def import_peaks(self):
hdf = h5py.File(self.filename)
pdataset = hdf.require_group("/peaks")
self.peaks = get_dataset(pdataset, "peakdata")
self.exgrid = get_dataset(pdataset, "extracts").transpose()
self.exvals = self.peaks[:, 0]
hdf.close()
def import_grids(self):
hdf = h5py.File(self.filename)
msdataset = hdf.require_group(self.topname)
# Mass Space
axis = get_dataset(msdataset, "mass_axis")
sum = get_dataset(msdataset, "mass_sum")
grid = get_dataset(msdataset, "mass_grid")
self.massdat = np.transpose([axis, sum])
try:
num = int(len(grid) / len(sum))
grid = grid.reshape((int(num), len(sum))).transpose()
grid2 = np.transpose([axis for n in range(num)])
grid3 = [grid2, grid]
self.massgrid = np.transpose(grid3)
except:
print("Mass Grid Warning:", grid.shape,
sum.shape) #, len(grid)/len(sum))
# MZ Space
axis = get_dataset(msdataset, "mz_axis")
sum = get_dataset(msdataset, "mz_sum")
grid = get_dataset(msdataset, "mz_grid")
self.mzdat = np.transpose([axis, sum])
try:
num = int(len(grid) / len(sum))
grid = grid.reshape((int(num), len(sum))).transpose()
grid2 = np.transpose([axis for n in range(num)])
grid3 = [grid2, grid]
self.mzgrid = np.transpose(grid3)
except:
print("mz grid Warning:", grid.shape,
sum.shape) #, len(grid)/len(sum))
hdf.close()
return num
def read_hdf5(self, file=None):
if file is None:
file = self.filename
else:
self.filename = file
hdf = h5py.File(file)
msdata = hdf.get(self.topname + "/" + str(self.index))
self.rawdata = get_dataset(msdata, "raw_data")
self.fitdat = get_dataset(msdata, "fit_data")
self.data2 = get_dataset(msdata, "processed_data")
if ud.isempty(self.data2) and not ud.isempty(self.rawdata):
self.data2 = deepcopy(self.rawdata)
self.massdat = get_dataset(msdata, "mass_data")
self.zdata = get_dataset(msdata, "charge_data")
if self.eng.config.datanorm == 1:
try:
self.data2[:, 1] /= np.amax(self.data2[:, 1])
except:
pass
try:
self.massdat[:, 1] /= np.amax(self.massdat[:, 1])
except:
pass
try:
self.zdata[:, 1] /= np.amax(self.zdata[:, 1])
except:
pass
self.mzgrid = get_dataset(msdata, "mz_grid")
self.massgrid = get_dataset(msdata, "mass_grid")
try:
self.ztab = self.zdata[:, 0]
except:
pass
self.baseline = get_dataset(msdata, "baseline")
self.attrs = dict(list(msdata.attrs.items()))
hdf.close()