import math import matplotlib.pyplot as plt GREEN = "\033[92m" YELLOW = "\033[93m" RED = "\033[91m" RESET = "\033[0m" COLOR_MAP = {"red":RED, "orange": YELLOW, "green": GREEN} class Tester: def __init__(self, predictor, data, title=None, size=250): self.predictor = predictor self.data = data self.title = title or predictor.__name__.replace("_", " ").title() self.size = size self.guesses = [] self.truths = [] self.errors = [] self.sles = [] self.colors = [] def color_for(self, error, truth): if error<40 or error/truth < 0.2: return "green" elif error<80 or error/truth < 0.4: return "orange" else: return "red" def run_datapoint(self, i): datapoint = self.data[i] guess = self.predictor(datapoint) truth = datapoint.price error = abs(guess - truth) log_error = math.log(truth+1) - math.log(guess+1) sle = log_error ** 2 color = self.color_for(error, truth) title = datapoint.title if len(datapoint.title) <= 40 else datapoint.title[:40]+"..." self.guesses.append(guess) self.truths.append(truth) self.errors.append(error) self.sles.append(sle) self.colors.append(color) print(f"{COLOR_MAP[color]}{i+1}: Guess: ${guess:,.2f} Truth: ${truth:,.2f} Error: ${error:,.2f} SLE: {sle:,.2f} Item: {title}{RESET}") def chart(self, title): max_error = max(self.errors) plt.figure(figsize=(12, 8)) max_val = max(max(self.truths), max(self.guesses)) plt.plot([0, max_val], [0, max_val], color='deepskyblue', lw=2, alpha=0.6) plt.scatter(self.truths, self.guesses, s=3, c=self.colors) plt.xlabel('Ground Truth') plt.ylabel('Model Estimate') plt.xlim(0, max_val) plt.ylim(0, max_val) plt.title(title) plt.show() def report(self): average_error = sum(self.errors) / self.size rmsle = math.sqrt(sum(self.sles) / self.size) hits = sum(1 for color in self.colors if color=="green") title = f"{self.title} Error=${average_error:,.2f} RMSLE={rmsle:,.2f} Hits={hits/self.size*100:.1f}%" self.chart(title) def run(self): self.error = 0 for i in range(self.size): self.run_datapoint(i) self.report() @classmethod def test(cls, function, data): cls(function, data).run()