Startup
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@@ -1,6 +1,6 @@
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#Tue Aug 15 09:48:10 CEST 2017
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maxValue=360.0
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minValue=-360.0
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#Tue Aug 15 10:08:21 CEST 2017
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maxValue=180.0
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minValue=-180.0
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offset=0.0
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precision=3
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resolution=0.01
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@@ -1,16 +1,16 @@
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#Tue Aug 15 09:48:16 CEST 2017
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#Tue Aug 15 10:16:59 CEST 2017
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colormap=Flame
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colormapAutomatic=true
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colormapMax=173.0
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colormapMin=59.0
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colormapAutomatic=false
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colormapMax=700.0
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colormapMin=0.0
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flipHorizontally=false
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flipVertically=false
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grayscale=false
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imageHeight=2160
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imageWidth=2560
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imageHeight=1680
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imageWidth=1744
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invert=false
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regionStartX=1
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regionStartY=1
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regionStartX=433
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regionStartY=241
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rescaleFactor=1.0
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rescaleOffset=0.0
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roiHeight=-1
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@@ -21,9 +21,9 @@ rotation=0.0
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rotationCrop=false
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scale=1.0
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serverURL=localhost\:10000
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spatialCalOffsetX=-861.4939970777481
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spatialCalOffsetY=-820.4883730911062
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spatialCalScaleX=-18.90359092620482
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spatialCalScaleY=-19.37984500632817
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spatialCalOffsetX=-221.59249098828724
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spatialCalOffsetY=-211.50118443104964
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spatialCalScaleX=-26.71415910899799
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spatialCalScaleY=-27.100271628191805
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spatialCalUnits=mm
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transpose=false
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@@ -1,4 +1,4 @@
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#Mon Aug 14 14:27:21 CEST 2017
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#Tue Aug 15 09:56:35 CEST 2017
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colormap=Flame
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colormapAutomatic=true
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colormapMax=578.797
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@@ -18,9 +18,9 @@ roiY=0
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rotation=0.0
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rotationCrop=false
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scale=1.0
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spatialCalOffsetX=487.729537366548
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spatialCalOffsetY=405.94160583941607
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spatialCalScaleX=1.0
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spatialCalScaleY=1.0
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spatialCalOffsetX=-861.4939970777481
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spatialCalOffsetY=-820.4883730911062
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spatialCalScaleX=-18.90359092620482
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spatialCalScaleY=-19.37984500632817
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spatialCalUnits=mm
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transpose=false
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@@ -1,18 +1,18 @@
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import numpy as np
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def ext(x, y):
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def extremum(x, y):
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"""
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Return extremum coordinates of quadratic fit
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"""
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p = np.polyfit(x, y, 2)
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f = np.poly1d(p)
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x_fit = 1.0 #np.linspace(min(x), max(x), 100)
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#y_fit = 2.0 #f(x_fit)
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if p[0] != 0:
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x_ext = -p[1]/2/p[0]
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y_ext = f(x_ext)
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else:
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x_ext = None
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y_ext = None
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return (x_ext, y_ext, x_ext)
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x_fit = np.linspace(min(x), max(x), 100)
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y_fit = f(x_fit)
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return (x_ext, y_ext, x_fit, y_fit)
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@@ -4,10 +4,9 @@ def hfitoff(data, xdeg):
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ret = call_jep("CPython/hfitoff", "hfitoff", [to_npa(data),to_npa(xdeg)])
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return (ret[0], ret[1], ret[2],ret[3], ret[4].data, ret[5].data)
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def ext(x, y):
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ret = call_jep("CPython/ext", "ext", [to_npa(x),to_npa(y)])
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#return (ret[0], ret[1], ret[2].data, ret[3].data)
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return (ret[0], ret[1], ret[2])
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def extremum(x, y):
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ret = call_jep("CPython/extremum", "extremum", [to_npa(x),to_npa(y)])
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return (ret[0], ret[1], ret[2].data, ret[3].data)
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def gfitoff(x, y, off=None, amp=None, com=None, sigma=None):
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ret = call_jep("CPython/gfitoff", "gfitoff", [to_npa(x), to_npa(y), off, amp, com, sigma])
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@@ -1,8 +1,8 @@
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import ch.psi.pshell.epics.Positioner as Positioner
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import ch.psi.pshell.epics.ChannelDouble as ChannelDouble
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dry_run = False
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do_elog = True
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dry_run = True
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do_elog = FalseTrue
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if get_exec_pars().source == CommandSource.ui:
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station = "STEST01"
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@@ -63,7 +63,7 @@ dx = camtool.stream.getChild("x_fit_standard_deviation")
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#Creating averagers
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x_averager = create_averager(x, nb, -1) # -1 event based, waits for the next value
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dx_averager = create_averager(dx, nb, -1)
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dx_averager.monitored=True # not blocking, will return last nb values
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dx_averager.monitored = True # not blocking, will return last nb values
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#Record callback: uptate of output plot
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def after_sample(record, scan):
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@@ -93,10 +93,12 @@ save_dataset(get_exec_pars().group + "/p", p)
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save_dataset(get_exec_pars().group + "/dp", dp)
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try:
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run("CPython/wrapper")
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(ph_p_max, p_max, ph_p_fit, p_fit) = ext(ph[i_max-5:i_max+6], p[i_max-5:i_max+6])
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(ph_dp_min, dp_min, ph_dp_fit, dp_fit) = ext(ph[i_min-5:i_min+6], dp[i_min-5:i_min+6])
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#plt.getSeries(2).appendData(ph_p_fit, p_fit)
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#plt.getSeries(3).appendData(ph_dp_fit, dp_fit)
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i_max = p.index(max(p))
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i_min = dp.index(min(dp))
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(ph_p_max, p_max, ph_p_fit, p_fit) = extremum(ph[i_max-5:i_max+6], p[i_max-5:i_max+6])
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(ph_dp_min, dp_min, ph_dp_fit, dp_fit) = extremum(ph[i_min-5:i_min+6], dp[i_min-5:i_min+6])
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plt.getSeries(2).appendData(ph_p_fit, p_fit)
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plt.getSeries(3).appendData(ph_dp_fit, dp_fit)
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except:
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raise Exception("Fit failure")
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