Moveton - 4 months ago 4x

Python Question

I have a pretty simple issue: I need to convert the file with geographical coordinates like

`Lat Long`

50 0 50 35 1 40

50 2 50 35 10 20

50 3 1 35 13 22

50 2 38 35 14 40

49 59 6 35 13 22

49 57 14 35 13 21

49 57 10 35 13 0

49 57 0 35 6 20

to the

`Lat Long`

50.01389,35.02778

50.04722,35.17222

etc.

Math is as simple as a pie: we have to devide minutes (0 and 1 in this particular case) by 60 and seconds (50 and 40) by 3600, then add these numbers and we will get the remainder of the degree (50 and 35).

Here is my script with numpy. I suppose, it looks to big for such a simple conversion, however I don't know how to do this simpler. Also I don't know how to end this script, so it could do what it should. Now it ends with adding minutes and seconds.

`import sys`

import numpy as np

filename = input('Please enter the file\'s name: ')

with open(filename, "r") as f:

sys.stdout = open('%s (converted).txt' % f.name, 'a')

data = np.loadtxt(f)

degree_lat, degree_long = data[:, 0], data[:, 3]

min_lat, sec_lat, min_long, sec_long = \

(data[:, 1] / 60), (data[:, 2] / 3600), (data[:, 4] / 60), (data[:, 5] / 3600)

remainder_lat, remainder_long = min_lat + sec_lat, min_long + sec_long

degree_result_lat = degree_lat + remainder_lat

degree_result_long = degree_long + remainder_long

Any suggestions would be greatly appreciated! Thanks and sorry for the amateur questions.

Answer

If I understand correctly what you have in `data`

array,

```
data = data.T # not strictly necessary, but simplifies following indexing
lat = data[0]+data[1]/60.+data[2]/3600.
lon = data[3]+data[4]/60.+data[5]/3600.
converted = np.vstack((lat,lon)).T
np.savetxt(outname, converted)
```

Line by line comment

`data.T`

transposes the array, columns becomes tows and in Python it's easier to address rows than columns...`data[0]+data[1]/60.+data[2]/3600.`

is a*vectorized*expression, each row of the`data`

array is an array on its own, and you can evaluate algebraic expressions, possibly using also`numpy`

's functions that accept, as arguments, vector expressions as well.- as aboveā¦
`np.vstack((lat,lon)).T`

we have two names that reference two different expressions, we want to combine them in a single array, so that we can use`np.savetxt()`

to save it. Using`np.vstack()`

we get an array like`[[lt0, lt1, ..., ltN], [ln0, ln1, ..., lnN]]`

but we want to save an array like

`[[lt0, ln0], [lt1, ln1], ...`

so we have to transpose the result of

`np.vstack()`

`np.savetxt(outname, converted)`

we save at once the whole array using one of the convenient conveniency functions offered by the`numpy`

libraries.

Note that, when using `numpy`

you should try to avoid explicit loops and instead relying on its ability to *vectorize* most expressions. This leads to much more efficient code.

Source (Stackoverflow)

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