modularized

maths/vectors/vector_add.py

@@ -0,0 +1,14 @@
+"""
+Add two vectors of the same dimension using NumPy.
+"""
+import numpy as np
+from typing import List, Union
+
+Vector = Union[List[float], np.ndarray]
+
+def vector_add(vector1: Vector, vector2: Vector) -> np.ndarray:
+    v1 = np.array(vector1)
+    v2 = np.array(vector2)
+    if v1.shape != v2.shape:
+        raise ValueError("Vectors must have the same dimensions for addition.")
+    return np.add(v1, v2)

maths/vectors/{vectors.py → vector_cross_product.py}

@@ -1,32 +1,11 @@
 """
-Vector operations for university level, using NumPy.
+Compute the cross product of two 3-dimensional vectors using NumPy.
 """
 import numpy as np
 from typing import List, Union
 
 Vector = Union[List[float], np.ndarray]
 
-def vector_add(vector1: Vector, vector2: Vector) -> np.ndarray:
-    v1 = np.array(vector1)
-    v2 = np.array(vector2)
-    if v1.shape != v2.shape:
-        raise ValueError("Vectors must have the same dimensions for addition.")
-    return np.add(v1, v2)
-
-def vector_subtract(vector1: Vector, vector2: Vector) -> np.ndarray:
-    v1 = np.array(vector1)
-    v2 = np.array(vector2)
-    if v1.shape != v2.shape:
-        raise ValueError("Vectors must have the same dimensions for subtraction.")
-    return np.subtract(v1, v2)
-
-def vector_dot_product(vector1: Vector, vector2: Vector) -> float:
-    v1 = np.array(vector1)
-    v2 = np.array(vector2)
-    if v1.shape != v2.shape:
-        raise ValueError("Vectors must have the same dimensions for dot product.")
-    return np.dot(v1, v2)
-
 def vector_cross_product(vector1: Vector, vector2: Vector) -> np.ndarray:
     v1 = np.array(vector1)
     v2 = np.array(vector2)

maths/vectors/vector_dot_product.py

@@ -0,0 +1,14 @@
+"""
+Compute the dot product of two vectors of the same dimension using NumPy.
+"""
+import numpy as np
+from typing import List, Union
+
+Vector = Union[List[float], np.ndarray]
+
+def vector_dot_product(vector1: Vector, vector2: Vector) -> float:
+    v1 = np.array(vector1)
+    v2 = np.array(vector2)
+    if v1.shape != v2.shape:
+        raise ValueError("Vectors must have the same dimensions for dot product.")
+    return np.dot(v1, v2)

maths/vectors/vector_subtract.py

@@ -0,0 +1,14 @@
+"""
+Subtract one vector from another of the same dimension using NumPy.
+"""
+import numpy as np
+from typing import List, Union
+
+Vector = Union[List[float], np.ndarray]
+
+def vector_subtract(vector1: Vector, vector2: Vector) -> np.ndarray:
+    v1 = np.array(vector1)
+    v2 = np.array(vector2)
+    if v1.shape != v2.shape:
+        raise ValueError("Vectors must have the same dimensions for subtraction.")
+    return np.subtract(v1, v2)

maths/vectors/vectors_interface.py

@@ -5,9 +5,10 @@ import gradio as gr
 import numpy as np
 import json
 from typing import Union
-from maths.vectors.vectors import (
-    vector_add, vector_subtract, vector_dot_product, vector_cross_product
-)
+from maths.vectors.vector_add import vector_add
+from maths.vectors.vector_subtract import vector_subtract
+from maths.vectors.vector_dot_product import vector_dot_product
+from maths.vectors.vector_cross_product import vector_cross_product
 
 def parse_vector(vector_str: str) -> np.ndarray:
     try: