amine23 - 1 year ago 172

Python Question

I have a 2D numpy array S representing a state space, with 80000000 rows (as states) and 5 columns (as state variables).

I initialize K0 with S, and at each iteration, I apply a state transition function f(x) on all of the states in Ki, and delete states whose f(x) is not in Ki, resulting Ki+1. Until it converges i.e. Ki+1 = Ki.

Going like this would take ages:

`K = S`

to_delete = [0]

While to_delete:

to_delete = []

for i in xrange(len(K)):

if not f(i) in K:

to_delete.append(K(i))

K = delete(K,to_delete,0)

So I wanted to make a vectorized implementation :

slice K in columns, apply f and, join them once again, thus obtaining f(K) somehow.

The question now is how to get an array of length len(K), say Sel, where each row Sel[i] determine whether f(K[i]) is in K. Exactly like the function in1d works.

Then it would be simple to make

`K=K[Sel]]`

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Answer Source

Your question is difficult to understand because it contains extraneous information and contains typos. If I understand correctly, you simply want an efficient way to perform a set operation on the rows of a 2D array (in this case the intersection of the rows of `K`

and `f(K)`

).

You can do this with numpy.in1d if you create structured array view.

Code:

if this is `K`

:

```
In [50]: k
Out[50]:
array([[6, 6],
[3, 7],
[7, 5],
[7, 3],
[1, 3],
[1, 5],
[7, 6],
[3, 8],
[6, 1],
[6, 0]])
```

and this is `f(K)`

(for this example I subtract 1 from the first col and add 1 to the second):

```
In [51]: k2
Out[51]:
array([[5, 7],
[2, 8],
[6, 6],
[6, 4],
[0, 4],
[0, 6],
[6, 7],
[2, 9],
[5, 2],
[5, 1]])
```

then you can find all rows in `K`

also found in `f(K)`

by doing something this:

```
In [55]: k[np.in1d(k.view(dtype='i,i').reshape(k.shape[0]),k2.view(dtype='i,i').
reshape(k2.shape[0]))]
Out[55]: array([[6, 6]])
```

`view`

and `reshape`

create flat structured views so that each row appears as a single element to `in1d`

. `in1d`

creates a boolean index of `k`

of matched items which is used to fancy index `k`

and return the filtered array.

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