optimization-dashboard 0.0.1

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Optimization Dashboard

Visualize multidimensional data from studies performed by Hyperactive and Gradient-Free-Optimizers.

Examples

import pandas as pd
from dashboard import Dashboard

# create so test dataset for this example
df_array = [[0.5, 6, 50, 0.6], [0.9, 7, 40, 0.7], [0.2, 9, 70, 0.8]]
columns = ["x1", "x2", "x3", "score"]
search_data = pd.DataFrame(df_array, columns=columns)
# save the dataframe to file
search_data.to_csv("./search_data")


board = Dashboard()
# the dashboard must read the dataframe from a file
board.open_search_data_file("./search_data")

The search data that is loaded from file must always follow the pattern below:

score	x1	x2	...
0.756	0.1	0.2	...
0.823	0.3	0.1	...
...	...	...	...
...	...	...	...

Hereby "x1", "x2", ... can be given any name. But "score" is always necessary!

API reference

• Dashboard(plots=[ "score_statistics", "1d_scatter", "2d_scatter", "3d_scatter", "parallel_coordinates", ] )
• .open_search_data_file(path)