adds pe2

src/probability_emote.py

@@ -26,6 +26,30 @@ def get_pe(w, ec=0.86, f=0.50):
     # print(f'f = {result}')
     return result
 
+@st.cache
+def get_pe2(w, ec=0.86, f=0.50):
+    result = 1-np.exp(-w*ec/(f+0.0001))
+    result = result
+    # result = np.clip(result, 0, 1)
+    # print(f'f = {result}')
+    return result
+
+@st.cache(suppress_st_warning=True)
+def get_pe3(w, ec=0.86, f=0.50):
+    result_np = np.zeros((len(f), len(f)))
+    st.markdown(result_np)
+    st.markdown(result_np[0])
+    for i, fi in enumerate(f):
+        result = 1-np.exp(-ec/f)
+        result = w*result
+        if i ==0:
+            result_np[i]=w*result
+        else:
+            result_np[i]=w*result + (1-w)*result_np[i-1]
+    # result = np.clip(result, 0, 1)
+    # print(f'f = {result}')
+    return result
+
 
 xdata1 = np.arange(0, 1.1, step=0.01)
 # rand = np.random.random_sample()
@@ -56,41 +80,54 @@ def get_text():
 
 
 @st.cache
-def get_equation_text(w=0.5, ec=0.7, rand=None, emotion_frequency=None):
-    text = f''' 
-    #### Equation
-    ```
-    frequency_penalty = 1 - emotion_frequency 
-    probability_emote = w * emotion_confidence + (1 - w) * frequency_penalty
-    ```
-    **probability_emote** = {proper_float(w)} * {proper_float(ec)} + {proper_float(1-w)} * frequency_penalty
-
-    '''
-    if rand is not None:
-        frequency_penalty = proper_float(1-emotion_frequency)
-        probability_emote = proper_float((w)*(ec)+(1-w)*frequency_penalty)
+def get_equation_text(w=0.5, ec=0.7, rand=None, emotion_frequency=None, graph_eq='PE1'):
+    if graph_eq=='PE1':
         text = f''' 
-    #### Equation
-    ```
-    frequency_penalty = 1 - emotion_frequency = 1 - {proper_float(emotion_frequency)}  = {frequency_penalty} 
-    probability_emote = w * emotion_confidence + (1 - w) * frequency_penalty
-    probability_emote = {proper_float(w)} * {proper_float(ec)} + {proper_float(1-w)} * {frequency_penalty}
-    ```
-    **probability_emote** = {probability_emote}
-    ```
-    Show_Emotion 
-      = probability_emote > (Random value between 0 and 1)
-    Random value = {rand}
-    Show_Emotion = {probability_emote} > {rand}
-    ```
-    **Show_Emotion** = {probability_emote > rand}
-    '''
+        #### Equation
+        ```
+        frequency_penalty = 1 - emotion_frequency 
+        probability_emote = w * emotion_confidence + (1 - w) * frequency_penalty
+        ```
+        **probability_emote** = {proper_float(w)} * {proper_float(ec)} + {proper_float(1-w)} * frequency_penalty
+
+        '''
+        if rand is not None:
+            frequency_penalty = proper_float(1-emotion_frequency)
+            probability_emote = proper_float((w)*(ec)+(1-w)*frequency_penalty)
+            text = f''' 
+        #### Equation
+        ```
+        frequency_penalty = 1 - emotion_frequency = 1 - {proper_float(emotion_frequency)}  = {frequency_penalty} 
+        probability_emote = w * emotion_confidence + (1 - w) * frequency_penalty
+        probability_emote = {proper_float(w)} * {proper_float(ec)} + {proper_float(1-w)} * {frequency_penalty}
+        ```
+        **probability_emote** = {probability_emote}
+        ```
+        Show_Emotion 
+        = probability_emote > (Random value between 0 and 1)
+        Random value = {rand}
+        Show_Emotion = {probability_emote} > {rand}
+        ```
+        **Show_Emotion** = {probability_emote > rand}
+        '''
+    elif graph_eq=='PE2' or graph_eq=='PE3':
+        # probability_emote = 1 - e ^ (frequency / emotion_confidence)
+        text = f''' 
+        #### Equation
+        ```
+        probability_emote = 1 - e ^ (- w * emotion_confidence / frequency)
+        ```
+        **probability_emote** = 1 - e ^ (- {proper_float(w)} * {proper_float(ec)} / frequency)
+
+        '''
+        
     return text
 
 
 
 
 def run_probability_emote(container_param):
+    graph_eq = container_param.selectbox('Select Equation', ['PE1', 'PE2', 'PE3'])
     w = set_input(container_param,
                             label='Weight w', key_slider='w_slider', key_input='w_input',
                             min_value=0.,
@@ -127,7 +164,7 @@ def run_probability_emote(container_param):
         emotion_frequency = 'emotion_frequency'
         rand = None
     st.markdown(get_equation_text(w=w, ec=score, rand=rand,
-                emotion_frequency=emotion_frequency))
+                emotion_frequency=emotion_frequency, graph_eq=graph_eq))
     fig = go.Figure()
     # fig.add_trace(go.Scatter(x=xdata1, y=np.ones_like(xdata1)*rand,
     #                       mode='markers', name='Random',
@@ -149,8 +186,12 @@ def run_probability_emote(container_param):
             mode='lines',
             line=dict(color='#ee00ee', width=8)
         ),)
+    
+    if graph_eq=='PE1': get_result = get_pe
+    elif graph_eq=='PE2': get_result = get_pe2
+    elif graph_eq=='PE3': get_result = get_pe3
     fig.add_trace(go.Scatter(
-        x=xdata1, y=get_pe(w=w, f=xdata1, ec=score),
+        x=xdata1, y=get_result(w=w, f=xdata1, ec=score),
         mode='lines',
         name='Probability-Emote',
         line=dict(color='#00eeee', width=4)