/usr/lib/python2.7/dist-packages/guiqwt/histogram.py is in python-guiqwt 3.0.2-1ubuntu1.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 | # -*- coding: utf-8 -*-
#
# Copyright © 2009-2010 CEA
# Pierre Raybaut
# Licensed under the terms of the CECILL License
# (see guiqwt/__init__.py for details)
# pylint: disable=C0103
"""
guiqwt.histogram
----------------
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`.
Example
~~~~~~~
Simple histogram plotting example:
.. literalinclude:: /../guiqwt/tests/histogram.py
Reference
~~~~~~~~~
.. autoclass:: HistogramItem
:members:
:inherited-members:
.. autoclass:: ContrastAdjustment
:members:
:inherited-members:
.. autoclass:: LevelsHistogram
:members:
:inherited-members:
"""
import weakref
import numpy as np
from guidata.qt.QtCore import Qt, Signal
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 guiqwt.tools import (SelectTool, BasePlotMenuTool, SelectPointTool,
AntiAliasingTool)
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):
self.data = data
def get_histogram(self, nbins):
"""Returns the histogram computed for nbins bins"""
return np.histogram(self.data, nbins)
assert_interfaces_valid(HistDataSource)
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):
"""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)
assert_interfaces_valid(HistogramItem)
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 EliminateOutliersParam(DataSet):
percent = FloatItem(_("Eliminate outliers")+" (%)",
default=2., min=0., max=100.-1e-6)
class ContrastAdjustment(PanelWidget):
"""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):
"""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):
"""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):
"""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)
|