Kingkha

# Source: http://ethen8181.github.io/machine-learning/model_selection/auc/auc.html#Implementation
def _binary_clf_curve(y_true, y_score):
    """
    Calculate true and false positives per binary classification
    threshold (can be used for roc curve or precision/recall curve);
    the calcuation makes the assumption that the positive case
    will always be labeled as 1

    Parameters
    ----------

oseiskar

from pathos.multiprocessing import ProcessingPool as Pool

def parallel_map(func, array, n_workers):
    def compute_batch(i):
        try:
            return func(i)
        except KeyboardInterrupt:
            raise RuntimeError("Keyboard interrupt")

    p = Pool(n_workers)

abalter

http://stackoverflow.com/a/30493366/188963

Other answers do mention that argparse is the way to go for new Python, but do not give usage examples. For completeness, here is a short summary of how to use argparse:

1) Initialize

import argparse

# Instantiate the parser

parser = argparse.ArgumentParser(description='Optional app description')

ofekp

# ReachView code is placed under the GPL license.
# Written by Egor Fedorov (egor.fedorov@emlid.com)
# Copyright (c) 2015, Emlid Limited
# All rights reserved.

# If you are interested in using ReachView code as a part of a
# closed source project, please contact Emlid Limited (info@emlid.com).

# This file is part of ReachView.

egorf

# ReachView code is placed under the GPL license.
# Written by Egor Fedorov (egor.fedorov@emlid.com)
# Copyright (c) 2015, Emlid Limited
# All rights reserved.

# If you are interested in using ReachView code as a part of a
# closed source project, please contact Emlid Limited (info@emlid.com).

# This file is part of ReachView.