import sys import itertools import warnings from typing import Callable from xml.sax.saxutils import escape from datetime import datetime, timezone import numpy as np from AnyQt.QtCore import Qt, QRectF, QSize, QTimer, pyqtSignal as Signal, \ QObject, QEvent from AnyQt.QtGui import QColor, QPen, QBrush, QPainterPath, QTransform, \ QPainter, QPalette from AnyQt.QtWidgets import QApplication, QToolTip, QGraphicsTextItem, \ QGraphicsRectItem, QGraphicsItemGroup import pyqtgraph as pg from pyqtgraph.graphicsItems.ScatterPlotItem import Symbols from pyqtgraph.graphicsItems.LegendItem import LegendItem as PgLegendItem from pyqtgraph.graphicsItems.TextItem import TextItem from Orange.preprocess.discretize import _time_binnings from Orange.util import utc_from_timestamp from Orange.widgets import gui from Orange.widgets.settings import Setting from Orange.widgets.utils import classdensity, colorpalettes from Orange.widgets.visualize.utils.customizableplot import Updater, \ CommonParameterSetter from Orange.widgets.visualize.utils.plotutils import ( HelpEventDelegate as EventDelegate, InteractiveViewBox as ViewBox, PaletteItemSample, SymbolItemSample, AxisItem, PlotWidget, DiscretizedScale ) SELECTION_WIDTH = 5 MAX_N_VALID_SIZE_ANIMATE = 1000 # maximum number of colors (including Other) MAX_COLORS = 11 class LegendItem(PgLegendItem): items = [] # Accessed in changeEvent after delete in tests?? def __init__( self, size=None, offset=None, pen=None, brush=None, ): super().__init__(size, offset) self.items = [] self.layout.setContentsMargins(5, 5, 5, 5) self.layout.setHorizontalSpacing(15) self.layout.setColumnAlignment(1, Qt.AlignLeft | Qt.AlignVCenter) if pen is not None: pen = QPen(pen) if brush is not None: brush = QBrush(brush) self.__pen = pen self.__brush = brush def restoreAnchor(self, anchors): """ Restore (parent) relative position from stored anchors. The restored position is within the parent bounds. """ anchor, parentanchor = anchors self.anchor(*bound_anchor_pos(anchor, parentanchor)) # pylint: disable=arguments-differ def paint(self, painter, _option, _widget=None): painter.setPen(self.pen()) painter.setBrush(self.brush()) rect = self.contentsRect() painter.drawRoundedRect(rect, 2, 2) def addItem(self, item, name): super().addItem(item, name) # Fix-up the label alignment, and color color = self.palette().color(QPalette.Text) _, label = self.items[-1] label.setText(name, justify="left", color=color) def clear(self): """ Clear all legend items. """ items = list(self.items) self.items = [] for sample, label in items: self.layout.removeItem(sample) self.layout.removeItem(label) sample.hide() label.hide() self.updateSize() def pen(self): if self.__pen is not None: return QPen(self.__pen) else: color = self.palette().color(QPalette.Disabled, QPalette.Text) color.setAlpha(100) pen = QPen(color, 1) pen.setCosmetic(True) return pen def brush(self): if self.__brush is not None: return QBrush(self.__brush) else: color = self.palette().color(QPalette.Window) color.setAlpha(150) return QBrush(color) def changeEvent(self, event: QEvent): if event.type() == QEvent.PaletteChange: color = self.palette().color(QPalette.Text) for _, label in self.items: label.setText(label.text, color=color) super().changeEvent(event) def bound_anchor_pos(corner, parentpos): corner = np.clip(corner, 0, 1) parentpos = np.clip(parentpos, 0, 1) irx, iry = corner prx, pry = parentpos if irx > 0.9 and prx < 0.1: irx = prx = 0.0 if iry > 0.9 and pry < 0.1: iry = pry = 0.0 if irx < 0.1 and prx > 0.9: irx = prx = 1.0 if iry < 0.1 and pry > 0.9: iry = pry = 1.0 return (irx, iry), (prx, pry) class ScatterPlotItem(pg.ScatterPlotItem): """ Modifies the behaviour of ScatterPlotItem as follows: - Add z-index. ScatterPlotItem paints points in order of appearance in self.data. Plotting by z-index is achieved by sorting before calling super().paint() and re-sorting afterwards. Re-sorting (instead of storing the original data) is needed because the inherited paint may modify the data. - Prevent multiple calls to updateSpots. ScatterPlotItem calls updateSpots at any change of sizes/colors/symbols, which then rebuilds the stored pixmaps for each symbol. Orange calls set* functions in succession, so we postpone updateSpots() to paint().""" def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) self._update_spots_in_paint = False self._z_mapping = None self._inv_mapping = None def setZ(self, z): """ Set z values for all points. Points with higher values are plotted on top of those with lower. Args: z (np.ndarray or None): a vector of z values """ if z is None: self._z_mapping = self._inv_mapping = None else: assert len(z) == len(self.data) self._z_mapping = np.argsort(z) self._inv_mapping = np.argsort(self._z_mapping) def setCoordinates(self, x, y): """ Change the coordinates of points while keeping other properties. Asserts that the number of points stays the same. Note. Pyqtgraph does not offer a method for this: setting coordinates invalidates other data. We therefore retrieve the data to set it together with the coordinates. Pyqtgraph also does not offer a (documented) method for retrieving the data, yet using data[prop]` looks reasonably safe. The alternative, updating the whole scatterplot from the Orange Table, is too slow. """ assert len(self.data) == len(x) == len(y) data = dict(x=x, y=y) for prop in ('pen', 'brush', 'size', 'symbol', 'data'): data[prop] = self.data[prop] self.setData(**data) def updateSpots(self, dataSet=None): # pylint: disable=unused-argument self._update_spots_in_paint = True self.update() # pylint: disable=arguments-differ def paint(self, painter, option, widget=None): try: if self._z_mapping is not None: assert len(self._z_mapping) == len(self.data) self.data = self.data[self._z_mapping] if self._update_spots_in_paint: self._update_spots_in_paint = False super().updateSpots() painter.setRenderHint(QPainter.SmoothPixmapTransform, True) super().paint(painter, option, widget) finally: if self._inv_mapping is not None: self.data = self.data[self._inv_mapping] def _define_symbols(): """ Add symbol ? to ScatterPlotItemSymbols, reflect the triangle to point upwards """ path = QPainterPath() path.addEllipse(QRectF(-0.35, -0.35, 0.7, 0.7)) path.moveTo(-0.5, 0.5) path.lineTo(0.5, -0.5) path.moveTo(-0.5, -0.5) path.lineTo(0.5, 0.5) Symbols["?"] = path path = QPainterPath() plusCoords = [ (-0.5, -0.1), (-0.5, 0.1), (-0.1, 0.1), (-0.1, 0.5), (0.1, 0.5), (0.1, 0.1), (0.5, 0.1), (0.5, -0.1), (0.1, -0.1), (0.1, -0.5), (-0.1, -0.5), (-0.1, -0.1) ] path.moveTo(*plusCoords[0]) for x, y in plusCoords[1:]: path.lineTo(x, y) path.closeSubpath() Symbols["+"] = path tr = QTransform() tr.rotate(180) Symbols['t'] = tr.map(Symbols['t']) tr = QTransform() tr.rotate(45) Symbols['x'] = tr.map(Symbols["+"]) _define_symbols() def _make_pen(color, width): p = QPen(color, width) p.setCosmetic(True) return p class AxisItem(AxisItem): """ Axis that if needed displays ticks appropriate for time data. """ _label_width = 80 def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) self._use_time = False def use_time(self, enable): """Enables axes to display ticks for time data.""" self._use_time = enable self.enableAutoSIPrefix(not enable) def is_time(self): return self._use_time def tickValues(self, minVal, maxVal, size): """Find appropriate tick locations.""" if not self._use_time: return super().tickValues(minVal, maxVal, size) # if timezone is not set, then local is used which cause exceptions minVal = max(minVal, datetime.min.replace(tzinfo=timezone.utc).timestamp() + 1) maxVal = min(maxVal, datetime.max.replace(tzinfo=timezone.utc).timestamp() - 1) mn = utc_from_timestamp(minVal).timetuple() mx = utc_from_timestamp(maxVal).timetuple() try: bins = _time_binnings(mn, mx, 6, 30)[-1] except (IndexError, ValueError): # cannot handle very large and very small time intervals return super().tickValues(minVal, maxVal, size) ticks = bins.thresholds # Remove ticks that will later be removed in AxisItem.generateDrawSpecs # because they are out of range. Removing them here is needed so that # they do not affect spaces and label format ticks = ticks[int((ticks[0] < minVal)) :len(ticks) - int((ticks[-1] > maxVal))] max_steps = max(int(size / self._label_width), 1) if len(ticks) > max_steps: # remove some of ticks so that they don't overlap step = int(np.ceil(float(len(ticks)) / max_steps)) ticks = ticks[::step] # In case of a single tick, `default` will inform tickStrings # about the appropriate scale. spacing = min((b - a for a, b in zip(ticks[:-1], ticks[1:])), default=maxVal - minVal) return [(spacing, ticks)] def tickStrings(self, values, scale, spacing): """Format tick values according to space between them.""" if not self._use_time: return super().tickStrings(values, scale, spacing) if spacing >= 3600 * 24 * 365: fmt = "%Y" elif spacing >= 3600 * 24 * 28: fmt = "%Y %b" elif spacing >= 3600 * 24: fmt = "%Y %b %d" elif spacing >= 3600: min_day = max_day = 1 if len(values) > 0: min_day = datetime.fromtimestamp( min(values), tz=timezone.utc).day max_day = datetime.fromtimestamp( max(values), tz=timezone.utc).day if min_day == max_day: fmt = "%Hh" else: fmt = "%d %Hh" elif spacing >= 60: fmt = "%H:%M" elif spacing >= 1: fmt = "%H:%M:%S" else: fmt = '%S.%f' return [utc_from_timestamp(x).strftime(fmt) for x in values] class ScatterBaseParameterSetter(CommonParameterSetter): CAT_LEGEND_LABEL = "Categorical legend" NUM_LEGEND_LABEL = "Numerical legend" NUM_LEGEND_SETTING = { Updater.SIZE_LABEL: (range(4, 50), 11), Updater.IS_ITALIC_LABEL: (None, False), } def __init__(self, master): super().__init__() self.master = master self.cat_legend_settings = {} self.num_legend_settings = {} def update_setters(self): self.initial_settings = { self.LABELS_BOX: { self.FONT_FAMILY_LABEL: self.FONT_FAMILY_SETTING, self.TITLE_LABEL: self.FONT_SETTING, self.LABEL_LABEL: self.FONT_SETTING, self.CAT_LEGEND_LABEL: self.FONT_SETTING, self.NUM_LEGEND_LABEL: self.NUM_LEGEND_SETTING, }, self.ANNOT_BOX: { self.TITLE_LABEL: {self.TITLE_LABEL: ("", "")}, } } def update_cat_legend(**settings): self.cat_legend_settings.update(**settings) Updater.update_legend_font(self.cat_legend_items, **settings) def update_num_legend(**settings): self.num_legend_settings.update(**settings) Updater.update_num_legend_font(self.num_legend, **settings) labels = self.LABELS_BOX self._setters[labels][self.CAT_LEGEND_LABEL] = update_cat_legend self._setters[labels][self.NUM_LEGEND_LABEL] = update_num_legend @property def title_item(self): return self.master.plot_widget.getPlotItem().titleLabel @property def cat_legend_items(self): items = self.master.color_legend.items if items and items[0] and isinstance(items[0][0], PaletteItemSample): items = [] return itertools.chain(self.master.shape_legend.items, items) @property def num_legend(self): items = self.master.color_legend.items if items and items[0] and isinstance(items[0][0], PaletteItemSample): return self.master.color_legend return None @property def labels(self): return self.master.labels class OWScatterPlotBase(gui.OWComponent, QObject): """ Provide a graph component for widgets that show any kind of point plot The component plots a set of points with given coordinates, shapes, sizes and colors. Its function is similar to that of a *view*, whereas the widget represents a *model* and a *controler*. The model (widget) needs to provide methods: - `get_coordinates_data`, `get_size_data`, `get_color_data`, `get_shape_data`, `get_label_data`, which return a 1d array (or two arrays, for `get_coordinates_data`) of `dtype` `float64`, except for `get_label_data`, which returns formatted labels; - `get_shape_labels` returns a list of strings for shape legend - `get_color_labels` returns strings for color legend, or a function for formatting numbers if the legend is continuous, or None for default formatting - `get_tooltip`, which gives a tooltip for a single data point - (optional) `impute_sizes`, `impute_shapes` get final coordinates and shapes, and replace nans; - `get_subset_mask` returns a bool array indicating whether a data point is in the subset or not (e.g. in the 'Data Subset' signal in the Scatter plot and similar widgets); - `get_palette` returns a palette appropriate for visualizing the current color data; - `is_continuous_color` decides the type of the color legend; The widget (in a role of controller) must also provide methods - `selection_changed` If `get_coordinates_data` returns `(None, None)`, the plot is cleared. If `get_size_data`, `get_color_data` or `get_shape_data` return `None`, all points will have the same size, color or shape, respectively. If `get_label_data` returns `None`, there are no labels. The view (this compomnent) provides methods `update_coordinates`, `update_sizes`, `update_colors`, `update_shapes` and `update_labels` that the widget (in a role of a controler) should call when any of these properties are changed. If the widget calls, for instance, the plot's `update_colors`, the plot will react by calling the widget's `get_color_data` as well as the widget's methods needed to construct the legend. The view also provides a method `reset_graph`, which should be called only when - the widget gets entirely new data - the number of points may have changed, for instance when selecting a different attribute for x or y in the scatter plot, where the points with missing x or y coordinates are hidden. Every `update_something` calls the plot's `get_something`, which calls the model's `get_something_data`, then it transforms this data into whatever is needed (colors, shapes, scaled sizes) and changes the plot. For the simplest example, here is `update_shapes`: ``` def update_shapes(self): if self.scatterplot_item: shape_data = self.get_shapes() self.scatterplot_item.setSymbol(shape_data) self.update_legends() def get_shapes(self): shape_data = self.master.get_shape_data() shape_data = self.master.impute_shapes( shape_data, len(self.CurveSymbols) - 1) return self.CurveSymbols[shape_data] ``` On the widget's side, `get_something_data` is essentially just: ``` def get_size_data(self): return self.get_column(self.attr_size) ``` where `get_column` retrieves a column while also filtering out the points with missing x and y and so forth. (Here we present the simplest two cases, "shapes" for the view and "sizes" for the model. The colors for the view are more complicated since they deal with discrete and continuous palettes, and the shapes for the view merge infrequent shapes.) The plot can also show just a random sample of the data. The sample size is set by `set_sample_size`, and the rest is taken care by the plot: the widget keeps providing the data for all points, selection indices refer to the entire set etc. Internally, sampling happens as early as possible (in methods `get_`). """ too_many_labels = Signal(bool) begin_resizing = Signal() step_resizing = Signal() end_resizing = Signal() label_only_selected = Setting(False) point_width = Setting(10) alpha_value = Setting(128) show_grid = Setting(False) show_legend = Setting(True) class_density = Setting(False) jitter_size = Setting(0) resolution = 256 CurveSymbols = np.array("o x t + d star ?".split()) MinShapeSize = 6 DarkerValue = 120 UnknownColor = (168, 50, 168) COLOR_DEFAULT = (128, 128, 128) MAX_VISIBLE_LABELS = 500 def __init__(self, scatter_widget, parent=None, view_box=ViewBox): QObject.__init__(self) gui.OWComponent.__init__(self, scatter_widget) self.subset_is_shown = False self.jittering_suspended = False self.view_box = view_box(self) _axis = {"left": AxisItem("left"), "bottom": AxisItem("bottom")} self.plot_widget = PlotWidget( viewBox=self.view_box, parent=parent, background=None, axisItems=_axis ) self.plot_widget.hideAxis("left") self.plot_widget.hideAxis("bottom") self.plot_widget.getPlotItem().buttonsHidden = True self.plot_widget.setAntialiasing(True) self.plot_widget.sizeHint = lambda: QSize(500, 500) self.density_img = None self.scatterplot_item = None self.scatterplot_item_sel = None self.labels = [] self.master = scatter_widget tooltip = self._create_drag_tooltip() self.view_box.setDragTooltip(tooltip) self.selection = None # np.ndarray self.n_valid = 0 self.n_shown = 0 self.sample_size = None self.sample_indices = None self.palette = None self.shape_legend = self._create_legend(((1, 0), (1, 0))) self.color_legend = self._create_legend(((1, 1), (1, 1))) self.update_legend_visibility() self.scale = None # DiscretizedScale self._too_many_labels = False # self.setMouseTracking(True) # self.grabGesture(QPinchGesture) # self.grabGesture(QPanGesture) self.update_grid_visibility() self._tooltip_delegate = EventDelegate(self.help_event) self.plot_widget.scene().installEventFilter(self._tooltip_delegate) self.view_box.sigTransformChanged.connect(self.update_density) self.view_box.sigRangeChangedManually.connect(self.update_labels) self.timer = None self.parameter_setter = ScatterBaseParameterSetter(self) def _create_legend(self, anchor): legend = LegendItem() legend.setParentItem(self.plot_widget.getViewBox()) legend.restoreAnchor(anchor) return legend def _create_drag_tooltip(self): tip_parts = [ (Qt.ControlModifier, "{}: Append to group". format("Cmd" if sys.platform == "darwin" else "Ctrl")), (Qt.ShiftModifier, "Shift: Add group"), (Qt.AltModifier, "Alt: Remove") ] all_parts = "
" + \ ", ".join(part for _, part in tip_parts) + \ "
" self.tiptexts = { modifier: all_parts.replace(part, "{}".format(part)) for modifier, part in tip_parts } self.tiptexts[Qt.NoModifier] = all_parts self.tip_textitem = text = QGraphicsTextItem() # Set to the longest text text.setHtml(self.tiptexts[Qt.ControlModifier]) text.setPos(4, 2) r = text.boundingRect() text.setTextWidth(r.width()) rect = QGraphicsRectItem(0, 0, r.width() + 8, r.height() + 4) color = self.plot_widget.palette().color(QPalette.Disabled, QPalette.Window) color.setAlpha(212) rect.setBrush(color) rect.setPen(QPen(Qt.NoPen)) self.update_tooltip() tooltip_group = QGraphicsItemGroup() tooltip_group.addToGroup(rect) tooltip_group.addToGroup(text) return tooltip_group def update_tooltip(self, modifiers=Qt.NoModifier): text = self.tiptexts[Qt.NoModifier] for mod in [Qt.ControlModifier, Qt.ShiftModifier, Qt.AltModifier]: if modifiers & mod: text = self.tiptexts.get(mod) break self.tip_textitem.setHtml(text) def suspend_jittering(self): if self.jittering_suspended: return self.jittering_suspended = True if self.jitter_size != 0: self.update_jittering() def unsuspend_jittering(self): if not self.jittering_suspended: return self.jittering_suspended = False if self.jitter_size != 0: self.update_jittering() def update_jittering(self): x, y = self.get_coordinates() if x is None or len(x) == 0 or self.scatterplot_item is None: return self.scatterplot_item.setCoordinates(x, y) self.scatterplot_item_sel.setCoordinates(x, y) self.update_labels() # TODO: Rename to remove_plot_items def clear(self): """ Remove all graphical elements from the plot Calls the pyqtgraph's plot widget's clear, sets all handles to `None`, removes labels and selections. This method should generally not be called by the widget. If the data is gone (*e.g.* upon receiving `None` as an input data signal), this should be handler by calling `reset_graph`, which will in turn call `clear`. Derived classes should override this method if they add more graphical elements. For instance, the regression line in the scatterplot adds `self.reg_line_item = None` (the line in the plot is already removed in this method). """ self.plot_widget.clear() self.density_img = None if self.timer is not None and self.timer.isActive(): self.timer.stop() self.timer = None self.scatterplot_item = None self.scatterplot_item_sel = None self.labels = [] self._signal_too_many_labels(False) self.view_box.init_history() self.view_box.tag_history() # TODO: I hate `keep_something` and `reset_something` arguments # __keep_selection is used exclusively be set_sample size which would # otherwise just repeat the code from reset_graph except for resetting # the selection. I'm uncomfortable with this; we may prefer to have a # method _reset_graph which does everything except resetting the selection, # and reset_graph would call it. def reset_graph(self, __keep_selection=False): """ Reset the graph to new data (or no data) The method must be called when the plot receives new data, in particular when the number of points change. If only their properties - like coordinates or shapes - change, an update method (`update_coordinates`, `update_shapes`...) should be called instead. The method must also be called when the data is gone. The method calls `clear`, followed by calls of all update methods. NB. Argument `__keep_selection` is for internal use only """ self.clear() if not __keep_selection: self.selection = None self.sample_indices = None self.update_coordinates() self.update_point_props() def set_sample_size(self, sample_size): """ Set the sample size Args: sample_size (int or None): sample size or `None` to show all points """ if self.sample_size != sample_size: self.sample_size = sample_size self.reset_graph(True) def update_point_props(self): """ Update the sizes, colors, shapes and labels The method calls the appropriate update methods for individual properties. """ self.update_sizes() self.update_colors() self.update_selection_colors() self.update_shapes() self.update_labels() # Coordinates # TODO: It could be nice if this method was run on entire data, not just # a sample. For this, however, it would need to either be called from # `get_coordinates` before sampling (very ugly) or call # `self.master.get_coordinates_data` (beyond ugly) or the widget would # have to store the ranges of unsampled data (ugly). # Maybe we leave it as it is. def _reset_view(self, x_data, y_data): """ Set the range of the view box Args: x_data (np.ndarray): x coordinates y_data (np.ndarray) y coordinates """ min_x, max_x = np.min(x_data), np.max(x_data) min_y, max_y = np.min(y_data), np.max(y_data) self.view_box.setRange( QRectF(min_x, min_y, max_x - min_x or 1, max_y - min_y or 1), padding=0.025) def _filter_visible(self, data): """Return the sample from the data using the stored sample_indices""" if data is None or self.sample_indices is None: return data else: return np.asarray(data[self.sample_indices]) def get_coordinates(self): """ Prepare coordinates of the points in the plot The method is called by `update_coordinates`. It gets the coordinates from the widget, jitters them and return them. The methods also initializes the sample indices if neededd and stores the original and sampled number of points. Returns: (tuple): a pair of numpy arrays containing (sampled) coordinates, or `(None, None)`. """ x, y = self.master.get_coordinates_data() if x is None: self.n_valid = self.n_shown = 0 return None, None self.n_valid = len(x) self._create_sample() x = self._filter_visible(x) y = self._filter_visible(y) # Jittering after sampling is OK if widgets do not change the sample # semi-permanently, e.g. take a sample for the duration of some # animation. If the sample size changes dynamically (like by adding # a "sample size" slider), points would move around when the sample # size changes. To prevent this, jittering should be done before # sampling (i.e. two lines earlier). This would slow it down somewhat. x, y = self.jitter_coordinates(x, y) return x, y def _create_sample(self): """ Create a random sample if the data is larger than the set sample size """ self.n_shown = min(self.n_valid, self.sample_size or self.n_valid) if self.sample_size is not None \ and self.sample_indices is None \ and self.n_valid != self.n_shown: random = np.random.RandomState(seed=0) self.sample_indices = random.choice( self.n_valid, self.n_shown, replace=False) # TODO: Is this really needed? np.sort(self.sample_indices) def jitter_coordinates(self, x, y): """ Display coordinates to random positions within ellipses with radiuses of `self.jittter_size` percents of spans """ if self.jitter_size == 0 or self.jittering_suspended: return x, y return self._jitter_data(x, y) def _jitter_data(self, x, y, span_x=None, span_y=None): if span_x is None: span_x = np.max(x) - np.min(x) if span_y is None: span_y = np.max(y) - np.min(y) random = np.random.RandomState(seed=0) rs = random.uniform(0, 1, len(x)) phis = random.uniform(0, 2 * np.pi, len(x)) magnitude = self.jitter_size / 100 return (x + magnitude * span_x * rs * np.cos(phis), y + magnitude * span_y * rs * np.sin(phis)) def update_coordinates(self): """ Trigger the update of coordinates while keeping other features intact. The method gets the coordinates by calling `self.get_coordinates`, which in turn calls the widget's `get_coordinate_data`. The number of coordinate pairs returned by the latter must match the current number of points. If this is not the case, the widget should trigger the complete update by calling `reset_graph` instead of this method. """ x, y = self.get_coordinates() if x is None or len(x) == 0: return self._reset_view(x, y) if self.scatterplot_item is None: if self.sample_indices is None: indices = np.arange(self.n_valid) else: indices = self.sample_indices kwargs = dict(x=x, y=y, data=indices) self.scatterplot_item = ScatterPlotItem(**kwargs) self.scatterplot_item.sigClicked.connect(self.select_by_click) self.scatterplot_item_sel = ScatterPlotItem(**kwargs) self.plot_widget.addItem(self.scatterplot_item_sel) self.plot_widget.addItem(self.scatterplot_item) else: self.scatterplot_item.setCoordinates(x, y) self.scatterplot_item_sel.setCoordinates(x, y) self.update_labels() self.update_density() # Todo: doesn't work: try MDS with density on # Sizes def get_sizes(self): """ Prepare data for sizes of points in the plot The method is called by `update_sizes`. It gets the sizes from the widget and performs the necessary scaling and sizing. The output is rounded to half a pixel for faster drawing. Returns: (np.ndarray): sizes """ size_column = self.master.get_size_data() if size_column is None: return np.full((self.n_shown,), self.MinShapeSize + (5 + self.point_width) * 0.5) size_column = self._filter_visible(size_column) size_column = size_column.copy() with warnings.catch_warnings(): warnings.simplefilter("ignore", category=RuntimeWarning) size_column -= np.nanmin(size_column) mx = np.nanmax(size_column) if mx > 0: size_column /= mx else: size_column[:] = 0.5 sizes = self.MinShapeSize + (5 + self.point_width) * size_column # round sizes to half pixel for smaller pyqtgraph's symbol pixmap atlas sizes = (sizes * 2).round() / 2 return sizes def update_sizes(self): """ Trigger an update of point sizes The method calls `self.get_sizes`, which in turn calls the widget's `get_size_data`. The result are properly scaled and then passed back to widget for imputing (`master.impute_sizes`). """ if self.scatterplot_item: size_data = self.get_sizes() size_imputer = getattr( self.master, "impute_sizes", self.default_impute_sizes) size_imputer(size_data) if self.timer is not None and self.timer.isActive(): self.timer.stop() self.timer = None current_size_data = self.scatterplot_item.data["size"].copy() diff = size_data - current_size_data widget = self class Timeout: # 0.5 - np.cos(np.arange(0.17, 1, 0.09) * np.pi) / 2 factors = [0.07, 0.16, 0.27, 0.41, 0.55, 0.68, 0.81, 0.9, 0.97, 1] def __init__(self): self._counter = 0 def __call__(self): factor = self.factors[self._counter] self._counter += 1 size = current_size_data + diff * factor if len(self.factors) == self._counter: widget.timer.stop() widget.timer = None size = size_data widget.scatterplot_item.setSize(size) widget.scatterplot_item_sel.setSize(size + SELECTION_WIDTH) if widget.timer is None: widget.end_resizing.emit() else: widget.step_resizing.emit() if self.n_valid <= MAX_N_VALID_SIZE_ANIMATE and \ np.all(current_size_data > 0) and np.any(diff != 0): # If encountered any strange behaviour when updating sizes, # implement it with threads self.begin_resizing.emit() interval = int(500 / len(Timeout.factors)) self.timer = QTimer(self.scatterplot_item, interval=interval) self.timer.timeout.connect(Timeout()) self.timer.start() else: self.begin_resizing.emit() self.scatterplot_item.setSize(size_data) self.scatterplot_item_sel.setSize(size_data + SELECTION_WIDTH) self.end_resizing.emit() update_point_size = update_sizes # backward compatibility (needed?!) update_size = update_sizes @classmethod def default_impute_sizes(cls, size_data): """ Fallback imputation for sizes. Set the size to two pixels smaller than the minimal size Returns: (bool): True if there was any missing data """ nans = np.isnan(size_data) if np.any(nans): size_data[nans] = cls.MinShapeSize - 2 return True else: return False # Colors def get_colors(self): """ Prepare data for colors of the points in the plot The method is called by `update_colors`. It gets the colors and the indices of the data subset from the widget (`get_color_data`, `get_subset_mask`), and constructs lists of pens and brushes for each data point. The method uses different palettes for discrete and continuous data, as determined by calling the widget's method `is_continuous_color`. If also marks the points that are in the subset as defined by, for instance the 'Data Subset' signal in the Scatter plot and similar widgets. (Do not confuse this with *selected points*, which are marked by circles around the points, which are colored by groups and thus independent of this method.) Returns: (tuple): a list of pens and list of brushes """ c_data = self.master.get_color_data() c_data = self._filter_visible(c_data) subset = self.master.get_subset_mask() subset = self._filter_visible(subset) self.subset_is_shown = subset is not None if c_data is None: # same color self.palette = None return self._get_same_colors(subset) elif self.master.is_continuous_color(): return self._get_continuous_colors(c_data, subset) else: return self._get_discrete_colors(c_data, subset) def _get_same_colors(self, subset, color=COLOR_DEFAULT): """ Return the same pen for all points while the brush color depends upon whether the point is in the subset or not Args: subset (np.ndarray): a bool array indicating whether a data point is in the subset or not (e.g. in the 'Data Subset' signal in the Scatter plot and similar widgets); Returns: (tuple): a list of pens and list of brushes """ alpha_subset, alpha_unset = self._alpha_for_subsets() if subset is not None: qcolor = QColor(*color, alpha_subset) brush = np.where(subset, QBrush(qcolor), QBrush(QColor(0, 0, 0, 0))) pen = np.where(subset, _make_pen(qcolor, 1.5), _make_pen(QColor(*color, alpha_unset), 1.5)) else: qcolor = QColor(*color, self.alpha_value) brush = np.full(self.n_shown, QBrush(qcolor)) pen = [_make_pen(qcolor, 1.5)] * self.n_shown return pen, brush def _get_continuous_colors(self, c_data, subset): """ Return the pens and colors whose color represent an index into a continuous palette. The same color is used for pen and brush, except the former is darker. If the data has a subset, the brush is transparent for points that are not in the subset. """ palette = self.master.get_palette() if np.isnan(c_data).all(): self.palette = palette return self._get_same_colors(subset, self.palette.nan_color) self.scale = DiscretizedScale(np.nanmin(c_data), np.nanmax(c_data)) bins = self.scale.get_bins() self.palette = \ colorpalettes.BinnedContinuousPalette.from_palette(palette, bins) colors = self.palette.values_to_colors(c_data) alphas = np.full((len(c_data), 1), self.alpha_value, dtype=np.ubyte) brush = np.hstack((colors, alphas)) pen = np.hstack( ((colors.astype(dtype=float) * 100 / self.DarkerValue).astype(np.ubyte), alphas)) # Reuse pens and brushes with the same colors because PyQtGraph then # builds smaller pixmap atlas, which makes the drawing faster def reuse(cache, fun, *args): if args not in cache: cache[args] = fun(args) return cache[args] def create_pen(col): return _make_pen(QColor(*col), 1.5) def create_brush(col): return QBrush(QColor(*col)) if subset is not None: alpha_subset, alpha_unset = self._alpha_for_subsets() brush[:, 3] = 0 brush[subset, 3] = alpha_subset pen[:, 3] = alpha_unset brush[subset, 3] = alpha_subset cached_pens = {} pen = [reuse(cached_pens, create_pen, *col) for col in pen.tolist()] cached_brushes = {} brush = np.array([reuse(cached_brushes, create_brush, *col) for col in brush.tolist()]) return pen, brush def _get_discrete_colors(self, c_data, subset): """ Return the pens and colors whose color represent an index into a discrete palette. The same color is used for pen and brush, except the former is darker. If the data has a subset, the brush is transparent for points that are not in the subset. """ self.palette = self.master.get_palette() c_data = c_data.copy() c_data[np.isnan(c_data)] = len(self.palette) c_data = c_data.astype(int) colors = self.palette.qcolors_w_nan if subset is None: for col in colors: col.setAlpha(self.alpha_value) pens = np.array( [_make_pen(col.darker(self.DarkerValue), 1.5) for col in colors]) pen = pens[c_data] brushes = np.array([QBrush(col) for col in colors]) brush = brushes[c_data] else: subset_colors = [QColor(col) for col in colors] alpha_subset, alpha_unset = self._alpha_for_subsets() for col in subset_colors: col.setAlpha(alpha_subset) for col in colors: col.setAlpha(alpha_unset) pens, subset_pens = ( np.array( [_make_pen(col.darker(self.DarkerValue), 1.5) for col in cols]) for cols in (colors, subset_colors)) pen = np.where(subset, subset_pens[c_data], pens[c_data]) brushes = np.array([QBrush(col) for col in subset_colors]) brush = brushes[c_data] black = np.full(len(brush), QBrush(QColor(0, 0, 0, 0))) brush = np.where(subset, brush, black) return pen, brush def _alpha_for_subsets(self): a, b, c = 1.2, -3.2, 3 x = self.alpha_value / 255 alpha_subset = 31 + int(224 * (a * x ** 3 + b * x ** 2 + c * x)) x = 1 - x alpha_unset = int(255 - 224 * (a * x ** 3 + b * x ** 2 + c * x)) return alpha_subset, alpha_unset def update_colors(self): """ Trigger an update of point colors The method calls `self.get_colors`, which in turn calls the widget's `get_color_data` to get the indices in the pallette. `get_colors` returns a list of pens and brushes to which this method uses to update the colors. Finally, the method triggers the update of the legend and the density plot. """ if self.scatterplot_item is not None: pen_data, brush_data = self.get_colors() self.scatterplot_item.setPen(pen_data, update=False, mask=None) self.scatterplot_item.setBrush(brush_data, mask=None) self.update_z_values() self.update_legends() self.update_density() update_alpha_value = update_colors def update_density(self): """ Remove the existing density plot (if there is one) and replace it with a new one (if enabled). The method gets the colors from the pens of the currently plotted points. """ if self.density_img: self.plot_widget.removeItem(self.density_img) self.density_img = None if self.class_density and self.scatterplot_item is not None: c_data = self.master.get_color_data() if c_data is None: return visible_c_data = self._filter_visible(c_data) mask = np.isfinite(visible_c_data) if not self.master.is_continuous_color(): mask = np.bitwise_and(mask, visible_c_data < MAX_COLORS - 1) pens = self.scatterplot_item.data['pen'] rgb_data = [ pen.color().getRgb()[:3] if pen is not None else (255, 255, 255) for known, pen in zip(mask, pens) if known] if len(set(rgb_data)) <= 1: return [min_x, max_x], [min_y, max_y] = self.view_box.viewRange() x_data, y_data = self.scatterplot_item.getData() self.density_img = classdensity.class_density_image( min_x, max_x, min_y, max_y, self.resolution, x_data[mask], y_data[mask], rgb_data) self.plot_widget.addItem(self.density_img, ignoreBounds=True) def update_selection_colors(self): """ Trigger an update of selection markers This update method is usually not called by the widget but by the plot, since it is the plot that handles the selections. Like other update methods, it calls the corresponding get method (`get_colors_sel`) which returns a list of pens and brushes. """ if self.scatterplot_item_sel is None: return pen, brush = self.get_colors_sel() self.scatterplot_item_sel.setPen(pen, update=False, mask=None) self.scatterplot_item_sel.setBrush(brush, mask=None) self.update_z_values() def get_colors_sel(self): """ Return pens and brushes for selection markers. A pen can is set to `Qt.NoPen` if a point is not selected. All brushes are completely transparent whites. Returns: (tuple): a list of pens and a list of brushes """ nopen = QPen(Qt.NoPen) if self.selection is None: pen = [nopen] * self.n_shown else: sels = np.max(self.selection) if sels == 1: pen = np.where( self._filter_visible(self.selection), _make_pen(QColor(255, 190, 0, 255), SELECTION_WIDTH), nopen) else: palette = colorpalettes.LimitedDiscretePalette( number_of_colors=sels + 1) pen = np.choose( self._filter_visible(self.selection), [nopen] + [_make_pen(palette[i], SELECTION_WIDTH) for i in range(sels)]) return pen, [QBrush(QColor(255, 255, 255, 0))] * self.n_shown # Labels def get_labels(self): """ Prepare data for labels for points The method returns the results of the widget's `get_label_data` Returns: (labels): a sequence of labels """ return self._filter_visible(self.master.get_label_data()) def update_labels(self): """ Trigger an update of labels The method calls `get_labels` which in turn calls the widget's `get_label_data`. The obtained labels are shown if the corresponding points are selected or if `label_only_selected` is `false`. """ for label in self.labels: self.plot_widget.removeItem(label) self.labels = [] mask = None if self.scatterplot_item is not None: x, y = self.scatterplot_item.getData() mask = self._label_mask(x, y) if mask is not None: labels = self.get_labels() if labels is None: mask = None self._signal_too_many_labels( bool(mask is not None and mask.sum() > self.MAX_VISIBLE_LABELS)) if self._too_many_labels or mask is None or not np.any(mask): return foreground = self.plot_widget.palette().color(QPalette.Text) labels = labels[mask] x = x[mask] y = y[mask] for label, xp, yp in zip(labels, x, y): ti = TextItem(label, foreground) ti.setPos(xp, yp) self.plot_widget.addItem(ti) self.labels.append(ti) ti.setFont(self.parameter_setter.label_font) def _signal_too_many_labels(self, too_many): if self._too_many_labels != too_many: self._too_many_labels = too_many self.too_many_labels.emit(too_many) def _label_mask(self, x, y): (x0, x1), (y0, y1) = self.view_box.viewRange() mask = np.logical_and( np.logical_and(x >= x0, x <= x1), np.logical_and(y >= y0, y <= y1)) if self.label_only_selected: sub_mask = self._filter_visible(self.master.get_subset_mask()) if self.selection is None: if sub_mask is None: return None else: sel_mask = sub_mask else: sel_mask = self._filter_visible(self.selection) != 0 if sub_mask is not None: sel_mask = np.logical_or(sel_mask, sub_mask) mask = np.logical_and(mask, sel_mask) return mask # Shapes def get_shapes(self): """ Prepare data for shapes of points in the plot The method is called by `update_shapes`. It gets the data from the widget's `get_shape_data`, and then calls its `impute_shapes` to impute the missing shape (usually with some default shape). Returns: (np.ndarray): an array of symbols (e.g. o, x, + ...) """ shape_data = self.master.get_shape_data() shape_data = self._filter_visible(shape_data) # Data has to be copied so the imputation can change it in-place # TODO: Try avoiding this when we move imputation to the widget if shape_data is not None: shape_data = np.copy(shape_data) shape_imputer = getattr( self.master, "impute_shapes", self.default_impute_shapes) shape_imputer(shape_data, len(self.CurveSymbols) - 1) if isinstance(shape_data, np.ndarray): shape_data = shape_data.astype(int) else: shape_data = np.zeros(self.n_shown, dtype=int) return self.CurveSymbols[shape_data] @staticmethod def default_impute_shapes(shape_data, default_symbol): """ Fallback imputation for shapes. Use the default symbol, usually the last symbol in the list. Returns: (bool): True if there was any missing data """ if shape_data is None: return False nans = np.isnan(shape_data) if np.any(nans): shape_data[nans] = default_symbol return True else: return False def update_shapes(self): """ Trigger an update of point symbols The method calls `get_shapes` to obtain an array with a symbol for each point and uses it to update the symbols. Finally, the method updates the legend. """ if self.scatterplot_item: shape_data = self.get_shapes() self.scatterplot_item.setSymbol(shape_data) self.update_legends() def update_z_values(self): """ Set z-values for point in the plot The order is as follows: - selected points that are also in the subset on top, - followed by selected points, - followed by points from the subset, - followed by the rest. Within each of these four groups, points are ordered by their colors. Points with less frequent colors are above those with more frequent. The points for which the value for the color is missing are at the bottom of their respective group. """ if not self.scatterplot_item: return subset = self.master.get_subset_mask() c_data = self.master.get_color_data() if subset is None and self.selection is None and c_data is None: self.scatterplot_item.setZ(None) return z = np.zeros(self.n_shown) if subset is not None: subset = self._filter_visible(subset) z[subset] += 1000 if self.selection is not None: z[self._filter_visible(self.selection) != 0] += 2000 if c_data is not None: c_nan = np.isnan(c_data) vis_data = self._filter_visible(c_data) vis_nan = np.isnan(vis_data) z[vis_nan] -= 999 if not self.master.is_continuous_color(): dist = np.bincount(c_data[~c_nan].astype(int)) vis_knowns = vis_data[~vis_nan].astype(int) argdist = np.argsort(dist) z[~vis_nan] -= argdist[vis_knowns] self.scatterplot_item.setZ(z) def update_grid_visibility(self): """Show or hide the grid""" self.plot_widget.showGrid(x=self.show_grid, y=self.show_grid) def update_legend_visibility(self): """ Show or hide legends based on whether they are enabled and non-empty """ self.shape_legend.setVisible( self.show_legend and bool(self.shape_legend.items)) self.color_legend.setVisible( self.show_legend and bool(self.color_legend.items)) def update_legends(self): """Update content of legends and their visibility""" cont_color = self.master.is_continuous_color() shape_labels = self.master.get_shape_labels() color_labels = self.master.get_color_labels() if not cont_color and shape_labels is not None \ and shape_labels == color_labels: colors = self.master.get_color_data() shapes = self.master.get_shape_data() mask = np.isfinite(colors) * np.isfinite(shapes) combined = (colors == shapes)[mask].all() else: combined = False if combined: self._update_combined_legend(shape_labels) else: self._update_shape_legend(shape_labels) if cont_color: self._update_continuous_color_legend(color_labels) else: self._update_color_legend(color_labels) self.update_legend_visibility() Updater.update_legend_font(self.parameter_setter.cat_legend_items, **self.parameter_setter.cat_legend_settings) Updater.update_num_legend_font(self.parameter_setter.num_legend, **self.parameter_setter.num_legend_settings) def _update_shape_legend(self, labels): self.shape_legend.clear() if labels is None or self.scatterplot_item is None: return color = QColor(0, 0, 0) color.setAlpha(self.alpha_value) for label, symbol in zip(labels, self.CurveSymbols): self.shape_legend.addItem( SymbolItemSample(pen=color, brush=color, size=10, symbol=symbol), escape(label)) def _update_continuous_color_legend(self, label_formatter: Callable[[float], str]): self.color_legend.clear() if self.scale is None or self.scatterplot_item is None: return label = PaletteItemSample(self.palette, self.scale, label_formatter) self.color_legend.addItem(label, "") self.color_legend.setGeometry(label.boundingRect()) def _update_color_legend(self, labels): self.color_legend.clear() if labels is None: return self._update_colored_legend(self.color_legend, labels, 'o') def _update_combined_legend(self, labels): # update_colored_legend will already clear the shape legend # so we remove colors here use_legend = \ self.shape_legend if self.shape_legend.items else self.color_legend self.color_legend.clear() self.shape_legend.clear() self._update_colored_legend(use_legend, labels, self.CurveSymbols) def _update_colored_legend(self, legend, labels, symbols): if self.scatterplot_item is None or not self.palette: return if isinstance(symbols, str): symbols = itertools.repeat(symbols, times=len(labels)) colors = self.palette.values_to_colors(np.arange(len(labels))) for color, label, symbol in zip(colors, labels, symbols): color = QColor(*color) pen = _make_pen(color.darker(self.DarkerValue), 1.5) color.setAlpha(self.alpha_value) brush = QBrush(color) legend.addItem( SymbolItemSample(pen=pen, brush=brush, size=10, symbol=symbol), escape(label)) def zoom_button_clicked(self): self.plot_widget.getViewBox().setMouseMode( self.plot_widget.getViewBox().RectMode) def pan_button_clicked(self): self.plot_widget.getViewBox().setMouseMode( self.plot_widget.getViewBox().PanMode) def select_button_clicked(self): self.plot_widget.getViewBox().setMouseMode( self.plot_widget.getViewBox().RectMode) def reset_button_clicked(self): self.plot_widget.getViewBox().autoRange() self.update_labels() def select_by_click(self, _, points): if self.scatterplot_item is not None: self.select(points) def select_by_rectangle(self, rect): if self.scatterplot_item is not None: x0, x1 = sorted((rect.topLeft().x(), rect.bottomRight().x())) y0, y1 = sorted((rect.topLeft().y(), rect.bottomRight().y())) x, y = self.master.get_coordinates_data() indices = np.flatnonzero( (x0 <= x) & (x <= x1) & (y0 <= y) & (y <= y1)) self.select_by_indices(indices.astype(int)) def unselect_all(self): if self.selection is not None: self.selection = None self.update_selection_colors() if self.label_only_selected: self.update_labels() self.master.selection_changed() def select(self, points): # noinspection PyArgumentList if self.scatterplot_item is None: return indices = [p.data() for p in points] self.select_by_indices(indices) def select_by_indices(self, indices): if self.selection is None: self.selection = np.zeros(self.n_valid, dtype=np.uint8) keys = QApplication.keyboardModifiers() if keys & Qt.ControlModifier: self.selection_append(indices) elif keys & Qt.ShiftModifier: self.selection_new_group(indices) elif keys & Qt.AltModifier: self.selection_remove(indices) else: self.selection_select(indices) def selection_select(self, indices): self.selection = np.zeros(self.n_valid, dtype=np.uint8) self.selection[indices] = 1 self._update_after_selection() def selection_append(self, indices): self.selection[indices] = max(np.max(self.selection), 1) self._update_after_selection() def selection_new_group(self, indices): self.selection[indices] = np.max(self.selection) + 1 self._update_after_selection() def selection_remove(self, indices): self.selection[indices] = 0 self._update_after_selection() def _update_after_selection(self): self._compress_indices() self.update_selection_colors() if self.label_only_selected: self.update_labels() self.master.selection_changed() def _compress_indices(self): indices = sorted(set(self.selection) | {0}) if len(indices) == max(indices) + 1: return mapping = np.zeros((max(indices) + 1,), dtype=int) for i, ind in enumerate(indices): mapping[ind] = i self.selection = mapping[self.selection] def get_selection(self): if self.selection is None: return np.array([], dtype=np.uint8) else: return np.flatnonzero(self.selection) def help_event(self, event): """ Create a `QToolTip` for the point hovered by the mouse """ if self.scatterplot_item is None: return False act_pos = self.scatterplot_item.mapFromScene(event.scenePos()) point_data = [p.data() for p in self.scatterplot_item.pointsAt(act_pos)] text = self.master.get_tooltip(point_data) if text: QToolTip.showText(event.screenPos(), text, widget=self.plot_widget) return True else: return False