Changeset 2100

Timestamp:

02/26/09 13:45:53 (3 years ago)

Author:

pierregm

Message:

* introduced convert_to_annual
* fixed frequency in _extrema
* doc update

Location:

trunk/timeseries/scikits/timeseries

Files:

• doc/source/conf.py (modified) (1 diff)
• doc/source/core.timeseries.conversion.rst (modified) (2 diffs)
• extras.py (modified) (2 diffs)
• lib/plotlib.py (modified) (2 diffs)
• tests/test_dates.py (modified) (2 diffs)
• tests/test_extras.py (modified) (1 diff)
• tseries.py (modified) (1 diff)

trunk/timeseries/scikits/timeseries/doc/source/conf.py

@@ -222 +222 @@
 intersphinx_mapping = {'http://docs.python.org/dev': None,
                        'http://docs.scipy.org/doc/numpy': None,
+                       'http://docs.scipy.org/doc/scipy/reference': None,
                        'http://matplotlib.sourceforge.net': None}
 

trunk/timeseries/scikits/timeseries/doc/source/core.timeseries.conversion.rst

@@ -50 +50 @@
 
 .. warning::
-   Be careful not to confuse the two methods :meth:`asfreq` and :meth:`convert`.
+   Be careful not to confuse the two methods :meth:`~TimeSeries.asfreq` 
+   and :meth:`~TimeSeries.convert`.
 
    * :meth:`~TimeSeries.asfreq` simply takes every date
@@ -62 +63 @@
      places the data from the original series into appropriate points in the new
      series.
+
+
+.. autosummary::
+   :toctree: generated/
+
+   convert
+   scikits.timeseries.extras.convert_to_annual

trunk/timeseries/scikits/timeseries/extras.py

@@ -24 +24 @@
 
 __all__ = ['accept_atmost_missing',
-           'count_missing',
+           'convert_to_annual', 'count_missing',
            'guess_freq',
            'isleapyear',
@@ -97 +97 @@
         raise NotImplementedError, "Not yet implemented for that frequency..."
     return missing
+
+
+
+def convert_to_annual(series):
+    """
+    Group a series by years, taking leap years into account.
+    
+    The output has as many rows as distinct years in the original series,
+    and as many columns as the length of a leap year in the units corresponding
+    to the original frequency (366 for daily frequency, 366*24 for hourly...).
+    The fist column of the output corresponds to Jan. 1st, 00:00:00,
+    while the last column corresponds to Dec, 31st, 23:59:59.
+    Entries corresponding to Feb. 29th are masked for non-leap years.
+
+    For example, if the initial series has a daily frequency, the 59th column
+    of the output always corresponds to Feb. 28th, the 61st column to Mar. 1st,
+    and the 60th column is masked for non-leap years.
+    With a hourly initial frequency, the (59*24)th column of the output always
+    correspond to Feb. 28th 23:00, the (61*24)th column to Mar. 1st, 00:00, and
+    the 24 columns between (59*24) and (61*24) are masked.
+
+    If the original frequency is less than daily, the output is equivalent to
+    ``series.convert('A', func=None)``.
+
+
+    Parameters
+    ----------
+    series : TimeSeries
+        A valid :class:`~scikits.timeseries.TimeSeries` object.
+
+    Returns
+    -------
+    aseries : TimeSeries
+        A 2D  :class:`~scikits.timeseries.TimeSeries` object with annual ('A')
+        frequency.
+    
+    """
+    dates = series.dates
+    if dates.freq < _c.FR_DAY:
+        return series.convert('A')
+    idx0228 = dates.date_to_index(Date(dates.freq,
+                                       year=dates[0].year, month=2, day=28,
+                                       hour=00, minute=00, second=00))
+    idx0301 = dates.date_to_index(Date(dates.freq,
+                                       year=dates[0].year, month=3, day=1,
+                                       hour=00, minute=00, second=00))
+    aseries = series.convert('A')
+    leapcondition = isleapyear(aseries.dates.years)
+    leapidx = np.arange(len(aseries), dtype=int)[~leapcondition]
+    aseries[leapidx, idx0301:] = aseries[leapidx, idx0228:idx0228-idx0301]
+    aseries[leapidx, idx0228:idx0301] = ma.masked
+    return aseries
+
+
 
 #.............................................................................

trunk/timeseries/scikits/timeseries/lib/plotlib.py

@@ -995 +995 @@
         """
     Plots the data parsed in argument to the current axes.
-    This command accepts the same optional keywords as :func:`matplotlib.plot`.
+    This command accepts the same optional keywords as :func:`matplotlib.pyplot.plot`.
 
     The argument ``args`` is a variable length argument, allowing for multiple
@@ -1014 +1014 @@
 
     a :class:`~scikits.timeseries.TimeSeries` object or one of its subclass
-       with or without a format string:
+    with or without a format string:
        The given time series is plotted with the given format.
        If no format string is given, the default format is used instead.

trunk/timeseries/scikits/timeseries/tests/test_dates.py

@@ -123 +123 @@
         _dt = ts.Date(freq='D', datetime=datetime.datetime(2007, 1, 1, 0, 0, 0, 0))
         assert_equal(_dt, _tsdt)
-        print "finished test_fromsobjects"
 
 
@@ -145 +144 @@
         assert_equal(date_array(n,length=3), d)
         assert_equal(date_array(n, n+2), d)
-        print "finished test_shortcuts"
 
 

trunk/timeseries/scikits/timeseries/tests/test_extras.py

@@ -78 +78 @@
         assert_equal(result._mask.all(-1), [1,1])
 
+    def test_convert_to_annual(self):
+        "Test convert_to_annual"
+        base = dict(D=1, H=24, T=24*60, S=24*3600)
+        #for fq in ('D', 'H', 'T', 'S'):
+        # Don't test for minuTe and Second frequency, too time consuming.
+        for fq in ('D', 'H'):
+            dates = date_array(start_date=Date(fq, '2001-01-01 00:00:00'),
+                               end_date=Date(fq, '2004-12-31 23:59:59'))
+            bq = base[fq]
+            series = time_series(range(365*bq)*3+range(366*bq),
+                                 dates=dates)
+            control = ma.masked_all((4, 366*bq), dtype=series.dtype)
+            control[0, :58*bq] = range(58*bq)
+            control[0, 59*bq:] = range(58*bq, 365*bq)
+            control[[1, 2]] = control[0]
+            control[3] = range(366*bq)
+            test = convert_to_annual(series)
+            assert_equal(test, control)
+
 
 

trunk/timeseries/scikits/timeseries/tseries.py

@@ -1305 +1305 @@
             _s = np.choose(idx, np.rollaxis(_series,axis,0))
             _d = np.choose(idx, np.rollaxis(_dates,axis,0))
-            result = time_series(_s, dates=_d)
+            result = time_series(_s, dates=_d, freq=_dates.freq)
         return result