Пример #1
0
    def _calculate_halpha_view(self):
        for ileaf, offset in enumerate(self.dataset.block_offsets):
            block = datfile_utilities.get_single_block_data(self.dataset.file, offset, self.dataset.block_shape)
            # this adds the temperature and pressure to the block
            block = process_data.create_data_dict(block, self.dataset.header)
            # interpolate ionisation and f parameter for each block
            block_ion, block_fpar = ionisation.block_interpolate_ionisation_f(block, self.dataset)
            block_ne = super()._get_ne(block, block_ion)
            n2 = block_ne**2 / (block_fpar * 1e16)              # parameter f is interpolated in units of 1e16 cm-3
            # calculate block opacity
            block_kappa = (np.pi * self.dataset.units.ec**2 / (self.dataset.units.m_e * self.dataset.units.c)) * \
                            self.f23 * n2 * self._gaussian(block)
            # integrate block along line of sight to get opacity
            l_edge, r_edge = process_data.get_block_edges(ileaf, self.dataset)
            opacity = super()._integrate_block(block_kappa, l_edge, r_edge)

            S = self._source_function()
            intensity = S * (1 - np.exp(-opacity))
            if self.simulation_type == 'filament':
                Ibgr = 2.2 * S
                intensity += Ibgr * np.exp(-opacity)
            # add integrated block to list, this preserves block index
            self.integrated_block_list.append(intensity)

        # merge all integrated blocks into one single 2D array
        view = super()._merge_integrated_blocks()
        # plot final result
        super()._plot_synthetic_view(view)
Пример #2
0
 def _calculate_faraday_view(self):
     for ileaf, offset in enumerate(self.dataset.block_offsets):
         block = datfile_utilities.get_single_block_data(
             self.dataset.file, offset, self.dataset.block_shape)
         # add pressure and temperature to block
         block = process_data.create_data_dict(block, self.dataset.header)
         block_ion, block_fpar = ionisation.block_interpolate_ionisation_f(
             block, self.dataset)
         block_ne = super()._get_ne(block, block_ion)
         prefactor = self.dataset.units.ec**3 / (2 * np.pi *
                                                 self.dataset.units.m_e**2 *
                                                 self.dataset.units.c**4)
         if self.line_of_sight == 'x':
             b_key = 'b1'
         elif self.line_of_sight == 'y':
             b_key = 'b2'
         else:
             b_key = 'b3'
         b_para = block[b_key] * self.dataset.units.unit_magneticfield
         l_edge, r_edge = process_data.get_block_edges(ileaf, self.dataset)
         fara_measure = super()._integrate_block(block_ne * b_para, l_edge,
                                                 r_edge) * prefactor
         self.integrated_block_list.append(fara_measure)
     view = super()._merge_integrated_blocks()
     super()._plot_synthetic_view(view)
     self.colorbar.set_label("rad cm$^{-2}$")
Пример #3
0
 def plot_1d(self):
     for ileaf, offset in enumerate(self.dataset.block_offsets):
         l_edge, r_edge = process_data.get_block_edges(ileaf, self.dataset)
         block = datfile_utilities.get_single_block_data(
             self.dataset.file, offset, self.dataset.block_shape)
         block = process_data.create_data_dict(block, self.dataset.header)
         x = np.linspace(l_edge, r_edge, self.dataset.header['block_nx'])
         self.ax.plot(x, block[self.var], '-k')
         self.ax.set_title(self.var)
Пример #4
0
    def plot_2d(self):
        if self.varmin is None or self.varmax is None:
            self.varmin, self.varmax = self.dataset.get_extrema(self.var)

        norm = None
        if self.logscale:
            norm = matplotlib.colors.LogNorm()
        # iterate over blocks in dataset
        for ileaf, offset in enumerate(self.dataset.block_offsets):
            # retrieve x and y coordinates for each block
            l_edge, r_edge = process_data.get_block_edges(ileaf, self.dataset)
            # read in block data (contains all variables)
            block = datfile_utilities.get_single_block_data(
                self.dataset.file, offset, self.dataset.block_shape)
            block = process_data.create_data_dict(block, self.dataset.header)
            x = np.linspace(l_edge[0], r_edge[0],
                            self.dataset.header['block_nx'][0])
            y = np.linspace(l_edge[1], r_edge[1],
                            self.dataset.header['block_nx'][1])
            im = self.ax.pcolormesh(x,
                                    y,
                                    block[self.var].T,
                                    cmap=self.cmap,
                                    vmin=self.varmin,
                                    vmax=self.varmax,
                                    norm=norm)

            # logic to draw the mesh
            if self.draw_mesh:
                if not r_edge[0] == self.dataset.header["xmax"][0]:
                    self.ax.vlines(x=r_edge[0],
                                   ymin=l_edge[1],
                                   ymax=r_edge[1],
                                   color=self.mesh_color,
                                   lw=self.mesh_linewidth,
                                   linestyle=self.mesh_linestyle,
                                   alpha=self.mesh_opacity)
                if not r_edge[1] == self.dataset.header["xmax"][1]:
                    self.ax.hlines(y=r_edge[1],
                                   xmin=l_edge[0],
                                   xmax=r_edge[0],
                                   color=self.mesh_color,
                                   lw=self.mesh_linewidth,
                                   linestyle=self.mesh_linestyle,
                                   alpha=self.mesh_opacity)
        self.ax.set_aspect('equal')
        divider = make_axes_locatable(self.ax)
        cax = divider.append_axes("right", size="5%", pad=0.05)
        self.colorbar = self.fig.colorbar(im, cax=cax)
        self.ax.set_title(self.var)
        self.fig.tight_layout()