def _initialize_window(self, parent, wxid):
""" Initialize the window with the specified Id. """
window = parent.FindWindowById(wxid)
sizer = wx.BoxSizer(wx.VERTICAL)
window.SetSizer(sizer)
window.SetAutoLayout(True)
window.SetBackgroundColour('white')
window.SetWindowStyleFlag(wx.CLIP_CHILDREN)
window.Refresh()
image = ImageResource('closed_folder_24x24')
bitmap = image.create_image().ConvertToBitmap()
image_widget = ImageWidget(window, bitmap=bitmap)
image_widget.control.SetBackgroundColour('white')
sizer.Add(image_widget.control, 0, wx.EXPAND)
text = wx.StaticText(window, -1, "Blah", style=wx.ALIGN_CENTRE)
sizer.Add(text, 0, wx.EXPAND)
# Resize the window to match the sizer's minimum size.
sizer.Fit(window)
return
def image_resource ( self, image_name ):
""" Returns the ImageResource object for the specified **image_name**.
"""
# Get the name of the image file:
volume_name, file_name = split_image_name( image_name )
if self.is_zip_file:
# See if we already have the image file cached in the file system:
cache_file = self._check_cache( file_name )
if cache_file is None:
# If not cached, then create a zip file reference:
ref = ZipFileReference(
resource_factory = resource_manager.resource_factory,
zip_file = self.zip_file,
path = self.path,
volume_name = self.name,
file_name = file_name )
else:
# Otherwise, create a cache file reference:
ref = ImageReference( resource_manager.resource_factory,
filename = cache_file )
else:
# Otherwise, create a normal file reference:
ref = ImageReference( resource_manager.resource_factory,
filename = join( self.path, file_name ) )
# Create the ImageResource object using the reference (note that the
# ImageResource class will not allow us to specify the reference in the
# constructor):
resource = ImageResource( file_name )
resource._ref = ref
# Return the ImageResource:
return resource
def __init__(self, parent, tool_bar, image_cache, item, controller,
show_labels):
""" Creates a new tool bar tool for an action item. """
self.item = item
self.tool_bar = tool_bar
# Create an appropriate tool depending on the style of the action.
action = self.item.action
# If the action has an image then convert it to a bitmap (as required
# by the toolbar).
if action.image is not None:
image = action.image.create_image()
path = action.image.absolute_path
bmp = image_cache.get_bitmap(path)
else:
from pyface.api import ImageResource
image = ImageResource('foo')
bmp = image.create_bitmap()
self.control_id = 1
self.control = None
if controller is not None:
self.controller = controller
controller.add_to_toolbar(self)
return
def _get_image ( self ):
path, name = split( self.file_name )
if splitext( name )[1] in ( '.png', '.gif', '.jpg', '.jpeg' ):
image = ImageResource( name, search_path = [ path ] )
else:
image = ImageResource( 'unknown' )
self._cur_image = image.create_image()
return image
def show_minibuffer(self, minibuffer, **kwargs):
# minibuffer_pane_info is stored in the TaskWindow instance because all
# tasks use the same minibuffer pane in the AUI manager
try:
info = self.window.minibuffer_pane_info
except AttributeError:
panel = wx.Panel(self.window.control, style=wx.NO_BORDER)
sizer = wx.BoxSizer(wx.HORIZONTAL)
close_image = ImageResource('cancel')
bmp = close_image.create_bitmap()
close = wx.BitmapButton(panel, -1, bmp, size=(bmp.GetWidth()+10, bmp.GetHeight()+10), style=wx.NO_BORDER)
close.Bind(wx.EVT_BUTTON, self.on_hide_minibuffer_or_cancel)
sizer.Add(close, 0, wx.EXPAND)
panel.SetSizer(sizer)
info = self.create_minibuffer_info()
self.window._aui_manager.AddPane(panel, info)
# info.window is set to panel in the AUI code
self.window.minibuffer_pane_info = info
repeat = False
if info.minibuffer is not None:
if info.minibuffer.is_repeat(minibuffer):
log.debug("Reusing old minibuffer control: %s" % info.minibuffer.control)
repeat = True
else:
log.debug("Removing old minibuffer control: %s" % info.minibuffer.control)
info.window.GetSizer().Hide(0)
info.window.GetSizer().Remove(0)
info.minibuffer.destroy_control()
log.debug("Children: %s" % info.window.GetSizer().Children)
if not repeat:
minibuffer.create_control(info.window)
info.window.GetSizer().Insert(0, minibuffer.control, 1, wx.EXPAND)
info.window.GetSizer().Layout()
minibuffer.focus()
info.minibuffer = minibuffer
log.debug("Window: %s, info: %s" % (self.window, info))
else:
info.minibuffer.focus()
info.minibuffer.repeat(minibuffer) # Include new minibuffer
if not info.IsShown():
info.Show()
self.window._aui_manager.Update()
class ExampleTask(Task):
""" A simple task for opening a blank editor.
"""
#### Task interface #######################################################
id = 'example.example_task'
name = 'Multi-Tab Editor'
active_editor = Property(Instance(IEditor),
depends_on='editor_area.active_editor')
editor_area = Instance(IEditorAreaPane)
menu_bar = SMenuBar(
SMenu(TaskAction(name='New', method='new', accelerator='Ctrl+N'),
id='File',
name='&File'),
SMenu(DockPaneToggleGroup(),
TaskToggleGroup(),
id='View',
name='&View'))
tool_bars = [
SToolBar(TaskAction(method='new',
tooltip='New file',
image=ImageResource('document_new')),
image_size=(32, 32)),
]
###########################################################################
# 'Task' interface.
###########################################################################
def _default_layout_default(self):
return TaskLayout(top=PaneItem('steps.example_pane'))
def create_central_pane(self):
""" Create the central pane: the script editor.
"""
self.editor_area = EditorAreaPane()
return self.editor_area
def create_dock_panes(self):
""" Create the file browser and connect to its double click event.
"""
pane = ExamplePane()
return [pane]
###########################################################################
# 'ExampleTask' interface.
###########################################################################
def new(self):
""" Opens a new empty window
"""
editor = Editor()
self.editor_area.add_editor(editor)
self.editor_area.activate_editor(editor)
self.activated()
#### Trait property getter/setters ########################################
def _get_active_editor(self):
if self.editor_area is not None:
return self.editor_area.active_editor
return None
def get_icon(self):
return ImageResource('logicle')
def get_icon(self):
return ImageResource('bead_calibration')
def get_icon(self):
return ImageResource('bleedthrough_piecewise')
def get_icon(self):
return ImageResource('radviz')
class NodeType(HasPrivateTraits):
""" The base class for all node types. """
# The default image used to represent nodes that DO NOT allow children.
DOCUMENT = ImageResource("document")
# The default image used to represent nodes that allow children and are NOT
# expanded.
CLOSED_FOLDER = ImageResource("closed_folder")
# The default image used to represent nodes that allow children and ARE
# expanded.
OPEN_FOLDER = ImageResource("open_folder")
# 'NodeType' interface -------------------------------------------------
# The node manager that the type belongs to.
node_manager = Instance("pyface.tree.node_manager.NodeManager")
# The image used to represent nodes that DO NOT allow children.
image = Image(DOCUMENT)
# The image used to represent nodes that allow children and are NOT
# expanded.
closed_image = Image(CLOSED_FOLDER)
# The image used to represent nodes that allow children and ARE expanded.
open_image = Image(OPEN_FOLDER)
# The default actions/groups/menus available on nodes of this type (shown
# on the context menu).
actions = Any # List
# The default action for nodes of this type. The default action is
# performed when a node is activated (i.e., double-clicked).
default_action = Instance(Action)
# The default actions/groups/menus for creating new children within nodes
# of this type (shown in the 'New' menu of the context menu).
new_actions = Any # List
# ------------------------------------------------------------------------
# 'NodeType' interface.
# ------------------------------------------------------------------------
# These methods are specific to the 'NodeType' interface ---------------
def is_type_for(self, node):
""" Returns True if a node is deemed to be of this type. """
raise NotImplementedError()
def allows_children(self, node):
""" Does the node allow children (ie. a folder vs a file). """
return False
def get_actions(self, node):
""" Returns the node-specific actions for a node. """
return self.actions
def get_context_menu(self, node):
""" Returns the context menu for a node. """
sat = Group(id="SystemActionsTop")
nsa = Group(id="NodeSpecificActions")
sab = Group(id="SystemActionsBottom")
# The 'New' menu.
new_actions = self.get_new_actions(node)
if new_actions is not None and len(new_actions) > 0:
sat.append(MenuManager(name="New", *new_actions))
# Node-specific actions.
actions = self.get_actions(node)
if actions is not None and len(actions) > 0:
for item in actions:
nsa.append(item)
# System actions (actions available on ALL nodes).
system_actions = self.node_manager.system_actions
if len(system_actions) > 0:
for item in system_actions:
sab.append(item)
context_menu = MenuManager(sat, nsa, sab)
context_menu.dump()
return context_menu
def get_copy_value(self, node):
""" Get the value that is copied for a node.
By default, returns the node itself.
"""
return node
def get_default_action(self, node):
""" Returns the default action for a node. """
return self.default_action
def get_new_actions(self, node):
""" Returns the new actions for a node. """
return self.new_actions
def get_paste_value(self, node):
""" Get the value that is pasted for a node.
By default, returns the node itself.
"""
return node
def get_monitor(self, node):
""" Returns a monitor that detects changes to a node.
Returns None by default, which indicates that the node is not
monitored.
"""
return None
# These methods are exactly the same as the 'TreeModel' interface -----#
def has_children(self, node):
""" Returns True if a node has children, otherwise False.
You only need to implement this method if children are allowed for the
node (ie. 'allows_children' returns True).
"""
return False
def get_children(self, node):
""" Returns the children of a node.
You only need to implement this method if children are allowed for the
node.
"""
raise NotImplementedError()
def get_drag_value(self, node):
""" Get the value that is dragged for a node.
By default, returns the node itself.
"""
return node
def can_drop(self, node, data):
""" Returns True if a node allows an object to be dropped onto it. """
return False
def drop(self, obj, data):
""" Drops an object onto a node. """
raise NotImplementedError()
def get_image(self, node, selected, expanded):
""" Returns the label image for a node. """
if self.allows_children(node):
if expanded:
order = ["open_image", "closed_image", "image"]
default = self.OPEN_FOLDER
else:
order = ["closed_image", "open_image", "image"]
default = self.CLOSED_FOLDER
else:
order = ["image", "open_image", "closed_image"]
default = self.DOCUMENT
# Use the search order to look for a trait that is NOT None.
for name in order:
image = getattr(self, name)
if image is not None:
break
# If no such trait is found then use the default image.
else:
image = default
return image
def get_selection_value(self, node):
""" Get the value that is used when a node is selected.
By default the selection value is the node itself.
"""
return node
def get_text(self, node):
""" Returns the label text for a node. """
return str(node)
def can_set_text(self, node, text):
""" Returns True if the node's label can be set. """
return len(text.strip()) > 0
def set_text(self, node, text):
""" Sets the label text for a node. """
pass
def is_collapsible(self, node):
""" Returns True if the node is collapsible, otherwise False. """
return True
def is_draggable(self, node):
""" Returns True if the node is draggablee, otherwise False. """
return True
def can_rename(self, node):
""" Returns True if the node can be renamed, otherwise False. """
return False
def is_editable(self, node):
""" Returns True if the node is editable, otherwise False.
If the node is editable, its text can be set via the UI.
DEPRECATED: Use 'can_rename'.
"""
return self.can_rename(node)
def is_expandable(self, node):
""" Returns True if the node is expandanble, otherwise False. """
return True
def get_icon(self):
return ImageResource('parallel_coords')
def get_image_resource(name):
path = os.path.dirname(os.path.abspath(__file__))
return ImageResource(name=name, search_path=[path])
class MATSCalibDamageFn(MATSExplore):
'''
Fitting algorithm for the damage function of the
quasi-ductile anisotropic material model.
The algorithm uses the TLoop instance to proceed step
by step with the computation. The value of the damage function
for the time step t_n is identified iteratively by adjusting
the values and evaluating the corresponding equilibrated stresses.
The control parameters of the algorithm are:
@param step_size: time step for fitting the damage parameter.
@param tmax: end time for fitting, it might be also be set implicitly
for integrity = 1 - full damage of the material.
'''
# store the fitted 'PhiFn' in the data base, i.e. 'CCSUniteCell'
store_fitted_phi_fn = Bool(True)
# default settings are overloaded with settings specified in 'ec_config'
max_eps = Property(Float)
def _get_max_eps(self):
# return 0.007 # set explicit value when calibration is aborted (mean
# value of strain)
return self.mfn_line_array_target.xdata[-1]
n_steps = Int(1)
log = Bool(False)
# TLine parameter
#
KMAX = Int
tolerance = Float
RESETMAX = Float
step_size = Property(Float, depends_on='max_eps,n_steps')
@cached_property
def _get_step_size(self):
print('step_size = ', self.max_eps / self.n_steps)
return self.max_eps / self.n_steps
def run_through(self):
'''Run the computation without fitting from the start to the end
'''
self.tloop.tline.max = self.tmax
self.tloop.tline.step = self.step_size
self.tloop.eval()
print('ending time', self.tloop.t_n1)
# show the response
def run_step_by_step(self):
'''Run the computation step by step from the start to the end
'''
n_steps = int(self.tmax / self.step_size)
self.tloop.tline.step = self.step_size
current_time = 0.
tmax = 0.
for i in range(n_steps):
print('STEP', i)
self.run_one_step()
def run_trial_step(self):
'''Run the computation one step starting from the
current time t_n to iterate the value for phi_new
which gives a fit with macroscopic stress curve.
NOTE: The trial step does not update 'U_n' or 't_n'!
'''
if self.log:
print('--------- run trial step: --------- ')
if len(self.tloop.U_n) == 0:
current_U_n = self.tloop.tstepper.new_cntl_var()
print('U_n = None: tloop.tstepper.new_cntl_var()',
self.tloop.tstepper.new_cntl_var())
else:
current_U_n = self.tloop.U_n[:]
current_time = self.tloop.t_n
self.run_one_step()
# reset the current time back
self.tloop.t_n = current_time
self.tloop.U_n[:] = current_U_n[:]
if self.log:
print('--------- end of trial step --------- ')
self.tloop.tstepper.sctx.update_state_on = False
def run_one_step(self):
'''Run the computation one step starting from the
current time t_n with the iterated value for phi_new
in order to update TLoop and save the new phi value in
the array ydata of PhiFnGeneral
NOTE: The calculated step does update 'U_n' or 't_n'!
'''
self.tloop.tline.step = self.step_size
current_time = self.tloop.t_n
tmax = current_time + self.step_size
self.tloop.tline.max = tmax
self.tloop.eval()
self.update_e_max_value_new = True
#--------------------------------------------------
# Data source for calibration within simdb
#--------------------------------------------------
ex_run = Instance(ExRun)
composite_tensile_test = Property
def _get_composite_tensile_test(self):
return self.ex_run.ex_type
composite_cross_section = Property
def _get_composite_cross_section(self):
return self.composite_tensile_test.ccs
def get_target_data_exdb_tensile_test(self):
'''Use the data from the ExDB
'''
ctt = self.composite_tensile_test
# save 'sig_eps_arr' in directory "/simdb/simdata/mats_calib_damage_fn"
simdata_dir = os.path.join(simdb.simdata_dir, 'mats_calib_damage_fn')
if os.path.isdir(simdata_dir) == False:
os.makedirs(simdata_dir)
ctt_key = str(self.composite_tensile_test.key)
filename = os.path.join(simdata_dir, 'eps-sig-arr_' + ctt_key + '.csv')
xdata, ydata = ctt.eps_c_interpolated_smoothed[:, None], \
ctt.sig_c_interpolated_smoothed[:, None]
eps_sig_arr = np.hstack([xdata, ydata])
print('eps_sig_arr')
np.savetxt(filename, eps_sig_arr, delimiter=';')
print('eps-sig-data saved to file %s' % (filename))
# smoothed data without jumps with interpolated starting point in the
# origin
return ctt.eps_c_interpolated_smoothed, ctt.sig_c_interpolated_smoothed
# return ctt.eps_c_interpolated, ctt.sig_c_interpolated # original data without jumps with interpolated starting point in the origin
# return ctt.eps_ironed, ctt.sig_c_ironed # original data without smoothing (without jumps)
# return ctt.eps_smooth, ctt.sig_c_smooth #smoothed data
#--------------------------------------------------
# interpolation function for fitting data:
#--------------------------------------------------
mfn_line_array_target = Property(Instance(MFnLineArray),
depends_on='ex_run')
@cached_property
def _get_mfn_line_array_target(self):
xdata, ydata = self.get_target_data_exdb_tensile_test()
print('xdata[-1]', xdata[-1])
return MFnLineArray(xdata=xdata, ydata=ydata)
fitted_phi_fn = Instance(MFnLineArray)
#---------------------------------------------------------------
# PLOT OBJECT
#-------------------------------------------------------------------
figure = Instance(Figure)
def _figure_default(self):
figure = Figure(facecolor='white')
figure.add_axes([0.12, 0.13, 0.85, 0.74])
return figure
data_changed = Event
def init(self):
#--------------------------------------------------
# for fitting use 'General'-function for 'phi_fn':
#--------------------------------------------------
# The value pair for the piecewise linear definition
# of 'phi_fn' value consists of current strain and the
# iterated 'phi_value'. The microplanes with a lower
# microplane strain level use an interpolated value
# for 'phi'
self.fitted_phi_fn = self.dim.mats_eval.phi_fn.mfn
self.fitted_phi_fn.xdata = [0]
self.fitted_phi_fn.ydata = [1]
self.fitted_phi_fn.data_changed = True
# initialize TLoop parameters:
self.tloop.setup()
self.tloop.tstepper.sctx.mats_state_array[:] = 0.0
self.tloop.U_n[:] = 0.0
self.tloop.rtrace_mngr.clear()
self.tloop.verbose_iteration = False
self.tloop.verbose_load_step = False
self.tloop.verbose_time = False
# set TLine parameters
self.tloop.tline.KMAX = self.KMAX
self.tloop.tline.tolerance = self.tolerance
self.tloop.tline.RESETMAX = self.RESETMAX
# store trial step data in the lists if trial steps are to be stored
# for the plotting method 'plot_trail_steps'
#
rec_trial_steps = True
phi_trial_list_i = []
sig_trial_list_i = []
phi_trial_list_n = []
sig_trial_list_n = []
def get_lack_of_fit(self, phi_trial):
'''Return the difference between the macroscopic stress calculated
based on the value of phi_trial (damage at the next step) and the
macroscopic stress defined as target data (=fitting curve)
'''
if self.log:
print('\n')
print("#'get_lack_of_fit' for the trial value # START")
print(' phi_trial = ', phi_trial)
# value of the principle macroscopic strain corresponds to control
# variable
current_time = self.tloop.t_n
if self.log:
print(' current_time = ', current_time)
print(' step_size = ', self.step_size)
# ------------------------------------
# add new pair in fitted_phi_fn
# ------------------------------------
# consisting of 'e_max_value_new' and 'phi_trial'
x = np.hstack(
[self.fitted_phi_fn.xdata[:], current_time + self.step_size])
y = np.hstack([self.fitted_phi_fn.ydata[:], phi_trial])
self.fitted_phi_fn.set(xdata=x, ydata=y)
self.fitted_phi_fn.data_changed = True
# ------------------------------------
# get state array before trial:
# ------------------------------------
mats_state_array_old = copy(self.tloop.tstepper.sctx.mats_state_array)
# ------------------------------------
# run trial step:
# ------------------------------------
if self.log:
print(' reset current_U_n =', self.tloop.U_n)
print('CURRENT PHI', self.dim.mats_eval.phi_fn.mfn.ydata)
# try the next equilibrium
self.run_trial_step()
# ------------------------------------
# reset mats_state_array:
# ------------------------------------
# Note: the material state array (i.e. the maximum microstrains) are
# updated within the iterations of each trial step, therefore a reset
# is necessary in order to start each trial step with the same state
# variables
self.tloop.tstepper.sctx.mats_state_array[:] = mats_state_array_old[:]
if self.log:
print(' reset state array')
# ------------------------------------
# remove trial value in fitted_phi_fn
# ------------------------------------
x = self.fitted_phi_fn.xdata[:-1]
y = self.fitted_phi_fn.ydata[:-1]
self.fitted_phi_fn.set(xdata=x, ydata=y)
self.fitted_phi_fn.data_changed = True
# ------------------------------------
# get the lack of fit
# ------------------------------------
# get calculated value for 'sig_app' based on the current value of 'phi_trial':
# and evaluate the difference between the obtained stress and the
# measured response
self.tloop.rtrace_mngr.rtrace_bound_list[0].redraw()
sig_app_trial = self.tloop.rtrace_mngr.rtrace_bound_list[
0].trace.ydata[-1]
# get corresponding value from the target data:
sig_app_target = self.mfn_line_array_target.get_value(current_time +
self.step_size)
# absolut error:
lack_of_fit_absolut = sig_app_trial - sig_app_target
# relative error:
lack_of_fit_relative = lack_of_fit_absolut / sig_app_target
if self.log:
print(' sig_app_trial ', sig_app_trial)
print(' sig_app_target', sig_app_target)
print(' lack_of_fit_absolute ', lack_of_fit_absolut)
print(' lack_of_fit_relative ', lack_of_fit_relative)
print('# get_lack_of_fit # END ')
if self.rec_trial_steps:
# store all trial values of 'phi_trail' and 'sig_app_trail' within each iteration to a global list
#
self.phi_trial_list_i.append(phi_trial)
self.sig_trial_list_i.append(sig_app_trial)
return lack_of_fit_relative
param_key = Str('')
phi_max_factor = Float(1.0)
xtol = Float(1e-6, label='lack-of-fit tolerance')
def fit_response(self):
'''iterate phi_trial in each incremental step such that the
lack of fit between the calculated stress and the target
curve is smaller then xtol defined in function 'brentq'.
NOTE: the method 'get_lack_of_fit' returns the relative error.
'''
self.tloop.reset()
phi_old = 1.0
# map the array dimensions to the plot axes
#
figure = self.figure
axes = figure.axes[0]
print('n_steps', self.n_steps)
for n in range(self.n_steps):
axes.clear()
phi_new = phi_old
# use scipy-functionality to get the iterated value of phi_new
# If the trial value calculated with phi_trial = phi_old
# is smaller then target value get_lack_of_fit has no sign change
# for phi_trial = phi_old and phi_trial = 0. which is a requirement
# for the function call 'brentq'. In this case the old value
# for phi_trial is used and tloop moves on one step
try:
# The method brentq has optional arguments such as
# 'xtol' - absolut error (default value = 1.0e-12)
# 'rtol' - relative error (not supported at the time)
# 'maxiter' - maximum numbers of iterations used
#
# Here xtol is used to specify the allowed RELATIVE error!
# therefore the relative lack of fit is returned in
# method 'get_lack_of_fit'
_xtol = self.xtol
phi_max = min(1.0, phi_old * self.phi_max_factor)
phi_min = phi_old * 0.2 # 0.0 # phi_old * 0.3
phi_new = brentq(self.get_lack_of_fit,
phi_min,
phi_max,
xtol=_xtol)
# @todo: check if 'brenth' gives better fitting results; faster?
# phi_new = brenth( self.get_lack_of_fit, 0., phi_old )
print('(#) n = ', n, phi_new, phi_max, phi_old,
phi_old - phi_new)
except ValueError:
if self.log:
lof_0 = self.get_lack_of_fit(0.)
lof_phi_old = self.get_lack_of_fit(phi_old)
print('No sign change between get_lack_of_fit(phi_old) = ',
lof_phi_old, ' and ')
print('get_lack_of_fit(0.) = ', lof_0)
print('Use old value for phi_trial. phi_old = ', phi_old)
else:
print('(!) n = ', n, phi_new, phi_max, phi_old,
phi_old - phi_new)
phi_new = phi_old
# current time corresponds to the current strain applied
#
current_time = self.tloop.t_n
# replace old 'phi_value' with iterated value:
#
phi_old = phi_new
# get mats_state_array:
# mats_state_array = copy(self.tloop.tstepper.sctx.mats_state_array)
# update phi_data:
#
x = np.hstack(
[self.fitted_phi_fn.xdata[:], current_time + self.step_size])
y = np.hstack([self.fitted_phi_fn.ydata[:], phi_new])
axes.plot(x, y, color='blue', linewidth=2)
self.data_changed = True
self.fitted_phi_fn.set(xdata=x, ydata=y)
self.fitted_phi_fn.data_changed = True
# run one step with the iterated value for phi in order to
# update the state array and to move forward one step:
if self.log:
print('\n')
print('### run_one_step ###')
print('### step', n, '###')
print('### current time:', current_time)
if self.rec_trial_steps:
# add entries of the iterations ('i') in the current step ('n')
# (yields a list of lists)
#
self.phi_trial_list_n.append(self.phi_trial_list_i)
self.sig_trial_list_n.append(self.sig_trial_list_i)
# delete the entries of the iterations ('i') in the last step ('n')
# and fill it with the iterations of the next step ('n+1')
#
self.phi_trial_list_i = []
self.sig_trial_list_i = []
self.run_one_step()
# print '(g%)' %(n)
self.fitted_phi_fn.changed = True
def store(self):
mats_key = self.dim.mats_eval.__class__.__name__
ctt_key = str(self.composite_tensile_test.key)
if self.store_fitted_phi_fn:
print(
"stored 'fitted_phi_fn' in CCSUnitCell with material model %s and calibration test %s"
% (mats_key, ctt_key))
print('ctt_key + self.param_key', ctt_key + self.param_key)
self.composite_cross_section.set_param(
mats_key,
ctt_key + self.param_key,
# self.composite_cross_section.set_param(mats_key,
# ctt_key,
copy(self.fitted_phi_fn))
# save 'sig_eps_arr' in directory
# "/simdb/simdata/mats_calib_damage_fn"
simdata_dir = os.path.join(simdb.simdata_dir,
'mats_calib_damage_fn')
if os.path.isdir(simdata_dir) == False:
os.makedirs(simdata_dir)
ctt_key = str(self.composite_tensile_test.key)
filename = os.path.join(
simdata_dir,
'eps-phi-arr_' + ctt_key + self.param_key + '.csv')
xdata, ydata = self.fitted_phi_fn.xdata[:,
None], self.fitted_phi_fn.ydata[:,
None]
eps_phi_arr = np.hstack([xdata, ydata])
np.savetxt(filename, eps_phi_arr, delimiter=';')
print('eps-phi-data saved to file %s' % (filename))
format_ticks = Bool(False)
def plot_trial_steps(self):
'''Plot target (sig-eps-curve of the tensile test) and trial curves
and corresponding phi function together with trail steps from the iteration process.
NOTE: the global variable 'rec_trial_steps' must be set to 'True' in order to store the iteration values
within the global variables 'phi_trial_list_n' and 'sig_trial_list_n'
n - index of the time steps to be considered
i - index of the iteration steps performed in order to fit the target curve
'''
#-------------------------------------------------------------------
# configure the style of the font to be used for labels and ticks
#-------------------------------------------------------------------
#
from matplotlib.font_manager import FontProperties
font = FontProperties()
# font.serif : Times, Palatino, New Century Schoolbook, Bookman, Computer Modern Roman
# font.sans-serif : Helvetica, Avant Garde, Computer Modern Sans serif
# font.cursive : Zapf Chancery
# font.monospace : Courier, Computer Modern Typewriter
font.set_name('Script MT')
# name = ['Times New Roman', 'Helvetica', 'Script MT'] #?
font.set_family('serif')
# family = ['serif', 'sans-serif', 'cursive', 'fantasy', 'monospace']
font.set_style('normal')
# style = ['normal', 'italic', 'oblique']
font.set_size('small')
# size = ['xx-small', 'x-small', 'small', 'medium', 'large', 'x-large', 'xx-large', '11']
font.set_variant('normal')
# variant= ['normal', 'small-caps']
font.set_weight('medium')
# weight = ['light', 'normal', 'medium', 'semibold', 'bold', 'heavy', 'black']
#-------------------------------------------------------------------
p.figure(facecolor='white', dpi=600,
figsize=(8, 6)) # white background
# time list corresponding to the specified numbers of steps and step size
#
step_list = [n * self.step_size for n in range(self.n_steps + 1)]
# get list of lists containing the trial values of 'sig_app' and 'phi_trail'
# the lists are defined as global variables of 'MATSCalibDamageFn' and are filled
# within the iteration process when the method 'get_lack_of_fit" is called
#
phi_trial_list_n = [[1.]] + self.phi_trial_list_n
sig_trial_list_n = [[0.]] + self.sig_trial_list_n
xrange = 10. # plotting range for strain [mm/m]
yrange = 15. # plotting range for stress [MPa]
for n in range(self.n_steps):
for i in range(len(phi_trial_list_n[n + 1])):
x = np.array([step_list[n], step_list[n + 1]])
eps = 1000. * x # plot strains in permil on the x-axis
#--------------------------------------
# sig-eps trial
#--------------------------------------
# plot the numerically calculated sig-eps-curve (tensile test)
# (with trial steps)
#
sig_trail = np.array(
[sig_trial_list_n[n][-1], sig_trial_list_n[n + 1][i]])
p.subplot(222)
p.plot(eps, sig_trail, color='k', linewidth=1)
p.xlabel(r'strain $\varepsilon$ [1E-3]', fontproperties=font)
p.ylabel('stress $\sigma$ [MPa]', fontproperties=font)
if self.format_ticks:
# format ticks for plot
p.axis([0, xrange, 0., yrange], fontproperties=font)
locs, labels = p.xticks()
p.xticks(locs, ["%.0f" % x for x in locs],
fontproperties=font)
locs, labels = p.yticks()
p.yticks(locs, ["%.0f" % x for x in locs],
fontproperties=font)
#--------------------------------------
# phi_trail
#--------------------------------------
# plot the fitted phi-function
# (with trial steps)
#
p.subplot(224)
phi_trail = np.array(
[phi_trial_list_n[n][-1], phi_trial_list_n[n + 1][i]])
p.plot(eps, phi_trail, color='k', linewidth=1)
p.xlabel(r'strain $\varepsilon$ [1E-3]', fontproperties=font)
p.ylabel('integrity $\phi$ [-]', fontproperties=font)
if self.format_ticks:
# format ticks for plot
p.yticks([0, 0.2, 0.4, 0.6, 0.8, 1.0])
p.axis([0, xrange, 0., 1.])
locs, labels = p.xticks()
p.xticks(locs, ["%.0f" % x for x in locs],
fontproperties=font)
locs, labels = p.yticks()
p.yticks(locs, ["%.1f" % x for x in locs],
fontproperties=font)
#--------------------------------------
# sig-eps target
#--------------------------------------
# plot the sig-eps-target curve (tensile test)
#
p.subplot(221)
eps = 1000. * self.mfn_line_array_target.xdata[:-1]
sig_target = self.mfn_line_array_target.ydata[:-1]
p.plot(eps, sig_target, color='black', linewidth=1)
p.xlabel(r'strain $\varepsilon$ [1E-3]', fontproperties=font)
p.ylabel('stress $\sigma$ [MPa]', fontproperties=font)
if self.format_ticks:
# format ticks for plot
p.axis([0, xrange, 0., yrange])
locs, labels = p.xticks()
p.xticks(locs, ["%.0f" % x for x in locs], fontproperties=font)
locs, labels = p.yticks()
p.yticks(locs, ["%.0f" % x for x in locs], fontproperties=font)
#--------------------------------------
# phi_trail (final)
#--------------------------------------
# plot the corresponding fitted phi-function
# (without trial steps)
#
p.subplot(223)
eps = 1000. * self.fitted_phi_fn.xdata[:-1]
phi_fn = self.fitted_phi_fn.ydata[:-1]
p.plot(eps, phi_fn, color='black', linewidth=1)
p.xlabel(r'strain $\varepsilon$ [1E-3]', fontproperties=font)
p.ylabel('integrity $\phi$ [-]', fontproperties=font)
if self.format_ticks:
# format ticks for plot
p.yticks([0, 0.2, 0.4, 0.6, 0.8, 1.0])
p.axis([0, xrange, 0., 1.])
locs, labels = p.xticks()
p.xticks(locs, ["%.0f" % x for x in locs], fontproperties=font)
locs, labels = p.yticks()
p.yticks(locs, ["%.1f" % x for x in locs], fontproperties=font)
# save figure with calibration process in directory
# "/simdb/simdata/lcc_table/output_images/save_fig_to_file.png"
simdata_dir = os.path.join(simdb.simdata_dir, 'mats_calib_damage_fn')
if os.path.isdir(simdata_dir) == False:
os.makedirs(simdata_dir)
ctt_key = self.test_key
filename = os.path.join(simdata_dir, ctt_key + self.param_key + '.pdf')
p.savefig(filename)
print('plot_trail_steps.png saved to file %s' % (filename))
filename = os.path.join(simdata_dir, ctt_key + self.param_key + '.png')
p.savefig(filename, dpi=600)
print('plot_trail_steps.png saved to file %s' % (filename))
p.show()
test_key = Property
def _get_test_key(self):
return str(self.composite_tensile_test.key)
#-------------------------------------------------------------------------
# User interaction
#-------------------------------------------------------------------------
toolbar = ToolBar(Action(
name="Run Calibration",
tooltip='Run damage function calibration for the current parameters',
image=ImageResource('kt-start'),
action="run_calibration"),
image_size=(22, 22),
show_tool_names=False,
show_divider=True,
name='calibration_toolbar')
traits_view = View(
HSplit(
Item('ex_run@', show_label=False),
VSplit(
Item('dim@',
id='mats_calib_damage_fn.run.split',
dock='tab',
resizable=True,
label='experiment run',
show_label=False),
id='mats_calib_damage_fn.mode_plot_data.vsplit',
dock='tab',
),
VSplit(
Group(
Item('figure',
editor=MPLFigureEditor(),
resizable=True,
show_label=False),
id='mats_calib_damage_fn.plot_sheet',
label='fitted damage function',
dock='tab',
),
id='mats_calib_damage_fn.plot.vsplit',
dock='tab',
),
id='mats_calib_damage_fn.hsplit',
dock='tab',
),
# menubar = self.default_menubar(),
resizable=True,
toolbar=toolbar,
handler=MATSCalibDamageFnController(),
title='Simvisage: damage function calibration',
id='mats_calib_damage_fn',
dock='tab',
buttons=[OKButton, CancelButton],
height=0.8,
width=0.8)
def get_icon(self):
return ImageResource('gauss_2d')
def get_icon(self):
return ImageResource('bar_chart')
def get_icon(self):
return ImageResource('scatterplot')
def _menu_bar_default(self):
menu_bar = SMenuBar(
SMenu(SMenu(SGroup(
TaskAction(name='New Simulation',
method='new_simulation_from_datasource',
image=ImageResource('office-chart-pie')),
TaskAction(name='New Simulation from Experiment',
method='new_simulation_from_experiments',
image=ImageResource('kchart'),
accelerator='Ctrl+N'),
id='NewSimulationGroup',
name='NewSimulationGroup',
),
id='NewMenu',
name='&New Simulation'),
SGroup(TaskAction(name='Save Project',
accelerator='Ctrl+S',
method='save',
image=ImageResource('document-save')),
TaskAction(name='Save Project As...',
accelerator='Ctrl+Shift+S',
method='save_request',
image=ImageResource('document-save-as')),
id='SaveGroup',
name='SaveGroup'),
SGroup(
TaskAction(name='Save User Data',
method='save_user_ds',
image=ImageResource('drive-harddisk')),
TaskAction(name='Export User Data As...',
method='request_export_user_ds',
image=ImageResource('document-import')),
id='SaveUserDataGroup',
name='SaveUserDataGroup',
),
SGroup(
TaskWindowAction(
name='Close',
accelerator='Ctrl+W',
method='close',
),
id='CloseGroup',
name='CloseGroup',
),
id='File',
name='&File'), SMenu(id='Edit', name='&Edit'),
SMenu(DockPaneToggleGroup(), id='View', name='&View'),
SMenu(
SGroup(
TaskAction(name='Parameter Explorer',
accelerator='Ctrl+Shift+N',
method='new_simulation_grid',
enabled_name='simulations_exist'),
TaskAction(name='Parameter Optimizer',
accelerator='Ctrl+Shift+M',
method='new_optimizer',
enabled_name='experiments_and_sim_exist'),
id='ParamExplorationGroup',
name='ParamExplorationGroup',
),
SGroup(
TaskAction(name='Run Simulations',
method='run_simulations',
accelerator='Ctrl+R',
enabled_name='simulations_exist',
image=ImageResource('arrow-right')),
TaskAction(name='Run Simulation Group',
method='run_simulation_groups',
accelerator='Ctrl+Shift+R',
enabled_name='simulation_groups_exist',
image=ImageResource('arrow-right-double')),
id='RunSimulationGroup',
name='RunSimulationGroup',
),
SGroup(
TaskAction(name='Plot Chomatogram(s)',
method='new_model_calibration_plot',
accelerator='Ctrl+P',
image=ImageResource('office-chart-line')),
TaskAction(name='Particle data animation',
method='new_animation_plot'),
id='PlotsGroup',
name='PlotsGroup',
),
SGroup(
TaskAction(name=STRIP_TOOL_NAME,
method='open_strip_fraction_editor',
enabled_name='_strip_component_exist'),
id='ConfigurationGroup',
name='ConfigurationGroup',
),
SGroup(TaskAction(name='Custom Python script...',
accelerator='Ctrl+I',
method='request_run_python_script',
tooltip='Modify the current project with '
'custom script.',
image=ImageResource('text-x-python')),
TaskAction(name='Interactive Python console...',
accelerator='Ctrl+J',
tooltip="(Jupyter) Python console to "
"interactively explore Reveal's code "
"and develop new tools/scripts.",
method='request_launch_python_console',
image=ImageResource('ipython_icon')),
id='RunPythonGroup',
name='RunPythonGroup'),
id='Tools',
name='&Tools',
), SMenu(id='Help', name='&Help'))
return menu_bar
class MyDocumentedItem(DocumentedItem):
add = ToolbarButton('%s' % name, orientation='horizontal',
image=ImageResource('add.ico'))
class DiffusionPipeline(Pipeline):
now = datetime.datetime.now().strftime("%Y%m%d_%H%M")
pipeline_name = Str("diffusion_pipeline")
#input_folders = ['DSI','DTI','HARDI','T1','T2']
input_folders = ['anat', 'dwi']
process_type = Str
diffusion_imaging_model = Str
subject = Str
subject_directory = Directory
derivatives_directory = Directory
ordered_stage_list = [
'Preprocessing', 'Registration', 'Diffusion', 'Connectome'
] # ,'MRTrixConnectome']
parcellation_scheme = Str
atlas_info = Dict()
global_conf = Global_Configuration()
view_mode = Enum('config_view', ['config_view', 'inspect_outputs_view'])
preprocessing = Button('Preprocessing')
#preprocessing.setIcon(QIcon(QPixmap("preprocessing.png")))
diffusion = Button('Diffusion')
#diffusion.setIcon(QIcon(QPixmap("diffusion.png")))
registration = Button('Registration')
#registration.setIcon(QIcon(QPixmap("registration.png")))
connectome = Button('Connectome')
#connectome.setIcon(QIcon(QPixmap("connectome.png")))
config_file = Str
pipeline_group = VGroup(HGroup(spring,
UItem('preprocessing',
style='custom',
width=450,
height=130,
resizable=True,
editor_args={
'image':
ImageResource('preprocessing'),
'label':
""
}),
spring,
show_labels=False,
label=""),
HGroup(spring,
UItem('registration',
style='custom',
width=500,
height=110,
resizable=True,
editor_args={
'image':
ImageResource('registration'),
'label': ""
}),
spring,
show_labels=False,
label=""),
HGroup(spring,
UItem('diffusion',
style='custom',
width=450,
height=240,
resizable=True,
editor_args={
'image':
ImageResource('diffusion'),
'label': ""
}),
spring,
show_labels=False,
label=""),
HGroup(spring,
UItem('connectome',
style='custom',
width=450,
height=130,
resizable=True,
editor_args={
'image':
ImageResource('connectome'),
'label': ""
}),
spring,
show_labels=False,
label=""),
spring,
springy=True)
def __init__(self, project_info):
self.stages = {
'Preprocessing': PreprocessingStage(),
'Registration': RegistrationStage(pipeline_mode="Diffusion"),
'Diffusion': DiffusionStage(),
'Connectome': ConnectomeStage()
}
Pipeline.__init__(self, project_info)
self.diffusion_imaging_model = project_info.diffusion_imaging_model
self.subject = project_info.subject
self.global_conf.subjects = project_info.subjects
self.global_conf.subject = self.subject
if len(project_info.subject_sessions) > 0:
self.global_conf.subject_session = project_info.subject_session
self.subject_directory = os.path.join(self.base_directory,
self.subject,
project_info.subject_session)
else:
self.global_conf.subject_session = ''
self.subject_directory = os.path.join(self.base_directory,
self.subject)
self.derivatives_directory = os.path.join(self.base_directory,
'derivatives')
self.stages['Connectome'].config.subject = self.subject
self.stages['Connectome'].config.on_trait_change(
self.update_vizualization_layout, 'circular_layout')
self.stages['Connectome'].config.on_trait_change(
self.update_vizualization_logscale, 'log_visualization')
self.stages['Diffusion'].config.on_trait_change(
self.update_outputs_recon, 'recon_processing_tool')
self.stages['Diffusion'].config.on_trait_change(
self.update_outputs_tracking, 'tracking_processing_tool')
# self.anat_flow = anat_flow
def update_outputs_recon(self, new):
self.stages['Diffusion'].define_inspect_outputs()
def update_outputs_tracking(self, new):
self.stages['Diffusion'].define_inspect_outputs()
def update_vizualization_layout(self, new):
self.stages['Connectome'].define_inspect_outputs()
self.stages['Connectome'].config.subject = self.subject
def update_vizualization_logscale(self, new):
self.stages['Connectome'].define_inspect_outputs()
self.stages['Connectome'].config.subject = self.subject
def _subject_changed(self, new):
self.stages['Connectome'].config.subject = new
def _diffusion_imaging_model_changed(self, new):
print "diffusion model changed"
self.stages['Diffusion'].config.diffusion_imaging_model = new
def check_config(self):
if self.stages['Connectome'].config.output_types == []:
return (
'\n\tNo output type selected for the connectivity matrices.\t\n\tPlease select at least one output type in the connectome configuration window.\t\n'
)
return ''
def _preprocessing_fired(self, info):
self.stages['Preprocessing'].configure_traits(view=self.view_mode)
def _diffusion_fired(self, info):
self.stages['Diffusion'].configure_traits(view=self.view_mode)
def _registration_fired(self, info):
self.stages['Registration'].configure_traits(view=self.view_mode)
def _connectome_fired(self, info):
# self.stages['MRTrixConnectome'].configure_traits()
self.stages['Connectome'].configure_traits(view=self.view_mode)
def _atlas_info_changed(self, new):
print "Atlas info changed : "
print new
def check_input1(self, gui=True):
print '**** Check Inputs ****'
diffusion_available = False
bvecs_available = False
bvals_available = False
t1_available = False
t2_available = False
valid_inputs = False
dwi_file = os.path.join(self.subject_directory, 'dwi',
self.subject + '_dwi.nii.gz')
bval_file = os.path.join(self.subject_directory, 'dwi',
self.subject + '_dwi.bval')
bvec_file = os.path.join(self.subject_directory, 'dwi',
self.subject + '_dwi.bvec')
T1_file = os.path.join(self.subject_directory, 'anat',
self.subject + '_T1w.nii.gz')
T2_file = os.path.join(self.subject_directory, 'anat',
self.subject + '_T2w.nii.gz')
print "Looking for...."
print "dwi_file : %s" % dwi_file
print "bvecs_file : %s" % bvec_file
print "bvals_file : %s" % bval_file
print "T1_file : %s" % T1_file
print "T2_file : %s" % T2_file
try:
layout = BIDSLayout(self.base_directory)
print "Valid BIDS dataset with %s subjects" % len(
layout.get_subjects())
for subj in layout.get_subjects():
self.global_conf.subjects.append('sub-' + str(subj))
# self.global_conf.subjects = ['sub-'+str(subj) for subj in layout.get_subjects()]
self.global_conf.modalities = [
str(mod) for mod in layout.get_modalities()
]
# mods = layout.get_modalities()
types = layout.get_types()
# print "Available modalities :"
# for mod in mods:
# print "-%s" % mod
for typ in types:
if typ == 'dwi' and os.path.isfile(dwi_file):
print "%s available" % typ
diffusion_available = True
if typ == 'T1w' and os.path.isfile(T1_file):
print "%s available" % typ
t1_available = True
if typ == 'T2w' and os.path.isfile(T2_file):
print "%s available" % typ
t2_available = True
except:
error(
message=
"Invalid BIDS dataset. Please see documentation for more details.",
title="Error",
buttons=['OK', 'Cancel'],
parent=None)
return
if os.path.isfile(bval_file): bvals_available = True
if os.path.isfile(bvec_file): bvecs_available = True
mem = Memory(base_dir=os.path.join(self.derivatives_directory, 'cmp',
self.subject, 'tmp', 'nipype'))
swap_and_reorient = mem.cache(SwapAndReorient)
if diffusion_available:
if bvals_available and bvecs_available:
self.stages[
'Diffusion'].config.diffusion_imaging_model_choices = self.diffusion_imaging_model
#Copy diffusion data to derivatives / cmp / subject / dwi
out_dwi_file = os.path.join(self.derivatives_directory, 'cmp',
self.subject, 'dwi',
self.subject + '_dwi.nii.gz')
out_bval_file = os.path.join(self.derivatives_directory, 'cmp',
self.subject, 'dwi',
self.subject + '_dwi.bval')
out_bvec_file = os.path.join(self.derivatives_directory, 'cmp',
self.subject, 'dwi',
self.subject + '_dwi.bvec')
shutil.copy(src=dwi_file, dst=out_dwi_file)
shutil.copy(src=bvec_file, dst=out_bvec_file)
shutil.copy(src=bval_file, dst=out_bval_file)
if t2_available:
print "Swap and reorient T2"
swap_and_reorient(
src_file=os.path.join(self.subject_directory, 'anat',
self.subject + '_T2w.nii.gz'),
ref_file=os.path.join(self.subject_directory, 'dwi',
self.subject + '_dwi.nii.gz'),
out_file=os.path.join(self.derivatives_directory,
'cmp', self.subject, 'anat',
self.subject + '_T2w.nii.gz'))
if t1_available:
swap_and_reorient(
src_file=os.path.join(self.subject_directory, 'anat',
self.subject + '_T1w.nii.gz'),
ref_file=os.path.join(self.subject_directory, 'dwi',
self.subject + '_dwi.nii.gz'),
out_file=os.path.join(self.derivatives_directory,
'cmp', self.subject, 'anat',
self.subject + '_T1w.nii.gz'))
valid_inputs = True
input_message = 'Inputs check finished successfully.\nDiffusion and morphological data available.'
else:
input_message = 'Error during inputs check.\nMorphological data (T1) not available.'
else:
input_message = 'Error during inputs check.\nDiffusion bvec or bval files not available.'
elif t1_available:
input_message = 'Error during inputs check. \nDiffusion data not available (DSI/DTI/HARDI).'
else:
input_message = 'Error during inputs check. No diffusion or morphological data available in folder ' + os.path.join(
self.base_directory, 'RAWDATA') + '!'
#diffusion_imaging_model = diffusion_imaging_model[0]
if gui:
#input_notification = Check_Input_Notification(message=input_message, diffusion_imaging_model_options=diffusion_imaging_model,diffusion_imaging_model=diffusion_imaging_model)
#input_notification.configure_traits()
print input_message
self.global_conf.diffusion_imaging_model = self.diffusion_imaging_model
# diffusion_file = os.path.join(self.subject_directory,'dwi',self.subject+'_dwi.nii.gz')
# n_vol = nib.load(diffusion_file).shape[3]
# if self.stages['Preprocessing'].config.end_vol == 0 or self.stages['Preprocessing'].config.end_vol == self.stages['Preprocessing'].config.max_vol or self.stages['Preprocessing'].config.end_vol >= n_vol-1:
# self.stages['Preprocessing'].config.end_vol = n_vol-1
# self.stages['Preprocessing'].config.max_vol = n_vol-1
self.stages[
'Registration'].config.diffusion_imaging_model = self.diffusion_imaging_model
self.stages[
'Diffusion'].config.diffusion_imaging_model = self.diffusion_imaging_model
else:
print input_message
self.global_conf.diffusion_imaging_model = self.diffusion_imaging_model
# diffusion_file = os.path.join(self.subject_directory,'dwi',self.subject+'_dwi.nii.gz')
# n_vol = nib.load(diffusion_file).shape[3]
# if self.stages['Preprocessing'].config.end_vol == 0 or self.stages['Preprocessing'].config.end_vol == self.stages['Preprocessing'].config.max_vol or self.stages['Preprocessing'].config.end_vol >= n_vol-1:
# self.stages['Preprocessing'].config.end_vol = n_vol-1
# self.stages['Preprocessing'].config.max_vol = n_vol-1
self.stages[
'Registration'].config.diffusion_imaging_model = self.diffusion_imaging_model
self.stages[
'Diffusion'].config.diffusion_imaging_model = self.diffusion_imaging_model
if t2_available:
self.stages['Registration'].config.registration_mode_trait = [
'Linear + Non-linear (FSL)'
] #,'BBregister (FS)','Nonlinear (FSL)']
if (t1_available and diffusion_available):
valid_inputs = True
else:
print "Missing required inputs."
error(
message=
"Missing required inputs. Please see documentation for more details.",
title="Error",
buttons=['OK', 'Cancel'],
parent=None)
for stage in self.stages.values():
if stage.enabled:
print stage.name
print stage.stage_dir
self.fill_stages_outputs()
return valid_inputs
def check_input(self, layout, gui=True):
print '**** Check Inputs ****'
diffusion_available = False
bvecs_available = False
bvals_available = False
valid_inputs = False
if self.global_conf.subject_session == '':
subject = self.subject
else:
subject = "_".join(
(self.subject, self.global_conf.subject_session))
dwi_file = os.path.join(self.subject_directory, 'dwi',
subject + '_dwi.nii.gz')
bval_file = os.path.join(self.subject_directory, 'dwi',
subject + '_dwi.bval')
bvec_file = os.path.join(self.subject_directory, 'dwi',
subject + '_dwi.bvec')
subjid = self.subject.split("-")[1]
try:
layout = BIDSLayout(self.base_directory)
print "Valid BIDS dataset with %s subjects" % len(
layout.get_subjects())
for subj in layout.get_subjects():
self.global_conf.subjects.append('sub-' + str(subj))
# self.global_conf.subjects = ['sub-'+str(subj) for subj in layout.get_subjects()]
self.global_conf.modalities = [
str(mod) for mod in layout.get_modalities()
]
# mods = layout.get_modalities()
types = layout.get_types()
# print "Available modalities :"
# for mod in mods:
# print "-%s" % mod
if self.global_conf.subject_session == '':
files = layout.get(subject=subjid,
type='dwi',
extensions='.nii.gz')
if len(files) > 0:
dwi_file = files[0].filename
print dwi_file
else:
error(message="Diffusion image not found for subject %s." %
(subjid),
title="Error",
buttons=['OK', 'Cancel'],
parent=None)
return
files = layout.get(subject=subjid,
type='dwi',
extensions='.bval')
if len(files) > 0:
bval_file = files[0].filename
print bval_file
else:
error(
message="Diffusion bval image not found for subject %s."
% (subjid),
title="Error",
buttons=['OK', 'Cancel'],
parent=None)
return
files = layout.get(subject=subjid,
type='dwi',
extensions='.bvec')
if len(files) > 0:
bvec_file = files[0].filename
print bvec_file
else:
error(
message="Diffusion bvec image not found for subject %s."
% (subjid),
title="Error",
buttons=['OK', 'Cancel'],
parent=None)
return
else:
sessid = self.global_conf.subject_session.split("-")[1]
files = layout.get(subject=subjid,
type='dwi',
extensions='.nii.gz',
session=sessid)
if len(files) > 0:
dwi_file = files[0].filename
print dwi_file
else:
error(
message=
"Diffusion image not found for subject %s, session %s."
% (subjid, self.global_conf.subject_session),
title="Error",
buttons=['OK', 'Cancel'],
parent=None)
return
files = layout.get(subject=subjid,
type='dwi',
extensions='.bval',
session=sessid)
if len(files) > 0:
bval_file = files[0].filename
print bval_file
else:
error(
message=
"Diffusion bval image not found for subject %s, session %s."
% (subjid, self.global_conf.subject_session),
title="Error",
buttons=['OK', 'Cancel'],
parent=None)
return
files = layout.get(subject=subjid,
type='dwi',
extensions='.bvec',
session=sessid)
if len(files) > 0:
bvec_file = files[0].filename
print bvec_file
else:
error(
message=
"Diffusion bvec image not found for subject %s, session %s."
% (subjid, self.global_conf.subject_session),
title="Error",
buttons=['OK', 'Cancel'],
parent=None)
return
print "Looking for...."
print "dwi_file : %s" % dwi_file
print "bvecs_file : %s" % bvec_file
print "bvals_file : %s" % bval_file
for typ in types:
if typ == 'dwi' and os.path.isfile(dwi_file):
print "%s available" % typ
diffusion_available = True
except:
error(
message=
"Invalid BIDS dataset. Please see documentation for more details.",
title="Error",
buttons=['OK', 'Cancel'],
parent=None)
return
if os.path.isfile(bval_file): bvals_available = True
if os.path.isfile(bvec_file): bvecs_available = True
if diffusion_available:
if bvals_available and bvecs_available:
self.stages[
'Diffusion'].config.diffusion_imaging_model_choices = self.diffusion_imaging_model
#Copy diffusion data to derivatives / cmp / subject / dwi
if self.global_conf.subject_session == '':
out_dwi_file = os.path.join(self.derivatives_directory,
'cmp', self.subject, 'dwi',
subject + '_dwi.nii.gz')
out_bval_file = os.path.join(self.derivatives_directory,
'cmp', self.subject, 'dwi',
subject + '_dwi.bval')
out_bvec_file = os.path.join(self.derivatives_directory,
'cmp', self.subject, 'dwi',
subject + '_dwi.bvec')
else:
out_dwi_file = os.path.join(
self.derivatives_directory, 'cmp', self.subject,
self.global_conf.subject_session, 'dwi',
subject + '_dwi.nii.gz')
out_bval_file = os.path.join(
self.derivatives_directory, 'cmp', self.subject,
self.global_conf.subject_session, 'dwi',
subject + '_dwi.bval')
out_bvec_file = os.path.join(
self.derivatives_directory, 'cmp', self.subject,
self.global_conf.subject_session, 'dwi',
subject + '_dwi.bvec')
if not os.path.isfile(out_dwi_file):
shutil.copy(src=dwi_file, dst=out_dwi_file)
if not os.path.isfile(out_bvec_file):
shutil.copy(src=bvec_file, dst=out_bvec_file)
if not os.path.isfile(out_bval_file):
shutil.copy(src=bval_file, dst=out_bval_file)
valid_inputs = True
input_message = 'Inputs check finished successfully.\nDiffusion and morphological data available.'
else:
input_message = 'Error during inputs check.\nDiffusion bvec or bval files not available.'
else:
if self.global_conf.subject_session == '':
input_message = 'Error during inputs check. No diffusion data available in folder ' + os.path.join(
self.base_directory, self.subject, 'dwi') + '!'
else:
input_message = 'Error during inputs check. No diffusion data available in folder ' + os.path.join(
self.base_directory, self.subject,
self.global_conf.subject_session, 'dwi') + '!'
#diffusion_imaging_model = diffusion_imaging_model[0]
if gui:
#input_notification = Check_Input_Notification(message=input_message, diffusion_imaging_model_options=diffusion_imaging_model,diffusion_imaging_model=diffusion_imaging_model)
#input_notification.configure_traits()
print input_message
self.global_conf.diffusion_imaging_model = self.diffusion_imaging_model
# if diffusion_available:
# n_vol = nib.load(dwi_file).shape[3]
# if self.stages['Preprocessing'].config.end_vol == 0 or self.stages['Preprocessing'].config.end_vol == self.stages['Preprocessing'].config.max_vol or self.stages['Preprocessing'].config.end_vol >= n_vol-1:
# self.stages['Preprocessing'].config.end_vol = n_vol-1
# self.stages['Preprocessing'].config.max_vol = n_vol-1
self.stages[
'Registration'].config.diffusion_imaging_model = self.diffusion_imaging_model
self.stages[
'Diffusion'].config.diffusion_imaging_model = self.diffusion_imaging_model
else:
print input_message
self.global_conf.diffusion_imaging_model = self.diffusion_imaging_model
# if diffusion_available:
# n_vol = nib.load(dwi_file).shape[3]
# if self.stages['Preprocessing'].config.end_vol == 0 or self.stages['Preprocessing'].config.end_vol == self.stages['Preprocessing'].config.max_vol or self.stages['Preprocessing'].config.end_vol >= n_vol-1:
# self.stages['Preprocessing'].config.end_vol = n_vol-1
# self.stages['Preprocessing'].config.max_vol = n_vol-1
self.stages[
'Registration'].config.diffusion_imaging_model = self.diffusion_imaging_model
self.stages[
'Diffusion'].config.diffusion_imaging_model = self.diffusion_imaging_model
if (diffusion_available):
valid_inputs = True
else:
print "Missing required inputs."
error(
message=
"Missing diffusion inputs. Please see documentation for more details.",
title="Error",
buttons=['OK', 'Cancel'],
parent=None)
for stage in self.stages.values():
if stage.enabled:
print stage.name
print stage.stage_dir
self.fill_stages_outputs()
return valid_inputs
def get_icon(self):
return ImageResource('range')
def _about_dialog_default(self):
""" Trait initializer. """
return AboutDialog(image=ImageResource("about"))
class FlowTask(Task):
"""
classdocs
"""
id = "edu.mit.synbio.cytoflowgui.flow_task"
name = "Cytometry analysis"
# the main workflow instance.
model = Instance(Workflow)
# the center pane
workflow_pane = Instance(WorkflowDockPane)
view_pane = Instance(ViewDockPane)
help_pane = Instance(HelpDockPane)
plot_params_pane = Instance(PlotParamsPane)
# plugin lists, to setup the interface
op_plugins = List(IOperationPlugin)
view_plugins = List(IViewPlugin)
menu_bar = SMenuBar(SMenu(TaskAction(name='Open...',
method='on_open',
accelerator='Ctrl+O'),
TaskAction(name='Save',
#image='save',
method='on_save',
accelerator='Ctrl+S'),
TaskAction(name='Save As...',
method='on_save_as',
accelerator='Ctrl+e'),
TaskAction(name='Save Plot...',
method='on_export',
accelerator='Ctrl+x'),
TaskAction(name='Export Jupyter notebook...',
method='on_notebook',
accelerator='Ctrl+I'),
# TaskAction(name='Preferences...',
# method='on_prefs',
# accelerator='Ctrl+P'),
id='File', name='&File'),
SMenu(TaskToggleGroup(),
id = 'View', name = '&View'),
SMenu(TaskAction(name = 'Online documentation...',
method = 'on_docs'),
TaskAction(name = 'Report a problem....',
method = 'on_problem'),
TaskAction(name='About...',
method='on_about'),
id="Help", name ="&Help"))
tool_bars = [ SToolBar(TaskAction(method='on_new',
name = "New",
tooltip='New workflow',
image=ImageResource('new')),
TaskAction(method='on_open',
name = "Open",
tooltip='Open a file',
image=ImageResource('open')),
TaskAction(method='on_save',
name = "Save",
tooltip='Save the current file',
image=ImageResource('save')),
TaskAction(method='on_export',
name = "Save Plot",
tooltip='Save the current plot',
image=ImageResource('export')),
TaskAction(method='on_notebook',
name='Notebook',
tooltip="Export to an Jupyter notebook...",
image=ImageResource('jupyter')),
TaskAction(method = "on_calibrate",
name = "Calibrate FCS...",
tooltip = "Calibrate FCS files",
image = ImageResource('tasbe')),
TaskAction(method = 'on_problem',
name = "Report a bug...",
tooltib = "Report a bug",
image = ImageResource('bug')))]
# TaskAction(method='on_prefs',
# name = "Prefs",
# tooltip='Preferences',
# image=ImageResource('prefs')),
# the file to save to if the user clicks "save" and has already clicked
# "open" or "save as".
filename = Str
def initialized(self):
if self.filename:
self.open_file(self.filename)
def activated(self):
# if we're coming back from the TASBE task, re-load the saved
# workflow
if self.model.backup_workflow:
self.model.workflow = self.model.backup_workflow
self.model.backup_workflow = []
return
# else, set up a new workflow
# add the import op
if not self.model.workflow:
self.add_operation(ImportPlugin().id)
self.model.selected = self.model.workflow[0]
self.model.modified = False
def _default_layout_default(self):
return TaskLayout(left = VSplitter(PaneItem("edu.mit.synbio.cytoflowgui.workflow_pane", width = 350),
PaneItem("edu.mit.synbio.cytoflowgui.help_pane", width = 350, height = 350)),
right = VSplitter(PaneItem("edu.mit.synbio.cytoflowgui.view_traits_pane", width = 350),
PaneItem("edu.mit.synbio.cytoflowgui.params_pane", width = 350, height = 350)),
top_left_corner = 'left',
bottom_left_corner = 'left',
top_right_corner = 'right',
bottom_right_corner = 'right')
def create_central_pane(self):
# set the toolbar image size
# this isn't really the right place for this, but it's the only
# place control passes back to user code before the toolbar
# is created.
dpi = self.window.control.physicalDpiX()
self.tool_bars[0].image_size = (int(0.4 * dpi), int(0.4 * dpi))
return self.application.plot_pane
def create_dock_panes(self):
self.workflow_pane = WorkflowDockPane(model = self.model,
plugins = self.op_plugins,
task = self)
self.view_pane = ViewDockPane(model = self.model,
plugins = self.view_plugins,
task = self)
self.help_pane = HelpDockPane(view_plugins = self.view_plugins,
op_plugins = self.op_plugins,
task = self)
self.plot_params_pane = PlotParamsPane(model = self.model,
task = self)
return [self.workflow_pane, self.view_pane, self.help_pane, self.plot_params_pane]
def on_new(self):
if self.model.modified:
ret = confirm(parent = None,
message = "Are you sure you want to discard the current workflow?",
title = "Clear workflow?")
if ret != YES:
return
self.filename = ""
self.window.title = "Cytoflow"
# clear the workflow
self.model.workflow = []
# add the import op
self.add_operation(ImportPlugin().id)
# and select the operation
self.model.selected = self.model.workflow[0]
self.model.modified = False
def on_open(self):
"""
Shows a dialog to open a file.
"""
if self.model.modified:
ret = confirm(parent = None,
message = "Are you sure you want to discard the current workflow?",
title = "Clear workflow?")
if ret != YES:
return
dialog = FileDialog(parent = self.window.control,
action = 'open',
wildcard = (FileDialog.create_wildcard("Cytoflow workflow", "*.flow") + ';' + #@UndefinedVariable
FileDialog.create_wildcard("All files", "*"))) #@UndefinedVariable
if dialog.open() == OK:
self.open_file(dialog.path)
self.filename = dialog.path
self.window.title = "Cytoflow - " + self.filename
def open_file(self, path):
try:
new_workflow = load_yaml(path)
# a few things to take care of when reloading.
# we do this in the try block to catch people who
# load valid YAML files that aren't from cytoflow.
for wi_idx, wi in enumerate(new_workflow):
# get wi lock
wi.lock.acquire()
# clear the wi status
wi.status = "loading"
# re-link the linked list.
if wi_idx > 0:
wi.previous_wi = new_workflow[wi_idx - 1]
if wi_idx < len(new_workflow) - 1:
wi.next_wi = new_workflow[wi_idx + 1]
except yaml.parser.ParserError as e:
error(None,
"Parser error loading {} -- is it a Cytoflow file?\n\n{}"
.format(path, str(e)))
return
except Exception as e:
error(None,
"{} loading {} -- is it a Cytoflow file?\n\n{}"
.format(e.__class__.__name__, path, str(e)))
return
# are we just running a smoke test?
if 'startup_test' in new_workflow[0].metadata:
def quit_app(app):
app.exit(force = True)
from pyface.timer.api import do_after
do_after(5*1000, quit_app, self.application)
return
# check that the FCS files are all there
wi = new_workflow[0]
assert(wi.operation.id == "edu.mit.synbio.cytoflow.operations.import")
missing_tubes = 0
for tube in wi.operation.tubes:
file = pathlib.Path(tube.file)
if not file.exists():
missing_tubes += 1
if missing_tubes == len(wi.operation.tubes):
warning(self.window.control,
"Cytoflow couldn't find any of the FCS files from that "
"workflow. If they've been moved, please open one FCS "
"file to show Cytoflow where they've been moved to.")
dialog = FileDialog(parent = self.window.control,
action = 'open',
wildcard = (FileDialog.create_wildcard("FCS files", "*.fcs *.lmd"))) # @UndefinedVariable
if dialog.open() == OK:
# find the "best" file match -- ie, the one with the longest
# tail match
fcs_path = pathlib.Path(dialog.path).parts
best_path_len = -1
for tube in wi.operation.tubes:
tube_path = pathlib.Path(tube.file).parts
for i in range(len(fcs_path)):
if list(reversed(fcs_path))[:i] == list(reversed(tube_path))[:i] and i > best_path_len:
best_path_len = i
if best_path_len >= 0:
for tube in wi.operation.tubes:
tube_path = pathlib.Path(tube.file).parts
new_path = fcs_path[:-1 * best_path_len] + tube_path[-1 * best_path_len :]
tube.file = str(pathlib.Path(*new_path))
elif missing_tubes > 0:
warning(self.window.control,
"Cytoflow couldn't find some of the FCS files from that "
"workflow. You'll need to re-load them from the Import "
"operation.")
# replace the current workflow with the one we just loaded
if False: # for debugging the loading of things
from .event_tracer import record_events
with record_events() as container:
self.model.workflow = new_workflow
container.save_to_directory(os.getcwd())
else:
self.model.workflow = new_workflow
self.model.modified = False
for wi in self.model.workflow:
wi.lock.release()
if self.model.debug:
self.model.run_all()
else:
ret = confirm(parent = None,
message = "Do you want to execute the workflow now?",
title = "Run workflow?")
if ret == YES:
self.model.run_all()
def on_save(self):
""" Save the file to the previous filename """
if self.filename:
save_yaml(self.model.workflow, self.filename)
self.model.modified = False
else:
self.on_save_as()
def on_save_as(self):
dialog = DefaultFileDialog(parent = self.window.control,
action = 'save as',
default_suffix = "flow",
wildcard = (FileDialog.create_wildcard("Cytoflow workflow", "*.flow") + ';' + #@UndefinedVariable
FileDialog.create_wildcard("All files", "*"))) #@UndefinedVariable
if dialog.open() == OK:
save_yaml(self.model.workflow, dialog.path)
self.filename = dialog.path
self.model.modified = False
self.window.title = "Cytoflow - " + self.filename
@on_trait_change('model.modified', post_init = True)
def _on_model_modified(self, val):
if val:
if not self.window.title.endswith("*"):
self.window.title += "*"
else:
if self.window.title.endswith("*"):
self.window.title = self.window.title[:-1]
def on_export(self):
task = next(x for x in self.window.tasks if x.id == 'edu.mit.synbio.cytoflowgui.export_task')
self.window.activate_task(task)
def on_calibrate(self):
task = next(x for x in self.window.tasks if x.id == 'edu.mit.synbio.cytoflowgui.tasbe_task')
self.window.activate_task(task)
def on_notebook(self):
"""
Shows a dialog to export the workflow to an Jupyter notebook
"""
dialog = DefaultFileDialog(parent = self.window.control,
action = 'save as',
default_suffix = "ipynb",
wildcard = (FileDialog.create_wildcard("Jupyter notebook", "*.ipynb") + ';' + #@UndefinedVariable
FileDialog.create_wildcard("All files", "*"))) # @UndefinedVariable
if dialog.open() == OK:
save_notebook(self.model.workflow, dialog.path)
def on_prefs(self):
pass
def on_docs(self):
webbrowser.open_new_tab("https://cytoflow.readthedocs.io/en/stable/manual.html")
def on_problem(self):
log = str(self._get_package_versions()) + "\n" + self.application.application_log.getvalue()
msg = "The best way to report a problem is send an application log to " \
"the developers. If you click 'Yes' below, you will be given then " \
"opportunity to save the log to a file and then file a " \
"new issue on GitHub at " \
"https://github.com/bpteague/cytoflow/issues/new"
dialog = ConfirmationDialog(message = msg,
informative = "Would you like to report an issue to the developers?")
if dialog.open() == YES:
dialog = DefaultFileDialog(parent = self.window.control,
action = 'save as',
default_suffix = "log",
wildcard = (FileDialog.create_wildcard("Log files", "*.log") + ';' + #@UndefinedVariable
FileDialog.create_wildcard("All files", "*"))) #@UndefinedVariable
if dialog.open() == OK:
with open(dialog.path, 'w') as f:
f.write(log)
webbrowser.open_new_tab("https://github.com/bpteague/cytoflow/issues/new")
return
def _get_package_versions(self):
from cytoflow import __version__ as cf_version
from fcsparser import __version__ as fcs_version
from pandas import __version__ as pd_version
from numpy import __version__ as np_version
from numexpr import __version__ as nxp_version
from bottleneck import __version__ as btl_version
from seaborn import __version__ as sns_version
from matplotlib import __version__ as mpl_version
from scipy import __version__ as scipy_version
from sklearn import __version__ as skl_version
from statsmodels import __version__ as stats_version
from pyface import __version__ as pyf_version
from envisage import __version__ as env_version
from traits import __version__ as trt_version
from traitsui import __version__ as trt_ui_version
from yapf import __version__ as yapf_version
from nbformat import __version__ as nb_version
from yaml import __version__ as yaml_version
return {"python" : sys.version,
"cytoflow" : cf_version,
"fcsparser" : fcs_version,
"pandas" : pd_version,
"numpy" : np_version,
"numexpr" : nxp_version,
"bottleneck" : btl_version,
"seaborn" : sns_version,
"matplotlib" : mpl_version,
"scipy" : scipy_version,
"scikit-learn" : skl_version,
"statsmodels" : stats_version,
"pyface" : pyf_version,
"envisage" : env_version,
"traits" : trt_version,
"traitsui" : trt_ui_version,
"nbformat" : nb_version,
"yapf" : yapf_version,
"yaml" : yaml_version}
def on_about(self):
versions = self._get_package_versions()
text = ["<b>Cytoflow {0}</b>".format(versions['cytoflow']),
"<p>"]
ver_text = ["{0} {1}".format(key, value) for key, value in versions.items()]
text.extend(ver_text)
text.extend(["Icons from the <a href=http://tango.freedesktop.org>Tango Desktop Project</a>",
"<a href=https://thenounproject.com/search/?q=setup&i=14287>Settings icon</a> by Paulo Sa Ferreira from <a href=https://thenounproject.com>The Noun Project</a>",
"<a href=https://thenounproject.com/search/?q=processing&i=849831>Processing icon</a> by Gregor Cresnar from <a href=https://thenounproject.com>The Noun Project</a>",
"<a href=http://www.freepik.com/free-photos-vectors/background>App icon from Starline - Freepik.com</a>",
"Cuvette image from Wikimedia Commons user <a href=http://commons.wikimedia.org/wiki/File:Hellma_Large_cone_cytometry_cell.JPG>HellmaUSA</a>"])
dialog = AboutDialog(text = text,
parent = self.window.control,
title = "About",
image = ImageResource('cuvette'),
additions = text)
dialog.open()
@on_trait_change('model.selected', post_init = True)
def _on_select_op(self, selected):
if selected:
self.view_pane.enabled = (selected is not None)
self.view_pane.default_view = selected.default_view.id if selected.default_view else ""
self.view_pane.selected_view = selected.current_view.id if selected.current_view else ""
self.help_pane.help_id = selected.operation.id
else:
self.view_pane.enabled = False
@on_trait_change('view_pane.selected_view', post_init = True)
def _on_select_view(self, view_id):
if not view_id:
return
# if we already have an instantiated view object, find it
try:
self.model.selected.current_view = next((x for x in self.model.selected.views if x.id == view_id))
except StopIteration:
# else make the new view
plugin = next((x for x in self.view_plugins if x.view_id == view_id))
view = plugin.get_view()
self.model.selected.views.append(view)
self.model.selected.current_view = view
self.help_pane.help_id = view_id
def add_operation(self, op_id):
# first, find the matching plugin
plugin = next((x for x in self.op_plugins if x.id == op_id))
# next, get an operation
op = plugin.get_operation()
# make a new workflow item
wi = WorkflowItem(operation = op,
deletable = (op_id != 'edu.mit.synbio.cytoflowgui.op_plugins.import'))
# if the op has a default view, add it to the wi
try:
wi.default_view = op.default_view()
wi.views.append(wi.default_view)
wi.current_view = wi.default_view
except AttributeError:
pass
# figure out where to add it
if self.model.selected:
idx = self.model.workflow.index(self.model.selected) + 1
else:
idx = len(self.model.workflow)
# the add_remove_items handler takes care of updating the linked list
self.model.workflow.insert(idx, wi)
# and make sure to actually select the new wi
self.model.selected = wi
class WorkbenchApplication(Application):
""" The entry point for an Envisage Workbench application.
i.e. a GUI application whose user interface is provided by the workbench
plugin.
This class handles the common case for Workbench applications, and it is
intended to be subclassed to change start/stop behaviour etc. In fact, I
generally create a subclass for every Workbench application I write since
it is a good place to put branding information etc.
"""
#### 'WorkbenchApplication' interface #####################################
# The Pyface GUI for the application (this is here to make it easy for
# parts of the application to get a reference to the GUI so they can get
# system metrics, etc.
gui = Instance(GUI)
# The workbench.
workbench = Instance(IWorkbench)
# The factory for creating the workbench (used *instead* of providing a
# workbench explicitly).
workbench_factory = Callable(Workbench)
# Branding information.
#
# The 'About' dialog.
about_dialog = Instance(Dialog)
# The icon used on window title bars etc.
icon = Instance(ImageResource, ImageResource("application.ico"))
# The name of the application (also used on window title bars etc).
name = Str("Workbench")
# The splash screen (None, the default, if no splash screen is required).
splash_screen = Instance(SplashScreen)
# The default position of the main window.
window_position = Tuple((200, 200))
# The default size of the main window.
window_size = Tuple((800, 600))
###########################################################################
# 'IApplication' interface.
###########################################################################
def run(self):
""" Run the application.
This does the following (so you don't have to ;^):-
1) Starts the application
2) Creates and opens a workbench window
3) Starts the GUI event loop
4) When the event loop terminates, stops the application
"""
logger.debug("---------- workbench application ----------")
# Make sure the GUI has been created (so that, if required, the splash
# screen is shown).
gui = self.gui
# Start the application.
if self.start():
# Create and open the first workbench window.
window = self.workbench.create_window(
position=self.window_position, size=self.window_size
)
window.open()
# We stop the application when the workbench has exited.
self.workbench.on_trait_change(self._on_workbench_exited, "exited")
# Start the GUI event loop.
#
# THIS CALL DOES NOT RETURN UNTIL THE GUI IS CLOSED.
gui.start_event_loop()
###########################################################################
# 'WorkbenchApplication' interface.
###########################################################################
#### Initializers #########################################################
def _about_dialog_default(self):
""" Trait initializer. """
return AboutDialog(image=ImageResource("about"))
def _gui_default(self):
""" Trait initializer. """
return GUI(splash_screen=self.splash_screen)
def _workbench_default(self):
""" Trait initializer. """
return self.create_workbench()
#### Methods ##############################################################
def about(self):
""" Display the about dialog. """
# fixme: We really need to create a new 'about dialog' every time so
# that it can have the active window as its parent.
self.about_dialog.open()
# fixme: Is this needed on the public API? Why can't we just do this in
# the default initializer (_workbench_default)?
def create_workbench(self):
""" Create the workbench. """
logger.debug("workbench factory %s", self.workbench_factory)
return self.workbench_factory(application=self)
def exit(self):
""" Exit the application.
This closes all open windows and hence exits the GUI event loop.
"""
self.workbench.exit()
###########################################################################
# Private interface.
###########################################################################
def _on_workbench_exited(self):
""" Dynamic trait change handler. """
# We don't invoke 'stop' directly because:-
#
# The workbench is often exited via a user action (either by closing
# the last open window, or by choosing 'File/Exit'). If this happens
# then the workbench 'exit' method is called from within an event
# handler which would cause the 'stop' method to get called *before*
# the handling of the window 'closed' event is complete. Hance, this
# might mean that somebody listening for the window being closed would
# get the event *after* the application had already stopped!
self.gui.invoke_later(self.stop)
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <https://www.gnu.org/licenses/>.
# ------------------------------------------------------------------------------
"""
Handle image and file resources.
"""
import os
from pyface.api import ImageResource
from traits.api import *
from traitsui.api import *
search_path = os.path.join(
os.path.split(os.path.abspath(__file__))[0], 'resources')
APPICON = ImageResource(name='appicon.png', search_path=search_path)
USER_GUIDE = os.path.join(search_path, 'docs', 'optoConfig96_guide.html')
class opView(View):
"""
Set the default icon.
"""
icon = Instance(ImageResource, APPICON)
class Examples(HasTraits):
_available_examples = Property
def trait_view(self, name='default'):
file_menu = Menu(
ActionGroup(Action(name='New \t Ctrl+N', action='new'),
Action(name='Open \t Ctrl+O', action='open'),
Action(name='Close \t Ctrl+W', action='close_tab')),
ActionGroup(Action(name='Save \t Ctrl+S', action='save'),
Action(name='Save As', action='saveAs')),
ActionGroup(Action(name='Exit \t Ctrl+Q', action='exit')),
name='File')
edit_menu = Menu(
ActionGroup(Action(name='Undo \t Ctrl+Z', action='undo'),
Action(name='Redo \t Ctrl+Y', action='redo')),
ActionGroup(Action(name='Cut \t Ctrl+X', action='cut'),
Action(name='Copy \t Ctrl+C', action='copy'),
Action(name='Paste \t Ctrl+V', action='paste')),
ActionGroup(
Action(name='Select All \t Ctrl+A', action='select_all')),
name='Edit')
search_menu = Menu(ActionGroup(
Action(name='Find \t Ctrl+F', action='enable_find'),
Action(name='Replace \t Ctrl+R', action='enable_replace')),
name='Search')
view_menu = Menu(ActionGroup(
Action(name='Toggle File Browser', action='toggle_file_browser')),
name='View')
prefs_menu = Menu(Action(name='Sync view on change',
action='toggle_sync_on_change',
checked=self.sync_on_change,
style='toggle'),
Action(name='Auto fix table',
action='toggle_auto_table_fix',
checked=self.auto_table_fix,
style='toggle'),
Action(name='Use Sphinx',
action='toggle_sphinx',
checked=self.use_sphinx,
style='toggle'),
Action(name='Set Sphinx resources path...',
action='change_sphinx_static_path'),
Action(name='Change font', action='change_font'),
name='Preferences')
help_menu = Menu(Action(name='About', action='about'), name='Help')
convert_menu = Menu(Action(name='Docutils - HTML',
action='docutils_rst2html'),
Action(name='Docutils - LaTeX',
action='docutils_rst2latex'),
Action(name='Sphinx - HTML',
action='sphinx_rst2html'),
Action(name='rst2pdf', action='rst2pdf'),
name='Convert')
menu_bar = MenuBar(file_menu, edit_menu, search_menu, view_menu,
prefs_menu, convert_menu, help_menu)
########################################################################
file_group = ActionGroup(
Action(tooltip='New', action='new', image=ImageResource('new')),
Action(tooltip='Open', action='open', image=ImageResource('open')),
Action(tooltip='Save', action='save', image=ImageResource('save')),
Action(tooltip='Save As',
action='saveAs',
image=ImageResource('save-as')),
Action(tooltip='Close',
action='close_tab',
image=ImageResource('close')))
edit_group = ActionGroup(
Action(tooltip='Cut', action='cut', image=ImageResource('cut')),
Action(tooltip='Copy', action='copy', image=ImageResource('copy')),
Action(tooltip='Paste',
action='paste',
image=ImageResource('paste')))
undo_group = ActionGroup(
Action(tooltip='Undo', action='undo', image=ImageResource('undo')),
Action(tooltip='Redo', action='redo', image=ImageResource('redo')))
search_group = ActionGroup(
Action(tooltip='Find',
action='enable_find',
image=ImageResource('find')),
Action(tooltip='Replace',
action='enable_replace',
image=ImageResource('replace')))
markup_group = ActionGroup(
Action(tooltip='Bold', action='bold', image=ImageResource('bold')),
Action(tooltip='Italic',
action='italic',
image=ImageResource('italic')),
Action(tooltip='Inline Literal',
action='inline_literal',
image=ImageResource('literal')),
Action(tooltip='Fix underline (Ctrl+D)',
action='fix_underline',
image=ImageResource('underline')),
Action(tooltip='Fix underline and overline (Ctrl+Shift+D)',
action='fix_under_overline',
image=ImageResource('under-over')))
sync_group = ActionGroup(
Action(tooltip='Sync rst2html',
action='sync_scrollbar_rst2html',
image=ImageResource('sync_rst2html')),
Action(tooltip='Sync html2rst',
action='sync_scrollbar_html2rst',
image=ImageResource('sync_html2rst')))
tool_bar = ToolBar(file_group, edit_group, undo_group, search_group,
markup_group, sync_group)
##################################
key_bindings = KeyBindings(
KeyBinding(binding1='Ctrl-n', method_name='new'),
KeyBinding(binding1='Ctrl-o', method_name='open'),
KeyBinding(binding1='Ctrl-s', method_name='save'),
KeyBinding(binding1='Ctrl-w', method_name='close_tab'),
KeyBinding(binding1='Ctrl-q', method_name='exit'),
KeyBinding(binding1='Ctrl-d', method_name='fix_underline'),
KeyBinding(binding1='Ctrl-Shift-d',
method_name='fix_under_overline'),
# The following are identical to the already set hotkeys in
# the source editor. We just want them to work regardless of
# whether the editor has focus.
KeyBinding(binding1='Ctrl-z', method_name='undo'),
KeyBinding(binding1='Ctrl-y', method_name='redo'),
KeyBinding(binding1='Ctrl-x', method_name='cut'),
KeyBinding(binding1='Ctrl-c', method_name='copy'),
KeyBinding(binding1='Ctrl-v', method_name='paste'),
KeyBinding(binding1='Ctrl-a', method_name='select_all'),
KeyBinding(binding1='Ctrl-f', method_name='enable_find'),
KeyBinding(binding1='Ctrl-r', method_name='enable_replace'))
return View(Group(Item('_tree',
style='custom',
width=0.25,
editor=InstanceEditor()),
Item('open_views',
style='custom',
editor=ListEditor(use_notebook=True,
deletable=True,
dock_style='tab',
ui_kind='panel',
selected='selected_view',
page_name='.title')),
id='rest_editor_view.EditorSplit',
orientation='horizontal',
layout='split',
show_labels=False),
id='rest_editor_view.EditorView',
handler=ReSTHTMLEditorHandler(),
width=1024,
height=786,
resizable=True,
menubar=menu_bar,
toolbar=tool_bar,
key_bindings=key_bindings,
title="reStructured Text Editor",
icon=self.icon)
def get_icon(self):
return ImageResource('tasbe')
def get_icon(self):
return ImageResource('stats_1d')
def get_icon(self):
return ImageResource('ratio')
def __init__(self, parent, tool_bar, image_cache, item, controller,
show_labels):
""" Creates a new tool bar tool for an action item. """
self.item = item
self.tool_bar = tool_bar
# Create an appropriate tool depending on the style of the action.
action = self.item.action
label = action.name
# Tool bar tools never have '...' at the end!
if label.endswith('...'):
label = label[:-3]
# And they never contain shortcuts.
label = label.replace('&', '')
# If the action has an image then convert it to a bitmap (as required
# by the toolbar).
if action.image is not None:
image = action.image.create_image(
self.tool_bar.GetToolBitmapSize()
)
path = action.image.absolute_path
bmp = image_cache.get_bitmap(path)
else:
from pyface.api import ImageResource
image = ImageResource('foo')
bmp = image.create_bitmap()
kind = _STYLE_TO_KIND_MAP[action.style]
tooltip = action.tooltip
longtip = action.description
if not show_labels:
label = ''
else:
self.tool_bar.SetSize((-1, 50))
self.control_id = wx.NewId()
self.control = tool_bar.AddLabelTool(
self.control_id, label, bmp, wx.NullBitmap, kind, tooltip, longtip, None
)
# Set the initial checked state.
tool_bar.ToggleTool(self.control_id, action.checked)
if hasattr(tool_bar, 'ShowTool'):
# Set the initial enabled/disabled state of the action.
tool_bar.EnableTool(self.control_id, action.enabled)
# Set the initial visibility
tool_bar.ShowTool(self.control_id, action.visible)
else:
# Set the initial enabled/disabled state of the action.
tool_bar.EnableTool(
self.control_id, action.enabled and action.visible)
# Wire it up.
wx.EVT_TOOL(parent, self.control_id, self._on_tool)
# Listen for trait changes on the action (so that we can update its
# enabled/disabled/checked state etc).
action.on_trait_change(self._on_action_enabled_changed, 'enabled')
action.on_trait_change(self._on_action_visible_changed, 'visible')
action.on_trait_change(self._on_action_checked_changed, 'checked')
if controller is not None:
self.controller = controller
controller.add_to_toolbar(self)
def get_icon(self):
return ImageResource(u'quad')
def get_icon(self):
return ImageResource('histogram')
def get_icon(self):
return ImageResource('autofluorescence')
view=demo_content_view
),
ObjectTreeNode(
node_for=[DemoVirtualDirectory],
label="nice_name",
view=demo_virtual_dir_view,
),
],
hide_root=True,
selected='selected_node',
)
next_tool = Action(
name='Next',
image=ImageResource("next"),
tooltip="Go to next file",
action="do_next",
enabled_when="_next_node is not None",
)
previous_tool = Action(
name='Previous',
image=ImageResource("previous"),
tooltip="Go to next file",
action="do_previous",
enabled_when="_previous_node is not None",
)
parent_tool = Action(
name='Parent',
def get_icon(self):
return ImageResource('violin')
def get_icon(self):
return ImageResource('xform_stat')