Table of Contents
Name | Direction | Type | Default | Description |
---|---|---|---|---|
InputWorkspace | Input | IMDWorkspace | Mandatory | An input MDEventWorkspace or MDHistoWorkspace with at least 3 dimensions. |
PeakDistanceThreshold | Input | number | 0.1 | Threshold distance for rejecting peaks that are found to be too close from each other. This should be some multiple of the radius of a peak. Default: 0.1. |
MaxPeaks | Input | number | 500 | Maximum number of peaks to find. Default: 500. |
DensityThresholdFactor | Input | number | 10 | The overall signal density of the workspace will be multiplied by this factor to get a threshold signal density below which boxes are NOT considered to be peaks. See the help. Default: 10.0 |
OutputWorkspace | Output | PeaksWorkspace | An output PeaksWorkspace with the peaks’ found positions. | |
AppendPeaks | Input | boolean | False | If checked, then append the peaks in the output workspace if it exists. If unchecked, the output workspace is replaced (Default). |
This algorithm is used to find single-crystal peaks in a multi-dimensional workspace (MDEventWorkspace or MDHistoWorkspace). It looks for high signal density areas, and is based on an algorithm designed by Dennis Mikkelson for ISAW.
The algorithm proceeds in this way:
Each peak created is placed in the output PeaksWorkspace, which can be a new workspace or replace the old one.
This algorithm works on a MDHistoWorkspace resulting from the BinMD v1 algorithm also. It works in the same way, except that the center of each bin is used since the centroid is not accessible. It may give better results on Workspace2D‘s that were converted to MDWorkspaces.
Example - IntegratePeaks:
The code iteslef works but disabled from doc tests as takes too long to complete. User should provide its own event nexus file instead of TOPAZ_3132_event.nxs used within this example. The original TOPAZ_3132_event.nxs file is availible in Mantid system tests repository.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 | #.. testcode:: exFindPeaksMD
def print_tableWS(pTWS,nRows):
''' Method to print part of the table workspace '''
tab_names=pTWS.keys();
for name in tab_names:
if len(name)>8:
name= name[0:8];
print "| {0:8} ".format(name),
print "|\n",
for i in xrange(0,nRows):
for name in tab_names:
col = pTWS.column(name);
data2pr=col[i]
if type(data2pr) is float:
print "| {0:>8.2f} ".format(data2pr),
else:
print "| {0:>8} ".format(data2pr),
print "|\n",
# load test workspace
Load(Filename=r'TOPAZ_3132_event.nxs',OutputWorkspace='TOPAZ_3132_event',LoadMonitors='1')
# build peak workspace necessary for IntegrateEllipsoids algorithm to work
ConvertToMD(InputWorkspace='TOPAZ_3132_event',QDimensions='Q3D',dEAnalysisMode='Elastic',Q3DFrames='Q_sample',LorentzCorrection='1',OutputWorkspace='TOPAZ_3132_md',\
MinValues='-25,-25,-25',MaxValues='25,25,25',SplitInto='2',SplitThreshold='50',MaxRecursionDepth='13',MinRecursionDepth='7')
peaks=FindPeaksMD(InputWorkspace='TOPAZ_3132_md',PeakDistanceThreshold='0.37680',MaxPeaks='50',DensityThresholdFactor='100',OutputWorkspace='TOPAZ_3132_peaks')
# print 10 rows of table workspace
print_tableWS(peaks,10)
|
Output:
1 2 3 4 5 6 7 8 9 10 11 12 13 | #.. testoutput:: exFindPeaksMD
| RunNumbe | DetID | h | k | l | Waveleng | Energy | TOF | DSpacing | Intens | SigInt | BinCount | BankName | Row | Col | QLab | QSample |
| 3132 | 1124984 | 0.00 | 0.00 | 0.00 | 3.10 | 8.49 | 14482.29 | 2.02 | 0.00 | 0.00 | 1668.00 | bank17 | 120.00 | 42.00 | [1.57771,1.21779,2.37854] | [2.99396,0.815958,0.00317344] |
| 3132 | 1156753 | 0.00 | 0.00 | 0.00 | 2.08 | 18.82 | 9725.74 | 1.30 | 0.00 | 0.00 | 1060.00 | bank17 | 145.00 | 166.00 | [2.48964,1.45725,3.88666] | [4.52618,1.71025,0.129461] |
| 3132 | 1141777 | 0.00 | 0.00 | 0.00 | 1.71 | 28.09 | 7963.17 | 1.05 | 0.00 | 0.00 | 96.00 | bank17 | 17.00 | 108.00 | [2.60836,2.31423,4.86391] | [5.69122,1.79492,-0.452799] |
| 3132 | 1125241 | 0.00 | 0.00 | 0.00 | 1.55 | 33.86 | 7252.16 | 1.01 | 0.00 | 0.00 | 83.00 | bank17 | 121.00 | 43.00 | [3.15504,2.42573,4.75121] | [5.97829,1.63473,0.0118744] |
| 3132 | 1170598 | 0.00 | 0.00 | 0.00 | 1.55 | 34.12 | 7224.59 | 0.95 | 0.00 | 0.00 | 73.00 | bank17 | 166.00 | 220.00 | [3.43363,1.70178,5.39301] | [6.07726,2.59962,0.281759] |
| 3132 | 1214951 | 0.00 | 0.00 | 0.00 | 1.89 | 22.79 | 8839.55 | 1.68 | 0.00 | 0.00 | 719.00 | bank18 | 231.00 | 137.00 | [2.73683,1.43808,2.11574] | [3.5786,0.470838,1.00329] |
| 3132 | 1207827 | 0.00 | 0.00 | 0.00 | 1.71 | 27.89 | 7991.70 | 1.32 | 0.00 | 0.00 | 447.00 | bank18 | 19.00 | 110.00 | [2.80324,2.29519,3.09134] | [4.71517,0.554412,0.37714] |
| 3132 | 1232949 | 0.00 | 0.00 | 0.00 | 1.24 | 53.28 | 5782.14 | 0.93 | 0.00 | 0.00 | 45.00 | bank18 | 53.00 | 208.00 | [4.29033,2.63319,4.46168] | [6.52658,1.27985,1.00646] |
| 3132 | 1189484 | 0.00 | 0.00 | 0.00 | 1.14 | 63.42 | 5299.28 | 0.96 | 0.00 | 0.00 | 31.00 | bank18 | 108.00 | 38.00 | [4.02414,3.39659,3.83664] | [6.4679,0.298896,0.726133] |
| 3132 | 1218337 | 0.00 | 0.00 | 0.00 | 1.01 | 79.81 | 4724.05 | 0.77 | 0.00 | 0.00 | 15.00 | bank18 | 33.00 | 151.00 | [4.96622,3.61607,5.32554] | [7.99244,1.19363,0.892655] |
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Categories: Algorithms | Optimization | PeakFinding | MDAlgorithms