Example #1
0
def set_nthreads(nthreads):
    """
    set_nthreads(nthreads)

    Sets the number of threads to be used during bcolz operation.

    This affects to both Blosc and Numexpr (if available).  If you want to
    change this number only for Blosc, use `blosc_set_nthreads` instead.

    Parameters
    ----------
    nthreads : int
        The number of threads to be used during bcolz operation.

    Returns
    -------
    out : int
        The previous setting for the number of threads.

    See Also
    --------
    blosc_set_nthreads

    """
    nthreads_old = bcolz.blosc_set_nthreads(nthreads)
    if bcolz.numexpr_here:
        bcolz.numexpr.set_num_threads(nthreads)
    return nthreads_old
Example #2
0
def set_nthreads(nthreads):
    """
    set_nthreads(nthreads)

    Sets the number of threads to be used during bcolz operation.

    This affects to both Blosc and Numexpr (if available).  If you want to
    change this number only for Blosc, use `blosc_set_nthreads` instead.

    Parameters
    ----------
    nthreads : int
        The number of threads to be used during bcolz operation.

    Returns
    -------
    out : int
        The previous setting for the number of threads.

    See Also
    --------
    blosc_set_nthreads

    """
    nthreads_old = bcolz.blosc_set_nthreads(nthreads)
    if bcolz.numexpr_here:
        bcolz.numexpr.set_num_threads(nthreads)
    return nthreads_old
import time

from tqdm import tqdm

import h5py  # for saving later usable files

import gc
from glob import glob

from sklearn.metrics import fbeta_score
from sklearn.model_selection import StratifiedKFold
import tensorflow as tf
import cv2
import bcolz
bcolz.blosc_set_nthreads(4)
bcolz.numexpr.set_num_threads(4)
#from joblib import Parallel, delayed
import image_ml_ext  #modified ImageDataGenerator

import random
random_seed = 2017
random.seed(random_seed)
np.random.seed(random_seed)


def f2_score(y_true, y_pred):
    # from https://www.kaggle.com/teasherm/keras-metric-for-f-score-tf-only
    y_true = tf.cast(y_true, "int32")
    y_pred = tf.cast(tf.round(y_pred),
                     "int32")  # implicit 0.5 threshold via tf.round
Example #4
0
"""
from __future__ import absolute_import

import os
import sys
sys.setrecursionlimit(8192)
import time
import re
import shutil
import zlib

import numpy as np
import bcolz
import numexpr as ne
bcolz.blosc_set_nthreads(2)
ne.set_num_threads(2)
import sqlalchemy as sql
from . import database

from . import compression
from .gemini_utils import get_gt_cols

def get_samples(metadata):
    return [x['name'] for x in metadata.tables['samples'].select().order_by("sample_id").execute()]

def get_n_variants(cur):
    return next(iter(cur.execute(sql.text("select count(*) from variants"))))[0]

def get_bcolz_dir(db):
    if not "://" in db: