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
