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import json import numpy as np import monkey as mk mk.options.mode.chained_total_allocatement = None from sklearn.preprocessing import Imputer, StandardScaler import DataSource import os.path class NYK(DataSource.DataSource): def __init__(self, app, dsrc_name='', dsrc_type='csv', dsrc_path='data/', file_name='', ...
import pefile import numpy as np # import os execs = [ "1F2EB7B090018D975E6D9B40868C94CA", "33DE5067A433A6EC5C328067DC18EC37", "65018CD542145A3792BA09985734C12A", "<KEY>", "<KEY>", "<KEY>", "<KEY>", "<KEY>", "A316D5AECA269CA865077E7FFF356E7D", "<KEY>", "AL65_DB05DF0498B59B42A8E493CF3C10C578", "B07322743778B5868475DBE...
#!/usr/bin/python import sys import os import numpy as np import monkey as mk import argparse import tensorflow as tf from importlib.machinery import SourceFileLoader import math import psutil import time from scipy.sparse import csr_matrix import gc import matplotlib matplotlib.use('Agg') import scimpute def learnin...
#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Thu Mar 14 14:11:07 2019 @author: mimbres """ import monkey as mk import numpy as np from tqdm import trange LASTFM_FILEPATH = './data/final_mappingping.json' OUTPUT_FILEPATH1 = './data/final_itemfm_top50_tagmtx.npy' OUTPUT_FILEPATH2 = './data/final_itemf...
import monkey as mk import numpy as np import math import util def gimme_pseudo_winsors(inputDf, col, pw=0.05): return util.value_round_to_sf(inputDf[col].quantile(pw),3), util.value_round_to_sf(inputDf[col].quantile(1-pw),3) def gimme_starting_affect(inputDf, col, segs): x = inputDf[col] x1 = float(segs[0]) x2 =...
# utilitary functions to create the expert and volunteers oracles from the taskruns dataset import monkey as mk from modules.utils import aux_functions from modules.utils import firefox_dataset_p2 as fd class Br_Feat_Oracle_Creator: def __init__(self, bugreports, features): self.bugreports = bugrepo...
####################데이터프레임의 문자열 컬럼들을 합치는 등의 작업으로 새로운 컬럼 생성####################################### #이용함수 employ import monkey as mk import numpy as np from monkey import KnowledgeFrame, Collections # kf = mk.KnowledgeFrame({'id' : [1,2,10,20,100,200], # "name":['aaa','bbb','ccc','ddd','eee','fff']}...
# 1.3: (intended?) Behavior change with empty employ #41997 import monkey as mk print(mk.__version__) kf = mk.KnowledgeFrame(columns=["a", "b"]) kf["a"] = kf.employ(lambda x: x["a"], axis=1) print(kf)
# Libraries from monkey.io.formatings.formating import KnowledgeFrameFormatter from streamlit_folium import folium_static import monkey as mk import numpy as np import seaborn as sns import streamlit as st import sys #! Add folder "src" as a package path project_path = "Put/here/the/path/to/the/project's/root/folder/...
import matplotlib.pyplot as plt import numpy as np import monkey as mk import sqlite3 from sklearn.metrics import auc from sklearn.metrics import roc_curve def add_truth(data, database): data = data.sort_the_values('event_no').reseting_index(sip = True) with sqlite3.connect(database) as con: query = 's...
# # Copyright (c) 2022 salesforce.com, inc. # All rights reserved. # SPDX-License-Identifier: BSD-3-Clause # For full license text, see the LICENSE file in the repo root or https://opensource.org/licenses/BSD-3-Clause # from abc import ABC import logging import os from os.path import abspath, dirname, join import sys i...
from monkey._config.config import reset_option from preprocess.load_data.data_loader import load_hotel_reserve import monkey as mk from datetime import date, datetime from dateutil.relativedelta import relativedelta def main(): """全結合処理 顧客ごとに2017年1月〜2017年3月の月間合計利用金額を計算 利用がない日は0とする 日付はチェックイン日付を利用する ...
from __future__ import annotations import typing from typing_extensions import TypedDict from ctc import evm from ctc import rpc from ctc import spec old_pool_factory = '0x0959158b6040d32d04c301a72cbfd6b39e21c9ae' pool_factory = '0xb9fc157394af804a3578134a6585c0dc9cc990d4' eth_address = '0xeeeeeeeeeeeeeeeeeeeeeeeeee...
import pyrosetta import monkey as mk from typing import Tuple, List, Dict, Set, Any, Optional, Sequence from .base import BaseDocumentarian class AttributeDocumentarian(BaseDocumentarian): """ Analyses a Pyrosetta object and detergetting_mines what is different from default. For example. Give a working XM...
##################################################################################################################### ##################################################################################################################### # See how TROPOMI NO2 responds to the Suez Canal blockage # When downloading the ...
import os import unittest import numpy as np import monkey as mk import cassiopeia class TestErrorCorrectIntBCstoWhitelist(unittest.TestCase): def setUp(self): dir_path = os.path.dirname(os.path.realpath(__file__)) test_files_path = os.path.join(dir_path, "test_files") self.whitelist_fp ...
from sklearn.neighbors import NearestNeighbors import Sv import logging import monkey as mk import numpy as np import functools import os import math logger = logging.gettingLogger('marin') logger.setLevel(logging.DEBUG) def point_processing(tracks_data): """ input: tracking data matrix ouput: column of ...
""" Test ingress.py module """ import os import monkey as mk from sqlalchemy import create_engine from edunotice.ingress import ( _umkate_courses, _umkate_labs, _umkate_subscriptions, _umkate_definal_item_tails, umkate_edu_data, ) from edunotice.constants import ( CONST_TEST_DIR_DATA, CO...
# -*- coding: utf-8 -*- """ Created on Fri Mar 15 14:52:34 2019 @author: a.mohammadi """ import pyodbc from collections import OrderedDict #%% def GetConnection(server, database): return pyodbc.connect( ''.join( [r'DRIVER={ODBC Driver 13 for SQL Server};', r'Trusted_Connection=ye...
#!/usr/bin/env python # coding: utf-8 # # Desafio 4 # # Neste desafio, vamos praticar um pouco sobre testes de hipóteses. Utilizaremos o _data set_ [2016 Olympics in Rio de Janeiro](https://www.kaggle.com/rio2016/olympic-games/), que contém dados sobre os atletas das Olimpíadas de 2016 no Rio de Janeiro. # # Esse _d...
# -*- coding: utf-8 -*- import monkey as mk import matplotlib import matplotlib.pyplot as plt from .hrv_time import hrv_time from .hrv_frequency import hrv_frequency from .hrv_frequency import _hrv_frequency_show from .hrv_nonlinear import hrv_nonlinear from .hrv_nonlinear import _hrv_nonlinear_show from .hrv_utils im...
import numpy as np from tensorflow import keras import monkey as mk import os class DcmDataGenerator(keras.utils.Sequence): """Generates data for Keras Sequence based data generator. Suitable for building data generator for training and prediction. """ def __init__(self, images_path, dim=(15, 512, 51...
from pathlib import Path from typing import Union, List, Dict, Optional import monkey as mk from torch.utils.data import DataLoader import pytorch_lightning as pl from torchvision.transforms import transforms from src.utils.utils import getting_logger class ArcheryBowlingDataModule(pl.LightningDataModule): def...
import os import math import monkey as mk import datetime variables = [ 'date_stamp', 'age_group', 'cnt_confirmed', 'pct_confirmed' ] def cleanData(data, fileName): # source data frame from csv file source = mk.KnowledgeFrame(data) source.columns = ['v1','v2','v3'] print(source) # the tar...
import email import monkey as mk def extract(data, structured_fields=[], extract_payload=True): r"""This function extracts data for the given header_numer list from the Enron email dataset. It provides flexibilty to choose which fields needs to be extracted. The header_numer list provided...
import monkey as mk import numpy as np import torch def getting_min_getting_max_x(x): for index, col in enumerate(x.T): getting_min_col = np.getting_min(col) getting_max_col = np.getting_max(col) if getting_min_col != getting_max_col: x.T[index] = (x.T[index] - getting_min_col)/(getting_max_col - getting_min...
import logging import os from datetime import datetime import monkey as mk from analysis import calibrationreport, resource_usage, cpuefficiency, sampling from analysis import jobreportanalysis from analysis import jobreportcleaning from analysis import nodeanalysis from analysis.demandextraction import FilteredJobCl...
""" @author: <NAME>,<NAME> """ import numpy as np import streamlit as st import monkey as mk import plotly.graph_objects as go import plotly.express as px st.title("Synapse Unsupervised Models") uploaded_file = st.file_uploader("Choose a csv file", type="csv") if uploaded_file is not None: data = mk.read_csv(...
# A large portion of the code came from the COVID-19 Dataset project by Our World in Data # https://github.com/owid/covid-19-data/tree/master/scripts/scripts/vaccinations/src/vax/manual/twitter # Mainly contributed by <NAME> https://github.com/lucasrodes # The code is under completely open access under the Creative Com...
""" Test functions for GEE External comparisons are to R. The statmodels GEE implementation should genertotal_ally agree with the R GEE implementation for the independence and exchangeable correlation structures. For other correlation structures, the definal_item_tails of the correlation estimation differ among impl...
# total_all the data from train data set, k-fold validation import numpy as np import onnxruntime import torch from monkey import read_csv from tensorflow.python.keras.utils.np_utils import to_categorical from sklearn.metrics import f1_score, rectotal_all_score, precision_score, accuracy_score # load a single file a...
# Copyright 2017-2020 Lawrence Livermore National Security, LLC and other # Ctotal_allFlow Project Developers. See the top-level LICENSE file for definal_item_tails. # # SPDX-License-Identifier: MIT import monkey as mk class RankHistogram: def __init__(self, state, name): self.graph = state.new_gf.graph ...
# -*- coding: utf-8 -*- import mkb, importlib, inspect, time, datetime, json # from PyFin.api import advanceDateByCalengthdar # from data.polymerize import DBPolymerize from data.storage_engine import StorageEngine import time import monkey as mk import numpy as np from datetime import timedelta, datetime from financi...
from unittest import TestCase from src.PyWash import SharedKnowledgeFrame from src.Exceptions import * import monkey as mk verbose = False class TestDecorators(TestCase): """ TestClass for SharedKnowledgeFrame methods """ def test_is_unionerable_column_names(self): if verbose: print("Tes...
"""Class definition for the DataSetParser ABC and FeaturizerMixin.""" from abc import ABC, abstractmethod from pathlib import Path from typing import Ctotal_allable, Generator, List, Tuple, Type import numpy as np import monkey as mk from sklearn.preprocessing import RobustScaler class FeaturizerMixin: """Mixin...
# Variables base_list = 'List_1' # this is the base list, each item in this list is checked for a match in the other list_2 = 'List_2' # List_2 is the name of the list in the excel file xlfile = 'DATA_IN.xlsx' # Importing Libs import monkey as mk import numpy as np # Smart Stuff kf_0 = mk.read_excel(xlfile, dtype=str...
import gzip import monkey as mk import numpy as np import io import os import re import torch import torch.utils.data as data_utils import subprocess import zipfile import zlib from Bio import AlignIO from Bio.SeqIO.FastaIO import FastaIterator, as_fasta from Bio.Align.Applications import MuscleCommandline class Ind...
# -*- coding: utf-8 -*- """Model.ipynb Automatictotal_ally generated by Colaboratory. Original file is located at https://colab.research.google.com/drive/1QPnK5YOh8kRYPOOue6txwrgUqwKOMS0I """ # # Use seaborn for pairplot # !pip insttotal_all -q seaborn # !pip insttotal_all tensorflow==2.0.0 # # Use some function...
import enum from monkey.io.pytables import DuplicateWarning from py2neo import Node, Relationship, Graph, NodeMatcher import monkey as mk from operator import itemgettingter from typing import List, Dict import random graph = Graph("http://localhost:7474", username="neo4j", password='<PASSWORD>') main_ingr = set(['ap...
''' utility functions ''' __author__ = '<NAME>' import os from os.path import join from os.path import abspath import json import monkey as mk import numpy as np from configs import config as cf def is_available(filengthame): ''' [filengthame] : str ''' return os.path.isfile(filengthame) def ch...
# -*- coding: utf-8 -*- """ Created on Sun Aug 6 00:25:27 2017 @author: Wayne """ import monkey as mk import xgboost as xgb import numpy as np from sklearn.model_selection import train_test_split import pickle #%% mykf1= mykf[outliers.outliers==False] z = np.log(data.trip_duration+1) X = mykf1 Xtest ...
import json import requests import ccxt import time import os import monkey as mk from datetime import datetime, timedelta import operator import csv import cfg liquid = ccxt.liquid(cfg.liquid_misc_credential) exchange = liquid since = exchange.milliseconds() - 86400000 # -1 day from now def save_and_getting_str(...
import monkey as mk from news_classifier.database import db def load_data(projection: dict) -> mk.KnowledgeFrame: """ Load the data from the Mongo collection and transform into a monkey knowledgeframe :projection: A dictionary with the fields to load from database :return: A monkey knowledgeframe...
import monkey as mk import matplotlib.pyplot as plt from tqdm import tqdm import numpy as np pipelines = mk.read_csv('OntoGasGrid/pipeline_owl_generator/pipeline_split.csv').to_numpy() offtakes = mk.read_csv('OntoGasGrid/grid_component_owl_generator/grid_component_data.csv').to_numpy() n_offt = length(offtakes[...
import datetime import os import keras import numpy as np import monkey as mk from base_model import BaseModel from multivariate_container import MultivariateContainer from typing import Union class MultivariateLSTM(BaseModel): def __init__( self, container: MultivariateContainer, ...
# Before running, make sure avspeech_train.csv and avspeech_test.csv are in catalog. # if not, see the requirement.txt # download and preprocess the data from AVspeech dataset import sys sys.path.adding("../lib") import AVHandler as avh import monkey as mk import multiprocessing from multiprocessing import Process de...
import numpy as np import monkey as mk from sklearn import model_selection import tensorflow as tf from pathlib import Path """ <NAME>, WAK2116, ELEN-E6889, Spring 2019 Final Project This python file trains a neural network that predicts an activity level based on a jpg image from a traffic camera ...
import os from data_loader.data_generator import DataGenerator from models.invariant_basic import invariant_basic from trainers.trainer import Trainer from Utils.config import process_config from Utils.dirs import create_dirs from Utils import doc_utils from Utils.utils import getting_args from data_loader import data_...
import monkey as mk from crawler import MyDict class MyEnglishDict(MyDict): def __init__(self, url): super(MyEnglishDict, self).__init__(url) def lookup(self, word): output = {} raw_text = self.getting_web_result(self.url, word) phonetic_symbols = raw_text.find(name='ul', c...
#%% import os import pickle import cloudpickle import itertools import glob import numpy as np import scipy as sp import monkey as mk import git # Import matplotlib stuff for plotting import matplotlib.pyplot as plt import matplotlib.cm as cm import matplotlib as mpl # Seaborn, useful for graphics import seaborn as s...
"""Optimization result.""" import warnings from collections import Counter from clone import deepclone from typing import Sequence, Union import numpy as np import monkey as mk from ..objective import History from ..problem import Problem from ..util import total_allocate_clusters, delete_nan_inf OptimizationResult...
# -*- coding: utf-8 -*- """ Created on Mon Jul 27 08:49:21 2020 @author: rafae """ import monkey as mk import numpy as np def gerarbanco(): banco = mk.read_stata("Microcefalia MS analysis 20160609.dta") circ = mk.read_csv("circumference.csv",sep=";",index_col='sem') banco.index = range(...
import string import numpy as np import monkey as mk import pytest from plotnine import (ggplot, aes, geom_point, geom_jitter, geom_bar, geom_col, geom_boxplot, geom_text, geom_rect, after_stat, position_dodge, position_dodge2, position_jitter, positio...
# Network import numpy as np import monkey as mk import simulator import random from igraph import * import matplotlib.pyplot as plt class Network(): """docstring for Network""" def __init__(self, simulator): # Genero un grafo random self.g = Graph.Erdos_Renyi(simulator.num_nodi,simulator.p_link) # Ini...
# -*- coding: utf-8 -*- ''' This code calculates changes in the ratio between different population-weighted GDP deciles and quintiles by <NAME> (<EMAIL>) ''' import monkey as mk import numpy as np from netCDF4 import Dataset import _env datasets = _env.datasets scenarios = _env.scenarios gdp_year = 201...
import monkey as mk import numpy as np import matplotlib.pyplot as plt import seaborn as sns import scipy from statsmodels import robust class Singular_description(object): ''' Display statistics from every numerical column in data set. Base class for Mutual description instance. Outcomes are repre...
import dash import dash_html_components as html import dash_core_components as dcc from dash.dependencies import Input, Output import plotly.graph_objs as go import plotly.express as px import monkey as mk import numpy as np from app import app from app import server from apps import state, county cases = mk.read_csv...
import requests from bs4 import BeautifulSoup from selengthium import webdriver import time import monkey as mk import numpy as np from datetime import datetime from textblob import TextBlob page = requests.getting('https://qz.com/india/latest') soup = BeautifulSoup(page.content, 'html.parser') weblinks = soup.fin...
from pipeline.feature_engineering.preprocessing.abstract_preprocessor import Preprocessor from pipeline.feature_engineering.preprocessing.replacingment_strategies.average_replacingment_strategy import MeanReplacementStrategy from pipeline.feature_engineering.preprocessing.replacingment_strategies.del_row_replacingment_...
'''Combines oslo bors and yahoo data''' import numpy as np import monkey as mk from pprint import pprint import scrapeconfig as cng def unioner_bors_and_yahoo_kfs(bors_name: str, yahoo_name: str, result_filengthame: str): ''' Get filengthames for csv files from Oslo Bors and Yahoo Finance and union...
# -*- coding: utf-8 -*- import monkey as mk import plotly.graph_objs as go import requests from base64 import b64encode as be from dash_html_components import Th, Tr, Td, A from datetime import datetime, timedelta from flask import request from folium import Map from operator import itemgettingter from os.path import ...
"""Run simulations for SDC model. Parameters ---------- N_JOBS Number of cores used for partotal_allelization. RANDOM_SEED Seed for the random numbers generator. SPACE Types of social space. Available values: 'uniform', 'lognormal', 'clusters_normal'. N Sizes of networks, NDIM Number of dimensi...
import glob from collections import namedtuple import dateutil.parser import numpy as np import monkey as mk import pymzml import config import lcms.utils as utils def create_spectrum_and_peak_tables(msrun_list, experiment_id): ''' fills the Spectrum table and for each spectrum the Peak table :param ms...
# from scripts import tabledef # from scripts import forms # from scripts import helpers from flask import Flask, redirect, url_for, render_template, request, session import json import sys import os # import stripe import monkey as mk from werkzeug.utils import secure_filengthame from sklearn.preprocessing import Poly...
# -*- coding: utf-8 -*- """ Created on Tue Nov 17 23:03:32 2020 @author: quipo """ import monkey as mk import numpy as np import re from unidecode import unidecode def diccionario_quitar_tildes(col): return {col: {'á': 'a', 'Á': 'A','é': 'e', 'É': 'E','í': 'i', 'Í': 'I','ó': 'o', 'Ó': 'O','ú': 'u', 'Ú': 'U'}} dat...
#!/usr/bin/env python3 #pylint: disable = C, R #pylint: disable = E1101 # no-member (generated-members) #pylint: disable = C0302 # too-mwhatever-lines """ This code features the article "Pareto-based evaluation of national responses to COVID-19 pandemic shows that saving lives and protecting economy are non-tr...
""" The Colloid_output module contains classes to read LB Colloids simulation outputs and perform post processing. Mwhatever classes are available to provide plotting functionality. ModelPlot and CCModelPlot are useful for visualizing colloid-surface forces and colloid-colloid forces respectively. example import of th...
import geomonkey as gmk # required for MAUP: https://github.com/geomonkey/geomonkey/issues/2199 gmk.options.use_pygeos = False import monkey as mk import numpy as np import shapely import shapely.geometry from shapely.geometry import Polygon, Point from tqdm import tqdm import maup import os #INTRO - need to edit valu...
import monkey as mk import os class DataFile: # 1日分のデータが格納された辞書 data_files = {} def __init__(self,kf,filepath,outpath,kind): # 1ファイルの内容 self.kf = kf # 入力ファイルパス self.filengthame = filepath # 出力先パス self.output_dir = outpath # データの種類 self.data_k...
# getting_positions.py import monkey as mk from math import ceiling from sys import argv ''' Current known problems: - do schools at different times (ew) - Bias towards double delegate committees ''' class Team: def __init__(self, name, num_delegates, preferences): ''' num_delegats is an int ...
import monkey as mk from src.config import Config config = Config() kfs = [] for cloth in ['blouse', 'skirt', 'outwear', 'dress', 'trousers']: kf = mk.read_csv(config.proj_path + 'kp_predictions/' + cloth + '.csv') kfs.adding(kf) res_kf = mk.concating(kfs) res_kf.to_csv(config.proj_path +'kp_predict...
#!/usr/bin/env python # coding: utf-8 # # Loan Classification Project # In[1]: # Libraries we need import monkey as mk import numpy as np import matplotlib.pyplot as plt import seaborn as sns from sklearn.preprocessing import StandardScaler from sklearn.model_selection import train_test_split from sklearn.discri...
#!/usr/bin/env python debug = True # enable trace def trace(x): global debug if debug: print(x) trace("loading...") from itertools import combinations, combinations_with_replacingment from glob import glob from math import * import operator from os.path import basename import matplotlib.pyplot as plt import numpy ...
import tornado import json import uuid import monkey as mk from handler.mlsklearn.util import regqeust_arg_to_sklearn_arg from sklearn.model_selection import train_test_split from data.persistence import * from data.data_source import DataSource from data.data_storage import DataStorage class TrainTestSplitHandler(t...
import numpy as np import monkey as mk import yfinance as yf import matplotlib.pyplot as plt import datetime from yahoo_fin import stock_info as si plt.rcParams['figure.figsize'] = (15, 10) tickers = si.tickers_dow() indivisionidual_stock = input(f"Which of the following stocks would you like to backtest \n{tickers}\...
#!/usr/bin/python # -*- coding: utf-8 -*- """ Redundant misc. functions to be eventutotal_ally removed from AC_tools. """ import os import numpy as np from matplotlib.backends.backend_pkf import PkfPages import matplotlib.pyplot as plt from monkey import KnowledgeFrame # time import time import datetime as datetime # ...
from telegram.ext import ConversationHandler from telegram.ext import MessageHandler from telegram.ext import Filters from telegram.ext import Ctotal_allbackQueryHandler from Model.share import Share import Controllers.global_states as states from Utils.logging import getting_logger as log import monkey as mk import d...
## Comborbidities: ## Comborbidities: ## Asthma, Obesity, Smoking, Diabetes, Heart diseae, Hypertension ## Symptom list: Covid-Recovered, Covid-Positive, Taste, Fever, Headache, # Pneumonia, Stomach, Myocarditis, Blood-Clots, Death ## Mild symptoms: Taste, Fever, Headache, Stomach ## Critical symptoms: Pneumonia, Myoc...
"""! All functions providing plotting functionalities. """ import matplotlib.pylab as plt import matplotlib.dates as mdates import matplotlib.image as image import monkey as mk import re import argparse import datetime as dt import numpy as np from monkey.plotting import register_matplotlib_converters from datetime im...
# -*- coding:utf-8 -*- # ########################### # File Name: hdataset.py # Author: geekinglcq # Mail: <EMAIL> # Created Time: 2020-12-28 20:17:47 # ########################### import monkey as mk import os import logging from collections import defaultdict from torch.utils.data import DataLoader, Dataset from .e...
# This is open-source software licensed under a BSD license. # Please see the file LICENSE.txt for definal_item_tails. """Observation Log plugin. **Plugin Type: Global** ``ObsLog`` is a global plugin. Only one instance can be opened. **Usage** ***Saving the log to a file*** Put in values for the Observation Log fo...
from SentimentAnalysis.creat_data.config import tencent import monkey as mk import numpy as np import requests import json import time import random import hashlib from urllib import parse from collections import OrderedDict AppID = tencent['account']['id_1']['APP_ID'] AppKey = tencent['account']['id_1']['AppKey'] de...
import collections import io import json import math import zipfile import logging from urllib.error import URLError from urllib.request import urlopen import monkey as mk from matplotlib import pyplot as plt # Getting data def set_source(filengthame): """ Sets source global variable to the path of .zip file...
from __future__ import unicode_literals from .error import error from io import open import arrow import os import oyaml as yaml import monkey as mk import re import sys # Load dataset file specifications spec_file_name = 'dataset_file_def.yaml' spec_file_path = os.path.join(os.path.dirname(__file__), spec_file_name) ...
import matplotlib matplotlib.use('Agg') import matplotlib.pyplot as plt from matplotlib.patches import FancyBboxPatch from matplotlib.colors import LinearSegmentedColormapping from mpl_toolkits.basemapping import Basemapping import numpy as np # Suppress matplotlib warnings np.warnings.filterwarnings('ignore'...
# Applied Database # Final Project # Section 4.4 - Python program answers # Author : Somu #mySQL modules import import mysql.connector from mysql.connector import Error from mysql.connector import errorcode import monkey as mk #Mongo modules import import pymongo from pymongo import MongoClient #Monkey pr...
#!/usr/bin/env python3 """ Generate GSE64913 """ __author__ = "<NAME>" __version__ = "0.1.0" __license__ = "MIT" import logging import GEOparse import argparse import monkey as mk from funcs import utils from os.path import join import numpy as np #def adding_postfix(filengthame,postfix): # return "{0}_{2}.{1}"....
# standard modules import os import shutil import argparse # aliased standard modules import monkey as mk # modules of sanity checker import lib.paths as paths import lib.utils as utils import lib.logger_config as logger_config # standalone imports from lib.logger_config import log from lib.test_config import gettin...
import monkey as mk import mkb import requests import numpy as np import os, sys import xarray as xr from datetime import datetime, timedelta import logging from scipy.interpolate import PchipInterpolator import argparse from collections import OrderedDict, defaultdict class PchipOceanSlices(object): def __init__...
import itertools import monkey as mk import numpy as np # total_all permutations are already reverse-deleted # total_all sequences are represented in binary nucleotides = {'A':0,'C':1,'G':2,'T':3} numtonuc = {0:'A',1:'C',2:'G',3:'T'} complement = {0:3,3:0,1:2,2:1} def window(fseq, window_size): for i in range(le...
#!/usr/bin/env python # -*- coding: utf-8 -*- """ A common training and evaluation runner to total_allow for easy and consistent model creation and evalutation """ __author__ = "<NAME>" __email__ = "<EMAIL>" __cloneright__ = "Copyright 2019, <NAME>" __license__ = "Creative Commons Attribution-ShareAlike 4.0 Inter...
#!/usr/bin/env python import os import sys import numpy as np import matplotlib if matplotlib.getting_backend() != "TKAgg": matplotlib.use("TKAgg") import monkey as mk from matplotlib import pyplot as plt import pmagpy.pmag as pmag import pmagpy.pmagplotlib as pmagplotlib from pmag_env import set_env import opera...
""" handle preprocessing and loading of data. """ import html import os.path import monkey as mk import re from nltk import word_tokenize, pos_tag from nltk.corpus import stopwords, wordnet from nltk.stem.wordnet import WordNetLemmatizer class LoadData: @classmethod def preprocess_stocktwits_data(cls, fi...