Animate like Google Finance charts in Matplotlib? - animation

I just started toying around with Matplotlib's Animation capabilities in order to produce a Google Finance looking chart.
I combined two examples I found on the project website (Draggable rectangle exercise, api example code: date_demo.py) and tweaked them a bit to come up with the code listed at the bottom.
While it doesn't look too bad, I would like the top chart (master) update dynamically as the bottom chart (slave) selection is moved around, and not only when the bottom selection is released. How can I do this? I tried to move the self.rect.figure.canvas.draw() bit to the on_motion method, but it seems to interfere with the blit stuff as the bottom selection won't render properly.
So I would assume the solution would be to do the intelligent animation for the bottom chart, i.e., the blit-ing bit, while the top chart is just re-drawn altogether. The issue is that the only way I can redraw anything is through the re-drawing the whole canvas, and this would include the bottom chart. I did find the draw() method for matplotlib.axes, but I can't get it to work. As I said above, preferably I would like to just re-draw the top chart while the bottom one is blit-ed the clever way. Does anyone know how to do this?
Here is my code so far. Please excuse the code, it's a bit untidy.
import datetime
import numpy as np
import sys
import time
import wx
import matplotlib
from matplotlib.figure import Figure
import matplotlib.dates as mdates
import matplotlib.ticker as mtickers
from matplotlib.backends.backend_wxagg import FigureCanvasWxAgg as FigureCanvas
import matplotlib.patches as mpatches
class DraggableRectangle:
lock = None
def __init__(self, rect, master, xMin, xMax):
self.rect = rect
self.press = None
self.background = None
self.xMax = xMax
self.xMin = xMin
self.master = master
def connect(self):
self.cidpress = self.rect.figure.canvas.mpl_connect('button_press_event', self.on_press)
self.cidrelease = self.rect.figure.canvas.mpl_connect('button_release_event', self.on_release)
self.cidmotion = self.rect.figure.canvas.mpl_connect('motion_notify_event', self.on_motion)
def on_press(self, event):
if event.inaxes != self.rect.axes: return
if DraggableRectangle.lock is not None: return
contains, attrd = self.rect.contains(event)
if not contains: return
x0, y0 = self.rect.xy
self.press = x0, y0, event.xdata, event.ydata
DraggableRectangle.lock = self
canvas = self.rect.figure.canvas
axes = self.rect.axes
self.rect.set_animated(True)
canvas.draw()
self.background = canvas.copy_from_bbox(self.rect.axes.bbox)
axes.draw_artist(self.rect)
canvas.blit(axes.bbox)
def on_motion(self, event):
if DraggableRectangle.lock is not self: return
if event.inaxes != self.rect.axes: return
x0, y0, xpress, ypress = self.press
dx = event.xdata - xpress
dy = 0
if x0+dx > self.xMax:
self.rect.set_x(self.xMax)
elif x0+dx < self.xMin:
self.rect.set_x(self.xMin)
else:
self.rect.set_x(x0+dx)
self.rect.set_y(y0+dy)
canvas = self.rect.figure.canvas
axes = self.rect.axes
canvas.restore_region(self.background)
self.master.set_xlim(self.rect.get_x(), self.rect.get_x() + 92)
axes.draw_artist(self.rect)
canvas.blit(axes.bbox)
def on_release(self, event):
if DraggableRectangle.lock is not self: return
self.press = None
DraggableRectangle.lock = None
self.rect.set_animated(False)
self.background = None
self.rect.figure.canvas.draw()
def disconnect(self):
self.rect.figure.canvas.mpl_disconnect(self.cidpress)
self.rect.figure.canvas.mpl_disconnect(self.cidrelease)
self.rect.figure.canvas.mpl_disconnect(self.cidmotion)
class MplCanvasFrame(wx.Frame):
def __init__(self):
wx.Frame.__init__(self, None, wx.ID_ANY, title='First Chart', size=(800, 700))
datafile = matplotlib.get_example_data('goog.npy')
r = np.load(datafile).view(np.recarray)
datesFloat = matplotlib.dates.date2num(r.date)
figure = Figure()
xMaxDatetime = r.date[len(r.date)-1]
xMinDatetime = r.date[0]
xMaxFloat = datesFloat[len(datesFloat)-1]
xMinFloat = datesFloat[0]
yMin = min(r.adj_close) // 5 * 5
yMax = (1 + max(r.adj_close) // 5) * 5
master = figure.add_subplot(211)
master.plot(datesFloat, r.adj_close)
master.xaxis.set_minor_locator(mdates.MonthLocator())
master.xaxis.set_major_locator(mdates.MonthLocator(bymonth=(1,4,7,10)))
master.xaxis.set_major_formatter(mdates.DateFormatter('%b-%y'))
master.set_xlim(datesFloat[120], datesFloat[120]+92)
master.yaxis.set_minor_locator(mtickers.MultipleLocator(50))
master.yaxis.set_major_locator(mtickers.MultipleLocator(100))
master.set_ylim(yMin, yMax)
master.set_position([0.05,0.20,0.92,0.75])
master.xaxis.grid(True, which='minor')
master.yaxis.grid(True, which='minor')
slave = figure.add_subplot(212, yticks=[])
slave.plot(datesFloat, r.adj_close)
slave.xaxis.set_minor_locator(mdates.MonthLocator())
slave.xaxis.set_major_locator(mdates.YearLocator())
slave.xaxis.set_major_formatter(mdates.DateFormatter('%b-%y'))
slave.set_xlim(xMinDatetime, xMaxDatetime)
slave.set_ylim(yMin, yMax)
slave.set_position([0.05,0.05,0.92,0.10])
rectangle = mpatches.Rectangle((datesFloat[120], yMin), 92, yMax-yMin, facecolor='yellow', alpha = 0.4)
slave.add_patch(rectangle)
canvas = FigureCanvas(self, -1, figure)
drag = DraggableRectangle(rectangle, master, xMinFloat, xMaxFloat - 92)
drag.connect()
app = wx.PySimpleApp()
frame = MplCanvasFrame()
frame.Show(True)
app.MainLoop()

I had a chance to work on this this morning (we are having a 2nd blizzard for the last 3 days). You are right, if you try to redraw the entire figure in the on_motion, it messes up the animation of the yellow rectangle. The key is to also blit the line on the master sub plot.
Try this code out:
import datetime
import numpy as np
import sys
import time
import wx
import matplotlib
from matplotlib.figure import Figure
import matplotlib.dates as mdates
import matplotlib.ticker as mtickers
from matplotlib.backends.backend_wxagg import FigureCanvasWxAgg as FigureCanvas
import matplotlib.patches as mpatches
class DraggableRectangle:
lock = None
def __init__(self, rect, master, xMin, xMax):
self.rect = rect
self.press = None
self.slave_background = None
self.master_background = None
self.xMax = xMax
self.xMin = xMin
self.master = master
self.master_line, = self.master.get_lines()
def connect(self):
self.cidpress = self.rect.figure.canvas.mpl_connect('button_press_event', self.on_press)
self.cidrelease = self.rect.figure.canvas.mpl_connect('button_release_event', self.on_release)
self.cidmotion = self.rect.figure.canvas.mpl_connect('motion_notify_event', self.on_motion)
def on_press(self, event):
if event.inaxes != self.rect.axes: return
if DraggableRectangle.lock is not None: return
contains, attrd = self.rect.contains(event)
if not contains: return
x0, y0 = self.rect.xy
self.press = x0, y0, event.xdata, event.ydata
DraggableRectangle.lock = self
canvas = self.rect.figure.canvas
axes = self.rect.axes
# set up our animated elements
self.rect.set_animated(True)
self.master_line.set_animated(True)
self.master.xaxis.set_visible(False) #we are not animating this
canvas.draw()
# backgrounds for restoring on animation
self.slave_background = canvas.copy_from_bbox(self.rect.axes.bbox)
self.master_background = canvas.copy_from_bbox(self.master.axes.bbox)
axes.draw_artist(self.rect)
canvas.blit(axes.bbox)
def on_motion(self, event):
if DraggableRectangle.lock is not self: return
if event.inaxes != self.rect.axes: return
x0, y0, xpress, ypress = self.press
dx = event.xdata - xpress
dy = 0
if x0+dx > self.xMax:
self.rect.set_x(self.xMax)
elif x0+dx < self.xMin:
self.rect.set_x(self.xMin)
else:
self.rect.set_x(x0+dx)
self.rect.set_y(y0+dy)
canvas = self.rect.figure.canvas
axes = self.rect.axes
# restore backgrounds
canvas.restore_region(self.slave_background)
canvas.restore_region(self.master_background)
# set our limits for animated line
self.master.set_xlim(self.rect.get_x(), self.rect.get_x() + 92)
# draw yellow box
axes.draw_artist(self.rect)
canvas.blit(axes.bbox)
#draw line
self.master.axes.draw_artist(self.master_line)
canvas.blit(self.master.axes.bbox)
def on_release(self, event):
if DraggableRectangle.lock is not self: return
self.press = None
DraggableRectangle.lock = None
# unanimate rect and lines
self.rect.set_animated(False)
self.master_line.set_animated(False)
self.slave_background = None
self.master_background = None
# redraw whole figure
self.master.xaxis.set_visible(True)
self.rect.figure.canvas.draw()
def disconnect(self):
self.rect.figure.canvas.mpl_disconnect(self.cidpress)
self.rect.figure.canvas.mpl_disconnect(self.cidrelease)
self.rect.figure.canvas.mpl_disconnect(self.cidmotion)
class MplCanvasFrame(wx.Frame):
def __init__(self):
wx.Frame.__init__(self, None, wx.ID_ANY, title='First Chart', size=(800, 700))
datafile = matplotlib.get_example_data('goog.npy')
r = np.load(datafile).view(np.recarray)
datesFloat = matplotlib.dates.date2num(r.date)
figure = Figure()
xMaxDatetime = r.date[len(r.date)-1]
xMinDatetime = r.date[0]
xMaxFloat = datesFloat[len(datesFloat)-1]
xMinFloat = datesFloat[0]
yMin = min(r.adj_close) // 5 * 5
yMax = (1 + max(r.adj_close) // 5) * 5
master = figure.add_subplot(211)
master.plot(datesFloat, r.adj_close)
master.xaxis.set_minor_locator(mdates.MonthLocator())
master.xaxis.set_major_locator(mdates.MonthLocator(bymonth=(1,4,7,10)))
master.xaxis.set_major_formatter(mdates.DateFormatter('%b-%y'))
master.set_xlim(datesFloat[120], datesFloat[120]+92)
master.yaxis.set_minor_locator(mtickers.MultipleLocator(50))
master.yaxis.set_major_locator(mtickers.MultipleLocator(100))
master.set_ylim(yMin, yMax)
master.set_position([0.05,0.20,0.92,0.75])
master.xaxis.grid(True, which='minor')
master.yaxis.grid(True, which='minor')
slave = figure.add_subplot(212, yticks=[])
slave.plot(datesFloat, r.adj_close)
slave.xaxis.set_minor_locator(mdates.MonthLocator())
slave.xaxis.set_major_locator(mdates.YearLocator())
slave.xaxis.set_major_formatter(mdates.DateFormatter('%b-%y'))
slave.set_xlim(xMinDatetime, xMaxDatetime)
slave.set_ylim(yMin, yMax)
slave.set_position([0.05,0.05,0.92,0.10])
rectangle = mpatches.Rectangle((datesFloat[120], yMin), 92, yMax-yMin, facecolor='yellow', alpha = 0.4)
slave.add_patch(rectangle)
canvas = FigureCanvas(self, -1, figure)
drag = DraggableRectangle(rectangle, master, xMinFloat, xMaxFloat - 92)
drag.connect()
app = wx.PySimpleApp()
frame = MplCanvasFrame()
frame.Show(True)
app.MainLoop()

Related

wxPython - Fixing buttons to a given position in a image

I'm building a software where I need to display buttons over a image and make it stay somewhat in the same position (the best as possible) when the sizer the image is in gets resized.
The button-display-on-image is already done. I just need to get the math working now. I've tried a bunch of stuff with no luck yet. I guess the magic need to happen in the updateButtons function.
Thanks!
import wx
import wx.lib.platebtn as pb
class MainFrame(wx.Frame):
def __init__(self, parent):
super().__init__(parent)
self.bInfoSizerVisibility = False
self.images = []
self.initUI()
self.CenterOnScreen()
self.Bind(wx.EVT_SIZE, self.OnResizing)
def initUI(self):
self.imageSizer = wx.BoxSizer(wx.VERTICAL)
self.imageSizer.SetMinSize((800, 600))
self.bitmap = None
self.image = None
self.aspect = None
self.bmpImage = wx.StaticBitmap(self, wx.ID_ANY)
self.imageSizer.Add(self.bmpImage, 1, wx.EXPAND)
self.btn = pb.PlateButton(self.bmpImage, -1, 'Click Me!', style=pb.PB_STYLE_NOBG)
self.btn.Bind(wx.EVT_BUTTON, self.test)
self.btn.Position = 250, 250
self.SetSizerAndFit(self.imageSizer)
self.frameImage()
def test(self, event):
print('Button Pressed!')
def updateButtons(self):
w, h = self.bmpImage.GetSize()
u, v = 0.3, 0.7
self.btn.Position = int(u * w), int(v * h)
def frameImage(self, isJustResize=False):
if not isJustResize:
self.bitmap = wx.Bitmap('image.jpg', wx.BITMAP_TYPE_ANY)
self.image = wx.Bitmap.ConvertToImage(self.bitmap)
self.aspect = self.image.GetSize()[1] / self.image.GetSize()[0]
self.Layout()
sW, sH = self.imageSizer.GetSize()
newW = sW
newH = int(newW * self.aspect)
if newH > sH:
newH = sH
newW = int(newH / self.aspect)
image = self.image.Scale(newW, newH)
self.bmpImage.SetBitmap(image.ConvertToBitmap())
self.Layout()
self.Refresh()
self.updateButtons()
# print(f"Image New Size: ({newW}, {newH})")
# print(f"App Size: {self.GetSize()}")
# print(f"imageSizer Size: {self.imageSizer.GetSize()}\n")
def OnResizing(self, event):
self.frameImage(True)
event.Skip()
app = wx.App()
frame = MainFrame(None)
frame.Show()
app.MainLoop()
You need to take into account the fact that as you resize the image, white space appears, either to the left and right, or on top and bottom. Remember, the button position is relative to the frame and not the image.
I have rewritten your updateButtons method to implement this.
I have assumed that your button's position will be 0.3 * the width of the image from the left and 0.7 * the height of the image from the top
import wx
import wx.lib.platebtn as pb
IMAGE_MINIMUM_SIZE = (800, 600)
BUTTON_POSITION_RATIO = (0.3, 0.7)
class MainFrame(wx.Frame):
def __init__(self, parent):
super().__init__(parent)
self.bInfoSizerVisibility = False
self.images = []
self.initUI()
self.CenterOnScreen()
self.Bind(wx.EVT_SIZE, self.OnResizing)
def initUI(self):
self.imageSizer = wx.BoxSizer(wx.VERTICAL)
self.imageSizer.SetMinSize(IMAGE_MINIMUM_SIZE)
self.bitmap = None
self.image = None
self.image_aspect = None
self.bmpImage = wx.StaticBitmap(self, wx.ID_ANY)
self.imageSizer.Add(self.bmpImage, 1, wx.EXPAND)
self.btn = pb.PlateButton(self, -1, 'Click Me!', style=pb.PB_STYLE_NOBG)
self.btn.Bind(wx.EVT_BUTTON, self.test)
self.SetSizerAndFit(self.imageSizer)
self.frameImage()
def test(self, event):
print('Button Pressed!')
def updateButtons(self):
frame_aspect = self.Size[0] / self.Size[1]
button_horizontal = int(self.Size[0] * BUTTON_POSITION_RATIO[0])
button_vertical = int(self.Size[1] * BUTTON_POSITION_RATIO[1])
if self.image_aspect <= frame_aspect:
# Frame is wider than image so find the horizontal white space size to add
image_width = self.Size[1] * self.image_aspect
horizontal_offset = (self.Size[0] - image_width)/2
button_horizontal = int(horizontal_offset + image_width * BUTTON_POSITION_RATIO[0])
elif self.image_aspect > frame_aspect:
# Frame is higher than image so find the vertical white space size to add
image_height = self.Size[0] / self.image_aspect
vertical_offset = (self.Size[1] - image_height)/2
button_vertical = int(vertical_offset + image_height * BUTTON_POSITION_RATIO[1])
self.btn.Position = (button_horizontal, button_vertical)
def frameImage(self, isJustResize=False):
if not isJustResize:
self.bitmap = wx.Bitmap('image.jpg', wx.BITMAP_TYPE_ANY)
self.image = wx.Bitmap.ConvertToImage(self.bitmap)
self.image_aspect = self.image.GetSize()[0] / self.image.GetSize()[1]
image_width, image_height = self.imageSizer.GetSize()
new_image_width = image_width
new_image_height = int(new_image_width / self.image_aspect)
if new_image_height > image_height:
new_image_height = image_height
new_image_width = int(new_image_height * self.image_aspect)
image = self.image.Scale(new_image_width, new_image_height)
self.bmpImage.SetBitmap(image.ConvertToBitmap())
self.Layout()
self.Refresh()
self.updateButtons()
def OnResizing(self, event):
self.frameImage(True)
event.Skip()
app = wx.App()
frame = MainFrame(None)
frame.Show()
app.MainLoop()

Updating matplotlib live graph in wxPython panel with scrolling x-axis

I am trying to animate a live graph in a wx.Panel. I would like to have the x-axis update like this example. Many of the examples I see are basic and don't take into consideration other controls and functions in the class. Others have so many extras that I get lost in the weeds. I can't get the animation command in the right place or update the x-axis. Here is the code:
import wx
import logging
import numpy as np
import matplotlib
import time
import matplotlib.animation as animation
matplotlib.use('WXAgg')
import matplotlib.pyplot as plt
from matplotlib.backends.backend_wxagg import FigureCanvasWxAgg as FigureCanvas
from matplotlib.backends.backend_wx import NavigationToolbar2Wx
from matplotlib.figure import Figure
fTemp = ""
x = 0
class TempClass(wx.Frame):
def __init__(self):
wx.Frame.__init__(self, None, -1, title="", size=(600,500))
panel = wx.Panel(self)
self.fig = Figure(figsize=(6,4), dpi=75, facecolor='lightskyblue', edgecolor='r')
self.canvas = FigureCanvas(self, -1, self.fig)
self.ax = self.fig.add_subplot(111)
self.ax2 = self.ax.twinx()
self.ax.set_ylim(60,90)
self.ax.set_xlim(0,24)
self.ax2.set_ylim(0,100)
# major ticks every 5, minor ticks every 1
xmajor_ticks = np.arange(0, 24, 5)
xminor_ticks = np.arange(0, 24, 1)
self.ax.set_xticks(xmajor_ticks)
self.ax.set_xticks(xminor_ticks, minor=True)
self.ax.grid()
self.ax.set_xlabel('Hour')
self.ax.set_ylabel('Temp')
self.ax2.set_ylabel('Humidity')
self.ax.set_title('Temperature')
# The graph does not show in the panel when this in uncommented
#self.ani = animation.FuncAnimation(self.fig, self.onPlotTemp, interval=1000)
self.fanSensorTimer = wx.Timer(self)
self.Bind(wx.EVT_TIMER, self.onPlotTemp, self.fanSensorTimer)
self.fanSensorBtn = wx.Button(self, -1, "Start Sensor")
self.Bind(wx.EVT_BUTTON, self.onStartTempPlot, self.fanSensorBtn)
font1 = wx.Font(18, wx.DEFAULT,wx.NORMAL,wx.BOLD)
self.displayTemp = wx.StaticText(self, -1, "Current Tempurature")
self.curTempTxt = wx.TextCtrl(self, -1, "0",size=(100,40), style=wx.TE_READONLY|wx.TE_CENTRE|wx.BORDER_NONE)
self.curTempTxt.SetFont(font1)
self.displayHum = wx.StaticText(self, -1, "Current Humidity")
self.curHumTxt = wx.TextCtrl(self, -1,"0", size=(100,40), style=wx.TE_READONLY|wx.TE_CENTRE|wx.BORDER_NONE)
self.curHumTxt.SetFont(font1)
self.displayBox = wx.GridBagSizer(hgap=5,vgap=5)
self.displayBox.Add(self.displayTemp, pos=(0,0), flag=wx.TOP|wx.LEFT, border=5)
self.displayBox.Add(self.displayHum, pos=(0,1), flag=wx.TOP, border=5)
self.displayBox.Add(self.curTempTxt, pos=(1,0), flag=wx.ALL, border=5)
self.displayBox.Add(self.curHumTxt, pos=(1,1), flag=wx.ALL, border=5)
#---------
self.vbox = wx.BoxSizer(wx.VERTICAL)
self.vbox.Add(self.canvas, wx.ALIGN_CENTER|wx.ALL, 1)
self.vbox.Add(self.fanSensorBtn)
self.vbox.Add(self.displayBox, wx.ALIGN_CENTER|wx.ALL, 1)
self.SetSizer(self.vbox)
self.vbox.Fit(self)
def start(self):
# get temp/humidity reading from node
pass
def readTemp(self, data1, data2):
"Populates Current Temp"
global fTemp
self.curTempTxt.Clear()
a = format(data1, '08b')
b = format(data2, '08b')
x = a+b
y = int(x, base=2)
cTemp = ((175.72 * y)/65536)-46.85
fTemp = cTemp *1.8+32
cel = format(cTemp,'.1f')
far = format(fTemp,'.1f')
self.curTempTxt.WriteText(far + (u'\u00b0')+"F")
def rh1(self, data1, data2):
"Populates Current RH"
global relhum
self.curHumTxt.Clear()
a = format(data1, '08b')
b = format(data2, '08b')
x = a+b
y = int(x, base=2)
rh = ((125 * y)/65536)-6
relhum = format(rh,'.1f')
self.curHumTxt.WriteText(relhum + " %")
def onStartTempPlot(self,event):
#set for a short time period for testing purposes
self.fanSensorTimer.Start(5000)
print "Timer Started"
def onPlotTemp(self,event):
global fTemp, x, relhum
x +=1
y = int(fTemp)
y2 = float(relhum)
self.ax.plot(x,y,'r.')
self.ax2.plot(x,y2,'k.')
self.fig.canvas.draw()
# send message to node for another reading of temp/humidity
if __name__ == "__main__":
app = wx.App(False)
frame = TempClass()
frame.Show()
frame.start()
logging.basicConfig(level=logging.DEBUG)
app.MainLoop()
I would like to see the x axis increment as the data is plotted beyond the 24 hour point on the graph; when data for point 25 appears, the first point is dropped and the x axis shows '25'. The animation is commented out because it causes the graph to disappear until a point is plotted.
Here is a runnable example of what I am trying to achieve with the x axis:
import numpy
from matplotlib.pylab import *
from mpl_toolkits.axes_grid1 import host_subplot
import matplotlib.animation as animation
# Sent for figure
font = {'size' : 9}
matplotlib.rc('font', **font)
# Setup figure and subplots
f0 = figure(num = 0, figsize = (6, 4))#, dpi = 100)
f0.suptitle("Oscillation decay", fontsize=12)
ax01 = subplot2grid((2, 2), (0, 0))
# Set titles of subplots
ax01.set_title('Position vs Time')
# set y-limits
ax01.set_ylim(0,2)
# sex x-limits
ax01.set_xlim(0,1)
# Turn on grids
ax01.grid(True)
# set label names
ax01.set_xlabel("x")
ax01.set_ylabel("py")
# Data Placeholders
yp1=zeros(0)
yv1=zeros(0)
yp2=zeros(0)
yv2=zeros(0)
t=zeros(0)
# set plots
p011, = ax01.plot(t,yp1,'b-', label="yp1")
p012, = ax01.plot(t,yp2,'g-', label="yp2")
# set lagends
ax01.legend([p011,p012], [p011.get_label(),p012.get_label()])
# Data Update
xmin = 0
xmax = 24
x = 0
def updateData(self):
global x
global yp1
global yv1
global yp2
global yv2
global t
tmpp1 = 1 + exp(-x) *sin(2 * pi * x)
tmpv1 = - exp(-x) * sin(2 * pi * x) + exp(-x) * cos(2 * pi * x) * 2 * pi
yp1=append(yp1,tmpp1)
yv1=append(yv1,tmpv1)
yp2=append(yp2,0.5*tmpp1)
yv2=append(yv2,0.5*tmpv1)
t=append(t,x)
x += 1
p011.set_data(t,yp1)
p012.set_data(t,yp2)
if x >= xmax-1:
p011.axes.set_xlim(x-xmax+1,x+1)
return p011
# interval: draw new frame every 'interval' ms
# frames: number of frames to draw
simulation = animation.FuncAnimation(f0, updateData, blit=False, frames=200, interval=20, repeat=False)
plt.show()
You are not incrementing the X axis limit or the ticks.
def onPlotTemp(self,event):
global fTemp, x, relhum
x +=1
y = int(fTemp)
y2 = float(relhum)
if x >= 24-1:
self.ax.set_xlim(x-24+1,x+1)
xmajor_ticks = np.arange(x-24+1,x+5, 5)
xminor_ticks = np.arange(x-24+1, x+1,1)
self.ax.set_xticks(xmajor_ticks)
self.ax.set_xticks(xminor_ticks, minor=True)
self.ax.plot(x,y,'r.')
self.ax2.plot(x,y2,'k.')
self.fig.canvas.draw()
I'm not sure if the above resets the ticks the way you want them but you get the idea. Obviously I have hard-coded 24 as your limit, you may want to create a variable to sort that out.

Optimize resizing picture on a button with PIL

self.image2Code:
from tkinter import *
from tkinter import font
from PIL import Image, ImageTk
class App(Tk):
def __init__(self):
Tk.__init__(self)
self.variables()
self.makeUI()
def variables(self):
self.buttonlist = []
self.font = font.Font(family = "Consolas", size = 12, weight = "bold")
def makeUI(self):
self.title("Changing font")
self.geometry("300x300")
self.minsize(200, 200)
self.maxsize(1000, 1000)
self.columnconfigure(0, weight = 1)
self.rowconfigure(0, weight = 1)
self.buttonlist.append(Button(self, height = 2, width = 4, font = self.font))
self.buttonlist[0].grid(row = 0, column = 0, sticky = W+E+S+N, padx = 2, pady = 2)
self.update()
self.image2 = Image.open("1.png")
self.image = ImageTk.PhotoImage(self.image2.resize((self.buttonlist[0].winfo_width(), self.buttonlist[0].winfo_height()), Image.ANTIALIAS))
self.buttonlist[0].configure(image = self.image)
self.buttonlist[0].bind("<Configure>", self.changeimage)
def changeimage(self, *args):
self.update()
#use smaller size
x = self.buttonlist[0].winfo_width()
y = self.buttonlist[0].winfo_height()
x = x if x < y else y
self.image = ImageTk.PhotoImage(self.image2.resize((x, x), Image.ANTIALIAS))
self.buttonlist[0].configure(image = self.image)
def main():
root = App()
root.mainloop()
if __name__ == "__main__":
main()
The problem:
The code works, the problem is that the program is slow on a quite powerful PC. It is making unnecessary calculations. My image is called "1.png".I don't know if I'm using the right approach.

Matplotlib Animation: updating radial view limit for polar plot

I'm trying to create an animated polar plot that, where the radial view limit increases/decreases to accommodate the radius. The yaxis updates just fine if I set polar=False, but it doesn't work correctly for a polar axis.
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
def data_gen():
t = data_gen.t
cnt = 0
while cnt < 1000:
cnt+=1
t += 0.05
yield t, 1.1 + np.sin(2*np.pi*t) * np.exp(t/10.)
data_gen.t = 0
plt.rc ('grid', color='g', lw=1, ls='-')
plt.rc ('xtick', labelsize=15, color='b')
plt.rc ('ytick', labelsize=15, color='b')
fig = plt.figure(figsize=(8,8))
ax1 = fig.add_axes([.05, .90, .9, .08], polar=False, axisbg='#BFBFBF', xticks=[], yticks=[])
ax2 = fig.add_axes([.05, .05, .9, .8], polar=True, axisbg='k')
#ax = fig.add_axes([.1,.1,.8,.8], polar=False, axisbg='k')
line, = ax2.plot([], [], lw=2)
ax2.set_ylim(0, 2.2)
ax2.set_xlim(0, 140)
ax2.grid(1)
xdata, ydata = [], []
title = ax1.text (0.02, 0.5, '', fontsize=14, transform=ax1.transAxes)
def init():
line.set_data([], [])
title.set_text ('')
return line, title
def run(data):
# update the data
t,y = data
xdata.append(t)
ydata.append(y)
ymin, ymax = ax2.get_ylim()
if y >= ymax:
ax2.set_ylim (ymin, 2*ymax)
ax2.figure.canvas.draw()
title.set_text ("time = %.3f, y(t) = 1.1 + sin(2*pi*t) + exp(t/10) = %.3f" % (t, y))
line.set_data(xdata, ydata)
return line, title
ani = animation.FuncAnimation(fig, run, data_gen, init, blit=True, interval=100, repeat=False)
Actually, the view limit does adjust, but the tick labels stay the same. Inserting raw_input() after the canvas is redrawn reveals that everything is redrawn correctly, but then the tick labels revert back to what they were before. Stranger still, this doesn't occur until the update() function is called a second time and returns.
I didn't have this problem when I animated the plot the old way, by calling draw() repeatedly. But I'd rather do it the right way with the animation module, as the old way had performance problems (The above code block is only to demonstrate the problem, and isn't the actual program that I'm writing).
I should note that I'm still learning MPL, so I apologize if some of my terminology is wrong.
If you use blit, the background is saved in cache for fast draw, you can clear the cache when the axis range is changed, add ani._blit_cache.clear():
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
def data_gen():
t = data_gen.t
cnt = 0
while cnt < 1000:
cnt+=1
t += 0.05
yield t, 1.1 + np.sin(2*np.pi*t) * np.exp(t/10.)
data_gen.t = 0
plt.rc ('grid', color='g', lw=1, ls='-')
plt.rc ('xtick', labelsize=15, color='b')
plt.rc ('ytick', labelsize=15, color='b')
fig = plt.figure(figsize=(8,8))
ax1 = fig.add_axes([.05, .90, .9, .08], polar=False, axisbg='#BFBFBF', xticks=[], yticks=[])
ax2 = fig.add_axes([.05, .05, .9, .8], polar=True, axisbg='k')
#ax = fig.add_axes([.1,.1,.8,.8], polar=False, axisbg='k')
line, = ax2.plot([], [], lw=2)
ax2.set_ylim(0, 2.2)
ax2.set_xlim(0, 140)
ax2.grid(1)
xdata, ydata = [], []
title = ax1.text (0.02, 0.5, '', fontsize=14, transform=ax1.transAxes)
def init():
line.set_data([], [])
title.set_text ('')
return line, title
def run(data):
# update the data
t,y = data
xdata.append(t)
ydata.append(y)
ymin, ymax = ax2.get_ylim()
if y >= ymax:
ax2.set_ylim (ymin, 2*ymax)
ani._blit_cache.clear() # <- add to clear background from blit cache
title.set_text('') # <- eliminate text artifact in title
ax2.figure.canvas.draw()
title.set_text ("time = %.3f, y(t) = 1.1 + sin(2*pi*t) + exp(t/10) = %.3f" % (t, y))
line.set_data(xdata, ydata)
return line, title
ani = animation.FuncAnimation(fig, run, data_gen, init, blit=True, interval=100, repeat=False)

tkinter: displaying a square grid

I'm trying to use tkinter to periodically refresh a square grid. Each square in the grid is painted a certain color (say obtained from a given function); in the center of each square, a smaller circle is drawn (the color is also obtained from a function).
If I have to do it from scratch, perhaps there's an example or a standard recipe I can use?
Here's a quick hack showing how to draw a grid of rectangles and circles, and how to update the display once a second. If you've never programmed in tk before, it uses concepts that are no doubt foreign to you. You'll need to read up on canvas object ids and tags, as well as what the after command does.
import Tkinter as tk
import random
class App(tk.Tk):
def __init__(self, *args, **kwargs):
tk.Tk.__init__(self, *args, **kwargs)
self.canvas = tk.Canvas(self, width=500, height=500, borderwidth=0, highlightthickness=0)
self.canvas.pack(side="top", fill="both", expand="true")
self.rows = 100
self.columns = 100
self.cellwidth = 25
self.cellheight = 25
self.rect = {}
self.oval = {}
for column in range(20):
for row in range(20):
x1 = column*self.cellwidth
y1 = row * self.cellheight
x2 = x1 + self.cellwidth
y2 = y1 + self.cellheight
self.rect[row,column] = self.canvas.create_rectangle(x1,y1,x2,y2, fill="blue", tags="rect")
self.oval[row,column] = self.canvas.create_oval(x1+2,y1+2,x2-2,y2-2, fill="blue", tags="oval")
self.redraw(1000)
def redraw(self, delay):
self.canvas.itemconfig("rect", fill="blue")
self.canvas.itemconfig("oval", fill="blue")
for i in range(10):
row = random.randint(0,19)
col = random.randint(0,19)
item_id = self.oval[row,col]
self.canvas.itemconfig(item_id, fill="green")
self.after(delay, lambda: self.redraw(delay))
if __name__ == "__main__":
app = App()
app.mainloop()

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