From cb858c79341fc48cbd959f431b6f792614ca68de Mon Sep 17 00:00:00 2001
From: Antti Soininen <soininen@ill.fr>
Date: Wed, 20 Sep 2017 13:35:23 +0200
Subject: [PATCH] Use named variables for slices instead of random-looking
numbers.
Re #20472
---
.../ComputeCalibrationCoefVanTest.py | 23 +++++++++++--------
1 file changed, 14 insertions(+), 9 deletions(-)
diff --git a/Framework/PythonInterface/test/python/plugins/algorithms/ComputeCalibrationCoefVanTest.py b/Framework/PythonInterface/test/python/plugins/algorithms/ComputeCalibrationCoefVanTest.py
index d1b14ec7adb..c3b6500598e 100644
--- a/Framework/PythonInterface/test/python/plugins/algorithms/ComputeCalibrationCoefVanTest.py
+++ b/Framework/PythonInterface/test/python/plugins/algorithms/ComputeCalibrationCoefVanTest.py
@@ -22,6 +22,10 @@ class ComputeCalibrationCoefVanTest(unittest.TestCase):
self._table = FindEPP(input_ws, OutputWorkspace="table")
AddSampleLog(self._input_ws, LogName='wavelength', LogText='4.0',
LogType='Number', LogUnit='Angstrom')
+ # These ranges correspond to 6*FWHM of the gaussian above,
+ # the integration ranges of ComputeCalibrationCoefVan.
+ self._lowerBoundRange = slice(28, 73)
+ self._upperBoundRange = slice(27, 74)
def test_output(self):
outputWorkspaceName = "output_ws"
@@ -52,11 +56,12 @@ class ComputeCalibrationCoefVanTest(unittest.TestCase):
self.assertTrue(alg_test.isExecuted())
wsoutput = AnalysisDataService.retrieve(outputWorkspaceName)
- # check whether sum is calculated correctly, for theta=0, dwf=1
- y_sumMin = np.sum(self._input_ws.readY(0)[28:73])
- y_sumMax = np.sum(self._input_ws.readY(0)[27:74])
- e_sumMin = np.sqrt(np.sum(np.square(self._input_ws.readE(0)[28:73])))
- e_sumMax = np.sqrt(np.sum(np.square(self._input_ws.readE(0)[27:74])))
+ # Check whether the sum is calculated correctly, for theta=0, dwf=1
+ # The result should be somewhere between the full bin sums.
+ y_sumMin = np.sum(self._input_ws.readY(0)[self._lowerBoundRange])
+ y_sumMax = np.sum(self._input_ws.readY(0)[self._upperBoundRange])
+ e_sumMin = np.sqrt(np.sum(np.square(self._input_ws.readE(0)[self._lowerBoundRange])))
+ e_sumMax = np.sqrt(np.sum(np.square(self._input_ws.readE(0)[self._upperBoundRange])))
self.assertLess(y_sumMin, wsoutput.readY(0)[0])
self.assertGreater(y_sumMax, wsoutput.readY(0)[0])
self.assertLess(e_sumMin, wsoutput.readE(0)[0])
@@ -140,10 +145,10 @@ class ComputeCalibrationCoefVanTest(unittest.TestCase):
else:
raise RuntimeError("Unsupported temperature supplied to " +
"_checkDWF(). Use 0K or 293K only.")
- y_sumMin = np.sum(self._input_ws.readY(1)[28:73])
- y_sumMax = np.sum(self._input_ws.readY(1)[27:74])
- e_sumMin = np.sqrt(np.sum(np.square(self._input_ws.readE(1)[28:73])))
- e_sumMax = np.sqrt(np.sum(np.square(self._input_ws.readE(1)[27:74])))
+ y_sumMin = np.sum(self._input_ws.readY(1)[self._lowerBoundRange])
+ y_sumMax = np.sum(self._input_ws.readY(1)[self._upperBoundRange])
+ e_sumMin = np.sqrt(np.sum(np.square(self._input_ws.readE(1)[self._lowerBoundRange])))
+ e_sumMax = np.sqrt(np.sum(np.square(self._input_ws.readE(1)[self._upperBoundRange])))
mvan = 0.001*50.942/N_A
Bcoef = 3.0*integral*1e+20*hbar*hbar/(2.0*mvan*k*389.0)
dwf = np.exp(
--
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