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Filter_by_time_stamp_ZYP.py(fichier créé)
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| 1 | + | # | |
| 2 | + | # Filter_by_time_stamp_ZYP.py | |
| 3 | + | # | |
| 4 | + | # --------------------------------------------------------------------------- | |
| 5 | + | # Script for filtering events based on time stamp | |
| 6 | + | # --------------------------------------------------------------------------- | |
| 7 | + | # | |
| 8 | + | # ---------------------------- | |
| 9 | + | # Yuanpeng Zhang @ Nov-10-2024 | |
| 10 | + | # ---------------------------- | |
| 11 | + | # | |
| 12 | + | from mantid.simpleapi import * | |
| 13 | + | ||
| 14 | + | ############################################################################### | |
| 15 | + | # ------------------------------ Input section -------------------------------- | |
| 16 | + | ############################################################################### | |
| 17 | + | ||
| 18 | + | # Inputs for runs information. | |
| 19 | + | title = 'output_th' | |
| 20 | + | IPTS = 32368 | |
| 21 | + | run = 1532451 | |
| 22 | + | background = None | |
| 23 | + | BackgroundScale = 1 | |
| 24 | + | vanadium = 1530874 # Run number or `None` | |
| 25 | + | vanadium_IPTS = 23858 | |
| 26 | + | out_dir = "/SNS/users/y8z/Temp" | |
| 27 | + | ||
| 28 | + | # Inputs for runs control. | |
| 29 | + | normaliseBy = 'Monitor' # One on (None, Monitor, Time) | |
| 30 | + | units = 'Theta' # One of (Theta, ElasticQ, ElasticDSpacing) | |
| 31 | + | Binning = '5,125,1200' # Min,Max,Number_of_bins | |
| 32 | + | log_binning = False | |
| 33 | + | ||
| 34 | + | # Inputs for time stamp for filtering | |
| 35 | + | # 'time_interval = 100' here means all data falling in between the start | |
| 36 | + | # and stop time will be filtered into a single dataset. | |
| 37 | + | start_time = '2024-10-23T03:44:06' | |
| 38 | + | stop_time = '2024-10-23T03:52:26' | |
| 39 | + | time_interval = '100' | |
| 40 | + | unit_of_time = 'Percent' | |
| 41 | + | time_tolerance = 0 | |
| 42 | + | ||
| 43 | + | ############################################################################### | |
| 44 | + | # ---------------------------- Execution section ------------------------------ | |
| 45 | + | ############################################################################### | |
| 46 | + | ||
| 47 | + | # Load vandium if not already loaded. | |
| 48 | + | vanadium_ws = 'HB2C_{}'.format(vanadium) | |
| 49 | + | ||
| 50 | + | if vanadium_ws not in mtd: | |
| 51 | + | LoadWAND(IPTS=vanadium_IPTS, | |
| 52 | + | RunNumbers=vanadium, | |
| 53 | + | OutputWorkspace=vanadium_ws) | |
| 54 | + | ||
| 55 | + | # Load background if needed and if not already loaded. | |
| 56 | + | if background is not None: | |
| 57 | + | background_ws = 'HB2C_{}'.format(background) | |
| 58 | + | if background_ws not in mtd: | |
| 59 | + | LoadEventNexus( | |
| 60 | + | Filename='/HFIR/HB2C/IPTS-{}/nexus/HB2C_{}.nxs.h5'.format( | |
| 61 | + | IPTS, background | |
| 62 | + | ), | |
| 63 | + | OutputWorkspace=background_ws, | |
| 64 | + | LoadMonitors=True | |
| 65 | + | ) | |
| 66 | + | else: | |
| 67 | + | background_ws = None | |
| 68 | + | ||
| 69 | + | # Load data if not already loaded | |
| 70 | + | ws = 'HB2C_{}'.format(run) | |
| 71 | + | ||
| 72 | + | if ws not in mtd: | |
| 73 | + | LoadEventNexus( | |
| 74 | + | Filename='/HFIR/HB2C/IPTS-{}/nexus/HB2C_{}.nxs.h5'.format(IPTS, run), | |
| 75 | + | OutputWorkspace=ws, | |
| 76 | + | LoadMonitors=True) | |
| 77 | + | # Mask detectors to be the same as vanadium | |
| 78 | + | MaskDetectors(ws, MaskedWorkspace=vanadium_ws) | |
| 79 | + | ||
| 80 | + | # Filter events | |
| 81 | + | GenerateEventsFilter(InputWorkspace=ws, | |
| 82 | + | OutputWorkspace='filter', | |
| 83 | + | InformationWorkspace='info', | |
| 84 | + | StartTime=start_time, | |
| 85 | + | StopTime=stop_time, | |
| 86 | + | TimeInterval=time_interval, | |
| 87 | + | TimeTolerance=time_tolerance, | |
| 88 | + | UnitOfTime=unit_of_time) | |
| 89 | + | FilterEvents(InputWorkspace=ws, | |
| 90 | + | SplitterWorkspace='filter', | |
| 91 | + | OutputWorkspaceBaseName=ws + '_filtered', | |
| 92 | + | InformationWorkspace='info', | |
| 93 | + | GroupWorkspaces=True, | |
| 94 | + | FilterByPulseTime=True, | |
| 95 | + | OutputWorkspaceIndexedFrom1=True) | |
| 96 | + | FilterEvents(InputWorkspace=ws + '_monitors', | |
| 97 | + | SplitterWorkspace='filter', | |
| 98 | + | OutputWorkspaceBaseName=ws + '_filtered_mon', | |
| 99 | + | InformationWorkspace='info', | |
| 100 | + | GroupWorkspaces=True, | |
| 101 | + | FilterByPulseTime=True, | |
| 102 | + | SpectrumWithoutDetector='Skip only if TOF correction', | |
| 103 | + | OutputWorkspaceIndexedFrom1=True) | |
| 104 | + | ||
| 105 | + | # Set the monitor count on filtered WS | |
| 106 | + | for n in range(mtd[ws + '_filtered'].getNumberOfEntries()): | |
| 107 | + | AddSampleLog( | |
| 108 | + | mtd[ws + '_filtered'].getItem(n), | |
| 109 | + | LogName="gd_prtn_chrg", | |
| 110 | + | LogType='Number', | |
| 111 | + | NumberType='Double', | |
| 112 | + | LogText=str( | |
| 113 | + | mtd[ws + '_filtered_mon'].getItem(n).getNumberEvents() | |
| 114 | + | ) | |
| 115 | + | ) | |
| 116 | + | ||
| 117 | + | if background is not None: | |
| 118 | + | AddSampleLog( | |
| 119 | + | background_ws, LogName="gd_prtn_chrg", | |
| 120 | + | LogType='Number', | |
| 121 | + | NumberType='Double', | |
| 122 | + | LogText=str( | |
| 123 | + | mtd[background_ws + '_monitors'].getNumberEvents() | |
| 124 | + | ) | |
| 125 | + | ) | |
| 126 | + | ||
| 127 | + | # Run powder diffraction reduction | |
| 128 | + | xmin, xmax, bins = Binning.split(',') | |
| 129 | + | WANDPowderReduction(ws + '_filtered', | |
| 130 | + | CalibrationWorkspace=vanadium_ws, | |
| 131 | + | BackgroundWorkspace=background_ws, | |
| 132 | + | BackgroundScale=BackgroundScale, | |
| 133 | + | XMin=xmin, | |
| 134 | + | XMax=xmax, | |
| 135 | + | NumberBins=bins, | |
| 136 | + | Target=units, | |
| 137 | + | LogBinning=log_binning, | |
| 138 | + | NormaliseBy=normaliseBy, | |
| 139 | + | OutputWorkspace=title) | |
| 140 | + | ||
| 141 | + | out_wksp = mtd[title] | |
| 142 | + | fn_tmp = f"{title}_" | |
| 143 | + | fn_tmp += f"{start_time}_{stop_time}.dat" | |
| 144 | + | SaveAscii( | |
| 145 | + | InputWorkspace=out_wksp, | |
| 146 | + | Filename=os.path.join( | |
| 147 | + | out_dir, | |
| 148 | + | fn_tmp | |
| 149 | + | ) | |
| 150 | + | ) | |
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