minor patch to multi-index broadcasting and vector initialization

chainladder/core/base.py

@@ -62,8 +62,10 @@ def __init__(self, data=None, origin=None, development=None,
                 format=development_format)
             self.development_grain = TriangleBase._get_grain(development_date)
         else:
-            development_date = origin_date + \
-                pd.tseries.offsets.MonthEnd(m_cnt[self.origin_grain])
+            development_date = pd.PeriodIndex(
+                origin_date + pd.tseries.offsets.MonthEnd(m_cnt[self.origin_grain]),
+                freq={'Y': 'A'}.get(self.origin_grain, self.origin_grain)
+                ).to_timestamp(how='e')
             self.development_grain = self.origin_grain
         development_date.name = 'development'
         # Summarize dataframe to the level specified in axes
@@ -116,7 +118,8 @@ def __init__(self, data=None, origin=None, development=None,
         # Set all axis values
         self.kdims = kdims.drop('index', 1).values
         self.odims = orig_unique
-        self.ddims = dev_lag_unique*m_cnt[self.development_grain]
+        self.ddims = dev_lag_unique if development else dev_lag[0:1].values
+        self.ddims = self.ddims*(m_cnt[self.development_grain])
         self.vdims = np.array(columns)
 
         # Set remaining triangle properties

chainladder/core/tests/test_triangle.py

@@ -344,3 +344,12 @@ def test_4loc():
     clrd = tri.groupby('LOB').sum()
     assert clrd.iloc[:3, :2, 0,0] == clrd[clrd.origin==tri.origin.min()][clrd.development==clrd.development.min()].loc['comauto':'othliab', :'CumPaidLoss', :, :]
     assert clrd.iloc[:3, :2, 0:1, -1] == clrd[clrd.development==tri.development.max()].loc['comauto':'othliab', :'CumPaidLoss', '1988', :]
+
+def test_init_vector():
+    a = raa[raa.development==12]
+    b = pd.DataFrame(
+        {'AccYear':[item for item in range(1981, 1991)],
+         'premium': [3000000]*10})
+    b = cl.Triangle(b, origin='AccYear', columns='premium')
+    assert np.all(a.valuation==b.valuation)
+    assert a.valuation_date == b.valuation_date

chainladder/methods/base.py

@@ -30,7 +30,7 @@ def _align_cdf(self, ultimate, sample_weight=None):
         """
         xp = ultimate.get_array_module()
         from chainladder.utils.utility_functions import num_to_nan
-        if self.cdf_.key_labels != ultimate.key_labels:
+        if self.cdf_.key_labels != ultimate.key_labels and len(self.ldf_.index) > 1:
             level = list(set(self.cdf_.key_labels).intersection(ultimate.key_labels))
             idx = ultimate.index[level].merge(
                 self.cdf_.index[level].reset_index(), how='left', on=level)['index'].values

docs/modules/triangle.rst

@@ -392,6 +392,14 @@ of the object using pandas-style ``loc``/``iloc`` or boolean filtering.
    need for ``reset_index()`` or trying to boolean-filter a ``MultiIndex``. This is
    a divergence from the pandas API.
 
+As of version ``0.7.6``, four-dimensional slicing is supported:
+**Example:**
+  >>> import chainladder as cl
+  >>> clrd = cl.load_sample('clrd')
+  >>> clrd.iloc[[0, 10, 3], 1:8, :5, :]
+  >>> clrd.loc[:'Aegis Grp', 'CumPaidLoss':, '1990':'1994', :48]
+
+
 
 Arithmetic
 ----------