minhpqn

import logging
import sys
from logging.handlers import TimedRotatingFileHandler

FORMATTER = logging.Formatter("%(asctime)s - %(name)s - %(levelname)s - %(message)s")
LOG_FILE = "my_app.log"

def get_console_handler():
	console_handler = logging.StreamHandler(sys.stdout)
	console_handler.setFormatter(FORMATTER)

minhpqn

"""
PyTorch implementation of a sequence labeler (POS taggger).

Basic architecture:
 - take words
 - run though bidirectional GRU
 - predict labels one word at a time (left to right), using a recurrent neural network "decoder"

The decoder updates hidden state based on:
 - most recent word

minhpqn

from sklearn.metrics import confusion_matrix

def print_cm(cm, labels, hide_zeroes=False, hide_diagonal=False, hide_threshold=None):
    """pretty print for confusion matrixes"""
    columnwidth = max([len(x) for x in labels]+[5]) # 5 is value length
    empty_cell = " " * columnwidth
    # Print header
    print "    " + empty_cell,
    for label in labels: 
        print "%{0}s".format(columnwidth) % label,

minhpqn

#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Chương trình chuyển đổi từ Tiếng Việt có dấu sang Tiếng Việt không dấu
Chỉnh sửa từ mã nguồn của anh NamNT
http://www.vithon.org/2009/06/14/x%E1%BB%AD-ly-ti%E1%BA%BFng-vi%E1%BB%87t-trong-python
"""

import re

INTAB = "ạảãàáâậầấẩẫăắằặẳẵóòọõỏôộổỗồốơờớợởỡéèẻẹẽêếềệểễúùụủũưựữửừứíìịỉĩýỳỷỵỹđẠẢÃÀÁÂẬẦẤẨẪĂẮẰẶẲẴÓÒỌÕỎÔỘỔỖỒỐƠỜỚỢỞỠÉÈẺẸẼÊẾỀỆỂỄÚÙỤỦŨƯỰỮỬỪỨÍÌỊỈĨÝỲỶỴỸĐ"

minhpqn

# the following two lines give a two-line status, with the current window highlighted
hardstatus alwayslastline
hardstatus string '%{= kG}[%{G}%H%? %1`%?%{g}][%= %{= kw}%-w%{+b yk} %n*%t%?(%u)%? %{-}%+w %=%{g}][%{B}%m/%d %{W}%C%A%{g}]'

# huge scrollback buffer
defscrollback 5000

# no welcome message
startup_message off

minhpqn

#List unique values in a DataFrame column
pd.unique(df.column_name.ravel())

#Convert Series datatype to numeric, getting rid of any non-numeric values
df['col'] = df['col'].astype(str).convert_objects(convert_numeric=True)

#Grab DataFrame rows where column has certain values
valuelist = ['value1', 'value2', 'value3']
df = df[df.column.isin(value_list)]