joshua vogelstein jovo

## connectomics.m
clear
clc
close all

%% sample ER graph & look at it

n=50;
p=0.5;
ER=rand(n)>1-p;
spy(ER)

## crcns.m


%% sample ER graph & look at it

n=50;
p=0.5;
ER=rand(n)>1-p;
spy(ER)

%% sample large ER graph & look at it

## markdown.html
<!DOCTYPE html>
<html>
    <head>
        <meta charset="utf-8">
        <title></title>
    </head>
    <body>
        <script src="https://cdnjs.cloudflare.com/ajax/libs/markdown-it/5.0.2/markdown-it.js" charset="utf-8"></script>
<div id="md-raw">
# My Paper

## download_kasthuri15.py
# Import the OCPy access module to get data from the server
import ocpy.access

# Pick a token whose dataset you wish to download.
TOKEN = 'kasthuri11'
RESOLUTION = '1'
DATA_LOCATION = "downloads/" + TOKEN

# Find the bounds of the dataset using `get_info()`:
project_information = ocpy.access.get_info(TOKEN)

## citation_prediction.m
clear
figure(1), clf, hold on

%% jovo

years= [2015:-1:2003]';
dyears=years-2000; min(dyears)
cites=[382 315 238 144 105 63 33 19 20 18 11 8 17]';

f=fit(dyears,cites,'exp1');

## thanks_for_coming.html
<body>
  <table id="bodyTable" border="0" width="100%" cellspacing="0" cellpadding="0">
    <tbody>
      <tr>
        <td align="center" valign="top">
          <table id="emailContainer" border="0" width="600" cellspacing="0" cellpadding="20">
            <tbody>
              <tr>
                <td align="center" valign="top">
                  <table id="emailHeader" border="0" width="100%" cellspacing="0" cellpadding="20">

## neurodata_table.tex
\documentclass[12pt]{article}

\usepackage{fullpage,times,subfigure,fancyhdr}
\pagestyle{fancy}
\oddsidemargin=-0.5in
\evensidemargin=0.0in
\textwidth=7.5in
\headwidth=6.5in
\textheight=9in
\headheight=12pt

## 2nd_moment_compare
clear all, clc
nvec=round(logspace(2,5,5));


d=3;
mu=zeros(3,1);
Cov=eye(3);
Cov(1)=2;
Corr=diag(diag(Cov))^(-1/2)*Cov*diag(diag(Cov))^(-1/2);

## uploadImages.py
import numpy as np
import tempfile
import h5py
import urllib2

# Initialize the token here
# Remember you have to create this token or this token must exist before you can post to it
token = "ocp_test"

# Create a temp file

## downsample.m
function [A] = downsample(fibergraph, down, directed)
% downsamples a sparse connectome fibergraph
%               down^3 is the size of one new voxel
%               directed is a boolean for whether or not the output graph is directed
%                        if false the graph will be symmetrified
	N = size(fibergraph,1);
	Nnew = N/down^3;
	[i,j,val] = find(fibergraph);
	[x,y,z] = mortonXYZ(i -1);
	i = XYZmorton(floor(x/down),floor(y/down),floor(z/down)) +1;
	clear
	clc
	close all

	%% sample ER graph & look at it

	n=50;
	p=0.5;
	ER=rand(n)>1-p;
	spy(ER)
	<!DOCTYPE html>
	<html>
	<head>
	<meta charset="utf-8">
	<title></title>
	</head>
	<body>
	<script src="https://cdnjs.cloudflare.com/ajax/libs/markdown-it/5.0.2/markdown-it.js" charset="utf-8"></script>
	<div id="md-raw">
	# My Paper
	# Import the OCPy access module to get data from the server
	import ocpy.access

	# Pick a token whose dataset you wish to download.
	TOKEN = 'kasthuri11'
	RESOLUTION = '1'
	DATA_LOCATION = "downloads/" + TOKEN

	# Find the bounds of the dataset using `get_info()`:
	project_information = ocpy.access.get_info(TOKEN)
	clear
	figure(1), clf, hold on

	%% jovo

	years= [2015:-1:2003]';
	dyears=years-2000; min(dyears)
	cites=[382 315 238 144 105 63 33 19 20 18 11 8 17]';

	f=fit(dyears,cites,'exp1');
	<body>
	<table id="bodyTable" border="0" width="100%" cellspacing="0" cellpadding="0">
	<tbody>
	<tr>
	<td align="center" valign="top">
	<table id="emailContainer" border="0" width="600" cellspacing="0" cellpadding="20">
	<tbody>
	<tr>
	<td align="center" valign="top">
	<table id="emailHeader" border="0" width="100%" cellspacing="0" cellpadding="20">
	\documentclass[12pt]{article}

	\usepackage{fullpage,times,subfigure,fancyhdr}
	\pagestyle{fancy}
	\oddsidemargin=-0.5in
	\evensidemargin=0.0in
	\textwidth=7.5in
	\headwidth=6.5in
	\textheight=9in
	\headheight=12pt
	clear all, clc
	nvec=round(logspace(2,5,5));


	d=3;
	mu=zeros(3,1);
	Cov=eye(3);
	Cov(1)=2;
	Corr=diag(diag(Cov))^(-1/2)Covdiag(diag(Cov))^(-1/2);
	import numpy as np
	import tempfile
	import h5py
	import urllib2

	# Initialize the token here
	# Remember you have to create this token or this token must exist before you can post to it
	token = "ocp_test"

	# Create a temp file
	function [A] = downsample(fibergraph, down, directed)
	% downsamples a sparse connectome fibergraph
	% down^3 is the size of one new voxel
	% directed is a boolean for whether or not the output graph is directed
	% if false the graph will be symmetrified
	N = size(fibergraph,1);
	Nnew = N/down^3;
	[i,j,val] = find(fibergraph);
	[x,y,z] = mortonXYZ(i -1);
	i = XYZmorton(floor(x/down),floor(y/down),floor(z/down)) +1;