Revert

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(sharp_split):  
+def init_DK_seed_frames():  
     
     collection = db["DK_NFL_seed_frame"] 
     cursor = collection.find()
@@ -63,12 +63,11 @@ def init_DK_seed_frames(sharp_split):
     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 fp_array
+    return DK_seed
 
 @st.cache_data(ttl = 600)
-def init_DK_Secondary_seed_frames(sharp_split):  
+def init_DK_Secondary_seed_frames():  
     
     collection = db["DK_NFL_Secondary_seed_frame"] 
     cursor = collection.find()
@@ -76,12 +75,11 @@ def init_DK_Secondary_seed_frames(sharp_split):
     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 fp_array
+    return DK_seed
 
 @st.cache_data(ttl = 599)
-def init_FD_seed_frames(sharp_split):  
+def init_FD_seed_frames():  
     
     collection = db["FD_NFL_seed_frame"] 
     cursor = collection.find()
@@ -89,12 +87,11 @@ def init_FD_seed_frames(sharp_split):
     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 fp_array
+    return FD_seed
 
 @st.cache_data(ttl = 599)
-def init_FD_Secondary_seed_frames(sharp_split):  
+def init_FD_Secondary_seed_frames():  
     
     collection = db["FD_NFL_Secondary_seed_frame"] 
     cursor = collection.find()
@@ -102,10 +99,8 @@ def init_FD_Secondary_seed_frames(sharp_split):
     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 fp_array
+    return FD_seed
 
 @st.cache_data(ttl = 599)
 def init_baselines():
@@ -151,9 +146,10 @@ def calculate_FD_value_frequencies(np_array):
     return combined_array
 
 @st.cache_data
-def sim_contest(Sim_size, seed_frame, maps_dict, Contest_Size):
+def sim_contest(Sim_size, seed_frame, maps_dict, sharp_split, 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__)
@@ -305,6 +301,22 @@ 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':
@@ -331,14 +343,6 @@ 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)),
@@ -347,7 +351,7 @@ 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, Contest_Size)
+                Sim_Winners = sim_contest(1000, st.session_state.working_seed, st.session_state.maps_dict, sharp_split, Contest_Size)
                 Sim_Winner_Frame = pd.DataFrame(np.concatenate(Sim_Winners))
                 
                 #st.table(Sim_Winner_Frame)
@@ -374,21 +378,9 @@ with tab1:
                 
             else:
                 if sim_site_var1 == 'Draftkings':
-                    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
+                    st.session_state.working_seed = DK_seed.copy()
                 elif sim_site_var1 == 'Fanduel':
-                    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.working_seed = FD_seed.copy()
                 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)),
@@ -397,7 +389,7 @@ 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, Contest_Size)
+                Sim_Winners = sim_contest(1000, st.session_state.working_seed, st.session_state.maps_dict, sharp_split, Contest_Size)
                 Sim_Winner_Frame = pd.DataFrame(np.concatenate(Sim_Winners))
                 
                 #st.table(Sim_Winner_Frame)