Source code for pymodaq_gui.plotting.data_viewers.viewer2D

from collections import OrderedDict
import copy
import datetime
import numpy as np
import sys
from typing import Union, Iterable, List, Dict

from qtpy import QtCore, QtGui, QtWidgets
from qtpy.QtCore import QObject, Slot, Signal
import pyqtgraph as pg
from pyqtgraph.graphicsItems.GradientEditorItem import Gradients
from pyqtgraph import ROI as pgROI

from pymodaq_utils import utils
from pymodaq_utils.logger import set_logger, get_module_name

from pymodaq_data.data import (Axis, DataToExport, DataFromRoi, DataRaw,
                               DataDistribution, DataWithAxes)

from pymodaq_gui.managers.roi_manager import ROIManager, DataDim
from pymodaq_gui.plotting.items.roi import SimpleRectROI

from pymodaq_gui.managers.action_manager import ActionManager
from pymodaq_gui.plotting.widgets import ImageWidget
from pymodaq_gui.plotting.data_viewers.viewer import ViewerBase
from pymodaq_gui.plotting.data_viewers.viewer1D import Viewer1D
from pymodaq_gui.plotting.data_viewers.viewer0D import Viewer0D
from pymodaq_gui.plotting.items.image import UniformImageItem, SpreadImageItem
from pymodaq_gui.plotting.items.axis_scaled import AXIS_POSITIONS, AxisItem_Scaled
from pymodaq_gui.plotting.items.crosshair import Crosshair
from pymodaq_gui.plotting.utils.filter import Filter2DFromCrosshair, Filter2DFromRois
from pymodaq_gui.plotting.utils.plot_utils import make_dashed_pens, RoiInfo


logger = set_logger(get_module_name(__file__))

Gradients.update(OrderedDict([
    ('red', {'ticks': [(0.0, (0, 0, 0, 255)), (1.0, (255, 0, 0, 255))], 'mode': 'rgb'}),
    ('green', {'ticks': [(0.0, (0, 0, 0, 255)), (1.0, (0, 255, 0, 255))], 'mode': 'rgb'}),
    ('blue', {'ticks': [(0.0, (0, 0, 0, 255)), (1.0, (0, 0, 255, 255))], 'mode': 'rgb'}),
    ('spread', {'ticks': [(0.0, (0, 0, 0, 255)), (1.0, (255, 255, 255, 255))], 'mode': 'rgb'}),]))

COLORS_DICT = dict(red=(255, 0, 0), green=(0, 255, 0), blue=(0, 0, 255), spread=(128, 128, 128))



IMAGE_TYPES = ['red', 'green', 'blue']
COLOR_LIST = utils.plot_colors
crosshair_pens = make_dashed_pens(color=(255, 255, 0))


[docs] def image_item_factory(item_type='uniform', axisOrder='row-major', pen='r') -> Union[UniformImageItem, SpreadImageItem]: if item_type == 'uniform': image = UniformImageItem(pen=pen) image.setOpts(axisOrder=axisOrder) elif item_type == 'spread': image = SpreadImageItem(pen=pen) image.setCompositionMode(QtGui.QPainter.CompositionMode_Plus) return image
[docs] def histogram_factory(image_item=None, gradient='red'): """ Create a pyqtgraph HistogramLUTWidget widget (histogram) and link it to the corresponding image_item Parameters ---------- image_item: (ImageItem) the image item to be linked with the histogram gradient: (str) either 'red', 'green', 'blue', 'spread' or one of the Gradients Returns ------- HistogramLUTWidget instance """ if gradient not in Gradients: raise KeyError(f'Possible gradient are {Gradients} not {gradient}') histo = pg.HistogramLUTWidget() if image_item is not None: histo.setImageItem(image_item) histo.gradient.loadPreset(gradient) return histo
[docs] class ImageDisplayer(QObject): """ This Object deals with the display of 2D data with a plotitem """ updated_item = Signal(dict) def __init__(self, plotitem, data_distribution: DataDistribution): super().__init__() self._plotitem = plotitem self._plotitem.addLegend() self.show_legend(False) self.display_type = data_distribution self._image_items: dict[str, Union[UniformImageItem, SpreadImageItem]] = dict([]) self._autolevels = False self._levels_sym = False self._data: DataWithAxes = None self.update_display_items()
[docs] def show_legend(self, show=True): self.legend.setVisible(show)
@property def legend(self): return self._plotitem.legend
[docs] def get_images(self): return self._image_items
[docs] def get_image(self, name): if name not in self._image_items: raise KeyError(f'The image {name} is not defined in {self.__class__.__name__}') else: return self._image_items[name]
@property def labels(self): if self._data is None: return [] else: return self._data.labels @property def autolevels(self): return self._autolevels
[docs] def set_autolevels(self, isautolevel: bool): self._autolevels = isautolevel
@property def levels_sym(self) -> bool: return self._levels_sym
[docs] def set_levels_sym(self, levels_sym: bool): self._levels_sym = levels_sym
[docs] def update_data(self, dwa: DataWithAxes): if dwa.labels != self.labels: self.update_display_items(dwa.labels) if dwa.distribution != self.display_type: self.display_type = dwa.distribution self._data = dwa for ind_data, data_array in enumerate(dwa.data): if data_array.size > 0: if self.display_type == 'uniform': self._image_items[IMAGE_TYPES[ind_data]].setImage(data_array, self.autolevels, levels_sym=self.levels_sym) else: nav_axes = dwa.get_nav_axes() data_array = np.stack((nav_axes[0].get_data(), nav_axes[1].get_data(), data_array), axis=0).T self._image_items[IMAGE_TYPES[ind_data]].setImage(data_array, self.autolevels, levels_sym=self.levels_sym)
[docs] def update_display_items(self, labels: List[str] = None): while len(self._image_items) > 0: self._plotitem.removeItem(self._image_items.pop(next(iter(self._image_items)))) if labels is None: labels = [] while len(labels) != len(IMAGE_TYPES): labels.append(IMAGE_TYPES[len(labels)]) for ind, img_key in enumerate(IMAGE_TYPES): self._image_items[img_key] = image_item_factory(self.display_type, pen=img_key[0]) self._plotitem.addItem(self._image_items[img_key]) if ind < len(labels): self.legend.addItem(self._image_items[img_key], labels[ind]) self.updated_item.emit(self._image_items)
[docs] def update_image_visibility(self, are_items_visible): if len(are_items_visible) != len(self._image_items): raise ValueError(f'The length of the argument is not equal with the number of images') for ind, key in enumerate(IMAGE_TYPES): self._image_items[key].setVisible(are_items_visible[ind])
[docs] class Histogrammer(QObject): gradient_changed = Signal() def __init__(self, histogram_container: QtWidgets.QWidget, histogram_refs=IMAGE_TYPES): super().__init__() self._histograms = dict([]) self._histogram_refs = histogram_refs self._histogram_container = histogram_container self.setup_histograms() self._autolevels = False self._levels_sym = False
[docs] def setup_histograms(self): for histo_key in self._histogram_refs: self._histograms[histo_key] = histogram_factory(None, gradient=histo_key) self.add_histogram(self._histograms[histo_key]) self._histograms[histo_key].setVisible(False) self._histograms[histo_key].item.sigLookupTableChanged.connect(lambda: self.gradient_changed.emit())
[docs] def get_histograms(self): return self._histograms
[docs] def get_histogram(self, name): if name not in self.get_histograms(): raise KeyError(f'The histogram {name} is not defined in {self.__class__.__name__}') else: return self._histograms[name]
@property def autolevels(self): return self._autolevels
[docs] @Slot(bool) def set_autolevels(self, isautolevels=True): self._autolevels = isautolevels for histo in self._histograms.values(): histo.region.setVisible(not isautolevels)
[docs] @Slot(bool) def activated(self, histo_action_checked): if histo_action_checked: for histo in self._histograms.values(): histo.regionChanged()
[docs] def affect_histo_to_imageitems(self, image_items): # TODO: if self._histogram_refs doesn't contains the same refs as image_items, we have an issue... for img_key in self._histogram_refs: self._histograms[img_key].setImageItem(image_items[img_key])
[docs] def add_histogram(self, histogram): if self._histogram_container.layout() is None: self._histogram_container.setLayout(QtWidgets.QHBoxLayout()) self._histogram_container.layout().addWidget(histogram)
[docs] def show_hide_histogram(self, checked, are_items_visible): for ind_histo, histo_name in enumerate(self._histogram_refs): self._histograms[histo_name].setVisible(are_items_visible[ind_histo] and checked)
[docs] def set_gradient(self, histo='red', gradient='grey'): """ Change the color gradient of the specified histogram Parameters ---------- histo: (str) either 'red', 'green', 'blue', 'spread' or 'all' gradient: (str or Gradient) """ if gradient in Gradients: if histo == 'all': for key in self._histogram_refs: self._histograms[key].item.gradient.loadPreset(gradient) else: self._histograms[histo].item.gradient.loadPreset(gradient)
[docs] class IsoCurver(QObject): def __init__(self, image_source, histogram_parent): super().__init__() self._histogram_parent = histogram_parent self.setup_iso_curve() self.update_image_source(image_source) self.update_histogram_parent(histogram_parent) self.show_hide_iso(False)
[docs] def setup_iso_curve(self, parent_image_item='red'): # # Isocurve drawing self._isocurve_item = pg.IsocurveItem(level=0.8, pen='g', axisOrder='row-major') self._isocurve_item.setZValue(5) # # Draggable line for setting isocurve level self._isoLine = pg.InfiniteLine(angle=0, movable=True, pen='g') self._isoLine.setValue(0.8) self._isoLine.setZValue(1000) # bring iso line above contrast controls self._isoLine.sigDragged.connect(self.update_isocurve)
[docs] def update_image_source(self, image_source): self._isocurve_item.setParentItem(image_source)
[docs] def update_histogram_parent(self, histogram): if histogram != self._histogram_parent: histogram.vb.removeItem(self._isoLine) self._histogram_parent = histogram histogram.vb.addItem(self._isoLine) histogram.vb.setMouseEnabled(y=False) # makes user interaction a little easier
[docs] def update_isocurve(self): self._isocurve_item.setLevel(self._isoLine.value())
[docs] def set_isocurve_data(self, data): self._isocurve_item.setData(data)
[docs] @Slot(bool) def show_hide_iso(self, show=True): if show: self._isocurve_item.show() self._isoLine.show() else: self._isocurve_item.hide() self._isoLine.hide()
[docs] class View2D(ActionManager, QtCore.QObject): lineout_types = ['hor', 'ver', 'int'] def __init__(self, parent_widget=None): QtCore.QObject.__init__(self) ActionManager.__init__(self, toolbar=QtWidgets.QToolBar()) self.ROIselect = SimpleRectROI([0, 0], [10, 10], centered=True, sideScalers=True) self._lineout_widgets = {widg_key: QtWidgets.QWidget() for widg_key in self.lineout_types} self.lineout_viewers: Dict[str, Viewer1D] = dict(hor=Viewer1D(self._lineout_widgets['hor'], show_toolbar=False, no_margins=True), ver=Viewer1D(self._lineout_widgets['ver'], show_toolbar=False, no_margins=True, flip_axes=True), int=Viewer0D(self._lineout_widgets['int'], show_toolbar=False, no_margins=True)) self.setup_actions() self.parent_widget = parent_widget if self.parent_widget is None: self.parent_widget = QtWidgets.QWidget() self.parent_widget.show() self.image_widget = ImageWidget() self.roi_manager = ROIManager(self.image_widget, DataDim.Data2D) self.roi_target: Union[pgROI, Crosshair] = None self.setup_widgets() self.histogrammer = Histogrammer(self.widget_histo) self.data_displayer: ImageDisplayer = None self.isocurver: IsoCurver = None self.crosshair = Crosshair(self.image_widget) self.connect_things() self.prepare_ui() self.set_axis_label('bottom', label='', units='Pxls') self.set_axis_label('left', label='', units='Pxls') self.set_image_displayer(DataDistribution['uniform'])
[docs] def clear_plot_item(self): for item in self.plotitem.items[:]: if isinstance(item, SpreadImageItem) or isinstance(item, UniformImageItem): self.plotitem.removeItem(item)
[docs] def set_image_displayer(self, data_distribution: DataDistribution): self.clear_plot_item() self.data_displayer = ImageDisplayer(self.plotitem, data_distribution) self.isocurver = IsoCurver(self.data_displayer.get_image('red'), self.histogrammer.get_histogram('red')) self.connect_action('isocurve', self.isocurver.show_hide_iso) self.data_displayer.updated_item.connect(self.histogrammer.affect_histo_to_imageitems) self.connect_action('autolevels', self.data_displayer.set_autolevels) self.connect_action('auto_levels_sym', self.data_displayer.set_levels_sym) for key in IMAGE_TYPES: self.connect_action(key, self.notify_visibility_data_displayer) self.histogrammer.affect_histo_to_imageitems(self.data_displayer.get_images()) if data_distribution.name == 'uniform': self.roi_target = pgROI(pos=(0, 0), size=(20, 20), movable=False, rotatable=False, resizable=False) self.plotitem.addItem(self.roi_target) elif data_distribution.name == 'spread': self.roi_target = Crosshair(self.image_widget, pen=(255, 255, 255)) self.roi_target.setVisible(False)
[docs] def show_roi_target(self, show=True): self.roi_target.setVisible(show)
[docs] def move_scale_roi_target(self, pos=None, size=None): """ Move and scale the target ROI (used to display a particular area, for instance the currently scanned points during a scan Parameters ---------- pos: (iterable) setting the central position of the ROI in the view size: (iterable) setting the size of the ROI """ if isinstance(self.roi_target, pgROI): if size is not None: x_offset, x_scaling, y_offset, y_scaling = self._get_axis_scaling_offset() size = list(np.divide(list(size), [x_scaling, y_scaling])) if list(self.roi_target.size()) != size: self.roi_target.setSize(size, center=(0.5, 0.5)) if pos is not None: pos = self.unscale_axis(*list(pos)) pos = list(pos) if list(self.roi_target.pos()) != pos: self.roi_target.setPos(pos) else: self.roi_target.set_crosshair_position(*list(pos))
[docs] def setup_widgets(self): vertical_layout = QtWidgets.QVBoxLayout() vertical_layout.setContentsMargins(5, 5, 5, 5) self.parent_widget.setLayout(vertical_layout) splitter_vertical = QtWidgets.QSplitter(QtCore.Qt.Vertical) vertical_layout.addWidget(splitter_vertical) splitter_vertical.addWidget(self.toolbar) self.graphs_widget = QtWidgets.QWidget() self.graphs_widget.setLayout(QtWidgets.QHBoxLayout()) self.graphs_widget.layout().setContentsMargins(0, 0, 0, 0) self.setup_graphs(self.graphs_widget.layout()) splitter_vertical.addWidget(self.graphs_widget) self.plotitem.addItem(self.ROIselect) self.splitter_VLeft.splitterMoved[int, int].connect(self.move_right_splitter) self.splitter_VRight.splitterMoved[int, int].connect(self.move_left_splitter) self.splitter_VLeft.setSizes([1, 0]) self.splitter_VRight.setSizes([1, 0])
[docs] def setup_graphs(self, graphs_layout): self.splitter = QtWidgets.QSplitter(QtCore.Qt.Horizontal) graphs_layout.addWidget(self.splitter) self.widget_histo = QtWidgets.QWidget() graphs_layout.addWidget(self.widget_histo) self.widget_histo.setLayout(QtWidgets.QHBoxLayout()) self.splitter_VLeft = QtWidgets.QSplitter(QtCore.Qt.Vertical) self.splitter_VRight = QtWidgets.QSplitter(QtCore.Qt.Vertical) self.splitter.addWidget(self.splitter_VLeft) self.splitter.addWidget(self.splitter_VRight) self.splitter_VLeft.addWidget(self.image_widget) self.splitter_VLeft.addWidget(self._lineout_widgets['hor']) self.splitter_VRight.addWidget(self._lineout_widgets['ver']) self.splitter_VRight.addWidget(self._lineout_widgets['int']) self.image_widget.add_scaled_axis('right') self.image_widget.add_scaled_axis('top') self.image_widget.add_scaled_axis('left') self.image_widget.add_scaled_axis('bottom') self.splitter.addWidget(self.roi_manager.roiwidget) self.roi_manager.roiwidget.setVisible(False)
[docs] def setup_actions(self): self.add_action('position', '(,)') self.add_action('red', 'Red Channel', 'r_icon', tip='Show/Hide Red Channel', checkable=True) self.add_action('green', 'Green Channel', 'g_icon', tip='Show/Hide Green Channel', checkable=True) self.add_action('blue', 'Blue Channel', 'b_icon', tip='Show/Hide Blue Channel', checkable=True) self.get_action('red').setChecked(True) self.get_action('green').setChecked(True) self.get_action('blue').setChecked(True) self.add_action('autolevels', 'AutoLevels', 'autoscale', tip='Scale Histogram to Min/Max intensity', checkable=True) self.add_action('auto_levels_sym', 'AutoLevels Sym.', 'autoscale', tip='Make the autoscale of the histograms symetric with respect to 0', checkable=True) self.add_action('histo', 'Histogram', 'Histogram', tip='Show/Hide Histogram', checkable=True) self.add_action('roi', 'ROI', 'Region', tip='Show/Hide ROI Manager', checkable=True) self.add_action('isocurve', 'IsoCurve', 'meshPlot', tip='Show/Hide Isocurve', checkable=True) self.add_action('aspect_ratio', 'Aspect Ratio', 'Zoom_1_1', tip='Fix Aspect Ratio', checkable=True, checked=True) self.add_action('crosshair', 'CrossHair', 'reset', tip='Show/Hide data Crosshair', checkable=True) self.add_action('ROIselect', 'ROI Select', 'Select_24', tip='Show/Hide ROI selection area', checkable=True) self.add_action('flip_ud', 'Flip UD', 'scale_vertically', tip='Flip the image up/down', checkable=True) self.add_action('flip_lr', 'Flip LR', 'scale_horizontally', tip='Flip the image left/right', checkable=True) self.add_action('rotate', 'Rotate', 'rotation2', tip='Rotate the image', checkable=True) self.add_action('opposite', 'Opposite', 'remove', tip='Take the opposite of the image', checkable=True) self.add_action('legend', 'Legend', 'RGB', tip='Show the legend', checkable=True)
[docs] def update_colors(self, colors: list): for ind, roi_name in enumerate(self.roi_manager.ROIs): self.lineout_viewers['hor'].update_colors(make_dashed_pens(colors[ind]), displayer=roi_name) self.lineout_viewers['ver'].update_colors(make_dashed_pens(colors[ind]), displayer=roi_name) self.lineout_viewers['int'].update_colors(make_dashed_pens(colors[ind]), displayer=roi_name)
[docs] def connect_things(self): self.connect_action('histo', self.histogrammer.activated) self.connect_action('autolevels', self.histogrammer.set_autolevels) self.roi_manager.new_ROI_signal.connect(self.update_roi_channels) self.roi_manager.new_ROI_signal.connect(self.add_roi_displayer) self.roi_manager.new_ROI_signal.connect(self.lineout_viewers['int'].get_action('clear').click) self.roi_manager.remove_ROI_signal.connect(self.remove_roi_displayer) self.roi_manager.color_signal.connect(self.update_colors) self.connect_action('isocurve', self.get_action('histo').trigger) self.connect_action('aspect_ratio', self.lock_aspect_ratio) self.connect_action('histo', self.show_hide_histogram) self.connect_action('roi', self.show_lineout_widgets) self.connect_action('roi', self.roi_clicked) self.connect_action('ROIselect', self.show_ROI_select) self.connect_action('crosshair', self.show_hide_crosshair) self.connect_action('crosshair', self.show_lineout_widgets) self.connect_action('legend', self.show_legend)
[docs] def show_legend(self, show=True): self.data_displayer.show_legend(show)
[docs] @Slot(str) def add_roi_displayer(self, roi_name=''): color = self.roi_manager.ROIs[roi_name].color self.lineout_viewers['hor'].view.add_data_displayer(roi_name, make_dashed_pens(color)) self.lineout_viewers['ver'].view.add_data_displayer(roi_name, make_dashed_pens(color)) self.lineout_viewers['int'].view.add_data_displayer(roi_name, make_dashed_pens(color))
[docs] @Slot(str) def remove_roi_displayer(self, roi_name=''): self.lineout_viewers['hor'].view.remove_data_displayer(roi_name) self.lineout_viewers['ver'].view.remove_data_displayer(roi_name) self.lineout_viewers['int'].view.remove_data_displayer(roi_name)
[docs] @Slot(str) def update_roi_channels(self, roi_name): """Update the use_channel setting each time a ROI is added""" roi = self.roi_manager.get_roi(roi_name) self.roi_manager.update_use_channel(self.data_displayer.labels.copy(),roi.index)
[docs] def prepare_ui(self): self.ROIselect.setVisible(False) self.show_hide_crosshair(False) self.show_lineout_widgets()
[docs] @Slot(DataRaw) def display_images(self, datas): self.data_displayer.update_data(datas) if self.is_action_checked('isocurve'): self.isocurver.set_isocurve_data(datas.data[0])
[docs] def display_roi_lineouts(self, roi_dte: DataToExport): if len(roi_dte) > 0: for lineout_type in self.lineout_types: for displayer_name in self.lineout_viewers[lineout_type].view.other_data_displayers: dwa = roi_dte.get_data_from_name_origin(lineout_type, displayer_name) if dwa is not None: self.lineout_viewers[lineout_type].view.display_data(dwa.deepcopy(), displayer=displayer_name)
[docs] def display_crosshair_lineouts(self, crosshair_dte: DataToExport): for lineout_type in self.lineout_types: dwa = crosshair_dte.get_data_from_name(lineout_type) if dwa is not None: self.lineout_viewers[lineout_type].view.display_data(dwa, displayer='crosshair')
[docs] def show_lineout_widgets(self): state = self.is_action_checked('roi') or self.is_action_checked('crosshair') if state: self.prepare_image_widget_for_lineouts() else: self.prepare_image_widget_for_lineouts(1)
[docs] @Slot(bool) def roi_clicked(self, isroichecked=True): self.roi_manager.roiwidget.setVisible(isroichecked) for k, roi in self.roi_manager.ROIs.items(): roi.setVisible(isroichecked)
[docs] def get_visible_images(self): are_items_visible = [] for key in IMAGE_TYPES: are_items_visible.append(self.is_action_visible(key) and self.is_action_checked(key)) return are_items_visible
[docs] def notify_visibility_data_displayer(self): are_items_visible = self.get_visible_images() self.data_displayer.update_image_visibility(are_items_visible)
[docs] @Slot(bool) def show_hide_histogram(self, show=True): are_items_visible = self.get_visible_images() self.histogrammer.show_hide_histogram(show, are_items_visible)
[docs] def prepare_image_widget_for_lineouts(self, ratio=0.7): QtGui.QGuiApplication.processEvents() self.splitter_VRight.splitterMoved[int, int].emit(int(ratio * self.parent_widget.height()), 1) self.splitter.moveSplitter(int(ratio * self.parent_widget.width()), 1) self.splitter_VLeft.moveSplitter(int(ratio * self.parent_widget.height()), 1) self.splitter_VLeft.splitterMoved[int, int].emit(int(ratio * self.parent_widget.height()), 1) QtGui.QGuiApplication.processEvents()
[docs] def collapse_lineout_widgets(self): self.prepare_image_widget_for_lineouts(ratio=1)
[docs] def get_view_range(self): return self.image_widget.view.viewRange()
[docs] def get_data_at(self, name='red', xy=(0, 0)): return self.data_displayer.get_image(name).get_val_at(xy)
[docs] def lock_aspect_ratio(self): lock = self.is_action_checked('aspect_ratio') x_offset, x_scaling, y_offset, y_scaling = self._get_axis_scaling_offset() ratio = x_scaling / y_scaling self.plotitem.vb.setAspectLocked(lock=lock, ratio=ratio)
[docs] @Slot(int, int) def move_left_splitter(self, pos, index): self.splitter_VLeft.blockSignals(True) self.splitter_VLeft.moveSplitter(pos, index) self.splitter_VLeft.blockSignals(False)
[docs] @Slot(int, int) def move_right_splitter(self, pos, index): self.splitter_VRight.blockSignals(True) self.splitter_VRight.moveSplitter(pos, index) self.splitter_VRight.blockSignals(False)
[docs] def get_double_clicked(self): return self.image_widget.view.sig_double_clicked
[docs] def get_axis(self, position='left') -> AxisItem_Scaled: if position not in AXIS_POSITIONS: raise KeyError(f'{position} is not a possible position for Axis: {AXIS_POSITIONS}') return self.image_widget.getAxis(position)
@property def plotitem(self): return self.image_widget.plotitem
[docs] def get_image_item(self, color='red'): return self.data_displayer.get_image(color)
[docs] def get_crosshair_signal(self): """Convenience function from the Crosshair""" return self.crosshair.crosshair_dragged
[docs] def get_crosshair_position(self): """Convenience function from the Crosshair""" return self.crosshair.get_positions()
[docs] def set_crosshair_position(self, *positions): """Convenience function from the Crosshair""" self.crosshair.set_crosshair_position(*positions)
[docs] @Slot(bool) def show_hide_crosshair(self, show=True): self.crosshair.setVisible(show) self.set_action_visible('position', show) self.crosshair.setVisible(show) if show: self.lineout_viewers['hor'].view.add_data_displayer('crosshair', plot_colors=crosshair_pens) self.lineout_viewers['ver'].view.add_data_displayer('crosshair', plot_colors=crosshair_pens) self.lineout_viewers['int'].view.add_data_displayer('crosshair', plot_colors=crosshair_pens) range = self.get_view_range() self.set_crosshair_position(np.mean(np.array(range[0])), np.mean(np.array(range[0]))) else: self.lineout_viewers['hor'].view.remove_data_displayer('crosshair') self.lineout_viewers['ver'].view.remove_data_displayer('crosshair') self.lineout_viewers['int'].view.remove_data_displayer('crosshair') logger.debug(f'Crosshair visible?: {self.crosshair.isVisible()}')
[docs] def show_ROI_select(self): self.ROIselect.setVisible(self.is_action_checked('ROIselect')) rect = self.data_displayer.get_image('red').boundingRect() self.ROIselect.setPos(rect.center()-QtCore.QPointF(rect.width() * 2 / 3, rect.height() * 2 / 3)/2) self.ROIselect.setSize(rect.size() * 2 / 3)
[docs] def set_image_labels(self, labels: List[str]): if self.data_displayer.labels != labels: action_names =['red', 'green', 'blue'] for action_name, label in zip(action_names[:len(labels)], labels): self.get_action(action_name).setToolTip('Show/Hide' f' - ' f'{label}')
[docs] def set_axis_label(self, position, label='', units=''): """ Convenience method to set label and unit of any view axes Parameters ---------- position: (str) any of AXIS_POSITIONS label: (str) text of the axis label units: (str) units of the axis label """ axis = self.get_axis(position) axis.setLabel(text=label, units=units)
[docs] def get_axis_label(self, position): axis = self.get_axis(position) return axis.axis_label, axis.axis_units
[docs] def set_axis_scaling(self, position='top', scaling=1, offset=0, label='', units='Pxls'): """ Method used to update the scaling of the right and top axes in order to translate pixels to real coordinates Parameters ---------- position: (str) axis position either one of AXIS_POSITIONS scaling: (float) scaling of the axis offset: (float) offset of the axis label: (str) text of the axis label units: (str) units of the axis label """ if scaling is None: scaling = 1 if offset is None: offset = 0 self.get_axis(position).axis_scaling = scaling self.get_axis(position).axis_offset = offset self.set_axis_label(position, label=label, units=units)
[docs] def scale_axis(self, xaxis, yaxis): """scale view coordinates from the regular axes to the scaled/offset ones""" x_offset, x_scaling, y_offset, y_scaling = self._get_axis_scaling_offset() return xaxis * x_scaling + x_offset, yaxis * y_scaling + y_offset
[docs] def unscale_axis(self, xaxis, yaxis): """scale view coordinates from the scaled/offset axes to the regular ones""" x_offset, x_scaling, y_offset, y_scaling = self._get_axis_scaling_offset() return (xaxis - x_offset) / x_scaling, (yaxis - y_offset) / y_scaling
def _get_axis_scaling_offset(self): x_offset = self.get_axis('top').axis_offset x_scaling = self.get_axis('top').axis_scaling y_offset = self.get_axis('right').axis_offset y_scaling = self.get_axis('right').axis_scaling return x_offset, x_scaling, y_offset, y_scaling
[docs] class Viewer2D(ViewerBase): """Object managing plotting and manipulation of 2D data using a View2D""" def __init__(self, parent: QtWidgets.QWidget = None, title=''): super().__init__(parent, title) self.just_init = True self._datas = None self.isdata = dict([]) self._is_gradient_manually_set = False self.view = View2D(parent) self.filter_from_rois = Filter2DFromRois(self.view.roi_manager, self.view.data_displayer.get_image('red'), IMAGE_TYPES) self.filter_from_rois.register_activation_signal(self.view.get_action('roi').triggered) self.filter_from_rois.register_target_slot(self.process_roi_lineouts) self.filter_from_crosshair = Filter2DFromCrosshair(self.view.crosshair, self.view.data_displayer.get_images(), IMAGE_TYPES) self.filter_from_crosshair.register_activation_signal(self.view.get_action('crosshair').triggered) self.filter_from_crosshair.register_target_slot(self.process_crosshair_lineouts) self.prepare_connect_ui() @property def roi_manager(self): """Convenience method """ return self.view.roi_manager @property def roi_target(self) -> pgROI: return self.view.roi_target
[docs] def move_roi_target(self, pos: Iterable[float] = None, size: Iterable[float] = (1, 1)): """move a specific read only ROI at the given position on the viewer""" self.view.move_scale_roi_target(pos, size)
@property def crosshair(self): """Convenience method """ return self.view.crosshair @property def image_widget(self): """Convenience method """ return self.view.image_widget
[docs] def get_data_at(self): """Convenience method """ return self.view.get_data_at()
[docs] def set_crosshair_position(self, xpos, ypos): """Convenience method to set the crosshair positions""" self.view.crosshair.set_crosshair_position(xpos=xpos, ypos=ypos)
[docs] def activate_roi(self, activate=True): """Activate the Roi manager using the corresponding action""" self.view.set_action_checked('roi', activate) self.view.get_action('roi').triggered.emit(activate)
[docs] def roi_changed(self, *args, **kwargs): self.filter_from_rois.filter_data(self._datas)
[docs] def crosshair_changed(self): self.filter_from_crosshair.filter_data(self._datas)
[docs] def set_gradient(self, image_key, gradient): """convenience function""" self.view.histogrammer.set_gradient(image_key, gradient)
def _show_data(self, data: DataWithAxes, *args, **kwargs): """Data to be plotted and eventually filtered using ROI... Parameters ---------- data: DataWithAxes """ if len(data) == 1 and not self._is_gradient_manually_set: self.set_gradient('red', 'grey') if len(data) > 3: logger.warning('Cannot plot on 2D plot more than 3 channels') data.data = data.data[:3] self.view.set_image_labels(data.labels) if data.distribution != self.view.data_displayer.display_type: self.view.set_image_displayer(data.distribution) self.filter_from_crosshair.set_graph_items(self.view.data_displayer.get_images()) self.get_axes_from_view(data) # in case axes were not specified into data, one try to get them from the view self.isdata['red'] = len(data) > 0 self.isdata['green'] = len(data) > 1 self.isdata['blue'] = len(data) > 2 self.update_data() if self.view.is_action_checked('aspect_ratio'): self.view.lock_aspect_ratio() self.set_visible_items() if not self.view.is_action_checked('roi'): self.data_to_export_signal.emit(self.data_to_export) self.autolevels_first()
[docs] def autolevels_first(self): if self.just_init and not self.is_action_checked('autolevels'): self.get_action('autolevels').trigger() self.update_data() self.get_action('autolevels').trigger() self.just_init = False
[docs] def get_axes_from_view(self, data: DataWithAxes): """Obtain axes info from the view Only for uniform data """ if data.distribution == DataDistribution['uniform']: if data.get_axis_from_index(0)[0] is None: axis_view = self.view.get_axis('right') axis = Axis(axis_view.axis_label, units=axis_view.axis_units, scaling=axis_view.axis_scaling, offset=axis_view.axis_offset, index=0) axis.create_linear_data(data.shape[0]) data.axes.append(axis) if data.get_axis_from_index(1)[0] is None: axis_view = self.view.get_axis('top') axis = Axis(axis_view.axis_label, units=axis_view.axis_units, scaling=axis_view.axis_scaling, offset=axis_view.axis_offset, index=1) axis.create_linear_data(data.shape[1]) data.axes.append(axis)
[docs] def update_data(self): if self._raw_data is not None: self._datas = self.set_image_transform() if self._datas.distribution.name == 'uniform': self.x_axis = self._datas.get_axis_from_index(1)[0] self.y_axis = self._datas.get_axis_from_index(0)[0] else: self.x_axis = self._datas.get_axis_from_index(0)[0] self.y_axis = self._datas.get_axis_from_index(0)[1] self.view.display_images(self._datas) if self.view.is_action_checked('roi'): self.roi_changed() if self.view.is_action_checked('crosshair'): self.crosshair_changed()
[docs] def set_image_transform(self) -> DataRaw: """ Deactivate some tool buttons if data type is "spread" then apply transform_image """ data = copy.deepcopy(self._raw_data) self.view.set_action_visible('flip_ud', data.distribution != 'spread') self.view.set_action_visible('flip_lr', data.distribution != 'spread') self.view.set_action_visible('rotate', data.distribution != 'spread') if data.distribution != 'spread': data = self.transform_image(data) return data
[docs] def transform_image(self, dwa: DataWithAxes): if self.view.is_action_checked('flip_ud'): dwa = np.flipud(dwa) if self.view.is_action_checked('flip_lr'): dwa = np.fliplr(dwa) if self.view.is_action_checked('rotate'): dwa = np.flipud(np.transpose(dwa)) if self.view.is_action_checked('opposite'): dwa = -dwa return dwa
[docs] def set_visible_items(self): for key in IMAGE_TYPES: self.view.set_action_visible(key, self.isdata[key]) self.view.notify_visibility_data_displayer()
[docs] def show_roi(self, show=True, show_roi_widget=True): """convenience function to control roi""" if show == (not self.view.is_action_checked('roi')): self.view.get_action('roi').trigger() self.view.roi_manager.roiwidget.setVisible(show_roi_widget)
[docs] def update_crosshair_data(self, crosshair_dte: DataToExport): try: posx, posy = self.view.get_crosshair_position() (posx_scaled, posy_scaled) = self.view.scale_axis(posx, posy) dat = f'({posx_scaled:.1e}{posy_scaled:.1e})\n' dwa_int = crosshair_dte.get_data_from_name('int') if dwa_int is not None: for ind_data in range(len(dwa_int)): dat += f' {dwa_int.labels[ind_data]}:{float(dwa_int[ind_data][0]):.1e}\n' self.view.set_action_text('position', dat) except Exception as e: logger.warning(str(e))
[docs] def prepare_connect_ui(self): self.view.ROIselect.sigRegionChangeFinished.connect(self.selected_region_changed) self.roi_manager.roi_changed.connect(self.roi_changed) self.roi_manager.roi_value_changed.connect(self.roi_changed) self.view.connect_action('flip_ud', slot=self.update_data) self.view.connect_action('flip_lr', slot=self.update_data) self.view.connect_action('rotate', slot=self.update_data) self.view.connect_action('autolevels', slot=self.update_data) self.view.connect_action('auto_levels_sym', slot=self.update_data) self.view.connect_action('opposite', slot=self.update_data) self.view.connect_action('isocurve', slot=self.update_data) self.view.histogrammer.gradient_changed.connect(lambda: setattr(self, '_is_gradient_manually_set', True)) # todo : self.view.lineout_plotter.roi_changed.connect(self.roi_changed) self.view.get_crosshair_signal().connect(self.crosshair_changed) self.view.get_double_clicked().connect(self.double_clicked)
[docs] def selected_region_changed(self): if self.view.is_action_checked('ROIselect'): pos = self.view.ROIselect.pos() size = self.view.ROIselect.size() # self.ROI_select_signal.emit(QtCore.QRectF(pos[0], pos[1], size[0], size[1])) self.roi_select_signal.emit(RoiInfo.info_from_rect_roi(self.view.ROIselect))
[docs] @Slot(float, float) def double_clicked(self, posx, posy): if self.view.is_action_checked('crosshair'): self.view.crosshair.set_crosshair_position(posx, posy) self.crosshair_changed() #scale positions of double_click with respect to real axes posx, posy = self.view.scale_axis(posx, posy) self.sig_double_clicked.emit(posx, posy)
@property def x_axis(self): return self.view.get_axis('top') @x_axis.setter def x_axis(self, axis: Axis = None): if axis is not None: self.view.set_axis_scaling('top', scaling=axis.scaling, offset=axis.offset, label=axis.label, units=axis.units) @property def y_axis(self): return self.view.get_axis('right') @y_axis.setter def y_axis(self, axis: Axis = None): if axis is not None: self.view.set_axis_scaling('right', scaling=axis.scaling, offset=axis.offset, label=axis.label, units=axis.units)
[docs] @Slot(DataToExport) def process_crosshair_lineouts(self, dte): self.view.display_crosshair_lineouts(dte) self.update_crosshair_data(dte) self.crosshair_dragged.emit(*self.view.scale_axis(*self.view.crosshair.get_positions()))
[docs] def process_roi_lineouts(self, roi_dte: DataToExport): if len(roi_dte) > 0: self.view.display_roi_lineouts(roi_dte) roi_dte_bis = roi_dte.deepcopy() for dwa in roi_dte_bis.data: if dwa.name == 'hor': dwa.name = f'Hlineout_{dwa.origin}' elif dwa.name == 'ver': dwa.name = f'Vlineout_{dwa.origin}' elif dwa.name == 'int': dwa.name = f'Integrated_{dwa.origin}' self.data_to_export.append(roi_dte_bis) self.measure_data_dict = dict([]) for roi_name in roi_dte_bis.get_origins(): dwa = roi_dte_bis.get_data_from_name_origin(f'Integrated_{roi_name}', roi_name) for ind, data_array in enumerate(dwa.data): self.measure_data_dict[f'{dwa.labels[ind]}:'] = float(data_array[0]) QtWidgets.QApplication.processEvents() self.view.roi_manager.settings.child('measurements').setValue(self.measure_data_dict) if not self._display_temporary: self.data_to_export_signal.emit(self.data_to_export) self.ROI_changed.emit()
[docs] def main_spread(): app = QtWidgets.QApplication(sys.argv) widget = QtWidgets.QWidget() prog = Viewer2D(widget) widget.show() def print_data(data: DataToExport): print(data) print('******') print(data.get_data_from_dim('Data1D')) prog.data_to_export_signal.connect(print_data) data_spread = np.load('../../../resources/triangulation_data.npy') prog.view.get_action('histo').trigger() prog.view.get_action('autolevels').trigger() prog.show_data(DataRaw(name='mydata', distribution='spread', data=[data_spread], axes=[])) sys.exit(app.exec_())
[docs] def main(data_distribution='uniform'): """either 'uniform' or 'spread'""" app = QtWidgets.QApplication(sys.argv) widget = QtWidgets.QWidget() widget_button = QtWidgets.QWidget() widget_button.setLayout(QtWidgets.QHBoxLayout()) button = QtWidgets.QPushButton('New Data') ndata = QtWidgets.QSpinBox() widget_button.layout().addWidget(button) widget_button.layout().addWidget(ndata) def print_data(data: DataToExport): print(data) print('******') print(data.get_data_from_dim('Data1D')) if data_distribution == 'uniform': data_to_plot = generate_uniform_data() elif data_distribution == 'spread': data_spread = np.load('../../../resources/triangulation_data.npy') data_to_plot = DataRaw(name='mydata', distribution='spread', data=[data_spread[:,2]], nav_indexes=(0,), axes=[Axis('xaxis', units='xpxl', data=data_spread[:,0], index=0, spread_order=0), Axis('yaxis', units='ypxl', data=data_spread[:,1], index=0, spread_order=1),]) prog = Viewer2D(widget) widget.show() prog.data_to_export_signal.connect(print_data) prog.view.get_action('histo').trigger() prog.view.get_action('autolevels').trigger() prog.show_data(data_to_plot) prog.view.show_roi_target(True) prog.view.move_scale_roi_target((50, 40), (10, 20)) button.clicked.connect(lambda: plot_data(prog, ndata.value())) widget_button.show() QtWidgets.QApplication.processEvents() sys.exit(app.exec_())
[docs] def generate_uniform_data() -> DataRaw: from pymodaq_utils.math_utils import gauss2D Nx = 100 Ny = 2 * Nx data_random = np.random.normal(size=(Ny, Nx)) x = 0.5 * np.linspace(-Nx / 2, Nx / 2 - 1, Nx) y = 0.2 * np.linspace(-Ny / 2, Ny / 2 - 1, Ny) x0 = 5 data_red = 3 * np.cos((x-x0) / 5) * gauss2D(x, x0, Nx / 10, y, -1, Ny / 10, 1, 90) + 0.5 * data_random data_red[data_red < -2] = np.nan data_green = 10 * gauss2D(x, -20, Nx / 10, y, -10, Ny / 20, 1, 0) data_green[70:80, 7:12] = np.nan data_to_plot = DataRaw(name='mydata', distribution='uniform', data=[data_red, data_green, data_red-data_green], labels = ['myreddata', 'mygreendata'], axes=[Axis('xaxis', units='xpxl', data=x, index=1), Axis('yaxis', units='ypxl', data=y, index=0), ]) return data_to_plot
[docs] def plot_data(viewer2D: Viewer2D, ndata: int = 2): if ndata > 0: dwa = generate_uniform_data() dwa.data = dwa.data[0:ndata] viewer2D.show_data(dwa)
[docs] def main_view(): app = QtWidgets.QApplication(sys.argv) form = QtWidgets.QWidget() prog = View2D(form) form.show() sys.exit(app.exec_())
if __name__ == '__main__': # pragma: no cover #main_view() main('uniform') #main('spread')