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import json
import functools

class Property:
  def __init__(self, name, descr_or_enum, required=False):
    self.name = name
    self.descr_or_enum = descr_or_enum
    self.required = required

  def to_dict(self):       

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"""
Schedule Work Breakdown Structure Uncertainty with Monte Carlo Simulations
"""
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt

def simulate(wbs, n=100000, proba=0.9):
    """ Simulate the possible completion time of a WBS project.
    Parameters

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sudo apt-get install pdftk poppler-utils texlive-extra-utils


# Merge
pdfunite in-1.pdf in-2.pdf in-n.pdf out-merged.pdf


# Rotate

# 1-endnorth

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import numpy as np
import pandas as pd
from scipy.io import loadmat

def mat2csv(file_mat, index=False):
    mat = loadmat(file_mat, squeeze_me=True)
    
    for colname in mat.keys():
        # ignore private column names
        if colname.startswith("__"):

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#include <vector>
#include <boost/dynamic_bitset.hpp>

namespace morton {

/**
    Interleaves a vector of bitsets into a unique bitset.
    @param axes the vector of axis.
    @return a interleaved bitset.
*/

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# -*- coding: utf-8 -*-
import pandas as pd
from shapefile import Reader as read_shp

def shp_to_df(shp_filepath):
  data = {}
  shp = read_shp(shp_filepath)
  fields = shp.fields[1:] # Skip 'DeletionFlag'
  records = shp.records()
  

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def arithmetic_features(X, operations=['+', '-', '/', '*'], commutative=False, inplace=False):
  df = X
  if not inplace:
    df = X.copy()

  from itertools import combinations
  for x, y in combinations(df.columns, 2):
    if '+' in operations:
      df['%s+%s' % (x, y)] = df[x] + df[y]

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# Functions
__err() { echo -e "\033[31mError:\033[0m $1"; exit; }
__warn(){ echo -e "\033[33mWarn :\033[0m $1"; }
__info(){ echo -e "\033[34mInfo :\033[0m $1"; }


# Use
__err "You must be root."
__warn "Missing temp file"
__info "Copying 'x' file"