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# -*- coding: utf-8 -*-
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# Copyright © 2009-2010 CEA
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# Licensed under the terms of the CECILL License
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# (see guiqwt/__init__.py for details)
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The `histogram` module provides histogram related objects:
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* :py:class:`guiqwt.histogram.HistogramItem`: an histogram plot item
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* :py:class:`guiqwt.histogram.ContrastAdjustment`: the `contrast
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* :py:class:`guiqwt.histogram.LevelsHistogram`: a curve plotting widget
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used by the `contrast adjustment panel` to compute, manipulate and
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display the image levels histogram
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``HistogramItem`` objects are plot items (derived from QwtPlotItem) that may
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be displayed on a 2D plotting widget like :py:class:`guiqwt.curve.CurvePlot`
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or :py:class:`guiqwt.image.ImagePlot`.
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Simple histogram plotting example:
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.. literalinclude:: ../guiqwt/tests/histogram.py
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.. autoclass:: HistogramItem
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.. autoclass:: ContrastAdjustment
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.. autoclass:: LevelsHistogram
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from PyQt4.QtCore import Qt
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from PyQt4.QtGui import QHBoxLayout, QVBoxLayout, QToolBar
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from PyQt4.Qwt5 import QwtPlotCurve
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from guidata.dataset.datatypes import DataSet
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from guidata.dataset.dataitems import FloatItem
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from guidata.utils import assert_interfaces_valid, update_dataset
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from guidata.configtools import get_icon, get_image_layout
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from guidata.qthelpers import add_actions, create_action
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from guiqwt.config import CONF, _
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from guiqwt.interfaces import (IBasePlotItem, IHistDataSource,
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IVoiImageItemType, IPanel)
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from guiqwt.panels import PanelWidget, ID_CONTRAST
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from guiqwt.curve import CurveItem, CurvePlot
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from guiqwt.image import ImagePlot
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from guiqwt.styles import HistogramParam, CurveParam
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from guiqwt.shapes import XRangeSelection
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from guiqwt.tools import (SelectTool, BasePlotMenuTool, SelectPointTool,
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from guiqwt.signals import (SIG_RANGE_CHANGED, SIG_VOI_CHANGED,
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SIG_ITEM_SELECTION_CHANGED, SIG_ACTIVE_ITEM_CHANGED)
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from guiqwt.plot import PlotManager
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class HistDataSource(object):
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An objects that provides an Histogram data source interface
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to a simple numpy array of data
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__implements__ = (IHistDataSource,)
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def __init__(self, data):
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def get_histogram(self, nbins):
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"""Returns the histogram computed for nbins bins"""
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return np.histogram(self.data, nbins)
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assert_interfaces_valid(HistDataSource)
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def lut_range_threshold(item, bins, percent):
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hist, bin_edges = item.get_histogram(bins)
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hist = np.concatenate((hist, [0]))
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threshold = .5*percent/100*hist.sum()
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i_bin_min = np.cumsum(hist).searchsorted(threshold)
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i_bin_max = -1-np.cumsum(np.flipud(hist)).searchsorted(threshold)
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return bin_edges[i_bin_min], bin_edges[i_bin_max]
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class HistogramItem(CurveItem):
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"""A Qwt item representing histogram data"""
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__implements__ = (IBasePlotItem,)
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def __init__(self, curveparam=None, histparam=None):
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self.hist_count = None
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self.hist_bins = None
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self.remove_first_bin = None
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self.old_logscale = None
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if curveparam is None:
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curveparam = CurveParam(_("Curve"), icon='curve.png')
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curveparam.curvestyle = "Steps"
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if histparam is None:
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self.histparam = HistogramParam(title=_("Histogram"),
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icon='histogram.png')
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self.histparam = histparam
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CurveItem.__init__(self, curveparam)
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self.setCurveAttribute(QwtPlotCurve.Inverted)
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def set_hist_source(self, src):
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(source: object with method 'get_histogram',
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e.g. objects derived from guiqwt.image.ImageItem)
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self.update_histogram()
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def set_hist_data(self, data):
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"""Set histogram data"""
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self.set_hist_source(HistDataSource(data))
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def set_logscale(self, state):
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"""Sets whether we use a logarithm or linear scale
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for the histogram counts"""
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self.logscale = state
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self.update_histogram()
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def get_logscale(self):
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"""Returns the status of the scale"""
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def set_remove_first_bin(self, state):
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self.remove_first_bin = state
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self.update_histogram()
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def get_remove_first_bin(self):
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return self.remove_first_bin
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def set_bins(self, n_bins):
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self.update_histogram()
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def compute_histogram(self):
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return self.source.get_histogram(self.bins)
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def update_histogram(self):
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if self.source is None:
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hist, bin_edges = self.compute_histogram()
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hist = np.concatenate((hist, [0]))
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if self.remove_first_bin:
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hist = np.log(hist+1)
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self.set_data(bin_edges, hist)
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# Autoscale only if logscale/bins have changed
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if self.bins != self.old_bins or self.logscale != self.old_logscale:
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self.plot().do_autoscale()
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self.old_bins = self.bins
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self.old_logscale = self.logscale
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plot.do_autoscale(replot=True)
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def update_params(self):
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self.histparam.update_hist(self)
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super(HistogramItem, self).update_params()
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def get_item_parameters(self, itemparams):
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super(HistogramItem, self).get_item_parameters(itemparams)
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itemparams.add("HistogramParam", self, self.histparam)
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def set_item_parameters(self, itemparams):
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update_dataset(self.histparam, itemparams.get("HistogramParam"),
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self.histparam.update_hist(self)
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super(HistogramItem, self).set_item_parameters(itemparams)
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assert_interfaces_valid(HistogramItem)
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class LevelsHistogram(CurvePlot):
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"""Image levels histogram widget"""
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def __init__(self, parent=None):
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super(LevelsHistogram, self).__init__(parent=parent, title="",
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self.antialiased = False
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# a dict of dict : plot -> selected items -> HistogramItem
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self._tracked_items = {}
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self.curveparam = CurveParam(_("Curve"), icon="curve.png")
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self.curveparam.read_config(CONF, "histogram", "curve")
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self.histparam = HistogramParam(_("Histogram"), icon="histogram.png")
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self.histparam.logscale = False
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self.histparam.remove_first_bin = True
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self.histparam.n_bins = 256
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self.range = XRangeSelection(0, 1)
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self.range_mono_color = self.range.shapeparam.sel_line.color
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self.range_multi_color = CONF.get("histogram",
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"range/multi/color", "red")
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self.add_item(self.range, z=5)
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self.connect(self, SIG_RANGE_CHANGED, self.range_changed)
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self.set_active_item(self.range)
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self.setMinimumHeight(80)
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self.setAxisMaxMajor(self.yLeft, 5)
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self.setAxisMaxMinor(self.yLeft, 0)
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self.set_axis_title('bottom', 'Levels')
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def connect_plot(self, plot):
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if not isinstance(plot, ImagePlot):
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# Connecting only to image plot widgets (allow mixing image and
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# curve widgets for the same plot manager -- e.g. in pyplot)
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self.connect(self, SIG_VOI_CHANGED, plot.notify_colormap_changed)
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self.connect(plot, SIG_ITEM_SELECTION_CHANGED, self.selection_changed)
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self.connect(plot, SIG_ACTIVE_ITEM_CHANGED, self.active_item_changed)
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def standard_tools(self, manager):
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manager.add_tool(SelectTool)
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manager.add_tool(BasePlotMenuTool, "item")
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manager.add_tool(BasePlotMenuTool, "axes")
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manager.add_tool(BasePlotMenuTool, "grid")
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manager.add_tool(AntiAliasingTool)
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manager.get_default_tool().activate()
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def tracked_items_gen(self):
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for plot, items in self._tracked_items.items():
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for item in items.items():
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yield item # tuple item,curve
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def __del_known_items(self, known_items, items):
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for item in known_items.keys():
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if item not in items:
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curve = known_items.pop(item)
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del_curves.append(curve)
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self.del_items(del_curves)
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def selection_changed(self, plot):
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items = plot.get_selected_items(IVoiImageItemType)
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known_items = self._tracked_items.setdefault(plot, {})
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self.__del_known_items(known_items, items)
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# Removing any cached item for other plots
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for other_plot, _items in self._tracked_items.items():
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if other_plot is not plot:
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if not other_plot.get_selected_items(IVoiImageItemType):
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other_known_items = self._tracked_items[other_plot]
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self.__del_known_items(other_known_items, [])
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# if all items are deselected we keep the last known
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# selection (for one plot only)
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for other_plot, _items in self._tracked_items.items():
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if other_plot.get_selected_items(IVoiImageItemType):
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self.__del_known_items(known_items, [])
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if item not in known_items:
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curve = HistogramItem(self.curveparam, self.histparam)
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curve.set_hist_source(item)
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self.add_item(curve, z=0)
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known_items[item] = curve
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nb_selected = len(list(self.tracked_items_gen()))
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self.curveparam.shade = 1.0/nb_selected
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for item, curve in self.tracked_items_gen():
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self.curveparam.update_curve(curve)
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self.histparam.update_hist(curve)
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self.active_item_changed(plot)
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def active_item_changed(self, plot):
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items = plot.get_selected_items(IVoiImageItemType)
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active = plot.get_last_active_item(IVoiImageItemType)
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active_range = active.get_lut_range()
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multiple_ranges = False
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for item, curve in self.tracked_items_gen():
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if active_range != item.get_lut_range():
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multiple_ranges = True
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if active_range is not None:
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_m, _M = active_range
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self.set_range_style(multiple_ranges)
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self.range.set_range(_m, _M, dosignal=False)
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def set_range_style(self, multiple_ranges):
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self.range.shapeparam.sel_line.color = self.range_multi_color
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self.range.shapeparam.sel_line.color = self.range_mono_color
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self.range.shapeparam.update_range(self.range)
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def set_range(self, _min, _max):
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self.set_range_style(False)
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self.range.set_range(_min, _max)
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# Range was not changed
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def range_changed(self, _rangesel, _min, _max):
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for item, curve in self.tracked_items_gen():
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item.set_lut_range([_min, _max])
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self.emit(SIG_VOI_CHANGED)
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def set_full_range(self):
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"""Set range bounds to image min/max levels"""
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for item, curve in self.tracked_items_gen():
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imin, imax = item.get_lut_range_full()
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if _min is None or _min>imin:
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if _max is None or _max<imax:
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self.set_range(_min, _max)
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def apply_min_func(self, item, curve, min):
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_min, _max = item.get_lut_range()
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def apply_max_func(self, item, curve, max):
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_min, _max = item.get_lut_range()
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def reduce_range_func(self, item, curve, percent):
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return lut_range_threshold(item, curve.bins, percent)
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def apply_range_function(self, func, *args, **kwargs):
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for item, curve in self.tracked_items_gen():
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_min, _max = func(item, curve, *args, **kwargs)
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item.set_lut_range([_min, _max])
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self.emit(SIG_VOI_CHANGED)
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self.active_item_changed(item.plot())
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def eliminate_outliers(self, percent):
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eliminate percent/2*N counts on each side of the histogram
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(where N is the total count number)
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self.apply_range_function(self.reduce_range_func, percent)
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def set_min(self, _min):
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self.apply_range_function(self.apply_min_func, _min)
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def set_max(self, _max):
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self.apply_range_function(self.apply_max_func, _max)
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class EliminateOutliersParam(DataSet):
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percent = FloatItem(_("Eliminate outliers")+" (%)",
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default=2., min=0., max=100.-1e-6)
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class ContrastAdjustment(PanelWidget):
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"""Contrast adjustment tool"""
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__implements__ = (IPanel,)
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PANEL_ID = ID_CONTRAST
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def __init__(self, parent=None):
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super(ContrastAdjustment, self).__init__(parent)
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widget_title = _("Contrast adjustment tool")
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widget_icon = "contrast.png"
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self.local_manager = None # local manager for the histogram plot
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self.manager = None # manager for the associated image plot
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# Storing min/max markers for each active image
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self.min_markers = {}
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self.max_markers = {}
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self.min_select_tool = None
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self.max_select_tool = None
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style = "<span style=\'color: #444444\'><b>%s</b></span>"
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layout, _label = get_image_layout(widget_icon,
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style % widget_title,
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alignment=Qt.AlignCenter)
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layout.setAlignment(Qt.AlignCenter)
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vlayout = QVBoxLayout()
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vlayout.addLayout(layout)
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self.local_manager = PlotManager(self)
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self.histogram = LevelsHistogram(parent)
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vlayout.addWidget(self.histogram)
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self.local_manager.add_plot(self.histogram)
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hlayout = QHBoxLayout()
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self.setLayout(hlayout)
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hlayout.addLayout(vlayout)
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self.toolbar = toolbar = QToolBar(self)
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toolbar.setOrientation(Qt.Vertical)
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# toolbar.setToolButtonStyle(Qt.ToolButtonTextBesideIcon)
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hlayout.addWidget(toolbar)
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self.histogram.standard_tools(self.local_manager)
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self.setWindowIcon(get_icon(widget_icon))
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self.setWindowTitle(widget_title)
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self.outliers_param = EliminateOutliersParam(widget_title)
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def register_panel(self, manager):
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"""Register panel to plot manager"""
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self.manager = manager
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default_toolbar = self.manager.get_default_toolbar()
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self.manager.add_toolbar(self.toolbar, "contrast")
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self.manager.set_default_toolbar(default_toolbar)
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for plot in manager.get_plots():
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self.histogram.connect_plot(plot)
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return self.manager.get_active_plot()
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def closeEvent(self, event):
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def setup_actions(self):
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fullrange_ac = create_action(self, _("Full range"),
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icon=get_icon("full_range.png"),
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triggered=self.histogram.set_full_range,
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tip=_("Scale the image's display range "
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"according to data range") )
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autorange_ac = create_action(self, _("Eliminate outliers"),
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icon=get_icon("eliminate_outliers.png"),
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triggered=self.eliminate_outliers,
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tip=_("Eliminate levels histogram "
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"outliers and scale the image's "
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"display range accordingly") )
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add_actions(self.toolbar,[fullrange_ac, autorange_ac])
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self.min_select_tool = self.manager.add_tool(SelectPointTool,
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title=_("Minimum level"),
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on_active_item=True,mode="create",
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tip=_("Select minimum level on image"),
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toolbar_id="contrast",
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end_callback=self.apply_min_selection)
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self.max_select_tool = self.manager.add_tool(SelectPointTool,
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title=_("Maximum level"),
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on_active_item=True,mode="create",
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tip=_("Select maximum level on image"),
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toolbar_id="contrast",
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end_callback=self.apply_max_selection)
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def eliminate_outliers(self):
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self.histogram.eliminate_outliers(param.percent)
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if self.outliers_param.edit(self, apply=apply):
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apply(self.outliers_param)
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def apply_min_selection(self, tool):
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item = self.get_plot().get_last_active_item(IVoiImageItemType)
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point = self.min_select_tool.get_coordinates()
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z = item.get_data(*point)
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self.histogram.set_min(z)
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def apply_max_selection(self, tool):
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item = self.get_plot().get_last_active_item(IVoiImageItemType)
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point = self.max_select_tool.get_coordinates()
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z = item.get_data(*point)
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self.histogram.set_max(z)
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def set_range(self, _min, _max):
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"""Set contrast panel's histogram range"""
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self.histogram.set_range(_min, _max)
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# Update the levels histogram in case active item data has changed:
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self.histogram.selection_changed(self.get_plot())
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assert_interfaces_valid(ContrastAdjustment)
added
removed
guiqwt/histogram.py
