def handle_show_iso_evo(self, obj):
from pychron.graph.stacked_regression_graph import StackedRegressionGraph
self.manager.load_raw_data(self.model)
g = StackedRegressionGraph()
for ni in obj[::-1]:
iso = next((i for i in self.model.isotopes.itervalues() if i.name == ni.name), None)
g.new_plot(padding=[60, 10, 10, 40])
g.new_series(iso.xs, iso.ys,
fit=iso.fit,
filter_outliers_dict=iso.filter_outliers_dict)
g.set_x_limits(min_=0, max_=iso.xs[-1] * 1.1)
g.set_x_title('Time (s)')
g.set_y_title(iso.name)
g.refresh()
g.window_title = '{} {}'.format(self.name, ','.join([i.name for i in obj]))
self.manager.application.open_view(g)
def handle_show_iso_evo(self, obj):
from pychron.graph.stacked_regression_graph import StackedRegressionGraph
self.manager.load_raw_data(self.model)
g = StackedRegressionGraph()
for ni in obj[::-1]:
iso = next((i for i in self.model.isotopes.itervalues()
if i.name == ni.name), None)
g.new_plot(padding=[60, 10, 10, 40])
g.new_series(iso.xs,
iso.ys,
fit=iso.fit,
filter_outliers_dict=iso.filter_outliers_dict)
g.set_x_limits(min_=0, max_=iso.xs[-1] * 1.1)
g.set_x_title('Time (s)')
g.set_y_title(iso.name)
g.refresh()
g.window_title = '{} {}'.format(self.name,
','.join([i.name for i in obj]))
self.manager.application.open_view(g)
def show_evolutions_factory(record_id, isotopes, show_evo=True, show_equilibration=False, show_baseline=False):
if WINDOW_CNT > 20:
information(None, 'You have too many Isotope Evolution windows open. Close some before proceeding')
return
from pychron.graph.stacked_regression_graph import StackedRegressionGraph
if not show_evo:
xmi = Inf
xma = -Inf
else:
xmi, xma = 0, -Inf
g = StackedRegressionGraph(resizable=True)
g.plotcontainer.spacing = 10
g.window_height = min(275 * len(isotopes), 800)
g.window_x = OX + XOFFSET * WINDOW_CNT
g.window_y = OY + YOFFSET * WINDOW_CNT
isotopes = sort_isotopes(isotopes, reverse=False, key=lambda x: x.name)
for i, iso in enumerate(isotopes):
ymi, yma = Inf, -Inf
p = g.new_plot(padding=[80, 10, 10, 40])
g.add_limit_tool(p, 'x')
g.add_limit_tool(p, 'y')
g.add_axis_tool(p, p.x_axis)
g.add_axis_tool(p, p.y_axis)
p.y_axis.title_spacing = 50
if show_equilibration:
sniff = iso.sniff
g.new_series(sniff.xs, sniff.ys,
type='scatter',
fit=None,
color='red')
ymi, yma = min_max(ymi, yma, sniff.ys)
xmi, xma = min_max(xmi, xma, sniff.xs)
if show_evo:
g.new_series(iso.xs, iso.ys,
fit=iso.fit,
filter_outliers_dict=iso.filter_outliers_dict,
color='black')
ymi, yma = min_max(ymi, yma, iso.ys)
xmi, xma = min_max(xmi, xma, iso.xs)
if show_baseline:
baseline = iso.baseline
g.new_series(baseline.xs, baseline.ys,
type='scatter', fit=baseline.fit,
filter_outliers_dict=baseline.filter_outliers_dict,
color='blue')
ymi, yma = min_max(ymi, yma, baseline.ys)
xmi, xma = min_max(xmi, xma, baseline.xs)
g.set_x_limits(min_=xmi, max_=xma, pad='0.025,0.05')
g.set_y_limits(min_=ymi, max_=yma, pad='0.05', plotid=i)
g.set_x_title('Time (s)', plotid=i)
g.set_y_title('{} (fA)'.format(iso.name), plotid=i)
g.refresh()
g.window_title = '{} {}'.format(record_id, ','.join([i.name for i in reversed(isotopes)]))
return g
def show_evolutions_factory(record_id,
isotopes,
show_evo=True,
show_equilibration=False,
show_baseline=False):
if WINDOW_CNT > 20:
information(
None,
'You have too many Isotope Evolution windows open. Close some before proceeding'
)
return
from pychron.graph.stacked_regression_graph import StackedRegressionGraph
if not show_evo:
xmi = Inf
xma = -Inf
else:
xmi, xma = 0, -Inf
g = StackedRegressionGraph(resizable=True)
g.plotcontainer.spacing = 10
g.window_height = min(275 * len(isotopes), 800)
g.window_x = OX + XOFFSET * WINDOW_CNT
g.window_y = OY + YOFFSET * WINDOW_CNT
isotopes = sort_isotopes(isotopes, reverse=False, key=lambda x: x.name)
for i, iso in enumerate(isotopes):
ymi, yma = Inf, -Inf
p = g.new_plot(padding=[80, 10, 10, 40])
g.add_limit_tool(p, 'x')
g.add_limit_tool(p, 'y')
g.add_axis_tool(p, p.x_axis)
g.add_axis_tool(p, p.y_axis)
p.y_axis.title_spacing = 50
if show_equilibration:
sniff = iso.sniff
g.new_series(sniff.xs,
sniff.ys,
type='scatter',
fit=None,
color='red')
ymi, yma = min_max(ymi, yma, sniff.ys)
xmi, xma = min_max(xmi, xma, sniff.xs)
if show_evo:
g.new_series(iso.xs,
iso.ys,
fit=iso.fit,
filter_outliers_dict=iso.filter_outliers_dict,
color='black')
ymi, yma = min_max(ymi, yma, iso.ys)
xmi, xma = min_max(xmi, xma, iso.xs)
if show_baseline:
baseline = iso.baseline
g.new_series(baseline.xs,
baseline.ys,
type='scatter',
fit=baseline.fit,
filter_outliers_dict=baseline.filter_outliers_dict,
color='blue')
ymi, yma = min_max(ymi, yma, baseline.ys)
xmi, xma = min_max(xmi, xma, baseline.xs)
g.set_x_limits(min_=xmi, max_=xma, pad='0.025,0.05')
g.set_y_limits(min_=ymi, max_=yma, pad='0.05', plotid=i)
g.set_x_title('Time (s)', plotid=i)
g.set_y_title('{} (fA)'.format(iso.name), plotid=i)
g.refresh()
g.window_title = '{} {}'.format(
record_id, ','.join([i.name for i in reversed(isotopes)]))
return g
