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@ -38,43 +38,14 @@ const PROBABILITY_MATRIX = {
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const RATE_MULTIPLIER = 10000;
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const RATE_MULTIPLIER = 10000;
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function intceil(val) {
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function range_length(range) {
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return Math.trunc(val + 0.99999);
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return range[1] - range[0];
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}
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function minimum_rate_from_given_and_base(given_price, buy_price) {
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return RATE_MULTIPLIER * (given_price - 0.99999) / buy_price;
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}
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function maximum_rate_from_given_and_base(given_price, buy_price) {
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return RATE_MULTIPLIER * (given_price + 0.00001) / buy_price;
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}
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function rate_range_from_given_and_base(given_price, buy_price) {
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return [
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minimum_rate_from_given_and_base(given_price, buy_price),
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maximum_rate_from_given_and_base(given_price, buy_price)
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];
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}
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function get_price(rate, basePrice) {
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return intceil(rate * basePrice / RATE_MULTIPLIER);
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}
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function* multiply_generator_probability(generator, probability) {
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for (const it of generator) {
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yield {...it, probability: it.probability * probability};
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}
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}
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}
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function clamp(x, min, max) {
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function clamp(x, min, max) {
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return Math.min(Math.max(x, min), max);
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return Math.min(Math.max(x, min), max);
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}
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}
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function range_length(range) {
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return range[1] - range[0];
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}
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function range_intersect(range1, range2) {
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function range_intersect(range1, range2) {
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if (range1[0] > range2[1] || range1[1] < range2[0]) {
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if (range1[0] > range2[1] || range1[1] < range2[0]) {
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return null;
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return null;
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@ -89,54 +60,6 @@ function range_intersect_length(range1, range2) {
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return range_length(range_intersect(range1, range2));
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return range_length(range_intersect(range1, range2));
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}
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}
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/*
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* This corresponds to the code:
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* for (int i = start; i < start + length; i++)
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* {
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* sellPrices[work++] =
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* intceil(randfloat(rate_min / RATE_MULTIPLIER, rate_max / RATE_MULTIPLIER) * basePrice);
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* }
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*
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* Would return the conditional probability given the given_prices, and modify
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* the predicted_prices array.
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* If the given_prices won't match, returns 0.
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*/
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function generate_individual_random_price(
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given_prices, predicted_prices, start, length, rate_min, rate_max) {
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rate_min *= RATE_MULTIPLIER;
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rate_max *= RATE_MULTIPLIER;
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const buy_price = given_prices[0];
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const rate_range = [rate_min, rate_max];
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let prob = 1;
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for (let i = start; i < start + length; i++) {
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let min_pred = get_price(rate_min, buy_price);
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let max_pred = get_price(rate_max, buy_price);
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if (!isNaN(given_prices[i])) {
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if (given_prices[i] < min_pred - FUDGE_FACTOR || given_prices[i] > max_pred + FUDGE_FACTOR) {
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// Given price is out of predicted range, so this is the wrong pattern
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return 0;
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}
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// TODO: How to deal with probability when there's fudge factor?
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// Clamp the value to be in range now so the probability won't be totally biased to fudged values.
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const real_rate_range =
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rate_range_from_given_and_base(clamp(given_prices[i], min_pred, max_pred), buy_price);
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prob *= range_intersect_length(rate_range, real_rate_range) /
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range_length(rate_range);
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min_pred = given_prices[i];
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max_pred = given_prices[i];
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}
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predicted_prices.push({
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min: min_pred,
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max: max_pred,
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});
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}
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return prob;
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}
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/*
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/*
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* Probability Density Function of rates.
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* Probability Density Function of rates.
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* Since the PDF is continuous*, we approximate it by a discrete probability function:
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* Since the PDF is continuous*, we approximate it by a discrete probability function:
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@ -274,6 +197,90 @@ class PDF {
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}
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}
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}
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}
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class Predictor {
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constructor(prices, first_buy, previous_pattern) {
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this.prices = prices;
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this.first_buy = first_buy;
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this.previous_pattern = previous_pattern;
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}
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intceil(val) {
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return Math.trunc(val + 0.99999);
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}
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minimum_rate_from_given_and_base(given_price, buy_price) {
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return RATE_MULTIPLIER * (given_price - 0.99999) / buy_price;
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}
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maximum_rate_from_given_and_base(given_price, buy_price) {
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return RATE_MULTIPLIER * (given_price + 0.00001) / buy_price;
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}
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rate_range_from_given_and_base(given_price, buy_price) {
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return [
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this.minimum_rate_from_given_and_base(given_price, buy_price),
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this.maximum_rate_from_given_and_base(given_price, buy_price)
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];
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}
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get_price(rate, basePrice) {
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return this.intceil(rate * basePrice / RATE_MULTIPLIER);
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}
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* multiply_generator_probability(generator, probability) {
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for (const it of generator) {
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yield {...it, probability: it.probability * probability};
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}
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}
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/*
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* This corresponds to the code:
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* for (int i = start; i < start + length; i++)
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* {
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* sellPrices[work++] =
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* intceil(randfloat(rate_min / RATE_MULTIPLIER, rate_max / RATE_MULTIPLIER) * basePrice);
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* }
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*
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* Would return the conditional probability given the given_prices, and modify
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* the predicted_prices array.
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* If the given_prices won't match, returns 0.
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*/
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generate_individual_random_price(
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given_prices, predicted_prices, start, length, rate_min, rate_max) {
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rate_min *= RATE_MULTIPLIER;
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rate_max *= RATE_MULTIPLIER;
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const buy_price = given_prices[0];
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const rate_range = [rate_min, rate_max];
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let prob = 1;
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for (let i = start; i < start + length; i++) {
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let min_pred = this.get_price(rate_min, buy_price);
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let max_pred = this.get_price(rate_max, buy_price);
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if (!isNaN(given_prices[i])) {
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if (given_prices[i] < min_pred - FUDGE_FACTOR || given_prices[i] > max_pred + FUDGE_FACTOR) {
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// Given price is out of predicted range, so this is the wrong pattern
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return 0;
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}
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// TODO: How to deal with probability when there's fudge factor?
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// Clamp the value to be in range now so the probability won't be totally biased to fudged values.
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const real_rate_range =
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this.rate_range_from_given_and_base(clamp(given_prices[i], min_pred, max_pred), buy_price);
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prob *= range_intersect_length(rate_range, real_rate_range) /
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range_length(rate_range);
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min_pred = given_prices[i];
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max_pred = given_prices[i];
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}
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predicted_prices.push({
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min: min_pred,
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max: max_pred,
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});
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}
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return prob;
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}
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/*
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/*
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* This corresponds to the code:
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* This corresponds to the code:
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* rate = randfloat(start_rate_min, start_rate_max);
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* rate = randfloat(start_rate_min, start_rate_max);
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@ -287,7 +294,7 @@ class PDF {
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* the predicted_prices array.
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* the predicted_prices array.
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* If the given_prices won't match, returns 0.
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* If the given_prices won't match, returns 0.
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*/
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*/
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function generate_decreasing_random_price(
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generate_decreasing_random_price(
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given_prices, predicted_prices, start, length, start_rate_min,
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given_prices, predicted_prices, start, length, start_rate_min,
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start_rate_max, rate_decay_min, rate_decay_max) {
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start_rate_max, rate_decay_min, rate_decay_max) {
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start_rate_min *= RATE_MULTIPLIER;
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start_rate_min *= RATE_MULTIPLIER;
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@ -300,8 +307,8 @@ function generate_decreasing_random_price(
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let prob = 1;
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let prob = 1;
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for (let i = start; i < start + length; i++) {
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for (let i = start; i < start + length; i++) {
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let min_pred = get_price(rate_pdf.min_value(), buy_price);
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let min_pred = this.get_price(rate_pdf.min_value(), buy_price);
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let max_pred = get_price(rate_pdf.max_value(), buy_price);
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let max_pred = this.get_price(rate_pdf.max_value(), buy_price);
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if (!isNaN(given_prices[i])) {
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if (!isNaN(given_prices[i])) {
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if (given_prices[i] < min_pred - FUDGE_FACTOR || given_prices[i] > max_pred + FUDGE_FACTOR) {
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if (given_prices[i] < min_pred - FUDGE_FACTOR || given_prices[i] > max_pred + FUDGE_FACTOR) {
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// Given price is out of predicted range, so this is the wrong pattern
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// Given price is out of predicted range, so this is the wrong pattern
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@ -310,7 +317,7 @@ function generate_decreasing_random_price(
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// TODO: How to deal with probability when there's fudge factor?
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// TODO: How to deal with probability when there's fudge factor?
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// Clamp the value to be in range now so the probability won't be totally biased to fudged values.
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// Clamp the value to be in range now so the probability won't be totally biased to fudged values.
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const real_rate_range =
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const real_rate_range =
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rate_range_from_given_and_base(clamp(given_prices[i], min_pred, max_pred), buy_price);
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this.rate_range_from_given_and_base(clamp(given_prices[i], min_pred, max_pred), buy_price);
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prob *= rate_pdf.range_limit(real_rate_range);
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prob *= rate_pdf.range_limit(real_rate_range);
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if (prob == 0) {
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if (prob == 0) {
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return 0;
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return 0;
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@ -341,7 +348,7 @@ function generate_decreasing_random_price(
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* the predicted_prices array.
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* the predicted_prices array.
|
|
|
|
* If the given_prices won't match, returns 0.
|
|
|
|
* If the given_prices won't match, returns 0.
|
|
|
|
*/
|
|
|
|
*/
|
|
|
|
function generate_peak_price(
|
|
|
|
generate_peak_price(
|
|
|
|
given_prices, predicted_prices, start, rate_min, rate_max) {
|
|
|
|
given_prices, predicted_prices, start, rate_min, rate_max) {
|
|
|
|
rate_min *= RATE_MULTIPLIER;
|
|
|
|
rate_min *= RATE_MULTIPLIER;
|
|
|
|
rate_max *= RATE_MULTIPLIER;
|
|
|
|
rate_max *= RATE_MULTIPLIER;
|
|
|
@ -354,8 +361,8 @@ function generate_peak_price(
|
|
|
|
// Prob(middle_price)
|
|
|
|
// Prob(middle_price)
|
|
|
|
const middle_price = given_prices[start + 1];
|
|
|
|
const middle_price = given_prices[start + 1];
|
|
|
|
if (!isNaN(middle_price)) {
|
|
|
|
if (!isNaN(middle_price)) {
|
|
|
|
const min_pred = get_price(rate_min, buy_price);
|
|
|
|
const min_pred = this.get_price(rate_min, buy_price);
|
|
|
|
const max_pred = get_price(rate_max, buy_price);
|
|
|
|
const max_pred = this.get_price(rate_max, buy_price);
|
|
|
|
if (middle_price < min_pred - FUDGE_FACTOR || middle_price > max_pred + FUDGE_FACTOR) {
|
|
|
|
if (middle_price < min_pred - FUDGE_FACTOR || middle_price > max_pred + FUDGE_FACTOR) {
|
|
|
|
// Given price is out of predicted range, so this is the wrong pattern
|
|
|
|
// Given price is out of predicted range, so this is the wrong pattern
|
|
|
|
return 0;
|
|
|
|
return 0;
|
|
|
@ -363,7 +370,7 @@ function generate_peak_price(
|
|
|
|
// TODO: How to deal with probability when there's fudge factor?
|
|
|
|
// TODO: How to deal with probability when there's fudge factor?
|
|
|
|
// Clamp the value to be in range now so the probability won't be totally biased to fudged values.
|
|
|
|
// Clamp the value to be in range now so the probability won't be totally biased to fudged values.
|
|
|
|
const real_rate_range =
|
|
|
|
const real_rate_range =
|
|
|
|
rate_range_from_given_and_base(clamp(middle_price, min_pred, max_pred), buy_price);
|
|
|
|
this.rate_range_from_given_and_base(clamp(middle_price, min_pred, max_pred), buy_price);
|
|
|
|
prob *= range_intersect_length(rate_range, real_rate_range) /
|
|
|
|
prob *= range_intersect_length(rate_range, real_rate_range) /
|
|
|
|
range_length(rate_range);
|
|
|
|
range_length(rate_range);
|
|
|
|
if (prob == 0) {
|
|
|
|
if (prob == 0) {
|
|
|
@ -393,15 +400,15 @@ function generate_peak_price(
|
|
|
|
if (isNaN(price)) {
|
|
|
|
if (isNaN(price)) {
|
|
|
|
continue;
|
|
|
|
continue;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
const min_pred = get_price(rate_min, buy_price) - 1;
|
|
|
|
const min_pred = this.get_price(rate_min, buy_price) - 1;
|
|
|
|
const max_pred = get_price(rate_range[1], buy_price) - 1;
|
|
|
|
const max_pred = this.get_price(rate_range[1], buy_price) - 1;
|
|
|
|
if (price < min_pred - FUDGE_FACTOR || price > max_pred + FUDGE_FACTOR) {
|
|
|
|
if (price < min_pred - FUDGE_FACTOR || price > max_pred + FUDGE_FACTOR) {
|
|
|
|
// Given price is out of predicted range, so this is the wrong pattern
|
|
|
|
// Given price is out of predicted range, so this is the wrong pattern
|
|
|
|
return 0;
|
|
|
|
return 0;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
// TODO: How to deal with probability when there's fudge factor?
|
|
|
|
// TODO: How to deal with probability when there's fudge factor?
|
|
|
|
// Clamp the value to be in range now so the probability won't be totally biased to fudged values.
|
|
|
|
// Clamp the value to be in range now so the probability won't be totally biased to fudged values.
|
|
|
|
const rate2_range = rate_range_from_given_and_base(clamp(price, min_pred, max_pred)+ 1, buy_price);
|
|
|
|
const rate2_range = this.rate_range_from_given_and_base(clamp(price, min_pred, max_pred)+ 1, buy_price);
|
|
|
|
const F = (t, ZZ) => {
|
|
|
|
const F = (t, ZZ) => {
|
|
|
|
if (t <= 0) {
|
|
|
|
if (t <= 0) {
|
|
|
|
return 0;
|
|
|
|
return 0;
|
|
|
@ -424,8 +431,8 @@ function generate_peak_price(
|
|
|
|
// since forward prediction is more useful here.
|
|
|
|
// since forward prediction is more useful here.
|
|
|
|
//
|
|
|
|
//
|
|
|
|
// Main spike 1
|
|
|
|
// Main spike 1
|
|
|
|
min_pred = get_price(rate_min, buy_price) - 1;
|
|
|
|
let min_pred = this.get_price(rate_min, buy_price) - 1;
|
|
|
|
max_pred = get_price(rate_max, buy_price) - 1;
|
|
|
|
let max_pred = this.get_price(rate_max, buy_price) - 1;
|
|
|
|
if (!isNaN(given_prices[start])) {
|
|
|
|
if (!isNaN(given_prices[start])) {
|
|
|
|
min_pred = given_prices[start];
|
|
|
|
min_pred = given_prices[start];
|
|
|
|
max_pred = given_prices[start];
|
|
|
|
max_pred = given_prices[start];
|
|
|
@ -437,7 +444,7 @@ function generate_peak_price(
|
|
|
|
|
|
|
|
|
|
|
|
// Main spike 2
|
|
|
|
// Main spike 2
|
|
|
|
min_pred = predicted_prices[start].min;
|
|
|
|
min_pred = predicted_prices[start].min;
|
|
|
|
max_pred = get_price(rate_max, buy_price);
|
|
|
|
max_pred = this.get_price(rate_max, buy_price);
|
|
|
|
if (!isNaN(given_prices[start + 1])) {
|
|
|
|
if (!isNaN(given_prices[start + 1])) {
|
|
|
|
min_pred = given_prices[start + 1];
|
|
|
|
min_pred = given_prices[start + 1];
|
|
|
|
max_pred = given_prices[start + 1];
|
|
|
|
max_pred = given_prices[start + 1];
|
|
|
@ -448,7 +455,7 @@ function generate_peak_price(
|
|
|
|
});
|
|
|
|
});
|
|
|
|
|
|
|
|
|
|
|
|
// Main spike 3
|
|
|
|
// Main spike 3
|
|
|
|
min_pred = get_price(rate_min, buy_price) - 1;
|
|
|
|
min_pred = this.get_price(rate_min, buy_price) - 1;
|
|
|
|
max_pred = predicted_prices[start + 1].max - 1;
|
|
|
|
max_pred = predicted_prices[start + 1].max - 1;
|
|
|
|
if (!isNaN(given_prices[start + 2])) {
|
|
|
|
if (!isNaN(given_prices[start + 2])) {
|
|
|
|
min_pred = given_prices[start + 2];
|
|
|
|
min_pred = given_prices[start + 2];
|
|
|
@ -462,8 +469,7 @@ function generate_peak_price(
|
|
|
|
return prob;
|
|
|
|
return prob;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
function*
|
|
|
|
* generate_pattern_0_with_lengths(
|
|
|
|
generate_pattern_0_with_lengths(
|
|
|
|
|
|
|
|
given_prices, high_phase_1_len, dec_phase_1_len, high_phase_2_len,
|
|
|
|
given_prices, high_phase_1_len, dec_phase_1_len, high_phase_2_len,
|
|
|
|
dec_phase_2_len, high_phase_3_len) {
|
|
|
|
dec_phase_2_len, high_phase_3_len) {
|
|
|
|
/*
|
|
|
|
/*
|
|
|
@ -516,14 +522,14 @@ function*
|
|
|
|
let probability = 1;
|
|
|
|
let probability = 1;
|
|
|
|
|
|
|
|
|
|
|
|
// High Phase 1
|
|
|
|
// High Phase 1
|
|
|
|
probability *= generate_individual_random_price(
|
|
|
|
probability *= this.generate_individual_random_price(
|
|
|
|
given_prices, predicted_prices, 2, high_phase_1_len, 0.9, 1.4);
|
|
|
|
given_prices, predicted_prices, 2, high_phase_1_len, 0.9, 1.4);
|
|
|
|
if (probability == 0) {
|
|
|
|
if (probability == 0) {
|
|
|
|
return;
|
|
|
|
return;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
// Dec Phase 1
|
|
|
|
// Dec Phase 1
|
|
|
|
probability *= generate_decreasing_random_price(
|
|
|
|
probability *= this.generate_decreasing_random_price(
|
|
|
|
given_prices, predicted_prices, 2 + high_phase_1_len, dec_phase_1_len,
|
|
|
|
given_prices, predicted_prices, 2 + high_phase_1_len, dec_phase_1_len,
|
|
|
|
0.6, 0.8, 0.04, 0.1);
|
|
|
|
0.6, 0.8, 0.04, 0.1);
|
|
|
|
if (probability == 0) {
|
|
|
|
if (probability == 0) {
|
|
|
@ -531,14 +537,14 @@ function*
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
// High Phase 2
|
|
|
|
// High Phase 2
|
|
|
|
probability *= generate_individual_random_price(given_prices, predicted_prices,
|
|
|
|
probability *= this.generate_individual_random_price(given_prices, predicted_prices,
|
|
|
|
2 + high_phase_1_len + dec_phase_1_len, high_phase_2_len, 0.9, 1.4);
|
|
|
|
2 + high_phase_1_len + dec_phase_1_len, high_phase_2_len, 0.9, 1.4);
|
|
|
|
if (probability == 0) {
|
|
|
|
if (probability == 0) {
|
|
|
|
return;
|
|
|
|
return;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
// Dec Phase 2
|
|
|
|
// Dec Phase 2
|
|
|
|
probability *= generate_decreasing_random_price(
|
|
|
|
probability *= this.generate_decreasing_random_price(
|
|
|
|
given_prices, predicted_prices,
|
|
|
|
given_prices, predicted_prices,
|
|
|
|
2 + high_phase_1_len + dec_phase_1_len + high_phase_2_len,
|
|
|
|
2 + high_phase_1_len + dec_phase_1_len + high_phase_2_len,
|
|
|
|
dec_phase_2_len, 0.6, 0.8, 0.04, 0.1);
|
|
|
|
dec_phase_2_len, 0.6, 0.8, 0.04, 0.1);
|
|
|
@ -553,7 +559,7 @@ function*
|
|
|
|
|
|
|
|
|
|
|
|
const prev_length = 2 + high_phase_1_len + dec_phase_1_len +
|
|
|
|
const prev_length = 2 + high_phase_1_len + dec_phase_1_len +
|
|
|
|
high_phase_2_len + dec_phase_2_len;
|
|
|
|
high_phase_2_len + dec_phase_2_len;
|
|
|
|
probability *= generate_individual_random_price(
|
|
|
|
probability *= this.generate_individual_random_price(
|
|
|
|
given_prices, predicted_prices, prev_length, 14 - prev_length, 0.9, 1.4);
|
|
|
|
given_prices, predicted_prices, prev_length, 14 - prev_length, 0.9, 1.4);
|
|
|
|
if (probability == 0) {
|
|
|
|
if (probability == 0) {
|
|
|
|
return;
|
|
|
|
return;
|
|
|
@ -567,7 +573,7 @@ function*
|
|
|
|
};
|
|
|
|
};
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
function* generate_pattern_0(given_prices) {
|
|
|
|
* generate_pattern_0(given_prices) {
|
|
|
|
/*
|
|
|
|
/*
|
|
|
|
decPhaseLen1 = randbool() ? 3 : 2;
|
|
|
|
decPhaseLen1 = randbool() ? 3 : 2;
|
|
|
|
decPhaseLen2 = 5 - decPhaseLen1;
|
|
|
|
decPhaseLen2 = 5 - decPhaseLen1;
|
|
|
@ -578,15 +584,15 @@ function* generate_pattern_0(given_prices) {
|
|
|
|
for (var dec_phase_1_len = 2; dec_phase_1_len < 4; dec_phase_1_len++) {
|
|
|
|
for (var dec_phase_1_len = 2; dec_phase_1_len < 4; dec_phase_1_len++) {
|
|
|
|
for (var high_phase_1_len = 0; high_phase_1_len < 7; high_phase_1_len++) {
|
|
|
|
for (var high_phase_1_len = 0; high_phase_1_len < 7; high_phase_1_len++) {
|
|
|
|
for (var high_phase_3_len = 0; high_phase_3_len < (7 - high_phase_1_len - 1 + 1); high_phase_3_len++) {
|
|
|
|
for (var high_phase_3_len = 0; high_phase_3_len < (7 - high_phase_1_len - 1 + 1); high_phase_3_len++) {
|
|
|
|
yield* multiply_generator_probability(
|
|
|
|
yield* this.multiply_generator_probability(
|
|
|
|
generate_pattern_0_with_lengths(given_prices, high_phase_1_len, dec_phase_1_len, 7 - high_phase_1_len - high_phase_3_len, 5 - dec_phase_1_len, high_phase_3_len),
|
|
|
|
this.generate_pattern_0_with_lengths(given_prices, high_phase_1_len, dec_phase_1_len, 7 - high_phase_1_len - high_phase_3_len, 5 - dec_phase_1_len, high_phase_3_len),
|
|
|
|
1 / (4 - 2) / 7 / (7 - high_phase_1_len));
|
|
|
|
1 / (4 - 2) / 7 / (7 - high_phase_1_len));
|
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
function* generate_pattern_1_with_peak(given_prices, peak_start) {
|
|
|
|
* generate_pattern_1_with_peak(given_prices, peak_start) {
|
|
|
|
/*
|
|
|
|
/*
|
|
|
|
// PATTERN 1: decreasing middle, high spike, random low
|
|
|
|
// PATTERN 1: decreasing middle, high spike, random low
|
|
|
|
peakStart = randint(3, 9);
|
|
|
|
peakStart = randint(3, 9);
|
|
|
@ -621,17 +627,17 @@ function* generate_pattern_1_with_peak(given_prices, peak_start) {
|
|
|
|
];
|
|
|
|
];
|
|
|
|
let probability = 1;
|
|
|
|
let probability = 1;
|
|
|
|
|
|
|
|
|
|
|
|
probability *= generate_decreasing_random_price(
|
|
|
|
probability *= this.generate_decreasing_random_price(
|
|
|
|
given_prices, predicted_prices, 2, peak_start - 2, 0.85, 0.9, 0.03, 0.05);
|
|
|
|
given_prices, predicted_prices, 2, peak_start - 2, 0.85, 0.9, 0.03, 0.05);
|
|
|
|
if (probability == 0) {
|
|
|
|
if (probability == 0) {
|
|
|
|
return;
|
|
|
|
return;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
// Now each day is independent of next
|
|
|
|
// Now each day is independent of next
|
|
|
|
min_randoms = [0.9, 1.4, 2.0, 1.4, 0.9, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4]
|
|
|
|
let min_randoms = [0.9, 1.4, 2.0, 1.4, 0.9, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4]
|
|
|
|
max_randoms = [1.4, 2.0, 6.0, 2.0, 1.4, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9]
|
|
|
|
let max_randoms = [1.4, 2.0, 6.0, 2.0, 1.4, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9]
|
|
|
|
for (let i = peak_start; i < 14; i++) {
|
|
|
|
for (let i = peak_start; i < 14; i++) {
|
|
|
|
probability *= generate_individual_random_price(
|
|
|
|
probability *= this.generate_individual_random_price(
|
|
|
|
given_prices, predicted_prices, i, 1, min_randoms[i - peak_start],
|
|
|
|
given_prices, predicted_prices, i, 1, min_randoms[i - peak_start],
|
|
|
|
max_randoms[i - peak_start]);
|
|
|
|
max_randoms[i - peak_start]);
|
|
|
|
if (probability == 0) {
|
|
|
|
if (probability == 0) {
|
|
|
@ -646,13 +652,13 @@ function* generate_pattern_1_with_peak(given_prices, peak_start) {
|
|
|
|
};
|
|
|
|
};
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
function* generate_pattern_1(given_prices) {
|
|
|
|
* generate_pattern_1(given_prices) {
|
|
|
|
for (var peak_start = 3; peak_start < 10; peak_start++) {
|
|
|
|
for (var peak_start = 3; peak_start < 10; peak_start++) {
|
|
|
|
yield* multiply_generator_probability(generate_pattern_1_with_peak(given_prices, peak_start), 1 / (10 - 3));
|
|
|
|
yield* this.multiply_generator_probability(this.generate_pattern_1_with_peak(given_prices, peak_start), 1 / (10 - 3));
|
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
function* generate_pattern_2(given_prices) {
|
|
|
|
* generate_pattern_2(given_prices) {
|
|
|
|
/*
|
|
|
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/*
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// PATTERN 2: consistently decreasing
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// PATTERN 2: consistently decreasing
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rate = 0.9;
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rate = 0.9;
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@ -679,7 +685,7 @@ function* generate_pattern_2(given_prices) {
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];
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];
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let probability = 1;
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let probability = 1;
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probability *= generate_decreasing_random_price(
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probability *= this.generate_decreasing_random_price(
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given_prices, predicted_prices, 2, 14 - 2, 0.85, 0.9, 0.03, 0.05);
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given_prices, predicted_prices, 2, 14 - 2, 0.85, 0.9, 0.03, 0.05);
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if (probability == 0) {
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if (probability == 0) {
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return;
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return;
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@ -693,7 +699,7 @@ function* generate_pattern_2(given_prices) {
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};
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};
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}
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}
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function* generate_pattern_3_with_peak(given_prices, peak_start) {
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* generate_pattern_3_with_peak(given_prices, peak_start) {
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/*
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/*
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// PATTERN 3: decreasing, spike, decreasing
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// PATTERN 3: decreasing, spike, decreasing
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@ -738,27 +744,27 @@ function* generate_pattern_3_with_peak(given_prices, peak_start) {
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];
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];
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let probability = 1;
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let probability = 1;
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probability *= generate_decreasing_random_price(
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probability *= this.generate_decreasing_random_price(
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given_prices, predicted_prices, 2, peak_start - 2, 0.4, 0.9, 0.03, 0.05);
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given_prices, predicted_prices, 2, peak_start - 2, 0.4, 0.9, 0.03, 0.05);
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if (probability == 0) {
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if (probability == 0) {
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return;
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return;
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}
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}
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// The peak
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// The peak
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probability *= generate_individual_random_price(
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probability *= this.generate_individual_random_price(
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given_prices, predicted_prices, peak_start, 2, 0.9, 1.4);
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given_prices, predicted_prices, peak_start, 2, 0.9, 1.4);
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if (probability == 0) {
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if (probability == 0) {
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return;
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return;
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}
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}
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probability *= generate_peak_price(
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probability *= this.generate_peak_price(
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given_prices, predicted_prices, peak_start + 2, 1.4, 2.0);
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given_prices, predicted_prices, peak_start + 2, 1.4, 2.0);
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if (probability == 0) {
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if (probability == 0) {
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return;
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return;
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}
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}
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if (peak_start + 5 < 14) {
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if (peak_start + 5 < 14) {
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probability *= generate_decreasing_random_price(
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probability *= this.generate_decreasing_random_price(
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given_prices, predicted_prices, peak_start + 5, 14 - (peak_start + 5),
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given_prices, predicted_prices, peak_start + 5, 14 - (peak_start + 5),
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0.4, 0.9, 0.03, 0.05);
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0.4, 0.9, 0.03, 0.05);
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if (probability == 0) {
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if (probability == 0) {
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@ -774,13 +780,13 @@ function* generate_pattern_3_with_peak(given_prices, peak_start) {
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};
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};
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}
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}
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function* generate_pattern_3(given_prices) {
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* generate_pattern_3(given_prices) {
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for (let peak_start = 2; peak_start < 10; peak_start++) {
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for (let peak_start = 2; peak_start < 10; peak_start++) {
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yield* multiply_generator_probability(generate_pattern_3_with_peak(given_prices, peak_start), 1 / (10 - 2));
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yield* this.multiply_generator_probability(this.generate_pattern_3_with_peak(given_prices, peak_start), 1 / (10 - 2));
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}
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}
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}
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}
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function get_transition_probability(previous_pattern) {
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get_transition_probability(previous_pattern) {
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if (typeof previous_pattern === 'undefined' || Number.isNaN(previous_pattern) || previous_pattern === null || previous_pattern < 0 || previous_pattern > 3) {
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if (typeof previous_pattern === 'undefined' || Number.isNaN(previous_pattern) || previous_pattern === null || previous_pattern < 0 || previous_pattern > 3) {
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// TODO: Fill the steady state pattern (https://github.com/mikebryant/ac-nh-turnip-prices/pull/90) here.
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// TODO: Fill the steady state pattern (https://github.com/mikebryant/ac-nh-turnip-prices/pull/90) here.
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return [0.346278, 0.247363, 0.147607, 0.258752];
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return [0.346278, 0.247363, 0.147607, 0.258752];
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@ -789,34 +795,37 @@ function get_transition_probability(previous_pattern) {
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return PROBABILITY_MATRIX[previous_pattern];
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return PROBABILITY_MATRIX[previous_pattern];
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}
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}
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function* generate_all_patterns(sell_prices, previous_pattern) {
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* generate_all_patterns(sell_prices, previous_pattern) {
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const generate_pattern_fns = [generate_pattern_0, generate_pattern_1, generate_pattern_2, generate_pattern_3];
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const generate_pattern_fns = [this.generate_pattern_0, this.generate_pattern_1, this.generate_pattern_2, this.generate_pattern_3];
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const transition_probability = get_transition_probability(previous_pattern);
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const transition_probability = this.get_transition_probability(previous_pattern);
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for (let i = 0; i < 4; i++) {
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for (let i = 0; i < 4; i++) {
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yield* multiply_generator_probability(generate_pattern_fns[i](sell_prices), transition_probability[i]);
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yield* this.multiply_generator_probability(generate_pattern_fns[i].bind(this)(sell_prices), transition_probability[i]);
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}
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}
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}
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}
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function* generate_possibilities(sell_prices, first_buy, previous_pattern) {
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* generate_possibilities(sell_prices, first_buy, previous_pattern) {
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if (first_buy || isNaN(sell_prices[0])) {
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if (first_buy || isNaN(sell_prices[0])) {
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for (var buy_price = 90; buy_price <= 110; buy_price++) {
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for (var buy_price = 90; buy_price <= 110; buy_price++) {
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sell_prices[0] = sell_prices[1] = buy_price;
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sell_prices[0] = sell_prices[1] = buy_price;
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if (first_buy) {
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if (first_buy) {
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yield* generate_pattern_3(sell_prices);
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yield* this.generate_pattern_3(sell_prices);
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} else {
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} else {
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// All buy prices are equal probability and we're at the outmost layer,
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// All buy prices are equal probability and we're at the outmost layer,
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// so don't need to multiply_generator_probability here.
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// so don't need to multiply_generator_probability here.
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yield* generate_all_patterns(sell_prices, previous_pattern)
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yield* this.generate_all_patterns(sell_prices, previous_pattern)
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}
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}
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}
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}
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} else {
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} else {
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yield* generate_all_patterns(sell_prices, previous_pattern)
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yield* this.generate_all_patterns(sell_prices, previous_pattern)
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}
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}
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}
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}
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function analyze_possibilities(sell_prices, first_buy, previous_pattern) {
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analyze_possibilities() {
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const generated_possibilities = Array.from(generate_possibilities(sell_prices, first_buy, previous_pattern));
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const sell_prices = this.prices;
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const first_buy = this.first_buy;
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const previous_pattern = this.previous_pattern;
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const generated_possibilities = Array.from(this.generate_possibilities(sell_prices, first_buy, previous_pattern));
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console.log(generated_possibilities);
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console.log(generated_possibilities);
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const total_probability = generated_possibilities.reduce((acc, it) => acc + it.probability, 0);
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const total_probability = generated_possibilities.reduce((acc, it) => acc + it.probability, 0);
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@ -846,7 +855,7 @@ function analyze_possibilities(sell_prices, first_buy, previous_pattern) {
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poss.weekMax = Math.max(...weekMaxes);
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poss.weekMax = Math.max(...weekMaxes);
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}
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}
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category_totals = {}
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let category_totals = {}
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for (let i of [0, 1, 2, 3]) {
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for (let i of [0, 1, 2, 3]) {
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category_totals[i] = generated_possibilities
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category_totals[i] = generated_possibilities
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.filter(value => value.pattern_number == i)
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.filter(value => value.pattern_number == i)
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@ -862,7 +871,7 @@ function analyze_possibilities(sell_prices, first_buy, previous_pattern) {
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return b.category_total_probability - a.category_total_probability || b.probability - a.probability;
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return b.category_total_probability - a.category_total_probability || b.probability - a.probability;
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});
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});
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global_min_max = [];
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let global_min_max = [];
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for (var day = 0; day < 14; day++) {
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for (var day = 0; day < 14; day++) {
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prices = {
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prices = {
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min: 999,
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min: 999,
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@ -889,3 +898,4 @@ function analyze_possibilities(sell_prices, first_buy, previous_pattern) {
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return generated_possibilities;
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return generated_possibilities;
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}
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}
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}
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