def compute(self, name, func, param=None, suffix=None, interactive=True):
try:
result = self.start_compute(name, func, param, suffix, interactive)
return self.end_compute(result)
except ComputationError, msg:
print _("Computation error: %s") % msg
return
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 setup_actions(self):
CrossSectionWidget.setup_actions(self)
self.peritem_ac = create_action(
self,
_("Per image cross-section"),
icon=get_icon("csperimage.png"),
toggled=self.cs_plot.toggle_perimage_mode,
tip=_(
"Enable the per-image cross-section mode, "
"which works directly on image rows/columns.\n"
"That is the fastest method to compute "
"cross-section curves but it ignores "
"image transformations (e.g. rotation)"
),
)
self.applylut_ac = create_action(
self,
_("Apply LUT\n(contrast settings)"),
icon=get_icon("csapplylut.png"),
toggled=self.cs_plot.toggle_apply_lut,
tip=_(
"Apply LUT (Look-Up Table) contrast settings.\n"
"This is the easiest way to compare images "
"which have slightly different level ranges.\n\n"
"Note: LUT is coded over 1024 levels (0...1023)"
),
)
self.peritem_ac.setChecked(True)
self.applylut_ac.setChecked(False)
def about(self):
QMessageBox.about( self, _("About ")+APP_NAME,
"""<b>%s</b> v%s<p>%s Matt Nottingham
<br>Copyright © 2015 Matt Nottingham
<p>Python %s, Qt %s, PyQt %s %s %s""" % \
(APP_NAME, VERS, _("Developped by"), platform.python_version(),
QT_VERSION_STR, PYQT_VERSION_STR, _("on"), platform.system()) )
def set_slice_value(self, value):
"""Set the current slice to a given value. If the value is not in the
measured discrete scale, it will interpolate data between the adjacent
slices.
\arg value a float within scale.min() and scale.max()
"""
assert isinstance(value,
(int, float)), _('Slice value has to be a float')
scale = self.measurement.param.axis3.get_scale()
if not scale.min() <= value <= scale.max():
raise ValueError, _('Slice value out of range')
if value in scale:
# get the index with value nearest to v
index = where(scale == value)[0][0]
self.set_data(self.measurement.rawdata[index, :, :])
else:
# get the lowest index with value nearest to v
index = where(scale > value)[0][0]
coef = (value - scale[index]) / (scale[index + 1] - scale[index])
rawdata = self.measurement.rawdata
interpolated_data = rawdata[index,:,:] * (1 - coef) \
+ rawdata[index+1,:,:] * coef
self.set_data(interpolated_data)
self.current_index = index
def exec_image_open_dialog(parent,
basedir='',
app_name=None,
to_grayscale=True,
dtype=None):
"""
Executes an image open dialog box (QFileDialog.getOpenFileName)
* parent: parent widget (None means no parent)
* basedir: base directory ('' means current directory)
* app_name (opt.): application name (used as a title for an eventual
error message box in case something goes wrong when saving image)
* to_grayscale (default=True): convert image to grayscale
Returns (filename, data) tuple if dialog is accepted, None otherwise
"""
saved_in, saved_out, saved_err = sys.stdin, sys.stdout, sys.stderr
sys.stdout = None
filename, _filter = getopenfilename(
parent, _("Open"), basedir,
io.iohandler.get_filters('load', dtype=dtype))
sys.stdin, sys.stdout, sys.stderr = saved_in, saved_out, saved_err
filename = to_text_string(filename)
try:
data = io.imread(filename, to_grayscale=to_grayscale)
except Exception as msg:
import traceback
traceback.print_exc()
QMessageBox.critical(parent,
_('Error') if app_name is None else app_name,
(_("%s could not be opened:") % osp.basename(filename))+\
"\n"+str(msg))
return
return filename, data
def get_infos(self):
"""Return formatted string with informations on current shape"""
return "<br>".join([
_("Center:") + " " + self.get_tr_center_str(),
_("Size:") + " " + self.get_tr_size_str(),
_("Angle:") + " %.1f°" % self.get_tr_angle(),
])
def about(self):
QMessageBox.about( self, _("About ")+APP_NAME,
"""<b>%s</b> v%s<p>%s Pierre Raybaut
<br>Copyright © 2009-2010 CEA
<p>Python %s, Qt %s, PyQt %s %s %s""" % \
(APP_NAME, VERSION, _("Developped by"), platform.python_version(),
QT_VERSION_STR, PYQT_VERSION_STR, _("on"), platform.system()) )
def create_window(self, items):
if not isinstance(items, (tuple, list)):
items = (items,)
for item in items:
if isinstance(item, ThothCurveItem):
window = self._create_curve_window(item)
elif isinstance(item, ThothImageItem):
window = self._create_image_window(item)
elif isinstance(item, ThothMapItem):
window = self._create_map_window(item)
else:
raise ValueError, _('Not supported measurement type')
other_tools = window.addToolBar(_("Other tools"))
window.add_toolbar(other_tools,
toolbar_id="other_tools")
for toolklass in (LabelTool, HRangeTool,
VCursorTool, HCursorTool, XCursorTool,
SegmentTool, RectangleTool, ObliqueRectangleTool,
CircleTool, EllipseTool,
MultiLineTool, FreeFormTool, PlaceAxesTool,
AnnotatedRectangleTool,
AnnotatedObliqueRectangleTool,
AnnotatedCircleTool, AnnotatedEllipseTool,
AnnotatedSegmentTool, AnnotatedPointTool,
WeightTool,
SelectPointTool,
ExtractCurveTool,
):
window.add_tool(toolklass, toolbar_id="other_tools")
self.register_window(window)
def about(self):
QMessageBox.about( self, _("About ")+APP_NAME,
"""<b>%s</b> v%s<p>%s Pierre Raybaut
<br>Copyright © 2009-2010 CEA
<p>Python %s, Qt %s, PyQt %s %s %s""" % \
(APP_NAME, VERSION, _("Developped by"), platform.python_version(),
QT_VERSION_STR, PYQT_VERSION_STR, _("on"), platform.system()) )
def exec_image_open_dialog(parent, basedir='', app_name=None,
to_grayscale=True, dtype=None):
"""
Executes an image open dialog box (QFileDialog.getOpenFileName)
* parent: parent widget (None means no parent)
* basedir: base directory ('' means current directory)
* app_name (opt.): application name (used as a title for an eventual
error message box in case something goes wrong when saving image)
* to_grayscale (default=True): convert image to grayscale
Returns (filename, data) tuple if dialog is accepted, None otherwise
"""
saved_in, saved_out, saved_err = sys.stdin, sys.stdout, sys.stderr
sys.stdout = None
filename, _filter = getopenfilename(parent, _("Open"), basedir,
io.iohandler.get_filters('load', dtype=dtype))
sys.stdin, sys.stdout, sys.stderr = saved_in, saved_out, saved_err
filename = to_text_string(filename)
try:
data = io.imread(filename, to_grayscale=to_grayscale)
except Exception as msg:
import traceback
traceback.print_exc()
QMessageBox.critical(parent,
_('Error') if app_name is None else app_name,
(_("%s could not be opened:") % osp.basename(filename))+\
"\n"+str(msg))
return
return filename, data
def compute_ifft(self):
"""Compute iFFT"""
import numpy.fft
from numpy import absolute
def func(data):
return array([
numpy.fft.fftshift(absolute(numpy.fft.ifft2(slice_)))
for slice_ in data
])
result = self.start_compute(_('Fourrier transform'), func)
new_x = numpy.fft.fftshift(
numpy.fft.fftfreq(self['axis1']['length'],
d=self['axis1']['increment']))
new_y = numpy.fft.fftshift(
numpy.fft.fftfreq(self['axis2']['length'],
d=self['axis2']['increment']))
result['unit'] = _('a.u.')
result['axis1']['start'] = new_x[0]
result['axis1']['increment'] = new_x[1] - new_x[0]
result['axis1']['unit'] = '1/%s' % result['axis1']['unit']
result['axis2']['start'] = new_y[0]
result['axis2']['increment'] = new_y[1] - new_y[0]
result['axis2']['unit'] = '1/%s' % result['axis2']['unit']
return self.end_compute(result)
def __floordiv__(self, a):
if not isinstance(a, (int, float)):
raise TypeError, _('Unsupported operand type')
new_param = self.param.copy()
new_param.processing += _('divided by %2.3g') % (a, ) + '\n'
new_data = self.rawdata // a
return Measurement(new_data, new_param)
def compute_spline_derivative(self, param=None, interactive=True):
""" Compute the derivative of the curve basde on spline
interpolation"""
from scipy.interpolate import splrep, splev
class SplineParam(DataSet):
s = FloatItem(_("s"),
default=0.1,
min=0,
help=_('''Larger s means more smoothing while
smaller values of s indicate less smoothing. 0 is no smoothing.'''))
if param is None:
param = SplineParam(_("Spline smoothing"))
def func(y, p):
tck = splrep(arange(len(y)), y, s=p.s) # get spline coef tuple
return splev(arange(len(y)), tck, der=1) # compute 1st derivative
result = self.start_compute(_("Spline derivative"), func, param,
lambda p: u"s=%i" % p.s, interactive)
if result['type'] == 'ivcurve':
result['type'] = 'didvcurve'
result['unit'] = _('a.u.')
else:
result['type'] == 'unknowncurve'
return self.end_compute(result)
def compute_savitzky(self, param=None, interactive=True):
"""Linewise smoothing of data based on the Savitzky-Golay
algorithm"""
import sgfilter
class SGParam(DataSet):
num_points = IntItem(_("Number of points"), default=8, min=2)
poly_degree = IntItem(_("Polynom degree"), default=4, min=1)
diff_order = 0
if param is None:
param = SGParam(_("Savitzky-Golay filter"))
def func(data, p):
return array([
sgfilter.savitzky(line, p.num_points, p.poly_degree,
p.diff_order) for line in data
])
return self.compute(_('Smoothed with Savitzky-Golay'),
func,
param,
lambda p: _("""%i points, polynom degree %i, differential order %i""") % \
(p.poly_degree, p.num_points,
p.diff_order),
interactive=interactive)
def add_buttons_to_layout(self, layout):
"""Add tool buttons to layout"""
# Image orientation
angle_label = QLabel(_("Angle (°):"))
layout.addWidget(angle_label)
self.angle_combo = QComboBox(self)
self.angle_combo.addItems(self.ROTATION_ANGLES)
self.angle_combo.setCurrentIndex(1)
self.angle_combo.currentIndexChanged.connect(
lambda index: self.apply_transformation())
layout.addWidget(self.angle_combo)
layout.addSpacing(10)
# Image flipping
flip_label = QLabel(_("Flip:"))
layout.addWidget(flip_label)
hflip = create_toolbutton(
self,
text="",
icon=get_icon("hflip.png"),
toggled=lambda state: self.apply_transformation(),
autoraise=False)
self.hflip_btn = hflip
layout.addWidget(hflip)
vflip = create_toolbutton(
self,
text="",
icon=get_icon("vflip.png"),
toggled=lambda state: self.apply_transformation(),
autoraise=False)
self.vflip_btn = vflip
layout.addWidget(vflip)
layout.addSpacing(15)
self.add_reset_button(layout)
def compute_savitzky(self, param=None, interactive=True):
"""Smooth or derivate data based on the Savitzky-Golay algorithm"""
import sgfilter
class SGParam(DataSet):
num_points = IntItem(_("Number of points"), default=8, min=2)
poly_degree = IntItem(_("Polynom degree"), default=4, min=1)
diff_order = IntItem(_("Differential order"), default=0, min=0)
if param is None:
param = SGParam(_("Savitzky-Golay filter"))
def func(y, p):
return sgfilter.savitzky(y, p.num_points, p.poly_degree,
p.diff_order)
try:
result = self.start_compute(_('Smoothed with Savitzky-Golay'),
func,
param,
lambda p: _("""%i points, polynom degree %i, differential order %i""") % \
(p.poly_degree, p.num_points,
p.diff_order),
interactive)
if param.diff_order == 1 and result['type'] == 'ivcurve':
result['type'] = 'didvcurve'
result['unit'] = _('a.u.')
else:
result['type'] == 'unknowncurve'
return self.end_compute(result)
except ComputationError, msg:
print msg
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 __init__(self, parent=None, section="plot"):
super(BasePlot, self).__init__(parent)
self._start_autoscaled = True
self.setSizePolicy(QSizePolicy.Expanding, QSizePolicy.Expanding)
self.manager = None
self.plot_id = None # id assigned by it's manager
self.filter = StatefulEventFilter(self)
self.items = []
self.active_item = None
self.last_selected = {
} # a mapping from item type to last selected item
self.axes_styles = [
AxeStyleParam(_("Left")),
AxeStyleParam(_("Right")),
AxeStyleParam(_("Bottom")),
AxeStyleParam(_("Top")),
]
self._active_xaxis = self.DEFAULT_ACTIVE_XAXIS
self._active_yaxis = self.DEFAULT_ACTIVE_YAXIS
self.read_axes_styles(section, self.AXIS_CONF_OPTIONS)
self.font_title = get_font(CONF, section, "title")
canvas = self.canvas()
canvas.setFocusPolicy(Qt.StrongFocus)
canvas.setFocusIndicator(QwtPlotCanvas.ItemFocusIndicator)
self.SIG_ITEM_MOVED.connect(self._move_selected_items_together)
self.legendDataChanged.connect(
lambda item, _legdata: item.update_item_parameters())
def add_buttons_to_layout(self, layout):
"""Add tool buttons to layout"""
# Image orientation
angle_label = QLabel(_("Angle (°):"))
layout.addWidget(angle_label)
self.angle_combo = QComboBox(self)
self.angle_combo.addItems(self.ROTATION_ANGLES)
self.angle_combo.setCurrentIndex(1)
self.angle_combo.currentIndexChanged.connect(
lambda index: self.apply_transformation())
layout.addWidget(self.angle_combo)
layout.addSpacing(10)
# Image flipping
flip_label = QLabel(_("Flip:"))
layout.addWidget(flip_label)
hflip = create_toolbutton(self, text="", icon=get_icon("hflip.png"),
toggled=lambda state: self.apply_transformation(),
autoraise=False)
self.hflip_btn = hflip
layout.addWidget(hflip)
vflip = create_toolbutton(self, text="", icon=get_icon("vflip.png"),
toggled=lambda state: self.apply_transformation(),
autoraise=False)
self.vflip_btn = vflip
layout.addWidget(vflip)
layout.addSpacing(15)
self.add_reset_button(layout)
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 setup_actions(self):
CrossSectionWidget.setup_actions(self)
self.peritem_ac = create_action(
self,
_("Per image cross-section"),
icon=get_icon("csperimage.png"),
toggled=self.cs_plot.toggle_perimage_mode,
tip=_(
"Enable the per-image cross-section mode, "
"which works directly on image rows/columns.\n"
"That is the fastest method to compute "
"cross-section curves but it ignores "
"image transformations (e.g. rotation)"
),
)
self.applylut_ac = create_action(
self,
_("Apply LUT\n(contrast settings)"),
icon=get_icon("csapplylut.png"),
toggled=self.cs_plot.toggle_apply_lut,
tip=_(
"Apply LUT (Look-Up Table) contrast settings.\n"
"This is the easiest way to compare images "
"which have slightly different level ranges.\n\n"
"Note: LUT is coded over 1024 levels (0...1023)"
),
)
self.peritem_ac.setChecked(True)
self.applylut_ac.setChecked(False)
def get_infos(self):
"""Return formatted string with informations on current shape"""
return "<br>".join([
_("Center:") + " " + self.get_tr_center_str(),
_("Size:") + " " + self.get_tr_size_str(),
_("Angle:") + " %.1f°" % self.get_tr_angle(),
])
def exec_image_save_dialog(parent, data, template=None,
basedir='', app_name=None):
"""
Executes an image save dialog box (QFileDialog.getSaveFileName)
* parent: parent widget (None means no parent)
* data: image pixel array data
* template: image template (pydicom dataset) for DICOM files
* basedir: base directory ('' means current directory)
* app_name (opt.): application name (used as a title for an eventual
error message box in case something goes wrong when saving image)
Returns filename if dialog is accepted, None otherwise
"""
saved_in, saved_out, saved_err = sys.stdin, sys.stdout, sys.stderr
sys.stdout = None
filename, _filter = getsavefilename(parent, _("Save as"), basedir,
io.iohandler.get_filters('save', dtype=data.dtype, template=template))
sys.stdin, sys.stdout, sys.stderr = saved_in, saved_out, saved_err
if filename:
filename = to_text_string(filename)
kwargs = {}
if osp.splitext(filename)[1].lower() == '.dcm':
kwargs['template'] = template
try:
io.imwrite(filename, data, **kwargs)
return filename
except Exception as msg:
import traceback
traceback.print_exc()
QMessageBox.critical(parent,
_('Error') if app_name is None else app_name,
(_("%s could not be written:") % osp.basename(filename))+\
"\n"+str(msg))
return
def about( self ):
QMessageBox.about( self, _("About ")+APP_NAME,
"""<b>%s</b> v%s<p>%s Darko Petrovic
<br>(Lisence goes here)
<p>Python %s, Qt %s, PyQt %s %s %s""" % \
(APP_NAME, VERSION, _("Developped by"), platform.python_version(),
QT_VERSION_STR, PYQT_VERSION_STR, _("on"), platform.system()) )
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 setup_actions(self):
self.export_ac = self.export_tool.action
self.lockscales_ac = create_action(
self,
_("Lock scales"),
icon=get_icon('axes.png'),
toggled=self.cs_plot.toggle_lockscales,
tip=_("Lock scales to main plot axes"))
self.lockscales_ac.setChecked(self.cs_plot.lockscales)
self.autoscale_ac = create_action(
self,
_("Auto-scale"),
icon=get_icon('csautoscale.png'),
toggled=self.cs_plot.toggle_autoscale)
self.autoscale_ac.toggled.connect(self.lockscales_ac.setDisabled)
self.autoscale_ac.setChecked(self.cs_plot.autoscale_mode)
self.refresh_ac = create_action(
self,
_("Refresh"),
icon=get_icon('refresh.png'),
triggered=lambda: self.cs_plot.update_plot())
self.autorefresh_ac = create_action(
self,
_("Auto-refresh"),
icon=get_icon('autorefresh.png'),
toggled=self.cs_plot.toggle_autorefresh)
self.autorefresh_ac.setChecked(self.cs_plot.autorefresh_mode)
def __add__(self, a):
if isinstance(a, self.__baseclass__):
return self.__baseclass__(self.measurement + a.measurement)
elif isinstance(a, (int, float)):
return self.__baseclass__(self.measurement + a)
else:
raise TypeError, _('Unsupported operand type')
def extract_curve(self, shape):
for item in self.get_active_plot().get_items():
if isinstance(item, ThothMapItem):
try:
item.compute_get_curve_at_position(*shape.get_pos())
except IndexError:
print _("Outside of image bound.")
break
def extract_curve(self, shape):
for item in self.get_active_plot().get_items():
if isinstance(item, ThothMapItem):
try:
item.compute_get_curve_at_position(*shape.get_pos())
except IndexError:
print _("Outside of image bound.")
break
def __init__(self, *args, **kwargs):
super(ROISelectTool, self).__init__(*args, **kwargs)
self.name = "ROI"
self.rect.label_txt = self.name
self.TIP = _("Select ROI")
self.TITLE = _("ROI")
'''
def compute_shift(self, param=None, interactive=True):
"""Shift the curve by the given amount"""
class ShiftParam(DataSet):
shift = FloatItem(_("Shift by"), default=1)
if param is None:
param = ShiftParam(_("Shift"))
return self.compute(_("Shifted"), lambda y, p: y + p.shift, param,
lambda p: _("shift = %.3f") % p.shift, interactive)
def __init__(self, parent):
QSplitter.__init__(self, parent)
self.parent = parent
self.Controlvalues = DataSetEditGroupBox(_("Control panel"),
Controlwidget,
show_button=False)
self.addWidget(self.Controlvalues)
self.HKvalues = DataSetShowGroupBox(_("Housekeeping"), HKwidget)
self.addWidget(self.HKvalues)
self.setSizes([2000, 1])
class SampleParameters(DataSet): #Sample parameters
index_medium = FloatItem(_("Medium index"), default=1.33, min=1.)
index_chamber = FloatItem(_("Chamber index closing the chamber"),
default=1.52,
min=1.)
index_sample = FloatItem(_("Sample index"), default=1., min=1.)
max_displacement = FloatItem(_("Max Displacement"),
default=20,
min=1.,
unit='pixels')
class RemoteParameters(ActivableDataSet): #Sequence parameters
#read database to know default directory
db = SqliteDB.DBReader()
directoryPath = DirectoryItem("Seq. dir.", default=db.DefaultDirectory)
first_holo_seq = IntItem(_("First hologram"), default=0, min=0)
#last holo seq is defined with framesNumberProp that is modified when a new directory is choose
last_holo_seq = IntItem(_("Last hologram"), default=framesNumberprop)
saveAllStack = ChoiceItem(_("Save All stacks"), [(True, 'Yes'),
(False, 'False')],
default=False)
def create_plot(self, options):
self.filter_gbox = DataSetEditGroupBox(_("Filter parameters"), FilterParam)
self.filter_gbox.setEnabled(False)
self.filter_gbox.SIG_APPLY_BUTTON_CLICKED.connect(self.apply_filter)
self.plot_layout.addWidget(self.filter_gbox, 0, 0)
self.param_gbox = DataSetShowGroupBox(_("Image parameters"), ImageParam)
self.plot_layout.addWidget(self.param_gbox, 0, 1)
options = dict(title=_("Image title"), zlabel=_("z-axis scale label"))
ImageDialog.create_plot(self, options, 1, 0, 1, 0)
def compute_scale(self, param=None, interactive=True):
"""Multiply the curve by the given factor"""
class ScaleParam(DataSet):
factor = FloatItem(_("Scaling factor"), default=1)
if param is None:
param = ScaleParam(_("Scaling"))
return self.compute(_("Scaled"), lambda y, p: y * p.factor, param,
lambda p: _("factor = %.3f") % p.factor,
interactive)
def edit_axis_parameters(self, axis_id):
"""Edit axis parameters"""
if axis_id in (self.Y_LEFT, self.Y_RIGHT):
title = _("Y Axis")
else:
title = _("X Axis")
param = AxisParam(title=title)
param.update_param(self, axis_id)
if param.edit(parent=self):
param.update_axis(self, axis_id)
self.replot()
def create_plot(self, options):
self.filter_gbox = DataSetEditGroupBox(_("Filter parameters"),
FilterParam)
self.filter_gbox.setEnabled(False)
self.filter_gbox.SIG_APPLY_BUTTON_CLICKED.connect(self.apply_filter)
self.plot_layout.addWidget(self.filter_gbox, 0, 0)
self.param_gbox = DataSetShowGroupBox(_("Image parameters"), ImageParam)
self.plot_layout.addWidget(self.param_gbox, 0, 1)
options = dict(title=_("Image title"), zlabel=_("z-axis scale label"))
ImageDialog.create_plot(self, options, 1, 0, 1, 0)
def edit_axis_parameters(self, axis_id):
"""Edit axis parameters"""
if axis_id in (self.Y_LEFT, self.Y_RIGHT):
title = _("Y Axis")
else:
title = _("X Axis")
param = AxisParam(title=title)
param.update_param(self, axis_id)
if param.edit(parent=self):
param.update_axis(self, axis_id)
self.replot()
def __getitem__(self, key):
if 'physical length' == key:
return self.get_physical_length()
elif 'length' == key:
return self.get_length()
elif 'scale' == key:
return self.get_scale()
else:
try:
return getattr(self, key)
except AttributeError:
raise KeyError, _("They are no such attributes %s.") % key
def setup(self):
"""Setup window parameters"""
self.setWindowIcon(get_icon("python.png"))
self.setWindowTitle(APP_NAME)
self.resize(QSize(600, 800))
# Welcome message in statusbar:
status = self.statusBar()
status.showMessage(_("Welcome to guiqwt application example!"), 5000)
# File menu
file_menu = self.menuBar().addMenu(_("File"))
new_action = create_action(
self,
_("New..."),
shortcut="Ctrl+N",
icon=get_icon("filenew.png"),
tip=_("Create a new image"),
triggered=self.new_image,
)
open_action = create_action(
self,
_("Open..."),
shortcut="Ctrl+O",
icon=get_icon("fileopen.png"),
tip=_("Open an image"),
triggered=self.open_image,
)
quit_action = create_action(
self,
_("Quit"),
shortcut="Ctrl+Q",
icon=get_std_icon("DialogCloseButton"),
tip=_("Quit application"),
triggered=self.close,
)
add_actions(file_menu, (new_action, open_action, None, quit_action))
# Help menu
help_menu = self.menuBar().addMenu("?")
about_action = create_action(
self,
_("About..."),
icon=get_std_icon("MessageBoxInformation"),
triggered=self.about,
)
add_actions(help_menu, (about_action, ))
main_toolbar = self.addToolBar("Main")
add_actions(main_toolbar, (
new_action,
open_action,
))
# Set central widget:
toolbar = self.addToolBar("Image")
self.mainwidget = CentralWidget(self, toolbar)
self.setCentralWidget(self.mainwidget)
def register_measurement(self, measurements):
if not isinstance(measurements, (tuple, list)):
measurements = (measurements,)
for measurement in measurements:
type_ = measurement.param.type
if type_ in ('ivcurve', 'didvcurve'):
self.register_item(ThothCurveItem(measurement))
elif type_ in ('topo','topofft'):
self.register_item(ThothImageItem(measurement))
elif type_ in ('ivmap','ivmapfft','didvmap','didvmapfft'):
self.register_item(ThothMapItem(measurement))
else:
raise ValueError, _('Not supported measurement type')
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 setup_actions(self):
self.export_ac = self.export_tool.action
self.autoscale_ac = create_action(self, _("Auto-scale"),
icon=get_icon('csautoscale.png'),
toggled=self.cs_plot.toggle_autoscale)
self.autoscale_ac.setChecked(self.cs_plot.autoscale_mode)
self.refresh_ac = create_action(self, _("Refresh"),
icon=get_icon('refresh.png'),
triggered=lambda: self.cs_plot.update_plot())
self.autorefresh_ac = create_action(self, _("Auto-refresh"),
icon=get_icon('autorefresh.png'),
toggled=self.cs_plot.toggle_autorefresh)
self.autorefresh_ac.setChecked(self.cs_plot.autorefresh_mode)
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 create_autofit_group(self):
auto_button = QPushButton(get_icon('apply.png'), _("Run"), self)
auto_button.clicked.connect(self.autofit)
autoprm_button = QPushButton(get_icon('settings.png'), _("Settings"),
self)
autoprm_button.clicked.connect(self.edit_parameters)
xrange_button = QPushButton(get_icon('xrange.png'), _("Bounds"), self)
xrange_button.setCheckable(True)
xrange_button.toggled.connect(self.toggle_xrange)
auto_layout = QVBoxLayout()
auto_layout.addWidget(auto_button)
auto_layout.addWidget(autoprm_button)
auto_layout.addWidget(xrange_button)
self.button_list += [auto_button, autoprm_button, xrange_button]
return create_groupbox(self, _("Automatic fit"), layout=auto_layout)
def about(html=True, copyright_only=False):
"""Return text about this package"""
import sys, os, os.path as osp, platform, guidata, guiqwt, qwt
from guiqwt.config import _
from guidata.qt.QtCore import QT_VERSION_STR, PYQT_VERSION_STR
name = __file__.split(osp.sep)[-2]
tf1 = (name, __version__, __description__)
tf2 = (platform.python_version(),
'64 bits' if sys.maxsize > 2**32 else '32 bits',
QT_VERSION_STR, PYQT_VERSION_STR,
qwt.__version__, guidata.__version__, guiqwt.__version__,
_("on"), platform.system())
if html:
short_desc = "This widget is powered by <b>%s</b> v%s"\
"<p>%s<p>Created by Pierre Raybaut" % tf1
desc = "Copyright © 2010-2016 CEA"\
"<p>Python %s %s, Qt %s, PyQt %s, "\
"PythonQwt %s, guidata %s, guiqwt %s %s %s" % tf2
if not copyright_only:
desc = short_desc + "<br>" + desc
else:
short_desc = """%s v%s : %s
Created by Pierre Raybaut""" % tf1
desc = """Copyright (c) 2010-2016 CEA
Python %s %s, Qt %s, PyQt %s, PythonQwt %s, guidata %s, guiqwt %s %s %s""" % tf2
if not copyright_only:
desc = short_desc + os.linesep + desc
return desc
def __init__(self, parent=None):
super(CrossSectionPlot, self).__init__(parent=parent, title="",
section="cross_section")
self.perimage_mode = True
self.autoscale_mode = True
self.autorefresh_mode = True
self.apply_lut = False
self.single_source = False
self.last_obj = None
self.known_items = {}
self._shapes = {}
self.curveparam = CurveParam(_("Curve"), icon="curve.png")
self.set_curve_style("cross_section", "curve")
if self._height is not None:
self.setSizePolicy(QSizePolicy.Expanding, QSizePolicy.Minimum)
elif self._width is not None:
self.setSizePolicy(QSizePolicy.Minimum, QSizePolicy.Expanding)
self.label = make.label(self.LABEL_TEXT, "C", (0, 0), "C")
self.label.set_readonly(True)
self.add_item(self.label)
self.setAxisMaxMajor(self.Z_AXIS, self.Z_MAX_MAJOR)
self.setAxisMaxMinor(self.Z_AXIS, 0)
def histogram2D(self, X, Y, NX=None, NY=None, logscale=None,
title=None, transparent=None, Z=None,
computation=-1,interpolation=0):
"""
Make a 2D Histogram `plot item`
(:py:class:`guiqwt.image.Histogram2DItem` object)
* X: data (1D array)
* Y: data (1D array)
* NX: Number of bins along x-axis (int)
* NY: Number of bins along y-axis (int)
* logscale: Z-axis scale (bool)
* title: item title (string)
* transparent: enable transparency (bool)
"""
basename = _("2D Histogram")
param = Histogram2DParam(title=basename, icon='histogram2d.png')
if NX is not None:
param.nx_bins = NX
if NY is not None:
param.ny_bins = NY
if logscale is not None:
param.logscale = int(logscale)
if title is not None:
param.label = title
else:
global HISTOGRAM2D_COUNT
HISTOGRAM2D_COUNT += 1
param.label = make_title(basename, HISTOGRAM2D_COUNT)
if transparent is not None:
param.transparent = transparent
param.computation = computation
param.interpolation = interpolation
return Histogram2DItem(X, Y, param, Z=Z)
def legend(self, anchor='TR', c=None, restrict_items=None):
"""
Make a legend `plot item`
(:py:class:`guiqwt.label.LegendBoxItem` or
:py:class:`guiqwt.label.SelectedLegendBoxItem` object)
* anchor: legend position in relative position (string)
* c (optional): position in canvas coordinates (tuple)
* restrict_items (optional):
- None: all items are shown in legend box
- []: no item shown
- [item1, item2]: item1, item2 are shown in legend box
"""
param = LegendParam(_("Legend"), icon='legend.png')
param.read_config(CONF, "plot", "legend")
param.abspos = True
param.absg = anchor
param.anchor = anchor
if c is None:
c = ANCHOR_OFFSETS[anchor]
param.xc, param.yc = c
if restrict_items is None:
return LegendBoxItem(param)
else:
return SelectedLegendBoxItem(param, restrict_items)
def __init__(self, parent):
QSplitter.__init__(self, parent)
# self.lineList = QListWidget(self)
# self.addWidget(self.lineList)
self.properties = DataSetEditGroupBox(_("Properties"), DAQParam)
self.properties.setEnabled(True)
self.addWidget(self.properties)
def __init__(self, wintitle="guiqwt plot", icon="guiqwt.svg",
toolbar=False, options=None, panels=None, param_cols=1,
legend_anchor='TR', auto_fit=True):
if wintitle is None:
wintitle = _('Curve fitting')
self.x = None
self.y = None
self.fitfunc = None
self.fitargs = None
self.fitkwargs = None
self.fitparams = None
self.autofit_prm = None
self.data_curve = None
self.fit_curve = None
self.legend = None
self.legend_anchor = legend_anchor
self.xrange = None
self.show_xrange = False
self.param_cols = param_cols
self.auto_fit_enabled = auto_fit
self.button_list = [] # list of buttons to be disabled at startup
self.fit_layout = None
self.params_layout = None
CurveWidgetMixin.__init__(self, wintitle=wintitle, icon=icon,
toolbar=toolbar, options=options,
panels=panels)
self.refresh()
def open(self, filename=None, *args):
if filename is None or isinstance(filename, (int, bool)):
# catch Qt signal-slot connection which may
# sends boolean from QAction signal
filename = QFileDialog.getOpenFileNames(None,
_('Open file'), '.')
if filename is None:
return
else:
filename = [unicode(fname) for fname in filename]
self.open(filename)
return
elif not isinstance(filename, (list,tuple)):
filename = [filename,]
if len(args) != 0:
filename.extend(args)
for fname in filename:
if re.match('.*flat$', fname):
self.ffp.open(fname)
measurements = self.ffp.get_measurements()
elif re.match('.*\.sxm$', fname):
self.nfp.open(fname)
measurements = self.nfp.get_measurements()
else:
measurements = []
print "Unknown file type"
for i in range(len(measurements)):
self.register_measurement(measurements.pop())
def __init__(self, wintitle="guiqwt plot", icon="guiqwt.png",
toolbar=False, options=None, parent=None, panels=None):
QDialog.__init__(self, parent)
self.setWindowFlags(Qt.Window)
# WidgetMixin copy
PlotManager.__init__(self, main=self)
self.main_layout = QVBoxLayout(self)
self.color_layout = QHBoxLayout()
self.plot_layout = QGridLayout()
self.option_layout = QHBoxLayout()
self.plot_widget = None
if panels is not None:
for panel in panels:
self.add_panel(panel)
self.toolbar = QToolBar(_("Tools"))
if not toolbar:
self.toolbar.hide()
# Configuring widget layout
self._setup_widget_properties(wintitle=wintitle, icon=icon)
self._setup_widget_layout()
# Options
self.option_callbacks = {}
self.legend = None
def xyimage(self, x, y, data, title=None, alpha_mask=None, alpha=None,
background_color=None, colormap=None,
interpolation='linear', eliminate_outliers=None,
xformat='%.1f', yformat='%.1f', zformat='%.1f'):
"""
Make an xyimage `plot item` (image with non-linear X/Y axes) from data
(:py:class:`guiqwt.image.XYImageItem` object)
* x: 1D NumPy array (or tuple, list: will be converted to array)
* y: 1D NumPy array (or tuple, list: will be converted to array
* data: 2D NumPy array (image pixel data)
* title: image title (optional)
* interpolation: 'nearest', 'linear' (default), 'antialiasing' (5x5)
"""
param = XYImageParam(title=_("Image"), icon='image.png')
self.__set_image_param(param, title, alpha_mask, alpha, interpolation,
background=background_color, colormap=colormap,
xformat=xformat, yformat=yformat,
zformat=zformat)
if isinstance(x, (list, tuple)):
x = array(x)
if isinstance(y, (list, tuple)):
y = array(y)
image = XYImageItem(x, y, data, param)
if eliminate_outliers is not None:
image.set_lut_range(lut_range_threshold(image, 256,
eliminate_outliers))
return image
def __init__(self, parent):
QSplitter.__init__(self, parent)
self.imagelist = QListWidget(self)
self.addWidget(self.imagelist)
self.properties = DataSetEditGroupBox(_("Properties"), ImageParam)
self.properties.setEnabled(False)
self.addWidget(self.properties)
def __init__(self, wintitle):
super(Window, self).__init__()
self.default_tool = None
self.plots = []
self.itemlist = PlotItemList(None)
self.contrast = ContrastAdjustment(None)
self.xcsw = XCrossSection(None)
self.ycsw = YCrossSection(None)
self.manager = PlotManager(self)
self.toolbar = QToolBar(_("Tools"), self)
self.manager.add_toolbar(self.toolbar, "default")
self.toolbar.setMovable(True)
self.toolbar.setFloatable(True)
self.addToolBar(Qt.TopToolBarArea, self.toolbar)
frame = QFrame(self)
self.setCentralWidget(frame)
self.layout = QGridLayout()
layout = QVBoxLayout(frame)
frame.setLayout(layout)
layout.addLayout(self.layout)
self.frame = frame
self.setWindowTitle(wintitle)
self.setWindowIcon(get_icon('guiqwt.svg'))
def __init__(self, wintitle="guiqwt plot", icon="guiqwt.svg",
toolbar=False, options=None, panels=None):
PlotManager.__init__(self, main=self)
self.plot_layout = QGridLayout()
if options is None:
options = {}
self.plot_widget = None
self.create_plot(options)
if panels is not None:
for panel in panels:
self.add_panel(panel)
self.toolbar = QToolBar(_("Tools"))
if not toolbar:
self.toolbar.hide()
# Configuring widget layout
self.setup_widget_properties(wintitle=wintitle, icon=icon)
self.setup_widget_layout()
# Configuring plot manager
self.add_toolbar(self.toolbar, "default")
self.register_tools()