Additional type hinting, documentation, fixed to gates.py, cleaning code

src/qcrypto/gates.py

@@ -1,43 +1,41 @@
 import numpy as np
-
-Pauli_gates = [
-    np.array([[0, 1], [1, 0]], dtype=np.complex_),
-    np.array([[0, -1j], [1j, 0]], dtype=np.complex_),
-    np.array([[1, 0], [0, -1]], dtype=np.complex_),
-]
-
-H_gate = (1 / np.sqrt(2)) * np.array([[1, 1], [1, -1]], dtype=np.complex_)
-
-
-def tensor_power(gate, N):
+import numpy.typing as npt
+from typing import Union, Dict
+
+Pauli: Dict[str, npt.NDArray[np.complex_]] = {
+    "x": np.array([[0, 1], [1, 0]], dtype=np.complex_),
+    "y": np.array([[0, -1j], [1j, 0]], dtype=np.complex_),
+    "z": np.array([[1, 0], [0, -1]], dtype=np.complex_),
+}
+
+H_gate: npt.NDArray[np.complex_] = (1 / np.sqrt(2)) * np.array([[1, 1], [1, -1]], dtype=np.complex_)
+
+def Phase_shift(phase: float) -> npt.NDArray[np.complex_]:
+    """Generates a phase shift gate for a given phase.
+
+    Args:
+        phase (float): The phase angle in radians.
+
+    Returns:
+        NDArray: A 2x2 numpy array representing the phase shift gate.
+    """
+    phase_shift_gate = np.array(
+        [1, 0],
+        [0, np.e**(1j * phase)]
+    )
+    return phase_shift_gate
+
+def tensor_power(gate: npt.NDArray[np.complex_], N: int) -> npt.NDArray[np.complex_]:
+    """Computes the tensor power of a 2x2 gate matrix.
+
+    Args:
+        gate (NDArray): A 2x2 numpy array representing a quantum gate.
+        N (int): The power to which the gate matrix is to be raised, tensor-wise.
+
+    Returns:
+        NDArray: A numpy array representing the N-th tensor power of the gate.
+    """
     result = gate
     for _ in range(N - 1):
         result = np.kron(result, gate)
     return result
-
-
-def Gate(state, gate):
-    N = int(np.log2(len(state)))
-    gate = tensor_power(gate, N)
-    new_state = np.dot(gate, state)
-    return new_state
-
-
-def Hadamard(state):
-    N = int(np.log2(len(state)))
-    gate = tensor_power(H_gate, N)
-    new_state = np.dot(gate, state)
-    return new_state
-
-
-def Pauli(state, i=0):
-    # N = int(np.log2(len(state)))
-    # gate = Pauli_gates[i]
-    # new_state = np.dot(gate, state)
-    # return new_state
-    pass
-
-
-def Rot(state, thetax=0, thetay=0, thetaz=0):
-    #     Rx = np.array([np.cos(thetax/2), -1j * np.sin(thetax/2)], [-1j * np.sin(thetax/2), np.cos(thetax/2)])
-    pass