class VResizeDialog(HasTraits):
txt = Str("hallo")
traits_view = View(
VGroup(Item("txt", width=_TXT_WIDTH, resizable=True)),
width=_DIALOG_WIDTH,
height=_DIALOG_HEIGHT,
resizable=True,
)
def test_vertical_layout(self):
view = View(
VGroup(
Item("txt1"),
Item("txt2"),
)
)
with reraise_exceptions(), \
create_ui(MultipleTrait(), ui_kwargs=dict(view=view)):
pass
class NewModelADialog(NewModelDialog):
"""Create a dialog requesting the parameters to create Model A."""
model_name = Str(MODEL_A_NAME)
nclasses = Int(5)
parameters_group = VGroup(
Item(name='nclasses',
editor=RangeEditor(mode='spinner', low=3, high=1000),
label='Number of annotation classes:',
width=100), )
class NoLabelResizeTestDialog(HasTraits):
""" Test the combination show_label=False, show_left=False.
"""
bool_item = Bool(True)
traits_view = View(VGroup(Item('bool_item',
resizable=True,
show_label=False),
show_left=False),
resizable=True)
def default_traits_view(self):
return View(
VGroup(
UItem(
"resizable_readonly_item",
resizable=True,
style="readonly",
), ),
height=_DIALOG_HEIGHT,
width=_DIALOG_WIDTH,
)
def traits_view(self):
ctrl_grp = VGroup(
# HGroup(UItem('add_band')),
UItem('highlight_bands', height=115,editor=ListEditor(mutable=False,
style='custom',
editor=InstanceEditor())))
v = View(
VSplit(
ctrl_grp,
UItem('container',
editor=ComponentEditor(height=700))))
return v
class VResizeDialog(HasTraits):
txt = Str('hallo')
traits_view = View(
VGroup(
Item('txt', width=_TXT_WIDTH, resizable=True),
),
width=_DIALOG_WIDTH,
height=_DIALOG_HEIGHT,
resizable=True
)
def traits_view(self):
w_view = 350 if is_display_small() else 480
parameters_group = VGroup(
Item('_'),
HGroup(
VGroup(
Spring(),
Item('handler.omega_hinton_diagram',
style='custom',
resizable=False,
show_label=False,
width=w_view), Spring()), Spring(),
VGroup(Spring(), Item('handler.view_omega', show_label=False),
Spring())), Spring(), Item('_'), Spring(),
HGroup(
VGroup(
UItem('handler.theta_views'),
UItem('handler.theta_view',
style='custom',
resizable=False,
width=w_view), Spring()), Spring(),
VGroup(Spring(), UItem('handler.view_theta'), Spring())))
body = VGroup(Include('info_group'), parameters_group)
traits_view = View(body, buttons=[OKButton], resizable=True)
return traits_view
class SaveFileDialog(HasTraits):
save_file = File(exists=False)
dpi = Int(300)
traits_view = View(VGroup(
Item('save_file',
label='Save to:',
editor=FileEditor(allow_dir=False, dialog_style='save',
entries=0),
style='simple'), Item('dpi', label='Resolution (dpi):')),
title='Save plot',
width=400,
resizable=True,
buttons=OKCancelButtons)
def traits_view(self):
db_table_editor = TableEditor(
columns=[
ObjectColumn(name='data_id',
label='Annotations ID',
editable=False,
width=0.65),
ObjectColumn(name='model_name', editable=False, width=0.20),
ObjectColumn(name='value',
label='Log likelihood',
editable=False,
width=0.15)
],
search=SearchIDFilter(),
editable=True,
deletable=True,
configurable=False,
sortable=True,
sort_model=False,
auto_size=False,
orientation='vertical',
show_toolbar=True,
selection_mode='row',
on_dclick=self.forward_to_model_data_view,
on_select=self.track_selection)
traits_view = View(
VGroup(
Item(
'results_table',
editor=db_table_editor,
show_label=False,
),
HGroup(
Item('open_to_main', show_label=False, width=100),
Item('delete_action',
show_label=False,
enabled_when='current_selection is not None',
width=100), Spring(),
Item('close_view', show_label=False, width=100)),
),
title='pyAnno results database',
width=800,
height=400,
resizable=True,
#buttons = [ 'OK' ],
kind='live')
return traits_view
class EnableWhenDialog(HasTraits):
""" Test labels for enable when. """
bool_item = Bool(True)
labelled_item = Str('test')
unlabelled_item = Str('test')
traits_view = View(VGroup(
Item('bool_item', ),
Item('labelled_item', enabled_when='bool_item'),
Item('unlabelled_item', enabled_when='bool_item', show_label=False),
),
resizable=True)
def traits_view(self):
self.statistics_name = "Cohen's Kappa"
traits_view = View(VGroup(
HGroup(Item("statistics_name", show_label=False),
Item("info_button", show_label=False)),
Spring(),
HGroup(
Spring(),
Item("stats_view",
style="custom",
show_label=False,
width=300,
resizable=False), Spring()),
),
width=400,
resizable=True)
return traits_view
class EnableWhenDialog(HasTraits):
""" Test labels for enable when. """
bool_item = Bool(True)
labelled_item = Str("test")
unlabelled_item = Str("test")
traits_view = View(
VGroup(
Item("bool_item"),
Item("labelled_item", enabled_when="bool_item"),
Item("unlabelled_item", enabled_when="bool_item",
show_label=False),
),
resizable=True,
)
class TestShowArray(HasTraits):
data = Array
view = View(Item('data',
editor=TabularEditor(adapter=Array2DAdapter(
ncolumns=2, format='%s', show_index=False)),
show_label=False),
title='Array2D editor',
width=0.3,
height=0.8,
resizable=True,
buttons=NoButtons)
VGroup(
Item('data',
editor=TabularEditor(adapter=Array2DAdapter(
ncolumns=2, format='%d', show_index=False)),
show_label=False)),
def traits_view(self):
traits_view = View(
VGroup(
Item('annotator_idx',
label='Annotator index',
editor=RangeEditor(mode='spinner',
low=0, high=self.theta.shape[0]-1,
),
),
HGroup(
Item('theta_j_view',
style='custom',
show_label=False),
),
),
width = 500,
height = 400,
resizable = True
)
return traits_view
def traits_view(self):
nclasses = self.beta.shape[1]
w_table = WIDTH_CELL * nclasses
h_table = HEIGHT_CELL * nclasses
w_view = min(MAX_WIDTH, w_table + W_MARGIN)
h_view = min(MAX_HEIGHT, h_table + HEIGHT_CELL + H_MARGIN)
view = View(
VGroup(
Label('Beta parameters (prior over pi):'),
UItem('beta',
editor=TabularEditor(
adapter=Array2DAdapter(ncolumns=nclasses,
format='%.4f',
show_index=True,
count_from_one=False),
),
width = w_table,
height = HEIGHT_CELL,
padding = 10
),
Label('Alpha parameters (prior over theta):'),
UItem('alpha',
editor=TabularEditor(
adapter=Array2DAdapter(ncolumns=nclasses,
format='%.4f',
show_index=True,
count_from_one=False),
),
width = w_table,
height = h_table,
padding = 10
),
),
width = w_view,
height = h_view,
scrollable = True,
resizable = True,
buttons = ['OK', 'Cancel']
)
return view
def _get_auto_group(self):
return VGroup(
HGroup(
icon_button_editor(
'plot_button',
'refresh',
tooltip='Replot the isotope evolutions. '
'This may take awhile if many analyses are selected'),
icon_button_editor('save_event',
'database_save',
tooltip='Save fits to database'),
Item(
'auto_update',
label='Auto Plot',
tooltip=
'Should the plot refresh after each change ie. "fit" or "show". '
'It is not advisable to use this option with many analyses'
)),
HGroup(
UItem('global_fit', editor=EnumEditor(name='fit_types')),
UItem('global_error_type',
editor=EnumEditor(name='error_types'))))
class EventSelectionDialog(HasTraits):
source_class_label = String("Select Event Source Classes")
severity_level_label = String("Select Event Severity Levels")
search = String(regex="^[_a-zA-Z0-9\*\.\$\^\?\s]*$")
shown_event_names_list = String(regex="[_a-zA-Z0-9\*\.\$\^\?\n]*")
quit_button = Button('Quit')
query_button = Button('Run Query...')
period_start_date = DelegatesTo("query_object")
period_end_date = DelegatesTo("query_object")
selected_list_of_event_severity_levels = DelegatesTo("query_object")
list_of_event_severity_levels = DelegatesTo("query_object")
selected_list_of_source_classes = DelegatesTo("query_object")
list_of_source_classes = DelegatesTo("query_object")
query_object = Instance(EventSelectionQuery)
spring = Spring
help_text = (
"Search engine like queries using alphanumeric characters and '_'and '.' \n"
+ "Space indicate OR-separated queries\n" +
"? = match any character\n" + "* = any number of characters\n" +
"^ = match beginning\n"
"$ = match end")
view = View(
Group(
VGroup(
HGroup(Item("period_start_date", label="Period"),
Item("period_end_date", show_label=False),
Item("", resizable=True, width=1.0, show_label=False),
HGroup(Item('quit_button', show_label=False),
Item('query_button', show_label=False)),
springy=True),
HGroup(
VGroup(
HGroup(
Item("severity_level_label",
show_label=False,
style="readonly")),
Item("selected_list_of_event_severity_levels",
editor=CheckListEditor(
name="list_of_event_severity_levels"),
style="custom",
show_label=False)),
VGroup(
HGroup(
Item("source_class_label",
show_label=False,
style="readonly")),
Item("selected_list_of_source_classes",
editor=CheckListEditor(
name="list_of_source_classes"),
style="custom",
show_label=False)),
# springy=True
),
show_border=True),
Item("_"),
VGroup(Item("search",
editor=HistoryEditor(auto_set=True),
show_label=False,
width=1.0,
tooltip=help_text),
Item(
name='shown_event_names_list',
style='readonly',
resizable=True,
show_label=False,
),
scrollable=True,
show_border=True),
orientation='vertical',
),
title='Select Events to Visualize',
dock='horizontal',
resizable=True,
width=.5,
height=.7)
def __init__(self, query_object, **kwargs):
'''
Creates a dialog window for selecting date period, source classes and event severity levels/types.
:param query_object:
:return:
'''
assert isinstance(query_object, EventSelectionQuery)
self.shown_event_names_list = "\n".join(
list(query_object.list_of_event_names))
self.query_object = query_object
self.query_start_date = query_object.period_start_date
self.query_end_date = query_object.period_end_date
HasTraits.__init__(self, **kwargs)
def _search_changed(self):
'''
Matches search query to the event names.
:return:
'''
query_st = str(self.search).strip()
if re.match("^[_a-zA-Z0-9\*\.\$\^\?\s]*$", query_st) is None:
return
query_st = query_st.replace(".", "\.")
query_st = query_st.replace("*", ".*")
query_st = query_st.replace("?", ".?")
queries = query_st.split()
print self.search, query_st, queries,
if len(queries) == 0:
queries = [""]
result = [
s for s in list(self.query_object.list_of_event_names)
for q in queries if re.search((".*%s.*" % q), s) is not None
]
self.query_object.selected_list_of_event_names = result
self.shown_event_names_list = "\n".join(result)
print len(self.shown_event_names_list)
def _save_search(self):
# A bug fix, stops the clearing of the search expression
tmp = self.search
self.search = " "
self.search = tmp
print len(self.query_object.selected_list_of_event_names)
def _query_button_changed(self):
self._save_search()
self.query_object.execute_query()
def _quit_button_changed(self):
self._save_search()
sys.exit(0)
class PosteriorPlot(PyannoPlotContainer):
# data to be displayed
posterior = Array
### plot-related traits
plot_width = Float
def _plot_width_default(self):
return 450 if is_display_small() else 500
plot_height = Float
def _plot_height_default(self):
return 600 if is_display_small() else 750
colormap_low = Float(0.0)
colormap_high = Float(1.0)
origin = Str('top left')
plot_container = Instance(HPlotContainer)
plot_posterior = Instance(Plot)
def _create_colormap(self):
if self.colormap_low is None:
self.colormap_low = self.posterior.min()
if self.colormap_high is None:
self.colormap_high = self.posterior.max()
colormap = Reds(
DataRange1D(low=self.colormap_low, high=self.colormap_high))
return colormap
def _plot_container_default(self):
data = self.posterior
nannotations, nclasses = data.shape
# create a plot data object
plot_data = ArrayPlotData()
plot_data.set_data("values", data)
# create the plot
plot = Plot(plot_data, origin=self.origin)
img_plot = plot.img_plot("values",
interpolation='nearest',
xbounds=(0, nclasses),
ybounds=(0, nannotations),
colormap=self._create_colormap())[0]
ndisp = 55
img_plot.y_mapper.range.high = ndisp
img_plot.y_mapper.domain_limits = ((0, nannotations))
self._set_title(plot)
plot.padding_top = 80
# create x axis for labels
label_axis = self._create_increment_one_axis(plot, 0.5, nclasses,
'top')
label_axis.title = 'classes'
self._add_index_axis(plot, label_axis)
plot.y_axis.title = 'items'
# tweak plot aspect
goal_aspect_ratio = 2.0
plot_width = (goal_aspect_ratio * self.plot_height * nclasses / ndisp)
self.plot_width = min(max(plot_width, 200), 400)
plot.aspect_ratio = self.plot_width / self.plot_height
# add colorbar
colormap = img_plot.color_mapper
colorbar = ColorBar(index_mapper=LinearMapper(range=colormap.range),
color_mapper=colormap,
plot=img_plot,
orientation='v',
resizable='',
width=15,
height=250)
colorbar.padding_top = plot.padding_top
colorbar.padding_bottom = int(self.plot_height - colorbar.height -
plot.padding_top)
colorbar.padding_left = 0
colorbar.padding_right = 30
# create a container to position the plot and the colorbar side-by-side
container = HPlotContainer(use_backbuffer=True)
container.add(plot)
container.add(colorbar)
container.bgcolor = 0xFFFFFF # light gray: 0xEEEEEE
# add pan tools
img_plot.tools.append(
PanTool(img_plot,
constrain=True,
constrain_direction="y",
speed=7.))
self.decorate_plot(container, self.posterior)
self.plot_posterior = plot
return container
def add_markings(self,
mark_classes,
mark_name,
marker_shape,
delta_x,
delta_y,
marker_size=5,
line_width=1.,
marker_color='white'):
plot = self.plot_posterior
nannotations = plot.data.arrays['values'].shape[0]
y_name = mark_name + '_y'
x_name = mark_name + '_x'
valid = is_valid(mark_classes)
y_values = np.arange(nannotations)[valid] + delta_y + 0.5
x_values = mark_classes[valid].astype(float) + delta_x + 0.5
plot.data.set_data(y_name, y_values)
plot.data.set_data(x_name, x_values)
plot.plot((x_name, y_name),
type='scatter',
name=mark_name,
marker=marker_shape,
marker_size=marker_size,
color='transparent',
outline_color=marker_color,
line_width=line_width)
def remove_markings(self, mark_name):
self.plot_posterior.delplot(mark_name)
def _create_resizable_view(self):
# resizable_view factory, as I need to compute the height of the plot
# from the number of annotations, and I couldn't find any other way to
# do that
# "touch" posterior_plot to have it initialize
self.plot_container
if is_display_small():
height = 760
else:
height = 800
resizable_plot_item = (Item(
'plot_container',
editor=ComponentEditor(),
resizable=True,
show_label=False,
width=self.plot_width,
height=self.plot_height,
))
resizable_view = View(VGroup(
Include('instructions_group'),
resizable_plot_item,
),
width=450,
height=height,
resizable=True)
return resizable_view
def traits_view(self):
return self._create_resizable_view()
pan_instructions = Str
def _pan_instructions_default(self):
return 'Left-click and drag to navigate items'
instructions_group = VGroup(
HGroup(Spring(),
Item('instructions', style='readonly', show_label=False),
Spring()),
HGroup(Spring(),
Item('pan_instructions', style='readonly', show_label=False),
Spring()))
def traits_view(self):
v = View(
VGroup(self._get_auto_group(), self._get_toggle_group(),
self._get_fit_group()))
return v
def traits_view(self):
## Model view
# adjust sizes to display size
if is_display_small():
# full view size
w_view, h_view = 1024, 768
w_data_create_group = 350
w_data_info_group = 500
h_annotations_stats = 270
else:
w_view, h_view = 1300, 850
w_data_create_group = 400
w_data_info_group = 700
h_annotations_stats = 330
model_create_group = (VGroup(HGroup(
UItem(name='model_name', width=200),
UItem(name='new_model', width=100),
UItem(name='get_info_on_model', width=100, height=25),
),
label='Create new model'))
model_group = (VGroup(
model_create_group,
VGroup(
Item('model_view', style='custom', show_label=False,
width=400),
label='Model view',
),
), )
## Data view
data_create_group = VGroup(
#Label('Open annotation file:', width=800),
HGroup(
Item('annotations_file',
style='simple',
label='Open file:',
width=w_data_create_group,
height=25), UItem('new_annotations', height=25)),
label='Load/create annotations',
show_border=False,
)
data_info_group = VGroup(
Item(
'annotations_view',
style='custom',
show_label=False,
visible_when='annotations_are_defined',
width=w_data_info_group,
),
Item('annotations_stats_view',
style='custom',
show_label=False,
visible_when='annotations_are_defined',
height=h_annotations_stats),
label='Data view',
)
data_group = (VGroup(
data_create_group,
data_info_group,
), )
## (Model,Data) view
model_data_group = (
VGroup(
#Item('info_string', show_label=False, style='readonly'),
Item('log_likelihood',
label='Log likelihood',
style='readonly'),
HGroup(
Item('ml_estimate',
enabled_when='annotations_are_defined'),
Item('map_estimate',
enabled_when='annotations_are_defined'),
Item('sample_posterior_over_accuracy',
enabled_when='annotations_are_defined'),
Item('estimate_labels',
enabled_when='annotations_are_defined'),
Spring(),
Item('add_to_database',
enabled_when='annotations_are_defined'),
Item('open_database'),
show_labels=False,
),
label='Model-data view',
))
## Full view
full_view = View(
VGroup(
HGroup(model_group, data_group),
model_data_group,
),
title='PyAnno - Models of data annotations by multiple curators',
width=w_view,
height=h_view,
resizable=False)
return full_view
class ProjectInfoUI(cmp.project.ProjectInfo):
"""Class that extends the :class:`ProjectInfo` with graphical components.
It supports graphically the setting of all processing properties / attributes
of an :class:`ProjectInfo` instance.
Attributes
-----------
creation_mode : traits.Enum
Mode for loading the dataset. Valid values are
'Load BIDS dataset', 'Install Datalad BIDS dataset'
install_datalad_dataset_via_ssh : traits.Bool
If set to True install the datalad dataset from a remote server
via ssh.(True by default)
ssh_user : traits.Str
Remote server username.
(Required if ``install_datalad_dataset_via_ssh`` is True)
ssh_pwd <traits.Password>
Remote server password.
(Required if ``install_datalad_dataset_via_ssh`` is True)
ssh_remote : traits.Str
Remote server IP or URL.
(Required if ``install_datalad_dataset_via_ssh`` is True)
datalad_dataset_path : traits.Directory
Path to the datalad dataset on the remote server.
(Required if ``install_datalad_dataset_via_ssh`` is True)
summary_view_button : traits.ui.Button
Button that shows the pipeline processing summary table
pipeline_processing_summary_view : traits.ui.VGroup
TraitsUI VGroup that contains ``Item('pipeline_processing_summary')``
dataset_view : traits.ui.View
TraitsUI View that shows a summary of project settings and
modality available for a given subject
traits_view : QtView
TraitsUI QtView that includes the View 'dataset_view'
create_view : traits.ui.View
Dialog view to create a BIDS Dataset
subject_view : traits.ui.View
Dialog view to select of subject
subject_session_view : traits.ui.View
Dialog view to select the subject session
dmri_bids_acq_view : traits.ui.View
Dialog view to select the diffusion acquisition model
anat_warning_view : traits.ui.View
View that displays a warning message regarding
the anatomical T1w data
anat_config_error_view : traits.ui.View
Error view that displays an error message regarding
the configuration of the anatomical pipeline
dmri_warning_view : traits.ui.View
View that displays a warning message regarding
the diffusion MRI data
dmri_config_error_view : traits.ui.View
View that displays an error message regarding
the configuration of the diffusion pipeline
fmri_warning_view : traits.ui.View
View that displays a warning message regarding
the functional MRI data
fmri_config_error_view : traits.ui.View
View that displays an error message regarding
the configuration of the fMRI pipeline
open_view : traits.ui.View
Dialog view to load a BIDS Dataset
anat_select_config_to_load : traits.ui.View
Dialog view to load the configuration file of the anatomical pipeline
diffusion_imaging_model_select_view : traits.ui.View
Dialog view to select the diffusion acquisition model
dmri_select_config_to_load : traits.ui.View
Dialog view to load the configuration file of the diffusion MRI pipeline
fmri_select_config_to_load : traits.ui.View
Dialog view to load the configuration file of the fMRI pipeline
"""
creation_mode = Enum("Load BIDS dataset", "Install Datalad BIDS dataset")
install_datalad_dataset_via_ssh = Bool(True)
ssh_user = String("remote_username")
ssh_pwd = Password("")
ssh_remote = String("IP address/ Machine name")
datalad_dataset_path = Directory(
"/shared/path/to/existing/datalad/dataset")
anat_runs = List()
anat_run = Enum(values="anat_runs")
dmri_runs = List()
dmri_run = Enum(values="dmri_runs")
fmri_runs = List()
fmri_run = Enum(values="fmri_runs")
summary_view_button = Button("Pipeline processing summary")
pipeline_processing_summary_view = VGroup(
Item("pipeline_processing_summary"))
dataset_view = VGroup(
VGroup(
HGroup(
Item(
"base_directory",
width=-0.3,
style="readonly",
label="",
resizable=True,
),
Item(
"number_of_subjects",
width=-0.3,
style="readonly",
label="Number of participants",
resizable=True,
),
"summary_view_button",
),
label="BIDS Dataset",
),
spring,
HGroup(
Group(
Item("subject",
style="simple",
show_label=True,
resizable=True)),
Group(
Item("subject_session",
style="simple",
label="Session",
resizable=True),
visible_when='subject_session!=""',
),
springy=True,
),
spring,
Group(
Item("t1_available", style="readonly", label="T1", resizable=True),
HGroup(
Item(
"dmri_available",
style="readonly",
label="Diffusion",
resizable=True,
),
Item(
"diffusion_imaging_model",
label="Model",
resizable=True,
enabled_when="dmri_available",
),
),
Item("fmri_available",
style="readonly",
label="BOLD",
resizable=True),
label="Modalities",
),
spring,
Group(
Item(
"anat_last_date_processed",
label="Anatomical pipeline",
style="readonly",
resizable=True,
enabled_when="t1_available",
),
Item(
"dmri_last_date_processed",
label="Diffusion pipeline",
style="readonly",
resizable=True,
enabled_when="dmri_available",
),
Item(
"fmri_last_date_processed",
label="fMRI pipeline",
style="readonly",
resizable=True,
enabled_when="fmri_available",
),
label="Last date processed",
),
spring,
Group(Item("number_of_cores", resizable=True),
label="Processing configuration"),
"550",
spring,
springy=True,
)
traits_view = QtView(Include("dataset_view"))
create_view = View(
Item("creation_mode", style="custom"),
Group(
Group(
Item("base_directory", label="BIDS Dataset"),
visible_when='creation_mode=="Load BIDS dataset"',
),
Group(
Item("install_datalad_dataset_via_ssh"),
visible_when='creation_mode=="Install Datalad/BIDS dataset"',
),
Group(
Item(
"ssh_remote",
label="Remote ssh server",
visible_when="install_datalad_dataset_via_ssh",
),
Item(
"ssh_user",
label="Remote username",
visible_when="install_datalad_dataset_via_ssh",
),
Item(
"ssh_pwd",
label="Remote password",
visible_when="install_datalad_dataset_via_ssh",
),
Item(
"datalad_dataset_path",
label="Datalad/BIDS Dataset Path/URL to be installed",
),
Item("base_directory", label="Installation directory"),
visible_when='creation_mode=="Install Datalad/BIDS dataset"',
),
),
kind="livemodal",
title="Data creation: BIDS dataset selection",
# style_sheet=style_sheet,
width=modal_width,
buttons=["OK", "Cancel"],
)
subject_view = View(
Group(Item("subject", label="Selected Subject")),
kind="modal",
title="Subject and session selection",
# style_sheet=style_sheet,
width=modal_width,
buttons=["OK", "Cancel"],
)
subject_session_view = View(
Group(
Item("subject", style="readonly", label="Selected Subject"),
Item("subject_session", label="Selected Session"),
),
kind="modal",
title="Session selection",
# style_sheet=style_sheet,
width=modal_width,
buttons=["OK", "Cancel"],
)
dmri_bids_acq_view = View(
Group(Item("dmri_bids_acq", label="Selected model"), ),
kind="modal",
title="Selection of diffusion acquisition model",
# style_sheet=style_sheet,
width=modal_width,
buttons=["OK", "Cancel"],
)
anat_warning_view = View(
Group(Item("anat_warning_msg", style="readonly", show_label=False), ),
title="Warning : Anatomical T1w data",
kind="modal",
width=modal_width,
# style_sheet=style_sheet,
buttons=["OK", "Cancel"],
)
anat_config_error_view = View(
Group(
Item("anat_config_error_msg", style="readonly",
show_label=False), ),
title="Error",
kind="modal",
width=modal_width,
# style_sheet=style_sheet,
buttons=["OK", "Cancel"],
)
dmri_warning_view = View(
Group(Item("dmri_warning_msg", style="readonly", show_label=False), ),
title="Warning : Diffusion MRI data",
kind="modal",
width=modal_width,
# style_sheet=style_sheet,
buttons=["OK", "Cancel"],
)
dmri_config_error_view = View(
Group(
Item("dmri_config_error_msg", style="readonly",
show_label=False), ),
title="Error",
kind="modal",
width=modal_width,
# style_sheet=style_sheet,
buttons=["OK", "Cancel"],
)
fmri_warning_view = View(
Group(Item("fmri_warning_msg", style="readonly", show_label=False), ),
title="Warning : fMRI data",
kind="modal",
width=modal_width,
# style_sheet=style_sheet,
buttons=["OK", "Cancel"],
)
fmri_config_error_view = View(
Group(
Item("fmri_config_error_msg", style="readonly",
show_label=False), ),
title="Error",
kind="modal",
width=modal_width,
# style_sheet=style_sheet,
buttons=["OK", "Cancel"],
)
open_view = View(
Item("creation_mode", label="Mode"),
Group(
Item("install_datalad_dataset_via_ssh"),
Item(
"ssh_remote",
label="Remote ssh server",
visible_when="install_datalad_dataset_via_ssh",
),
Item(
"ssh_user",
label="Remote username",
visible_when="install_datalad_dataset_via_ssh",
),
Item(
"ssh_pwd",
label="Remote password",
visible_when="install_datalad_dataset_via_ssh",
),
Item(
"datalad_dataset_path",
label="Datalad/BIDS Dataset Path/URL to be installed",
),
Item("base_directory", label="Installation directory"),
visible_when='creation_mode=="Install Datalad BIDS dataset"',
),
Group(
Item("base_directory", label="BIDS Dataset"),
visible_when='creation_mode=="Load BIDS dataset"',
),
kind="livemodal",
title="BIDS Dataset Creation/Loading",
# style_sheet=style_sheet,
width=600,
height=250,
buttons=["OK", "Cancel"],
)
anat_select_config_to_load = View(
Group(
Item("anat_config_to_load_msg", style="readonly",
show_label=False),
Item(
"anat_config_to_load",
style="custom",
editor=EnumEditor(name="anat_available_config"),
show_label=False,
),
),
title="Select configuration for anatomical pipeline",
kind="modal",
width=modal_width,
# style_sheet=style_sheet,
buttons=["OK", "Cancel"],
)
anat_custom_map_view = View(
Group(
Item(
"anat_custom_last_stage",
editor=EnumEditor(name="anat_stage_names"),
style="custom",
show_label=False,
), ),
title="Select until which stage to process the anatomical pipeline.",
kind="modal",
width=modal_width,
# style_sheet=style_sheet,
buttons=["OK", "Cancel"],
)
diffusion_imaging_model_select_view = View(
Group(Item("diffusion_imaging_model",
label="Diffusion MRI modality"), ),
title="Please select diffusion MRI modality",
kind="modal",
width=modal_width,
buttons=["OK", "Cancel"],
)
dmri_select_config_to_load = View(
Group(
Item("dmri_config_to_load_msg", style="readonly",
show_label=False), ),
Item(
"dmri_config_to_load",
style="custom",
editor=EnumEditor(name="dmri_available_config"),
show_label=False,
),
title="Select configuration for diffusion pipeline",
kind="modal",
width=modal_width,
# style_sheet=style_sheet,
buttons=["OK", "Cancel"],
)
dmri_custom_map_view = View(
Group(
Item(
"dmri_custom_last_stage",
editor=EnumEditor(name="dmri_stage_names"),
style="custom",
show_label=False,
), ),
title="Select until which stage to process the diffusion pipeline.",
kind="modal",
width=modal_width,
# style_sheet=style_sheet,
buttons=["OK", "Cancel"],
)
fmri_select_config_to_load = View(
Group(
Item("fmri_config_to_load_msg", style="readonly",
show_label=False), ),
Item(
"fmri_config_to_load",
style="custom",
editor=EnumEditor(name="fmri_available_config"),
show_label=False,
),
title="Select configuration for fMRI pipeline",
kind="modal",
width=modal_width,
# style_sheet=style_sheet,
buttons=["OK", "Cancel"],
)
fmri_custom_map_view = View(
Group(
Item(
"fmri_custom_last_stage",
editor=EnumEditor(name="fmri_stage_names"),
style="custom",
show_label=False,
), ),
title="Select until which stage to process the fMRI pipeline.",
kind="modal",
width=modal_width,
# style_sheet=style_sheet,
buttons=["OK", "Cancel"],
)
def _summary_view_button_fired(self):
self.configure_traits(view="pipeline_processing_summary_view")
class DummyDataView3(BaseDataView):
description = (
"Empty dummy data view that actually has a even longer description")
view = View(VGroup())
class DummyDataView2(BaseDataView):
description = None
view = View(VGroup())
class DummyDataView1(BaseDataView):
description = "Empty data view with a long description"
view = View(VGroup())
def traits_view(self):
if is_display_small():
w_view = 400
else:
w_view = 510
parameters_group = VGroup(
Item('_'),
HGroup(
Item('handler.edit_prior',
show_label=False,
width=100),
Spring(),
),
Item('_'),
HGroup(
VGroup(
Spring(),
Item('handler.pi_hinton_diagram',
style='custom',
resizable=False,
show_label=False,
width=w_view),
Spring(),
),
Spring(),
VGroup(
Spring(),
Item('handler.view_pi', show_label=False),
Spring()
),
),
Item('_'),
HGroup(
VGroup(
Item('handler.theta_views',
show_label=False),
Item('handler.theta_view',
style='custom',
resizable=False,
show_label=False,
width = w_view),
Spring()
),
VGroup(
Spring(),
Item('handler.view_theta', show_label=False),
Spring()
)
),
)
body = VGroup(
Include('info_group'),
parameters_group
)
traits_view = View(body, buttons=[OKButton], resizable=True)
return traits_view
class Recorder(HasTraits, ICameraListener):
"""Container to save all records of a experiment"""
#=========================================================================
# Important components to interact
#=========================================================================
plotview = Instance(PlotView, ())
#=========================================================================
# Properties of the recorder
#=========================================================================
input_ports = List(Port)
container = List(List)
record_information = List()
images = List()
record_mode = Bool()
logger = getLogger('Application')
def __init__(self, record_mode):
self.logger.debug('Initialize Recorder')
self.record_mode = record_mode
self.plotview.model = self
self.result_viewer = ResultViewer(self)
def append(self, info, rec):
"""Appends new values to the recorder.
:param info: Values of the input ports.
:type info: List(Float)
:param rec: Recording time.
:type rec: str.
"""
pid, value = info
for i in range(self.n):
p = self.input_ports[i]
if p.id == pid:
self.container[i].append((rec, value))
def reset(self, input_ports):
"""Reset all information of the recorder
:param input_ports: All input ports of the measuring card
:type input_ports: List(Port)
"""
del self.input_ports[:]
del self.container[:]
del self.record_information[:]
self.plotview.update_subplots(input_ports)
self.n = len(input_ports)
for i in range(self.n):
self.input_ports.append(input_ports[i])
self.container.append([])
def get_values(self):
"""Returns all recorded values"""
res = []
for i in range(len(self.container[0])):
row = []
for j in range(self.n):
rec, val = self.container[j][i]
row.append(val)
row.insert(0, time_to_secs(rec))
res.append(row)
return array(res)
#=========================================================================
# Update methods
#=========================================================================
def _update_record_information(self, index):
"""Update the record information by the given index
:param index: Index of the values which should show
:type index: int
"""
self.index = index
del self.record_information[:]
for i in range(self.n):
rec, val = self.container[i][index]
label = '{0}: {1:.3f}'.format(self.input_ports[i].name, val)
self.record_information.append(label)
self.record_information.append('Time: {0}'.format(rec))
if not self.show_reference:
files = get_all_files(images_dir)
self.update_reference(files[0])
self.plotview.update_focus_point(index)
self.result_viewer.update_image(index)
def update_reference(self, f):
"""Load the reference image from the reference dir"""
self.logger.debug("Update reference image [Recorder]")
self.reference_image = ImageResource(join(resized_images_dir, f))
self.show_reference = True
def _update_plots(self):
# Update all values with the currently values of the recorder.
self.plotview.update_values(self.get_values())
def update_image(self, index):
self.result_viewer.show_recorded_image(index)
#=========================================================================
# Methods to save and load the data
#=========================================================================
def save(self):
self.logger.debug("Save recorded values [Recorder]")
Recorder.save_values(self.get_values())
Recorder.save_images(self.images)
@staticmethod
def save_values(values):
save(join(recorder_dir, recording_file), values)
@staticmethod
def save_images(images):
data = {}
data["images"] = []
for img in images:
data["images"].append(img)
with open(join(recorder_dir, recorder_file), 'w') as f:
dump(data, f, indent=2)
def load(self, input_ports):
self.logger.debug("Load recorded values [Recorder]")
with open(join(recorder_dir, recorder_file), 'r') as f:
data = jload(f)
self.images = data["images"]
values = load(join(recorder_dir, recording_file))
self.reset(input_ports)
nv = len(values)
nip = len(input_ports)
self.plotview.update_subplots(input_ports)
self.plotview.update_values(values)
for i in range(nv):
t = secs_to_time(values[i, 0])
for j in range(nip):
self.container[j].append((t, values[i, j + 1]))
self.result_viewer.show_images=False
self._update_record_information(0)
self.show_images=True
#=========================================================================
# Traitsview + Traitsevent
#=========================================================================
result_viewer = Instance(ResultViewer)
scroll_able = Bool(True)
show_images = Bool(False)
show_reference = Bool(False)
reference_image = Image()
def _show_images_changed(self):
self.result_viewer.show_images=self.show_images
view = View(
VGroup(
HGroup(
VGroup(
InstanceUItem('plotview', style='custom', width=400),
VGroup(
UItem('record_information',
editor=ListStrEditor(auto_add=False, editable=False)),
label="Recorded values:",
visible_when='show_images'
)
),
VGroup(
VGroup(
UItem('reference_image', width=300, height=225),
label='Reference Image:',
visible_when='show_reference'
),
VGroup(
UItem('result_viewer', style='custom',
visible_when='show_images'),
),
layout='normal'
),
)
)
)
