def __init__(self):
super().__init__()
self.resize(420, 400)
self.show()
plot = self.addPlot() # title="non-interactive")
# prepare demonstration data:
data = np.fromfunction(
lambda i, j: (1 + 0.3 * np.sin(i)) * (i)**2 + (j)**2, (100, 100))
noisy_data = data * (1 + 0.2 * np.random.random(data.shape))
# Example: False color image with interactive level adjustment
img = pg.ImageItem(image=noisy_data
) # create monochrome image from demonstration data
plot.addItem(img) # add to PlotItem 'plot'
cm = pg.colormap.get('CET-L9') # prepare a linear color map
bar = pg.ColorBarItem(values=(0, 20_000),
cmap=cm) # prepare interactive color bar
# Have ColorBarItem control colors of img and appear in 'plot':
bar.setImageItem(img, insert_in=plot)
self.timer = pg.QtCore.QTimer(singleShot=True)
self.timer.timeout.connect(self.export)
self.timer.start(100)
def __init__(self, parent=None, lockAspect=False, raw=False):
super().__init__(parent)
self.ui = Ui_Form_static()
self.ui.setupUi(self)
# Some options for Raw Images
self.raw = raw
# Image pane setup
self.image_layout = Qt.QtWidgets.QHBoxLayout(self.ui.imageFrame)
self.image_layout.setContentsMargins(0, 0, 0, 0)
self.image_layout.setSpacing(0)
self.image_win = pg.GraphicsLayoutWidget()
self.image_layout.addWidget(self.image_win)
self.imageViewBox = RectViewBox(lockAspect=lockAspect)
self.image_plot = self.image_win.addPlot(viewBox=self.imageViewBox)
self.imageItem = pgXDImageItem(raw=self.raw)
self.image_plot.addItem(self.imageItem)
# Make Label Item for showing position
self.make_pos_label()
self.histogram = pg.ColorBarItem(width=15)
# Have ColorBarItem control colors of img and appear in 'plot':
self.histogram.setImageItem(self.imageItem, insert_in=self.image_plot)
self.raw_image = np.zeros(0)
self.displayed_image = np.zeros(0)
self.show()
def __init__(self, parent: Optional[QtWidgets.QWidget] = None) -> None:
super().__init__(parent)
self.plot: pg.PlotItem = self.graphicsLayout.addPlot()
cmap = pg.colormap.get('viridis', source='matplotlib')
self.colorbar: pg.ColorBarItem = pg.ColorBarItem(interactive=True, values=(0, 1),
cmap=cmap, width=15)
self.graphicsLayout.addItem(self.colorbar)
self.img: Optional[pg.ImageItem] = None
self.scatter: Optional[pg.ScatterPlotItem] = None
self.scatterZVals: Optional[np.ndarray] = None
def __init__(self, *args, **kwargs):
super(MainWindow, self).__init__(*args, **kwargs)
gr_wid = pg.GraphicsLayoutWidget(show=True)
self.setCentralWidget(gr_wid)
self.setWindowTitle('pyqtgraph example: Correlation matrix display')
self.resize(600, 500)
self.show()
corrMatrix = np.array([[1., 0.5184571, -0.70188642],
[0.5184571, 1., -0.86094096],
[-0.70188642, -0.86094096, 1.]])
columns = ["A", "B", "C"]
pg.setConfigOption('imageAxisOrder',
'row-major') # Switch default order to Row-major
correlogram = pg.ImageItem()
# create transform to center the corner element on the origin, for any assigned image:
tr = QtGui.QTransform().translate(-0.5, -0.5)
correlogram.setTransform(tr)
correlogram.setImage(corrMatrix)
plotItem = gr_wid.addPlot(
) # add PlotItem to the main GraphicsLayoutWidget
plotItem.invertY(True) # orient y axis to run top-to-bottom
plotItem.setDefaultPadding(0.0) # plot without padding data range
plotItem.addItem(correlogram) # display correlogram
# show full frame, label tick marks at top and left sides, with some extra space for labels:
plotItem.showAxes(True, showValues=(True, True, False, False), size=20)
# define major tick marks and labels:
ticks = [(idx, label) for idx, label in enumerate(columns)]
for side in ('left', 'top', 'right', 'bottom'):
plotItem.getAxis(side).setTicks(
(ticks, [])) # add list of major ticks; no minor ticks
plotItem.getAxis('bottom').setHeight(
10) # include some additional space at bottom of figure
colorMap = pg.colormap.get(
"CET-D1") # choose perceptually uniform, diverging color map
# generate an adjustabled color bar, initially spanning -1 to 1:
bar = pg.ColorBarItem(values=(-1, 1), colorMap=colorMap)
# link color bar and color map to correlogram, and show it in plotItem:
bar.setImageItem(correlogram, insert_in=plotItem)
def loadAnImage(self, image, colormap, cmap_limits, opacity = 1):
""" load single image and colorbar to the widget. This function will be looped for
multiple images later
"""
# get pg image item
img = pg.ImageItem()
# add image to the graphicsview widget
self.canvas.addItem(img)
# set the color map
cmap = pg.ColorMap(pos=np.linspace(0, 1, len(colormap)), color=colormap)
#image = np.squeeze(tf.imread(image_path))
# set image to the image item with cmap
img.setImage(np.array(image), lut=cmap.getLookupTable(), opacity = opacity)
# set colorbar for thresholding
bar = pg.ColorBarItem(
values=cmap_limits,
cmap=cmap,
limits=(0, None),
orientation='vertical'
)
bar.setImageItem(img)
# set composition mode to plus for overlaying
img.setCompositionMode(QtGui.QPainter.CompositionMode_Plus)
def _replot(self):
logger.info('')
self.kymographPlot.clear()
self.kymographPlot.show()
if self.ba is None:
return
myTif = self.ba.tifData
#self.myImageItem = pg.ImageItem(myTif, axisOrder='row-major')
# TODO: set height to micro-meters
axisOrder = 'row-major'
rect = [0, 0, self.ba.recordingDur,
self.ba.tifData.shape[0]] # x, y, w, h
if self.myImageItem is None:
# first time build
self.myImageItem = kymographImage(myTif,
axisOrder=axisOrder,
rect=rect)
# redirect hover to self (to display intensity
self.myImageItem.hoverEvent = self.hoverEvent
else:
# second time update
myTif = self.ba.tifData
self.myImageItem.setImage(myTif, axisOrder=axisOrder, rect=rect)
self.kymographPlot.addItem(self.myImageItem)
# color bar with contrast !!!
if myTif.dtype == np.dtype('uint8'):
bitDepth = 8
elif myTif.dtype == np.dtype('uint16'):
bitDepth = 16
else:
bitDepth = 16
logger.error(f'Did not recognize tif dtype: {myTif.dtype}')
minTif = np.nanmin(myTif)
maxTif = np.nanmax(myTif)
#print(type(dtype), dtype) # <class 'numpy.dtype[uint16]'> uint16
cm = pg.colormap.get('Greens_r',
source='matplotlib') # prepare a linear color map
#values = (0, 2**bitDepth)
values = (0, maxTif)
limits = values
logger.info(
f'color bar bit depth is {bitDepth} with values is {values}')
bar = pg.ColorBarItem(
values=values, limits=limits, cmap=cm,
orientation='horizontal') # prepare interactive color bar
# Have ColorBarItem control colors of img and appear in 'plot':
bar.setImageItem(self.myImageItem, insert_in=self.kymographPlot)
kymographRect = self.ba.getKymographRect()
if kymographRect is not None:
xRoiPos = kymographRect[0]
yRoiPos = kymographRect[3]
top = kymographRect[1]
right = kymographRect[2]
bottom = kymographRect[3]
widthRoi = right - xRoiPos + 1
#heightRoi = bottom - yRoiPos + 1
heightRoi = top - yRoiPos + 1
'''
else:
# TODO: Put this logic into function in bAbfText
pos, size = self.ba.defaultTifRoi()
xRoiPos = 0 # startSeconds
yRoiPos = 0 # pixels
widthRoi = myTif.shape[1]
heightRoi = myTif.shape[0]
tifHeightPercent = myTif.shape[0] * 0.2
#print('tifHeightPercent:', tifHeightPercent)
yRoiPos += tifHeightPercent
heightRoi -= 2 * tifHeightPercent
'''
# TODO: get this out of replot, recreating the ROI is causing runtime error
pos = (xRoiPos, yRoiPos)
size = (widthRoi, heightRoi)
if self.myLineRoi is None:
self.myLineRoi = pg.ROI(pos=pos,
size=size,
parent=self.myImageItem)
self.myLineRoi.addScaleHandle((0, 0), (1, 1),
name='topleft') # at origin
self.myLineRoi.addScaleHandle((0.5, 0), (0.5, 1)) # top center
self.myLineRoi.addScaleHandle((0.5, 1), (0.5, 0)) # bottom center
self.myLineRoi.addScaleHandle((0, 0.5), (1, 0.5)) # left center
self.myLineRoi.addScaleHandle((1, 0.5), (0, 0.5)) # right center
self.myLineRoi.addScaleHandle((1, 1), (0, 0),
name='bottomright') # bottom right
self.myLineRoi.sigRegionChangeFinished.connect(
self.kymographChanged)
else:
self.myLineRoi.setPos(pos, finish=False)
self.myLineRoi.setSize(size, finish=False)
# background kymograph ROI
backgroundRect = self.ba.getKymographBackgroundRect(
) # keep this in the backend
if backgroundRect is not None:
xRoiPos = backgroundRect[0]
yRoiPos = backgroundRect[1]
right = backgroundRect[2]
bottom = backgroundRect[3]
widthRoi = right - xRoiPos + 1
heightRoi = bottom - yRoiPos + 1
# TODO: get this out of replot, recreating the ROI is causing runtime error
self.myLineRoiBackground = pg.ROI(pos=(xRoiPos, yRoiPos),
size=(widthRoi, heightRoi),
parent=self.myImageItem)
# update min/max labels
# TODO: also display min max within roi ???
self.tifMinLabel.setText(f'Min:{minTif}')
self.tifMaxLabel.setText(f'Max:{maxTif}')
self._updateRoiMinMax(kymographRect)
def __init__(self, *args, **kwargs):
super(MainWindow, self).__init__(*args, **kwargs)
gr_wid = pg.GraphicsLayoutWidget(show=True)
self.setCentralWidget(gr_wid)
self.setWindowTitle('pyqtgraph example: Interactive color bar')
self.resize(800, 700)
self.show()
## Create image items
data = np.fromfunction(
lambda i, j: (1 + 0.3 * np.sin(i)) * (i)**2 + (j)**2, (100, 100))
noisy_data = data * (1 + 0.2 * np.random.random(data.shape))
noisy_transposed = noisy_data.transpose()
#--- add non-interactive image with integrated color ------------------
p1 = gr_wid.addPlot(title="non-interactive")
# Basic steps to create a false color image with color bar:
i1 = pg.ImageItem(image=data)
p1.addItem(i1)
p1.addColorBar(i1, colorMap='CET-L9',
values=(0, 30_000)) # , interactive=False)
#
p1.setMouseEnabled(x=False, y=False)
p1.disableAutoRange()
p1.hideButtons()
p1.setRange(xRange=(0, 100), yRange=(0, 100), padding=0)
p1.showAxes(True, showValues=(True, False, False, True))
#--- add interactive image with integrated horizontal color bar -------
i2 = pg.ImageItem(image=noisy_data)
p2 = gr_wid.addPlot(1, 0, 1, 1, title="interactive")
p2.addItem(i2, title='')
# inserted color bar also works with labels on the right.
p2.showAxis('right')
p2.getAxis('left').setStyle(showValues=False)
p2.getAxis('bottom').setLabel('bottom axis label')
p2.getAxis('right').setLabel('right axis label')
bar = pg.ColorBarItem(values=(0, 30_000),
colorMap='CET-L4',
label='horizontal color bar',
limits=(0, None),
rounding=1000,
orientation='h',
pen='#8888FF',
hoverPen='#EEEEFF',
hoverBrush='#EEEEFF80')
bar.setImageItem(i2, insert_in=p2)
#--- multiple images adjusted by a separate color bar ------------------------
i3 = pg.ImageItem(image=noisy_data)
p3 = gr_wid.addPlot(0, 1, 1, 1, title="shared 1")
p3.addItem(i3)
i4 = pg.ImageItem(image=noisy_transposed)
p4 = gr_wid.addPlot(1, 1, 1, 1, title="shared 2")
p4.addItem(i4)
cmap = pg.colormap.get('CET-L8')
bar = pg.ColorBarItem(
# values = (-15_000, 15_000),
limits=(-30_000, 30_000), # start with full range...
rounding=1000,
width=10,
colorMap=cmap)
bar.setImageItem([i3, i4])
bar.setLevels(low=-5_000,
high=15_000) # ... then adjust to retro sunset.
# manually adjust reserved space at top and bottom to align with plot
bar.getAxis('bottom').setHeight(21)
bar.getAxis('top').setHeight(31)
gr_wid.addItem(bar, 0, 2, 2, 1) # large bar spanning both rows
def __init__(self, *args, **kwargs):
super(self.__class__, self).__init__(*args, **kwargs)
args, _ = parser.parse_known_args()
if args.samplerate == None:
self.samplerate = \
int(sd.query_devices(args.input_device)['default_samplerate'])
else:
self.samplerate = int(args.samplerate)
print(f"INFO -- Sampling rate at {self.samplerate} Hz")
self.threadpool = QtCore.QThreadPool()
self.q = queue.Queue()
self.setFixedSize(args.width, args.height)
self.mainbox = QtWidgets.QWidget()
self.setCentralWidget(self.mainbox)
self.layout = QtWidgets.QGridLayout()
self.mainbox.setLayout(self.layout)
# Widgets
self.spec_plot = SpectrogramWidget()
self.wave_plot = WaveFormWidget()
for i, widget in enumerate([self.spec_plot, self.wave_plot]):
self.layout.addWidget(widget, i, 0)
# Initialize x and y
self.length = self.samplerate * args.duration
self.y = np.random.rand(self.length, len(args.channels))
self.x = np.linspace(0, args.duration, num=self.length)
self.zcr = librosa.feature.zero_crossing_rate(self.y.mean(axis=1))[0]
# Wave Plot
self.waveline_1 = self.wave_plot.plot(x=self.x,
y=self.y[:, 0],
pen=pg.mkPen('g', width=0.5),
name='channel_1')
self.waveline_2 = self.wave_plot.plot(x=self.x,
y=self.y[:, 1],
pen=pg.mkPen('y', width=0.5),
name='channel_2')
self.waveline_3 = self.wave_plot.plot(x=np.linspace(
0, args.duration, self.zcr.shape[0]),
y=self.zcr,
pen=pg.mkPen('r', width=2),
name='zcr')
# Spectrogram
self.fmax = int(
librosa.core.fft_frequencies(sr=self.samplerate,
n_fft=args.n_fft)[-1])
D = librosa.stft(y=self.y.mean(axis=1), n_fft=args.n_fft, center=False)
self.specdata = librosa.amplitude_to_db(np.abs(D), ref=np.max)
# M = librosa.feature.melspectrogram(
# y=self.y.mean(axis=1),
# sr=self.samplerate,
# n_fft=args.n_fft,
# n_mels=args.n_mels)
# self.specdata = librosa.power_to_db(S=M, ref=np.max)
self.F0 = librosa.yin(y=self.y.mean(axis=1),
sr=self.samplerate,
frame_length=2048,
fmin=librosa.note_to_hz('C2'),
fmax=librosa.note_to_hz('C5'),
center=False)
self.spec_image = pg.ImageItem(item=self.specdata.T)
self.spec_plot.addItem(item=self.spec_image)
self.f0_line = self.spec_plot.plot(x=np.linspace(
0, args.duration, self.F0.shape[0]),
y=self.F0,
pen=pg.mkPen('r', width=2),
name='f0')
self.bar = pg.ColorBarItem(values=(librosa.note_to_hz('C2'),
librosa.note_to_hz('C5')),
cmap=pg.colormap.get('CET-L9'))
self.bar.setImageItem(self.spec_image)
# Start audio stream and animations
self.start_stream()
if args.input_device == 'Virtual Input (VB-Audio Virtual Cable), Windows DirectSound':
self.play_media(media_url=args.media_url,
type='stream',
volume=100)
self.animate()
self.show()
def __init__(self,
array,
y_scale,
y_spacing,
chan_map,
nav_trace,
x_scale=1,
load_channels='all',
max_zoom=120.0,
units='V'):
"""
Scroller GUI loading a minimal amount of timeseries to display.
X-units are currently assumed to be seconds.
Parameters
----------
array : array-like
Array-like access to a mapped array (i.e. can index with
array[i, range] slices).
y_scale : float
Scale the raw samples to units.
y_spacing : float
Spacing for the channel traces (in units)
chan_map : ChannelMap
Matrix map of the channels.
nav_trace : array-like (1D)
Navigation trace that is the same length as the channel
timeseries. If not given, then mean of channels is used.
**THIS MAY BE A COSTLY COMPUTATION**
x_scale : float (optional)
X-axis scale (e.g. sampling interval)
load_channels : sequence | 'all'
Order of (subset of) channels to load. Otherwise load all in array.
units : str
Y-axis units
"""
nchan = array.shape[0]
if isinstance(load_channels, str) and load_channels.lower() == 'all':
load_channels = range(nchan)
self.chan_map = chan_map
elif len(load_channels) == len(chan_map):
self.chan_map = chan_map
elif len(load_channels) < len(chan_map):
# "load_channels" indexes an array of recording channels
# that may include grounded channels or other junk.
raise NotImplementedError('cannot yet subset data channels')
# new_cm = ChannelMap( [chan_map[i] for i in load_channels],
# chan_map.geometry,
# col_major=chan_map.col_major )
# self.chan_map = new_cm
else:
raise ValueError('cannot map the listed channels')
self.array = array
self.y_scale = y_scale
if isinstance(load_channels, str) and load_channels == 'all':
load_channels = list(range(len(array)))
self.load_channels = load_channels
# The main window + layout
self.win = pg.GraphicsLayoutWidget(border=(10, 10, 10))
layout = self.win.ci
# Adding columns to layout: just titles on the top row
layout.addLabel('Array heatmap')
layout.addLabel('Zoomed plot')
layout.addLabel('|')
# Next row has 1) the heatmap image with the colorbar widget
layout.nextRow()
sub_layout = layout.addLayout(colspan=1)
self.img = pg.ImageItem(
image=np.random.randn(*self.chan_map.geometry) *
y_spacing) # * 1e6 / 2)
cmap = pg.colormap.get('coolwarm', source='matplotlib')
p_img = sub_layout.addPlot()
self.p_img = p_img
p_img.getViewBox().setAspectLocked()
p_img.addItem(self.img)
p_img.hideAxis('bottom')
p_img.hideAxis('left')
mid_x, top_y = self.chan_map.geometry[1] / 2.0, self.chan_map.geometry[
0] + 2.0
# add a text label on top of the box ("anchor" has text box is centered on its x, y position)
self.frame_text = pg.TextItem('empty',
anchor=(0.5, 0.5),
color=(255, 255, 255))
self.frame_text.setPos(mid_x, top_y)
# self.vb_img.addItem(self.frame_text)
p_img.getViewBox().addItem(self.frame_text)
p_img.getViewBox().autoRange()
# colorbar
self.cb = pg.ColorBarItem(limits=None,
cmap=cmap,
hoverBrush='#EEEEFF80',
rounding=10e-6,
values=(-y_spacing, y_spacing))
self.cb.getAxis('left').setLabel('')
self.cb.getAxis('right').setLabel('Voltage', units='V')
self.cb.setImageItem(self.img)
sub_layout.addItem(self.cb)
# 2) the stacked traces plot (colspan 2)
axis = PlainSecAxis(orientation='bottom')
self.p1 = layout.addPlot(colspan=2,
row=1,
col=1,
axisItems={'bottom': axis})
self.p1.enableAutoRange(axis='y', enable=True)
self.p1.setAutoVisible(y=False)
self.p1.setLabel('left', 'Amplitude', units=units)
self.p1.setLabel('bottom', 'Time')
# Next layout row has the navigator plot (colspan 3)
layout.nextRow()
# The navigator plot
axis = HMSAxis(orientation='bottom')
self.p2 = layout.addPlot(row=2,
col=0,
colspan=3,
axisItems={'bottom': axis})
self.p2.setLabel('left', 'Amplitude', units=units)
self.p2.setLabel('bottom', 'Time')
self.region = pg.LinearRegionItem()
self.region.setZValue(10)
initial_pts = 5000
self.region.setRegion([0, initial_pts * x_scale])
# Add the LinearRegionItem to the ViewBox,
# but tell the ViewBox to exclude this
# item when doing auto-range calculations.
self.p2.addItem(self.region, ignoreBounds=True)
self.p1.setAutoVisible(y=True)
self.p1.setXRange(0, initial_pts * x_scale)
self.p1.vb.setLimits(maxXRange=max_zoom)
# Multiple curve set that calls up data on-demand
self.curve_manager = CurveManager(plot=self.p1)
curves = PlotCurveCollection(array, load_channels, x_scale, y_scale,
y_spacing)
curves.setPen(color='w', width=1)
self.curve_manager.add_new_curves(curves, 'all', set_source=True)
# Set the heatmap to track these curves
self.curve_manager.heatmap_name = 'all'
# Selected curve & label set that calls up data on-demand
labels = ['({}, {})'.format(i, j) for i, j in zip(*chan_map.to_mat())]
selected_curves = LabeledCurveCollection(curves,
labels,
clickable=True)
self.curve_manager.add_new_curves(selected_curves, 'selected')
for text in selected_curves.texts:
self.p1.addItem(text)
# Add mean trace to bottom plot
self.nav_trace = pg.PlotCurveItem(x=np.arange(len(nav_trace)) *
x_scale,
y=nav_trace)
self.p2.addItem(self.nav_trace)
self.p2.setXRange(0, min(5e4, len(nav_trace)) * x_scale)
self.p2.setYRange(*np.percentile(nav_trace, [1, 99]))
# Set bidirectional plot interaction
# need to hang onto references?
self._db_cnx1 = DebounceCallback.connect(self.region.sigRegionChanged,
self.update_zoom_callback)
self._db_cnx2 = DebounceCallback.connect(self.p1.sigXRangeChanged,
self.update_region_callback)
# Do navigation jumps (if shift key is down)
self.p2.scene().sigMouseClicked.connect(self.jump_nav)
# Do fine interaction in zoomed plot with vertical line
self.vline = pg.InfiniteLine(angle=90, movable=False)
self.p1.addItem(self.vline)
self.p1.scene().sigMouseMoved.connect(self.fine_nav)
# final adjustments to rows: args are (row, stretch)
self.win.centralWidget.layout.setRowStretchFactor(0, 0.5)
self.win.centralWidget.layout.setRowStretchFactor(1, 5)
self.win.centralWidget.layout.setRowStretchFactor(2, 2.5)
# a callable frame filter may be set on this object to affect frame display
self.frame_filter = None
# set up initial frame
self.set_mean_image()
def updateplot(self):
self.mainloop()
if not self.ui.drawingCheck.checkState() == QtCore.Qt.Checked: return
for li in range(self.nlines):
maxchan=li-HaasoscopeLibQt.num_chan_per_board*HaasoscopeLibQt.num_board
if maxchan>=0: # these are the slow ADC channels
self.lines[li].setData(d.xydataslow[maxchan][0],d.xydataslow[maxchan][1])
else:
self.lines[li].setData(d.xydata[li][0],d.xydata[li][1])
if d.dologicanalyzer:
for li in np.arange(d.num_logic_inputs):
self.lines[d.logicline1+li].setData(d.xydatalogic[li][0],d.xydatalogic[li][1])
if d.dofft:
self.fftui.fftline.setPen(self.linepens[d.fftchan])
self.fftui.fftline.setData(d.fftfreqplot_xdata,d.fftfreqplot_ydata)
self.fftui.ui.plot.setTitle("FFT plot of channel "+str(d.fftchan))
self.fftui.ui.plot.setLabel('bottom', d.fftax_xlabel)
self.fftui.ui.plot.setRange(xRange=(0.0, d.fftax_xlim))
now = time.time()
dt = now - self.fftui.fftlastTime
if dt>3.0 or self.fftyrange<d.fftfreqplot_ydatamax*1.1:
self.fftui.fftlastTime = now
self.fftui.ui.plot.setRange(yRange=(0.0, d.fftfreqplot_ydatamax*1.1))
self.fftyrange = d.fftfreqplot_ydatamax * 1.1
if not self.fftui.isVisible(): # closed the fft window
d.dofft = False
self.ui.fftCheck.setCheckState(QtCore.Qt.Unchecked)
if d.recorddata:
if self.firstpersist:
self.image1 = pg.ImageItem(image=d.recorded2d,opacity=0.5)
self.persistui.ui.plot.addItem(self.image1)
self.persistui.ui.plot.setTitle("Persist plot of channel "+str(d.recorddatachan))
self.cmap = pg.colormap.get('CET-D8')
self.firstpersist=False
else:
self.image1.setImage(image=d.recorded2d,opacity=0.5)
self.image1.setRect(QtCore.QRectF(d.min_x,d.min_y,d.max_x-d.min_x,d.max_y-d.min_y))
self.persistui.ui.plot.setLabel('bottom', d.xlabel)
self.bar = pg.ColorBarItem(interactive=False, values= (0, np.max(d.recorded2d)), cmap=self.cmap)
self.bar.setImageItem(self.image1)
if not self.persistui.isVisible(): # closed the fft window
d.recorddata = False
self.ui.persistCheck.setCheckState(QtCore.Qt.Unchecked)
if self.ui.decodeCheck.checkState() == QtCore.Qt.Checked:
# delete all previous labels
for label in self.decodelabels:
self.ui.plot.removeItem(label)
if d.downsample>=0:
resulttext,resultstart,resultend = d.decode()
#print(resulttext,resultstart, d.min_x, d.max_x, d.xscale, d.xscaling)
item=0
while item<len(resulttext):
label = pg.TextItem(resulttext[item])
label.setColor(self.linepens[d.selectedchannel].color())
x=d.min_x+resultstart[item]*1e9/d.xscaling
label.setPos( QtCore.QPointF(x, -1) )
#print(x)
self.ui.plot.addItem(label)
self.decodelabels.append(label)
item=item+1
else:
print("can't decode when downsample is <0... go slower!")
now = time.time()
dt = now - self.lastTime + 0.00001
self.lastTime = now
if self.fps is None:
self.fps = 1.0/dt
else:
s = np.clip(dt*3., 0, 1)
self.fps = self.fps * (1-s) + (1.0/dt) * s
self.ui.plot.setTitle('%0.2f fps' % self.fps)
app.processEvents()
