philerooski

import bridgeclient # https://github.com/larssono/bridgeclient
import functools


def get_bridge_client(email, password, study):
    bridge = bridgeclient.bridgeConnector(email, password, study=study)
    return bridge


"""

philerooski

import synapseclient
import argparse
import pandas
import json
import os


DUMMY_ARG = "dummy"  # A 'None' like string we can pass to boto

philerooski

# Entry function to extract tremor features

######################
# Load Libraries
######################
library(optparse)
library(data.table)
library(plyr)
library(tidyverse)

philerooski

library("synapseClient")
synapseLogin()

library("plyr")
library("dplyr")
library("ggplot2")
library("jsonlite")
library("parallel")
library("tidyr")
library("lubridate")

philerooski

import synapseclient
import pandas
import argparse
import boto3
import os
import json
import uuid


AWS_BATCH_ARRAY_SIZE_LIMIT = 10000

philerooski

rm(list=ls())
options(stringsAsFactors = F)
library(synapser)
library(tidyverse)
library(lubridate)

fetch_and_prep <- function() {
  mpower_f <- synGet("syn21213531") #"syn11488492")
  mpower <- read_tsv(mpower_f$path)
  now <- lubridate::now()

philerooski

library(synapser)
library(tidyverse)

PROJECT_ID <- "syn12030321"
UDALL_USERS <- "syn18691020"
AT_HOME_PD_USERS <- "syn16786935"


get_users <- function(user_table_id) {
  user_table <- as_tibble(synTableQuery(paste(

philerooski

"""
Compute MD5 hashes of files in a local directory or in an S3 bucket.
Outputs a CSV file with columns `path` and `md5`.
When computing MD5 hashes of objects in an S3 bucket, `path` corresponds
to the S3 URI.
"""

import multiprocessing as mp
import boto3 as boto
import pandas as pd

philerooski

import pandas as pd
import argparse
import hashlib
import re
import os


def read_args():
    parser = argparse.ArgumentParser()
    parser.add_argument("target_dir",

philerooski