coexist.plots.access#
- coexist.plots.access(access_data, select=<function <lambda>>, epochs=Ellipsis, colors=['rgb(228,26,28)', 'rgb(55,126,184)', 'rgb(77,175,74)', 'rgb(152,78,163)', 'rgb(255,127,0)', 'rgb(255,255,51)', 'rgb(166,86,40)', 'rgb(247,129,191)', 'rgb(153,153,153)'], overall=False, means=True, confidence=True)[source]#
Create a Plotly figure showing the solutions tried, uncertainties and error values found in a coexist.Access run.
- Parameters:
- access_data
coexist.AccessData
orstr
An AccessData object containing all information about an ACCES run; you can initialise it with
coexist.AccessData.read("folder_path")
. Alternatively, supply thefolder_path
directly.- select
function
,default
lambda
results:results
[:, -1] <numpy.inf
A filtering function used to plot only selected solutions tried, based on an input 2D table results, with columns formatted as [param1, param2, …, param1_std, param2_std, …, overall_std, error_value]. E.g. to only plot solutions with an error value smaller than 100:
select = lambda results: results[:, -1] < 100
.- epochs
int
or iterable orEllipsis
,default
Ellipsis
The index or indices of the epochs to plot. An int signifies a single epoch, an iterable (list-like) signifies multiple epochs, while an Ellipsis (…) signifies all epochs.
- colors
list
[str
],default
plotly.express.colors.qualitative.Set1
A list of colors used for each parameter plotted.
- overallbool,
default
False
If True, also plot the overall standard deviation progression; note that sometimes all parameters converge but the overall std-dev remains high.
- meansbool,
default
True
If True, also plot the centre of the region explored by CMA-ES.
- confidencebool,
default
True
If True, also plot the standard deviation of each parameter as confidence intervals.
- access_data
- Returns:
plotly.graph_objs.Figure
A Plotly figure containing subplots with the solutions tried. Call the .show() method to display it.
Examples
If coexist.Access(filepath, random_seed = 12345) was run, the directory “access_seed12345” would have been created. Plot its results:
>>> import coexist >>> data = coexist.AccessData.read("access_seed12345") >>> fig = coexist.plots.access(data) >>> fig.show()
Or more tersely:
>>> import coexist >>> coexist.plots.access("access_seed12345").show()
Only plot solution combinations that yielded an error value < 100:
>>> coexist.plots.access( >>> data, >>> select = lambda results: results[:, -1] < 100, >>> ).show()