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Interactive_Bayesian_Updating.ipynb

@@ -102,12 +102,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [],
    "source": [
     "%matplotlib inline\n",
-    "supress_warnings = False\n",
+    "supress_warnings = True\n",
     "from ipywidgets import interactive                        # widgets and interactivity\n",
     "from ipywidgets import widgets                            # widgets and interactivity\n",
     "import matplotlib; import matplotlib.pyplot as plt        # plotting\n",
@@ -140,7 +140,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -177,7 +177,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 39,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -198,18 +198,18 @@
     "\n",
     "def run_plot_summary1(P_happening,P_positive_given_happening,P_positive_given_not_happening):\n",
     "    digits = 3\n",
-    "    P_not_positive_given_happening = np.round((1 - P_positive_given_happening),digits)\n",
-    "    P_not_positive_given_not_happening = np.round((1 - P_positive_given_not_happening),digits)\n",
-    "    P_not_happening = np.round((1.0 - P_happening),digits)\n",
+    "    P_not_positive_given_happening = (1 - P_positive_given_happening)\n",
+    "    P_not_positive_given_not_happening = (1 - P_positive_given_not_happening)\n",
+    "    P_not_happening = (1.0 - P_happening)\n",
     "    \n",
-    "    P_positive = np.round((P_positive_given_happening * P_happening + P_positive_given_not_happening * P_not_happening),digits)\n",
-    "    P_not_positive = np.round((P_not_positive_given_happening * P_happening + P_not_positive_given_not_happening * P_not_happening),digits)\n",
+    "    P_positive = (P_positive_given_happening * P_happening + P_positive_given_not_happening * P_not_happening)\n",
+    "    P_not_positive = (P_not_positive_given_happening * P_happening + P_not_positive_given_not_happening * P_not_happening)\n",
     "    \n",
-    "    P_happening_given_positive = np.round(((P_positive_given_happening * P_happening) / P_positive),digits)\n",
-    "    P_not_happening_given_positive = np.round((P_positive_given_not_happening * P_not_happening) / P_positive,digits)\n",
+    "    P_happening_given_positive = ((P_positive_given_happening * P_happening) / P_positive)\n",
+    "    P_not_happening_given_positive = ((P_positive_given_not_happening * P_not_happening) / P_positive)\n",
     "    \n",
-    "    P_happening_given_not_positive = np.round(((P_not_positive_given_happening * P_happening) / P_not_positive),digits)\n",
-    "    P_not_happening_given_not_positive = np.round(((P_not_positive_given_not_happening * P_not_happening) / P_not_positive),digits)\n",
+    "    P_happening_given_not_positive = ((P_not_positive_given_happening * P_happening) / P_not_positive)\n",
+    "    P_not_happening_given_not_positive = ((P_not_positive_given_not_happening * P_not_happening) / P_not_positive)\n",
     "        \n",
     "    plt.subplot(111)\n",
     "    plt.plot()\n",
@@ -283,13 +283,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 42,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "9f463f05380247aca636afc2264ae0a0",
+       "model_id": "081c8551585642b2b2ea6136696b799d",
        "version_major": 2,
        "version_minor": 0
       },
@@ -303,12 +303,12 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "70ad5e2b4fc24f499708c4b904c1dc3a",
+       "model_id": "1d10d27396dd478e8c684f41495c3fd9",
        "version_major": 2,
        "version_minor": 0
       },
       "text/plain": [
-       "Output()"
+       "Output(outputs=({'output_type': 'display_data', 'data': {'text/plain': '<Figure size 640x480 with 1 Axes>', 'i…"
       ]
      },
      "metadata": {},
@@ -343,7 +343,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 44,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -362,18 +362,18 @@
     "\n",
     "def run_plot_summary(P_happening,P_positive_given_happening,P_positive_given_not_happening):\n",
     "    digits = 3\n",
-    "    P_not_positive_given_happening = np.round((1 - P_positive_given_happening),digits)\n",
-    "    P_not_positive_given_not_happening = np.round((1 - P_positive_given_not_happening),digits)\n",
-    "    P_not_happening = np.round((1.0 - P_happening),digits)\n",
+    "    P_not_positive_given_happening = (1 - P_positive_given_happening)\n",
+    "    P_not_positive_given_not_happening = (1 - P_positive_given_not_happening)\n",
+    "    P_not_happening = (1.0 - P_happening)\n",
     "    \n",
-    "    P_positive = np.round((P_positive_given_happening * P_happening + P_positive_given_not_happening * P_not_happening),digits)\n",
-    "    P_not_positive = np.round((P_not_positive_given_happening * P_happening + P_not_positive_given_not_happening * P_not_happening),digits)\n",
+    "    P_positive = (P_positive_given_happening * P_happening + P_positive_given_not_happening * P_not_happening)\n",
+    "    P_not_positive = (P_not_positive_given_happening * P_happening + P_not_positive_given_not_happening * P_not_happening)\n",
     "    \n",
-    "    P_happening_given_positive = np.round(((P_positive_given_happening * P_happening) / P_positive),digits)\n",
-    "    P_not_happening_given_positive = np.round((P_positive_given_not_happening * P_not_happening) / P_positive,digits)\n",
+    "    P_happening_given_positive = ((P_positive_given_happening * P_happening) / P_positive)\n",
+    "    P_not_happening_given_positive = (P_positive_given_not_happening * P_not_happening) / P_positive\n",
     "    \n",
-    "    P_happening_given_not_positive = np.round(((P_not_positive_given_happening * P_happening) / P_not_positive),digits)\n",
-    "    P_not_happening_given_not_positive = np.round(((P_not_positive_given_not_happening * P_not_happening) / P_not_positive),digits)\n",
+    "    P_happening_given_not_positive = ((P_not_positive_given_happening * P_happening) / P_not_positive)\n",
+    "    P_not_happening_given_not_positive = ((P_not_positive_given_not_happening * P_not_happening) / P_not_positive)\n",
     "        \n",
     "    plt.subplot(211)\n",
     "    plt.plot()\n",
@@ -531,13 +531,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 47,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "65fba05d2f634969b120b5c7d078538b",
+       "model_id": "d72830d524704fe69cf2ef205e0ad4c5",
        "version_major": 2,
        "version_minor": 0
       },
@@ -551,12 +551,12 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "6e48ff1254f1405b8ac2fbf7077f467f",
+       "model_id": "a1990c0264884670a49ffa4ecf045daa",
        "version_major": 2,
        "version_minor": 0
       },
       "text/plain": [
-       "Output()"
+       "Output(outputs=({'output_type': 'display_data', 'data': {'text/plain': '<Figure size 640x480 with 2 Axes>', 'i…"
       ]
      },
      "metadata": {},
@@ -604,10 +604,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
-   "metadata": {
-    "scrolled": false
-   },
+   "execution_count": 49,
+   "metadata": {},
    "outputs": [],
    "source": [
     "l = widgets.Text(value='                                                      Bayesian Updating Demo, Michael Pyrcz, Professor, The University of Texas at Austin',\n",
@@ -682,13 +680,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 52,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "9a31e99091f84068a54e39d26bccbfca",
+       "model_id": "b4f1ca08d731472986942298dc82a0a1",
        "version_major": 2,
        "version_minor": 0
       },
@@ -702,7 +700,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "858e1eda25dd4a0a8f70c9cdf3032709",
+       "model_id": "2f3199f4b3d243b5932dd4d9a3571ced",
        "version_major": 2,
        "version_minor": 0
       },
@@ -795,9 +793,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.4"
+   "version": "3.12.4"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }