allowing coverage method to accept interval array as domain specifica…

…tion (#16)

piso/docstrings/accessor.py

@@ -593,10 +593,12 @@ def join_params(list_of_param_strings):
 
 Parameters
 ----------
-domain : :class:`pandas.Interval`, or tuple equivalent, optional
-    Specifies the domain (lower and upper bounds) over which to assess the "coverage".
-    If *domain* is `None`, then the domain is considered to be the extremities of the intervals
-    contained in *interval_array*
+domain : :py:class:`tuple`, :class:`pandas.Interval`, :class:`pandas.IntervalIndex` or :class:`pandas.arrays.IntervalArray`, optional
+    Specifies the domain over which to calculate the "coverage".  If *domain* is `None`,
+    then the domain is considered to be the extremities of the intervals contained in the interval array the accessor belongs to.
+    If *domain* is a tuple then it should specify lower and upper bounds, and be equivalent to a
+    :class:`pandas.Interval`.  If *domain* is a :class:`pandas.IntervalIndex` or :class:`pandas.arrays.IntervalArray`
+    then the intervals it contains define a possibly disconnected domain.
 
 Returns
 ----------
@@ -622,6 +624,12 @@ def join_params(list_of_param_strings):
 
 >>> arr1.piso.coverage(pd.Interval(-10, 10))
 0.3
+
+>>> domain = pd.arrays.IntervalArray.from_tuples(
+...     [(4,6), (7, 9)],
+... )
+>>> arr1.piso.coverage(domain)
+0.5
 """
 
 complement_docstring = """

piso/docstrings/intervalarray.py

@@ -599,10 +599,12 @@ def join_params(list_of_param_strings):
 ----------
 interval_array : :class:`pandas.IntervalIndex` or :class:`pandas.arrays.IntervalArray`
     Contains the (possibly overlapping) intervals which partially, or wholly cover the domain.
-domain : :class:`pandas.Interval`, or tuple equivalent, optional
-    Specifies the domain (lower and upper bounds) over which to assess the "coverage".
-    If *domain* is `None`, then the domain is considered to be the extremities of the intervals
-    contained in *interval_array*
+domain : :py:class:`tuple`, :class:`pandas.Interval`, :class:`pandas.IntervalIndex` or :class:`pandas.arrays.IntervalArray`, optional
+    Specifies the domain over which to calculate the "coverage".  If *domain* is `None`,
+    then the domain is considered to be the extremities of the intervals contained in *interval_array*
+    If *domain* is a tuple then it should specify lower and upper bounds, and be equivalent to a
+    :class:`pandas.Interval`.  If *domain* is a :class:`pandas.IntervalIndex` or :class:`pandas.arrays.IntervalArray`
+    then the intervals it contains define a possibly disconnected domain.
 
 Returns
 ----------
@@ -627,6 +629,12 @@ def join_params(list_of_param_strings):
 
 >>> piso.coverage(arr1, pd.Interval(-10, 10))
 0.3
+
+>>> domain = pd.arrays.IntervalArray.from_tuples(
+...     [(4,6), (7, 9)],
+... )
+>>> piso.coverage(arr1, domain)
+0.5
 """
 
 

piso/intervalarray.py

@@ -173,8 +173,14 @@ def _get_domain_tuple(interval_array, domain):
 
 @Appender(docstrings.coverage_docstring, join="\n", indents=1)
 def coverage(interval_array, domain=None):
-    domain = _get_domain_tuple(interval_array, domain)
-    return _interval_x_to_stairs(interval_array).make_boolean().clip(*domain).mean()
+    stepfunction = _interval_x_to_stairs(interval_array).make_boolean()
+    if isinstance(domain, (pd.IntervalIndex, pd.arrays.IntervalArray)):
+        domain = _interval_x_to_stairs(domain)
+        result = stepfunction.where(domain).mean()
+    else:
+        domain = _get_domain_tuple(interval_array, domain)
+        result = stepfunction.clip(*domain).mean()
+    return result
 
 
 @Appender(docstrings.complement_docstring, join="\n", indents=1)

tests/test_single_interval_array.py

@@ -496,7 +496,14 @@ def test_isdisjoint(interval_index, tuples, expected, closed, date_type, how):
 )
 @pytest.mark.parametrize(
     "domain, expected",
-    [(None, 10 / 12), ((0, 10), 0.8), (pd.Interval(0, 10), 0.8), ((15, 20), 0)],
+    [
+        (None, 10 / 12),
+        ((0, 10), 0.8),
+        (pd.Interval(0, 10), 0.8),
+        ((15, 20), 0),
+        (pd.IntervalIndex.from_tuples([(0, 6), (10, 12)]), 1),
+        (pd.IntervalIndex.from_tuples([(6, 7), (9, 10)]), 0),
+    ],
 )
 @pytest.mark.parametrize(
     "closed",
@@ -507,6 +514,8 @@ def test_isdisjoint(interval_index, tuples, expected, closed, date_type, how):
     ["supplied", "accessor", "package"],
 )
 def test_coverage(interval_index, domain, expected, closed, how):
+    if hasattr(domain, "set_closed"):
+        domain = domain.set_closed(closed)
     ia = make_ia1(interval_index, closed)
     result = perform_op(
         ia,