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.SIG_RANGE_CHANGED.connect(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 histogram(
self,
data,
bins=None,
logscale=None,
title="",
color=None,
xaxis="bottom",
yaxis="left",
):
"""
Make 1D Histogram `plot item`
(:py:class:`guiqwt.histogram.HistogramItem` object)
* data (1D NumPy array)
* bins: number of bins (int)
* logscale: Y-axis scale (bool)
"""
basename = _("Histogram")
histparam = HistogramParam(title=basename, icon="histogram.png")
curveparam = CurveParam(_("Curve"), icon="curve.png")
curveparam.read_config(CONF, "histogram", "curve")
if not title:
global HISTOGRAM_COUNT
HISTOGRAM_COUNT += 1
title = make_title(basename, HISTOGRAM_COUNT)
curveparam.label = title
if color is not None:
curveparam.line.color = color
if bins is not None:
histparam.n_bins = bins
if logscale is not None:
histparam.logscale = logscale
return self.phistogram(data, curveparam, histparam, xaxis, yaxis)
def histogram(self, data, bins=None, logscale=None,
title="", color=None, xaxis="bottom", yaxis="left"):
"""
Make 1D Histogram `plot item`
(:py:class:`guiqwt.histogram.HistogramItem` object)
* data (1D NumPy array)
* bins: number of bins (int)
* logscale: Y-axis scale (bool)
"""
basename = _("Histogram")
histparam = HistogramParam(title=basename, icon='histogram.png')
curveparam = CurveParam(_("Curve"), icon='curve.png')
curveparam.read_config(CONF, "histogram", "curve")
if not title:
global HISTOGRAM_COUNT
HISTOGRAM_COUNT += 1
title = make_title(basename, HISTOGRAM_COUNT)
curveparam.label = title
if color is not None:
curveparam.line.color = color
if bins is not None:
histparam.n_bins = bins
if logscale is not None:
histparam.logscale = logscale
return self.phistogram(data, curveparam, histparam, xaxis, yaxis)
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 __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 __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)
class LevelsHistogram(CurvePlot):
"""Image levels histogram widget"""
#: Signal emitted by LevelsHistogram when LUT range was changed
SIG_VOI_CHANGED = Signal()
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.SIG_RANGE_CHANGED.connect(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.SIG_VOI_CHANGED.connect(plot.notify_colormap_changed)
plot.SIG_ITEM_SELECTION_CHANGED.connect(self.selection_changed)
plot.SIG_ITEM_REMOVED.connect(self.item_removed)
plot.SIG_ACTIVE_ITEM_CHANGED.connect(self.active_item_changed)
def tracked_items_gen(self):
for plot, items in list(self._tracked_items.items()):
for item in list(items.items()):
yield item # tuple item,curve
def __del_known_items(self, known_items, items):
del_curves = []
for item in list(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 list(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 list(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 list(self._tracked_items.items()):
if item in items:
curve = items.pop(item)
self.del_items([curve])
self.replot()
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.SIG_VOI_CHANGED.emit()
def set_full_range(self):
"""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.SIG_VOI_CHANGED.emit()
if item is not None:
self.active_item_changed(item.plot())
def eliminate_outliers(self, percent):
"""
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 HistogramItem(CurveItem):
"""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):
"""
Set histogram source
*source*:
Object with method `get_histogram`, e.g. objects derived from
:py:data:`guiqwt.image.ImageItem`
"""
self.source = weakref.ref(src)
self.update_histogram()
def get_hist_source(self):
"""
Return histogram source
*source*:
Object with method `get_histogram`, e.g. objects derived from
:py:data:`guiqwt.image.ImageItem`
"""
if self.source is not None:
return self.source()
def set_hist_data(self, data):
"""Set histogram data"""
self.set_hist_source(HistDataSource(data))
def set_logscale(self, state):
"""Sets whether we use a logarithm or linear scale
for the histogram counts"""
self.logscale = state
self.update_histogram()
def get_logscale(self):
"""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)
class LevelsHistogram(CurvePlot):
"""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 list(self._tracked_items.items()):
for item in list(items.items()):
yield item # tuple item,curve
def __del_known_items(self, known_items, items):
del_curves = []
for item in list(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 list(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 list(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 list(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):
"""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):
"""
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 HistogramItem(CurveItem):
"""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):
"""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):
"""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):
"""Set histogram data"""
self.set_hist_source(HistDataSource(data))
def set_logscale(self, state):
"""Sets whether we use a logarithm or linear scale
for the histogram counts"""
self.logscale = state
self.update_histogram()
def get_logscale(self):
"""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)
