Beispiel #1
0
	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")
Beispiel #2
0
ramp.transform().append(Volt2m_y)
triangle.transform().append(Volt2m_x)

# for some reason we only want to take those values where the triangle moves up.
# to exclude all other values we let diaGrabber calculate the middle-difference
# of the last 3 values of the triangle-signal
# because of the simulated scan we could also only use the last value, but
# in real measurements the fluctuation of a signal can be so large that we need
# to middle our calculations in some way
triangle.calc().append(calc.delta(3))
# now we define to exclude all values where the result of the calculated values
# is less than zero:
triangle.exclude().append(exclude.calcSmallerValue(triangle.calc().get(0), 0.0))

# we give the source to our target:
t = target.fineMatrix(f)

# we initiate the graphical user interface:
p = plot.Gui(t,
	colorTheme = "bright")

# our source is relatively large, maybe we dont want to readout every line in it.
# to spare time we choose only to read every fifth line in the first run:
f.setArgs(readoutEveryNLine=5)

# we readout the source and fill the target with its values
t.fill()
# we command to plot
p.plot()
###################
######(SEE?)#######
Beispiel #3
0
	name="merge", unit="-", cellRange="F3:F600", merge=merge.max())

# the given prefix 'm' stands for milli. If you use this attribute all values
# were transformed in the readout. in this case /1000
one = ods.basisDimension(
	name="one",unit="m/s", cellRange="A3:A600", resolution=40)
two = ods.basisDimension(
	name="two", prefix="m", unit="m/s", cellRange="B3:B600", resolution=40)
three = ods.basisDimension(
	name="three", prefix="m", unit="m/s", cellRange="C3:C600", resolution=40)
four = ods.basisDimension(
	name="four", prefix="m", unit="m/s", cellRange="D3:D600", resolution=40)


# now we put the source 'ods' into the target
t = target.fineMatrix( ods )

# the command to fill the target with the values of the source
t.fill()


# to see the result we need to create a instance of plot.Gui:
p = plot.Gui(t,
	colorTheme = "bright",
	closeWhenFinished = False)
# there are many ways to individualize the Gui. You can find all possible
# attributes in the documentation of this class.


# now the command to plot:
p.plot()