[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

Author: pre-commit-ci[bot]

docs/source/_static/images/make_infectiousness_period.ipynb

@@ -126,7 +126,7 @@
    "source": [
     "dist_mean = 2 * 0.12 + 4 * 0.29 + 6 * 0.47 + 10 * 0.12\n",
     "dist_var = (\n",
-    "    2 ** 2 * 0.12 + 4 ** 2 * 0.29 + 6 ** 2 * 0.47 + 10 ** 2 * 0.12 - dist_mean ** 2\n",
+    "    2**2 * 0.12 + 4**2 * 0.29 + 6**2 * 0.47 + 10**2 * 0.12 - dist_mean**2\n",
     ")\n",
     "dist_std = np.sqrt(dist_var)\n",
     "dist_mean, dist_std"

docs/source/_static/images/make_time_until_death.ipynb

@@ -41,7 +41,7 @@
    "source": [
     "mean = 11.74\n",
     "std = 8.79\n",
-    "var = 8.79 ** 2\n",
+    "var = 8.79**2\n",
     "\n",
     "print(mean, std)"
    ]

docs/source/_static/images/make_time_until_icu_recovery.ipynb

@@ -41,7 +41,7 @@
    "source": [
     "mean = 18.8\n",
     "std = 12.21\n",
-    "var = std ** 2\n",
+    "var = std**2\n",
     "\n",
     "print(mean, std)"
    ]

docs/source/explanations/assortative_matching.ipynb

@@ -331,7 +331,6 @@
     "\n",
     "data = {}\n",
     "for value in assortative_matching_params:\n",
-    "\n",
     "    # Change assortative matching in params.\n",
     "    params.loc[(\"assortative_matching\", \"meet_people\", \"group\"), \"value\"] = value\n",
     "\n",

docs/source/reference_guides/events.rst

@@ -66,7 +66,6 @@ day from contacts and multiple events are merged with a logical OR.
         newly_infected = pd.Series(data=False, index=states.index)
 
         if date == date_of_carnival_session:
-
             adults_in_heinsberg = states.query(
                 "county == 'Kreis Heinsberg' and age_group >= '10 - 19'"
             ).index

docs/source/tutorials/how_to_model_immunity.ipynb

@@ -583,7 +583,6 @@
     "\n",
     "df_dict = {}\n",
     "for value in resistance_factors:\n",
-    "\n",
     "    # update the immunity resistance factor\n",
     "    params.loc[(\"virus_strain\", \"b117\", \"immunity_resistance_factor\"), \"value\"] = value\n",
     "\n",
@@ -636,7 +635,6 @@
     "value_to_ax = {0: 5, 0.5: 6, 1: 7}\n",
     "\n",
     "for value, color in [(0, \"tab:blue\"), (0.5, \"tab:green\"), (1, \"tab:orange\")]:\n",
-    "\n",
     "    df_dict[value].resample(\"D\", on=\"date\")[\"ever_infected\"].mean().plot(\n",
     "        ax=axs[0], color=color, label=value\n",
     "    )\n",

setup.cfg

@@ -7,7 +7,7 @@ url = https://github.com/covid-19-impact-lab/sid
 author = Janos Gabler, Tobias Raabe, Klara Roehrl
 author_email = [email protected]
 license = MIT
-license_file = LICENSE
+license_files = LICENSE
 platforms = any
 classifiers =
     Development Status :: 3 - Alpha
@@ -16,10 +16,6 @@ classifiers =
     Operating System :: OS Independent
     Programming Language :: Python :: 3
     Programming Language :: Python :: 3 :: Only
-    Programming Language :: Python :: 3.6
-    Programming Language :: Python :: 3.7
-    Programming Language :: Python :: 3.8
-    Programming Language :: Python :: 3.9
     Topic :: Scientific/Engineering
 project_urls =
     Changelog = https://sid-dev.readthedocs.io/en/latest/changes.html
@@ -41,7 +37,7 @@ install_requires =
     python-snappy
     seaborn
     tqdm
-python_requires = >=3.6
+python_requires = >=3.8
 include_package_data = True
 package_dir =
     =src

src/sid/contacts.py

@@ -740,7 +740,6 @@ def _sum_preserving_round(arr):
     deviation = 0
 
     for i in range(len(arr)):
-
         floor_value = int(arr[i])
         deviation += arr[i] - floor_value
 

src/sid/initial_conditions.py

@@ -255,7 +255,6 @@ def sample_initial_distribution_of_infections_and_immunity(
     states = update_derived_state_variables(states, derived_state_variables)
 
     for burn_in_date in initial_conditions["burn_in_periods"]:
-
         states["date"] = burn_in_date
         states["period"] = timestamp_to_sid_period(burn_in_date)
 

src/sid/msm.py

@@ -156,7 +156,7 @@ def _msm(
     moment_errors = flat_simulated_moments - flat_empirical_moments
 
     root_contribs = np.sqrt(np.diagonal(weighting_matrix)) * moment_errors
-    value = np.sum(root_contribs ** 2)
+    value = np.sum(root_contribs**2)
 
     out = {
         "value": value,

src/sid/update_states.py

@@ -289,7 +289,7 @@ def _get_waning_immunity_coefficients(
         ("immunity", "immunity_waning", f"slope_after_maximum_{event}"), "value"
     ]
 
-    slope_before_maximum = maximum_immunity / (time_to_reach_maximum ** 3)
+    slope_before_maximum = maximum_immunity / (time_to_reach_maximum**3)
     intercept_after_maximum = (
         maximum_immunity - slope_after_maximum * time_to_reach_maximum
     )