trivial changes for more idiomatic python (#33)

qiskit_addon_sqd/counts.py

@@ -43,7 +43,7 @@ def counts_to_arrays(counts: dict[str, float | int]) -> tuple[np.ndarray, np.nda
               bit's value
             - A 1D array containing the probability with which each bitstring was sampled
     """
-    if counts == {}:
+    if not counts:
         return np.array([]), np.array([])
     prob_dict = normalize_counts_dict(counts)
     bs_mat = np.array([[bit == "1" for bit in bitstring] for bitstring in prob_dict])
@@ -151,9 +151,9 @@ def generate_counts_bipartite_hamming(
 
 def normalize_counts_dict(counts: dict[str, float | int]) -> dict[str, float]:
     """Convert a counts dictionary into a probability dictionary."""
-    if counts == {}:
+    if not counts:
         return counts
 
-    total_counts = float(sum(counts.values()))
+    total_counts = sum(counts.values())
 
     return {bs: count / total_counts for bs, count in counts.items()}

qiskit_addon_sqd/fermion.py

@@ -78,8 +78,8 @@ def solve_fermion(
     """
     addresses = _check_addresses(addresses)
 
-    num_up = bin(addresses[0][0])[2:].count("1")
-    num_dn = bin(addresses[1][0])[2:].count("1")
+    num_up = format(addresses[0][0], "b").count("1")
+    num_dn = format(addresses[1][0], "b").count("1")
 
     # Number of molecular orbitals
     norb = hcore.shape[0]
@@ -163,8 +163,8 @@ def optimize_orbitals(
     """
     addresses = _check_addresses(addresses)
 
-    num_up = bin(addresses[0][0])[2:].count("1")
-    num_dn = bin(addresses[1][0])[2:].count("1")
+    num_up = format(addresses[0][0], "b").count("1")
+    num_dn = format(addresses[1][0], "b").count("1")
 
     # TODO: Need metadata showing the optimization history
     ## hcore and eri in physicist ordering
@@ -339,17 +339,17 @@ def _check_addresses(
 ) -> tuple[np.ndarray, np.ndarray]:
     """Make sure the hamming weight is consistent in all determinants."""
     addr_up, addr_dn = addresses
-    addr_up_ham = bin(addr_up[0])[2:].count("1")
+    addr_up_ham = format(addr_up[0], "b").count("1")
     for i, addr in enumerate(addr_up):
-        ham = bin(addr)[2:].count("1")
+        ham = format(addr, "b").count("1")
         if ham != addr_up_ham:
             raise ValueError(
                 f"Spin-up address in index 0 has hamming weight {addr_up_ham}, but address in "
                 f"index {i} has hamming weight {ham}."
             )
-    addr_dn_ham = bin(addr_dn[0])[2:].count("1")
+    addr_dn_ham = format(addr_dn[0], "b").count("1")
     for i, addr in enumerate(addr_dn):
-        ham = bin(addr)[2:].count("1")
+        ham = format(addr, "b").count("1")
         if ham != addr_dn_ham:
             raise ValueError(
                 f"Spin-down address in index 0 has hamming weight {addr_dn_ham}, but address in "

qiskit_addon_sqd/subsampling.py

@@ -67,9 +67,10 @@ def postselect_and_subsample(
         ValueError: Hamming weights must be non-negative integers.
         ValueError: Samples per batch and number of batches must be positive integers.
     """
-    if bitstring_matrix.shape[0] < 1:
+    num_bitstrings = len(bitstring_matrix)
+    if num_bitstrings == 0:
         return [np.array([])] * num_batches
-    if len(probabilities) != bitstring_matrix.shape[0]:
+    if len(probabilities) != num_bitstrings:
         raise ValueError(
             "The number of elements in the probabilities array must match the number of rows in the bitstring matrix."
         )

test/test_counts.py

@@ -25,7 +25,7 @@
 class TestCounts(unittest.TestCase):
     def setUp(self):
         self.max_val = 16
-        self.counts = {bin(i)[2:].zfill(4): 100 for i in range(self.max_val)}
+        self.counts = {format(i, "04b"): 100 for i in range(self.max_val)}
 
     def test_counts_to_arrays(self):
         with self.subTest("Basic test"):