Package index • irishbuoys

Data Access

Functions for downloading and accessing buoy data

download_buoy_data(): Download Data from Irish Weather Buoy Network ERDDAP Server
get_latest_timestamp(): Get Latest Data Timestamp from ERDDAP
get_stations(): Get Available Stations

Database Management

Functions for DuckDB and Parquet storage

buoy_tbl(): Get Lazy Reference to Buoy Data Table
connect_duckdb(): Create or Connect to Irish Buoys DuckDB Database
create_buoy_schema(): Create Database Schema for Buoy Data
load_to_duckdb(): Load Data into DuckDB Database
query_buoy_data(): Query Buoy Data from Database
get_database_stats(): Get Database Statistics
init_parquet_storage(): Parquet-based Storage Backend for Irish Buoys Data
save_to_parquet(): Save Data to Parquet with Optimal Compression
query_parquet(): Query Parquet Files with DuckDB
analyze_parquet_storage(): Analyze Parquet Storage
incremental_update(): Perform Incremental Data Update
incremental_update_parquet(): Incremental Update with Parquet Storage
initialize_database(): Initialize Database with Historical Data
convert_duckdb_to_parquet(): Convert Existing DuckDB to Parquet

Wave Analysis

Functions for wave science and rogue wave detection

wave_glossary(): Glossary of Wave Measurement Terms
explain_hs_formula(): Explain Why Hs Equals 4 Times Standard Deviation
explain_wave_height_measurement(): Explain How Individual Wave Heights Are Measured (Zero-Crossing Method)
explain_measurement_period(): Explain the 17.5-Minute Measurement Period
explain_hourly_averaging(): Explain Hourly Averaging Process
wave_science_documentation(): Generate Wave Science Documentation
calculate_hs_from_elevation(): Calculate Significant Wave Height from Raw Elevations
calculate_rms_wave_height(): Calculate RMS Wave Height
hs_from_rms(): Estimate Hs from RMS Wave Height
detect_rogue_waves(): Rogue Wave Detection and Analysis
analyze_rogue_statistics(): Analyze Rogue Wave Statistics
calculate_wave_steepness(): Calculate Wave Steepness
add_wave_metrics(): Add Wave Metrics to Data
rogue_wave_report(): Get Rogue Wave Summary Report
test_rogue_propagation(): Test Spatial Propagation of Rogue Wave Events

Extreme Value Analysis

Functions for fitting extreme value models

fit_gev_annual_maxima(): Fit GEV Distribution to Annual Maxima
fit_gpd_threshold(): Fit GPD Distribution to Threshold Exceedances
calculate_return_levels(): Calculate Return Levels
calculate_gpd_return_levels(): Calculate GPD Return Levels from Per-Station Fits
create_return_level_plot_data(): Create Return Level Plot Data
ci_bootstrap_return_levels(): Bootstrap Confidence Intervals for GPD Return Levels
ci_order_statistics(): Order-Statistics Confidence Intervals for Quantiles
ci_parametric_bootstrap(): Parametric Bootstrap CIs for GPD Return Levels
analyze_gust_factor(): Analyze Gust Factor
compare_rogue_wave_gust(): Compare Rogue Wave and Rogue Gust Occurrence

Trend Analysis

Seasonal decomposition and trend detection

decompose_stl(): Perform STL Decomposition
calculate_seasonal_means(): Calculate Seasonal Means
calculate_annual_trends(): Calculate Annual Trends
detect_anomalies(): Detect Anomalies
compute_acf_summary(): Compute ACF Summary
mann_kendall_test(): Mann-Kendall Trend Test
trend_summary_report(): Create Trend Summary Report

Wave Modeling

Machine learning models for wave prediction

wave_model: Wave Height Prediction Model
prepare_wave_features(): Prepare Features for Wave Height Prediction
train_wave_model(): Train Wave Height Prediction Model
evaluate_wave_model(): Evaluate Wave Height Model
predict_wave_height(): Predict Wave Height
wave_model_report(): Generate Wave Model Report

Visualization

Functions for creating interactive plots

irishbuoys_layout(): Standard Plotly Theme for Irish Buoys Package
irishbuoys_ggplotly(): Apply Irish Buoys theme to ggplotly object
create_plot_rogue_all(): Create Rogue Wave All Stations Plot
create_plot_rogue_by_station(): Create Rogue Wave By Station Subplot
create_plot_wind_beaufort(): Create Wind Speed by Beaufort Scale Plot
create_plot_week_of_year(): Create Week of Year Stacked Bar Plot
create_plot_time_of_day(): Create Time of Day Bar Plot
create_plot_monthly_wave(): Create Monthly Wave Height Bar Plot
create_plot_monthly_wind(): Create Monthly Wind Speed Bar Plot
create_plot_annual_trends(): Create Annual Trends Line Plot
create_plot_return_levels(): Create Return Levels Plot
create_plot_return_levels_per_station(): Create Per-Station Return Levels Plot
create_plot_gust_by_category(): Create Gust Factor by Category Plot
create_plot_rogue_gusts(): Create Rogue Gusts by Station Plot
create_plot_stl(): Create STL Decomposition Plot
create_plot_rogue_gusts_all(): Create Rogue Gusts All Stations Plot
create_plot_rogue_gusts_by_station(): Create Rogue Gusts By Station Subplot
create_plot_gusts_vs_waves(): Create Rogue Gusts vs Rogue Waves Scatter Plot

Email Reporting

Functions for generating and sending email summaries

generate_weekly_summary(): Generate Weekly Summary Statistics
create_email_summary(): Create HTML Email Summary
generate_and_send_summary(): Generate and Send Summary Email
validate_email_freshness(): Validate Email Data Freshness

Data Validation

Functions for validating data quality with pointblank

validate_buoy_data(): Validate analysis data with pointblank
validate_rogue_events(): Validate rogue wave events data
generate_validation_reports(): Generate validation reports for website
create_validation_summary(): Create a validation summary for the pipeline
detect_outliers_iqr(): Detect Outliers using IQR Method
compute_data_coverage(): Compute Data Coverage and Gaps

Joint Analysis

Functions for multi-station spatial analysis

analyze_joint_extremes(): Analyze Joint Extremes Between Stations
analyze_station_pairs(): Analyze All Station Pairs
cross_correlation_stations(): Calculate Cross-Correlation Between Two Stations
compute_extremal_dependence(): Compute Pairwise Extremal Dependence Across Stations
fit_bivariate_copula(): Fit Bivariate Copula for Joint Extremes
fit_spatial_maxstable(): Fit a Max-Stable Process to Station Annual Maxima
get_station_info(): Station Information with Coordinates
haversine_distance(): Calculate Distance Between Two Stations
joint_analysis_summary(): Create Joint Analysis Summary
predict_station_lagged(): Predict Station from Another with Optimal Lag
station_distance_matrix(): Calculate Distance Matrix Between All Stations

API

Functions for REST and static JSON API endpoints

api_plumber: Plumber API for irishbuoys
api_static: Static API Generation Functions
create_api_router(): Create the irishbuoys Plumber Router
run_api(): Run the irishbuoys REST API
generate_api_index(): Generate API Index
generate_api_latest(): Generate Latest Observations
generate_api_status(): Generate Station Status Endpoint
generate_api_sources(): Generate Data Sources Endpoint
generate_api_trends(): Generate Trends Endpoint
generate_api_spatial(): Generate Spatial Correlations Endpoint
generate_api_extremes(): Generate Extremes Endpoint
generate_api_decomposition(): Generate Decomposition Endpoint
generate_api_gust_factors(): Generate Gust Factors Endpoint
generate_api_methods(): Generate Methods Endpoint

Storm Alerts

Storm forecast monitoring and email alerts

send_storm_alert(): Send Storm Alert Email
fetch_open_meteo_forecast(): Fetch Wind Forecast from Open-Meteo for a Single Station
fetch_all_forecasts(): Fetch Forecasts for All Buoy Stations
detect_storm_events(): Detect Storm Events from Forecast Data
create_storm_alert_email(): Create Storm Alert Email
fetch_met_eireann_warnings(): Fetch Met Eireann Marine Warnings
knots_to_beaufort(): Convert Wind Speed in Knots to Beaufort Scale
beaufort_to_description(): Convert Beaufort Number to Description

Prediction Calibration

Track and calibrate prediction accuracy

read_predictions(): Read and reconcile predictions from JSONL
compute_calibration(): Compute calibration metrics for predictions

Documentation

Data dictionary and variable documentation

get_data_dictionary(): Irish Weather Buoy Network Data Dictionary
get_variable_docs(): Get Detailed Variable Documentation