v1.7.0

• Density coloring implemented with the gradient parameter.

In this example, the cmap=Set1 will be used to color the class labels. The coloring will have a continuous scale towards the borders.

pca.scatter(cmap='Set1', gradient='#ffffff')

v1.6.4

• Title can be changed in the figures
• Fix when normalizing out PCs by the conversion of dataframe into a numpy array.

1.6.3

• Fix for newer versions of Python related to dict_items. Thanks @tgy!
• Fix in case no explained variance is detected.

1.6.2

• The .plot functionality will show the total explained variance across the components when selecting on explained variance: n_components<1
• docstring updates
• Some code cleaning

1.6.1

• Fixes for biplot when choosing different PC to plot.
• New parameter for biplot, to color the arrow: model.biplot(color_arrow='g')

1.6.0

• Added parameter in biplot and biplot3d to choose the PC axes.

fig, ax = model.biplot(PC=[0, 1])
fig, ax = model.biplot3d(PC=[0, 1, 2])

1.5.5

• added doi

1.5.4

• Fix in case PCs are selected based on percentage explained variance. In cases when new samples needed to be transformed with the existing model, an error occurred.
• Licence added to the setup file

1.5.3

• Fix for plot in case only 1PC is detected.

1.5.2

• Added functionality to train/infer mode for outlier detection in Hotelling's T2 and SPE #15 and #16
• Added functionality to use lists as input for the model #17