visualise_grid_rolling_metric_heatmap#

API documentation for tradeexecutor.visual.grid_search_advanced.visualise_grid_rolling_metric_heatmap Python function.

visualise_grid_rolling_metric_heatmap(df, width=1200, height_per_row=500, extra_height_margin=100, charts_per_row=3, range_start=None, range_end=None, discrete_parameters=True, scale=(- 2, 2), colorscale='RdYlGn')[source]#

Create an “animation” for two grid search parameters how results evolve over time as a heatmap.

TODO: Visual Studio Code ignores any given height.

Parameters:

  • df (DataFrame) – Created by calculate_rolling_metrics()

  • charts_per_row – How many mini charts display per Plotly row

  • range_start –

    Visualise slice of full backtest period.

    Inclusive.

  • range_end –

    Visualise slice of full backtest period.

    Inclusive.

  • discrete_parameters – Measured parameters are category like, not linear.

  • scale – Heatmap scale.

Returns:

List of figure s, one for each index timestamp.

Return type:

Figure