Update notebooks

gyorilab · Dec 6, 2024 · 0a4bc75 · 0a4bc75
1 parent 5915c7a
commit 0a4bc75
Show file tree

Hide file tree

Showing 3 changed files with 309 additions and 171 deletions.
diff --git a/notebooks/hackathon_2024.12/ModelA.ipynb b/notebooks/hackathon_2024.12/ModelA.ipynb
@@ -84,7 +84,6 @@
     "    'rho': {'value': 0.8},\n",
     "    'nu': {'value': 0.045},\n",
     "    'beta_hh': {'value': 0.03},\n",
-    "    #'beta_rh': {'value': 0.3045},\n",
     "    'beta_rh': {'value': 0.03045},\n",
     "    'beta_rr': {'value': 0.025},\n",
     "    'alpha': {'value': 0.75},\n",
@@ -123,14 +122,6 @@
     "case_expr = sp.parse_expr('P + I1 + I2 + H')\n"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "4b6fe932",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
   {
    "cell_type": "code",
    "execution_count": 2,

diff --git a/notebooks/hackathon_2024.12/ModelB.ipynb b/notebooks/hackathon_2024.12/ModelB.ipynb
@@ -45,6 +45,45 @@
     "N_h = S_h(t) + E_h(t) + I_h(t) + Q(t) + R(t)\n",
     "N_r = S_r(t) + E_r(t) + I_r(t)\n",
     "\n",
+    "\n",
+    "human_infection_rate = ((beta_1 * I_r(t) + beta_2 * I_h(t)) * S_h(t)) / N_h\n",
+    "rodent_infection_rate = (beta_3 * S_r(t) * I_r(t)) / N_r\n",
+    "\n",
+    "odes = [\n",
+    "    sp.Eq(\n",
+    "        S_h(t).diff(t),\n",
+    "        theta_h - human_infection_rate - mu_h * S_h(t) + phi * Q(t),\n",
+    "    ),\n",
+    "    sp.Eq(\n",
+    "        E_h(t).diff(t),\n",
+    "        human_infection_rate - (alpha_1 + alpha_2 + mu_h) * E_h(t),\n",
+    "    ),\n",
+    "    sp.Eq(\n",
+    "        I_h(t).diff(t),\n",
+    "        alpha_1 * E_h(t) - (mu_h + delta_h + gamma) * I_h(t),\n",
+    "    ),\n",
+    "    sp.Eq(\n",
+    "        Q(t).diff(t),\n",
+    "        alpha_2 * E_h(t) - (phi + tau + delta_h + mu_h) * Q(t),\n",
+    "    ),\n",
+    "    sp.Eq(\n",
+    "        R(t).diff(t),\n",
+    "        gamma * I_h(t) + tau * Q(t) - mu_h * R(t),\n",
+    "    ),\n",
+    "    sp.Eq(\n",
+    "        S_r(t).diff(t),\n",
+    "        theta_r - rodent_infection_rate - mu_r * S_r(t),\n",
+    "    ),\n",
+    "    sp.Eq(\n",
+    "        E_r(t).diff(t),\n",
+    "        rodent_infection_rate - (mu_r + alpha_3) * E_r(t),\n",
+    "    ),\n",
+    "    sp.Eq(\n",
+    "        I_r(t).diff(t),\n",
+    "        alpha_3 * E_r(t) - (mu_r + delta_r) * I_r(t),\n",
+    "    ),\n",
+    "]\n",
+    "\n",
     "concept_data = {\n",
     "    \"S_h\": {\n",
     "        \"identifiers\": {\"ido\": \"0000514\"},\n",
@@ -85,43 +124,6 @@
     "        \"context\": {\"species\": \"ncbitaxon:9989\"},\n",
     "    },\n",
     "}\n",
-    "human_infection_rate = ((beta_1 * I_r(t) + beta_2 * I_h(t)) * S_h(t)) / N_h\n",
-    "rodent_infection_rate = (beta_3 * S_r(t) * I_r(t)) / N_r\n",
-    "\n",
-    "odes = [\n",
-    "    sp.Eq(\n",
-    "        S_h(t).diff(t),\n",
-    "        theta_h - human_infection_rate - mu_h * S_h(t) + phi * Q(t),\n",
-    "    ),\n",
-    "    sp.Eq(\n",
-    "        E_h(t).diff(t),\n",
-    "        human_infection_rate - (alpha_1 + alpha_2 + mu_h) * E_h(t),\n",
-    "    ),\n",
-    "    sp.Eq(\n",
-    "        I_h(t).diff(t),\n",
-    "        alpha_1 * E_h(t) - (mu_h + delta_h + gamma) * I_h(t),\n",
-    "    ),\n",
-    "    sp.Eq(\n",
-    "        Q(t).diff(t),\n",
-    "        alpha_2 * E_h(t) - (phi + tau + delta_h + mu_h) * Q(t),\n",
-    "    ),\n",
-    "    sp.Eq(\n",
-    "        R(t).diff(t),\n",
-    "        gamma * I_h(t) + tau * Q(t) - mu_h * R(t),\n",
-    "    ),\n",
-    "    sp.Eq(\n",
-    "        S_r(t).diff(t),\n",
-    "        theta_r - rodent_infection_rate - mu_r * S_r(t),\n",
-    "    ),\n",
-    "    sp.Eq(\n",
-    "        E_r(t).diff(t),\n",
-    "        rodent_infection_rate - (mu_r + alpha_3) * E_r(t),\n",
-    "    ),\n",
-    "    sp.Eq(\n",
-    "        I_r(t).diff(t),\n",
-    "        alpha_3 * E_r(t) - (mu_r + delta_r) * I_r(t),\n",
-    "    ),\n",
-    "]\n",
     "\n",
     "\n",
     "parameter_data = {\n",
@@ -179,41 +181,6 @@
     "}\n"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "id": "bc4495c3",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "{'theta_h': {'value': 1740000.0},\n",
-       " 'theta_r': {'value': 120000.0},\n",
-       " 'beta_1': {'value': 0.00025},\n",
-       " 'beta_2': {'value': 6e-05},\n",
-       " 'beta_3': {'value': 0.027},\n",
-       " 'alpha_1': {'value': 0.2},\n",
-       " 'alpha_2': {'value': 2.0},\n",
-       " 'alpha_3': {'value': 0.2},\n",
-       " 'phi': {'value': 2.0},\n",
-       " 'tau': {'value': 0.52},\n",
-       " 'gamma': {'value': 0.83},\n",
-       " 'mu_r': {'value': 1.5},\n",
-       " 'mu_h': {'value': 0.02},\n",
-       " 'delta_h': {'value': 0.2},\n",
-       " 'delta_r': {'value': 0.5}}"
-      ]
-     },
-     "execution_count": 3,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "parameter_data"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 4,