Package for plotting GPRegression results

pygp plotting tools

Tools to plot Gaussian process pygp.gp regression output.

pygp.plot.gpr_plot.plot_sausage(X, mean, std, alpha=None, format_fill={'alpha': 0.1, 'facecolor': 'k'}, format_line={'color': 'g', 'lw': 3, 'ls': 'dashed', 'alpha': 1}, ax=None)

plot saussage plot of GP. I.e:

returns: : [fill_plot, line_plot]

The fill and the line of the sausage plot. (i.e. green line and gray fill of the example above)

Parameters:

X : [double]

Interval X for which the saussage shall be plottet.

mean : [double]

The mean of to be plottet.

std : [double]

Pointwise standard deviation.

format_fill : {format}

The format of the fill. See http://matplotlib.sourceforge.net/ for details.

format_line : {format}

The format of the mean line. See http://matplotlib.sourceforge.net/ for details.

pygp.plot.gpr_plot.plot_training_data(x, y, shift=None, replicate_indices=None, format_data={'marker': '.', 'alpha': 0.5, 'markersize': 9, 'linestyle': '--', 'lw': 1}, draw_arrows=0, plot_old=False)

Plot training data input x and output y into the active figure (See http://matplotlib.sourceforge.net/ for details of figure).

Instance plot without replicate groups:

Instance plot with two replicate groups and a shift in x-koords:

Parameters:

x : [double]

Input x (e.g. time).

y : [double]

Output y (e.g. expression).

shift : [double]

The shift of each replicate group.

replicate_indices : [int]

Indices of replicates for each x, rexpectively

format_data : {format}

Format of the data points. See http://matplotlib.sourceforge.net/ for details.

draw_arrows : int

draw given number of arrows (if greator than len(replicate) draw all arrows. Arrows will show the time shift for time points, respectively.