def _create_ideogram(self): self.ideogram_options = IdeogramOptionsManager() model = IdeogramModel(analyses=self.analyses, plot_options=self.ideogram_options.plotter_options) model.refresh_panels() p = model.next_panel() self.ideogram_graph = p.make_graph() self.ideogram_model = model self.ideogram_panel = p
def _create_ideogram(self): self.ideogram_options = IdeogramOptionsManager() model = IdeogramModel( analyses=self.analyses, plot_options=self.ideogram_options.plotter_options) model.refresh_panels() p = model.next_panel() self.ideogram_graph = p.make_graph() self.ideogram_model = model self.ideogram_panel = p
def get_component(self, ans, plotter_options): # meta = None # if self.figure_model: # meta = self.figure_model.dump_metadata() if plotter_options is None: pom = IdeogramOptionsManager() plotter_options = pom.plotter_options from pychron.processing.plotters.ideogram.ideogram_model import IdeogramModel model = IdeogramModel(plot_options=plotter_options) model.analyses = ans iv = FigureContainer(model=model) # if meta: # model.load_metadata(meta) return model, iv.component
def get_component(self, ans, plotter_options): # meta = None # if self.figure_model: # meta = self.figure_model.dump_metadata() if plotter_options is None: pom = IdeogramOptionsManager() plotter_options = pom.plotter_options model = self.figure_model if not model: from pychron.processing.plotters.ideogram.ideogram_model import IdeogramModel model = IdeogramModel(plot_options=plotter_options, titles=self.titles) model.trait_set(plot_options=plotter_options, titles=self.titles, analyses=ans) iv = FigureContainer(model=model) component = iv.component po = plotter_options m = po.mean_calculation_kind s = po.nsigma es = po.error_bar_nsigma ecm = po.error_calc_method captext = u'Mean: {} +/-{}\u03c3 Data: +/-{}\u03c3. ' \ u'Error Type:{}. Analyses omitted from calculation \n' \ u'indicated by open squares. Dashed line represents ' \ u'cumulative probability for all analyses'.format(m, s, es, ecm) self._add_caption(component, plotter_options, default_captext=captext) # if meta: # model.load_metadata(meta) return model, component