CODEWITHSUNDEEP
pythonnumpy
SOCKet
SOCKet

Reputation: 191

resize an array with a specific value

I have an array phase

 [ (3.0535400914168154, 0.371345899229, 0.312953794281, -0.0125231427371, 0.0)
 (3.056684825749555, 0.373971853521, 0.313682391117, -0.0264543909236, 0.0)
 (3.0598295600822953, 0.376861295611, 0.314535588286, -0.041169303628, 0.0)]

and I would like to resize with the method resize

phase.resize(MAXLINE)

and I get this result

[ (3.0535400914168154, 0.371345899229, 0.312953794281, -0.0125231427371, 0.0)
 (3.056684825749555, 0.373971853521, 0.313682391117, -0.0264543909236, 0.0)
 (3.0598295600822953, 0.376861295611, 0.314535588286, -0.041169303628, 0.0)
 (0.0, 0.0, 0.0, 0.0, 0.0) (0.0, 0.0, 0.0, 0.0, 0.0)
 (0.0, 0.0, 0.0, 0.0, 0.0)]

I would like to know if it's possible to set a specific value (Nan or -99999) instead of the default value 0.0

Upvotes: 3

Views: 19322

Answers (3)

farhawa
farhawa

Reputation: 10417

If you are not attached to np.resize() you can do it this way:

import numpy as np


old_array =  [ (3.0535400914168154, 0.371345899229, 0.312953794281, -0.0125231427371, 0.0),
(3.056684825749555, 0.373971853521, 0.313682391117, -0.0264543909236, 0.0),
(3.0598295600822953, 0.376861295611, 0.314535588286, -0.041169303628, 0.0)]

maxline = 20


# If you want fullfil extra dimension with NaN 
arr = [(np.NAN,)*len(old_array[0])]*(maxline - len(old_array))

# If you want fullfil extra dimension with anything else
# arr = np.array([(ANYTHING_YOU_WANT,)*len(old_array[0])]*(maxline - old_array.size))

new_ = old_array + arr

print numpy.array(new_)

>> 

[(3.0535400914168154, 0.371345899229, 0.312953794281, -0.0125231427371, 0.0), (3
.056684825749555, 0.373971853521, 0.313682391117, -0.0264543909236, 0.0), (3.059
8295600822953, 0.376861295611, 0.314535588286, -0.041169303628, 0.0), (nan, nan,
 nan, nan, nan), (nan, nan, nan, nan, nan), (nan, nan, nan, nan, nan), (nan, nan
, nan, nan, nan), (nan, nan, nan, nan, nan), (nan, nan, nan, nan, nan), (nan, na
n, nan, nan, nan), (nan, nan, nan, nan, nan), (nan, nan, nan, nan, nan), (nan, n
an, nan, nan, nan), (nan, nan, nan, nan, nan), (nan, nan, nan, nan, nan), (nan,
nan, nan, nan, nan), (nan, nan, nan, nan, nan), (nan, nan, nan, nan, nan), (nan,
 nan, nan, nan, nan), (nan, nan, nan, nan, nan)]

Upvotes: 1

drevicko
drevicko

Reputation: 15180

Making the assumption that you want your array to have shape (MAXLINE,5) and that your array is a 2-dimensional array and not a list of tuples (as the format in your question seems to suggest), this would work:

import numpy as np
MAXLINE = 4
a=np.array([ [3.0535400914168154, 0.371345899229, 0.312953794281, -0.0125231427371, 0.0],
 [3.056684825749555, 0.373971853521, 0.313682391117, -0.0264543909236, 0.0],
 [3.0598295600822953, 0.376861295611, 0.314535588286, -0.041169303628, 0.0]])
np.append(a,np.ones((MAXLINE-a.shape[0],a.shape[1]))*np.NAN,axis=0)

produces:

array([[ 3.05354009,  0.3713459 ,  0.31295379, -0.01252314,  0.        ],
       [ 3.05668483,  0.37397185,  0.31368239, -0.02645439,  0.        ],
       [ 3.05982956,  0.3768613 ,  0.31453559, -0.0411693 ,  0.        ],
       [        nan,         nan,         nan,         nan,         nan]])

Explanation:

np.ones() takes a shape parameter, so I'm adding enough rows to make the final shape (MAXLINE,5), where 5 is the number of columns of a (ie: a.shape[1]).

In np.append(), the axis=0 parameter tells numpy to add rows. If you don't have this, it flattens the arrays.

Of course, you can replace np.NAN with any value you prefer.

Upvotes: 2

Michael Kazarian
Michael Kazarian

Reputation: 4462

Because Python arrays don't might resize arrays you can use numpy or write own functions, similar below:

def resize(array, new_size, new_value=0):
    """Resize to biggest or lesser size."""
    element_size = len(array[0]) #Quantity of new elements equals to quantity of first element
    if new_size > len(array):
        new_size = new_size - 1
        while len(array)<=new_size:
            n = tuple(new_value for i in range(element_size))
            array.append(n)
    else:
        array = array[:new_size]
    return array
#Test it
a =  [ (3.0535400914168154, 0.371345899229, 0.312953794281, -0.0125231427371, 0.0),
(3.056684825749555, 0.373971853521, 0.313682391117, -0.0264543909236, 0.0),
(3.0598295600822953, 0.376861295611, 0.314535588286, -0.041169303628, 0.0)]
a = resize(a, 5)
print a
a = resize(a, 2)
print a
a = resize(a, 3, 28)
print a 

#Output:
#New size 5, default value 0
#[(3.0535400914168154, 0.371345899229, 0.312953794281, -0.0125231427371, 0.0), (3.056684825749555, 0.373971853521, 0.313682391117, -0.0264543909236, 0.0), (3.0598295600822953, 0.376861295611, 0.314535588286, -0.041169303628, 0.0), (0, 0, 0, 0, 0), (0, 0, 0, 0, 0)]
#new size 2
#[(3.0535400914168154, 0.371345899229, 0.312953794281, -0.0125231427371, 0.0), (3.056684825749555, 0.373971853521, 0.313682391117, -0.0264543909236, 0.0)]
#New size 4, default value 28
#[(3.0535400914168154, 0.371345899229, 0.312953794281, -0.0125231427371, 0.0), (3.056684825749555, 0.373971853521, 0.313682391117, -0.0264543909236, 0.0), (28, 28, 28, 28, 28)]

Upvotes: 1

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