198 lines
6.9 KiB
Python
198 lines
6.9 KiB
Python
#Parameters (global variables):
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# ranges: list of RangeSelection havinf args = (step_size, step_time, iterations)
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# pass_energy
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# save_scienta_image
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#
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# skip_iteration: if set to 1 then skips after end of current iteration
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from ch.psi.pshell.data.LayoutDefault import ATTR_WRITABLE_DIMENSION as ATTR_WRITABLE_DIMENSION
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import org.jfree.chart.axis.NumberAxis as NumberAxis
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cur_range = 0
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cur_iteration = 0
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if Scienta.acquisitionMode != Scienta.AcquisitionMode.Swept:
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Scienta.acquisitionMode = Scienta.AcquisitionMode.Swept
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ret=[]
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adjusted_ranges = []
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for cur_range in range(len(ranges)):
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r = ranges[cur_range]
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ar = [round(r.min / r.vars[1]) * r.vars[1], round(r.max / r.vars[1]) * r.vars[1]]
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adjusted_ranges.append(ar)
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set_exec_pars(open = True)
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#Global arguments
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Scienta.passEnergy = pass_energy
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names=[]
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names.append("Online Spectrum")
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for i in range(len(ranges)):
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names.append(str(ranges[i]))
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plots = plot(None, names)
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for p in plots[1:]:
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p.getAxis(p.AxisId.X).label = "kinetic energy"
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eb_axis = NumberAxis("binding energy")
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eb_axis.inverted = True
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jf = p.chart.plot
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jf.setDomainAxis(1, eb_axis)
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jf.getDomainAxis(1).labelPaint = jf.getDomainAxis(0).labelPaint
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jf.getDomainAxis(1).labelFont = jf.getDomainAxis(0).labelFont
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jf.getDomainAxis(1).tickLabelPaint = jf.getDomainAxis(0).tickLabelPaint
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jf.getDomainAxis(1).tickLabelFont = jf.getDomainAxis(0).tickLabelFont
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# online spectrum
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p = plots[0]
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spectrum_series = p.getSeries(0)
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spectrum_eb_axis = p.chart.plot.getDomainAxis(1)
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def plot_cur_spectrum_eb():
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"""
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plot online spectrum function for forked task.
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with binding energy scale.
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issue: this should not set the axis while the plot is zoomed!
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"""
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global spectrum_series
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global spectrum_eb_axis
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try:
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while get_context().state.running:
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y = Scienta.spectrum.take(100)
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x = Scienta.spectrumX
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spectrum_series.setData(x, y)
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# adjust the binding energy scale
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# if Eph returns an invalid number, we take energy_high as photon energy
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ephot = Eph.take(100)
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elo = Scienta.lowEnergy.take(100)
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ehi = Scienta.highEnergy.take(100)
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workfunc = 4.5
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if ephot is not float or ephot < 0.:
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ephot = ehi
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eb1 = ephot - elo - workfunc
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eb2 = ephot - ehi - workfunc
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spectrum_eb_axis.setRange(eb2, eb1)
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time.sleep(1.0)
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finally:
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print "Stopping spectrum plotting"
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def plot_cur_spectrum():
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try:
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while get_context().state.running:
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y = Scienta.spectrum.take(100)
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x = Scienta.spectrumX
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spectrum_series.setData(x, y)
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time.sleep(1.0)
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finally:
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print "Stopping spectrum plotting"
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task = None
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# measurements
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try:
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for cur_range in range(len(ranges)):
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cur_iteration = 0
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skip_iteration = False
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Scienta.lowEnergy.write(adjusted_ranges[cur_range][0])
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Scienta.highEnergy.write(adjusted_ranges[cur_range][1])
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Scienta.update()
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vars = ranges[cur_range].vars
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Scienta.stepTime.write(vars[0])
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Scienta.stepSize.write(vars[1])
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Scienta.setIterations(1)
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set_adc_averaging()
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#iterations done in script
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xdata = None
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ydata = None
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image_data = None
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task = fork(plot_cur_spectrum_eb)
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path="scan" + str(cur_range+1) + "/"
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for cur_iteration in range(vars[2]):
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p = plots[cur_range+1]
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p.setTitle(str(ranges[cur_range]) + " - iteration " + str(cur_iteration+1))
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while True:
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wait_beam()
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trig_scienta()
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spectrum_array = Scienta.spectrum.read()
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if beam_ok:
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if image_data is None:
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(_width, _height) = Scienta.getImageSize()
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break
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if ydata is None:
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ydata = spectrum_array
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else:
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for k in range (len(spectrum_array)):
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ydata[k] = ydata[k] + spectrum_array[k]
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if xdata is None:
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xdata = Scienta.spectrumX
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p.getSeries(0).setData(xdata, ydata)
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# adjust the binding energy scale
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# if Eph returns an invalid number, we take energy_high as photon energy
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eb_axis = p.chart.plot.getDomainAxis(1)
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ephot = Eph.take(100)
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elo = Scienta.lowEnergy.take(100)
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ehi = Scienta.highEnergy.take(100)
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workfunc = 4.5
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if ephot is not float or ephot < 0.:
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ephot = ehi
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eb1 = ephot - elo - workfunc
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eb2 = ephot - ehi - workfunc
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eb_axis.setRange(eb2, eb1)
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if save_scienta_image:
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image_array = Scienta.dataMatrix.read()
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if _width != len(image_array[0]) or _height != len(image_array):
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err = "Scienta image size changed during the acquisition: " + str((len(image_array[0]), len(image_array))) + " - original: " + str((_width, _height))
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print err
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log(err)
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raise Exception(err)
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if image_data is None:
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image_data = image_array
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else:
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for k in range (len(image_data)):
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for j in range (len(image_data[0])):
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image_data[k][j] = image_data[k][j] + image_array[k][j]
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if skip_iteration:
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break
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save_dataset(path + "ScientaSpectrum", ydata)
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set_attribute(path, "Iterations",cur_iteration+1)
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if save_scienta_image:
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save_dataset(path + "ScientaImage", image_data, features = {"compression":True})
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if cur_iteration==0:
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save_dataset(path + "ScientaChannels", xdata)
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set_attribute(path + "ScientaChannels", ATTR_WRITABLE_DIMENSION, 1)
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set_attribute(path, "Range Low", adjusted_ranges[cur_range][0])
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set_attribute(path, "Range High", adjusted_ranges[cur_range][1])
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set_attribute(path, "Step Time", vars[0])
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set_attribute(path, "Step Size", vars[1])
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set_attribute(path, "Pass Energy",pass_energy)
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set_attribute(path, "Readables", ["ScientaSpectrum","ScientaImage"] if save_scienta_image else ["ScientaSpectrum",])
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set_attribute(path, "Writables", ["ScientaChannels",])
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create_diag_datasets(path)
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append_diag_datasets(path)
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plots[cur_range+1].setTitle(str(ranges[cur_range]))
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ret.append((xdata, ydata))
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finally:
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cur_range = -1
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if not Scienta.isReady():
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Scienta.stop()
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Scienta.update()
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task[0].cancel(True)
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if ENDSCAN:
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after_scan()
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set_return(to_array(ret,'o')) |