shhong

#!/bin/bash
set -e

IVVER=18
NRNVER=r1059
XQVER=2.7.5
READLINE=/usr/local/opt/readline/
PYTHONBIN=/usr/bin/python

NRNDIR=/Applications/NEURON-$NRNVER

shhong

TITLE Morris-Lecar spiking dynamics

COMMENT

Written by Sungho Hong
Computational Neuroscience Unit
Okinawa Institute of Science and Technology
[email protected]

ENDCOMMENT

shhong

#!/usr/bin/env python
"""
This script is for a Monte Carlo simulation of the following puzzle: you
first put a white ball in a bag containing another "original" ball with
unknown color, which can be black or white with probability of 1/2. The
question is what is the probability that the original ball was white if
you pick one of two balls in the bag randomly and the chosen ball is
white. As a matter of fact, this problem is equivalent to finding the
probability of choosing a white ball out of one black and two white
balls, which should be 2/3.

shhong

TITLE Wang-Buzsaki model
 
COMMENT

Sungho Hong, CNS Unit, Okinawa Inst Sci Tech. Mar 2008
ENDCOMMENT
 
UNITS {
        (mA) = (milliamp)
        (mV) = (millivolt)

shhong

#!/usr/bin/env python

"""
nsb_entropy.py

June, 2011 written by Sungho Hong, Computational Neuroscience Unit, Okinawa Institute of
Science and Technology
May, 2019 updated to Python 3 by Charlie Strauss, Los Alamos National Lab

This script is a python version of Mathematica functions by Christian Mendl

shhong

from distutils.core import setup, Extension
from glob import glob

# directory containing libblas and liblapack
ATLAS_LIB_DIR = '/usr/lib'

# Set to 1 if you are using the random number generators in the GNU
# Scientific Library.
BUILD_GSL = 0

shhong

from numpy import mod, median
from numpy import pi
from numpy import vstack, hstack

def restrict_phase(theta):
  return mod(theta+pi, 2*pi)-pi


def drmap(i,j, uu):
  x = restrict_phase(uu[i,1:-1]-uu[j,1:-1])

shhong

x = pickle.load(open('final.no.40.pkl','r'))

In [383]: cgm = loadtxt('/Users/shhong/CGM/hwidth_HHLS_40.dat').tolist()

In [384]: l = []

In [385]: for k in cgm:
    l.append([(int(k[0]), int(k[1])), k[2]])
   .....:     
   .....: