Signal Evaluation

API reference for sovai.extensions.signal_evaluation

Module: sovai.extensions.signal_evaluation

Classes

SignalEvaluator

class SignalEvaluator

Attributes

• verbose

• df_factor

• positions

• rebalance_mask

• holdings

• returns

• position_returns

• resampled_returns

• portfolio_returns

• cumulative_returns

• performance_plot

• performance_table

• stress_plot

• distribution_plot

• drawdown_plot

• drawdown_table

• returns_heatmap_plot

• turnover_plot

• signal_correlation_plot

• signal_decile_plot

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Functions

enrich_figure_with_llm_metadata()

def enrich_figure_with_llm_metadata(
    fig,
    title: Optional[str] = None,
    description: Optional[str] = None,
    key_stats: Optional[Dict[str, Any]] = None,
    downsample: bool = False,
    target_points: int = 768,
    include_image_export: bool = True,
    image_format: str = 'png',
    image_width: int = 1600,
    image_height: int = 900,
    image_scale: int = 2,
    category: str = 'signal_evaluation',
) -> None

Enrich a Plotly figure with LLM-ready metadata.

This function adds metadata to fig.layout.meta that can be used for feeding the figure to an LLM. Modifies the figure in-place.

Parameters

Parameter	Type	Description
fig	—	plotly.graph_objects.Figure The Plotly figure to enrich
title	Optional[str]	str, optional Chart title override
description	Optional[str]	str, optional Chart description
key_stats	Optional[Dict[str, Any]]	dict, optional Dictionary of key statistics
downsample	bool	bool Whether to apply LTTB downsampling in the compressed spec
target_points	int	int Target number of points for downsampling
include_image_export	bool	bool Whether to generate image export metadata
image_format	str	str Image format ('png', 'webp', 'jpeg', 'svg')
image_width	int	int Image width in pixels
image_height	int	int Image height in pixels
image_scale	int	int Image scale factor

Returns

None (modifies fig in-place)

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export_figure_for_llm()

def export_figure_for_llm(
    fig,
    include_image: bool = True,
    image_format: str = 'png',
    return_base64: bool = True,
) -> Dict[str, Any]

Export a figure with LLM metadata for direct use in LLM prompts.

Parameters

Parameter	Type	Description
fig	—	plotly.graph_objects.Figure The Plotly figure with LLM metadata
include_image	bool	bool Whether to export the actual image
image_format	str	str Image format ('png', 'webp', 'jpeg', 'svg')
return_base64	bool	bool Whether to return image as base64 (vs. raw bytes)

Returns

dict : Contains chart_card, spec_capsule, alt_text, and optionally image

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