def __init__(self): s = settings1() s.f.readout_every_n_line = 50 s.Ux.resolution = 20 s.Uy.resolution = 20 t1 = target.coarseMatrix(s.basis_dim,s.merge_dim,s.derivate_dim, s.f) t1.fill(s.f) p = plot.matrix(t1) p.heatMap("grob20") p.save("20grob", "vglGrobFein") t2 = target.fineMatrix(s.basis_dim,s.merge_dim,s.derivate_dim, s.f) t2.fill(s.f) p = plot.matrix(t2) p.heatMap("fein20") p.save("20fein", "vglGrobFein") s.Ux.resolution = 150 s.Uy.resolution = 150 t1 = target.coarseMatrix(s.basis_dim,s.merge_dim,s.derivate_dim, s.f) t1.fill(s.f) p = plot.matrix(t1) p.graph("3D") p.show() p.heatMap("grob150") p.save("150fein", "vglGrobFein") t1.interpolate("cubic") p = plot.matrix(t1) p.heatMap("grob150-int") p.save("150int_grob", "vglGrobFein") t2 = target.fineMatrix(s.basis_dim,s.merge_dim,s.derivate_dim, s.f) t2.fill(s.f) p = plot.matrix(t2) p.heatMap("fein150") p.save("150fein", "vglGrobFein") p = plot.matrix(t2, "densityMatrix") p.heatMap("fein155_dichte") p.save("150fein_density", "vglGrobFein") t2.interpolate("cubic") p = plot.matrix(t2) p.heatMap("fein150-int") p.save("150int_fein", "vglGrobFein")
def __init__(self): s = settings1() s.f.readout_every_n_line = 10 s.Ux.calc = [] s.Ux.exclude = [] #counter c = s.f.dimension("counter",None) c.setCounter(0,1/20e6) resolution = 300 #c.setCounter(0,1) #resolution = 1 c.includeChronic(resolution) #Ux.includeFromTo(-0.017, 0.01)#ausschnitt s.basis_dim = [c]# s.merge_dim = [s.Ux,s.Uy] c.setPlotRange(None,None,10) #c.setPlotOnlyRecentPosition() #s.f.readout_every_n_line = 50 #s.basis_dim.append(s.t) #s.t.resolution = 1000 t = target.coarseMatrix(s.basis_dim,s.merge_dim,s.derivate_dim, s.f) p = plot.interactive(t, fps = 20, enableAutoRange = ['x']) #t.fill(s.f) t.save("counter1", "test","bin") t.save("counter1", "test","txt")
def __init__(self): s = settings1() file_name = "50ma scharf 622ma 50µm.txt"#" s.Ux.resolution = 100 s.Uy.resolution = 100 s.f.setReadoutEverNLine(1) t = target.coarseMatrix(s.basis_dim,s.merge_dim,s.derivate_dim, s.f) t.fill(s.f) t.save("fein2", "test","bin") t.save("fein2", "test","txt")
def __init__(self): s = settings1() s.Ux.exclude = [] t = target.coarseMatrix(s.basis_dim,s.merge_dim,s.derivate_dim) t.fill(s.f) t.interpolate('cubic') p = plot.matrix(t) p.heatMap() p.show() p.save("rein", "test")
def __init__(self): s = settings1() s.basis_dim = [s.t] s.merge_dim = s.I t = target.coarseMatrix(s.basis_dim,s.merge_dim,s.derivate_dim) t.fill(s.f) t.interpolate('cubic') p = plot.matrix(t) p.graph() p.show() p.save("zweiD", "test")
def __init__(self): s = settings1() #s.Ux.resolution = 100 #s.Uy.resolution = 100 s.f.readout_every_n_line = 1 t = target.coarseMatrix(s.basis_dim,s.merge_dim,s.derivate_dim, s.f) t.fill() t.interpolate('cubic') p = plot.matPlotLib(t) #p.graph() p.heatMap() #p = plot.multiPlot(t) p.show() t.save("fein", "test","bin") t.save("fein", "test","txt")
def __init__(self): s = settings1() t = target.coarseMatrix(s.basis_dim,s.merge_dim,s.derivate_dim, s.f) t.load("fein2", "test","bin") t.transformDim() t.interpolate('cubic') dEB_types = [0.6] t.eval2dGaussianDistribution(dEB_types, 0) p = plot.matrix(t) #p = plot.multiPlot(t) p.plot() p.heatMap() p.show() p.save("dEB", "test")
def __init__(self): s = settings1() #s.f.readout_every_n_line = 50 #s.basis_dim.append(s.t) #s.t.resolution = 1000 t = target.coarseMatrix(s.basis_dim,s.merge_dim,s.derivate_dim, s.f) #t.fill(s.f) t.load("fein2", "test","bin") t.transformDim() t.interpolate('cubic') #dEB_types = [0.6] #t.eval2dGaussianDistribution(dEB_types) #p = plot.matrix(t) p = plot.multiPlot(t) p.show()
def __init__(self): s = settings4 s.f.setReadoutEverNLine(100)#(1000)##e5) s.f.setInfoEveryNLines(1000) t = target.coarseMatrix(s.basis_dim,s.merge_dim,s.derivate_dim, s.f) t.fill() #t.interpolate('cubic') #p = plot.matPlotLib(t) ##p.graph() #p.heatMap() ##p = plot.multiPlot(t) #p.show() #s.c.setPlotRange(None,None,10) #s.c.setPlotOnlyRecentPosition() #p = plot.interactive(t, fps = 20, enableAutoRange = ['x']) t.save("fein_s", "test","bin")
two = p.mergeDimension("time", "B2:B100") #two.merge = merge.mean() #basis_dim = [one] #merge_dim = [two] #derivate_dim = one#nicht impl. #s.Ux.resolution = 100 #s.Uy.resolution = 100 p.setReadoutEveryNLine = 3 t = target.coarseMatrix(p) t.fill() #t.transformDim() #t.interpolate('cubic') #t.eval2dGaussianDistribution([0.5]) p = plot.matPlotLib(t) p.graph() #p.heatMap() #p = plot.multiPlot(t) p.show() #t.save("fein", "test","bin") #t.save("fein", "test","txt")
dataType="float", ## we don't want to see the statusbar for every file, so we set: silentReadout=True ## if you want to have a message for every new file readout, set ## silentReadout to False ) ## if we dont want to do further work on the dimensions itself we dont have to ## write x = source.xDimension - just calling the method is enough f.basisDimension(name="distance",unit="m", index=0, resolution=300) f.mergeDimension(name="Temperature",unit="K",index=1) ## here comes the new part: the folders in the main 'timeFolder' will ## represent a basisDimension. trough defining index='folder' ## if you have a nested system of folders you can add further basisDimensions ## like the following. in this case the order of reference builds the folder-system f.basisDimension(name="time",unit="s",index="folder", resolution=300) ## we create a target and a GUI-instance t = target.coarseMatrix( (f) ) p = plot.Gui(t,colorTheme = "bright") ## we command diaGrabber to readout all source-files and to fill the target through: t.fill() ## we command to plot: p.plot() # the interactive readout works too: t.fillInteractive(p, fps=5)
name="Type", unit="-", cellRange="d2:d317",merge=merge.max()) bestHeight = schroeder.mergeDimension( name="best height/Schroeder", prefix="c", unit="m", cellRange="c2:c317") bestHeight.alias().append(type_max) # in contrast to prof. mueller prof. schroeder also captured the quantity of the # butterflies: quantity = schroeder.mergeDimension( name="Quantity", unit="-", cellRange="e2:e317") # now we hand over the results of Prof. Schroeder and Prof. Mueller to the target: t = target.coarseMatrix( (schroeder,mueller) ) #we create the Gui-instance p = plot.Gui(t, colorTheme = "bright") # we fill our target interactive # (later we will see the routes that both profs. have taken) t.fillInteractive(p, # ..and limit the number of readout-lines per second to 20 lps=20, # ... frames per second will be 5 fps=5, # ... and show (at first) only two merge-values show=[("best height/Schroeder",'x','y'),("best height/Mueller",'x','y')] )