From 4c339eb78b5e80fb0b4369508bc04851b348df04 Mon Sep 17 00:00:00 2001
From: Mirko Birbaumer <mirko.birbaumer@hslu.ch>
Date: Mon, 14 Oct 2024 06:59:40 +0000
Subject: [PATCH] adapted smc monte carlo

---
 notebooks/Model Comparison/MC_2_1.ipynb | 37 ++++++++++---------------
 1 file changed, 15 insertions(+), 22 deletions(-)

diff --git a/notebooks/Model Comparison/MC_2_1.ipynb b/notebooks/Model Comparison/MC_2_1.ipynb
index a774090..d66ef90 100644
--- a/notebooks/Model Comparison/MC_2_1.ipynb	
+++ b/notebooks/Model Comparison/MC_2_1.ipynb	
@@ -2,7 +2,9 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "source": [
     "# Bayes-Faktor für Münzwurf"
    ]
@@ -20,20 +22,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 13,
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Matplotlib is building the font cache; this may take a moment.\n",
-      "WARNING (pytensor.tensor.blas): Using NumPy C-API based implementation for BLAS functions.\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "%matplotlib inline\n",
     "import pymc as pm\n",
@@ -49,7 +42,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 14,
    "metadata": {
     "tags": []
    },
@@ -126,7 +119,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 12,
    "metadata": {
     "tags": []
    },
@@ -135,13 +128,13 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "<xarray.DataArray 'log_marginal_likelihood' ()> Size: 8B\n",
-      "array(11.16)\n"
+      "11.16\n"
      ]
     }
    ],
    "source": [
-    "print(np.round(np.exp(trace_smc_0.sample_stats[\"log_marginal_likelihood\"].mean() - trace_smc_1.sample_stats[\"log_marginal_likelihood\"].mean()),2))"
+    "BF_smc = np.exp(trace_smc_0.sample_stats[\"log_marginal_likelihood\"].mean() - trace_smc_1.sample_stats[\"log_marginal_likelihood\"].mean())\n",
+    "print(np.round(BF_smc.item(),2))"
    ]
   },
   {
@@ -158,7 +151,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 15,
    "metadata": {
     "tags": []
    },
@@ -229,7 +222,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 16,
    "metadata": {
     "tags": []
    },
@@ -238,13 +231,13 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "<xarray.DataArray 'log_marginal_likelihood' ()> Size: 8B\n",
-      "array(0.68)\n"
+      "11.21\n"
      ]
     }
    ],
    "source": [
-    "print(np.round(np.exp(trace_BF_0.sample_stats[\"log_marginal_likelihood\"].mean() - trace_BF_1.sample_stats[\"log_marginal_likelihood\"].mean()),2))"
+    "BF_smc = np.exp(trace_smc_0.sample_stats[\"log_marginal_likelihood\"].mean() - trace_smc_1.sample_stats[\"log_marginal_likelihood\"].mean())\n",
+    "print(np.round(BF_smc.item(),2))"
    ]
   }
  ],
-- 
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