| |
| from collections import OrderedDict |
|
|
| import numpy as np |
|
|
|
|
| class LogBuffer: |
|
|
| def __init__(self): |
| self.val_history = OrderedDict() |
| self.n_history = OrderedDict() |
| self.output = OrderedDict() |
| self.ready = False |
|
|
| def clear(self): |
| self.val_history.clear() |
| self.n_history.clear() |
| self.clear_output() |
|
|
| def clear_output(self): |
| self.output.clear() |
| self.ready = False |
|
|
| def update(self, vars, count=1): |
| assert isinstance(vars, dict) |
| for key, var in vars.items(): |
| if key not in self.val_history: |
| self.val_history[key] = [] |
| self.n_history[key] = [] |
| self.val_history[key].append(var) |
| self.n_history[key].append(count) |
|
|
| def average(self, n=0): |
| """Average latest n values or all values.""" |
| assert n >= 0 |
| for key in self.val_history: |
| values = np.array(self.val_history[key][-n:]) |
| nums = np.array(self.n_history[key][-n:]) |
| avg = np.sum(values * nums) / np.sum(nums) |
| self.output[key] = avg |
| self.ready = True |
|
|
