update lint

.pre-commit-config.yaml

@@ -4,19 +4,19 @@ ci:
   autoupdate_commit_msg: "ci(pre-commit.ci): autoupdate"
 
 repos:
-  - repo: https://github.com/charliermarsh/ruff-pre-commit
-    rev: v0.0.267
+  - repo: https://github.com/astral-sh/ruff-pre-commit
+    rev: v0.1.3
     hooks:
       - id: ruff
-        args: [--fix]
+        args: [--fix, --unsafe-fixes]
 
   - repo: https://github.com/psf/black
-    rev: 23.3.0
+    rev: 23.10.1
     hooks:
       - id: black
 
   - repo: https://github.com/pre-commit/mirrors-mypy
-    rev: v1.3.0
+    rev: v1.6.1
     hooks:
       - id: mypy
         files: "^motile/"

docs/source/install.rst

@@ -29,7 +29,7 @@ Do I have to use ``conda``?
 ---------------------------
 
 Kinda. ``motile`` uses `ilpy <https://github.com/funkelab/ilpy>`_ to solve the
-optimzation problem. Conda packages for ``ilpy`` are available for all major
+optimization problem. Conda packages for ``ilpy`` are available for all major
 platforms, linking against the conda packages for SCIP and Gurobi.
 
 It is possible to not use ``conda``: If you have SCIP or Gurobi installed

docs/source/learning.rst

@@ -117,7 +117,7 @@ to the solver.
 
 In the example above, the :class:`motile.variables.EdgeSelected` variable
 (which is the target of the cost :class:`motile.costs.EdgeSelection`), has the
-follwing weights and features:
+following weights and features:
 
 .. math::
   \vct{w}

docs/source/quickstart.rst

@@ -142,7 +142,7 @@ Variables are instantiated and managed by the solver. All we have to do is to
 ask the solver for the kind of variables we are interested in via
 :func:`Solver.get_variables`. The returned value (e.g., ``node_selected``) is a
 dictionary that maps *what* to *where*: in the case of node variables, the
-dictionary keys are the nodes themselves (an integer) and the dictionay values
+dictionary keys are the nodes themselves (an integer) and the dictionary values
 are the indices in the ``solution`` vector where we can find the value of the
 variable. Both node and edge indicators are binary variables (one if selected,
 zero otherwise).

motile/costs/disappear.py

@@ -14,7 +14,6 @@ class Disappear(Costs):
     """Costs for :class:`motile.variables.NodeDisappear` variables.
 
     Args:
-
         constant (float):
             A constant cost for each node that ends a track.
     """

motile/plot.py

@@ -103,7 +103,7 @@ def draw_track_graph(
     if position_func is None:
 
         def position_func(node: NodeId) -> float:
-            return float(graph.nodes[node][position_attribute])  # type: ignore
+            return float(graph.nodes[node][position_attribute])
 
     alpha_node_func: ReturnsFloat
     alpha_edge_func: ReturnsFloat
@@ -113,10 +113,10 @@ def position_func(node: NodeId) -> float:
     if alpha_attribute is not None:
 
         def alpha_node_func(node):
-            return graph.nodes[node].get(alpha_attribute, 1.0)  # type: ignore
+            return graph.nodes[node].get(alpha_attribute, 1.0)
 
         def alpha_edge_func(edge):
-            return graph.edges[edge].get(alpha_attribute, 1.0)  # type: ignore
+            return graph.edges[edge].get(alpha_attribute, 1.0)
 
     elif alpha_func is None:
 
@@ -135,10 +135,10 @@ def alpha_edge_func(_):
     if label_attribute is not None:
 
         def label_node_func(node):
-            return graph.nodes[node].get(label_attribute, "")  # type: ignore
+            return graph.nodes[node].get(label_attribute, "")
 
         def label_edge_func(edge):
-            return graph.edges[edge].get(label_attribute, "")  # type: ignore
+            return graph.edges[edge].get(label_attribute, "")
 
     elif label_func is None:
 
@@ -339,6 +339,6 @@ def _to_rgba(
         return [_to_rgba(color, a) for a in alpha]
 
     # we fake alpha by mixing with white(ish)
-    # transparancy is tricky...
+    # transparency is tricky...
     r, g, b = tuple(int(c * alpha + 220 * (1.0 - alpha)) for c in color)
     return f"rgb({r},{g},{b})"

motile/track_graph.py

@@ -1,6 +1,7 @@
 from __future__ import annotations
 
 import logging
+from collections import defaultdict
 from typing import TYPE_CHECKING, Any, DefaultDict, Hashable, Iterator
 
 logger = logging.getLogger(__name__)
@@ -45,8 +46,8 @@ def __init__(
 
         self.nodes: dict[NodeId, GraphObject] = {}
         self.edges: dict[EdgeId, GraphObject] = {}
-        self.prev_edges: DefaultDict[NodeId, list[EdgeId]] = DefaultDict(list)
-        self.next_edges: DefaultDict[NodeId, list[EdgeId]] = DefaultDict(list)
+        self.prev_edges: defaultdict[NodeId, list[EdgeId]] = DefaultDict(list)
+        self.next_edges: defaultdict[NodeId, list[EdgeId]] = DefaultDict(list)
 
         if nx_graph:
             self.add_from_nx_graph(nx_graph)

motile/variables/node_disappear.py

@@ -14,9 +14,10 @@
 
 
 class NodeDisappear(Variable["NodeId"]):
-    r"""A binary variable for each node that indicates whether the node is the
-    end of a track (i.e., the node is selected and has no selected outgoing
-    edges).
+    r"""Binary variable to indicate whether a node disappears.
+
+    This variable indicates whether the node is the end of a track (i.e., the node is
+    selected and has no selected outgoing edges).
 
     This variable is coupled to the node and edge selection variables through
     the following linear constraints: