goraj

import numpy as np
from sklearn.datasets import load_digits
from sklearn.metrics import roc_auc_score
import lightgbm as lgbm


if __name__ == '__main__':
    np.random.seed(4242)
    d = load_digits()

goraj

bool video_recorder::setup_videoio(cv::Mat & mat, double fps) {

	std::string cmdline = ffmpeg_path_.string() + 
		" -framerate " + std::to_string(static_cast<int>(fps)) +
		" -f image2pipe -vcodec png -i - -c:v libx264 -pix_fmt yuv444p" +
		" -preset faster " +
		//" -preset ultrafast " +
		" -crf 14" +
		//" -qp 0 " +
		" -vf drawtext=\"fontcolor = white:fontfile = " +

goraj

def offset_version_detection(quality_string = ''):
    """Tries to detect phred score offset automatically.
    Args:
        quality_string used to estimate format version and offset
    Returns:
        Phred offset
    Raises:
        ValueError: Cannot evaluate empty quality string
        ValueError: Cannot evaluate phred offset
    """

goraj

# -*- coding: utf-8 -*-
"""
Created on Wed Mar 21 08:36:44 2018

@author: user
"""
import cv2
import numpy as np

goraj

# -*- coding: utf-8 -*-
"""
@author: goraj
"""
import lightgbm as lgbm
from sklearn.datasets import load_digits
import numpy as np

from sklearn.model_selection import train_test_split
from sklearn.metrics import roc_auc_score

goraj

def ic50_in_nM_to_pic50(nM):
    try:
        return 9.0 - math.log10(float(nM))
    except Exception as e:
        return 0.0
           
def ic50_in_uM_to_pic50(uM):
    nM = uM * 1000
    return ic50_in_nM_to_pic50(nM)
    

goraj

def make_window_borderless(self):
        """
            Requires: pywin32
            https://www.lfd.uci.edu/~gohlke/pythonlibs/#pywin32
            import win32gui as wg
            import win32api as wa
            import win32con as wc
            
            Based on: https://github.com/howardjohn/pyty/blob/master/src/window_api.py
        """

goraj

# -*- coding: utf-8 -*-
"""
Created on Fri Aug 10 21:41:24 2018

@author: goraj
"""
import numpy as np
from sklearn.ensemble import RandomForestClassifier

from warnings import warn

goraj

'''
>>> dask.__version__
'1.0.0'

>>> umap.__version__
'0.3.7'
'''
from dask.distributed import Client

def do_run(arg1, arg2):

goraj

-bash-4.2$ ./Miniconda3-latest-Linux-x86_64.sh -b -p ~/m3_centos7
PREFIX=/home/username/m3_centos7
installing: python-3.7.0-hc3d631a_0 ...


Python 3.7.0 (default, Jun 28 2018, 13:15:42)
[GCC 7.2.0]
installing: ca-certificates-2018.03.07-0 ...
installing: conda-env-2.6.0-1 ...
installing: libgcc-ng-8.2.0-hdf63c60_1 ...