Dnaiel - 1 year ago 204

Python Question

I want to initialize a numpy array of size (n,m) that can only contain zeros or ones.

Furthermore, I want to later to np.bitwise_or with the array.

For example, If I try:

`import numpy as np`

myArray = np.zeros([4,4])

myRow = myArray[1,]

myCol = myArray[,1]

np.bitwise_or(myRow, myCol)

It fails:

`TypeError: ufunc 'bitwise_or' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''`

How can I do this in a similar manner but without errors?

If I try,

`np.bitwise_or([0,0,0,0], [0,0,0,0])`

it actually works.

Recommended for you: Get network issues from **WhatsUp Gold**. **Not end users.**

Answer Source

By default, `np.zeros`

will use a float dtype, and you can't perform the bitwise operations on floats. `np.bitwise_or([0,0,0,0], [0,0,0,0])`

acts on integers, which is why it works.

If you pass an integer dtype instead when you construct `myArray`

, it'll work too:

```
In [9]: myArray = np.zeros([4,4], dtype=int)
In [10]: myRow = myArray[1,:]
In [11]: myCol = myArray[:,1]
In [12]: np.bitwise_or(myRow, myCol)
Out[12]: array([0, 0, 0, 0])
```

or we could call `astype(int)`

:

```
In [14]: myArray = np.array([[1.0,0.0,1.0,0.0], [1.0,1.0,1.0,0.0]])
In [15]: np.bitwise_or(myArray[0].astype(int), myArray[1].astype(int))
Out[15]: array([1, 1, 1, 0])
```

That said, if you know the array is always going to contain only 0 or 1, you should consider a `bool`

array instead:

```
In [21]: myArray = myArray.astype(bool)
In [22]: np.bitwise_or(myArray[0], myArray[1])
Out[22]: array([ True, True, True, False], dtype=bool)
```

Recommended from our users: **Dynamic Network Monitoring from WhatsUp Gold from IPSwitch**. ** Free Download**