yjzhang

import numpy as np
from scipy.stats import norm

# particle filter for localization using echolocation

# given: measurements, accelerometer readings, heading

# user's state: [x, y, theta]

# control: d(theta), d(position)

yjzhang

# code to draw a DNA sequence logo...

import matplotlib.pyplot as plt
from matplotlib import transforms
import matplotlib.patheffects

import numpy as np

def entropy(row):
    return -sum(x*np.log2(x+0.0000001) for x in row)

yjzhang

# Online k-means algorithm
# see http://www.cs.princeton.edu/courses/archive/fall08/cos436/Duda/C/sk_means.htm

import numpy as np

def k_means(data, k, threshhold=2):
    """
    Does k-means clustering of the data.

    Args:

yjzhang

#!/bin/bash

for var in "$@"; do
    filename=${var%.*}
    #echo $filename
    #echo $@
    echo "writing to $filename.html"
    pandoc $var --self-contained --toc -c /home/yjzhang/Dropbox/Notes/buttondown.css -s --mathml -o $filename.html
done

yjzhang

cimport cython

import numpy as np
cimport numpy as np

from libc.math cimport log2

ctypedef fused int2:
    short
    int

yjzhang

def password_gen(num_chars, chars):
    """
    This is a generator
    that outputs all passwords of lowercase letters of length
    num_chars.

    Inputs:
    num_chars- the length of the password
    chars- a list of the characters that can be part of the password
    """

yjzhang

# Plotting clusterings with matplotlib

import numpy as np
import matplotlib.pyplot as plt

def plot_clusterings(data, clusterings, k):
    """
    Args:
        data - n x d numpy array
        clusterings - 1 x n numpy array, values from 0 to k-1

yjzhang

from random import randint

def random_string(n):
    return ''.join(chr(randint(0, 25) + ord('a')) for i in range(n))

yjzhang

import os
import binascii

print binascii.hexlify(os.urandom(10))