Removes determinant and sympy dependency

Author: DrPaulSharp

requirements.txt

@@ -5,7 +5,6 @@ lxml
 # Calculation
 numpy
 scipy
-sympy
 
 # Unit testing
 pytest

sasdata/quantities/quantity.py

@@ -5,7 +5,6 @@
 
 import h5py
 import numpy as np
-import sympy as sp
 from numpy._typing import ArrayLike
 
 from sasdata.quantities import units
@@ -64,18 +63,6 @@ def matinv(a: Union["Quantity[ArrayLike]", ArrayLike]):
         return np.linalg.inv(a)
 
 
-def determinant(a: Union["Quantity[ArrayLike]", ArrayLike]):
-    """Find the determinant of an array or an array based quantity."""
-    if isinstance(a, Quantity):
-        return DerivedQuantity(
-            value=np.linalg.det(a.value),
-            units=a.units,  # TODO: hmmm, need to think about this
-            history=QuantityHistory.apply_operation(Determinant, a.history),
-        )
-    else:
-        return np.linalg.det(a)
-
-
 def norm_1(a: Union["Quantity[ArrayLike]", ArrayLike], axes: int | tuple[int] | None = None):
     """Caculate the 1-norm of an array or an array based quantity."""
     if isinstance(a, Quantity):
@@ -1201,22 +1188,6 @@ def __eq__(self, other):
         return False
 
 
-class Determinant(UnaryOperation):
-    """Array Determinant - backed by numpy's det method"""
-
-    serialisation_name = "determinant"
-
-    def evaluate(self, variables: dict[int, T]) -> T:
-        return np.linalg.det(self.a.evaluate(variables))
-
-    def _derivative(self, hash_value: int) -> Operation:
-        return Trace(sp.adjugate(self.a) * self.a._derivative(hash_value))
-
-    def _clean(self):
-        clean_a = self.a._clean()
-        return Determinant(clean_a)  # Do nothing for now - can consider identity matrix and common columns
-
-
 class Dot(BinaryOperation):
     """Dot product - backed by numpy's dot method"""
 
@@ -1280,10 +1251,6 @@ def _clean(self):
             # Removes double inversions
             return clean_a.a
 
-        elif isinstance(clean_a, Determinant):
-            # Inverse of determinant is determinant of inverse
-            return Determinant(MatInv(clean_a.a))
-
         else:
             return MatInv(clean_a)
 
@@ -1451,7 +1418,6 @@ def __eq__(self, other):
     Log,
     Transpose,
     Trace,
-    Determinant,
     Dot,
     MatMul,
     MatInv,

test/quantities/utest_operations.py

@@ -11,7 +11,6 @@
     ArcTan,
     Constant,
     Cos,
-    Determinant,
     Div,
     Dot,
     Exp,
@@ -52,7 +51,7 @@
 )
 
 
-@pytest.fixture(params=[Determinant, Inv, Exp, Ln, MatInv, Neg, Sin, ArcSin, Cos, ArcCos, Tan, ArcTan, Transpose])
+@pytest.fixture(params=[Inv, Exp, Ln, MatInv, Neg, Sin, ArcSin, Cos, ArcCos, Tan, ArcTan, Transpose])
 def unary_operation(request):
     return request.param(x)
 
@@ -205,8 +204,6 @@ def test_evaluation(op, result):
         (ArcCos, -1.0, math.pi),
         (ArcTan, 0.0, 0.0),
         (ArcTan, -1.0, -0.25 * math.pi),
-        (Determinant, np.array([[1, 2], [3, 4]]), pytest.approx(-2.0)),
-        (Determinant, np.array([[1, 4, 1], [2, 4, 2], [3, 4, 3]]), pytest.approx(0.0)),
         (Trace, np.array([[1, 2], [3, 4]]), pytest.approx(5.0)),
         (Trace, np.array([[1, 4, 1], [2, 4, 2], [3, 4, 3]]), pytest.approx(8.0)),
     ],
@@ -264,8 +261,6 @@ def test_matmul_evaluation(op, a, b, result):
 )
 def test_axis_none_evaluation(op, a, result):
     f = op(Constant(a))
-    print(f.evaluate({}))
-    print(result)
     assert (f.evaluate({}) == result).all()