I am a bit new to NumPy and Python. I have string text in the format like below:
lat0 37.792480, lon0 -122.397450
lat1 39.792480, lon1 -132.397450
...
I want to load the only floating numbers to my array as 2d array with 0th column as lat and 1st column as lan. What should be the pattern for this kind of data loading.
Since you mention numpy, this is one way:
import numpy as np
lst = ['lat0 37.792480, lon0 -122.397450',
'lat1 39.792480, lon1 -132.397450']
res = np.array([[i.rsplit(None, 1)[-1] for i in x.split(',')] for x in lst]).astype(float)
# array([[ 37.79248, -122.39745],
# [ 39.79248, -132.39745]])
If you have string mytext.txt like so,
lat0 37.792480, lon0 -122.397450
lat1 39.792480, lon1 -132.397450
You can read input from a text file into your python program run.py likepython run.py < mytext.txt
You can also open and read your textfile in python like
with open('mytext.txt') as f:
text = f.readlines()
Because i've recently been using python 3's input(), I'll explain using that option.
However you need to know the number of lines in mytext.txt, because input() is line by line.
Apparently in unix you can run wc -l < mytext.txt for # of lines.
import numpy as np
coordinates = np.zeros([numlines, numlines]) # Instantiate array.
for i in range(numlines):
data = input() # How we can read text from standard input.
data = data.split(',') # Split by comma, giving ['latN float1', ' lonN float2']
lat = data[0].split()[1] # Isolate 'latN float1', split by ' ', get 'float1'.
lon = data[1].split()[1] # Isolate 'lonN float2', split by ' ', get 'float2'.
lat = float(lat) # Convert from string to float.
lon = float(lon) # Convert from string to float.
coordinates[i] = lat, lon # Replace zeros with lat, lon
You'll have a numpy array: array([[lat0, lon0], [lat1, lon1]...,[, latN, lonN]])
