def _graph_linear_j(self, x, y, r, reg, refresh):
g = self.graph
if not isinstance(g, RegressionGraph):
g = RegressionGraph(
container_dict={'bgcolor': self.plotter_options.bgcolor})
self.graph = g
po = self.plotter_options
g.clear()
plot = g.new_plot(padding=po.get_paddings())
if po.model_kind == WEIGHTED_MEAN_1D:
fit = 'weighted mean'
else:
fit = po.least_squares_fit
_, scatter, line = g.new_series(x=reg.xs,
y=reg.ys,
yerror=reg.yserr,
fit=fit)
ebo = ErrorBarOverlay(component=scatter, orientation='y')
scatter.underlays.append(ebo)
scatter.error_bars = ebo
add_inspector(scatter, self._additional_info)
add_axes_tools(g, plot)
g.set_x_title(po.one_d_axis)
g.set_y_title('J')
g.add_statistics()
miy = 100
may = -1
if self._individual_analyses_enabled:
sel = [
i for i, (a, x, y, e) in enumerate(zip(*self._analyses))
if a.is_omitted()
]
# plot the individual analyses
iscatter, iys = self._graph_individual_analyses(fit=None,
add_tools=False)
miy = min(iys)
may = max(iys)
# set metadata last because it will trigger a refresh
self.suppress_metadata_change = True
iscatter.index.metadata['selections'] = sel
self.suppress_metadata_change = False
g.set_y_limits(min_=miy, max_=may, pad='0.1')
g.set_x_limits(pad='0.1')
g.refresh()
fys = line.value.get_data()
self.max_j = fys.max()
self.min_j = fys.min()
