import numpy as np


def load_mixture(fname):
    with open(fname) as f:
        return np.array([float(_) for _ in f.read().split()])


def load_populations(fname):
    pop_names = []
    populations = []
    for line in open(fname):
        data = line.split()
        pop_names.append(data[0])
        populations.append(np.array([float(_) for _ in data[1:]]))
    return pop_names, populations

8aee8b3fd1ebea726433fb4a657c17ab3dac73d4
<mask token>

<mask token>


def load_mixture(fname):
    with open(fname) as f:
        return np.array([float(_) for _ in f.read().split()])


<mask token>

<mask token>


def load_mixture(fname):
    with open(fname) as f:
        return np.array([float(_) for _ in f.read().split()])


def load_populations(fname):
    pop_names = []
    populations = []
    for line in open(fname):
        data = line.split()
        pop_names.append(data[0])
        populations.append(np.array([float(_) for _ in data[1:]]))
    return pop_names, populations

import numpy as np


def load_mixture(fname):
    with open(fname) as f:
        return np.array([float(_) for _ in f.read().split()])


def load_populations(fname):
    pop_names = []
    populations = []
    for line in open(fname):
        data = line.split()
        pop_names.append(data[0])
        populations.append(np.array([float(_) for _ in data[1:]]))
    return pop_names, populations
