def default_traits_view(self):
"""The default traits view of the Engine View.
"""
view = View(HSplit(
Item('engine',
id='mayavi.engine_rich_view.pipeline_view',
springy=True,
resizable=True,
editor=self.tree_editor,
dock='tab',
label='Pipeline'),
Item('engine',
id='mayavi.engine_rich_view.current_selection',
editor=InstanceEditor(
view='current_selection_view'),
springy=True,
resizable=True,
style='custom'),
show_labels=False,
id='mayavi.engine_rich_view_group',
),
id='enthought.mayavi.engine_rich_view',
help=False,
resizable=True,
undo=False,
revert=False,
ok=False,
cancel=False,
title='Mayavi pipeline',
icon=self.icon,
toolbar=self.toolbar,
handler=EngineRichViewHandler)
return view
class Nirvana(HasTraits):
xcontrol = Instance(XControl)
csetting = Instance(XSetting)
figure = Instance(Figure) # 控制绘图控件的Figure对象
view = View(
HSplit( #
Item("figure", editor=MPLFigureEditor(), show_label=False,width=0.85),
Group(
Item('xcontrol',style='custom',show_label=False),
Item('csetting',style='custom',show_label=False),
show_labels = False, # 组中的所有控件都不显示标签
layout = 'tabbed',
),
show_labels = False # 组中的所有控件都不显示标签
),
resizable=True,
height=0.95,
width=0.99,
buttons=[OKButton,]
)
def _figure_default(self):
figure = Figure()
figure.add_axes([0.05, 0.04, 0.9, 0.92])
return figure
def _xcontrol_default(self):
return XControl(figure=self.figure)
def _csetting_default(self):
cs = XSetting(figure=self.figure)
cs.generate_candidate([base_infos,index_infos,custom_infos])
return cs
class EvapoRate(HasTraits):
" Bring up the whole mess"
er_plots = Instance(ER_plot_component)
er_state = Instance(ER_State)
plots_view = View(HSplit(
Item('er_plots', style='custom', show_label=False, width=0.7),
Item('er_state', style='custom', show_label=False, label='State'),
),
resizable=True,
height=0.7,
width=0.6,
x=0.1,
y=0.1,
title='EvapoRate HR@KIT2012-18 (git-version)')
traits_view = View(
Item('er_state', style='custom', show_label=False),
resizable=True,
x=-0.01,
y=0.05,
#height=0.7, width=0.6,
title='EvapoRate HR@KIT2012-18 (git-version)')
def _er_plots_default(self):
er_plots = ER_plot_component(data=self.data)
self.data.er_plots = er_plots
return er_plots
def _er_state_default(self):
er_state = ER_State(data=self.data)
self.data.er_state = er_state
return er_state
def default_traits_view(self):
view = View(
HSplit(
VSplit(
Item("object_class", editor=self.tree_editor, show_label=False,
visible_when="object.show_tree"),
Group(
Item("search", label="搜索"),
Item("search_result_str", show_label=False,
editor=ListStrEditor(editable=False, selected_index="search_result_index")),
label="Search"),
),
Item("current_document", style="custom", show_label=False,
editor=CodeEditor(lexer="null", search="top", line = "current_line",
mark_lines="mark_lines", mark_color=0xff7777)),
id = "tvtkdoc.hsplit"
),
width = 700,
height = 500,
resizable = True,
title = "TVTK文档浏览器",
id = "tvtkdoc",
handler = TVTKDocumentHandler(),
)
return view
def traits_view(self):
""" Default traits view for this class. """
help_action = Action(name='Info', action='preferences_help')
buttons = ['OK', 'Cancel']
if self.show_apply:
buttons = ['Apply'] + buttons
if self.show_help:
buttons = [help_action] + buttons
# A tree editor for preferences nodes.
tree_editor = TreeEditor(nodes=[
TreeNode(
node_for=[PreferencesNode],
auto_open=False,
children='children',
label='name',
rename=False,
copy=False,
delete=False,
insert=False,
menu=None,
),
],
on_select=self._selection_changed,
editable=False,
hide_root=True,
selected='selected_node',
show_icons=False)
view = View(
HSplit(
Item(
name='root',
editor=tree_editor,
show_label=False,
width=250,
),
Item(
name='selected_page',
#editor = WidgetEditor(),
show_label=False,
width=450,
style='custom',
),
),
buttons=buttons,
handler=PreferencesManagerHandler(model=self),
resizable=True,
title='Preferences',
width=.3,
height=.3,
kind='modal')
self.selected_page = self.pages[0]
return view
class ListDemo(HasTraits):
items = List(Str)
view = View(HSplit(Item("items", style="custom", show_label=False),
Item("items",
style="custom",
editor=CheckListEditor(values=filter_types,
cols=4)),
Item("items", editor=SetEditor(values=filter_types)),
show_labels=False),
resizable=True,
width=600,
title=u"简单列表编辑器演示")
class ComponentViewer(HasTraits):
""" A viewer of components for testing purposes """
# The component being viewed
component = Instance(Component)
# The canvas to which the component is added
canvas = Instance(Canvas)
# A view into a subsection of the canvas
viewport = Instance(Viewport)
# Default view
traits_view = View(HSplit(
Group(Item("viewport", editor=ComponentEditor(), show_label=False)),
Group(Item(name="component", style="custom", show_label=False),
scrollable=True)),
resizable=True,
id="canvas_viewer",
width=.6,
height=.4,
title="Viewer")
def _canvas_default(self):
""" Trait initialiser """
canvas = Canvas(draw_axes=True, bgcolor="honeydew")
return canvas
def _viewport_default(self):
""" Trait initialiser """
viewport = Viewport(component=self.canvas, enable_zoom=True)
viewport.tools.append(ViewportPanTool(viewport))
return viewport
def _component_changed(self, old, new):
""" Handles the component being changed.
"""
canvas = self.canvas
if old is not None:
canvas.remove(old)
if new is not None:
canvas.add(new)
def _anytrait_changed_for_component(self, new):
""" Handles redrawing of the canvas. """
self.canvas.request_redraw()
class MyDemo(HasTraits):
scene = Instance(SceneModel, ())
source = Instance(tvtk.ParametricFunctionSource, ())
func_name = Enum([c.__name__ for c in source_types])
func = Property(depends_on="func_name")
traits_view = View(HSplit(
VGroup(
Item("func_name", show_label=False),
Tabbed(
Item("func",
style="custom",
editor=InstanceEditor(),
show_label=False),
Item("source", style="custom", show_label=False))),
Item("scene", style="custom", show_label=False, editor=SceneEditor())),
resizable=True,
width=700,
height=600)
def __init__(self, *args, **kwds):
super(MyDemo, self).__init__(*args, **kwds)
self._make_pipeline()
def _get_func(self):
return sources[self.func_name]
def _make_pipeline(self):
self.func.on_trait_change(self.on_change, "anytrait")
src = self.source
src.on_trait_change(self.on_change, "anytrait")
src.parametric_function = self.func
map = tvtk.PolyDataMapper(input_connection=src.output_port)
act = tvtk.Actor(mapper=map)
self.scene.add_actor(act)
self.src = src
def _func_changed(self, old_func, this_func):
if old_func is not None:
old_func.on_trait_change(self.on_change, "anytrait", remove=True)
this_func.on_trait_change(self.on_change, "anytrait")
self.src.parametric_function = this_func
self.scene.render()
def on_change(self):
self.scene.render()
class ActorView(HasTraits):
cube = Instance(tvtk.CubeSource, ())
scene = Instance(SceneModel)
traits_view = View(HSplit(
Item("scene", style="custom", editor=SceneEditor(), show_label=False),
Item("cube", style="custom", show_label=False)),
resizable=True,
width=700,
height=600)
def _scene_default(self):
cube = self.cube
map = tvtk.PolyDataMapper(input=cube.output)
act = tvtk.Actor(mapper=map)
scene = SceneModel()
scene.add_actor(act)
return scene
def default_traits_view(self):
'''
Generates the view from the param items.
'''
#rf_param_items = [ Item( 'model.' + name, format_str = '%g' ) for name in self.model.param_keys ]
plot_param_items = [
Item('max_x', label='max x value'),
Item('n_points', label='No of plot points')
]
control_items = [
Item('show', show_label=False),
Item('clear', show_label=False),
]
view = View(
HSplit(
VGroup(
Item('@resp_func', show_label=False), #*rf_param_items,
label='Function Parameters',
id='stats.spirrid_bak.rf_model_view.rf_params',
scrollable=True),
VGroup(*plot_param_items,
label='Plot Parameters',
id='stats.spirrid_bak.rf_model_view.plot_params'),
VGroup(
Item('model.comment', show_label=False, style='readonly'),
label='Comment',
id='stats.spirrid_bak.rf_model_view.comment',
scrollable=True,
),
VGroup(HGroup(*control_items),
Item('figure',
editor=MPLFigureEditor(),
resizable=True,
show_label=False),
label='Plot',
id='stats.spirrid_bak.rf_model_view.plot'),
dock='tab',
id='stats.spirrid_bak.rf_model_view.split'),
kind='modal',
resizable=True,
dock='tab',
buttons=[OKButton],
id='stats.spirrid_bak.rf_model_view')
return view
class Model(HasTraits):
a = Code("print 'hello'")
b = Button("click me")
traits_view = View(HSplit(
VGroup(
Tabbed(
Item('a'),
Item('a'),
Item('a')),
Item('b')),
VSplit(
VGroup('b','b','b'),
HGroup('a', show_border=True,
label="traits is great")),
dock="horizontal"
),
resizable=True,
id="my.test.program.id")
class bcsr_gui(HasTraits):
n_rows = Long(0)
n_cols = Long(0)
n_mem = Float(0)
n_bs = Long(0)
rows = Array
cols = Array
values = Array
#matrix = Instance (tt)
view = View(Group(Item('n_rows', style='readonly', label='Number of rows'),
Item('n_cols',
style='readonly',
label='Number of columns'),
Item('n_bs', style='readonly', label='Block size'),
Item('n_mem',
style='readonly',
label='Total allocated memory (MB)'),
HSplit(
Item('rows',
show_label=False,
style='readonly',
editor=ArrayViewEditor(titles=['rows_ptr'],
format='%d',
font='Arial 8')),
Item('cols',
show_label=False,
style='readonly',
editor=ArrayViewEditor(titles=['cols_ind'],
format='%d',
font='Arial 8')),
Item('values',
show_label=False,
style='readonly',
editor=ArrayViewEditor(titles=['values'],
format='%lf',
font='Arial 8'))),
label='Matrix properties:',
show_border=True),
title='Block CSR matrix viewer',
width=0.5,
height=0.5,
resizable=True)
class OCCModel(HasTraits):
shapes = List
shape_list = Instance(ShapeList)
traits_view=View(HSplit(
Item('shape_list', editor=occ_tree, show_label=False,
width=-300),
Item('shape_list', editor=CustomEditor(MakeCanvas),
show_label=False, resizable=True),
id="occ.traits.test_feature_model_layout",
dock="fixed"
),
resizable=True,
width=1000,
height=800,
id="occ.traits.test_feature_model"
)
def _shapes_changed(self, vnew):
self.shape_list = ShapeList(shapes=vnew)
class PythonBrowser ( HasPrivateTraits ):
dir = Directory
files = List( FileInfo )
file_info = Instance( FileInfo )
code = Code
view = View(
HSplit(
Item( 'dir', style = 'custom' ),
VSplit(
Item( 'files', editor = tabular_editor ),
Item( 'code', style = 'readonly' ),
show_labels = False ),
show_labels = False
),
resizable = True,
width = 0.75,
height = 0.75
)
#-- Event Handlers ---------------------------------------------------------
def _dir_changed ( self, dir ):
self.files = [ FileInfo( file_name = join( dir, name ) )
for name in listdir( dir )
if ((splitext( name )[1] == '.py') and
isfile( join( dir, name ) )) ]
def _file_info_changed ( self, file_info ):
fh = None
try:
fh = open( file_info.file_name, 'rb' )
self.code = fh.read()
except:
pass
if fh is not None:
fh.close()
class EqualizerDesigner(HasTraits):
'''均衡器设计器的主界面'''
equalizers = Instance(Equalizers)
# 保存绘图数据的对象
plot_data = Instance(AbstractPlotData)
# 绘制波形图的容器
container = Instance(Component)
plot_gain = Instance(Component)
plot_phase = Instance(Component)
save_button = Button("Save")
load_button = Button("Load")
export_button = Button("Export")
view = View(VGroup(
HGroup(Item("load_button"),
Item("save_button"),
Item("export_button"),
show_labels=False),
HSplit(
VGroup(
Item("equalizers", style="custom", show_label=False),
show_border=True,
),
Item("container",
editor=ComponentEditor(size=(800, 300)),
show_label=False),
)),
resizable=True,
width=800,
height=500,
title="Equalizer Designer")
def _create_plot(self, data, name, type="line"):
p = Plot(self.plot_data)
p.plot(data, name=name, title=name, type=type)
p.tools.append(PanTool(p))
zoom = ZoomTool(component=p, tool_mode="box", always_on=False)
p.overlays.append(zoom)
p.title = name
p.index_scale = "log"
return p
def __init__(self):
super(EqualizerDesigner, self).__init__()
self.plot_data = ArrayPlotData(f=FREQS, gain=[], phase=[])
self.plot_gain = self._create_plot(("f", "gain"), "Gain(dB)")
self.plot_phase = self._create_plot(("f", "phase"), "Phase(degree)")
self.container = VPlotContainer()
self.container.add(self.plot_phase)
self.container.add(self.plot_gain)
self.plot_gain.padding_bottom = 20
self.plot_phase.padding_top = 20
def _equalizers_default(self):
return Equalizers()
@on_trait_change("equalizers.h")
def redraw(self):
gain = 20 * np.log10(np.abs(self.equalizers.h))
phase = np.angle(self.equalizers.h, deg=1)
self.plot_data.set_data("gain", gain)
self.plot_data.set_data("phase", phase)
def _save_button_fired(self):
dialog = FileDialog(action="save as", wildcard='EQ files (*.eq)|*.eq')
result = dialog.open()
if result == OK:
f = file(dialog.path, "wb")
pickle.dump(self.equalizers, f)
f.close()
def _load_button_fired(self):
dialog = FileDialog(action="open", wildcard='EQ files (*.eq)|*.eq')
result = dialog.open()
if result == OK:
f = file(dialog.path, "rb")
self.equalizers = pickle.load(f)
f.close()
def _export_button_fired(self):
dialog = FileDialog(action="save as", wildcard='c files (*.c)|*.c')
result = dialog.open()
if result == OK:
self.equalizers.export(dialog.path)
class RespFuncView(ModelView):
def __init__(self, **kw):
super(RespFuncView, self).__init__(**kw)
self._redraw()
self.on_trait_change(self._redraw, 'model.values')
model = Instance(RespFunc)
def _model_default(self):
return RespFunc()
figure = Instance(Figure)
def _figure_default(self):
figure = Figure(facecolor='white')
figure.add_axes([0.08, 0.13, 0.85, 0.74])
return figure
data_changed = Event(True)
count = Int
def _redraw(self):
self.count += 1
print('redraw', self.count)
# data post-processing
#
xdata, ydata = self.model.values
if self.model.approach.plot.yvalues == 'forces':
ylabel = 'pull-out force [N]'
else:
ydata = ydata / self.model.approach.Af
ylabel = 'pull-out stress [N/m2]'
title = self.model.boundary.type.BC
if title[0] == 'd':
xlabel = 'crack opening [m]'
else:
xlabel = 'displacement [m]'
figure = self.figure
axes = figure.axes[0]
axes.clear()
axes.plot(xdata, ydata, color='blue', linewidth=2, linestyle='solid')
axes.set_xlabel(xlabel, weight='semibold')
axes.set_ylabel(ylabel, weight='semibold')
axes.set_title( title, \
size='large', color='black', \
weight='bold', position=( .5, 1.03 ) )
axes.set_axis_bgcolor(color='white')
axes.ticklabel_format(scilimits=(-3., 4.))
axes.grid(color='gray', linestyle='--', linewidth=0.1, alpha=0.4)
self.data_changed = True
plot_button = Button('Plot pull-out')
def _plot_button_fired(self):
self._redraw()
traits_view = View(
HSplit(
VGroup(
Item('@model.boundary', show_label=False),
Item('@model.approach', show_label=False),
id='rf.model',
dock='tab',
label='pull-out model',
),
VGroup(
Item('figure',
editor=MPLFigureEditor(),
resizable=True,
show_label=False),
#Item('plot_button', show_label = False),
label='plot sheet',
id='rf.figure_window',
dock='tab',
),
id='rf.viewmodel.hsplit',
),
title='Response Function',
id='rf.viewmodel',
dock='tab',
kind='live',
resizable=True,
height=0.8,
width=0.8,
buttons=[OKButton])
def open(self, uiinfo):
file_name = open_file(filter=['*.pst'],
extensions=[FileInfo(), TextInfo()])
if file_name == '':
return
file = open(file_name, 'r')
self.model = pickle.load(file)
file.close()
def save(self, uiinfo):
file_name = save_file(filter=['*.pst'],
extensions=[FileInfo(), TextInfo()])
if file_name == '':
return
print('writing into', file_name)
file = open(file_name, 'w')
pickle.dump(self.model, file)
file.close()
class CSModelView(ModelView):
model = Instance(ClampSetup)
def _model_default(self):
return ClampSetup()
figure = Instance(Figure)
def _figure_default(self):
figure = Figure(facecolor='white')
figure.add_axes([0.08, 0.13, 0.85, 0.74])
return figure
data_changed = Event
@on_trait_change('model.+modified')
def refresh(self):
figure = self.figure
axes = figure.gca()
axes.clear()
cs = self.model
xu, u, xe, e = cs.get_values()
axes.set_xlabel('position on yarn', weight='semibold')
axes.set_axis_bgcolor(color='white')
axes.ticklabel_format(scilimits=(-3., 4.))
axes.grid(color='gray', linestyle='--', linewidth=0.5, alpha=0.7)
if cs.switch == 'strains':
axes.plot(xe, e, lw=2, color='blue')
axes.set_ylabel('strains [-]', weight='semibold')
axes.plot(array([cs.l1, cs.l1]),
array([0, max(e)]),
lw=2,
color='red',
linestyle='dashed')
axes.plot(array([cs.l1 + cs.L, cs.l1 + cs.L]),
array([0, max(e)]),
lw=2,
color='red',
linestyle='dashed')
axes.text(cs.l1 + cs.L / 2,
max(e) * 0.95,
'clamp',
size='large',
ha='center')
axes.text(cs.l1 + cs.L + cs.lt / 2,
max(e) * 0.95,
'tested length',
size='large',
ha='center')
elif cs.switch == 'displacement':
axes.plot(xu, u, lw=2, color='blue')
axes.set_ylabel('displacement [m]', weight='semibold')
axes.plot(array([cs.l1, cs.l1]),
array([0, max(u)]),
lw=2,
color='red',
linestyle='dashed')
axes.plot(array([cs.l1 + cs.L, cs.l1 + cs.L]),
array([0, max(u)]),
lw=2,
color='red',
linestyle='dashed')
axes.text(cs.l1 + cs.L / 2,
max(u) * 0.95,
'clamp',
size='large',
ha='center')
axes.text(cs.l1 + cs.L + cs.lt / 2,
max(u) * 0.95,
'tested length',
size='large',
ha='center')
else:
print 'NOT YET IMPLEMENTED'
# axes.plot(xslip, yslip, lw = 2, color = 'blue')
# axes.set_ylabel('slip in clamp [m]', weight = 'semibold')
# axes.set_xlabel('position in clamp [mm]', weight = 'semibold')
self.data_changed = True
traits_view = View(HSplit(
VGroup(
Item('model@', show_label=False, resizable=True),
label='Material parameters',
id='cs.viewmodel.model',
dock='tab',
),
VSplit(
VGroup(
Item('figure',
editor=MPLFigureEditor(),
resizable=True,
show_label=False),
label='yarn displacement',
id='cs.viewmodel.plot_window',
dock='tab',
),
id='cs.viewmodel.right',
),
id='cs.viewmodel.splitter',
),
title='tested yarn',
id='cs.viewmodel',
dock='tab',
resizable=True,
buttons=[OKButton],
height=0.8,
width=0.8)
class MayaviViewer(HasTraits):
"""
This class represents a Mayavi based viewer for the particles. They
are queried from a running solver.
"""
particle_arrays = List(Instance(ParticleArrayHelper), [])
pa_names = List(Str, [])
client = Instance(MultiprocessingClient)
host = Str('localhost', desc='machine to connect to')
port = Int(8800, desc='port to use to connect to solver')
authkey = Password('pysph', desc='authorization key')
host_changed = Bool(True)
scene = Instance(MlabSceneModel, ())
controller = Property()
########################################
# Timer traits.
timer = Instance(Timer)
interval = Range(2,
20.0,
5.0,
desc='frequency in seconds with which plot is updated')
########################################
# Solver info/control.
current_time = Float(0.0, desc='the current time in the simulation')
iteration = Int(0, desc='the current iteration number')
pause_solver = Bool(False, desc='if the solver should be paused')
########################################
# The layout of the dialog created
view = View(HSplit(
Group(
Group(
Item(name='host'),
Item(name='port'),
Item(name='authkey'),
label='Connection',
),
Group(
Item(name='current_time'),
Item(name='iteration'),
Item(name='pause_solver'),
Item(name='interval'),
label='Solver',
),
Group(
Item(name='particle_arrays',
style='custom',
show_label=False,
editor=ListEditor(use_notebook=True,
deletable=False,
page_name='.name'))),
),
Item('scene',
editor=SceneEditor(scene_class=MayaviScene),
height=480,
width=500,
show_label=False),
),
resizable=True,
title='Mayavi Particle Viewer')
######################################################################
# `MayaviViewer` interface.
######################################################################
@on_trait_change('scene.activated')
def start_timer(self):
# Just accessing the timer will start it.
t = self.timer
if not t.IsRunning():
t.Start(int(self.interval * 1000))
@on_trait_change('scene.activated')
def update_plot(self):
# do not update if solver is paused
if self.pause_solver:
return
controller = self.controller
if controller is None:
return
self.current_time = controller.get_t()
for idx, name in enumerate(self.pa_names):
pa = controller.get_named_particle_array(name)
self.particle_arrays[idx].particle_array = pa
######################################################################
# Private interface.
######################################################################
@on_trait_change('host,port,authkey')
def _mark_reconnect(self):
self.host_changed = True
def _get_controller(self):
''' get the controller, also sets the iteration count '''
reconnect = self.host_changed
if not reconnect:
try:
c = self.client.controller
self.iteration = c.get_count()
except Exception as e:
logger.info(
'Error: no connection or connection closed: reconnecting')
reconnect = True
self.client = None
if reconnect:
self.host_changed = False
try:
if MultiprocessingClient.is_available((self.host, self.port)):
self.client = MultiprocessingClient(address=(self.host,
self.port),
authkey=self.authkey)
else:
return None
except Exception as e:
logger.info('Could not connect: check if solver is running')
return None
c = self.client.controller
self.iteration = c.get_count()
return self.client.controller
def _client_changed(self, old, new):
if self.client is None:
return
else:
self.pa_names = self.client.controller.get_particle_array_names()
self.scene.mayavi_scene.children[:] = []
self.particle_arrays = [
ParticleArrayHelper(scene=self.scene, name=x)
for x in self.pa_names
]
# Turn on the legend for the first particle array.
if len(self.particle_arrays) > 0:
self.particle_arrays[0].show_legend = True
def _timer_event(self):
# catch all Exceptions else timer will stop
try:
self.update_plot()
except Exception as e:
logger.info('Exception: %s caught in timer_event' % e)
def _interval_changed(self, value):
t = self.timer
if t is None:
return
if t.IsRunning():
t.Stop()
t.Start(int(value * 1000))
def _timer_default(self):
return Timer(int(self.interval * 1000), self._timer_event)
def _pause_solver_changed(self, value):
c = self.client.controller
if value:
c.pause_on_next()
else:
c.cont()
class tcWindow(HasTraits):
project = tcProject
plot = tcPlot
def __init__(self, project):
self.project = project
self.plot = create_timechart_container(project)
self.plot_range_tools = self.plot.range_tools
self.plot_range_tools.on_trait_change(self._selection_time_changed,
"time")
self.trait_view().title = self.get_title()
def get_title(self):
if self.project.filename == "dummy":
return "PyTimechart: Please Open a File"
return "PyTimechart:" + self.project.filename
# Create an action that exits the application.
status = Str("Welcome to PyTimechart")
traits_view = View(
HSplit(
VSplit(
Item('project',
show_label=False,
editor=InstanceEditor(view='process_view'),
style='custom',
width=150),
# Item('plot_range_tools', show_label = False, editor=InstanceEditor(view = 'selection_view'), style='custom',width=150,height=100)
),
Item('plot', show_label=False, editor=ComponentEditor()),
),
toolbar=ToolBar(*_create_toolbar_actions(),
image_size=(24, 24),
show_tool_names=False),
menubar=MenuBar(*_create_menubar_actions()),
statusbar=[
StatusItem(name='status'),
],
resizable=True,
width=1280,
height=1024,
handler=tcActionHandler())
def _on_open_trace_file(self):
if open_file(None) and self.project.filename == "dummy":
self._ui.dispose()
def _on_view_properties(self):
self.plot.options.edit_traits()
def _on_exit(self, n=None):
self.close()
sys.exit(0)
def close(self, n=None):
pass
def _on_about(self):
aboutBox().edit_traits()
def _on_doc(self):
browse_doc()
def _selection_time_changed(self):
self.status = "selection time:%s" % (self.plot_range_tools.time)
class PointSelectionDemo(HasTraits):
color = Enum(Colors.keys())
green_selection = List()
red_selection = List()
plot = Instance(Plot)
data = Instance(ArrayPlotData)
traits_view = View(HSplit(
Item('plot', editor=ComponentEditor(), show_label=False),
VGroup(
Item("color", show_label=False, style="custom"),
Heading(u"绿色选择点"),
Item("green_selection", show_label=False, style="readonly"),
Heading(u"红色选择点"),
Item("red_selection", show_label=False, style="readonly"),
)),
width=800,
height=400,
resizable=True,
title=u"数据点选择演示")
def __init__(self, **traits):
super(PointSelectionDemo, self).__init__(**traits)
x = np.random.rand(100)
y = np.random.rand(100)
data = ArrayPlotData(x=x, y=y)
plot = Plot(data, padding=25)
self.scatter = scatter = plot.plot(("x", "y"),
type="scatter",
marker_size=4)[0]
self.select_tools = {}
for i, c in enumerate(Colors.keys()):
hover_name = "hover_%s" % c
selection_name = "selections_%s" % c
self.select_tools[c] = ScatterInspector(
scatter,
hover_metadata_name=hover_name,
selection_metadata_name=selection_name)
scatter.overlays.append(
ScatterInspectorOverlay(
scatter,
hover_metadata_name=hover_name,
selection_metadata_name=selection_name,
hover_color="transparent",
hover_outline_color=c,
hover_marker_size=6,
hover_line_width=1,
selection_color=Colors[c],
))
scatter.active_tool = self.select_tools[self.color]
scatter.index.on_trait_change(self.selection_changed,
'metadata_changed')
self.plot = plot
self.data = data
def _color_changed(self):
self.scatter.active_tool = self.select_tools[self.color]
def selection_changed(self):
x = self.scatter.index.get_data()
y = self.scatter.value.get_data()
metadata = self.scatter.index.metadata
selection = metadata.get("selections_green", [])
self.green_selection = [
"%d, (%f, %f)" % (s, x[s], y[s]) for s in selection
]
selection = metadata.get("selections_red", [])
self.red_selection = [
"%d, (%f, %f)" % (s, x[s], y[s]) for s in selection
]
class Graph(HasTraits):
"""
绘图组件，包括左边的数据选择控件和右边的绘图控件
"""
name = Str # 绘图名，显示在标签页标题和绘图标题中
data_source = Instance(DataSource) # 保存数据的数据源
figure = Instance(Figure) # 控制绘图控件的Figure对象
selected_xaxis = Str # X轴所用的数据名
selected_items = List # Y轴所用的数据列表
clear_button = Button(u"清除") # 快速清除Y轴的所有选择的数据
view = View(
HSplit( # HSplit分为左右两个区域，中间有可调节宽度比例的调节手柄
# 左边为一个组
VGroup(
Item("name"), # 绘图名编辑框
Item("clear_button"), # 清除按钮
Heading(u"X轴数据"), # 静态文本
# X轴选择器，用EnumEditor编辑器，即ComboBox控件，控件中的候选数据从
# data_source的names属性得到
Item("selected_xaxis", editor=
EnumEditor(name="object.data_source.names", format_str=u"%s")),
Heading(u"Y轴数据"), # 静态文本
# Y轴选择器，由于Y轴可以多选，因此用CheckBox列表编辑，按两列显示
Item("selected_items", style="custom",
editor=CheckListEditor(name="object.data_source.names",
cols=2, format_str=u"%s")),
show_border = True, # 显示组的边框
scrollable = True, # 组中的控件过多时，采用滚动条
show_labels = False # 组中的所有控件都不显示标签
),
# 右边绘图控件
Item("figure", editor=MPLFigureEditor(), show_label=False, width=600)
)
)
def _name_changed(self):
"""
当绘图名发生变化时，更新绘图的标题
"""
axe = self.figure.axes[0]
axe.set_title(self.name)
self.figure.canvas.draw()
def _clear_button_fired(self):
"""
清除按钮的事件处理
"""
self.selected_items = []
self.update()
def _figure_default(self):
"""
figure属性的缺省值，直接创建一个Figure对象
"""
figure = Figure()
figure.add_axes([0.1, 0.1, 0.85, 0.80]) #添加绘图区域，四周留有边距
return figure
def _selected_items_changed(self):
"""
Y轴数据选择更新
"""
self.update()
def _selected_xaxis_changed(self):
"""
X轴数据选择更新
"""
self.update()
def update(self):
"""
重新绘制所有的曲线
"""
axe = self.figure.axes[0]
axe.clear()
try:
xdata = self.data_source.data[self.selected_xaxis]
except:
return
for field in self.selected_items:
axe.plot(xdata, self.data_source.data[field], label=field)
axe.set_xlabel(self.selected_xaxis)
axe.set_title(self.name)
axe.legend()
self.figure.canvas.draw()
class PlotOMatic(HasTraits):
io_driver_list = Instance(IODriverList)
variables = Instance(Variables)
viewers = Instance(Viewers)
selected_viewer = Instance(Viewer)
handler = PlotOMaticHandler()
viewer_node = TreeNode(node_for=[Viewer],
auto_open=True,
label='name',
menu=Menu(handler.remove_viewer_action),
icon_path='icons/',
icon_item='plot.png')
tree_editor = TreeEditor(nodes=[
TreeNode(
node_for=[IODriverList],
auto_open=True,
children='io_drivers',
label='=Input Drivers',
menu=Menu(handler.refresh_tree_action,
handler.add_io_driver_actions_menu),
view=View(),
),
TreeNode(node_for=[IODriver],
auto_open=True,
children='_decoders',
label='name',
add=[DataDecoder],
menu=Menu(handler.remove_io_driver_action,
handler.refresh_tree_action,
handler.add_decoder_actions_menu),
icon_path='icons/',
icon_open='input.png',
icon_group='input.png'),
TreeNode(node_for=[DataDecoder],
auto_open=True,
children='',
label='name',
menu=Menu(handler.refresh_tree_action,
handler.remove_decoder_action),
icon_path='icons/',
icon_item='decoder.png'),
TreeNode(node_for=[IODriverList],
auto_open=True,
children='viewers',
label='=Viewers',
menu=Menu(handler.refresh_tree_action,
handler.add_viewer_actions_menu),
view=View()), viewer_node
],
hide_root=True,
orientation='vertical')
view = View(HSplit(
Item(name='io_driver_list',
editor=tree_editor,
resizable=True,
show_label=False,
width=.32),
VSplit(
Item(name='selected_viewer',
style='custom',
resizable=True,
show_label=False,
editor=InstanceEditor(view='view')),
Item(name='variables', show_label=False, style='custom',
height=.3))),
menubar=MenuBar(handler.file_menu, handler.data_menu),
title='Plot-o-matic',
resizable=True,
width=1000,
height=600,
handler=PlotOMaticHandler())
def __init__(self, **kwargs):
HasTraits.__init__(self, **kwargs)
self.viewer_node.on_select = self.click_viewer
def click_viewer(self, viewer):
self.selected_viewer = viewer
self.viewers.select_viewer(viewer)
def start(self):
self.io_driver_list.start_all()
self.viewers.start()
def stop(self):
self.viewers.stop()
self.io_driver_list.stop_all()
def get_config(self):
config = {}
config['io_drivers'] = self.io_driver_list.get_config()
config['viewers'] = self.viewers.get_config()
return config
def set_config(self, config):
if 'io_drivers' in config:
self.io_driver_list.set_config(config['io_drivers'])
if 'viewers' in config:
self.viewers.set_config(config['viewers'])
self.variables.clear()
class ImageSelections(HasTraits):
analysis = Instance(MultiSelections, transient=True)
figure = Instance(Figure, transient=True)
data = Array
def _analysis_default(self):
return MultiSelections()
def _figure_default(self):
def selection_callback(pos1, pos2):
if pos1 == pos2:
self.analysis.selection.set_from_corners(pos1)
else:
self.analysis.selection.set_from_corners(pos1, pos2)
figure = Figure(process_selection=selection_callback)
return figure
@on_trait_change('data')
def image_show(self):
self.figure.update_image(self.data)
@on_trait_change('analysis.updated')
def show_selection2(self):
def plot(selection, color, index):
s = selection
x, y = list(
map(lambda *args: args, s.top_left, s.top_right,
s.bottom_right, s.bottom_left, s.top_left))
self.figure.plot_data(x, y, str(index), color)
for i in range(len(self.analysis.selections) + 1):
self.figure.del_plot(str(i))
# self.figure.del_plot('all')
for index, selection in enumerate(self.analysis.selections):
if self.analysis.index == index:
color = 'red'
else:
color = 'black'
plot(selection, color, index)
view = View(
HSplit(
Item('figure', style='custom', width=0.5),
Group(Item('analysis',
style="custom",
resizable=True,
width=0.5,
show_label=False),
scrollable=True),
show_labels=False,
),
width=1200,
height=800,
resizable=True,
# statusbar = [ StatusItem( name = 'error')],
# title = 'Image selector'
)
class FieldExplorer(HasTraits):
scene = Instance(SceneModel, ())
wire = Instance(WireLoop)
interact = Bool(False)
ipl = Instance(tvtk.PlaneWidget, (), {
'resolution': 50,
'normal': [1., 0., 0.]
})
#plane_src = Instance(tvtk.PlaneSource, ())
calc_B = Instance(tvtk.ProgrammableFilter, ())
glyph = Instance(tvtk.Glyph3D, (), {'scale_factor': 0.02})
scale_factor = DelegatesTo("glyph")
lm = Instance(LUTManager, ())
traits_view = View(HSplit(
Item("scene", style="custom", editor=SceneEditor(), show_label=False),
VGroup(Item("wire", style="custom", show_label=False),
Item("interact"), Item("scale_factor"), Item("lm")),
),
resizable=True,
width=700,
height=600)
def _interact_changed(self, i):
self.ipl.interactor = self.scene.interactor
self.ipl.place_widget()
if i:
self.ipl.on()
else:
self.ipl.off()
def make_probe(self):
src = self.ipl.poly_data_algorithm
map = tvtk.PolyDataMapper(lookup_table=self.lm.lut)
act = tvtk.Actor(mapper=map)
calc_B = self.calc_B
calc_B.input = src.output
def execute():
print "calc fields!"
output = calc_B.poly_data_output
points = output.points.to_array().astype('d')
nodes = self.wire.nodes.astype('d')
vectors = calc_wire_B_field(nodes, points, self.wire.radius)
output.point_data.vectors = vectors
mag = np.sqrt((vectors**2).sum(axis=1))
map.scalar_range = (mag.min(), mag.max())
calc_B.set_execute_method(execute)
cone = tvtk.ConeSource(height=0.05, radius=0.01, resolution=15)
cone.update()
glyph = self.glyph
glyph.input_connection = calc_B.output_port
glyph.source = cone.output
glyph.scale_mode = 'scale_by_vector'
glyph.color_mode = 'color_by_vector'
map.input_connection = glyph.output_port
self.scene.add_actor(act)
def on_update(self):
self.calc_B.modified()
self.scene.render()
def _wire_changed(self, anew):
anew.on_trait_change(self.on_update, "update")
self.scene.add_actor(anew.actor)
class TriangleWave(HasTraits):
# 指定三角波的最窄和最宽范围，由于Range类型不能将常数和Traits属性名混用
# 所以定义这两个值不变的Trait属性
low = Float(0.02)
hi = Float(1.0)
# 三角波形的宽度
wave_width = Range("low", "hi", 0.5)
# 三角波的顶点C的x轴坐标
length_c = Range("low", "wave_width", 0.5)
# 三角波的定点的y轴坐标
height_c = Float(1.0)
# FFT计算所使用的取样点数，这里用一个Enum类型的属性以供用户从列表中选择
fftsize = Enum([(2**x) for x in range(6, 12)])
# FFT频谱图的x轴上限值
fft_graph_up_limit = Range(0, 400, 20)
# 用于显示FFT的结果
peak_list = Str
# 采用多少个频率合成三角波
N = Range(1, 40, 4)
# 保存绘图数据的对象
plot_data = Instance(AbstractPlotData)
# 绘制波形图的容器
plot_wave = Instance(Component)
# 绘制FFT频谱图的容器
plot_fft = Instance(Component)
# 包括两个绘图的容器
container = Instance(Component)
# 设置用户界面的视图， 注意一定要指定窗口的大小，这样绘图容器才能正常初始化
view = View(HSplit(
VSplit(
VGroup(Item("wave_width", editor=scrubber, label="波形宽度"),
Item("length_c", editor=scrubber, label="最高点x坐标"),
Item("height_c", editor=scrubber, label="最高点y坐标"),
Item("fft_graph_up_limit", editor=scrubber, label="频谱图范围"),
Item("fftsize", label="FFT点数"), Item("N", label="合成波频率数")),
Item("peak_list",
style="custom",
show_label=False,
width=100,
height=250)),
VGroup(Item("container",
editor=ComponentEditor(size=(600, 300)),
show_label=False),
orientation="vertical")),
resizable=True,
width=800,
height=600,
title="三角波FFT演示")
# 创建绘图的辅助函数，创建波形图和频谱图有很多类似的地方，因此单独用一个函数以
# 减少重复代码
def _create_plot(self, data, name, type="line"):
p = Plot(self.plot_data)
p.plot(data, name=name, title=name, type=type)
p.tools.append(PanTool(p))
zoom = ZoomTool(component=p, tool_mode="box", always_on=False)
p.overlays.append(zoom)
p.title = name
return p
def __init__(self):
# 首先需要调用父类的初始化函数
super(TriangleWave, self).__init__()
# 创建绘图数据集，暂时没有数据因此都赋值为空，只是创建几个名字，以供Plot引用
self.plot_data = ArrayPlotData(x=[], y=[], f=[], p=[], x2=[], y2=[])
# 创建一个垂直排列的绘图容器，它将频谱图和波形图上下排列
self.container = VPlotContainer()
# 创建波形图，波形图绘制两条曲线： 原始波形(x,y)和合成波形(x2,y2)
self.plot_wave = self._create_plot(("x", "y"), "Triangle Wave")
self.plot_wave.plot(("x2", "y2"), color="red")
# 创建频谱图，使用数据集中的f和p
self.plot_fft = self._create_plot(("f", "p"), "FFT", type="scatter")
# 将两个绘图容器添加到垂直容器中
self.container.add(self.plot_wave)
self.container.add(self.plot_fft)
# 设置
self.plot_wave.x_axis.title = "Samples"
self.plot_fft.x_axis.title = "Frequency pins"
self.plot_fft.y_axis.title = "(dB)"
# 改变fftsize为1024，因为Enum的默认缺省值为枚举列表中的第一个值
self.fftsize = 1024
# FFT频谱图的x轴上限值的改变事件处理函数，将最新的值赋值给频谱图的响应属性
def _fft_graph_up_limit_changed(self):
self.plot_fft.x_axis.mapper.range.high = self.fft_graph_up_limit
def _N_changed(self):
self.plot_sin_combine()
# 多个trait属性的改变事件处理函数相同时，可以用@on_trait_change指定
@on_trait_change("wave_width, length_c, height_c, fftsize")
def update_plot(self):
# 计算三角波
global y_data
x_data = np.arange(0, 1.0, 1.0 / self.fftsize)
func = self.triangle_func()
# 将func函数的返回值强制转换成float64
y_data = np.cast["float64"](func(x_data))
# 计算频谱
fft_parameters = np.fft.fft(y_data) / len(y_data)
# 计算各个频率的振幅
fft_data = np.clip(
20 * np.log10(np.abs(fft_parameters))[:self.fftsize / 2 + 1], -120,
120)
# 将计算的结果写进数据集
self.plot_data.set_data("x", np.arange(0, self.fftsize)) # x坐标为取样点
self.plot_data.set_data("y", y_data)
self.plot_data.set_data("f", np.arange(0, len(fft_data))) # x坐标为频率编号
self.plot_data.set_data("p", fft_data)
# 合成波的x坐标为取样点，显示2个周期
self.plot_data.set_data("x2", np.arange(0, 2 * self.fftsize))
# 更新频谱图x轴上限
self._fft_graph_up_limit_changed()
# 将振幅大于-80dB的频率输出
peak_index = (fft_data > -80)
peak_value = fft_data[peak_index][:20]
result = []
for f, v in zip(np.flatnonzero(peak_index), peak_value):
result.append("%s : %s" % (f, v))
self.peak_list = "\n".join(result)
# 保存现在的fft计算结果，并计算正弦合成波
self.fft_parameters = fft_parameters
self.plot_sin_combine()
# 计算正弦合成波，计算2个周期
def plot_sin_combine(self):
index, data = fft_combine(self.fft_parameters, self.N, 2)
self.plot_data.set_data("y2", data)
# 返回一个ufunc计算指定参数的三角波
def triangle_func(self):
c = self.wave_width
c0 = self.length_c
hc = self.height_c
def trifunc(x):
x = x - int(x) # 三角波的周期为1，因此只取x坐标的小数部分进行计算
if x >= c: r = 0.0
elif x < c0: r = x / c0 * hc
else: r = (c - x) / (c - c0) * hc
return r
# 用trifunc函数创建一个ufunc函数，可以直接对数组进行计算, 不过通过此函数
# 计算得到的是一个Object数组，需要进行类型转换
return np.frompyfunc(trifunc, 1, 1)
class FitGUI(ModelView):
""" Implements a Model-View style controller and default view that provides
a matplolib graphical representation of an ImpedanceAnalysis model.
"""
text_display = Str
params_gui = Instance(ParameterSetGUI)
fit_button = Button()
plot = Instance(IPlot)
has_fit = Bool(False)
pick_mode = Int(0)
view = View(
HSplit(
VGroup(
Item(
'text_display',
style='custom',
show_label=False,
#springy = True,
height=0.50,
width=0.20,
),
# VGrid(
# Item('model.selection_low_index', width=0.05,),
# Item('model.selection_high_index', width=0.05,),
Item(
'params_gui',
show_label=False,
style='custom',
springy=True,
#height=0.30,
width=0.20,
),
Item(
'fit_button',
label="Run Fit",
show_label=False,
#style='custom',
#springy = True,
#height=0.30,
width=0.20,
),
# columns = 1,
# ),
),
Item(
'plot',
#editor = MPLFigureEditor(), #this editor will automatically find and connect the _handle_onpick method for handling matplotlib's object picking events
style='custom',
show_label=False,
height=0.80,
width=0.60,
),
),
height=0.80,
width=0.80,
resizable=True,
)
#--------------------------------------------------------------------------
def run_fit(self):
self.model.fit()
self.has_fit = True
new_params = self.model.params
self.params_gui.model = new_params
self.params_gui.render_fields() #FIXME - to use a gentler field update
self._print(self.model.fit_log, loc='front')
self.update_plot()
# def _plot_default(self):
# return SimpleFunctionPlot()
@on_trait_change('model')
def update_all(self):
self.params_gui = ParameterSetGUI(self.model.params)
self._clear_display()
self.update_plot()
@on_trait_change('plot')
def setup_onpick_handler(self):
self.plot.register_onpick_handler(self._handle_onpick)
def update_plot(self):
self.plot.clear()
Xs = []
Ys = []
#get all the data
X_data, Y_data, W_data = self.model.get_data()
Xs.append(X_data)
Ys.append(Y_data)
#get the data selection
X_sel, Y_sel, W_sel = self.model.get_selection()
Xs.append(X_sel)
Ys.append(Y_sel)
if self.has_fit:
X_fit, Y_fit = self.model.interpolate(density=10)
Xs.append(X_fit)
Ys.append(Y_fit)
self.plot.render(Xs, Ys, fmts=['b.', 'kx', 'r-'], pickable=[0])
self.plot.redraw()
def _fit_button_fired(self):
self.run_fit()
#--------------------------------------------------------------------------
def _handle_onpick(self, event):
"handles a data point pick event depending on the mode"
#extract information from the event
line = event.artist
ind = event.ind[
0] #the selected data index as first (nearest) in the group
X = line.get_xdata()
Y = line.get_ydata()
x = X[ind]
y = Y[ind]
pick_mode = self.pick_mode
print event.__dict__
if pick_mode == 0:
self._print("\nlow point selected at index: %s (%e, %e)" %
(ind, x, y),
loc='front')
self.model.selection_low_index = ind
self.model.selection_high_index = Undefined
self.pick_mode = 1
time.sleep(0.1)
elif pick_mode == 1:
self._print("\nhigh point selected at index: %s (%e, %e)" %
(ind, x, y),
loc='front')
self.model.selection_high_index = ind
if self.model.selection_low_index != self.model.selection_high_index:
self.run_fit()
self.pick_mode = 0
#--------------------------------------------------------------------------
def _clear_display(self):
self.text_display = ""
def _print(self, text, indent="\t", level=0, newline='\n', loc='front'):
text = str(text)
if level >= 1: #reformat the text to indent it
text_lines = text.split(newline)
space = indent * level
text_lines = ["%s%s" % (space, line) for line in text_lines]
text = newline.join(text_lines)
if loc == 'end':
self.text_display += text + newline
elif loc == 'front':
self.text_display = text + newline + self.text_display
else:
raise ValueError, "'loc' must be 'front' or 'end'"
class Images(HasTraits):
"""Main class for image point selections
"""
filenames = Instance(Filenames, ())
analysis = Instance(RectangleSelections, transient=True)
filters = List(Instance(BaseFilter))
figure = Instance(Figure, transient=True)
data = Array
def _filters_default(self):
return [Rotate(), GaussianFilter()]
def _analysis_default(self):
return RectangleSelections()
def _figure_default(self):
def selection_callback(pos1, pos2):
try:
if pos1 == pos2:
self.analysis.selection.set_from_points(pos1)
else:
self.analysis.selection.set_from_points(pos1, pos2)
except:
pass
figure = Figure(process_selection=selection_callback)
return figure
@on_trait_change('filenames.selected')
def open_image(self):
data = imread(self.filenames.selected)
for f in self.filters:
data = f.process(data)
self.data = data
@on_trait_change('data,analysis.updated')
def image_show(self):
try:
self.figure.plot_image(self.data)
except:
pass
@on_trait_change('analysis.updated')
def show_selection2(self):
def plot(selection, color, index):
s = selection
x, y = list(
map(lambda *args: args, s.top_left, s.top_right,
s.bottom_right, s.bottom_left, s.top_left))
self.figure.plot_data(x, y, str(index), color)
for i in range(len(self.analysis.selections) + 1):
self.figure.del_plot(str(i))
for index, selection in enumerate(self.analysis.selections):
if self.analysis.index == index:
color = 'red'
else:
color = 'black'
try:
plot(selection, color, index)
except:
pass
view = View(
VSplit(HSplit(Item('figure', style='custom', width=0.6, height=0.7),
Group(Item('analysis',
style="custom",
resizable=True,
width=0.4,
height=0.7,
show_label=False),
scrollable=True),
show_labels=False),
HSplit(
Group(
Item('filenames',
style='custom',
show_label=False,
height=0.3)),
Item('filters@',
id='notebook',
show_label=False,
editor=ListEditor(use_notebook=True,
deletable=False,
selected='selected',
export='DockWindowShell',
page_name='.name_'))),
show_labels=False),
width=1000,
height=800,
resizable=True,
)
class ImageTimeseriesViewer(BaseDataViewer):
plots = Dict
plotdata = Instance(ArrayPlotData)
image = Any
time_index = Int
time_points = Int
time = Any
traits_view = View(
Tabbed(
HSplit(
VGroup(
Item('plot',
editor=ComponentEditor(),
show_label=False,
resizable=True,
label='View'),
Item("time_index",
style='custom',
editor=RangeEditor(low=0, high_name='time_points')),
Item("time", style='readonly'),
),
Item('tasks', style='custom', show_label=False, label='Tasks'),
),
Item('results', style='custom', show_label=False, label='Results'),
), )
def _time_points_default(self):
return self.data.shape[0] - 1
def _time_index_default(self):
return 0
def _time_default(self):
return self.get_data_time(0, 0)
def _plotdata_default(self):
data = self.get_data_slice(0, 0)
plotdata = ArrayPlotData()
plotdata.set_data('xy', data)
return plotdata
def _time_index_changed(self):
self.select_xy_slice(self.time_index)
def select_xy_slice(self, t):
data = self.get_data_slice(t, 0)
self.time = self.get_data_time(t, 0)
self.plotdata.set_data('xy', data)
self.image.invalidate_and_redraw()
def reset(self):
pass
def redraw(self):
self.image.invalidate_and_redraw()
def get_plot(self):
pixel_sizes = self.data_source.pixel_sizes
shape = self.data.shape[1:]
m = min(pixel_sizes)
s = [int(d * sz / m) for d, sz in zip(shape, pixel_sizes)]
plot_sizes = dict(xy=(s[1], s[0]))
plot = Plot(
self.plotdata,
padding=30,
fixed_preferred_size=plot_sizes['xy'],
)
image = plot.img_plot('xy', colormap=bone)[0]
image.overlays.append(ZoomTool(image))
image.tools.append(PanTool(image, drag_button='right'))
imgtool = ImageInspectorTool(image)
image.tools.append(imgtool)
overlay = ImageInspectorOverlay(component=image,
bgcolor='white',
image_inspector=imgtool)
image.overlays.append(overlay)
self.image = image
self.plots = dict(xy=image)
return plot
# -*- coding: utf-8 -*-
class MainWindow(HasTraits):
parameter_file_collections = Instance(ParameterFileCollectionList)
parameter_files = Instance(ParameterFileCollection)
plot_frame_tabs = List(Instance(DataObject))
open_parameterfile = Button
shell = PythonValue
def _shell_default(self):
return globals()
notebook_editor = ListEditor(editor=InstanceEditor(editable=True),
use_notebook=True)
traits_view = View(
VSplit(
HSplit(
VGroup(
Item(
'parameter_file_collections',
width=120.0,
height=500.0,
show_label=False,
editor=TreeEditor(
editable=False,
nodes=[
TreeNode(
node_for=[ParameterFileCollectionList],
children='parameter_file_collections',
label="=Data Collections"),
TreeNode(node_for=[ParameterFileCollection],
children='parameter_files',
label="name",
view=View()),
TreeNode(node_for=[ParameterFile],
children='data_objects',
label="name",
menu=Menu(
Action(name='Slice',
action='object.do_slice'),
Action(name='Project',
action='object.do_proj'),
Action(name='VTK',
action='object.do_vtk')),
view=View()),
TreeNode(node_for=[DataObject],
children='',
label="name"),
],
show_icons=False),
), Item('open_parameterfile', show_label=False)),
Item('plot_frame_tabs',
style='custom',
editor=notebook_editor,
show_label=False,
height=500.0,
width=500.0),
),
HGroup(
#Item('shell', editor=ShellEditor(share=True),
#show_label=False, height=120.0),
),
),
resizable=True,
width=800.0,
height=660.0,
title="reason v2 [prototype]")
def _open_parameterfile_fired(self):
print "OPENING"
def _parameter_file_collections_default(self):
return ParameterFileCollectionList()