Quickstart¶

This quickstart guide will help you get up and running with dominosee for analyzing interconnected hydroclimatic extreme events.

Basic Usage¶

First, import the necessary packages:

import numpy as np
import xarray as xr
import matplotlib.pyplot as plt
import dominosee as ds

Event Analysis¶

One of the core functionalities of dominosee is selecting and analyzing event periods:

# Create sample event data
events = np.random.randn(100, 10)  # 100 time steps, 10 events
duration = np.arange(1, 11)        # Duration of each event

# Select the first few days of events based on duration
first_period = ds.select_first_period(events, duration, days=5)

# Plot the results
plt.figure(figsize=(10, 6))
plt.plot(first_period)
plt.title('First 5 Days of Events')
plt.xlabel('Time Step')
plt.ylabel('Value')
plt.grid(True)
plt.show()

Working with xarray DataArrays¶

For multidimensional gridded climate data, dominosee provides xarray-compatible functions:

# Create a sample xarray DataArray
times = pd.date_range('2025-01-01', periods=100)
events = np.random.randn(100, 5, 3)  # time, event, location

da = xr.DataArray(
    events,
    dims=('time', 'event', 'location'),
    coords={
        'time': times,
        'event': np.arange(5),
        'location': ['A', 'B', 'C']
    }
)

# Create duration array
duration = xr.DataArray(
    np.array([3, 5, 2, 7, 4]),
    dims=('event'),
    coords={'event': np.arange(5)}
)

# Select first period using xarray function
first_period_xr = ds.select_first_period_xr(da, duration, days=3)

# Plot results for one location
first_period_xr.sel(location='A').plot.line(x='time')
plt.title('First 3 Days of Events at Location A')
plt.grid(True)
plt.show()

Network Analysis¶

dominosee can generate and analyze networks from event data:

# Generate a sample network from event data
# This is a simplified example
network = ds.generate_network(da, threshold=0.5)

# Analyze network properties
centrality = ds.calculate_centrality(network)

# Visualize the network
ds.plot_network(network, centrality)

Next Steps¶

To dive deeper into dominosee:

Explore the User Guide for detailed explanations
Check out the examples/index for practical examples
Refer to the API Reference for complete function documentation