How to create the numpy equivalent to a 1x2 linspace array

Question

At first i needed an array like this: [0. , 0.25, 0.5 , 0.75, 1. ] which is np.linspace(0,1,5). But now I need an array like this:

[[0.  ,  0.],
 [0.25,  0.5],
 [0.5 ,  1.],
 [0.75,  1.5],
 [1.  ,  2]]

Note that array[1][0] != array[1][1]!

Can't really explain how but it should sort of like this:

array[:][0] = np.linspace(0,1,5)
array[:][1] = np.linspace(0,2,5)

Where array[0][0] is np.linspace(0,1,5)[0] and array[1][0] is np.linspace(0,1,5)[1]

I hope you kind of understand what array I'm trying to build here. Thanks in advance!

Rifat Alptekin Çetin · Accepted Answer · 2019-04-30 23:57:58Z

1

please notice that your first column is np.linspace(0,1,5) and second one np.linspace(0,2,5) so you can create that array with this two component first make an array from this two with shape 2x5 than when you transpose the array it turns to your 5x2 array:

np.array([np.linspace(0,1,5),np.linspace(0,2,5)]).T

edited Apr 30, 2019 at 23:57

answered Apr 30, 2019 at 23:52

Rifat Alptekin Çetin

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1 Comment

Mathis Van Eetvelde Over a year ago

Exactly what I needed! Thank you so very much!

Katekarin · Accepted Answer · 2019-05-01 00:38:51Z

0

np.c_ is the numpy function for this

np.c_[np.linspace(0,1,5),np.linspace(0,2,5)]

Output:

       [0.25, 0.5 ],
       [0.5 , 1.  ],
       [0.75, 1.5 ],
       [1.  , 2.  ]])

edited May 1, 2019 at 0:38

answered May 1, 2019 at 0:30

Katekarin

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1 Comment

Mathis Van Eetvelde Over a year ago

Hi, I found this to be a much better solution than the one I originally chose to be the answer!

Warren Weckesser · Accepted Answer · 2019-04-30 23:47:59Z

0

Here's one way:

In [33]: start = np.array([0, 0])                                                                                     

In [34]: stop = np.array([1, 2])                                                                                      

In [35]: n = 5                                                                                                        

In [36]: np.linspace(0, 1, n).reshape(-1, 1)*(stop - start) + start                                                      
Out[36]: 
array([[0.  , 0.  ],
       [0.25, 0.5 ],
       [0.5 , 1.  ],
       [0.75, 1.5 ],
       [1.  , 2.  ]])

answered Apr 30, 2019 at 23:47

Warren Weckesser

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Comments

Sheldore · Accepted Answer · 2019-05-01 12:29:05Z

0

You second array is just twice of your first array. So you can also consider the following

a = np.linspace(0,1,5)
b = 2*a

np.column_stack((a, b))

# array([[0.  , 0.  ],
#        [0.25, 0.5 ],
#        [0.5 , 1.  ],
#        [0.75, 1.5 ],
#        [1.  , 2.  ]])

Alternatively, you can do either

np.vstack((a,b)).T

OR

np.concatenate((a.reshape(5,1), b.reshape(5,1)), axis=1)

answered May 1, 2019 at 12:29

Sheldore

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