pxii_bec/bec_widgets/profiles/DailySetup.ini

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+
+[profile]
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truncated
+screenshot_at=2026-10-10T20:20:15Z

pxii_bec/bec_widgets/profiles/daily_setup.ini

@@ -0,0 +1,457 @@
+[BECDockArea]
+acceptDrops=false
+accessibleDescription=
+accessibleIdentifier=
+accessibleName=
+autoFillBackground=false
+baseSize=@Size(0 0)
+contextMenuPolicy=@Variant(\0\0\0\x7f\0\0\0\x16Qt::ContextMenuPolicy\0\0\0\0\x1)
+cursor=@Variant(\0\0\0J\0\0)
+enabled=true
+focusPolicy=@Variant(\0\0\0\x7f\0\0\0\x10Qt::FocusPolicy\0\0\0\0\0)
+geometry=@Rect(0 23 1670 1505)
+inputMethodHints=@Variant(\0\0\0\x7f\0\0\0\x14Qt::InputMethodHint\0\0\0\0\0)
+layoutDirection=@Variant(\0\0\0\x7f\0\0\0\x14Qt::LayoutDirection\0\0\0\0\0)
+maximumSize=@Size(16777215 16777215)
+minimumSize=@Size(0 0)
+mode=creator
+mouseTracking=false
+sizeIncrement=@Size(0 0)
+sizePolicy=@Variant(\0\0\0K\0\0\0U)
+statusTip=
+tabletTracking=false
+toolTip=
+toolTipDuration=-1
+whatsThis=
+windowFilePath=
+windowModality=@Variant(\0\0\0\x7f\0\0\0\x13Qt::WindowModality\0\0\0\0\0)
+windowModified=false
+windowOpacity=1
+windowTitle=BEC - TestLayout4
+workspace_is_locked=false
+
+[BECDockArea.ads%3A%3ACDockManager.ads%3A%3ACDockSplitter.ads%3A%3ACDockSplitter.ads%3A%3ACDockAreaWidget.Info.dockWidgetScrollArea.qt_scrollarea_viewport.Info]
+acceptDrops=false
+accessibleDescription=
+accessibleIdentifier=
+accessibleName=
+autoFillBackground=true
+baseSize=@Size(0 0)
+contextMenuPolicy=@Variant(\0\0\0\x7f\0\0\0\x16Qt::ContextMenuPolicy\0\0\0\0\x1)
+cursor=@Variant(\0\0\0J\0\0)
+enabled=true
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pxii_bec/daily_setup_files/.~lock.daily_beamline_health.csv#

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pxii_bec/daily_setup_files/daily_beamline_health.csv

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pxii_bec/daily_setup_files/weekly_beamline_health.csv

@@ -0,0 +1,21 @@
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pxii_bec/daily_setup_files/weekly_beamline_health2.csv

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+2026-09-30T11:04:59,12400.034824637,5.30728340148926,-0.041712079687562,0.140038499999999,0.873851000000002,0.102714193725642,0.152251956176556,0.22052,-0.64071,0.01188100007843,-0.012323516377797,0.013475582102897,-0.002578973845116,-0.042749327098526,-0.061238705041222,,
+2026-09-30T11:39:23,12400,5.307,-0.042,0.140108499999998,0.873990000000001,0.102007521057185,0.152334925842084,0.22002,-0.64121,0.0135,-0.0108,0.0095,0.000379,-0.0371,-0.0659,5.64,-1.65
+2026-09-30T11:45:21,12400,5.307,-0.0417,0.14,0.874,0.102,0.152,0.224,-0.639,0.014,-0.0129,0.0118,-0.0001,-0.0399,-0.0652,6.1,-1.63

pxii_bec/device_configs/pxii-devices.yaml

@@ -55,8 +55,8 @@ aerotech:
   deviceConfig:
     prefix: http://mx-x10sa-queue-01:5234
   deviceTags:
-  - motors
   - aerotech
+  - motors
   enabled: true
   onFailure: buffer
   readoutPriority: baseline
@@ -65,15 +65,15 @@ aerotech:
       mount: 0
       work: 0
     x:
-      in: -8.1e-06
+      in: 0.05999735
       out: -10
       safe: -50
     y:
       mount: -0.0
-      work: -0.02600108
+      work: -0.03099898
     z:
       mount: 0
-      work: -0.00900383
+      work: -0.0090031
 bcu_bpm1:
   description: BCU BPM Channel 1
   deviceClass: ophyd.EpicsSignalRO
@@ -302,7 +302,7 @@ bs_x:
   onFailure: buffer
   readoutPriority: baseline
   userParameter:
-    in: 0.39119736
+    in: 0.44000227
 bs_y:
   description: Beamstop Y
   deviceClass: ophyd_devices.EpicsMotor
@@ -314,7 +314,7 @@ bs_y:
   onFailure: buffer
   readoutPriority: baseline
   userParameter:
-    in: 0.76699895
+    in: -3.3000017
 bs_z:
   description: Beamstop Z
   deviceClass: ophyd_devices.EpicsMotor
@@ -330,7 +330,7 @@ bs_z:
     max_blout: 70
     min: 13
     safe: 45.1
-    samp: 16.408
+    samp: 16.80557617
     type: continuous
     work_min: 20
 bsf_f1_y:
@@ -444,7 +444,7 @@ coll_x:
   onFailure: buffer
   readoutPriority: baseline
   userParameter:
-    in: 0.67471002
+    in: 0.68249115
 coll_y:
   description: Collimator Y
   deviceClass: ophyd_devices.EpicsMotor
@@ -456,7 +456,7 @@ coll_y:
   onFailure: buffer
   readoutPriority: baseline
   userParameter:
-    in: 39.02
+    in: 39.01884961
     intermediate: 32
     out: 20.002
     park: 1
@@ -560,6 +560,8 @@ dcm_pitch:
   enabled: true
   onFailure: buffer
   readoutPriority: baseline
+  userParameter:
+    offset: 0
 dcm_x:
   description: DCM Lateral
   deviceClass: ophyd_devices.EpicsMotorEC
@@ -1310,6 +1312,17 @@ samcam_sigma:
   onFailure: buffer
   readOnly: true
   readoutPriority: monitored
+samcam_thresh:
+  description: Sample Camera Threshold
+  deviceClass: ophyd.EpicsSignal
+  deviceConfig:
+    auto_monitor: true
+    read_pv: X10SA-ES-MS:Stats5:CentroidThreshold
+  deviceTags:
+  - scam
+  enabled: true
+  onFailure: buffer
+  readoutPriority: baseline
 samcam_x:
   description: Sample Camera X
   deviceClass: ophyd.EpicsSignalRO
@@ -1322,6 +1335,29 @@ samcam_x:
   onFailure: buffer
   readOnly: true
   readoutPriority: monitored
+samcam_xcurs:
+  description: Sample Camera X Cursor
+  deviceClass: ophyd.EpicsSignal
+  deviceConfig:
+    auto_monitor: true
+    read_pv: X10SA-ES-MS:Stats5:CursorX
+  deviceTags:
+  - scam
+  enabled: true
+  onFailure: buffer
+  readoutPriority: baseline
+samcam_xcursprof:
+  description: Sample Camera X Cursor Profile
+  deviceClass: ophyd.EpicsSignalRO
+  deviceConfig:
+    auto_monitor: true
+    read_pv: X10SA-ES-MS:Stats5:ProfileCursorX_RBV
+  deviceTags:
+  - scam
+  enabled: true
+  onFailure: buffer
+  readOnly: true
+  readoutPriority: monitored
 samcam_xsig:
   description: Sample Camera X Sigma
   deviceClass: ophyd.EpicsSignalRO
@@ -1346,6 +1382,18 @@ samcam_y:
   onFailure: buffer
   readOnly: true
   readoutPriority: monitored
+samcam_ycursprof:
+  description: Sample Camera Y Cursor Profile
+  deviceClass: ophyd.EpicsSignalRO
+  deviceConfig:
+    auto_monitor: true
+    read_pv: X10SA-ES-MS:Stats5:ProfileCursorY_RBV
+  deviceTags:
+  - scam
+  enabled: true
+  onFailure: buffer
+  readOnly: true
+  readoutPriority: monitored
 samcam_ysig:
   description: Sample Camera Y Sigma
   deviceClass: ophyd.EpicsSignalRO
@@ -1723,7 +1771,6 @@ transm:
   deviceClass: ophyd_devices.EpicsSignal
   deviceConfig:
     read_pv: X10SA-ES-SSFI:TRANSM-SET
-    write_pv: X10SA-ES-SSFI:TRANSM-SET
   deviceTags:
   - transm
   enabled: true

pxii_bec/macros/EvalFlux.py

@@ -2,68 +2,71 @@ def evalflux():
 
     from APscripts import read_data_csv, fitpoly
 
-    data=read_data_csv('FLUX_x10sa_20260709_174259.txt')
-
-    einv=data[:, 0]
-    fcalfinv = data[:, 6] # if energy top down
+    data = read_data_csv("FLUX_x10sa_20260709_174259.txt")
 
+    einv = data[:, 0]
+    fcalfinv = data[:, 6]  # if energy top down
 
     e = einv[::-1]
     flcf = fcalfinv[::-1]
 
     # omit the last values (>= 27 keV)
 
-    len(e) # = 25
+    len(e)  # = 25
     e = e[0:21]
-    flcf =flcf[0:21]/1.e9 ## divide by 1e9 for better readability
+    flcf = flcf[0:21] / 1.0e9  ## divide by 1e9 for better readability
 
     fitpoly(e, flcf, 3)
 
     # Polynomial coefficients of the fit fct:  3 [-0.00026213  0.01171065 -0.05379571  0.04478851]
 
 
-def csplinex(x,y,en):
+def csplinex(x, y, en):
     from scipy.interpolate import CubicSpline
 
     # Create spline
     cs = CubicSpline(x, y)
-    y_cs = cs(en) 
+    y_cs = cs(en)
     return y_cs
 
-    
+
 def flux_bcu():
-    e = get_current_energy()/1000.
-    bcusum = read_av(dev.bcu_bpmsum,10)
-    flux = fl_bcubpm(e,bcusum)
-    return f"{flux:.2e}"  
-    
+    e = get_current_energy() / 1000.0
+    bcusum = read_av(dev.bcu_bpmsum, 10)
+    flux = fl_bcubpm(e, bcusum)
+    return f"{flux:.2e}"
+
+
 def flux_i1():
-    e = get_current_energy()/1000
-    i1 = read_av(dev.i1,10)
+    e = get_current_energy() / 1000
+    i1 = read_av(dev.i1, 10)
     flux = fl_i1(e, i1)
-    return f"{flux:.2e}"  
-    
-def fl_bcubpm(e,bcusum):
-    import numpy as np    
-    fact = 1.e9 
-    coeff = [-0.00026213,  0.01171065, -0.05379571,  0.04478851]
-    if e > 24 :
-        coeff = [4.83704287e-05, -3.17174523e-03,  7.33131161e-02, -5.91926617e-01, 1.66572494e+00]
+    return f"{flux:.2e}"
+
+
+def fl_bcubpm(e, bcusum):
+    import numpy as np
+
+    fact = 1.0e9
+    coeff = [-0.00026213, 0.01171065, -0.05379571, 0.04478851]
+    if e > 24:
+        coeff = [4.83704287e-05, -3.17174523e-03, 7.33131161e-02, -5.91926617e-01, 1.66572494e00]
     polynomial = np.poly1d(coeff)
     fl = polynomial(e) * bcusum * fact
-    #print(f'flux from {bcusum} with en {e} is {fl:.2e} ph/s')
-    
-    return fl 
-    
-def fl_i1(e,i1):
+    # print(f'flux from {bcusum} with en {e} is {fl:.2e} ph/s')
+
+    return fl
+
+
+def fl_i1(e, i1):
     import pandas as pd
 
     file = "luts/I1flcalf.csv"
-    df = pd.read_csv(file)  
+    df = pd.read_csv(file)
     a = df["En"]
     b = df["Fl/I1"]
-    
-    fl_i1 =  csplinex(a,b,e) *i1 
-    print(f'flux from {i1} with en {e} is {fl_i1:.2} ph/s ')
+
+    fl_i1 = csplinex(a, b, e) * i1
+    print(f"flux from {i1} with en {e} is {fl_i1:.2} ph/s ")
 
     return fl_i1

pxii_bec/macros/KB_Class.py

@@ -13,10 +13,12 @@ class KBMirror:
             self.P2 = 0.583490
             self.P3 = -0.372950
             self.L1 = -0.955798
-            self.curv_approx_fact =  0.9550 # 0.9550 # origin: 1.0121 
-            self.s1 = 24.15   
+            self.curv_approx_fact = 0.9550  # 0.9550 # origin: 1.0121
+            self.s1 = 24.15
             self.s2 = 1.45
-            self.asym0 = 0.114 ## origin: 0.0.08  + 0.034  # user asymm, eg 0.4750, will be added ( - sign) 
+            self.asym0 = (
+                0.114  ## origin: 0.0.08  + 0.034  # user asymm, eg 0.4750, will be added ( - sign)
+            )
 
         elif self.mirror_type == "PXII_HFM":
             self.C0 = 0.060453
@@ -24,10 +26,12 @@ class KBMirror:
             self.P2 = 0.586057
             self.P3 = -0.088093
             self.L1 = -0.999445
-            self.curv_approx_fact = 0.8810   # origin: # 0.995 
-            self.s1 = 24.90   
+            self.curv_approx_fact = 0.8810  # origin: # 0.995
+            self.s1 = 24.90
             self.s2 = 0.7
-            self.asym0 = 0.06455    ## origin: -0.0107 + 0.07525          # added user asymm 2.75 (-sign)  
+            self.asym0 = (
+                0.06455  ## origin: -0.0107 + 0.07525          # added user asymm 2.75 (-sign)
+            )
 
         else:
             raise ValueError(f"Unknown mirror type: {self.mirror_type}")
@@ -59,7 +63,7 @@ class KBMirror:
         return s2, R
 
     def get_benders(self, th=3.0, defocus_mm=0.0, user_asymmetry=0.0):
-        asym = self.asym0 - user_asymmetry #### sign is important! 
+        asym = self.asym0 - user_asymmetry  #### sign is important!
         s2_target = self.s2 + defocus_mm / 1000
         curv = self.ellipse_to_curvature(s2_target, th)
         BU, BD = self.curvature_to_bend(curv, asym)
@@ -69,16 +73,12 @@ class KBMirror:
         curv, asym = self.bend_to_curvature(BU, BD)
         s2_rb, R0 = self.curvature_to_ellipse(curv, th)
         defocus_mm = (s2_rb - self.s2) * 1000
-        bend_rad_m = 1/curv *1000
+        bend_rad_m = 1 / curv * 1000
         return {
             "curvature": curv,
-            "bend_rad_m":  bend_rad_m,
-            "bend_rad0_m":  R0,
+            "bend_rad_m": bend_rad_m,
+            "bend_rad0_m": R0,
             "asymmetry": asym,
             "s2": s2_rb,
-            "defocus_mm": defocus_mm
+            "defocus_mm": defocus_mm,
         }
-
-
-
-    

pxii_bec/macros/Undu_Helpers.py

@@ -45,8 +45,40 @@ def exponential_func2(x, a, b, c, d):
 
 ##################################
 
-
+# #####  Sept 2026 Data ######################################
 def return_harmon():
+    # from 3rd to 19th Energy range from 6 keV to 30 keV
+    # harmonics, Sept 2026
+    import numpy as np
+
+    nharm = 19
+    h = [np.array([]) for _ in range(nharm + 1)]
+    h[0] = np.array([0])
+    h[1] = np.array([0])
+    h[2] = np.array([0])
+    h[3] = np.array([0.095, -0.276, 4.154])  # 3rd harmon
+    h[4] = np.array([0.00692593, -0.131504, 1.45763, -0.864603])
+    h[5] = np.array([0.00269444 , - 0.0616905 , 0.967925,  - 0.295405])
+    h[6] = np.array([ 0.00248148 , - 0.0767908 , 1.2178 , - 1.91516  ])
+    h[7] = np.array([0.00110017 , - 0.0369968 , 0.77334 ,- 0.688198  ])
+    h[8] = np.array([0.000643939 , - 0.0226645 , 0.570453 , - 0.0479048  ])
+    h[9] = np.array([0.00021633 , -0.00619517  , 0.315392 , 0.971667  ])
+    h[10] = np.array([ 0.000708236 , - 0.0357576 , 0.851686 - 2.48765  ])
+    h[11] = np.array([ 0.000589549 , -0.0328631 , 0.837705 , - 2.90326 ])
+    h[12] = np.array([ 0.00218182 , 0.1212 , 1.74739 ])
+    h[13] = np.array([ 0.197702, 0.757869 ])
+    h[14] = np.array([ 0.183733, 0.762778 ])
+    h[15] = np.array([ 0.170381, 0.783155 ])
+    h[16] = np.array([ 0.157321,  0.850464 ])
+    h[17] = np.array([0.1466, 0.8906  ])
+    h[18] = np.array([0.1362, 0.9538  ])
+    h[19] = np.array([0.128, 0.985 ])
+
+
+    return h
+
+# #####  July 2025 Data ######################################
+def return_harmon_old():
     # from 3rd to 21th Energy range from 6 keV to 30 keV
     # harmonics, July 2025
     import numpy as np
@@ -97,7 +129,7 @@ def plot_harmon(e_start, e_end, h_no, pr_out=False):
     plt.show()
 
 
-def setu19(en, *harm_no, detune=0):
+def setu19(en, *harm_no, detune=0, simul = 0, iexp = 0):
     """
     set the U19 to the gaps defined in Jul2025, or the "theoretical" ones for higher
     harmonics
@@ -106,32 +138,43 @@ def setu19(en, *harm_no, detune=0):
     en in keV, possibly select a special harmonics, or detune [0/1] to a value
     with a nicer beam shape but less flux
     """
-    g0 = dev.id_gap.readback.get()
-
-    fitpar_u19 = np.array([2.17078531, 0.519452, -0.00720255])  # measured from U19
+    if not simul:
+        g0 = dev.id_gap.readback.get()
 
+    #fitpar_u19 = np.array([2.17078531, 0.519452, -0.00720255])  # measured from U19
+    fitpar_u19 = np.array([ 2.22322523,  0.50396248, -0.00783873]) # measured from U19, Sept2026
+    
     h_all = return_harmon()
     # dep on energy -> select harmonics
     if harm_no:
         harm = int(harm_no[0])
+
         print("Selected harmonics is:", harm)
 
     else:
         print("Using the default optimised harmonics")
         if en <= 7:
             harm = 3  #   h = h[3]
-        elif 7 < en <= 10:
+        elif 7 < en <= 10.5:
             harm = 5
-        elif 10 < en <= 13:
+        elif 10.5 < en < 13:
             harm = 7
-        elif 13 < en <= 16:
+        elif 13 <= en <= 16.5:
             harm = 9
-        elif 16 < en <= 19:
+        elif 16.5 < en <= 19.5:
             harm = 11
-        elif 19 < en <= 22:
+        elif 19.5 < en <= 22.5: 
             harm = 13
+        elif 22.5 < en <= 25.5: ## 22 
+            harm = 15
+        elif 25.5 < en <= 28.5: ## 22 
+            harm = 17
+        elif 28.5 < en <= 30: ## 22 
+            harm = 19
+            
+            
 
-    if en <= 22:
+    if (en <= 30 and harm <=19):
         h = h_all[harm]
         print(f"harmonics is {harm}.")
 
@@ -146,32 +189,33 @@ def setu19(en, *harm_no, detune=0):
     # 29: 15, 17, 19
     # 30: 19
     ##
-    if 23 < en <= 25:
-        n = 15
+    if (iexp and harm_no):
+        harm_selected = int(harm_no[0])
+        print("Selected harmonics is:", harm_selected)
+        n= harm_selected
         enorm = en / n
         g = exponential_func0(enorm, fitpar_u19[0], fitpar_u19[1], fitpar_u19[2])
-    elif 25 < en <= 29:
-        n = 17
-        enorm = en / n
-        g = exponential_func0(enorm, fitpar_u19[0], fitpar_u19[1], fitpar_u19[2])
-    elif 29 < en:
-        n = 19
+    elif (iexp):    
+        n = harm  # default for that energy range, as set before 
         enorm = en / n
+        print('exp fct fit used')
         g = exponential_func0(enorm, fitpar_u19[0], fitpar_u19[1], fitpar_u19[2])
 
-    print("Undulator has been ", g0, " mm")
-    if 4.5 <= g <= 20:
-        print("Moving Undulator gap to ", g, " mm")
-    else:
-        print("not a valid gap, do nothing")
+        
+    if not simul:
+        print("Undulator has been ", g0, " mm")
+        if 4.5 <= g <= 20:
+            print("Moving Undulator gap to ", g, " mm")
+        else:
+            print("not a valid gap, do nothing")
 
-    if detune:
-        g = g * 0.996
-        print("moving to detuned gap value, slightly below max, about 0.15 % ")
+        if detune:
+            g = g * 0.996
+            print("moving to detuned gap value, slightly below max, about 0.15 % ")
     # print("move disabled!!")
-    res = scans.umv(dev.id_gap, g, relative=False)
+        scans.umv(dev.id_gap, g, relative=False)
 
-    return
+    return round(g,4) 
 
 
 ##################################
@@ -192,7 +236,8 @@ def harmon_walk(estart=7.5, end_en=13):
 
 ##################################
 def gap_harm(e=12.4):
-    fitpar_u19 = np.array([2.17078531, 0.519452, -0.00720255])
+    # old values fitpar_u19 = np.array([2.17078531, 0.519452, -0.00720255])
+    fitpar_u19 = np.array([2.22322523,  0.50396248, -0.00783873]) 
     fitpar_u17 = np.array([2.17078572, 0.46477267, -0.005766])
     e = float(input("Please enter an energy between 6 and 30: "))
 
@@ -305,9 +350,26 @@ def long_gscan(estart=6, end_en=30.5, g_low=4.5, g_high=9.0, nsteps=1000, sett =
     
     return
 
+def plottest(wname):
+    #wname="GapScan" 
+    existing_docks = bec.gui.windows
+    if existing_docks.get(wname) is None:
+        dock_area = bec.gui.new(name=wname, geometry = [4000, 900, 700, 700])
+        wr = dock_area.new(bec.gui.available_widgets.Waveform, object_name="Plot")
+        mot = dev.id_gap
+        det = dev.lu_bpmsum
+    else:
+        dock_area = open_docks[wname]
+        wr=  dock_area.Plot
+        wr.plot(device_x=mot, device_y=det)  ## names first !
+    # wr.plot(x=mot.name,y=det.name)           ### this comes later
+    wr.x_label = mot.name
+    wr.y_label = det.name
+
+
 
 ##################################
-def gscan(centre=0, gomax=0, detune=0,sett=1):
+def gscan(deltag = 0.05,centre=0, gomax=0, detune=0,sett=1, silent=0, iplot=1, isave=0):
     """
     Scan the ID GAP and go
     to the max of lu_bpm intensity
@@ -319,34 +381,58 @@ def gscan(centre=0, gomax=0, detune=0,sett=1):
     """
     import time
 
-    dock_area = bec.gui.new(name="GapScan", geometry = [4000, 900, 700, 700])
-    wr = dock_area.new(bec.gui.available_widgets.Waveform)
+    wname="GapScan"
+    
     mot = dev.id_gap
-    det = dev.lu_bpmsum
+    det = dev.lu_bpmsum    
+ 
+    existing_docks = bec.gui.windows
+    if existing_docks.get(wname) is None:
+        dock_area = bec.gui.new(name=wname, geometry = [4000, 900, 700, 700])
+        wr = dock_area.new(bec.gui.available_widgets.Waveform, object_name="Plot")
+    else:
+        dock_area = existing_docks[wname]
+        wr=  dock_area.Plot
+        wr.clear_all()
     wr.plot(device_x=mot, device_y=det)  ## names first !
     # wr.plot(x=mot.name,y=det.name)           ### this comes later
     wr.x_label = mot.name
     wr.y_label = det.name
 
     g0 = dev.id_gap.readback.get()
-    deltag = 0.05
+    #deltag = 0.05
     steps = 30
     resol = 2*deltag/steps
+    if resol < 0.002:
+        resol = 0.003
+        steps = round(2*deltag/resol)
+        
+    start=-deltag
+    stop = deltag
     print(f"Gap resol is {resol} mm ")
-    
-    ds = scans.line_scan(dev.id_gap, -deltag, deltag, steps=steps,  settling_time=sett,exp_time=0.5, relative=True)
+    if (g0-deltag < 4.5):
+        start=g0-4.5 
+    ds = scans.line_scan(dev.id_gap, start, stop, steps=steps,  settling_time=sett,exp_time=0.1, relative=True)
     gap_data = ds.scan.live_data.id_gap.id_gap.val
     bpm_data = ds.scan.live_data.lu_bpmsum.lu_bpmsum.val
     
     gap_data=np.array(gap_data)
     bpm_data = np.array(bpm_data)
-    
+
+    if isave:
+        en = round(getenergy())
+        dirname = "/sls/x10sa/config/commissioning/Data/GapsFE_0p3/" 
+        combined = np.column_stack((gap_data, bpm_data))
+        filename = dirname + "gap" + str(en)+"_"+str(g0*100)[0:3]+ ".txt"
+        with open(filename, "w") as f:
+            np.savetxt(f, combined, delimiter=",", fmt="%5f")
+        
 
     maxy = max(bpm_data)
     indmax = np.argmax(bpm_data)
-    gm = gap_data[indmax]
+    gmax = gap_data[indmax]
 
-    gcen, xm = fit_plot(gap_data, bpm_data, model="voigt")
+    gcen, xm = fit_plot(gap_data, bpm_data, tmodel="voigt", silent=silent, iplot=iplot)
 
     if gomax:
         gm = xm
@@ -354,6 +440,8 @@ def gscan(centre=0, gomax=0, detune=0,sett=1):
         gm = gcen
 
     print("gap off by ", g0 - gm, " mm")
+
+    print(f"gcen = {gcen}, gmax = {xm} or {gmax}")
     if detune:
         gm = gm * 0.996
         print("moving to detuned gap value, slightly (0.15 %) below max")
@@ -366,4 +454,31 @@ def gscan(centre=0, gomax=0, detune=0,sett=1):
         else:
             print("Fit too far off, try using option gomax=1")
 
-    return
+    return gm, xm 
+
+##################################
+
+def bfield_x10sa(gap):
+    if gap < 4.5 or gap > 20:
+        print("no valid gap!") 
+        return
+
+    ### values for the U19
+    l_u = 19
+    a = 3.22482942
+    b = -0.30100054
+    c = 0.00808649
+    
+    b0 = exponential_func0(gap, a,b,c )
+    b0= round(b0,4)
+    # K  =  e/mc * l_u/2pi * B
+    k = round(0.0934 *l_u * b0,2)
+    
+    print(f'### X10SA and U19 ###  ')   
+    print(f'for a gap of {gap} mm : ')   
+    print(f'B0 = {b0}')
+    print(f'K = {k}')
+    
+    return b0, k
+
+##################################

pxii_bec/macros/analyse_luts.py

@@ -0,0 +1,645 @@
+"""Analyse LUT data to determine fits for DCM and undulator parameters."""
+
+import numpy as np
+import pandas as pd
+import matplotlib.pyplot as plt
+from scipy.signal import savgol_filter
+
+from pxii_bec.scripts import beamline_context as bl
+
+
+
+def get_data(filename):
+    """Open the raw DCM calibration data file."""
+
+    filename = bl.env.lut_dir / f"{filename}"
+
+    return pd.read_csv(filename)
+
+
+def format_polynomial(fit):
+    """Return polynomial coefficients as a readable equation string."""
+
+    terms = []
+    order = len(fit) - 1
+
+    for i, coeff in enumerate(fit):
+        power = order - i
+
+        if power > 1:
+            term = f"{coeff:+.3e} x^{power}"
+        elif power == 1:
+            term = f"{coeff:+.3e} x"
+        else:
+            term = f"{coeff:+.4f}"
+
+        terms.append(term)
+
+    return " ".join(terms).lstrip("+")
+
+
+def plot_lut(
+    ax,
+    arr,
+    fit_order,
+    xname=None,
+    yname=None,
+    title=None,
+    show_equation=True,
+):
+    """
+    Fit LUT data and draw the data and fit onto an existing axes.
+
+    Parameters
+    ----------
+    ax : matplotlib.axes.Axes
+        Axes on which to draw the plot.
+    arr : numpy.ndarray
+        Two-column array containing x and y data.
+    fit_order : int
+        Polynomial order to fit.
+    xname : str, optional
+        X-axis label.
+    yname : str, optional
+        Y-axis label.
+    title : str, optional
+        Plot title.
+    show_equation : bool, optional
+        Display the fitted polynomial on the plot.
+
+    Returns
+    -------
+    numpy.ndarray
+        Polynomial coefficients.
+    """
+
+    x = arr[:, 0]
+    y = arr[:, 1]
+
+    fit = np.polyfit(x, y, fit_order)
+    p = np.poly1d(fit)
+
+    x_range = np.linspace(x.min(), x.max(), 100)
+
+    ax.scatter(
+        x,
+        y,
+        label="Data",
+        color="rebeccapurple",
+    )
+
+    ax.plot(
+        x_range,
+        p(x_range),
+        label="Polynomial fit",
+        color="lightcoral",
+    )
+
+    if xname is not None:
+        ax.set_xlabel(xname)
+
+    if yname is not None:
+        ax.set_ylabel(yname)
+
+    if title is not None:
+        ax.set_title(title)
+
+    if show_equation:
+        equation = format_polynomial(fit)
+
+        ax.text(
+            0.02,
+            0.02,
+            equation,
+            transform=ax.transAxes,
+            fontsize=9,
+            verticalalignment="bottom",
+            bbox=dict(
+                boxstyle="round",
+                facecolor="whitesmoke",
+                edgecolor="lightgray",
+                alpha=0.8,
+            ),
+        )
+
+    return fit
+
+
+def lut_plot(
+    arr,
+    xname,
+    yname,
+    title,
+    fit_order,
+    save=False,
+):
+    """
+    Create a standalone LUT plot.
+
+    This is useful for calibration plots such as DCM pitch where only
+    one fit is required.
+    """
+
+    savefile = bl.env.lut_dir / f"{title}.png"
+
+    fig, ax = plt.subplots()
+
+    fit = plot_lut(
+        ax,
+        arr,
+        fit_order,
+        xname=xname,
+        yname=yname,
+        title=title,
+        show_equation=True,
+    )
+
+    ax.legend(fontsize=9)
+
+    fig.tight_layout()
+
+    if save:
+        fig.savefig(savefile, bbox_inches="tight")
+        plt.close(fig)
+    else:
+        plt.show()
+
+    print(np.poly1d(fit))
+
+    return fit
+
+def pitch_analysis(filename, save=False):
+    """Compare DCM pitch calibration against energy and Bragg angle."""
+
+    df = get_data(filename)
+
+    fits = {}
+
+    for xname, fit_order in [("energy", 4), ("bragg", 2)]:
+
+        x = df[xname].to_numpy()
+        pitch = df["pitch"].to_numpy()
+
+        fit = lut_plot(
+            df[[xname, "pitch"]].to_numpy(),
+            xname="Energy" if xname == "energy" else "Bragg angle",
+            yname="pitch",
+            title=f"DCM_Pitch_Calibration_{xname}",
+            fit_order=fit_order,
+            save=save,
+        )
+
+        # Calculate residuals
+        fitted_pitch = np.polyval(fit, x)
+        residuals = pitch - fitted_pitch
+
+        rms = np.sqrt(np.mean(residuals**2))
+        max_residual = np.max(np.abs(residuals))
+
+        print(f"\n{xname.capitalize()} fit (order {fit_order})")
+        print(f"RMS residual: {rms:.6g}")
+        print(f"Max residual: {max_residual:.6g}")
+
+        for xi, residual in zip(x, residuals):
+            print(f"  {xi:10.3f}: {residual:+.6g}")
+
+        fits[xname] = {
+            "fit": fit,
+            "residuals": residuals,
+            "rms": rms,
+            "max_residual": max_residual,
+        }
+
+    return fits
+
+def pitch_analysis_bragg(filename, fit_order=2, save=False):
+    """Fit and plot the DCM pitch calibration."""
+
+    df = get_data(filename)
+
+    pitch = df[["bragg", "pitch"]]
+
+    fit = lut_plot(
+        pitch.to_numpy(),
+        xname="Bragg angle",
+        yname="pitch",
+        title="DCM_Pitch_Calibration",
+        fit_order=fit_order,
+        save=save,
+    )
+
+    return fit
+
+def pitch_analysis_energy(filename, fit_order=3, save=False):
+    """Fit and plot the DCM pitch calibration."""
+
+    df = get_data(filename)
+
+    pitch = df[["energy", "pitch"]]
+
+    fit = lut_plot(
+        pitch.to_numpy(),
+        xname="energy",
+        yname="pitch",
+        title="DCM_Pitch_Calibration",
+        fit_order=fit_order,
+        save=save,
+    )
+
+    return fit
+
+def ge_edge_analysis(filename, save=False):
+    """
+    Analyse a Ge K-edge scan.
+
+    Finds the approximate absorption edge from the largest negative
+    derivative of the BCU BPM sum signal.
+
+    Parameters
+    ----------
+    filename : str
+        CSV filename without the .csv extension.
+    save : bool, optional
+        Save the plots to the LUT directory instead of displaying them.
+
+    Returns
+    -------
+    dict
+        Measured edge energy, expected edge energy, energy offset,
+        and derivative data.
+    """
+
+    # Known Ge K absorption edge
+    expected_edge = 11103.1  # eV
+
+    df = get_data(filename)
+
+    energy = df["Energy"].to_numpy()
+    signal1 = df["bcu_bpmsum"].to_numpy()
+    signal = df["transmission"].to_numpy()
+
+    # ----------------------------------------------------------
+    # Calculate derivative
+    # ----------------------------------------------------------
+    # smooth_signal = savgol_filter(
+    #     signal,
+    #     window_length=11,
+    #     polyorder=2,
+    # )
+    # derivative = np.gradient(smooth_signal, energy)
+
+    derivative = np.gradient(signal, energy)
+
+    # Ge absorption causes the BPM signal to fall, so locate
+    # the strongest negative derivative.
+    edge_idx = np.argmin(derivative)
+
+    measured_edge = energy[edge_idx]
+    edge_derivative = derivative[edge_idx]
+
+    energy_offset = expected_edge - measured_edge
+
+    # ----------------------------------------------------------
+    # Print results
+    # ----------------------------------------------------------
+
+    print()
+    print("Ge K-edge analysis")
+    print("------------------")
+    print(f"Expected edge:  {expected_edge:.2f} eV")
+    print(f"Measured edge:  {measured_edge:.2f} eV")
+    print(f"Energy offset:  {energy_offset:+.2f} eV")
+    print()
+
+    # ----------------------------------------------------------
+    # Plot BPM signal
+    # ----------------------------------------------------------
+
+    fig1, ax1 = plt.subplots()
+
+    ax1.plot(
+        energy,
+        signal,
+        "o-",
+        markersize=4,
+        label="Data",
+    )
+
+    # ax1.plot(
+    #     energy,
+    #     smooth_signal,
+    #     "-",
+    #     label="Smoothed",
+    # )
+
+    ax1.axvline(
+        measured_edge,
+        linestyle="--",
+        label=f"Measured edge: {measured_edge:.2f} eV",
+    )
+    if energy.min() <= expected_edge <= energy.max():
+        ax1.axvline(
+            expected_edge,
+            linestyle=":",
+            label=f"Expected edge: {expected_edge:.1f} eV",
+        )
+
+    ax1.set_xlabel("Energy (eV)")
+    ax1.set_ylabel("Transmission (BCU BPM / SS BPM)")
+    ax1.set_title("Ge K-edge scan")
+    ax1.legend()
+
+    fig1.tight_layout()
+
+    # ----------------------------------------------------------
+    # Plot derivative
+    # ----------------------------------------------------------
+
+    fig2, ax2 = plt.subplots()
+
+    ax2.plot(
+        energy,
+        derivative,
+        "o-",
+        markersize=4,
+    )
+
+    ax2.plot(
+        measured_edge,
+        edge_derivative,
+        "o",
+        markersize=8,
+        label=f"Edge: {measured_edge:.2f} eV",
+    )
+
+    ax2.axvline(
+        measured_edge,
+        linestyle="--",
+    )
+
+    ax2.set_xlabel("Energy (eV)")
+    ax2.set_ylabel("d(Transmission) / dE")
+    ax2.set_title("Ge K-edge derivative")
+    ax2.legend()
+
+    fig2.tight_layout()
+
+    # ----------------------------------------------------------
+    # Save or display
+    # ----------------------------------------------------------
+
+    if save:
+        signal_file = bl.env.daily_setup_dir / "Ge_edge_signal.png"
+        derivative_file = bl.env.daily_setup_dir / "Ge_edge_derivative.png"
+
+        fig1.savefig(signal_file, bbox_inches="tight", dpi=150)
+        fig2.savefig(derivative_file, bbox_inches="tight", dpi=150)
+
+        plt.close(fig1)
+        plt.close(fig2)
+
+        print(f"Saved: {signal_file}")
+        print(f"Saved: {derivative_file}")
+
+    else:
+        plt.show()
+
+    return {
+        "expected_edge": expected_edge,
+        "measured_edge": measured_edge,
+        "energy_offset": energy_offset,
+        "signal_png": signal_file,
+        "derivative_png": derivative_file,
+    }
+
+def perp_analysis(filename):
+    """Select the DCM perpendicular translation calibration data."""
+
+    df = get_data(filename)
+    sel = df[['energy','dcm_perp', 'xi_cam_x']]
+    savefile = bl.env.lut_dir / "perp_actual_calc.csv"
+    with open(savefile, 'w', encoding='utf-8') as f:
+        f.write("energy,calc_perp,actual_perp\n")
+
+    energies = [8000, 10000, 12400, 15000, 18000, 20000, 22000, 25000]
+    for energy in energies:
+
+        data = sel[sel['energy']== energy]
+        print(data)
+
+        target = 149.4 # value of xi_cam_x at 12.4 keV
+
+        x = data["dcm_perp"].to_numpy()
+        y = data["xi_cam_x"].to_numpy()
+
+        # Linear fit: gap = slope * energy + intercept
+        slope, intercept = np.polyfit(x, y, 1)
+
+        # perp_value = intercept/-slope
+        perp_value = (target - intercept)/slope
+        calc_per = calc_perp_position(energy)
+
+
+        with open(savefile, 'a', encoding='utf-8') as f:
+            f.write(f"{energy},{calc_per:.4f},{perp_value:.4f}\n")
+
+        # print(
+        #     f"Energy = {energy} eV, "
+        #     f"Calculated perp = {calc_per:.4f}, "
+        #     f"Actual perp = {perp_value:.4f}"
+        #     )
+
+
+        # fig, ax = plt.subplots(figsize = (5,7))
+        # ax.scatter(x,y)
+        # ax.set_title(f"{energy}")
+    
+        # # Generate fitted line only over the measured range
+        # x_fit = np.linspace(x.min(), x.max(), 100)
+        # y_fit = slope * x_fit + intercept
+
+        # # # Plot fit first and get its automatically assigned colour
+        # line, = ax.plot(
+        #     x_fit,
+        #     y_fit,
+        #     label=energy,
+        # )
+        # plt.show()
+
+    # return results
+
+    # conv_factor = 12365.75 / (2 * 3.13481)
+
+    # df["costheta"] = np.cos(conv_factor / df["energy"])
+
+    # perp = df[["costheta", "bsccam_x"]]
+
+    # return (
+    #     perp.to_numpy(),
+    #     "costheta",
+    #     "bsccam_x",
+    # )
+
+
+def roll_analysis():
+    """Select the DCM roll calibration data."""
+
+    df = get_data()
+
+    roll = df[["energy", "roll"]]
+
+    # Select the useful linear range
+    roll = roll[
+        (roll["roll"] > 0.1)
+        & (roll["roll"] < 9.6)
+    ]
+
+    return (
+        roll.to_numpy(),
+        "energy",
+        "roll",
+    )
+
+
+def gap_analysis(save=False):
+    """
+    Fit and plot the undulator gap calibration for all harmonics.
+
+    Produces one plot containing all harmonic data and linear fits.
+    Prints fit coefficients in a format that can be copied directly
+    into pxii_parameters.py.
+    """
+
+    df = get_data()
+    gap = df[["energy", "gap", "harmonic"]]
+
+    fig, ax = plt.subplots(figsize=(10, 7))
+
+    results = {}
+    HARMONICS = [
+        "H3",
+        "H5",
+        "H7",
+        "H9",
+        "H11",
+        "H13",
+        "H15",
+        "H17",
+        "H19",
+    ]
+    for harmonic in HARMONICS:
+
+        data = gap[gap["harmonic"] == harmonic]
+
+        if data.empty:
+            print(f"{harmonic}: no data")
+            continue
+
+        x = data["energy"].to_numpy()
+        y = data["gap"].to_numpy()
+
+        # Linear fit: gap = slope * energy + intercept
+        slope, intercept = np.polyfit(x, y, 1)
+
+        # Store results
+        min_gap_energy = (4.5 - intercept) / slope
+
+        results[harmonic] = {
+            "slope": slope,
+            "intercept": intercept,
+            "min_gap_energy": min_gap_energy,
+        }
+
+        # Generate fitted line only over the measured range
+        x_fit = np.linspace(x.min(), x.max(), 100)
+        y_fit = slope * x_fit + intercept
+
+        # Plot fit first and get its automatically assigned colour
+        line, = ax.plot(
+            x_fit,
+            y_fit,
+            label=harmonic,
+        )
+
+        # Plot measured points using the same colour
+        ax.scatter(
+            x,
+            y,
+            color=line.get_color(),
+            s=35,
+            zorder=3,
+        )
+
+    ax.set_xlabel("energy (eV)")
+    ax.set_ylabel("gap (mm)")
+    ax.set_title("Undulator Gap Calibration")
+
+    ax.legend(
+        title="Harmonic",
+        fontsize=9,
+    )
+
+    fig.tight_layout()
+
+    if save:
+        savefile = bl.env.lut_dir / "Undulator_Gap_Calibration.png"
+
+        fig.savefig(
+            savefile,
+            bbox_inches="tight",
+            dpi=150,
+        )
+
+        plt.close(fig)
+
+    else:
+        plt.show()
+
+    # ----------------------------------------------------------
+    # Print fit summary
+    # ----------------------------------------------------------
+
+    print()
+    print("Linear fits: gap = slope * energy + intercept")
+    print()
+    print(
+        f"{'Harmonic':<10}"
+        f"{'Slope':>16}"
+        f"{'Intercept':>16}"
+        f"{'Energy at 4.5 mm':>20}"
+    )
+
+    print("-" * 62)
+
+    for harmonic, result in results.items():
+
+        print(
+            f"{harmonic:<10}"
+            f"{result['slope']:>16.8e}"
+            f"{result['intercept']:>16.8e}"
+            f"{result['min_gap_energy']:>16.0f} eV"
+        )
+
+    # ----------------------------------------------------------
+    # Print copy/paste-ready parameters
+    # ----------------------------------------------------------
+
+    print()
+    print("Copy/paste into pxii_parameters:")
+    print()
+    print("harmonics = {")
+
+    for harmonic, result in results.items():
+
+        print(
+            f'    "{harmonic}": '
+            f'np.array(['
+            f'{result["slope"]:.8e}, '
+            f'{result["intercept"]:.8e}'
+            f']),'
+        )
+
+    print("}")
+
+    return results
+

pxii_bec/macros/bcu_bpm_positions.py

@@ -6,7 +6,7 @@ import time
 import numpy as np
 
 
-def compute_norm(n_readings=5):
+def compute_norm_bcu(n_readings=5):
     """Average normalized BPM X/Y from repeated sets of four channels."""
 
     xn_values = []
@@ -31,20 +31,36 @@ def compute_norm(n_readings=5):
 
         time.sleep(0.1)
 
-    return float(np.mean(xn_values)), float(np.mean(yn_values))
+    return {
+        "bcu_Xnorm": float(np.mean(xn_values)), 
+        "bcu_Ynorm": float(np.mean(yn_values)),
+    }
 
 
 def get_bcu_beampos():
-    """Determine beam position"""
-    bpm_xn, bpm_yn = compute_norm()
+    """Determine beam position from BCU BPM"""
+    # Check that there is a reading first
+    if get_value(dev.bcu_bpmsum) < 1:
+        return {
+            "ok": False,
+            "message": "Reading too low on BCU BPM"
+        }
+
+    result = compute_norm_bcu()
     bpm_x = dev.bcu_bpm_x.position
     bpm_y = dev.bcu_bpm_y.position
 
-    beam_x = beam_offset_um(bpm_xn, bpm_x, BPM_X_Calibration)
+    beam_x = beam_offset_um(result["bcu_Xnorm"], bpm_x, BCU_BPM_X_Calibration)
 
-    beam_y = beam_offset_um(bpm_yn, bpm_y, BPM_Y_Calibration)
+    beam_y = beam_offset_um(result["bcu_Ynorm"], bpm_y, BCU_BPM_Y_Calibration)
 
-    return beam_x, beam_y
+    return {
+        "ok": True,
+        "bcu_Xnorm": result["bcu_Xnorm"],
+        "bcu_Ynorm": result["bcu_Ynorm"],
+        "bcu_x_um": beam_x, 
+        "bcu_y_um": beam_y,
+    }
 
 
 def beam_offset_um(bpm_signal, bpm_motor_position, calibration):

pxii_bec/macros/beamline_planner.py

@@ -2,6 +2,7 @@
 
 from collections import defaultdict, deque
 from enum import Enum
+
 # from pxii_bec.scripts import beamline_context as bl
 
 # from enums import BeamlineState, TemperatureMode
@@ -74,7 +75,6 @@ class StateChangePlanner:
             state_name = BeamlineState(state_name)
         target = self._merged_state(state_name, modifier)
 
-
         plan = self._plan(target)
 
         print("PLAN:")
@@ -102,7 +102,7 @@ class StateChangePlanner:
     def available_states(self):
         """Return a list of available states"""
         return list(self.states.keys())
-    
+
     def state_devices(self):
         """Return the set of devices that participate in
         beamline state definitions"""
@@ -111,14 +111,13 @@ class StateChangePlanner:
 
         for state in self.states.values():
             devices.update(state.keys())
-        
+
         return sorted(devices)
 
     def get_positions(self):
         """Return current positions of devices that are used
         in state transitions"""
-        return {name: self.devices[name].pos
-                for name in self.state_devices()}
+        return {name: self.devices[name].pos for name in self.state_devices()}
 
     def print_positions(self):
         """Return current state of all devices"""
@@ -131,7 +130,7 @@ class StateChangePlanner:
         """Return a dict of {device: (before, after)} pairs for devices that changed state"""
         after = self.get_positions()
         return {k: (before[k], after[k]) for k in before if before[k] != after[k]}
-    
+
     def __get_closest_states(self):
         """
         Return states ordered by number of mismatches.
@@ -148,21 +147,9 @@ class StateChangePlanner:
             for dev, expected in config.items():
 
                 if not self.devices[dev].is_at(expected):
-                    mismatches.append(
-                        (
-                            dev,
-                            self.devices[dev].pos,
-                            expected,
-                        )
-                    )
+                    mismatches.append((dev, self.devices[dev].pos, expected))
 
-            results.append(
-                (
-                    state.name,
-                    len(mismatches),
-                    mismatches,
-                )
-            )
+            results.append((state.name, len(mismatches), mismatches))
 
         return sorted(results, key=lambda x: x[1])
 
@@ -173,10 +160,7 @@ class StateChangePlanner:
             print(f"\n{state}: {count} mismatch(es)")
 
             for dev, actual, expected in mismatches:
-                print(
-                    f"  {dev:15s} "
-                    f"{actual:10s} -> {expected}"
-                )  
+                print(f"  {dev:15s} " f"{actual:10s} -> {expected}")
 
     def current_state(self):
         """Return all current matching BeamlineState and TemperatureMode combinations,

pxii_bec/macros/beampos_with_en.py

@@ -1,19 +1,19 @@
 def beampos_with_en(planner):
-    deltat = 2 
-    record_beampos_until("23:00",planner,interval_minutes=deltat)
+    deltat = 2
+    record_beampos_until("23:00", planner, interval_minutes=deltat)
     bl_energy(6000)
-    record_beampos_until("00:00",planner,interval_minutes=deltat)
-    bl_energy(8000)    
-    record_beampos_until("01:00",planner,interval_minutes=deltat)
-    bl_energy(10000)    
-    record_beampos_until("02:00",planner,interval_minutes=deltat)
+    record_beampos_until("00:00", planner, interval_minutes=deltat)
+    bl_energy(8000)
+    record_beampos_until("01:00", planner, interval_minutes=deltat)
+    bl_energy(10000)
+    record_beampos_until("02:00", planner, interval_minutes=deltat)
     bl_energy(12000)
-    record_beampos_until("03:00",planner,interval_minutes=deltat)
+    record_beampos_until("03:00", planner, interval_minutes=deltat)
     bl_energy(12400)
-    record_beampos_until("04:00",planner,interval_minutes=deltat)
+    record_beampos_until("04:00", planner, interval_minutes=deltat)
     bl_energy(14000)
-    record_beampos_until("05:00",planner,interval_minutes=deltat)
+    record_beampos_until("05:00", planner, interval_minutes=deltat)
     bl_energy(16000)
-    record_beampos_until("06:00",planner,interval_minutes=deltat)
+    record_beampos_until("06:00", planner, interval_minutes=deltat)
     bl_energy(18000)
-    record_beampos_until("07:00",planner,interval_minutes=deltat)
+    record_beampos_until("07:00", planner, interval_minutes=deltat)

pxii_bec/macros/build_devices.py

@@ -63,14 +63,7 @@ def build_devices(yaml_file):
     return state_devices
 
 
-def update_position(
-    device,
-    position,
-    value,
-    axis=None,
-    force=False,
-    max_delta=0.5,
-):
+def update_position(device, position, value, axis=None, force=False, max_delta=0.5):
     """
     Update a single saved position in memory.
 
@@ -189,13 +182,7 @@ def update_positions(updates):
     return save_and_reload()
 
 
-def save_current_position(
-    device,
-    position,
-    axis=None,
-    force=False,
-    max_delta=0.5,
-):
+def save_current_position(device, position, axis=None, force=False, max_delta=0.5):
     """
     Save the current motor position as a named position.
     """

pxii_bec/macros/calculator.py

@@ -2,6 +2,7 @@
 
 from dataclasses import dataclass
 import numpy as np
+
 # from pxii_parameters import (EnergyDefaults, CamConversion)
 
 
@@ -60,9 +61,7 @@ def convert_to_degrees(angle_mrad: float) -> float:
     return np.rad2deg(angle_mrad / 1000)
 
 
-def create_conversion_result(
-    energy_ev: float, wavelength: float, bragg_angle_mrad: float
-) -> dict:
+def create_conversion_result(energy_ev: float, wavelength: float, bragg_angle_mrad: float) -> dict:
     """
     Creates a dictionary containing converted values of energy and angles.
 
@@ -226,9 +225,7 @@ def validate_energy(energy_ev):
     return energy_ev
 
 
-def convert_from_bragg(
-    bragg_angle_mrad: float, temp=120, print_result: bool = False
-) -> dict:
+def convert_from_bragg(bragg_angle_mrad: float, temp=120, print_result: bool = False) -> dict:
     """
     Convert the Bragg angle to wavelength and energy, returning the result as a dictionary.
 
@@ -274,9 +271,7 @@ def convert_from_energy(energy_ev: float, temp=120, print_result: bool = False)
     """
     energy_ev = validate_energy(energy_ev)
     wavelength = calculate_wavelength_from_energy(energy_ev)
-    bragg_angle_mrad = float(
-        calculate_bragg_angle_from_wavelength(wavelength, temp=temp)
-    )
+    bragg_angle_mrad = float(calculate_bragg_angle_from_wavelength(wavelength, temp=temp))
     result = create_conversion_result(energy_ev, wavelength, bragg_angle_mrad)
     if print_result:
         print_conversion_result(result)
@@ -284,9 +279,7 @@ def convert_from_energy(energy_ev: float, temp=120, print_result: bool = False)
 
 
 def convert_from_wavelength(
-    wavelength: float,
-    temp: float = 120,
-    print_result: bool = False,
+    wavelength: float, temp: float = 120, print_result: bool = False
 ) -> dict:
     """
     Convert a given wavelength value into corresponding energy, Bragg angle, and
@@ -312,19 +305,14 @@ def convert_from_wavelength(
             outside of the permitted range, returns None.
     """
     energy_ev = calculate_energy_from_wavelength(wavelength)
-    bragg_angle_mrad = float(
-        calculate_bragg_angle_from_wavelength(wavelength, temp=temp)
-    )
+    bragg_angle_mrad = float(calculate_bragg_angle_from_wavelength(wavelength, temp=temp))
     result = create_conversion_result(energy_ev, wavelength, bragg_angle_mrad)
     if print_result:
         print_conversion_result(result)
     return result
 
 
-def calc_perp_position(
-    energy_ev: float,
-    print_result: bool = False,
-) -> float:
+def calc_perp_position(energy_ev: float, beam_offset = None, print_result: bool = False) -> float:
     """
     Calculate the perpendicular motor position based on provided energy in electron-volts (eV).
 
@@ -344,8 +332,12 @@ def calc_perp_position(
         None
     """
     result = convert_from_energy(energy_ev, print_result=False)
+
+    if beam_offset is None:
+        beam_offset = EnergyDefaults.beam_offset
+
     bragg_angle_rad = result["bragg_angle_mrad"] / 1000
-    perp_offset = float(EnergyDefaults.beam_offset / (2 * np.cos(bragg_angle_rad))) - 3
+    perp_offset = float(beam_offset / (2 * np.cos(bragg_angle_rad))) - 3
     if print_result:
         print(f"Perp = {perp_offset: .4f}")
     return perp_offset
@@ -355,7 +347,7 @@ def calc_scam_microns(pixels, zoom=1000):
     """Convert pixels to microns for the sample camera"""
     return float(pixels / (CamConversion.a * np.exp(CamConversion.b * zoom)))
 
+
 def calc_sscam_microns(pixels):
     """Convert pixels to microns for the ss camera"""
-    return pixels*20
-
+    return pixels * 20

pxii_bec/macros/calibrate_bpm.py

@@ -8,35 +8,172 @@ import numpy as np
 import pandas as pd
 import matplotlib.pyplot as plt
 
+from pxii_bec.scripts import beamline_context as bl
+from pxii_bec.macros.beamline_planner import BeamlineState
 
-# def compute_norm(n_readings=5):
-#     """Average normalized BPM X/Y from repeated sets of four channels."""
 
-#     xn_values = []
-#     yn_values = []
+def compute_norm_ss(n_readings=5):
+    """Average normalized BPM X/Y from repeated sets of four channels."""
 
-#     for _ in range(n_readings):
-#         bpm1 = dev.bcu_bpm1.read()["bcu_bpm1"]["value"]
-#         bpm2 = dev.bcu_bpm2.read()["bcu_bpm2"]["value"]
-#         bpm3 = dev.bcu_bpm3.read()["bcu_bpm3"]["value"]
-#         bpm4 = dev.bcu_bpm4.read()["bcu_bpm4"]["value"]
+    xn_values = []
+    yn_values = []
+    for _ in range(n_readings):
+        bpm1 = dev.ss_bpm1.read()["ss_bpm1"]["value"]
+        bpm2 = dev.ss_bpm2.read()["ss_bpm2"]["value"]
+        bpm3 = dev.ss_bpm3.read()["ss_bpm3"]["value"]
+        bpm4 = dev.ss_bpm4.read()["ss_bpm4"]["value"]
 
-#         total = bpm1 + bpm2 + bpm3 + bpm4
+        total = bpm1 + bpm2 + bpm3 + bpm4
 
-#         if total == 0:
-#             continue
+        if total == 0:
+            continue
 
-#         xn = ((bpm1 + bpm2) - (bpm3 + bpm4)) / total
-#         yn = ((bpm1 + bpm3) - (bpm2 + bpm4)) / total
+        xn = ((bpm1 + bpm2) - (bpm3 + bpm4)) / total
+        yn = ((bpm1 + bpm3) - (bpm2 + bpm4)) / total
 
-#         xn_values.append(xn)
-#         yn_values.append(yn)
+        xn_values.append(xn)
+        yn_values.append(yn)
 
-#         time.sleep(0.1)
+        time.sleep(0.1)
 
-#     return float(np.mean(xn_values)), float(np.mean(yn_values))
+    return {
+        "ss_Xnorm": float(np.mean(xn_values)), 
+        "ss_Ynorm": float(np.mean(yn_values)),
+    }
 
 
+def compute_norm_lu(n_readings=5):
+    """Average normalized BPM X/Y from repeated sets of four channels."""
+
+    xn_values = []
+    yn_values = []
+
+    for _ in range(n_readings):
+        bpm1 = dev.lu_bpm1.read()["lu_bpm1"]["value"]
+        bpm2 = dev.lu_bpm2.read()["lu_bpm2"]["value"]
+        bpm3 = dev.lu_bpm3.read()["lu_bpm3"]["value"]
+        bpm4 = dev.lu_bpm4.read()["lu_bpm4"]["value"]
+
+        total = bpm1 + bpm2 + bpm3 + bpm4
+
+        if total == 0:
+            continue
+
+        xn = ((bpm1 + bpm2) - (bpm3 + bpm4)) / total
+        yn = ((bpm1 + bpm3) - (bpm2 + bpm4)) / total
+
+        xn_values.append(xn)
+        yn_values.append(yn)
+
+        time.sleep(0.1)
+
+    return {
+        "lu_Xnorm": float(np.mean(xn_values)), 
+        "lu_Ynorm": float(np.mean(yn_values)),
+    }
+
+
+
+def run_calibration_ss():
+    """Scan bpm in x and y and record normalised x and y positions"""
+    centred_x = 2.8625
+    centred_y = -1.3874
+    now = datetime.now()
+    fnow = filenow()
+    print(f"moving bpm to {centred_x}, {centred_y}")
+    umv(dev.ss_bpm_y, centred_y)
+    umv(dev.ss_bpm_x, centred_x)
+
+    # # # Calibrate in X
+    # umv(dev.bsf_sl_xsize, 0.3)
+    # umv(dev.bsf_sl_xsize, 0.4)
+    # filename = bl.env.lut_dir / "bpm_calib" / f"ss_bpm_x_{fnow}.csv"
+    # xn_data = []
+    # x_positions = np.linspace(centred_x - 0.3, centred_x + 0.3, 51)
+    # with open(filename, "w", encoding="utf-8") as f:
+    #     f.write(f"Xpos,Xnorm,BPM1,BPM2,BPM3,BPM4\n")
+    # for x in x_positions:
+    #     umv(dev.ss_bpm_x, x)
+    #     print(f"Moving BPM X to {x} mm")
+    #     time.sleep(0.2)
+    #     xn, yn = compute_norm_ss()
+    #     xn_data.append(xn)
+    #     with open(filename, "a", encoding="utf-8") as f:
+    #         f.write(f"{x},{xn}\n")
+
+    # # Calibrate in Y
+    umv(dev.ss_bpm_x, centred_x)
+    umv(dev.bsf_sl_xsize, 0.3)
+    umv(dev.bsf_sl_ysize, 0.4)
+    filename = bl.env.lut_dir / "bpm_calib" / f"ss_bpm_y_{fnow}.csv"
+    y_positions = np.linspace(centred_y - 0.04, centred_y + 0.04, 41)
+    yn_data = []
+    with open(filename, "w", encoding="utf-8") as f:
+        f.write(f"Ypos,Ynorm,BPM1,BPM2,BPM3,BPM4\n")
+    for y in y_positions:
+        umv(dev.ss_bpm_y, y)
+        print(f"Moving BPM Y to {y} mm")
+        time.sleep(0.2)
+        xn, yn = compute_norm_ss()
+        yn_data.append(yn)
+        with open(filename, "a", encoding="utf-8") as f:
+            f.write(f"{y},{yn}\n")
+
+    umv(dev.ss_bpm_x, centred_x)
+    umv(dev.ss_bpm_y, centred_y)
+    umv(dev.bsf_sl_ysize, 3.0)
+    umv(dev.bsf_sl_xsize, 3.0)
+
+def run_calibration_lu():
+    """Scan bpm in x and y and record normalised x and y positions"""
+    centred_x = 2.1816
+    centred_y = 3.0175
+    now = datetime.now()
+    fnow = filenow()
+    print(f"moving bpm to {centred_x}, {centred_y}")
+    umv(dev.lu_bpm_y, centred_y)
+    umv(dev.lu_bpm_x, centred_x)
+
+    # # Calibrate in X
+    # umv(dev.bsf_sl_xsize, 0.3)
+    # umv(dev.bsf_sl_xsize, 0.4)
+    # filename = bl.env.lut_dir / "bpm_calib" / f"lu_bpm_x_{fnow}.csv"
+    # xn_data = []
+    # x_positions = np.linspace(centred_x - 0.3, centred_x + 0.3, 51)
+    # with open(filename, "w", encoding="utf-8") as f:
+    #     f.write(f"Xpos,Xnorm\n")
+    # for x in x_positions:
+    #     umv(dev.lu_bpm_x, x)
+    #     print(f"Moving BPM X to {x} mm")
+    #     time.sleep(0.2)
+    #     xn, yn = compute_norm_lu()
+    #     xn_data.append(xn)
+    #     with open(filename, "a", encoding="utf-8") as f:
+    #         f.write(f"{x},{xn}\n")
+
+    # # Calibrate in Y
+    umv(dev.lu_bpm_x, centred_x)
+    umv(dev.bsf_sl_xsize, 0.3)
+    umv(dev.bsf_sl_ysize, 0.4)
+    filename = bl.env.lut_dir / "bpm_calib" / f"lu_bpm_y_{fnow}.csv"
+    y_positions = np.linspace(centred_y - 0.04, centred_y + 0.04, 41)
+    yn_data = []
+    with open(filename, "w", encoding="utf-8") as f:
+        f.write(f"Ypos,Ynorm,BPM1,BPM2,BPM3,BPM4\n")
+    for y in y_positions:
+        umv(dev.lu_bpm_y, y)
+        print(f"Moving BPM Y to {y} mm")
+        time.sleep(0.2)
+        xn, yn = compute_norm_lu()
+        yn_data.append(yn)
+        with open(filename, "a", encoding="utf-8") as f:
+            f.write(f"{y},{yn}\n")
+
+    umv(dev.lu_bpm_x, centred_x)
+    umv(dev.lu_bpm_y, centred_y)
+    umv(dev.bsf_sl_ysize, 3.0)
+    umv(dev.bsf_sl_xsize, 3.0)
+
 def run_calibration(env):
     """Scan bpm in x and y and record normalised x and y positions"""
     centred_x = 0.444
@@ -86,27 +223,20 @@ def run_calibration(env):
     umv(dev.bcu_bpm_y, centred_y)
     umv(dev.ss_sl_ysize, 3.0)
 
-def read_bpm_calibration_data(
-    env,
-    x_y,
-    rundate,
-    bpm_name="bcu_bpm",
-):
+
+def read_bpm_calibration_data(env, x_y, rundate, bpm_name="bcu_bpm"):
     """Read BPM calibration data from CSV."""
 
     filename = env.lut_dir / f"bpm_calib/{bpm_name}_{x_y}_{rundate}.csv"
 
-    data = np.loadtxt(
-        filename,
-        delimiter=",",
-        skiprows=1,
-    )
+    data = np.loadtxt(filename, delimiter=",", skiprows=1)
 
     position = data[:, 0]
     bpm_norm = data[:, 1]
 
     return position, bpm_norm
 
+
 # def fit_bpm_linear(env, filename, x_y, plot=True):
 #     """
 #     Fit the linear region of a BPM calibration scan.
@@ -200,31 +330,17 @@ def read_bpm_calibration_data(
 #         plt.tight_layout()
 #         plt.show()
 
-#     return result   
-
-
+#     return result
 
 
 def polynomial_calibration(
-    env,
-    x_y,
-    rundate,
-    bpm_name="bcu_bpm",
-    degree=5,
-    signal_limit=0.9,
-    plot=True,
+    env, x_y, rundate, bpm_name="bcu_bpm", degree=5, signal_limit=0.9, plot=True
 ):
 
     # BPM centre during calibration run
-    bpm_centre = {"x": 0.441,"y": -1.5405,}
+    bpm_centre = {"x": 0.441, "y": -1.5405}
 
-
-    xdata, ydata = read_bpm_calibration_data(
-        env,
-        x_y,
-        rundate=rundate,
-        bpm_name=bpm_name,
-    )
+    xdata, ydata = read_bpm_calibration_data(env, x_y, rundate=rundate, bpm_name=bpm_name)
 
     # Keep useful BPM range
     mask = np.abs(ydata) < signal_limit
@@ -262,26 +378,13 @@ def polynomial_calibration(
     print(f"    crosshair_bpm_position = None")
 
     if plot:
-        signal_fit = np.linspace(
-            signal.min(),
-            signal.max(),
-            500,
-        )
+        signal_fit = np.linspace(signal.min(), signal.max(), 500)
 
         position_fit = np.polyval(coeffs, signal_fit)
 
         plt.figure(figsize=(7, 5))
-        plt.scatter(
-            ydata,
-            xdata,
-            alpha=0.4,
-            label="Calibration data",
-        )
-        plt.plot(
-            signal_fit,
-            position_fit,
-            label=f"{degree}th-order polynomial",
-        )
+        plt.scatter(ydata, xdata, alpha=0.4, label="Calibration data")
+        plt.plot(signal_fit, position_fit, label=f"{degree}th-order polynomial")
 
         plt.xlabel(f"BPM {x_y} normalized signal")
         plt.ylabel(f"BPM {x_y} position (mm)")
@@ -292,5 +395,3 @@ def polynomial_calibration(
         plt.show()
 
     return coeffs
-
-

pxii_bec/macros/check.py

@@ -5,7 +5,6 @@ from datetime import datetime
 
 from bec_lib.device import Signal, Positioner
 
-
 # -------------------------------------------------------------------
 # Status Enum
 # -------------------------------------------------------------------
@@ -454,6 +453,9 @@ def filter_results(results, statuses=None):
 
 
 def run_check(show_all=False, scilog=False):
+    """Check the status of beamline motors (must exist as devices in BEC).
+    For a full list of checked devices, use run_check(show_all=True).
+    Results will be logged in scilog if scilog=True"""
 
     results = check2()
 

pxii_bec/macros/chmirrh.py

@@ -1,136 +1,134 @@
-import numpy as np 
-import math, time 
+import numpy as np
+import math, time
 import matplotlib.pyplot as plt
 import scipy
+
 ########################################################
-### scan FE slits and check BPMs before and after mirror 
+### scan FE slits and check BPMs before and after mirror
 ########################################################
 
-def gaussfit(x,y,p):
-# define a gaussian fitting function where
-# p[0] = amplitude
-# p[1] = mean
-# p[2] = sigma
-# p[3] = const offset 
-    
-    fitfct = lambda p, x0: p[0]*np.exp(-(x0-p[1])**2/(2.0*p[2]**2))+p[3]
-    #fitfct = lambda p, x0: p[0]*np.exp(-(x0-p[1])**2/(2.0*p[2]**2))
-    errfct = lambda p, x0,y0: fitfct(p,x0)-y0  
+
+def gaussfit(x, y, p):
+    # define a gaussian fitting function where
+    # p[0] = amplitude
+    # p[1] = mean
+    # p[2] = sigma
+    # p[3] = const offset
+
+    fitfct = lambda p, x0: p[0] * np.exp(-((x0 - p[1]) ** 2) / (2.0 * p[2] ** 2)) + p[3]
+    # fitfct = lambda p, x0: p[0]*np.exp(-(x0-p[1])**2/(2.0*p[2]**2))
+    errfct = lambda p, x0, y0: fitfct(p, x0) - y0
 
     # guess fit parameters
-    ind0 = np.where(y==max(y))[0] 
-    p0=np.c_[max(y), x[ind0], np.std(y), np.mean(y[0:5])]
-    #p0=scipy.c_[max(y), np.where(y==max(y))[0], np.std(y)]
-                  # array generation [[]], and taking only one dimens
+    ind0 = np.where(y == max(y))[0]
+    p0 = np.c_[max(y), x[ind0], np.std(y), np.mean(y[0:5])]
+    # p0=scipy.c_[max(y), np.where(y==max(y))[0], np.std(y)]
+    # array generation [[]], and taking only one dimens
     # fit a gaussian to the correlation function
 
-    #print('p0 = ' , p0)
-    p1, success = scipy.optimize.leastsq(errfct, p0.copy()[0],
-                                     args=(x,y))
+    # print('p0 = ' , p0)
+    p1, success = scipy.optimize.leastsq(errfct, p0.copy()[0], args=(x, y))
 
-    #plt.figure()
-    bestfit=fitfct(p1,x)
-    #print('************************', x,y)
-    plt.plot(x,y,'r*')    
-    plt.plot(x,bestfit,'r-')
+    # plt.figure()
+    bestfit = fitfct(p1, x)
+    # print('************************', x,y)
+    plt.plot(x, y, "r*")
+    plt.plot(x, bestfit, "r-")
 
     # different fit fct
-    #popt, pcov = curve_fit(fitfct, x, y)
-    #newfit=fitfct(popt,x)
-    #plt.plot(x,newfit,'g+')
+    # popt, pcov = curve_fit(fitfct, x, y)
+    # newfit=fitfct(popt,x)
+    # plt.plot(x,newfit,'g+')
 
-    
     plt.show()
 
     return bestfit, p1
 
-def scan_fe_sl(dir = "y"):
-    if dir in ["y","v"]:
-        sdir ="vertical"
+
+def scan_fe_sl(dir="y"):
+    if dir in ["y", "v"]:
+        sdir = "vertical"
         fe_size0 = dev.fe_sl_ysize.user_readback.get()
-        print('Closing vertical FE slits to 0.1')  
+        print("Closing vertical FE slits to 0.1")
         umv(dev.fe_sl_ysize, 0.1)
-        s = scans.line_scan(dev.fe_sl_ycen,-1,1, exp_time=02., steps=21, relative=True)
+        s = scans.line_scan(dev.fe_sl_ycen, -1, 1, exp_time=02.0, steps=21, relative=True)
         time.sleep(0.1)
         umv(dev.fe_sl_ysize, fe_size0)
-        print(f'Opening {sdir} FE slits to {fe_size0}')
-    if dir in ["x","h"]:
-        sdir ="horizontal"
+        print(f"Opening {sdir} FE slits to {fe_size0}")
+    if dir in ["x", "h"]:
+        sdir = "horizontal"
         fe_size0 = dev.fe_sl_xsize.user_readback.get()
-        print('Closing horizontal FE slits to 0.1')  
+        print("Closing horizontal FE slits to 0.1")
         umv(dev.fe_sl_xsize, 0.1)
-        s = scans.line_scan(dev.fe_sl_xcen,-1,1, exp_time=02., steps=21, relative=True)
+        s = scans.line_scan(dev.fe_sl_xcen, -1, 1, exp_time=02.0, steps=21, relative=True)
         time.sleep(0.1)
         umv(dev.fe_sl_xsize, fe_size0)
-        print(f'Opening {sdir} FE slits to {fe_size0}')
+        print(f"Opening {sdir} FE slits to {fe_size0}")
     else:
-        print('no valid direction, doing nothing') 
-    
-def mirrh(dir='y'):
-    
-    #dat_ss = read_data_csv("/home/anuschka/SS_pitch2p94.csv")
-    #dat_bcu = read_data_csv("/home/anuschka/BCU_pitch2p94.csv")
+        print("no valid direction, doing nothing")
+
+
+def mirrh(dir="y"):
+
+    # dat_ss = read_data_csv("/home/anuschka/SS_pitch2p94.csv")
+    # dat_bcu = read_data_csv("/home/anuschka/BCU_pitch2p94.csv")
 
     scan_fe_sl(dir=dir)
     ind = -1
-    if dir in ["x","h"]:
-        slitmot = 'fe_sl_xcen'
-    if dir in ["y","v"]:
-        slitmot = 'fe_sl_ycen'        
-    
-    dat_ss = save_data(ind, slitmot, 'ss_bpmsum', isave = 0)
-    dat_bcu = save_data(ind, slitmot, 'bcu_bpmsum', isave = 0)
-    
+    if dir in ["x", "h"]:
+        slitmot = "fe_sl_xcen"
+    if dir in ["y", "v"]:
+        slitmot = "fe_sl_ycen"
 
-    data_xs = dat_ss[0]      # csv would be: dat_ss[:, 0]
+    dat_ss = save_data(ind, slitmot, "ss_bpmsum", isave=0)
+    dat_bcu = save_data(ind, slitmot, "bcu_bpmsum", isave=0)
+
+    data_xs = dat_ss[0]  # csv would be: dat_ss[:, 0]
     data_ys = dat_ss[1]
-    
+
     data_xb = dat_bcu[0]
     data_yb = dat_bcu[1]
 
-    #plt.figure()
+    # plt.figure()
 
-    #plt.plot(data_xs, data_ys, "*")
-    #plt.plot(data_xb, data_yb, "+")
+    # plt.plot(data_xs, data_ys, "*")
+    # plt.plot(data_xb, data_yb, "+")
 
-    data_ys_norm = data_ys/max(data_ys) # looks better than data_ys/sum(data_ys)
-    data_yb_norm = data_yb/max(data_yb)
+    data_ys_norm = data_ys / max(data_ys)  # looks better than data_ys/sum(data_ys)
+    data_yb_norm = data_yb / max(data_yb)
 
     plt.figure()
 
     plt.plot(data_xs, data_ys_norm, "*")
     plt.plot(data_xb, data_yb_norm, "+")
 
-
-    y= data_ys_norm
-    xm = np.where(y==max(y))[0]
+    y = data_ys_norm
+    xm = np.where(y == max(y))[0]
     xmi = data_xs[xm]
-    #print('xm, xmi', xm, xmi) 
+    # print('xm, xmi', xm, xmi)
 
-    pf1 = [1, xmi , np.std(data_ys_norm), np.mean(y[0:5])]     # bg = 0 
-    fit_s, ps = gaussfit(data_xs,data_ys_norm, pf1) 
+    pf1 = [1, xmi, np.std(data_ys_norm), np.mean(y[0:5])]  # bg = 0
+    fit_s, ps = gaussfit(data_xs, data_ys_norm, pf1)
 
-    y= data_yb_norm
-    xm = np.where(y==max(y))[0]
+    y = data_yb_norm
+    xm = np.where(y == max(y))[0]
     xmi = data_xb[xm]
-    #print('xm, xmi', xm, xmi) 
+    # print('xm, xmi', xm, xmi)
 
     pf2 = [1, xmi, np.std(data_yb_norm), np.mean(y[0:5])]  # bg = -11
-    fit_b, pb = gaussfit(data_xb,data_yb_norm, pf2) 
-
+    fit_b, pb = gaussfit(data_xb, data_yb_norm, pf2)
 
     plt.figure()
 
-    plt.plot(data_xs, fit_s-ps[3], "*")
-    plt.plot(data_xs, fit_s-ps[3])
-    plt.plot(data_xb, fit_b-pb[3], "+")
-    plt.plot(data_xb, fit_b-pb[3])
+    plt.plot(data_xs, fit_s - ps[3], "*")
+    plt.plot(data_xs, fit_s - ps[3])
+    plt.plot(data_xb, fit_b - pb[3], "+")
+    plt.plot(data_xb, fit_b - pb[3])
 
-    print('Fit Params of First BPM, SS, ps', ps)
-    print('Fit Params of Second BPM, BCU, pb', pb)
+    print("Fit Params of First BPM, SS, ps", ps)
+    print("Fit Params of Second BPM, BCU, pb", pb)
     print()
-    if abs(ps[1]-pb[1]) > 0.05:
-        print('***** WARNING ******, mirror height not ok')
-    if abs(ps[2]-pb[2]) > 0.05:
-        print('***** WARNING ******, mirror not catching full beam')
-    
+    if abs(ps[1] - pb[1]) > 0.05:
+        print("***** WARNING ******, mirror height not ok")
+    if abs(ps[2] - pb[2]) > 0.05:
+        print("***** WARNING ******, mirror not catching full beam")

pxii_bec/macros/create_daily_setup_gui.py

@@ -0,0 +1,29 @@
+def create_daily_setup():
+    dock = bec.gui.new("DailySetup")
+    # plot1 = dock.new(widget="Waveform", object_name= "Plot_1")
+    # plot2 = dock.new(widget="Waveform", object_name= "Plot_2", relative_to="Plot_1", where="bottom")
+    # plot3 = dock.new(widget="Waveform", object_name= "Plot_3", relative_to = "Plot_2", where="bottom")
+    # plot4 = dock.new(widget="Waveform", object_name= "Plot_4", relative_to="Plot_1", where="right")
+    # plot5 = dock.new(widget="Waveform", object_name= "Plot_5", relative_to="Plot_2", where="right")
+    # plot6 = dock.new(widget="Waveform", object_name= "Plot_6", relative_to="Plot_3", where="right")
+    # log = dock.new(widget="TextBox", object_name= "Info", relative_to="Plot_1",where="left")
+    # progress = dock.new(widget="TextBox", object_name= "Progress", relative_to="Info", where="left")
+    progress = dock.new(widget="TextBox", object_name= "Progress")
+    log = dock.new(widget="TextBox", object_name= "Info", relative_to="Progress", where ="right")
+    plot1 = dock.new(widget="Waveform", object_name= "Plot_1", relative_to="Info", where ="right")
+    plot2 = dock.new(widget="Waveform", object_name= "Plot_2", relative_to="Plot_1", where="right")
+    plot3 = dock.new(widget="Waveform", object_name= "Plot_3", relative_to = "Plot_1", where="bottom")
+    plot4 = dock.new(widget="Waveform", object_name= "Plot_4", relative_to="Plot_2", where="bottom")
+    plot5 = dock.new(widget="Waveform", object_name= "Plot_5", relative_to = "Plot_3", where="bottom")
+    plot6 = dock.new(widget="Waveform", object_name= "Plot_6", relative_to="Plot_4", where="bottom")
+    dock.set_layout_ratios(
+    horizontal=[1,2,1.2,1.2],
+    vertical=[1,1,1],
+    )
+
+    progress.set_plain_text("")
+    log.set_plain_text("")
+
+    dock.save_profile()
+
+

pxii_bec/macros/devices_manager.py

@@ -1,9 +1,9 @@
 """
 This module manages the initialization of devices."""
 
-#from guards import attach_guards
-#from policies import attach_policies
-#from build_devices import build_devices
+# from guards import attach_guards
+# from policies import attach_policies
+# from build_devices import build_devices
 
 
 class DeviceManager:

pxii_bec/macros/enScan.py

@@ -11,7 +11,7 @@ def en_plothist(hindex: int, signal_name: str, isave=1):
     s=scans.line_scan(dev.dcm_bragg, 178.5, 179.5, steps=240, relative=False
     data_x, data_y = en_plothist(-1,"bcu_bpmsum")
 
-    scanned with 
+    scanned with
     scans.line_scan(dev.aerotech.y,-0.05,0.05, steps=101, settling_time=0.5, relative=True)
     """
 
@@ -21,54 +21,56 @@ def en_plothist(hindex: int, signal_name: str, isave=1):
 
     if hindex < 0:
         h = bec.history[hindex]
-        print('by scan number')
+        print("by scan number")
     else:
         h = bec.history.get_by_scan_number(hindex)
-        print('by scan number')
+        print("by scan number")
 
     md = h.metadata["bec"]
-    sno = md['dataset_number']
+    sno = md["dataset_number"]
     print(f"number of scan = {sno}")
-    scanvar = list(md["args"].keys())[0]  # string, returns the variable of the last performed scan
+    #scanvar = list(md["args"].keys())[0]  # string, returns the variable of the last performed scan
     # data = h.devices[device_name][signal].read()["value"]
     # data_x = h.devices.dcm_pitch.dcm_pitch.read()["value"]
     # data_y = h.devices.lu_bpmsum.lu_bpmsum.read()["value"]
     # data_x = h.devices[device_name][device_name].read()["value"]
 
-    # that works ... 
-    #print(list(md['args'].keys()))
-    val = list(md['args'].keys())
-    #val[0] = 'aerotech.x'
-    devicenam =  val[0]
-    print('device = ', devicenam)
+    # that works ...
+    # print(list(md['args'].keys()))
+    ## val = list(md["args"].keys())   no longer !!!!! to be checked !!! 
+    # val[0] = 'aerotech.x'
+    ##devicenam = val[0]
+    ##print("device = ", devicenam)
+    devicenam = md["scan_report_devices"][0].decode()
+
+    
     data_xd = md["positions"]  # last scan knows which device ... however, double array
     data_x = data_xd.flatten()
     print("dx = ", data_x)
-    #data_y = h.devices[signal_name][signal_name].read()["value"]
+    # data_y = h.devices[signal_name][signal_name].read()["value"]
     data_y1 = h.devices["bcu_bpmsum"]["bcu_bpmsum"].read()["value"]
     data_y2 = h.devices["ss_bpmsum"]["ss_bpmsum"].read()["value"]
-    
-    #print("dy = ", data_y)
 
-    data_y = data_y1/data_y2
-    rev = 0 
-    #if val[0][9] == 'x':
+    # print("dy = ", data_y)
+
+    data_y = data_y1 / data_y2
+    rev = 0
+    # if val[0][9] == 'x':
     #     rev = 1
-    smoothplotgrad(data_x, data_y, reverse = rev)
-   # g, xm = justfit(data_x, data_y, model=model, ibg=ibg)
+    smoothplotgrad(data_x, data_y, reverse=rev)
+    # g, xm = justfit(data_x, data_y, model=model, ibg=ibg)
 
-#    plt.ion()
-#    plt.figure()
-#    plt.plot(data_x, data_y, "*")
-#    plt.plot(data_x, g.best_fit)
-#    plt.xlabel(scanvar)
-#    plt.ylabel(signal_name)
-#    plt.show()
+    #    plt.ion()
+    #    plt.figure()
+    #    plt.plot(data_x, data_y, "*")
+    #    plt.plot(data_x, g.best_fit)
+    #    plt.xlabel(scanvar)
+    #    plt.ylabel(signal_name)
+    #    plt.show()
 
-#    gcen = g.pars["center"].value
+    #    gcen = g.pars["center"].value
 
-
-    if isave: 
+    if isave:
         ans = "n"
         ans = input("Store data in csv file? y/n ")
         if ans == "y":
@@ -79,5 +81,4 @@ def en_plothist(hindex: int, signal_name: str, isave=1):
             with open(filename, "w") as f:
                 np.savetxt(f, combined, delimiter=",", fmt="%.9e")
 
-
     return data_x, data_y

pxii_bec/macros/findattr.py

@@ -3,8 +3,9 @@
 
 # if you know the attribute you are searching for:
 
+
 def check_attr(obj, attr):
-# att as string 
+    # att as string
 
     attr = getattr(obj, attr)
 
@@ -13,7 +14,9 @@ def check_attr(obj, attr):
         print("values:", attr.values())
         print("items:", attr.items())
 
-# Automatically Detect All Dictionary Attributes:   
+
+# Automatically Detect All Dictionary Attributes:
+
 
 def list_dict_attr_single(obj):
     for attr_name, value in vars(obj).items():
@@ -22,8 +25,9 @@ def list_dict_attr_single(obj):
             print("  Keys:", list(value.keys()))
             print("  Items:")
             for key, val in value.items():
-                print(f"     {key} -> {val}") 
-            
+                print(f"     {key} -> {val}")
+
+
 # Also Handle Nested Dictionaries:
 
 
@@ -34,16 +38,11 @@ def list_dict_attr(obj):
             print(" " * indent + str(key) + ":", end=" ")
             if isinstance(value, dict):
                 print()
-                print_dict(value, indent+1)
+                print_dict(value, indent + 1)
             else:
-                print(value) 
-    
+                print(value)
+
     for attr_name, value in vars(obj).items():
         if isinstance(value, dict):
             print(f"\nDictionary attribute: {attr_name}")
             print_dict(value)
-            
-
-
-
-

pxii_bec/macros/flux_di.py

@@ -1,131 +1,132 @@
 #!/usr/bin/env python
-# ### PYTHON pro to determine the flux from the current 
-# ### on a Si diode 
-# ### A Pauluhn, Dec 2012 
-# ### from IDL pro flux_diode.pro (2010) 
+# ### PYTHON pro to determine the flux from the current
+# ### on a Si diode
+# ### A Pauluhn, Dec 2012
+# ### from IDL pro flux_diode.pro (2010)
 
 
 ## NOTE: for TRANSFER DIODE:
-## switch off ANY ambient light 
-## note that: 10 um Si, and 0 um Al  for transfer diode Hamamatsu 
+## switch off ANY ambient light
+## note that: 10 um Si, and 0 um Al  for transfer diode Hamamatsu
 
-# ### import the standard 
-import os, sys, string, time 
+# ### import the standard
+import os, sys, string, time
 import re
 import numpy as np
 import math
 
 
-
-
 def fluxcalc(curr, en, t_air, t_si, t_al):
 
-    #------ parameters:
-    rsi = 2.33      # g/cm^3 density of Si
-    ral = 2.699     # g/cm^3 density of Al 
-    rair = 1.205e-3  # g/cm^3 density of air 
+    # ------ parameters:
+    rsi = 2.33  # g/cm^3 density of Si
+    ral = 2.699  # g/cm^3 density of Al
+    rair = 1.205e-3  # g/cm^3 density of air
 
-    eps_si = 3.62 # eV , energy req for charge separation in Si (el/hole pair) 
-    e = 1.602e-19 # As , elem charge 
+    eps_si = 3.62  # eV , energy req for charge separation in Si (el/hole pair)
+    e = 1.602e-19  # As , elem charge
 
     t_si = 0.0012  # thickness of diode in cm (==12 micrometres) ; [*10000]
-    t_al = 0.002   # thickness of diode in cm (==20 micrometres) 
+    t_al = 0.002  # thickness of diode in cm (==20 micrometres)
 
-    #--------- calc----------------------------------------------------
-    #energy deposit in Silicon
-    #ratio of photoelectric cross section to density for Silicon
-    #alog10(A_Si)= 4.158 - 2.238*alog10(Ep) - 0.477*alog10(Ep)^2 + 0.0789*alog10(Ep)^3 
+    # --------- calc----------------------------------------------------
+    # energy deposit in Silicon
+    # ratio of photoelectric cross section to density for Silicon
+    # alog10(A_Si)= 4.158 - 2.238*alog10(Ep) - 0.477*alog10(Ep)^2 + 0.0789*alog10(Ep)^3
 
-    ps = np.poly1d([0.0789, - 0.477, - 2.238, 4.158])
-    #print ps
-    # ps.c 
-    # print ps(2.3) 
+    ps = np.poly1d([0.0789, -0.477, -2.238, 4.158])
+    # print ps
+    # ps.c
+    # print ps(2.3)
 
-    leval = math.log10(en) 
-    hlp_si = ps(leval) 
-    a_si = np.pow(10, hlp_si) 
-    #efact = np.exp(-A_Si*rsi*t_Si) 
-    #sifact =1 - efact
-    sifact = - np.expm1(-a_si*rsi*t_si) 
-    #print 'sifact = ', sifact
+    leval = math.log10(en)
+    hlp_si = ps(leval)
+    a_si = np.pow(10, hlp_si)
+    # efact = np.exp(-A_Si*rsi*t_Si)
+    # sifact =1 - efact
+    sifact = -np.expm1(-a_si * rsi * t_si)
+    # print 'sifact = ', sifact
 
-    fl = 1000.*curr * eps_si/1.602/en/sifact *1.e13 # curr expected in A
-    #print 'fl = ', fl 
+    fl = 1000.0 * curr * eps_si / 1.602 / en / sifact * 1.0e13  # curr expected in A
+    # print 'fl = ', fl
+
+    # Aluminium attenuation
+    # ratio of photoelectric cross section to density for Aluminium
+    pa = np.poly1d([0.0638, -0.413, -2.349, 4.106])
 
-    #Aluminium attenuation
-    #ratio of photoelectric cross section to density for Aluminium
-    pa = np.poly1d([ 0.0638, - 0.413, - 2.349, 4.106])
-    
     hlp_al = pa(leval)
-    a_al = pow(10, hlp_al) 
+    a_al = pow(10, hlp_al)
 
     # attenuation due to aluminium
-    alfact = np.exp(-a_al*ral*t_al)
-    #print 'alfact = ', alfact
+    alfact = np.exp(-a_al * ral * t_al)
+    # print 'alfact = ', alfact
     # Air attenuation
     # ratio of photoelectric cross section to density for air
 
-    pair = np.poly1d([0.928, - 2.348, - 1.026, 3.153])
+    pair = np.poly1d([0.928, -2.348, -1.026, 3.153])
     hlp_air = pair(leval)
-    a_air = np.pow(10, hlp_air) 
+    a_air = np.pow(10, hlp_air)
 
-    #print('hlp_air, a_air, rair, t_air = ', hlp_air, a_air, rair , t_air)
+    # print('hlp_air, a_air, rair, t_air = ', hlp_air, a_air, rair , t_air)
 
-    # attenuation due to air 
-    airfact = np.exp(-a_air*rair*t_air/10.)
-    #airfact = 1.
+    # attenuation due to air
+    airfact = np.exp(-a_air * rair * t_air / 10.0)
+    # airfact = 1.
 
-    
-    #print 'airfact = ', airfact
-    #print ' t_air = ', t_air 
+    # print 'airfact = ', airfact
+    # print ' t_air = ', t_air
 
-    # total flux from photocurrent 
-    fl = fl/alfact/airfact
-    #print 'fl = ', fl 
+    # total flux from photocurrent
+    fl = fl / alfact / airfact
+    # print 'fl = ', fl
+
+    return fl
 
-    return fl 
 
 #
 # Main
 #
 
-def flux_x10sa(curr, en, silent = 0):
+
+def flux_x10sa(curr, en, silent=0):
     # curr = input('Please enter the current [in A] ')
     curr = float(curr)
     if not silent:
-        print('Current =  ', curr)
+        print("Current =  ", curr)
     # en = input('Please enter the energy [in keV] ')
     en = float(en)
     if not silent:
-        print('Energy =  ', en)
+        print("Energy =  ", en)
     ## d_det = input('Please enter the detector distance [in mm] ')
     d_det = dev.det_z.user_readback.get()
-    d_off = 15 ## at X10SA   ### input('Please enter the OFFSET of the diode to det surface [in mm] ') 
-    
-    t_air = float(d_det) +  float(d_off)
+    d_off = (
+        15  ## at X10SA   ### input('Please enter the OFFSET of the diode to det surface [in mm] ')
+    )
 
-    t_si = 12 # um ## at X10SA    
+    t_air = float(d_det) + float(d_off)
+
+    t_si = 12  # um ## at X10SA
     #  t_si = input('Please enter the Si thickness of diode [in um] ') #  if not silent:
-    t_si = float(t_si) / 10000. # to cm 
+    t_si = float(t_si) / 10000.0  # to cm
 
-    t_al = 20 # um ## at X10SA
-    #  t_al = input('Please enter the Al thickness of diode [in um] ') 
-    t_al = float(t_al) / 10000. # to cm
+    t_al = 20  # um ## at X10SA
+    #  t_al = input('Please enter the Al thickness of diode [in um] ')
+    t_al = float(t_al) / 10000.0  # to cm
 
     if not silent:
-        print('Air path length (CARE ! add det distance and offset of diode) =  ', t_air) # include additional diode distance
+        print(
+            "Air path length (CARE ! add det distance and offset of diode) =  ", t_air
+        )  # include additional diode distance
 
-
-    fl = fluxcalc(curr, en, t_air,t_si, t_al)
+    fl = fluxcalc(curr, en, t_air, t_si, t_al)
     if not silent:
-        print( " Diode Current = %.6f  A " % curr)
-        print( " Energy = %.4f  keV "  % en )
+        print(" Diode Current = %.6f  A " % curr)
+        print(" Energy = %.4f  keV " % en)
 
-        #print( " Thickness of active Si layer = %.4f\t  cm " % t_si) #*10000. 
-        #print( " Thickness of Al layer in front of diode = %.4f\t  cm "  % t_al) #*10000. 
-        print( " Length of path of air in front of diode = %.4f\t  mm " % t_air) #*10000.
+        # print( " Thickness of active Si layer = %.4f\t  cm " % t_si) #*10000.
+        # print( " Thickness of Al layer in front of diode = %.4f\t  cm "  % t_al) #*10000.
+        print(" Length of path of air in front of diode = %.4f\t  mm " % t_air)  # *10000.
 
-        print (" Flux = %6.2e\t ph/s "  % fl)
+        print(" Flux = %6.2e\t ph/s " % fl)
 
     return fl
-

pxii_bec/macros/flux_macros.py

@@ -256,7 +256,7 @@ def bpm2flux(energy=None, bpmsum=None, transm=None):
 
     """
     calibration_min_energy = 6500
-    calibration_max_energy = 21000
+    # calibration_max_energy = 21000
 
     if energy is None:
         energy = get_current_energy()
@@ -266,14 +266,14 @@ def bpm2flux(energy=None, bpmsum=None, transm=None):
         # bpmsum =  read_av(dev.bcu_bpmsum,10) # do not add to traffic jam
 
     if transm is None:
-        transm = dev.transm.read()["transm"]["value"]
+        transm = dev.transm.read(cached=True)["transm"]["value"]
 
-    if not calibration_min_energy <= energy <= calibration_max_energy:
-        raise ValueError(
-            f"Energy {energy:.0f} eV is outside the calibrated range "
-            f"{calibration_min_energy:.0f}–"
-            f"{calibration_max_energy:.0f} eV"
-        )
+    # if not calibration_min_energy <= energy <= calibration_max_energy:
+    #     raise ValueError(
+    #         f"Energy {energy:.0f} eV is outside the calibrated range "
+    #         f"{calibration_min_energy:.0f}–"
+    #         f"{calibration_max_energy:.0f} eV"
+    #     )
 
     # coeffs = [
     #    1.06436277e5,
@@ -296,3 +296,17 @@ def bpm2flux(energy=None, bpmsum=None, transm=None):
         )
 
     return float(flux), float(full_flux)
+
+def transmission_for_flux(target_flux):
+    """
+    Calculate the transmission required to give target_flux
+    at the current energy.
+
+    Transmission is returned as a fraction from 0 to 1.
+    """
+
+    _, full_flux = bpm2flux()
+
+    transmission = target_flux / full_flux
+
+    return float(np.clip(transmission, 0.0, 1.0))

pxii_bec/macros/knifehist.py

@@ -10,7 +10,7 @@ def knife_plothist(hindex: int, signal_name: str, isave=1):
     Example:
     data_x, data_y = knife_plothist(-1,"xidode")
 
-    scanned with 
+    scanned with
     scans.line_scan(dev.aerotech.y,-0.05,0.05, steps=101, settling_time=0.5, relative=True)
     """
 
@@ -20,13 +20,13 @@ def knife_plothist(hindex: int, signal_name: str, isave=1):
 
     if hindex < 0:
         h = bec.history[hindex]
-        print('by scan number')
+        print("by scan number")
     else:
         h = bec.history.get_by_scan_number(hindex)
-        print('by scan number')
+        print("by scan number")
 
     md = h.metadata["bec"]
-    sno = md['dataset_number']
+    sno = md["dataset_number"]
     print(f"number of scan = {sno}")
     scanvar = list(md["args"].keys())[0]  # string, returns the variable of the last performed scan
     # data = h.devices[device_name][signal].read()["value"]
@@ -34,37 +34,36 @@ def knife_plothist(hindex: int, signal_name: str, isave=1):
     # data_y = h.devices.lu_bpmsum.lu_bpmsum.read()["value"]
     # data_x = h.devices[device_name][device_name].read()["value"]
 
-    # that works ... 
-    #print(list(md['args'].keys()))
-    val = list(md['args'].keys())
-    #val[0] = 'aerotech.x'
-    devicenam =  val[0]
-    print('device = ', devicenam)
+    # that works ...
+    # print(list(md['args'].keys()))
+    val = list(md["args"].keys())
+    # val[0] = 'aerotech.x'
+    devicenam = val[0]
+    print("device = ", devicenam)
     data_xd = md["positions"]  # last scan knows which device ... however, double array
     data_x = data_xd.flatten()
     print("dx = ", data_x)
-    #data_y = h.devices[signal_name][signal_name].read()["value"]
-    data_y = h.devices["xidiode"]["xidiode"].read()["value"]    
+    # data_y = h.devices[signal_name][signal_name].read()["value"]
+    data_y = h.devices["xidiode"]["xidiode"].read()["value"]
     print("dy = ", data_y)
 
-    rev = 0 
-    if val[0][9] == 'x':
+    rev = 0
+    if val[0][9] == "x":
         rev = 1
-    smoothplotgrad(data_x, data_y, reverse = rev)
-   # g, xm = justfit(data_x, data_y, model=model, ibg=ibg)
+    smoothplotgrad(data_x, data_y, reverse=rev)
+    # g, xm = justfit(data_x, data_y, model=model, ibg=ibg)
 
-#    plt.ion()
-#    plt.figure()
-#    plt.plot(data_x, data_y, "*")
-#    plt.plot(data_x, g.best_fit)
-#    plt.xlabel(scanvar)
-#    plt.ylabel(signal_name)
-#    plt.show()
+    #    plt.ion()
+    #    plt.figure()
+    #    plt.plot(data_x, data_y, "*")
+    #    plt.plot(data_x, g.best_fit)
+    #    plt.xlabel(scanvar)
+    #    plt.ylabel(signal_name)
+    #    plt.show()
 
-#    gcen = g.pars["center"].value
+    #    gcen = g.pars["center"].value
 
-
-    if isave: 
+    if isave:
         ans = "n"
         ans = input("Store data in csv file? y/n ")
         if ans == "y":
@@ -75,5 +74,4 @@ def knife_plothist(hindex: int, signal_name: str, isave=1):
             with open(filename, "w") as f:
                 np.savetxt(f, combined, delimiter=",", fmt="%.9e")
 
-
     return data_x, data_y

pxii_bec/macros/luts/.~lock.dcm_calibration_4thOct.csv#

@@ -0,0 +1 @@
+,mcauley_k,x10sa-vcons-01.psi.ch,08.10.2026 15:28,file:///home/mcauley_k/.config/libreoffice/4;

pxii_bec/macros/luts/.~lock.temp.csv#

@@ -0,0 +1 @@
+,mcauley_k,x10sa-vcons-01.psi.ch,08.10.2026 13:22,file:///home/mcauley_k/.config/libreoffice/4;

pxii_bec/macros/luts/20260930_ge_edge.csv

@@ -0,0 +1,62 @@
+Energy,Bragg,bcu_bpmsum
+10953.10,181.54,470.19
+10957.97,181.46,438.23
+10962.84,181.38,400.62
+10967.71,181.30,356.31
+10972.59,181.22,306.11
+10977.48,181.13,260.07
+10982.37,181.05,220.42
+10987.26,180.97,183.83
+10992.16,180.89,149.68
+10997.06,180.81,118.61
+11001.97,180.73,92.83
+11006.88,180.64,71.99
+11011.79,180.56,55.37
+11016.71,180.48,42.38
+11021.64,180.40,32.61
+11026.57,180.32,25.78
+11031.50,180.24,20.77
+11036.44,180.16,17.35
+11041.38,180.07,14.84
+11046.33,179.99,12.82
+11051.28,179.91,11.37
+11056.23,179.83,10.35
+11061.19,179.75,9.51
+11066.16,179.67,8.88
+11071.13,179.59,8.40
+11076.10,179.50,7.76
+11081.08,179.42,7.14
+11086.06,179.34,6.48
+11091.05,179.26,5.77
+11096.04,179.18,4.60
+11101.04,179.10,2.02
+11106.04,179.01,-0.36
+11111.05,178.93,-0.44
+11116.06,178.85,-0.49
+11121.07,178.77,-0.56
+11126.09,178.69,-0.61
+11131.12,178.61,-0.59
+11136.15,178.53,-0.78
+11141.18,178.44,-0.69
+11146.22,178.36,-0.77
+11151.26,178.28,-0.95
+11156.31,178.20,-0.89
+11161.36,178.12,-0.93
+11166.42,178.04,-0.83
+11171.48,177.95,-0.80
+11176.54,177.87,-0.86
+11181.62,177.79,-0.84
+11186.69,177.71,-0.84
+11191.77,177.63,-0.81
+11196.86,177.55,-0.87
+11201.95,177.47,-0.81
+11207.04,177.38,-0.87
+11212.14,177.30,-0.85
+11217.24,177.22,-0.87
+11222.35,177.14,-0.89
+11227.46,177.06,-0.89
+11232.58,176.98,-0.98
+11237.70,176.89,-1.00
+11242.83,176.81,-0.91
+11247.96,176.73,-0.94
+11253.10,176.65,-0.93

pxii_bec/macros/luts/20260930_ge_edge_coarse.csv

@@ -0,0 +1,42 @@
+Energy,Bragg,ss_bpmsum,bcu_bpmsum,i1,transmission
+11003.00,180.71,40337.50,5034.70,-3.155e-08,0.124814
+11007.91,180.63,37732.95,4708.18,-2.250e-08,0.124776
+11012.83,180.55,34281.68,4266.30,-3.557e-08,0.124448
+11017.75,180.46,30615.46,3784.28,-1.949e-08,0.123607
+11022.67,180.38,26805.50,3293.21,-2.652e-08,0.122856
+11027.60,180.30,22925.68,2777.94,-4.461e-08,0.121172
+11032.54,180.22,19156.72,2341.29,-3.356e-08,0.122218
+11037.47,180.14,15677.61,1953.26,-3.456e-08,0.124589
+11042.42,180.06,12596.19,1561.34,-2.853e-08,0.123954
+11047.36,179.98,9918.65,1227.28,-2.351e-08,0.123734
+11052.32,179.89,7733.56,966.71,-4.260e-08,0.125003
+11057.27,179.81,5977.05,749.14,-2.954e-08,0.125336
+11062.23,179.73,4610.51,573.09,-3.155e-08,0.124301
+11067.20,179.65,3555.33,435.38,-3.758e-08,0.122458
+11072.17,179.57,2781.84,332.98,-3.255e-08,0.119699
+11077.14,179.49,2220.76,256.63,-3.758e-08,0.115557
+11082.12,179.40,1810.15,200.61,-2.552e-08,0.110823
+11087.11,179.32,1511.84,158.34,-3.255e-08,0.104733
+11092.09,179.24,1291.08,122.44,-2.753e-08,0.094832
+11097.09,179.16,1134.07,85.85,4.825e-06,0.075699
+11102.08,179.08,1016.08,26.46,1.285e-06,0.026045
+11107.09,179.00,927.11,1.40,-3.959e-08,0.001512
+11112.09,178.92,851.57,0.96,-3.657e-08,0.001123
+11117.10,178.83,790.39,0.71,-3.657e-08,0.000900
+11122.12,178.75,741.22,0.76,-3.858e-08,0.001029
+11127.14,178.67,701.79,0.69,-3.858e-08,0.000981
+11132.16,178.59,669.60,0.61,-3.858e-08,0.000907
+11137.19,178.51,643.20,0.52,-4.763e-08,0.000803
+11142.23,178.43,621.27,0.48,-3.758e-08,0.000771
+11147.27,178.35,601.54,0.48,-3.959e-08,0.000794
+11152.31,178.26,585.43,0.35,-4.763e-08,0.000592
+11157.36,178.18,565.35,0.36,-3.255e-08,0.000640
+11162.41,178.10,548.24,0.40,-3.858e-08,0.000726
+11167.47,178.02,530.61,0.33,-2.250e-08,0.000621
+11172.53,177.94,516.14,0.36,-4.562e-08,0.000707
+11177.60,177.86,502.31,0.16,-3.054e-08,0.000326
+11182.67,177.77,481.54,0.28,-4.763e-08,0.000577
+11187.74,177.69,458.78,0.00,-2.853e-08,0.000007
+11192.82,177.61,442.42,0.07,-5.064e-08,0.000160
+11197.91,177.53,420.53,0.02,-2.753e-08,0.000050
+11203.00,177.45,401.79,-0.06,-3.255e-08,-0.000153

pxii_bec/macros/luts/20260930_ge_edge_fine.csv

@@ -0,0 +1,62 @@
+Energy,Bragg,ss_bpmsum,bcu_bpmsum,transmission
+11087.00,179.33,38560.26,4535.26,0.117615
+11087.50,179.32,38275.33,4463.22,0.116608
+11088.00,179.31,37999.53,4402.33,0.115852
+11088.50,179.30,37721.18,4343.98,0.115160
+11088.99,179.29,37433.34,4282.19,0.114395
+11089.49,179.28,37162.01,4224.25,0.113671
+11089.99,179.28,36904.09,4161.01,0.112752
+11090.49,179.27,36648.40,4089.77,0.111595
+11090.99,179.26,36323.22,4012.69,0.110472
+11091.49,179.25,36017.72,3929.25,0.109092
+11091.99,179.24,35694.92,3845.33,0.107728
+11092.49,179.24,35384.70,3760.69,0.106280
+11092.99,179.23,35063.40,3678.15,0.104900
+11093.49,179.22,34734.79,3590.19,0.103360
+11093.99,179.21,34414.03,3499.21,0.101680
+11094.48,179.20,34086.77,3403.19,0.099839
+11094.98,179.19,33768.33,3300.05,0.097726
+11095.48,179.19,33447.18,3189.84,0.095369
+11095.98,179.18,33094.10,3068.68,0.092726
+11096.48,179.17,32745.61,2944.15,0.089910
+11096.98,179.16,32377.90,2807.15,0.086699
+11097.48,179.15,31997.60,2661.17,0.083168
+11097.98,179.15,31669.44,2509.51,0.079241
+11098.48,179.14,31301.86,2342.72,0.074843
+11098.98,179.13,30946.58,2168.22,0.070063
+11099.48,179.12,30599.35,1976.57,0.064595
+11099.98,179.11,30238.94,1777.62,0.058786
+11100.48,179.11,29827.78,1551.64,0.052020
+11100.98,179.10,29476.59,1319.85,0.044776
+11101.48,179.09,29100.97,1068.57,0.036719
+11101.98,179.08,28749.53,815.70,0.028373
+11102.48,179.07,28376.86,577.46,0.020350
+11102.98,179.06,27983.70,363.72,0.012998
+11103.48,179.06,27609.67,201.28,0.007290
+11103.98,179.05,27256.50,93.88,0.003444
+11104.48,179.04,26875.74,37.45,0.001394
+11104.98,179.03,26496.50,13.07,0.000493
+11105.48,179.02,26113.35,5.24,0.000200
+11105.98,179.02,25731.34,2.71,0.000105
+11106.48,179.01,25355.73,2.30,0.000091
+11106.98,179.00,24961.87,1.74,0.000070
+11107.48,178.99,24564.77,1.50,0.000061
+11107.98,178.98,24188.86,1.34,0.000055
+11108.48,178.97,23802.97,1.42,0.000059
+11108.98,178.97,23424.93,1.32,0.000056
+11109.48,178.96,23028.96,1.20,0.000052
+11109.99,178.95,22653.38,1.05,0.000047
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+11110.99,178.93,21872.37,0.91,0.000041
+11111.49,178.93,21461.83,0.86,0.000040
+11111.99,178.92,21102.15,0.76,0.000036
+11112.49,178.91,20718.33,0.72,0.000035
+11112.99,178.90,20363.01,0.66,0.000033
+11113.49,178.89,19982.21,0.64,0.000032
+11113.99,178.88,19623.79,0.57,0.000029
+11114.49,178.88,19255.10,0.56,0.000029
+11114.99,178.87,18913.77,0.49,0.000026
+11115.50,178.86,18561.76,0.54,0.000029
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+11116.50,178.84,17847.83,0.44,0.000024
+11117.00,178.84,17486.73,0.48,0.000028

pxii_bec/macros/luts/20261007_ge_edge_coarse.csv

@@ -0,0 +1,42 @@
+Energy,Bragg,ss_bpmsum,bcu_bpmsum,transmission
+11003.00,180.71,39854.34,5135.60,0.128859
+11007.91,180.63,37192.26,4756.05,0.127877
+11012.83,180.55,34019.56,4326.89,0.127188
+11017.75,180.46,30427.58,3878.67,0.127472
+11022.67,180.38,26633.96,3368.52,0.126474
+11027.60,180.30,22820.00,2854.62,0.125093
+11032.54,180.22,19140.74,2436.85,0.127312
+11037.47,180.14,15684.96,1992.82,0.127053
+11042.42,180.06,12620.92,1595.40,0.126409
+11047.36,179.98,9966.27,1272.07,0.127637
+11052.32,179.89,7781.57,998.18,0.128274
+11057.27,179.81,6015.60,772.56,0.128426
+11062.23,179.73,4630.19,586.27,0.126618
+11067.20,179.65,3571.05,441.95,0.123758
+11072.17,179.57,2779.62,332.68,0.119686
+11077.14,179.49,2211.73,253.72,0.114715
+11082.12,179.40,1796.12,194.46,0.108265
+11087.11,179.32,1494.90,146.82,0.098212
+11092.09,179.24,1287.16,101.68,0.078999
+11097.09,179.16,1118.17,35.77,0.031992
+11102.08,179.08,989.75,1.87,0.001892
+11107.09,179.00,896.34,1.43,0.001593
+11112.09,178.92,821.20,1.06,0.001293
+11117.10,178.83,761.17,0.86,0.001135
+11122.12,178.75,714.76,0.70,0.000980
+11127.14,178.67,679.67,0.61,0.000890
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+11152.31,178.26,561.83,0.28,0.000495
+11157.36,178.18,541.53,0.31,0.000567
+11162.41,178.10,526.27,0.23,0.000435
+11167.47,178.02,506.37,0.19,0.000376
+11172.53,177.94,485.59,0.12,0.000238
+11177.60,177.86,470.40,0.16,0.000341
+11182.67,177.77,449.74,0.08,0.000184
+11187.74,177.69,430.29,0.03,0.000063
+11192.82,177.61,407.55,0.07,0.000167
+11197.91,177.53,388.94,0.07,0.000178
+11203.00,177.45,373.55,0.10,0.000264

pxii_bec/macros/luts/20261007_ge_edge_fine.csv

@@ -0,0 +1,62 @@
+Energy,Bragg,ss_bpmsum,bcu_bpmsum,transmission
+11087.00,179.33,40803.39,4923.21,0.120657
+11087.50,179.32,40632.73,4872.86,0.119925
+11088.00,179.31,40434.30,4822.80,0.119275
+11088.50,179.30,40234.38,4773.51,0.118643
+11088.99,179.29,40033.04,4719.28,0.117885
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+11089.99,179.28,39643.25,4613.48,0.116375
+11090.49,179.27,39445.42,4562.87,0.115676
+11090.99,179.26,39261.94,4506.05,0.114769
+11091.49,179.25,39036.39,4442.76,0.113811
+11091.99,179.24,38813.22,4370.94,0.112615
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+11104.98,179.03,31027.85,120.78,0.003893
+11105.48,179.02,30634.91,50.59,0.001651
+11105.98,179.02,30266.85,18.11,0.000598
+11106.48,179.01,30028.47,6.72,0.000224
+11106.98,179.00,29680.09,3.60,0.000121
+11107.48,178.99,29252.87,2.66,0.000091
+11107.98,178.98,28968.99,2.14,0.000074
+11108.48,178.97,28606.73,1.86,0.000065
+11108.98,178.97,28298.05,1.75,0.000062
+11109.48,178.96,27894.51,1.59,0.000057
+11109.99,178.95,27513.24,1.50,0.000055
+11110.49,178.94,27192.70,1.41,0.000052
+11110.99,178.93,26814.59,1.44,0.000054
+11111.49,178.93,26416.19,1.27,0.000048
+11111.99,178.92,26059.44,1.25,0.000048
+11112.49,178.91,25677.19,1.18,0.000046
+11112.99,178.90,25304.06,1.06,0.000042
+11113.49,178.89,24924.72,1.02,0.000041
+11113.99,178.88,24519.39,0.98,0.000040
+11114.49,178.88,24145.24,0.89,0.000037
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pxii_bec/macros/luts/20261011_ge_edge_medium.csv

@@ -0,0 +1,42 @@
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pxii_bec/macros/luts/20261014_ge_edge_medium.csv

@@ -0,0 +1,42 @@
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pxii_bec/macros/luts/20261017_ge_edge_medium.csv

@@ -0,0 +1,42 @@
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pxii_bec/macros/luts/bs_checks_20260914.csv

@@ -0,0 +1,14 @@
+Energy,I2_in,I2_out
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pxii_bec/macros/luts/daily_beamline_health.csv

@@ -0,0 +1,2 @@
+timestamp,energy_eV,flux_ph_s,beam_start_x_px,beam_start_y_px,vfm_ydr_start_mm,hfm_xd_start_mm,vfm_ydr_final_mm,hfm_xd_final_mm,beam_final_x_um,beam_final_y_um,vfm_y_mm,vfm_ydr_mm,vfm_pitch_mrad,hfm_x_mm,hfm_xd_mm,hfm_pitch_mrad
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pxii_bec/macros/luts/dcm_calibration_20260902.csv

@@ -0,0 +1,65 @@
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pxii_bec/macros/luts/dcm_calibration_20260903.csv

@@ -0,0 +1,2 @@
+energy,harmonic,gap,pitch,samcam_x,samcam_y,zoom=800.0
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pxii_bec/macros/luts/dcm_calibration_20260923.csv

@@ -0,0 +1,14 @@
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pxii_bec/macros/luts/dcm_calibration_20261004.csv

@@ -0,0 +1,15 @@
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pxii_bec/macros/luts/dcm_calibration_20261004.csv_2

@@ -0,0 +1,15 @@
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+energy,pitch,lu_Xnorm,lu_Ynorm,ss_Xnorm,ss_Ynorm,bcu_x,bcu_y,samcam_x,samcam_y,zoom=1000.0

pxii_bec/macros/luts/dcm_calibration_20261004_first_half.csv

@@ -0,0 +1,14 @@
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+18000,-5.5278,0.088299,0.029077,0.57684,0.074821,21.01,0.89,0.9228,0.9236

pxii_bec/macros/luts/dcm_calibration_4thOct.csv

@@ -0,0 +1,28 @@
+energy,pitch,lu_Xnorm,lu_Ynorm,ss_Xnorm,ss_Ynorm,bcu_x,bcu_y,samcam_x,samcam_y,zoom=1000.0
+6000,-5.5651,0.031085,0.036155,0.0052168,0.0041921,10.75,-1.11,-8.771,-4.583
+7000,-5.5546,0.026899,0.026529,-0.0073424,0.053473,6.16,-1.84,-0.7224,-2.887
+8000,-5.5484,0.066689,0.032268,0.005212,0.0042436,7.95,-2.62,0.9412,-3.068
+9000,-5.5441,0.041593,0.029141,-0.010786,0.042077,12.07,-0.95,-0.5363,-2.653
+10000,-5.5411,0.042201,0.013278,0.025073,0.053635,13.84,-0.60,1.682,-1.665
+11000,-5.5382,0.065656,0.022891,0.027213,0.041838,21.11,-0.06,1.831,-3.373
+12000,-5.5358,0.045707,0.02277,0.021949,0.053366,12.55,0.30,-0.132,-0.07301
+13000,-5.5344,0.046219,0.014825,0.079975,0.088181,17.28,0.47,0.2965,0.02576
+14000,-5.5325,0.071565,0.024777,0.096642,0.083641,20.87,0.44,-0.04888,0.1838
+15000,-5.5313,0.063579,0.021258,0.15225,0.12223,18.18,0.67,0.06056,0.4581
+16000,-5.5304,0.11033,0.023619,0.2533,0.17271,22.24,0.90,1.668,0.6958
+17000,-5.529,0.094652,0.026446,0.32328,0.23969,23.89,0.86,0.6903,0.5908
+18000,-5.5278,0.088299,0.029077,0.57684,0.074821,21.01,0.89,0.9228,0.9236
+18500,-5.5278,0.079312,0.031407,0.57597,0.41821,21.95,0.86,0.4968,0.9468
+19000,-5.5277,0.10892,0.034869,0.672,-0.043649,22.96,0.79,1.274,0.7789
+19500,-5.5273,0.1123,0.037979,0.65287,0.41444,29.04,0.98,1.399,0.7602
+20000,-5.527,0.10889,0.042196,0.76301,0.55486,280.03,-0.09,1.669,0.9976
+20500,-5.5268,0.11885,0.048114,0.94538,0.64762,25.79,1.31,1.943,0.8993
+21000,-5.5264,0.11568,0.055515,1.157,0.84596,22.99,2.12,2.15,1.261
+21500,-5.5257,0.10583,0.061478,1.4832,1.0726,22.62,4.43,1.107,2.616
+22000,-5.5253,0.14069,0.053697,1.1677,0.83326,25.98,7.66,1.164,7.532
+22500,-5.5251,0.14969,0.059799,1.1592,-0.24509,26.08,6.51,1.278,8.663
+23000,-5.5247,0.14373,0.075002,1.5391,0.66679,26.93,7.41,1.376,5.2
+23500,-5.5243,0.14984,0.091189,2.0988,1.5083,27.65,6.24,0.9794,6.096
+24000,-5.5242,0.14755,0.10074,2.6501,1.955,29.90,6.02,0.9268,5.937
+24500,-5.5239,0.15082,0.11364,3.4195,2.5418,32.97,4.64,1.019,4.126
+25000,-5.5237,0.18897,0.10096,2.2261,1.6208,39.12,3.63,2.495,3.873

pxii_bec/macros/luts/dcm_calibration_fail_20261004.csv

@@ -0,0 +1 @@
+energy,scan,reason

pxii_bec/macros/luts/dcm_calibration_failures_20260902.csv

@@ -0,0 +1,7 @@
+energy,scan,reason
+23400,mono_pitch,Peak FWHM spans only 0.00 scan steps (minimum 1.5); centre uncertainty is large (0.000267)
+24900,gap,An alarm has occurred. Severity: MAJOR.
+ValueError.
+	 An error occurred during 'set' on device 'id_gap'.
+
+ValueError: 4.4999 outside of user-specified limits

pxii_bec/macros/luts/dcm_calibration_failures_20260903.csv

@@ -0,0 +1,3 @@
+energy,scan,reason
+25400,gap,User abort.
+25400,mono_pitch_exception,User abort.

pxii_bec/macros/luts/gap_scint_20261005-1702.csv

@@ -0,0 +1 @@
+energy,lu_bpmsum,lu_Xnorm,lu_Ynorm,samcam_x,samcam_y

pxii_bec/macros/luts/gap_scint_20261005-1703.csv

@@ -0,0 +1 @@
+energy,lu_bpmsum,lu_Xnorm,lu_Ynorm,samcam_x,samcam_y

pxii_bec/macros/luts/gap_scint_20261005-1707.csv

@@ -0,0 +1 @@
+energy,lu_bpmsum,lu_Xnorm,lu_Ynorm,samcam_x,samcam_y

pxii_bec/macros/luts/gap_scint_20261005-1709.csv

@@ -0,0 +1 @@
+energy,gap,lu_bpmsum,lu_Xnorm,lu_Ynorm,samcam_x,samcam_y

pxii_bec/macros/luts/gap_scint_20261005-1710.csv

@@ -0,0 +1 @@
+energy,gap,lu_bpmsum,lu_Xnorm,lu_Ynorm,samcam_x,samcam_y

pxii_bec/macros/luts/gap_scint_20261005-1713.csv

@@ -0,0 +1 @@
+energy,gap,lu_bpmsum,lu_Xnorm,lu_Ynorm,samcam_x,samcam_y

pxii_bec/macros/luts/gap_scint_20261005-1716.csv

@@ -0,0 +1,21 @@
+energy,gap,lu_bpmsum,lu_Xnorm,lu_Ynorm,samcam_x,samcam_y
+22000,4.5350,44.8,0.232,0.093,5.3,7.1
+22000,4.5360,46.0,0.230,0.092,5.3,7.2
+22000,4.5371,48.7,0.223,0.086,5.3,7.4
+22000,4.5381,52.3,0.216,0.081,5.1,7.6
+22000,4.5392,56.5,0.205,0.076,5.3,7.8
+22000,4.5403,61.0,0.199,0.074,5.1,7.9
+22000,4.5413,65.0,0.193,0.070,5.3,8.0
+22000,4.5424,69.7,0.188,0.066,5.4,8.2
+22000,4.5434,74.5,0.181,0.064,5.4,8.3
+22000,4.5445,79.0,0.179,0.063,5.4,8.4
+22000,4.5455,83.5,0.177,0.066,5.6,8.5
+22000,4.5466,88.1,0.175,0.058,5.7,8.7
+22000,4.5476,92.8,0.173,0.059,5.7,8.8
+22000,4.5487,96.8,0.172,0.058,5.9,8.9
+22000,4.5497,101.2,0.171,0.056,6.2,9.0
+22000,4.5508,105.2,0.175,0.058,6.3,9.1
+22000,4.5518,109.1,0.173,0.055,6.5,9.2
+22000,4.5529,112.5,0.174,0.057,6.8,9.3
+22000,4.5540,115.8,0.177,0.057,7.0,9.4
+22000,4.5550,120.1,0.181,0.056,7.3,9.5

pxii_bec/macros/luts/gap_xi_20261005-1702.csv

@@ -0,0 +1 @@
+energy,lu_bpmsum,lu_Xnorm,lu_Ynorm,xi_cam_x,xi_cam_y

pxii_bec/macros/luts/gap_xi_20261005-1703.csv

@@ -0,0 +1 @@
+energy,lu_bpmsum,lu_Xnorm,lu_Ynorm,xi_cam_x,xi_cam_y

pxii_bec/macros/luts/gap_xi_20261005-1707.csv

@@ -0,0 +1,21 @@
+energy,lu_bpmsum,lu_Xnorm,lu_Ynorm,xi_cam_x,xi_cam_y
+22000,44.0,0.231,0.097,151.6,207.8
+22000,45.2,0.229,0.090,151.7,207.7
+22000,47.8,0.219,0.085,151.8,207.7
+22000,51.2,0.211,0.084,151.8,207.7
+22000,55.3,0.200,0.079,152.0,207.9
+22000,59.2,0.199,0.075,152.1,208.2
+22000,63.9,0.191,0.074,152.3,208.3
+22000,68.3,0.188,0.069,152.5,208.3
+22000,72.8,0.179,0.067,152.6,208.5
+22000,77.3,0.180,0.065,152.8,208.7
+22000,82.3,0.175,0.063,152.9,208.9
+22000,86.3,0.174,0.063,152.9,209.0
+22000,90.6,0.175,0.062,153.1,209.1
+22000,94.9,0.174,0.060,153.2,209.3
+22000,99.3,0.173,0.059,153.2,209.5
+22000,102.7,0.177,0.058,153.5,209.6
+22000,106.3,0.179,0.060,153.7,209.7
+22000,110.0,0.179,0.059,153.9,210.0
+22000,113.4,0.182,0.055,154.5,210.1
+22000,117.0,0.185,0.056,155.2,210.0

pxii_bec/macros/luts/gap_xi_20261005-1709.csv

@@ -0,0 +1 @@
+energy,gap,lu_bpmsum,lu_Xnorm,lu_Ynorm,xi_cam_x,xi_cam_y

pxii_bec/macros/luts/gap_xi_20261005-1710.csv

@@ -0,0 +1 @@
+energy,gap,lu_bpmsum,lu_Xnorm,lu_Ynorm,xi_cam_x,xi_cam_y

pxii_bec/macros/luts/gap_xi_20261005-1713.csv

@@ -0,0 +1,21 @@
+energy,gap,lu_bpmsum,lu_Xnorm,lu_Ynorm,xi_cam_x,xi_cam_y
+22000,4.5350,45.1,0.229,0.099,151.0,208.2
+22000,4.5360,46.7,0.229,0.096,151.3,207.8
+22000,4.5371,49.5,0.218,0.093,151.5,207.8
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+22000,4.5403,61.7,0.194,0.073,151.7,208.1
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+22000,4.5540,118.7,0.179,0.054,153.8,210.1
+22000,4.5550,122.2,0.181,0.054,154.5,210.2

pxii_bec/macros/luts/gap_xi_20261005-1716.csv

@@ -0,0 +1 @@
+energy,gap,lu_bpmsum,lu_Xnorm,lu_Ynorm,xi_cam_x,xi_cam_y

pxii_bec/macros/luts/perp.csv

@@ -0,0 +1,49 @@
+energy,dcm_pitch,dcm_perp,lu_bpmsum,lu_Xnorm,lu_Ynorm,bcu_bpmsum,bcu_x,bcu_y,samcam_x,samcam_y
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+25000,-5.52407,0.00896,47.0,0.204,0.089,28.7,44.89,3.06,4.34,4.10

pxii_bec/macros/luts/perp_1.csv

@@ -0,0 +1,50 @@
+energy,dcm_pitch,dcm_perp,lu_bpmsum,lu_Xnorm,lu_Ynorm,bcu_bpmsum,bcu_x,bcu_y,samcam_x,samcam_y
+8000,-5.54961,0.04605,10420.1,0.376,0.029,3631.0,49.15,0.67,11.52,5.97
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+10000,-5.53996,0.01018,2146.7,0.395,0.012,4173.7,66.21,1.79,12.24,7.50
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+12400,-5.53288,0.01365,1743.4,0.225,0.020,1130.1,39.95,2.37,9.01,10.02
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+

pxii_bec/macros/luts/perp_actual_calc.csv

@@ -0,0 +1,9 @@
+energy,calc_perp,actual_perp
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+10000,0.0604,0.1549
+12400,0.0389,0.1239
+15000,0.0264,0.1273
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+22000,0.0122,0.1089
+25000,0.0094,0.1293

pxii_bec/macros/luts/perp_xi_20261005-1539.csv

@@ -0,0 +1,7 @@
+energy,dcm_pitch,dcm_perp,lu_bpms,lu_Xnorm,lu_Ynorm,xi_cam_x,xi_cam_y
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pxii_bec/macros/luts/perp_xi_20261005-1541.csv

@@ -0,0 +1,37 @@
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pxii_bec/macros/luts/perp_xi_20261005-1607.csv

@@ -0,0 +1,7 @@
+energy,dcm_pitch,dcm_perp,lu_bpms,lu_Xnorm,lu_Ynorm,xi_cam_x,xi_cam_y
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pxii_bec/macros/luts/perp_xi_20261005-1615.csv

@@ -0,0 +1,7 @@
+energy,dcm_pitch,dcm_perp,lu_bpms,lu_Xnorm,lu_Ynorm,xi_cam_x,xi_cam_y
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pxii_bec/macros/luts/perp_xi_20261005-1620.csv

@@ -0,0 +1,6 @@
+energy,dcm_pitch,dcm_perp,lu_bpms,lu_Xnorm,lu_Ynorm,xi_cam_x,xi_cam_y
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pxii_bec/macros/luts/perp_xi_20261005-1631.csv

@@ -0,0 +1,7 @@
+energy,dcm_pitch,dcm_perp,lu_bpms,lu_Xnorm,lu_Ynorm,xi_cam_x,xi_cam_y
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pxii_bec/macros/luts/pitch_comparison.csv

@@ -0,0 +1,14 @@
+energy,23rd Sep,6th Sep,offset
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pxii_bec/macros/luts/roll_20260923_6000.csv

@@ -0,0 +1,10 @@
+Roll,Y pos
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pxii_bec/macros/luts/roll_20260924_25000.csv

@@ -0,0 +1,10 @@
+Roll,Y pos
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pxii_bec/macros/luts/roll_20260924_6000.csv

@@ -0,0 +1,10 @@
+Roll,Y pos
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pxii_bec/macros/luts/roll_20260930_25000.csv

@@ -0,0 +1,10 @@
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pxii_bec/macros/luts/roll_20260930_6000.csv

@@ -0,0 +1,10 @@
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pxii_bec/macros/luts/roll_20261008_25000.csv

@@ -0,0 +1,10 @@
+Roll,Y pos
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pxii_bec/macros/luts/roll_20261008_6000.csv

@@ -0,0 +1,10 @@
+Roll,Y pos
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