changed the behavior of the simular: given shots = None now returns t…

…he distribution in the form of floats (instead of integers scaled with some number)
eclipse-qrisp · Mar 2, 2025 · 3ee5074 · 3ee5074
1 parent fe30b71
commit 3ee5074
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Showing 4 changed files with 15 additions and 18 deletions.
diff --git a/src/qrisp/jasp/testing_utils.py b/src/qrisp/jasp/testing_utils.py
@@ -51,9 +51,9 @@ def testing_function(*args):
 
             # new_key = int(new_key, base=2)
             try:
-                new_counts_dic[new_key] += counts[key]/100000
+                new_counts_dic[new_key] += counts[key]
             except KeyError:
-                new_counts_dic[new_key] = counts[key]/100000
+                new_counts_dic[new_key] = counts[key]
 
         for k in old_counts_dic.keys():
             if abs(old_counts_dic[k] - new_counts_dic[k]) > 1E-4:

diff --git a/src/qrisp/misc/utility.py b/src/qrisp/misc/utility.py
@@ -1331,10 +1331,10 @@ def get_measurement_from_qc(qc, qubits, backend, shots=None):
     counts = new_counts_dic
 
     # Plot result (if needed)
-
+    if shots is not None:
     # Normalize counts
-    for key in counts.keys():
-        counts[key] = counts[key] / abs(no_of_shots_executed)
+        for key in counts.keys():
+            counts[key] = counts[key] / abs(no_of_shots_executed)
 
     return counts
 

diff --git a/src/qrisp/simulator/simulator.py b/src/qrisp/simulator/simulator.py
@@ -163,26 +163,23 @@ def run(qc, shots, token="", iqs=None, insert_reset=True):
         # The iqs object contains the outcome bitstrings in the attribute .outcome_list
         # and the probablities in .cl_prob. In order to ensure qiskit compatibility, we
         # reverse the bitstrings
-
+        cl_prob = np.round(cl_prob, 5)
         norm = np.sum(cl_prob)
         cl_prob = cl_prob/norm
 
         res = {}
         #If shots >= 1000000, no samples will be drawn and the distribution will
         #be returned instead
         if shots is None:
-            shots = 100000
 
             for j in range(len(outcome_list)):
 
                 outcome_str = bin(outcome_list[j])[2:].zfill(len(mes_list))
 
-                shot_val = int(np.round(cl_prob[j]*abs(shots)))
-
                 try:
-                    res[outcome_str] += shot_val
+                    res[outcome_str] += cl_prob[j]
                 except KeyError:
-                    res[outcome_str] = shot_val
+                    res[outcome_str] = cl_prob[j]
 
         #Generate samples
         else:

diff --git a/tests/test_uncomputation_example.py b/tests/test_uncomputation_example.py
@@ -75,13 +75,13 @@ def sqrt_oracle(qf):
     print(qf)
 
     assert qf.get_measurement() == {0.5: 0.9453289065781315, 
-                                    0.0: 0.007810156203124062, 
-                                    1.0: 0.007810156203124062, 
-                                    1.5: 0.007810156203124062, 
-                                    2.0: 0.007810156203124062, 
-                                    2.5: 0.007810156203124062, 
-                                    3.0: 0.007810156203124062, 
-                                    3.5: 0.007810156203124062}
+                                    0.0: 0.007810156203124063, 
+                                    1.0: 0.007810156203124063, 
+                                    1.5: 0.007810156203124063, 
+                                    2.0: 0.007810156203124063, 
+                                    2.5: 0.007810156203124063, 
+                                    3.0: 0.007810156203124063, 
+                                    3.5: 0.007810156203124063}
 
 
     # ---------