More typing stuff for mypy to pass

Author: gaffney2010

axelrod/deterministic_cache.py

@@ -14,7 +14,7 @@
 
 import pickle
 from collections import UserDict
-from typing import List, Tuple
+from typing import List, Optional, Tuple
 
 from axelrod import Classifiers
 
@@ -104,7 +104,7 @@ class DeterministicCache(UserDict):
     methods to save/load the cache to/from a file.
     """
 
-    def __init__(self, file_name: str = None) -> None:
+    def __init__(self, file_name: Optional[str] = None) -> None:
         """Initialize a new cache.
 
         Parameters

axelrod/ecosystem.py

@@ -12,7 +12,7 @@
 """
 
 import random
-from typing import Callable, List
+from typing import Callable, List, Optional
 
 from axelrod.result_set import ResultSet
 
@@ -29,8 +29,8 @@ class Ecosystem(object):
     def __init__(
         self,
         results: ResultSet,
-        fitness: Callable[[float], float] = None,
-        population: List[int] = None,
+        fitness: Optional[Callable[[float], float]] = None,
+        population: Optional[List[int]] = None,
     ) -> None:
         """Create a new ecosystem.
 

axelrod/fingerprint.py

@@ -1,7 +1,7 @@
 import os
 from collections import namedtuple
 from tempfile import mkstemp
-from typing import Any, List, Union
+from typing import Any, List, Optional, Union
 
 import dask.dataframe as dd
 import matplotlib.pyplot as plt
@@ -280,10 +280,10 @@ def fingerprint(
         turns: int = 50,
         repetitions: int = 10,
         step: float = 0.01,
-        processes: int = None,
-        filename: str = None,
+        processes: Optional[int] = None,
+        filename: Optional[str] = None,
         progress_bar: bool = True,
-        seed: int = None,
+        seed: Optional[int] = None,
     ) -> dict:
         """Build and play the spatial tournament.
 
@@ -358,7 +358,7 @@ def plot(
         self,
         cmap: str = "seismic",
         interpolation: str = "none",
-        title: str = None,
+        title: Optional[str] = None,
         colorbar: bool = True,
         labels: bool = True,
     ) -> plt.Figure:
@@ -437,11 +437,11 @@ def fingerprint(
         self,
         turns: int = 50,
         repetitions: int = 1000,
-        noise: float = None,
-        processes: int = None,
-        filename: str = None,
+        noise: Optional[float] = None,
+        processes: Optional[int] = None,
+        filename: Optional[str] = None,
         progress_bar: bool = True,
-        seed: int = None,
+        seed: Optional[int] = None,
     ) -> np.ndarray:
         """Creates a spatial tournament to run the necessary matches to obtain
         fingerprint data.
@@ -556,7 +556,7 @@ def plot(
         self,
         cmap: str = "viridis",
         interpolation: str = "none",
-        title: str = None,
+        title: Optional[str] = None,
         colorbar: bool = True,
         labels: bool = True,
         display_names: bool = False,

axelrod/mock_player.py

@@ -1,5 +1,5 @@
 from itertools import cycle
-from typing import List
+from typing import List, Optional
 
 from axelrod.action import Action
 from axelrod.player import Player
@@ -14,7 +14,7 @@ class MockPlayer(Player):
 
     name = "Mock Player"
 
-    def __init__(self, actions: List[Action] = None) -> None:
+    def __init__(self, actions: Optional[List[Action]] = None) -> None:
         super().__init__()
         if not actions:
             actions = []

axelrod/moran.py

@@ -18,15 +18,15 @@ def __init__(
         self,
         players: List[Player],
         turns: int = DEFAULT_TURNS,
-        prob_end: float = None,
+        prob_end: Optional[float] = None,
         noise: float = 0,
         game: Game = None,
         deterministic_cache: DeterministicCache = None,
         mutation_rate: float = 0.0,
         mode: str = "bd",
         interaction_graph: Graph = None,
         reproduction_graph: Graph = None,
-        fitness_transformation: Callable = None,
+        fitness_transformation: Optional[Callable] = None,
         mutation_method="transition",
         stop_on_fixation=True,
         seed=None,
@@ -175,7 +175,7 @@ def set_players(self) -> None:
         self.populations = [self.population_distribution()]
 
     def fitness_proportionate_selection(
-        self, scores: List, fitness_transformation: Callable = None
+        self, scores: List, fitness_transformation: Optional[Callable] = None
     ) -> int:
         """Randomly selects an individual proportionally to score.
 
@@ -229,7 +229,7 @@ def mutate(self, index: int) -> Player:
         # Just clone the player
         return self.players[index].clone()
 
-    def death(self, index: int = None) -> int:
+    def death(self, index: Optional[int] = None) -> int:
         """
         Selects the player to be removed.
 
@@ -258,7 +258,7 @@ def death(self, index: int = None) -> int:
             i = self.index[vertex]
         return i
 
-    def birth(self, index: int = None) -> int:
+    def birth(self, index: Optional[int] = None) -> int:
         """The birth event.
 
         Parameters
@@ -349,7 +349,6 @@ def _matchup_indices(self) -> Set[Tuple[int, int]]:
         # The other calculations are unnecessary
         if self.mode == "db":
             source = self.index[self.dead]
-            self.dead = None
             sources = sorted(self.interaction_graph.out_vertices(source))
         else:
             # birth-death is global

axelrod/plot.py

@@ -1,5 +1,5 @@
 import pathlib
-from typing import List, Union
+from typing import List, Optional, Union
 
 import matplotlib
 import matplotlib.pyplot as plt
@@ -25,8 +25,8 @@ def _violinplot(
         self,
         data: dataType,
         names: namesType,
-        title: titleType = None,
-        ax: matplotlib.axes.SubplotBase = None,
+        title: Optional[titleType] = None,
+        ax: Optional[matplotlib.axes.Axes] = None,
     ) -> matplotlib.figure.Figure:
         """For making violinplots."""
 
@@ -76,7 +76,7 @@ def _boxplot_xticks_labels(self):
         return [str(n) for n in self.result_set.ranked_names]
 
     def boxplot(
-        self, title: titleType = None, ax: matplotlib.axes.SubplotBase = None
+        self, title: Optional[titleType] = None, ax: Optional[matplotlib.axes.Axes] = None
     ) -> matplotlib.figure.Figure:
         """For the specific mean score boxplot."""
         data = self._boxplot_dataset
@@ -98,7 +98,7 @@ def _winplot_dataset(self):
         return wins, ranked_names
 
     def winplot(
-        self, title: titleType = None, ax: matplotlib.axes.SubplotBase = None
+        self, title: Optional[titleType] = None, ax: Optional[matplotlib.axes.Axes] = None
     ) -> matplotlib.figure.Figure:
         """Plots the distributions for the number of wins for each strategy."""
 
@@ -126,7 +126,7 @@ def _sdv_plot_dataset(self):
         return diffs, ranked_names
 
     def sdvplot(
-        self, title: titleType = None, ax: matplotlib.axes.SubplotBase = None
+        self, title: Optional[titleType] = None, ax: Optional[matplotlib.axes.Axes] = None
     ) -> matplotlib.figure.Figure:
         """Score difference violin plots to visualize the distributions of how
         players attain their payoffs."""
@@ -143,7 +143,7 @@ def _lengthplot_dataset(self):
         ]
 
     def lengthplot(
-        self, title: titleType = None, ax: matplotlib.axes.SubplotBase = None
+        self, title: Optional[titleType] = None, ax: Optional[matplotlib.axes.Axes] = None
     ) -> matplotlib.figure.Figure:
         """For the specific match length boxplot."""
         data = self._lengthplot_dataset
@@ -174,8 +174,8 @@ def _payoff_heatmap(
         self,
         data: dataType,
         names: namesType,
-        title: titleType = None,
-        ax: matplotlib.axes.SubplotBase = None,
+        title: Optional[titleType] = None,
+        ax: Optional[matplotlib.axes.Axes] = None,
         cmap: str = "viridis",
     ) -> matplotlib.figure.Figure:
         """Generic heatmap plot"""
@@ -202,15 +202,15 @@ def _payoff_heatmap(
         return figure
 
     def pdplot(
-        self, title: titleType = None, ax: matplotlib.axes.SubplotBase = None
+        self, title: Optional[titleType] = None, ax: Optional[matplotlib.axes.Axes] = None
     ) -> matplotlib.figure.Figure:
         """Payoff difference heatmap to visualize the distributions of how
         players attain their payoffs."""
         matrix, names = self._pdplot_dataset
         return self._payoff_heatmap(matrix, names, title=title, ax=ax)
 
     def payoff(
-        self, title: titleType = None, ax: matplotlib.axes.SubplotBase = None
+        self, title: Optional[titleType] = None, ax: Optional[matplotlib.axes.Axes] = None
     ) -> matplotlib.figure.Figure:
         """Payoff heatmap to visualize the distributions of how
         players attain their payoffs."""
@@ -223,9 +223,9 @@ def payoff(
     def stackplot(
         self,
         eco,
-        title: titleType = None,
+        title: Optional[titleType] = None,
         logscale: bool = True,
-        ax: matplotlib.axes.SubplotBase = None,
+        ax: Optional[matplotlib.axes.Axes] = None,
     ) -> matplotlib.figure.Figure:
 
         populations = eco.population_sizes

axelrod/strategies/adaptive.py

@@ -1,4 +1,4 @@
-from typing import List
+from typing import List, Optional
 
 from axelrod.action import Action
 from axelrod.player import Player
@@ -26,7 +26,7 @@ class Adaptive(Player):
         "manipulates_state": False,
     }
 
-    def __init__(self, initial_plays: List[Action] = None) -> None:
+    def __init__(self, initial_plays: Optional[List[Action]] = None) -> None:
         super().__init__()
         if not initial_plays:
             initial_plays = [C] * 6 + [D] * 5

axelrod/strategies/ann.py

@@ -1,4 +1,4 @@
-from typing import List, Tuple
+from typing import List, Optional, Tuple
 
 import numpy as np
 
@@ -198,7 +198,7 @@ class ANN(Player):
     }
 
     def __init__(
-        self, num_features: int, num_hidden: int, weights: List[float] = None
+        self, num_features: int, num_hidden: int, weights: Optional[List[float]] = None
     ) -> None:
         Player.__init__(self)
         self.num_features = num_features
@@ -236,10 +236,10 @@ def __init__(
         self,
         num_features: int,
         num_hidden: int,
-        weights: List[float] = None,
-        mutation_probability: float = None,
+        weights: Optional[List[float]] = None,
+        mutation_probability: Optional[float] = None,
         mutation_distance: int = 5,
-        seed: int = None,
+        seed: Optional[int] = None,
     ) -> None:
         EvolvablePlayer.__init__(self, seed=seed)
         (

axelrod/strategies/calculator.py

@@ -1,3 +1,5 @@
+from typing import Optional
+
 from axelrod._strategy_utils import detect_cycle
 from axelrod.action import Action
 from axelrod.player import Player
@@ -32,7 +34,7 @@ def __init__(self) -> None:
         self.joss_instance = Joss()
         super().__init__()
 
-    def set_seed(self, seed: int = None):
+    def set_seed(self, seed: Optional[int] = None):
         super().set_seed(seed)
         self.joss_instance.set_seed(seed)
 

axelrod/strategies/cycler.py

@@ -1,6 +1,6 @@
 import copy
 import itertools
-from typing import List, Tuple
+from typing import List, Optional, Tuple
 
 from axelrod.action import Action, actions_to_str, str_to_actions
 from axelrod.evolvable_player import (
@@ -109,11 +109,11 @@ class EvolvableCycler(Cycler, EvolvablePlayer):
 
     def __init__(
         self,
-        cycle: str = None,
-        cycle_length: int = None,
+        cycle: Optional[str] = None,
+        cycle_length: Optional[int] = None,
         mutation_probability: float = 0.2,
         mutation_potency: int = 1,
-        seed: int = None,
+        seed: Optional[int] = None,
     ) -> None:
         EvolvablePlayer.__init__(self, seed=seed)
         cycle, cycle_length = self._normalize_parameters(cycle, cycle_length)