Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

Fixing tuple, and 'UTC has no key' errors in examples/FinRL_PaperTrading_Demo.ipynb #1186

Merged
merged 2 commits into from
Mar 20, 2024
Merged

Fixing tuple, and 'UTC has no key' errors in examples/FinRL_PaperTrading_Demo.ipynb #1186

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
c5621f6
fix: tuple and 'UTC has no key' errors
kurone02 Mar 18, 2024
f125cbf
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] Mar 18, 2024
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
29 changes: 16 additions & 13 deletions examples/FinRL_PaperTrading_Demo.ipynb
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -317,9 +317,9 @@
" action, logprob = [t.squeeze(0) for t in get_action(state.unsqueeze(0))[:2]]\n",
"\n",
" ary_action = convert(action).detach().cpu().numpy()\n",
" ary_state, reward, done, _ = env.step(ary_action)\n",
" ary_state, reward, done, _, _ = env.step(ary_action)\n",
" if done:\n",
" ary_state = env.reset()\n",
" ary_state, _ = env.reset()\n",
"\n",
" states[i] = state\n",
" actions[i] = action\n",
Expand Down Expand Up @@ -411,11 +411,12 @@
" self.if_discrete = False # discrete action or continuous action\n",
"\n",
" def reset(self) -> np.ndarray: # reset the agent in env\n",
" return self.env.reset()\n",
" resetted_env, _ = self.env.reset()\n",
" return resetted_env\n",
"\n",
" def step(self, action: np.ndarray) -> (np.ndarray, float, bool, dict): # agent interacts in env\n",
" # We suggest that adjust action space to (-1, +1) when designing a custom env.\n",
" state, reward, done, info_dict = self.env.step(action * 2)\n",
" state, reward, done, info_dict, _ = self.env.step(action * 2)\n",
" return state.reshape(self.state_dim), float(reward), done, info_dict\n",
"\n",
" \n",
Expand All @@ -424,7 +425,9 @@
"\n",
" env = build_env(args.env_class, args.env_args)\n",
" agent = args.agent_class(args.net_dims, args.state_dim, args.action_dim, gpu_id=args.gpu_id, args=args)\n",
" agent.states = env.reset()[np.newaxis, :]\n",
"\n",
" new_env, _ = env.reset()\n",
" agent.states = new_env[np.newaxis, :]\n",
"\n",
" evaluator = Evaluator(eval_env=build_env(args.env_class, args.env_args),\n",
" eval_per_step=args.eval_per_step,\n",
Expand Down Expand Up @@ -502,14 +505,14 @@
"def get_rewards_and_steps(env, actor, if_render: bool = False) -> (float, int): # cumulative_rewards and episode_steps\n",
" device = next(actor.parameters()).device # net.parameters() is a Python generator.\n",
"\n",
" state = env.reset()\n",
" state, _ = env.reset()\n",
" episode_steps = 0\n",
" cumulative_returns = 0.0 # sum of rewards in an episode\n",
" for episode_steps in range(12345):\n",
" tensor_state = torch.as_tensor(state, dtype=torch.float32, device=device).unsqueeze(0)\n",
" tensor_action = actor(tensor_state)\n",
" action = tensor_action.detach().cpu().numpy()[0] # not need detach(), because using torch.no_grad() outside\n",
" state, reward, done, _ = env.step(action)\n",
" state, reward, done, _, _ = env.step(action)\n",
" cumulative_returns += reward\n",
"\n",
" if if_render:\n",
Expand All @@ -525,7 +528,7 @@
"id": "9tzAw9k26nAC"
},
"source": [
"##DRL Agent Class"
"## DRL Agent Class"
]
},
{
Expand Down Expand Up @@ -634,7 +637,7 @@
"\n",
" # test on the testing env\n",
" _torch = torch\n",
" state = environment.reset()\n",
" state, _ = environment.reset()\n",
" episode_returns = [] # the cumulative_return / initial_account\n",
" episode_total_assets = [environment.initial_total_asset]\n",
" with _torch.no_grad():\n",
Expand All @@ -644,7 +647,7 @@
" action = (\n",
" a_tensor.detach().cpu().numpy()[0]\n",
" ) # not need detach(), because with torch.no_grad() outside\n",
" state, reward, done, _ = environment.step(action)\n",
" state, reward, done, _, _ = environment.step(action)\n",
"\n",
" total_asset = (\n",
" environment.amount\n",
Expand Down Expand Up @@ -1693,8 +1696,8 @@
"source": [
"def get_trading_days(start, end):\n",
" nyse = tc.get_calendar('NYSE')\n",
" df = nyse.sessions_in_range(pd.Timestamp(start,tz=pytz.UTC),\n",
" pd.Timestamp(end,tz=pytz.UTC))\n",
" df = nyse.sessions_in_range(pd.Timestamp(start),\n",
" pd.Timestamp(end))\n",
" trading_days = []\n",
" for day in df:\n",
" trading_days.append(str(day)[:10])\n",
Expand Down Expand Up @@ -1889,7 +1892,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.10"
"version": "3.10.11"
},
"vscode": {
"interpreter": {
Expand Down
2 changes: 1 addition & 1 deletion requirements.txt
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -43,7 +43,7 @@ swig

tensorboardX
wheel>=0.33.6
wrds

# market data & paper trading API
yfinance
wrds