Hi! I'v got two numpy arrays. The first array contains some zeros (which are distributed randomly over the length of the array), which I would like to remove. My issue is that I would also like to remove the entries of the second array at the index positions where the first array elements are zero. I only came up with a very cumbers...
It was recently asked how to do a file slurp in python: link text And it was recommended to use something like with open('x.txt') as x: f = x.read() How would I go about doing this to read the file in and convert the endian representation of the data? For example, I have a 1GB binary file that's just a bunch of single precision flo...
I would like to use use numpy's least square algorithm to solve for a camera matrix from 6 known 3D -> 2D point correspondence. I have been using this website as a reference: http://homepages.inf.ed.ac.uk/rbf/CVonline/LOCAL%5FCOPIES/OWENS/LECT9/node4.html Currently my camera matrix seems to have very small values: [[ -1.01534118e-11 ...
I'm using pythoncomplete omnicompletion in vim. It works great when I instantiate classes directly, eg import numpy as np x = np.ndarray(l) then x attributes complete correctly. But I work with numpy and matplotlib so usually use factory functions ie x = np.zeros((2,2)) f = plt.figure() ax = f.add_subplot(111) Is there any wa...
Short Question: Lets say, I want to solve Project Euler problem 9 using python and some equation solving libraries. a + b + c = 1000. a2 + b2 = c2 How do you do it. Long Question: I want to solve a set of equations; linear, sometimes may be quadratic too. Not a specific problem; but often, I have been in situation I wanted to. I...
I would like to delete selected columns in a numpy.array . This is what I do: n [397]: a = array([[ NaN, 2., 3., NaN], .....: [ 1., 2., 3., 9]]) In [398]: print a [[ NaN 2. 3. NaN] [ 1. 2. 3. 9.]] In [399]: z = any(isnan(a), axis=0) In [400]: print z [ True False False True] In [401]: delete(a, z, ax...
I'm interested in finding for a particular Numpy type (e.g. np.int64, np.uint32, np.float32, etc.) what the range of all possible valid values is (e.g. np.int32 can store numbers up to 2**31-1). Of course, I guess one can theoretically figure this out for each type, but is there a way to do this at run time to ensure more portable code? ...
I'm trying to generate random 64-bit integer values for integers and floats using Numpy, within the entire range of valid values for that type. To generate random 32-bit floats, I can use: In [2]: np.random.uniform(low=np.finfo(np.float32).min,high=np.finfo(np.float32).max,size=10) Out[2]: array([ 1.47351436e+37, 9.93620693e+37, 2...
If I create a recarray in this way: In [29]: np.rec.fromrecords([(1,'hello'),(2,'world')],names=['a','b']) The result looks fine: Out[29]: rec.array([(1, 'hello'), (2, 'world')], dtype=[('a', '<i8'), ('b', '|S5')]) But if I want to specify the data types: In [32]: np.rec.fromrecords([(1,'hello'),(2,'world')],dtype=[('a',np...
I want to convert an int64 numpy array to a uint64 numpy array, adding 2**63 to the values in the process so that they are still within the valid range allowed by the arrays. So for example if I start from a = np.array([-2**63,2**63-1], dtype=np.int64) I want to end up with np.array([0.,2**64], dtype=np.uint64) Sounds simple at fir...
Hello everybody, why do the following lines not work as I expect? import numpy as np a = np.array([0,1,2,1,1]) a[a==1][1:] = 3 print a >>> [0 1 2 1 1] # I would expect [0 1 2 3 3] Is this a 'bug' or is there another recommended way to this? On the other hand, the following works: a[a==1] = 3 print a >>> [0 3 2 3 3] Cheers, Philip...
How to create 3 dimensions matrix in numpy , like matlab a(:,:,:) . I try to convert matlab code that create 3d matrix to python by use numpy.array and i don't know how to create 3d matrix/array in numpy ...
I have two arrays (a and b) with n integer elements in the range (0,N). typo: arrays with 2^n integers where the largest integer takes the value N = 3^n I want to calculate the sum of every combination of elements in a and b (sum_ij_ = a_i_ + b_j_ for all i,j). Then take modulus N (sum_ij_ = sum_ij_ % N), and finally calculate the fre...
I have read samples out of a wave file using the wave module, but it gives the samples as a string, it's out of wave so it's little endian (for example, '`\x00'). What is the easiest way to convert this into a python integer, or a numpy.int16 type? (It will eventually become a numpy.int16, so going directly there is fine). Code needs t...
I have the following code: r = numpy.zeros(shape = (width, height, 9)) It creates a width x height x 9 matrix filled with zeros. Instead, I'd like to know if there's a function or way to initialize them instead to NaN. Is there any? Without having to resort to manually doing loops and such? Thanks ...
I'm having troubles loading a numpy matrix. I successfully saved it to disk through: self.q.dump(fileName) and now I want to be able to load it. From what I understand, the load command should do the trick: self.q.load(fileName) but it seems not. Anyone knows what might be wrong? Maybe the function is not called load? ...
I have two Numpy record arrays that have exactly the same fields. What is the easiest way to combine them into one (i.e. append one table on to the other)? ...
I want to achieve the following: Have a AxBxC matrix (where A,B,C are integers). Access that matrix not as matrix[a, b, c] but as matrix[(a, b), c], this is, I have two variables, var1 = (x, y) and var2 = z and want access my matrix as matrix[var1, var2]. How can this be done? I am using numpy matrix, if it makes any difference. I k...
I found repmat([1;1], [1 1 1]) in MATLAB code. I am trying to find a NumPy command to do the same thing, but I found that can't use with 3d [1 1 1] ? ...
I have used NumPy for my Master thesis. I've converted parts of the code from MATLAB code, but I have doubts in NumPy/Python when I reference: m = numpy.ones((10,2)) m[:,0] which returns: array([ 1., 1., 1., 1., 1., 1., 1., 1., 1., 1.]) and when I ref to: m[:,0:1] it returns: array([[ 1.], [ 1.], [ 1.], ...