> ## Documentation Index
> Fetch the complete documentation index at: https://docs.idoptlab.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Quickstart

> Install ram-idopt and run your first life cycle cost analysis in under five minutes

## Requirements

* Python 3.10 or later
* An Excel parameter file describing your aircraft (see [Input Format](/guides/input-format))

***

## Install

Clone the repository and install in editable mode:

```bash theme={null}
git clone https://github.com/Idopt-Lab/regional-air-mobility-design-operations.git
cd regional-air-mobility-design-operations
pip install -e .
```

This pulls in all required dependencies automatically (`numpy`, `pandas`, `scipy`, `matplotlib`, `openpyxl`).

<Tip>
  Use a virtual environment to keep dependencies isolated:

  ```bash theme={null}
  python -m venv .venv && source .venv/bin/activate
  pip install -e .
  ```
</Tip>

***

## Run a single-aircraft analysis

```python theme={null}
from ram_idopt.aircraft.cost.LCC import load_parameters, calculate_metrics

# Load parameters from your Excel config file
params = load_parameters("MyAircraft_Cost_Model_1500hrs.xlsx")

# Compute all cost metrics
results = calculate_metrics(params)

print(f"Total annual cost:      ${results.Total_Annual_Costs:,.0f}")
print(f"Annual fixed costs:     ${results.Annual_Fixed_Costs:,.0f}")
print(f"Annual variable costs:  ${results.Annual_Variable_Costs:,.0f}")
print(f"Revenue CASM:           ${results.Revenue_CASM:.4f} / seat-nm")
print(f"Fare per pax-nm:        ${results.Fare_per_Pax_NM:.4f}")
print(f"Life cycle total cost:  ${results.Life_Cycle_Total_Cost:,.0f}")
```

***

## Compare multiple aircraft

Place several Excel files in the same directory and call `run_comparison`:

```python theme={null}
from pathlib import Path
from ram_idopt.aircraft.cost.LCC import run_comparison, print_comparison_table, create_comparison_charts

files = list(Path("configs/").glob("*Cost_Model*.xlsx"))

df, full_results = run_comparison(files)

# Print ranked table to console
print_comparison_table(df)

# Save bar charts, cumulative cost lines, and cost-breakdown pies
create_comparison_charts(df, full_results, output_dir=Path("outputs/"))
```

**Console output (example):**

```
Aircraft              | Rev CASM  | $/Pax-NM  | Annual Cost   | LC Total      | Seats
------------------------------------------------------------------------------------------
Joby S4               |   0.1823  |   0.0365  |  1,204,500    |  8,431,500    |   4
Archer Midnight       |   0.2011  |   0.0402  |  1,387,200    |  9,710,400    |   4
Conventional Cessna   |   0.2540  |   0.0508  |  1,892,000    | 13,244,000    |   4
```

***

## Run from the command line

If you have Excel files in the same directory as `LCC.py`, you can run the script directly:

```bash theme={null}
python src/ram_idopt/aircraft/cost/LCC.py
```

It will auto-discover all `*Cost_Model*.xlsx` files, print the comparison table, and write charts to the current directory.

***

## Run tests

```bash theme={null}
pytest tests/
```

Or with the standard library runner:

```bash theme={null}
python -m unittest discover -s tests -p "test*.py"
```