def main(
env_name, n_epoch, learning_rate, gamma, n_hidden,
seed_val=0, max_steps=1000
):
'''train an a2c network some gym env'''
# define env
env = gym.make(env_name)
env.seed(seed_val)
np.random.seed(seed_val)
torch.manual_seed(seed_val)
# define agent
state_dim, n_actions, action_space_type = get_env_info(env)
agent = Agent(state_dim, n_hidden, n_actions)
optimizer = torch.optim.Adam(agent.parameters(), lr=learning_rate)
# train
log_step = np.zeros((n_epoch,))
log_return = np.zeros((n_epoch,))
log_loss_v = np.zeros((n_epoch,))
log_loss_p = np.zeros((n_epoch,))
for i in range(n_epoch):
cumulative_reward, step, probs, rewards, values = run(
agent, env, gamma=gamma, max_steps=max_steps
)
# update weights
returns = compute_returns(rewards, gamma=gamma, normalize=True)
loss_policy, loss_value = compute_a2c_loss(probs, values, returns)
loss = loss_policy + loss_value
optimizer.zero_grad()
loss.backward()
optimizer.step()
# log message
log_step[i] = step
log_return[i] = cumulative_reward
log_loss_v[i] = loss_value.item()
log_loss_p[i] = loss_policy.item()
if np.mod(i, 10) == 0:
print(
'Epoch : %.3d | R: %.2f, steps: %4d | L: pi: %.2f, V: %.2f' %
(i, log_return[i], log_step[i], log_loss_p[i], log_loss_v[i])
)
# save weights
# ckpt_fname = f'../log/agent-{env_name}-{n_epoch}.pth'
ckpt_fname = f'../log/agent-{env_name}.pth'
torch.save(agent.state_dict(), ckpt_fname)
'''show learning curve: return, steps'''
f, axes = plt.subplots(2, 1, figsize=(7, 7), sharex=True)
axes[0].plot(log_return)
axes[1].plot(log_step)
axes[0].set_title(f'Learning curve: {env_name}')
axes[0].set_ylabel('Return')
axes[1].set_ylabel('#steps')
axes[1].set_xlabel('Epoch')
sns.despine()
f.tight_layout()
f.savefig(f'../figs/lc-{env_name}.png', dpi=120)
def main(env_name, n_hidden):
'''render the performance of a saved ckpt'''
# define env and agent
env = gym.make(env_name).env
state_dim, n_actions, action_space_type = get_env_info(env)
agent = Agent(state_dim, n_hidden, n_actions)
agent.load_state_dict(torch.load(f'../log/agent-{env_name}.pth'))
agent.eval()
cumulative_reward, step, probs, rewards, values = run(agent,
env,
render=True)
def spot_get_market_summary():
url = "/api/{0}/market_summary".format(get_spot_api_version())
env = get_env_info()
ret = {}
try:
resp = requests.get(get_spot_full_url(env["API_HOST"], url))
resp.raise_for_status()
except HTTPError as http_err:
print("HTTP error occurred: {0}".format(http_err))
except Exception as err:
print("Other error occurred: {0}".format(err))
else:
ret = resp.json()
return ret
def futures_get_trades(params):
url = "/api/{0}/trades".format(get_futures_api_version())
env = get_env_info()
ret = {}
try:
resp = requests.get(get_futures_full_url(env["API_HOST"], url),
params=params)
resp.raise_for_status()
except HTTPError as http_err:
print("HTTP error occurred: {0}".format(http_err))
except Exception as err:
print("Other error occurred: {0}".format(err))
else:
ret = resp.json()
return ret
def earn_get_orders():
url = "/api/{0}/invest/orders".format(get_spot_api_version())
env = get_env_info()
headers = gen_headers(env["API_KEY"], env["API_SECRET_KEY"], url)
ret = {}
try:
resp = requests.get(get_spot_full_url(env["API_HOST"], url),
headers=headers)
resp.raise_for_status()
except HTTPError as http_err:
print("HTTP error occurred: {0}".format(http_err))
except Exception as err:
print("Other error occurred: {0}".format(err))
else:
ret = resp.json()
return ret
def otc_accept_quote(quote_id):
url = "/api/{0}/accept/{1}".format(get_otc_api_version(), quote_id)
env = get_env_info()
headers = gen_headers(env["API_KEY"], env["API_SECRET_KEY"], url)
ret = {}
try:
resp = requests.post(get_otc_full_url(env["API_HOST"], url),
headers=headers)
resp.raise_for_status()
except HTTPError as http_err:
print("HTTP error occurred: {0}".format(http_err))
except Exception as err:
print("Other error occurred: {0}".format(err))
else:
ret = resp.json()
return ret
def spot_place_limit_order(data):
url = "/api/{0}/order".format(get_spot_api_version())
env = get_env_info()
headers = gen_headers(env["API_KEY"], env["API_SECRET_KEY"], url,
json.dumps(data))
ret = {}
try:
resp = requests.post(get_spot_full_url(env["API_HOST"], url),
json=data,
headers=headers)
resp.raise_for_status()
except HTTPError as http_err:
print("HTTP error occurred: {0}".format(http_err))
except Exception as err:
print("Other error occurred: {0}".format(err))
else:
ret = resp.json()
return ret
def futures_change_settlement_currency(data):
url = "/api/{0}/settle_in".format(get_futures_api_version())
env = get_env_info()
headers = gen_headers(env["API_KEY"], env["API_SECRET_KEY"], url,
json.dumps(data))
ret = {}
try:
resp = requests.post(
get_futures_full_url(env["API_HOST"], url),
json=data,
headers=headers,
)
resp.raise_for_status()
except HTTPError as http_err:
print("HTTP error occurred: {0}".format(http_err))
except Exception as err:
print("Other error occurred: {0}".format(err))
else:
ret = resp
return ret
def spot_get_wallet_address(currency):
url = "/api/{0}/user/wallet/address".format(get_spot_api_version())
env = get_env_info()
headers = gen_headers(env["API_KEY"], env["API_SECRET_KEY"], url)
ret = {}
params = {"currency": currency}
try:
resp = requests.get(
get_spot_full_url(env["API_HOST"], url),
params=params,
headers=headers,
)
resp.raise_for_status()
except HTTPError as http_err:
print("HTTP error occurred: {0}".format(http_err))
except Exception as err:
print("Other error occurred: {0}".format(err))
else:
ret = resp.json()
return ret
def earn_get_history(page_number=1, page_size=10):
url = "/api/{0}/invest/history".format(get_spot_api_version())
env = get_env_info()
headers = gen_headers(env["API_KEY"], env["API_SECRET_KEY"], url)
params = {
"pageNumber": page_number,
"pageSize": page_size,
}
ret = {}
try:
# page_number is 1-based
resp = requests.get(
get_spot_full_url(env["API_HOST"], url),
params=params,
headers=headers,
)
resp.raise_for_status()
except HTTPError as http_err:
print("HTTP error occurred: {0}".format(http_err))
except Exception as err:
print("Other error occurred: {0}".format(err))
else:
ret = resp.json()
return ret
def main():
bot.run(utils.get_env_info('DISCORD_TOKEN'))
print(message)
def on_error(ws, error):
print(error)
def on_close(ws, close_status_code, close_msg):
print("### socket closed ###")
def on_open(ws):
payload = {
"op": "subscribe",
"args": ["orderBookApi:BTCPFC_0"],
}
ws.send(json.dumps(payload))
if __name__ == "__main__":
# websocket.enableTrace(True)
env = get_env_info()
ws = websocket.WebSocketApp(
get_futures_ws_url(env["WS_HOST"]),
on_open=on_open,
on_message=on_message,
on_error=on_error,
on_close=on_close,
)
ws.run_forever()
