Basic Usage Examples

This guide walks through a typical workflow using the macromodel framework, from data preprocessing to running a simulation and extracting summary results.

1. Data Preprocessing with DataWrapper

First, preprocess your data using the DataWrapper class. This step harmonizes and prepares all the data needed for the simulation.

from macro_data.configuration_utils import default_data_configuration
from macro_data import DataWrapper

# Configure data preprocessing
config = default_data_configuration(countries=["FRA"], proxy_country_dict={})

# Create DataWrapper instance
creator = DataWrapper.from_config(
    configuration=config,
    raw_data_path="path/to/raw/data",
    single_hfcs_survey=True
)

# Save processed data for later use
creator.save("./data_fra.pkl")

2. Running a Simulation

Once you have preprocessed data, you can run a simulation. Here's a step-by-step example:

from macro_data import DataWrapper
from macromodel.configurations import CountryConfiguration, SimulationConfiguration
from macromodel.simulation import Simulation

# Load preprocessed data
preprocessed_data = DataWrapper.init_from_pickle("./data_fra.pkl")

# Set up simulation configuration
country_config = CountryConfiguration()
sim_config = SimulationConfiguration(country_configurations={"FRA": country_config})

# Initialize simulation
simulation = Simulation.from_datawrapper(
    datawrapper=preprocessed_data,
    simulation_configuration=sim_config
)

# Run the simulation (runs for the configured number of steps)
simulation.run()

3. Extracting and Interpreting Results

After running the simulation, you can extract summary results for each country using the shallow_df_dict() method:

# Get a dictionary of shallow (summary) DataFrames for each country
shallow_outputs = simulation.shallow_df_dict()

# For France, get the summary DataFrame
shallow_output_df = shallow_outputs["FRA"]

# For example, get the total nominal production of all firms in France:
total_production = shallow_output_df["Production"]
print("Total nominal production (all firms):", total_production)

The shallow_output_df contains key economic indicators for the country, such as:

• Production: Total nominal production of all firms
• Sales, Wages, Profits, Taxes Paid on Production, etc.
• Unemployment Rate, Imports, Exports, and more

You can use these outputs for further analysis, validation, or visualization.

---

Tip:

• The shallow_output method (see API docs) provides a concise summary of the main economic metrics for each country, including GDP, inflation, unemployment, and sectoral outputs.