def _sniff_graph_default(self):
g = StackedGraph(container_dict=dict(padding=5, bgcolor='gray',
stack_order=self.stack_order,
spacing=5),
bind_index=False,
use_data_tool=False,
padding_bottom=35)
g.page_name = 'Equil.'
return g
def _update_half_ring_graph(self):
self.ring_graph = g = StackedGraph()
g.plotcontainer.spacing = 10
g.plotcontainer.stack_order = 'top_to_bottom'
poss = list(self._group_rings())[0]
g.new_plot()
for m in (2, 3, 5, 10):
monitors, unknowns = [], []
for i, p in enumerate(poss):
if not i % m:
monitors.append(p)
else:
unknowns.append(p)
# monitors = poss[::5]
# unknowns = poss[1::2]
x, y, z, ze, j, je, sj, sje = self._extract_position_arrays(
monitors)
unkpts = [(p.x, p.y) for p in unknowns]
unkj = [p.mean_j for p in unknowns]
fx, fy, mx, my = self.model_plane(x, y, z, ze, model_points=unkpts)
x, y = zip(*unkpts)
mx = arctan2(x, y)
ys = (unkj - my) / unkj * 100
s = g.new_series(mx, ys)[0]
def setup_graph(self, an):
container = HPlotContainer()
sg = StackedGraph()
sg.plotcontainer.spacing = 5
sg.plotcontainer.stack_order = 'top_to_bottom'
isos = an.sorted_values(reverse=False)
for i, iso in enumerate(isos):
sniff = iso.sniff
sg.new_plot(ytitle=iso.name, xtitle='Time (s)', title='Equilibration')
if sniff.xs.shape[0]:
sg.new_series(sniff.offset_xs, sniff.ys, marker='circle', type='scatter')
sg.set_y_limits(pad='0.1', plotid=i)
bg = StackedRegressionGraph()
bg.plotcontainer.spacing = 5
bg.plotcontainer.stack_order = 'top_to_bottom'
for i, iso in enumerate(isos):
baseline = iso.baseline
bg.new_plot(ytitle=baseline.detector, xtitle='Time (s)', title='Baseline')
if baseline.xs.shape[0]:
bg.new_series(baseline.offset_xs, baseline.ys,
color='red', type='scatter', fit=baseline.fit)
bg.set_y_limits(pad='0.1', plotid=i)
ig = StackedRegressionGraph()
ig.plotcontainer.spacing = 5
ig.plotcontainer.stack_order = 'top_to_bottom'
for i, iso in enumerate(isos):
ig.new_plot(ytitle=iso.name, xtitle='Time (s)', title='Isotope')
if iso.xs.shape[0]:
ig.new_series(iso.offset_xs, iso.ys,
color='blue', type='scatter', fit=iso.fit)
ig.set_y_limits(pad='0.1', plotid=i)
container.add(sg.plotcontainer)
container.add(ig.plotcontainer)
container.add(bg.plotcontainer)
self.container = container
def setup_graph(self, response_data, request_data, setpoint_data):
self.graph = g = StackedGraph(container_dict={'spacing': 10})
ret = False
pid = 0
if response_data:
try:
x, y = unpack(response_data, fmt='<ff', decode=True)
if x[1:]:
p = g.new_plot()
p.value_range.tight_bounds = False
g.set_x_title('Time (s)')
g.set_y_title('Temp C')
g.new_series(x[1:], y[1:])
pid += 1
ret = True
if setpoint_data:
x, y = unpack(setpoint_data, fmt='<ff', decode=True)
if x[1:]:
g.new_series(x[1:], y[1:])
except ValueError:
pass
if request_data:
try:
x, y = unpack(request_data, fmt='<ff', decode=True)
if x[1:]:
p = self.graph.new_plot()
g.set_x_title('Time')
g.set_y_title('% Power')
g.new_series(x[1:], y[1:])
g.set_y_limits(min_=0, max_=max(y) * 1.1, plotid=pid)
ret = True
except ValueError:
pass
return ret
def _graph_default(self):
g = StackedGraph(container_dict=dict(padding=5))
plot = g.new_plot(
# show_legend='ul',
padding=5)
plot.overlays.append(
ZoomTool(plot,
minimum_screen_delta=5,
enable_wheel=False,
drag_button='left',
tool_mode='range',
always_on_top=True,
axis='index'))
# plot.on_trait_change(self._update, 'index_mapper.range.updated')
plot.overlays.append(LegendOverlay(plot))
g.set_axis_traits(axis='y', visible=False)
g.set_axis_traits(axis='x', visible=False)
g.set_grid_traits(grid='x', visible=False)
g.set_grid_traits(grid='y', visible=False)
return g
def _graph_default(self):
g = StackedGraph(container_dict=dict(padding=5))
plot = g.new_plot(
# show_legend='ul',
padding=5)
plot.overlays.append(ZoomTool(plot,
minimum_screen_delta=5,
enable_wheel=False,
drag_button='left',
tool_mode='range',
always_on_top=True,
axis='index'
))
# plot.on_trait_change(self._update, 'index_mapper.range.updated')
plot.overlays.append(LegendOverlay(plot))
g.set_axis_traits(axis='y', visible=False)
g.set_axis_traits(axis='x', visible=False)
g.set_grid_traits(grid='x', visible=False)
g.set_grid_traits(grid='y', visible=False)
return g
return v
if __name__ == '__main__':
# m = MLLabel()
# m.text = '<sup>40</sup>Ar'
# d = Demo()
# d.plot = Plot()
# d.plot.padding_left = 80
# d.plot.data = ArrayPlotData()
# d.plot.data['x'] = [1, 2, 3, 4]
# d.plot.data['y'] = [1, 2, 3, 4]
# d.plot.plot(('x', 'y'))
from pychron.graph.stacked_graph import StackedGraph
g = StackedGraph()
plot = g.new_plot(padding_left=100, padding_bottom=100)
xa = plot.x_axis
xa.title_color = 'red'
xa.title = 'sasfas'
nxa = MPlotAxis()
nxa.title = '<sup>39</sup>Ar/<sup>40</sup>Ar'
# nxa.title = '39Ar/40Ar'
nxa.clone(xa)
ya = plot.y_axis
ya.title_color = 'red'
ya.title = 'sasfas'
ya.title_font = 'modern 36'
nya = MPlotAxis()
nya.title = '<sup>39</sup>Ar/<sup>40</sup>Ar'
def show_extraction_graph(self):
if not self.has_active_editor(klass=RecallEditor):
return
from pychron.graph.stacked_graph import StackedGraph
from numpy import array
import struct
import base64
an = self.active_editor.analysis
data = an.get_extraction_data()
def extract_blob(blob):
blob = base64.b64decode(blob)
x, y = array([
struct.unpack('<ff', blob[i:i + 8])
for i in xrange(0, len(blob), 8)
]).T
x[0] = 0
return x, y
g = StackedGraph()
g.window_title = 'Extraction Results - {}'.format(an.record_id)
g.new_plot(padding=[70, 10, 10, 60])
xx, yy = extract_blob(data['request'])
g.new_series(xx, yy, plotid=0)
g.set_y_limits(pad='0.1')
g.new_plot(padding=[70, 10, 10, 10])
xx, yy = extract_blob(data['response'])
g.new_series(xx, yy, plotid=1)
g.set_y_title('Temp (C)', plotid=0)
g.set_x_title('Time (s)', plotid=0)
g.set_y_title('% Output', plotid=1)
open_view(g)
def _update_ring_graph(self):
self.ring_graph = g = StackedGraph()
g.plotcontainer.spacing = 10
g.plotcontainer.stack_order = 'top_to_bottom'
self.deviation_graph = dg = StackedGraph()
dg.plotcontainer.spacing = 10
dg.plotcontainer.stack_order = 'top_to_bottom'
self.spoke_graph = sg = StackedGraph()
sg.plotcontainer.spacing = 10
sg.plotcontainer.stack_order = 'top_to_bottom'
l, h = 0, 0
dl, dh = 0, 0
for poss in self._group_rings():
poss = list(poss)
x, y, z, ze, j, je, sj, sje = self._extract_position_arrays(poss)
fx, fy, mx, my = self.model_plane(x, y, z, ze)
x = arctan2(x, y)
plot = g.new_plot(padding_left=100,
padding_top=20,
padding_right=10,
padding_bottom=30)
s = g.new_series(x, z, yerror=ze, type='scatter')[0]
ebo = ErrorBarOverlay(component=s, orientation='y')
s.underlays.append(ebo)
g.new_series(x, j, color='green')
# g.new_series(x, sj)
g.new_series(fx, fy, color='blue')
l = min(min(x), l)
h = max(max(x), h)
plot = dg.new_plot(padding_left=100,
padding_top=20,
padding_right=10,
padding_bottom=30)
ds = (j - z) / z * 100
ds2 = (my - z) / z * 100
# dg.new_series(x, (my-j)/j*100)
dg.new_series(x, ds, color='green')
dg.new_series(mx, ds2, color='blue')
dl = min(min(ds), dl)
dh = max(max(ds), dh)
for i, p in enumerate(g.plots):
g.set_x_limits(l, h, plotid=i, pad='0.05')
dg.set_x_limits(l, h, plotid=i, pad='0.05')
dg.set_y_limits(dl, dh, plotid=i, pad='0.05')
for spoke, poss in self._group_spokes():
print(spoke)
x, y, z, ze, j, je, sj, sje = self._extract_position_arrays(poss)
x = (x**2 + y**2)**0.5
plot = sg.new_plot(padding_left=100,
padding_top=20,
padding_right=10,
padding_bottom=30)
s = sg.new_series(x, z, yerror=ze, type='scatter')[0]
ebo = ErrorBarOverlay(component=s, orientation='y')
s.underlays.append(ebo)
sg.new_series(x, j, color='green')
def _make_graph(self, lumens, duration):
g = StackedGraph(container_dict=dict(stack_order='top_to_bottom'))
g.new_plot(ytitle='Output (W)')
g.new_series()
g.new_plot(ytitle='Residual')
g.new_series(plotid=1)
g.new_plot(ytitle='Lumens', xtitle='time (s)')
g.new_series(plotid=2)
g.add_horizontal_rule(lumens, plotid=2)
g.set_x_limits(0, duration * 1.1)
return g
def _make_graph(self, lumens, duration):
g = StackedGraph(container_dict=dict(stack_order='top_to_bottom'))
g.new_plot(
ytitle='Output (W)'
)
g.new_series()
g.new_plot(
ytitle='Residual'
)
g.new_series(plotid=1)
g.new_plot(
ytitle='Lumens',
xtitle='time (s)')
g.new_series(plotid=2)
g.add_horizontal_rule(lumens, plotid=2)
g.set_x_limits(0, duration * 1.1)
return g
def show_extraction_graph(self):
if not self.has_active_editor(klass=RecallEditor):
return
from pychron.graph.stacked_graph import StackedGraph
from numpy import array
import struct
import base64
an = self.active_editor.analysis
data = an.get_extraction_data()
def extract_blob(blob):
blob = base64.b64decode(blob)
if blob != 'No Response':
x, y = array([struct.unpack('<ff', blob[i:i + 8]) for i in range(0, len(blob), 8)]).T
x[0] = 0
else:
x, y = [], []
return x, y
g = StackedGraph()
g.window_title = 'Extraction Results - {}'.format(an.record_id)
g.new_plot(padding=[70, 10, 10, 60])
xx, yy = extract_blob(data['request'])
g.new_series(xx, yy, plotid=0)
g.set_y_limits(pad='0.1')
g.new_plot(padding=[70, 10, 10, 10])
xx, yy = extract_blob(data['response'])
g.new_series(xx, yy, plotid=1)
g.set_y_title('Temp (C)', plotid=0)
g.set_x_title('Time (s)', plotid=0)
g.set_y_title('% Output', plotid=1)
open_view(g)
return v
if __name__ == '__main__':
# m = MLLabel()
# m.text = '<sup>40</sup>Ar'
# d = Demo()
# d.plot = Plot()
# d.plot.padding_left = 80
# d.plot.data = ArrayPlotData()
# d.plot.data['x'] = [1, 2, 3, 4]
# d.plot.data['y'] = [1, 2, 3, 4]
# d.plot.plot(('x', 'y'))
from pychron.graph.stacked_graph import StackedGraph
g = StackedGraph()
plot = g.new_plot(padding_left=100, padding_bottom=100)
xa = plot.x_axis
xa.title_color = 'red'
xa.title = 'sasfas'
nxa = MPlotAxis()
nxa.title = '<sup>39</sup>Ar/<sup>40</sup>Ar'
# nxa.title = '39Ar/40Ar'
nxa.clone(xa)
ya = plot.y_axis
ya.title_color = 'red'
ya.title = 'sasfas'
ya.title_font = 'modern 36'
nya = MPlotAxis()
nya.title = '<sup>39</sup>Ar/<sup>40</sup>Ar'
def _graph_default(self):
g = StackedGraph()
g.new_plot(show_legend=True, padding=[30, 20, 10, 40], ytitle='Ar40', xtitle='# points')
g.new_plot(padding=[30, 20, 10, 10], ytitle='Ar40_err')
g.new_plot(padding=[30, 20, 10, 40], ytitle='Ar36')
g.new_plot(padding=[30, 20, 10, 10], ytitle='Ar36_err')
g.new_plot(padding=[30, 20, 10, 10], ytitle='Ar40/Ar36')
g.new_plot(padding=[30, 20, 10, 10], ytitle='%Diff')
# g.new_plot(padding=[20, 20, 10, 10], ytitle='Ar40_err')
return g
def _graph_default(self):
g = StackedGraph()
g.new_plot(show_legend=True,
padding=[30, 20, 10, 40],
ytitle='Ar40',
xtitle='# points')
g.new_plot(padding=[30, 20, 10, 10], ytitle='Ar40_err')
g.new_plot(padding=[30, 20, 10, 40], ytitle='Ar36')
g.new_plot(padding=[30, 20, 10, 10], ytitle='Ar36_err')
g.new_plot(padding=[30, 20, 10, 10], ytitle='Ar40/Ar36')
g.new_plot(padding=[30, 20, 10, 10], ytitle='%Diff')
# g.new_plot(padding=[20, 20, 10, 10], ytitle='Ar40_err')
return g
def setup_graph(self, an):
container = HPlotContainer()
container_dict = {'spacing': 5, 'stack_order': 'top_to_bottom'}
sg = StackedGraph(container_dict=container_dict)
sg.plotcontainer.spacing = 5
sg.plotcontainer.stack_order = 'top_to_bottom'
isos = an.sorted_values(reverse=False)
add_sniff = True
sisos = [iso for iso in isos if iso.sniff.offset_xs.shape[0]]
for i, iso in enumerate(sisos):
sniff = iso.sniff
sg.new_plot(ytitle=iso.name,
xtitle='Time (s)',
title='Equilibration')
sg.new_series(sniff.offset_xs,
sniff.ys,
marker='circle',
type='scatter')
sg.set_y_limits(pad='0.1', plotid=i)
sg.set_x_limits(min_=0, max_=max(sniff.offset_xs) * 1.05, plotid=i)
bg = StackedRegressionGraph(container_dict=container_dict)
add_baseline = True
ig = StackedRegressionGraph(container_dict=container_dict)
iisos = [iso for iso in isos if iso.offset_xs.shape[0]]
baselines = []
for i, iso in enumerate(iisos):
if iso.baseline.offset_xs.shape[0]:
baselines.append(iso.baseline)
ig.new_plot(ytitle='{}({})'.format(iso.name, iso.detector),
xtitle='Time (s)',
title='Isotope')
ig.new_series(iso.offset_xs,
iso.ys,
display_filter_bounds=True,
filter_outliers_dict=iso.filter_outliers_dict,
color='blue',
type='scatter',
fit=iso.efit)
ig.set_regressor(iso.regressor, i)
ig.set_y_limits(pad='0.1', plotid=i)
ig.set_x_limits(min_=0, max_=max(iso.offset_xs) * 1.05, plotid=i)
ig.refresh()
# bisos = [iso for iso in isos if iso.baseline.offset_xs.shape[0]]
# plotted_baselines = []
# for i, iso in enumerate(bisos):
# baseline = iso.baseline
# if baseline.detector in plotted_baselines:
# continue
# plotted_baselines.append(baseline.detector)
# for iso in bisos:
for i, baseline in enumerate(baselines):
bg.new_plot(ytitle=baseline.detector,
xtitle='Time (s)',
title='Baseline')
bg.new_series(baseline.offset_xs,
baseline.ys,
filter_outliers_dict=baseline.filter_outliers_dict,
display_filter_bounds=True,
color='red',
type='scatter',
fit=baseline.efit)
bg.set_regressor(baseline.regressor, i)
bg.set_y_limits(pad='0.1', plotid=i)
bg.set_x_limits(pad='0.025', plotid=i)
bg.refresh()
container.add(sg.plotcontainer)
container.add(ig.plotcontainer)
container.add(bg.plotcontainer)
self.container = container
