Fix some formatting deltas and exclude some rules that apply more bro…

…adly than before.

pyproject.toml

@@ -89,6 +89,8 @@ ignore = [
 "tests/**.py" = ["E", "PL", "W", "N", "NPY", "RUF", "B"]
 # Ignore everything for now
 "docs/**.py" = ["E", "F", "PL", "W", "I", "N", "NPY", "RUF", "B"]
+"docs/**.ipynb" = ["E", "F", "PL", "W", "I", "N", "NPY", "RUF", "B"]
+"profiling/**.ipynb" = ["E", "F", "PL", "W", "I", "N", "NPY", "RUF", "B"]
 
 [tool.ruff.format]
 docstring-code-format = true

pyttb/cp_apr.py

@@ -1138,7 +1138,7 @@ def tt_cp_apr_pqnr(  # noqa: PLR0912,PLR0913,PLR0915
 
 
 @overload
-def tt_calcpi_prowsubprob(  # noqa: PLR0913
+def tt_calcpi_prowsubprob(
     Data: ttb.sptensor,
     Model: ttb.ktensor,
     rank: int,
@@ -1150,7 +1150,7 @@ def tt_calcpi_prowsubprob(  # noqa: PLR0913
 
 
 @overload
-def tt_calcpi_prowsubprob(  # noqa: PLR0913
+def tt_calcpi_prowsubprob(
     Data: ttb.tensor,
     Model: ttb.ktensor,
     rank: int,

pyttb/gcp/fg_est.py

@@ -17,7 +17,7 @@
 
 
 @overload
-def estimate(  # noqa: PLR0913
+def estimate(
     model: ttb.ktensor,
     data_subs: np.ndarray,
     data_vals: np.ndarray,
@@ -30,7 +30,7 @@ def estimate(  # noqa: PLR0913
 
 
 @overload
-def estimate(  # noqa: PLR0913
+def estimate(
     model: ttb.ktensor,
     data_subs: np.ndarray,
     data_vals: np.ndarray,
@@ -43,7 +43,7 @@ def estimate(  # noqa: PLR0913
 
 
 @overload
-def estimate(  # noqa: PLR0913
+def estimate(
     model: ttb.ktensor,
     data_subs: np.ndarray,
     data_vals: np.ndarray,

pyttb/sptensor.py

@@ -830,7 +830,7 @@ def innerprod(
 
         >>> S = ttb.sptensor()
         >>> S[0, 0] = 1
-        ... S[1, 1] = 2
+        >>> S[1, 1] = 2
         >>> S
         sparse tensor of shape (2, 2) with 2 nonzeros
         [0, 0] = 1.0
@@ -899,7 +899,7 @@ def isequal(self, other: Union[sptensor, ttb.tensor]) -> bool:
 
         >>> S = ttb.sptensor()
         >>> S[0, 0] = 1
-        ... S[1, 1] = 2
+        >>> S[1, 1] = 2
         >>> S
         sparse tensor of shape (2, 2) with 2 nonzeros
         [0, 0] = 1.0
@@ -940,7 +940,7 @@ def logical_and(self, other: Union[float, sptensor, ttb.tensor]) -> sptensor:
 
         >>> S = ttb.sptensor()
         >>> S[0, 0] = 1
-        ... S[1, 1] = 2
+        >>> S[1, 1] = 2
         >>> S
         sparse tensor of shape (2, 2) with 2 nonzeros
         [0, 0] = 1.0
@@ -1005,7 +1005,7 @@ def logical_not(self) -> sptensor:
 
         >>> S = ttb.sptensor()
         >>> S[0, 0] = 1
-        ... S[1, 1] = 2
+        >>> S[1, 1] = 2
         >>> S
         sparse tensor of shape (2, 2) with 2 nonzeros
         [0, 0] = 1.0
@@ -1048,7 +1048,7 @@ def logical_or(
 
         >>> S = ttb.sptensor()
         >>> S[0, 0] = 1
-        ... S[1, 1] = 2
+        >>> S[1, 1] = 2
         >>> S.logical_or(S)
         sparse tensor of shape (2, 2) with 2 nonzeros
         [0, 0] = 1.0
@@ -1119,7 +1119,7 @@ def logical_xor(
 
         >>> S = ttb.sptensor()
         >>> S[0, 0] = 1
-        ... S[1, 1] = 2
+        >>> S[1, 1] = 2
         >>> S.logical_xor(S)
         empty sparse tensor of shape (2, 2)
 
@@ -1178,7 +1178,7 @@ def mask(self, W: sptensor) -> np.ndarray:
 
         >>> S = ttb.sptensor()
         >>> S[0, 0] = 1
-        ... S[1, 1] = 2
+        >>> S[1, 1] = 2
         >>> S
         sparse tensor of shape (2, 2) with 2 nonzeros
         [0, 0] = 1.0
@@ -1189,7 +1189,7 @@ def mask(self, W: sptensor) -> np.ndarray:
 
         >>> W = ttb.sptensor()
         >>> W[0, 0] = 1
-        ... W[1, 1] = 1
+        >>> W[1, 1] = 1
         >>> S.mask(W)
         array([[1.],
                [2.]])
@@ -1199,7 +1199,7 @@ def mask(self, W: sptensor) -> np.ndarray:
 
         >>> W = ttb.sptensor()
         >>> W[0, 0] = 1
-        ... W[1, 0] = 1
+        >>> W[1, 0] = 1
         >>> S.mask(W)
         array([[1.],
                [0.]])

pyttb/tenmat.py

@@ -22,7 +22,7 @@ class tenmat:
 
     __slots__ = ("tshape", "rindices", "cindices", "data")
 
-    def __init__(  # noqa: PLR0912, PLR0913
+    def __init__(  # noqa: PLR0912
         self,
         data: Optional[np.ndarray] = None,
         rdims: Optional[np.ndarray] = None,