from dataclasses import dataclass import time from .filters import ExponentialFilter def shear_magnitude(sample): return (float(sample["fshearx"]) ** 2 + float(sample["fsheary"]) ** 2) ** 0.5 @dataclass class ForceBaseline: left_normal: float = 0.0 right_normal: float = 0.0 left_shear: float = 0.0 right_shear: float = 0.0 @dataclass class ForceFeedback: left_normal: float right_normal: float min_normal: float max_normal: float normal_diff: float left_shear: float right_shear: float max_shear: float shear_diff: float class TactileFeedbackProcessor: def __init__(self, config, normal_converter, shear_converter): self.config = config self.normal_converter = normal_converter self.shear_converter = shear_converter self.baseline = ForceBaseline() self.reset_filters() def reset_filters(self): self.left_normal_filter = ExponentialFilter(self.config.filter_alpha) self.right_normal_filter = ExponentialFilter(self.config.filter_alpha) self.left_shear_filter = ExponentialFilter(self.config.shear_filter_alpha) self.right_shear_filter = ExponentialFilter(self.config.shear_filter_alpha) def calibrate_baseline(self, reader): seconds = self.config.baseline_seconds if seconds <= 0: self.baseline = ForceBaseline() return self.baseline left_values = [] right_values = [] left_shear_values = [] right_shear_values = [] deadline = time.perf_counter() + seconds while time.perf_counter() < deadline: left, right = reader.get_samples(timeout=0.2) if left is not None: left_values.append(self.normal_converter.convert(left["fnormal"])) left_shear_values.append(self.shear_converter.convert(shear_magnitude(left))) if right is not None: right_values.append(self.normal_converter.convert(right["fnormal"])) right_shear_values.append(self.shear_converter.convert(shear_magnitude(right))) time.sleep(0.01) self.baseline = ForceBaseline( left_normal=sum(left_values) / len(left_values) if left_values else 0.0, right_normal=sum(right_values) / len(right_values) if right_values else 0.0, left_shear=sum(left_shear_values) / len(left_shear_values) if left_shear_values else 0.0, right_shear=sum(right_shear_values) / len(right_shear_values) if right_shear_values else 0.0, ) return self.baseline def read(self, reader, timeout=0.3): left, right = reader.get_samples(timeout=timeout) if left is None or right is None: return None left_force = max( 0.0, self.normal_converter.convert(left["fnormal"]) - self.baseline.left_normal, ) right_force = max( 0.0, self.normal_converter.convert(right["fnormal"]) - self.baseline.right_normal, ) left_shear = max( 0.0, self.shear_converter.convert(shear_magnitude(left)) - self.baseline.left_shear, ) right_shear = max( 0.0, self.shear_converter.convert(shear_magnitude(right)) - self.baseline.right_shear, ) left_normal = self.left_normal_filter.update(left_force) right_normal = self.right_normal_filter.update(right_force) left_shear_filtered = self.left_shear_filter.update(left_shear) right_shear_filtered = self.right_shear_filter.update(right_shear) return ForceFeedback( left_normal=left_normal, right_normal=right_normal, min_normal=min(left_normal, right_normal), max_normal=max(left_normal, right_normal), normal_diff=left_normal - right_normal, left_shear=left_shear_filtered, right_shear=right_shear_filtered, max_shear=max(left_shear_filtered, right_shear_filtered), shear_diff=left_shear_filtered - right_shear_filtered, )