jphollowed - 1 year ago 107

Python Question

If I try

`x = np.append(x, (2,3))`

the tuple

`(2,3)`

`2`

`3`

`x`

`x = np.array([], dtype = tuple)`

or

`x = np.array([], dtype = (int,2))`

What is the proper way to do this?

Answer Source

I agree with @user2357112 comment:

appending to NumPy arrays is catastrophically slower than appending to ordinary lists. It's an operation that they are not at all designed for

Here's a little benchmark:

```
# measure execution time
import timeit
import numpy as np
def f1(num_iterations):
x = np.dtype((np.int32, (2, 1)))
for i in range(num_iterations):
x = np.append(x, (i, i))
def f2(num_iterations):
x = np.array([(0, 0)])
for i in range(num_iterations):
x = np.vstack((x, (i, i)))
def f3(num_iterations):
x = []
for i in range(num_iterations):
x.append((i, i))
x = np.array(x)
N = 50000
print timeit.timeit('f1(N)', setup='from __main__ import f1, N', number=1)
print timeit.timeit('f2(N)', setup='from __main__ import f2, N', number=1)
print timeit.timeit('f3(N)', setup='from __main__ import f3, N', number=1)
```

I wouldn't use neither np.append nor vstack, I'd just create my python array properly and then use it to construct the np.array

**EDIT**

Here's the benchmark output on my laptop:

- append: 12.4983000173
- vstack: 1.60663705793
- list: 0.0252208517006

[Finished in 14.3s]