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• Python sort 2-D list by time string

  - by Mark Kennedy

  How do I sort a multi dimensional list like this based on a time string? The sublists can be of different sizes (i.e. 4 and 5, here) I want to sort by comparing the first time string in each sublist (sublist[-4]) x = (['1513', '08:19PM', '10:21PM', 1, 4], ['1290', '09:45PM', '11:43PM', 1, 4], ['0690', '07:25AM', '09:19AM', 1, 4], ['0201', '08:50AM', '10:50AM', 1, 4], ['1166', '04:35PM', '06:36PM', 1, 4], ['0845', '05:40PM', '07:44PM', 1, 4], ['1267', '07:05PM', '09:07PM', 1, 4], ['1513', '08:19PM', '10:21PM', 1, 4], ['1290', '09:45PM', '11:43PM', 1, 4], ['8772', '0159', '12:33PM', '02:43PM', 1, 5], ['0888', '0570', '09:42PM', '12:20AM', 1, 5], ['2086', '2231', '04:10PM', '06:20PM', 1, 5]) The sorted result would be sortedX = (['0690', '07:25AM', '09:19AM', 1, 4], ['0201', '08:50AM', '10:50AM', 1, 4], ['1166', '04:35PM', '06:36PM', 1, 4], ['0845', '05:40PM', '07:44PM', 1, 4], ['1267', '07:05PM', '09:07PM', 1, 4], ['1513', '08:19PM', '10:21PM', 1, 4], ['1513', '08:19PM', '10:21PM', 1, 4], ['1290', '09:45PM', '11:43PM', 1, 4], ['1290', '09:45PM', '11:43PM', 1, 4], ['8772', '0159', '12:33PM', '02:43PM', 1, 5], ['2086', '2231', '04:10PM', '06:20PM', 1, 5], ['0888', '0570', '09:42PM', '12:20AM', 1, 5]) I tried the following: sortedX = sorted(x, key=lambda k : k[-4]) #k[-4] is the first time string and it works but it doesn't respect the sublist size ordering

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• converting python list of strings to their type

  - by user248237

  given a list of python strings, how can I automatically convert them to their correct type? Meaning, if I have: ["hello", "3", "3.64", "-1"] I'd like this to be converted to the list ["hello", 3, 3.64, -1] where the first element is a stirng, the second an int, the third a float and the fourth an int. how can I do this? thanks.

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• averaging matrix efficiently

  - by user248237

  in Python, given an n x p matrix, e.g. 4 x 4, how can I return a matrix that's 4 x 2 that simply averages the first two columns and the last two columns for all 4 rows of the matrix? e.g. given: a = array([[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12], [13, 14, 15, 16]]) return a matrix that has the average of a[:, 0] and a[:, 1] and the average of a[:, 2] and a[:, 3]. I want this to work for an arbitrary matrix of n x p assuming that the number of columns I am averaging of n is obviously evenly divisible by n. let me clarify: for each row, I want to take the average of the first two columns, then the average of the last two columns. So it would be: 1 + 2 / 2, 3 + 4 / 2 <- row 1 of new matrix 5 + 6 / 2, 7 + 8 / 2 <- row 2 of new matrix, etc. which should yield a 4 by 2 matrix rather than 4 x 4. thanks.

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• how do I remove rows/columns from this matrix using python

  - by banditKing

  My matrix looks like this. ['Hotel', ' "excellent"', ' "very good"', ' "average"', ' "poor"', ' "terrible"', ' "cheapest"', ' "rank"', ' "total reviews"'] ['westin', ' 390', ' 291', ' 70', ' 43', ' 19', ' 215', ' 27', ' 813'] ['ramada', ' 136', ' 67', ' 53', ' 30', ' 24', ' 149', ' 49', ' 310 '] ['sutton place', '489', ' 293', ' 106', ' 39', ' 20', ' 299', ' 24', ' 947'] ['loden', ' 681', ' 134', ' 17', ' 5', ' 0', ' 199', ' 4', ' 837'] ['hampton inn downtown', ' 241', ' 166', ' 26', ' 5', ' 1', ' 159', ' 21', ' 439'] ['shangri la', ' 332', ' 45', ' 20', ' 8', ' 2', ' 325', ' 8', ' 407'] ['residence inn marriott', ' 22', ' 15', ' 5', ' 0', ' 0', ' 179', ' 35', ' 42'] ['pan pacific', ' 475', ' 262', ' 86', ' 29', ' 16', ' 249', ' 15', ' 868'] ['sheraton wall center', ' 277', ' 346', ' 150', ' 80', ' 26', ' 249', ' 45', ' 879'] ['westin bayshore', ' 390', ' 291', ' 70', ' 43', ' 19', ' 199', ' 813'] I want to remove the top row and the 0th column from this and create a new matrix. How do I do this? Normally in java or so Id use the following code: for (int y; y< matrix[x].length; y++) for(int x; x < matrix[Y].length; x++) { if(x == 0 || y == 0) { continue } else { new_matrix[x][y] = matrix[x][y]; } } Is there a way such as this in python to iterate and selectively copy elements? Thanks EDIT Im also trying to convert each matrix element from a string to a float as I iterate over the matrix. This my updated modified code based on the answer below. A = [] f = open("csv_test.csv",'rt') try: reader = csv.reader(f) for row in reader: A.append(row) finally: f.close() new_list = [row[1:] for row in A[1:]] l = np.array(new_list) l.astype(np.float32) print l However Im getting an error --> l.astype(np.float32) print l ValueError: setting an array element with a sequence.

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• how to solve a weired swig python c++ interfacing type error

  - by user2981648

  I want to use swig to switch a simple cpp function to python and use "scipy.integrate.quadrature" function to calculate the integration. But python 2.7 reports a type error. Do you guys know what is going on here? Thanks a lot. Furthermore, "scipy.integrate.quad" runs smoothly. So is there something special for "scipy.integrate.quadrature" function? The code is in the following: File "testfunctions.h": #ifndef TESTFUNCTIONS_H #define TESTFUNCTIONS_H double test_square(double x); #endif File "testfunctions.cpp": #include "testfunctions.h" double test_square(double x) { return x * x; } File "swig_test.i" : /* File : swig_test.i */ %module swig_test %{ #include "testfunctions.h" %} /* Let's just grab the original header file here */ %include "testfunctions.h" File "test.py": import scipy.integrate import _swig_test print scipy.integrate.quadrature(_swig_test.test_square, 0., 1.) error info: UMD has deleted: _swig_test Traceback (most recent call last): File "<stdin>", line 1, in <module> File "C:\Python27\lib\site-packages\spyderlib\widgets\externalshell\sitecustomize.py", line 523, in runfile execfile(filename, namespace) File "D:\data\haitaliu\Desktop\Projects\swig_test\Release\test.py", line 4, in <module> print scipy.integrate.quadrature(_swig_test.test_square, 0., 1.) File "C:\Python27\lib\site-packages\scipy\integrate\quadrature.py", line 161, in quadrature newval = fixed_quad(vfunc, a, b, (), n)[0] File "C:\Python27\lib\site-packages\scipy\integrate\quadrature.py", line 61, in fixed_quad return (b-a)/2.0*sum(w*func(y,*args),0), None File "C:\Python27\lib\site-packages\scipy\integrate\quadrature.py", line 90, in vfunc return func(x, *args) TypeError: in method 'test_square', argument 1 of type 'double'

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• Best way in Python to determine all possible intersections in a matrix?

  - by ssweens

  So if I have a matrix (list of lists) of unique words as my column headings, document ids as my row headings, and a 0 or 1 as the values if the word exists in that particular document. What I'd like to know is how to determine all the possible combinations of words and documents where more than one word is in common with more than one document. So something like: [[Docid_3, Docid_5], ['word1', 'word17', 'word23']], [[Docid_3, Docid_9, Docid_334], ['word2', 'word7', 'word23', 'word68', 'word982']], and so on for each possible combination. Would love a solution that provides the complete set of combinations and one that yields only the combinations that are not a subset of another, so from the example, not [[Docid_3, Docid_5], ['word1', 'word17']] since it's a complete subset of the first example. I feel like there is an elegant solution that just isn't coming to mind and the beer isn't helping. Thanks.

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• undo or reverse argsort(), python

  - by Vincent

  Given an array 'a' I would like to sort the array by columns "a.sort(axis=0)" do some stuff to the array and then undo the sort. By that I don't mean re sort but basically reversing how each element was moved. I assume argsort() is what I need but it is not clear to me how to sort an array with the results of argsort() or more importantly apply the reverse/inverse of argsort() Here is a little more detail I have an array a, shape(a) = rXc I need to sort each column aargsort = a.argsort(axis=0) # May use this later aSort = a.sort(axis=0) now average each row aSortRM = asort.mean(axis=1) now replace each col in a row with the row mean. is there a better way than this aWithMeans = ones_like(a) for ind in range(r) # r = number of rows aWithMeans[ind]* aSortRM[ind] Now I need to undo the sort I did in the first step. ????

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• getting smallest of coordinates that differ by N or more in Python

  - by user248237

  suppose I have a list of coordinates: data = [[(10, 20), (100, 120), (0, 5), (50, 60)], [(13, 20), (300, 400), (100, 120), (51, 62)]] and I want to take all tuples that either appear in each list in data, or any tuple that differs from all tuples in lists other than its own by 3 or less. How can I do this efficiently in Python? For the above example, the results should be: [[(100, 120), # since it occurs in both lists (10, 20), (13, 20), # since they differ by only 3 (50, 60), (51, 60)]] (0, 5) and (300, 400) would not be included, since they don't appear in both lists and are not different from elements in lists other than their own by 3 or less. how can this be computed? thanks.

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• Choosing randomly all the elements in the the list just once

  - by Dalek

  How is it possible to randomly choose a number from a list with n elements, n time without picking the same element of the list twice. I wrote a code to choose the sequence number of the elements in the list but it is slow: >>>redshift=np.array([0.92,0.17,0.51,1.33,....,0.41,0.82]) >>>redshift.shape (1225,) exclude=[] k=0 ng=1225 while (k < ng): flag1=0 sq=random.randint(0, ng) while (flag1<1): if sq in exclude: flag1=1 sq=random.randint(0, ng) else: print sq exclude.append(sq) flag1=0 z=redshift[sq] k+=1 It doesn't choose all the sequence number of elements in the list.

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• speeding up parsing of files

  - by user248237

  the following function parses a CSV file into a list of dictionaries, where each element in the list is a dictionary where the values are indexed by the header of the file (assumed to be the first line.) this function is very very slow, taking ~6 seconds for a file that's relatively small (less than 30,000 lines.) how can I speed it up? def csv2dictlist_raw(filename, delimiter='\t'): f = open(filename) header_line = f.readline().strip() header_fields = header_line.split(delimiter) dictlist = [] # convert data to list of dictionaries for line in f: values = map(tryEval, line.strip().split(delimiter)) dictline = dict(zip(header_fields, values)) dictlist.append(dictline) return (dictlist, header_fields) thanks.

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• installing NUMPY for Mac OSX 10.7. (Lion) for use with Python

  - by user1744871

  I Need to use nltk and numpy with Python. I am a newbie to Python and initially used the python 2.7.3 that came with my mac (currently running OSX 10.7.5). I learned that the apple version of python may not be robust so I downloaded the standard version from python.org. I have downloaded the nltk program for Mac OSX 10.7. This seemed to install fine. I am trying to download and install numpy using the instructions from the scipy website. http://www.scipy.org/Installing_SciPy/Mac_OS_X. I cloned numpy from github but when I tried to build it using the following command $ python setup.py build I received the following error MacOS/Python: can't open file 'setup.py': [Errno 2] No such file or directory I also tried to build it using the scons command $ python setupscons.py scons --jobs=2 and received the following error /Library/Frameworks/Python.framework/Versions/2.7/Resources/Python.app/Contents/MacOS/Python: can't open file 'setupscons.py': [Errno 2] No such file or directory Can anyone think of a possible workaround?

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• Can I avoid a threaded UDP socket in Python dropping data?

  - by 666craig

  First off, I'm new to Python and learning on the job, so be gentle! I'm trying to write a threaded Python app for Windows that reads data from a UDP socket (thread-1), writes it to file (thread-2), and displays the live data (thread-3) to a widget (gtk.Image using a gtk.gdk.pixbuf). I'm using queues for communicating data between threads. My problem is that if I start only threads 1 and 3 (so skip the file writing for now), it seems that I lose some data after the first few samples. After this drop it looks fine. Even by letting thread 1 complete before running thread 3, this apparent drop is still there. Apologies for the length of code snippet (I've removed the thread that writes to file), but I felt removing code would just prompt questions. Hope someone can shed some light :-) import socket import threading import Queue import numpy import gtk gtk.gdk.threads_init() import gtk.glade import pygtk class readFromUDPSocket(threading.Thread): def __init__(self, socketUDP, readDataQueue, packetSize, numScans): threading.Thread.__init__(self) self.socketUDP = socketUDP self.readDataQueue = readDataQueue self.packetSize = packetSize self.numScans = numScans def run(self): for scan in range(1, self.numScans + 1): buffer = self.socketUDP.recv(self.packetSize) self.readDataQueue.put(buffer) self.socketUDP.close() print 'myServer finished!' class displayWithGTK(threading.Thread): def __init__(self, displayDataQueue, image, viewArea): threading.Thread.__init__(self) self.displayDataQueue = displayDataQueue self.image = image self.viewWidth = viewArea[0] self.viewHeight = viewArea[1] self.displayData = numpy.zeros((self.viewHeight, self.viewWidth, 3), dtype=numpy.uint16) def run(self): scan = 0 try: while True: if not scan % self.viewWidth: scan = 0 buffer = self.displayDataQueue.get(timeout=0.1) self.displayData[:, scan, 0] = numpy.fromstring(buffer, dtype=numpy.uint16) self.displayData[:, scan, 1] = numpy.fromstring(buffer, dtype=numpy.uint16) self.displayData[:, scan, 2] = numpy.fromstring(buffer, dtype=numpy.uint16) gtk.gdk.threads_enter() self.myPixbuf = gtk.gdk.pixbuf_new_from_data(self.displayData.tostring(), gtk.gdk.COLORSPACE_RGB, False, 8, self.viewWidth, self.viewHeight, self.viewWidth * 3) self.image.set_from_pixbuf(self.myPixbuf) self.image.show() gtk.gdk.threads_leave() scan += 1 except Queue.Empty: print 'myDisplay finished!' pass def quitGUI(obj): print 'Currently active threads: %s' % threading.enumerate() gtk.main_quit() if __name__ == '__main__': # Create socket (IPv4 protocol, datagram (UDP)) and bind to address socketUDP = socket.socket(socket.AF_INET, socket.SOCK_DGRAM) host = '192.168.1.5' port = 1024 socketUDP.bind((host, port)) # Data parameters samplesPerScan = 256 packetsPerSecond = 1200 packetSize = 512 duration = 1 # For now, set a fixed duration to log data numScans = int(packetsPerSecond * duration) # Create array to store data data = numpy.zeros((samplesPerScan, numScans), dtype=numpy.uint16) # Create queue for displaying from readDataQueue = Queue.Queue(numScans) # Build GUI from Glade XML file builder = gtk.Builder() builder.add_from_file('GroundVue.glade') window = builder.get_object('mainwindow') window.connect('destroy', quitGUI) view = builder.get_object('viewport') image = gtk.Image() view.add(image) viewArea = (1200, samplesPerScan) # Instantiate & start threads myServer = readFromUDPSocket(socketUDP, readDataQueue, packetSize, numScans) myDisplay = displayWithGTK(readDataQueue, image, viewArea) myServer.start() myDisplay.start() gtk.gdk.threads_enter() gtk.main() gtk.gdk.threads_leave() print 'gtk.main finished!'

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• Can I avoid a threaded UDP socket in Pyton dropping data?

  - by 666craig

  First off, I'm new to Python and learning on the job, so be gentle! I'm trying to write a threaded Python app for Windows that reads data from a UDP socket (thread-1), writes it to file (thread-2), and displays the live data (thread-3) to a widget (gtk.Image using a gtk.gdk.pixbuf). I'm using queues for communicating data between threads. My problem is that if I start only threads 1 and 3 (so skip the file writing for now), it seems that I lose some data after the first few samples. After this drop it looks fine. Even by letting thread 1 complete before running thread 3, this apparent drop is still there. Apologies for the length of code snippet (I've removed the thread that writes to file), but I felt removing code would just prompt questions. Hope someone can shed some light :-) import socket import threading import Queue import numpy import gtk gtk.gdk.threads_init() import gtk.glade import pygtk class readFromUDPSocket(threading.Thread): def __init__(self, socketUDP, readDataQueue, packetSize, numScans): threading.Thread.__init__(self) self.socketUDP = socketUDP self.readDataQueue = readDataQueue self.packetSize = packetSize self.numScans = numScans def run(self): for scan in range(1, self.numScans + 1): buffer = self.socketUDP.recv(self.packetSize) self.readDataQueue.put(buffer) self.socketUDP.close() print 'myServer finished!' class displayWithGTK(threading.Thread): def __init__(self, displayDataQueue, image, viewArea): threading.Thread.__init__(self) self.displayDataQueue = displayDataQueue self.image = image self.viewWidth = viewArea[0] self.viewHeight = viewArea[1] self.displayData = numpy.zeros((self.viewHeight, self.viewWidth, 3), dtype=numpy.uint16) def run(self): scan = 0 try: while True: if not scan % self.viewWidth: scan = 0 buffer = self.displayDataQueue.get(timeout=0.1) self.displayData[:, scan, 0] = numpy.fromstring(buffer, dtype=numpy.uint16) self.displayData[:, scan, 1] = numpy.fromstring(buffer, dtype=numpy.uint16) self.displayData[:, scan, 2] = numpy.fromstring(buffer, dtype=numpy.uint16) gtk.gdk.threads_enter() self.myPixbuf = gtk.gdk.pixbuf_new_from_data(self.displayData.tostring(), gtk.gdk.COLORSPACE_RGB, False, 8, self.viewWidth, self.viewHeight, self.viewWidth * 3) self.image.set_from_pixbuf(self.myPixbuf) self.image.show() gtk.gdk.threads_leave() scan += 1 except Queue.Empty: print 'myDisplay finished!' pass def quitGUI(obj): print 'Currently active threads: %s' % threading.enumerate() gtk.main_quit() if __name__ == '__main__': # Create socket (IPv4 protocol, datagram (UDP)) and bind to address socketUDP = socket.socket(socket.AF_INET, socket.SOCK_DGRAM) host = '192.168.1.5' port = 1024 socketUDP.bind((host, port)) # Data parameters samplesPerScan = 256 packetsPerSecond = 1200 packetSize = 512 duration = 1 # For now, set a fixed duration to log data numScans = int(packetsPerSecond * duration) # Create array to store data data = numpy.zeros((samplesPerScan, numScans), dtype=numpy.uint16) # Create queue for displaying from readDataQueue = Queue.Queue(numScans) # Build GUI from Glade XML file builder = gtk.Builder() builder.add_from_file('GroundVue.glade') window = builder.get_object('mainwindow') window.connect('destroy', quitGUI) view = builder.get_object('viewport') image = gtk.Image() view.add(image) viewArea = (1200, samplesPerScan) # Instantiate & start threads myServer = readFromUDPSocket(socketUDP, readDataQueue, packetSize, numScans) myDisplay = displayWithGTK(readDataQueue, image, viewArea) myServer.start() myDisplay.start() gtk.gdk.threads_enter() gtk.main() gtk.gdk.threads_leave() print 'gtk.main finished!'

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• How to remove the boundary effects arising due to zero padding in scipy/numpy fft?

  - by Omkar

  I have made a python code to smoothen a given signal using the Weierstrass transform, which is basically the convolution of a normalised gaussian with a signal. The code is as follows: #Importing relevant libraries from __future__ import division from scipy.signal import fftconvolve import numpy as np def smooth_func(sig, x, t= 0.002): N = len(x) x1 = x[-1] x0 = x[0] # defining a new array y which is symmetric around zero, to make the gaussian symmetric. y = np.linspace(-(x1-x0)/2, (x1-x0)/2, N) #gaussian centered around zero. gaus = np.exp(-y**(2)/t) #using fftconvolve to speed up the convolution; gaus.sum() is the normalization constant. return fftconvolve(sig, gaus/gaus.sum(), mode='same') If I run this code for say a step function, it smoothens the corner, but at the boundary it interprets another corner and smoothens that too, as a result giving unnecessary behaviour at the boundary. I explain this with a figure shown in the link below. Boundary effects This problem does not arise if we directly integrate to find convolution. Hence the problem is not in Weierstrass transform, and hence the problem is in the fftconvolve function of scipy. To understand why this problem arises we first need to understand the working of fftconvolve in scipy. The fftconvolve function basically uses the convolution theorem to speed up the computation. In short it says: convolution(int1,int2)=ifft(fft(int1)*fft(int2)) If we directly apply this theorem we dont get the desired result. To get the desired result we need to take the fft on a array double the size of max(int1,int2). But this leads to the undesired boundary effects. This is because in the fft code, if size(int) is greater than the size(over which to take fft) it zero pads the input and then takes the fft. This zero padding is exactly what is responsible for the undesired boundary effects. Can you suggest a way to remove this boundary effects? I have tried to remove it by a simple trick. After smoothening the function I am compairing the value of the smoothened signal with the original signal near the boundaries and if they dont match I replace the value of the smoothened func with the input signal at that point. It is as follows: i = 0 eps=1e-3 while abs(smooth[i]-sig[i])> eps: #compairing the signals on the left boundary smooth[i] = sig[i] i = i + 1 j = -1 while abs(smooth[j]-sig[j])> eps: # compairing on the right boundary. smooth[j] = sig[j] j = j - 1 There is a problem with this method, because of using an epsilon there are small jumps in the smoothened function, as shown below: jumps in the smooth func Can there be any changes made in the above method to solve this boundary problem?

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• Problem with Python3 picking Python2 package

  - by zetah

  I installed python3-numpy package, but trying to import it in Python3 interpreter I get this: $ python3 Python 3.2.3 (default, May 3 2012, 15:54:42) [GCC 4.6.3] on linux2 Type "help", "copyright", "credits" or "license" for more information. >>> import numpy Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/home/zetah/.local/lib/python2.7/site-packages/numpy/__init__.py", line 128, in <module> from version import git_revision as __git_revision__ ImportError: No module named version >>> Looking in Synaptic I see python3-numpy is installed in /usr/lib/python3/dist-packages/numpy/ Why is it picking wrong package and what can I do to remedy this? Update: OK, in my ~/.profile I have this line: PYTHONPATH=$PYTHONPATH:$HOME/.local/lib/python2.7/site-packages but if I remove this line then my Python 2.7 local packages (which I build from source) wont work Update 2: Everything seems to work perfect without $PYTHONPATH. I guess it was in my .profile file for nothing Please close this question

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• What is the easiest way to read wav-files using Python [summary]?

  - by Roman

  I want to use Python to access a wav-file and write its content in a form which allows me to analyze it (let's say arrays). I heard that "audiolab" is a suitable tool for that (it transforms numpy arrays into wav and vica versa). I have installed the "audiolab" but I had a problem with the version of numpy (I could not "from numpy.testing import Tester"). I had 1.1.1. version of numpy. I have installed a newer version on numpy (1.4.0). But then I got a new set of errors: Traceback (most recent call last): File "test.py", line 7, in import scikits.audiolab File "/usr/lib/python2.5/site-packages/scikits/audiolab/init.py", line 25, in from pysndfile import formatinfo, sndfile File "/usr/lib/python2.5/site-packages/scikits/audiolab/pysndfile/init.py", line 1, in from _sndfile import Sndfile, Format, available_file_formats, available_encodings File "numpy.pxd", line 30, in scikits.audiolab.pysndfile._sndfile (scikits/audiolab/pysndfile/_sndfile.c:9632) ValueError: numpy.dtype does not appear to be the correct type object I gave up to use audiolab and thought that I can use "wave" package to read in a wav-file. I asked a question about that but people recommended to use scipy instead. OK, I decided to focus on scipy (I have 0.6.0. version). But when I tried to do the following: from scipy.io import wavfile x = wavfile.read('/usr/share/sounds/purple/receive.wav') I get the following: Traceback (most recent call last): File "test3.py", line 4, in <module> from scipy.io import wavfile File "/usr/lib/python2.5/site-packages/scipy/io/__init__.py", line 23, in <module> from numpy.testing import NumpyTest ImportError: cannot import name NumpyTest So, I gave up to use scipy. Can I use just wave package? I do not need much. I just need to have content of wav-file in human readable format and than I will figure out what to do with that.

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• side effect gotchas in python/numpy? horror stories and narrow escapes wanted

  - by shabbychef

  I am considering moving from Matlab to Python/numpy for data analysis and numerical simulations. I have used Matlab (and SML-NJ) for years, and am very comfortable in the functional environment without side effects (barring I/O), but am a little reluctant about the side effects in Python. Can people share their favorite gotchas regarding side effects, and if possible, how they got around them? As an example, I was a bit surprised when I tried the following code in Python: lofls = [[]] * 4 #an accident waiting to happen! lofls[0].append(7) #not what I was expecting... print lofls #gives [[7], [7], [7], [7]] #instead, I should have done this (I think) lofls = [[] for x in range(4)] lofls[0].append(7) #only appends to the first list print lofls #gives [[7], [], [], []] thanks in advance

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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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• How to install suggested packages in apt-get

  - by Alaa Ali

  EDIT: I solved my issue. I will answer my own question, but in 5 hours because I don't have permission now. I know the question has been asked before, but please hear me out. So I wanted to install screenlets. I ran sudo apt-get install screenlets, and this is what I got: The following extra packages will be installed: libart-2.0-2 libbonobo2-0 libbonobo2-common libbonoboui2-0 libbonoboui2-common libgnome2-0 libgnomecanvas2-0 libgnomecanvas2-common libgnomeui-0 libgnomeui-common libtidy-0.99-0 python-beautifulsoup python-evolution python-feedparser python-gmenu python-gnome2 python-numpy python-pyorbit python-rsvg python-tz python-utidylib screenlets-pack-basic Suggested packages: libbonobo2-bin python-gnome2-doc python-numpy-doc python-numpy-dbg python-nose python-dev gfortran python-pyorbit-dbg screenlets-pack-all python-dcop Recommended packages: python-numeric python-gnome2-extras The following NEW packages will be installed: libart-2.0-2 libbonobo2-0 libbonobo2-common libbonoboui2-0 libbonoboui2-common libgnome2-0 libgnomecanvas2-0 libgnomecanvas2-common libgnomeui-0 libgnomeui-common libtidy-0.99-0 python-beautifulsoup python-evolution python-feedparser python-gmenu python-gnome2 python-numpy python-pyorbit python-rsvg python-tz python-utidylib screenlets screenlets-pack-basic 0 upgraded, 23 newly installed, 0 to remove and 2 not upgraded. People say that Recommended packages are installed by default, but they are clearly not included in the NEW packages that will be installed above. I also decided to include the Suggested packages in the installation, so I ran sudo apt-get --install-suggests install screenlets instead, but I got a HUGE list of NEW packages that will be installed; that number is precisely 0 upgraded, 944 newly installed, 0 to remove and 2 not upgraded. Should'nt I be getting only around 10 extra packages?

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• IPython tab completion not working

  - by djpark121

  Tab completion on IPython seems not to be working. For example, import numpy numpy.<tab> simply adds a tab. import numpy num<tab> just adds a tab, too. Could you please suggest some possible causes for this problem? I am running Windows 7 and Python 2.6.5.

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• compute mean in python for a generator

  - by nmaxwell

  Hi, I'm doing some statistics work, I have a (large) collection of random numbers to compute the mean of, I'd like to work with generators, because I just need to compute the mean, so I don't need to store the numbers. The problem is that numpy.mean breaks if you pass it a generator. I can write a simple function to do what I want, but I'm wondering if there's a proper, built-in way to do this? It would be nice if I could say "sum(values)/len(values)", but len doesn't work for genetators, and sum already consumed values. here's an example: import numpy def my_mean(values): n = 0 Sum = 0.0 try: while True: Sum += next(values) n += 1 except StopIteration: pass return float(Sum)/n X = [k for k in range(1,7)] Y = (k for k in range(1,7)) print numpy.mean(X) print my_mean(Y) these both give the same, correct, answer, buy my_mean doesn't work for lists, and numpy.mean doesn't work for generators. I really like the idea of working with generators, but details like this seem to spoil things. thanks for any help -nick

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• C++ Arrays manipulations (python-like operations)

  - by Linai

  Hi Guys, I'm trying to figure out the best C++ library/package for array manipulations in a manner of python. Basically I need a simplicity like this: values = numpy.array(inp.data) idx1 = numpy.where(values > -2.14) idx2 = numpy.where(values < 2.0) res1 = (values[idx1] - diff1)/1000 res1 = (values[idx2] - diff2)*1000 In python it's just 5 lines, but the simplest way in C++ i can think of is quite a number of nested loops. Pls advise..

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• Why do I get "unsupported architecture" errors trying to install a Python library in OSX?

  - by Emma518

  I am trying to install a Python library in the Presto package, source http://www.cv.nrao.edu/~sransom/presto/ Using 'gmake fftfit' I get the following error: cd fftfit_src ; f2py-2.7 -c fftfit.pyf *.f running build running config_cc unifing config_cc, config, build_clib, build_ext, build commands --compiler options running config_fc unifing config_fc, config, build_clib, build_ext, build commands --fcompiler options running build_src build_src building extension "fftfit" sources creating /var/folders/sx/j_l_qvys4bv00_38pfvy3m8h0000gp/T/tmp9MmLz8/src.macosx-10.9-x86_64-2.7 f2py options: [] f2py: fftfit.pyf Reading fortran codes... Reading file 'fftfit.pyf' (format:free) Post-processing... Block: fftfit Block: cprof Block: fftfit Post-processing (stage 2)... Building modules... Building module "fftfit"... Constructing wrapper function "cprof"... c,amp,pha = cprof(y,[nmax,nh]) Constructing wrapper function "fftfit"... shift,eshift,snr,esnr,b,errb,ngood = fftfit(prof,s,phi,[nmax]) Wrote C/API module "fftfit" to file "/var/folders/sx/j_l_qvys4bv00_38pfvy3m8h0000gp/T/tmp9MmLz8/src.macosx-10.9-x86_64- 2.7/fftfitmodule.c" adding '/var/folders/sx/j_l_qvys4bv00_38pfvy3m8h0000gp/T/tmp9MmLz8/src.macosx-10.9-x86_64-2.7/fortranobject.c' to sources. adding '/var/folders/sx/j_l_qvys4bv00_38pfvy3m8h0000gp/T/tmp9MmLz8/src.macosx-10.9-x86_64-2.7' to include_dirs. copying /Library/Python/2.7/site-packages/numpy-1.8.2-py2.7-macosx-10.9- intel.egg/numpy/f2py/src/fortranobject.c -> /var/folders/sx/j_l_qvys4bv00_38pfvy3m8h0000gp/T/tmp9MmLz8/src.macosx-10.9-x86_64-2.7 copying /Library/Python/2.7/site-packages/numpy-1.8.2-py2.7-macosx-10.9-intel.egg/numpy/f2py/src/fortranobject.h -> /var/folders/sx/j_l_qvys4bv00_38pfvy3m8h0000gp/T/tmp9MmLz8/src.macosx-10.9-x86_64-2.7 build_src: building npy-pkg config files running build_ext customize UnixCCompiler customize UnixCCompiler using build_ext customize Gnu95FCompiler Found executable /usr/local/bin/gfortran customize Gnu95FCompiler customize Gnu95FCompiler using build_ext building 'fftfit' extension compiling C sources C compiler: /usr/bin/clang -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -arch ppc -arch i386 -arch x86_64 -g -O2 creating /var/folders/sx/j_l_qvys4bv00_38pfvy3m8h0000gp/T/tmp9MmLz8/var creating /var/folders/sx/j_l_qvys4bv00_38pfvy3m8h0000gp/T/tmp9MmLz8/var/folders creating /var/folders/sx/j_l_qvys4bv00_38pfvy3m8h0000gp/T/tmp9MmLz8/var/folders/sx creating /var/folders/sx/j_l_qvys4bv00_38pfvy3m8h0000gp/T/tmp9MmLz8/var/folders/sx/j_l_qvys4bv00_38pfvy3m8h0000gp creating /var/folders/sx/j_l_qvys4bv00_38pfvy3m8h0000gp/T/tmp9MmLz8/var/folders/sx/j_l_qvys4bv00_38pfvy3m8h00 00gp/T creating /var/folders/sx/j_l_qvys4bv00_38pfvy3m8h0000gp/T/tmp9MmLz8/var/folders/sx/j_l_qvys4bv00_38pfvy3m8h00 00gp/T/tmp9MmLz8 creating /var/folders/sx/j_l_qvys4bv00_38pfvy3m8h0000gp/T/tmp9MmLz8/var/folders/sx/j_l_qvys4bv00_38pfvy3m8h00 00gp/T/tmp9MmLz8/src.macosx-10.9-x86_64-2.7 compile options: '-I/var/folders/sx/j_l_qvys4bv00_38pfvy3m8h0000gp/T/tmp9MmLz8/src.macosx-10.9- x86_64-2.7 -I/Library/Python/2.7/site-packages/numpy-1.8.2-py2.7-macosx-10.9- intel.egg/numpy/core/include - I/opt/local/Library/Frameworks/Python.framework/Versions/2.7/include/python2.7 -c' clang: /var/folders/sx/j_l_qvys4bv00_38pfvy3m8h0000gp/T/tmp9MmLz8/src.macosx-10.9-x86_64- 2.7/fftfitmodule.c In file included from /var/folders/sx/j_l_qvys4bv00_38pfvy3m8h0000gp/T/tmp9MmLz8/src.macosx- 10.9-x86_64-2.7/fftfitmodule.c:16: In file included from /opt/local/Library/Frameworks/Python.framework/Versions/2.7/include/python2.7/Python.h:19: In file included from /Applications/Xcode.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr/bin/../lib/clang/ 5.1/include/limits.h:38: In file included from /usr/include/limits.h:63: /usr/include/sys/cdefs.h:658:2: error: Unsupported architecture #error Unsupported architecture ^ In file included from /var/folders/sx/j_l_qvys4bv00_38pfvy3m8h0000gp/T/tmp9MmLz8/src.macosx- 10.9-x86_64-2.7/fftfitmodule.c:16: In file included from /opt/local/Library/Frameworks/Python.framework/Versions/2.7/include/python2.7/Python.h:19: In file included from /Applications/Xcode.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr/bin/../lib/clang/ 5.1/include/limits.h:38: In file included from /usr/include/limits.h:64: /usr/include/machine/limits.h:8:2: error: architecture not supported #error architecture not supported ^ In file included from /var/folders/sx/j_l_qvys4bv00_38pfvy3m8h0000gp/T/tmp9MmLz8/src.macosx- 10.9-x86_64-2.7/fftfitmodule.c:16: In file included from /opt/local/Library/Frameworks/Python.framework/Versions/2.7/include/python2.7/Python.h:33: In file included from /usr/include/stdio.h:67: In file included from /usr/include/_types.h:27: In file included from /usr/include/sys/_types.h:33: /usr/include/machine/_types.h:34:2: error: architecture not supported #error architecture not supported ^ In file included from /var/folders/sx/j_l_qvys4bv00_38pfvy3m8h0000gp/T/tmp9MmLz8/src.macosx- 10.9-x86_64-2.7/fftfitmodule.c:16: In file included from /opt/local/Library/Frameworks/Python.framework/Versions/2.7/include/python2.7/Python.h:33: In file included from /usr/include/stdio.h:67: In file included from /usr/include/_types.h:27: /usr/include/sys/_types.h:94:9: error: unknown type name '__int64_t' typedef __int64_t __darwin_blkcnt_t; /* total blocks */ ^ /usr/include/sys/_types.h:95:9: error: unknown type name '__int32_t' typedef __int32_t __darwin_blksize_t; /* preferred block size */ ^ /usr/include/sys/_types.h:96:9: error: unknown type name '__int32_t' typedef __int32_t __darwin_dev_t; /* dev_t */ ^ /usr/include/sys/_types.h:99:9: error: unknown type name '__uint32_t' typedef __uint32_t __darwin_gid_t; /* [???] process and group IDs */ ^ /usr/include/sys/_types.h:100:9: error: unknown type name '__uint32_t' typedef __uint32_t __darwin_id_t; /* [XSI] pid_t, uid_t, or gid_t*/ ^ /usr/include/sys/_types.h:101:9: error: unknown type name '__uint64_t' typedef __uint64_t __darwin_ino64_t; /* [???] Used for 64 bit inodes */ ^ /usr/include/sys/_types.h:107:9: error: unknown type name '__darwin_natural_t' typedef __darwin_natural_t __darwin_mach_port_name_t; /* Used by mach */ ^ /usr/include/sys/_types.h:109:9: error: unknown type name '__uint16_t' typedef __uint16_t __darwin_mode_t; /* [???] Some file attributes */ ^ /usr/include/sys/_types.h:110:9: error: unknown type name '__int64_t' typedef __int64_t __darwin_off_t; /* [???] Used for file sizes */ ^ /usr/include/sys/_types.h:111:9: error: unknown type name '__int32_t' typedef __int32_t __darwin_pid_t; /* [???] process and group IDs */ ^ /usr/include/sys/_types.h:131:9: error: unknown type name '__uint32_t' typedef __uint32_t __darwin_sigset_t; /* [???] signal set */ ^ /usr/include/sys/_types.h:132:9: error: unknown type name '__int32_t' typedef __int32_t __darwin_suseconds_t; /* [???] microseconds */ ^ /usr/include/sys/_types.h:133:9: error: unknown type name '__uint32_t' typedef __uint32_t __darwin_uid_t; /* [???] user IDs */ ^ /usr/include/sys/_types.h:134:9: error: unknown type name '__uint32_t' typedef __uint32_t __darwin_useconds_t; /* [???] microseconds */ ^ In file included from /var/folders/sx/j_l_qvys4bv00_38pfvy3m8h0000gp/T/tmp9MmLz8/src.macosx- 10.9-x86_64-2.7/fftfitmodule.c:16: In file included from /opt/local/Library/Frameworks/Python.framework/Versions/2.7/include/python2.7/Python.h:33: In file included from /usr/include/stdio.h:71: /usr/include/sys/_types/_va_list.h:31:9: error: unknown type name '__darwin_va_list'; did you mean '__builtin_va_list'? typedef __darwin_va_list va_list; ^ note: '__builtin_va_list' declared here In file included from /var/folders/sx/j_l_qvys4bv00_38pfvy3m8h0000gp/T/tmp9MmLz8/src.macosx- 10.9-x86_64-2.7/fftfitmodule.c:16: In file included from /opt/local/Library/Frameworks/Python.framework/Versions/2.7/include/python2.7/Python.h:33: In file included from /usr/include/stdio.h:72: /usr/include/sys/_types/_size_t.h:30:9: error: unknown type name '__darwin_size_t'; did you mean '__darwin_ino_t'? typedef __darwin_size_t size_t; ^ /usr/include/sys/_types.h:103:26: note: '__darwin_ino_t' declared here typedef __darwin_ino64_t __darwin_ino_t; /* [???] Used for inodes */ ^ fatal error: too many errors emitted, stopping now [-ferror-limit=] 20 errors generated. In file included from /var/folders/sx/j_l_qvys4bv00_38pfvy3m8h0000gp/T/tmp9MmLz8/src.macosx- 10.9-x86_64-2.7/fftfitmodule.c:16: In file included from /opt/local/Library/Frameworks/Python.framework/Versions/2.7/include/python2.7/Python.h:19: In file included from /Applications/Xcode.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr/bin/../lib/clang/5.1/include/limits.h:38: In file included from /usr/include/limits.h:63: /usr/include/sys/cdefs.h:658:2: error: Unsupported architecture #error Unsupported architecture ^ In file included from /var/folders/sx/j_l_qvys4bv00_38pfvy3m8h0000gp/T/tmp9MmLz8/src.macosx- 10.9-x86_64-2.7/fftfitmodule.c:16: In file included from /opt/local/Library/Frameworks/Python.framework/Versions/2.7/include/python2.7/Python.h:19: In file included from /Applications/Xcode.app/Contents/Developer/Toolchains/XcodeDefault.xctoolchain/usr/bin/../lib/clang/ 5.1/include/limits.h:38: In file included from /usr/include/limits.h:64: /usr/include/machine/limits.h:8:2: error: architecture not supported #error architecture not supported ^ In file included from /var/folders/sx/j_l_qvys4bv00_38pfvy3m8h0000gp/T/tmp9MmLz8/src.macosx- 10.9-x86_64-2.7/fftfitmodule.c:16: In file included from /opt/local/Library/Frameworks/Python.framework/Versions/2.7/include/python2.7/Python.h:33: In file included from /usr/include/stdio.h:67: In file included from /usr/include/_types.h:27: In file included from /usr/include/sys/_types.h:33: /usr/include/machine/_types.h:34:2: error: architecture not supported #error architecture not supported ^ In file included from /var/folders/sx/j_l_qvys4bv00_38pfvy3m8h0000gp/T/tmp9MmLz8/src.macosx- 10.9-x86_64-2.7/fftfitmodule.c:16: In file included from /opt/local/Library/Frameworks/Python.framework/Versions/2.7/include/python2.7/Python.h:33: In file included from /usr/include/stdio.h:67: In file included from /usr/include/_types.h:27: /usr/include/sys/_types.h:94:9: error: unknown type name '__int64_t' typedef __int64_t __darwin_blkcnt_t; /* total blocks */ ^ /usr/include/sys/_types.h:95:9: error: unknown type name '__int32_t' typedef __int32_t __darwin_blksize_t; /* preferred block size */ ^ /usr/include/sys/_types.h:96:9: error: unknown type name '__int32_t' typedef __int32_t __darwin_dev_t; /* dev_t */ ^ /usr/include/sys/_types.h:99:9: error: unknown type name '__uint32_t' typedef __uint32_t __darwin_gid_t; /* [???] process and group IDs */ ^ /usr/include/sys/_types.h:100:9: error: unknown type name '__uint32_t' typedef __uint32_t __darwin_id_t; /* [XSI] pid_t, uid_t, or gid_t*/ ^ /usr/include/sys/_types.h:101:9: error: unknown type name '__uint64_t' typedef __uint64_t __darwin_ino64_t; /* [???] Used for 64 bit inodes */ ^ /usr/include/sys/_types.h:107:9: error: unknown type name '__darwin_natural_t' typedef __darwin_natural_t __darwin_mach_port_name_t; /* Used by mach */ ^ /usr/include/sys/_types.h:109:9: error: unknown type name '__uint16_t' typedef __uint16_t __darwin_mode_t; /* [???] Some file attributes */ ^ /usr/include/sys/_types.h:110:9: error: unknown type name '__int64_t' typedef __int64_t __darwin_off_t; /* [???] Used for file sizes */ ^ /usr/include/sys/_types.h:111:9: error: unknown type name '__int32_t' typedef __int32_t __darwin_pid_t; /* [???] process and group IDs */ ^ /usr/include/sys/_types.h:131:9: error: unknown type name '__uint32_t' typedef __uint32_t __darwin_sigset_t; /* [???] signal set */ ^ /usr/include/sys/_types.h:132:9: error: unknown type name '__int32_t' typedef __int32_t __darwin_suseconds_t; /* [???] microseconds */ ^ /usr/include/sys/_types.h:133:9: error: unknown type name '__uint32_t' typedef __uint32_t __darwin_uid_t; /* [???] user IDs */ ^ /usr/include/sys/_types.h:134:9: error: unknown type name '__uint32_t' typedef __uint32_t __darwin_useconds_t; /* [???] microseconds */ ^ In file included from /var/folders/sx/j_l_qvys4bv00_38pfvy3m8h0000gp/T/tmp9MmLz8/src.macosx-10.9-x86_64-2.7/fftfitmodule.c:16: In file included from /opt/local/Library/Frameworks/Python.framework/Versions/2.7/include/python2.7/Python.h:33: In file included from /usr/include/stdio.h:71: /usr/include/sys/_types/_va_list.h:31:9: error: unknown type name '__darwin_va_list'; did you mean '__builtin_va_list'? typedef __darwin_va_list va_list; ^ note: '__builtin_va_list' declared here In file included from /var/folders/sx/j_l_qvys4bv00_38pfvy3m8h0000gp/T/tmp9MmLz8/src.macosx-10.9-x86_64-2.7/fftfitmodule.c:16: In file included from /opt/local/Library/Frameworks/Python.framework/Versions/2.7/include/python2.7/Python.h:33: In file included from /usr/include/stdio.h:72: /usr/include/sys/_types/_size_t.h:30:9: error: unknown type name '__darwin_size_t'; did you mean '__darwin_ino_t'? typedef __darwin_size_t size_t; ^ /usr/include/sys/_types.h:103:26: note: '__darwin_ino_t' declared here typedef __darwin_ino64_t __darwin_ino_t; /* [???] Used for inodes */ ^ fatal error: too many errors emitted, stopping now [-ferror-limit=] 20 errors generated. error: Command "/usr/bin/clang -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -arch ppc -arch i386 -arch x86_64 -g -O2 -I/var/folders/sx/j_l_qvys4bv00_38pfvy3m8h0000gp/T/tmp9MmLz8/src.macosx- 10.9-x86_64-2.7 -I/Library/Python/2.7/site-packages/numpy-1.8.2-py2.7-macosx-10.9- intel.egg/numpy/core/include - I/opt/local/Library/Frameworks/Python.framework/Versions/2.7/include/python2.7 -c /var/folders/sx/j_l_qvys4bv00_38pfvy3m8h0000gp/T/tmp9MmLz8/src.macosx-10.9-x86_64-2.7/fftfitmodule.c -o /var/folders/sx/j_l_qvys4bv00_38pfvy3m8h0000gp/T/tmp9MmLz8/var/folders/sx/j_l_qvys4bv00_38pfvy3m8h00 00gp/T/tmp9MmLz8/src.macosx-10.9-x86_64-2.7/fftfitmodule.o" failed with exit status 1 Makefile:5: recipe for target 'fftfit' failed gmake: *** [fftfit] Error 1 How can I solve this architecture problem?

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• How to install matplotlib on OS X?

  - by Paperflyer

  I want to install matplotlib on OS X. If possible, using homebrew. I installed Python 2.7.1 using brew install python, I modified my path to use it I installed pip using brew install pip I installed numpy 1.5.1 using pip install numpy I installed scipy 0.8.0 using pip install scipy This is where it gets hairy. pip install matplotlib will fetch the wrong version of matplotlib, which is incompatible with the recent version of numpy. The solution is to fetch the correct version of matplotlib manually: pip install -f http://sourceforge.net/projects/matplotlib/files/matplotlib/matplotlib-1.0.1/matplotlib-1.0.1.tar.gz matplotlib But, that version fails to compile since it can't find the freetype headers: In file included from src/ft2font.cpp:1: src/ft2font.h:14:22: error: ft2build.h: No such file or directory These headers are actually installed in /usr/X11/include as part of the X11 developer tools. So, how can I make matplotlib use these headers?

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• Memory limiting solutions for greedy applications that can crash OS?

  - by Hooked

  I use my computer for scientific programming. It has a healthy 8GB of RAM and 12GB of swap space. Often, as my problems have gotten larger, I exceed all of the available RAM. Rather than crashing (which would be preferred), it seems Ubuntu starts loading everything into swap, including Unity and any open terminals. If I don't catch a run-away program in time, there is nothing I can do but wait - it takes 4-5 minutes to switch to a command prompt eg. Ctrl-Alt-F2 where I can kill the offending process. Since my own stupidity is out of scope of this forum, how can I prevent Ubuntu from crashing via thrashing when I use up all of the available memory from a single offending program? At-home experiment*! Open a terminal, launch python and if you have numpy installed try this: >>> import numpy >>> [numpy.zeros((10**4, 10**4)) for _ in xrange(50)] * Warning: may have adverse effects, monitor the process via iotop or top to kill it in time. If not, I'll see you after your reboot.

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