def test_peaks1d(self):
"test 1D peak picker"
print(self.test_peaks1d.__doc__)
M = np.zeros((30))
M[5] = 20
M[7] = 8
M[15] = 11
M[10] = 20
d = _NPKData(buffer=M)
d.pp(threshold=3)
self.assertEqual(list(d.peaks.pos), [5.0, 7.0, 10.0, 15.0])
self.assertEqual(list(d.peaks.intens), [20.0, 8.0, 20.0, 11.0])
d.peaks.report(NbMaxPeaks=2)
def test_peaks2d(self):
"test 2D peak picker"
print(self.test_peaks2d.__doc__)
M = np.zeros((30, 30))
M[5, 7] = 20
M[10, 12] = 20
d = _NPKData(buffer=M)
d.pp(
threshold=10
) # 3*d.std was just right - but does not work anymore with robust_stats() !
self.assertEqual(list(d.peaks.posF1), [5, 10])
self.assertEqual(list(d.peaks.posF2), [7, 12])
self.assertEqual(list(d.peaks.intens), [20.0, 20.0])
def test_center1d(self):
x = np.arange(5)
y = center(x, 2.2, 10.0, 1.2)
# y == [ -2.36111111e+01 -4.44089210e-15 9.72222222e+00 5.55555556e+00 -1.25000000e+01]
self.assertAlmostEqual(y[2], 9.72222222)
d = _NPKData(buffer=np.maximum(y, 0.0))
d.peaks = Peak1DList(source=d)
d.peaks.append(Peak1D(0, "0", 9.7, 2))
d.peaks[-1].width = 1.0
d.centroid(npoints=3)
self.assertAlmostEqual(d.peaks[0].pos, 2.2)
self.assertAlmostEqual(d.peaks[0].intens, 10.0)
self.assertAlmostEqual(d.peaks[0].width, 1.2 * np.sqrt(2))
d.peaks.report(NbMaxPeaks=10)
def test_center2d(self):
M = np.zeros((20, 20))
# add one peak at (F1,F2) 5.3, 7.9 with widthes (5.0,1.3)
for y in range(1, 10):
for x in range(6, 11):
# yo, x0 intens, widthy, widthx
M[y, x] = center2d(np.array([y, x]), 5.3, 7.9, 20.0, 5.0, 1.3)
#print (M[1:10,6:11])
self.assertAlmostEqual(M[2, 7], 5.87777515)
d = _NPKData(buffer=np.maximum(M, 0.0))
d.peaks = Peak2DList(source=d)
# self, Id, label, intens, posF1, posF2
d.peaks.append(Peak2D(0, "0", 18.0, 5, 8))
d.centroid(npoints_F1=5)
self.assertAlmostEqual(d.peaks[0].posF1, 5.3)
self.assertAlmostEqual(d.peaks[0].posF2, 7.9)
self.assertAlmostEqual(d.peaks[0].intens, 20.0)
self.assertAlmostEqual(d.peaks[0].widthF1, 5.0 * np.sqrt(2))
self.assertAlmostEqual(d.peaks[0].widthF2, 1.3 * np.sqrt(2))