Search Results

Search found 13534 results on 542 pages for 'python 2 6'.

Page 367/542 | < Previous Page | 363 364 365 366 367 368 369 370 371 372 373 374  | Next Page >

  • Why does my buffered GraphicsContext application have a flickering problem?

    - by Bibendum
    import wx class MainFrame(wx.Frame): def __init__(self,parent,title): wx.Frame.__init__(self, parent, title=title, size=(640,480)) self.mainPanel=DoubleBufferTest(self,-1) self.Show(True) class DoubleBufferTest(wx.Panel): def __init__(self,parent=None,id=-1): wx.Panel.__init__(self,parent,id,style=wx.FULL_REPAINT_ON_RESIZE) self.SetBackgroundColour("#FFFFFF") self.timer = wx.Timer(self) self.timer.Start(100) self.Bind(wx.EVT_TIMER, self.update, self.timer) self.Bind(wx.EVT_PAINT,self.onPaint) def onPaint(self,event): event.Skip() dc = wx.MemoryDC() dc.SelectObject(wx.EmptyBitmap(640, 480)) gc = wx.GraphicsContext.Create(dc) gc.PushState() gc.SetBrush(wx.Brush("#CFCFCF")) bgRect=gc.CreatePath() bgRect.AddRectangle(0,0,640,480) gc.FillPath(bgRect) gc.PopState() dc2=wx.PaintDC(self) dc2.Blit(0,0,640,480,dc,0,0) def update(self,event): self.Refresh() app = wx.App(False) f=MainFrame(None,"Test") app.MainLoop() I've come up with this code to draw double buffered GraphicsContext content onto a panel, but there's a constant flickering across the window. I've tried different kinds of paths, like lines and curves but it's still there and I don't know what's causing it.

    Read the article

  • etree.findall: 'OR'-lookup?

    - by piquadrat
    I want to find all stylesheet definitions in a XHTML file with lxml.etree.findall. This could be as simple as elems = tree.findall('link[@rel="stylesheet"]') + tree.findall('style') But the problem with CSS style definitions is that the order matters, e.g. <link rel="stylesheet" type="text/css" href="/media/css/first.css" /> <style>body:{font-size: 10px;}</style> <link rel="stylesheet" type="text/css" href="/media/css/second.css" /> if the contents of the style tag is applied after the rules in the two link tags, the result may be completely different from the one where the rules are applied in order of definition. So, how would I do a lookup that inlcudes both link[@rel="stylesheet"] and style?

    Read the article

  • How To Run Postgres locally

    - by Rohit Rayudu
    I read the Postgres docs for Flask and they said that to run Postgres you should have the following code app = Flask(__name__) app.config['SQLALCHEMY_DATABASE_URI'] = postgresql://localhost/[YOUR_DB_NAME]' db = SQLAlchemy(app) How do I know my database name? I wrote db as the name - but I got an error sqlalchemy.exc.OperationalError: (OperationalError) FATAL: database "[db]" does not exist Running Heroku with Flask if that helps

    Read the article

  • How to improve efficiency in loops?

    - by Jacob Worldly
    I have the following code, which translates the input string into morse code. My code runs through every letter in the string and then through every character in the alphabet. This is very inefficient, because what if I was reading from a very large file, instead of a small alphabet string. Is there any way that I could improve my code, Maybe using the module re, to match my string with the morse code characters? morse_alphabet = ".- -... -.-. -.. . ..-. --. .... .. .--- -.- .-.. -- -. --- .--. --.- .-. ... - ..- ...- .-- -..- -.-- --.." ALPHABET = "abcdefghijklmnopqrstuvwxyz" morse_letters = morse_alphabet.split(" ") result = [] count_character = 0 def t(code): for character in code: count_letter = 0 for letter in ALPHABET: lower_character = code[count_character].lower() lower_letter = letter.lower() if lower_character == lower_letter: result.append(morse_letters[count_letter]) count_letter += 1 count_character += 1 return result

    Read the article

  • How to make scipy.interpolate give a an extrapolated result beyond the input range?

    - by Salim Fadhley
    I'm trying to port a program which uses a hand-rolled interpolator (developed by a mathematitian colleage) over to use the interpolators provided by scipy. I'd like to use or wrap the scipy interpolator so that it has as close as possible behavior to the old interpolator. A key difference between the two functions is that in our original interpolator - if the input value is above or below the input range, our original interpolator will extrapolate the result. If you try this with the scipy interpolator it raises a ValueError. Consider this program as an example: import numpy as np from scipy import interpolate x = np.arange(0,10) y = np.exp(-x/3.0) f = interpolate.interp1d(x, y) print f(9) print f(11) # Causes ValueError, because it's greater than max(x) Is there a sensible way to make it so that instead of crashing, the final line will simply do a linear extrapolate, continuing the gradients defined by the first and last two pouints to infinity. Note, that in the real software I'm not actually using the exp function - that's here for illustration only!

    Read the article

  • ImportError and Django driving me crazy

    - by John Peebles
    OK, I have the following directory structure (it's a django project): - project -- app and within the app folder, there is a scraper.py file which needs to reference a class defined within models.py I'm trying to do the following: import urllib2 import os import sys import time import datetime import re import BeautifulSoup sys.path.append('/home/userspace/Development/') os.environ['DJANGO_SETTINGS_MODULE'] = 'project.settings' from project.app.models import ClassName and this code just isn't working. I get an error of: Traceback (most recent call last): File "scraper.py", line 14, in from project.app.models import ClassName ImportError: No module named project.app.models This code above used to work, but broke somewhere along the line and I'm extremely confused as to why I'm having problems. On SnowLeopard using python2.5.

    Read the article

  • How can I draw a log-normalized imshow plot with a colorbar representing the raw data in matplotlib

    - by Adam Fraser
    I'm using matplotlib to plot log-normalized images but I would like the original raw image data to be represented in the colorbar rather than the [0-1] interval. I get the feeling there's a more matplotlib'y way of doing this by using some sort of normalization object and not transforming the data beforehand... in any case, there could be negative values in the raw image. import matplotlib.pyplot as plt import numpy as np def log_transform(im): '''returns log(image) scaled to the interval [0,1]''' try: (min, max) = (im[im > 0].min(), im.max()) if (max > min) and (max > 0): return (np.log(im.clip(min, max)) - np.log(min)) / (np.log(max) - np.log(min)) except: pass return im a = np.ones((100,100)) for i in range(100): a[i] = i f = plt.figure() ax = f.add_subplot(111) res = ax.imshow(log_transform(a)) # the colorbar drawn shows [0-1], but I want to see [0-99] cb = f.colorbar(res) I've tried using cb.set_array, but that didn't appear to do anything, and cb.set_clim, but that rescales the colors completely. Thanks in advance for any help :)

    Read the article

  • Preserving the dimensions of a slice from a Numpy 3d array

    - by Brendan
    I have a 3d array, a, of shape say a.shape = (10, 10, 10) When slicing, the dimensions are squeezed automatically i.e. a[:,:,5].shape = (10, 10) I'd like to preserve the number of dimensions but also ensure that the dimension that was squeezed is the one that shows 1 i.e. a[:,:,5].shape = (10, 10, 1) I have thought of re-casting the array and passing ndmin but that just adds the extra dimensions to the start of the shape tuple regardless of where the slice came from in the array a.

    Read the article

  • split twice in the same expression?

    - by UcanDoIt
    Imagine I have the following: inFile = "/adda/adas/sdas/hello.txt" # that instruction give me hello.txt Name = inFile.name.split("/") [-1] # that one give me the name I want - just hello Name1 = Name.split(".") [0] Is there any chance to simplify that doing the same job in just one expression?

    Read the article

  • Attribute Error in django

    - by itsandy
    Hi all, I am having an attribute error while working with django-registration it says 'NoneType' object has no attribute 'strip' I dropped my db table and created again but the error doesnt go..can anyone help..

    Read the article

  • Obtaining references to function objects on the execution stack from the frame object?

    - by Marcin
    Given the output of inspect.stack(), is it possible to get the function objects from anywhere from the stack frame and call these? If so, how? (I already know how to get the names of the functions.) Here is what I'm getting at: Let's say I'm a function and I'm trying to determine if my caller is a generator or a regular function? I need to call inspect.isgeneratorfunction() on the function object. And how do you figure out who called you? inspect.stack(), right? So if I can somehow put those together, I'll have the answer to my question. Perhaps there is an easier way to do this?

    Read the article

  • matplotlib.pyplot, preserve aspect ratio of the plot

    - by Headcrab
    Assuming we have a polygon coordinates as polygon = [(x1, y1), (x2, y2), ...], the following code displays the polygon: import matplotlib.pyplot as plt plt.fill(*zip(*polygon)) plt.show() By default it is trying to adjust the aspect ratio so that the polygon (or whatever other diagram) fits inside the window, and automatically changing it so that it fits even after resizing. Which is great in many cases, except when you are trying to estimate visually if the image is distorted. How to fix the aspect ratio to be strictly 1:1? (Not sure if "aspect ratio" is the right term here, so in case it is not - I need both X and Y axes to have 1:1 scale, so that (0, 1) on both X and Y takes an exact same amount of screen space. And I need to keep it 1:1 no matter how I resize the window.)

    Read the article

  • how to speed up the code??

    - by kaushik
    i have very huge code about 600 lines plus. cant post the whole thing here. but a particular code snippet is taking so much time,leading to problems. here i post that part of code please tell me what to do speed up the processing.. please suggest the part which may be the reason and measure to improve them if this small part of code is understandable. using_data={} def join_cost(a , b): global using_data #print a #print b save_a=[] save_b=[] print 1 #for i in range(len(m)): #if str(m[i][0])==str(a): save_a=database_index[a] #for i in range(len(m)): # if str(m[i][0])==str(b): #print 'save_a',save_a #print 'save_b',save_b print 2 save_b=database_index[b] using_data[save_a[0]]=save_a s=str(save_a[1]).replace('phone','text') s=str(s)+'.pm' p=os.path.join("c:/begpython/wavnk/",s) x=open(p , 'r') print 3 for i in range(6): x.readline() k2='a' j=0 o=[] while k2 is not '': k2=x.readline() k2=k2.rstrip('\n') oj=k2.split(' ') o=o+[oj] #print o[j] j=j+1 #print j #print o[2][0] temp=long(1232332) end_time=save_a[4] #print end_time k=(j-1) for i in range(k): diff=float(o[i][0])-float(end_time) if diff<0: diff=diff*(-1) if temp>diff: temp=diff pm_row=i #print pm_row #print temp #print o[pm_row] #pm_row=3 q=[] print 4 l=str(p).replace('.pm','.mcep') z=open(l ,'r') for i in range(pm_row): z.readline() k3=z.readline() k3=k3.rstrip('\n') q=k3.split(' ') #print q print 5 s=str(save_b[1]).replace('phone','text') s=str(s)+'.pm' p=os.path.join("c:/begpython/wavnk/",s) x=open(p , 'r') for i in range(6): x.readline() k2='a' j=0 o=[] while k2 is not '': k2=x.readline() k2=k2.rstrip('\n') oj=k2.split(' ') o=o+[oj] #print o[j] j=j+1 #print j #print o[2][0] temp=long(1232332) strt_time=save_b[3] #print strt_time k=(j-1) for i in range(k): diff=float(o[i][0])-float(strt_time) if diff<0: diff=diff*(-1) if temp>diff: temp=diff pm_row=i #print pm_row #print temp #print o[pm_row] #pm_row=3 w=[] l=str(p).replace('.pm','.mcep') z=open(l ,'r') for i in range(pm_row): z.readline() k3=z.readline() k3=k3.rstrip('\n') w=k3.split(' ') #print w cost=0 for i in range(12): #print q[i] #print w[i] h=float(q[i])-float(w[i]) cost=cost+math.pow(h,2) j_cost=math.sqrt(cost) #print cost return j_cost def target_cost(a , b): a=(b+1)*3 b=(a+1)*2 t_cost=(a+b)*5/2 return t_cost r1='shht:ra_77' r2='grx_18' g=[] nodes=[] nodes=nodes+[[r1]] for i in range(len(y_in_db_format)): g=y_in_db_format[i] #print g #print g[0] g.remove(str(g[0])) nodes=nodes+[g] nodes=nodes+[[r2]] print nodes print "lenght of nodes",len(nodes) lists=[] #lists=lists+[r1] for i in range(len(nodes)): for j in range(len(nodes[i])): lists=lists+[nodes[i][j]] #lists=lists+[r2] print lists distance={} for i in range(len(lists)): if i==0: distance[str(lists[i])]=0 else: distance[str(lists[i])]=long(123231223) #print distance group_dist=[] infinity=long(123232323) for i in range(len(nodes)): distances=[] for j in range(len(nodes[i])): #distances=[] if i==0: distances=distances+[[nodes[i][j], 0]] else: distances=distances+[[nodes[i][j],infinity]] group_dist=group_dist+[distances] #print distances print "group_distances",group_dist #print "check",group_dist[0][0][1] #costs={} #for i in range(len(lists)): #if i==0: # costs[str(lists[i])]=1 #else: # costs[str(lists[i])]=get_selfcost(lists[i]) path=[] for i in range(len(nodes)): mini=[] if i!=(len(nodes)-1): #temp=long(123234324) #Now calculate the cost between the current node and each of its neighbour for k in range(len(nodes[(i+1)])): for j in range(len(nodes[i])): current=nodes[i][j] #print "current_node",current j_distance=join_cost( current , nodes[i+1][k]) #t_distance=target_cost( current , nodes[i+1][k]) t_distance=34 #print distance #print "distance between current and neighbours",distance total_distance=(.5*(float(group_dist[i][j][1])+float(j_distance))+.5*(float(t_distance))) #print "total distance between the intial_nodes and current neighbour",total_distance if int(group_dist[i+1][k][1]) > int(total_distance): group_dist[i+1][k][1]=total_distance #print "updated distance",group_dist[i+1][k][1] a=current #print "the neighbour",nodes[i+1][k],"updated the value",a mini=mini+[[str(nodes[i+1][k]),a]] print mini

    Read the article

  • how to speed up the code??

    - by kaushik
    in my program i have a method which requires about 4 files to be open each time it is called,as i require to take some data.all this data from the file i have been storing in list for manupalation. I approximatily need to call this method about 10,000 times.which is making my program very slow? any method for handling this files in a better ways and is storing the whole data in list time consuming what is better alternatives for list? I can give some code,but my previous question was closed as that only confused everyone as it is a part of big program and need to be explained completely to understand,so i am not giving any code,please suggest ways thinking this as a general question... thanks in advance

    Read the article

  • Django: Filtering datetime field by *only* the year value?

    - by unclaimedbaggage
    Hi folks, I'm trying to spit out a django page which lists all entries by the year they were created. So, for example: 2010: Note 4 Note 5 Note 6 2009: Note 1 Note 2 Note 3 It's proving more difficult than I would have expected. The model from which the data comes is below: class Note(models.Model): business = models.ForeignKey(Business) note = models.TextField() created = models.DateTimeField(auto_now_add=True) updated = models.DateTimeField(auto_now=True) class Meta: db_table = 'client_note' @property def note_year(self): return self.created.strftime('%Y') def __unicode__(self): return '%s' % self.note I've tried a few different ways, but seem to run into hurdles down every path. I'm guessing an effective 'group by' method would do the trick (PostGres DB Backend), but I can't seem to find any Django functionality that supports it. I tried getting individual years from the database but I struggled to find a way of filtering datetime fields by just the year value. Finally, I tried adding the note_year @property but because it's derived, I can't filter those values. Any suggestions for an elegant way to do this? I figure it should be pretty straightforward, but I'm having a heckuva time with it. Any ideas much appreciated.

    Read the article

  • twisted reactor stops too early

    - by pygabriel
    I'm doing a batch script to connect to a tcp server and then exiting. My problem is that I can't stop the reactor, for example: cmd = raw_input("Command: ") # custom factory, the protocol just send a line reactor.connectTCP(HOST,PORT, CommandClientFactory(cmd) d = defer.Deferred() d.addCallback(lambda x: reactor.stop()) reactor.callWhenRunning(d.callback,None) reactor.run() In this code the reactor stops before that the tcp connection is done and the cmd is passed. How can I stop the reactor after that all the operation are finished?

    Read the article

< Previous Page | 363 364 365 366 367 368 369 370 371 372 373 374  | Next Page >