class ArrayImagePlot(qt.QWidget):
"""
Widget for plotting an image from a multi-dimensional signal array
and two 1D axes array.
The signal array can have an arbitrary number of dimensions, the only
limitation being that the last two dimensions must have the same length as
the axes arrays.
Sliders are provided to select indices on the first (n - 2) dimensions of
the signal array, and the plot is updated to show the image corresponding
to the selection.
If one or both of the axes does not have regularly spaced values, the
the image is plotted as a coloured scatter plot.
"""
def __init__(self, parent=None):
"""
:param parent: Parent QWidget
"""
super(ArrayImagePlot, self).__init__(parent)
self.__signals = None
self.__signals_names = None
self.__x_axis = None
self.__x_axis_name = None
self.__y_axis = None
self.__y_axis_name = None
self._plot = Plot2D(self)
self._plot.setDefaultColormap(
Colormap(name="viridis",
vmin=None,
vmax=None,
normalization=Colormap.LINEAR))
self._plot.getIntensityHistogramAction().setVisible(True)
self._plot.setKeepDataAspectRatio(True)
# not closable
self._selector = NumpyAxesSelector(self)
self._selector.setNamedAxesSelectorVisibility(False)
self._selector.selectionChanged.connect(self._updateImage)
self._auxSigSlider = HorizontalSliderWithBrowser(parent=self)
self._auxSigSlider.setMinimum(0)
self._auxSigSlider.setValue(0)
self._auxSigSlider.valueChanged[int].connect(self._sliderIdxChanged)
self._auxSigSlider.setToolTip("Select auxiliary signals")
layout = qt.QVBoxLayout()
layout.addWidget(self._plot)
layout.addWidget(self._selector)
layout.addWidget(self._auxSigSlider)
self.setLayout(layout)
def _sliderIdxChanged(self, value):
self._updateImage()
def getPlot(self):
"""Returns the plot used for the display
:rtype: Plot2D
"""
return self._plot
def setImageData(self,
signals,
x_axis=None,
y_axis=None,
signals_names=None,
xlabel=None,
ylabel=None,
title=None,
isRgba=False,
xscale=None,
yscale=None):
"""
:param signals: list of n-D datasets, whose last 2 dimensions are used as the
image's values, or list of 3D datasets interpreted as RGBA image.
:param x_axis: 1-D dataset used as the image's x coordinates. If
provided, its lengths must be equal to the length of the last
dimension of ``signal``.
:param y_axis: 1-D dataset used as the image's y. If provided,
its lengths must be equal to the length of the 2nd to last
dimension of ``signal``.
:param signals_names: Names for each image, used as subtitle and legend.
:param xlabel: Label for X axis
:param ylabel: Label for Y axis
:param title: Graph title
:param isRgba: True if data is a 3D RGBA image
:param str xscale: Scale of X axis in (None, 'linear', 'log')
:param str yscale: Scale of Y axis in (None, 'linear', 'log')
"""
self._selector.selectionChanged.disconnect(self._updateImage)
self._auxSigSlider.valueChanged.disconnect(self._sliderIdxChanged)
self.__signals = signals
self.__signals_names = signals_names
self.__x_axis = x_axis
self.__x_axis_name = xlabel
self.__y_axis = y_axis
self.__y_axis_name = ylabel
self.__title = title
self._selector.clear()
if not isRgba:
self._selector.setAxisNames(["Y", "X"])
img_ndim = 2
else:
self._selector.setAxisNames(["Y", "X", "RGB(A) channel"])
img_ndim = 3
self._selector.setData(signals[0])
if len(signals[0].shape) <= img_ndim:
self._selector.hide()
else:
self._selector.show()
self._auxSigSlider.setMaximum(len(signals) - 1)
if len(signals) > 1:
self._auxSigSlider.show()
else:
self._auxSigSlider.hide()
self._auxSigSlider.setValue(0)
self._axis_scales = xscale, yscale
self._updateImage()
self._plot.resetZoom()
self._selector.selectionChanged.connect(self._updateImage)
self._auxSigSlider.valueChanged.connect(self._sliderIdxChanged)
def _updateImage(self):
selection = self._selector.selection()
auxSigIdx = self._auxSigSlider.value()
legend = self.__signals_names[auxSigIdx]
images = [img[selection] for img in self.__signals]
image = images[auxSigIdx]
x_axis = self.__x_axis
y_axis = self.__y_axis
if x_axis is None and y_axis is None:
xcalib = NoCalibration()
ycalib = NoCalibration()
else:
if x_axis is None:
# no calibration
x_axis = numpy.arange(image.shape[1])
elif numpy.isscalar(x_axis) or len(x_axis) == 1:
# constant axis
x_axis = x_axis * numpy.ones((image.shape[1], ))
elif len(x_axis) == 2:
# linear calibration
x_axis = x_axis[0] * numpy.arange(image.shape[1]) + x_axis[1]
if y_axis is None:
y_axis = numpy.arange(image.shape[0])
elif numpy.isscalar(y_axis) or len(y_axis) == 1:
y_axis = y_axis * numpy.ones((image.shape[0], ))
elif len(y_axis) == 2:
y_axis = y_axis[0] * numpy.arange(image.shape[0]) + y_axis[1]
xcalib = ArrayCalibration(x_axis)
ycalib = ArrayCalibration(y_axis)
self._plot.remove(kind=(
"scatter",
"image",
))
if xcalib.is_affine() and ycalib.is_affine():
# regular image
xorigin, xscale = xcalib(0), xcalib.get_slope()
yorigin, yscale = ycalib(0), ycalib.get_slope()
origin = (xorigin, yorigin)
scale = (xscale, yscale)
self._plot.getXAxis().setScale('linear')
self._plot.getYAxis().setScale('linear')
self._plot.addImage(image,
legend=legend,
origin=origin,
scale=scale,
replace=True,
resetzoom=False)
else:
xaxisscale, yaxisscale = self._axis_scales
if xaxisscale is not None:
self._plot.getXAxis().setScale('log' if xaxisscale ==
'log' else 'linear')
if yaxisscale is not None:
self._plot.getYAxis().setScale('log' if yaxisscale ==
'log' else 'linear')
scatterx, scattery = numpy.meshgrid(x_axis, y_axis)
# fixme: i don't think this can handle "irregular" RGBA images
self._plot.addScatter(numpy.ravel(scatterx),
numpy.ravel(scattery),
numpy.ravel(image),
legend=legend)
if self.__title:
title = self.__title
if len(self.__signals_names) > 1:
# Append dataset name only when there is many datasets
title += '\n' + self.__signals_names[auxSigIdx]
else:
title = self.__signals_names[auxSigIdx]
self._plot.setGraphTitle(title)
self._plot.getXAxis().setLabel(self.__x_axis_name)
self._plot.getYAxis().setLabel(self.__y_axis_name)
def clear(self):
old = self._selector.blockSignals(True)
self._selector.clear()
self._selector.blockSignals(old)
self._plot.clear()
class ArrayComplexImagePlot(qt.QWidget):
"""
Widget for plotting an image of complex from a multi-dimensional signal array
and two 1D axes array.
The signal array can have an arbitrary number of dimensions, the only
limitation being that the last two dimensions must have the same length as
the axes arrays.
Sliders are provided to select indices on the first (n - 2) dimensions of
the signal array, and the plot is updated to show the image corresponding
to the selection.
If one or both of the axes does not have regularly spaced values, the
the image is plotted as a coloured scatter plot.
"""
def __init__(self, parent=None, colormap=None):
"""
:param parent: Parent QWidget
"""
super(ArrayComplexImagePlot, self).__init__(parent)
self.__signals = None
self.__signals_names = None
self.__x_axis = None
self.__x_axis_name = None
self.__y_axis = None
self.__y_axis_name = None
self._plot = ComplexImageView(self)
if colormap is not None:
for mode in (ComplexImageView.ComplexMode.ABSOLUTE,
ComplexImageView.ComplexMode.SQUARE_AMPLITUDE,
ComplexImageView.ComplexMode.REAL,
ComplexImageView.ComplexMode.IMAGINARY):
self._plot.setColormap(colormap, mode)
self._plot.getPlot().getIntensityHistogramAction().setVisible(True)
self._plot.setKeepDataAspectRatio(True)
# not closable
self._selector = NumpyAxesSelector(self)
self._selector.setNamedAxesSelectorVisibility(False)
self._selector.selectionChanged.connect(self._updateImage)
self._auxSigSlider = HorizontalSliderWithBrowser(parent=self)
self._auxSigSlider.setMinimum(0)
self._auxSigSlider.setValue(0)
self._auxSigSlider.valueChanged[int].connect(self._sliderIdxChanged)
self._auxSigSlider.setToolTip("Select auxiliary signals")
layout = qt.QVBoxLayout()
layout.addWidget(self._plot)
layout.addWidget(self._selector)
layout.addWidget(self._auxSigSlider)
self.setLayout(layout)
def _sliderIdxChanged(self, value):
self._updateImage()
def getPlot(self):
"""Returns the plot used for the display
:rtype: PlotWidget
"""
return self._plot.getPlot()
def setImageData(self,
signals,
x_axis=None,
y_axis=None,
signals_names=None,
xlabel=None,
ylabel=None,
title=None):
"""
:param signals: list of n-D datasets, whose last 2 dimensions are used as the
image's values, or list of 3D datasets interpreted as RGBA image.
:param x_axis: 1-D dataset used as the image's x coordinates. If
provided, its lengths must be equal to the length of the last
dimension of ``signal``.
:param y_axis: 1-D dataset used as the image's y. If provided,
its lengths must be equal to the length of the 2nd to last
dimension of ``signal``.
:param signals_names: Names for each image, used as subtitle and legend.
:param xlabel: Label for X axis
:param ylabel: Label for Y axis
:param title: Graph title
"""
self._selector.selectionChanged.disconnect(self._updateImage)
self._auxSigSlider.valueChanged.disconnect(self._sliderIdxChanged)
self.__signals = signals
self.__signals_names = signals_names
self.__x_axis = x_axis
self.__x_axis_name = xlabel
self.__y_axis = y_axis
self.__y_axis_name = ylabel
self.__title = title
self._selector.clear()
self._selector.setAxisNames(["Y", "X"])
self._selector.setData(signals[0])
if len(signals[0].shape) <= 2:
self._selector.hide()
else:
self._selector.show()
self._auxSigSlider.setMaximum(len(signals) - 1)
if len(signals) > 1:
self._auxSigSlider.show()
else:
self._auxSigSlider.hide()
self._auxSigSlider.setValue(0)
self._updateImage()
self._plot.getPlot().resetZoom()
self._selector.selectionChanged.connect(self._updateImage)
self._auxSigSlider.valueChanged.connect(self._sliderIdxChanged)
def _updateImage(self):
selection = self._selector.selection()
auxSigIdx = self._auxSigSlider.value()
images = [img[selection] for img in self.__signals]
image = images[auxSigIdx]
x_axis = self.__x_axis
y_axis = self.__y_axis
if x_axis is None and y_axis is None:
xcalib = NoCalibration()
ycalib = NoCalibration()
else:
if x_axis is None:
# no calibration
x_axis = numpy.arange(image.shape[1])
elif numpy.isscalar(x_axis) or len(x_axis) == 1:
# constant axis
x_axis = x_axis * numpy.ones((image.shape[1], ))
elif len(x_axis) == 2:
# linear calibration
x_axis = x_axis[0] * numpy.arange(image.shape[1]) + x_axis[1]
if y_axis is None:
y_axis = numpy.arange(image.shape[0])
elif numpy.isscalar(y_axis) or len(y_axis) == 1:
y_axis = y_axis * numpy.ones((image.shape[0], ))
elif len(y_axis) == 2:
y_axis = y_axis[0] * numpy.arange(image.shape[0]) + y_axis[1]
xcalib = ArrayCalibration(x_axis)
ycalib = ArrayCalibration(y_axis)
self._plot.setData(image)
if xcalib.is_affine():
xorigin, xscale = xcalib(0), xcalib.get_slope()
else:
_logger.warning("Unsupported complex image X axis calibration")
xorigin, xscale = 0., 1.
if ycalib.is_affine():
yorigin, yscale = ycalib(0), ycalib.get_slope()
else:
_logger.warning("Unsupported complex image Y axis calibration")
yorigin, yscale = 0., 1.
self._plot.setOrigin((xorigin, yorigin))
self._plot.setScale((xscale, yscale))
if self.__title:
title = self.__title
if len(self.__signals_names) > 1:
# Append dataset name only when there is many datasets
title += '\n' + self.__signals_names[auxSigIdx]
else:
title = self.__signals_names[auxSigIdx]
self._plot.setGraphTitle(title)
self._plot.getXAxis().setLabel(self.__x_axis_name)
self._plot.getYAxis().setLabel(self.__y_axis_name)
def clear(self):
old = self._selector.blockSignals(True)
self._selector.clear()
self._selector.blockSignals(old)
self._plot.setData(None)
class XYVScatterPlot(qt.QWidget):
"""
Widget for plotting one or more scatters
(with identical x, y coordinates).
"""
def __init__(self, parent=None):
"""
:param parent: Parent QWidget
"""
super(XYVScatterPlot, self).__init__(parent)
self.__y_axis = None
"""1D array"""
self.__y_axis_name = None
self.__values = None
"""List of 1D arrays (for multiple scatters with identical
x, y coordinates)"""
self.__x_axis = None
self.__x_axis_name = None
self.__x_axis_errors = None
self.__y_axis = None
self.__y_axis_name = None
self.__y_axis_errors = None
self._plot = ScatterView(self)
self._plot.setColormap(
Colormap(name="viridis",
vmin=None,
vmax=None,
normalization=Colormap.LINEAR))
self._slider = HorizontalSliderWithBrowser(parent=self)
self._slider.setMinimum(0)
self._slider.setValue(0)
self._slider.valueChanged[int].connect(self._sliderIdxChanged)
self._slider.setToolTip("Select auxiliary signals")
layout = qt.QGridLayout()
layout.setContentsMargins(0, 0, 0, 0)
layout.addWidget(self._plot, 0, 0)
layout.addWidget(self._slider, 1, 0)
self.setLayout(layout)
def _sliderIdxChanged(self, value):
self._updateScatter()
def getScatterView(self):
"""Returns the :class:`ScatterView` used for the display
:rtype: ScatterView
"""
return self._plot
def getPlot(self):
"""Returns the plot used for the display
:rtype: PlotWidget
"""
return self._plot.getPlotWidget()
def setScattersData(self,
y,
x,
values,
yerror=None,
xerror=None,
ylabel=None,
xlabel=None,
title="",
scatter_titles=None,
xscale=None,
yscale=None):
"""
:param ndarray y: 1D array for y (vertical) coordinates.
:param ndarray x: 1D array for x coordinates.
:param List[ndarray] values: List of 1D arrays of values.
This will be used to compute the color map and assign colors
to the points. There should be as many arrays in the list as
scatters to be represented.
:param ndarray yerror: 1D array of errors for y (same shape), or None.
:param ndarray xerror: 1D array of errors for x, or None
:param str ylabel: Label for Y axis
:param str xlabel: Label for X axis
:param str title: Main graph title
:param List[str] scatter_titles: Subtitles (one per scatter)
:param str xscale: Scale of X axis in (None, 'linear', 'log')
:param str yscale: Scale of Y axis in (None, 'linear', 'log')
"""
self.__y_axis = y
self.__x_axis = x
self.__x_axis_name = xlabel or "X"
self.__y_axis_name = ylabel or "Y"
self.__x_axis_errors = xerror
self.__y_axis_errors = yerror
self.__values = values
self.__graph_title = title or ""
self.__scatter_titles = scatter_titles
self._slider.valueChanged[int].disconnect(self._sliderIdxChanged)
self._slider.setMaximum(len(values) - 1)
if len(values) > 1:
self._slider.show()
else:
self._slider.hide()
self._slider.setValue(0)
self._slider.valueChanged[int].connect(self._sliderIdxChanged)
if xscale is not None:
self._plot.getXAxis().setScale('log' if xscale ==
'log' else 'linear')
if yscale is not None:
self._plot.getYAxis().setScale('log' if yscale ==
'log' else 'linear')
self._updateScatter()
def _updateScatter(self):
x = self.__x_axis
y = self.__y_axis
idx = self._slider.value()
if self.__graph_title:
title = self.__graph_title # main NXdata @title
if len(self.__scatter_titles) > 1:
# Append dataset name only when there is many datasets
title += '\n' + self.__scatter_titles[idx]
else:
title = self.__scatter_titles[idx] # scatter dataset name
self._plot.setGraphTitle(title)
self._plot.setData(x,
y,
self.__values[idx],
xerror=self.__x_axis_errors,
yerror=self.__y_axis_errors)
self._plot.resetZoom()
self._plot.getXAxis().setLabel(self.__x_axis_name)
self._plot.getYAxis().setLabel(self.__y_axis_name)
def clear(self):
self._plot.getPlotWidget().clear()
class ArrayImagePlot(qt.QWidget):
"""
Widget for plotting an image from a multi-dimensional signal array
and two 1D axes array.
The signal array can have an arbitrary number of dimensions, the only
limitation being that the last two dimensions must have the same length as
the axes arrays.
Sliders are provided to select indices on the first (n - 2) dimensions of
the signal array, and the plot is updated to show the image corresponding
to the selection.
If one or both of the axes does not have regularly spaced values, the
the image is plotted as a coloured scatter plot.
"""
def __init__(self, parent=None):
"""
:param parent: Parent QWidget
"""
super(ArrayImagePlot, self).__init__(parent)
self.__signals = None
self.__signals_names = None
self.__x_axis = None
self.__x_axis_name = None
self.__y_axis = None
self.__y_axis_name = None
self._plot = Plot2D(self)
self._plot.setDefaultColormap(Colormap(name="viridis",
vmin=None, vmax=None,
normalization=Colormap.LINEAR))
self._plot.getIntensityHistogramAction().setVisible(True)
# not closable
self._selector = NumpyAxesSelector(self)
self._selector.setNamedAxesSelectorVisibility(False)
self._selector.selectionChanged.connect(self._updateImage)
self._auxSigSlider = HorizontalSliderWithBrowser(parent=self)
self._auxSigSlider.setMinimum(0)
self._auxSigSlider.setValue(0)
self._auxSigSlider.valueChanged[int].connect(self._sliderIdxChanged)
self._auxSigSlider.setToolTip("Select auxiliary signals")
layout = qt.QVBoxLayout()
layout.addWidget(self._plot)
layout.addWidget(self._selector)
layout.addWidget(self._auxSigSlider)
self.setLayout(layout)
def _sliderIdxChanged(self, value):
self._updateImage()
def getPlot(self):
"""Returns the plot used for the display
:rtype: Plot2D
"""
return self._plot
def setImageData(self, signals,
x_axis=None, y_axis=None,
signals_names=None,
xlabel=None, ylabel=None,
title=None, isRgba=False):
"""
:param signals: list of n-D datasets, whose last 2 dimensions are used as the
image's values, or list of 3D datasets interpreted as RGBA image.
:param x_axis: 1-D dataset used as the image's x coordinates. If
provided, its lengths must be equal to the length of the last
dimension of ``signal``.
:param y_axis: 1-D dataset used as the image's y. If provided,
its lengths must be equal to the length of the 2nd to last
dimension of ``signal``.
:param signals_names: Names for each image, used as subtitle and legend.
:param xlabel: Label for X axis
:param ylabel: Label for Y axis
:param title: Graph title
:param isRgba: True if data is a 3D RGBA image
"""
self._selector.selectionChanged.disconnect(self._updateImage)
self._auxSigSlider.valueChanged.disconnect(self._sliderIdxChanged)
self.__signals = signals
self.__signals_names = signals_names
self.__x_axis = x_axis
self.__x_axis_name = xlabel
self.__y_axis = y_axis
self.__y_axis_name = ylabel
self.__title = title
self._selector.clear()
if not isRgba:
self._selector.setAxisNames(["Y", "X"])
img_ndim = 2
else:
self._selector.setAxisNames(["Y", "X", "RGB(A) channel"])
img_ndim = 3
self._selector.setData(signals[0])
if len(signals[0].shape) <= img_ndim:
self._selector.hide()
else:
self._selector.show()
self._auxSigSlider.setMaximum(len(signals) - 1)
if len(signals) > 1:
self._auxSigSlider.show()
else:
self._auxSigSlider.hide()
self._auxSigSlider.setValue(0)
self._updateImage()
self._selector.selectionChanged.connect(self._updateImage)
self._auxSigSlider.valueChanged.connect(self._sliderIdxChanged)
def _updateImage(self):
selection = self._selector.selection()
auxSigIdx = self._auxSigSlider.value()
legend = self.__signals_names[auxSigIdx]
images = [img[selection] for img in self.__signals]
image = images[auxSigIdx]
x_axis = self.__x_axis
y_axis = self.__y_axis
if x_axis is None and y_axis is None:
xcalib = NoCalibration()
ycalib = NoCalibration()
else:
if x_axis is None:
# no calibration
x_axis = numpy.arange(image.shape[1])
elif numpy.isscalar(x_axis) or len(x_axis) == 1:
# constant axis
x_axis = x_axis * numpy.ones((image.shape[1], ))
elif len(x_axis) == 2:
# linear calibration
x_axis = x_axis[0] * numpy.arange(image.shape[1]) + x_axis[1]
if y_axis is None:
y_axis = numpy.arange(image.shape[0])
elif numpy.isscalar(y_axis) or len(y_axis) == 1:
y_axis = y_axis * numpy.ones((image.shape[0], ))
elif len(y_axis) == 2:
y_axis = y_axis[0] * numpy.arange(image.shape[0]) + y_axis[1]
xcalib = ArrayCalibration(x_axis)
ycalib = ArrayCalibration(y_axis)
self._plot.remove(kind=("scatter", "image",))
if xcalib.is_affine() and ycalib.is_affine():
# regular image
xorigin, xscale = xcalib(0), xcalib.get_slope()
yorigin, yscale = ycalib(0), ycalib.get_slope()
origin = (xorigin, yorigin)
scale = (xscale, yscale)
self._plot.addImage(image, legend=legend,
origin=origin, scale=scale,
replace=True)
else:
scatterx, scattery = numpy.meshgrid(x_axis, y_axis)
# fixme: i don't think this can handle "irregular" RGBA images
self._plot.addScatter(numpy.ravel(scatterx),
numpy.ravel(scattery),
numpy.ravel(image),
legend=legend)
title = ""
if self.__title:
title += self.__title
if not title.strip().endswith(self.__signals_names[auxSigIdx]):
title += "\n" + self.__signals_names[auxSigIdx]
self._plot.setGraphTitle(title)
self._plot.getXAxis().setLabel(self.__x_axis_name)
self._plot.getYAxis().setLabel(self.__y_axis_name)
self._plot.resetZoom()
def clear(self):
old = self._selector.blockSignals(True)
self._selector.clear()
self._selector.blockSignals(old)
self._plot.clear()
class XYVScatterPlot(qt.QWidget):
"""
Widget for plotting one or more scatters
(with identical x, y coordinates).
"""
def __init__(self, parent=None):
"""
:param parent: Parent QWidget
"""
super(XYVScatterPlot, self).__init__(parent)
self.__y_axis = None
"""1D array"""
self.__y_axis_name = None
self.__values = None
"""List of 1D arrays (for multiple scatters with identical
x, y coordinates)"""
self.__x_axis = None
self.__x_axis_name = None
self.__x_axis_errors = None
self.__y_axis = None
self.__y_axis_name = None
self.__y_axis_errors = None
self._plot = ScatterView(self)
self._plot.setColormap(Colormap(name="viridis",
vmin=None, vmax=None,
normalization=Colormap.LINEAR))
self._slider = HorizontalSliderWithBrowser(parent=self)
self._slider.setMinimum(0)
self._slider.setValue(0)
self._slider.valueChanged[int].connect(self._sliderIdxChanged)
self._slider.setToolTip("Select auxiliary signals")
layout = qt.QGridLayout()
layout.setContentsMargins(0, 0, 0, 0)
layout.addWidget(self._plot, 0, 0)
layout.addWidget(self._slider, 1, 0)
self.setLayout(layout)
def _sliderIdxChanged(self, value):
self._updateScatter()
def getPlot(self):
"""Returns the plot used for the display
:rtype: PlotWidget
"""
return self._plot.getPlotWidget()
def setScattersData(self, y, x, values,
yerror=None, xerror=None,
ylabel=None, xlabel=None,
title="", scatter_titles=None):
"""
:param ndarray y: 1D array for y (vertical) coordinates.
:param ndarray x: 1D array for x coordinates.
:param List[ndarray] values: List of 1D arrays of values.
This will be used to compute the color map and assign colors
to the points. There should be as many arrays in the list as
scatters to be represented.
:param ndarray yerror: 1D array of errors for y (same shape), or None.
:param ndarray xerror: 1D array of errors for x, or None
:param str ylabel: Label for Y axis
:param str xlabel: Label for X axis
:param str title: Main graph title
:param List[str] scatter_titles: Subtitles (one per scatter)
"""
self.__y_axis = y
self.__x_axis = x
self.__x_axis_name = xlabel or "X"
self.__y_axis_name = ylabel or "Y"
self.__x_axis_errors = xerror
self.__y_axis_errors = yerror
self.__values = values
self.__graph_title = title or ""
self.__scatter_titles = scatter_titles
self._slider.valueChanged[int].disconnect(self._sliderIdxChanged)
self._slider.setMaximum(len(values) - 1)
if len(values) > 1:
self._slider.show()
else:
self._slider.hide()
self._slider.setValue(0)
self._slider.valueChanged[int].connect(self._sliderIdxChanged)
self._updateScatter()
def _updateScatter(self):
x = self.__x_axis
y = self.__y_axis
idx = self._slider.value()
title = ""
if self.__graph_title:
title += self.__graph_title + "\n" # main NXdata @title
title += self.__scatter_titles[idx] # scatter dataset name
self._plot.setGraphTitle(title)
self._plot.setData(x, y, self.__values[idx],
xerror=self.__x_axis_errors,
yerror=self.__y_axis_errors)
self._plot.resetZoom()
self._plot.getXAxis().setLabel(self.__x_axis_name)
self._plot.getYAxis().setLabel(self.__y_axis_name)
def clear(self):
self._plot.getPlotWidget().clear()
class _Axis(qt.QWidget):
"""Widget displaying an axis.
It allows to display and scroll in the axis, and provide a widget to
map the axis with a named axis (the one from the view).
"""
valueChanged = qt.Signal(int)
"""Emitted when the location on the axis change."""
axisNameChanged = qt.Signal(object)
"""Emitted when the user change the name of the axis."""
def __init__(self, parent=None):
"""Constructor
:param parent: Parent of the widget
"""
super(_Axis, self).__init__(parent)
self.__axisNumber = None
self.__customAxisNames = set([])
self.__label = qt.QLabel(self)
self.__axes = qt.QComboBox(self)
self.__axes.currentIndexChanged[int].connect(self.__axisMappingChanged)
self.__slider = HorizontalSliderWithBrowser(self)
self.__slider.valueChanged[int].connect(self.__sliderValueChanged)
layout = qt.QHBoxLayout(self)
layout.setContentsMargins(0, 0, 0, 0)
layout.addWidget(self.__label)
layout.addWidget(self.__axes)
layout.addWidget(self.__slider, 10000)
layout.addStretch(1)
self.setLayout(layout)
def slider(self):
"""Returns the slider used to display axes location.
:rtype: HorizontalSliderWithBrowser
"""
return self.__slider
def setAxis(self, number, position, size):
"""Set axis information.
:param int number: The number of the axis (from the original numpy
array)
:param int position: The current position in the axis (for a slicing)
:param int size: The size of this axis (0..n)
"""
self.__label.setText("Dimension %s" % number)
self.__axisNumber = number
self.__slider.setMaximum(size - 1)
def axisNumber(self):
"""Returns the axis number.
:rtype: int
"""
return self.__axisNumber
def setAxisName(self, axisName):
"""Set the current used axis name.
If this name is not available an exception is raised. An empty string
means that no name is selected.
:param str axisName: The new name of the axis
:raise ValueError: When the name is not available
"""
if axisName == "" and self.__axes.count() == 0:
self.__axes.setCurrentIndex(-1)
self.__updateSliderVisibility()
for index in range(self.__axes.count()):
name = self.__axes.itemData(index)
if name == axisName:
self.__axes.setCurrentIndex(index)
self.__updateSliderVisibility()
return
raise ValueError("Axis name '%s' not found", axisName)
def axisName(self):
"""Returns the selected axis name.
If no names are selected, an empty string is retruned.
:rtype: str
"""
index = self.__axes.currentIndex()
if index == -1:
return ""
return self.__axes.itemData(index)
def setAxisNames(self, axesNames):
"""Set the available list of names for the axis.
:param list[str] axesNames: List of available names
"""
self.__axes.clear()
previous = self.__axes.blockSignals(True)
self.__axes.addItem(" ", "")
for axis in axesNames:
self.__axes.addItem(axis, axis)
self.__axes.blockSignals(previous)
self.__updateSliderVisibility()
def setCustomAxis(self, axesNames):
"""Set the available list of named axis which can be set to a value.
:param list[str] axesNames: List of customable axis names
"""
self.__customAxisNames = set(axesNames)
self.__updateSliderVisibility()
def __axisMappingChanged(self, index):
"""Called when the selected name change.
:param int index: Selected index
"""
self.__updateSliderVisibility()
name = self.axisName()
self.axisNameChanged.emit(name)
def __updateSliderVisibility(self):
"""Update the visibility of the slider according to axis names and
customable axis names."""
name = self.axisName()
isVisible = name == "" or name in self.__customAxisNames
self.__slider.setVisible(isVisible)
def value(self):
"""Returns the current selected position in the axis.
:rtype: int
"""
return self.__slider.value()
def __sliderValueChanged(self, value):
"""Called when the selected position in the axis change.
:param int value: Position of the axis
"""
self.valueChanged.emit(value)
def setNamedAxisSelectorVisibility(self, visible):
"""Hide or show the named axis combobox.
If both the selector and the slider are hidden,
hide the entire widget.
:param visible: boolean
"""
self.__axes.setVisible(visible)
name = self.axisName()
if not visible and name != "":
self.setVisible(False)
else:
self.setVisible(True)
class _Axis(qt.QWidget):
"""Widget displaying an axis.
It allows to display and scroll in the axis, and provide a widget to
map the axis with a named axis (the one from the view).
"""
valueChanged = qt.Signal(int)
"""Emitted when the location on the axis change."""
axisNameChanged = qt.Signal(object)
"""Emitted when the user change the name of the axis."""
def __init__(self, parent=None):
"""Constructor
:param parent: Parent of the widget
"""
super(_Axis, self).__init__(parent)
self.__axisNumber = None
self.__customAxisNames = set([])
self.__label = qt.QLabel(self)
self.__axes = qt.QComboBox(self)
self.__axes.currentIndexChanged[int].connect(self.__axisMappingChanged)
self.__slider = HorizontalSliderWithBrowser(self)
self.__slider.valueChanged[int].connect(self.__sliderValueChanged)
layout = qt.QHBoxLayout(self)
layout.setContentsMargins(0, 0, 0, 0)
layout.addWidget(self.__label)
layout.addWidget(self.__axes)
layout.addWidget(self.__slider, 10000)
layout.addStretch(1)
self.setLayout(layout)
def slider(self):
"""Returns the slider used to display axes location.
:rtype: HorizontalSliderWithBrowser
"""
return self.__slider
def setAxis(self, number, position, size):
"""Set axis information.
:param int number: The number of the axis (from the original numpy
array)
:param int position: The current position in the axis (for a slicing)
:param int size: The size of this axis (0..n)
"""
self.__label.setText("Dimension %s" % number)
self.__axisNumber = number
self.__slider.setMaximum(size - 1)
def axisNumber(self):
"""Returns the axis number.
:rtype: int
"""
return self.__axisNumber
def setAxisName(self, axisName):
"""Set the current used axis name.
If this name is not available an exception is raised. An empty string
means that no name is selected.
:param str axisName: The new name of the axis
:raise ValueError: When the name is not available
"""
if axisName == "" and self.__axes.count() == 0:
self.__axes.setCurrentIndex(-1)
self.__updateSliderVisibility()
for index in range(self.__axes.count()):
name = self.__axes.itemData(index)
if name == axisName:
self.__axes.setCurrentIndex(index)
self.__updateSliderVisibility()
return
raise ValueError("Axis name '%s' not found", axisName)
def axisName(self):
"""Returns the selected axis name.
If no names are selected, an empty string is retruned.
:rtype: str
"""
index = self.__axes.currentIndex()
if index == -1:
return ""
return self.__axes.itemData(index)
def setAxisNames(self, axesNames):
"""Set the available list of names for the axis.
:param List[str] axesNames: List of available names
"""
self.__axes.clear()
previous = self.__axes.blockSignals(True)
self.__axes.addItem(" ", "")
for axis in axesNames:
self.__axes.addItem(axis, axis)
self.__axes.blockSignals(previous)
self.__updateSliderVisibility()
def setCustomAxis(self, axesNames):
"""Set the available list of named axis which can be set to a value.
:param List[str] axesNames: List of customable axis names
"""
self.__customAxisNames = set(axesNames)
self.__updateSliderVisibility()
def __axisMappingChanged(self, index):
"""Called when the selected name change.
:param int index: Selected index
"""
self.__updateSliderVisibility()
name = self.axisName()
self.axisNameChanged.emit(name)
def __updateSliderVisibility(self):
"""Update the visibility of the slider according to axis names and
customable axis names."""
name = self.axisName()
isVisible = name == "" or name in self.__customAxisNames
self.__slider.setVisible(isVisible)
def value(self):
"""Returns the current selected position in the axis.
:rtype: int
"""
return self.__slider.value()
def __sliderValueChanged(self, value):
"""Called when the selected position in the axis change.
:param int value: Position of the axis
"""
self.valueChanged.emit(value)
def setNamedAxisSelectorVisibility(self, visible):
"""Hide or show the named axis combobox.
If both the selector and the slider are hidden,
hide the entire widget.
:param visible: boolean
"""
self.__axes.setVisible(visible)
name = self.axisName()
if not visible and name != "":
self.setVisible(False)
else:
self.setVisible(True)