I have been asked to test a library provided by a 3rd party. The library is known to be accurate to n significant figures. Any less significant errors can safely be ignored. I want to write a function to help me compare the results: def nearlyequal( a, b, sigfig=5 ): The purpose of this function is to determine if two floating-point n...
I need to sort two arrays simultaneously, or rather I need to sort one of the arrays and bring the corresponding element of its associated array with it as I sort. That is if the array is [(5, 33), (4, 44), (3, 55)] and I sort by the first axis (labeled below dtype='alpha') then I want: [(3.0, 55.0) (4.0, 44.0) (5.0, 33.0)]. These are ...
I'm sure I must be being very dumb, but I can't figure out how to use an array or matrix in the way that I would normally use a list. I.e., I want to create an empty array (or matrix) and then add one column (or row) to it at a time. At the moment the only way I can find to do this is like: mat = None for col in columns: if mat is ...
I am working at some plots and statistics for work and I am not sure how I can do some statistics using numpy: I have a list of prices and another one of basePrices. And I want to know how many prices are with X percent above basePrice, how many are with Y percent above basePrice. Is there a simple way to do that using numpy? ...
I read the documentation on NumPy C API I could find, but still wasn't able to find out whether there is a possibility to construct a matrix object with C API — not a two-dimensional array. The function is intended for work with math matrices, and I don't want strange results if the user calls matrix multiplication forgetting to convert ...
I'm just starting with NumPy so I may be missing some core concepts... What's the best way to create a NumPy array from a dictionary whose values are lists? Something like this: d = { 1: [10,20,30] , 2: [50,60], 3: [100,200,300,400,500] } Should turn into something like: data = [ [10,20,30,?,?], [50,60,?,?,?], [100,200,300,40...
On my 64-bit Debian/Lenny system (4GByte RAM + 4GByte swap partition) I can successfully do: v=array(10000*random([512,512,512]),dtype=np.int16) f=fftn(v) but with f being a np.complex128 the memory consumption is shocking, and I can't do much more with the result (e.g modulate the coefficients and then f=ifftn(f) ) without a MemoryEr...
Hi, I need to do auto-correlation of a set of numbers, which as I understand it is just the correlation of the set with itself. I've tried it using numpy's correlate function, but I don't believe the result, as it almost always gives a vector where the first number is not the largest, as it ought to be. So, this question is really tw...
The pickle module seems to use string escape characters when pickling; this becomes inefficient e.g. on numpy arrays. Consider the following z = numpy.zeros(1000, numpy.uint8) len(z.dumps()) len(cPickle.dumps(z.dumps())) The lengths are 1133 characters and 4249 characters respectively. z.dumps() reveals something like "\x00\x00" (act...
I've been asked to provide Numpy & Scipy as python egg files. Unfortunately Numpy and Scipy do not make official releases of their product in .egg form for a Win32 platform - that means if I want eggs then I have to compile them myself. At the moment my employer provides Visual Studio.Net 2003, which will compile no version of Numpy lat...
I was happy in my world of python and matplotlib with a good level of familiarity. I notied Xcode on my Mac wasn't working so I installed the latest version from Apple and it somehow broke my install of matplotlib (or numpy?)! I'm now getting ... /sw/lib/python2.5/site-packages/matplotlib-0.91.1-py2.5-macosx- 10.5-i386.egg/matplotlib/n...
While idly surfing the namespace I noticed an odd looking object called "Ellipsis", it does not seem to be or do anything special, but it's a globally available builtin. After a search I found that it is used in some obscure variant of the slicing syntax by Numpy and Scipy... but almost nothing else. Was this object added to the lang...
Surely a 0d array is scalar, but Numpy does not seem to think so... am I missing something or am I just misunderstanding the concept? >>> foo = numpy.array(1.11111111111, numpy.float64) >>> numpy.ndim(foo) 0 >>> numpy.isscalar(foo) False >>> foo.item() 1.11111111111 ...
I'd like to produce sounds that would resemble audio from real instruments. The problem is that I have very little clue how to get that. What I know this far from real instruments is that sounds they output are rarely clean. But how to produce such unclean sounds? This far I've gotten to do this, it produces quite plain sound from whic...
Hi, Let's say I have a set of vectors (readings from sensor 1, readings from sensor 2, readings from sensor 3 -- indexed first by timestamp and then by sensor id) that I'd like to correlate to a separate set of vectors (temperature, humidity, etc -- also all indexed first by timestamp and secondly by type). What is the cleanest way in ...
I would like to calculate a hash of a Python class containing a dataset for Machine Learning. The hash is meant to be used for caching, so I was thinking of md5 or sha1. The problem is that most of the data is stored in NumPy arrays; these do not provide a __hash__() member. Currently I do a pickle.dumps() for each member and calculate a...
This is what I need to do- I have this equation- Ax = y Where A is a rational m*n matrix (m<=n), and x and y are vectors of the right size. I know A and y, I don't know what x is equal to. I also know that there is no x where Ax equals exactly y. I want to find the vector x' such that Ax' is as close as possible to y. Meaning that (Ax...
I have a 2d array that looks like this: XX xx What's the most efficient way to add an extra row and column: xxy xxy yyy For bonus points, I'd like to also be able to knock out single rows and columns, so for example in the matrix below I'd like to be able to knock out all of the a's leaving only the x's - specifically I'm trying to...
I'm interested in converting a numpy array into a sparse dictionary as quickly as possible. Let me elaborate: Given the array: numpy.array([12,0,0,0,3,0,0,1]) I wish to produce the dictionary: {0:12, 4:3, 7:1} As you can see, we are simply converting the sequence type into an explicit mapping from indices that are nonzero to their...
I'm using Python and Numpy to calculate a best fit polynomial of arbitrary degree. I pass a list of x values, y values, and the degree of the polynomial I want to fit (linear, quadratic, etc.). This much works, but I also want to calculate r (coefficient of correlation) and r-squared(coefficient of determination). I am comparing my re...