Storing and Plotting Additional QED-C Metrics

.gitignore

@@ -44,3 +44,7 @@ docs/_build/
 
 # mypy
 .mypy_cache/
+
+# QC-App-Oriented-Benchmarks
+__data/
+__images/

metriq_gym/benchmarks/qedc_benchmarks.py

@@ -19,6 +19,7 @@
 from metriq_gym.helpers.task_helpers import flatten_counts
 
 from _common import metrics
+from _common.qiskit import execute as ex
 
 
 QEDC_BENCHMARK_IMPORTS: dict[JobType, str] = {
@@ -32,36 +33,34 @@
 Type: QEDC_Metrics
 Description: 
     The structure for all returned QED-C circuit metrics. 
-    The first key represents the number of qubits for the group of circuits.
-    The second key represents the unique identifier for a circuit in the group. 
+
+    1. The first key represents the number of qubits for the group of circuits or the subtitle.
+    2. The second key represents the unique identifier for a circuit in the group. 
         - This may be a secret string for Bernstein-Vazirani, theta value for Phase-Estimation, 
           and so on. Benchmark specific documentation can be found in QED-C's 
           QC-App-Oriented-Benchmarks repository.
-    The third key represents the metric being stored.
+    3. The third key represents the metric being stored.
+
 Example for Bernstein-Vazirani:
 {
 '3':    {
-        '1': {'create_time': 0.16371703147888184,
-              'fidelity': 1.0,
+        '1': {'fidelity': 1.0,
               'hf_fidelity': 1.0},
-        '2': {'create_time': 0.0005087852478027344,
-              'fidelity': 1.0,
+        '2': {'fidelity': 1.0,
               'hf_fidelity': 1.0}
         },
 '4':    {
-        '1': {'create_time': 0.0005209445953369141,
-              'fidelity': 1.0,
+        '1': {'fidelity': 1.0,
               'hf_fidelity': 1.0},
-        '3': {'create_time': 0.00047206878662109375,
-              'fidelity': 1.0,
+        '3': {'fidelity': 1.0,
               'hf_fidelity': 1.0},
-        '5': {'create_time': 0.0005078315734863281,
-              'fidelity': 1.0,
+        '5': {'fidelity': 1.0,
               'hf_fidelity': 1.0}
         }
+'subtitle': "device = X"
 }
 """
-QEDC_Metrics = dict[str, dict[str, dict[str, float]]]
+QEDC_Metrics = dict[str, dict[str, dict[str, float]] | str]
 
 
 @dataclass
@@ -141,7 +140,7 @@ def get_counts(self, _):
     benchmark_name = str(params["benchmark_name"])
     benchmark = import_benchmark_module(benchmark_name)
 
-    # Restore circuit metrics dictionary from the dispatch data
+    # Restore circuit metrics from the dispatch data
     metrics.circuit_metrics = job_data.circuit_metrics
 
     # Iterate and get the metrics for each circuit in the list.
@@ -171,8 +170,32 @@ def get_counts(self, _):
                 None, result_object, int(num_qubits), int(circuit_id), params["num_shots"]
             )
 
+        # Store the fidelity.
         metrics.store_metric(num_qubits, circuit_id, "fidelity", fidelity)
 
+    # Code below plots the metrics:
+
+    # Compute statistics for metrics.
+    metrics.aggregate_metrics()
+
+    # Set backend information for plot titles.
+    provider_name = "qBraid"
+    device_name = "<unknown>"
+
+    # Set plot titles.
+    benchmark_title = f"{benchmark_name} ({params.get('method', '1')})"
+    subtitle = f"Benchmark Results - {benchmark_title} - {provider_name}"
+    metrics.circuit_metrics["subtitle"] = f"device = {device_name}"
+
+    # Determine which metrics to plot.
+    filters = ["fidelity", "hf_fidelity", "depth", "2q", "vbplot"]
+
+    # Plot the metrics.
+    metrics.plot_metrics(subtitle, filters=filters)
+
+    # Remove subtilte key.
+    metrics.circuit_metrics.pop("subtitle", None)
+
     return metrics.circuit_metrics
 
 
@@ -184,7 +207,8 @@ def get_circuits_and_metrics(
     Uses QED-C submodule to obtain circuits and circuit metrics.
 
     Args:
-        params: the parameters to run the benchmark with, also includes benchmark_name.
+        benchmark_name: the name of the benchmark.
+        params: the parameters to run the benchmark with.
 
     Returns:
         circuits: the list of quantum circuits for the benchmark.
@@ -201,9 +225,12 @@ def get_circuits_and_metrics(
         get_circuits=True,
     )
 
-    # Remove the subtitle key to keep our desired format.
+    # Remove the subtitle key for iterating purposes.
     circuit_metrics.pop("subtitle", None)
 
+    # Copy any initial creation metrics (i.e. create_time).
+    metrics.circuit_metrics = circuit_metrics
+
     # Store the circuit identifiers and a flat list of circuits.
     circuit_identifiers = []
     flat_circuits = []
@@ -212,7 +239,16 @@ def get_circuits_and_metrics(
             circuit_identifiers.append((num_qubits, circuit_id))
             flat_circuits.append(circuits[num_qubits][circuit_id])
 
-    return flat_circuits, circuit_metrics, circuit_identifiers
+            # Compute circuit properties (depth, etc.) and store to metrics.
+            ex.compute_and_store_circuit_info(
+                circuits[num_qubits][circuit_id],
+                str(num_qubits),
+                str(circuit_id),
+                do_transpile_metrics=True,
+                use_normalized_depth=True,
+            )
+
+    return flat_circuits, metrics.circuit_metrics, circuit_identifiers
 
 
 class QEDCBenchmark(Benchmark):

metriq_gym/schemas/examples/bernstein_vazirani.example.json

@@ -2,7 +2,7 @@
     "benchmark_name": "Bernstein-Vazirani",
     "num_shots": 1000,
     "min_qubits": 2,
-    "max_qubits": 6,
+    "max_qubits": 10,
     "skip_qubits": 1,
     "max_circuits": 3,
     "method": 1

metriq_gym/schemas/examples/hidden_shift.example.json

@@ -2,7 +2,7 @@
     "benchmark_name": "Hidden Shift",
     "num_shots": 1000,
     "min_qubits": 2,
-    "max_qubits": 6,
+    "max_qubits": 10,
     "skip_qubits": 1,
     "max_circuits": 3,
     "method": 1

metriq_gym/schemas/examples/phase_estimation.example.json

@@ -2,7 +2,7 @@
     "benchmark_name": "Phase Estimation",
     "num_shots": 1000,
     "min_qubits": 2,
-    "max_qubits": 6,
+    "max_qubits": 10,
     "skip_qubits": 1,
     "max_circuits": 3,
     "method": 1,

metriq_gym/schemas/examples/quantum_fourier_transform.example.json

@@ -2,7 +2,7 @@
     "benchmark_name": "Quantum Fourier Transform",
     "num_shots": 1000,
     "min_qubits": 2,
-    "max_qubits": 6,
+    "max_qubits": 10,
     "skip_qubits": 1,
     "max_circuits": 3,
     "method": 1,

metriq_gym/schemas/phase_estimation.schema.json

@@ -62,7 +62,6 @@
       "description": "Creates circuits with mid-circuit measurements.",
       "default": false,
       "examples": [true]
-
     }
   },
   "required": ["benchmark_name"],

metriq_gym/schemas/quantum_fourier_transform.schema.json

@@ -64,7 +64,6 @@
       "description": "Creates circuits with mid-circuit measurements.",
       "default": false,
       "examples": [true]
-
     }
   },
   "required": ["benchmark_name"],