MrAE

#!/usr/bin/env runhaskell
module Root2 where

import System.IO
import Data.Ratio
import Data.List
import Data.Maybe

-- Some helper functions regarding the square root of 2.

MrAE

# An example to show how to use sed and awk to filter rows to read in 
# by matching a pattern.

## generate some toy data
X <- data.frame(matrix(runif(1e3, 0,1), 100,10))
dim(X)

X[[11]] <- Sys.time() - c(1:nrow(X))*1e5

## Write the test data.

MrAE

Keybase proof

I hereby claim:

• I am mrae on github.
• I am mrae_sqrt2 (https://keybase.io/mrae_sqrt2) on keybase.
• I have a public key ASD-t7qFeSy5PFwf1wD6DjDW10flKg1g5M1xb9QYWsAvmAo

To claim this, I am signing this object:

MrAE

header-includes
\usepackage{lipsum}

Section

In this section we introduce the work and present notation and goals.

Here is a nother paragraph to continue exposition.

MrAE

import numpy as np
import pytest
import io

# Using commit 5f6f5147f32c822e0871578355b2d314d16a5f63
from rerf.RerF import fastPredict, fastRerF, fastPredictPost
from contextlib import redirect_stdout


def get_params(forest):

MrAE

---
title: "C++-RerF gini function experiment:"
author: "Jesse Leigh Patsolic"
output: 
  pdf_document:
  html_document:
    keep_md: true
---

<!--

MrAE

#

require(rerf)

data(mnist)

subind <- mnist$Ytrain %in% c(3:5)
Y <- mnist$Ytrain[subind]
X <- mnist$Xtrain[subind, ]

MrAE

body { background: #222; color: #e6e6e6; }

a { color: #949494; }

a:link, a:visited { color: #949494; }

a:hover, a:active, a:focus { color: #c7c7c7; }

hr { border-bottom: 1px solid #424242; border-top: 1px solid #222; }

MrAE

XeLaTeX to LaTeX fonts

Changes to neurodata.sty

1. Remove fontspec package
2. Add scaled option to helvet package i.e. \usepackage[scaled]{helvet}
3. Remove vspace commands in @maketitle code block.
4. Add/subtract the following lines (without -/+ of course):

MrAE

K15 F0 Synaptome data

Data files

locations.csv give the locations of the detected synapses.

k15F0_jlp_1e3.csv are the feature vectors of each location stored in a data.frame This is probably the one you'll want to use for analysis.