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qfettes / DeepRL-Tutorials

Star 870

Contains high quality implementations of Deep Reinforcement Learning algorithms written in PyTorch

reinforcement-learning gae deep-reinforcement-learning rainbow python3 pytorch deep-q-network actor-critic double-dqn quantile-regression dueling-dqn categorical-dqn ppo advantage-actor-critic a2c deep-recurrent-q-network prioritized-experience-replay multi-step-learning noisy-networks deeprl-tutorials
  • Updated May 19, 2021
  • Jupyter Notebook

BY571 / DQN-Atari-Agents

Star 61

DQN-Atari-Agents: Modularized & Parallel PyTorch implementation of several DQN Agents, i.a. DDQN, Dueling DQN, Noisy DQN, C51, Rainbow, and DRQN

multiprocessing parallel-computing deep-reinforcement-learning rainbow multi-environment openai reinforcement-learning-algorithms atari c51 reinforcement-learning-agent drqn prioritized-experience-replay dqn-pytorch multi-step-dqn ddqn-pyotrch dueling-dqn-pytorch noisy-dqn n-step-dqn
  • Updated Dec 18, 2020
  • Jupyter Notebook
flutter-charts

infinum / flutter-charts

Star 42
Open

Incorrect Offset calculation in TargetLineDecoration

vsilux
vsilux commented Jan 24, 2022

When we setting ChartData. axisMin the Offset in TargetLineDecoration.applyPaintTransform calculates wrongly.

The problem is in:
Offset(state.defaultPadding.left + state.defaultMargin.left, _height - (state.defaultMargin.bottom + state.defaultPadding.bottom) - (scale * (target ?? 0.0) + _minValue);

instead of adding _minValue we should subtract it from `scale * (target ?? 0.

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