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  • Python - calculate multinomial probability density functions on large dataset?

    - by Seafoid
    Hi, I originally intended to use MATLAB to tackle this problem but the inbuilt functions has limitations that do not suit my goal. The same limitation occurs in NumPy. I have two tab-delimited files. The first is a file showing amino acid residue, frequency and count for an in-house database of protein structures, i.e. A 0.25 1 S 0.25 1 T 0.25 1 P 0.25 1 The second file consists of quadruplets of amino acids and the number of times they occur, i.e. ASTP 1 Note, there are 8,000 such quadruplets. Based on the background frequency of occurence of each amino acid and the count of quadruplets, I aim to calculate the multinomial probability density function for each quadruplet and subsequently use it as the expected value in a maximum likelihood calculation. The multinomial distribution is as follows: f(x|n, p) = n!/(x1!*x2!*...*xk!)*((p1^x1)*(p2^x2)*...*(pk^xk)) where x is the number of each of k outcomes in n trials with fixed probabilities p. n is 4 four in all cases in my calculation. I have created three functions to calculate this distribution. # functions for multinomial distribution def expected_quadruplets(x, y): expected = x*y return expected # calculates the probabilities of occurence raised to the number of occurrences def prod_prob(p1, a, p2, b, p3, c, p4, d): prob_prod = (pow(p1, a))*(pow(p2, b))*(pow(p3, c))*(pow(p4, d)) return prob_prod # factorial() and multinomial_coefficient() work in tandem to calculate C, the multinomial coefficient def factorial(n): if n <= 1: return 1 return n*factorial(n-1) def multinomial_coefficient(a, b, c, d): n = 24.0 multi_coeff = (n/(factorial(a) * factorial(b) * factorial(c) * factorial(d))) return multi_coeff The problem is how best to structure the data in order to tackle the calculation most efficiently, in a manner that I can read (you guys write some cryptic code :-)) and that will not create an overflow or runtime error. To data my data is represented as nested lists. amino_acids = [['A', '0.25', '1'], ['S', '0.25', '1'], ['T', '0.25', '1'], ['P', '0.25', '1']] quadruplets = [['ASTP', '1']] I initially intended calling these functions within a nested for loop but this resulted in runtime errors or overfloe errors. I know that I can reset the recursion limit but I would rather do this more elegantly. I had the following: for i in quadruplets: quad = i[0].split(' ') for j in amino_acids: for k in quadruplets: for v in k: if j[0] == v: multinomial_coefficient(int(j[2]), int(j[2]), int(j[2]), int(j[2])) I haven'te really gotten to how to incorporate the other functions yet. I think that my current nested list arrangement is sub optimal. I wish to compare the each letter within the string 'ASTP' with the first component of each sub list in amino_acids. Where a match exists, I wish to pass the appropriate numeric values to the functions using indices. Is their a better way? Can I append the appropriate numbers for each amino acid and quadruplet to a temporary data structure within a loop, pass this to the functions and clear it for the next iteration? Thanks, S :-)

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  • Python performance: iteration and operations on nested lists

    - by J.J.
    Problem Hey folks. I'm looking for some advice on python performance. Some background on my problem: Given: A mesh of nodes of size (x,y) each with a value (0...255) starting at 0 A list of N input coordinates each at a specified location within the range (0...x, 0...y) Increment the value of the node at the input coordinate and the node's neighbors within range Z up to a maximum of 255. Neighbors beyond the mesh edge are ignored. (No wrapping) BASE CASE: A mesh of size 1024x1024 nodes, with 400 input coordinates and a range Z of 75 nodes. Processing should be O(x*y*Z*N). I expect x, y and Z to remain roughly around the values in the base case, but the number of input coordinates N could increase up to 100,000. My goal is to minimize processing time. Current results I have 2 current implementations: f1, f2 Running speed on my 2.26 GHz Intel Core 2 Duo with Python 2.6.1: f1: 2.9s f2: 1.8s f1 is the initial naive implementation: three nested for loops. f2 is replaces the inner for loop with a list comprehension. Code is included below for your perusal. Question How can I further reduce the processing time? I'd prefer sub-1.0s for the test parameters. Please, keep the recommendations to native Python. I know I can move to a third-party package such as numpy, but I'm trying to avoid any third party packages. Also, I've generated random input coordinates, and simplified the definition of the node value updates to keep our discussion simple. The specifics have to change slightly and are outside the scope of my question. thanks much! f1 is the initial naive implementation: three nested for loops. 2.9s def f1(x,y,n,z): rows = [] for i in range(x): rows.append([0 for i in xrange(y)]) for i in range(n): inputX, inputY = (int(x*random.random()), int(y*random.random())) topleft = (inputX - z, inputY - z) for i in xrange(max(0, topleft[0]), min(topleft[0]+(z*2), x)): for j in xrange(max(0, topleft[1]), min(topleft[1]+(z*2), y)): if rows[i][j] <= 255: rows[i][j] += 1 f2 is replaces the inner for loop with a list comprehension. 1.8s def f2(x,y,n,z): rows = [] for i in range(x): rows.append([0 for i in xrange(y)]) for i in range(n): inputX, inputY = (int(x*random.random()), int(y*random.random())) topleft = (inputX - z, inputY - z) for i in xrange(max(0, topleft[0]), min(topleft[0]+(z*2), x)): l = max(0, topleft[1]) r = min(topleft[1]+(z*2), y) rows[i][l:r] = [j+1 for j in rows[i][l:r] if j < 255]

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  • wxpython - Nested Notebooks

    - by madtowneast
    I have been trying to make my nested notebooks a little bit more appealing code wise. At the moment, I got this #!/usr/bin/env python import os import sys import datetime import numpy as np from readmonifile import MonitorFile from sortmonifile import sort import wx class NestedPanelOne(wx.Panel): #---------------------------------------------------------------------- # First notebook that creates the tab to select the component number #---------------------------------------------------------------------- def __init__(self, parent, label, data): wx.Panel.__init__(self, parent=parent, id=wx.ID_ANY) sizer = wx.BoxSizer(wx.VERTICAL) #Loop creating the tabs according to the component name nestedNotebook = wx.Notebook(self, wx.ID_ANY) for slabel in sorted(data[label].keys()): tab = NestedPanelTwo(nestedNotebook, label, slabel, data) nestedNotebook.AddPage(tab,slabel) sizer = wx.BoxSizer(wx.VERTICAL) sizer.Add(nestedNotebook, 1, wx.ALL|wx.EXPAND, 5) self.SetSizer(sizer) class NestedPanelTwo(wx.Panel): #------------------------------------------------------------------------------ # Second notebook that creates the tab to select the main monitoring variables #------------------------------------------------------------------------------ def __init__(self, parent, label, slabel, data): wx.Panel.__init__(self, parent=parent, id=wx.ID_ANY) sizer = wx.BoxSizer(wx.VERTICAL) nestedNotebook = wx.Notebook(self, wx.ID_ANY) for sslabel in sorted(data[label][slabel][data[label][slabel].keys()[0]].keys()): tab = NestedPanelThree(nestedNotebook, label, slabel, sslabel, data) nestedNotebook.AddPage(tab, sslabel) sizer.Add(nestedNotebook, 1, wx.ALL|wx.EXPAND, 5) self.SetSizer(sizer) class NestedPanelThree(wx.Panel): #------------------------------------------------------------------------------- # Third notebook that creates checkboxes to select the monitoring sub-variables #------------------------------------------------------------------------------- def __init__(self, parent, label, slabel, sslabel, data): wx.Panel.__init__(self, parent=parent, id=wx.ID_ANY) labels=[] chbox =[] chboxdict={} for ssslabel in sorted(data[label][slabel][data[label][slabel].keys()[0]][sslabel].keys()): labels.append(ssslabel) for item in list(set(labels)): cb = wx.CheckBox(self, -1, item) chbox.append(cb) chboxdict[item]=cb gridSizer = wx.GridSizer(np.shape(list(set(labels)))[0],3, 5, 5) gridSizer.AddMany(chbox) self.SetSizer(gridSizer) ######################################################################## class NestedNotebookDemo(wx.Notebook): #--------------------------------------------------------------------------------- # Main notebook creating tabs for the monitored components #--------------------------------------------------------------------------------- def __init__(self, parent, data): wx.Notebook.__init__(self, parent, id=wx.ID_ANY, style= wx.BK_DEFAULT ) for label in sorted(data.keys()): print label tab = NestedPanelOne(self,label, data) self.AddPage(tab, label) ######################################################################## class DemoFrame(wx.Frame): #---------------------------------------------------------------------- # Putting it all together #---------------------------------------------------------------------- def __init__(self,data): wx.Frame.__init__(self, None, wx.ID_ANY, "pDAQ monitoring plotting tool", size=(800,400) ) panel = wx.Panel(self) notebook = NestedNotebookDemo(panel, data) sizer = wx.BoxSizer(wx.VERTICAL) sizer.Add(notebook, 1, wx.ALL|wx.EXPAND, 5) panel.SetSizer(sizer) self.Layout() #Menu Bar to be added later ''' menubar = wx.MenuBar() file = wx.Menu() file.Append(1, '&Quit', 'Exit Tool') menubar.Append(file, '&File') self.SetMenuBar(menubar) self.Bind(wx.EVT_MENU, self.OnClose, id=1) ''' self.Show() #---------------------------------------------------------------------- if __name__ == "__main__": if len(sys.argv) == 1: raise SystemExit("Please specify a file to process") for f in sys.argv[1:]: data=sort.sorting(f) print data['stringHub'].keys() print data.keys() print data[data.keys()[0]].keys() print 'test' app = wx.PySimpleApp() frame = DemoFrame(data) app.MainLoop() print 'testend' and I would like to reduce this whole mess into something that only has three nested for loops, so something like for label in sorted(data.keys()): self.SubNoteBooks[label] = wx.Notebook(self.Notebook, wx.ID_ANY) self.Notebook.AddPage(self.SubNoteBooks[label], label) for slabel in sorted(data[label].keys()): self.SubNoteBooks[label][slabel] = wx.Notebook(self, wx.ID_ANY) self.SubNoteBooks[label].AddPage(self.SubNoteBooks[label][slabel], slabel) for sslabel in sorted(data[label][slabel][data[label][slabel].keys()[0]].keys()): self.SubNoteBooks[label][slabel][sslabel] = wx.Notebook(self.Notebook, wx.ID_ANY) self.Notebook.AddPage(self.SubNoteBooks[label][slabel][sslabel], sslabel) I have been trying to fiddle this around but the problem seems to be the line self.SubNoteBooks[label][slabel] = wx.Notebook(self, wx.ID_ANY) I get the error: Traceback (most recent call last): File "./reducelinenumbers.py", line 162, in <module> frame = DemoFrame(data) File "./reducelinenumbers.py", line 126, in __init__ self.SubNoteBooks[label][slabel] = wx.Notebook(self, wx.ID_ANY) TypeError: 'Notebook' object does not support item assignment I understand why notebook is being type raises a TypeError here. Is there a way around this? Thanks a bunch in advance.

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  • What is the wrong of this converted code?

    - by Gum Slashy
    I'm developing shape identification project using javacv and I have found some opencv code to identify U shapes in particular image and I have try to convert it in to javacv but it doesn't provide same out put. Can you please help me to convert this opencv code into javacv? This is Opencv code import cv2 import numpy as np img = cv2.imread('sofud.jpg') gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) ret,thresh = cv2.threshold(gray,127,255,1) contours,hierarchy = cv2.findContours(thresh,cv2.RETR_LIST,cv2.CHAIN_APPROX_SIMPLE) for cnt in contours: x,y,w,h = cv2.boundingRect(cnt) if 10 < w/float(h) or w/float(h) < 0.1: cv2.rectangle(img,(x,y),(x+w,y+h),(0,0,255),2) cv2.imshow('res',img) cv2.waitKey(0) cv2.destroyAllWindows() This is the expected output This is the code that I have converted import com.googlecode.javacpp.Loader; import com.googlecode.javacv.CanvasFrame; import static com.googlecode.javacpp.Loader.*; import static com.googlecode.javacv.cpp.opencv_core.*; import static com.googlecode.javacv.cpp.opencv_imgproc.*; import static com.googlecode.javacv.cpp.opencv_highgui.*; import java.io.File; import javax.swing.JFileChooser; public class TestBeam { public static void main(String[] args) { CvMemStorage storage=CvMemStorage.create(); CvSeq squares = new CvContour(); squares = cvCreateSeq(0, sizeof(CvContour.class), sizeof(CvSeq.class), storage); JFileChooser f=new JFileChooser(); int result=f.showOpenDialog(f);//show dialog box to choose files File myfile=null; String path=""; if(result==0){ myfile=f.getSelectedFile();//selected file taken to myfile path=myfile.getAbsolutePath();//get the path of the file } IplImage src = cvLoadImage(path);//hear path is actual path to image IplImage grayImage = IplImage.create(src.width(), src.height(), IPL_DEPTH_8U, 1); cvCvtColor(src, grayImage, CV_RGB2GRAY); cvThreshold(grayImage, grayImage, 127, 255, CV_THRESH_BINARY); CvSeq cvSeq=new CvSeq(); CvMemStorage memory=CvMemStorage.create(); cvFindContours(grayImage, memory, cvSeq, Loader.sizeof(CvContour.class), CV_RETR_CCOMP, CV_CHAIN_APPROX_SIMPLE); System.out.println(cvSeq.total()); for (int i = 0; i < cvSeq.total(); i++) { CvRect rect=cvBoundingRect(cvSeq, i); int x=rect.x(),y=rect.y(),h=rect.height(),w=rect.width(); if (10 < (w/h) || (w/h) < 0.1){ cvRectangle(src, cvPoint(x, y), cvPoint(x+w, y+h), CvScalar.RED, 1, CV_AA, 0); //cvSeqPush(squares, rect); } } CanvasFrame cnvs=new CanvasFrame("Beam"); cnvs.setDefaultCloseOperation(javax.swing.JFrame.EXIT_ON_CLOSE); cnvs.showImage(src); //cvShowImage("Final ", src); } } This is the out put that I got please can some one help me to solve this problem ?

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  • OpenCV install problems on Studio 12.04 - broken dependencies

    - by Will
    I'm trying to follow the Ubuntu OpenCV documentation at OpenCV. The provided script has a line which executed for some time, taking away more packages than I expected (such as ubuntu-studio video); sudo apt-get -qq remove ffmpeg x264 libx264-dev When the script gets to the line below, it bombs; sudo apt-get -qq install libopencv-dev build-essential checkinstall cmake pkg-config yasm libtiff4-dev libjpeg-dev libjasper-dev libavcodec-dev libavformat-dev libswscale-dev libdc1394-22-dev libxine-dev libgstreamer0.10-dev libgstreamer-plugins-base0.10-dev libv4l-dev python-dev python-numpy libtbb-dev libqt4-dev libgtk2.0-dev libfaac-dev libmp3lame-dev libopencore-amrnb-dev libopencore-amrwb-dev libtheora-dev libvorbis-dev libxvidcore-dev x264 v4l-utils ffmpeg The error msg is; E: Unable to correct problems, you have held broken packages. I've since run Update-Manager, run sudo apt-get updates, rebooted, tried the above script line manually, and still no change. I've just run sudo apt-get install -f and nothing seemed to change. It did mention that some packages were no longer needed and could be removed by apt-get autoremove, so I ran that. It removed a number of packages, so I reran the install command above. Still same problem of held broken packages. I just ran sudo apt-get -u dist-upgrade Part of the response was; The following packages have been kept back: gstreamer0.10-ffmpeg I'm not sure what that means. I do know that it shows up in my Update-Manager and cannot be checked I then ran sudo dpkg --configure -a and then reran sudo apt-get -f install and the package was still not upgraded, though there was this very interesting comment; Some packages could not be installed. This may mean that you have requested an impossible situation or if you are using the unstable distribution that some required packages have not yet been created or been moved out of Incoming. The following information may help to resolve the situation: The following packages have unmet dependencies: gstreamer0.10-ffmpeg : Depends: libavcodec53 (< 5:0) but it is not going to be installed or libavcodec-extra-53 (< 5:0) but 5:0.7.2-1ubuntu1+codecs1~oneiric2 is to be installed E: Unable to correct problems, you have held broken packages. Then I ran sudo apt-get -u dist-upgrade It showed I had one held package, so I ran; sudo apt-get -o Debug::pkgProblemResolver=yes dist-upgrade It also exited without upgrading the package, so I ran; sudo apt-get remove --dry-run gstreamer0.10-ffmpeg:i386 And it gave me; *The following packages will be REMOVED: arista gstreamer0.10-ffmpeg 0 upgraded, 0 newly installed, 2 to remove and 0 not upgraded. Remv arista [0.9.7-3ubuntu1] Remv gstreamer0.10-ffmpeg [0.10.12-1ubuntu1]* But when I reran sudo apt-get -u dist-upgrade It showed the package was still there. *The following packages have been kept back: gstreamer0.10-ffmpeg 0 upgraded, 0 newly installed, 0 to remove and 1 not upgraded.* Update: Just went into Synaptic PM and completely removed gstreamer0.10-ffmpeg Reran sudo apt-get -u dist-upgrade And was told; 0 upgraded, 0 newly installed, 0 to remove and 0 not upgraded. However, when I ran the original apt-get to install opencv (first code at the top of this question), it still gave me the same broken package errors. So I tried $ cat /etc/apt/sources.list # # deb cdrom:[Ubuntu-Studio 11.10 _Oneiric Ocelot_ - Release i386 (20111011.1)]/ oneiric main multiverse restricted universe # deb cdrom:[Ubuntu-Studio 11.10 _Oneiric Ocelot_ - Release i386 (20111011.1)]/ oneiric main multiverse restricted universe # See http://help.ubuntu.com/community/UpgradeNotes for how to upgrade to # newer versions of the distribution. deb http://us.archive.ubuntu.com/ubuntu/ precise main restricted deb-src http://us.archive.ubuntu.com/ubuntu/ precise main restricted ## Major bug fix updates produced after the final release of the ## distribution. deb http://us.archive.ubuntu.com/ubuntu/ precise-updates main restricted deb-src http://us.archive.ubuntu.com/ubuntu/ precise-updates main restricted ## N.B. software from this repository is ENTIRELY UNSUPPORTED by the Ubuntu ## team. Also, please note that software in universe WILL NOT receive any ## review or updates from the Ubuntu security team. deb http://us.archive.ubuntu.com/ubuntu/ precise universe deb-src http://us.archive.ubuntu.com/ubuntu/ precise universe deb http://us.archive.ubuntu.com/ubuntu/ precise-updates universe deb-src http://us.archive.ubuntu.com/ubuntu/ precise-updates universe ## N.B. software from this repository is ENTIRELY UNSUPPORTED by the Ubuntu ## team, and may not be under a free licence. Please satisfy yourself as to ## your rights to use the software. Also, please note that software in ## multiverse WILL NOT receive any review or updates from the Ubuntu ## security team. deb http://us.archive.ubuntu.com/ubuntu/ precise multiverse deb-src http://us.archive.ubuntu.com/ubuntu/ precise multiverse deb http://us.archive.ubuntu.com/ubuntu/ precise-updates multiverse deb-src http://us.archive.ubuntu.com/ubuntu/ precise-updates multiverse ## N.B. software from this repository may not have been tested as ## extensively as that contained in the main release, although it includes ## newer versions of some applications which may provide useful features. ## Also, please note that software in backports WILL NOT receive any review ## or updates from the Ubuntu security team. deb http://security.ubuntu.com/ubuntu precise-security main restricted deb-src http://security.ubuntu.com/ubuntu precise-security main restricted deb http://security.ubuntu.com/ubuntu precise-security universe deb-src http://security.ubuntu.com/ubuntu precise-security universe deb http://security.ubuntu.com/ubuntu precise-security multiverse deb-src http://security.ubuntu.com/ubuntu precise-security multiverse ## Uncomment the following two lines to add software from Canonical's ## 'partner' repository. ## This software is not part of Ubuntu, but is offered by Canonical and the ## respective vendors as a service to Ubuntu users. deb http://archive.canonical.com/ubuntu precise partner # deb-src http://archive.canonical.com/ubuntu oneiric partner ## Uncomment the following two lines to add software from Ubuntu's ## 'extras' repository. ## This software is not part of Ubuntu, but is offered by third-party ## developers who want to ship their latest software. # deb http://extras.ubuntu.com/ubuntu oneiric main # deb-src http://extras.ubuntu.com/ubuntu oneiric main # deb http://download.opensuse.org/repositories/home:/popinet/xUbuntu_11.04 ./ # disabled on upgrade to precise and then; $ cat /etc/apt/sources.list.d/* But I don't have enough reputation to post the results here (it says I need at least 10 reputation points to post more than 2 links), so I don't know how to provide the requested feedback. Then tried; $ sudo apt-get check [sudo] password for <abcd>: Reading package lists... Done Building dependency tree Reading state information... Done However, no resolution of the problem yet. What else do I need to do? Will an upgrade to Ubuntu Studio 13.xx solve this problem (or compound it)?

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  • python: what are efficient techniques to deal with deeply nested data in a flexible manner?

    - by AlexandreS
    My question is not about a specific code snippet but more general, so please bear with me: How should I organize the data I'm analyzing, and which tools should I use to manage it? I'm using python and numpy to analyse data. Because the python documentation indicates that dictionaries are very optimized in python, and also due to the fact that the data itself is very structured, I stored it in a deeply nested dictionary. Here is a skeleton of the dictionary: the position in the hierarchy defines the nature of the element, and each new line defines the contents of a key in the precedent level: [AS091209M02] [AS091209M01] [AS090901M06] ... [100113] [100211] [100128] [100121] [R16] [R17] [R03] [R15] [R05] [R04] [R07] ... [1263399103] ... [ImageSize] [FilePath] [Trials] [Depth] [Frames] [Responses] ... [N01] [N04] ... [Sequential] [Randomized] [Ch1] [Ch2] Edit: To explain a bit better my data set: [individual] ex: [AS091209M02] [imaging session (date string)] ex: [100113] [Region imaged] ex: [R16] [timestamp of file] ex [1263399103] [properties of file] ex: [Responses] [regions of interest in image ] ex [N01] [format of data] ex [Sequential] [channel of acquisition: this key indexes an array of values] ex [Ch1] The type of operations I perform is for instance to compute properties of the arrays (listed under Ch1, Ch2), pick up arrays to make a new collection, for instance analyze responses of N01 from region 16 (R16) of a given individual at different time points, etc. This structure works well for me and is very fast, as promised. I can analyze the full data set pretty quickly (and the dictionary is far too small to fill up my computer's ram : half a gig). My problem comes from the cumbersome manner in which I need to program the operations of the dictionary. I often have stretches of code that go like this: for mk in dic.keys(): for rgk in dic[mk].keys(): for nk in dic[mk][rgk].keys(): for ik in dic[mk][rgk][nk].keys(): for ek in dic[mk][rgk][nk][ik].keys(): #do something which is ugly, cumbersome, non reusable, and brittle (need to recode it for any variant of the dictionary). I tried using recursive functions, but apart from the simplest applications, I ran into some very nasty bugs and bizarre behaviors that caused a big waste of time (it does not help that I don't manage to debug with pdb in ipython when I'm dealing with deeply nested recursive functions). In the end the only recursive function I use regularly is the following: def dicExplorer(dic, depth = -1, stp = 0): '''prints the hierarchy of a dictionary. if depth not specified, will explore all the dictionary ''' if depth - stp == 0: return try : list_keys = dic.keys() except AttributeError: return stp += 1 for key in list_keys: else: print '+%s> [\'%s\']' %(stp * '---', key) dicExplorer(dic[key], depth, stp) I know I'm doing this wrong, because my code is long, noodly and non-reusable. I need to either use better techniques to flexibly manipulate the dictionaries, or to put the data in some database format (sqlite?). My problem is that since I'm (badly) self-taught in regards to programming, I lack practical experience and background knowledge to appreciate the options available. I'm ready to learn new tools (SQL, object oriented programming), whatever it takes to get the job done, but I am reluctant to invest my time and efforts into something that will be a dead end for my needs. So what are your suggestions to tackle this issue, and be able to code my tools in a more brief, flexible and re-usable manner?

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  • matplotlib and python multithread file processing

    - by Napseis
    I have a large number of files to process. I have written a script that get, sort and plot the datas I want. So far, so good. I have tested it and it gives the desired result. Then I wanted to do this using multithreading. I have looked into the doc and examples on the internet, and using one thread in my program works fine. But when I use more, at some point I get random matplotlib error, and I suspect some conflict there, even though I use a function with names for the plots, and iI can't see where the problem could be. Here is the whole script should you need more comment, i'll add them. Thank you. #!/usr/bin/python import matplotlib matplotlib.use('GTKAgg') import numpy as np from scipy.interpolate import griddata import matplotlib.pyplot as plt import matplotlib.colors as mcl from matplotlib import rc #for latex import time as tm import sys import threading import Queue #queue in 3.2 and Queue in 2.7 ! import pdb #the debugger rc('text', usetex=True)#for latex map=0 #initialize the map index. It will be use to index the array like this: array[map,[x,y]] time=np.zeros(1) #an array to store the time middle_h=np.zeros((0,3)) #x phi c #for the middle of the box current_file=open("single_void_cyl_periodic_phi_c_middle_h_out",'r') for line in current_file: if line.startswith('# === time'): map+=1 np.append(time,[float(line.strip('# === time '))]) elif line.startswith('#'): pass else: v=np.fromstring(line,dtype=float,sep=' ') middle_h=np.vstack( (middle_h,v[[1,3,4]]) ) current_file.close() middle_h=middle_h.reshape((map,-1,3)) #3d array: map, x, phi,c ##### def load_and_plot(): #will load a map file, and plot it along with the corresponding profile loaded before while not exit_flag: print("fecthing work ...") #try: if not tasks_queue.empty(): map_index=tasks_queue.get() print("----> working on map: %s" %map_index) x,y,zp=np.loadtxt("single_void_cyl_growth_periodic_post_map_"+str(map_index),unpack=True, usecols=[1, 2,3]) for i,el in enumerate(zp): if el<0.: zp[i]=0. xv=np.unique(x) yv=np.unique(y) X,Y= np.meshgrid(xv,yv) Z = griddata((x, y), zp, (X, Y),method='nearest') figure=plt.figure(num=map_index,figsize=(14, 8)) ax1=plt.subplot2grid((2,2),(0,0)) ax1.plot(middle_h[map_index,:,0],middle_h[map_index,:,1],'*b') ax1.grid(True) ax1.axis([-15, 15, 0, 1]) ax1.set_title('Profiles') ax1.set_ylabel(r'$\phi$') ax1.set_xlabel('x') ax2=plt.subplot2grid((2,2),(1,0)) ax2.plot(middle_h[map_index,:,0],middle_h[map_index,:,2],'*r') ax2.grid(True) ax2.axis([-15, 15, 0, 1]) ax2.set_ylabel('c') ax2.set_xlabel('x') ax3=plt.subplot2grid((2,2),(0,1),rowspan=2,aspect='equal') sub_contour=ax3.contourf(X,Y,Z,np.linspace(0,1,11),vmin=0.) figure.colorbar(sub_contour,ax=ax3) figure.savefig('single_void_cyl_'+str(map_index)+'.png') plt.close(map_index) tasks_queue.task_done() else: print("nothing left to do, other threads finishing,sleeping 2 seconds...") tm.sleep(2) # except: # print("failed this time: %s" %map_index+". Sleeping 2 seconds") # tm.sleep(2) ##### exit_flag=0 nb_threads=2 tasks_queue=Queue.Queue() threads_list=[] jobs=list(range(map)) #each job is composed of a map print("inserting jobs in the queue...") for job in jobs: tasks_queue.put(job) print("done") #launch the threads for i in range(nb_threads): working_bee=threading.Thread(target=load_and_plot) working_bee.daemon=True print("starting thread "+str(i)+' ...') threads_list.append(working_bee) working_bee.start() #wait for all tasks to be treated tasks_queue.join() #flip the flag, so the threads know it's time to stop exit_flag=1 for t in threads_list: print("waiting for threads %s to stop..."%t) t.join() print("all threads stopped")

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  • Multiple data series in real time plot

    - by Gr3n
    Hi, I'm kind of new to Python and trying to create a plotting app for values read via RS232 from a sensor. I've managed (after some reading and copying examples online) to get a plot working that updates on a timer which is great. My only trouble is that I can't manage to get multiple data series into the same plot. Does anyone have a solution to this? This is the code that I've worked out this far: import os import pprint import random import sys import wx # The recommended way to use wx with mpl is with the WXAgg backend import matplotlib matplotlib.use('WXAgg') from matplotlib.figure import Figure from matplotlib.backends.backend_wxagg import FigureCanvasWxAgg as FigCanvas, NavigationToolbar2WxAgg as NavigationToolbar import numpy as np import pylab DATA_LENGTH = 100 REDRAW_TIMER_MS = 20 def getData(): return int(random.uniform(1000, 1020)) class GraphFrame(wx.Frame): # the main frame of the application def __init__(self): wx.Frame.__init__(self, None, -1, "Usart plotter", size=(800,600)) self.Centre() self.data = [] self.paused = False self.create_menu() self.create_status_bar() self.create_main_panel() self.redraw_timer = wx.Timer(self) self.Bind(wx.EVT_TIMER, self.on_redraw_timer, self.redraw_timer) self.redraw_timer.Start(REDRAW_TIMER_MS) def create_menu(self): self.menubar = wx.MenuBar() menu_file = wx.Menu() m_expt = menu_file.Append(-1, "&Save plot\tCtrl-S", "Save plot to file") self.Bind(wx.EVT_MENU, self.on_save_plot, m_expt) menu_file.AppendSeparator() m_exit = menu_file.Append(-1, "E&xit\tCtrl-X", "Exit") self.Bind(wx.EVT_MENU, self.on_exit, m_exit) self.menubar.Append(menu_file, "&File") self.SetMenuBar(self.menubar) def create_main_panel(self): self.panel = wx.Panel(self) self.init_plot() self.canvas = FigCanvas(self.panel, -1, self.fig) # pause button self.pause_button = wx.Button(self.panel, -1, "Pause") self.Bind(wx.EVT_BUTTON, self.on_pause_button, self.pause_button) self.Bind(wx.EVT_UPDATE_UI, self.on_update_pause_button, self.pause_button) self.hbox1 = wx.BoxSizer(wx.HORIZONTAL) self.hbox1.Add(self.pause_button, border=5, flag=wx.ALL | wx.ALIGN_CENTER_VERTICAL) self.vbox = wx.BoxSizer(wx.VERTICAL) self.vbox.Add(self.canvas, 1, flag=wx.LEFT | wx.TOP | wx.GROW) self.vbox.Add(self.hbox1, 0, flag=wx.ALIGN_LEFT | wx.TOP) self.panel.SetSizer(self.vbox) #self.vbox.Fit(self) def create_status_bar(self): self.statusbar = self.CreateStatusBar() def init_plot(self): self.dpi = 100 self.fig = Figure((3.0, 3.0), dpi=self.dpi) self.axes = self.fig.add_subplot(111) self.axes.set_axis_bgcolor('white') self.axes.set_title('Usart data', size=12) pylab.setp(self.axes.get_xticklabels(), fontsize=8) pylab.setp(self.axes.get_yticklabels(), fontsize=8) # plot the data as a line series, and save the reference # to the plotted line series # self.plot_data = self.axes.plot( self.data, linewidth=1, color="blue", )[0] def draw_plot(self): # redraws the plot xmax = len(self.data) if len(self.data) > DATA_LENGTH else DATA_LENGTH xmin = xmax - DATA_LENGTH ymin = 0 ymax = 4096 self.axes.set_xbound(lower=xmin, upper=xmax) self.axes.set_ybound(lower=ymin, upper=ymax) # enable grid #self.axes.grid(True, color='gray') # Using setp here is convenient, because get_xticklabels # returns a list over which one needs to explicitly # iterate, and setp already handles this. # pylab.setp(self.axes.get_xticklabels(), visible=True) self.plot_data.set_xdata(np.arange(len(self.data))) self.plot_data.set_ydata(np.array(self.data)) self.canvas.draw() def on_pause_button(self, event): self.paused = not self.paused def on_update_pause_button(self, event): label = "Resume" if self.paused else "Pause" self.pause_button.SetLabel(label) def on_save_plot(self, event): file_choices = "PNG (*.png)|*.png" dlg = wx.FileDialog( self, message="Save plot as...", defaultDir=os.getcwd(), defaultFile="plot.png", wildcard=file_choices, style=wx.SAVE) if dlg.ShowModal() == wx.ID_OK: path = dlg.GetPath() self.canvas.print_figure(path, dpi=self.dpi) self.flash_status_message("Saved to %s" % path) def on_redraw_timer(self, event): if not self.paused: newData = getData() self.data.append(newData) self.draw_plot() def on_exit(self, event): self.Destroy() def flash_status_message(self, msg, flash_len_ms=1500): self.statusbar.SetStatusText(msg) self.timeroff = wx.Timer(self) self.Bind( wx.EVT_TIMER, self.on_flash_status_off, self.timeroff) self.timeroff.Start(flash_len_ms, oneShot=True) def on_flash_status_off(self, event): self.statusbar.SetStatusText('') if __name__ == '__main__': app = wx.PySimpleApp() app.frame = GraphFrame() app.frame.Show() app.MainLoop()

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  • CodePlex Daily Summary for Monday, July 29, 2013

    CodePlex Daily Summary for Monday, July 29, 2013Popular ReleasesGIS Raster Tile Normalizer for GeoServer: V110 Extended to tile DEMs: 1) Now imports large DEM datasets. They are stored as 3.25 degree tiles in GeoTIFF 32 bit single band tiles ready to be used by GeoServer. Also, parallel colorized hillshade tiles are optionally created for easy visualization in GeoServer. 2) No longer uses FWTools, but the more recent 32 bit Windows 1.9 GDAL installation from Tamas at http://www.gisinternals.com/sdk/. Also required is Python 2.7, the GDAL Python Bindings from Tamas, and the Numpy python libraries. This is because we use th...R.NET: R.NET 1.5: The major changes in v1.5 are: Initialize method must be called before using R. Settings should be passed to the method. EagerEvaluate method renamed to Evaluate (use Defer method when you want old version of Evaluate).TX264: 0.9.7: --0.9.7 -Added: Encoding time will be shown in the log -Added: 64bit FLAC.exe -Added: Tx264 will now write version info file to its own folder -Added: Option to set encoder priorties (thx to XanaMuui&Ruriko) -Fixed: A possible error where source files were deleted -Updated: x264 to rev2345 -Updated: MediaInfo to 0.7.64 -Updated: MkvToolNix to 6.3.0 -Updated: FLAC to 1.3.0 -Updated: AlphaControls to 8.42 Stable -Updated: QAAC to 2.19 -Updated: SoX build with unicode by Lord_MulderMedia Companion: Media Companion MC3.574b: Some good bug fixes been going on with the new XBMC-Link function. Thanks to all who were able to do testing and gave feedback. New:* Added some adhoc extra General movie filters, one of which is Plot = Outline (see fixes above). To see the filters, add the following line to your config.xml: <ShowExtraMovieFilters>True</ShowExtraMovieFilters>. The others are: Imdb in folder name, Imdb in not folder name & Imdb not in folder name & year mismatch. * Movie - display <tag> list on browser tab ...OfflineBrowser: Preview Release with Search: I've added search to this release.VG-Ripper & PG-Ripper: VG-Ripper 2.9.46: changes FIXED LoginMath.NET Numerics: Math.NET Numerics v2.6.0: What's New in Math.NET Numerics 2.6 - Announcement, Explanations and Sample Code. New: Linear Curve Fitting Linear least-squares fitting (regression) to lines, polynomials and linear combinations of arbitrary functions. Multi-dimensional fitting. Also works well in F# with the F# extensions. New: Root Finding Brent's method. ~Candy Chiu, Alexander Täschner Bisection method. ~Scott Stephens, Alexander Täschner Broyden's method, for multi-dimensional functions. ~Alexander Täschner ...AJAX Control Toolkit: July 2013 Release: AJAX Control Toolkit Release Notes - July 2013 Release Version 7.0725July 2013 release of the AJAX Control Toolkit. AJAX Control Toolkit .NET 4.5 – AJAX Control Toolkit for .NET 4.5 and sample site (Recommended). AJAX Control Toolkit .NET 4 – AJAX Control Toolkit for .NET 4 and sample site (Recommended). AJAX Control Toolkit .NET 3.5 – AJAX Control Toolkit for .NET 3.5 and sample site (Recommended). Notes: - Instructions for using the AJAX Control Toolkit with ASP.NET 4.5 can be found at...MJP's DirectX 11 Samples: Specular Antialiasing Sample: Sample code to complement my presentation that's part of the Physically Based Shading in Theory and Practice course at SIGGRAPH 2013, entitled "Crafting a Next-Gen Material Pipeline for The Order: 1886". Demonstrates various methods of preventing aliasing from specular BRDF's when using high-frequency normal maps. The zip file contains source code as well as a pre-compiled x64 binary.English Practice Helper: English Practice Helper Demo v1.1: Fix some bug in sentences compareKartris E-commerce: Kartris v2.5003: This fixes an issue where search engines appear to identify as IE and so trigger the noIE page if there is not a non-responsive skin specified.Blue Mercs Data Gateway: Blue Mercs Data Gateway 2.0: Changes made for major release v2.0 build in support for Microsoft Access Database build in logging support (with optional stopwatch duration) implemented thread DbContext that can be referenced to share context accross layers implented 'having' sql keyword implemented 'top(n)' and 'first' sql keywords implemented 'distinct' sql keyword implemented sql column expressions implemented CTE (common table expressions) joins are refactored allow auto join on keys when using entiti...Wix Test: WIX Test Bootstrapper (Burn): WIX Test Bootstrapper and MSI setup files. Alfa versions.ScriptZilla: ScriptZilla 1.2.5.1: New Programming Languages(C++ too !) and An Better Editor.SSISConnectionBuilder: Alpha 2: Removed SSIS SDK dependencies.VBDownloader: VBDownloader 1.0: VBDownloader v1.0 The open source solution for downloads First releasemysqllib: mysqllib 1.5: La nuova versione 1.5 vede espandersi questa libreria con nuovi metodi e nuove caratteristiche interessanti. Ecco i cambiamenti: (NEW) Aggiunta classe MySqlTable per visualizzare tutti i dettagli della tabella, tra cui una lista di dettagli delle colonne (NEW) Aggiunta classe MySqlColumn per visualizzare tutti i dettagli della colonna, tra cui una lista dei valori della colonna (NEW) Nuovi metodi GetTable(...) e GetColumn(...) per risultati dettagliati di tabelle e colonne (NEW) Nuovi met...GoAgent GUI: GoAgent GUI 1.3.5 Alpha (20130723): ????????Alpha?,???????????,?????????????。 ??????????GoAgent???(???phus lu?GitHub??????GoAgent??????,??????????????????) ????????????????????????Bug ?????????。??????????????。 ????issue????,????????,????????????????。LogicCircuit: LogicCircuit 2.13.07.22: Logic Circuit - is educational software for designing and simulating logic circuits. Intuitive graphical user interface, allows you to create unrestricted circuit hierarchy with multi bit buses, debug circuits behavior with oscilloscope, and navigate running circuits hierarchy. Changes of this versionYou can make visual elements of the circuit been visible on its symbols. This way you can build composite displays, keyboards and reuse them. Please read about displays for more details http://ww...LINQ to Twitter: LINQ to Twitter v2.1.08: Supports .NET 3.5, .NET 4.0, .NET 4.5, Silverlight 4.0, Windows Phone 7.1, Windows Phone 8, Client Profile, Windows 8, and Windows Azure. 100% Twitter API coverage. Also supports Twitter API v1.1! Also on NuGet.New Projects#Zyan Drench, a game for Android: Zyan Drench is a simple yet very entertaining game for Android phones developed using Zyan Communication Framework: http://zyan.com.de Crzy Game Launcher: All in one game launcher and updater. Keep your game up-to-date with this simple to use launcher.Ecobee API: This project is a portable .NET Library wrapping the Ecobee Thermostat API.Fire-Fighting Kinect Game: Fire-Fighting Kinect Game A fire-fighting game that uses Vizard virtual reality software and the Microsoft Kinect to allow the player to put out virtual fires.Fish Atlantis: This is our homework.FreeBee 900 Pro - Open Source XBee® Pro Alternative: https://hg.codeplex.com/freebee900proFuelRex: FuelRex foi feito pra lhe ajudar em seu dia a dia. Facilite seus cálculos e obtenha números reais sobre o gasto de combustíveis, em um aplicativo totalmente.KbdPlayground: A collection of .NET helpers and experimentsMailChimpNET: MailChimpNET provides a .NET PCL based wrapper around the mailchimp.com web API.MVC Generator: Addin for Visual Studio that generates MVC from Entity Framework files. A Rapid Scaffolder with options.One More ENgine project: OMEN projet (One More ENgine) main objective is to provide a simple application container.Orchard Podcasts: The Orchard Podcasting module allows users to create and publish a podcast feed (Yahoo Media RSS) for consumption by users using Orchard v1.6+.Outlook 2013 Backup Add-In: Automatically backups psd-files after closing Outlook. This plugin is compatible with Outlook 2013 32/64 Bit Version. Project Emilie: A little help to make your WinRT XAML projects truly fast and fluid, based on work from two of the top Windows 8 applications.Search WPF: A small utility to browse the WPF classes and interfaces.sGaming: Silverlight 3D EngineTelerik Connect: Simple ASP.NET Project aiming to build a copy of the LinkedIn website functionality.Testing The Unittesting Tools in Visual Studio: This project is a collection of testprograms for verifying the different test adapters available for Visual Studio. TvLinks Torrent Searcher: Easy way to search Torrents for TV Series.xnaGaming: XNA game engine

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  • OpenGL basics: calling glDrawElements once per object

    - by Bethor
    Hi all, continuing on from my explorations of the basics of OpenGL (see this question), I'm trying to figure out the basic principles of drawing a scene with OpenGL. I am trying to render a simple cube repeated n times in every direction. My method appears to yield terrible performance : 1000 cubes brings performance below 50fps (on a QuadroFX 1800, roughly a GeForce 9600GT). My method for drawing these cubes is as follows: done once: set up a vertex buffer and array buffer containing my cube vertices in model space set up an array buffer indexing the cube for drawing as 12 triangles done for each frame: update uniform values used by the vertex shader to move all cubes at once done for each cube, for each frame: update uniform values used by the vertex shader to move each cube to its position call glDrawElements to draw the positioned cube Is this a sane method ? If not, how does one go about something like this ? I'm guessing I need to minimize calls to glUniform, glDrawElements, or both, but I'm not sure how to do that. Full code for my little test : (depends on gletools and pyglet) I'm aware that my init code (at least) is really ugly; I'm concerned with the rendering code for each frame right now, I'll move to something a little less insane for the creation of the vertex buffers and such later on. import pyglet from pyglet.gl import * from pyglet.window import key from numpy import deg2rad, tan from gletools import ShaderProgram, FragmentShader, VertexShader, GeometryShader vertexData = [-0.5, -0.5, -0.5, 1.0, -0.5, 0.5, -0.5, 1.0, 0.5, -0.5, -0.5, 1.0, 0.5, 0.5, -0.5, 1.0, -0.5, -0.5, 0.5, 1.0, -0.5, 0.5, 0.5, 1.0, 0.5, -0.5, 0.5, 1.0, 0.5, 0.5, 0.5, 1.0] elementArray = [2, 1, 0, 1, 2, 3,## back face 4, 7, 6, 4, 5, 7,## front face 1, 3, 5, 3, 7, 5,## top face 2, 0, 4, 2, 4, 6,## bottom face 1, 5, 4, 0, 1, 4,## left face 6, 7, 3, 6, 3, 2]## right face def toGLArray(input): return (GLfloat*len(input))(*input) def toGLushortArray(input): return (GLushort*len(input))(*input) def initPerspectiveMatrix(aspectRatio = 1.0, fov = 45): frustumScale = 1.0 / tan(deg2rad(fov) / 2.0) fzNear = 0.5 fzFar = 300.0 perspectiveMatrix = [frustumScale*aspectRatio, 0.0 , 0.0 , 0.0 , 0.0 , frustumScale, 0.0 , 0.0 , 0.0 , 0.0 , (fzFar+fzNear)/(fzNear-fzFar) , -1.0, 0.0 , 0.0 , (2*fzFar*fzNear)/(fzNear-fzFar), 0.0 ] return perspectiveMatrix class ModelObject(object): vbo = GLuint() vao = GLuint() eao = GLuint() initDone = False verticesPool = [] indexPool = [] def __init__(self, vertices, indexing): super(ModelObject, self).__init__() if not ModelObject.initDone: glGenVertexArrays(1, ModelObject.vao) glGenBuffers(1, ModelObject.vbo) glGenBuffers(1, ModelObject.eao) glBindVertexArray(ModelObject.vao) initDone = True self.numIndices = len(indexing) self.offsetIntoVerticesPool = len(ModelObject.verticesPool) ModelObject.verticesPool.extend(vertices) self.offsetIntoElementArray = len(ModelObject.indexPool) ModelObject.indexPool.extend(indexing) glBindBuffer(GL_ARRAY_BUFFER, ModelObject.vbo) glEnableVertexAttribArray(0) #position glVertexAttribPointer(0, 4, GL_FLOAT, GL_FALSE, 0, 0) glBindBuffer(GL_ELEMENT_ARRAY_BUFFER, ModelObject.eao) glBufferData(GL_ARRAY_BUFFER, len(ModelObject.verticesPool)*4, toGLArray(ModelObject.verticesPool), GL_STREAM_DRAW) glBufferData(GL_ELEMENT_ARRAY_BUFFER, len(ModelObject.indexPool)*2, toGLushortArray(ModelObject.indexPool), GL_STREAM_DRAW) def draw(self): glDrawElements(GL_TRIANGLES, self.numIndices, GL_UNSIGNED_SHORT, self.offsetIntoElementArray) class PositionedObject(object): def __init__(self, mesh, pos, objOffsetUf): super(PositionedObject, self).__init__() self.mesh = mesh self.pos = pos self.objOffsetUf = objOffsetUf def draw(self): glUniform3f(self.objOffsetUf, self.pos[0], self.pos[1], self.pos[2]) self.mesh.draw() w = 800 h = 600 AR = float(h)/float(w) window = pyglet.window.Window(width=w, height=h, vsync=False) window.set_exclusive_mouse(True) pyglet.clock.set_fps_limit(None) ## input forward = [False] left = [False] back = [False] right = [False] up = [False] down = [False] inputs = {key.Z: forward, key.Q: left, key.S: back, key.D: right, key.UP: forward, key.LEFT: left, key.DOWN: back, key.RIGHT: right, key.PAGEUP: up, key.PAGEDOWN: down} ## camera camX = 0.0 camY = 0.0 camZ = -1.0 def simulate(delta): global camZ, camX, camY scale = 10.0 move = scale*delta if forward[0]: camZ += move if back[0]: camZ += -move if left[0]: camX += move if right[0]: camX += -move if up[0]: camY += move if down[0]: camY += -move pyglet.clock.schedule(simulate) @window.event def on_key_press(symbol, modifiers): global forward, back, left, right, up, down if symbol in inputs.keys(): inputs[symbol][0] = True @window.event def on_key_release(symbol, modifiers): global forward, back, left, right, up, down if symbol in inputs.keys(): inputs[symbol][0] = False ## uniforms for shaders camOffsetUf = GLuint() objOffsetUf = GLuint() perspectiveMatrixUf = GLuint() camRotationUf = GLuint() program = ShaderProgram( VertexShader(''' #version 330 layout(location = 0) in vec4 objCoord; uniform vec3 objOffset; uniform vec3 cameraOffset; uniform mat4 perspMx; void main() { mat4 translateCamera = mat4(1.0f, 0.0f, 0.0f, 0.0f, 0.0f, 1.0f, 0.0f, 0.0f, 0.0f, 0.0f, 1.0f, 0.0f, cameraOffset.x, cameraOffset.y, cameraOffset.z, 1.0f); mat4 translateObject = mat4(1.0f, 0.0f, 0.0f, 0.0f, 0.0f, 1.0f, 0.0f, 0.0f, 0.0f, 0.0f, 1.0f, 0.0f, objOffset.x, objOffset.y, objOffset.z, 1.0f); vec4 modelCoord = objCoord; vec4 positionedModel = translateObject*modelCoord; vec4 cameraPos = translateCamera*positionedModel; gl_Position = perspMx * cameraPos; }'''), FragmentShader(''' #version 330 out vec4 outputColor; const vec4 fillColor = vec4(1.0f, 1.0f, 1.0f, 1.0f); void main() { outputColor = fillColor; }''') ) shapes = [] def init(): global camOffsetUf, objOffsetUf with program: camOffsetUf = glGetUniformLocation(program.id, "cameraOffset") objOffsetUf = glGetUniformLocation(program.id, "objOffset") perspectiveMatrixUf = glGetUniformLocation(program.id, "perspMx") glUniformMatrix4fv(perspectiveMatrixUf, 1, GL_FALSE, toGLArray(initPerspectiveMatrix(AR))) obj = ModelObject(vertexData, elementArray) nb = 20 for i in range(nb): for j in range(nb): for k in range(nb): shapes.append(PositionedObject(obj, (float(i*2), float(j*2), float(k*2)), objOffsetUf)) glEnable(GL_CULL_FACE) glCullFace(GL_BACK) glFrontFace(GL_CW) glEnable(GL_DEPTH_TEST) glDepthMask(GL_TRUE) glDepthFunc(GL_LEQUAL) glDepthRange(0.0, 1.0) glClearDepth(1.0) def update(dt): print pyglet.clock.get_fps() pyglet.clock.schedule_interval(update, 1.0) @window.event def on_draw(): with program: pyglet.clock.tick() glClear(GL_COLOR_BUFFER_BIT|GL_DEPTH_BUFFER_BIT) glUniform3f(camOffsetUf, camX, camY, camZ) for shape in shapes: shape.draw() init() pyglet.app.run()

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  • Graphics glitch when drawing to a Cairo context obtained from a gtk.DrawingArea inside a gtk.Viewport.

    - by user410023
    I am trying to redraw the part of the DrawingArea that is visible in the Viewport in the expose-event handler. However, it seems that I am doing something wrong with the coordinates that are passed to the event handler because there is garbage at the edge of the Viewport when scrolling. Can anyone tell what I am doing wrong? Here is a small example: import pygtk pygtk.require("2.0") import gtk from numpy import array from math import pi class Circle(object): def init(self, position = [0., 0.], radius = 0., edge = (0., 0., 0.), fill = None): self.position = position self.radius = radius self.edge = edge self.fill = fill def draw(self, ctx): rect = array(ctx.clip_extents()) rect[2] -= rect[0] rect[3] -= rect[1] center = rect[2:4] / 2 ctx.arc(center[0], center[1], self.radius, 0., 2. * pi) if self.fill != None: ctx.set_source_rgb(*self.fill) ctx.fill_preserve() ctx.set_source_rgb(*self.edge) ctx.stroke() class Scene(object): class Proxy(object): directory = {} def init(self, target, layers = set()): self.target = target self.layers = layers Scene.Proxy.directory[target] = self def __init__(self, viewport): self.objects = {} self.layers = [set()] self.viewport = viewport self.signals = {} def draw(self, ctx): x = self.viewport.get_hadjustment().value y = self.viewport.get_vadjustment().value ctx.set_source_rgb(1., 1., 1.) ctx.paint() ctx.translate(x, y) for obj in self: obj.draw(ctx) def add(self, item, layer = 0): item = Scene.Proxy(item, layers = set((layer,))) assert(hasattr(item.target, "draw")) assert(isinstance(layer, int)) item.layers.add(layer) while not layer < len(self.layers): self.layers.append(set()) self.layers[layer].add(item) if not item in self.objects: self.objects[item] = set() self.objects[item].add(layer) def remove(self, item, layers = None): item = Scene.Proxy.directory[item] if layers == None: layers = self.objects[item] for layer in layers: layer.remove(item) item.layers.remove(layer) if len(item.layers) == 0: self.objects.remove(item) def __iter__(self): for layer in self.layers: for item in layer: yield item.target class App(object): def init(self): signals = { "canvas_exposed": self.update_canvas, "gtk_main_quit": gtk.main_quit } self.builder = gtk.Builder() self.builder.add_from_file("graphics_glitch.glade") self.window = self.builder.get_object("window") self.viewport = self.builder.get_object("viewport") self.canvas = self.builder.get_object("canvas") self.scene = Scene(self.viewport) signals.update(self.scene.signals) self.builder.connect_signals(signals) self.window.show() def update_canvas(self, widget, event): ctx = self.canvas.window.cairo_create() self.scene.draw(ctx) ctx.clip() if name == "main": app = App() scene = app.scene scene.add(Circle((0., 0.), 10.)) gtk.main() And the Glade file "graphics_glitch.glade": <?xml version="1.0"?> <interface> <requires lib="gtk+" version="2.16"/> <!-- interface-naming-policy project-wide --> <object class="GtkWindow" id="window"> <property name="width_request">200</property> <property name="height_request">200</property> <property name="visible">True</property> <signal name="destroy" handler="gtk_main_quit"/> <child> <object class="GtkScrolledWindow" id="scrolledwindow1"> <property name="visible">True</property> <property name="can_focus">True</property> <property name="hadjustment">h_adjust</property> <property name="vadjustment">v_adjust</property> <property name="hscrollbar_policy">automatic</property> <property name="vscrollbar_policy">automatic</property> <child> <object class="GtkViewport" id="viewport"> <property name="visible">True</property> <property name="resize_mode">queue</property> <child> <object class="GtkDrawingArea" id="canvas"> <property name="width_request">640</property> <property name="height_request">480</property> <property name="visible">True</property> <signal name="expose_event" handler="canvas_exposed"/> </object> </child> </object> </child> </object> </child> </object> <object class="GtkAdjustment" id="h_adjust"> <property name="lower">-1000</property> <property name="upper">1000</property> <property name="step_increment">1</property> <property name="page_increment">25</property> <property name="page_size">25</property> </object> <object class="GtkAdjustment" id="v_adjust"> <property name="lower">-1000</property> <property name="upper">1000</property> <property name="step_increment">1</property> <property name="page_increment">25</property> <property name="page_size">25</property> </object> </interface> Thanks! --Dan

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  • creating a color coded time chart using colorbar and colormaps in python

    - by Rusty
    I'm trying to make a time tracking chart based on a daily time tracking file that I used. I wrote code that crawls through my files and generates a few lists. endTimes is a list of times that a particular activity ends in minutes going from 0 at midnight the first day of the month to however many minutes are in a month. labels is a list of labels for the times listed in endTimes. It is one shorter than endtimes since the trackers don't have any data about before 0 minute. Most labels are repeats. categories contains every unique value of labels in order of how well I regard that time. I want to create a colorbar or a stack of colorbars (1 for eachday) that will depict how I spend my time for a month and put a color associated with each label. Each value in categories will have a color associated. More blue for more good. More red for more bad. It is already in order for the jet colormap to be right, but I need to get desecrate color values evenly spaced out for each value in categories. Then I figure the next step would be to convert that to a listed colormap to use for the colorbar based on how the labels associated with the categories. I think this is the right way to do it, but I am not sure. I am not sure how to associate the labels with color values. Here is the last part of my code so far. I found one function to make a discrete colormaps. It does, but it isn't what I am looking for and I am not sure what is happening. Thanks for the help! # now I need to develop the graph import numpy as np from matplotlib import pyplot,mpl import matplotlib from scipy import interpolate from scipy import * def contains(thelist,name): # checks if the current list of categories contains the one just read for val in thelist: if val == name: return True return False def getCategories(lastFile): ''' must determine the colors to use I would like to make a gradient so that the better the task, the closer to blue bad labels will recieve colors closer to blue read the last file given for the information on how I feel the order should be then just keep them in the order of how good they are in the tracker use a color range and develop discrete values for each category by evenly spacing them out any time not found should assume to be sleep sleep should be white ''' tracker = open(lastFile+'.txt') # open the last file # find all the categories categories = [] for line in tracker: pos = line.find(':') # does it have a : or a ? if pos==-1: pos=line.find('?') if pos != -1: # ignore if no : or ? name = line[0:pos].strip() # split at the : or ? if contains(categories,name)==False: # if the category is new categories.append(name) # make a new one return categories # find good values in order of last day newlabels=[] for val in getCategories(lastDay): if contains(labels,val): newlabels.append(val) categories=newlabels # convert discrete colormap to listed colormap python for ii,val in enumerate(labels): if contains(categories,val)==False: labels[ii]='sleep' # create a figure fig = pyplot.figure() axes = [] for x in range(endTimes[-1]%(24*60)): ax = fig.add_axes([0.05, 0.65, 0.9, 0.15]) axes.append(ax) # figure out the colors to use # stole this function to make a discrete colormap # http://www.scipy.org/Cookbook/Matplotlib/ColormapTransformations def cmap_discretize(cmap, N): """Return a discrete colormap from the continuous colormap cmap. cmap: colormap instance, eg. cm.jet. N: Number of colors. Example x = resize(arange(100), (5,100)) djet = cmap_discretize(cm.jet, 5) imshow(x, cmap=djet) """ cdict = cmap._segmentdata.copy() # N colors colors_i = np.linspace(0,1.,N) # N+1 indices indices = np.linspace(0,1.,N+1) for key in ('red','green','blue'): # Find the N colors D = np.array(cdict[key]) I = interpolate.interp1d(D[:,0], D[:,1]) colors = I(colors_i) # Place these colors at the correct indices. A = zeros((N+1,3), float) A[:,0] = indices A[1:,1] = colors A[:-1,2] = colors # Create a tuple for the dictionary. L = [] for l in A: L.append(tuple(l)) cdict[key] = tuple(L) # Return colormap object. return matplotlib.colors.LinearSegmentedColormap('colormap',cdict,1024) # jet colormap goes from blue to red (good to bad) cmap = cmap_discretize(mpl.cm.jet, len(categories)) cmap.set_over('0.25') cmap.set_under('0.75') #norm = mpl.colors.Normalize(endTimes,cmap.N) print endTimes print labels # make a color list by matching labels to a picture #norm = mpl.colors.ListedColormap(colorList) cb1 = mpl.colorbar.ColorbarBase(axes[0],cmap=cmap ,orientation='horizontal' ,boundaries=endTimes ,ticks=endTimes ,spacing='proportional') pyplot.show()

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  • Creating a new plugin for mpld3

    - by sjp14051
    Toward learning how to create a new mpld3 plugin, I took an existing example, LinkedDataPlugin (http://mpld3.github.io/examples/heart_path.html), and modified it slightly by deleting references to lines object. That is, I created the following: class DragPlugin(plugins.PluginBase): JAVASCRIPT = r""" mpld3.register_plugin("drag", DragPlugin); DragPlugin.prototype = Object.create(mpld3.Plugin.prototype); DragPlugin.prototype.constructor = DragPlugin; DragPlugin.prototype.requiredProps = ["idpts", "idpatch"]; DragPlugin.prototype.defaultProps = {} function DragPlugin(fig, props){ mpld3.Plugin.call(this, fig, props); }; DragPlugin.prototype.draw = function(){ var patchobj = mpld3.get_element(this.props.idpatch, this.fig); var ptsobj = mpld3.get_element(this.props.idpts, this.fig); var drag = d3.behavior.drag() .origin(function(d) { return {x:ptsobj.ax.x(d[0]), y:ptsobj.ax.y(d[1])}; }) .on("dragstart", dragstarted) .on("drag", dragged) .on("dragend", dragended); patchobj.path.attr("d", patchobj.datafunc(ptsobj.offsets, patchobj.pathcodes)); patchobj.data = ptsobj.offsets; ptsobj.elements() .data(ptsobj.offsets) .style("cursor", "default") .call(drag); function dragstarted(d) { d3.event.sourceEvent.stopPropagation(); d3.select(this).classed("dragging", true); } function dragged(d, i) { d[0] = ptsobj.ax.x.invert(d3.event.x); d[1] = ptsobj.ax.y.invert(d3.event.y); d3.select(this) .attr("transform", "translate(" + [d3.event.x,d3.event.y] + ")"); patchobj.path.attr("d", patchobj.datafunc(ptsobj.offsets, patchobj.pathcodes)); } function dragended(d, i) { d3.select(this).classed("dragging", false); } } mpld3.register_plugin("drag", DragPlugin); """ def __init__(self, points, patch): print "Points ID : ", utils.get_id(points) self.dict_ = {"type": "drag", "idpts": utils.get_id(points), "idpatch": utils.get_id(patch)} However, when I try to link the plugin to a figure, as in plugins.connect(fig, DragPlugin(points[0], patch)) I get an error, 'module' is not callable, pointing to this line. What does this mean and why doesn't it work? Thanks. I'm adding additional code to show that linking more than one Plugin might be problematic. But this may be entirely due to some silly mistake on my part, or there is a way around it. The following code based on LinkedViewPlugin generates three panels, in which the top and the bottom panel are supposed to be identical. Mouseover in the middle panel was expected to control the display in the top and bottom panels, but updates occur in the bottom panel only. It would be nice to be able to figure out how to reflect the changes in multiple panels. Thanks. import matplotlib import matplotlib.pyplot as plt import numpy as np import mpld3 from mpld3 import plugins, utils class LinkedView(plugins.PluginBase): """A simple plugin showing how multiple axes can be linked""" JAVASCRIPT = """ mpld3.register_plugin("linkedview", LinkedViewPlugin); LinkedViewPlugin.prototype = Object.create(mpld3.Plugin.prototype); LinkedViewPlugin.prototype.constructor = LinkedViewPlugin; LinkedViewPlugin.prototype.requiredProps = ["idpts", "idline", "data"]; LinkedViewPlugin.prototype.defaultProps = {} function LinkedViewPlugin(fig, props){ mpld3.Plugin.call(this, fig, props); }; LinkedViewPlugin.prototype.draw = function(){ var pts = mpld3.get_element(this.props.idpts); var line = mpld3.get_element(this.props.idline); var data = this.props.data; function mouseover(d, i){ line.data = data[i]; line.elements().transition() .attr("d", line.datafunc(line.data)) .style("stroke", this.style.fill); } pts.elements().on("mouseover", mouseover); }; """ def __init__(self, points, line, linedata): if isinstance(points, matplotlib.lines.Line2D): suffix = "pts" else: suffix = None self.dict_ = {"type": "linkedview", "idpts": utils.get_id(points, suffix), "idline": utils.get_id(line), "data": linedata} class LinkedView2(plugins.PluginBase): """A simple plugin showing how multiple axes can be linked""" JAVASCRIPT = """ mpld3.register_plugin("linkedview", LinkedViewPlugin2); LinkedViewPlugin2.prototype = Object.create(mpld3.Plugin.prototype); LinkedViewPlugin2.prototype.constructor = LinkedViewPlugin2; LinkedViewPlugin2.prototype.requiredProps = ["idpts", "idline", "data"]; LinkedViewPlugin2.prototype.defaultProps = {} function LinkedViewPlugin2(fig, props){ mpld3.Plugin.call(this, fig, props); }; LinkedViewPlugin2.prototype.draw = function(){ var pts = mpld3.get_element(this.props.idpts); var line = mpld3.get_element(this.props.idline); var data = this.props.data; function mouseover(d, i){ line.data = data[i]; line.elements().transition() .attr("d", line.datafunc(line.data)) .style("stroke", this.style.fill); } pts.elements().on("mouseover", mouseover); }; """ def __init__(self, points, line, linedata): if isinstance(points, matplotlib.lines.Line2D): suffix = "pts" else: suffix = None self.dict_ = {"type": "linkedview", "idpts": utils.get_id(points, suffix), "idline": utils.get_id(line), "data": linedata} fig, ax = plt.subplots(3) # scatter periods and amplitudes np.random.seed(0) P = 0.2 + np.random.random(size=20) A = np.random.random(size=20) x = np.linspace(0, 10, 100) data = np.array([[x, Ai * np.sin(x / Pi)] for (Ai, Pi) in zip(A, P)]) points = ax[1].scatter(P, A, c=P + A, s=200, alpha=0.5) ax[1].set_xlabel('Period') ax[1].set_ylabel('Amplitude') # create the line object lines = ax[0].plot(x, 0 * x, '-w', lw=3, alpha=0.5) ax[0].set_ylim(-1, 1) ax[0].set_title("Hover over points to see lines") linedata = data.transpose(0, 2, 1).tolist() plugins.connect(fig, LinkedView(points, lines[0], linedata)) # second set of lines exactly the same but in a different panel lines2 = ax[2].plot(x, 0 * x, '-w', lw=3, alpha=0.5) ax[2].set_ylim(-1, 1) ax[2].set_title("Hover over points to see lines #2") plugins.connect(fig, LinkedView2(points, lines2[0], linedata)) mpld3.show()

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