Skip to content

Commit

Permalink
Examples: Updated notebooks outputs
Browse files Browse the repository at this point in the history
  • Loading branch information
@AlejandroCN7
AlejandroCN7 committed Aug 3, 2023
1 parent 994a1cd commit 1c3a030
Show file tree
Hide file tree
Showing 10 changed files with 1,061 additions and 669 deletions.
37 changes: 20 additions & 17 deletions examples/basic_example.ipynb
View file
Original file line number Diff line number Diff line change
Expand Up @@ -93,10 +93,13 @@
"output_type": "stream",
"text": [
"#----------------------------------------------------------------------------------------------#\n",
"\u001b[38;20m[ENVIRONMENT] (INFO) : Starting a new episode... [Episode 1]\u001b[0m\n",
"\u001b[38;20m[ENVIRONMENT] (INFO) : Starting a new episode... [demo-v1] [Episode 1]\u001b[0m\n",
"#----------------------------------------------------------------------------------------------#\n",
"\u001b[38;20m[MODELING] (INFO) : Episode directory created [/workspaces/sinergym/examples/Eplus-env-demo-v1-res1/Eplus-env-sub_run1]\u001b[0m\n",
"\u001b[38;20m[MODELING] (INFO) : Weather file USA_PA_Pittsburgh-Allegheny.County.AP.725205_TMY3.epw used.\u001b[0m\n",
"\u001b[38;20m[MODELING] (INFO) : Updated building model with whole Output:Variable available names\u001b[0m\n",
"\u001b[38;20m[MODELING] (INFO) : Updated building model with whole Output:Meter available names\u001b[0m\n",
"\u001b[38;20m[MODELING] (INFO) : Adapting weather to building model. [USA_PA_Pittsburgh-Allegheny.County.AP.725205_TMY3.epw]\u001b[0m\n",
"\u001b[38;20m[ENVIRONMENT] (INFO) : Saving episode output path... [/workspaces/sinergym/examples/Eplus-env-demo-v1-res1/Eplus-env-sub_run1/output]\u001b[0m\n"
]
},
Expand All @@ -117,18 +120,18 @@
"\u001b[38;20m[SIMULATOR] (INFO) : Handles initialized.\u001b[0m\n",
"\u001b[38;20m[SIMULATOR] (INFO) : Handles are ready.\u001b[0m\n",
"\u001b[38;20m[SIMULATOR] (INFO) : System is ready.\u001b[0m\n",
"Reward: -1.4254385096063296 {'time_elapsed(hours)': 0.75, 'year': 1995, 'month': 1, 'day': 1, 'hour': 0, 'is_raining': False, 'action': [18.540745, 28.084728], 'timestep': 2, 'reward': -1.4254385096063296, 'reward_energy': -0.09759966457086716, 'reward_comfort': -2.753277354641792, 'total_energy': 975.9966457086716, 'abs_comfort': 2.753277354641792, 'temperatures': [17.246722645358208]}\n",
"Reward: -1369.2197847359469 {'time_elapsed(hours)': 744.2916666666666, 'year': 2004, 'month': 2, 'day': 1, 'hour': 0, 'is_raining': False, 'action': [18.048912, 23.24202], 'timestep': 2976, 'reward': -0.13879983228543358, 'reward_energy': -0.27759966457086716, 'reward_comfort': -0.0, 'total_energy': 2775.9966457086716, 'abs_comfort': 0.0, 'temperatures': [20.94143053913133]}\n",
"Reward: -3121.5818268631465 {'time_elapsed(hours)': 1416.3333333333333, 'year': 2000, 'month': 3, 'day': 1, 'hour': 0, 'is_raining': False, 'action': [20.70321, 24.11236], 'timestep': 5664, 'reward': -0.4304559999611765, 'reward_energy': -0.0476985272671676, 'reward_comfort': -0.8132134726551854, 'total_energy': 476.98527267167594, 'abs_comfort': 0.8132134726551854, 'temperatures': [19.186786527344815]}\n",
"Reward: -4817.432184179871 {'time_elapsed(hours)': 2160.3333333333335, 'year': 1991, 'month': 4, 'day': 1, 'hour': 0, 'is_raining': False, 'action': [18.886724, 26.37917], 'timestep': 8640, 'reward': -0.0034341956839029878, 'reward_energy': -0.0068683913678059755, 'reward_comfort': -0.0, 'total_energy': 68.68391367805975, 'abs_comfort': 0.0, 'temperatures': [20.1250083354098]}\n",
"Reward: -6830.4931391804 {'time_elapsed(hours)': 2880.25, 'year': 1996, 'month': 5, 'day': 1, 'hour': 0, 'is_raining': False, 'action': [18.255701, 28.491814], 'timestep': 11520, 'reward': -0.0, 'reward_energy': -0.0, 'reward_comfort': -0.0, 'total_energy': 0.0, 'abs_comfort': 0.0, 'temperatures': [22.099550361450305]}\n",
"Reward: -8891.369958504001 {'time_elapsed(hours)': 3624.25, 'year': 2003, 'month': 6, 'day': 1, 'hour': 0, 'is_raining': False, 'action': [16.891432, 28.060535], 'timestep': 14496, 'reward': -0.0, 'reward_energy': -0.0, 'reward_comfort': -0.0, 'total_energy': 0.0, 'abs_comfort': 0.0, 'temperatures': [23.388148594833684]}\n",
"Reward: -10613.544902375545 {'time_elapsed(hours)': 4344.25, 'year': 2004, 'month': 7, 'day': 1, 'hour': 0, 'is_raining': False, 'action': [19.811148, 29.473894], 'timestep': 17376, 'reward': -0.0, 'reward_energy': -0.0, 'reward_comfort': -0.0, 'total_energy': 0.0, 'abs_comfort': 0.0, 'temperatures': [23.22310697120138]}\n",
"Reward: -12178.826605654973 {'time_elapsed(hours)': 5088.25, 'year': 1994, 'month': 8, 'day': 1, 'hour': 0, 'is_raining': False, 'action': [18.472122, 26.706238], 'timestep': 20352, 'reward': -0.030628211524101445, 'reward_energy': -0.0, 'reward_comfort': -0.06125642304820289, 'total_energy': 0.0, 'abs_comfort': 0.06125642304820289, 'temperatures': [22.938743576951797]}\n",
"Reward: -13711.784653572497 {'time_elapsed(hours)': 5832.25, 'year': 1996, 'month': 9, 'day': 1, 'hour': 0, 'is_raining': False, 'action': [15.052247, 28.259514], 'timestep': 23328, 'reward': -0.31878632879905133, 'reward_energy': -0.0, 'reward_comfort': -0.6375726575981027, 'total_energy': 0.0, 'abs_comfort': 0.6375726575981027, 'temperatures': [22.362427342401897]}\n",
"Reward: -15691.896746976563 {'time_elapsed(hours)': 6552.333333333333, 'year': 1999, 'month': 10, 'day': 1, 'hour': 0, 'is_raining': False, 'action': [21.668655, 22.537306], 'timestep': 26208, 'reward': -0.38977939388862204, 'reward_energy': -0.0, 'reward_comfort': -0.7795587877772441, 'total_energy': 0.0, 'abs_comfort': 0.7795587877772441, 'temperatures': [22.220441212222756]}\n",
"Reward: -17863.08688751622 {'time_elapsed(hours)': 7296.375, 'year': 2004, 'month': 11, 'day': 1, 'hour': 0, 'is_raining': False, 'action': [17.013231, 29.407843], 'timestep': 29184, 'reward': -0.0060932427794117335, 'reward_energy': -0.012186485558823467, 'reward_comfort': -0.0, 'total_energy': 121.86485558823466, 'abs_comfort': 0.0, 'temperatures': [20.352258351173194]}\n",
"Reward: -18935.145464227342 {'time_elapsed(hours)': 8016.3125, 'year': 1997, 'month': 12, 'day': 1, 'hour': 0, 'is_raining': True, 'action': [22.160416, 28.180706], 'timestep': 32064, 'reward': -0.3741989706835282, 'reward_energy': -0.013222958731539714, 'reward_comfort': -0.7351749826355167, 'total_energy': 132.22958731539714, 'abs_comfort': 0.7351749826355167, 'temperatures': [19.264825017364483]}\n",
"Reward: -1.4254385096063296 {'time_elapsed(hours)': 0.5, 'month': 1, 'day': 1, 'hour': 0, 'is_raining': False, 'action': [21.817875, 23.054222], 'timestep': 2, 'reward': -1.4254385096063296, 'reward_energy': -0.09759966457086716, 'reward_comfort': -2.753277354641792, 'total_energy': 975.9966457086716, 'abs_comfort': 2.753277354641792, 'temperatures': [17.246722645358208]}\n",
"Reward: -1394.7826506188903 {'time_elapsed(hours)': 744.3333333333334, 'month': 2, 'day': 1, 'hour': 0, 'is_raining': False, 'action': [21.997723, 22.894978], 'timestep': 2977, 'reward': -0.04879983228543358, 'reward_energy': -0.09759966457086716, 'reward_comfort': -0.0, 'total_energy': 975.9966457086716, 'abs_comfort': 0.0, 'temperatures': [20.498780432410737]}\n",
"Reward: -3066.78837616243 {'time_elapsed(hours)': 1416.3125, 'month': 3, 'day': 1, 'hour': 0, 'is_raining': False, 'action': [16.752909, 27.053444], 'timestep': 5665, 'reward': -0.026568975416104906, 'reward_energy': -0.05313795083220981, 'reward_comfort': -0.0, 'total_energy': 531.3795083220981, 'abs_comfort': 0.0, 'temperatures': [21.512972013113217]}\n",
"Reward: -4709.293729177251 {'time_elapsed(hours)': 2160.3333333333335, 'month': 4, 'day': 1, 'hour': 0, 'is_raining': False, 'action': [17.1067, 27.596006], 'timestep': 8641, 'reward': -0.20446464864375535, 'reward_energy': -0.0, 'reward_comfort': -0.4089292972875107, 'total_energy': 0.0, 'abs_comfort': 0.4089292972875107, 'temperatures': [19.59107070271249]}\n",
"Reward: -6749.687501258369 {'time_elapsed(hours)': 2880.25, 'month': 5, 'day': 1, 'hour': 0, 'is_raining': False, 'action': [16.926786, 27.206514], 'timestep': 11521, 'reward': -0.0, 'reward_energy': -0.0, 'reward_comfort': -0.0, 'total_energy': 0.0, 'abs_comfort': 0.0, 'temperatures': [21.854637974986215]}\n",
"Reward: -8825.38683295474 {'time_elapsed(hours)': 3624.25, 'month': 6, 'day': 1, 'hour': 0, 'is_raining': False, 'action': [20.450157, 25.871521], 'timestep': 14497, 'reward': -0.0, 'reward_energy': -0.0, 'reward_comfort': -0.0, 'total_energy': 0.0, 'abs_comfort': 0.0, 'temperatures': [23.33089573323892]}\n",
"Reward: -10535.06315803729 {'time_elapsed(hours)': 4344.25, 'month': 7, 'day': 1, 'hour': 0, 'is_raining': False, 'action': [21.933506, 29.778053], 'timestep': 17377, 'reward': -0.010234480286959169, 'reward_energy': -0.0, 'reward_comfort': -0.020468960573918338, 'total_energy': 0.0, 'abs_comfort': 0.020468960573918338, 'temperatures': [22.97953103942608]}\n",
"Reward: -12101.875214060821 {'time_elapsed(hours)': 5088.25, 'month': 8, 'day': 1, 'hour': 0, 'is_raining': False, 'action': [17.418365, 28.15558], 'timestep': 20353, 'reward': -0.08497719632228318, 'reward_energy': -0.0, 'reward_comfort': -0.16995439264456635, 'total_energy': 0.0, 'abs_comfort': 0.16995439264456635, 'temperatures': [22.830045607355434]}\n",
"Reward: -13628.224742555516 {'time_elapsed(hours)': 5832.25, 'month': 9, 'day': 1, 'hour': 0, 'is_raining': False, 'action': [18.141188, 23.852926], 'timestep': 23329, 'reward': -0.34856257767809495, 'reward_energy': -0.0, 'reward_comfort': -0.6971251553561899, 'total_energy': 0.0, 'abs_comfort': 0.6971251553561899, 'temperatures': [22.30287484464381]}\n",
"Reward: -15604.503745255817 {'time_elapsed(hours)': 6552.333333333333, 'month': 10, 'day': 1, 'hour': 0, 'is_raining': False, 'action': [19.657272, 23.77765], 'timestep': 26209, 'reward': -0.005330003468504883, 'reward_energy': -0.010660006937009766, 'reward_comfort': -0.0, 'total_energy': 106.60006937009766, 'abs_comfort': 0.0, 'temperatures': [21.42654933751714]}\n",
"Reward: -17794.149582078517 {'time_elapsed(hours)': 7296.375, 'month': 11, 'day': 1, 'hour': 0, 'is_raining': False, 'action': [18.784815, 24.138014], 'timestep': 29185, 'reward': -0.006359279454720524, 'reward_energy': -0.012718558909441048, 'reward_comfort': -0.0, 'total_energy': 127.18558909441047, 'abs_comfort': 0.0, 'temperatures': [21.016856425029037]}\n",
"Reward: -18838.972733052567 {'time_elapsed(hours)': 8016.333333333333, 'month': 12, 'day': 1, 'hour': 0, 'is_raining': True, 'action': [16.190203, 24.723541], 'timestep': 32065, 'reward': -0.8149987978345082, 'reward_energy': -0.016586334952939066, 'reward_comfort': -1.6134112607160773, 'total_energy': 165.86334952939066, 'abs_comfort': 1.6134112607160773, 'temperatures': [18.386588739283923]}\n",
"Progress: |***************************************************************************************************| 99%\n"
]
}
Expand Down Expand Up @@ -163,7 +166,7 @@
},
{
"cell_type": "code",
"execution_count": 3,
"execution_count": 5,
"metadata": {
"collapsed": false,
"pycharm": {
Expand All @@ -175,7 +178,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[38;20m[ENVIRONMENT] (INFO) : Environment closed.\u001b[0m\n"
"\u001b[38;20m[ENVIRONMENT] (INFO) : Environment closed. [demo-v1]\u001b[0m\n"
]
}
],
Expand Down Expand Up @@ -210,7 +213,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
"Mean reward: -0.5715457603415743 Cumulative reward: -20026.39189660931\n"
"Mean reward: -0.5678685244508332 Cumulative reward: -19898.11309675785\n"
]
}
],
Expand All @@ -227,7 +230,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"The [list of environments](https://github.com/ugr-sail/sinergym/blob/main/sinergym/__init__.py) that we have registered in Sinergym is extensive and we use buildings files changing particularities. For example, continuous action space or discrete, noise over weather, runperiod, timesteps, reward function, etc. We will see it in the following notebooks."
"The [list of environments](https://github.com/ugr-sail/sinergym/blob/main/sinergym/__init__.py) that we have registered in Sinergym is extensive and we use buildings files changing particularities. For example, continuous or discrete action spaces, different types of weathers, noise over weather, runperiod, timesteps, reward functions, etc. We will see it in the following notebooks."
]
}
],
Expand Down
Loading

0 comments on commit 1c3a030

Please sign in to comment.