[pre-commit.ci] pre-commit autoupdate

.pre-commit-config.yaml

@@ -42,7 +42,7 @@ repos:
       - id: python-use-type-annotations
       - id: text-unicode-replacement-char
   - repo: https://github.com/pycqa/isort
-    rev: 8.0.1
+    rev: 9.0.0b1
     hooks:
       - id: isort
         name: isort
@@ -55,13 +55,13 @@ repos:
   #       args:
   #         - --py37-plus
   - repo: https://github.com/psf/black-pre-commit-mirror
-    rev: 26.1.0
+    rev: 26.5.1
     hooks:
       - id: black
         language_version: python3.12
         exclude: tests/utils/fast_upper_envelope_org.py
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.15.4
+    rev: v0.16.1
     hooks:
       - id: ruff
         # exclude: |
@@ -70,7 +70,7 @@ repos:
         #     docs/source/conf.py|
         #   )$
   - repo: https://github.com/PyCQA/docformatter
-    rev: v1.7.7
+    rev: v1.7.8
     hooks:
       - id: docformatter
         args:

docs/time_period2_ops.py

@@ -24,7 +24,7 @@ def _parse_args() -> argparse.Namespace:
 
 
 def utility_crra_jax(
-    consumption: jnp.ndarray, choice: int, params: Dict[str, float]
+    consumption: jnp.ndarray, choice: int, params: dict[str, float]
 ) -> jnp.ndarray:
     utility_consumption = (consumption ** (1 - params["rho"]) - 1) / (1 - params["rho"])
     utility = utility_consumption - (1 - choice) * params["delta"]
@@ -50,7 +50,7 @@ def value_func_numba(
     test_resources / f"pol{period}.csv", delimiter=",", dtype=float
 )
 
-params: Dict[str, float] = {"beta": 0.95, "rho": 1.95, "delta": 0.35}
+params: dict[str, float] = {"beta": 0.95, "rho": 1.95, "delta": 0.35}
 state_choice = {"lagged_choice": 0, "choice": 0}
 
 

docs/tutorials/getting_started.ipynb

@@ -2,25 +2,35 @@
  "cells": [
   {
    "cell_type": "code",
-   "outputs": [],
-   "source": [
-    "import numpy as np\n",
-    "from upper_envelope.fues_numba.fues_numba import fast_upper_envelope_wrapper\n",
-    "import numba as nb\n",
-    "from collections import namedtuple\n"
-   ],
+   "execution_count": 1,
+   "id": "c71bb4b54fd1da58",
    "metadata": {
-    "collapsed": false,
     "ExecuteTime": {
      "end_time": "2024-05-24T06:42:04.589484405Z",
      "start_time": "2024-05-24T06:42:04.167227740Z"
-    }
+    },
+    "collapsed": false
    },
-   "id": "c71bb4b54fd1da58",
-   "execution_count": 1
+   "outputs": [],
+   "source": [
+    "from collections import namedtuple\n",
+    "\n",
+    "import numba as nb\n",
+    "import numpy as np\n",
+    "from upper_envelope.fues_numba.fues_numba import fast_upper_envelope_wrapper\n"
+   ]
   },
   {
    "cell_type": "code",
+   "execution_count": 2,
+   "id": "ab4b0dcb970dac41",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-05-24T06:42:04.611236211Z",
+     "start_time": "2024-05-24T06:42:04.609614665Z"
+    },
+    "collapsed": false
+   },
    "outputs": [],
    "source": [
     "@nb.njit\n",
@@ -50,27 +60,18 @@
     "    utility = utility_consumption - (1 - params_ntuple.choice) * params_ntuple.delta\n",
     "\n",
     "    return utility"
-   ],
-   "metadata": {
-    "collapsed": false,
-    "ExecuteTime": {
-     "end_time": "2024-05-24T06:42:04.611236211Z",
-     "start_time": "2024-05-24T06:42:04.609614665Z"
-    }
-   },
-   "id": "ab4b0dcb970dac41",
-   "execution_count": 2
+   ]
   },
   {
    "cell_type": "code",
    "execution_count": 3,
    "id": "initial_id",
    "metadata": {
-    "collapsed": true,
     "ExecuteTime": {
      "end_time": "2024-05-24T06:42:04.613370376Z",
      "start_time": "2024-05-24T06:42:04.609954700Z"
-    }
+    },
+    "collapsed": true
    },
    "outputs": [],
    "source": [
@@ -89,6 +90,15 @@
   },
   {
    "cell_type": "code",
+   "execution_count": 4,
+   "id": "61b7b971c6f81237",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-05-24T06:42:04.614201145Z",
+     "start_time": "2024-05-24T06:42:04.610074325Z"
+    },
+    "collapsed": false
+   },
    "outputs": [],
    "source": [
     "resource_dir = \"../../tests/resources/\"\n",
@@ -108,19 +118,19 @@
     "    \"n_constrained_points_to_add\": n_constrained_points_to_add,\n",
     "    \"n_points_to_scan\": 10,\n",
     "}"
-   ],
-   "metadata": {
-    "collapsed": false,
-    "ExecuteTime": {
-     "end_time": "2024-05-24T06:42:04.614201145Z",
-     "start_time": "2024-05-24T06:42:04.610074325Z"
-    }
-   },
-   "id": "61b7b971c6f81237",
-   "execution_count": 4
+   ]
   },
   {
    "cell_type": "code",
+   "execution_count": 5,
+   "id": "415a872b98d65631",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-05-24T06:42:04.614607376Z",
+     "start_time": "2024-05-24T06:42:04.610206856Z"
+    },
+    "collapsed": false
+   },
    "outputs": [],
    "source": [
     "\n",
@@ -130,19 +140,19 @@
     "tuning_params_tuple = namedtuple(\"tunings\", tuning_params.keys())(\n",
     "    *tuning_params.values()\n",
     ")"
-   ],
-   "metadata": {
-    "collapsed": false,
-    "ExecuteTime": {
-     "end_time": "2024-05-24T06:42:04.614607376Z",
-     "start_time": "2024-05-24T06:42:04.610206856Z"
-    }
-   },
-   "id": "415a872b98d65631",
-   "execution_count": 5
+   ]
   },
   {
    "cell_type": "code",
+   "execution_count": 6,
+   "id": "df76ba014c57934d",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2024-05-24T06:42:14.783923576Z",
+     "start_time": "2024-05-24T06:42:04.611563430Z"
+    },
+    "collapsed": false
+   },
    "outputs": [],
    "source": [
     "endog_grid_refined, policy_refined, value_refined = fast_upper_envelope_wrapper(\n",
@@ -156,16 +166,7 @@
     "    discount_factor=beta,\n",
     "    tuning_params=tuning_params_tuple,\n",
     ")"
-   ],
-   "metadata": {
-    "collapsed": false,
-    "ExecuteTime": {
-     "end_time": "2024-05-24T06:42:14.783923576Z",
-     "start_time": "2024-05-24T06:42:04.611563430Z"
-    }
-   },
-   "id": "df76ba014c57934d",
-   "execution_count": 6
+   ]
   }
  ],
  "metadata": {

docs/tutorials/ue_drued_jorg.ipynb

@@ -26,10 +26,10 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import numpy as np\n",
     "import jax\n",
     "import jax.numpy as jnp\n",
     "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
     "\n",
     "import upper_envelope.jax as upenv\n",
     "\n",

src/upper_envelope/jax/drued_jorg_jax.py

@@ -1,7 +1,8 @@
 from __future__ import annotations
 
+from collections.abc import Callable
 from functools import partial
-from typing import Callable, Dict, Optional
+from typing import Dict, Optional
 
 import jax
 import jax.numpy as jnp
@@ -16,7 +17,7 @@ def drued_jorg_jax(
     expected_value_zero_savings: jnp.ndarray | float,
     value_function: Callable,
     value_function_args=(),
-    value_function_kwargs: Optional[Dict] = None,
+    value_function_kwargs: dict | None = None,
 ):
     """Compute a simple 1D upper envelope on a given common grid.
 

src/upper_envelope/jax/fues_jax/check_and_scan_funcs.py

@@ -256,7 +256,7 @@ def forward_scan(
     n_points_to_scan: int,
     is_scan_needed,
     jump_thresh: float,
-) -> Tuple[float, int]:
+) -> tuple[float, int]:
     """Find next point on same value function as most recent point on upper envelope.
 
     We use the forward scan to find the next point that lies on the same value
@@ -322,7 +322,7 @@ def backward_scan(
     n_points_to_scan: int,
     is_scan_needed,
     jump_thresh: float,
-) -> Tuple[float, int]:
+) -> tuple[float, int]:
     """Find previous point on same value function as idx_to_scan_from.
 
     We use the backward scan to find the preceding point that lies on the same value

src/upper_envelope/jax/fues_jax/fues_jax.py

@@ -6,8 +6,9 @@
 
 """
 
+from collections.abc import Callable
 from functools import partial
-from typing import Callable, Dict, Optional, Tuple
+from typing import Dict, Optional, Tuple
 
 import jax
 import jax.numpy as jnp
@@ -35,13 +36,13 @@ def fues_jax(
     value: jnp.ndarray,
     expected_value_zero_savings: jnp.ndarray | float,
     value_function: Callable,
-    value_function_args: Optional[Tuple] = (),
-    value_function_kwargs: Optional[Dict] = None,
+    value_function_args: tuple | None = (),
+    value_function_kwargs: dict | None = None,
     n_constrained_points_to_add=None,
     n_final_wealth_grid=None,
     jump_thresh=2,
     n_points_to_scan=10,
-) -> Tuple[jnp.ndarray, jnp.ndarray, jnp.ndarray]:
+) -> tuple[jnp.ndarray, jnp.ndarray, jnp.ndarray]:
     """Drop suboptimal points and refines the endogenous grid, policy, and value.
 
     Computes the upper envelope over the overlapping segments of the
@@ -185,7 +186,7 @@ def fues_jax_unconstrained(
     n_final_wealth_grid=None,
     jump_thresh=2,
     n_points_to_scan=10,
-) -> Tuple[jnp.ndarray, jnp.ndarray, jnp.ndarray]:
+) -> tuple[jnp.ndarray, jnp.ndarray, jnp.ndarray]:
     """Remove suboptimal points from the endogenous grid, policy, and value function.
 
     Args:
@@ -249,8 +250,8 @@ def scan_value_function(
     expected_value_zero_savings,
     n_final_wealth_grid: int,
     jump_thresh: float,
-    n_points_to_scan: Optional[int] = 0,
-) -> Tuple[jnp.ndarray, jnp.ndarray, jnp.ndarray]:
+    n_points_to_scan: int | None = 0,
+) -> tuple[jnp.ndarray, jnp.ndarray, jnp.ndarray]:
     """Scan the value function to remove suboptimal points and add intersection points.
 
     Args:

src/upper_envelope/math_funcs.py

@@ -158,7 +158,7 @@ def _find_linear_intersection(
     y3: float | jnp.ndarray,
     x4: float | jnp.ndarray,
     y4: float | jnp.ndarray,
-) -> Tuple[float | jnp.ndarray, float | jnp.ndarray]:
+) -> tuple[float | jnp.ndarray, float | jnp.ndarray]:
     """Find the linear intersection of two lines.
 
     Args:
@@ -176,7 +176,6 @@ def _find_linear_intersection(
         tuple: x and y coordinates of the intersection point.
 
     """
-
     slope1 = calc_gradient(x1, y1, x2, y2)
     slope2 = calc_gradient(x3, y3, x4, y4)
 

src/upper_envelope/numba/drued_jorg_numba.py

@@ -1,4 +1,4 @@
-from typing import Callable
+from collections.abc import Callable
 
 import numpy as np
 from numba import njit