class Config(SignalNode.Config):
"""Config widget displayed for LSLInput."""
def __init__(self, parent=None):
super().__init__(parent=parent)
self.data_source = QComboBox()
for source in LSLInput.data_sources:
self.data_source.addItem(source.name)
self.data_source.currentTextChanged.connect(self._adjust)
self.channel_count = QLabel()
self.channel_count.setFrameStyle(QFrame.Panel | QFrame.Sunken)
self.channel_count.setAlignment(Qt.AlignCenter)
self.channel_count.setMargin(5)
self.frequency = QLabel()
self.frequency.setFrameStyle(QFrame.Panel | QFrame.Sunken)
self.frequency.setAlignment(Qt.AlignCenter)
self.frequency.setMargin(5)
layout = QFormLayout()
self.setLayout(layout)
layout.addRow("Data source:", self.data_source)
layout.addRow("Channel count:", self.channel_count)
layout.addRow("Frequency:", self.frequency)
self._adjust()
def _adjust(self):
"""Adjust displayed values after a change."""
# Sync changes with the node
self.updateModel()
# Find the data_source with the selected name
for data_source in LSLInput.data_sources:
if data_source.name == self.data_source.currentText():
break
else:
data_source = None
# Update displays to show new information
self.channel_count.setText(str(data_source.channel_count))
self.frequency.setText(str(data_source.frequency) + " Hz")
def updateModel(self):
n = self.node()
if n is None:
return
n.setDataSource(self.data_source.currentText())
def updateView(self):
n = self.node()
if n is None:
return
self.data_source.blockSignals(True)
self.data_source.setCurrentText(n.dataSource())
self.data_source.blockSignals(False)
def comboBoxSelectItemByText(combobox: QtWidgets.QComboBox, value, block=False):
index = combobox.findText(value)
if index >= 0:
if block:
block_state = combobox.blockSignals(True)
combobox.setCurrentIndex(index)
if block:
combobox.blockSignals(block_state)
def setEditorData(self, editor: QComboBox, index: QModelIndex):
"""Update the editor."""
items = [artist.name for artist in self._manager.context.artists]
current = index.model().data(index, RoleTaskArtist)
try:
row = items.index(current)
except ValueError: # None is not in list
row = -1
editor.blockSignals(True)
editor.setCurrentIndex(row)
editor.blockSignals(False)
class Config(SignalNode.Config):
"""Config widget displayed for LSLInput."""
def __init__(self, parent=None):
super().__init__(parent=parent)
self.smoothing_factor = QDoubleSpinBox()
self.smoothing_factor.setMinimum(0)
self.smoothing_factor.setMaximum(1)
self.smoothing_factor.setSingleStep(0.1)
self.smoothing_factor.setPrefix("x")
self.smoothing_factor.valueChanged.connect(self.updateModel)
self.method = QComboBox()
self.method.addItem("Rectification")
self.method.addItem("Fourier Transform")
self.method.addItem("Hilbert Transform")
self.method.addItem("cFIR")
self.method.currentTextChanged.connect(self.updateModel)
self.smoother_type = QComboBox()
for name in EnvelopeDetector.smoother_name_to_type:
self.smoother_type.addItem(name)
self.smoother_type.currentTextChanged.connect(self.updateModel)
layout = QFormLayout()
self.setLayout(layout)
layout.addRow("Smoothing factor", self.smoothing_factor)
layout.addRow("Method", self.method)
layout.addRow("Smoother type", self.smoother_type)
def updateModel(self):
n = self.node()
if n is None:
return
smoothing_factor = self.smoothing_factor.value()
method = self.method.currentText()
smoother_type = n.smoother_name_to_type[self.smoother_type.currentText()]
n.setSmoothingFactor(smoothing_factor)
n.setMethod(method)
n.setSmootherType(smoother_type)
def updateView(self):
n = self.node()
if n is None:
return
self.smoothing_factor.blockSignals(True)
self.method.blockSignals(True)
self.smoother_type.blockSignals(True)
self.smoothing_factor.setValue(n.smoothingFactor())
self.method.setCurrentText(n.method())
self.smoother_type.setCurrentText(n.smoother_type_to_name[n.smootherType()])
self.smoothing_factor.blockSignals(False)
self.method.blockSignals(False)
self.smoother_type.blockSignals(False)
class LabeledComboBox(QWidget):
currentTextChanged = Signal(str)
def __init__(self, label_string, items=[]):
super(LabeledComboBox, self).__init__()
self.label = QLabel(label_string)
self.combo_box = QComboBox(self)
self.items = items
for item in self.items:
self.combo_box.addItem(item)
self.previous_item = [None, None]
self.combo_box.currentTextChanged.connect(self._currentTextChanged)
ComboBoxLayout = QVBoxLayout(self)
ComboBoxLayout.addWidget(self.label)
ComboBoxLayout.addWidget(self.combo_box)
def currentText(self):
return self.combo_box.currentText()
def _currentTextChanged(self, text):
self.previous_item = [
self.previous_item[1],
self.combo_box.currentText()
]
self.currentTextChanged.emit(text)
def revert(self):
self.setCurrentText(self.previous_item[0], quiet=True)
self.previous_item = [None, self.previous_item[0]]
def setCurrentText(self, value, quiet=False):
if quiet:
self.combo_box.blockSignals(True)
self.combo_box.setCurrentText(value)
self.combo_box.blockSignals(False)
else:
self.combo_box.setCurrentText(value)
def update_combobox(box: QComboBox, labels: List[str]) -> None:
"""Update the combobox menu."""
box.blockSignals(True)
box.clear()
box.insertItems(0, labels)
box.blockSignals(False)
def set_combobox_index(box: QComboBox, index: int) -> None:
"""Update the index on the given QComboBox without sending a signal."""
box.blockSignals(True)
box.setCurrentIndex(index)
box.blockSignals(False)
class Config(SignalNode.Config):
"""Config widget displayed for BandpassFilter."""
def __init__(self, parent=None):
super().__init__(parent=parent)
# Upper bound ----------------------------------------------------------------------------------------------
self.lower_bound_enable = QCheckBox()
self.lower_bound_enable.setChecked(True)
self.lower_bound_enable.stateChanged.connect(self.updateModel)
self.lower_bound = QDoubleSpinBox()
self.lower_bound.valueChanged.connect(self.updateModel)
self.lower_bound.setMinimum(0)
self.lower_bound.setMaximum(250)
self.lower_bound.setSuffix(" Hz")
layout = QHBoxLayout()
layout.setContentsMargins(0, 0, 0, 0)
lower_bound_widget = QWidget()
lower_bound_widget.setContentsMargins(0, 0, 0, 0)
lower_bound_widget.setLayout(layout)
layout.addWidget(self.lower_bound_enable)
layout.addWidget(self.lower_bound)
# Lower bound ----------------------------------------------------------------------------------------------
self.upper_bound_enable = QCheckBox()
self.upper_bound_enable.setChecked(True)
self.upper_bound_enable.stateChanged.connect(self.updateModel)
self.upper_bound = QDoubleSpinBox()
self.upper_bound.valueChanged.connect(self.updateModel)
self.upper_bound.setMinimum(0)
self.upper_bound.setMaximum(250)
self.upper_bound.setSuffix(" Hz")
layout = QHBoxLayout()
layout.setContentsMargins(0, 0, 0, 0)
upper_bound_widget = QWidget()
upper_bound_widget.setContentsMargins(0, 0, 0, 0)
upper_bound_widget.setLayout(layout)
layout.addWidget(self.upper_bound_enable)
layout.addWidget(self.upper_bound)
# Filter type and length -----------------------------------------------------------------------------------
self.filter_type = QComboBox()
for name in BandpassFilter.filter_name_to_type:
self.filter_type.addItem(name)
self.filter_type.currentTextChanged.connect(self.updateModel)
self.filter_length = QSpinBox()
self.filter_length.setMinimum(2)
self.filter_length.setMaximum(1000000)
self.filter_length.setValue(1000)
self.filter_length.valueChanged.connect(self.updateModel)
self.filter_order = QSpinBox()
self.filter_order.setRange(1, 4)
self.filter_order.valueChanged.connect(self.updateModel)
# ----------------------------------------------------------------------------------------------------------
layout = QFormLayout()
layout.addRow("Lower bound:", lower_bound_widget)
layout.addRow("Upper bound:", upper_bound_widget)
layout.addRow("Filter type:", self.filter_type)
layout.addRow("Filter order:", self.filter_order)
layout.addRow("Filter length:", self.filter_length)
self.setLayout(layout)
def updateModel(self):
n = self.node()
if n is None:
return
if self.lower_bound_enable.isChecked():
lower_bound = self.lower_bound.value()
else:
lower_bound = None
if self.upper_bound_enable.isChecked():
upper_bound = self.upper_bound.value()
else:
upper_bound = None
filter_type = n.filter_name_to_type[self.filter_type.currentText()]
filter_length = self.filter_length.value()
filter_order = self.filter_order.value()
n.setLowerBound(lower_bound)
n.setUpperBound(upper_bound)
n.setFilterType(filter_type)
n.setFilterLength(filter_length)
n.setFilterOrder(filter_order)
def updateView(self):
n = self.node()
if n is None:
return
# Prevent view fields from emitting signals while they are updated
self.lower_bound.blockSignals(True)
self.upper_bound.blockSignals(True)
self.filter_type.blockSignals(True)
self.filter_length.blockSignals(True)
self.filter_order.blockSignals(True)
if n.upperBound() is None:
self.upper_bound_enable.setChecked(False)
else:
self.upper_bound_enable.setChecked(True)
self.upper_bound.setValue(n.upperBound())
if n.lowerBound() is None:
self.lower_bound_enable.setChecked(False)
else:
self.lower_bound_enable.setChecked(True)
self.lower_bound.setValue(n.lowerBound())
self.filter_type.setCurrentText(
n.filter_type_to_name[n.filterType()])
self.filter_length.setValue(n.filterLength())
self.filter_order.setValue(n.filterOrder())
# Release the block and call adjust
self.lower_bound.blockSignals(False)
self.upper_bound.blockSignals(False)
self.filter_type.blockSignals(False)
self.filter_length.blockSignals(False)
self.filter_order.blockSignals(False)
self._adjust()
def _adjust(self):
"""Adjust displayed values and limits in response to changes."""
# Enable spinbox widgets based on their checkbox
self.lower_bound.setEnabled(self.lower_bound_enable.isChecked())
self.upper_bound.setEnabled(self.upper_bound_enable.isChecked())
# Adjust min and max so that lower_bound is never higher than upper_bound
if self.lower_bound_enable.isChecked():
self.upper_bound.setMinimum(self.lower_bound.value())
else:
self.upper_bound.setMinimum(0)
if self.upper_bound_enable.isChecked():
self.lower_bound.setMaximum(self.upper_bound.value())
else:
self.lower_bound.setMaximum(250)
if self.filter_type.currentText() == "Butterworth":
self.filter_order.setEnabled(True)
else:
self.filter_order.setEnabled(False)
class MayaNodeWidget(QWidget):
"""Widget allowing Maya node selection with a persistent cache.
Users should connect to the node_changed signal.
"""
node_changed = Signal(str)
def __init__(self, label=None, name=None, parent=None):
"""Constructor
:param label: Optional label text.
:param name: Unique name used to query persistent data.
:param parent: Parent QWidget.
"""
super(MayaNodeWidget, self).__init__(parent)
self.cache = StringCache("cmt.mayanodewidget.{}".format(name),
parent=self)
self._layout = QHBoxLayout(self)
self._layout.setContentsMargins(0, 0, 0, 0)
self.setLayout(self._layout)
if label:
label = QLabel(label, self)
label.setSizePolicy(QSizePolicy.Fixed, QSizePolicy.Fixed)
self._layout.addWidget(label)
self._combo_box = QComboBox(self)
self._combo_box.setEditable(True)
self._combo_box.setSizePolicy(QSizePolicy.Expanding, QSizePolicy.Fixed)
self._combo_box.setInsertPolicy(QComboBox.InsertAtTop)
self._combo_box.setModel(self.cache)
self._combo_box.editTextChanged.connect(self.edit_changed)
self._layout.addWidget(self._combo_box)
button = QPushButton("<", self)
button.released.connect(self.use_selected)
button.setSizePolicy(QSizePolicy.Fixed, QSizePolicy.Fixed)
self._layout.addWidget(button)
@property
def node(self):
return self._combo_box.currentText()
@node.setter
def node(self, value):
self._combo_box.setEditText(value)
def edit_changed(self, text):
"""Slot called whenever the text changes in the combobox.
:param text: New text.
"""
if not text:
return
if cmds.objExists(text):
self.node_changed.emit(text)
self._combo_box.blockSignals(True)
self._push(text)
self._combo_box.blockSignals(False)
def use_selected(self):
"""Populate the combobox with the name of the selected node."""
selected = cmds.ls(sl=True)
if selected:
self._push(selected[0])
def _push(self, node):
"""Push a new node onto the cache.
:param path: Node name.
"""
self.cache.push(node)
self._combo_box.setCurrentIndex(0)
class WMatSelectV(QGroupBox):
"""
Material related widget including a Label, a Combobox to select a material
and a Button to edit a material libary.
WMatSelect is instantiated to empty material data, so it has to be referenced
to actual material data with the update method prior to its first usage.
"""
# Signal to W_MachineSetup to know that the save popup is needed
saveNeeded = Signal()
def __init__(self, parent=None):
"""
Set a reference to a material libray and material data path,
updates the Combobox by the material names of the libary
and set a referenced material by name.
Parameters
----------
self :
A WMatSelect object
parent :
A reference to the widgets parent
Returns
-------
"""
# Build the interface according to the .ui file
QGroupBox.__init__(self, parent)
self.verticalLayout = QVBoxLayout(self)
self.c_mat_type = QComboBox(self)
self.c_mat_type.setObjectName(u"c_mat_type")
self.verticalLayout.addWidget(self.c_mat_type)
self.b_matlib = QPushButton(self)
self.b_matlib.setObjectName(u"b_matlib")
self.b_matlib.setText("Edit Materials")
self.verticalLayout.addWidget(self.b_matlib)
# Create the property of the widget
self.mat_win = None # DMatLib widget
self.obj = None # object that has a material attribute
self.mat_attr_name = "" # material attribute name
self.matlib = list() # Matlib
self.matlib_path = "" # Path to save the matlib
self.def_mat = "M400-50A" # Default material
self.is_hide_button = False # To hide the "Edit material" button
# Connect the signals
self.c_mat_type.currentIndexChanged.connect(self.set_mat_type)
self.b_matlib.clicked.connect(self.s_open_matlib)
def update(self, obj, mat_attr_name, matlib, matlib_path=""):
"""
Set a reference to a material libray and material data path,
updates the Combobox by the material names of the libary
and set a referenced material by name.
Parameters
----------
self :
A WMatSelect object
obj :
A pyleecan object that has a material attribute
mat_attr_name :
A string of the material attribute name
matlib :
A material libary, i.e. a list of Material objects
matlib_path :
A string containing the path of material data
Returns
-------
"""
self.c_mat_type.blockSignals(True)
# Set material combobox according to matlib names
self.obj = obj
self.mat_attr_name = mat_attr_name
self.matlib = matlib
self.matlib_path = matlib_path
if self.is_hide_button:
self.b_matlib.hide()
else:
self.b_matlib.show()
# Update the list of materials
self.c_mat_type.clear()
items_to_add = []
# Add RefMatLib materials
items_to_add.extend([mat.name for mat in matlib.dict_mat["RefMatLib"]])
# Add machine-specific materials
items_to_add.extend(
[mat.name for mat in matlib.dict_mat["MachineMatLib"]])
self.c_mat_type.addItems(items_to_add)
mat = getattr(self.obj, mat_attr_name, None)
if mat is None or mat.name is None:
# Default lamination material: M400-50A
index = self.c_mat_type.findText(self.def_mat)
if index != -1:
# self.mat.__init__(init_dict=self.matlib[index].as_dict())
setattr(
self.obj,
self.mat_attr_name,
self.matlib.dict_mat["RefMatLib"][index],
)
else:
index = self.c_mat_type.findText(mat.name)
self.c_mat_type.setCurrentIndex(index)
self.c_mat_type.blockSignals(False)
def setText(self, txt):
"""
Set the Label's text
Parameters
----------
self :
A WMatSelect object
txt :
A text string
Returns
-------
"""
self.setTitle(txt)
def set_mat_type(self, index):
"""
Signal to set the referenced material from the material libary
by the selected Combobox index
Parameters
----------
self :
A WMatSelect object
index :
Current index of the combobox
Returns
-------
"""
if index >= len(self.matlib.dict_mat["RefMatLib"]):
index -= len(self.matlib.dict_mat["RefMatLib"])
dict_key = "MachineMatLib"
else:
dict_key = "RefMatLib"
setattr(self.obj, self.mat_attr_name,
self.matlib.dict_mat[dict_key][index])
# Notify the machine GUI that the machine has changed
self.saveNeeded.emit()
def s_open_matlib(self):
"""
Open the GUI (DMatLib widget) to Edit the Material library
Parameters
----------
self :
A WMatSelect object
Returns
-------
"""
if self.c_mat_type.currentIndex() >= len(
self.matlib.dict_mat["RefMatLib"]):
index = self.c_mat_type.currentIndex() - len(
self.matlib.dict_mat["RefMatLib"])
key = "MachineMatLib"
else:
index = self.c_mat_type.currentIndex()
key = "RefMatLib"
self.mat_win = DMatLib(self.matlib, key, index)
self.mat_win.accepted.connect(self.set_matlib)
self.mat_win.saveNeeded.connect(self.emit_save)
self.mat_win.show()
def emit_save(self):
"""
Emit saveNeeded if a material has been edited
"""
self.saveNeeded.emit()
def set_matlib(self):
"""Update the matlib with the new value
Parameters
----------
self :
A WMatSelect object
Returns
-------
"""
# Empty and fill the list to keep the same object (to change it everywhere)
# del self.matlib[:]
# self.matlib.extend(self.mat_win.matlib)
# Update the material
# index = int(self.mat_win.nav_mat.currentItem().text()[:3]) - 1
# not needed if machine materials are "connected" properly
# mat_dict = (self.mat_win.matlib[index]).as_dict()
# self.mat.__init__(init_dict=mat_dict)
# Do not clear for now to keep editor (DMatLib) open
# # Clear the window
# self.mat_win.deleteLater()
# self.mat_win = None
# Update the widget
# Avoid trigger signal currentIndexChanged
self.c_mat_type.blockSignals(True)
self.c_mat_type.clear()
items_to_add = []
# Add RefMatLib materials
items_to_add.extend(
[mat.name for mat in self.matlib.dict_mat["RefMatLib"]])
# Add machine-specific materials
items_to_add.extend(
[mat.name for mat in self.matlib.dict_mat["MachineMatLib"]])
self.c_mat_type.addItems(items_to_add)
index = self.c_mat_type.findText(
getattr(self.obj, self.mat_attr_name).name)
self.c_mat_type.setCurrentIndex(index)
self.c_mat_type.blockSignals(False)
class FittingResultViewer(QDialog):
PAGE_ROWS = 20
logger = logging.getLogger("root.QGrain.ui.FittingResultViewer")
result_marked = Signal(SSUResult)
def __init__(self, reference_viewer: ReferenceResultViewer, parent=None):
super().__init__(parent=parent, f=Qt.Window)
self.setWindowTitle(self.tr("SSU Fitting Result Viewer"))
self.__fitting_results = [] # type: list[SSUResult]
self.retry_tasks = {} # type: dict[UUID, SSUTask]
self.__reference_viewer = reference_viewer
self.init_ui()
self.boxplot_chart = BoxplotChart(parent=self, toolbar=True)
self.typical_chart = SSUTypicalComponentChart(parent=self,
toolbar=True)
self.distance_chart = DistanceCurveChart(parent=self, toolbar=True)
self.mixed_distribution_chart = MixedDistributionChart(
parent=self, toolbar=True, use_animation=True)
self.file_dialog = QFileDialog(parent=self)
self.async_worker = AsyncWorker()
self.async_worker.background_worker.task_succeeded.connect(
self.on_fitting_succeeded)
self.async_worker.background_worker.task_failed.connect(
self.on_fitting_failed)
self.update_page_list()
self.update_page(self.page_index)
self.normal_msg = QMessageBox(self)
self.remove_warning_msg = QMessageBox(self)
self.remove_warning_msg.setStandardButtons(QMessageBox.No
| QMessageBox.Yes)
self.remove_warning_msg.setDefaultButton(QMessageBox.No)
self.remove_warning_msg.setWindowTitle(self.tr("Warning"))
self.remove_warning_msg.setText(
self.tr("Are you sure to remove all SSU results?"))
self.outlier_msg = QMessageBox(self)
self.outlier_msg.setStandardButtons(QMessageBox.Discard
| QMessageBox.Retry
| QMessageBox.Ignore)
self.outlier_msg.setDefaultButton(QMessageBox.Ignore)
self.retry_progress_msg = QMessageBox()
self.retry_progress_msg.addButton(QMessageBox.Ok)
self.retry_progress_msg.button(QMessageBox.Ok).hide()
self.retry_progress_msg.setWindowTitle(self.tr("Progress"))
self.retry_timer = QTimer(self)
self.retry_timer.setSingleShot(True)
self.retry_timer.timeout.connect(
lambda: self.retry_progress_msg.exec_())
def init_ui(self):
self.data_table = QTableWidget(100, 100)
self.data_table.setEditTriggers(QAbstractItemView.NoEditTriggers)
self.data_table.setSelectionBehavior(QAbstractItemView.SelectRows)
self.data_table.setAlternatingRowColors(True)
self.data_table.setContextMenuPolicy(Qt.CustomContextMenu)
self.main_layout = QGridLayout(self)
self.main_layout.addWidget(self.data_table, 0, 0, 1, 3)
self.previous_button = QPushButton(
qta.icon("mdi.skip-previous-circle"), self.tr("Previous"))
self.previous_button.setToolTip(
self.tr("Click to back to the previous page."))
self.previous_button.clicked.connect(self.on_previous_button_clicked)
self.current_page_combo_box = QComboBox()
self.current_page_combo_box.addItem(self.tr("Page {0}").format(1))
self.current_page_combo_box.currentIndexChanged.connect(
self.update_page)
self.next_button = QPushButton(qta.icon("mdi.skip-next-circle"),
self.tr("Next"))
self.next_button.setToolTip(self.tr("Click to jump to the next page."))
self.next_button.clicked.connect(self.on_next_button_clicked)
self.main_layout.addWidget(self.previous_button, 1, 0)
self.main_layout.addWidget(self.current_page_combo_box, 1, 1)
self.main_layout.addWidget(self.next_button, 1, 2)
self.distance_label = QLabel(self.tr("Distance"))
self.distance_label.setToolTip(
self.
tr("It's the function to calculate the difference (on the contrary, similarity) between two samples."
))
self.distance_combo_box = QComboBox()
self.distance_combo_box.addItems(built_in_distances)
self.distance_combo_box.setCurrentText("log10MSE")
self.distance_combo_box.currentTextChanged.connect(
lambda: self.update_page(self.page_index))
self.main_layout.addWidget(self.distance_label, 2, 0)
self.main_layout.addWidget(self.distance_combo_box, 2, 1, 1, 2)
self.menu = QMenu(self.data_table)
self.menu.setShortcutAutoRepeat(True)
self.mark_action = self.menu.addAction(
qta.icon("mdi.marker-check"),
self.tr("Mark Selection(s) as Reference"))
self.mark_action.triggered.connect(self.mark_selections)
self.remove_selection_action = self.menu.addAction(
qta.icon("fa.remove"), self.tr("Remove Selection(s)"))
self.remove_selection_action.triggered.connect(self.remove_selections)
self.remove_all_action = self.menu.addAction(qta.icon("fa.remove"),
self.tr("Remove All"))
self.remove_all_action.triggered.connect(self.remove_all_results)
self.plot_loss_chart_action = self.menu.addAction(
qta.icon("mdi.chart-timeline-variant"), self.tr("Plot Loss Chart"))
self.plot_loss_chart_action.triggered.connect(self.show_distance)
self.plot_distribution_chart_action = self.menu.addAction(
qta.icon("fa5s.chart-area"), self.tr("Plot Distribution Chart"))
self.plot_distribution_chart_action.triggered.connect(
self.show_distribution)
self.plot_distribution_animation_action = self.menu.addAction(
qta.icon("fa5s.chart-area"),
self.tr("Plot Distribution Chart (Animation)"))
self.plot_distribution_animation_action.triggered.connect(
self.show_history_distribution)
self.detect_outliers_menu = self.menu.addMenu(
qta.icon("mdi.magnify"), self.tr("Detect Outliers"))
self.check_nan_and_inf_action = self.detect_outliers_menu.addAction(
self.tr("Check NaN and Inf"))
self.check_nan_and_inf_action.triggered.connect(self.check_nan_and_inf)
self.check_final_distances_action = self.detect_outliers_menu.addAction(
self.tr("Check Final Distances"))
self.check_final_distances_action.triggered.connect(
self.check_final_distances)
self.check_component_mean_action = self.detect_outliers_menu.addAction(
self.tr("Check Component Mean"))
self.check_component_mean_action.triggered.connect(
lambda: self.check_component_moments("mean"))
self.check_component_std_action = self.detect_outliers_menu.addAction(
self.tr("Check Component STD"))
self.check_component_std_action.triggered.connect(
lambda: self.check_component_moments("std"))
self.check_component_skewness_action = self.detect_outliers_menu.addAction(
self.tr("Check Component Skewness"))
self.check_component_skewness_action.triggered.connect(
lambda: self.check_component_moments("skewness"))
self.check_component_kurtosis_action = self.detect_outliers_menu.addAction(
self.tr("Check Component Kurtosis"))
self.check_component_kurtosis_action.triggered.connect(
lambda: self.check_component_moments("kurtosis"))
self.check_component_fractions_action = self.detect_outliers_menu.addAction(
self.tr("Check Component Fractions"))
self.check_component_fractions_action.triggered.connect(
self.check_component_fractions)
self.degrade_results_action = self.detect_outliers_menu.addAction(
self.tr("Degrade Results"))
self.degrade_results_action.triggered.connect(self.degrade_results)
self.try_align_components_action = self.detect_outliers_menu.addAction(
self.tr("Try Align Components"))
self.try_align_components_action.triggered.connect(
self.try_align_components)
self.analyse_typical_components_action = self.menu.addAction(
qta.icon("ei.tags"), self.tr("Analyse Typical Components"))
self.analyse_typical_components_action.triggered.connect(
self.analyse_typical_components)
self.load_dump_action = self.menu.addAction(
qta.icon("fa.database"), self.tr("Load Binary Dump"))
self.load_dump_action.triggered.connect(self.load_dump)
self.save_dump_action = self.menu.addAction(
qta.icon("fa.save"), self.tr("Save Binary Dump"))
self.save_dump_action.triggered.connect(self.save_dump)
self.save_excel_action = self.menu.addAction(
qta.icon("mdi.microsoft-excel"), self.tr("Save Excel"))
self.save_excel_action.triggered.connect(
lambda: self.on_save_excel_clicked(align_components=False))
self.save_excel_align_action = self.menu.addAction(
qta.icon("mdi.microsoft-excel"),
self.tr("Save Excel (Force Alignment)"))
self.save_excel_align_action.triggered.connect(
lambda: self.on_save_excel_clicked(align_components=True))
self.data_table.customContextMenuRequested.connect(self.show_menu)
# necessary to add actions of menu to this widget itself,
# otherwise, the shortcuts will not be triggered
self.addActions(self.menu.actions())
def show_menu(self, pos: QPoint):
self.menu.popup(QCursor.pos())
def show_message(self, title: str, message: str):
self.normal_msg.setWindowTitle(title)
self.normal_msg.setText(message)
self.normal_msg.exec_()
def show_info(self, message: str):
self.show_message(self.tr("Info"), message)
def show_warning(self, message: str):
self.show_message(self.tr("Warning"), message)
def show_error(self, message: str):
self.show_message(self.tr("Error"), message)
@property
def distance_name(self) -> str:
return self.distance_combo_box.currentText()
@property
def distance_func(self) -> typing.Callable:
return get_distance_func_by_name(self.distance_combo_box.currentText())
@property
def page_index(self) -> int:
return self.current_page_combo_box.currentIndex()
@property
def n_pages(self) -> int:
return self.current_page_combo_box.count()
@property
def n_results(self) -> int:
return len(self.__fitting_results)
@property
def selections(self):
start = self.page_index * self.PAGE_ROWS
temp = set()
for item in self.data_table.selectedRanges():
for i in range(item.topRow(),
min(self.PAGE_ROWS + 1,
item.bottomRow() + 1)):
temp.add(i + start)
indexes = list(temp)
indexes.sort()
return indexes
def update_page_list(self):
last_page_index = self.page_index
if self.n_results == 0:
n_pages = 1
else:
n_pages, left = divmod(self.n_results, self.PAGE_ROWS)
if left != 0:
n_pages += 1
self.current_page_combo_box.blockSignals(True)
self.current_page_combo_box.clear()
self.current_page_combo_box.addItems(
[self.tr("Page {0}").format(i + 1) for i in range(n_pages)])
if last_page_index >= n_pages:
self.current_page_combo_box.setCurrentIndex(n_pages - 1)
else:
self.current_page_combo_box.setCurrentIndex(last_page_index)
self.current_page_combo_box.blockSignals(False)
def update_page(self, page_index: int):
def write(row: int, col: int, value: str):
if isinstance(value, str):
pass
elif isinstance(value, int):
value = str(value)
elif isinstance(value, float):
value = f"{value: 0.4f}"
else:
value = value.__str__()
item = QTableWidgetItem(value)
item.setTextAlignment(Qt.AlignCenter)
self.data_table.setItem(row, col, item)
# necessary to clear
self.data_table.clear()
if page_index == self.n_pages - 1:
start = page_index * self.PAGE_ROWS
end = self.n_results
else:
start, end = page_index * self.PAGE_ROWS, (page_index +
1) * self.PAGE_ROWS
self.data_table.setRowCount(end - start)
self.data_table.setColumnCount(7)
self.data_table.setHorizontalHeaderLabels([
self.tr("Resolver"),
self.tr("Distribution Type"),
self.tr("N_components"),
self.tr("N_iterations"),
self.tr("Spent Time [s]"),
self.tr("Final Distance"),
self.tr("Has Reference")
])
sample_names = [
result.sample.name for result in self.__fitting_results[start:end]
]
self.data_table.setVerticalHeaderLabels(sample_names)
for row, result in enumerate(self.__fitting_results[start:end]):
write(row, 0, result.task.resolver)
write(row, 1,
self.get_distribution_name(result.task.distribution_type))
write(row, 2, result.task.n_components)
write(row, 3, result.n_iterations)
write(row, 4, result.time_spent)
write(
row, 5,
self.distance_func(result.sample.distribution,
result.distribution))
has_ref = result.task.initial_guess is not None or result.task.reference is not None
write(row, 6, self.tr("Yes") if has_ref else self.tr("No"))
self.data_table.resizeColumnsToContents()
def on_previous_button_clicked(self):
if self.page_index > 0:
self.current_page_combo_box.setCurrentIndex(self.page_index - 1)
def on_next_button_clicked(self):
if self.page_index < self.n_pages - 1:
self.current_page_combo_box.setCurrentIndex(self.page_index + 1)
def get_distribution_name(self, distribution_type: DistributionType):
if distribution_type == DistributionType.Normal:
return self.tr("Normal")
elif distribution_type == DistributionType.Weibull:
return self.tr("Weibull")
elif distribution_type == DistributionType.SkewNormal:
return self.tr("Skew Normal")
else:
raise NotImplementedError(distribution_type)
def add_result(self, result: SSUResult):
if self.n_results == 0 or \
(self.page_index == self.n_pages - 1 and \
divmod(self.n_results, self.PAGE_ROWS)[-1] != 0):
need_update = True
else:
need_update = False
self.__fitting_results.append(result)
self.update_page_list()
if need_update:
self.update_page(self.page_index)
def add_results(self, results: typing.List[SSUResult]):
if self.n_results == 0 or \
(self.page_index == self.n_pages - 1 and \
divmod(self.n_results, self.PAGE_ROWS)[-1] != 0):
need_update = True
else:
need_update = False
self.__fitting_results.extend(results)
self.update_page_list()
if need_update:
self.update_page(self.page_index)
def mark_selections(self):
for index in self.selections:
self.result_marked.emit(self.__fitting_results[index])
def remove_results(self, indexes):
results = []
for i in reversed(indexes):
res = self.__fitting_results.pop(i)
results.append(res)
self.update_page_list()
self.update_page(self.page_index)
def remove_selections(self):
indexes = self.selections
self.remove_results(indexes)
def remove_all_results(self):
res = self.remove_warning_msg.exec_()
if res == QMessageBox.Yes:
self.__fitting_results.clear()
self.update_page_list()
self.update_page(0)
def show_distance(self):
results = [self.__fitting_results[i] for i in self.selections]
if results is None or len(results) == 0:
return
result = results[0]
self.distance_chart.show_distance_series(result.get_distance_series(
self.distance_name),
title=result.sample.name)
self.distance_chart.show()
def show_distribution(self):
results = [self.__fitting_results[i] for i in self.selections]
if results is None or len(results) == 0:
return
result = results[0]
self.mixed_distribution_chart.show_model(result.view_model)
self.mixed_distribution_chart.show()
def show_history_distribution(self):
results = [self.__fitting_results[i] for i in self.selections]
if results is None or len(results) == 0:
return
result = results[0]
self.mixed_distribution_chart.show_result(result)
self.mixed_distribution_chart.show()
def load_dump(self):
filename, _ = self.file_dialog.getOpenFileName(
self, self.tr("Select a binary dump file of SSU results"), None,
self.tr("Binary dump (*.dump)"))
if filename is None or filename == "":
return
with open(filename, "rb") as f:
results = pickle.load(f) # type: list[SSUResult]
valid = True
if isinstance(results, list):
for result in results:
if not isinstance(result, SSUResult):
valid = False
break
else:
valid = False
if valid:
if self.n_results != 0 and len(results) != 0:
old_classes = self.__fitting_results[0].classes_φ
new_classes = results[0].classes_φ
classes_inconsistent = False
if len(old_classes) != len(new_classes):
classes_inconsistent = True
else:
classes_error = np.abs(old_classes - new_classes)
if not np.all(np.less_equal(classes_error, 1e-8)):
classes_inconsistent = True
if classes_inconsistent:
self.show_error(
self.
tr("The results in the dump file has inconsistent grain-size classes with that in your list."
))
return
self.add_results(results)
else:
self.show_error(self.tr("The binary dump file is invalid."))
def save_dump(self):
if self.n_results == 0:
self.show_warning(self.tr("There is not any result in the list."))
return
filename, _ = self.file_dialog.getSaveFileName(
self, self.tr("Save the SSU results to binary dump file"), None,
self.tr("Binary dump (*.dump)"))
if filename is None or filename == "":
return
with open(filename, "wb") as f:
pickle.dump(self.__fitting_results, f)
def save_excel(self, filename, align_components=False):
if self.n_results == 0:
return
results = self.__fitting_results.copy()
classes_μm = results[0].classes_μm
n_components_list = [
result.n_components for result in self.__fitting_results
]
count_dict = Counter(n_components_list)
max_n_components = max(count_dict.keys())
self.logger.debug(
f"N_components: {count_dict}, Max N_components: {max_n_components}"
)
flags = []
if not align_components:
for result in results:
flags.extend(range(result.n_components))
else:
n_components_desc = "\n".join([
self.tr("{0} Component(s): {1}").format(n_components, count)
for n_components, count in count_dict.items()
])
self.show_info(
self.tr("N_components distribution of Results:\n{0}").format(
n_components_desc))
stacked_components = []
for result in self.__fitting_results:
for component in result.components:
stacked_components.append(component.distribution)
stacked_components = np.array(stacked_components)
cluser = KMeans(n_clusters=max_n_components)
flags = cluser.fit_predict(stacked_components)
# check flags to make it unique
flag_index = 0
for i, result in enumerate(self.__fitting_results):
result_flags = set()
for component in result.components:
if flags[flag_index] in result_flags:
if flags[flag_index] == max_n_components:
flags[flag_index] = max_n_components - 1
else:
flag_index[flag_index] += 1
result_flags.add(flags[flag_index])
flag_index += 1
flag_set = set(flags)
picked = []
for target_flag in flag_set:
for i, flag in enumerate(flags):
if flag == target_flag:
picked.append(
(target_flag,
logarithmic(classes_μm,
stacked_components[i])["mean"]))
break
picked.sort(key=lambda x: x[1])
flag_map = {flag: index for index, (flag, _) in enumerate(picked)}
flags = np.array([flag_map[flag] for flag in flags])
wb = openpyxl.Workbook()
prepare_styles(wb)
ws = wb.active
ws.title = self.tr("README")
description = \
"""
This Excel file was generated by QGrain ({0}).
Please cite:
Liu, Y., Liu, X., Sun, Y., 2021. QGrain: An open-source and easy-to-use software for the comprehensive analysis of grain size distributions. Sedimentary Geology 423, 105980. https://doi.org/10.1016/j.sedgeo.2021.105980
It contanins 4 + max(N_components) sheets:
1. The first sheet is the sample distributions of SSU results.
2. The second sheet is used to put the infomation of fitting.
3. The third sheet is the statistic parameters calculated by statistic moment method.
4. The fouth sheet is the distributions of unmixed components and their sum of each sample.
5. Other sheets are the unmixed end-member distributions which were discretely stored.
The SSU algorithm is implemented by QGrain.
""".format(QGRAIN_VERSION)
def write(row, col, value, style="normal_light"):
cell = ws.cell(row + 1, col + 1, value=value)
cell.style = style
lines_of_desc = description.split("\n")
for row, line in enumerate(lines_of_desc):
write(row, 0, line, style="description")
ws.column_dimensions[column_to_char(0)].width = 200
ws = wb.create_sheet(self.tr("Sample Distributions"))
write(0, 0, self.tr("Sample Name"), style="header")
ws.column_dimensions[column_to_char(0)].width = 16
for col, value in enumerate(classes_μm, 1):
write(0, col, value, style="header")
ws.column_dimensions[column_to_char(col)].width = 10
for row, result in enumerate(results, 1):
if row % 2 == 0:
style = "normal_dark"
else:
style = "normal_light"
write(row, 0, result.sample.name, style=style)
for col, value in enumerate(result.sample.distribution, 1):
write(row, col, value, style=style)
QCoreApplication.processEvents()
ws = wb.create_sheet(self.tr("Information of Fitting"))
write(0, 0, self.tr("Sample Name"), style="header")
ws.column_dimensions[column_to_char(0)].width = 16
headers = [
self.tr("Distribution Type"),
self.tr("N_components"),
self.tr("Resolver"),
self.tr("Resolver Settings"),
self.tr("Initial Guess"),
self.tr("Reference"),
self.tr("Spent Time [s]"),
self.tr("N_iterations"),
self.tr("Final Distance [log10MSE]")
]
for col, value in enumerate(headers, 1):
write(0, col, value, style="header")
if col in (4, 5, 6):
ws.column_dimensions[column_to_char(col)].width = 10
else:
ws.column_dimensions[column_to_char(col)].width = 10
for row, result in enumerate(results, 1):
if row % 2 == 0:
style = "normal_dark"
else:
style = "normal_light"
write(row, 0, result.sample.name, style=style)
write(row, 1, result.distribution_type.name, style=style)
write(row, 2, result.n_components, style=style)
write(row, 3, result.task.resolver, style=style)
write(row,
4,
self.tr("Default") if result.task.resolver_setting is None
else result.task.resolver_setting.__str__(),
style=style)
write(row,
5,
self.tr("None") if result.task.initial_guess is None else
result.task.initial_guess.__str__(),
style=style)
write(row,
6,
self.tr("None") if result.task.reference is None else
result.task.reference.__str__(),
style=style)
write(row, 7, result.time_spent, style=style)
write(row, 8, result.n_iterations, style=style)
write(row, 9, result.get_distance("log10MSE"), style=style)
ws = wb.create_sheet(self.tr("Statistic Moments"))
write(0, 0, self.tr("Sample Name"), style="header")
ws.merge_cells(start_row=1, start_column=1, end_row=2, end_column=1)
ws.column_dimensions[column_to_char(0)].width = 16
headers = []
sub_headers = [
self.tr("Proportion"),
self.tr("Mean [φ]"),
self.tr("Mean [μm]"),
self.tr("STD [φ]"),
self.tr("STD [μm]"),
self.tr("Skewness"),
self.tr("Kurtosis")
]
for i in range(max_n_components):
write(0,
i * len(sub_headers) + 1,
self.tr("C{0}").format(i + 1),
style="header")
ws.merge_cells(start_row=1,
start_column=i * len(sub_headers) + 2,
end_row=1,
end_column=(i + 1) * len(sub_headers) + 1)
headers.extend(sub_headers)
for col, value in enumerate(headers, 1):
write(1, col, value, style="header")
ws.column_dimensions[column_to_char(col)].width = 10
flag_index = 0
for row, result in enumerate(results, 2):
if row % 2 == 0:
style = "normal_light"
else:
style = "normal_dark"
write(row, 0, result.sample.name, style=style)
for component in result.components:
index = flags[flag_index]
write(row,
index * len(sub_headers) + 1,
component.fraction,
style=style)
write(row,
index * len(sub_headers) + 2,
component.logarithmic_moments["mean"],
style=style)
write(row,
index * len(sub_headers) + 3,
component.geometric_moments["mean"],
style=style)
write(row,
index * len(sub_headers) + 4,
component.logarithmic_moments["std"],
style=style)
write(row,
index * len(sub_headers) + 5,
component.geometric_moments["std"],
style=style)
write(row,
index * len(sub_headers) + 6,
component.logarithmic_moments["skewness"],
style=style)
write(row,
index * len(sub_headers) + 7,
component.logarithmic_moments["kurtosis"],
style=style)
flag_index += 1
ws = wb.create_sheet(self.tr("Unmixed Components"))
ws.merge_cells(start_row=1, start_column=1, end_row=1, end_column=2)
write(0, 0, self.tr("Sample Name"), style="header")
ws.column_dimensions[column_to_char(0)].width = 16
for col, value in enumerate(classes_μm, 2):
write(0, col, value, style="header")
ws.column_dimensions[column_to_char(col)].width = 10
row = 1
for result_index, result in enumerate(results, 1):
if result_index % 2 == 0:
style = "normal_dark"
else:
style = "normal_light"
write(row, 0, result.sample.name, style=style)
ws.merge_cells(start_row=row + 1,
start_column=1,
end_row=row + result.n_components + 1,
end_column=1)
for component_i, component in enumerate(result.components, 1):
write(row, 1, self.tr("C{0}").format(component_i), style=style)
for col, value in enumerate(
component.distribution * component.fraction, 2):
write(row, col, value, style=style)
row += 1
write(row, 1, self.tr("Sum"), style=style)
for col, value in enumerate(result.distribution, 2):
write(row, col, value, style=style)
row += 1
ws_dict = {}
flag_set = set(flags)
for flag in flag_set:
ws = wb.create_sheet(self.tr("Unmixed EM{0}").format(flag + 1))
write(0, 0, self.tr("Sample Name"), style="header")
ws.column_dimensions[column_to_char(0)].width = 16
for col, value in enumerate(classes_μm, 1):
write(0, col, value, style="header")
ws.column_dimensions[column_to_char(col)].width = 10
ws_dict[flag] = ws
flag_index = 0
for row, result in enumerate(results, 1):
if row % 2 == 0:
style = "normal_dark"
else:
style = "normal_light"
for component in result.components:
flag = flags[flag_index]
ws = ws_dict[flag]
write(row, 0, result.sample.name, style=style)
for col, value in enumerate(component.distribution, 1):
write(row, col, value, style=style)
flag_index += 1
wb.save(filename)
wb.close()
def on_save_excel_clicked(self, align_components=False):
if self.n_results == 0:
self.show_warning(self.tr("There is not any SSU result."))
return
filename, _ = self.file_dialog.getSaveFileName(
None, self.tr("Choose a filename to save SSU Results"), None,
"Microsoft Excel (*.xlsx)")
if filename is None or filename == "":
return
try:
self.save_excel(filename, align_components)
self.show_info(
self.tr("SSU results have been saved to:\n {0}").format(
filename))
except Exception as e:
self.show_error(
self.
tr("Error raised while save SSU results to Excel file.\n {0}"
).format(e.__str__()))
def on_fitting_succeeded(self, result: SSUResult):
result_replace_index = self.retry_tasks[result.task.uuid]
self.__fitting_results[result_replace_index] = result
self.retry_tasks.pop(result.task.uuid)
self.retry_progress_msg.setText(
self.tr("Tasks to be retried: {0}").format(len(self.retry_tasks)))
if len(self.retry_tasks) == 0:
self.retry_progress_msg.close()
self.logger.debug(
f"Retried task succeeded, sample name={result.task.sample.name}, distribution_type={result.task.distribution_type.name}, n_components={result.task.n_components}"
)
self.update_page(self.page_index)
def on_fitting_failed(self, failed_info: str, task: SSUTask):
# necessary to remove it from the dict
self.retry_tasks.pop(task.uuid)
if len(self.retry_tasks) == 0:
self.retry_progress_msg.close()
self.show_error(
self.tr("Failed to retry task, sample name={0}.\n{1}").format(
task.sample.name, failed_info))
self.logger.warning(
f"Failed to retry task, sample name={task.sample.name}, distribution_type={task.distribution_type.name}, n_components={task.n_components}"
)
def retry_results(self, indexes, results):
assert len(indexes) == len(results)
if len(results) == 0:
return
self.retry_progress_msg.setText(
self.tr("Tasks to be retried: {0}").format(len(results)))
self.retry_timer.start(1)
for index, result in zip(indexes, results):
query = self.__reference_viewer.query_reference(result.sample)
ref_result = None
if query is None:
nearby_results = self.__fitting_results[
index - 5:index] + self.__fitting_results[index + 1:index +
6]
ref_result = self.__reference_viewer.find_similar(
result.sample, nearby_results)
else:
ref_result = query
keys = ["mean", "std", "skewness"]
# reference = [{key: comp.logarithmic_moments[key] for key in keys} for comp in ref_result.components]
task = SSUTask(
result.sample,
ref_result.distribution_type,
ref_result.n_components,
resolver=ref_result.task.resolver,
resolver_setting=ref_result.task.resolver_setting,
# reference=reference)
initial_guess=ref_result.last_func_args)
self.logger.debug(
f"Retry task: sample name={task.sample.name}, distribution_type={task.distribution_type.name}, n_components={task.n_components}"
)
self.retry_tasks[task.uuid] = index
self.async_worker.execute_task(task)
def degrade_results(self):
degrade_results = [] # type: list[SSUResult]
degrade_indexes = [] # type: list[int]
for i, result in enumerate(self.__fitting_results):
for component in result.components:
if component.fraction < 1e-3:
degrade_results.append(result)
degrade_indexes.append(i)
break
self.logger.debug(
f"Results should be degrade (have a redundant component): {[result.sample.name for result in degrade_results]}"
)
if len(degrade_results) == 0:
self.show_info(
self.tr("No fitting result was evaluated as an outlier."))
return
self.show_info(
self.
tr("The results below should be degrade (have a redundant component:\n {0}"
).format(", ".join(
[result.sample.name for result in degrade_results])))
self.retry_progress_msg.setText(
self.tr("Tasks to be retried: {0}").format(len(degrade_results)))
self.retry_timer.start(1)
for index, result in zip(degrade_indexes, degrade_results):
reference = []
n_redundant = 0
for component in result.components:
if component.fraction < 1e-3:
n_redundant += 1
else:
reference.append(
dict(mean=component.logarithmic_moments["mean"],
std=component.logarithmic_moments["std"],
skewness=component.logarithmic_moments["skewness"]
))
task = SSUTask(
result.sample,
result.distribution_type,
result.n_components -
n_redundant if result.n_components > n_redundant else 1,
resolver=result.task.resolver,
resolver_setting=result.task.resolver_setting,
reference=reference)
self.logger.debug(
f"Retry task: sample name={task.sample.name}, distribution_type={task.distribution_type.name}, n_components={task.n_components}"
)
self.retry_tasks[task.uuid] = index
self.async_worker.execute_task(task)
def ask_deal_outliers(self, outlier_results: typing.List[SSUResult],
outlier_indexes: typing.List[int]):
assert len(outlier_indexes) == len(outlier_results)
if len(outlier_results) == 0:
self.show_info(
self.tr("No fitting result was evaluated as an outlier."))
else:
if len(outlier_results) > 100:
self.outlier_msg.setText(
self.
tr("The fitting results have the component that its fraction is near zero:\n {0}...(total {1} outliers)\nHow to deal with them?"
).format(
", ".join([
result.sample.name
for result in outlier_results[:100]
]), len(outlier_results)))
else:
self.outlier_msg.setText(
self.
tr("The fitting results have the component that its fraction is near zero:\n {0}\nHow to deal with them?"
).format(", ".join([
result.sample.name for result in outlier_results
])))
res = self.outlier_msg.exec_()
if res == QMessageBox.Discard:
self.remove_results(outlier_indexes)
elif res == QMessageBox.Retry:
self.retry_results(outlier_indexes, outlier_results)
else:
pass
def check_nan_and_inf(self):
if self.n_results == 0:
self.show_warning(self.tr("There is not any result in the list."))
return
outlier_results = []
outlier_indexes = []
for i, result in enumerate(self.__fitting_results):
if not result.is_valid:
outlier_results.append(result)
outlier_indexes.append(i)
self.logger.debug(
f"Outlier results with the nan or inf value(s): {[result.sample.name for result in outlier_results]}"
)
self.ask_deal_outliers(outlier_results, outlier_indexes)
def check_final_distances(self):
if self.n_results == 0:
self.show_warning(self.tr("There is not any result in the list."))
return
elif self.n_results < 10:
self.show_warning(self.tr("The results in list are too less."))
return
distances = []
for result in self.__fitting_results:
distances.append(result.get_distance(self.distance_name))
distances = np.array(distances)
self.boxplot_chart.show_dataset([distances],
xlabels=[self.distance_name],
ylabel=self.tr("Distance"))
self.boxplot_chart.show()
# calculate the 1/4, 1/2, and 3/4 postion value to judge which result is invalid
# 1. the mean squared errors are much higher in the results which are lack of components
# 2. with the component number getting higher, the mean squared error will get lower and finally reach the minimum
median = np.median(distances)
upper_group = distances[np.greater(distances, median)]
lower_group = distances[np.less(distances, median)]
value_1_4 = np.median(lower_group)
value_3_4 = np.median(upper_group)
distance_QR = value_3_4 - value_1_4
outlier_results = []
outlier_indexes = []
for i, (result,
distance) in enumerate(zip(self.__fitting_results, distances)):
if distance > value_3_4 + distance_QR * 1.5:
# which error too small is not outlier
# if distance > value_3_4 + distance_QR * 1.5 or distance < value_1_4 - distance_QR * 1.5:
outlier_results.append(result)
outlier_indexes.append(i)
self.logger.debug(
f"Outlier results with too greater distances: {[result.sample.name for result in outlier_results]}"
)
self.ask_deal_outliers(outlier_results, outlier_indexes)
def check_component_moments(self, key: str):
if self.n_results == 0:
self.show_warning(self.tr("There is not any result in the list."))
return
elif self.n_results < 10:
self.show_warning(self.tr("The results in list are too less."))
return
max_n_components = 0
for result in self.__fitting_results:
if result.n_components > max_n_components:
max_n_components = result.n_components
moments = []
for i in range(max_n_components):
moments.append([])
for result in self.__fitting_results:
for i, component in enumerate(result.components):
if np.isnan(component.logarithmic_moments[key]) or np.isinf(
component.logarithmic_moments[key]):
pass
else:
moments[i].append(component.logarithmic_moments[key])
# key_trans = {"mean": self.tr("Mean"), "std": self.tr("STD"), "skewness": self.tr("Skewness"), "kurtosis": self.tr("Kurtosis")}
key_label_trans = {
"mean": self.tr("Mean [φ]"),
"std": self.tr("STD [φ]"),
"skewness": self.tr("Skewness"),
"kurtosis": self.tr("Kurtosis")
}
self.boxplot_chart.show_dataset(
moments,
xlabels=[f"C{i+1}" for i in range(max_n_components)],
ylabel=key_label_trans[key])
self.boxplot_chart.show()
outlier_dict = {}
for i in range(max_n_components):
stacked_moments = np.array(moments[i])
# calculate the 1/4, 1/2, and 3/4 postion value to judge which result is invalid
# 1. the mean squared errors are much higher in the results which are lack of components
# 2. with the component number getting higher, the mean squared error will get lower and finally reach the minimum
median = np.median(stacked_moments)
upper_group = stacked_moments[np.greater(stacked_moments, median)]
lower_group = stacked_moments[np.less(stacked_moments, median)]
value_1_4 = np.median(lower_group)
value_3_4 = np.median(upper_group)
distance_QR = value_3_4 - value_1_4
for j, result in enumerate(self.__fitting_results):
if result.n_components > i:
distance = result.components[i].logarithmic_moments[key]
if distance > value_3_4 + distance_QR * 1.5 or distance < value_1_4 - distance_QR * 1.5:
outlier_dict[j] = result
outlier_results = []
outlier_indexes = []
for index, result in sorted(outlier_dict.items(), key=lambda x: x[0]):
outlier_indexes.append(index)
outlier_results.append(result)
self.logger.debug(
f"Outlier results with abnormal {key} values of their components: {[result.sample.name for result in outlier_results]}"
)
self.ask_deal_outliers(outlier_results, outlier_indexes)
def check_component_fractions(self):
outlier_results = []
outlier_indexes = []
for i, result in enumerate(self.__fitting_results):
for component in result.components:
if component.fraction < 1e-3:
outlier_results.append(result)
outlier_indexes.append(i)
break
self.logger.debug(
f"Outlier results with the component that its fraction is near zero: {[result.sample.name for result in outlier_results]}"
)
self.ask_deal_outliers(outlier_results, outlier_indexes)
def try_align_components(self):
if self.n_results == 0:
self.show_warning(self.tr("There is not any result in the list."))
return
elif self.n_results < 10:
self.show_warning(self.tr("The results in list are too less."))
return
import matplotlib.pyplot as plt
n_components_list = [
result.n_components for result in self.__fitting_results
]
count_dict = Counter(n_components_list)
max_n_components = max(count_dict.keys())
self.logger.debug(
f"N_components: {count_dict}, Max N_components: {max_n_components}"
)
n_components_desc = "\n".join([
self.tr("{0} Component(s): {1}").format(n_components, count)
for n_components, count in count_dict.items()
])
self.show_info(
self.tr("N_components distribution of Results:\n{0}").format(
n_components_desc))
x = self.__fitting_results[0].classes_μm
stacked_components = []
for result in self.__fitting_results:
for component in result.components:
stacked_components.append(component.distribution)
stacked_components = np.array(stacked_components)
cluser = KMeans(n_clusters=max_n_components)
flags = cluser.fit_predict(stacked_components)
figure = plt.figure(figsize=(6, 4))
cmap = plt.get_cmap("tab10")
axes = figure.add_subplot(1, 1, 1)
for flag, distribution in zip(flags, stacked_components):
plt.plot(x, distribution, c=cmap(flag), zorder=flag)
axes.set_xscale("log")
axes.set_xlabel(self.tr("Grain-size [μm]"))
axes.set_ylabel(self.tr("Frequency"))
figure.tight_layout()
figure.show()
outlier_results = []
outlier_indexes = []
flag_index = 0
for i, result in enumerate(self.__fitting_results):
result_flags = set()
for component in result.components:
if flags[flag_index] in result_flags:
outlier_results.append(result)
outlier_indexes.append(i)
break
else:
result_flags.add(flags[flag_index])
flag_index += 1
self.logger.debug(
f"Outlier results that have two components in the same cluster: {[result.sample.name for result in outlier_results]}"
)
self.ask_deal_outliers(outlier_results, outlier_indexes)
def analyse_typical_components(self):
if self.n_results == 0:
self.show_warning(self.tr("There is not any result in the list."))
return
elif self.n_results < 10:
self.show_warning(self.tr("The results in list are too less."))
return
self.typical_chart.show_typical(self.__fitting_results)
self.typical_chart.show()
class ReferenceResultViewer(QDialog):
PAGE_ROWS = 20
logger = logging.getLogger("root.QGrain.ui.ReferenceResultViewer")
def __init__(self, parent=None):
super().__init__(parent=parent, f=Qt.Window)
self.setWindowTitle(self.tr("SSU Reference Result Viewer"))
self.__fitting_results = []
self.__reference_map = {}
self.retry_tasks = {}
self.init_ui()
self.distance_chart = DistanceCurveChart(parent=self, toolbar=True)
self.mixed_distribution_chart = MixedDistributionChart(
parent=self, toolbar=True, use_animation=True)
self.file_dialog = QFileDialog(parent=self)
self.update_page_list()
self.update_page(self.page_index)
self.remove_warning_msg = QMessageBox(self)
self.remove_warning_msg.setStandardButtons(QMessageBox.No
| QMessageBox.Yes)
self.remove_warning_msg.setDefaultButton(QMessageBox.No)
self.remove_warning_msg.setWindowTitle(self.tr("Warning"))
self.remove_warning_msg.setText(
self.tr("Are you sure to remove all SSU results?"))
self.normal_msg = QMessageBox(self)
def init_ui(self):
self.data_table = QTableWidget(100, 100)
self.data_table.setEditTriggers(QAbstractItemView.NoEditTriggers)
self.data_table.setSelectionBehavior(QAbstractItemView.SelectRows)
self.data_table.setAlternatingRowColors(True)
self.data_table.setContextMenuPolicy(Qt.CustomContextMenu)
self.main_layout = QGridLayout(self)
self.main_layout.addWidget(self.data_table, 0, 0, 1, 3)
self.previous_button = QPushButton(
qta.icon("mdi.skip-previous-circle"), self.tr("Previous"))
self.previous_button.setToolTip(
self.tr("Click to back to the previous page."))
self.previous_button.clicked.connect(self.on_previous_button_clicked)
self.current_page_combo_box = QComboBox()
self.current_page_combo_box.addItem(self.tr("Page {0}").format(1))
self.current_page_combo_box.currentIndexChanged.connect(
self.update_page)
self.next_button = QPushButton(qta.icon("mdi.skip-next-circle"),
self.tr("Next"))
self.next_button.setToolTip(self.tr("Click to jump to the next page."))
self.next_button.clicked.connect(self.on_next_button_clicked)
self.main_layout.addWidget(self.previous_button, 1, 0)
self.main_layout.addWidget(self.current_page_combo_box, 1, 1)
self.main_layout.addWidget(self.next_button, 1, 2)
self.distance_label = QLabel(self.tr("Distance"))
self.distance_label.setToolTip(
self.
tr("It's the function to calculate the difference (on the contrary, similarity) between two samples."
))
self.distance_combo_box = QComboBox()
self.distance_combo_box.addItems(built_in_distances)
self.distance_combo_box.setCurrentText("log10MSE")
self.distance_combo_box.currentTextChanged.connect(
lambda: self.update_page(self.page_index))
self.main_layout.addWidget(self.distance_label, 2, 0)
self.main_layout.addWidget(self.distance_combo_box, 2, 1, 1, 2)
self.menu = QMenu(self.data_table)
self.mark_action = self.menu.addAction(
qta.icon("mdi.marker-check"),
self.tr("Mark Selection(s) as Reference"))
self.mark_action.triggered.connect(self.mark_selections)
self.unmark_action = self.menu.addAction(
qta.icon("mdi.do-not-disturb"), self.tr("Unmark Selection(s)"))
self.unmark_action.triggered.connect(self.unmark_selections)
self.remove_action = self.menu.addAction(
qta.icon("fa.remove"), self.tr("Remove Selection(s)"))
self.remove_action.triggered.connect(self.remove_selections)
self.remove_all_action = self.menu.addAction(qta.icon("fa.remove"),
self.tr("Remove All"))
self.remove_all_action.triggered.connect(self.remove_all_results)
self.plot_loss_chart_action = self.menu.addAction(
qta.icon("mdi.chart-timeline-variant"), self.tr("Plot Loss Chart"))
self.plot_loss_chart_action.triggered.connect(self.show_distance)
self.plot_distribution_chart_action = self.menu.addAction(
qta.icon("fa5s.chart-area"), self.tr("Plot Distribution Chart"))
self.plot_distribution_chart_action.triggered.connect(
self.show_distribution)
self.plot_distribution_animation_action = self.menu.addAction(
qta.icon("fa5s.chart-area"),
self.tr("Plot Distribution Chart (Animation)"))
self.plot_distribution_animation_action.triggered.connect(
self.show_history_distribution)
self.load_dump_action = self.menu.addAction(
qta.icon("fa.database"), self.tr("Load Binary Dump"))
self.load_dump_action.triggered.connect(
lambda: self.load_dump(mark_ref=True))
self.save_dump_action = self.menu.addAction(
qta.icon("fa.save"), self.tr("Save Binary Dump"))
self.save_dump_action.triggered.connect(self.save_dump)
self.data_table.customContextMenuRequested.connect(self.show_menu)
def show_menu(self, pos):
self.menu.popup(QCursor.pos())
def show_message(self, title: str, message: str):
self.normal_msg.setWindowTitle(title)
self.normal_msg.setText(message)
self.normal_msg.exec_()
def show_info(self, message: str):
self.show_message(self.tr("Info"), message)
def show_warning(self, message: str):
self.show_message(self.tr("Warning"), message)
def show_error(self, message: str):
self.show_message(self.tr("Error"), message)
@property
def distance_name(self) -> str:
return self.distance_combo_box.currentText()
@property
def distance_func(self) -> typing.Callable:
return get_distance_func_by_name(self.distance_combo_box.currentText())
@property
def page_index(self) -> int:
return self.current_page_combo_box.currentIndex()
@property
def n_pages(self) -> int:
return self.current_page_combo_box.count()
@property
def n_results(self) -> int:
return len(self.__fitting_results)
@property
def selections(self):
start = self.page_index * self.PAGE_ROWS
temp = set()
for item in self.data_table.selectedRanges():
for i in range(item.topRow(),
min(self.PAGE_ROWS + 1,
item.bottomRow() + 1)):
temp.add(i + start)
indexes = list(temp)
indexes.sort()
return indexes
def update_page_list(self):
last_page_index = self.page_index
if self.n_results == 0:
n_pages = 1
else:
n_pages, left = divmod(self.n_results, self.PAGE_ROWS)
if left != 0:
n_pages += 1
self.current_page_combo_box.blockSignals(True)
self.current_page_combo_box.clear()
self.current_page_combo_box.addItems(
[self.tr("Page {0}").format(i + 1) for i in range(n_pages)])
if last_page_index >= n_pages:
self.current_page_combo_box.setCurrentIndex(n_pages - 1)
else:
self.current_page_combo_box.setCurrentIndex(last_page_index)
self.current_page_combo_box.blockSignals(False)
def update_page(self, page_index: int):
def write(row: int, col: int, value: str):
if isinstance(value, str):
pass
elif isinstance(value, int):
value = str(value)
elif isinstance(value, float):
value = f"{value: 0.4f}"
else:
value = value.__str__()
item = QTableWidgetItem(value)
item.setTextAlignment(Qt.AlignCenter)
self.data_table.setItem(row, col, item)
# necessary to clear
self.data_table.clear()
if page_index == self.n_pages - 1:
start = page_index * self.PAGE_ROWS
end = self.n_results
else:
start, end = page_index * self.PAGE_ROWS, (page_index +
1) * self.PAGE_ROWS
self.data_table.setRowCount(end - start)
self.data_table.setColumnCount(8)
self.data_table.setHorizontalHeaderLabels([
self.tr("Resolver"),
self.tr("Distribution Type"),
self.tr("N_components"),
self.tr("N_iterations"),
self.tr("Spent Time [s]"),
self.tr("Final Distance"),
self.tr("Has Reference"),
self.tr("Is Reference")
])
sample_names = [
result.sample.name for result in self.__fitting_results[start:end]
]
self.data_table.setVerticalHeaderLabels(sample_names)
for row, result in enumerate(self.__fitting_results[start:end]):
write(row, 0, result.task.resolver)
write(row, 1,
self.get_distribution_name(result.task.distribution_type))
write(row, 2, result.task.n_components)
write(row, 3, result.n_iterations)
write(row, 4, result.time_spent)
write(
row, 5,
self.distance_func(result.sample.distribution,
result.distribution))
has_ref = result.task.initial_guess is not None or result.task.reference is not None
write(row, 6, self.tr("Yes") if has_ref else self.tr("No"))
is_ref = result.uuid in self.__reference_map
write(row, 7, self.tr("Yes") if is_ref else self.tr("No"))
self.data_table.resizeColumnsToContents()
def on_previous_button_clicked(self):
if self.page_index > 0:
self.current_page_combo_box.setCurrentIndex(self.page_index - 1)
def on_next_button_clicked(self):
if self.page_index < self.n_pages - 1:
self.current_page_combo_box.setCurrentIndex(self.page_index + 1)
def get_distribution_name(self, distribution_type: DistributionType):
if distribution_type == DistributionType.Normal:
return self.tr("Normal")
elif distribution_type == DistributionType.Weibull:
return self.tr("Weibull")
elif distribution_type == DistributionType.SkewNormal:
return self.tr("Skew Normal")
else:
raise NotImplementedError(distribution_type)
def add_result(self, result: SSUResult):
if self.n_results == 0 or \
(self.page_index == self.n_pages - 1 and \
divmod(self.n_results, self.PAGE_ROWS)[-1] != 0):
need_update = True
else:
need_update = False
self.__fitting_results.append(result)
self.update_page_list()
if need_update:
self.update_page(self.page_index)
def add_results(self, results: typing.List[SSUResult]):
if self.n_results == 0 or \
(self.page_index == self.n_pages - 1 and \
divmod(self.n_results, self.PAGE_ROWS)[-1] != 0):
need_update = True
else:
need_update = False
self.__fitting_results.extend(results)
self.update_page_list()
if need_update:
self.update_page(self.page_index)
def mark_results(self, results: typing.List[SSUResult]):
for result in results:
self.__reference_map[result.uuid] = result
self.update_page(self.page_index)
def unmark_results(self, results: typing.List[SSUResult]):
for result in results:
if result.uuid in self.__reference_map:
self.__reference_map.pop(result.uuid)
self.update_page(self.page_index)
def add_references(self, results: typing.List[SSUResult]):
self.add_results(results)
self.mark_results(results)
def mark_selections(self):
results = [
self.__fitting_results[selection] for selection in self.selections
]
self.mark_results(results)
def unmark_selections(self):
results = [
self.__fitting_results[selection] for selection in self.selections
]
self.unmark_results(results)
def remove_results(self, indexes):
results = []
for i in reversed(indexes):
res = self.__fitting_results.pop(i)
results.append(res)
self.unmark_results(results)
self.update_page_list()
self.update_page(self.page_index)
def remove_selections(self):
indexes = self.selections
self.remove_results(indexes)
def remove_all_results(self):
res = self.remove_warning_msg.exec_()
if res == QMessageBox.Yes:
self.__fitting_results.clear()
self.update_page_list()
self.update_page(0)
def show_distance(self):
results = [self.__fitting_results[i] for i in self.selections]
if results is None or len(results) == 0:
return
result = results[0]
self.distance_chart.show_distance_series(result.get_distance_series(
self.distance_name),
title=result.sample.name)
self.distance_chart.show()
def show_distribution(self):
results = [self.__fitting_results[i] for i in self.selections]
if results is None or len(results) == 0:
return
result = results[0]
self.mixed_distribution_chart.show_model(result.view_model)
self.mixed_distribution_chart.show()
def show_history_distribution(self):
results = [self.__fitting_results[i] for i in self.selections]
if results is None or len(results) == 0:
return
result = results[0]
self.mixed_distribution_chart.show_result(result)
self.mixed_distribution_chart.show()
def load_dump(self, mark_ref=False):
filename, _ = self.file_dialog.getOpenFileName(
self, self.tr("Select a binary dump file of SSU results"), None,
self.tr("Binary dump (*.dump)"))
if filename is None or filename == "":
return
with open(filename, "rb") as f:
results = pickle.load(f)
valid = True
if isinstance(results, list):
for result in results:
if not isinstance(result, SSUResult):
valid = False
break
else:
valid = False
if valid:
self.add_results(results)
if mark_ref:
self.mark_results(results)
else:
self.show_error(self.tr("The binary dump file is invalid."))
def save_dump(self):
if self.n_results == 0:
self.show_warning(self.tr("There is not any result in the list."))
return
filename, _ = self.file_dialog.getSaveFileName(
self, self.tr("Save the SSU results to binary dump file"), None,
self.tr("Binary dump (*.dump)"))
if filename is None or filename == "":
return
with open(filename, "wb") as f:
pickle.dump(self.__fitting_results, f)
def find_similar(self, target: GrainSizeSample,
ref_results: typing.List[SSUResult]):
assert len(ref_results) != 0
# sample_moments = logarithmic(sample.classes_φ, sample.distribution)
# keys_to_check = ["mean", "std", "skewness", "kurtosis"]
start_time = time.time()
from scipy.interpolate import interp1d
min_distance = 1e100
min_result = None
trans_func = interp1d(target.classes_φ,
target.distribution,
bounds_error=False,
fill_value=0.0)
for result in ref_results:
# TODO: To scale the classes of result to that of sample
# use moments to calculate? MOMENTS MAY NOT BE PERFECT, MAY IGNORE THE MINOR DIFFERENCE
# result_moments = logarithmic(result.classes_φ, result.distribution)
# distance = sum([(sample_moments[key]-result_moments[key])**2 for key in keys_to_check])
trans_dist = trans_func(result.classes_φ)
distance = self.distance_func(result.distribution, trans_dist)
if distance < min_distance:
min_distance = distance
min_result = result
self.logger.debug(
f"It took {time.time()-start_time:0.4f} s to query the reference from {len(ref_results)} results."
)
return min_result
def query_reference(self, sample: GrainSizeSample):
if len(self.__reference_map) == 0:
self.logger.debug("No result is marked as reference.")
return None
return self.find_similar(sample, self.__reference_map.values())
class QGroundObjectBuyMenu(QDialog):
layout_changed_signal = Signal(QTgoLayout)
def __init__(
self,
parent: QWidget,
ground_object: TheaterGroundObject,
game: Game,
current_group_value: int,
) -> None:
super().__init__(parent)
self.setMinimumWidth(350)
self.setWindowTitle("Buy ground object @ " + ground_object.obj_name)
self.setWindowIcon(EVENT_ICONS["capture"])
self.mainLayout = QGridLayout()
self.setLayout(self.mainLayout)
self.force_group_selector = QComboBox()
self.force_group_selector.setMinimumWidth(250)
self.layout_selector = QComboBox()
self.layout_selector.setMinimumWidth(250)
# Get the layouts and fill the combobox
tasks = []
if isinstance(ground_object, SamGroundObject):
role = GroupRole.AIR_DEFENSE
elif isinstance(ground_object, VehicleGroupGroundObject):
role = GroupRole.GROUND_FORCE
elif isinstance(ground_object, EwrGroundObject):
role = GroupRole.AIR_DEFENSE
tasks.append(GroupTask.EARLY_WARNING_RADAR)
else:
raise NotImplementedError(
f"Unhandled TGO type {ground_object.__class__}")
if not tasks:
tasks = role.tasks
for group in game.blue.armed_forces.groups_for_tasks(tasks):
self.force_group_selector.addItem(group.name, userData=group)
self.force_group_selector.setEnabled(
self.force_group_selector.count() > 1)
self.force_group_selector.adjustSize()
force_group = self.force_group_selector.itemData(
self.force_group_selector.currentIndex())
for layout in force_group.layouts:
self.layout_selector.addItem(layout.name, userData=layout)
self.layout_selector.adjustSize()
self.layout_selector.setEnabled(len(force_group.layouts) > 1)
selected_template = self.layout_selector.itemData(
self.layout_selector.currentIndex())
self.theater_layout = QTgoLayout(selected_template, force_group)
self.layout_selector.currentIndexChanged.connect(self.layout_changed)
self.force_group_selector.currentIndexChanged.connect(
self.force_group_changed)
template_selector_layout = QGridLayout()
template_selector_layout.addWidget(QLabel("Armed Forces Group:"), 0, 0,
Qt.AlignLeft)
template_selector_layout.addWidget(self.force_group_selector,
0,
1,
alignment=Qt.AlignRight)
template_selector_layout.addWidget(QLabel("Layout:"), 1, 0,
Qt.AlignLeft)
template_selector_layout.addWidget(self.layout_selector,
1,
1,
alignment=Qt.AlignRight)
self.mainLayout.addLayout(template_selector_layout, 0, 0)
self.template_layout = QGroundObjectTemplateLayout(
game,
ground_object,
self.theater_layout,
self.layout_changed_signal,
current_group_value,
)
self.template_layout.close_dialog_signal.connect(self.close_dialog)
self.mainLayout.addWidget(self.template_layout, 1, 0)
self.setLayout(self.mainLayout)
def force_group_changed(self) -> None:
# Prevent ComboBox from firing change Events
self.layout_selector.blockSignals(True)
unit_group = self.force_group_selector.itemData(
self.force_group_selector.currentIndex())
self.layout_selector.clear()
for layout in unit_group.layouts:
self.layout_selector.addItem(layout.name, userData=layout)
self.layout_selector.adjustSize()
# Enable if more than one template is available
self.layout_selector.setEnabled(len(unit_group.layouts) > 1)
# Enable Combobox Signals again
self.layout_selector.blockSignals(False)
self.layout_changed()
def layout_changed(self) -> None:
self.layout()
self.theater_layout.layout = self.layout_selector.itemData(
self.layout_selector.currentIndex())
self.theater_layout.force_group = self.force_group_selector.itemData(
self.force_group_selector.currentIndex())
self.layout_changed_signal.emit(self.theater_layout)
def close_dialog(self) -> None:
self.accept()
class FilePathWidget(QWidget):
"""Widget allowing file path selection with a persistent cache.
Users should connect to the path_changed signal.
"""
any_file = 0
existing_file = 1
directory = 2
path_changed = Signal(str)
def __init__(self,
label=None,
file_mode=any_file,
file_filter=None,
name=None,
parent=None):
"""Constructor
:param label: Optional label text.
:param file_mode: Sets the file dialog mode. One of
FilePathWidget.[any_file|existing_file|directory].
:param file_filter: File filter text example 'Python Files (*.py)'.
:param name: Unique name used to query persistent data.
:param parent: Parent QWidget.
"""
super(FilePathWidget, self).__init__(parent)
self.file_mode = file_mode
if file_filter is None:
file_filter = "Any File (*)"
self.file_filter = file_filter
self.cache = StringCache("cmt.filepathwidget.{}".format(name),
parent=self)
self._layout = QHBoxLayout(self)
self._layout.setContentsMargins(0, 0, 0, 0)
self.setLayout(self._layout)
if label:
label = QLabel(label, self)
label.setSizePolicy(QSizePolicy.Fixed, QSizePolicy.Fixed)
self._layout.addWidget(label)
self._combo_box = QComboBox(self)
self._combo_box.setEditable(True)
self._combo_box.setSizePolicy(QSizePolicy.MinimumExpanding,
QSizePolicy.Fixed)
self._combo_box.setInsertPolicy(QComboBox.InsertAtTop)
self._combo_box.setMinimumWidth(50)
self._combo_box.setModel(self.cache)
self._combo_box.editTextChanged.connect(self.edit_changed)
self._layout.addWidget(self._combo_box)
button = QPushButton("Browse", self)
button.released.connect(self.show_dialog)
button.setSizePolicy(QSizePolicy.Fixed, QSizePolicy.Fixed)
self._layout.addWidget(button)
@property
def path(self):
return self._combo_box.currentText()
@path.setter
def path(self, value):
self._combo_box.setEditText(value)
def edit_changed(self, text):
"""Slot called whenever the text changes in the combobox.
:param text: New text.
"""
if not text:
return
text = text.replace("\\", "/")
if (os.path.isfile(text) and self.file_mode != FilePathWidget.directory
) or (os.path.isdir(text)
and self.file_mode == FilePathWidget.directory):
self.path_changed.emit(text)
self._combo_box.blockSignals(True)
self._push(text)
self._combo_box.blockSignals(False)
def show_dialog(self):
"""Show the file browser dialog."""
dialog = QFileDialog(self)
dialog.setNameFilter(self.file_filter)
file_mode = [
QFileDialog.AnyFile,
QFileDialog.ExistingFile,
QFileDialog.Directory,
][self.file_mode]
dialog.setFileMode(file_mode)
dialog.setModal(True)
if self.cache:
dialog.setHistory(self.cache.stringList())
for value in self.cache.stringList():
if os.path.exists(value):
if os.path.isfile(value):
directory = os.path.dirname(value)
dialog.selectFile(value)
else:
directory = value
dialog.setDirectory(directory)
break
if dialog.exec_() == QDialog.Accepted:
path = dialog.selectedFiles()
if path:
self._push(path[0])
def _push(self, path):
"""Push a new path onto the cache.
:param path: Path value.
"""
self.cache.push(path)
self._combo_box.setCurrentIndex(0)
