optPilot package

optPilot.Annotate module

class optPilot.Annotate.AnnoteFinder(rdata, obj1_idx, obj2_idx, annotes_idx, name_to_column_map, axis=None, xtol=None, ytol=None)[source]

Bases: object

Callback for matplotlib to display an annotation when points are clicked on.

The point which is closest to the click and within xtol and ytol is identified.

@See http://www.scipy.org/Cookbook/Matplotlib/Interactive_Plotting for details.

Register this function like this:

>>> scatter(xdata, ydata)
>>> af = AnnoteFinder(xdata, ydata, annotes)
>>> connect('button_press_event', af)

__init__(rdata, obj1_idx, obj2_idx, annotes_idx, name_to_column_map, axis=None, xtol=None, ytol=None)[source]

drawAnnote(axis, x, y, annote_idx)[source]

drawSpecificAnnote(annote)[source]

getAnchor(x, y)[source]

listifyData(idx)[source]

optPilot.Annotate.distance(x1, x2, y1, y2)[source]

optPilot.Interpolator module

class optPilot.Interpolator.Interpolator[source]

Bases: object

It is built on scipy.interpolate.Rbf

It has to be used with python3.x

__init__()[source]

evaluate(coords)[source]

Interpolate to new coordinates coords

Parameters:: coords (numpy.ndarray (N,)) – New coordinates where to interpolate
Returns:: Interpolated values
Return type:: numpy.ndarray (N,)

train(coords, values, function='linear', smooth=0)[source]

Train the interpolator with values at given coordinates coords

Parameters:

coords (numpy.ndarray (N, M,)) – Coordinates of the nodes (each column is an axis)
values (numpy.ndarray (N,)) – Values of the nodes

Notes

For further information about scipy.interpolate.Rbf see https://docs.scipy.org/doc/scipy-0.19.0/reference/generated/scipy.interpolate.Rbf.html

optPilot.visualize module

class optPilot.visualize.OptData(generation, path, filename_postfix, selected_ids)[source]

Bases: object

__init__(generation, path, filename_postfix, selected_ids)[source]

getX()[source]

getY()[source]

get_variables()[source]

readData()[source]

readInitialData()[source]

class optPilot.visualize.Plotter[source]

Bases: object

__init__()[source]

add_reset()[source]

add_slider(pos, name, min, max)[source]

plot(obj)[source]

setupPlot(width=1388.5)[source]

optPilot.visualize.computeLimits(data, selected_ids)[source]

optPilot.visualize.getXY(generation, path, filename_postfix, selected_ids)[source]

optPilot.visualize.improveName(name)[source]

optPilot.visualize.main(argv)[source]

optPilot.visualize.readJSONData(filename)[source]

optPilot.visualize_parallel_coords module

optPilot.visualize_parallel_coords.find(lst, key, value)[source]

optPilot.visualize_parallel_coords.natural_sort(l)[source]

optPilot.visualize_parallel_coords.plot_parcoords(path, filename_postfix, generation, filename)[source]

References

(30. April 2018)

optPilot.visualize_parallel_coords.sort_list(names, dimension, key)[source]

optPilot.visualize_pf module

optPilot.visualize_pf.computeLimits(data, selected_ids)[source]

optPilot.visualize_pf.improveName(name)[source]

optPilot.visualize_pf.main(argv)[source]

optPilot.visualize_pf.onpick(event)[source]

optPilot.visualize_pf.plot(data, xlim, ylim, num, prefix, selected_obj, show_single, plotAll)[source]

optPilot.visualize_pf.readDAT_0(filename)[source]

optPilot.visualize_pf.readData(filename)[source]

optPilot.visualize_pf.readJSONData(filename)[source]

optPilot.visualize_pf.saveVideo(img_path, video_name)[source]

optPilot.visualize_pf.setupPlot(width=1388.5)[source]