data_to_raw_heightmap.py

data_to_raw_heightmap.py

from collections import defaultdict
import numpy as np
import time

# A CSV File with about 35 million lines looking like this:
# 578559.000 5917080.000 5.608
# 578560.000 5917080.000 5.639
# 578562.000 5917080.000 -2.629
# ...
FILENAME = "../../Sources/HH_bis_28082013_1m_NN_UTM.txt"
# FILENAME = "../../Sources/test.txt"

def benchmark(functions, iterations):
    """
    used for benchmarking performance-critical code

    """
    counts = defaultdict(list)
    for i in range(iterations):
        for func in functions:
            start_time = time.time()
            func()
            counts[func].append(time.time() - start_time)

    for key, vals in counts.items():
        print key.__name__, ":", sum(vals) / float(len(vals))


def convert_file(filename):
    arr = np.fromfile(filename, dtype=np.double, sep=' ')
    arr.tofile(filename + '.dat')

def get_extrema(filename):
    arr = np.fromfile(filename + '.dat', dtype=np.double)
    print('File read')
    num_rows = len(arr) // 3
    arr = arr.reshape((num_rows, 3)).T
    ret = {}
    for i, name in enumerate(['x', 'y', 'z']):
        ret[name] = {
            'min': np.min(arr[i]),
            'max': np.max(arr[i])
        }
    return ret

# convert_file(FILENAME)
print(get_extrema(FILENAME))