Source code for guiqwt.histogram

# Copyright © 2009-2010 CEA
# Pierre Raybaut
# Licensed under the terms of the CECILL License
# (see guiqwt/ for details)

# pylint: disable=C0103


The `histogram` module provides histogram related objects:
    * :py:class:`guiqwt.histogram.HistogramItem`: an histogram plot item
    * :py:class:`guiqwt.histogram.ContrastAdjustment`: the `contrast 
      adjustment panel`
    * :py:class:`guiqwt.histogram.LevelsHistogram`: a curve plotting widget 
      used by the `contrast adjustment panel` to compute, manipulate and 
      display the image levels histogram

``HistogramItem`` objects are plot items (derived from QwtPlotItem) that may 
be displayed on a 2D plotting widget like :py:class:`guiqwt.curve.CurvePlot` 
or :py:class:`guiqwt.image.ImagePlot`.


Simple histogram plotting example:

.. literalinclude:: ../guiqwt/tests/


.. autoclass:: HistogramItem
.. autoclass:: ContrastAdjustment
.. autoclass:: LevelsHistogram

import weakref
import numpy as np
from guidata.qt.QtCore import Qt
from guidata.qt.QtGui import QHBoxLayout, QVBoxLayout, QToolBar

from guidata.dataset.datatypes import DataSet
from guidata.dataset.dataitems import FloatItem
from guidata.utils import assert_interfaces_valid, update_dataset
from guidata.configtools import get_icon, get_image_layout
from guidata.qthelpers import add_actions, create_action

# Local imports
from guiqwt.transitional import QwtPlotCurve
from guiqwt.config import CONF, _
from guiqwt.interfaces import (IBasePlotItem, IHistDataSource,
                               IVoiImageItemType, IPanel)
from guiqwt.panels import PanelWidget, ID_CONTRAST
from guiqwt.curve import CurveItem, CurvePlot
from guiqwt.image import ImagePlot
from guiqwt.styles import HistogramParam, CurveParam
from guiqwt.shapes import XRangeSelection
from import (SelectTool, BasePlotMenuTool, SelectPointTool,
from guiqwt.signals import (SIG_RANGE_CHANGED, SIG_VOI_CHANGED,
from guiqwt.plot import PlotManager

class HistDataSource(object):
    An objects that provides an Histogram data source interface
    to a simple numpy array of data
    __implements__ = (IHistDataSource,)
    def __init__(self, data): = data

    def get_histogram(self, nbins):
        """Returns the histogram computed for nbins bins"""
        return np.histogram(, nbins)


def hist_range_threshold(hist, bin_edges, percent):
    hist = np.concatenate((hist, [0]))
    threshold = .5*percent/100*hist.sum()
    i_bin_min = np.cumsum(hist).searchsorted(threshold)
    i_bin_max = -1-np.cumsum(np.flipud(hist)).searchsorted(threshold)
    return bin_edges[i_bin_min], bin_edges[i_bin_max]

def lut_range_threshold(item, bins, percent):
    hist, bin_edges = item.get_histogram(bins)
    return hist_range_threshold(hist, bin_edges, percent)

class HistogramItem(CurveItem):
[docs] """A Qwt item representing histogram data""" __implements__ = (IBasePlotItem,) def __init__(self, curveparam=None, histparam=None): self.hist_count = None self.hist_bins = None self.bins = None self.old_bins = None self.source = None self.logscale = None self.old_logscale = None if curveparam is None: curveparam = CurveParam(_("Curve"), icon='curve.png') curveparam.curvestyle = "Steps" if histparam is None: self.histparam = HistogramParam(title=_("Histogram"), icon='histogram.png') else: self.histparam = histparam CurveItem.__init__(self, curveparam) self.setCurveAttribute(QwtPlotCurve.Inverted) def set_hist_source(self, src):
[docs] """Set histogram source (source: object with method 'get_histogram', e.g. objects derived from guiqwt.image.ImageItem)""" self.source = weakref.ref(src) self.update_histogram() def get_hist_source(self):
[docs] """Return histogram source (source: object with method 'get_histogram', e.g. objects derived from guiqwt.image.ImageItem)""" if self.source is not None: return self.source() def set_hist_data(self, data):
[docs] """Set histogram data""" self.set_hist_source(HistDataSource(data)) def set_logscale(self, state):
[docs] """Sets whether we use a logarithm or linear scale for the histogram counts""" self.logscale = state self.update_histogram() def get_logscale(self):
[docs] """Returns the status of the scale""" return self.logscale def set_bins(self, n_bins):
self.bins = n_bins self.update_histogram() def get_bins(self): return self.bins def compute_histogram(self): return self.get_hist_source().get_histogram(self.bins) def update_histogram(self): if self.get_hist_source() is None: return hist, bin_edges = self.compute_histogram() hist = np.concatenate((hist, [0])) if self.logscale: hist = np.log(hist+1) self.set_data(bin_edges, hist) # Autoscale only if logscale/bins have changed if self.bins != self.old_bins or self.logscale != self.old_logscale: if self.plot(): self.plot().do_autoscale() self.old_bins = self.bins self.old_logscale = self.logscale plot = self.plot() if plot is not None: plot.do_autoscale(replot=True) def update_params(self): self.histparam.update_hist(self) CurveItem.update_params(self) def get_item_parameters(self, itemparams): CurveItem.get_item_parameters(self, itemparams) itemparams.add("HistogramParam", self, self.histparam) def set_item_parameters(self, itemparams): update_dataset(self.histparam, itemparams.get("HistogramParam"), visible_only=True) self.histparam.update_hist(self) CurveItem.set_item_parameters(self, itemparams) assert_interfaces_valid(HistogramItem)
class LevelsHistogram(CurvePlot):
[docs] """Image levels histogram widget""" def __init__(self, parent=None): super(LevelsHistogram, self).__init__(parent=parent, title="", section="histogram") self.antialiased = False # a dict of dict : plot -> selected items -> HistogramItem self._tracked_items = {} self.curveparam = CurveParam(_("Curve"), icon="curve.png") self.curveparam.read_config(CONF, "histogram", "curve") self.histparam = HistogramParam(_("Histogram"), icon="histogram.png") self.histparam.logscale = False self.histparam.n_bins = 256 self.range = XRangeSelection(0, 1) self.range_mono_color = self.range.shapeparam.sel_line.color self.range_multi_color = CONF.get("histogram", "range/multi/color", "red") self.add_item(self.range, z=5) self.connect(self, SIG_RANGE_CHANGED, self.range_changed) self.set_active_item(self.range) self.setMinimumHeight(80) self.setAxisMaxMajor(self.Y_LEFT, 5) self.setAxisMaxMinor(self.Y_LEFT, 0) if parent is None: self.set_axis_title('bottom', 'Levels') def connect_plot(self, plot): if not isinstance(plot, ImagePlot): # Connecting only to image plot widgets (allow mixing image and # curve widgets for the same plot manager -- e.g. in pyplot) return self.connect(self, SIG_VOI_CHANGED, plot.notify_colormap_changed) self.connect(plot, SIG_ITEM_SELECTION_CHANGED, self.selection_changed) self.connect(plot, SIG_ITEM_REMOVED, self.item_removed) self.connect(plot, SIG_ACTIVE_ITEM_CHANGED, self.active_item_changed) def tracked_items_gen(self): for plot, items in self._tracked_items.items(): for item in items.items(): yield item # tuple item,curve def __del_known_items(self, known_items, items): del_curves = [] for item in known_items.keys(): if item not in items: curve = known_items.pop(item) del_curves.append(curve) self.del_items(del_curves) def selection_changed(self, plot): items = plot.get_selected_items(item_type=IVoiImageItemType) known_items = self._tracked_items.setdefault(plot, {}) if items: self.__del_known_items(known_items, items) if len(items) == 1: # Removing any cached item for other plots for other_plot, _items in self._tracked_items.items(): if other_plot is not plot: if not other_plot.get_selected_items( item_type=IVoiImageItemType): other_known_items = self._tracked_items[other_plot] self.__del_known_items(other_known_items, []) else: # if all items are deselected we keep the last known # selection (for one plot only) for other_plot, _items in self._tracked_items.items(): if other_plot.get_selected_items(item_type=IVoiImageItemType): self.__del_known_items(known_items, []) break for item in items: if item not in known_items: curve = HistogramItem(self.curveparam, self.histparam) curve.set_hist_source(item) self.add_item(curve, z=0) known_items[item] = curve nb_selected = len(list(self.tracked_items_gen())) if not nb_selected: self.replot() return self.curveparam.shade = 1.0/nb_selected for item, curve in self.tracked_items_gen(): self.curveparam.update_curve(curve) self.histparam.update_hist(curve) self.active_item_changed(plot) # Rescaling histogram plot axes for better visibility ymax = None for item in known_items: curve = known_items[item] _x, y = curve.get_data() ymax0 = y.mean()+3*y.std() if ymax is None or ymax0 > ymax: ymax = ymax0 ymin, _ymax = self.get_axis_limits("left") if ymax is not None: self.set_axis_limits("left", ymin, ymax) self.replot() def item_removed(self, item): for plot, items in self._tracked_items.items(): if item in items: items.pop(item) break def active_item_changed(self, plot): items = plot.get_selected_items(item_type=IVoiImageItemType) if not items: #XXX: workaround return active = plot.get_last_active_item(IVoiImageItemType) if active: active_range = active.get_lut_range() else: active_range = None multiple_ranges = False for item, curve in self.tracked_items_gen(): if active_range != item.get_lut_range(): multiple_ranges = True if active_range is not None: _m, _M = active_range self.set_range_style(multiple_ranges) self.range.set_range(_m, _M, dosignal=False) self.replot() def set_range_style(self, multiple_ranges): if multiple_ranges: self.range.shapeparam.sel_line.color = self.range_multi_color else: self.range.shapeparam.sel_line.color = self.range_mono_color self.range.shapeparam.update_range(self.range) def set_range(self, _min, _max): if _min < _max: self.set_range_style(False) self.range.set_range(_min, _max) self.replot() return True else: # Range was not changed return False def range_changed(self, _rangesel, _min, _max): for item, curve in self.tracked_items_gen(): item.set_lut_range([_min, _max]) self.emit(SIG_VOI_CHANGED) def set_full_range(self):
[docs] """Set range bounds to image min/max levels""" _min = _max = None for item, curve in self.tracked_items_gen(): imin, imax = item.get_lut_range_full() if _min is None or _min>imin: _min = imin if _max is None or _max<imax: _max = imax if _min is not None: self.set_range(_min, _max) def apply_min_func(self, item, curve, min):
_min, _max = item.get_lut_range() return min, _max def apply_max_func(self, item, curve, max): _min, _max = item.get_lut_range() return _min, max def reduce_range_func(self, item, curve, percent): return lut_range_threshold(item, curve.bins, percent) def apply_range_function(self, func, *args, **kwargs): item = None for item, curve in self.tracked_items_gen(): _min, _max = func(item, curve, *args, **kwargs) item.set_lut_range([_min, _max]) self.emit(SIG_VOI_CHANGED) if item is not None: self.active_item_changed(item.plot()) def eliminate_outliers(self, percent):
[docs] """ Eliminate outliers: eliminate percent/2*N counts on each side of the histogram (where N is the total count number) """ self.apply_range_function(self.reduce_range_func, percent) def set_min(self, _min):
self.apply_range_function(self.apply_min_func, _min) def set_max(self, _max): self.apply_range_function(self.apply_max_func, _max) class EliminateOutliersParam(DataSet):
percent = FloatItem(_("Eliminate outliers")+" (%)", default=2., min=0., max=100.-1e-6) class ContrastAdjustment(PanelWidget):
[docs] """Contrast adjustment tool""" __implements__ = (IPanel,) PANEL_ID = ID_CONTRAST PANEL_TITLE = _("Contrast adjustment tool") PANEL_ICON = "contrast.png" def __init__(self, parent=None): super(ContrastAdjustment, self).__init__(parent) self.local_manager = None # local manager for the histogram plot self.manager = None # manager for the associated image plot # Storing min/max markers for each active image self.min_markers = {} self.max_markers = {} # Select point tools self.min_select_tool = None self.max_select_tool = None style = "<span style=\'color: #444444\'><b>%s</b></span>" layout, _label = get_image_layout(self.PANEL_ICON, style % self.PANEL_TITLE, alignment=Qt.AlignCenter) layout.setAlignment(Qt.AlignCenter) vlayout = QVBoxLayout() vlayout.addLayout(layout) self.local_manager = PlotManager(self) self.histogram = LevelsHistogram(parent) vlayout.addWidget(self.histogram) self.local_manager.add_plot(self.histogram) hlayout = QHBoxLayout() self.setLayout(hlayout) hlayout.addLayout(vlayout) self.toolbar = toolbar = QToolBar(self) toolbar.setOrientation(Qt.Vertical) # toolbar.setToolButtonStyle(Qt.ToolButtonTextBesideIcon) hlayout.addWidget(toolbar) # Add standard plot-related tools to the local manager lman = self.local_manager lman.add_tool(SelectTool) lman.add_tool(BasePlotMenuTool, "item") lman.add_tool(BasePlotMenuTool, "axes") lman.add_tool(BasePlotMenuTool, "grid") lman.add_tool(AntiAliasingTool) lman.get_default_tool().activate() self.outliers_param = EliminateOutliersParam(self.PANEL_TITLE) def register_panel(self, manager):
[docs] """Register panel to plot manager""" self.manager = manager default_toolbar = self.manager.get_default_toolbar() self.manager.add_toolbar(self.toolbar, "contrast") self.manager.set_default_toolbar(default_toolbar) self.setup_actions() for plot in manager.get_plots(): self.histogram.connect_plot(plot) def configure_panel(self):
[docs] """Configure panel""" self.min_select_tool = self.manager.add_tool(SelectPointTool, title=_("Minimum level"), on_active_item=True,mode="create", tip=_("Select minimum level on image"), toolbar_id="contrast", end_callback=self.apply_min_selection) self.max_select_tool = self.manager.add_tool(SelectPointTool, title=_("Maximum level"), on_active_item=True,mode="create", tip=_("Select maximum level on image"), toolbar_id="contrast", end_callback=self.apply_max_selection) def get_plot(self):
return self.manager.get_active_plot() def closeEvent(self, event): self.hide() event.ignore() def setup_actions(self): fullrange_ac = create_action(self, _("Full range"), icon=get_icon("full_range.png"), triggered=self.histogram.set_full_range, tip=_("Scale the image's display range " "according to data range") ) autorange_ac = create_action(self, _("Eliminate outliers"), icon=get_icon("eliminate_outliers.png"), triggered=self.eliminate_outliers, tip=_("Eliminate levels histogram " "outliers and scale the image's " "display range accordingly") ) add_actions(self.toolbar,[fullrange_ac, autorange_ac]) def eliminate_outliers(self): def apply(param): self.histogram.eliminate_outliers(param.percent) if self.outliers_param.edit(self, apply=apply): apply(self.outliers_param) def apply_min_selection(self, tool): item = self.get_plot().get_last_active_item(IVoiImageItemType) point = self.min_select_tool.get_coordinates() z = item.get_data(*point) self.histogram.set_min(z) def apply_max_selection(self, tool): item = self.get_plot().get_last_active_item(IVoiImageItemType) point = self.max_select_tool.get_coordinates() z = item.get_data(*point) self.histogram.set_max(z) def set_range(self, _min, _max):
[docs] """Set contrast panel's histogram range""" self.histogram.set_range(_min, _max) # Update the levels histogram in case active item data has changed: self.histogram.selection_changed(self.get_plot()) assert_interfaces_valid(ContrastAdjustment)