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{
    "description": "Basic client-server edition",
    "plugins": [
        "tiddlywiki/tiddlyweb",
        "tiddlywiki/filesystem",
        "tiddlywiki/highlight"
    ],
    "themes": [
        "tiddlywiki/vanilla",
        "tiddlywiki/snowwhite",

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function res = dydt(t,y,S, w)
  indices2={[1,5], [11], [11], [2,5], [12], [12], [5,13], [12,6], [3,9], [14], [14], [4,9], [15], [15], [7,7], [12], [2,6], [13], [10,6], [16], [10,13], [17], [17], [8], [7], [6], [4], [3]};
  % w=ones(28,1);
  % w=randn(28,1);
  v = w;
  for j=1:28
    for i=indices2{j}
      v(j) = v(j) * y(i);
    end
  end

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import numpy as np
import gym
import matplotlib.pyplot

from math import *
import tensorflow as tf
from keras.layers import Input, Dense, concatenate
from keras.models import Sequential, Model

env = gym.make('CartPole-v1')

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import random
from deap import creator, base, tools, algorithms
from scoop import futures
toolbox = base.Toolbox()
toolbox.register("map", futures.map)

creator.create("FitnessMax", base.Fitness, weights=(1.0,))
creator.create("Individual", list, fitness=creator.FitnessMax)
number_of_parameters = 100
size_of_population = 100

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import matplotlib.pyplot as plt
import numpy as np
from matplotlib.collections import LineCollection

%matplotlib inline


def find_intersection(p1,p2,coord):
    if coord == 1: coord2 = 2
    if coord == 2: coord2 = 1

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# coding: utf-8

# In[1]:


import math
import torch
from torch.nn.parameter import Parameter
import torch.nn.functional as F

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import os
import sys

# os.environ["PYSPARK_PYTHON"]="/usr/local/shared/python/3.6.3/bin/python3"
# os.environ["PYSPARK_DRIVER_PYTHON"]="/usr/local/shared/python/3.6.3/bin/python3"

#pip3 install pyspark
from pyspark import SparkContext
sc = SparkContext.getOrCreate()
print(sc._jsc.sc().getExecutorMemoryStatus())

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#!/bin/bash

comp=$(hostname)

url=$(curl -s 127.0.0.1:4040/api/tunnels | jq -r '.tunnels[0].public_url')
curl -X POST -H "Content-Type: application/json" -d '{"value1":"'${url}'","value2":"'${comp}'"}' https://maker.ifttt.com/trigger/ngrok_url/with/key/[iftt key]
echo 

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import os
import sys
import pandas as pd
if not os.path.exists("floofs"):
  os.mkdir("floofs")

d = pd.read_csv("e621_"+sys.argv[1]+".csv")
d=d[d["rating"]=="s"]

import urllib.request

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sudo apt-get update
sudo apt-get install libcr-dev mpich
#apt install python3-pip
#pip3 install tensorflow
pip3 install mpi4py pandas torch torchvision GPy matplotlib tensorflow_probability==0.7 keras
sudo apt-get install htop
#then edit the GPy file. should send them a pull request..