CF84 - 11 months ago 137

Python Question

I have two input numpy arrays with, respectively, latitude and longitude coordinates of a set of points:

`lats`

`lons`

I have inherited a function which converts each

`(lat,lon)`

`(E,N)`

`def convert(lat,lon): #takes two floats as arguments (unit: degrees)`

...

computation #Actual function is too long to post

...

return N,E #returns two floats (unit: meters)

I was thinking of modifying the function so that it returns a list:

`return [N,E]`

in such a way that:

`rows = int(lat.shape[0]) #lat and lon have the same shape`

cols = int(lat.shape[1])

easting=numpy.zeros(shape=(rows,cols))

northing=numpy.zeros(shape=(rows,cols))

for i in range(0, rows):

for j in range(0, cols):

northing=convert(lon[i][j])[0] #first element of the returned list

easting=convert(lat[i][j])[1] #second element of the returned list

I have not yet tested this, but by looking at it I don't feel very comfortable this will work. Any insights will be much appreciated.

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Answer Source

Let's define a trivial conversion

```
def convert(lat, lon):
return lat*np.pi/180, lon*np.pi/180
```

`frompyfunc`

is a useful way of applying 'scalar' function to arrays; We can even have it take in 2 arrays, and return 2 arrays (in a tuple)

```
In [233]: f = np.frompyfunc(convert,2,2)
In [234]: lats=np.linspace(-45,45,5)
In [235]: lons=np.linspace(0,100,5)
In [236]: out = f(lats, lons)
In [237]: out
Out[237]:
(array([-0.7853981633974483, -0.39269908169872414, 0.0, 0.39269908169872414,
0.7853981633974483], dtype=object),
array([0.0, 0.4363323129985824, 0.8726646259971648, 1.3089969389957472,
1.7453292519943295], dtype=object))
```

One feature is that it returns an object array, while you probably want a float array:

```
In [238]: out[0].astype(float)
Out[238]: array([-0.78539816, -0.39269908, 0. , 0.39269908, 0.78539816])
```

Or with unpacking:

```
In [239]: rlat, rlon = f(lats, lons)
In [240]: rlat.astype(float)
Out[240]: array([-0.78539816, -0.39269908, 0. , 0.39269908, 0.78539816])
```

`frompyfunc`

does iterate through the inputs. In other tests it tends to be 2x faster than more explicit loops. And in this case, since it returns a tuple you don't have to call it twice to get 2 results.

As written, this `convert`

works just as well with arrays as with scalars, so

```
In [241]: convert(lats, lons)
Out[241]:
(array([-0.78539816, -0.39269908, 0. , 0.39269908, 0.78539816]),
array([ 0. , 0.43633231, 0.87266463, 1.30899694, 1.74532925]))
```

which will be much faster than any version that loops in Python.

So for real speed you want `convert`

to work directly with arrays. But if it can't do that, then `frompyfunc`

is a modest improvement over do-it-yourself loops.

Another advantage to `frompyfunc`

- it applies array broadcasting, as in

```
f( lats[:,None], lons[None,:])
```

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