Calculating distance between two elements only in the array in python

Question

So I have two questions: First I'm trying to print my array that contains 1004 elements but it's printing only the first 29 elements and then jumping to 974 to continue printing. How can I get the full array of 1004 elements?

This is my code

paired_data = []
for x in data:
    closest, ignored = pairwise_distances_argmin_min(x, result)
    paired_data.append([x, result[closest]])
#print paired_data
S = pd.DataFrame(paired_data, columns=['x','center'])
print S
# distance
Y = pdist(S, 'euclidean')
print Y

Also I want to calculate the distance between each two elements of the array. for example

0 [5, 4] [3, 2]

1 [22, -10] [78, 90]

I want to calculate the distance( Euclidean ) between [5, 4] and [3, 2] and so on for all the rest of the array.

Welcome to Stack Overflow! To keep things from getting confusing, can you please edit your question so it only has one question in it, then ask another question for your second question? — David Wolever
– David Wolever, Commented Mar 3, 2015 at 19:57
Oh dang, I didn't realize that was a restriction! Well, check out this answer which addresses your first question: stackoverflow.com/questions/1987694/print-the-full-numpy-array — David Wolever
– David Wolever, Commented Mar 3, 2015 at 19:59
you might also find docs.scipy.org/doc/scipy/reference/generated/… helpful — Joran Beasley
– Joran Beasley, Commented Mar 3, 2015 at 20:01

Hugh Bothwell · Accepted Answer · 2015-03-03 20:24:25Z

1

Another solution to #1:

print(S.to_string())    # print the entire table

and to get distances

# assumes Python 3
from functools import partial

def dist(row, col1, col2):
    return sum((c2 - c1)**2 for c1,c2 in zip(row[col1], row[col2])) ** 0.5

# compose a function (name the columns it applies to)
s_dist = partial(dist, col1="x", col2="center")
# apply it
S["dist"] = S.apply(s_dist, axis=1)

edited Mar 3, 2015 at 20:24

answered Mar 3, 2015 at 20:05

Hugh Bothwell

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7 Comments

Hugh Bothwell Over a year ago

@Micheal: I think it should work as is, but I do not have anything but 3.4 on this machine to test with.

Micheal Over a year ago

If I want to square ( ^2) each of these distances (1004 distances values), and then sum all of them after do the square, how can I do that?

Hugh Bothwell Over a year ago

@Micheal: it is an n-dimensional Euclidean distance. If you want sum of squares, try sq_sum = (S["dist"]**2).sum().

Micheal Over a year ago

so why you multiply it by ** 0.5?

Hugh Bothwell Over a year ago

** is exponentiation, not multiplication, so x ** 0.5 is square root of x.

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