def _plot_series(self, po, pid, omits):
graph = self.graph
try:
ys = [ai.nominal_value for ai in self._unpack_attr(po.name)]
yerr = [ai.std_dev for ai in self._unpack_attr(po.name)]
n = [ai.record_id for ai in self.sorted_analyses]
args = graph.new_series(x=self.xs,
y=ys,
display_index=ArrayDataSource(data=n),
yerror=yerr,
fit=po.fit,
plotid=pid,
type='scatter')
if len(args) == 2:
scatter, p = args
else:
p, scatter, l = args
sel = scatter.index.metadata.get('selections', [])
sel += omits
scatter.index.metadata['selections'] = list(set(sel))
if po.use_time_axis:
p.x_axis.tick_generator = ScalesTickGenerator(
scale=CalendarScaleSystem())
#p.value_scale = po.scale
self._add_error_bars(scatter, yerr, 'y', 1, visible=po.y_error)
except (KeyError, ZeroDivisionError), e:
print 'Series', e
def set_time_xaxis(self, plotid=None):
if plotid is None:
plotid = len(self.plots) - 1
p = self.plots[plotid]
p.x_axis.tick_generator = ScalesTickGenerator(
scale=CalendarScaleSystem())
def set_time_xaxis(self, plotid=None):
from chaco.scales_tick_generator import ScalesTickGenerator
from chaco.scales.time_scale import CalendarScaleSystem
if plotid is None:
plotid = len(self.plots) - 1
p = self.plots[plotid]
p.x_axis.tick_generator = ScalesTickGenerator(
scale=CalendarScaleSystem())
def _plot_series(self, po, pid, xs, ys):
graph = self.graph
try:
scatter, p = graph.new_series(x=xs,
y=ys,
fit=po.fit,
plotid=pid,
type='scatter')
if po.use_time_axis:
p.x_axis.tick_generator = ScalesTickGenerator(
scale=CalendarScaleSystem())
except (KeyError, ZeroDivisionError), e:
print 'Series', e
def _plot_series(self, po, pid, omits):
graph = self.graph
try:
if po.name == 'AnalysisType':
ys = list(self._unpack_attr(po.name))
kw = dict(y=ys, colors=ys, type='cmap_scatter', marker_size=4, color_map_name='gist_rainbow')
yerr = None
value_format = analysis_type_formatter
set_ylimits = False
else:
value_format = None
ys = array([ai.nominal_value for ai in self._unpack_attr(po.name)])
yerr = array([ai.std_dev for ai in self._unpack_attr(po.name)])
kw = dict(y=ys, yerror=yerr, type='scatter')
set_ylimits = True
n = [ai.record_id for ai in self.sorted_analyses]
args = graph.new_series(x=self.xs,
display_index=ArrayDataSource(data=n),
fit=po.fit,
plotid=pid,
# type='scatter',
add_inspector=False,
**kw)
if len(args) == 2:
scatter, p = args
else:
p, scatter, l = args
sel = scatter.index.metadata.get('selections', [])
sel += omits
scatter.index.metadata['selections'] = list(set(sel))
self._add_scatter_inspector(scatter, value_format=value_format)
if po.use_time_axis:
p.x_axis.tick_generator = ScalesTickGenerator(scale=CalendarScaleSystem())
#p.value_scale = po.scale
end_caps = True
if po.y_error and yerr is not None:
self._add_error_bars(scatter, yerr, 'y', 2, end_caps, visible=True)
if set_ylimits:
mi, mx = min(ys - 2 * yerr), max(ys + 2 * yerr)
graph.set_y_limits(min_=mi, max_=mx, pad='0.1', plotid=pid)
except (KeyError, ZeroDivisionError, AttributeError), e:
print 'Series', e
def _set_scale(axis, system):
p = curplot()
if p:
if axis == 'x':
log_linear_trait = 'index_scale'
ticks = p.x_ticks
else:
log_linear_trait = 'value_scale'
ticks = p.y_ticks
if system == 'time':
system = CalendarScaleSystem()
if isinstance(system, six.string_types):
setattr(p, log_linear_trait, system)
else:
if system is None:
system = dict(linear=p.linear_scale, log=p.log_scale).get(
p.get(log_linear_trait), p.linear_scale)
ticks.scale = system
p.request_redraw()
def test_calendar_scale_system_01():
css = CalendarScaleSystem()
ticks = css.ticks(0,10)
assert len(ticks) == 11
assert (np.array(ticks) == np.linspace(0,10,11)).all()
def test_calendar_scale_system_01():
css = CalendarScaleSystem()
ticks = css.ticks(0, 10)
assert len(ticks) == 11
assert (np.array(ticks) == np.linspace(0, 10, 11)).all()
def test_calendar_scale_system_01(self):
css = CalendarScaleSystem()
ticks = css.ticks(0, 10)
self.assertEqual(len(ticks), 11)
nptest.assert_array_equal(np.array(ticks), np.linspace(0, 10, 11))
def _plot_series(self, po, pid, omits):
graph = self.graph
try:
if po.name == 'AnalysisType':
from pychron.pipeline.plot.plotter.ticks import analysis_type_formatter
ys = list(self._unpack_attr(po.name))
kw = dict(y=ys,
colors=ys,
type='cmap_scatter',
fit='',
color_map_name='gist_rainbow')
yerr = None
value_format = analysis_type_formatter
set_ylimits = False
else:
set_ylimits = True
value_format = None
ys = array(
[ai.nominal_value for ai in self._unpack_attr(po.name)])
yerr = array([ai.std_dev for ai in self._unpack_attr(po.name)])
kw = dict(y=ys,
yerror=yerr,
type='scatter',
fit='{}_{}'.format(po.fit, po.error_type),
filter_outliers_dict=po.filter_outliers_dict)
# print ys
n = [ai.record_id for ai in self.sorted_analyses]
args = graph.new_series(x=self.xs,
display_index=ArrayDataSource(data=n),
plotid=pid,
add_inspector=False,
marker=po.marker,
marker_size=po.marker_size,
**kw)
if len(args) == 2:
scatter, p = args
else:
p, scatter, l = args
sel = scatter.index.metadata.get('selections', [])
sel += omits
scatter.index.metadata['selections'] = list(set(sel))
def af(i, x, y, analysis):
return ('Run Date: {}'.format(
analysis.rundate.strftime('%m-%d-%Y %H:%M')),
'Rel. Time: {:0.4f}'.format(x))
self._add_scatter_inspector(scatter,
additional_info=af,
value_format=value_format)
if po.use_time_axis:
p.x_axis.tick_generator = ScalesTickGenerator(
scale=CalendarScaleSystem())
# p.value_scale = po.scale
end_caps = True
if po.y_error and yerr is not None:
self._add_error_bars(scatter,
yerr,
'y',
2,
end_caps,
visible=True)
if set_ylimits:
mi, mx = min(ys - 2 * yerr), max(ys + 2 * yerr)
graph.set_y_limits(min_=mi, max_=mx, pad='0.1', plotid=pid)
except (KeyError, ZeroDivisionError, AttributeError), e:
import traceback
traceback.print_exc()
print 'Series', e
def new_plot(self, **kw):
p = super(ContextGraph, self).new_plot(**kw)
p.x_axis.tick_generator = ScalesTickGenerator(
scale=CalendarScaleSystem())
return p