Are there any libraries or techniques that simplify computing equations ? Take the following two examples: F = B * { [ a * b * sumOf (A / B ''' for all i ''' ) ] / [ sumOf(c * d * j) ] } where: F = cost from i to j B, a, b, c, d, j are all vectors in the format [ [zone_i, zone_j, cost_of_i_to_j], [..]] This should produce a vecto...
I can't get this snippet to work: #base code A = array([ [ 1, 2, 10 ], [ 1, 3, 20 ], [ 1, 4, 30 ], [ 2, 1, 15 ], [ 2, 3, 25 ], [ 2, 4, 35 ], [ 3, 1, 17 ], [ 3, 2, 27 ], [ 3, 4, 37 ], [ 4, 1, 13 ], [ 4, 2, 23 ], ...
I have a C++ function returning a std::vector and I want to use it in python, so I'm using the C numpy api: static PyObject * py_integrate(PyObject *self, PyObject *args){ ... std::vector<double> integral; cpp_function(integral); // this change integral npy_intp size = {integral.size()}; PyObject *out = PyArray_SimpleNewFromData(1, &...
greetings, I'm not sure if this is a dumb question or not. Lets say I have 3 numpy arrays, A1,A2,A3, and 3 floats, c1,c2,c3 and I'd like to evaluate B = A1*c1+ A2*c2+ A3*c3 will numpy compute this as for example, E1 = A1*c1 E2 = A2*c2 E3 = A3*c3 D1 = E1+E2 B = D1+E3 or is it more clever than that? In c++ I had a neat way to a...
I am doing a hierarchical clustering a 2 dimensional matrix by correlation distance metric (i.e. 1 - Pearson correlation). My code is the following (the data is in a variable called "data"): from hcluster import * Y = pdist(data, 'correlation') cluster_type = 'average' Z = linkage(Y, cluster_type) dendrogram(Z) The error I get is: ...
Is there a way to make Python floating point numbers follow numpy's rules regarding +/- Inf and NaN? For instance, making 1.0/0.0 = Inf. >>> from numpy import * >>> ones(1)/0 array([ Inf]) >>> 1.0/0.0 Traceback (most recent call last): File "<stdin>", line 1, in <module> ZeroDivisionError: float division Numpy's divide function div...
what's the easiest way to take the intersection of N-many lists in python? if I have two lists a and b, I know I can do: a = set(a) b = set(b) intersect = a.intersection(b) but I want to do something like a & b & c & d & ... for an arbitrary set of lists (ideally without converting to a set first, but if that's the easiest / most eff...
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 Pyt...
In an answer to an earlier question of mine regarding fixing the colorspace for scatter images of 4D data, Tom10 suggested plotting values as symbols in order to double-check my data. An excellent idea. I've run some similar demos in the past, but I can't for the life of me find the demo I remember being quite simple. So, what's the e...
Hi, I am new to numpy. Am wonder is there a way to do lookup of two ndarray of different shapes? for example, i have 2 ndarrays as below: X = array([[0, 3, 6], [3, 3, 3], [6, 0, 3]]) Y = array([[0, 100], [3, 500], [6, 800]]) and would like to lookup each element of X in Y, then be able to return the secon...
how can I do a hierarchical clustering (in this case for gene expression data) in Python in a way that shows the matrix of gene expression values along with the dendrogram? What I mean is like the example here: http://www.mathworks.cn/access/helpdesk/help/toolbox/bioinfo/ug/a1060813239b1.html shown after bullet point 6 (Figure 1), whe...
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 aver...
I've been trying to find a good and flexible way to parse CSV files in Python but none of the standard options seem to fit the bill. I am tempted to write my own but I think that some combination of what exists in numpy/scipy and the csv module can do what I need, and so I don't want to reinvent the wheel. I'd like the standard feature...
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...
I'm in the process of trying to switch from R to Python (mainly issues around general flexibility). With Numpy, matplotlib and ipython, I've am able to cover all my use cases save for merging 'datasets'. I would like to simulate SQL's join by clause (inner, outer, full) purely in python. R handles this with the 'merge' function. I've t...
How can I compute the z-score for matrices in Python? Suppose I have the array: a = array([[ 1, 2, 3], [ 30, 35, 36], [2000, 6000, 8000]]) and I want to compute the z-score for each row. The solution I came up with is: array([zs(item) for item in a]) where zs is in scipy.stats.stats. Is there a...
Hello, I'm using cPickle to save my Database into file. The code looks like that: def Save_DataBase(): import cPickle from scipy import * from numpy import * a=Results.VersionName #filename='D:/results/'+a[a.find('/')+1:-a.find('/')-2]+Results.AssType[:3]+str(random.randint(0,100))+Results.Distribution+".lft" filename='D:/results/pppp...
Hi everybody I have two questions regarding python libraries: I would like to know if there is something like a "super" python library which lets me install ALL or at least all scientific useful python libraries, which I can install once and then I have all I need. There is a number of annoying problems when installing different libra...
suppose I have a dictionary whose keys are strings. How can I efficiently make a new dictionary from that which contains only the keys present in some list? for example: # a dictionary mapping strings to stuff mydict = {'quux': ..., 'bar': ..., 'foo': ...} # list of keys to be selected from mydict keys_to_select = ...
I'm trying to build numpy 1.2.1 as a module for a third-party python interpreter (custom-built, py2.4 linux x86_64) so that I can make calls to numpy from within it. Let's call this one interpreter A. The thing is, the system-wide python interpreter (also py2.4, let's call it B) from the vendor is built with --enable-unicode=ucs4, while...