# Numpy where function multiple conditions

I have an array of distances called dists. I want to select dists which are between two values. I wrote the following line of code to do that:

```
dists[(np.where(dists >= r)) and (np.where(dists <= r + dr))]
```

However this selects only for the condition

```
(np.where(dists <= r + dr))
```

If I do the commands sequentially by using a temporary variable it works fine. Why does the above code not work, and how do I get it to work?

Cheers

The best way in **your particular case** would just be to change your two criteria to one criterion:

```
dists[abs(dists - r - dr/2.) <= dr/2.]
```

It only creates one boolean array, and in my opinion is easier to read because it says, *is dist within a dr or r?* (Though I'd redefine

`r`

to be the center of your region of interest instead of the beginning, so `r = r + dr/2.`

) But that doesn't answer your question.**The answer to your question:**

You don't actually need `where`

if you're just trying to filter out the elements of `dists`

that don't fit your criteria:

```
dists[(dists >= r) & (dists <= r+dr)]
```

Because the `&`

will give you an elementwise `and`

(the parentheses are necessary).

Or, if you do want to use `where`

for some reason, you can do:

```
dists[(np.where((dists >= r) & (dists <= r + dr)))]
```

**Why:**

The reason it doesn't work is because `np.where`

returns a list of indices, not a boolean array. You're trying to get `and`

between two lists of numbers, which of course doesn't have the `True`

/`False`

values that you expect. If `a`

and `b`

are both `True`

values, then `a and b`

returns `b`

. So saying something like `[0,1,2] and [2,3,4]`

will just give you `[2,3,4]`

. Here it is in action:

```
In [230]: dists = np.arange(0,10,.5)
In [231]: r = 5
In [232]: dr = 1
In [233]: np.where(dists >= r)
Out[233]: (array([10, 11, 12, 13, 14, 15, 16, 17, 18, 19]),)
In [234]: np.where(dists <= r+dr)
Out[234]: (array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]),)
In [235]: np.where(dists >= r) and np.where(dists <= r+dr)
Out[235]: (array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]),)
```

What you were expecting to compare was simply the boolean array, for example

```
In [236]: dists >= r
Out[236]:
array([False, False, False, False, False, False, False, False, False,
False, True, True, True, True, True, True, True, True,
True, True], dtype=bool)
In [237]: dists <= r + dr
Out[237]:
array([ True, True, True, True, True, True, True, True, True,
True, True, True, True, False, False, False, False, False,
False, False], dtype=bool)
In [238]: (dists >= r) & (dists <= r + dr)
Out[238]:
array([False, False, False, False, False, False, False, False, False,
False, True, True, True, False, False, False, False, False,
False, False], dtype=bool)
```

Now you can call `np.where`

on the combined boolean array:

```
In [239]: np.where((dists >= r) & (dists <= r + dr))
Out[239]: (array([10, 11, 12]),)
In [240]: dists[np.where((dists >= r) & (dists <= r + dr))]
Out[240]: array([ 5. , 5.5, 6. ])
```

Or simply index the original array with the boolean array using fancy indexing

```
In [241]: dists[(dists >= r) & (dists <= r + dr)]
Out[241]: array([ 5. , 5.5, 6. ])
```

From: stackoverflow.com/q/16343752

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