Plot Results¶

This guide shows how to render interactive charts from persisted results.

Prerequisites¶

• Results already uploaded to the backend (see Upload Results).
• A ResultsAPI client configured and authenticated.

Plot Through ResultsService¶

from owi.metadatabase.results import ResultsAPI
from owi.metadatabase.results.services import ApiResultsRepository, ResultsService

api = ResultsAPI(api_root="https://owimetadatabase-dev.azurewebsites.net/api/v1",
                 token="your-api-token")
service = ResultsService(repository=ApiResultsRepository(api=api))

Available Plot Types¶

Comparison Plot¶

Scatter chart comparing metrics across references with a location dropdown:

plot = service.plot_results(
    "LifetimeDesignFrequencies",
    filters={"analysis_id": 46},
    plot_type="comparison",
)
display(plot.notebook)  # Jupyter widget

Location Plot¶

Scatter chart grouping values by turbine with a metric dropdown:

plot = service.plot_results(
    "LifetimeDesignFrequencies",
    filters={"analysis_id": 46},
    plot_type="location",
)
display(plot.notebook)

Geo Plot¶

Geographic map projecting results onto the site layout:

plot = service.plot_results(
    "LifetimeDesignFrequencies",
    filters={"analysis_id": 46},
    plot_type="geo",
)
display(plot.notebook)

Time Series Plot¶

Line chart for time-indexed data (e.g. LifetimeDesignVerification):

plot = service.plot_results(
    "LifetimeDesignVerification",
    filters={"analysis_id": 50},
    plot_type="time_series",
)
display(plot.notebook)

Water-depth Trend Plot¶

Scatter chart for LifetimeDesignVerification results with one dropdown entry per metric. The x-axis uses each turbine's asset-location elevation as absolute water depth, and the y-axis uses the verification frequency value. Turbines without an elevation value are skipped.

plot = service.plot_results(
    "LifetimeDesignVerification",
    filters={"analysis_id": 50},
    plot_type="water_depth_trend",
)
display(plot.notebook)

Cross-analysis Fleetwide Plot¶

Fleetwide overlay combining actual frequency reference lines with verification points across assets. Unlike the single-analysis plot types above, this plot is selected only by plot_type; the contributing analyses are passed through named source_filters.

plot = service.plot_results(
    plot_type="cross_analysis_fleetwide",
    source_filters={
        "frequency": {"analysis_id": 46},
        "verification": {"analysis_id": 50},
    },
)
display(plot.notebook)

Cross-analysis Delta Histogram Plot¶

Fleetwide histogram comparing each design frequency reference with the latest available design verification value for the same turbine and metric. The x-axis is Δ design frequency [%], calculated as (latest_verification - design_frequency) / design_frequency * 100, and the y-axis is # samples. Each metric is available from the dropdown; within each metric, bars are grouped by reference_label using shared histogram bins so the counts align. The chart has no title, keeps a reference_label legend, and differentiates references by both color and fill pattern.

Rows without a matching latest verification value, or with missing or zero design_frequency, are skipped.

plot = service.plot_results(
    plot_type="cross_analysis_fleetwide_delta_histogram",
    source_filters={
        "frequency": {"analysis_id": 46},
        "verification": {"analysis_id": 50},
    },
)
display(plot.notebook)

Cross-analysis Asset Plot¶

Asset-level overlay combining verification points over time with dashed frequency reference levels. Use shared filters such as location_id to scope the plot for an asset page.

plot = service.plot_results(
    plot_type="cross_analysis_asset",
    filters={"location_id": 123},
    source_filters={
        "frequency": {"analysis_id": 46},
        "verification": {"analysis_id": 50},
    },
)
display(plot.notebook)

Histogram Plot¶

Bar chart for binned data (e.g. WindSpeedHistogram):

plot = service.plot_results(
    "WindSpeedHistogram",
    filters={"analysis_id": 55},
    plot_type="histogram",
)
display(plot.notebook)

Access Plot Outputs¶

Every PlotResponse provides multiple output formats: