def _func():
open_view(im)
if auto_close:
minutes = 2
t = Timer(60 * minutes, im.close_ui)
t.setDaemon(True)
t.start()
def show_summary(self):
"""
show a summary view for ``spec`` using its ``result``
:return:
"""
if self.selected:
open_view(self.selected[0].result)
def _func():
open_view(im)
if auto_close:
minutes = 2
t = Timer(60 * minutes, im.close_ui)
t.setDaemon(True)
t.start()
def _do_diff_fired(self):
if self.selected_commits:
lhs = self.selected_lhs
rhs = self.selected_rhs
lhsid = lhs.hexsha[:8]
lhsdate = isoformat_date(lhs.date)
rhsid = rhs.hexsha[:8]
rhsdate = rhs.date.isoformat()
diffs = []
for a in ('blanks', 'icfactors', 'intercepts'):
p = analysis_path((self.uuid, self.record_id), self.repository_identifier, modifier=a)
dd = get_diff(self.repo, lhs.hexsha, rhs.hexsha, p)
if dd:
diffs.append((a, dd))
if diffs:
v = DiffView(self.record_id, lhsid, rhsid, lhsdate, rhsdate)
for a, (aa, bb) in diffs:
func = getattr(v, 'set_{}'.format(a))
a = aa.data_stream.read().decode('utf-8')
b = bb.data_stream.read().decode('utf-8')
func(json.loads(a), json.loads(b))
v.finish()
open_view(v)
else:
information(None, 'No Differences between {} and {}'.format(lhsid, rhsid))
def _make_correlation(self, idx, ytitle):
fi = self.figures[0]
plots = list(fi.options.get_plotable_aux_plots())
tag = plots[idx].plot_name
n = len(self.figures)
r, c = filled_grid(n)
g = RegressionGraph(container_dict={
'kind': 'g',
'shape': (r, c)
},
window_title='Correlation')
for i, fi in enumerate(self.figures):
gi = fi.analysis_group
p = g.new_plot(xtitle='age',
ytitle=ytitle,
title='{}({})'.format(gi.sample, gi.identifier))
xs = [nominal_value(a.uage) for a in gi.clean_analyses()]
ys = [nominal_value(a.get_value(tag)) for a in gi.clean_analyses()]
g.new_series(xs,
ys,
fit='linear',
use_error_envelope=False,
plotid=i)
g.add_correlation_statistics(plotid=i)
g.set_x_limits(pad='0.1', plotid=i)
g.set_y_limits(pad='0.1', plotid=i)
g.refresh()
open_view(g)
def _do_diff_fired(self):
if self.selected_commits:
lhs = self.selected_lhs
rhs = self.selected_rhs
lhsid = lhs.hexsha[:8]
lhsdate = isoformat_date(lhs.date)
rhsid = rhs.hexsha[:8]
rhsdate = rhs.date.isoformat()
diffs = []
for a in ('blanks', 'icfactors', 'intercepts'):
p = analysis_path((self.uuid, self.record_id),
self.repository_identifier,
modifier=a)
dd = get_diff(self.repo, lhs.hexsha, rhs.hexsha, p)
if dd:
diffs.append((a, dd))
if diffs:
v = DiffView(self.record_id, lhsid, rhsid, lhsdate, rhsdate)
for a, (aa, bb) in diffs:
func = getattr(v, 'set_{}'.format(a))
a = aa.data_stream.read().decode('utf-8')
b = bb.data_stream.read().decode('utf-8')
func(json.loads(a), json.loads(b))
v.finish()
open_view(v)
else:
information(
None,
'No Differences between {} and {}'.format(lhsid, rhsid))
def perform(self, event):
app = event.task.window.application
# spec_man = app.get_service(SPECTROMETER_PROTOCOL)
from pychron.spectrometer.readout_view import new_readout_view
rv = app.get_service('pychron.spectrometer.readout_view.ReadoutView')
v = new_readout_view(rv)
open_view(rv, view=v)
def perform(self, event):
app = event.task.window.application
# spec_man = app.get_service(SPECTROMETER_PROTOCOL)
from pychron.spectrometer.readout_view import new_readout_view
rv = app.get_service('pychron.spectrometer.readout_view.ReadoutView')
v = new_readout_view(rv)
open_view(rv, view=v)
def _started_fired(self):
st = self.startup_tester
if st.results:
v = ResultsView(model=st)
open_view(v)
if globalv.use_testbot:
from pychron.testbot.testbot import TestBot
testbot = TestBot(application=self)
testbot.run()
def _started_fired(self):
st = self.startup_tester
if st.results:
v = ResultsView(model=st)
open_view(v)
if globalv.use_testbot:
from pychron.testbot.testbot import TestBot
testbot = TestBot(application=self)
testbot.run()
def start(self):
super(ThermoSpectrometerPlugin, self).start()
if to_bool(self.application.preferences.get('pychron.spectrometer.auto_open_readout')):
from pychron.spectrometer.readout_view import new_readout_view
#
# spec = self.application.get_service(
# 'pychron.spectrometer.base_spectrometer_manager.BaseSpectrometerManager')
# ro, v = new_readout_view(spectrometer=spec.spectrometer)
rv = self.application.get_service(ReadoutView)
v = new_readout_view(rv)
open_view(rv, view=v)
def _handle_figure_event(self, evt):
kind, args = evt
if kind == 'correlation':
self._make_correlation(*args)
elif kind == 'identify_peaks':
ps =[]
for fi in self.figures:
print('peaks', fi.peaks)
if fi.peaks is not None:
ps.extend(fi.peaks)
from pychron.pipeline.identify_peak_view import IdentifyPeakView
ipv = IdentifyPeakView(ps)
open_view(ipv)
def show_summary(self):
"""
show a summary view for ``spec`` using its ``result``
:return:
"""
if self.executed_selected:
from pychron.core.ui.text_editor import myTextEditor
v = View(UItem('summary', style='custom', editor=myTextEditor(editable=False,
fontsize=14)),
title='Summary',
width=900,
kind='livemodal',
resizable=True)
open_view(self.executed_selected[0].result, view=v)
def start(self):
super(ThermoSpectrometerPlugin, self).start()
if to_bool(
self.application.preferences.get(
'pychron.spectrometer.auto_open_readout')):
from pychron.spectrometer.readout_view import new_readout_view
#
# spec = self.application.get_service(
# 'pychron.spectrometer.base_spectrometer_manager.BaseSpectrometerManager')
# ro, v = new_readout_view(spectrometer=spec.spectrometer)
rv = self.application.get_service(ReadoutView)
v = new_readout_view(rv)
open_view(rv, view=v)
def show_isotope_evolutions(self, isotopes=None, **kw):
if isotopes:
if isinstance(isotopes[0], (str, unicode)):
isotopes = [self.isotopes[i] for i in isotopes]
else:
isotopes = self.isotopes.values()
keys = [k.name for k in isotopes]
self.load_raw_data(keys)
g = show_evolutions_factory(self.record_id, isotopes, **kw)
if g:
open_view(g, handler=CloseHandler())
return g
def _identify_peaks(self, ps):
from pychron.pipeline.identify_peak_view import IdentifyPeakView
source = self.application.get_service(
'pychron.sparrow.sparrow.Sparrow')
if source is None:
self.warning_dialog(
'At least on datasource plugin is required, e.g. Sparrow')
return
if source.connect():
ipv = IdentifyPeakView(ps, source=source)
open_view(ipv)
else:
self.warning_dialog('Failed to connect to a relevant datasource')
def show_isotope_evolutions(self, isotopes=None, **kw):
if isotopes:
if isinstance(isotopes[0], (str, unicode)):
isotopes = [self.isotopes[i] for i in isotopes]
else:
isotopes = self.isotopes.values()
keys = [k.name for k in isotopes]
self.load_raw_data(keys)
g = show_evolutions_factory(self.record_id, isotopes, **kw)
if g:
open_view(g, handler=CloseHandler())
return g
def perform(self, event):
path = self.path
if path is None:
dlg = FileDialog(action='open',
wildcard='*.log;*.json|log|*.json',
default_directory=paths.log_dir)
if dlg.open() == OK:
path = dlg.path
if path:
klass = TwistedLogModel if path.endswith('.json') else LogModel
lm = klass()
lm.open_file(path)
lv = LogViewer(model=lm)
open_view(lv)
def show_summary(self):
"""
show a summary view for ``spec`` using its ``result``
:return:
"""
if self.executed_selected:
from pychron.core.ui.text_editor import myTextEditor
v = View(UItem('summary',
style='custom',
editor=myTextEditor(editable=False, fontsize=14)),
title='Summary',
width=900,
kind='livemodal',
resizable=True)
open_view(self.executed_selected[0].result, view=v)
def edit_conditionals(name,
detectors=None,
root=None,
save_as=False,
kinds=None,
title=''):
if not root:
root = paths.queue_conditionals_dir
if not save_as:
if not name and not save_as:
path = get_file_path(root)
if not path:
return
else:
path = os.path.join(root, name)
else:
path = ''
cev = ConditionalsEditView(detectors, root=root, title=title)
cev.open(path, save_as)
if kinds:
cev.group_names = kinds
info = open_view(cev, kind='livemodal')
if info.result:
cev.dump()
return cev.name
def edit_conditionals(name, detectors=None, root=None, save_as=False,
kinds=None, title=''):
if not root:
root = paths.queue_conditionals_dir
if not save_as:
if not name and not save_as:
path = get_file_path(root)
if not path:
return
else:
path = os.path.join(root, name)
else:
path = ''
cev = ConditionalsEditView(detectors, root=root, title=title)
cev.open(path, save_as)
if kinds:
cev.group_names = kinds
info = open_view(cev, kind='livemodal')
if info.result:
cev.dump()
return cev.name
def _application_initialized_fired(self):
if globalv.use_startup_tests:
st = StartupTester()
for plugin in iter(self.plugin_manager):
st.test_plugin(plugin)
if st.results:
if globalv.show_startup_results or not st.all_passed:
v = ResultsView(model=st)
open_view(v)
if globalv.use_testbot:
from pychron.testbot.testbot import TestBot
testbot = TestBot(application=self)
testbot.run()
def do_import_analyses(dvc, sources):
from pychron.data_mapper.view import DVCIrradiationImporterView, DVCAnalysisImporterView
from pychron.data_mapper.model import DVCIrradiationImporterModel, DVCAnalysisImporterModel
from pychron.envisage.view_util import open_view
model = DVCAnalysisImporterModel(dvc=dvc, sources=sources)
# model.source = next((k for k, v in sources.iteritems() if v == default_source), None)
# model.source = sources.keys()[0]
model.repository_identifier = 'wiscartest'
model.extract_device = 'Laser'
model.mass_spectrometer = 'Noblesse'
model.principal_investigator = 'WiscAr'
for k,v in sources.items():
if isinstance(k, WiscArNuSource):
model.source = k
root = os.path.dirname(__file__)
k.directory = os.path.join(root, 'tests', 'data', 'wiscar')
k.nice_path = os.path.join(root, 'tests', 'data', 'wiscar.nice')
k.metadata_path = os.path.join(root, 'tests', 'data', 'WISCAR_test_metadata.txt')
break
view = DVCAnalysisImporterView(model=model)
info = open_view(view)
return info.result
def do_import_analyses(dvc, sources):
from pychron.data_mapper.view import DVCIrradiationImporterView, DVCAnalysisImporterView
from pychron.data_mapper.model import DVCIrradiationImporterModel, DVCAnalysisImporterModel
from pychron.envisage.view_util import open_view
model = DVCAnalysisImporterModel(dvc=dvc, sources=sources)
# model.source = next((k for k, v in sources.iteritems() if v == default_source), None)
# model.source = sources.keys()[0]
model.repository_identifier = 'wiscartest'
model.extract_device = 'Laser'
model.mass_spectrometer = 'Noblesse'
model.principal_investigator = 'WiscAr'
for k, v in sources.items():
if isinstance(k, WiscArNuSource):
model.source = k
root = os.path.dirname(__file__)
k.directory = os.path.join(root, 'tests', 'data', 'wiscar')
k.nice_path = os.path.join(root, 'tests', 'data', 'wiscar.nice')
k.metadata_path = os.path.join(root, 'tests', 'data',
'WISCAR_test_metadata.txt')
break
view = DVCAnalysisImporterView(model=model)
info = open_view(view)
return info.result
def do_import_irradiation(dvc, sources, default_source=None):
model = DVCImporterModel(dvc=dvc, sources=sources)
model.source = next((k for k, v in sources.iteritems() if v == default_source), None)
view = DVCImporterView(model=model)
info = open_view(view)
return info.result
def do_import_irradiation(dvc, sources, default_source=None):
model = DVCImporterModel(dvc=dvc, sources=sources)
model.source = next(
(k for k, v in sources.iteritems() if v == default_source), None)
view = DVCImporterView(model=model)
info = open_view(view)
return info.result
def _pre_execute(self):
pattern = self.pattern
kind = pattern.kind
if kind == 'SeekPattern':
from pychron.graph.graph import Graph
g = Graph(window_x=1000, window_y=100, window_height=900)
self._info = open_view(g)
self._seek_graph = g
def do_import_irradiation(dvc, sources, default_source=None):
from pychron.data_mapper.view import DVCIrradiationImporterView, DVCAnalysisImporterView
from pychron.data_mapper.model import DVCIrradiationImporterModel, DVCAnalysisImporterModel
from pychron.envisage.view_util import open_view
model = DVCIrradiationImporterModel(dvc=dvc, sources=sources)
# model.source = next((k for k, v in sources.iteritems() if v == default_source), None)
view = DVCIrradiationImporterView(model=model)
info = open_view(view)
return info.result
def _pre_execute(self):
pattern = self.pattern
kind = pattern.kind
if kind == 'SeekPattern':
from pychron.graph.graph import Graph
g = Graph(window_x=1000, window_y=100, window_height=900)
self._info = open_view(g)
self._seek_graph = g
def do_import_irradiation(dvc, sources, default_source=None):
from pychron.data_mapper.view import DVCIrradiationImporterView, DVCAnalysisImporterView
from pychron.data_mapper.model import DVCIrradiationImporterModel, DVCAnalysisImporterModel
from pychron.envisage.view_util import open_view
model = DVCIrradiationImporterModel(dvc=dvc, sources=sources)
# model.source = next((k for k, v in sources.iteritems() if v == default_source), None)
view = DVCIrradiationImporterView(model=model)
info = open_view(view)
return info.result
def _pre_execute(self, evt):
self.debug('pre execute')
pattern = self.pattern
kind = pattern.kind
if kind in ('SeekPattern', 'DragonFlyPeakPattern'):
self._info = open_view(pattern, view='execution_graph_view')
if evt is not None:
evt.set()
self.debug('pre execute finished')
def _pre_execute(self, evt):
self.debug('pre execute')
pattern = self.pattern
kind = pattern.kind
if kind in ('SeekPattern', 'DragonFlyPeakPattern'):
self._info = open_view(pattern, view='execution_graph_view')
if evt is not None:
evt.set()
self.debug('pre execute finished')
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)
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)
def _make_correlation(self, refplot, xtitle):
fi = self.figures[0]
n = len(list(fi.options.get_plotable_aux_plots()))
plots = list(reversed(fi.graph.plots))
xs = refplot.data.get_data('y1')
r, c = filled_grid(n - 1)
g = RegressionGraph(container_dict={
'kind': 'g',
'shape': (r, c)
},
window_title='Correlation')
i = 0
for pp in plots:
ytitle = pp.y_axis.title
if ytitle == xtitle:
continue
g.new_plot(xtitle=xtitle, ytitle=ytitle, padding=[80, 10, 10, 40])
ys = pp.data.get_data('y1')
g.new_series(xs,
ys,
fit='linear',
use_error_envelope=False,
plotid=i)
g.add_correlation_statistics(plotid=i)
g.set_x_limits(pad='0.1', plotid=i)
g.set_y_limits(pad='0.1', plotid=i)
i += 1
g.refresh()
open_view(g)
def _view_snapshot(self, local_path, remote_path, image):
from pychron.lasers.laser_managers.snapshot_view import SnapshotView
open_required = False
try:
sv = self.application.snapshot_view
except AttributeError:
sv = None
open_required = True
if sv is None:
sv = SnapshotView()
self.application.snapshot_view = sv
sv.set_image(local_path, remote_path, image)
if open_required:
info = open_view(sv)
self.application.snapshot_view_info = info
else:
if self.application.snapshot_view_info.control:
self.application.snapshot_view_info.control.raise_()
else:
info = open_view(sv)
self.application.snapshot_view_info = info
def _view_snapshot(self, local_path, remote_path, image):
from pychron.lasers.laser_managers.snapshot_view import SnapshotView
open_required = False
try:
sv = self.application.snapshot_view
except AttributeError:
sv = None
open_required = True
if sv is None:
sv = SnapshotView()
self.application.snapshot_view = sv
sv.set_image(local_path, remote_path, image)
if open_required:
info = open_view(sv)
self.application.snapshot_view_info = info
else:
if self.application.snapshot_view_info.control:
self.application.snapshot_view_info.control.raise_()
else:
info = open_view(sv)
self.application.snapshot_view_info = info
def get_selection(self):
from pychron.loading.load_view_selection import LoadViewSelectionModel, LoadViewSelectionController
self.setup()
if self.loads:
self.use_measured = True
self.load_name = self.loads[-1]
oeditable = self.canvas.editable
self.canvas.editable = False
lvsm = LoadViewSelectionModel(manager=self)
lvc = LoadViewSelectionController(model=lvsm)
info = open_view(lvc)
self.canvas.editable = oeditable
self.use_measured = False
if info.result:
return lvsm.selected_positions
else:
self.warning_dialog('No Loads available')
def get_selection(self):
from pychron.loading.load_view_selection import LoadViewSelectionModel, LoadViewSelectionController
self.setup()
if self.loads:
self.use_measured = True
self.load_name = self.loads[-1]
oeditable = self.canvas.editable
self.canvas.editable = False
lvsm = LoadViewSelectionModel(manager=self)
lvc = LoadViewSelectionController(model=lvsm)
info = open_view(lvc)
self.canvas.editable = oeditable
self.use_measured = False
if info.result:
return lvsm.selected_positions
else:
self.warning_dialog('No Loads available')
def edit_analysis(self):
self.debug('Edit analysis data')
if not self.has_active_editor():
return
editor = self.active_editor
if not isinstance(editor, RecallEditor):
self.warning_dialog('Active tab must be a Recall tab')
return
if hasattr(editor, 'edit_view') and editor.edit_view:
editor.edit_view.show()
else:
e = AnalysisEditView(editor, dvc=self.dvc)
info = open_view(e)
e.control = info.control
editor.edit_view = e
def edit_analysis(self):
self.debug('Edit analysis data')
if not self.has_active_editor():
return
editor = self.active_editor
if not isinstance(editor, RecallEditor):
self.warning_dialog('Active tab must be a Recall tab')
return
if hasattr(
editor,
'edit_view') and editor.edit_view and editor.edit_view.control:
editor.edit_view.show()
else:
e = AnalysisEditView(editor, dvc=self.dvc)
info = open_view(e)
# info = e.edit_traits()
e.control = info.control
editor.edit_view = e
def cdd_operate_voltage_scan_task_factory(self):
obj = CDDOperatingVoltageScan(spectrometer=self.spectrometer)
info = obj.edit_traits(kind='livemodal')
if info.result:
open_view(obj.graph)
obj.execute()
def controller_execute_button_changed(self, info):
graph = self.model.make_graph()
if self.model.execute():
self.model.do_scan()
open_view(graph)
def setup_peak_center(self, detector=None, isotope=None,
integration_time=1.04,
directions='Increase',
center_dac=None, plot_panel=None, new=False,
standalone_graph=True, name='', show_label=False,
window=0.015, step_width=0.0005, min_peak_height=1.0, percent=80,
deconvolve=None,
use_interpolation=False,
interpolation_kind='linear',
dac_offset=None, calculate_all_peaks=False,
config_name=None,
use_configuration_dac=True):
if deconvolve is None:
n_peaks, select_peak = 1, 1
if dac_offset is not None:
use_dac_offset = True
spec = self.spectrometer
spec.save_integration()
self.debug('setup peak center. detector={}, isotope={}'.format(detector, isotope))
self._setup_config()
pcc = None
if detector is None or isotope is None:
self.debug('ask user for peak center configuration')
self.peak_center_config.load(dac=spec.magnet.dac)
if config_name:
self.peak_center_config.active_name = config_name
info = self.peak_center_config.edit_traits()
if not info.result:
return
else:
pcc = self.peak_center_config.active_item
elif config_name:
self.peak_center_config.load(dac=spec.magnet.dac)
self.peak_center_config.active_name = config_name
pcc = self.peak_center_config.active_item
if pcc:
if not detector:
detector = pcc.active_detectors
if not isotope:
isotope = pcc.isotope
directions = pcc.directions
integration_time = pcc.integration_time
window = pcc.window
min_peak_height = pcc.min_peak_height
step_width = pcc.step_width
percent = pcc.percent
use_interpolation = pcc.use_interpolation
interpolation_kind = pcc.interpolation_kind
n_peaks = pcc.n_peaks
select_peak = pcc.select_n_peak
use_dac_offset = pcc.use_dac_offset
dac_offset = pcc.dac_offset
calculate_all_peaks = pcc.calculate_all_peaks
if center_dac is None and use_configuration_dac:
center_dac = pcc.dac
spec.set_integration_time(integration_time)
period = int(integration_time * 1000 * 0.9)
if not isinstance(detector, (tuple, list)):
detector = (detector,)
ref = detector[0]
ref = self.spectrometer.get_detector(ref)
self.reference_detector = ref
self.reference_isotope = isotope
if center_dac is None:
center_dac = self.get_center_dac(ref, isotope)
if len(detector) > 1:
ad = detector[1:]
else:
ad = []
pc = self.peak_center
if not pc or new:
pc = PeakCenter()
pc.trait_set(center_dac=center_dac,
period=period,
window=window,
percent=percent,
min_peak_height=min_peak_height,
step_width=step_width,
directions=directions,
reference_detector=ref,
additional_detectors=ad,
reference_isotope=isotope,
spectrometer=spec,
show_label=show_label,
use_interpolation=use_interpolation,
interpolation_kind=interpolation_kind,
n_peaks=n_peaks,
select_peak=select_peak,
use_dac_offset=use_dac_offset,
dac_offset=dac_offset,
calculate_all_peaks=calculate_all_peaks)
self.peak_center = pc
graph = pc.graph
graph.name = name
if plot_panel:
plot_panel.set_peak_center_graph(graph)
else:
graph.close_func = self.close
if standalone_graph:
# set graph window attributes
graph.window_title = 'Peak Center {}({}) @ {:0.3f}'.format(ref, isotope, center_dac)
graph.window_width = 300
graph.window_height = 250
open_view(graph)
return self.peak_center
def controller_execute_button_changed(self, info):
graph = self.model.make_graph()
if self.model.execute():
self.model.do_scan()
open_view(graph)
def perform(self, event):
app = event.task.window.application
man = app.get_service('pychron.hardware.flag_manager.FlagManager')
open_view(man)
def _execute_scan(self):
name = os.path.join(paths.scripts_dir, '{}_scan.yaml'.format(self.name))
import csv
d = os.path.join(paths.data_dir, 'diode_scans')
p, _cnt = unique_path(d, 'scan', extension='csv')
st = None
py = self.laser_manager.pyrometer
tc = self.laser_manager.get_device('temperature_monitor')
yd = yaml.load(open(name).read())
power = yd['power']
duration = yd['duration']
power_on = yd['power_on']
power_off = yd['power_off']
period = yd['period']
if 'temp' in yd:
temp = yd['temp']
else:
temp = None
g = StreamStackedGraph()
g.new_plot(scan_delay=1, )
g.new_series(x=[], y=[])
g.new_plot(scan_delay=1, )
g.new_series(x=[], y=[], plotid=1)
open_view(g)
self.laser_manager.stage_manager.start_recording()
time.sleep(1)
def gfunc(v1, v2):
g.record(v1)
g.record(v2, plotid=1)
pi = 0
with open(p, 'w') as wfile:
writer = csv.writer(wfile)
t = 0
ti = 0
while ti <= duration:
if self._cancel:
break
# print ti, power_off, pi, ti >= power_off, (ti >= power_off and pi)
if ti == power_on:
# turn on set laser to power
if temp:
self.laser_manager.set_laser_temperature(temp)
pi = temp
else:
pi = power
self.laser_manager.set_laser_power(power)
elif ti >= power_off and pi:
print 'setting power off'
if temp:
self.laser_manager.set_laser_temperature(0)
else:
self.laser_manager.set_laser_power(0)
pi = 0
if st is None:
st = time.time()
t = time.time() - st
py_t = py.read_temperature(verbose=False)
tc_t = tc.read_temperature(verbose=False)
gfunc(py_t, tc_t)
writer.writerow((ti, pi, t, py_t, tc_t))
ti += 1
time.sleep(period)
if temp:
self.laser_manager.set_laser_temperature(0)
else:
self.laser_manager.set_laser_power(0)
self.laser_manager.stage_manager.stop_recording()
self._executing = False
def perform(self, event=None):
pm = PatternMakerView()
open_view(pm)
def perform(self, event=None):
pm = PatternMakerView()
if pm.load_pattern():
open_view(pm)
def open_pattern(self):
pm = self._pattern_maker_view_factory()
if pm.load_pattern():
open_view(pm)
def new_pattern(self):
pm = self._pattern_maker_view_factory()
open_view(pm)
def cdd_operate_voltage_scan_task_factory(self):
obj = CDDOperatingVoltageScan(spectrometer=self.spectrometer)
info = obj.edit_traits(kind='livemodal')
if info.result:
open_view(obj.graph)
obj.execute()
def show_pattern(self):
self.pattern.window_x = 50
self.pattern.window_y = 50
open_view(self.pattern, view='graph_view')
def perform(self, event):
from pychron.extraction_line.stop_watch import StopWatch
sw = StopWatch()
open_view(sw)
def perform(self, event):
man = self._get_manager(event)
open_view(man.explanation)
def _execute_calibration(self):
name = os.path.join(paths.scripts_dir, '{}_calibration_scan.yaml'.format(self.name))
import csv
d = os.path.join(paths.data_dir, 'diode_scans')
p, _cnt = unique_path(d, 'calibration', extension='csv')
# st = None
#
# py = self.laser_manager.pyrometer
# tc = self.laser_manager.get_device('temperature_monitor')
g = StreamStackedGraph()
g.clear()
g.new_plot(scan_delay=1)
g.new_series(x=[], y=[])
g.new_plot(scan_delay=1)
g.new_series(x=[], y=[], plotid=1)
open_view(g)
record = False
if record:
self.laser_manager.stage_manager.start_recording()
time.sleep(1)
# def gfunc(t, v1, v2):
# g.add_datum((t, v1))
# g.add_datum((t, v2), plotid=1)
def gfunc(v1, v2):
g.record(v1)
g.record(v2, plotid=1)
yd = yaml.load(open(name).read())
start = yd['start']
end = yd['end']
step = yd['step']
mean_tol = yd['mean_tol']
std = yd['std']
n = (end - start) / step + 1
# nn = 30
#
# py = self.laser_manager.pyrometer
# tc = self.laser_manager.get_device('temperature_monitor')
with open(p, 'w') as wfile:
writer = csv.writer(wfile)
st = time.time()
for ti in linspace(start, end, n):
if self._cancel:
break
args = self._equilibrate_temp(ti, gfunc, st, mean_tol, std)
if args:
self.info('{} equilibrated'.format(ti))
py_t, tc_t = args
writer.writerow((ti, py_t, tc_t))
else:
break
self.laser_manager.set_laser_temperature(0)
if record:
self.laser_manager.stage_manager.stop_recording()
self._executing = False
def perform(self, event):
manager = self._get_manager(event)
open_view(manager.pyscript_editor)
def diff_selected(self):
if self._validate_diff():
if len(self.selected_commits) == 2:
l, r = self.selected_commits
dv = self._diff_view_factory(l, r)
open_view(dv)
def perform(self, event):
manager = self._get_manager(event)
if manager.multiplexer_manager:
open_view(manager.multiplexer_manager)
