Revert "Add polynomial s shape impact function"

This reverts commit fd72a29.

Author: Chahan Kropf

climada/entity/impact_funcs/base.py

@@ -273,70 +273,3 @@ def set_sigmoid_impf(self, *args, **kwargs):
         LOGGER.warning("The use of ImpactFunc.set_sigmoid_impf is deprecated."
                        "Use ImpactFunc.from_sigmoid_impf instead.")
         self.__dict__ = ImpactFunc.from_sigmoid_impf(*args, **kwargs).__dict__
-
-    @classmethod
-    def from_poly_s_shape(
-        cls,
-        intensity: tuple[float, float, float],
-        threshold: float,
-        half_point: float,
-        upper_limit: float,
-        exponent: float,
-        haz_type: str,
-        impf_id: int = 1,
-        **kwargs):
-        """S-shape polynomial impact function hinging on four parameter.
-
-        f(I) = D(I)**exponent / (1 + D(I)**exponent) * upper_limit
-
-        D(I) = max[I - threshold, 0] / (half_point - threshold)
-
-        This function is inspired by Emanuel et al. (2011)
-        https://doi.org/10.1175/WCAS-D-11-00007.1
-
-        Parameters
-        ----------
-        intensity: tuple(float, float, float)
-            tuple of 3 intensity numbers along np.arange(min, max, step)
-        threshold : float
-            Intensity threshold below which there is no impact.
-            Should in general be larger than 0 for computational efficiency
-            of impacts.
-        half_point : float
-            Intensity at which 50% of maxixmum impact is expected.
-            Must be larger than thres.
-        upper_limit : float
-            Maximum impact value. Must be larger than 0.
-        exponent: float
-            Exponent of the polynomial. Must be larger than 0.
-        haz_type: str
-            Reference string for the hazard (e.g., 'TC', 'RF', 'WS', ...)
-        impf_id : int, optional, default=1
-            Impact function id
-        kwargs :
-            keyword arguments passed to ImpactFunc()
-
-        Returns
-        -------
-        impf : climada.entity.impact_funcs.ImpactFunc
-            s-shapep polynomial impact function
-        """
-        intensity = np.arange(*intensity)
-
-        if threshold > half_point:
-            mdd = np.zeros_like(intensity)
-        else:
-            D = (intensity - threshold) / (half_point - threshold)
-            D[D < 0] = 0
-            mdd = D**exponent / (1 + D**exponent) * upper_limit
-        paa = np.ones_like(intensity)
-
-        impf = cls(
-            haz_type=haz_type,
-            id=impf_id,
-            intensity=intensity,
-            paa=paa,
-            mdd=mdd,
-            **kwargs
-        )
-        return impf

climada/entity/impact_funcs/test/test_base.py

@@ -47,6 +47,7 @@ def test_from_step(self):
         self.assertEqual(imp_fun.haz_type, 'TC')
         self.assertEqual(imp_fun.id, 2)
 
+
     def test_from_sigmoid(self):
         """Check default impact function: sigmoid function"""
         inten = (0, 100, 5)
@@ -59,34 +60,6 @@ def test_from_sigmoid(self):
         self.assertEqual(imp_fun.haz_type, 'RF')
         self.assertEqual(imp_fun.id, 2)
 
-    def test_from_poly_s_shape(self):
-        """Check default impact function: polynomial s-shape"""
-        inten = (0, 5, 1)
-        impf = ImpactFunc.from_poly_s_shape(
-            inten, threshold=0.2, half_point=1, upper_limit=0.8, exponent=4,
-            haz_type='RF', impf_id=2, intensity_unit='m'
-            )
-        correct_mdd = np.array([0, 0.4, 0.76995746, 0.79470418, 0.79843158])
-        self.assertTrue(np.array_equal(impf.paa, np.ones(5)))
-        np.testing.assert_array_almost_equal(impf.mdd, correct_mdd)
-        self.assertTrue(np.array_equal(impf.intensity, np.arange(0, 5, 1)))
-        self.assertEqual(impf.haz_type, 'RF')
-        self.assertEqual(impf.id, 2)
-        self.assertEqual(impf.intensity_unit, 'm')
-
-        # If threshold > half_point, mdd should all be 0
-        impf = ImpactFunc.from_poly_s_shape(
-            inten, threshold=2, half_point=1, upper_limit=0.8, exponent=4,
-            haz_type='RF', impf_id=2, intensity_unit='m'
-            )
-        correct_mdd = np.array([0, 0.4, 0.76995746, 0.79470418, 0.79843158])
-        self.assertTrue(np.array_equal(impf.paa, np.ones(5)))
-        np.testing.assert_array_almost_equal(impf.mdd, np.zeros(5))
-        self.assertTrue(np.array_equal(impf.intensity, np.arange(0, 5, 1)))
-        self.assertEqual(impf.haz_type, 'RF')
-        self.assertEqual(impf.id, 2)
-        self.assertEqual(impf.intensity_unit, 'm')
-
 # Execute Tests
 if __name__ == "__main__":
     TESTS = unittest.TestLoader().loadTestsFromTestCase(TestInterpolation)