feat: remove invalid_value functionality in bisect (#13)

* feat: remove invalid_value functionality in bisect

BREAKING CHANGE: remove invalid_value parameter and functionality in bisect method, instead raise ValueError. By extension, changes behaviour of compute_conductor_ampacity which had invaluid_value set to 0 when bisect failed.

* test that bisect raises ValueError

* fix bisect function for array inputs, more tests

* Update tests/test_solver.py

* Update tests/test_solver.py

---------

Co-authored-by: Amund Faller Råheim <[email protected]>
Co-authored-by: Gunnhild Svandal Presthus <[email protected]>

linerate/solver.py

@@ -1,5 +1,5 @@
 from functools import partial
-from typing import Callable, Optional
+from typing import Callable
 
 import numpy as np
 
@@ -13,7 +13,6 @@ def bisect(
     xmin: FloatOrFloatArray,
     xmax: FloatOrFloatArray,
     tolerance: float,
-    invalid_value: Optional[float] = None,
 ) -> FloatOrFloatArray:
     r"""Compute the roots of a function using a vectorized bisection method.
 
@@ -32,9 +31,6 @@ def bisect(
         bounded within an interval of size :math:`\Delta x` or less. The bisection method will
         run for :math:`\left\lceil\frac{x_\max - x_\min}{\Delta x}\right\rceil`
         iterations.
-    invalid_value:
-        If provided, then the this value is used whenever
-        :math:`\text{sign}(f(\mathbf{x}_\min)) = \text{sign}(f(\mathbf{x}_\max))`.
 
     Returns
     -------
@@ -43,20 +39,18 @@ def bisect(
         there is a root :math:`x_i \in [\tilde{x}_i - 0.5 \Delta x, \tilde{x}_i + 0.5 \Delta x]`
         so :math:`f_i(x_i) = 0`.
     """
-    if not np.isfinite(xmin) or not np.isfinite(xmax):
+    if not np.all(np.isfinite(xmin)) or not np.all(np.isfinite(xmax)):
         raise ValueError("xmin and xmax must be finite.")
     interval = np.max(np.abs(xmax - xmin))
 
     f_left = f(xmin)
     f_right = f(xmax)
 
     invalid_mask = np.sign(f_left) == np.sign(f_right)
-    if np.any(invalid_mask) and invalid_value is None:
+    if np.any(invalid_mask):
         raise ValueError(
             "f(xmin) and f(xmax) have the same sign. Consider increasing the search interval."
         )
-    elif isinstance(invalid_mask, bool) and invalid_mask:
-        return invalid_value  # type: ignore
 
     while interval > tolerance:
         xmid = 0.5 * (xmax + xmin)
@@ -69,7 +63,7 @@ def bisect(
         f_left = np.where(mask, f_mid, f_left)
         f_right = np.where(mask, f_right, f_mid)
 
-    out = np.where(invalid_mask, invalid_value, 0.5 * (xmax + xmin))  # type: ignore
+    out = 0.5 * (xmax + xmin)
     return out
 
 
@@ -139,7 +133,7 @@ def compute_conductor_ampacity(
         :math:`\Delta I~\left[\text{A}\right]`. The numerical accuracy of the ampacity. The
         bisection iterations will stop once the numerical ampacity uncertainty is below
         :math:`\Delta I`. The bisection method will run for
-        :math:`\left\lceil\frac{I_\text{min} - I_\text{min}}{\Delta I}\right\rceil` iterations.
+        :math:`\left\lceil\frac{I_\text{max} - I_\text{min}}{\Delta I}\right\rceil` iterations.
 
     Returns
     -------
@@ -148,4 +142,4 @@ def compute_conductor_ampacity(
     """
     f = partial(heat_balance, max_conductor_temperature)
 
-    return bisect(f, min_ampacity, max_ampacity, tolerance, invalid_value=0)
+    return bisect(f, min_ampacity, max_ampacity, tolerance)

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "linerate"
-version = "0.0.7-post.3+62231f4"
+version = "1.0.0"
 description = "Library for computing line ampacity ratings for overhead lines"
 authors = ["Statnett Datascience <[email protected]>", "Yngve Mardal Moe <[email protected]>"]
 repository = "https://github.com/statnett/linerate.git"

tests/test_solver.py

@@ -1,3 +1,4 @@
+import numpy as np
 import pytest
 
 import linerate.solver as solver
@@ -31,17 +32,58 @@ def heat_balance(conductor_temperature, current):
     assert conductor_temperature == pytest.approx(9000, rel=1e-7)
 
 
-def test_compute_conductor_temperature_caps_ampacity_at_zero():
-    def heat_balance(conductor_temperature, current):
+def test_bisect_raises_value_error():
+    def heat_balance(current):
         A = current
-        T = conductor_temperature
-        return (A + 100 * T) * (current + 200 * T)
+        T = 90
+        return (A + 100 * T) * (A + 100 * T)
 
-    conductor_temperature = solver.compute_conductor_ampacity(
+    with pytest.raises(ValueError):
+        solver.bisect(
+            heat_balance,
+            xmin=0,
+            xmax=10_000,
+            tolerance=1e-8,
+        )
+
+
+def test_bisect_handles_function_returning_array_happy_path():
+    def heat_balance(currents: np.array):
+        A = currents
+        T = 90
+        res = (A - 100 * T) * (currents + 100 * T)
+        return res
+
+    solution = solver.bisect(
         heat_balance,
-        max_conductor_temperature=90,
-        min_ampacity=0,
-        max_ampacity=10_000,
+        xmin=np.array([0, 0]),
+        xmax=np.array([10_000, 10_000]),
         tolerance=1e-8,
     )
-    assert conductor_temperature == pytest.approx(0, rel=1e-7)
+    np.testing.assert_array_almost_equal(solution, [9_000, 9_000], decimal=8)
+
+
+def test_bisect_raises_valueerror_when_same_sign_for_array_input():
+    def heat_balance(currents: np.array):
+        A = currents
+        T = 90
+        res = (A - 100 * T) * (currents + 100 * T)
+        return res
+
+    with pytest.raises(ValueError):
+        solver.bisect(
+            heat_balance,
+            xmin=np.array([0, 0]),
+            xmax=np.array([10_000, 8_000]),
+            tolerance=1e-8,
+        )
+
+
+def test_bisect_raises_valueerror_when_infinite_in_array_input():
+    with pytest.raises(ValueError):
+        solver.bisect(
+            lambda x: x,
+            xmin=np.array([-np.inf, 0]),
+            xmax=np.array([10_000, 10_000]),
+            tolerance=1e-8,
+        )