numpy.md

Numpy

Set operations for 1D numeric arrays based on sorting.

np.lib.arraysetops?
:Contains:
  ediff1d -> The differences between consecutive elements of an array.
  unique,
  intersect1d -> Return the sorted, unique values that are in both of the input arrays.
  setxor1d -> Return the sorted, unique values that are in only one (not both) of the
              input arrays.
  setdiff1d -> Return the sorted, unique values in `ar1` that are not in `ar2`
  in1d -> Test whether each element of a 1-D array is also present in a second array
  union1d -> Return the unique, sorted array of values that are in either of the two
             input arrays.

Tools and tricks

Convert string to file object

import io fo=io.StringIO('[[1,2,3]]')

Convert object (dict, lists,...) to recoverable string

import json
m = {'id': 2, 'name': 'hussain'}
n = json.dumps(m)
o = json.loads(n)
print o['id'], o['name']

Similarity bewteen strings

import Levenshtein Levenshtein.ratio(s1,s2) # > 0.6

How to split a list or array into pairs in all possible ways

In[1]: import itertools In[2]: a=[0,1,2] #or np.array(a) In[3]: list(itertools.combinations(a, 2)) Out[3]: [(0, 1), (0, 2), (1, 2)]

Convert a function which accepts only float function into a function which accepts numpy arrays.

Sifloat=lambda t: integrate.quad(lambda x:sp.sin(x)/x,0,t)[0]

only accepts floats as input. We can define a new function with numpy.vectorize which returns an array if an array is used as input

import numpy as np
import scipy as sp
import scipy.integrate as integrate

Sifloat=lambda t: integrate.quad(lambda x:sp.sin(x)/x,0,t)[0]
def Si(x):
    try:
        nn=np.array(x).shape[0]
        Si=np.vectorize(Sifloat)
    except IndexError:
        Si=Sifloat        
    return Si(x)

>>> Si(1)
0.9460830703671831
>>> Si([1,2])
array([ 0.94608307,  1.60541298])

Make the sorted permutations of n elements in a list, l, of m>=n entries

import itertools
prmts=[]
for p in itertools. permutations(l, n):
    if sorted(p) not in prmts:
        prmts.append(sorted(p))

Append list of Python dictionaries to a file without loading it

See This notebook