Numpy: Difference between revisions
From charlesreid1
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<source lang="python"> | <source lang="python"> | ||
# You can initialize an array with []: | |||
In [62]: x=[] | In [62]: x=[] | ||
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In [64]: x | In [64]: x | ||
Out[64]: array([], dtype=float64) | Out[64]: array([], dtype=float64) | ||
# to be more direct about it, | |||
In [66]: x = np.array([],dtype=np.float64) | In [66]: x = np.array([],dtype=np.float64) | ||
| Line 17: | Line 21: | ||
In [67]: x | In [67]: x | ||
Out[67]: array([], dtype=float64) | Out[67]: array([], dtype=float64) | ||
# Now you can append to the empty array | |||
In [71]: x = append(x,1) | |||
In [72]: x = append(x,2) | |||
In [73]: x=append(x,3) | |||
In [74]: x | |||
Out[74]: array([ 1., 2., 3.]) | |||
</source> | </source> | ||
Revision as of 19:28, 28 July 2013
Arrays
Initializing an empty array
Sometimes you want to initalize an empty array, which is a really inefficient use of memory for large matrices but you could care less if it's a dozen items.
# You can initialize an array with []:
In [62]: x=[]
In [63]: x=np.array(x)
In [64]: x
Out[64]: array([], dtype=float64)
# to be more direct about it,
In [66]: x = np.array([],dtype=np.float64)
In [67]: x
Out[67]: array([], dtype=float64)
# Now you can append to the empty array
In [71]: x = append(x,1)
In [72]: x = append(x,2)
In [73]: x=append(x,3)
In [74]: x
Out[74]: array([ 1., 2., 3.])