How to use nexusformat - 10 common examples

def get_model(self, f=None):
        self.read_parameters()
        fit = Fit(self.data, self.functions)
        if self.plot_checkbox.isChecked():
            x = fit.x
        else:
            xmin, xmax = self.get_limits()
            x = np.linspace(xmin, xmax, 1001)
        return NXdata(NXfield(fit.get_model(x, f), name='model'),
                      NXfield(x, name=fit.data.nxaxes[0].nxname), 
                      title='Fit Results')

if len(scan.G) > 0:
                entry.G = NXlog()
                desc = "SPEC geometry arrays, meanings defined by SPEC diffractometer support"
                # e.g.: SPECD/four.mac
                # http://certif.com/spec_manual/fourc_4_9.html
                entry.G.attrs['description'] = desc
                for item, value in scan.G.items():
                    entry.G[item] = NXfield(list(map(float, value.split())))
            if scan.T != '':
                entry['counting_basis'] = NXfield('SPEC scan with constant counting time')
                entry['T'] = NXfield(float(scan.T))
                entry['T'].units = 'seconds'
                entry['T'].description = 'SPEC scan with constant counting time'
            elif scan.M != '':
                entry['counting_basis'] = NXfield('SPEC scan with constant monitor count')
                entry['M'] = NXfield(float(scan.M))
                entry['M'].units = 'counts'
                entry['M'].description = 'SPEC scan with constant monitor count'
            if scan.Q != '':
                entry['Q'] = NXfield(list(map(float,scan.Q)))
                entry['Q'].description = 'hkl at start of scan'

            root['scan_' + str(key)] = entry

            self.progress_bar.setValue(int(key))
            self.update_progress()

        return root

def fix_spe(spe_file):

    entry = NXentry()
    entry.title = spe_file.nxname
    entry.incident_energy = spe_file['data/NXSPE_info/fixed_energy']
    entry.data = spe_file.data.data
    entry.data.error.rename('errors')

    s = raw_input("Emin Emax Phimin Phimax dPhi: ")
    xmin, xmax, ymin, ymax, dy = [float(i) for i in s.split(' ')]    
    mfit(entry.data, xmin, xmax, ymin, ymax, dy)
    
    return entry

scan.interpret()
            entry = NXentry()
            entry.title = str(scan)
            entry.date = utils.iso8601(scan.date)  
            entry.command = scan.scanCmd 
            entry.scan_number = NXfield(scan.scanNum)
            entry.comments = '\n'.join(scan.comments)
            entry.data = self.scan_NXdata(scan)            # store the scan data
            entry.positioners = self.metadata_NXlog(scan.positioner, 
                                                    'SPEC positioners (#P & #O lines)')
            if hasattr(scan, 'metadata') and len(scan.metadata) > 0:
                entry.metadata = self.metadata_NXlog(scan.metadata, 
                                                     'SPEC metadata (UNICAT-style #H & #V lines)')

            if len(scan.G) > 0:
                entry.G = NXlog()
                desc = "SPEC geometry arrays, meanings defined by SPEC diffractometer support"
                # e.g.: SPECD/four.mac
                # http://certif.com/spec_manual/fourc_4_9.html
                entry.G.attrs['description'] = desc
                for item, value in scan.G.items():
                    entry.G[item] = NXfield(list(map(float, value.split())))
            if scan.T != '':
                entry['counting_basis'] = NXfield('SPEC scan with constant counting time')
                entry['T'] = NXfield(float(scan.T))
                entry['T'].units = 'seconds'
                entry['T'].description = 'SPEC scan with constant counting time'
            elif scan.M != '':
                entry['counting_basis'] = NXfield('SPEC scan with constant monitor count')
                entry['M'] = NXfield(float(scan.M))
                entry['M'].units = 'counts'
                entry['M'].description = 'SPEC scan with constant monitor count'

return '\n'.join(tree.split('\n')[0:50])+'\n...'
            else:
                return tree
        elif role == QtCore.Qt.DecorationRole:
            if isinstance(self.node, NXroot):
                if self.node.nxfilemode == 'r':
                    if self.node._file_modified:
                        return self._locked_modified
                    else:
                        return self._locked
                elif self.node.nxfilemode == 'rw':
                    if self.node._file_modified:
                        return self._unlocked_modified
                    else:
                        return self._unlocked
            elif isinstance(self.node, NXlink):
                return self._linked
            else:
                return None

def save_fit(self):
        """Saves fit results to an NXentry"""
        self.read_parameters()
        group = NXprocess()
        group['data'] = self.data
        for f in self.functions:
            group[f.name] = self.get_model(f)
            parameters = NXparameters()
            for p in f.parameters:
                parameters[p.name] = NXfield(p.value, error=p.stderr, 
                                             initial_value=p.init_value,
                                             min=str(p.min), max=str(p.max))
            group[f.name].insert(parameters)
        if self.fit is not None:
            group['program'] = 'lmfit'
            group['version'] = lmfit.__version__
            group['title'] = 'Fit Results'
            group['fit'] = self.get_model()
            fit = NXparameters()
            fit.nfev = self.fit.result.nfev
            fit.chisq = self.fit.result.chisqr
            fit.redchi = self.fit.result.redchi
            fit.message = self.fit.result.message
            group['statistics'] = fit

def scan_NXdata(self, scan):
        '''
        return the scan data in an NXdata object
        '''
        nxdata = NXdata()

        if len(scan.data) == 0:       # what if no data?
            # since no data available, provide trivial, fake data
            # this keeps the NXdata base class compliant with the NeXus standard
            nxdata.attrs['description'] = 'SPEC scan has no data'
            nxdata['noSpecData_y'] = NXfield([0, 0])   # primary Y axis
            nxdata['noSpecData_x'] = NXfield([0, 0])   # primary X axis
            nxdata.nxsignal = nxdata['noSpecData_y']
            nxdata.nxaxes   = [nxdata['noSpecData_x'], ]
            return nxdata

        nxdata.attrs['description'] = 'SPEC scan data'
        
        scan_type = scan.scanCmd.split()[0]
        if scan_type in ('mesh', 'hklmesh'):
            # hklmesh  H 1.9 2.1 100  K 1.9 2.1 100  -800000

def save_fit(self):
        """Saves fit results to an NXentry"""
        self.read_parameters()
        group = NXprocess()
        group['data'] = self.data
        for f in self.functions:
            group[f.name] = self.get_model(f)
            parameters = NXparameters()
            for p in f.parameters:
                parameters[p.name] = NXfield(p.value, error=p.stderr, 
                                             initial_value=p.init_value,
                                             min=str(p.min), max=str(p.max))
            group[f.name].insert(parameters)
        if self.fit is not None:
            group['program'] = 'lmfit'
            group['version'] = lmfit.__version__
            group['title'] = 'Fit Results'
            group['fit'] = self.get_model()
            fit = NXparameters()
            fit.nfev = self.fit.result.nfev

#histogram and normalize 
        norm, nbin = np.histogramdd((Ein,Qin), bins=(Eb,Qb))
        hist, hbin = np.histogramdd((Ein,Qin), bins=(Eb,Qb), weights=datain)
        if self.entry['data'].nxerrors:
            histe, hbin = np.histogramdd((Ein,Qin), bins=(Eb,Qb), weights=errorsin*errorsin)
            histe = histe**0.5
            err = histe/norm

        I = NXfield(hist/norm, name='S(Q,E)')

        Qb = NXfield(Qb[:-1]+dQ/2., name='Q')
        Eb = NXfield(Eb[:-1]+dE/2., name='E')

        result = NXdata(I, (Eb, Qb))
        if self.entry.data.nxerrors:
            result.errors = NXfield(err)
        return result

qmax = Q.max()
        emin = E.min()
        emax = E.max()
        NQ = int((qmax-qmin)/dQ) + 1
        NE = int((emax-emin)/dE) + 1
        Qb = np.linspace(qmin, qmax, NQ)
        Eb = np.linspace(emin, emax, NE)
        #histogram and normalize 
        norm, nbin = np.histogramdd((Ein,Qin), bins=(Eb,Qb))
        hist, hbin = np.histogramdd((Ein,Qin), bins=(Eb,Qb), weights=datain)
        if self.entry['data'].nxerrors:
            histe, hbin = np.histogramdd((Ein,Qin), bins=(Eb,Qb), weights=errorsin*errorsin)
            histe = histe**0.5
            err = histe/norm

        I = NXfield(hist/norm, name='S(Q,E)')

        Qb = NXfield(Qb[:-1]+dQ/2., name='Q')
        Eb = NXfield(Eb[:-1]+dE/2., name='E')

        result = NXdata(I, (Eb, Qb))
        if self.entry.data.nxerrors:
            result.errors = NXfield(err)
        return result