################################################################################################### # Deployment specific global definitions - executed after startup.py ################################################################################################### from mathutils import estimate_peak_indexes, fit_gaussians, create_fit_point_list, Gaussian from mathutils import fit_polynomial,fit_gaussian, fit_harmonic, calculate_peaks from mathutils import PolynomialFunction, Gaussian, HarmonicOscillator import java.awt.Color as Color def fit(ydata, xdata = None): """ Gaussian fit """ if xdata is None: xdata = frange(0, len(ydata), 1) max_y= max(ydata) index_max = ydata.index(max_y) max_x= xdata[index_max] print "Max index:" + str(index_max), print " x:" + str(max_x), print " y:" + str(max_y) gaussians = fit_gaussians(ydata, xdata, [index_max,]) (norm, mean, sigma) = gaussians[0] p = plot([ydata],["data"],[xdata], title="Fit" )[0] fitted_gaussian_function = Gaussian(norm, mean, sigma) scale_x = [float(min(xdata)), float(max(xdata)) ] points = max((len(xdata)+1), 100) resolution = (scale_x[1]-scale_x[0]) / points fit_y = [] fit_x = frange(scale_x[0],scale_x[1],resolution, True) for x in fit_x: fit_y.append(fitted_gaussian_function.value(x)) p.addSeries(LinePlotSeries("fit")) p.getSeries(1).setData(fit_x, fit_y) if abs(mean - xdata[index_max]) < ((scale_x[0] + scale_x[1])/2): print "Mean -> " + str(mean) p.addMarker(mean, None, "Mean="+str(round(norm,2)), Color.MAGENTA.darker()) return (norm, mean, sigma) else: p.addMarker(max_x, None, "Max="+str(round(max_x,2)), Color.GRAY) print "Invalid gaussian fit: " + str(mean) return (None, None, None) def hfit(ydata, xdata = None): """ Harmonic fit """ if xdata is None: xdata = frange(0, len(ydata), 1) max_y= max(ydata) index_max = ydata.index(max_y) max_x= xdata[index_max] start,end = min(xdata), max(xdata) (amplitude, angular_frequency, phase) = fit_harmonic(ydata, xdata) fitted_harmonic_function = HarmonicOscillator(amplitude, angular_frequency, phase) print "amplitude = ", amplitude print "angular frequency = ", angular_frequency print "phase = ", phase f = angular_frequency/ (2* math.pi) print "frequency = ", f resolution = 0.01 fit_y = [] for x in frange(start,end,resolution, True): fit_y.append(fitted_harmonic_function.value(x)) fit_x = frange(start, end+resolution, resolution) p = plot(ydata,"data", xdata, title="HFit")[0] p.addSeries(LinePlotSeries("fit")) p.getSeries(1).setData(fit_x, fit_y) #m = (phase + math.pi)/ angular_frequency m = -phase / angular_frequency if (m0: plots[0].clear() def add_convex_hull_plot(title, x,y, name=None, clear = False, x_range = None, y_range = None): plots = get_plots(title = title) p = None if len(plots)==0: p = plot(None,name=name, title = title)[0] if x_range is not None: p.getAxis(p.AxisId.X).setRange(x_range[0], x_range[1]) if y_range is not None: p.getAxis(p.AxisId.Y).setRange(y_range[0], y_range[1]) p.setLegendVisible(True) else: p = plots[0] if clear: p.clear() p.addSeries(LinePlotSeries(name)) s = p.getSeries(name) s.setLinesVisible(False) s.setPointSize(3) s.setData(to_array(x,'d') , to_array(y,'d')) p.repaint() #Convex Hull #In the first time the plot shows, it takes some time for the color to be assigned timeout = 0 while s.color is None and timeout<1000: time.sleep(0.001) timeout = timeout + 1 hull = LinePlotSeries(name + "Hull", s.color) p.addSeries(hull) #Bounding box #x1,x2,y1,y2 = min(x), max(x), min(y), max(y) #(hx,hy) = ([x1,x2, x2, x1, x1], [y1, y1, y2, y2, y1]) (hx,hy) = convex_hull(x=x, y=y) hx.append(hx[0]); hy.append(hy[0]) hull.setLineWidth(2) hull.setData(hx,hy) hull.setColor(s.color) return [hx,hy]