#!/usr/bin/env python2
# We want to know, of the files we have, what is the breakdown?
import os
import pandas
from brainbehavior.pubmed import Pubmed
# First we need to download full article text
# Create a pubmed object
email = "*****@*****.**"
pm = Pubmed(email)
# Get pubmed ids for all articles in database
pc_ids = pm.get_pubmed_central_ids()
# We are going to download them here
download_folder = "/scratch/PI/russpold/data/PUBMED/articles"
# Submit scripts to download in batches of 100
iters = len(pc_ids) / 100
# Subset matrix to files we have downloaded
subset = pandas.DataFrame(columns=pm.ftp.columns)
for i in range(0, iters):
print "%s of %s" % (i, iters)
download_subfolder = "%s/%s" % (download_folder, i)
start = i * 100
if i != iters:
end = start + 100
else:
#!/usr/bin/env python2 # This script will download pubmed papers for a given start and end index in the current # ftp manifest file # Usage : download_pubmed_muhaha.py start end download_folder import sys import pandas from brainbehavior.pubmed import Pubmed # Get the start and end index of ids from the command line start = int(sys.argv[1]) end = int(sys.argv[2]) download_folder = sys.argv[3] email = sys.argv[4] # First we need to download full article text # Create a pubmed object pm = Pubmed(email) # Get pubmed ids for articles in database pc_ids = pm.get_pubmed_central_ids() # Filter down to indices that we want pc_ids = pc_ids[start:end] # Download the articles! pm.download_pubmed(pc_ids,download_folder)
#!/usr/bin/env python2 # This script will download pubmed papers for a given start and end index in the current # ftp manifest file # Usage : download_pubmed_muhaha.py start end download_folder import sys import pandas from brainbehavior.pubmed import Pubmed # Get the start and end index of ids from the command line pmid = sys.argv[1] download_folder = sys.argv[2] email = sys.argv[3] # First we need to download full article text # Create a pubmed object pm = Pubmed(email) # Download the articles! pm.download_pubmed([pmid],download_folder)
#!/usr/bin/env python2
# We want to know, of the files we have, what is the breakdown?
import os
import pandas
from brainbehavior.pubmed import Pubmed
# First we need to download full article text
# Create a pubmed object
email = "*****@*****.**"
pm = Pubmed(email)
# Get pubmed ids for all articles in database
pc_ids = pm.get_pubmed_central_ids()
# We are going to download them here
download_folder = "/scratch/PI/russpold/data/PUBMED/articles"
# Submit scripts to download in batches of 100
iters = len(pc_ids)/100
# Subset matrix to files we have downloaded
subset = pandas.DataFrame(columns=pm.ftp.columns)
for i in range(0,iters):
print "%s of %s" %(i,iters)
download_subfolder = "%s/%s" %(download_folder,i)
start = i*100
if i != iters:
end = start + 100
#!/usr/bin/env python2
# This script will launch instances of download_pubmed_muhaha.py
import os
import time
from brainbehavior.pubmed import Pubmed
from glob import glob
# First we need to download full article text
# Create a pubmed object
email = "*****@*****.**"
pm = Pubmed(email)
# Get pubmed ids for all articles in database
pc_ids = pm.get_pubmed_central_ids()
# Download folder
download_folder = "/scratch/PI/russpold/data/PUBMED/articles"
# Submit scripts to download in batches of 100
start = 0
iters = len(pc_ids)/100
# Function to submit a single iteration of a missing job
def submit_single_missing(pmid,download_folder,email):
jobname = "pm_%s" %(pmid)
filey = open(".job/%s.job" % (jobname),"w")
filey.writelines("#!/bin/bash\n")
filey.writelines("#SBATCH --job-name=%s\n" %(jobname))
filey.writelines("#SBATCH --output=.out/%s.out\n" %(jobname))