class PlotWindow(DataWindow, Ui_plotWindow):
"""Window to display 2D plots"""
def __init__(self, parent=None):
DataWindow.__init__(self, parent)
self.plot = pyqtgraph.PlotWidget(self.plotFrame, antialiasing=True)
self.plot.hideAxis('bottom')
self.legend = self.plot.addLegend()
self.legend.hide()
self._finish_layout()
self.actionLegend_Box.triggered.connect(self.on_view_legend_box)
self.actionX_axis.triggered.connect(self.on_view_x_axis)
self.actionY_axis.triggered.connect(self.on_view_y_axis)
self.acceptable_data_types = ['scalar', 'vector', 'tuple', 'triple', 'running_hist', 'histogram' , 'normalized_histogram']
self.exclusive_source = False
self.line_colors = [(252, 175, 62), (114, 159, 207), (255, 255, 255),
(239, 41, 41), (138, 226, 52), (173, 127, 168)]
self.colorbar = None
self.colormap = None
self.current_index = -1
self.last_vector_y = {}
self.last_vector_x = None
self.hline = None
self.vline = None
self.hline_color = (0,204,0)
self.vline_color = (204,0,0)
self._settings_diag = LinePlotSettings(self)
self._histograms = {}
self._normalized_histograms = {}
self.updateFonts()
self.plot.scene().sigMouseMoved.connect(self._onMouseMoved)
def on_view_legend_box(self):
"""Show/hide legend box"""
action = self.sender()
if(action.isChecked()):
self.legend.show()
else:
self.legend.hide()
def on_view_x_axis(self):
"""Show/hide X axis"""
action = self.sender()
if(action.isChecked()):
self.plot.showAxis('bottom')
else:
self.plot.hideAxis('bottom')
def on_view_y_axis(self):
"""Show/hide Y axis"""
action = self.sender()
if(action.isChecked()):
self.plot.showAxis('left')
else:
self.plot.hideAxis('left')
def _on_plot_settings(self):
"""Show the plot settings dialog"""
self._settings_diag.histAutorange.toggled.connect(self._on_histogram_autorange)
if(self._settings_diag.exec_()):
self._settings_diag._read_bg_file()
# Show changes immediately
self.replot()
def _on_histogram_autorange(self, checked):
if checked:
self._settings_diag.histMin.setEnabled(False)
self._settings_diag.histMax.setEnabled(False)
else:
self._settings_diag.histMin.setEnabled(True)
self._settings_diag.histMax.setEnabled(True)
def get_time(self, index=None):
"""Returns the time of the given index, or the time of the last data point"""
if index is None:
index = self.current_index
# Check if we have last_vector
if (self.last_vector_x is not None):
dt = datetime.datetime.fromtimestamp(self.last_vector_x[index])
return dt
# Check if we have enabled_sources
source = None
if(self._enabled_sources):
for ds in self._enabled_sources.keys():
if(len(self._enabled_sources[ds])):
title = self._enabled_sources[ds][0]
source = ds
break
# There might be no data yet, so no plotdata
if(source is not None and title in source.plotdata and
source.plotdata[title].x is not None):
pd = source.plotdata[title]
dt = datetime.datetime.fromtimestamp(pd.x[index])
return dt
else:
return datetime.datetime.now()
def _configure_axis(self, source, title, hist=False):
"""Configures the x and y axis of the plot, according to the
source/title configuration and content type"""
conf = source.conf[title]
if(self.actionX_axis.isChecked()):
if 'xlabel' in conf and self._settings_diag.x_auto.isChecked():
self._settings_diag.x_label.setText(conf['xlabel'])
if hist:
self.plot.setLabel('bottom', self._settings_diag.y_label.text())
else:
self.plot.setLabel('bottom', self._settings_diag.x_label.text())
if(self.actionY_axis.isChecked()):
if 'ylabel' in conf and self._settings_diag.y_auto.isChecked():
self._settings_diag.y_label.setText(conf['ylabel'])
if hist:
self.plot.setLabel('left', 'Counts')
else:
self.plot.setLabel('left', self._settings_diag.y_label.text())
def _set_range(self, xmin, xmax, ymin, ymax):
if not self._settings_diag.xlimits_auto.isChecked():
try:
xmin = float(str(self._settings_diag.xmin.text()))
except ValueError:
pass
try:
xmax = float(str(self._settings_diag.xmax.text()))
except ValueError:
pass
if not self._settings_diag.ylimits_auto.isChecked():
try:
ymin = float(str(self._settings_diag.ymin.text()))
except ValueError:
pass
try:
ymax = float(str(self._settings_diag.ymax.text()))
except ValueError:
pass
if (xmax - xmin) == 0.:
xmin -= 0.1
xmax += 0.1
if (ymax - ymin) == 0.:
ymin -= 0.1
ymax += 0.1
self.plot.setRange(xRange=(xmin, xmax), yRange=(ymin, ymax))
def replot(self):
"""Replot data"""
self.plot.clear()
# Init background if defined in a data source
if self._settings_diag.bg is None:
alert_flag = False
for source, title in self.source_and_titles():
conf = source.conf[title]
if "bg_filename" in conf:
conf_bg = {}
for k,v in conf.items():
if k.startswith("bg_"):
conf_bg[k] = v
self._settings_diag._configure_bg(**conf_bg)
# Use only first if there are many
break
alert_flag = False
for source, title in self.source_and_titles():
conf = source.conf[title]
if "alert" in conf and self.actionToggleAlert.isChecked() and conf['alert']:
alert_flag = True
if alert_flag:
os.system('afplay -v %f src/interface/ui/sounds/%s.wav &' %(self.volume,self.sound))
if not self.alertBlinkTimer.isActive():
self.alertBlinkTimer.start()
else:
if self.alertBlinkTimer.isActive():
self.alertBlinkTimer.stop()
self.setStyleSheet("")
# Load background if configured
self._update_bg()
color_index = 0
titlebar = []
self.plot.plotItem.legend.items = []
xmins = []
xmaxs = []
ymins = []
ymaxs = []
for source, title in self.source_and_titles():
if(title not in source.plotdata or source.plotdata[title].y is None):
continue
pd = source.plotdata[title]
titlebar.append(pd.title)
conf = source.conf[title]
color = self.line_colors[color_index % len(self.line_colors)]
pen = None
symbol = None
symbol_pen = None
symbol_brush = None
symbol_size = None
histoangle = 0
if(self.actionLines.isChecked()):
pen = color
if(self.actionPoints.isChecked()):
symbol = 'o'
symbol_pen = color
symbol_brush = color
symbol_size = 3
if(source.data_type[title] == 'scalar') or (source.data_type[title] == 'running_hist'):
y = numpy.array(pd.y, copy=False)
self.last_vector_y = {}
self.last_vector_x = None
elif(source.data_type[title] == 'tuple'):
y = pd.y[:,1]
symbol_brush = (255,255,255,120)
symbol_pen = None
symbol_size = 8
elif(source.data_type[title] == 'triple'):
if self.colormap is None:
vmin, vmax = (0,1)
if 'vmin' in conf:
vmin = conf['vmin']
if 'vmax' in conf:
vmax = conf['vmax']
stops = numpy.r_[vmin, vmax]
colors = numpy.array([[0, 0, 1, 0.7], [1, 0, 0, 1.0]])
self.colormap = pyqtgraph.ColorMap(stops, colors)
if 'zlabel' in conf:
zlabel = conf['zlabel']
else:
zlabel = 'z'
if self.colorbar is not None:
self.plot.scene().removeItem(self.colorbar)
self.colorbar = ColorBar(self.colormap, 10, 200, label=zlabel)
self.plot.scene().addItem(self.colorbar)
self.actionPoints.setChecked(1)
self.actionLines.setChecked(0)
self.colorbar.translate(self.geometry().width() - self.colorbar.zone[2], 20.0)
y = pd.y[:,1]
z = pd.y[:,2]
symbol_brush = self.colormap.map(z, 'qcolor')
symbol_pen = None
symbol_size = 8
elif source.data_type[title] == 'vector':
if(self.current_index == -1):
y = numpy.array(pd.y[self.current_index % pd.y.shape[0]], copy=False)
self.last_vector_y[title] = numpy.array(pd.y)
self.last_vector_x = numpy.array(pd.x)
else:
y = self.last_vector_y[title][self.current_index % self.last_vector_y[title].shape[0]]
elif source.data_type[title] == 'histogram':
if title not in self._histograms:
self._histograms[title] = Histogram(conf["hmin"], conf["hmax"], conf["bins"])
x = self._histograms[title].values_x
y = self._histograms[title].values_y
elif source.data_type[title] == 'normalized_histogram':
if title not in self._normalized_histograms:
self._normalized_histograms[title] = NormalizedHistogram(conf["hmin"], conf["hmax"],
conf["bins"])
x = self._normalized_histograms[title].values_x
y = self._normalized_histograms[title].values_y
x = None
if(source.data_type[title] == 'scalar') or (source.data_type[title] == 'running_hist'):
x = numpy.array(pd.x, copy=False)
sorted_x = numpy.argsort(x)
x = x[sorted_x]
y = y[sorted_x]
if self._settings_diag.showTrendScalar.isChecked():
wl = int(self._settings_diag.windowLength.text())
y = utils.array.runningMean(y, min(y.size-1,wl))
x = x[-y.size:]
elif(source.data_type[title] == 'tuple') or (source.data_type[title] == 'triple'):
x = pd.y[:,0]
elif(source.data_type[title] == 'vector'):
if len(y.shape) == 2:
x = y[0,:]
y = y[1,:]
else:
if 'xmin' in conf and 'xmax' in conf:
xmin = conf['xmin']
xmax = conf['xmax']
else:
xmin = 0
xmax = source.plotdata[title].y.shape[-1] + xmin
x = numpy.linspace(xmin,xmax, y.shape[-1])
if(self._settings_diag.histogram.isChecked()):
bins = int(self._settings_diag.histBins.text())
histMode = self._settings_diag.histMode.currentText()
if (self._settings_diag.histAutorange.isChecked()):
hmin, hmax = y.min(), y.max()
self._settings_diag.histMin.setText("%.2f"%hmin)
self._settings_diag.histMax.setText("%.2f"%hmax)
else:
hmin = float(self._settings_diag.histMin.text())
hmax = float(self._settings_diag.histMax.text())
if histMode == 'count':
y,x = numpy.histogram(y, range=(hmin, hmax), bins=bins)
elif histMode == 'mean':
num,x = numpy.histogram(y, range=(hmin, hmax), bins=bins, weights=x)
den,x = numpy.histogram(y, range=(hmin, hmax), bins=bins)
y = num/(den+1e-20)
x = (x[:-1]+x[1:])/2.0
histoangle = 90
self._configure_axis(source, title, hist=True)
elif(source.data_type[title] == "histogram"):
ringbuffer = pd.y
# Clear histogram if asked for
if pd.clear_histogram:
self._histograms[title].reset()
pd.clear_histogram = False
self._histograms[title].add_values_from_ringbuffer(ringbuffer)
x = self._histograms[title].values_x
y = self._histograms[title].values_y
elif(source.data_type[title] == "normalized_histogram"):
ringbuffer = pd.y
# Clear histogram if asked for
print("clear_histograms = {0}".format(pd.clear_histograms))
if pd.clear_histograms:
self._histograms[title].reset()
pd.clear_histograms = False
self._normalized_histograms[title].add_values_from_ringbuffer(ringbuffer)
x = self._normalized_histograms[title].values_x
y = self._normalized_histograms[title].values_y
else:
self._configure_axis(source, title)
self.plot.setLogMode(x=self._settings_diag.logx.isChecked(),
y=self._settings_diag.logy.isChecked())
if self._settings_diag.showMainLine.isChecked():
plt = self.plot.plot(x=x, y=y, clear=False, pen=pen, symbol=symbol,
symbolPen=symbol_pen, symbolBrush=symbol_brush, symbolSize=symbol_size)
self.legend.addItem(plt, pd.title)
if 'hline' in conf and conf['hline'] is not None:
self.plot.getPlotItem().removeItem(self.hline)
self.hline = pyqtgraph.InfiniteLine(angle=0 + histoangle, movable=False, pen=self.hline_color)
self.plot.getPlotItem().addItem(self.hline)
self.hline.setPos(conf['hline'])
if 'vline' in conf and conf['vline'] is not None:
self.plot.getPlotItem().removeItem(self.vline)
self.vline = pyqtgraph.InfiniteLine(angle=90 + histoangle, movable=False, pen=self.vline_color)
self.plot.getPlotItem().addItem(self.vline)
self.vline.setPos(conf['vline'])
xmins.append(x.min())
xmaxs.append(x.max())
ymins.append(y.min())
ymaxs.append(y.max())
color_index += 1
if (source.data_type[title] == 'vector') and (self._settings_diag.showTrendVector.isChecked()):
for trend in ['mean', 'median', 'std', 'min', 'max']:
if eval('self._settings_diag.trendVector_%s.isChecked()' %trend):
_trend = getattr(numpy, trend)
if len(pd.y.shape) == 3:
ytrend = _trend(numpy.array(pd.y[:,1,:], copy=False), axis=0)
else:
ytrend = _trend(numpy.array(pd.y, copy=False), axis=0)
plt_trend = self.plot.plot(x=x, y=ytrend, clear=False, pen=self.line_colors[color_index % len(self.line_colors)], symbol=symbol,
symbolPen=symbol_pen, symbolBrush=symbol_brush, symbolSize=symbol_size)
self.legend.addItem(plt_trend, trend)
color_index += 1
self.setWindowTitle(", ".join(titlebar))
dt = self.get_time()
# Round to miliseconds
self.timeLabel.setText('%02d:%02d:%02d.%03d' % (dt.hour, dt.minute, dt.second, dt.microsecond/1000))
self.dateLabel.setText(str(dt.date()))
# Set ranges
if len(xmins) > 0:
self._set_range(min(xmins), max(xmaxs), min(ymins), max(ymaxs))
# Various options
if self._settings_diag.aspect_locked.isChecked():
self.plot.getViewBox().setAspectLocked()
if self._settings_diag.flip_x.isChecked():
self.plot.getViewBox().invertX()
if self._settings_diag.flip_y.isChecked():
self.plot.getViewBox().invertY()
def _change_index_by(self, amount):
"""Changes the history index when displaying a vector"""
if self.last_vector_x is None:
return
self.current_index += amount
if(self.current_index > -1):
self.current_index = -1
if(self.current_index < -len(self.last_vector_x)):
self.current_index = -len(self.last_vector_x)
def keyPressEvent(self, event):
"""Handle key presses"""
key = event.key()
if key == QtCore.Qt.Key_Right:
self._change_index_by(1)
self.replot()
elif key == QtCore.Qt.Key_Left:
self._change_index_by(-1)
self.replot()
def get_state(self, _settings = None):
"""Returns settings that can be used to restore the widget to the current state"""
settings = _settings or {}
settings['window_type'] = 'PlotWindow'
settings['viewbox'] = self.plot.getViewBox().getState()
settings['x_view'] = self.actionX_axis.isChecked()
settings['y_view'] = self.actionY_axis.isChecked()
settings['lines'] = self.actionLines.isChecked()
settings['points'] = self.actionPoints.isChecked()
settings['legend'] = self.actionLegend_Box.isChecked()
settings = self._settings_diag.get_state(settings)
return DataWindow.get_state(self, settings)
def restore_from_state(self, settings, data_sources):
self._settings_diag.restore_from_state(settings)
self.plot.getViewBox().setState(settings['viewbox'])
self.actionX_axis.setChecked(settings['x_view'])
self.actionX_axis.triggered.emit(settings['x_view'])
self.actionY_axis.setChecked(settings['y_view'])
self.actionY_axis.triggered.emit(settings['y_view'])
self.actionLines.setChecked(settings['lines'])
self.actionPoints.setChecked(settings['points'])
self.actionLegend_Box.setChecked(settings['legend'])
self.actionLegend_Box.triggered.emit(settings['legend'])
return DataWindow.restore_from_state(self, settings, data_sources)
def _update_bg(self):
if self._settings_diag.bg is not None:
VB = self.plot.getViewBox()
B = pyqtgraph.ImageItem(image=self._settings_diag.bg, autoLevels=True)
xmin = float(self._settings_diag.bg_xmin.text())
ymin = float(self._settings_diag.bg_xmin.text())
width = float(self._settings_diag.bg_xmax.text()) - xmin
height = float(self._settings_diag.bg_ymax.text()) - ymin
rect = QtCore.QRectF(xmin, ymin, width, height)
B.setRect(rect)
VB.addItem(B, ignoreBounds=True)
def updateFonts(self):
f = self.title.font()
size = int(self.settings.value("plotFontSize"))
f.setPointSize(size)
self.title.setFont(f)
f = QtGui.QFont()
f.setPointSize(size)
ax = self.plot.getAxis('left')
ax.setTickFont(f)
ax = self.plot.getAxis('bottom')
ax.setTickFont(f)
def _onMouseMoved(self, pos):
view = self.plot
xy = view.mapToView(pos)
x = xy.x()
y = xy.y()
self.xLabel.setText("%f" % (x))
self.yLabel.setText("%f" % (y))
def replot(self):
"""Replot data"""
self.plot.clear()
# Init background if defined in a data source
if self._settings_diag.bg is None:
alert_flag = False
for source, title in self.source_and_titles():
conf = source.conf[title]
if "bg_filename" in conf:
conf_bg = {}
for k,v in conf.items():
if k.startswith("bg_"):
conf_bg[k] = v
self._settings_diag._configure_bg(**conf_bg)
# Use only first if there are many
break
alert_flag = False
for source, title in self.source_and_titles():
conf = source.conf[title]
if "alert" in conf and self.actionToggleAlert.isChecked() and conf['alert']:
alert_flag = True
if alert_flag:
os.system('afplay -v %f src/interface/ui/sounds/%s.wav &' %(self.volume,self.sound))
if not self.alertBlinkTimer.isActive():
self.alertBlinkTimer.start()
else:
if self.alertBlinkTimer.isActive():
self.alertBlinkTimer.stop()
self.setStyleSheet("")
# Load background if configured
self._update_bg()
color_index = 0
titlebar = []
self.plot.plotItem.legend.items = []
xmins = []
xmaxs = []
ymins = []
ymaxs = []
for source, title in self.source_and_titles():
if(title not in source.plotdata or source.plotdata[title].y is None):
continue
pd = source.plotdata[title]
titlebar.append(pd.title)
conf = source.conf[title]
color = self.line_colors[color_index % len(self.line_colors)]
pen = None
symbol = None
symbol_pen = None
symbol_brush = None
symbol_size = None
histoangle = 0
if(self.actionLines.isChecked()):
pen = color
if(self.actionPoints.isChecked()):
symbol = 'o'
symbol_pen = color
symbol_brush = color
symbol_size = 3
if(source.data_type[title] == 'scalar') or (source.data_type[title] == 'running_hist'):
y = numpy.array(pd.y, copy=False)
self.last_vector_y = {}
self.last_vector_x = None
elif(source.data_type[title] == 'tuple'):
y = pd.y[:,1]
symbol_brush = (255,255,255,120)
symbol_pen = None
symbol_size = 8
elif(source.data_type[title] == 'triple'):
if self.colormap is None:
vmin, vmax = (0,1)
if 'vmin' in conf:
vmin = conf['vmin']
if 'vmax' in conf:
vmax = conf['vmax']
stops = numpy.r_[vmin, vmax]
colors = numpy.array([[0, 0, 1, 0.7], [1, 0, 0, 1.0]])
self.colormap = pyqtgraph.ColorMap(stops, colors)
if 'zlabel' in conf:
zlabel = conf['zlabel']
else:
zlabel = 'z'
if self.colorbar is not None:
self.plot.scene().removeItem(self.colorbar)
self.colorbar = ColorBar(self.colormap, 10, 200, label=zlabel)
self.plot.scene().addItem(self.colorbar)
self.actionPoints.setChecked(1)
self.actionLines.setChecked(0)
self.colorbar.translate(self.geometry().width() - self.colorbar.zone[2], 20.0)
y = pd.y[:,1]
z = pd.y[:,2]
symbol_brush = self.colormap.map(z, 'qcolor')
symbol_pen = None
symbol_size = 8
elif source.data_type[title] == 'vector':
if(self.current_index == -1):
y = numpy.array(pd.y[self.current_index % pd.y.shape[0]], copy=False)
self.last_vector_y[title] = numpy.array(pd.y)
self.last_vector_x = numpy.array(pd.x)
else:
y = self.last_vector_y[title][self.current_index % self.last_vector_y[title].shape[0]]
elif source.data_type[title] == 'histogram':
if title not in self._histograms:
self._histograms[title] = Histogram(conf["hmin"], conf["hmax"], conf["bins"])
x = self._histograms[title].values_x
y = self._histograms[title].values_y
elif source.data_type[title] == 'normalized_histogram':
if title not in self._normalized_histograms:
self._normalized_histograms[title] = NormalizedHistogram(conf["hmin"], conf["hmax"],
conf["bins"])
x = self._normalized_histograms[title].values_x
y = self._normalized_histograms[title].values_y
x = None
if(source.data_type[title] == 'scalar') or (source.data_type[title] == 'running_hist'):
x = numpy.array(pd.x, copy=False)
sorted_x = numpy.argsort(x)
x = x[sorted_x]
y = y[sorted_x]
if self._settings_diag.showTrendScalar.isChecked():
wl = int(self._settings_diag.windowLength.text())
y = utils.array.runningMean(y, min(y.size-1,wl))
x = x[-y.size:]
elif(source.data_type[title] == 'tuple') or (source.data_type[title] == 'triple'):
x = pd.y[:,0]
elif(source.data_type[title] == 'vector'):
if len(y.shape) == 2:
x = y[0,:]
y = y[1,:]
else:
if 'xmin' in conf and 'xmax' in conf:
xmin = conf['xmin']
xmax = conf['xmax']
else:
xmin = 0
xmax = source.plotdata[title].y.shape[-1] + xmin
x = numpy.linspace(xmin,xmax, y.shape[-1])
if(self._settings_diag.histogram.isChecked()):
bins = int(self._settings_diag.histBins.text())
histMode = self._settings_diag.histMode.currentText()
if (self._settings_diag.histAutorange.isChecked()):
hmin, hmax = y.min(), y.max()
self._settings_diag.histMin.setText("%.2f"%hmin)
self._settings_diag.histMax.setText("%.2f"%hmax)
else:
hmin = float(self._settings_diag.histMin.text())
hmax = float(self._settings_diag.histMax.text())
if histMode == 'count':
y,x = numpy.histogram(y, range=(hmin, hmax), bins=bins)
elif histMode == 'mean':
num,x = numpy.histogram(y, range=(hmin, hmax), bins=bins, weights=x)
den,x = numpy.histogram(y, range=(hmin, hmax), bins=bins)
y = num/(den+1e-20)
x = (x[:-1]+x[1:])/2.0
histoangle = 90
self._configure_axis(source, title, hist=True)
elif(source.data_type[title] == "histogram"):
ringbuffer = pd.y
# Clear histogram if asked for
if pd.clear_histogram:
self._histograms[title].reset()
pd.clear_histogram = False
self._histograms[title].add_values_from_ringbuffer(ringbuffer)
x = self._histograms[title].values_x
y = self._histograms[title].values_y
elif(source.data_type[title] == "normalized_histogram"):
ringbuffer = pd.y
# Clear histogram if asked for
print("clear_histograms = {0}".format(pd.clear_histograms))
if pd.clear_histograms:
self._histograms[title].reset()
pd.clear_histograms = False
self._normalized_histograms[title].add_values_from_ringbuffer(ringbuffer)
x = self._normalized_histograms[title].values_x
y = self._normalized_histograms[title].values_y
else:
self._configure_axis(source, title)
self.plot.setLogMode(x=self._settings_diag.logx.isChecked(),
y=self._settings_diag.logy.isChecked())
if self._settings_diag.showMainLine.isChecked():
plt = self.plot.plot(x=x, y=y, clear=False, pen=pen, symbol=symbol,
symbolPen=symbol_pen, symbolBrush=symbol_brush, symbolSize=symbol_size)
self.legend.addItem(plt, pd.title)
if 'hline' in conf and conf['hline'] is not None:
self.plot.getPlotItem().removeItem(self.hline)
self.hline = pyqtgraph.InfiniteLine(angle=0 + histoangle, movable=False, pen=self.hline_color)
self.plot.getPlotItem().addItem(self.hline)
self.hline.setPos(conf['hline'])
if 'vline' in conf and conf['vline'] is not None:
self.plot.getPlotItem().removeItem(self.vline)
self.vline = pyqtgraph.InfiniteLine(angle=90 + histoangle, movable=False, pen=self.vline_color)
self.plot.getPlotItem().addItem(self.vline)
self.vline.setPos(conf['vline'])
xmins.append(x.min())
xmaxs.append(x.max())
ymins.append(y.min())
ymaxs.append(y.max())
color_index += 1
if (source.data_type[title] == 'vector') and (self._settings_diag.showTrendVector.isChecked()):
for trend in ['mean', 'median', 'std', 'min', 'max']:
if eval('self._settings_diag.trendVector_%s.isChecked()' %trend):
_trend = getattr(numpy, trend)
if len(pd.y.shape) == 3:
ytrend = _trend(numpy.array(pd.y[:,1,:], copy=False), axis=0)
else:
ytrend = _trend(numpy.array(pd.y, copy=False), axis=0)
plt_trend = self.plot.plot(x=x, y=ytrend, clear=False, pen=self.line_colors[color_index % len(self.line_colors)], symbol=symbol,
symbolPen=symbol_pen, symbolBrush=symbol_brush, symbolSize=symbol_size)
self.legend.addItem(plt_trend, trend)
color_index += 1
self.setWindowTitle(", ".join(titlebar))
dt = self.get_time()
# Round to miliseconds
self.timeLabel.setText('%02d:%02d:%02d.%03d' % (dt.hour, dt.minute, dt.second, dt.microsecond/1000))
self.dateLabel.setText(str(dt.date()))
# Set ranges
if len(xmins) > 0:
self._set_range(min(xmins), max(xmaxs), min(ymins), max(ymaxs))
# Various options
if self._settings_diag.aspect_locked.isChecked():
self.plot.getViewBox().setAspectLocked()
if self._settings_diag.flip_x.isChecked():
self.plot.getViewBox().invertX()
if self._settings_diag.flip_y.isChecked():
self.plot.getViewBox().invertY()
def replot(self):
"""Replot data"""
self.plot.clear()
color_index = 0
titlebar = []
self.plot.plotItem.legend.items = []
for source, title in self.source_and_titles():
if(title not in source.plotdata or source.plotdata[title].y is None):
continue
pd = source.plotdata[title]
titlebar.append(pd.title)
color = self.line_colors[color_index % len(self.line_colors)]
pen = None
symbol = None
symbol_pen = None
symbol_brush = None
symbol_size = None
if(self.actionLines.isChecked()):
pen = color
if(self.actionPoints.isChecked()):
symbol = 'o'
symbol_pen = color
symbol_brush = color
symbol_size = 3
if(source.data_type[title] == 'scalar') or (source.data_type[title] == 'running_hist'):
y = numpy.array(pd.y, copy=False)
self.last_vector_y = {}
self.last_vector_x = None
elif(source.data_type[title] == 'tuple'):
y = pd.y[:,1]
symbol_brush = (255,255,255,120)
symbol_pen = None
symbol_size = 8
elif(source.data_type[title] == 'triple'):
conf = source.conf[title]
if self.colormap is None:
vmin, vmax = (0,1)
if 'vmin' in conf:
vmin = conf['vmin']
if 'vmax' in conf:
vmax = conf['vmax']
stops = numpy.r_[vmin, vmax]
colors = numpy.array([[0, 0, 1, 0.7], [1, 0, 0, 1.0]])
self.colormap = pyqtgraph.ColorMap(stops, colors)
if 'zlabel' in conf:
zlabel = conf['zlabel']
else:
zlabel = 'z'
if self.colorbar is not None:
self.plot.scene().removeItem(self.colorbar)
self.colorbar = ColorBar(self.colormap, 10, 200, label=zlabel)
self.plot.scene().addItem(self.colorbar)
self.actionPoints.setChecked(1)
self.actionLines.setChecked(0)
self.colorbar.translate(self.geometry().width() - self.colorbar.zone[2], 20.0)
y = pd.y[:,1]
z = pd.y[:,2]
symbol_brush = self.colormap.map(z, 'qcolor')
symbol_pen = None
symbol_size = 8
elif source.data_type[title] == 'vector':
if(self.current_index == -1):
y = numpy.array(pd.y[self.current_index % pd.y.shape[0]], copy=False)
self.last_vector_y[title] = numpy.array(pd.y)
self.last_vector_x = numpy.array(pd.x)
else:
y = self.last_vector_y[title][self.current_index % self.last_vector_y[title].shape[0]]
x = None
if(source.data_type[title] == 'scalar') or (source.data_type[title] == 'running_hist'):
x = numpy.array(pd.x, copy=False)
sorted_x = numpy.argsort(x)
x = x[sorted_x]
y = y[sorted_x]
if self._settings_diag.showTrendScalar.isChecked():
wl = int(self._settings_diag.windowLength.text())
y = utils.array.runningMean(y, wl)
x = x[-max(len(y),1):]
self._configure_ylimits(source, title)
elif(source.data_type[title] == 'tuple') or (source.data_type[title] == 'triple'):
x = pd.y[:,0]
elif(source.data_type[title] == 'vector'):
if len(y.shape) == 2:
x = y[0,:]
y = y[1,:]
else:
xmin, xmax = self._configure_xlimits(source, title)
x = numpy.linspace(xmin,xmax, y.shape[-1])
if(self._settings_diag.histogram.isChecked()):
bins = int(self._settings_diag.histBins.text())
if (self._settings_diag.histAutorange.isChecked()):
hmin, hmax = y.min(), y.max()
self._settings_diag.histMin.setText("%.2f"%hmin)
self._settings_diag.histMax.setText("%.2f"%hmax)
else:
hmin = float(self._settings_diag.histMin.text())
hmax = float(self._settings_diag.histMax.text())
y,x = numpy.histogram(y, range=(hmin, hmax), bins=bins)
x = (x[:-1]+x[1:])/2.0
self._configure_axis(source, title, hist=True)
else:
self._configure_axis(source, title)
self.plot.setLogMode(x=self._settings_diag.logx.isChecked(),
y=self._settings_diag.logy.isChecked())
plt = self.plot.plot(x=x, y=y, clear=False, pen=pen, symbol=symbol,
symbolPen=symbol_pen, symbolBrush=symbol_brush, symbolSize=symbol_size)
self.legend.addItem(plt, pd.title)
color_index += 1
if (source.data_type[title] == 'vector') and (self._settings_diag.showTrendVector.isChecked()):
for trend in ['mean', 'median', 'std', 'min', 'max']:
if eval('self._settings_diag.trendVector_%s.isChecked()' %trend):
_trend = getattr(numpy, trend)
if len(pd.y.shape) == 3:
ytrend = _trend(numpy.array(pd.y[:,1,:], copy=False), axis=0)
else:
ytrend = _trend(numpy.array(pd.y, copy=False), axis=0)
plt_trend = self.plot.plot(x=x, y=ytrend, clear=False, pen=self.line_colors[color_index % len(self.line_colors)], symbol=symbol,
symbolPen=symbol_pen, symbolBrush=symbol_brush, symbolSize=symbol_size)
self.legend.addItem(plt_trend, trend)
color_index += 1
self.setWindowTitle(", ".join(titlebar))
dt = self.get_time()
# Round to miliseconds
self.timeLabel.setText('%02d:%02d:%02d.%03d' % (dt.hour, dt.minute, dt.second, dt.microsecond/1000))
self.dateLabel.setText(str(dt.date()))
class PlotWindow(DataWindow, Ui_plotWindow):
"""Window to display 2D plots"""
def __init__(self, parent=None):
DataWindow.__init__(self, parent)
self.plot = pyqtgraph.PlotWidget(self.plotFrame, antialiasing=True)
self.plot.hideAxis('bottom')
self.legend = self.plot.addLegend()
self.legend.hide()
self._finish_layout()
self.actionLegend_Box.triggered.connect(self.on_view_legend_box)
self.actionX_axis.triggered.connect(self.on_view_x_axis)
self.actionY_axis.triggered.connect(self.on_view_y_axis)
self.acceptable_data_types = ['scalar', 'vector', 'tuple', 'triple', 'running_hist' ]
self.exclusive_source = False
self.line_colors = [(252, 175, 62), (114, 159, 207), (255, 255, 255),
(239, 41, 41), (138, 226, 52), (173, 127, 168)]
self.colorbar = None
self.colormap = None
self.current_index = -1
self.last_vector_y = {}
self.last_vector_x = None
self._settings_diag = LinePlotSettings(self)
self.x_auto = True
self.y_auto = True
self.x_label = ''
self.y_label = ''
def on_view_legend_box(self):
"""Show/hide legend box"""
action = self.sender()
if(action.isChecked()):
self.legend.show()
else:
self.legend.hide()
def on_view_x_axis(self):
"""Show/hide X axis"""
action = self.sender()
if(action.isChecked()):
self.plot.showAxis('bottom')
else:
self.plot.hideAxis('bottom')
def on_view_y_axis(self):
"""Show/hide Y axis"""
action = self.sender()
if(action.isChecked()):
self.plot.showAxis('left')
else:
self.plot.hideAxis('left')
def _on_plot_settings(self):
"""Show the plot settings dialog"""
self._settings_diag.x_auto.setChecked(self.x_auto)
self._settings_diag.y_auto.setChecked(self.y_auto)
self._settings_diag.x_label.setText(self.x_label)
self._settings_diag.y_label.setText(self.y_label)
self._settings_diag.histAutorange.toggled.connect(self._on_histogram_autorange)
if(self._settings_diag.exec_()):
self.x_auto = self._settings_diag.x_auto.isChecked()
if(self.x_auto is False):
self.x_label = self._settings_diag.x_label.text()
self.y_auto = self._settings_diag.y_auto.isChecked()
if(self.y_auto is False):
self.y_label = self._settings_diag.y_label.text()
# Show changes immediately
self.replot()
def _on_histogram_autorange(self, checked):
if checked:
self._settings_diag.histMin.setEnabled(False)
self._settings_diag.histMax.setEnabled(False)
else:
self._settings_diag.histMin.setEnabled(True)
self._settings_diag.histMax.setEnabled(True)
def get_time(self, index=None):
"""Returns the time of the given index, or the time of the last data point"""
if index is None:
index = self.current_index
# Check if we have last_vector
if (self.last_vector_x is not None):
dt = datetime.datetime.fromtimestamp(self.last_vector_x[index])
return dt
# Check if we have enabled_sources
source = None
if(self._enabled_sources):
for ds in self._enabled_sources.keys():
if(len(self._enabled_sources[ds])):
title = self._enabled_sources[ds][0]
source = ds
break
# There might be no data yet, so no plotdata
if(source is not None and title in source.plotdata and
source.plotdata[title].x is not None):
pd = source.plotdata[title]
dt = datetime.datetime.fromtimestamp(pd.x[index])
return dt
else:
return datetime.datetime.now()
def _configure_axis(self, source, title, hist=False):
"""Configures the x and y axis of the plot, according to the
source/title configuration and content type"""
conf = source.conf[title]
if(self.actionX_axis.isChecked()):
if 'xlabel' in conf and self.x_auto:
self.x_label = conf['xlabel']
if hist:
self.plot.setLabel('bottom', self.y_label)
else:
self.plot.setLabel('bottom', self.x_label)
if(self.actionY_axis.isChecked()):
if 'ylabel' in conf and self.y_auto:
self.y_label = conf['ylabel']
if hist:
self.plot.setLabel('left', 'Counts')
else:
self.plot.setLabel('left', self.y_label)
def _configure_xlimits(self, source, title):
conf = source.conf[title]
xmin = 0
xmax = source.plotdata[title].y.shape[-1] + xmin
if 'xmin' in conf and 'xmax' in conf:
xmin = conf['xmin']
xmax = conf['xmax']
return xmin, xmax
def _configure_ylimits(self, source, title):
ymin = source.plotdata[title].y.min
ymax = source.plotdata[title].y.max
if ymin == ymax == 0:
ymin = -0.1
ymax = 0.1
if not self._settings_diag.ylimits_auto.isChecked():
ymin = float(str(self._settings_diag.ymin.text()))
ymax = float(str(self._settings_diag.ymax.text()))
self.plot.setRange(yRange=(ymin, ymax))
def replot(self):
"""Replot data"""
self.plot.clear()
color_index = 0
titlebar = []
self.plot.plotItem.legend.items = []
for source, title in self.source_and_titles():
if(title not in source.plotdata or source.plotdata[title].y is None):
continue
pd = source.plotdata[title]
titlebar.append(pd.title)
color = self.line_colors[color_index % len(self.line_colors)]
pen = None
symbol = None
symbol_pen = None
symbol_brush = None
symbol_size = None
if(self.actionLines.isChecked()):
pen = color
if(self.actionPoints.isChecked()):
symbol = 'o'
symbol_pen = color
symbol_brush = color
symbol_size = 3
if(source.data_type[title] == 'scalar') or (source.data_type[title] == 'running_hist'):
y = numpy.array(pd.y, copy=False)
self.last_vector_y = {}
self.last_vector_x = None
elif(source.data_type[title] == 'tuple'):
y = pd.y[:,1]
symbol_brush = (255,255,255,120)
symbol_pen = None
symbol_size = 8
elif(source.data_type[title] == 'triple'):
conf = source.conf[title]
if self.colormap is None:
vmin, vmax = (0,1)
if 'vmin' in conf:
vmin = conf['vmin']
if 'vmax' in conf:
vmax = conf['vmax']
stops = numpy.r_[vmin, vmax]
colors = numpy.array([[0, 0, 1, 0.7], [1, 0, 0, 1.0]])
self.colormap = pyqtgraph.ColorMap(stops, colors)
if 'zlabel' in conf:
zlabel = conf['zlabel']
else:
zlabel = 'z'
if self.colorbar is not None:
self.plot.scene().removeItem(self.colorbar)
self.colorbar = ColorBar(self.colormap, 10, 200, label=zlabel)
self.plot.scene().addItem(self.colorbar)
self.actionPoints.setChecked(1)
self.actionLines.setChecked(0)
self.colorbar.translate(self.geometry().width() - self.colorbar.zone[2], 20.0)
y = pd.y[:,1]
z = pd.y[:,2]
symbol_brush = self.colormap.map(z, 'qcolor')
symbol_pen = None
symbol_size = 8
elif source.data_type[title] == 'vector':
if(self.current_index == -1):
y = numpy.array(pd.y[self.current_index % pd.y.shape[0]], copy=False)
self.last_vector_y[title] = numpy.array(pd.y)
self.last_vector_x = numpy.array(pd.x)
else:
y = self.last_vector_y[title][self.current_index % self.last_vector_y[title].shape[0]]
x = None
if(source.data_type[title] == 'scalar') or (source.data_type[title] == 'running_hist'):
x = numpy.array(pd.x, copy=False)
sorted_x = numpy.argsort(x)
x = x[sorted_x]
y = y[sorted_x]
if self._settings_diag.showTrendScalar.isChecked():
wl = int(self._settings_diag.windowLength.text())
y = utils.array.runningMean(y, wl)
x = x[-max(len(y),1):]
self._configure_ylimits(source, title)
elif(source.data_type[title] == 'tuple') or (source.data_type[title] == 'triple'):
x = pd.y[:,0]
elif(source.data_type[title] == 'vector'):
if len(y.shape) == 2:
x = y[0,:]
y = y[1,:]
else:
xmin, xmax = self._configure_xlimits(source, title)
x = numpy.linspace(xmin,xmax, y.shape[-1])
if(self._settings_diag.histogram.isChecked()):
bins = int(self._settings_diag.histBins.text())
if (self._settings_diag.histAutorange.isChecked()):
hmin, hmax = y.min(), y.max()
self._settings_diag.histMin.setText("%.2f"%hmin)
self._settings_diag.histMax.setText("%.2f"%hmax)
else:
hmin = float(self._settings_diag.histMin.text())
hmax = float(self._settings_diag.histMax.text())
y,x = numpy.histogram(y, range=(hmin, hmax), bins=bins)
x = (x[:-1]+x[1:])/2.0
self._configure_axis(source, title, hist=True)
else:
self._configure_axis(source, title)
self.plot.setLogMode(x=self._settings_diag.logx.isChecked(),
y=self._settings_diag.logy.isChecked())
plt = self.plot.plot(x=x, y=y, clear=False, pen=pen, symbol=symbol,
symbolPen=symbol_pen, symbolBrush=symbol_brush, symbolSize=symbol_size)
self.legend.addItem(plt, pd.title)
color_index += 1
if (source.data_type[title] == 'vector') and (self._settings_diag.showTrendVector.isChecked()):
for trend in ['mean', 'median', 'std', 'min', 'max']:
if eval('self._settings_diag.trendVector_%s.isChecked()' %trend):
_trend = getattr(numpy, trend)
if len(pd.y.shape) == 3:
ytrend = _trend(numpy.array(pd.y[:,1,:], copy=False), axis=0)
else:
ytrend = _trend(numpy.array(pd.y, copy=False), axis=0)
plt_trend = self.plot.plot(x=x, y=ytrend, clear=False, pen=self.line_colors[color_index % len(self.line_colors)], symbol=symbol,
symbolPen=symbol_pen, symbolBrush=symbol_brush, symbolSize=symbol_size)
self.legend.addItem(plt_trend, trend)
color_index += 1
self.setWindowTitle(", ".join(titlebar))
dt = self.get_time()
# Round to miliseconds
self.timeLabel.setText('%02d:%02d:%02d.%03d' % (dt.hour, dt.minute, dt.second, dt.microsecond/1000))
self.dateLabel.setText(str(dt.date()))
def _change_index_by(self, amount):
"""Changes the history index when displaying a vector"""
if self.last_vector_x is None:
return
self.current_index += amount
if(self.current_index > -1):
self.current_index = -1
if(self.current_index < -len(self.last_vector_x)):
self.current_index = -len(self.last_vector_x)
def keyPressEvent(self, event):
"""Handle key presses"""
key = event.key()
if key == QtCore.Qt.Key_Right:
self._change_index_by(1)
self.replot()
elif key == QtCore.Qt.Key_Left:
self._change_index_by(-1)
self.replot()
def get_state(self, _settings = None):
"""Returns settings that can be used to restore the widget to the current state"""
settings = _settings or {}
settings['window_type'] = 'PlotWindow'
settings['viewbox'] = self.plot.getViewBox().getState()
settings['x_view'] = self.actionX_axis.isChecked()
settings['y_view'] = self.actionY_axis.isChecked()
settings['lines'] = self.actionLines.isChecked()
settings['points'] = self.actionPoints.isChecked()
settings['legend'] = self.actionLegend_Box.isChecked()
return DataWindow.get_state(self, settings)
def restore_from_state(self, settings, data_sources):
self.plot.getViewBox().setState(settings['viewbox'])
self.actionX_axis.setChecked(settings['x_view'])
self.actionX_axis.triggered.emit(settings['x_view'])
self.actionY_axis.setChecked(settings['y_view'])
self.actionY_axis.triggered.emit(settings['y_view'])
self.actionLines.setChecked(settings['lines'])
self.actionPoints.setChecked(settings['points'])
self.actionLegend_Box.setChecked(settings['legend'])
self.actionLegend_Box.triggered.emit(settings['legend'])
return DataWindow.restore_from_state(self, settings, data_sources)
class PlotWindow(DataWindow, Ui_plotWindow):
"""Window to display 2D plots"""
def __init__(self, parent=None):
DataWindow.__init__(self, parent)
self.plot = pyqtgraph.PlotWidget(self.plotFrame, antialiasing=True)
self.plot.hideAxis('bottom')
self.legend = self.plot.addLegend()
self.legend.hide()
self._finish_layout()
self.actionLegend_Box.triggered.connect(self.on_view_legend_box)
self.actionX_axis.triggered.connect(self.on_view_x_axis)
self.actionY_axis.triggered.connect(self.on_view_y_axis)
self.acceptable_data_types = ['scalar', 'vector', 'tuple', 'triple', 'running_hist', 'histogram' ]
self.exclusive_source = False
self.line_colors = [(252, 175, 62), (114, 159, 207), (255, 255, 255),
(239, 41, 41), (138, 226, 52), (173, 127, 168)]
self.colorbar = None
self.colormap = None
self.current_index = -1
self.last_vector_y = {}
self.last_vector_x = None
self.hline = None
self.vline = None
self.hline_color = (0,204,0)
self.vline_color = (204,0,0)
self._settings_diag = LinePlotSettings(self)
self._histograms = {}
self.updateFonts()
self.plot.scene().sigMouseMoved.connect(self._onMouseMoved)
def on_view_legend_box(self):
"""Show/hide legend box"""
action = self.sender()
if(action.isChecked()):
self.legend.show()
else:
self.legend.hide()
def on_view_x_axis(self):
"""Show/hide X axis"""
action = self.sender()
if(action.isChecked()):
self.plot.showAxis('bottom')
else:
self.plot.hideAxis('bottom')
def on_view_y_axis(self):
"""Show/hide Y axis"""
action = self.sender()
if(action.isChecked()):
self.plot.showAxis('left')
else:
self.plot.hideAxis('left')
def _on_plot_settings(self):
"""Show the plot settings dialog"""
self._settings_diag.histAutorange.toggled.connect(self._on_histogram_autorange)
if(self._settings_diag.exec_()):
self._settings_diag._read_bg_file()
# Show changes immediately
self.replot()
def _on_histogram_autorange(self, checked):
if checked:
self._settings_diag.histMin.setEnabled(False)
self._settings_diag.histMax.setEnabled(False)
else:
self._settings_diag.histMin.setEnabled(True)
self._settings_diag.histMax.setEnabled(True)
def get_time(self, index=None):
"""Returns the time of the given index, or the time of the last data point"""
if index is None:
index = self.current_index
# Check if we have last_vector
if (self.last_vector_x is not None):
dt = datetime.datetime.fromtimestamp(self.last_vector_x[index])
return dt
# Check if we have enabled_sources
source = None
if(self._enabled_sources):
for ds in self._enabled_sources.keys():
if(len(self._enabled_sources[ds])):
title = self._enabled_sources[ds][0]
source = ds
break
# There might be no data yet, so no plotdata
if(source is not None and title in source.plotdata and
source.plotdata[title].x is not None):
pd = source.plotdata[title]
dt = datetime.datetime.fromtimestamp(pd.x[index])
return dt
else:
return datetime.datetime.now()
def _configure_axis(self, source, title, hist=False):
"""Configures the x and y axis of the plot, according to the
source/title configuration and content type"""
conf = source.conf[title]
if(self.actionX_axis.isChecked()):
if 'xlabel' in conf and self._settings_diag.x_auto.isChecked():
self._settings_diag.x_label.setText(conf['xlabel'])
if hist:
self.plot.setLabel('bottom', self._settings_diag.y_label.text())
else:
self.plot.setLabel('bottom', self._settings_diag.x_label.text())
if(self.actionY_axis.isChecked()):
if 'ylabel' in conf and self._settings_diag.y_auto.isChecked():
self._settings_diag.y_label.setText(conf['ylabel'])
if hist:
self.plot.setLabel('left', 'Counts')
else:
self.plot.setLabel('left', self._settings_diag.y_label.text())
def _set_range(self, xmin, xmax, ymin, ymax):
if not self._settings_diag.xlimits_auto.isChecked():
try:
xmin = float(str(self._settings_diag.xmin.text()))
except ValueError:
pass
try:
xmax = float(str(self._settings_diag.xmax.text()))
except ValueError:
pass
if not self._settings_diag.ylimits_auto.isChecked():
try:
ymin = float(str(self._settings_diag.ymin.text()))
except ValueError:
pass
try:
ymax = float(str(self._settings_diag.ymax.text()))
except ValueError:
pass
if (xmax - xmin) == 0.:
xmin -= 0.1
xmax += 0.1
if (ymax - ymin) == 0.:
ymin -= 0.1
ymax += 0.1
self.plot.setRange(xRange=(xmin, xmax), yRange=(ymin, ymax))
def replot(self):
"""Replot data"""
self.plot.clear()
# Init background if defined in a data source
if self._settings_diag.bg is None:
alert_flag = False
for source, title in self.source_and_titles():
conf = source.conf[title]
if "bg_filename" in conf:
conf_bg = {}
for k,v in conf.items():
if k.startswith("bg_"):
conf_bg[k] = v
self._settings_diag._configure_bg(**conf_bg)
# Use only first if there are many
break
alert_flag = False
for source, title in self.source_and_titles():
conf = source.conf[title]
if "alert" in conf and self.alert and conf['alert']:
alert_flag = True
if alert_flag:
os.system('afplay -v %f src/interface/ui/sounds/%s.wav &' %(self.volume,self.sound))
if not self.alertBlinkTimer.isActive():
self.alertBlinkTimer.start()
else:
if self.alertBlinkTimer.isActive():
self.alertBlinkTimer.stop()
self.setStyleSheet("")
# Load background if configured
self._update_bg()
color_index = 0
titlebar = []
self.plot.plotItem.legend.items = []
xmins = []
xmaxs = []
ymins = []
ymaxs = []
for source, title in self.source_and_titles():
if(title not in source.plotdata or source.plotdata[title].y is None):
continue
pd = source.plotdata[title]
titlebar.append(pd.title)
conf = source.conf[title]
color = self.line_colors[color_index % len(self.line_colors)]
pen = None
symbol = None
symbol_pen = None
symbol_brush = None
symbol_size = None
histoangle = 0
if(self.actionLines.isChecked()):
pen = color
if(self.actionPoints.isChecked()):
symbol = 'o'
symbol_pen = color
symbol_brush = color
symbol_size = 3
if(source.data_type[title] == 'scalar') or (source.data_type[title] == 'running_hist'):
y = numpy.array(pd.y, copy=False)
self.last_vector_y = {}
self.last_vector_x = None
elif(source.data_type[title] == 'tuple'):
y = pd.y[:,1]
symbol_brush = (255,255,255,120)
symbol_pen = None
symbol_size = 8
elif(source.data_type[title] == 'triple'):
if self.colormap is None:
vmin, vmax = (0,1)
if 'vmin' in conf:
vmin = conf['vmin']
if 'vmax' in conf:
vmax = conf['vmax']
stops = numpy.r_[vmin, vmax]
colors = numpy.array([[0, 0, 1, 0.7], [1, 0, 0, 1.0]])
self.colormap = pyqtgraph.ColorMap(stops, colors)
if 'zlabel' in conf:
zlabel = conf['zlabel']
else:
zlabel = 'z'
if self.colorbar is not None:
self.plot.scene().removeItem(self.colorbar)
self.colorbar = ColorBar(self.colormap, 10, 200, label=zlabel)
self.plot.scene().addItem(self.colorbar)
self.actionPoints.setChecked(1)
self.actionLines.setChecked(0)
self.colorbar.translate(self.geometry().width() - self.colorbar.zone[2], 20.0)
y = pd.y[:,1]
z = pd.y[:,2]
symbol_brush = self.colormap.map(z, 'qcolor')
symbol_pen = None
symbol_size = 8
elif source.data_type[title] == 'vector':
if(self.current_index == -1):
y = numpy.array(pd.y[self.current_index % pd.y.shape[0]], copy=False)
self.last_vector_y[title] = numpy.array(pd.y)
self.last_vector_x = numpy.array(pd.x)
else:
y = self.last_vector_y[title][self.current_index % self.last_vector_y[title].shape[0]]
elif source.data_type[title] == 'histogram':
if title not in self._histograms:
self._histograms[title] = Histogram(conf["hmin"], conf["hmax"], conf["bins"])
x = self._histograms[title].values_x
y = self._histograms[title].values_y
x = None
if(source.data_type[title] == 'scalar') or (source.data_type[title] == 'running_hist'):
x = numpy.array(pd.x, copy=False)
sorted_x = numpy.argsort(x)
x = x[sorted_x]
y = y[sorted_x]
if self._settings_diag.showTrendScalar.isChecked():
wl = int(self._settings_diag.windowLength.text())
y = utils.array.runningMean(y, min(y.size-1,wl))
x = x[-y.size:]
elif(source.data_type[title] == 'tuple') or (source.data_type[title] == 'triple'):
x = pd.y[:,0]
elif(source.data_type[title] == 'vector'):
if len(y.shape) == 2:
x = y[0,:]
y = y[1,:]
else:
if 'xmin' in conf and 'xmax' in conf:
xmin = conf['xmin']
xmax = conf['xmax']
else:
xmin = 0
xmax = source.plotdata[title].y.shape[-1] + xmin
x = numpy.linspace(xmin,xmax, y.shape[-1])
if(self._settings_diag.histogram.isChecked()):
bins = int(self._settings_diag.histBins.text())
histMode = self._settings_diag.histMode.currentText()
if (self._settings_diag.histAutorange.isChecked()):
hmin, hmax = y.min(), y.max()
self._settings_diag.histMin.setText("%.2f"%hmin)
self._settings_diag.histMax.setText("%.2f"%hmax)
else:
hmin = float(self._settings_diag.histMin.text())
hmax = float(self._settings_diag.histMax.text())
if histMode == 'count':
y,x = numpy.histogram(y, range=(hmin, hmax), bins=bins)
elif histMode == 'mean':
num,x = numpy.histogram(y, range=(hmin, hmax), bins=bins, weights=x)
den,x = numpy.histogram(y, range=(hmin, hmax), bins=bins)
y = num/(den+1e-20)
x = (x[:-1]+x[1:])/2.0
histoangle = 90
self._configure_axis(source, title, hist=True)
elif(source.data_type[title] == "histogram"):
ringbuffer = pd.y
self._histograms[title].add_values_from_ringbuffer(ringbuffer)
x = self._histograms[title].values_x
y = self._histograms[title].values_y
else:
self._configure_axis(source, title)
self.plot.setLogMode(x=self._settings_diag.logx.isChecked(),
y=self._settings_diag.logy.isChecked())
plt = self.plot.plot(x=x, y=y, clear=False, pen=pen, symbol=symbol,
symbolPen=symbol_pen, symbolBrush=symbol_brush, symbolSize=symbol_size)
if 'hline' in conf and conf['hline'] is not None:
self.plot.getPlotItem().removeItem(self.hline)
self.hline = pyqtgraph.InfiniteLine(angle=0 + histoangle, movable=False, pen=self.hline_color)
self.plot.getPlotItem().addItem(self.hline)
self.hline.setPos(conf['hline'])
if 'vline' in conf and conf['vline'] is not None:
self.plot.getPlotItem().removeItem(self.vline)
self.vline = pyqtgraph.InfiniteLine(angle=90 + histoangle, movable=False, pen=self.vline_color)
self.plot.getPlotItem().addItem(self.vline)
self.vline.setPos(conf['vline'])
xmins.append(x.min())
xmaxs.append(x.max())
ymins.append(y.min())
ymaxs.append(y.max())
self.legend.addItem(plt, pd.title)
color_index += 1
if (source.data_type[title] == 'vector') and (self._settings_diag.showTrendVector.isChecked()):
for trend in ['mean', 'median', 'std', 'min', 'max']:
if eval('self._settings_diag.trendVector_%s.isChecked()' %trend):
_trend = getattr(numpy, trend)
if len(pd.y.shape) == 3:
ytrend = _trend(numpy.array(pd.y[:,1,:], copy=False), axis=0)
else:
ytrend = _trend(numpy.array(pd.y, copy=False), axis=0)
plt_trend = self.plot.plot(x=x, y=ytrend, clear=False, pen=self.line_colors[color_index % len(self.line_colors)], symbol=symbol,
symbolPen=symbol_pen, symbolBrush=symbol_brush, symbolSize=symbol_size)
self.legend.addItem(plt_trend, trend)
color_index += 1
self.setWindowTitle(", ".join(titlebar))
dt = self.get_time()
# Round to miliseconds
self.timeLabel.setText('%02d:%02d:%02d.%03d' % (dt.hour, dt.minute, dt.second, dt.microsecond/1000))
self.dateLabel.setText(str(dt.date()))
# Set ranges
if len(xmins) > 0:
self._set_range(min(xmins), max(xmaxs), min(ymins), max(ymaxs))
# Various options
if self._settings_diag.aspect_locked.isChecked():
self.plot.getViewBox().setAspectLocked()
if self._settings_diag.flip_x.isChecked():
self.plot.getViewBox().invertX()
if self._settings_diag.flip_y.isChecked():
self.plot.getViewBox().invertY()
def _change_index_by(self, amount):
"""Changes the history index when displaying a vector"""
if self.last_vector_x is None:
return
self.current_index += amount
if(self.current_index > -1):
self.current_index = -1
if(self.current_index < -len(self.last_vector_x)):
self.current_index = -len(self.last_vector_x)
def keyPressEvent(self, event):
"""Handle key presses"""
key = event.key()
if key == QtCore.Qt.Key_Right:
self._change_index_by(1)
self.replot()
elif key == QtCore.Qt.Key_Left:
self._change_index_by(-1)
self.replot()
def get_state(self, _settings = None):
"""Returns settings that can be used to restore the widget to the current state"""
settings = _settings or {}
settings['window_type'] = 'PlotWindow'
settings['viewbox'] = self.plot.getViewBox().getState()
settings['x_view'] = self.actionX_axis.isChecked()
settings['y_view'] = self.actionY_axis.isChecked()
settings['lines'] = self.actionLines.isChecked()
settings['points'] = self.actionPoints.isChecked()
settings['legend'] = self.actionLegend_Box.isChecked()
settings = self._settings_diag.get_state(settings)
return DataWindow.get_state(self, settings)
def restore_from_state(self, settings, data_sources):
self._settings_diag.restore_from_state(settings)
self.plot.getViewBox().setState(settings['viewbox'])
self.actionX_axis.setChecked(settings['x_view'])
self.actionX_axis.triggered.emit(settings['x_view'])
self.actionY_axis.setChecked(settings['y_view'])
self.actionY_axis.triggered.emit(settings['y_view'])
self.actionLines.setChecked(settings['lines'])
self.actionPoints.setChecked(settings['points'])
self.actionLegend_Box.setChecked(settings['legend'])
self.actionLegend_Box.triggered.emit(settings['legend'])
return DataWindow.restore_from_state(self, settings, data_sources)
def _update_bg(self):
if self._settings_diag.bg is not None:
VB = self.plot.getViewBox()
B = pyqtgraph.ImageItem(image=self._settings_diag.bg, autoLevels=True)
xmin = float(self._settings_diag.bg_xmin.text())
ymin = float(self._settings_diag.bg_xmin.text())
width = float(self._settings_diag.bg_xmax.text()) - xmin
height = float(self._settings_diag.bg_ymax.text()) - ymin
rect = QtCore.QRectF(xmin, ymin, width, height)
B.setRect(rect)
VB.addItem(B, ignoreBounds=True)
def updateFonts(self):
f = self.title.font()
size = int(self.settings.value("plotFontSize"))
f.setPointSize(size)
self.title.setFont(f)
f = QtGui.QFont()
f.setPointSize(size)
ax = self.plot.getAxis('left')
ax.setTickFont(f)
ax = self.plot.getAxis('bottom')
ax.setTickFont(f)
def _onMouseMoved(self, pos):
view = self.plot
xy = view.mapToView(pos)
x = xy.x()
y = xy.y()
self.xLabel.setText("%f" % (x))
self.yLabel.setText("%f" % (y))
def replot(self):
"""Replot data"""
self.plot.clear()
# Init background if defined in a data source
if self._settings_diag.bg is None:
alert_flag = False
for source, title in self.source_and_titles():
conf = source.conf[title]
if "bg_filename" in conf:
conf_bg = {}
for k,v in conf.items():
if k.startswith("bg_"):
conf_bg[k] = v
self._settings_diag._configure_bg(**conf_bg)
# Use only first if there are many
break
alert_flag = False
for source, title in self.source_and_titles():
conf = source.conf[title]
if "alert" in conf and self.alert and conf['alert']:
alert_flag = True
if alert_flag:
os.system('afplay -v %f src/interface/ui/sounds/%s.wav &' %(self.volume,self.sound))
if not self.alertBlinkTimer.isActive():
self.alertBlinkTimer.start()
else:
if self.alertBlinkTimer.isActive():
self.alertBlinkTimer.stop()
self.setStyleSheet("")
# Load background if configured
self._update_bg()
color_index = 0
titlebar = []
self.plot.plotItem.legend.items = []
xmins = []
xmaxs = []
ymins = []
ymaxs = []
for source, title in self.source_and_titles():
if(title not in source.plotdata or source.plotdata[title].y is None):
continue
pd = source.plotdata[title]
titlebar.append(pd.title)
conf = source.conf[title]
color = self.line_colors[color_index % len(self.line_colors)]
pen = None
symbol = None
symbol_pen = None
symbol_brush = None
symbol_size = None
histoangle = 0
if(self.actionLines.isChecked()):
pen = color
if(self.actionPoints.isChecked()):
symbol = 'o'
symbol_pen = color
symbol_brush = color
symbol_size = 3
if(source.data_type[title] == 'scalar') or (source.data_type[title] == 'running_hist'):
y = numpy.array(pd.y, copy=False)
self.last_vector_y = {}
self.last_vector_x = None
elif(source.data_type[title] == 'tuple'):
y = pd.y[:,1]
symbol_brush = (255,255,255,120)
symbol_pen = None
symbol_size = 8
elif(source.data_type[title] == 'triple'):
if self.colormap is None:
vmin, vmax = (0,1)
if 'vmin' in conf:
vmin = conf['vmin']
if 'vmax' in conf:
vmax = conf['vmax']
stops = numpy.r_[vmin, vmax]
colors = numpy.array([[0, 0, 1, 0.7], [1, 0, 0, 1.0]])
self.colormap = pyqtgraph.ColorMap(stops, colors)
if 'zlabel' in conf:
zlabel = conf['zlabel']
else:
zlabel = 'z'
if self.colorbar is not None:
self.plot.scene().removeItem(self.colorbar)
self.colorbar = ColorBar(self.colormap, 10, 200, label=zlabel)
self.plot.scene().addItem(self.colorbar)
self.actionPoints.setChecked(1)
self.actionLines.setChecked(0)
self.colorbar.translate(self.geometry().width() - self.colorbar.zone[2], 20.0)
y = pd.y[:,1]
z = pd.y[:,2]
symbol_brush = self.colormap.map(z, 'qcolor')
symbol_pen = None
symbol_size = 8
elif source.data_type[title] == 'vector':
if(self.current_index == -1):
y = numpy.array(pd.y[self.current_index % pd.y.shape[0]], copy=False)
self.last_vector_y[title] = numpy.array(pd.y)
self.last_vector_x = numpy.array(pd.x)
else:
y = self.last_vector_y[title][self.current_index % self.last_vector_y[title].shape[0]]
elif source.data_type[title] == 'histogram':
if title not in self._histograms:
self._histograms[title] = Histogram(conf["hmin"], conf["hmax"], conf["bins"])
x = self._histograms[title].values_x
y = self._histograms[title].values_y
x = None
if(source.data_type[title] == 'scalar') or (source.data_type[title] == 'running_hist'):
x = numpy.array(pd.x, copy=False)
sorted_x = numpy.argsort(x)
x = x[sorted_x]
y = y[sorted_x]
if self._settings_diag.showTrendScalar.isChecked():
wl = int(self._settings_diag.windowLength.text())
y = utils.array.runningMean(y, min(y.size-1,wl))
x = x[-y.size:]
elif(source.data_type[title] == 'tuple') or (source.data_type[title] == 'triple'):
x = pd.y[:,0]
elif(source.data_type[title] == 'vector'):
if len(y.shape) == 2:
x = y[0,:]
y = y[1,:]
else:
if 'xmin' in conf and 'xmax' in conf:
xmin = conf['xmin']
xmax = conf['xmax']
else:
xmin = 0
xmax = source.plotdata[title].y.shape[-1] + xmin
x = numpy.linspace(xmin,xmax, y.shape[-1])
if(self._settings_diag.histogram.isChecked()):
bins = int(self._settings_diag.histBins.text())
histMode = self._settings_diag.histMode.currentText()
if (self._settings_diag.histAutorange.isChecked()):
hmin, hmax = y.min(), y.max()
self._settings_diag.histMin.setText("%.2f"%hmin)
self._settings_diag.histMax.setText("%.2f"%hmax)
else:
hmin = float(self._settings_diag.histMin.text())
hmax = float(self._settings_diag.histMax.text())
if histMode == 'count':
y,x = numpy.histogram(y, range=(hmin, hmax), bins=bins)
elif histMode == 'mean':
num,x = numpy.histogram(y, range=(hmin, hmax), bins=bins, weights=x)
den,x = numpy.histogram(y, range=(hmin, hmax), bins=bins)
y = num/(den+1e-20)
x = (x[:-1]+x[1:])/2.0
histoangle = 90
self._configure_axis(source, title, hist=True)
elif(source.data_type[title] == "histogram"):
ringbuffer = pd.y
self._histograms[title].add_values_from_ringbuffer(ringbuffer)
x = self._histograms[title].values_x
y = self._histograms[title].values_y
else:
self._configure_axis(source, title)
self.plot.setLogMode(x=self._settings_diag.logx.isChecked(),
y=self._settings_diag.logy.isChecked())
plt = self.plot.plot(x=x, y=y, clear=False, pen=pen, symbol=symbol,
symbolPen=symbol_pen, symbolBrush=symbol_brush, symbolSize=symbol_size)
if 'hline' in conf and conf['hline'] is not None:
self.plot.getPlotItem().removeItem(self.hline)
self.hline = pyqtgraph.InfiniteLine(angle=0 + histoangle, movable=False, pen=self.hline_color)
self.plot.getPlotItem().addItem(self.hline)
self.hline.setPos(conf['hline'])
if 'vline' in conf and conf['vline'] is not None:
self.plot.getPlotItem().removeItem(self.vline)
self.vline = pyqtgraph.InfiniteLine(angle=90 + histoangle, movable=False, pen=self.vline_color)
self.plot.getPlotItem().addItem(self.vline)
self.vline.setPos(conf['vline'])
xmins.append(x.min())
xmaxs.append(x.max())
ymins.append(y.min())
ymaxs.append(y.max())
self.legend.addItem(plt, pd.title)
color_index += 1
if (source.data_type[title] == 'vector') and (self._settings_diag.showTrendVector.isChecked()):
for trend in ['mean', 'median', 'std', 'min', 'max']:
if eval('self._settings_diag.trendVector_%s.isChecked()' %trend):
_trend = getattr(numpy, trend)
if len(pd.y.shape) == 3:
ytrend = _trend(numpy.array(pd.y[:,1,:], copy=False), axis=0)
else:
ytrend = _trend(numpy.array(pd.y, copy=False), axis=0)
plt_trend = self.plot.plot(x=x, y=ytrend, clear=False, pen=self.line_colors[color_index % len(self.line_colors)], symbol=symbol,
symbolPen=symbol_pen, symbolBrush=symbol_brush, symbolSize=symbol_size)
self.legend.addItem(plt_trend, trend)
color_index += 1
self.setWindowTitle(", ".join(titlebar))
dt = self.get_time()
# Round to miliseconds
self.timeLabel.setText('%02d:%02d:%02d.%03d' % (dt.hour, dt.minute, dt.second, dt.microsecond/1000))
self.dateLabel.setText(str(dt.date()))
# Set ranges
if len(xmins) > 0:
self._set_range(min(xmins), max(xmaxs), min(ymins), max(ymaxs))
# Various options
if self._settings_diag.aspect_locked.isChecked():
self.plot.getViewBox().setAspectLocked()
if self._settings_diag.flip_x.isChecked():
self.plot.getViewBox().invertX()
if self._settings_diag.flip_y.isChecked():
self.plot.getViewBox().invertY()