Remove unused get_samples() function for noiseless simulation

This can be replaced by using the get_samples_noisy() and a noiseless aer simulator.

Author: kaminotesf

.gitignore

@@ -178,5 +178,6 @@ cython_debug/
 .pypirc
 
 # Ignore everything under tutorial/forest gallery
+/forest\ gallery
 /tutorials/forest\ gallery/
 CLAUDE.md

hadamard_random_forest/__init__.py

@@ -24,7 +24,6 @@
 from .sample import (
     get_circuits,
     get_circuits_hardware,
-    get_samples,
     get_samples_noisy,
     get_samples_hardware,
     get_statevector
@@ -48,7 +47,6 @@
     "generate_random_forest",
     "get_circuits",
     "get_circuits_hardware",
-    "get_samples",
     "get_samples_noisy",
     "get_samples_hardware",
     "get_statevector",

hadamard_random_forest/sample.py

@@ -14,7 +14,6 @@
 from qiskit.providers import Backend
 from qiskit.transpiler import generate_preset_pass_manager
 from qiskit_ibm_runtime import SamplerV2 as Sampler
-from qiskit_aer.primitives import Sampler as Aer_Sampler
 from mthree import M3Mitigation
 import mthree.utils as mthree_utils
 
@@ -47,40 +46,6 @@ def get_circuits(
     return circuits
 
 
-def get_samples(
-    num_qubits: int,
-    sampler: Aer_Sampler | Sampler,
-    circuits: List[qiskit.QuantumCircuit],
-    parameters: np.ndarray
-) -> List[np.ndarray]:
-    """
-    Execute circuits and collect probability distributions using a noiseless sampler.
-
-    Args:
-        num_qubits: Number of qubits (defines statevector size 2**num_qubits).
-        sampler: Sampler object providing run().result().quasi_dists.
-        circuits: List of QuantumCircuit to execute.
-        parameters: 1D array of parameter values to bind to each circuit.
-
-    Returns:
-        List of 1D numpy arrays of length 2**num_qubits representing probabilities.
-    """
-    n = len(circuits)
-    if isinstance(sampler, Aer_Sampler):
-        results = sampler.run(circuits, [parameters] * n).result().quasi_dists
-    elif isinstance(sampler, Sampler):
-        results = sampler.run([(qc, parameters) for qc in circuits]).result()[0].data.meas.get_counts()
-    else:
-        raise ValueError("Sampler must be of type qiskit_aer.primitives.Sampler or qiskit_ibm_runtime.SamplerV2.")
-    
-    samples: List[np.ndarray] = []
-    for res in results:
-        proba = np.zeros(2**num_qubits, dtype=float)
-        for idx, val in res.items():
-            proba[idx] = val
-        samples.append(proba)
-    return samples
-
 
 def get_samples_noisy(
     num_qubits: int,

tests/test_sample.py

@@ -1,12 +1,12 @@
 import unittest
 import numpy as np
 from qiskit.circuit.random import random_circuit
-from qiskit_aer.primitives import Sampler as Aer_Sampler
+from qiskit_aer import AerSimulator
 from qiskit.circuit.library import real_amplitudes
 from hadamard_random_forest.sample import (
     get_statevector,
     get_circuits,
-    get_samples
+    get_samples_noisy
 )
 
 class TestSample(unittest.TestCase):
@@ -26,25 +26,6 @@ def test_get_circuits(self):
             self.assertEqual(circuit.num_qubits, num_qubits)
             self.assertIsNotNone(circuit)
 
-    def test_get_samples(self):
-        """Test the get_samples function."""
-        num_qubits = 3
-        sampler = Aer_Sampler()
-        base_circuit = real_amplitudes(num_qubits)
-        circuits = get_circuits(num_qubits, base_circuit)
-        parameters = np.random.rand(base_circuit.num_parameters)
-        samples = get_samples(num_qubits, sampler, circuits, parameters)
-        
-        # Original tests
-        self.assertIsInstance(samples, list)
-        self.assertEqual(len(samples), 4)
-        
-        # Enhanced tests
-        for sample in samples:
-            self.assertIsInstance(sample, np.ndarray)
-            self.assertEqual(sample.shape, (8,))  # 2^3 = 8
-            self.assertTrue(np.all(sample >= 0))  # Non-negative probabilities
-            self.assertAlmostEqual(np.sum(sample), 1.0, places=10)  # Normalized
 
     def test_get_statevector(self):
         """Test the get_statevector function."""
@@ -69,13 +50,14 @@ def test_integration(self):
         """Test the complete workflow integration."""
         num_qubits = 2  # Smaller for faster testing
         num_trees = 3
-        sampler = Aer_Sampler()
+        backend_sim = AerSimulator()
         base_circuit = real_amplitudes(num_qubits)
         parameters = np.random.rand(base_circuit.num_parameters)
+        shots = 1024
 
         # Complete workflow
         circuits = get_circuits(num_qubits, base_circuit)
-        samples = get_samples(num_qubits, sampler, circuits, parameters)
+        samples = get_samples_noisy(num_qubits, circuits, shots, parameters, backend_sim, error_mitigation=False)
         statevector = get_statevector(num_qubits, num_trees, samples, save_tree=False)
 
         # Validate end-to-end