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import matplotlib.pyplot as plt | |
from numpy.fft import fft | |
from numpy.fft import fftshift | |
import numpy as np | |
import random | |
dictionary = ['A','C','G','T'] | |
def generate_random_sequence(N): | |
return [dictionary[random.randint(0,len(dictionary)-1)] for _ in range(N)] |
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#include <stdio.h> | |
#include <tchar.h> | |
#include <Windows.h> | |
#include <iostream> | |
HHOOK hHook{ NULL }; | |
enum Keys | |
{ | |
ShiftKey = 16, |
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#!/usr/bin/env python | |
# -*- coding: utf-8 -*- | |
"""Urls to Hyperlinks. | |
This script takes line-separated urls from stdin and writes formatted hyperlinks to stdout. | |
Usage: | |
# cat urls.txt | python ltoh.py > hyperlinks. | |
""" |
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//more details: http://www.bogotobogo.com/cplusplus/multithreaded2A.php | |
#include <Windows.h> | |
#include <process.h> | |
#include <stdio.h> | |
unsigned int __stdcall test_thread(void *data) { | |
printf("Thread Started"); | |
return 0; | |
} |
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<html> | |
<head> | |
<style> | |
#content { | |
font-size: 18; | |
text-align: center; | |
padding-top: 150px; | |
} | |
.blurry-text { | |
color: transparent; |
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from tensorflow.examples.tutorials.mnist import input_data | |
import tensorflow as tf | |
import matplotlib.pyplot as plt | |
# Load data | |
mnist = input_data.read_data_sets('MNIST_data', one_hot=True) | |
# Neural Network Initialization |
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"""CNN from https://www.microsoft.com/en-us/research/wp-content/uploads/2003/08/icdar03.pdf""" | |
from tensorflow.examples.tutorials.mnist import input_data | |
mnist = input_data.read_data_sets('MNIST_data', one_hot=True) | |
import tensorflow as tf | |
def weight_variable(shape): | |
initial = tf.random_normal(shape, stddev=0.05) | |
return tf.Variable(initial) |
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""" | |
This script provides coordinate transformations from Geodetic -> ECEF, ECEF -> ENU | |
and Geodetic -> ENU (the composition of the two previous functions). Running the script | |
by itself runs tests. | |
based on https://gist.github.com/govert/1b373696c9a27ff4c72a. | |
""" | |
import math | |
a = 6378137 | |
b = 6356752.3142 |
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""" | |
Author: Shane Barratt | |
Email: [email protected] | |
K-means script that works with NaN entries. | |
""" | |
import numpy as np | |
import IPython as ipy | |
import matplotlib.pyplot as plt |
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