Visualization.py File Reference

Namespaces
	Visualization

Functions
def	Visualization.main (y_test, history, test_predictions, NViz)
def	Visualization.plot_history (history, ss_label, space_label)
def	Visualization.plot_predictions (y_test, test_predictions, NViz, ss_label, space_label)
	PLOT OF THE PREDICTIONS FOR SUPERVISED REGRESSION FROM SINGLE SHOTS ###. More...
def	Visualization.SaveHistoryToFile (HISTORY, keys, HistoryFileName)
def	Visualization.AddKeysToPlot (PLOT, HISTORY, keys, pattern, legend)
def	Visualization.grid_display (list_of_images, list_of_titles=[], no_of_columns=2, figsize=(10, 10))
def	Visualization.result_averaging (y_test, test_predictions)
def	Visualization.get_labels ()
def	Visualization.folder_creation ()

Variables
	Visualization.threshold
	Visualization.NSamples = int(inp.NShots/inp.NShotsPerSample)
	Visualization.TestingFraction = len(y_test[:,0])
	ax.hist(phases, density=1, bins=n_bins) More...
list	Visualization.indices = []
list	Visualization.titles = []
list	Visualization.corrplot = []
	Visualization.VizGrid = np.reshape(np.loadtxt('VizGrid.txt', usecols=[0,1]),(-1,2))
	Visualization.fig
	Visualization.axes
	Visualization.ncols
	Visualization.sharex
	Visualization.True
	Visualization.sharey
	Visualization.left
	Visualization.None
	Visualization.bottom
	Visualization.right
	Visualization.top
	Visualization.wspace
	Visualization.hspace
int	Visualization.j = 0
	Visualization.cmap = plt.get_cmap('Blues')
	Visualization.c_max = np.amax(corrplot)
	Visualization.c_min = np.amin(corrplot)
	Visualization.adjustable
	Visualization.aspect
	Visualization.im = ax.pcolormesh(VizGrid[0:inp.Npoints,0],VizGrid[0:inp.Npoints,0], corrplot[j] , cmap=cmap, vmax=c_max, vmin=c_min)
	Visualization.divider = make_axes_locatable(ax)
	Visualization.cax = divider.append_axes("right", size="5%", pad=0.05)
	Visualization.dpi
	Visualization.bbox_inches
	Visualization.Grid