From 8f4988224596830c5c4526765ebb40bdc214426c Mon Sep 17 00:00:00 2001 From: Mike Bryant Date: Wed, 15 Apr 2020 15:30:10 +0100 Subject: [PATCH] Revert "Make probability accurate by condition probability on the value." This reverts commit 3fa1867340d8d3566d7322d10fe5c7fc8aff5b3e. --- js/predictions.js | 484 +++++++++++----------------------------------- 1 file changed, 116 insertions(+), 368 deletions(-) diff --git a/js/predictions.js b/js/predictions.js index c5da355..27b5e93 100644 --- a/js/predictions.js +++ b/js/predictions.js @@ -9,6 +9,13 @@ const PATTERN = { SMALL_SPIKE: 3, }; +const PATTERN_COUNTS = { + [PATTERN.FLUCTUATING]: 56, + [PATTERN.LARGE_SPIKE]: 7, + [PATTERN.DECREASING]: 1, + [PATTERN.SMALL_SPIKE]: 8, +}; + const PROBABILITY_MATRIX = { [PATTERN.FLUCTUATING]: { [PATTERN.FLUCTUATING]: 0.20, @@ -50,42 +57,10 @@ function maximum_rate_from_given_and_base(given_price, buy_price) { return RATE_MULTIPLIER * (given_price + 0.00001) / buy_price; } -function rate_range_from_given_and_base(given_price, buy_price) { - return [ - minimum_rate_from_given_and_base(given_price, buy_price), - maximum_rate_from_given_and_base(given_price, buy_price) - ]; -} - function get_price(rate, basePrice) { return intceil(rate * basePrice / RATE_MULTIPLIER); } -function* multiply_generator_probability(generator, probability) { - for (const it of generator) { - yield {...it, probability: it.probability * probability}; - } -} - -function range_length(range) { - return range[1] - range[0]; -} - -function range_intersect(range1, range2) { - if (range1[0] > range2[1] || range1[1] < range2[0]) { - return null; - } - return [Math.max(range1[0], range2[0]), Math.min(range1[1], range2[1])]; -} - -function range_intersect_length(range1, range2) { - if (range1[0] > range2[1] || range1[1] < range2[0]) { - return 0; - } - return range_length(range_intersect(range1, range2)); -} - - /* * This corresponds to the code: * for (int i = start; i < start + length; i++) @@ -94,9 +69,8 @@ function range_intersect_length(range1, range2) { * intceil(randfloat(rate_min / RATE_MULTIPLIER, rate_max / RATE_MULTIPLIER) * basePrice); * } * - * Would return the conditional probability given the given_prices, and modify - * the predicted_prices array. - * If the given_prices won't match, returns 0. + * Would modify the predicted_prices array. + * If the given_prices won't match, returns false, otherwise returns true */ function generate_individual_random_price( given_prices, predicted_prices, start, length, rate_min, rate_max) { @@ -104,8 +78,6 @@ function generate_individual_random_price( rate_max *= RATE_MULTIPLIER; const buy_price = given_prices[0]; - const rate_range = [rate_min, rate_max]; - let prob = 1; for (let i = start; i < start + length; i++) { let min_pred = get_price(rate_min, buy_price); @@ -113,14 +85,7 @@ function generate_individual_random_price( if (!isNaN(given_prices[i])) { if (given_prices[i] < min_pred - FUDGE_FACTOR || given_prices[i] > max_pred + FUDGE_FACTOR) { // Given price is out of predicted range, so this is the wrong pattern - return 0; - } - if (given_prices[i] >= min_pred || given_prices[i] <= max_pred) { - // The value in the FUDGE_FACTOR range is ignored so that it don't give a probability 0. - const real_rate_range = - rate_range_from_given_and_base(given_prices[i], buy_price); - prob *= range_intersect_length(rate_range, real_rate_range) / - range_length(rate_range); + return false; } min_pred = given_prices[i]; max_pred = given_prices[i]; @@ -131,144 +96,7 @@ function generate_individual_random_price( max: max_pred, }); } - return prob; -} - -/* - * Probability Density Function of rates. - * Since the PDF is continuous*, we approximate it by a discrete probability function: - * the value in range [(x - 0.5), (x + 0.5)) has a uniform probability - * prob[x - value_start]; - * - * Note that we operate all rate on the (* RATE_MULTIPLIER) scale. - * - * (*): Well not really since it only takes values that "float" can represent in some form, but the - * space is too large to compute directly in JS. - */ -class PDF { - /* - * Initialize a PDF in range [a, b], a and b can be non-integer. - * if uniform is true, then initialize the probability to be uniform, else initialize to a - * all-zero (invalid) PDF. - */ - constructor(a, b, uniform = true) { - this.value_start = Math.round(a); - this.value_end = Math.round(b); - const range = [a, b]; - const total_length = range_length(range); - this.prob = Array(this.value_end - this.value_start + 1); - if (uniform) { - for (let i = 0; i < this.prob.length; i++) { - this.prob[i] = - range_intersect_length(this.range_of(i), range) / total_length; - } - } - } - - range_of(idx) { - // TODO: consider doing the "exclusive end" properly. - return [this.value_start + idx - 0.5, this.value_start + idx + 0.5 - 1e-9]; - } - - min_value() { - return this.value_start - 0.5; - } - - max_value() { - return this.value_end + 0.5 - 1e-9; - } - - normalize() { - const total_probability = this.prob.reduce((acc, it) => acc + it, 0); - for (let i = 0; i < this.prob.length; i++) { - this.prob[i] /= total_probability; - } - } - - /* - * Limit the values to be in the range, and return the probability that the value was in this - * range. - */ - range_limit(range) { - let [start, end] = range; - start = Math.max(start, this.min_value()); - end = Math.min(end, this.max_value()); - if (start >= end) { - // Set this to invalid values - this.value_start = this.value_end = 0; - this.prob = []; - return 0; - } - - let prob = 0; - const start_idx = Math.round(start) - this.value_start; - const end_idx = Math.round(end) - this.value_start; - for (let i = start_idx; i <= end_idx; i++) { - const bucket_prob = this.prob[i] * range_intersect_length(this.range_of(i), range); - this.prob[i] = bucket_prob; - prob += bucket_prob; - } - - this.prob = this.prob.slice(start_idx, end_idx + 1); - this.value_start = Math.round(start); - this.value_end = Math.round(end); - this.normalize(); - - return prob; - } - - /* - * Subtract the PDF by a uniform distribution in [rate_decay_min, rate_decay_max] - * - * For simplicity, we assume that rate_decay_min and rate_decay_max are both integers. - */ - decay(rate_decay_min, rate_decay_max) { - const ret = new PDF( - this.min_value() - rate_decay_max, this.max_value() - rate_decay_min, false); - /* - // O(n^2) naive algorithm for reference, which would be too slow. - for (let i = this.value_start; i <= this.value_end; i++) { - const unit_prob = this.prob[i - this.value_start] / (rate_decay_max - rate_decay_min) / 2; - for (let j = rate_decay_min; j < rate_decay_max; j++) { - // ([i - 0.5, i + 0.5] uniform) - ([j, j + 1] uniform) - // -> [i - j - 1.5, i + 0.5 - j] with a triangular PDF - // -> approximate by - // [i - j - 1.5, i - j - 0.5] uniform & - // [i - j - 0.5, i - j + 0.5] uniform - ret.prob[i - j - 1 - ret.value_start] += unit_prob; // Part A - ret.prob[i - j - ret.value_start] += unit_prob; // Part B - } - } - */ - // Transform to "CDF" - for (let i = 1; i < this.prob.length; i++) { - this.prob[i] += this.prob[i - 1]; - } - // Return this.prob[l - this.value_start] + ... + this.prob[r - 1 - this.value_start]; - // This assume that this.prob is already transformed to "CDF". - const sum = (l, r) => { - l -= this.value_start; - r -= this.value_start; - if (l < 0) l = 0; - if (r > this.prob.length) r = this.prob.length; - if (l >= r) return 0; - return this.prob[r - 1] - (l == 0 ? 0 : this.prob[l - 1]); - }; - - for (let x = 0; x < ret.prob.length; x++) { - // i - j - 1 - ret.value_start == x (Part A) - // -> i = x + j + 1 + ret.value_start, j in [rate_decay_min, rate_decay_max) - ret.prob[x] = sum(x + rate_decay_min + 1 + ret.value_start, x + rate_decay_max + 1 + ret.value_start); - - // i - j - ret.value_start == x (Part B) - // -> i = x + j + ret.value_start, j in [rate_decay_min, rate_decay_max) - ret.prob[x] += sum(x + rate_decay_min + ret.value_start, x + rate_decay_max + ret.value_start); - } - this.prob = ret.prob; - this.value_start = ret.value_start; - this.value_end = ret.value_end; - this.normalize(); - } + return true; } /* @@ -280,38 +108,33 @@ class PDF { * rate -= randfloat(rate_decay_min, rate_decay_max); * } * - * Would return the conditional probability given the given_prices, and modify - * the predicted_prices array. - * If the given_prices won't match, returns 0. + * Would modify the predicted_prices array. + * If the given_prices won't match, returns false, otherwise returns true */ function generate_decreasing_random_price( - given_prices, predicted_prices, start, length, start_rate_min, - start_rate_max, rate_decay_min, rate_decay_max) { - start_rate_min *= RATE_MULTIPLIER; - start_rate_max *= RATE_MULTIPLIER; + given_prices, predicted_prices, start, length, rate_min, + rate_max, rate_decay_min, rate_decay_max) { + rate_min *= RATE_MULTIPLIER; + rate_max *= RATE_MULTIPLIER; rate_decay_min *= RATE_MULTIPLIER; rate_decay_max *= RATE_MULTIPLIER; const buy_price = given_prices[0]; - let rate_pdf = new PDF(start_rate_min, start_rate_max); - let prob = 1; for (let i = start; i < start + length; i++) { - let min_pred = get_price(rate_pdf.min_value(), buy_price); - let max_pred = get_price(rate_pdf.max_value(), buy_price); + let min_pred = get_price(rate_min, buy_price); + let max_pred = get_price(rate_max, buy_price); if (!isNaN(given_prices[i])) { if (given_prices[i] < min_pred - FUDGE_FACTOR || given_prices[i] > max_pred + FUDGE_FACTOR) { // Given price is out of predicted range, so this is the wrong pattern - return 0; + return false; } if (given_prices[i] >= min_pred || given_prices[i] <= max_pred) { - // The value in the FUDGE_FACTOR range is ignored so that it don't give a probability 0. - const real_rate_range = - rate_range_from_given_and_base(given_prices[i], buy_price); - prob *= rate_pdf.range_limit(real_rate_range); - if (prob == 0) { - return 0; - } + // The value in the FUDGE_FACTOR range is ignored so the rate range would not be empty. + const real_rate_min = minimum_rate_from_given_and_base(given_prices[i], buy_price); + const real_rate_max = maximum_rate_from_given_and_base(given_prices[i], buy_price); + rate_min = Math.max(rate_min, real_rate_min); + rate_max = Math.min(rate_max, real_rate_max); } min_pred = given_prices[i]; max_pred = given_prices[i]; @@ -322,9 +145,10 @@ function generate_decreasing_random_price( max: max_pred, }); - rate_pdf.decay(rate_decay_min, rate_decay_max); + rate_min -= rate_decay_max; + rate_max -= rate_decay_min; } - return prob; + return true; } @@ -335,9 +159,8 @@ function generate_decreasing_random_price( * sellPrices[work++] = intceil(rate * basePrice); * sellPrices[work++] = intceil(randfloat(rate_min, rate) * basePrice) - 1; * - * Would return the conditional probability given the given_prices, and modify - * the predicted_prices array. - * If the given_prices won't match, returns 0. + * Would modify the predicted_prices array. + * If the given_prices won't match, returns false, otherwise returns true */ function generate_peak_price( given_prices, predicted_prices, start, rate_min, rate_max) { @@ -345,83 +168,15 @@ function generate_peak_price( rate_max *= RATE_MULTIPLIER; const buy_price = given_prices[0]; - let prob = 1; - let rate_range = [rate_min, rate_max]; - - // * Calculate the probability first. - // Prob(middle_price) - const middle_price = given_prices[start + 1]; - if (!isNaN(middle_price)) { - const min_pred = get_price(rate_min, buy_price); - const max_pred = get_price(rate_max, buy_price); - 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 - return 0; - } - if (middle_price >= min_pred || middle_price <= max_pred) { - // The value in the FUDGE_FACTOR range is ignored so that it don't give a probability 0. - const real_rate_range = - rate_range_from_given_and_base(middle_price, buy_price); - prob *= range_intersect_length(rate_range, real_rate_range) / - range_length(rate_range); - if (prob == 0) { - return 0; - } - - rate_range = range_intersect(rate_range, real_rate_range); - } - } - const left_price = given_prices[start]; - const right_price = given_prices[start + 2]; - // Prob(left_price | middle_price), Prob(right_price | middle_price) - // - // A = rate_range[0], B = rate_range[1], C = rate_min, X = rate, Y = randfloat(rate_min, rate) - // rate = randfloat(A, B); sellPrices[work++] = intceil(randfloat(C, rate) * basePrice) - 1; - // - // => X->U(A,B), Y->U(C,X), Y-C->U(0,X-A), Y-C->U(0,1)*(X-A), Y-C->U(0,1)*U(C-A,B-A), - // let Z=Y-C, Z1=C-A, Z2=B-A, Z->U(0,1)*U(Z1,Z2) - // Prob(Z>=t) = integral_{x=0}^{1} [min(t/x,Z2)-min(t/x,Z1)]/ (Z2-Z1) - // let F(t, ZZ) = integral_{x=0}^{1} min(t/x, ZZ) - // 1. if ZZ < t, then min(t/x, ZZ) = ZZ -> F(t, ZZ) = ZZ - // 2. if ZZ >= t, then F(t, ZZ) = integral_{x=0}^{t/ZZ} ZZ + integral_{x=t/ZZ}^{1} t/x - // = t - t/ZZ log(t/ZZ) - // Prob(Z>=t) = (F(t, Z2) - F(t, Z1)) / (Z2 - Z1) - // Prob(Y>=t) = Prob(Z>=t-C) - for (const price of [left_price, right_price]) { - if (isNaN(price)) { - continue; - } - const min_pred = get_price(rate_min, buy_price) - 1; - const max_pred = get_price(rate_range[1], buy_price) - 1; - if (price < min_pred - FUDGE_FACTOR || price > max_pred + FUDGE_FACTOR) { - // Given price is out of predicted range, so this is the wrong pattern - return 0; - } - if (price >= min_pred || price <= max_pred) { - // The value in the FUDGE_FACTOR range is ignored so that it don't give a probability 0. - const rate2_range = rate_range_from_given_and_base(price + 1, buy_price); - const F = (t, ZZ) => (ZZ < t ? ZZ : t - t / ZZ * Math.log(t / ZZ)); - const [A, B] = rate_range; - const C = rate_min; - const Z1 = C - A; - const Z2 = B - A; - const PY = (t) => (F(t - C, Z2) - F(t - C, Z1)) / (Z2 - Z1); - prob *= PY(rate2_range[1]) - PY(rate2_range[0]); - if (prob == 0) { - return 0; - } - } - } - - // * Then generate the real predicted range. - // We're doing things in different order then how we calculate probability, - // since forward prediction is more useful here. - // // Main spike 1 min_pred = get_price(rate_min, buy_price) - 1; max_pred = get_price(rate_max, buy_price) - 1; if (!isNaN(given_prices[start])) { + if (given_prices[start] < min_pred - FUDGE_FACTOR || given_prices[peak_start + 2] > max_pred + FUDGE_FACTOR) { + // Given price is out of predicted range, so this is the wrong pattern + return false; + } min_pred = given_prices[start]; max_pred = given_prices[start]; } @@ -432,8 +187,12 @@ function generate_peak_price( // Main spike 2 min_pred = predicted_prices[start].min; - max_pred = get_price(rate_max, buy_price); + max_pred = intceil(2.0 * buy_price); if (!isNaN(given_prices[start + 1])) { + if (given_prices[start + 1] < min_pred - FUDGE_FACTOR || given_prices[start + 1] > max_pred + FUDGE_FACTOR) { + // Given price is out of predicted range, so this is the wrong pattern + return false; + } min_pred = given_prices[start + 1]; max_pred = given_prices[start + 1]; } @@ -443,9 +202,13 @@ function generate_peak_price( }); // Main spike 3 - min_pred = get_price(rate_min, buy_price) - 1; + min_pred = intceil(1.4 * buy_price) - 1; max_pred = predicted_prices[start + 1].max - 1; if (!isNaN(given_prices[start + 2])) { + if (given_prices[start + 2] < min_pred - FUDGE_FACTOR || given_prices[start + 2] > max_pred + FUDGE_FACTOR) { + // Given price is out of predicted range, so this is the wrong pattern + return false; + } min_pred = given_prices[start + 2]; max_pred = given_prices[start + 2]; } @@ -454,7 +217,7 @@ function generate_peak_price( max: max_pred, }); - return prob; + return true; } function* @@ -508,36 +271,31 @@ function* max: buy_price, }, ]; - let probability = 1; // High Phase 1 - probability *= generate_individual_random_price( - given_prices, predicted_prices, 2, high_phase_1_len, 0.9, 1.4); - if (probability == 0) { + if (!generate_individual_random_price( + given_prices, predicted_prices, 2, high_phase_1_len, 0.9, 1.4)) { return; } // Dec Phase 1 - probability *= generate_decreasing_random_price( - given_prices, predicted_prices, 2 + high_phase_1_len, dec_phase_1_len, - 0.6, 0.8, 0.04, 0.1); - if (probability == 0) { + if (!generate_decreasing_random_price( + given_prices, predicted_prices, 2 + high_phase_1_len, dec_phase_1_len, + 0.6, 0.8, 0.04, 0.1)) { return; } // High Phase 2 - probability *= 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); - if (probability == 0) { + if (!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)) { return; } // Dec Phase 2 - probability *= generate_decreasing_random_price( - given_prices, predicted_prices, - 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); - if (probability == 0) { + if (!generate_decreasing_random_price( + given_prices, predicted_prices, + 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)) { return; } @@ -548,17 +306,16 @@ function* const prev_length = 2 + high_phase_1_len + dec_phase_1_len + high_phase_2_len + dec_phase_2_len; - probability *= generate_individual_random_price( - given_prices, predicted_prices, prev_length, 14 - prev_length, 0.9, 1.4); - if (probability == 0) { + if (!generate_individual_random_price( + given_prices, predicted_prices, prev_length, 14 - prev_length, 0.9, + 1.4)) { return; } yield { pattern_description: "Fluctuating", pattern_number: 0, - prices: predicted_prices, - probability, + prices: predicted_prices }; } @@ -573,9 +330,7 @@ function* generate_pattern_0(given_prices) { 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_3_len = 0; high_phase_3_len < (7 - high_phase_1_len - 1 + 1); high_phase_3_len++) { - yield* 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), - 1 / (4 - 2) / 7 / (7 - high_phase_1_len)); + yield* 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); } } } @@ -614,11 +369,10 @@ function* generate_pattern_1_with_peak(given_prices, peak_start) { max: buy_price, }, ]; - let probability = 1; - probability *= generate_decreasing_random_price( - given_prices, predicted_prices, 2, peak_start - 2, 0.85, 0.9, 0.03, 0.05); - if (probability == 0) { + if (!generate_decreasing_random_price( + given_prices, predicted_prices, 2, peak_start - 2, 0.85, 0.9, 0.03, + 0.05)) { return; } @@ -626,24 +380,22 @@ function* generate_pattern_1_with_peak(given_prices, peak_start) { 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] for (let i = peak_start; i < 14; i++) { - probability *= generate_individual_random_price( - given_prices, predicted_prices, i, 1, min_randoms[i - peak_start], - max_randoms[i - peak_start]); - if (probability == 0) { + if (!generate_individual_random_price( + given_prices, predicted_prices, i, 1, min_randoms[i - peak_start], + max_randoms[i - peak_start])) { return; } } yield { pattern_description: "Large spike", pattern_number: 1, - prices: predicted_prices, - probability, + prices: predicted_prices }; } function* generate_pattern_1(given_prices) { 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* generate_pattern_1_with_peak(given_prices, peak_start); } } @@ -672,19 +424,16 @@ function* generate_pattern_2(given_prices) { max: buy_price, }, ]; - let probability = 1; - probability *= generate_decreasing_random_price( - given_prices, predicted_prices, 2, 14 - 2, 0.85, 0.9, 0.03, 0.05); - if (probability == 0) { + if (!generate_decreasing_random_price( + given_prices, predicted_prices, 2, 14 - 2, 0.85, 0.9, 0.03, 0.05)) { return; } yield { pattern_description: "Decreasing", pattern_number: 2, - prices: predicted_prices, - probability, + prices: predicted_prices }; } @@ -733,30 +482,27 @@ function* generate_pattern_3_with_peak(given_prices, peak_start) { ]; let probability = 1; - probability *= generate_decreasing_random_price( - given_prices, predicted_prices, 2, peak_start - 2, 0.4, 0.9, 0.03, 0.05); - if (probability == 0) { + if (!generate_decreasing_random_price( + given_prices, predicted_prices, 2, peak_start - 2, 0.4, 0.9, 0.03, + 0.05)) { return; } // The peak - probability *= generate_individual_random_price( - given_prices, predicted_prices, peak_start, 2, 0.9, 1.4); - if (probability == 0) { + if (!generate_individual_random_price( + given_prices, predicted_prices, peak_start, 2, 0.9, 1.4)) { return; } - probability *= generate_peak_price( - given_prices, predicted_prices, peak_start + 2, 1.4, 2.0); - if (probability == 0) { + if (!generate_peak_price( + given_prices, predicted_prices, peak_start + 2, 1.4, 2.0)) { return; } if (peak_start + 5 < 14) { - probability *= generate_decreasing_random_price( - given_prices, predicted_prices, peak_start + 5, 14 - (peak_start + 5), - 0.4, 0.9, 0.03, 0.05); - if (probability == 0) { + if (!generate_decreasing_random_price( + given_prices, predicted_prices, peak_start + 5, + 14 - (peak_start + 5), 0.4, 0.9, 0.03, 0.05)) { return; } } @@ -764,60 +510,62 @@ function* generate_pattern_3_with_peak(given_prices, peak_start) { yield { pattern_description: "Small spike", pattern_number: 3, - prices: predicted_prices, - probability, + prices: predicted_prices }; } function* generate_pattern_3(given_prices) { - for (let peak_start = 2; peak_start < 10; peak_start++) { - yield* multiply_generator_probability(generate_pattern_3_with_peak(given_prices, peak_start), 1 / (10 - 2)); + for (var peak_start = 2; peak_start < 10; peak_start++) { + yield* generate_pattern_3_with_peak(given_prices, peak_start); } } -function get_transition_probability(previous_pattern) { - if (typeof previous_pattern === 'undefined' || Number.isNaN(previous_pattern) || previous_pattern === null || previous_pattern < 0 || previous_pattern > 3) { - // TODO: Fill the steady state pattern (https://github.com/mikebryant/ac-nh-turnip-prices/pull/90) here. - return [0.346278, 0.247363, 0.147607, 0.258752]; - } - - return PROBABILITY_MATRIX[previous_pattern]; -} - -function* generate_all_patterns(sell_prices, previous_pattern) { - const generate_pattern_fns = [generate_pattern_0, generate_pattern_1, generate_pattern_2, generate_pattern_3]; - const transition_probability = get_transition_probability(previous_pattern); - - for (let i = 0; i < 4; i++) { - yield* multiply_generator_probability(generate_pattern_fns[i](sell_prices), transition_probability[i]); - } -} - -function* generate_possibilities(sell_prices, first_buy, previous_pattern) { +function* generate_possibilities(sell_prices, first_buy) { if (first_buy || isNaN(sell_prices[0])) { for (var buy_price = 90; buy_price <= 110; buy_price++) { sell_prices[0] = sell_prices[1] = buy_price; if (first_buy) { yield* generate_pattern_3(sell_prices); } else { - // All buy prices are equal probability and we're at the outmost layer, - // so don't need to multiply_generator_probability here. - yield* generate_all_patterns(sell_prices, previous_pattern) + yield* generate_pattern_0(sell_prices); + yield* generate_pattern_1(sell_prices); + yield* generate_pattern_2(sell_prices); + yield* generate_pattern_3(sell_prices); } } } else { - yield* generate_all_patterns(sell_prices, previous_pattern) + yield* generate_pattern_0(sell_prices); + yield* generate_pattern_1(sell_prices); + yield* generate_pattern_2(sell_prices); + yield* generate_pattern_3(sell_prices); } } -function analyze_possibilities(sell_prices, first_buy, previous_pattern) { - const generated_possibilities = Array.from(generate_possibilities(sell_prices, first_buy, previous_pattern)); +function row_probability(possibility, previous_pattern) { + return PROBABILITY_MATRIX[previous_pattern][possibility.pattern_number] / PATTERN_COUNTS[possibility.pattern_number]; +} - const total_probability = generated_possibilities.reduce((acc, it) => acc + it.probability, 0); - for (const it of generated_possibilities) { - it.probability /= total_probability; +function get_probabilities(possibilities, previous_pattern) { + if (typeof previous_pattern === 'undefined' || Number.isNaN(previous_pattern) || previous_pattern === null || previous_pattern < 0 || previous_pattern > 3) { + return possibilities } + var max_percent = possibilities.map(function (poss) { + return row_probability(poss, previous_pattern); + }).reduce(function (prev, current) { + return prev + current; + }, 0); + + return possibilities.map(function (poss) { + poss.probability = row_probability(poss, previous_pattern) / max_percent; + return poss; + }); +} + +function analyze_possibilities(sell_prices, first_buy, previous_pattern) { + generated_possibilities = Array.from(generate_possibilities(sell_prices, first_buy)); + generated_possibilities = get_probabilities(generated_possibilities, previous_pattern); + for (let poss of generated_possibilities) { var weekMins = []; var weekMaxes = [];