renamed root folder from src

readme.md

@@ -46,13 +46,22 @@ This test period is directly after the training period and it looks like the use
     - Then open tensorflow-VPG.ipynb in jupyter
     - Or try an alternative agent  with tensorforce-PPO.ipynb and train
 
-# Details
+# Files
 
 - enviroments/portfolio.py - contains an openai environment for porfolio trading
 - tensorforce-VPG.ipynb - notebook to try a policy gradient agent
 - tensorforce-PPO - notebook to try a PPO agent
 - data/poloniex_30m.hdf - hdf file with cryptocurrency 30 minutes prices
 
+# Using the environment
+
+There are three environments here to use them:
+```py
+
+```
+
+CryptoPortfolioMLP-v0
+
 # Tests
 
 We have partial test coverage of the environment, just run:

rl_portfolio_management/environments/__init__.py

@@ -7,20 +7,20 @@ df_train = pd.read_hdf('./data/poloniex_30m.hf', key='train')
 
 env_specs_args = [
     dict(id='CryptoPortfolioMLP-v0',
-         entry_point='src.environments.portfolio:PortfolioEnv',
+         entry_point='rl_portfolio_management.environments.portfolio:PortfolioEnv',
          kwargs=dict(
              output_mode='mlp',
              df=df_train
          )),
     dict(id='CryptoPortfolioEIIE-v0',
-         entry_point='src.environments.portfolio:PortfolioEnv',
+         entry_point='rl_portfolio_management.environments.portfolio:PortfolioEnv',
          kwargs=dict(
              output_mode='EIIE',
              df=df_train
          )
          ),
     dict(id='CryptoPortfolioAtari-v0',
-         entry_point='src.environments.portfolio:PortfolioEnv',
+         entry_point='rl_portfolio_management.environments.portfolio:PortfolioEnv',
          kwargs=dict(
              output_mode='atari',
              df=df_train

tensorforce-PPO.ipynb

@@ -163,7 +163,7 @@
    },
    "outputs": [],
    "source": [
-    "from src.environments.portfolio import PortfolioEnv"
+    "from rl_portfolio_management.environments.portfolio import PortfolioEnv"
    ]
   },
   {
@@ -609,8 +609,8 @@
    },
    "outputs": [],
    "source": [
-    "from src.callbacks.tensorforce import EpisodeFinishedTQDM\n",
-    "from src.util import MDD, sharpe"
+    "from rl_portfolio_management.callbacks.tensorforce import EpisodeFinishedTQDM\n",
+    "from rl_portfolio_management.util import MDD, sharpe"
    ]
   },
   {

tensorforce-VPG.ipynb

@@ -123,7 +123,7 @@
    },
    "outputs": [],
    "source": [
-    "from src.environments.portfolio import PortfolioEnv"
+    "from rl_portfolio_management.environments.portfolio import PortfolioEnv"
    ]
   },
   {

test/test_callbacks.py

@@ -3,7 +3,7 @@ import numpy as np
 
 import os
 os.sys.path.append('.')
-from src.callbacks.notebook_plot import LivePlotNotebook
+from rl_portfolio_management.callbacks.notebook_plot import LivePlotNotebook
 
 def test_live_plot_notebook():
     # Test

test/test_env.py

@@ -9,7 +9,7 @@ import numpy as np
 import gym
 from gym.envs.tests import test_envs
 
-from src.environments import PortfolioEnv, env_specs
+from rl_portfolio_management.environments import PortfolioEnv, env_specs
 
 
 @pytest.mark.parametrize("spec_id", env_specs)

test/test_utils.py

@@ -1,5 +1,5 @@
-from src.data.utils import random_shift, normalize, scale_to_start
-from src.util import sharpe, MDD
+from rl_portfolio_management.data.utils import random_shift, normalize, scale_to_start
+from rl_portfolio_management.util import sharpe, MDD
 
 import pandas as pd
 import numpy as np