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pyqtgraph - move origin of ArrowItem to local center

I'm using pyqtgraph to plot tracks of a robot (the path that the bot drove). Now I want to add a marker to the plot to indicate the bots current position and heading. I thought ArrowItem would be the right choice, because it is scale invariant and can be rotated easily. However the local origin of the arrow is at its tip like this
but I want it to be in the center like this
How can I do that? I would also appreciate different solutions to this problem.
Update
After applying eyllansec's code I get some rendering problems. A minimal example (one has to zoom or move the view to disable the auto scaling):
import pyqtgraph as pg
import numpy as np
import time
class CenteredArrowItem(pg.ArrowItem):
def paint(self, p, *args):
p.translate(-self.boundingRect().center())
pg.ArrowItem.paint(self, p, *args)
if __name__ == '__main__':
app = pg.QtGui.QApplication([])
window = pg.GraphicsWindow(size=(1280, 720))
window.setAntialiasing(True)
tracker = window.addPlot(title='Tracker')
while True:
for i in range(300):
arrow = CenteredArrowItem(angle=i, headLen=40, tipAngle=45, baseAngle=30)
arrow.setPos(i / 300, i / 300)
tracker.addItem(arrow)
app.processEvents()
time.sleep(0.02)
tracker.removeItem(arrow)
As you may noticed I'm adding and removing the arrow each iteration. This is because arrow.setStyle(angle=i) is not working as it does not update the rotation of the arrow (probably a bug).

A possible solution is to overwrite the paint method of ArrowItem and move the QPainter:
import numpy as np
from pyqtgraph.Qt import QtGui, QtCore
import pyqtgraph as pg
class MyArrowItem(pg.ArrowItem):
def paint(self, p, *args):
p.translate(-self.boundingRect().center())
pg.ArrowItem.paint(self, p, *args)
app = QtGui.QApplication([])
w = QtGui.QMainWindow()
p = pg.PlotWidget()
p.showGrid(x = True, y = True, alpha = 0.3)
w.show()
w.resize(640, 480)
w.setCentralWidget(p)
w.setWindowTitle('pyqtgraph example: Arrow')
a = pg.ArrowItem(angle=-160, tipAngle=60, headLen=40, tailLen=40, tailWidth=20, pen={'color': 'w', 'width': 3}, brush='r')
b = MyArrowItem(angle=-160, tipAngle=60, headLen=40, tailLen=40, tailWidth=20, pen={'color': 'w', 'width': 3})
a.setPos(10,0)
b.setPos(10,0)
p.addItem(a)
p.addItem(b)
## Start Qt event loop unless running in interactive mode or using pyside.
if __name__ == '__main__':
import sys
if (sys.flags.interactive != 1) or not hasattr(QtCore, 'PYQT_VERSION'):
QtGui.QApplication.instance().exec_()
As shown in the following figure, the red arrow is the default ArrowItem, and the blue is the offset, both are located in the same position with respect to the plot.
Update:
The problem is caused by the method that rotates the item used as the center of coordinates using the center of transformations by default, that is to say the (0, 0), we must move it:
import pyqtgraph as pg
import numpy as np
import time
from pyqtgraph.Qt import QtGui, QtCore
from pyqtgraph import functions as fn
class CenteredArrowItem(pg.ArrowItem):
def setStyle(self, **opts):
# http://www.pyqtgraph.org/documentation/_modules/pyqtgraph/graphicsItems/ArrowItem.html#ArrowItem.setStyle
self.opts.update(opts)
opt = dict([(k,self.opts[k]) for k in ['headLen', 'tipAngle', 'baseAngle', 'tailLen', 'tailWidth']])
tr = QtGui.QTransform()
path = fn.makeArrowPath(**opt)
tr.rotate(self.opts['angle'])
p = -path.boundingRect().center()
tr.translate(p.x(), p.y())
self.path = tr.map(path)
self.setPath(self.path)
self.setPen(fn.mkPen(self.opts['pen']))
self.setBrush(fn.mkBrush(self.opts['brush']))
if self.opts['pxMode']:
self.setFlags(self.flags() | self.ItemIgnoresTransformations)
else:
self.setFlags(self.flags() & ~self.ItemIgnoresTransformations)
if __name__ == '__main__':
app = pg.QtGui.QApplication([])
window = pg.GraphicsWindow(size=(1280, 720))
window.setAntialiasing(True)
tracker = window.addPlot(title='Tracker')
while True:
for i in range(300):
arrow = CenteredArrowItem(angle=i, headLen=40, tipAngle=45, baseAngle=30)
arrow.setPos(i / 300, i / 300)
tracker.addItem(arrow)
app.processEvents()
time.sleep(0.02)
tracker.removeItem(arrow)

After digging through the source code of pyqtgraph I ended up with a special function that suits my needs. I apply the translation when creating the arrow path, instead when rendering it. Fortunately this also solves the roation bug (for whatever reason).
Example:
import pyqtgraph as pg
import numpy as np
import time
import pyqtgraph.functions
class CenteredArrowItem(pg.ArrowItem):
def setData(self, x, y, angle):
self.opts['angle'] = angle
opt = dict([(k, self.opts[k]) for k in ['headLen', 'tipAngle', 'baseAngle', 'tailLen', 'tailWidth']])
path = pg.functions.makeArrowPath(**opt)
b = path.boundingRect()
tr = pg.QtGui.QTransform()
tr.rotate(angle)
tr.translate(-b.x() - b.width() / 2, -b.y() - b.height() / 2)
self.path = tr.map(path)
self.setPath(self.path)
self.setPos(x, y)
if __name__ == '__main__':
app = pg.QtGui.QApplication([])
window = pg.GraphicsWindow(size=(1280, 720))
window.setAntialiasing(True)
tracker = window.addPlot(title='Tracker')
arrow = CenteredArrowItem(headLen=40, tipAngle=45, baseAngle=30)
tracker.addItem(arrow)
tracker.addItem(pg.InfiniteLine(pos=(0,0), angle=45))
center = pg.ScatterPlotItem([], [], brush='r')
tracker.addItem(center)
while True:
for i in range(300):
arrow.setData(i, i, i)
center.setData([i], [i])
app.processEvents()
time.sleep(0.02)

Widget is appearing next to image?

I am attempting to put pyqtgraph ROI widgets (information here) on top of a .PNG image. When I import the image into the program, it comes out rotated and flipped the wrong way. I assume this is a bug. To attempt to fix it, I have rotated the image BUT when I do so, my ROI widget goes off of the image. How do I fix this?
Without image rotation:
i = Image.open("del.png")
a = array(i) #converting to numpy array
img1a = pg.ImageItem(a)
v1a.addItem(img1a)
Once I add img1a.rotate(90) to the code above, the ROI widget goes off the screen. How do I position the image the correct way and have my ROI widget appear normally on top of the image?
The entire code is found below (edited from this example found here.)
import pyqtgraph as pg
from pyqtgraph.Qt import QtCore, QtGui
import numpy as np
from numpy import array
from PIL import Image
## create GUI
app = QtGui.QApplication([])
w = pg.GraphicsWindow(size=(1000,800), border=True)
w.setWindowTitle('pyqtgraph example: ROI Examples')
text = """text"""
w1 = w.addLayout(row=0, col=0)
label1 = w1.addLabel(text, row=0, col=0)
v1a = w1.addViewBox(row=1, col=0, lockAspect=True)
#img1a = pg.ImageItem(arr)
i = Image.open("del.png")
a = array(i)
img1a = pg.ImageItem(a)
v1a.addItem(img1a)
img1a.rotate(90)
v1a.disableAutoRange('xy')
v1a.autoRange()
rois = []
rois.append(pg.EllipseROI([150, 150], [1, 1], pen=(4,9)))
rois.append(pg.EllipseROI([0, 0], [300, 300], pen=(4,9)))
for roi in rois:
v1a.addItem(roi)
## Start Qt event loop unless running in interactive mode or using pyside.
if __name__ == '__main__':
import sys
if (sys.flags.interactive != 1) or not hasattr(QtCore, 'PYQT_VERSION'):
QtGui.QApplication.instance().exec_()

You do not have to rotate the item, but you must rotate the image for it you can use numpy.rot90:
i = Image.open("del.png")
a = array(i)
a = np.rot90(a, -1)
img1a = pg.ImageItem(a)
v1a.addItem(img1a)
v1a.disableAutoRange('xy')
v1a.autoRange()

MoviePy + VisPy only saving black screen to .gif

I have a script that animates a simple canvas using VisPy (in the "bad" way) successfully. However, when i export the animation to file, whether it's a .gif, or video formats (.MP4, etc) most of the time it produces a completely black image that doesn't change. Other, seemingly random times it does actually save the correct animation. I have literally tried everything I can think of.
import vispy
import vispy.scene
from make_shape import Make_shape
from vispy.scene import visuals
from vispy import app, gloo
from moviepy.editor import VideoClip
from vispy.gloo.util import _screenshot
# Canvas setup
canvas = vispy.scene.SceneCanvas(keys='interactive', show=True, resizable=True)
view = canvas.central_widget.add_view()
# Initial shape data
cube = Make_shape(3)
verts = cube.verts()
linepos = cube.frame(verts)
# Adds initial visuals to shape data
# lines can be done as a function with LinePlot
scatter = visuals.Markers()
lines = visuals.Line()
axis = visuals.XYZAxis(parent=view.scene)
scatter.set_data(verts, edge_color=None, face_color=(1, 1, 1, .5), size=10)
lines.set_data(pos=linepos, connect="segments")
view.add(scatter)
view.add(lines)
# Animation of visuals
def update(ev):
global verts, scatter
verts += 0.0005
linepos = cube.frame(verts)
scatter.set_data(pos=verts)
lines.set_data(pos=linepos)
#Ttime = 5
#intv = 0.000001
#intr = int(Ttime / intv)
timer = app.Timer()
timer.connect(update)
timer.start(interval=.01, iterations=500)
# Setup of camera
# view.camera = 'turntable'
# view.camera = 'perspective'
view.camera = 'arcball'
view.camera.center = (0.5, 0.5, 0.5)
view.camera.distance = 100
#view.camera.set_range(x=(-0.5, 1))
view.camera.fov = (1)
# Runs animation
if __name__ == '__main__':
import sys
if sys.flags.interactive != 1:
vispy.app.run()
# Writes animation to file
def make_frame(t):
update(t)
canvas.on_draw(None)
return _screenshot((0, 0, canvas.size[0], canvas.size[1]))[:, :, :3]
animation = VideoClip(make_frame, duration=5)
animation.write_gif("test_animation2.gif", fps=24) # export as GIF (slow)
# animation.write_videofile(fname+".mp4", fps=24) # export as video

My PyQt plot's Y axes are upside down (even the text)?

Today is the first day I have tried using PyQtGraph. I really like it so far except I can't seem to fully comprehend how things work..
I am trying to place two FFT plot widgets into the same window. After much trial and error I found what I thought was the proper way to do it. However now I have two plots which show the correct information but everything on the Y axis is inverted.
Also it seems zooming and panning are not correct either (the whole plot moves, not just the data within it).
This image shows the two real-time audio fft plots both within a single GraphicsWindow. On the left I use addPlot with addItem and on the right I use addViewBox with addItem.
To be thorough I have tried using item.invertY(True) and item.scale(1,-1).
In both cases it will invert the Y axis data but not the text or axes, nor does it address the panning/zooming issues..
This Python script is everything I was able to write.
It was based off of this file: pyqtgraph live running spectrogram from microphone
import numpy as np
import pyqtgraph as pg
import pyaudio
from PyQt4 import QtCore, QtGui
FS = 44100 #Hz
CHUNKSZ = 1024 #samples
class MicrophoneRecorder():
def __init__(self, signal):
self.signal = signal
self.p = pyaudio.PyAudio()
self.stream = self.p.open(format=pyaudio.paInt16,
channels=1,
rate=FS,
input=True,
frames_per_buffer=CHUNKSZ)
def read(self):
data = self.stream.read(CHUNKSZ)
y = np.fromstring(data, 'int16')
self.signal.emit(y)
def close(self):
self.stream.stop_stream()
self.stream.close()
self.p.terminate()
class SpectrogramWidget2(pg.PlotWidget):
read_collected = QtCore.pyqtSignal(np.ndarray)
def __init__(self):
super(SpectrogramWidget2, self).__init__()
self.img = pg.ImageItem()
self.addItem(self.img)
self.img_array = np.zeros((1000, CHUNKSZ/2+1))
# bipolar colormap
pos = np.array([0., 0.5, 1.])
color = np.array([[0,0,0,255], [0,255,0,255], [255,0,0,255]], dtype=np.ubyte)
cmap = pg.ColorMap(pos, color)
pg.colormap
lut = cmap.getLookupTable(0.0, 1.0, 256)
# set colormap
self.img.setLookupTable(lut)
self.img.setLevels([0,100])
# setup the correct scaling for y-axis
freq = np.arange((CHUNKSZ/2)+1)/(float(CHUNKSZ)/FS)
yscale = 1.0/(self.img_array.shape[1]/freq[-1])
self.img.scale((1./FS)*CHUNKSZ, yscale)
self.setLabel('left', 'Frequency', units='Hz')
# prepare window for later use
self.win = np.hanning(CHUNKSZ)
#self.show()
def update(self, chunk):
# normalized, windowed frequencies in data chunk
spec = np.fft.rfft(chunk*self.win) / CHUNKSZ
# get magnitude
psd = abs(spec)
# convert to dB scaleaxis
psd = 20 * np.log10(psd)
# roll down one and replace leading edge with new data
self.img_array = np.roll(self.img_array, -1, 0)
self.img_array[-1:] = psd
self.img.setImage(self.img_array, autoLevels=False)
class SpectrogramWidget(pg.PlotWidget):
read_collected = QtCore.pyqtSignal(np.ndarray)
def __init__(self):
super(SpectrogramWidget, self).__init__()
self.img = pg.ImageItem()
self.addItem(self.img)
self.img_array = np.zeros((1000, CHUNKSZ/2+1))
# bipolar colormap
pos = np.array([0., 0.5, 1.])
color = np.array([[0,0,0,255], [0,255,0,255], [255,0,0,255]], dtype=np.ubyte)
cmap = pg.ColorMap(pos, color)
pg.colormap
lut = cmap.getLookupTable(0.0, 1.0, 256)
# set colormap
self.img.setLookupTable(lut)
self.img.setLevels([0,100])
# setup the correct scaling for y-axis
freq = np.arange((CHUNKSZ/2)+1)/(float(CHUNKSZ)/FS)
yscale = 1.0/(self.img_array.shape[1]/freq[-1])
self.img.scale((1./FS)*CHUNKSZ, yscale)
self.setLabel('left', 'Frequency', units='Hz')
# prepare window for later use
self.win = np.hanning(CHUNKSZ)
#self.show()
def update(self, chunk):
# normalized, windowed frequencies in data chunk
spec = np.fft.rfft(chunk*self.win) / CHUNKSZ
# get magnitude
psd = abs(spec)
# convert to dB scaleaxis
psd = 20 * np.log10(psd)
# roll down one and replace leading edge with new data
self.img_array = np.roll(self.img_array, -1, 0)
self.img_array[-1:] = psd
self.img.setImage(self.img_array, autoLevels=False)
if __name__ == '__main__':
app = QtGui.QApplication([])
win = pg.GraphicsWindow(title="Basic plotting examples")
#win.resize(1000,600)
w = SpectrogramWidget()
w.read_collected.connect(w.update)
spectrum1 = win.addPlot(title="Spectrum 1")#win.addViewBox()
item = w.getPlotItem()
spectrum1.addItem(item)
w2 = SpectrogramWidget2()
w2.read_collected.connect(w2.update)
spectrum2 = win.addViewBox()
spectrum2.addItem(w2.getPlotItem())
mic = MicrophoneRecorder(w.read_collected)
mic2 = MicrophoneRecorder(w2.read_collected)
# time (seconds) between reads
interval = FS/CHUNKSZ
t = QtCore.QTimer()
t.timeout.connect(mic.read)
t.start((1000/interval) ) #QTimer takes ms
t2 = QtCore.QTimer()
t2.timeout.connect(mic2.read)
t2.start((1000/interval) ) #QTimer takes ms
app.exec_()
mic.close()
Thank you for any help!

I have no idea why doing this causes things to be mirrored, but the issue is related to using the plotItem from a plot in another plot (I think that's what you're doing?)
Anyway, PlotWidgets shouldn't be used like that. They are just normal Qt Widgets, so add them to a Qt layout like you would with any other Qt Widget.
if __name__ == '__main__':
app = QtGui.QApplication([])
win = QtGui.QMainWindow()
widget = QtGui.QWidget()
win.setCentralWidget(widget)
layout = QtGui.QHBoxLayout(widget)
win.show()
w = SpectrogramWidget()
w.read_collected.connect(w.update)
layout.addWidget(w)
w2 = SpectrogramWidget2()
w2.read_collected.connect(w2.update)
layout.addWidget(w2)
# .... etc
P.S. Is there a reason you have two identical classes with a different name? You could just instantiate multiple copies of the same class. E.g.
w = SpectrogramWidget()
w2 = SpectrogramWidget()

Python/Matplotlib/Pyside Fast Timetrace scrolling

I have large time-traces that must be inspected visually, so I need a fast scrolling tool.
How can I achieve the fastest Maplotlib/Pyside scrolling?
Right know, I added a PySide scroll-bar to a MPL figure and update the x-range of the plot with set_xlim() method. This is not fast enough especially because in the final application I have at least 8 time-traces in different subplots that must all scroll together. A figure of the plot is attached.
Is there room for improvement?
Here I attach the demo code that demonstrate the relatively low scrolling. It's long but it's almost all boiler-plate code. The interesting bit (that needs improvement) is in xpos_changed() method where the plot xlimits are changed.
EDIT: Below I incorporated some micro-optimizations suggested by tcaswell, but the update speed is not improved.
from PySide import QtGui, QtCore
import pylab as plt
import numpy as np
N_SAMPLES = 1e6
def test_plot():
time = np.arange(N_SAMPLES)*1e-3
sample = np.random.randn(N_SAMPLES)
plt.plot(time, sample, label="Gaussian noise")
plt.title("1000s Timetrace \n (use the slider to scroll and the spin-box to set the width)")
plt.xlabel('Time (s)')
plt.legend(fancybox=True)
q = ScrollingToolQT(plt.gcf(), scroll_step=10)
return q # WARNING: it's important to return this object otherwise
# python will delete the reference and the GUI will not respond!
class ScrollingToolQT(object):
def __init__(self, fig, scroll_step=10):
# Setup data range variables for scrolling
self.fig = fig
self.scroll_step = scroll_step
self.xmin, self.xmax = fig.axes[0].get_xlim()
self.width = 1 # axis units
self.pos = 0 # axis units
self.scale = 1e3 # conversion betweeen scrolling units and axis units
# Save some MPL shortcuts
self.ax = self.fig.axes[0]
self.draw = self.fig.canvas.draw
#self.draw_idle = self.fig.canvas.draw_idle
# Retrive the QMainWindow used by current figure and add a toolbar
# to host the new widgets
QMainWin = fig.canvas.parent()
toolbar = QtGui.QToolBar(QMainWin)
QMainWin.addToolBar(QtCore.Qt.BottomToolBarArea, toolbar)
# Create the slider and spinbox for x-axis scrolling in toolbar
self.set_slider(toolbar)
self.set_spinbox(toolbar)
# Set the initial xlimits coherently with values in slider and spinbox
self.ax.set_xlim(self.pos,self.pos+self.width)
self.draw()
def set_slider(self, parent):
self.slider = QtGui.QSlider(QtCore.Qt.Horizontal, parent=parent)
self.slider.setTickPosition(QtGui.QSlider.TicksAbove)
self.slider.setTickInterval((self.xmax-self.xmin)/10.*self.scale)
self.slider.setMinimum(self.xmin*self.scale)
self.slider.setMaximum((self.xmax-self.width)*self.scale)
self.slider.setSingleStep(self.width*self.scale/4.)
self.slider.setPageStep(self.scroll_step*self.width*self.scale)
self.slider.setValue(self.pos*self.scale) # set the initial position
self.slider.valueChanged.connect(self.xpos_changed)
parent.addWidget(self.slider)
def set_spinbox(self, parent):
self.spinb = QtGui.QDoubleSpinBox(parent=parent)
self.spinb.setDecimals(3)
self.spinb.setRange(0.001,3600.)
self.spinb.setSuffix(" s")
self.spinb.setValue(self.width) # set the initial width
self.spinb.valueChanged.connect(self.xwidth_changed)
parent.addWidget(self.spinb)
def xpos_changed(self, pos):
#pprint("Position (in scroll units) %f\n" %pos)
pos /= self.scale
self.ax.set_xlim(pos, pos+self.width)
self.draw()
def xwidth_changed(self, width):
#pprint("Width (axis units) %f\n" % step)
if width <= 0: return
self.width = width
self.slider.setSingleStep(self.width*self.scale/5.)
self.slider.setPageStep(self.scroll_step*self.width*self.scale)
old_xlim = self.ax.get_xlim()
self.xpos_changed(old_xlim[0]*self.scale)
if __name__ == "__main__":
q = test_plot()
plt.show()

As requested in the comments, here is a pyqtgraph demo which scrolls two large traces together (via mouse).
The documentation isn't complete for the pyqtgraph project but there are some good examples you can view with python -m pyqtgraph.examples which should point you in the right direction. The crosshair.py example might be particularly interesting for you.
If you go with pyqtgraph, connect your slider widget to the setXRange method in the last line of this demo.
from pyqtgraph.Qt import QtGui, QtCore
import pyqtgraph as pg
import numpy as np
app = QtGui.QApplication([])
win = pg.GraphicsWindow()
x = np.arange(1e5)
y1 = np.random.randn(x.size)
y2 = np.random.randn(x.size)
p1 = win.addPlot(x=x, y=y1, name='linkToMe')
p1.setMouseEnabled(x=True, y=False)
win.nextRow()
p2 = win.addPlot(x=x, y=y2)
p2.setXLink('linkToMe')
p1.setXRange(2000,3000)

This seems a bit faster/more responsive:
from PySide import QtGui, QtCore
import pylab as plt
import numpy as np
N_SAMPLES = 1e6
def test_plot():
time = np.arange(N_SAMPLES)*1e-3
sample = np.random.randn(N_SAMPLES)
plt.plot(time, sample, label="Gaussian noise")
plt.legend(fancybox=True)
plt.title("Use the slider to scroll and the spin-box to set the width")
q = ScrollingToolQT(plt.gcf())
return q # WARNING: it's important to return this object otherwise
# python will delete the reference and the GUI will not respond!
class ScrollingToolQT(object):
def __init__(self, fig):
# Setup data range variables for scrolling
self.fig = fig
self.xmin, self.xmax = fig.axes[0].get_xlim()
self.step = 1 # axis units
self.scale = 1e3 # conversion betweeen scrolling units and axis units
# Retrive the QMainWindow used by current figure and add a toolbar
# to host the new widgets
QMainWin = fig.canvas.parent()
toolbar = QtGui.QToolBar(QMainWin)
QMainWin.addToolBar(QtCore.Qt.BottomToolBarArea, toolbar)
# Create the slider and spinbox for x-axis scrolling in toolbar
self.set_slider(toolbar)
self.set_spinbox(toolbar)
# Set the initial xlimits coherently with values in slider and spinbox
self.set_xlim = self.fig.axes[0].set_xlim
self.draw_idle = self.fig.canvas.draw_idle
self.ax = self.fig.axes[0]
self.set_xlim(0, self.step)
self.fig.canvas.draw()
def set_slider(self, parent):
# Slider only support integer ranges so use ms as base unit
smin, smax = self.xmin*self.scale, self.xmax*self.scale
self.slider = QtGui.QSlider(QtCore.Qt.Horizontal, parent=parent)
self.slider.setTickPosition(QtGui.QSlider.TicksAbove)
self.slider.setTickInterval((smax-smin)/10.)
self.slider.setMinimum(smin)
self.slider.setMaximum(smax-self.step*self.scale)
self.slider.setSingleStep(self.step*self.scale/5.)
self.slider.setPageStep(self.step*self.scale)
self.slider.setValue(0) # set the initial position
self.slider.valueChanged.connect(self.xpos_changed)
parent.addWidget(self.slider)
def set_spinbox(self, parent):
self.spinb = QtGui.QDoubleSpinBox(parent=parent)
self.spinb.setDecimals(3)
self.spinb.setRange(0.001, 3600.)
self.spinb.setSuffix(" s")
self.spinb.setValue(self.step) # set the initial width
self.spinb.valueChanged.connect(self.xwidth_changed)
parent.addWidget(self.spinb)
def xpos_changed(self, pos):
#pprint("Position (in scroll units) %f\n" %pos)
# self.pos = pos/self.scale
pos /= self.scale
self.set_xlim(pos, pos + self.step)
self.draw_idle()
def xwidth_changed(self, xwidth):
#pprint("Width (axis units) %f\n" % step)
if xwidth <= 0: return
self.step = xwidth
self.slider.setSingleStep(self.step*self.scale/5.)
self.slider.setPageStep(self.step*self.scale)
old_xlim = self.ax.get_xlim()
self.xpos_changed(old_xlim[0] * self.scale)
# self.set_xlim(self.pos,self.pos+self.step)
# self.fig.canvas.draw()
if __name__ == "__main__":
q = test_plot()
plt.show()