rename highest_threshold to pointwise_highest

src/icepool/__init__.py

@@ -48,7 +48,7 @@
 
 from icepool.function import (d, z, __getattr__, coin, stochastic_round,
                               one_hot, iter_cartesian_product, from_cumulative,
-                              from_rv, highest_threshold, lowest_threshold, min_outcome, 
+                              from_rv, pointwise_highest, pointwise_lowest, min_outcome, 
                               max_outcome, consecutive, sorted_union,
                               commonize_denominator, reduce, accumulate, map, 
                               map_function, map_and_time, map_to_pool)
@@ -147,7 +147,7 @@
     'd', 'z', 'coin', 'stochastic_round', 'one_hot', 'Outcome', 'Die',
     'Population', 'tupleize', 'vectorize', 'Vector', 'Symbols', 'Again',
     'CountsKeysView', 'CountsValuesView', 'CountsItemsView', 'from_cumulative',
-    'from_rv', 'highest_threshold', 'lowest_threshold', 'lowest', 'highest', 'middle', 'min_outcome', 'max_outcome',
+    'from_rv', 'pointwise_highest', 'pointwise_lowest', 'lowest', 'highest', 'middle', 'min_outcome', 'max_outcome',
     'consecutive', 'sorted_union', 'commonize_denominator', 'reduce',
     'accumulate', 'map', 'map_function', 'map_and_time', 'map_to_pool',
     'Reroll', 'RerollType', 'Pool', 'standard_pool', 'MultisetGenerator',

src/icepool/function.py

@@ -235,35 +235,41 @@ def _iter_outcomes(
         else:
             yield arg
 
-def highest_threshold(*dice: 'icepool.Die[T]') -> 'icepool.Die[T]':
+def pointwise_highest(*dice: 'icepool.Die[T]') -> 'icepool.Die[T]':
     """Selects the highest chance of rolling >= each outcome among the arguments.
 
     Specifically, for each outcome, the chance of the result rolling >= to that 
     outcome is the same as the highest chance of rolling >= that outcome among
     the arguments.
 
-    The result has the same mathematical structure as a probability
-    distribution, hence the result is a `Die`, even if it is difficult to
-    interpret as a physical process.
+    Equivalently, any quantile in the result is the highest of that quantile
+    among the arguments.
+
+    This is useful for selecting from several possible moves where you are
+    trying to get >= a threshold that is known but could change depending on the
+    situation.
     
     Args:
         dice: Any number of dice.
     """
     dice = commonize_denominator(*dice)
     outcomes = sorted_union(*dice)
-    cumulative = [max(die.quantity('>=', outcome) for die in dice) for outcome in outcomes]
-    return from_cumulative(outcomes, cumulative, reverse=True)
+    cumulative = [min(die.quantity('<=', outcome) for die in dice) for outcome in outcomes]
+    return from_cumulative(outcomes, cumulative)
 
-def lowest_threshold(*dice: 'icepool.Die[T]') -> 'icepool.Die[T]':
+def pointwise_lowest(*dice: 'icepool.Die[T]') -> 'icepool.Die[T]':
     """Selects the highest chance of rolling <= each outcome among the arguments.
     
     Specifically, for each outcome, the chance of the result rolling <= to that 
     outcome is the same as the highest chance of rolling <= that outcome among
     the arguments.
 
-    The result has the same mathematical structure as a probability
-    distribution, hence the result is a `Die`, even if it is difficult to
-    interpret as a physical process.
+    Equivalently, any quantile in the result is the lowest of that quantile
+    among the arguments.
+
+    This is useful for selecting from several possible moves where you are
+    trying to get <= a threshold that is known but could change depending on the
+    situation.
     
     Args:
         dice: Any number of dice.

tests/function_test.py

@@ -1,7 +1,7 @@
 import icepool
 import pytest
 
-from icepool import d4, d6, d8, d10, d12, d20, min_outcome, max_outcome, highest_threshold, lowest_threshold
+from icepool import d4, d6, d8, d10, d12, d20, min_outcome, max_outcome, pointwise_highest, pointwise_lowest
 
 
 def test_min_outcome_single_arg():
@@ -27,15 +27,15 @@ def test_max_outcome_multiple_arg():
 def test_max_outcome_bare_outcome():
     assert max_outcome(d6, d8, 10, 2) == 10
 
-def test_highest_threshold():
-    result = highest_threshold(3 @ d6, d20)
+def test_pointwise_highest():
+    result = pointwise_highest(3 @ d6, d20)
     for outcome in range(1, 21):
         assert result.probability('>=', outcome) == max(
             (3 @ d6).probability('>=', outcome),
             d20.probability('>=', outcome))
 
-def test_lowest_threshold():
-    result = lowest_threshold(3 @ d6, d20)
+def test_pointwise_lowest():
+    result = pointwise_lowest(3 @ d6, d20)
     for outcome in range(1, 21):
         assert result.probability('<=', outcome) == max(
             (3 @ d6).probability('<=', outcome),