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')]
)
