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()