visualise_3d_scatter

API documentation for tradeexecutor.analysis.grid_search.visualise_3d_scatter Python function.

visualise_3d_scatter(flattened_result, parameter_x, parameter_y, parameter_z, measured_metric, color_continuous_scale='Bluered_r', height=600)

Draw a 3D scatter plot for grid search results.

Create an interactive 3d chart to explore three different parameters and one performance measurement of the grid search results.

Example:

from tradeexecutor.analysis.grid_search import analyse_grid_search_result
table = analyse_grid_search_result(grid_search_results)
flattened_results = table.reset_index()
flattened_results["Annualised return %"] = flattened_results["Annualised return"] * 100
fig = visualise_3d_scatter(
    flattened_results,
    parameter_x="rsi_days",
    parameter_y="rsi_high",
    parameter_z="rsi_low",
    measured_metric="Annualised return %"
)
fig.show()

Parameters:

• flattened_result (DataFrame) –

  Grid search results as a DataFrame.

  Created by analyse_grid_search_result().

• parameter_x (str) – X axis

• parameter_y (str) – Y axis

• parameter_z (str) – Z axis

• parameter_colour –

  Output we compare.

  E.g. Annualised return

• color_continuous_scale –

  The name of Plotly gradient used for the colour scale.

  See the Plotly continuos scale color gradient options.

• measured_metric (str) –

Returns:

Plotly figure to display

Return type:

Figure