Fixes for mypy.

pytket/pytket/circuit/display/utils.py

@@ -160,7 +160,6 @@ def format_logic_exp(exp: Union[LogicExp, Bit, BitRegister, int]) -> str:
                 exp.op.value,
                 format_logic_exp(exp.args[1]),
             )
-    return ""
 
 
 def get_gate_colour(op_type: str) -> str:

pytket/pytket/utils/outcomearray.py

@@ -15,9 +15,10 @@
 """`OutcomeArray` class and associated methods."""
 import operator
 from functools import reduce
-from typing import Counter, List, Sequence, Dict, Tuple, Any, cast
+from typing import Counter, List, Sequence, Dict, Tuple, Any, Optional, cast
 
 import numpy as np
+from numpy.typing import ArrayLike
 
 
 class OutcomeArray(np.ndarray):
@@ -57,12 +58,13 @@ def __array_finalize__(self, obj):  # type: ignore
         # see InfoArray.__array_finalize__ for comments
         if obj is None:
             return
-        self._width: int = getattr(obj, "_width", None)
+        self._width: Optional[int] = getattr(obj, "_width", None)
 
     @property
     def width(self) -> int:
         """Number of bit entries stored, less than or equal to the bit capacity of the
         array."""
+        assert type(self._width) is int
         return self._width
 
     @property
@@ -77,7 +79,7 @@ def __eq__(self, other: "OutcomeArray") -> bool:  # type: ignore
         return bool(np.array_equal(self, other) and self.width == other.width)
 
     @classmethod
-    def from_readouts(cls, readouts: Sequence[Sequence[int]]) -> "OutcomeArray":
+    def from_readouts(cls, readouts: ArrayLike) -> "OutcomeArray":
         """Create OutcomeArray from a 2D array like object of read-out integers,
         e.g. [[1, 1, 0], [0, 1, 1]]"""
         readouts_ar = np.array(readouts, dtype=int)

pytket/pytket/utils/spam.py

@@ -449,13 +449,14 @@ def calculate_matrices(self, results_list: List[BackendResult]) -> None:
                     # produced state
                     measured_state_index = binary_to_int(measured_state)
                     # update characterisation matrix
-                    self.subsets_matrix_map[qb_sub][
-                        measured_state_index, prepared_state_index
-                    ] += count
+                    M = self.subsets_matrix_map[qb_sub]
+                    assert type(M) is np.ndarray
+                    M[measured_state_index, prepared_state_index] += count
 
         # normalise everything
         self.characterisation_matrices = [
-            mat / np.sum(mat, axis=0) for mat in self.subsets_matrix_map.values()
+            mat / np.sum(cast(np.ndarray, mat), axis=0)
+            for mat in self.subsets_matrix_map.values()
         ]
 
     def get_parallel_measure(self, circuit: Circuit) -> ParallelMeasures: