Refactor seed frame initialization functions to accept 'sharp_split' parameter, enhancing flexibility in data handling. Update contest simulation logic to conditionally load seed frames based on selected slate and site, improving user experience and code maintainability.

app.py

@@ -55,7 +55,7 @@ dk_columns = ['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'TE', 'FLEX', 'DST', 'sal
 fd_columns = ['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'TE', 'FLEX', 'DST', 'salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own']
 
 @st.cache_data(ttl = 600)
-def init_DK_seed_frames():  
+def init_DK_seed_frames(sharp_split):  
     
     collection = db["DK_NFL_seed_frame"] 
     cursor = collection.find()
@@ -63,11 +63,12 @@ def init_DK_seed_frames():
     raw_display = pd.DataFrame(list(cursor))
     raw_display = raw_display[['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'TE', 'FLEX', 'DST', 'salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own']]
     DK_seed = raw_display.to_numpy()
+    fp_array = DK_seed[:sharp_split, :]
 
-    return DK_seed
+    return fp_array
 
 @st.cache_data(ttl = 600)
-def init_DK_Secondary_seed_frames():  
+def init_DK_Secondary_seed_frames(sharp_split):  
     
     collection = db["DK_NFL_Secondary_seed_frame"] 
     cursor = collection.find()
@@ -75,11 +76,12 @@ def init_DK_Secondary_seed_frames():
     raw_display = pd.DataFrame(list(cursor))
     raw_display = raw_display[['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'TE', 'FLEX', 'DST', 'salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own']]
     DK_seed = raw_display.to_numpy()
+    fp_array = DK_seed[:sharp_split, :]
 
-    return DK_seed
+    return fp_array
 
 @st.cache_data(ttl = 599)
-def init_FD_seed_frames():  
+def init_FD_seed_frames(sharp_split):  
     
     collection = db["FD_NFL_seed_frame"] 
     cursor = collection.find()
@@ -87,11 +89,12 @@ def init_FD_seed_frames():
     raw_display = pd.DataFrame(list(cursor))
     raw_display = raw_display[['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'TE', 'FLEX', 'DST', 'salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own']]
     FD_seed = raw_display.to_numpy()
+    fp_array = FD_seed[:sharp_split, :]
 
-    return FD_seed
+    return fp_array
 
 @st.cache_data(ttl = 599)
-def init_FD_Secondary_seed_frames():  
+def init_FD_Secondary_seed_frames(sharp_split):  
     
     collection = db["FD_NFL_Secondary_seed_frame"] 
     cursor = collection.find()
@@ -99,8 +102,10 @@ def init_FD_Secondary_seed_frames():
     raw_display = pd.DataFrame(list(cursor))
     raw_display = raw_display[['QB', 'RB1', 'RB2', 'WR1', 'WR2', 'WR3', 'TE', 'FLEX', 'DST', 'salary', 'proj', 'Team', 'Team_count', 'Secondary', 'Secondary_count', 'Own']]
     FD_seed = raw_display.to_numpy()
+    fp_array = FD_seed[:sharp_split, :]
 
-    return FD_seed
+
+    return fp_array
 
 @st.cache_data(ttl = 599)
 def init_baselines():
@@ -146,10 +151,9 @@ def calculate_FD_value_frequencies(np_array):
     return combined_array
 
 @st.cache_data
-def sim_contest(Sim_size, seed_frame, maps_dict, sharp_split, Contest_Size):
+def sim_contest(Sim_size, seed_frame, maps_dict, Contest_Size):
     SimVar = 1
     Sim_Winners = []
-    fp_array = seed_frame[:sharp_split, :]
     
     # Pre-vectorize functions
     vec_projection_map = np.vectorize(maps_dict['Projection_map'].__getitem__)
@@ -301,22 +305,6 @@ with tab1:
 
         sim_slate_var1 = st.radio("Which data are you loading?", ('Main Slate', 'Secondary Slate'), key='sim_slate_var1')
         sim_site_var1 = st.radio("What site are you working with?", ('Draftkings', 'Fanduel'), key='sim_site_var1')
-        if sim_site_var1 == 'Draftkings':
-            if sim_slate_var1 == 'Main Slate':
-                DK_seed = init_DK_seed_frames()
-            elif sim_slate_var1 == 'Secondary Slate':
-                DK_seed = init_DK_Secondary_seed_frames()
-                
-            raw_baselines = dk_raw
-            column_names = dk_columns
-        elif sim_site_var1 == 'Fanduel':
-            if sim_slate_var1 == 'Main Slate':
-                FD_seed = init_FD_seed_frames()
-            elif sim_slate_var1 == 'Secondary Slate':
-                FD_seed = init_FD_Secondary_seed_frames()
-                
-            raw_baselines = fd_raw
-            column_names = fd_columns
             
         contest_var1 = st.selectbox("What contest size are you simulating?", ('Small', 'Medium', 'Large', 'Custom'))
         if contest_var1 == 'Small':
@@ -343,6 +331,14 @@ with tab1:
     with col2:
         if st.button("Run Contest Sim"):
             if 'working_seed' in st.session_state:
+                if sim_site_var1 == 'Draftkings':
+                        
+                    raw_baselines = dk_raw
+                    column_names = dk_columns
+                elif sim_site_var1 == 'Fanduel':
+                    
+                    raw_baselines = fd_raw
+                    column_names = fd_columns
                 st.session_state.maps_dict = {
                         'Projection_map':dict(zip(raw_baselines.Player,raw_baselines.Median)),
                         'Salary_map':dict(zip(raw_baselines.Player,raw_baselines.Salary)),
@@ -351,7 +347,7 @@ with tab1:
                         'Team_map':dict(zip(raw_baselines.Player,raw_baselines.Team)),
                         'STDev_map':dict(zip(raw_baselines.Player,raw_baselines.STDev))
                         }
-                Sim_Winners = sim_contest(1000, st.session_state.working_seed, st.session_state.maps_dict, sharp_split, Contest_Size)
+                Sim_Winners = sim_contest(1000, st.session_state.working_seed, st.session_state.maps_dict, Contest_Size)
                 Sim_Winner_Frame = pd.DataFrame(np.concatenate(Sim_Winners))
                 
                 #st.table(Sim_Winner_Frame)
@@ -378,9 +374,21 @@ with tab1:
                 
             else:
                 if sim_site_var1 == 'Draftkings':
-                    st.session_state.working_seed = DK_seed.copy()
+                    if sim_slate_var1 == 'Main Slate':
+                        st.session_state.working_seed = init_DK_seed_frames(sharp_split)
+                    elif sim_slate_var1 == 'Secondary Slate':
+                        st.session_state.working_seed = init_DK_Secondary_seed_frames(sharp_split)
+                        
+                    raw_baselines = dk_raw
+                    column_names = dk_columns
                 elif sim_site_var1 == 'Fanduel':
-                    st.session_state.working_seed = FD_seed.copy()
+                    if sim_slate_var1 == 'Main Slate':
+                        st.session_state.working_seed = init_FD_seed_frames(sharp_split)
+                    elif sim_slate_var1 == 'Secondary Slate':
+                        st.session_state.working_seed = init_FD_Secondary_seed_frames(sharp_split)
+                    
+                    raw_baselines = fd_raw
+                    column_names = fd_columns
                 st.session_state.maps_dict = {
                         'Projection_map':dict(zip(raw_baselines.Player,raw_baselines.Median)),
                         'Salary_map':dict(zip(raw_baselines.Player,raw_baselines.Salary)),
@@ -389,7 +397,7 @@ with tab1:
                         'Team_map':dict(zip(raw_baselines.Player,raw_baselines.Team)),
                         'STDev_map':dict(zip(raw_baselines.Player,raw_baselines.STDev))
                         }
-                Sim_Winners = sim_contest(1000, st.session_state.working_seed, st.session_state.maps_dict, sharp_split, Contest_Size)
+                Sim_Winners = sim_contest(1000, st.session_state.working_seed, st.session_state.maps_dict, Contest_Size)
                 Sim_Winner_Frame = pd.DataFrame(np.concatenate(Sim_Winners))
                 
                 #st.table(Sim_Winner_Frame)