with test and assertion

Author: TomerGoldfriend

applications/physical_systems/quantum_maps/quantum_sawtooth_map.ipynb

@@ -503,17 +503,29 @@
    ]
   },
   {
-   "cell_type": "markdown",
+   "cell_type": "code",
+   "execution_count": 19,
    "id": "29",
    "metadata": {},
+   "outputs": [],
    "source": [
-    "## Technical Notes"
+    "for i in range(len(timesteps)):\n",
+    "    df = results_simulator[i].dataframe\n",
+    "    assert float(df.loc[df[\"p\"] == -2, \"probability\"].iloc[0]) > 0.9"
    ]
   },
   {
    "cell_type": "markdown",
    "id": "30",
    "metadata": {},
+   "source": [
+    "## Technical Notes"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "31",
+   "metadata": {},
    "source": [
     "Below we derive the time-evolution of the quantum sawtooth map. We start with the classical map and go through several renormalizations and redefinitions.\n",
     "The classical system is written for the so-called action-angle variables $(p,q)$\n",
@@ -559,7 +571,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "31",
+   "id": "32",
    "metadata": {},
    "source": [
     "## References\n",

tests/notebooks/test_quantum_sawtooth_map.py

@@ -1,22 +1,22 @@
 from tests.utils_for_testbook import (
     validate_quantum_program_size,
-    validate_quantum_model,
     wrap_testbook,
 )
 from testbook.client import TestbookNotebookClient
 
 
 @wrap_testbook("quantum_sawtooth_map", timeout_seconds=60)
 def test_notebook(tb: TestbookNotebookClient) -> None:
-    # test models
-    validate_quantum_model(tb.ref("qmod"))
     # test quantum programs
     validate_quantum_program_size(
         tb.ref_pydantic("qprog"),
-        expected_width=None,
-        expected_depth=None,
-        expected_cx_count=None,
+        expected_width=5,  # actual 3
+        expected_depth=100,  # actual 49
     )
 
     # test notebook content
-    pass  # Todo
+    timesteps = tb.ref("timesteps")
+    res_simulator = tb.ref_pydantic("results_simulator")
+    for i in range(len(timesteps)):
+        df = res_simulator[i].dataframe
+        assert float(df.loc[df["p"] == -2, "probability"].iloc[0]) > 0.9