alexlenail

import pdb
import pandas as pd
import os
import json
import requests
from argparse import ArgumentParser

ENRICHR_ADDLIST = 'http://amp.pharm.mssm.edu/Enrichr/addList'
ENRICHR_EXPORT = 'http://amp.pharm.mssm.edu/Enrichr/export'
DATABASES =['KEGG_2016', 'Reactome_2016', 'BioCarta_2016']

alexlenail

def save_as_pickled_object(obj, output_dir, filename):
	"""
	This is a defensive way to write pickle.write, allowing for very large files on all platforms
	"""
	filepath = os.path.join(output_dir, filename)
	max_bytes = 2**31 - 1
	bytes_out = pickle.dumps(obj)
	n_bytes = sys.getsizeof(bytes_out)
	with open(filepath, 'wb') as f_out:
		for idx in range(0, n_bytes, max_bytes):

alexlenail

var form = document.createElement('form');
form.setAttribute('method', 'post');
form.setAttribute('action', 'http://cbl-gorilla.cs.technion.ac.il/servlet/GOrilla');
form.setAttribute('target', '_blank');
form.setAttribute('enctype', 'multipart/form-data');

var application_field = document.createElement('input');
application_field.setAttribute("type", "hidden");
application_field.setAttribute("name", "application");
application_field.setAttribute("value", "gorilla");

alexlenail

var DefaultDict = (initValue) => new Proxy({}, {
    get: (target, name) => name in target ? target[name] :
        (target[name] = (typeof initValue === 'function' ? initValue() : initValue))
});

statistics = DefaultDict(() => DefaultDict(() => DefaultDict(0)));

// Thanks @jonathanzong!

alexlenail

matrix = {
        values: [[1, 2], [3, 4]], // sorted row-wise by default

    rows_iter:         function () { return this.values },
    columns_iter:      function () { return iterator_over_the_transpose_of(this.values) },
    flat_rows_iter:    function () { return iterator_over_flattened(this.values) },
    flat_columns_iter: function () { return iterator_over_the_flattened_transpose_of(this.values) },

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