diff --git a/markov.ipynb b/markov.ipynb
index cb27148..d760b8d 100644
--- a/markov.ipynb
+++ b/markov.ipynb
@@ -54,8 +54,8 @@
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\n"
      },
      "metadata": {
       "needs_background": "light"
@@ -74,6 +74,7 @@
     "plt.legend()\n",
     "plt.title(\"State Probability Density Functions\")\n",
     "\n",
+    "plt.xlabel(\"Observation\")\n",
     "plt.ylabel(\"Probability Density\")\n",
     "plt.grid(linestyle=\"--\")\n",
     "\n",
@@ -115,8 +116,8 @@
      "output_type": "display_data",
      "data": {
       "text/plain": "<Figure size 432x288 with 1 Axes>",
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\n"
      },
      "metadata": {
       "needs_background": "light"
@@ -135,6 +136,7 @@
     "plt.legend()\n",
     "plt.title(\"State Probability Density Functions\")\n",
     "\n",
+    "plt.xlabel(\"Observation\")\n",
     "plt.ylabel(\"Probability Density\")\n",
     "plt.grid(linestyle=\"--\")\n",
     "\n",
@@ -179,7 +181,7 @@
      "output_type": "execute_result",
      "data": {
       "text/plain": [
-       "1.9197737567283167e-10"
+       "0.0"
       ]
      },
      "metadata": {},
@@ -193,7 +195,7 @@
     "print(model.forward[:, -1])\n",
     "\n",
     "# model.forward\n",
-    "model.p_observations_forward\n"
+    "model.calculate_p_obs_backward()\n"
    ]
   },
   {
@@ -212,14 +214,14 @@
      "output_type": "stream",
      "name": "stdout",
      "text": [
-      "7 5.0\n6 1.9\n5 1.6\n4 3.0\n3 1.9\n2 -0.4\n1 3.4\n0 4.2\n"
+      "[[4.51463205e-11 2.00832344e-09 4.73407226e-08 3.05688962e-07\n  1.32372112e-06 1.72295786e-05 6.38239858e-05 2.70158900e-04\n  2.00000000e-02]\n [6.42838621e-10 1.26112896e-09 3.08743846e-09 2.17626845e-08\n  3.11069468e-07 1.17967571e-06 3.78233027e-05 5.73291424e-03\n  3.00000000e-02]]\n"
      ]
     },
     {
      "output_type": "execute_result",
      "data": {
       "text/plain": [
-       "2.0542341126222686e-10"
+       "1.973930126315074e-10"
       ]
      },
      "metadata": {},
@@ -230,8 +232,8 @@
     "model = MarkovModel(states=[state1, state2], observations=observations, state_transitions=state_transition)\n",
     "model.populate_backward()\n",
     "\n",
-    "# model.backward\n",
-    "model.p_observations_backward\n"
+    "print(model.backward)\n",
+    "model.calculate_p_obs_backward()\n"
    ]
   },
   {
@@ -250,7 +252,7 @@
      "output_type": "stream",
      "name": "stdout",
      "text": [
-      "7 5.0\n6 1.9\n5 1.6\n4 3.0\n3 1.9\n2 -0.4\n1 3.4\n0 4.2\nforward: 1.9197737567283167e-10\nbackward: 2.0542341126222686e-10\n"
+      "forward: 1.9197737567283167e-10\nbackward: 1.973930126315074e-10\n"
      ]
     }
    ],
@@ -259,9 +261,48 @@
     "model.populate_forward()\n",
     "model.populate_backward()\n",
     "\n",
-    "print(\"forward:\", model.p_observations_forward)\n",
-    "print(\"backward:\", model.p_observations_backward)\n"
+    "print(\"forward:\", model.calculate_p_obs_forward())\n",
+    "print(\"backward:\", model.calculate_p_obs_backward())\n"
    ]
+  },
+  {
+   "source": [
+    "# Occupation Likelihoods (5)"
+   ],
+   "cell_type": "markdown",
+   "metadata": {}
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "output_type": "stream",
+     "name": "stdout",
+     "text": [
+      "[[2.26103724e-03 2.09632799e-03 7.13729340e-02 6.86226851e-01\n  6.86050012e-01 6.81074885e-01 6.85886077e-01 6.70320364e-01\n  5.86805704e-02]\n [1.02594873e+00 1.02619579e+00 9.22280884e-01 9.07573738e-09\n  2.65267897e-04 7.72795708e-03 5.11169721e-04 2.38597389e-02\n  9.41319430e-01]]\n"
+     ]
+    }
+   ],
+   "source": [
+    "model = MarkovModel(states=[state1, state2], observations=observations, state_transitions=state_transition)\n",
+    "model.populate_forward()\n",
+    "model.populate_backward()\n",
+    "\n",
+    "model.calculate_p_obs_forward()\n",
+    "\n",
+    "model.populate_occupation()\n",
+    "\n",
+    "print(model.occupation)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ]
 }
\ No newline at end of file
diff --git a/markov.py b/markov.py
index 0ed6b16..82dedc9 100644
--- a/markov.py
+++ b/markov.py
@@ -1,22 +1,10 @@
 from dataclasses import dataclass, field
 from typing import List
 import numpy as np
+from numpy import log as ln
 
 from maths import gaussian
 
-@dataclass
-class Likelihood:
-    forward: float  # forward likelihood
-    backward: float  # backward likelihood
-
-@dataclass
-class TimeStep:
-    states: List[Likelihood] = field(default_factory=list)
-
-@dataclass
-class Transition:
-    pass
-
 class MarkovModel:
 
     def __init__(self, states: list, observations: list = list(), state_transitions: list = list()):
@@ -27,7 +15,12 @@ class MarkovModel:
         # self.timesteps = list()
 
         self.forward = np.zeros((len(states), len(observations)))
+        self.p_obs_forward = 0
+
         self.backward = np.zeros((len(states), len(observations)))
+        self.p_obs_backward = 0
+
+        self.occupation = np.zeros((len(states), len(observations)))
 
     def get_other_state_index(self, state_in):
         """For when state changes, get other index for retrieving state transitions (FOR 0 INDEXING)"""
@@ -41,6 +34,13 @@ class MarkovModel:
     def get_other_state_number(self, state_in):
         """For when state changes, get other number for retrieving state transitions (FOR 1 INDEXING)"""
         return self.get_other_state_index(state_in - 1) + 1
+
+    def populate(self):
+        self.populate_forward()
+        self.calculate_p_obs_forward()
+        self.populate_backward()
+        self.calculate_p_obs_backward()
+        self.populate_occupation()
     
     def populate_forward(self):
         for t, observation in enumerate(self.observations): # iterate through observations (time)
@@ -48,56 +48,112 @@ class MarkovModel:
 
                 state_number = state_index + 1 # for easier reading (arrays 0-indexed, numbers start at 1)
 
-                if t == 0: # calcualte initial
+                if t == 0: # calcualte initial, 0 = first row = initial
                     self.forward[state_index, t] = self.state_transitions[0, state_number] * gaussian(observation, state.mean, state.std_dev)
                 else:
-                    # each state for each time has two paths leading to
+                    # each state for each time has two paths leading to it, the same state (this) and the other state (other)
 
                     other_index = self.get_other_state_index(state_index)
                     other_number = other_index + 1 # for 1 indexing
                     
-                    #                      previous value             prob of changing from previous state to current
+                    # previous value * prob of changing from previous state to current
                     this_to_this = self.forward[state_index, t - 1] * self.state_transitions[state_number, state_number]
                     other_to_this = self.forward[other_index, t - 1] * self.state_transitions[other_number, state_number]
 
                     self.forward[state_index, t] = (this_to_this + other_to_this) * gaussian(observation, state.mean, state.std_dev)
 
     @property
-    def p_observations_forward(self):
+    def observation_likelihood(self):
+        """abstraction for getting p(obs|model) for future calculations (occupation/transition)"""
+        return self.p_obs_forward
+
+    def calculate_p_obs_forward(self):
 
         sum = 0
         for state_index, final_likelihood in enumerate(self.forward[:, -1]):            
             sum += final_likelihood * self.state_transitions[state_index + 1, -1] # get exit prob from state transitions
 
+        self.p_obs_forward = sum
         return sum
 
-    #TODO finish
     def populate_backward(self):
 
         # initialise from exit probabilities
         self.backward[:, -1] = self.state_transitions[1:len(self.states) + 1, -1]
 
         for t, observation in list(enumerate(self.observations[1:]))[::-1]: # iterate backwards through observations (time)
-            print(t, observation)
+            # print(t, observation)
             for state_index, state in enumerate(self.states):
 
                 state_number = state_index + 1 # for easier reading (arrays 0-indexed, numbers start at 1)
 
                 other_index = self.get_other_state_index(state_index)
                 other_number = other_index + 1 # for 1 indexing
+
+                # observation for transitions from the same state
+                this_state_gaussian = gaussian(observation, self.states[state_index].mean, self.states[state_index].std_dev)
+                # observation for transitions from the other state
+                other_state_gaussian = gaussian(observation, self.states[other_index].mean, self.states[other_index].std_dev)
                 
-                #                      previous value             prob of changing from previous state to current
-                this_to_this = self.backward[state_index, t + 1] * self.state_transitions[state_number, state_number]
-                other_to_this = self.backward[other_index, t + 1] * self.state_transitions[other_number, state_number]
+                # beta * a * b
+                this_from_this = self.backward[state_index, t + 1] * self.state_transitions[state_number, state_number] * this_state_gaussian
+                other_from_this = self.backward[other_index, t + 1] * self.state_transitions[other_number, state_number] * other_state_gaussian
 
-                self.backward[state_index, t] = (this_to_this + other_to_this) * gaussian(observation, state.mean, state.std_dev)
+                self.backward[state_index, t] = (this_from_this + other_from_this)
 
-    #TODO finish
-    @property
-    def p_observations_backward(self):
+    def calculate_p_obs_backward(self):
 
         sum = 0
-        for state_index, initial_likelihood in enumerate(self.backward[:, 0]):            
+        for state_index, initial_likelihood in enumerate(self.backward[:, 0]):
+            # pi * b * beta
             sum += self.state_transitions[0, state_index + 1] * gaussian(self.observations[0], self.states[state_index].mean, self.states[state_index].std_dev) * initial_likelihood
 
+        self.p_obs_backward = sum
         return sum
+
+    def populate_occupation(self):
+        for t, observation in enumerate(self.observations): # iterate through observations (time)
+            for state_index, state in enumerate(self.states):
+                
+                forward_backward = self.forward[state_index, t] * self.backward[state_index, t]
+                self.occupation[state_index, t] = forward_backward / self.observation_likelihood
+
+    def transition_likelihood(self, from_index, to_index, t):
+        if t == 0:
+            print("no transition likelihood for t == 0")
+
+        forward = self.forward[from_index, t - 1]
+        transition = self.state_transitions[from_index + 1, to_index + 1]
+        emission = gaussian(self.observations[t], self.states[to_index].mean, self.states[to_index].std_dev)
+        backward = self.backward[to_index, t]
+
+        return (forward * transition * emission * backward) / self.observation_likelihood
+
+    def baum_welch_state_transitions(self):
+
+        new_transitions = np.zeros((len(self.states), len(self.states)))
+
+        # i
+        for from_index, from_state in enumerate(self.states):
+            # j
+            for to_index, to_state in enumerate(self.states):
+                
+                transition_sum = 0
+                for t in range(1, len(self.observations)):
+                    transition_sum += self.transition_likelihood(from_index, to_index, t)
+
+                occupation_sum = 0
+                for t in range(0, len(self.observations)):
+                    occupation_sum = self.occupation[to_index, t]
+
+                new_transitions[from_index, to_index] = transition_sum / occupation_sum
+
+        return new_transitions
+
+
+
+# child object to replace normal prob/likeli operations with log prob operations (normal prob for debugging)
+class LogMarkovModel(MarkovModel):
+
+    def log_state_transitions(self):
+        self.state_transitions = ln(self.state_transitions)
diff --git a/report/report.lyx b/report/report.lyx
index ef3e4d6..a4c56b4 100644
--- a/report/report.lyx
+++ b/report/report.lyx
@@ -323,6 +323,17 @@ lstparams "language=Python,breaklines=true,frame=tb,otherkeywords={self},emph={S
 \end_inset
 
 
+\end_layout
+
+\begin_layout Standard
+\begin_inset CommandInset include
+LatexCommand lstinputlisting
+filename "../maths.py"
+lstparams "language=Python,breaklines=true,frame=tb,otherkeywords={self},emph={State},emphstyle={\\ttb\\color{darkred}},basicstyle={\\ttfamily},commentstyle={\\color{commentgreen}\\itshape},keywordstyle={\\color{darkblue}},emphstyle={\\color{red}},stringstyle={\\color{red}},caption={Maths utility file with definitions for a gaussian},label={maths-listing}"
+
+\end_inset
+
+
 \end_layout
 
 \begin_layout Standard
diff --git a/scratchpad.ipynb b/scratchpad.ipynb
index 5a3b378..755f35e 100644
--- a/scratchpad.ipynb
+++ b/scratchpad.ipynb
@@ -11,7 +11,7 @@
     "\n",
     "from constants import *\n",
     "from maths import gaussian\n",
-    "from markov import MarkovModel"
+    "from markov import MarkovModel, LogMarkovModel"
    ]
   },
   {
@@ -72,7 +72,7 @@
      "output_type": "display_data",
      "data": {
       "text/plain": "<Figure size 432x288 with 1 Axes>",
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\n"
      },
      "metadata": {
       "needs_background": "light"
@@ -231,7 +231,7 @@
     "fig = plt.figure(figsize=(18,6))\n",
     "ax = fig.add_subplot(1, 1, 1, projection=\"3d\")\n",
     "\n",
-    "y_width = 0.25\n",
+    "y_width = 0.6\n",
     "\n",
     "X = np.arange(1, 10)\n",
     "Y = np.arange(1, 3) - 0.5*y_width\n",
@@ -248,10 +248,78 @@
     "\n",
     "ax.set_xlabel(\"Observation\")\n",
     "ax.set_ylabel(\"State\")\n",
+    "ax.view_init(30, -80)\n",
     "# plt.zlabel(\"Forward Likelihood\")\n",
     "fig.show()"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "output_type": "execute_result",
+     "data": {
+      "text/plain": [
+       "-0.6931471805599453"
+      ]
+     },
+     "metadata": {},
+     "execution_count": 11
+    }
+   ],
+   "source": [
+    "from numpy import log as ln\n",
+    "\n",
+    "ln(0.5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "output_type": "stream",
+     "name": "stdout",
+     "text": [
+      "[[0.   0.44 0.56 0.  ]\n [0.   0.92 0.06 0.02]\n [0.   0.04 0.93 0.03]\n [0.   0.   0.   0.  ]]\n[[       -inf -0.82098055 -0.5798185         -inf]\n [       -inf -0.08338161 -2.81341072 -3.91202301]\n [       -inf -3.21887582 -0.07257069 -3.5065579 ]\n [       -inf        -inf        -inf        -inf]]\n"
+     ]
+    }
+   ],
+   "source": [
+    "model = LogMarkovModel(states=[state1, state2], observations=observations, state_transitions=state_transition)\n",
+    "\n",
+    "print(model.state_transitions)\n",
+    "model.log_state_transitions()\n",
+    "print(model.state_transitions)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "output_type": "execute_result",
+     "data": {
+      "text/plain": [
+       "array([[48.59040575,  1.01024542],\n",
+       "       [11.76531328,  2.09407832]])"
+      ]
+     },
+     "metadata": {},
+     "execution_count": 13
+    }
+   ],
+   "source": [
+    "model = MarkovModel(states=[state1, state2], observations=observations, state_transitions=state_transition)\n",
+    "model.populate()\n",
+    "\n",
+    "model.baum_welch_state_transitions()"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,