[WIP] Demos

examples/2024_yr4_impact_risk.ipynb

@@ -32,7 +32,7 @@
     "\n",
     "orbit = query_sbdb([\"2024 YR4\"])\n",
     "\n",
-    "print(orbit.to_dataframe())"
+    "orbit.to_dataframe()"
    ]
   },
   {
@@ -48,7 +48,52 @@
     "approx_impact_date = Timestamp.from_iso8601([\"2032-12-22\"], scale=\"tdb\")\n",
     "thirty_days_after_impact = approx_impact_date.add_days(30)\n",
     "days_until_thirty_days_after_impact, _ = thirty_days_after_impact.difference(orbit.coordinates.time)\n",
-    "print(days_until_thirty_days_after_impact)"
+    "days_until_thirty_days_after_impact"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Let's propagate the nominal orbit to about 30 days before the impact time and do a quick minimum orbit intersection distance (MOID) calculation. The propagation we do before hand is important because the MOID calculation uses 2-body dynamics (a simple Keplerian orbit) and that approximation does not hold for long periods of time."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from adam_assist import ASSISTPropagator\n",
+    "\n",
+    "propagator = ASSISTPropagator()\n",
+    "propagated_orbit = propagator.propagate_orbits(orbit, approx_impact_date.add_days(-30), covariance=True)\n",
+    "propagated_orbit.to_dataframe()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from adam_core.dynamics.moid import calculate_perturber_moids\n",
+    "from adam_core.coordinates import OriginCodes\n",
+    "\n",
+    "moids = calculate_perturber_moids(propagated_orbit, OriginCodes.EARTH)\n",
+    "moids.to_dataframe()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from adam_core.constants import KM_P_AU\n",
+    "\n",
+    "# Compute moid in KM\n",
+    "moids.select(\"perturber.code\", \"EARTH\").moid[0].as_py() * KM_P_AU"
    ]
   },
   {
@@ -60,9 +105,7 @@
     "# Now we initialize our propagator, and pass it to our calculate_impacts function\n",
     "from adam_core.dynamics.impacts import calculate_impacts, CollisionConditions\n",
     "from adam_core.coordinates import Origin\n",
-    "from adam_assist import ASSISTPropagator\n",
     "\n",
-    "propagator = ASSISTPropagator()\n",
     "\n",
     "# Define the collision conditions including a potential impact on the Moon\n",
     "conditions = CollisionConditions.from_kwargs(\n",
@@ -77,11 +120,52 @@
     "    days_until_thirty_days_after_impact[0].as_py(),\n",
     "    propagator,\n",
     "    num_samples=10000,\n",
-    "    processes=60, # Multiprocessing speeds things up if you have the CPUs\n",
+    "    processes=10, # Multiprocessing speeds things up if you have the CPUs\n",
     "    conditions=conditions,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "variants.to_dataframe()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "impacts.to_dataframe()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Alternatively, if we don't know the impact date (which is the case in reality at discovery)\n",
+    "from adam_core.orbits import VariantOrbits\n",
+    "\n",
+    "variants_orbits = VariantOrbits.create(\n",
+    "    orbit,\n",
+    "    method=\"monte-carlo\",\n",
+    "    num_samples=10000,\n",
+    "    seed=612,\n",
     ")\n",
     "\n",
-    "print(variants, impacts)"
+    "variants, impacts = propagator.detect_collisions(\n",
+    "    variants_orbits,\n",
+    "    8 * 365, # Propagate for 8 years\n",
+    "    conditions=conditions,\n",
+    "    max_processes=10,\n",
+    ")\n",
+    "impacts.to_dataframe()"
    ]
   },
   {
@@ -91,7 +175,7 @@
    "outputs": [],
    "source": [
     "# Now we can summarize the returns, a simple ratio in our case\n",
-    "# with only 1 orbit considered\n",
+    "# with only 1 orbit considered/\n",
     "from adam_core.dynamics.impacts import calculate_impact_probabilities\n",
     "ip = calculate_impact_probabilities(variants, impacts, conditions=conditions)\n",
     "ip.to_dataframe()"
@@ -118,7 +202,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -148,11 +232,11 @@
     "    propagated_best_fit_orbit, \n",
     "    propagated_variants, \n",
     "    impacts, \n",
-    "    title=\"2024 YR4 Impact Simulation (Simulated on 2025-03-14)\",\n",
+    "    title=\"2024 YR4 Impact Simulation (Simulated on 2025-04-03)\",\n",
     "    sample_impactors=None,\n",
     "    sample_non_impactors=0.1\n",
     ")\n",
-    "fig.write_html(\"2024YR4_impact_simulation.html\")"
+    "fig.write_html(\"2024YR4_impact_simulation_20250403.html\")"
    ]
   },
   {
@@ -162,6 +246,15 @@
     "And there you have it. "
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fig"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -184,7 +277,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.3"
+   "version": "3.11.5"
   }
  },
  "nbformat": 4,