neuromancer.psl.plot module

# TODO: stream plots for phase spaces of ODEs # TODO: generate correlation network - https://python-graph-gallery.com/327-network-from-correlation-matrix/ # TODO: plot information-theoretic measures for time series data - https: // elife - asu.github.io / PyInform / timeseries.html

neuromancer.psl.plot.get_colors(k)

Returns k colors evenly spaced across the color wheel. :param k: (int) Number of colors you want. :return:

neuromancer.psl.plot.pltCL(Y, U=None, D=None, X=None, R=None, Ymin=None, Ymax=None, Umin=None, Umax=None, figname=None)

plot trained open loop dataset Ytrue: ground truth training signal Ytrain: trained model response

neuromancer.psl.plot.pltCorrelate(X, figname=None)

plot correlation matrices of time series data https://realpython.com/numpy-scipy-pandas-correlation-python/

neuromancer.psl.plot.pltOL(Y, Ytrain=None, U=None, D=None, X=None, figname=None)

plot trained open loop dataset Ytrue: ground truth training signal Ytrain: trained model response

neuromancer.psl.plot.pltPhase(X, Xtrain=None, figname=None)

plot phase space for 2D and 3D state spaces

https://matplotlib.org/3.2.1/gallery/images_contours_and_fields/plot_streamplot.html https://matplotlib.org/3.1.1/api/_as_gen/matplotlib.pyplot.streamplot.html https://matplotlib.org/3.2.1/api/_as_gen/matplotlib.pyplot.quiver.html http://kitchingroup.cheme.cmu.edu/blog/2013/02/21/Phase-portraits-of-a-system-of-ODEs/ http://systems-sciences.uni-graz.at/etextbook/sw2/phpl_python.html

neuromancer.psl.plot.pltRecurrence(X, figname=None)

plot recurrence of time series data https://pyts.readthedocs.io/en/stable/auto_examples/image/plot_rp.html https://pyts.readthedocs.io/en/stable/auto_examples/multivariate/plot_joint_rp.html#sphx-glr-auto-examples-multivariate-plot-joint-rp-py https://pyts.readthedocs.io/en/stable/auto_examples/image/plot_mtf.html https://arxiv.org/pdf/1610.07273.pdf https://pyts.readthedocs.io/en/stable/auto_examples/image/plot_gaf.html#sphx-glr-auto-examples-image-plot-gaf-py