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  • Cookies with urllib

    - by CMC
    This will probably seem like a really simple question, and I am quite confused as to why this is so difficult for me. I would like to write a function that takes three inputs: [url, data, cookies] that will use urllib (not urllib2) to get the contents of the requested url. I figured it'd be simple, so I wrote the following: def fetch(url, data = None, cookies = None): if isinstance(data, dict): data = urllib.urlencode(data) if isinstance(cookies, dict): # TODO: find a better way to do this cookies = "; ".join([str(key) + "=" + str(cookies[key]) for key in cookies]) opener = urllib.FancyURLopener() opener.addheader("Cookie", cookies) obj = opener.open(url, data) result = obj.read() obj.close() return result This doesn't work, as far as I can tell (can anyone confirm that?) and I'm stumped.

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  • Problem trying to achieve a join using the `comments` contrib in Django

    - by NiKo
    Hi, Django rookie here. I have this model, comments are managed with the django_comments contrib: class Fortune(models.Model): author = models.CharField(max_length=45, blank=False) title = models.CharField(max_length=200, blank=False) slug = models.SlugField(_('slug'), db_index=True, max_length=255, unique_for_date='pub_date') content = models.TextField(blank=False) pub_date = models.DateTimeField(_('published date'), db_index=True, default=datetime.now()) votes = models.IntegerField(default=0) comments = generic.GenericRelation( Comment, content_type_field='content_type', object_id_field='object_pk' ) I want to retrieve Fortune objects with a supplementary nb_comments value for each, counting their respectve number of comments ; I try this query: >>> Fortune.objects.annotate(nb_comments=models.Count('comments')) From the shell: >>> from django_fortunes.models import Fortune >>> from django.db.models import Count >>> Fortune.objects.annotate(nb_comments=Count('comments')) [<Fortune: My first fortune, from NiKo>, <Fortune: Another One, from Dude>, <Fortune: A funny one, from NiKo>] >>> from django.db import connection >>> connection.queries.pop() {'time': '0.000', 'sql': u'SELECT "django_fortunes_fortune"."id", "django_fortunes_fortune"."author", "django_fortunes_fortune"."title", "django_fortunes_fortune"."slug", "django_fortunes_fortune"."content", "django_fortunes_fortune"."pub_date", "django_fortunes_fortune"."votes", COUNT("django_comments"."id") AS "nb_comments" FROM "django_fortunes_fortune" LEFT OUTER JOIN "django_comments" ON ("django_fortunes_fortune"."id" = "django_comments"."object_pk") GROUP BY "django_fortunes_fortune"."id", "django_fortunes_fortune"."author", "django_fortunes_fortune"."title", "django_fortunes_fortune"."slug", "django_fortunes_fortune"."content", "django_fortunes_fortune"."pub_date", "django_fortunes_fortune"."votes" LIMIT 21'} Below is the properly formatted sql query: SELECT "django_fortunes_fortune"."id", "django_fortunes_fortune"."author", "django_fortunes_fortune"."title", "django_fortunes_fortune"."slug", "django_fortunes_fortune"."content", "django_fortunes_fortune"."pub_date", "django_fortunes_fortune"."votes", COUNT("django_comments"."id") AS "nb_comments" FROM "django_fortunes_fortune" LEFT OUTER JOIN "django_comments" ON ("django_fortunes_fortune"."id" = "django_comments"."object_pk") GROUP BY "django_fortunes_fortune"."id", "django_fortunes_fortune"."author", "django_fortunes_fortune"."title", "django_fortunes_fortune"."slug", "django_fortunes_fortune"."content", "django_fortunes_fortune"."pub_date", "django_fortunes_fortune"."votes" LIMIT 21 Can you spot the problem? Django won't LEFT JOIN the django_comments table with the content_type data (which contains a reference to the fortune one). This is the kind of query I'd like to be able to generate using the ORM: SELECT "django_fortunes_fortune"."id", "django_fortunes_fortune"."author", "django_fortunes_fortune"."title", COUNT("django_comments"."id") AS "nb_comments" FROM "django_fortunes_fortune" LEFT OUTER JOIN "django_comments" ON ("django_fortunes_fortune"."id" = "django_comments"."object_pk") LEFT OUTER JOIN "django_content_type" ON ("django_comments"."content_type_id" = "django_content_type"."id") GROUP BY "django_fortunes_fortune"."id", "django_fortunes_fortune"."author", "django_fortunes_fortune"."title", "django_fortunes_fortune"."slug", "django_fortunes_fortune"."content", "django_fortunes_fortune"."pub_date", "django_fortunes_fortune"."votes" LIMIT 21 But I don't manage to do it, so help from Django veterans would be much appreciated :) Hint: I'm using Django 1.2-DEV Thanks in advance for your help.

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  • [numpy] storing record arrays in object arrays

    - by Peter Prettenhofer
    I'd like to convert a list of record arrays -- dtype is (uint32, float32) -- into a numpy array of dtype np.object: X = np.array(instances, dtype = np.object) where instances is a list of arrays with data type np.dtype([('f0', '<u4'), ('f1', '<f4')]). However, the above statement results in an array whose elements are also of type np.object: X[0] array([(67111L, 1.0), (104242L, 1.0)], dtype=object) Does anybody know why? The following statement should be equivalent to the above but gives the desired result: X = np.empty((len(instances),), dtype = np.object) X[:] = instances X[0] array([(67111L, 1.0), (104242L, 1.0), dtype=[('f0', '<u4'), ('f1', '<f4')]) thanks & best regards, peter

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  • how to load an image to a grid using pygame, instead of just using a fill color?

    - by yao jiang
    I am trying to create a "map of a city" using pygame. I want to be able to put images of buildings in specific grid coords rather than just filling them in with a color. This is how I am creating this map grid: def clear(): for r in range(rows): for c in range(rows): if r%3 == 1 and c%3 == 1: color = brown; grid[r][c] = 1; else: color = white; grid[r][c] = 0; pygame.draw.rect(screen, color, [(margin+width)*c+margin, (margin+height)*r+margin, width, height]) pygame.display.flip(); Now how do I put images of buildings in those brown colored grids at those specific locations? I've tried some of the samples online but can't seem to get them to work. Any help is appreciated. If anyone have a good source for free sprites that I can use for pygame, please let me know. Thanks!

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  • Programming an Event listener for files in a directory on Linux

    - by Epitaph
    On Ubuntu linux, when you watch a flash video, it gets saved temporarily in the /tmp as flv files while the video buffers. I use vlc to directly play these files. Currently, I have scripted a shortcut that directly scans and opens the latest file in /tmp with vlc, when clicked. But, I want to program a Java application that will continually monitor this /tmp directory for any new flv files, and open it in vlc automatically. I know I can use Runtime.exec() to open the VLC application with the flv files. But, I DO NOT want to run a while(true) loop (with sleep) to scan for files. How can I make use of Event Handling (Java or any other language) on Linux to complete this task?

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  • PyQt: Get the position of QGraphicsWidgets in a QGraphicsGridLayout

    - by Chris Phillips
    I have a fairly simple PyQt application in which I'm placing instances of a QGraphicsWidget in a QGraphicsGridLayout and want to connect the widgets with lines drawn with a QGraphicsPath. Unfortunately, no matter what I try, I always get (0, 0) back as the position for both the start and end widgets. I'm constructing the graph with a recursive function that adds widgets to the scene and layout. Once the recursive function is complete, the layout is added to a new widget, which is added to the scene to show everything. The edges are added to the scene as widgets are created. How do I get a non-zero position of any of the widgets in the grid layout?

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  • Using numpy.apply

    - by andylei
    What's wrong with this snippet of code? import numpy as np from scipy import stats d = np.arange(10.0) cutoffs = [stats.scoreatpercentile(d, pct) for pct in range(0, 100, 20)] f = lambda x: np.sum(x > cutoffs) fv = np.vectorize(f) # why don't these two lines output the same values? [f(x) for x in d] # => [0, 1, 2, 2, 3, 3, 4, 4, 5, 5] fv(d) # => array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0]) Any ideas?

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  • What algorithms are suitable for this simple machine learning problem?

    - by user213060
    I have a what I think is a simple machine learning question. Here is the basic problem: I am repeatedly given a new object and a list of descriptions about the object. For example: new_object: 'bob' new_object_descriptions: ['tall','old','funny']. I then have to use some kind of machine learning to find previously handled objects that had similar descriptions, for example, past_similar_objects: ['frank','steve','joe']. Next, I have an algorithm that can directly measure whether these objects are indeed similar to bob, for example, correct_objects: ['steve','joe']. The classifier is then given this feedback training of successful matches. Then this loop repeats with a new object. a Here's the pseudo-code: Classifier=new_classifier() while True: new_object,new_object_descriptions = get_new_object_and_descriptions() past_similar_objects = Classifier.classify(new_object,new_object_descriptions) correct_objects = calc_successful_matches(new_object,past_similar_objects) Classifier.train_successful_matches(object,correct_objects) But, there are some stipulations that may limit what classifier can be used: There will be millions of objects put into this classifier so classification and training needs to scale well to millions of object types and still be fast. I believe this disqualifies something like a spam classifier that is optimal for just two types: spam or not spam. (Update: I could probably narrow this to thousands of objects instead of millions, if that is a problem.) Again, I prefer speed when millions of objects are being classified, over accuracy. What are decent, fast machine learning algorithms for this purpose?

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  • openerp client customization

    - by iamgopal
    openerp client seems to be nice and working , i would like to hack it and use it as a front end to my open erp solution. but the documentation regarding client side design or customization is poor on openerp site , is there any good reference or documentation available for further digging in to openerp client side coding ? or more : if any similar client solution available that can be plug in to any back end system. ( i.e. rich internet client )

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  • Making HTTP POST request

    - by infrared
    I'm trying to make a POST request to retrieve information about a book. Here is the code that returns HTTP code: 302, Moved import httplib, urllib params = urllib.urlencode({ 'isbn' : '9780131185838', 'catalogId' : '10001', 'schoolStoreId' : '15828', 'search' : 'Search' }) headers = {"Content-type": "application/x-www-form-urlencoded", "Accept": "text/plain"} conn = httplib.HTTPConnection("bkstr.com:80") conn.request("POST", "/webapp/wcs/stores/servlet/BuybackSearch", params, headers) response = conn.getresponse() print response.status, response.reason data = response.read() conn.close() When I try from a browser, from this page: http://www.bkstr.com/webapp/wcs/stores/servlet/BuybackMaterialsView?langId=-1&catalogId=10001&storeId=10051&schoolStoreId=15828 , it works. What am I missing in my code? Thanks EDIT: Here's what I get when I call print response.msg 302 Moved Date: Tue, 07 Sep 2010 16:54:29 GMT Vary: Host,Accept-Encoding,User-Agent Location: http://www.bkstr.com/webapp/wcs/stores/servlet/BuybackSearch X-UA-Compatible: IE=EmulateIE7 Content-Length: 0 Content-Type: text/plain; charset=utf-8 Seems that the location points to the same url I'm trying to access in the first place? EDIT2: I've tried using urllib2 as suggested here. Here is the code: import urllib, urllib2 url = 'http://www.bkstr.com/webapp/wcs/stores/servlet/BuybackSearch' values = {'isbn' : '9780131185838', 'catalogId' : '10001', 'schoolStoreId' : '15828', 'search' : 'Search' } data = urllib.urlencode(values) req = urllib2.Request(url, data) response = urllib2.urlopen(req) print response.geturl() print response.info() the_page = response.read() print the_page And here is the output: http://www.bkstr.com/webapp/wcs/stores/servlet/BuybackSearch Date: Tue, 07 Sep 2010 16:58:35 GMT Pragma: No-cache Cache-Control: no-cache Expires: Thu, 01 Jan 1970 00:00:00 GMT Set-Cookie: JSESSIONID=0001REjqgX2axkzlR6SvIJlgJkt:1311s25dm; Path=/ Vary: Accept-Encoding,User-Agent X-UA-Compatible: IE=EmulateIE7 Content-Length: 0 Connection: close Content-Type: text/html; charset=utf-8 Content-Language: en-US Set-Cookie: TSde3575=225ec58bcb0fdddfad7332c2816f1f152224db2f71e1b0474c866f3b; Path=/

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  • Is this the correct way to convert a UTC datetime string into localtime?

    - by Steve
    Is this the correct way to convert a UTC string into local time allowing for daylight savings? It looks ok to me but you never know :) import time UTC_STRING = "2010-03-25 02:00:00" stamp = time.mktime(time.strptime(UTC_STRING,"%Y-%m-%d %H:%M:%S")) stamp -= time.timezone now = time.localtime() if now[8] == 1: stamp += 60*60 elif now[8] == -1: stamp -= 60*60 print 'UTC: ', time.gmtime(stamp) print 'Local: ', time.localtime(stamp) --- Results from New Zealand (GMT+12 dst=1) --- UTC: (2010, 3, 25, 2, 0, 0, 3, 84, 0) Local: (2010, 3, 25, 15, 0, 0, 3, 84, 1)

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  • 404 not found in telnet, works fine in browser

    - by Viranch Mehta
    i am having a very irritating problem, when i open a url ( http://celebs.widewallpapers.net/md/a/adriana-lima/1440/Adriana-Lima-1440x900-002.jpg ) in browser, it works fine.. but when i try to access it by telnet on bash, i get 404 not found!! my exact terminal: $ telnet celebs.widewallpapers.net 80 HEAD /md/a/adriana-lima/1440/Adriana-Lima-1440x900-002.jpg HTTP/1.0 [enter] [enter] HTTP/1.1 404 Not Found Server: nginx Date: Sun, 23 May 2010 21:36:05 GMT Content-Type: text/html; charset=windows-1251 Content-Length: 166 Connection: close please help me with this as i m trying to make a C batch-downloader, which is almost working as same as the telnet.

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  • How do I automatically rebuild the Sphinx index under django-sphinx?

    - by Apreche
    I just setup django-sphinx, and it is working beautifully. I am now able to search my model and get amazing results. The one problem is that I have to build the index by hand using the indexer command. That means every time I add new content, I have to manually hit the command line to rebuild the search index. That is just not acceptable. I could make a cron job that automatically runs the indexer command every so often, but that's far from optimal. New data won't be indexed until the cron runs again. In addition, the indexer will run unnecessarily most times as my site doesn't have data being added very often. How do I set it up so that the Sphinx index will automatically rebuild itself whenever data is added to or modified in a searchable django model?

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  • PyML 0.7.2 - How to prevent accuracy from dropping after storing/loading a classifier?

    - by Michael Aaron Safyan
    This is a followup from "Save PyML.classifiers.multi.OneAgainstRest(SVM()) object?". The solution to that question was close, but not quite right, (the SparseDataSet is broken, so attempting to save/load with that dataset container type will fail, no matter what. Also, PyML is inconsistent in terms of whether labels should be numbers or strings... it turns out that the oneAgainstRest function is actually not good enough, because the labels need to be strings and simultaneously convertible to floats, because there are places where it is assumed to be a string and elsewhere converted to float) and so after a great deal of hacking and such I was finally able to figure out a way to save and load my multi-class classifier without it blowing up with an error.... however, although it is no longer giving me an error message, it is still not quite right as the accuracy of the classifier drops significantly when it is saved and then reloaded (so I'm still missing a piece of the puzzle). I am currently using the following custom mutli-class classifier for training, saving, and loading: class SVM(object): def __init__(self,features_or_filename,labels=None,kernel=None): if isinstance(features_or_filename,str): filename=features_or_filename; if labels!=None: raise ValueError,"Labels must be None if loading from a file."; with open(os.path.join(filename,"uniquelabels.list"),"rb") as uniquelabelsfile: self.uniquelabels=sorted(list(set(pickle.load(uniquelabelsfile)))); self.labeltoindex={}; for idx,label in enumerate(self.uniquelabels): self.labeltoindex[label]=idx; self.classifiers=[]; for classidx, classname in enumerate(self.uniquelabels): self.classifiers.append(PyML.classifiers.svm.loadSVM(os.path.join(filename,str(classname)+".pyml.svm"),datasetClass = PyML.VectorDataSet)); else: features=features_or_filename; if labels==None: raise ValueError,"Labels must not be None when training."; self.uniquelabels=sorted(list(set(labels))); self.labeltoindex={}; for idx,label in enumerate(self.uniquelabels): self.labeltoindex[label]=idx; points = [[float(xij) for xij in xi] for xi in features]; self.classifiers=[PyML.SVM(kernel) for label in self.uniquelabels]; for i in xrange(len(self.uniquelabels)): currentlabel=self.uniquelabels[i]; currentlabels=['+1' if k==currentlabel else '-1' for k in labels]; currentdataset=PyML.VectorDataSet(points,L=currentlabels,positiveClass='+1'); self.classifiers[i].train(currentdataset,saveSpace=False); def accuracy(self,pts,labels): logger=logging.getLogger("ml"); correct=0; total=0; classindexes=[self.labeltoindex[label] for label in labels]; h=self.hypotheses(pts); for idx in xrange(len(pts)): if h[idx]==classindexes[idx]: logger.info("RIGHT: Actual \"%s\" == Predicted \"%s\"" %(self.uniquelabels[ classindexes[idx] ], self.uniquelabels[ h[idx] ])); correct+=1; else: logger.info("WRONG: Actual \"%s\" != Predicted \"%s\"" %(self.uniquelabels[ classindexes[idx] ], self.uniquelabels[ h[idx] ])) total+=1; return float(correct)/float(total); def prediction(self,pt): h=self.hypothesis(pt); if h!=None: return self.uniquelabels[h]; return h; def predictions(self,pts): h=self.hypotheses(self,pts); return [self.uniquelabels[x] if x!=None else None for x in h]; def hypothesis(self,pt): bestvalue=None; bestclass=None; dataset=PyML.VectorDataSet([pt]); for classidx, classifier in enumerate(self.classifiers): val=classifier.decisionFunc(dataset,0); if (bestvalue==None) or (val>bestvalue): bestvalue=val; bestclass=classidx; return bestclass; def hypotheses(self,pts): bestvalues=[None for pt in pts]; bestclasses=[None for pt in pts]; dataset=PyML.VectorDataSet(pts); for classidx, classifier in enumerate(self.classifiers): for ptidx in xrange(len(pts)): val=classifier.decisionFunc(dataset,ptidx); if (bestvalues[ptidx]==None) or (val>bestvalues[ptidx]): bestvalues[ptidx]=val; bestclasses[ptidx]=classidx; return bestclasses; def save(self,filename): if not os.path.exists(filename): os.makedirs(filename); with open(os.path.join(filename,"uniquelabels.list"),"wb") as uniquelabelsfile: pickle.dump(self.uniquelabels,uniquelabelsfile,pickle.HIGHEST_PROTOCOL); for classidx, classname in enumerate(self.uniquelabels): self.classifiers[classidx].save(os.path.join(filename,str(classname)+".pyml.svm")); I am using the latest version of PyML (0.7.2, although PyML.__version__ is 0.7.0). When I construct the classifier with a training dataset, the reported accuracy is ~0.87. When I then save it and reload it, the accuracy is less than 0.001. So, there is something here that I am clearly not persisting correctly, although what that may be is completely non-obvious to me. Would you happen to know what that is?

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  • Unexplained file not found for an existing file

    - by knishua
    Following is the error that occurs in this part of the code. Although the path is valid, a RuntimeError occurs—strange. What is happening, and how can I get this to work? for root,dirs,files in os.walk(self.path): for f in files : if (f.split('.')[1] == "mb"): z = utils.executeInMainThreadWithResult(self.contains,(f.split('.')[0])) if not (isinstance(z,NoneType)): cmds.symbolButton(self.arSubCategory + f.split('.')[0], image=(z[1].replace("\\","/")), width = 35,height = 70, c = "h.imp_file(" + "\"" + root.replace("\\","/") + "/" + f + "\"" + ")") def contains(self,imageName): print 'imageName : ',imageName,'\n' for root, dirs, files in os.walk(self.path+"images"): for g in files: x = re.search(imageName,g) if not (isinstance(x, NoneType)): print 'g ',root+"/"+g.replace("\\","/"),'\n' return (1,(root+"/"+g)) Error: # z is (1, 'T:/Reference_Library/Reference_work/Char_models/Workfiles/images\\rboxdisk1\\female\\highpoly/granny01_highpoly.jpg') Error: File not found: T:/Reference_Library/Reference_work/Char_models/Workfiles/images/rboxdisk1/female/highpoly/granny01_highpoly.jpg Traceback (most recent call last): File "<maya console>", line 115, in <module> File "<maya console>", line 65, in showWindowanimLibrary RuntimeError: File not found: T:/Reference_Library/Reference_work/Char_models/Workfiles/images/rboxdisk1/female/highpoly/granny01_highpoly.jpg

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  • pyODBC and Unicode Problem

    - by Aviv Giladi
    Hey guys, I'm working with pyODBC communicate with a MS SQL 2005 Express server. The table to which i'm trying to save the data consists of nvarchar columns. query = u"INSERT INTO tblPersons (name, birthday, gender) VALUES('" query = query + name + u"', '" query = query + birthday + u"', '" query = query + gender + u"')" cur.execute(query ) The variables name, birthrday and gende are read from an Excel file and they are Unicode strings. When I execute the query and either look at the table with SQL Server Management Studio or execute a query that fetches the data that was just inserted, all the data that was written in a non-English languages turn into question marks. The data that was written in English is preserved and appears in the table in the correct way. I tried adding CHARSET=UTF16 to my connection string, but had no luck with that. I can use UTF-8 which works fine but as a working convention, I need all the data saved in my DB to be UTF16. Thanks!

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  • Issue reading packets from a pcap file. dpkt module. What gives?

    - by Chris
    I am running the following test script to try to read packets from a sample .pcap file I have downloaded. It won't seem to run. I have all of the modules, but no examples seem to be running. import socket import dpkt import sys pcapReader = dpkt.pcap.Reader(file("test1.pcap", "rb")) for ts, data in pcapReader: ether = dpkt.ethernet.Ethernet(data) if ether.type != dpkt.ethernet.ETH_TYPE_IP: raise ip = ether.data src = socket.inet_ntoa(ip.src) dst = socket.inet_ntoa(ip.dst) print "%s -> %s" % (src, dst) For some reason, this is not being interpreted properly. When running it, I get KeyError: 138 module body in test.py at line 4 function __init__ in pcap.py at line 105 Program exited. Why is this? What's wrong?

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  • Installing PySide - OSX

    - by jeremynealbrown
    Anyone had success installing and using PySide on OSX? I am following the install instructions on the PySide site, though I'm running into issues building the API Extractor. I run cmake on the CMakeLists.txt file inside the api extractor dir and: This error is thrown- CMake Error at /Applications/CMake 2.8-0.app/Contents/share/cmake-2.8/Modules/FindBoost.cmake:894 (message): Unable to find the requested Boost libraries. Unable to find the Boost header files. Please set BOOST_ROOT to the root directory containing Boost or BOOST_INCLUDEDIR to the directory containing Boost's headers. Call Stack (most recent call first): CMakeLists.txt:5 (find_package) I am new to building source w/ cmake and I'm not event really sure what Boost is. Any light you might shed on the set up process would be great. Thanks

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  • Django TestCase testing order

    - by ziang
    If there are several methods in the test class, I found that the order to execute is alphabetical. But I want to customize the order of execution. How to define the execution order? For example: testTestA will be loaded first than testTestB. class Test(TestCase): def setUp(self): ... def testTestB(self): #test code def testTestA(self): #test code

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  • PyOpenGL - passing transformation matrix into shader

    - by M-V
    I am having trouble passing projection and modelview matrices into the GLSL shader from my PyOpenGL code. My understanding is that OpenGL matrices are column major, but when I pass in projection and modelview matrices as shown, I don't see anything. I tried the transpose of the matrices, and it worked for the modelview matrix, but the projection matrix doesn't work either way. Here is the code: import OpenGL from OpenGL.GL import * from OpenGL.GL.shaders import * from OpenGL.GLU import * from OpenGL.GLUT import * from OpenGL.GLUT.freeglut import * from OpenGL.arrays import vbo import numpy, math, sys strVS = """ attribute vec3 aVert; uniform mat4 uMVMatrix; uniform mat4 uPMatrix; uniform vec4 uColor; varying vec4 vCol; void main() { // option #1 - fails gl_Position = uPMatrix * uMVMatrix * vec4(aVert, 1.0); // option #2 - works gl_Position = vec4(aVert, 1.0); // set color vCol = vec4(uColor.rgb, 1.0); } """ strFS = """ varying vec4 vCol; void main() { // use vertex color gl_FragColor = vCol; } """ # particle system class class Scene: # initialization def __init__(self): # create shader self.program = compileProgram(compileShader(strVS, GL_VERTEX_SHADER), compileShader(strFS, GL_FRAGMENT_SHADER)) glUseProgram(self.program) self.pMatrixUniform = glGetUniformLocation(self.program, 'uPMatrix') self.mvMatrixUniform = glGetUniformLocation(self.program, "uMVMatrix") self.colorU = glGetUniformLocation(self.program, "uColor") # attributes self.vertIndex = glGetAttribLocation(self.program, "aVert") # color self.col0 = [1.0, 1.0, 0.0, 1.0] # define quad vertices s = 0.2 quadV = [ -s, s, 0.0, -s, -s, 0.0, s, s, 0.0, s, s, 0.0, -s, -s, 0.0, s, -s, 0.0 ] # vertices self.vertexBuffer = glGenBuffers(1) glBindBuffer(GL_ARRAY_BUFFER, self.vertexBuffer) vertexData = numpy.array(quadV, numpy.float32) glBufferData(GL_ARRAY_BUFFER, 4*len(vertexData), vertexData, GL_STATIC_DRAW) # render def render(self, pMatrix, mvMatrix): # use shader glUseProgram(self.program) # set proj matrix glUniformMatrix4fv(self.pMatrixUniform, 1, GL_FALSE, pMatrix) # set modelview matrix glUniformMatrix4fv(self.mvMatrixUniform, 1, GL_FALSE, mvMatrix) # set color glUniform4fv(self.colorU, 1, self.col0) #enable arrays glEnableVertexAttribArray(self.vertIndex) # set buffers glBindBuffer(GL_ARRAY_BUFFER, self.vertexBuffer) glVertexAttribPointer(self.vertIndex, 3, GL_FLOAT, GL_FALSE, 0, None) # draw glDrawArrays(GL_TRIANGLES, 0, 6) # disable arrays glDisableVertexAttribArray(self.vertIndex) class Renderer: def __init__(self): pass def reshape(self, width, height): self.width = width self.height = height self.aspect = width/float(height) glViewport(0, 0, self.width, self.height) glEnable(GL_DEPTH_TEST) glDisable(GL_CULL_FACE) glClearColor(0.8, 0.8, 0.8,1.0) glutPostRedisplay() def keyPressed(self, *args): sys.exit() def draw(self): glClear(GL_COLOR_BUFFER_BIT | GL_DEPTH_BUFFER_BIT) # build projection matrix fov = math.radians(45.0) f = 1.0/math.tan(fov/2.0) zN, zF = (0.1, 100.0) a = self.aspect pMatrix = numpy.array([f/a, 0.0, 0.0, 0.0, 0.0, f, 0.0, 0.0, 0.0, 0.0, (zF+zN)/(zN-zF), -1.0, 0.0, 0.0, 2.0*zF*zN/(zN-zF), 0.0], numpy.float32) # modelview matrix mvMatrix = numpy.array([1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.5, 0.0, -5.0, 1.0], numpy.float32) # render self.scene.render(pMatrix, mvMatrix) # swap buffers glutSwapBuffers() def run(self): glutInitDisplayMode(GLUT_RGBA) glutInitWindowSize(400, 400) self.window = glutCreateWindow("Minimal") glutReshapeFunc(self.reshape) glutDisplayFunc(self.draw) glutKeyboardFunc(self.keyPressed) # Checks for key strokes self.scene = Scene() glutMainLoop() glutInit(sys.argv) prog = Renderer() prog.run() When I use option #2 in the shader without either matrix, I get the following output: What am I doing wrong?

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  • Bug when drawing a QImage on a widget with PIL and PyQt

    - by oulipo
    I'm trying to write a small graphic application, and I need to construct some image using PIL that I show in a widget. The image is correctly constructed (I can check with im.show()), I can convert it to a QImage, that I can save normally to disk (using QImage.save), but if I try to draw it directly on my QWidget, it only show a white square. Here I commented out the code that is not working (converting the Image into QImage then QPixmap result in a white square), and I made a dirty hack to save the image to a temporary file and load it directly in a QPixmap, which work but is not what I want to do https://gist.github.com/f6d479f286ad75bf72b7 Someone has an idea? If it can help, when I try to save my QImage in a BMP file, I can access its content, but if I try to save it to a PNG it is completely white

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  • SQL Alchemy related Objects Error

    - by alex
    from sqlalchemy.orm import relation, backref from sqlalchemy import Table, Column, Integer, String, MetaData, ForeignKey, Date, Sequence from sqlalchemy.ext.declarative import declarative_base Base = declarative_base() class GUI_SCENARIO(Base): __tablename__ = 'GUI_SCENARIO' Scenario_ID = Column(Integer, primary_key=True) Definition_Date = Column(Date) guiScenarioDefinition = relation('GUI_SCENARIO_DEFINITION', order_by='GUI_SCENARIO_DEFINITION.Scenario_Definition_ID', backref='guiScenario') def __init__(self, Scenario_ID=None, Definition_Date=None): self.Scenario_ID = Scenario_ID self.Definition_Date = Definition_Date class GUI_SCENARIO_DEFINITION(Base): __tablename__='GUI_SCENARIO_DEFINITION' Scenario_Definition_ID = Column(Integer, Sequence('Scenario_Definition_ID_SEQ'), primary_key=True) Scenario_FK = Column(Integer, ForeignKey('GUI_SCENARIO.Scenario_ID')) Definition_Date=Column(Date) guiScenario = relation(GUI_SCENARIO, backref=backref('guiScenarioDefinition', order_by=Scenario_Definition_ID)) def __init__(self, Scenario_FK, Definition_Date): self.Scenario_FK = Scenario_FK self.Definition_Date = Definition_Date guiScenario = relation(GUI_SCENARIO, backref=backref('guiScenarioDefinition', order_by=Scenario_Definition_ID)) tableNameScenario = "GUI_SCENARIO" scenarioClass = getattr(MappingTablesScenario, tableNameScenario) tableScenario = Table(tableNameScenario, meta, autoload=True) mapper(scenarioClass, tableScenario) scenarioName = scenarioDefinition.name scenarioDefinitionDate = datetime.today() newScenario = MappingTablesScenario.GUI_SCENARIO(scenarioName, scenarioDefinitionDate) print newScenario.guiScenarioDefinition If I try to get the objects related to a scenarioObject, I always get this error: AttributeError: 'GUI_SCENARIO' object has no attribute 'guiScenarioDefinition' Does anyone know, why I get this error?

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  • pycurl script can't login to website

    - by The Jug
    I'm currently trying to get a grasp on pycurl. I'm attempting to login to my own website. After logging into the site it should redirect to the main page. However when trying this script it just gets returned to the login page. What might I be doing wrong? import pycurl import urllib import StringIO import pycurl pf = {'username' : 'user', 'password' : 'pass' } fields = urllib.urlencode(pf) pageContents = StringIO.StringIO() p = pycurl.Curl() p.setopt(pycurl.FOLLOWLOCATION, 1) p.setopt(pycurl.COOKIEFILE, './cookie_test.txt') p.setopt(pycurl.COOKIEJAR, './cookie_test.txt') p.setopt(pycurl.POST, 1) p.setopt(pycurl.POSTFIELDS, fields) p.setopt(pycurl.WRITEFUNCTION, pageContents.write) p.setopt(pycurl.URL, 'http://localhost') p.perform() pageContents.seek(0) print pageContents.readlines()

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  • Is it possible to use Regex through Hexadecimal to find email addresses

    - by LukeJenx
    Not sure if this is even possible but I have been looking at using Regex to get an email address that is in Hex. Basically this is to build up some of my automated forensic tools but I am having problems on making a suitable Regex algorithm. Regex for email: /^([a-z0-9_.-]+)@([\da-z.-]+).([a-z.]{2,6})$/ Hex values: @ = 40 . = 2E .com = 636f6d _ = 5f A/a = 41/61 [1] Z/z = 5a/7a - = 2d This is what I have got at the moment (it only takes into account lower case and .com). But it doesn't work! Have I messed something simple up? "/^([61-7a]+)40([61-7a]+)23(636f6d)$/" [1] I know email can only be lower case but I need to take uppercase into account too.

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