henryrossiter

function cosineDistanceBetweenPoints(lat1, lon1, lat2, lon2) {
  const R = 6371e3;
  const p1 = lat1 * Math.PI/180;
  const p2 = lat2 * Math.PI/180;
  const deltaP = p2 - p1;
  const deltaLon = lon2 - lon1;
  const deltaLambda = (deltaLon * Math.PI) / 180;
  const a = Math.sin(deltaP/2) * Math.sin(deltaP/2) +
            Math.cos(p1) * Math.cos(p2) *
            Math.sin(deltaLambda/2) * Math.sin(deltaLambda/2);

henryrossiter

function pythagoreanDistanceBetweenPoints(lat1, lon1, lat2, lon2) {
  const R = 6371e3;
  const x = (lon2-lon1) * Math.cos((lat1+lat2)/2);
  const y = (lat2-lat1);
  const d = Math.sqrt(x*x + y*y) * R;
  return d;
}

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function haversineDistanceBetweenPoints(lat1, lon1, lat2, lon2) {
  const R = 6371e3;
  const p1 = lat1 * Math.PI/180;
  const p2 = lat2 * Math.PI/180;
  const deltaLon = lon2 - lon1;
  const deltaLambda = (deltaLon * Math.PI) / 180;
  const d = Math.acos(
    Math.sin(p1) * Math.sin(p2) + Math.cos(p1) * Math.cos(p2) * Math.cos(deltaLambda),
  ) * R;
  return d;

henryrossiter

import sys
import time
from fairlay_public_api import FairlayPythonPublic

fairlay = FairlayPythonPublic()

# Dictionary to store up-to-date market asks and bids
order_dict = {}
while True:
    markets = fairlay.get_markets_and_odds({

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import numpy as np
def moving_average(a, n=3) :
    ret = np.cumsum(a, dtype=float)
    ret[n:] = ret[n:] - ret[:-n]
    return ret[n - 1:] / n

n = 12
plt.plot(moving_average(btc_data, n=n))
plt.plot(btc_data[n - 1:])
plt.title('Daily Low Bitcoin Prices - 1 Year')

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import matplotlib.pyplot as plt
plt.plot(btc_data)
plt.title('Daily Low Bitcoin Prices - 1 Year')
plt.ylabel('Daily Low - USD')
plt.show()

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# Fetch a dict of a year of BTC prices
btc_data = getYearHistoricals('BTC')['data_points']

# Tranform price dict to list of low prices
btc_data = [float(point['low_price']) for point in btc_data]

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def getYearHistoricals(symbol):
  symbol_dict = {
    'BTC': '3d961844-d360-45fc-989b-f6fca761d511',
    'ETH': '76637d50-c702-4ed1-bcb5-5b0732a81f48',
    'LTC': '383280b1-ff53-43fc-9c84-f01afd0989cd',
    'BCH': '2f2b77c4-e426-4271-ae49-18d5cb296d3a',
    'DOGE': '1ef78e1b-049b-4f12-90e5-555dcf2fe204',
    'ETC': '7b577ce3-489d-4269-9408-796a0d1abb3a',
    'BSV': '086a8f9f-6c39-43fa-ac9f-57952f4a1ba6'
  }

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import robin_stocks as r

username = ''
password = ''
r.login(username, password)

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def getHistoricals(symbol, span='year'):
  symbol_dict = {
    'BTC': '3d961844-d360-45fc-989b-f6fca761d511',
    'ETH': '76637d50-c702-4ed1-bcb5-5b0732a81f48',
    'LTC': '383280b1-ff53-43fc-9c84-f01afd0989cd',
    'BCH': '2f2b77c4-e426-4271-ae49-18d5cb296d3a',
    'DOGE': '1ef78e1b-049b-4f12-90e5-555dcf2fe204',
    'ETC': '7b577ce3-489d-4269-9408-796a0d1abb3a',
    'BSV': '086a8f9f-6c39-43fa-ac9f-57952f4a1ba6'
  }