How-to: asap kde¶

asap kde sub_command is for performing kernel density estimation of the data. One can do the cluster using the high-dimensional design matrix generated by asap gen_desc, or the low-dimensional projections of the design matrix generated by the command asap map.

Overview of sub-commands¶

sub-commands that select the specific algorithm for kernel density estimations:

option	description
kde_internal	Internal implementation of KDE
kde_scipy	Scipy implementation of KDE
kde_sklearn	Scikit-learn implementation of KDE
plot_pca	Plot the KDE results using a PCA map

asap kde¶

Kernel density estimation using the design matrix. This command function evaluated before the specific ones, we setup the general stuff here, such as read the files.

asap kde [OPTIONS] COMMAND1 [ARGS]... [COMMAND2 [ARGS]...]...

Options

-f, --fxyz <fxyz>¶: Input file that contains XYZ coordinates. See a list of possible input formats: https://wiki.fysik.dtu.dk/ase/ase/io/io.html If a wildcard * is used, all files matching the pattern is read.

-p, --prefix <prefix>¶: Prefix to be used for the output file.

--only_use_species <only_use_species>¶: Only use the atomic descriptors of species with the specified atomic number. Only makes sense if already using –use_atomic_descriptors.

-ua, --use_atomic_descriptors, --use_atomic¶: Use atomic descriptors instead of global ones.

-dm, --design_matrix <design_matrix>¶: Location of descriptor matrix file or name of the tags in ase xyz file the type is a list ‘[dm1, dm2]’, as we can put together simutanously several design matrix.

--savetxt, --no-savetxt¶: Save the results to the txt file

--savexyz, --no-savexyz¶: Save the results to the xyz file

kde_internal¶

Internal implementation of KDE

asap kde kde_internal [OPTIONS]

Options

-d, --dimension <dimension>¶

The number of the first D dimensions to keep when doing KDE.

Default: 8

kde_scipy¶

Scipy implementation of KDE

asap kde kde_scipy [OPTIONS]

Options

-d, --dimension <dimension>¶

The number of the first D dimensions to keep when doing KDE.

Default: 50

-bw, --bw_method <bw_method>¶: This can be ‘scott’, ‘silverman’, a scalar constant or a callable.

kde_sklearn¶

Scikit-learn implementation of KDE

asap kde kde_sklearn [OPTIONS]

Options

-d, --dimension <dimension>¶

The number of the first D dimensions to keep when doing KDE.

Default: 50

--metric <metric>¶

controls how distance is computed in the ambient space of the input data. See: https://scikit-learn.org/stable/modules/density.html#kernel-density-estimation

Default: euclidean

--algorithm <algorithm>¶

Algorithm to use

Default: auto
Options: kd_tree|ball_tree|auto

--kernel <kernel>¶

Kernel to use

Default: gaussian
Options: gaussian|tophat|epanechnikov|exponential|linear|cosine

-bw, --bandwidth <bandwidth>¶

Bandwidth of the kernel

Default: 1

plot_pca¶

Plot the KDE results using a PCA map

asap kde plot_pca [OPTIONS]

Options

-s, --style <style>¶

Style of the plot.

Default: default
Options: default|journal

-ar, --aspect_ratio <aspect_ratio>¶

Aspect ratio of the plot

Default: 2

-a, --annotate <annotate>¶: Location of tags to annotate the samples.

--adjusttext, --no-adjusttext¶: Adjust the annotation texts so they do not overlap.

--peratom¶: Save the per-atom projection.

--scale, --no-scale¶: Standard scaling of the coordinates.

-d, --dimension <dimension>¶: Number of the dimensions to keep in the output XYZ file.

--axes <axes>¶: Plot the projection along which projection axes.

-p, --prefix <prefix>¶: Prefix to be used for the output file.

Note