jdmonaco

"""
Circular-linear correlation for regressing onto circular phase variables 
based on the method established by:

    Kempter R, Leibold C, Buzsáki G, Diba K, Schmidt R. Quantifying 
        circular-linear associations: hippocampal phase precession. 
        J Neurosci Methods. 2012;207(1):113–24. 
        doi:10.1016/j.jneumeth.2012.03.007.

Implemented By: @jdmonaco (github) / @j_d_monaco (twitter)

jdmonaco

jdmonaco

"""
Spike train cross-correlogram methods.
"""

import time
import numpy as np
import matplotlib.pyplot as plt
from scipy import real
from scipy.fftpack import fft, ifft

jdmonaco

"""
Limited-lag numpy implementation of spike train cross-correlation.
"""

import numpy as np


def xcorr(a, b, maxlag=1.0, bins=128):
    """
    Compute the cross-correlogram of two spike train arrays.

jdmonaco

#!/bin/bash

mkdir -p ~/Library/Desktop\ Pictures
cd ~/Library/Desktop\ Pictures

find /Library/Desktop\ Pictures/ -size +1M -name "*.jpg" -exec ln -s "{}" . \; 2>/dev/null
find /Library/Screen\ Savers/ -size +1M -name "*.jpg" -exec ln -s "{}" . \; 2>/dev/null

jdmonaco

#!/usr/bin/osascript

on run argv

    set mateScript to "mate -l " & item 1 of argv & " " & item 2 of argv

    tell application "Terminal"
        set thisTab to do script mateScript
        set visible of window 1 to false
        delay 0.5

jdmonaco

#!/usr/bin/env python

"""
organize-photos.py - Organize an unstructured folder tree of photos and movie
    files into a month-and-year folder structure.

Note: This is a minor rewrite of @cliss's extension [1,2] of @drdrang's
photo management scripts [3], and includes a tweak from @jamiepinkham [4,5].
The lists of raw [6] and video [7] file extensions were found elsewhere.

jdmonaco

#!/usr/bin/osascript

on run argv
  
	set browser to "Chrome"
	
	set leftKey to 123
	set upKey to 126
	set downKey to 125
	set rightKey to 124

jdmonaco

convert -delay %filltext:name=delay x0.01s:default=10:width=2% -resize %filltext:name=width:default=256:width=3% %filltext:name=glob:default=IMG*.JPG% %filltext:name=output:default=output.gif%

jdmonaco

from collections import namedtuple

import numpy as np
import scipy.stats as st

TtestResults = namedtuple("Ttest", "T p")

def t_welch(x, y, tails=2):
    """
    Welch's t-test for two unequal-size samples, not assuming equal variances