ROI: {round(roi_current,1)}
Marginal ROI: {round(marginal_roi_current,1)}
""",
unsafe_allow_html=True,
)
st.session_state["project_dct"]["scenario_planner"]["scenario"] = (
st.session_state["scenario"]
)
with st.expander("See Response Curves", expanded=True):
fig = plot_response_curves()
st.plotly_chart(fig, use_container_width=True)
def update_optimization_bounds(channel_name, bound_type):
index = 0 if bound_type == "lower" else 1
update_key = (
f"{channel_name}_b_lower"
if bound_type == "lower"
else f"{channel_name}_b_upper"
)
st.session_state["project_dct"]["scenario_planner"][
unique_key
].channels[channel_name].bounds[index] = st.session_state[update_key]
def update_optimization_bounds_all(bound_type):
index = 0 if bound_type == "lower" else 1
update_key = (
f"all_b_lower" if bound_type == "lower" else f"all_b_upper"
)
for channel_name, _channel in st.session_state["project_dct"][
"scenario_planner"
][unique_key].channels.items():
_channel.bounds[index] = st.session_state[update_key]
with st.expander("Optimization setup"):
bounds_placeholder = st.container()
with bounds_placeholder:
st.subheader("Optimization Bounds")
with st.container():
bounds_columns = st.columns((1, 0.35, 0.35, 1))
with bounds_columns[0]:
st.write("##")
st.write("Update all channels")
with bounds_columns[1]:
st.number_input(
"Lower",
min_value=-100,
max_value=500,
key=f"all_b_lower",
# label_visibility="hidden",
on_change=update_optimization_bounds_all,
args=("lower",),
step=5,
value=-10,
)
with bounds_columns[2]:
st.number_input(
"Higher",
value=10,
min_value=-100,
max_value=500,
key=f"all_b_upper",
# label_visibility="hidden",
on_change=update_optimization_bounds_all,
args=("upper",),
step=5,
)
st.divider()
st.write("#### Channel wise bounds")
# st.divider()
# bounds_columns = st.columns((1, 0.35, 0.35, 1))
# with bounds_columns[0]:
# st.write("Channel")
# with bounds_columns[1]:
# st.write("Lower")
# with bounds_columns[2]:
# st.write("Upper")
# st.divider()
for channel_name, _channel in st.session_state["project_dct"][
"scenario_planner"
][unique_key].channels.items():
st.session_state[f"{channel_name}_b_lower"] = _channel.bounds[0]
st.session_state[f"{channel_name}_b_upper"] = _channel.bounds[1]
with bounds_placeholder:
with st.container():
bounds_columns = st.columns((1, 0.35, 0.35, 1))
with bounds_columns[0]:
st.write("##")
st.write(channel_name)
with bounds_columns[1]:
st.number_input(
"Lower",
min_value=-100,
max_value=500,
key=f"{channel_name}_b_lower",
label_visibility="hidden",
on_change=update_optimization_bounds,
args=(
channel_name,
"lower",
),
)
with bounds_columns[2]:
st.number_input(
"Higher",
min_value=-100,
max_value=500,
key=f"{channel_name}_b_upper",
label_visibility="hidden",
on_change=update_optimization_bounds,
args=(
channel_name,
"upper",
),
)
st.divider()
_columns = st.columns(2)
with _columns[0]:
st.subheader("Save Scenario")
scenario_name = st.text_input(
"Scenario name",
key="scenario_input",
placeholder="Scenario name",
label_visibility="collapsed",
)
st.button(
"Save",
on_click=lambda: save_scenario(scenario_name),
disabled=len(st.session_state["scenario_input"]) == 0,
)
summary_df = pd.DataFrame(st.session_state["acutual_predicted"])
summary_df.drop_duplicates(
subset="Channel_name", keep="last", inplace=True
)
summary_df_sorted = summary_df.sort_values(by="Delta", ascending=False)
summary_df_sorted["Delta_percent"] = np.round(
(
(
summary_df_sorted["Optimized_spend"]
/ summary_df_sorted["Actual_spend"]
)
- 1
)
* 100,
2,
)
with open("summary_df.pkl", "wb") as f:
pickle.dump(summary_df_sorted, f)
# st.dataframe(summary_df_sorted)
# ___columns=st.columns(3)
# with ___columns[2]:
# fig=summary_plot(summary_df_sorted, x='Delta_percent', y='Channel_name', title='Delta', text_column='Delta_percent')
# st.plotly_chart(fig,use_container_width=True)
# with ___columns[0]:
# fig=summary_plot(summary_df_sorted, x='Actual_spend', y='Channel_name', title='Actual Spend', text_column='Actual_spend')
# st.plotly_chart(fig,use_container_width=True)
# with ___columns[1]:
# fig=summary_plot(summary_df_sorted, x='Optimized_spend', y='Channel_name', title='Planned Spend', text_column='Optimized_spend')
# st.plotly_chart(fig,use_container_width=True)
elif auth_status == False:
st.error("Username/Password is incorrect")
if auth_status != True:
try:
username_forgot_pw, email_forgot_password, random_password = (
authenticator.forgot_password("Forgot password")
)
if username_forgot_pw:
st.session_state["config"]["credentials"]["usernames"][
username_forgot_pw
]["password"] = stauth.Hasher([random_password]).generate()[0]
send_email(email_forgot_password, random_password)
st.success("New password sent securely")
# Random password to be transferred to user securely
elif username_forgot_pw == False:
st.error("Username not found")
except Exception as e:
st.error(e)
update_db("9_Scenario_Planner.py")