Update black in pre-commit.

Closes #1223.

.pre-commit-config.yaml

@@ -1,6 +1,6 @@
 repos:
   - repo: https://github.com/psf/black
-    rev: 20.8b1
+    rev: 22.3.0
     hooks:
       - id: black
         language_version: python3

docs/selection_example.py

@@ -147,7 +147,7 @@ def adaptive_introgression(seed):
         model,
         contig,
         samples,
-        seed=rng.randrange(1, 2 ** 32),
+        seed=rng.randrange(1, 2**32),
         extended_events=extended_events,
         slim_scaling_factor=10,
         slim_burn_in=0.1,

requirements/development.txt

@@ -1,4 +1,4 @@
-black
+black>=22.1.0
 blacken-docs
 codecov
 coverage

stdpopsim/catalog/AraTha/species.py

@@ -58,7 +58,7 @@
     common_name="A. thaliana",
     genome=_genome,
     generation_time=1.0,
-    population_size=10 ** 4,
+    population_size=10**4,
     citations=[
         stdpopsim.Citation(
             doi="https://doi.org/10.1890/0012-9658(2002)083[1006:GTINSO]2.0.CO;2",

stdpopsim/catalog/HomSap/demographic_models.py

@@ -1500,14 +1500,14 @@ def _AJ():
 
     # effective population sizes
     NANC = 7300  # not inferred. Value taken from Gutenkunst et al. 2009
-    NYRI = 10 ** 4.26
-    NCHB = 10 ** 3.61
-    NCEU = 10 ** 4.52
-    NM = 10 ** 5.64
-    NJ = 10 ** 5.55
-    NAg = 10 ** 3.04
-    NWA = 10 ** 3.82
-    NEA = 10 ** 6.29
+    NYRI = 10**4.26
+    NCHB = 10**3.61
+    NCEU = 10**4.52
+    NM = 10**5.64
+    NJ = 10**5.55
+    NAg = 10**3.04
+    NWA = 10**3.82
+    NEA = 10**6.29
 
     # admixture proportion from European to Ashkenazi Jews.
     m = 0.17

stdpopsim/catalog/HomSap/species.py

@@ -96,7 +96,7 @@
     common_name="Human",
     genome=_genome,
     generation_time=30,
-    population_size=10 ** 4,
+    population_size=10**4,
     citations=[
         _tremblay2000.because(stdpopsim.CiteReason.GEN_TIME),
         _takahata1993.because(stdpopsim.CiteReason.POP_SIZE),

stdpopsim/engines.py

@@ -249,7 +249,7 @@ def simulate(
         self._warn_mutation_rate_mismatch(contig, demographic_model)
 
         rng = np.random.default_rng(seed)
-        seeds = rng.integers(1, 2 ** 31 - 1, size=2)
+        seeds = rng.integers(1, 2**31 - 1, size=2)
 
         ts = msprime.sim_ancestry(
             samples=samples,

stdpopsim/qc/HomSap.py

@@ -1114,14 +1114,14 @@ def GladsteinAshkSubstructure():
 
     # Population sizes from supp tab 3
     N_ANC = 7300
-    N_YRI = 10 ** 4.26
-    N_CEU = 10 ** 4.52
-    N_CHB = 10 ** 3.61
-    N_WA = 10 ** 3.82
-    N_EA = 10 ** 6.29
-    N_Ag = 10 ** 3.04
-    N_J = 10 ** 5.55
-    N_M = 10 ** 5.64
+    N_YRI = 10**4.26
+    N_CEU = 10**4.52
+    N_CHB = 10**3.61
+    N_WA = 10**3.82
+    N_EA = 10**6.29
+    N_Ag = 10**3.04
+    N_J = 10**5.55
+    N_M = 10**5.64
 
     # Migration rate from CEU to ASHK ancestral pop
     m = 0.17

stdpopsim/slim_engine.py

@@ -1604,7 +1604,7 @@ def _recap_and_rescale(self, ts, seed, recap_epoch, contig, slim_scaling_factor)
         ts = tables.tree_sequence()
 
         rng = random.Random(seed)
-        s0 = rng.randrange(1, 2 ** 32)
+        s0 = rng.randrange(1, 2**32)
         population_configurations = [
             msprime.PopulationConfiguration(
                 initial_size=pop.start_size,
@@ -1633,7 +1633,7 @@ def _recap_and_rescale(self, ts, seed, recap_epoch, contig, slim_scaling_factor)
             assert len(dfe["proportions"]) == len(dfe["mutation_types"])
             for prop, mt in zip(dfe["proportions"], dfe["mutation_types"]):
                 if mt["is_neutral"]:
-                    mut_seed = rng.randrange(1, 2 ** 32)
+                    mut_seed = rng.randrange(1, 2**32)
                     # Figuring out SLiM mutation id metadata
 
                     def _get_next_id(ts):

tests/test_AraTha.py

@@ -6,7 +6,7 @@ class TestSpecies(test_species.SpeciesTestBase):
     species = stdpopsim.get_species("AraTha")
 
     def test_basic_attributes(self):
-        assert self.species.population_size == 10 ** 4
+        assert self.species.population_size == 10**4
         assert self.species.generation_time == 1
 
 

tests/test_HomSap.py

@@ -12,7 +12,7 @@ class TestSpecies(test_species.SpeciesTestBase):
     species = stdpopsim.get_species("HomSap")
 
     def test_basic_attributes(self):
-        assert self.species.population_size == 10 ** 4
+        assert self.species.population_size == 10**4
         assert self.species.generation_time == 30
 
 

tests/test_PonAbe.py

@@ -6,7 +6,7 @@ class TestSpecies(test_species.SpeciesTestBase):
     species = stdpopsim.get_species("PonAbe")
 
     def test_basic_attributes(self):
-        assert self.species.population_size == 1.79 * 10 ** 4
+        assert self.species.population_size == 1.79 * 10**4
         assert self.species.generation_time == 20
 
 

validation.py

@@ -646,7 +646,7 @@ def do_simulations(rng, path, num_replicates, executor, key):
     out_dir = path / "trees" / key
     out_dir.mkdir(parents=True, exist_ok=True)
     func = functools.partial(simulation_functions[key], out_dir)
-    seeds = (rng.randrange(1, 2 ** 32) for _ in range(num_replicates))
+    seeds = (rng.randrange(1, 2**32) for _ in range(num_replicates))
     res = list(executor.map(func, seeds))
     files, times = zip(*res)
     # dump timing info to a file