Issues with Test Cases

[Ibrahim Jarif <ja...@gmail.com>]

Why does the following function

==================================================================
def _rcmes_calc_average_on_new_time_unit(data, dates, unit):
 """ Rebin 3d array and list of dates using the provided unit parameter

    :param data: Input data that needs to be averaged
    :type data: 3D masked numpy array of shape (times, lats, lons)
    :param dates: List of dates that correspond to the given data values
    :type dates: Python datetime objects
    :param unit: Time unit to average the data into
    :type unit: String matching one of these values : full | annual |
monthly | daily

    :returns: meanstorem, newTimesList
    :rtype: 3D numpy masked array the same shape as the input array, list
of python datetime objects
    """

    # Check if the user-selected temporal grid is valid. If not, EXIT
    acceptable =
(unit=='full')|(unit=='annual')|(unit=='monthly')|(unit=='daily')
    if not acceptable:
        print 'Error: unknown unit type selected for time averaging: EXIT'
        return -1,-1,-1,-1

    nt, ny, nx = data.shape
    if unit == 'full':
        new_data = ma.mean(data, axis=0)
        new_date = [dates[dates.size/2]]
    if unit == 'annual':
        years = [d.year for d in dates]
        years_sorted = np.unique(years)
        new_data = ma.zeros([years_sorted.size, ny, nx])
        it = 0
        new_date = []
        for year in years_sorted:
            index = np.where(years == year)[0]
            new_data[it,:] = ma.mean(data[index,:], axis=0)
            new_date.append(datetime.datetime(year=year, month=7, day=2))
            it = it+1

=======================================
have new_date.append(datetime.datetime(year=year, month=7, day=2) ?
Shouldn't it be datetime(year=year, month=1, day=1) ?

Re: Issues with Test Cases

[Ibrahim Jarif <ja...@gmail.com>]

If that's the case, why is it being compared with ten_year_annual_times
generated like

==============================================================================
ten_year_annual_times = np.array([datetime.datetime(year, 1, 1) for year in
range(2000, 2010)])
==============================================================================

in testing?

This test will always return false.

Re: Issues with Test Cases

[Michael Anderson <mi...@gmail.com>]

Others can correct me, but I believe it's normalizing to the mid point of
the interval.  July 2nd is the halfway point in the year just as the next
section new_date.append(datetime.datetime(year=year, month=month, day=15))
the 15th is more or less the middle of the month when the unit is monthly.

On Fri, Feb 26, 2016 at 11:28 AM, Ibrahim Jarif <ja...@gmail.com>
wrote:

> Why does the following function
>
> ==================================================================
> def _rcmes_calc_average_on_new_time_unit(data, dates, unit):
>  """ Rebin 3d array and list of dates using the provided unit parameter
>
>     :param data: Input data that needs to be averaged
>     :type data: 3D masked numpy array of shape (times, lats, lons)
>     :param dates: List of dates that correspond to the given data values
>     :type dates: Python datetime objects
>     :param unit: Time unit to average the data into
>     :type unit: String matching one of these values : full | annual |
> monthly | daily
>
>     :returns: meanstorem, newTimesList
>     :rtype: 3D numpy masked array the same shape as the input array, list
> of python datetime objects
>     """
>
>     # Check if the user-selected temporal grid is valid. If not, EXIT
>     acceptable =
> (unit=='full')|(unit=='annual')|(unit=='monthly')|(unit=='daily')
>     if not acceptable:
>         print 'Error: unknown unit type selected for time averaging: EXIT'
>         return -1,-1,-1,-1
>
>     nt, ny, nx = data.shape
>     if unit == 'full':
>         new_data = ma.mean(data, axis=0)
>         new_date = [dates[dates.size/2]]
>     if unit == 'annual':
>         years = [d.year for d in dates]
>         years_sorted = np.unique(years)
>         new_data = ma.zeros([years_sorted.size, ny, nx])
>         it = 0
>         new_date = []
>         for year in years_sorted:
>             index = np.where(years == year)[0]
>             new_data[it,:] = ma.mean(data[index,:], axis=0)
>             new_date.append(datetime.datetime(year=year, month=7, day=2))
>             it = it+1
>
> =======================================
> have new_date.append(datetime.datetime(year=year, month=7, day=2) ?
> Shouldn't it be datetime(year=year, month=1, day=1) ?
>