How to use the nexusformat.nexus.NXdata function in nexusformat

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')

def display_logo(self):
        """Display the NeXpy logo in the plotting pane."""
        self.plot(NXdata(logo, title='NeXpy'), image=True)
        self.ax.xaxis.set_visible(False)
        self.ax.yaxis.set_visible(False)
        self.ax.title.set_visible(False)
        self.draw()

grid_locator2=locator)

        if self.number < 101:
            plotview = self
        plotviews[self.label] = self
        self.plotviews = plotviews

        self.projection_panel = None
        self.customize_panel = None

        if self.label != "Main":
            self.add_menu_action()
            self.show()

        #Add dummy NXdata group to ensure properties resolve properly
        self.data = self.plotdata = NXdata((0,1), [(0,1)])

        #Display the NeXpy logo in the plotting window
        self.figure.clf()
        self.ax.imshow(logo)
        self.ax.axes.get_xaxis().set_visible(False)
        self.ax.axes.get_yaxis().set_visible(False)
        self.draw()

else:
                self.errors = None
            plotdata = NXdata(self.signal, self.axes[0], self.errors)
        else:
            self.xaxis = self.axis[self.ndim-1]
            self.yaxis = self.axis[self.ndim-2]
            if self.ndim > 2:
                self.zaxis = self.axis[self.ndim-3]
                self.zaxis.lo = self.zaxis.hi = self.zaxis.min
                for i in range(self.ndim-3):
                    self.axis[i].lo = self.axis[i].hi \
                        = self.axis[i].data.min()
            else:
                self.zaxis = None
            self.vaxis = self.axis['signal']
            plotdata = NXdata(self.signal, [self.axes[i] for i in [-2,-1]])

        plotdata['title'] = self.data.nxtitle

        return plotdata

else:
                self.errors = None
            plotdata = NXdata(self.signal, self.axes[0], self.errors)
        else:
            self.xaxis = self.axis[self.ndim-1]
            self.yaxis = self.axis[self.ndim-2]
            if self.ndim > 2:
                for i in range(self.ndim-2):
                    self.axis[i].lo = self.axis[i].hi \
                        = np.float(self.axis[i].data[idx[i]])
                self.zaxis = self.axis[self.ndim - 3]
                self.zaxis.lo = self.zaxis.hi = self.axis[self.ndim - 3].lo
            else:
                self.zaxis = None
            self.vaxis = self.axis['signal']
            plotdata = NXdata(self.signal, [self.axes[i] for i in [-2,-1]])

        plotdata['title'] = self.data.nxtitle

        return plotdata

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

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

self.axis['signal'] = NXPlotAxis(self.signal)

        for i in range(self.ndim):
            if over:
                self.axis[i].set_data(self.axes[i], self.shape[i])
            else:
                self.axis[i] = NXPlotAxis(self.axes[i], i, self.shape[i])

        if self.ndim == 1:
            self.xaxis = self.axis[0]
            self.yaxis = self.axis['signal']
            if self.data.nxerrors and self.data.nxerrors != self.data.nxsignal:
                self.errors = self.data.nxerrors
            else:
                self.errors = None
            plotdata = NXdata(self.signal, self.axes[0], self.errors)
        else:
            self.xaxis = self.axis[self.ndim-1]
            self.yaxis = self.axis[self.ndim-2]
            if self.ndim > 2:
                for i in range(self.ndim-2):
                    self.axis[i].lo = self.axis[i].hi \
                        = np.float(self.axis[i].data[idx[i]])
                self.zaxis = self.axis[self.ndim - 3]
                self.zaxis.lo = self.zaxis.hi = self.axis[self.ndim - 3].lo
            else:
                self.zaxis = None
            self.vaxis = self.axis['signal']
            plotdata = NXdata(self.signal, [self.axes[i] for i in [-2,-1]])

        plotdata['title'] = self.data.nxtitle