def test_sample_peaks():
pm = _load()
rtmin = pm.spectra[0].rt
rtmax = pm.spectra[-1].rt
mzmin = min(min(s.peaks[:, 0]) for s in pm.spectra)
mzmax = max(max(s.peaks[:, 0]) for s in pm.spectra)
res = sample_peaks(pm, rtmin, rtmax, mzmin, mzmax, 1)
assert res is not None
assert res.shape == (1, 2)
res = sample_peaks(pm, rtmin, rtmax, mzmin, mzmax, 10000)
assert res is not None
assert res.shape == (9876, 2)
s0 = pm.spectra[0]
pm.spectra = [s0]
res = sample_peaks(pm, rtmin, rtmax, mzmin, mzmax, 10000)
assert res is not None
assert res.shape == (76, 2), res.shape
dist = np.linalg.norm(res[0:2, :] - pm.spectra[0].peaks[0:2, :])
assert dist == 0.0
def do_backspace_pressed(self, filter, evt):
""" reset axes of plot """
all_peaks = []
for i, (pm, rtmin, rtmax, mzmin, mzmax, npeaks) in enumerate(self.data):
peaks = sample_peaks(pm, rtmin, rtmax, mzmin, mzmax, npeaks)
curve = self.curves[i]
curve.set_data(peaks[:, 0], peaks[:, 1])
all_peaks.append(peaks)
if len(all_peaks):
self.all_peaks = np.vstack(all_peaks)
else:
self.all_peaks = np.zeros((0, 2))
self.reset_x_limits()
def test_sample_peaks():
pm = _load()
rtmin = pm.spectra[0].rt
rtmax = pm.spectra[-1].rt
mzmin = min(min(s.peaks[:, 0]) for s in pm.spectra)
mzmax = max(max(s.peaks[:, 0]) for s in pm.spectra)
res = sample_peaks(pm, rtmin, rtmax, mzmin, mzmax, 1)
assert res is not None
assert res.shape == (1, 2)
res = sample_peaks(pm, rtmin, rtmax, mzmin, mzmax, 10000)
assert res is not None
assert res.shape == (9876, 2)
s0 = pm.spectra[0]
pm.spectra = [s0]
res = sample_peaks(pm, rtmin, rtmax, mzmin, mzmax, 10000)
assert res is not None
assert res.shape == (76, 2), res.shape
dist = np.linalg.norm(res[0:2, :] - pm.spectra[0].peaks[0:2, :])
assert dist == 0.0
def resample_peaks(self, mzmin, mzmax):
if mzmin == self.latest_mzmin and mzmax == self.latest_mzmax:
return
self.latest_mzmin = mzmin
self.latest_mzmax = mzmax
all_peaks = []
for i, (pm, rtmin, rtmax, __, __, npeaks) in enumerate(self.data):
peaks = sample_peaks(pm, rtmin, rtmax, mzmin, mzmax, npeaks)
curve = self.curves[i]
curve.set_data(peaks[:, 0], peaks[:, 1])
all_peaks.append(peaks)
if len(all_peaks):
self.all_peaks = np.vstack(all_peaks)
else:
self.all_peaks = np.zeros((0, 2))
