Merge branch 'main' into refactor-splines

docs/source/i_guide.rst

@@ -94,6 +94,7 @@ independently by providing basic inputs.
              },
              index_base=308.95,
              index_lag=3,
+             interpolation="linear_index",
              id="us_cpi",
          )
 

pyproject.toml

@@ -145,7 +145,6 @@ exclude = [
     "/instruments",
     "fx_volatility.py",
     "legs.py",
-    "periods.py",
     "solver.py",
 ]
 strict = true

python/rateslib/curves/curves.py

@@ -3058,7 +3058,7 @@ def _get_node_vector(self) -> Arr1dF64 | Arr1dObj:  # pragma: no cover
 
 def average_rate(
     effective: datetime, termination: datetime, convention: str, rate: DualTypes
-) -> tuple[DualTypes, float, int]:
+) -> tuple[Number, float, int]:
     """
     Return the geometric, 1 calendar day, average rate for the rate in a period.
 
@@ -3081,7 +3081,7 @@ def average_rate(
     """
     d: float = _DCF1d[convention.upper()]
     n: int = (termination - effective).days
-    _: DualTypes = ((1 + n * d * rate / 100) ** (1 / n) - 1) / d
+    _: Number = ((1 + n * d * rate / 100) ** (1 / n) - 1) / d
     return _ * 100, d, n
 
 

python/rateslib/dual/__init__.py

@@ -22,7 +22,7 @@
 
 
 def _dual_float(val: DualTypes) -> float:
-    """Overload for the float() builtin to handle Pyo3 issues with Variabe"""
+    """Overload for the float() builtin to handle Pyo3 issues with Variable"""
     try:
         return float(val)  # type: ignore[arg-type]
     except TypeError as e:  # val is not Number but a Variable

python/rateslib/fx_volatility.py

@@ -92,7 +92,7 @@ def __init__(
         self.expiry = expiry
         self.t_expiry = (expiry - eval_date).days / 365.0
         self.t_expiry_sqrt = self.t_expiry**0.5
-        self.delta_type = _validate_delta_type(delta_type)
+        self.delta_type: str = _validate_delta_type(delta_type)
 
         self.__set_nodes__(nodes, ad)
 
@@ -196,7 +196,7 @@ def get_from_strike(
         w_deli: DualTypes | NoInput = NoInput(0),
         w_spot: DualTypes | NoInput = NoInput(0),
         expiry: datetime | NoInput(0) = NoInput(0),
-    ) -> tuple:
+    ) -> tuple[DualTypes, DualTypes, DualTypes]:
         """
         Given an option strike return associated delta and vol values.
 
@@ -820,7 +820,7 @@ def __init__(
                 raise ValueError("Surface `expiries` are not sorted or contain duplicates.\n")
 
         self.delta_indexes = delta_indexes
-        self.delta_type = _validate_delta_type(delta_type)
+        self.delta_type: str = _validate_delta_type(delta_type)
         self.smiles = [
             FXDeltaVolSmile(
                 nodes=dict(zip(self.delta_indexes, node_values[i, :], strict=False)),
@@ -893,7 +893,7 @@ def _get_node_vars(self):
             vars += tuple(f"{smile.id}{i}" for i in range(smile.n))
         return vars
 
-    def get_smile(self, expiry: datetime):
+    def get_smile(self, expiry: datetime) -> FXDeltaVolSmile:
         """
         Construct a *DeltaVolSmile* with linear total variance interpolation over delta indexes.
 
@@ -1352,7 +1352,9 @@ def _d_plus(K: DualTypes, f: DualTypes, vol_sqrt_t: DualTypes) -> DualTypes:
     return _d_plus_min(K, f, vol_sqrt_t, +0.5)
 
 
-def _delta_type_constants(delta_type, w, u):
+def _delta_type_constants(
+    delta_type: str, w: DualTypes, u: DualTypes
+) -> tuple[float, DualTypes, DualTypes]:
     """
     Get the values: (eta, z_w, z_u) for the type of expressed delta
 

python/rateslib/legs.py

@@ -1084,13 +1084,17 @@ def index_fixings(self, value):
         for i, period in enumerate(self.periods):
             if isinstance(period, IndexFixedPeriod | IndexCashflow):
                 if isinstance(value, Series):
-                    _ = IndexMixin._index_value(
+                    val: DualTypes | None = IndexMixin._index_value(
                         i_fixings=value,
                         i_method=self.index_method,
                         i_lag=self.index_lag,
                         i_date=period.end,
                         i_curve=NoInput(0),  # ! NoInput returned for periods beyond Series end.
                     )
+                    if val is None:
+                        _: DualTypes | NoInput = NoInput(0)
+                    else:
+                        _ = val
                 elif isinstance(value, list):
                     if i >= len(value):
                         _ = NoInput(0)  # some fixings are unknown, list size is limited
@@ -1106,20 +1110,26 @@ def index_base(self):
         return self._index_base
 
     @index_base.setter
-    def index_base(self, value):
+    def index_base(self, value: DualTypes | Series[DualTypes] | NoInput) -> None:
         if isinstance(value, Series):
-            value = IndexMixin._index_value(
+            _: DualTypes | None = IndexMixin._index_value(
                 i_fixings=value,
                 i_method=self.index_method,
                 i_lag=self.index_lag,
                 i_date=self.schedule.effective,
                 i_curve=NoInput(0),  # not required because i_fixings is Series
             )
-        self._index_base = value
+            if _ is None:
+                ret: DualTypes | NoInput = NoInput(0)
+            else:
+                ret = _
+        else:
+            ret = value
+        self._index_base = ret
         # if value is not None:
         for period in self.periods:
             if isinstance(period, IndexFixedPeriod | IndexCashflow):
-                period.index_base = value
+                period.index_base = self._index_base
 
 
 class ZeroFloatLeg(BaseLeg, _FloatLegMixin):