RITM Age and Efforts calculation

 Great! Here's how you can implement the described Excel logic in your Streamlit app using Python:

🛠️ Step-by-step Implementation in Streamlit

python
import streamlit as st
import math

# Inputs from user or model
ritm_age_days = st.number_input("Predicted RITM Age (in days)", value=5.0)
effort_hours = st.number_input("Predicted Effort (in hours)", value=40.0)
num_ritm = st.number_input("Number of RITMs", value=1, step=1, min_value=1)
num_fte = st.number_input("Number of FTEs", value=1, step=1, min_value=1)

# Convert effort to days (8 hours/day)
effort_in_days = math.ceil(effort_hours / 8)

# Effort multiplier based on number of RITMs
if num_ritm == 1:
    effort_multiplier_ritm = 0
else:
    effort_multiplier_ritm = (effort_in_days * num_ritm) - effort_in_days

# Effort multiplier considering number of FTEs
if num_fte >= num_ritm:
    effort_multiplier_fte = effort_multiplier_ritm
else:
    effort_multiplier_fte = math.ceil(effort_multiplier_ritm / num_fte)

# Total RITM Age calculation
if effort_multiplier_fte == 1:
    total_ritm_age = ritm_age_days
elif num_fte >= num_ritm:
    total_ritm_age = ritm_age_days
else:
    total_ritm_age = ritm_age_days + effort_multiplier_fte

# Display the results
st.write(f"**Effort in Days:** {effort_in_days}")
st.write(f"**Effort Multiplier (RITM):** {effort_multiplier_ritm}")
st.write(f"**Effort Multiplier (FTE):** {effort_multiplier_fte}")
st.success(f"**Total RITM Age:** {total_ritm_age} days")

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✅ What This Does

• Takes model predictions and user inputs.

• Translates Excel logic into Python math with correct condition handling.