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sample_words sample_data
20160122

Produce sample words

Use the sowpods file to generate a list of words that fulfills a special condition (eg length, starting letter) Use is made of the function random.sample(population, k) to take a unique sample of a larger list.

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    import random 

    # get 7 random words of length 5, that start with a given begin-letter 
    for beginletter in list('aeiou'): 
        f=open("/home/willem/20141009_sowpod/sowpods.txt","r") 
        allwords=[]
        for line in f:
            line=line.rstrip('\n')
            if len(line)==5 and line.startswith(beginletter): 
                allwords.append(line)
        f.close()
        print random.sample( allwords, 7 )

Output:

 ['argot', 'along', 'addax', 'azans', 'aboil', 'aband']
 ['erred', 'ester', 'ekkas', 'entry', 'eldin', 'eruvs']
 ['imino', 'islet', 'inurn', 'iller', 'idiom', 'izars']
 ['oches', 'outer', 'odist', 'orbit', 'ofays', 'outed']
 ['unlaw', 'upjet', 'upend', 'urged', 'urent', 'uncus']
numpy magic sample_data
20141021

The magic matrices (a la octave).

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magic3= np.array(
   [[8,   1,   6],
    [3,   5,   7],
    [4,   9,   2] ] )

magic4= np.array(
   [[16,    2,    3,   13],
    [ 5,   11,   10,    8],
    [ 9,    7,    6,   12],
    [ 4,   14,   15,    1]] ) 

magic5= np.array( 
   [[17,   24,    1,    8,   15],
    [23,    5,    7,   14,   16],
    [ 4,    6,   13,   20,   22],
    [10,   12,   19,   21,    3],
    [11,   18,   25,    2,    9]] )

magic6= np.array(
   [[35,    1,    6,   26,   19,   24],
    [ 3,   32,    7,   21,   23,   25],
    [31,    9,    2,   22,   27,   20],
    [ 8,   28,   33,   17,   10,   15],
    [30,    5,   34,   12,   14,   16],
    [ 4,   36,   29,   13,   18,   11]] )

magic7= np.array(
     [ [30,  39,  48,   1,  10,  19,  28],
       [38,  47,   7,   9,  18,  27,  29],
       [46,   6,   8,  17,  26,  35,  37],
       [ 5,  14,  16,  25,  34,  36,  45],
       [13,  15,  24,  33,  42,  44,   4],
       [21,  23,  32,  41,  43,   3,  12],
       [22,  31,  40,  49,   2,  11,  20] ] ) 

# no_more_magic

Sum column-wise (ie add up the elements for each column):

np.sum(magic3,axis=0)
array([15, 15, 15])

Sum row-wise (ie add up elements for each row):

np.sum(magic3,axis=1)
array([15, 15, 15])

Okay, a magic matrix is maybe not the best way to show row/column wise sums. Consider this:

rc= np.array([[0, 1, 2, 3, 4, 5],
              [0, 1, 2, 3, 4, 5],
              [0, 1, 2, 3, 4, 5]])

np.sum(rc,axis=0)           # sum over rows
[0,  3,  6,  9, 12, 15]

np.sum(rc,axis=1)           # sum over columns 
[15, 
 15, 
 15]

np.sum(rc)                  # sum every element
45
 
Notes by Willem Moors. Generated on momo:/home/willem/sync/20151223_datamungingninja/pythonbook at 2019-07-31 19:22