Sarah Segel: Merge pull request #94 from automl/bug/pre-commit-hooks

development/.buildinfo

@@ -1,4 +1,4 @@
 # Sphinx build info version 1
 # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
-config: 427e04ae34191866870e58fc211b7707
+config: 268198ccf5ff446d476157fe5db16dc4
 tags: 645f666f9bcd5a90fca523b33c5a78b7

development/_downloads/486eb49d7cdf943097f599661017192d/parallel_coordinates.py

@@ -34,5 +34,5 @@
     # Finally, you can load the figure. Here, the filter variables play a role.
     # Alternatively: Use the matplotlib output (`load_mpl_outputs`) if available.
     figure = plugin.load_outputs(run, inputs, outputs)  # plotly.go figure
-    figure.write_image("examples/api/parallel_coordinates.png", scale=2.)
+    figure.write_image("examples/api/parallel_coordinates.png", scale=2.0)
     # figure.show()

development/_downloads/99282791bd8a0f766c85ce43b212a6b7/pdp.ipynb

@@ -15,7 +15,7 @@
       },
       "outputs": [],
       "source": [
-        "from deepcave.plugins.hyperparameter.pdp import PartialDependencies\nfrom deepcave.runs.converters.deepcave import DeepCAVERun\nfrom pathlib import Path\n\n\nif __name__ == \"__main__\":\n    # Instantiate the run\n    run = DeepCAVERun.from_path(Path(\"logs/DeepCAVE/minimal/run_2\"))\n    objective_id = run.get_objective_ids()[0]\n    budget_id = run.get_budget_ids()[-1]\n\n    # Instantiate the plugin\n    plugin = PartialDependencies()\n    inputs = plugin.generate_inputs(\n        hyperparameter_name_1=\"alpha\",\n        hyperparameter_name_2=\"beta\",\n        objective_id=objective_id,\n        budget_id=budget_id,\n        show_confidence=False,\n        show_ice=True,\n    )\n    # Note: Filter variables are not considered.\n    outputs = plugin.generate_outputs(run, inputs)\n\n    # Finally, you can load the figure. Here, the filter variables play a role.\n    # Alternatively: Use the matplotlib output (`load_mpl_outputs`) if available.\n    figure = plugin.load_outputs(run, inputs, outputs)  # plotly.go figure\n    figure.write_image(\"examples/api/pdp.png\")\n    #figure.show()"
+        "from deepcave.plugins.hyperparameter.pdp import PartialDependencies\nfrom deepcave.runs.converters.deepcave import DeepCAVERun\nfrom pathlib import Path\n\n\nif __name__ == \"__main__\":\n    # Instantiate the run\n    run = DeepCAVERun.from_path(Path(\"logs/DeepCAVE/minimal/run_2\"))\n    objective_id = run.get_objective_ids()[0]\n    budget_id = run.get_budget_ids()[-1]\n\n    # Instantiate the plugin\n    plugin = PartialDependencies()\n    inputs = plugin.generate_inputs(\n        hyperparameter_name_1=\"alpha\",\n        hyperparameter_name_2=\"beta\",\n        objective_id=objective_id,\n        budget_id=budget_id,\n        show_confidence=False,\n        show_ice=True,\n    )\n    # Note: Filter variables are not considered.\n    outputs = plugin.generate_outputs(run, inputs)\n\n    # Finally, you can load the figure. Here, the filter variables play a role.\n    # Alternatively: Use the matplotlib output (`load_mpl_outputs`) if available.\n    figure = plugin.load_outputs(run, inputs, outputs)  # plotly.go figure\n    figure.write_image(\"examples/api/pdp.png\")\n    # figure.show()"
       ]
     }
   ],

development/_downloads/aabae18a223fa014a3ff3692699ee5e2/importances.ipynb

@@ -15,7 +15,7 @@
       },
       "outputs": [],
       "source": [
-        "from deepcave.plugins.hyperparameter.importances import Importances\nfrom deepcave.runs.converters.deepcave import DeepCAVERun\nfrom pathlib import Path\n\n\nif __name__ == \"__main__\":\n    # Instantiate the run\n    run = DeepCAVERun.from_path(Path(\"logs/DeepCAVE/minimal/run_2\"))\n\n    objective_id = run.get_objective_ids()[0]\n    budget_ids = run.get_budget_ids()\n\n    # Instantiate the plugin\n    plugin = Importances()\n    inputs = plugin.generate_inputs(\n        hyperparameter_names=run.configspace.get_hyperparameter_names(),\n        objective_id=objective_id,\n        budget_ids=budget_ids,\n        method=\"global\",\n        n_hps=3,\n        n_trees=10\n    )\n    # Note: Filter variables are not considered.\n    outputs = plugin.generate_outputs(run, inputs)\n\n    # Finally, you can load the figure. Here, the filter variables play a role.\n    # Alternatively: Use the matplotlib output (`load_mpl_outputs`) if available.\n    figure = plugin.load_outputs(run, inputs, outputs)  # plotly.go figure\n    figure.write_image(\"examples/api/importances.png\", scale=2.)\n    # figure.show()"
+        "from deepcave.plugins.hyperparameter.importances import Importances\nfrom deepcave.runs.converters.deepcave import DeepCAVERun\nfrom pathlib import Path\n\n\nif __name__ == \"__main__\":\n    # Instantiate the run\n    run = DeepCAVERun.from_path(Path(\"logs/DeepCAVE/minimal/run_2\"))\n\n    objective_id = run.get_objective_ids()[0]\n    budget_ids = run.get_budget_ids()\n\n    # Instantiate the plugin\n    plugin = Importances()\n    inputs = plugin.generate_inputs(\n        hyperparameter_names=run.configspace.get_hyperparameter_names(),\n        objective_id=objective_id,\n        budget_ids=budget_ids,\n        method=\"global\",\n        n_hps=3,\n        n_trees=10,\n    )\n    # Note: Filter variables are not considered.\n    outputs = plugin.generate_outputs(run, inputs)\n\n    # Finally, you can load the figure. Here, the filter variables play a role.\n    # Alternatively: Use the matplotlib output (`load_mpl_outputs`) if available.\n    figure = plugin.load_outputs(run, inputs, outputs)  # plotly.go figure\n    figure.write_image(\"examples/api/importances.png\", scale=2.0)\n    # figure.show()"
       ]
     }
   ],

development/_downloads/e839af13aa37ae3d835848af3db8e085/pdp.py

@@ -34,4 +34,4 @@
     # Alternatively: Use the matplotlib output (`load_mpl_outputs`) if available.
     figure = plugin.load_outputs(run, inputs, outputs)  # plotly.go figure
     figure.write_image("examples/api/pdp.png")
-    #figure.show()
+    # figure.show()

development/_downloads/e9c545ae14a903164c9a627d1b3a375a/parallel_coordinates.ipynb

@@ -15,7 +15,7 @@
       },
       "outputs": [],
       "source": [
-        "from deepcave.plugins.objective.parallel_coordinates import ParallelCoordinates\nfrom deepcave.runs.converters.deepcave import DeepCAVERun\nfrom pathlib import Path\n\n\nif __name__ == \"__main__\":\n    # Instantiate the run\n    run = DeepCAVERun.from_path(Path(\"logs/DeepCAVE/minimal/run_2\"))\n    objective_id = run.get_objective_ids()[0]\n    budget_id = run.get_budget_ids()[-1]\n\n    # Instantiate the plugin\n    plugin = ParallelCoordinates()\n    inputs = plugin.generate_inputs(\n        hyperparameter_names=run.configspace.get_hyperparameter_names(),\n        objective_id=objective_id,\n        budget_id=budget_id,\n        show_important_only=True,\n        show_unsuccessful=False,\n        hide_hps=False,\n        n_hps=3,\n    )\n    # Note: Filter variables are not considered.\n    outputs = plugin.generate_outputs(run, inputs)\n\n    # Finally, you can load the figure. Here, the filter variables play a role.\n    # Alternatively: Use the matplotlib output (`load_mpl_outputs`) if available.\n    figure = plugin.load_outputs(run, inputs, outputs)  # plotly.go figure\n    figure.write_image(\"examples/api/parallel_coordinates.png\", scale=2.)\n    # figure.show()"
+        "from deepcave.plugins.objective.parallel_coordinates import ParallelCoordinates\nfrom deepcave.runs.converters.deepcave import DeepCAVERun\nfrom pathlib import Path\n\n\nif __name__ == \"__main__\":\n    # Instantiate the run\n    run = DeepCAVERun.from_path(Path(\"logs/DeepCAVE/minimal/run_2\"))\n    objective_id = run.get_objective_ids()[0]\n    budget_id = run.get_budget_ids()[-1]\n\n    # Instantiate the plugin\n    plugin = ParallelCoordinates()\n    inputs = plugin.generate_inputs(\n        hyperparameter_names=run.configspace.get_hyperparameter_names(),\n        objective_id=objective_id,\n        budget_id=budget_id,\n        show_important_only=True,\n        show_unsuccessful=False,\n        hide_hps=False,\n        n_hps=3,\n    )\n    # Note: Filter variables are not considered.\n    outputs = plugin.generate_outputs(run, inputs)\n\n    # Finally, you can load the figure. Here, the filter variables play a role.\n    # Alternatively: Use the matplotlib output (`load_mpl_outputs`) if available.\n    figure = plugin.load_outputs(run, inputs, outputs)  # plotly.go figure\n    figure.write_image(\"examples/api/parallel_coordinates.png\", scale=2.0)\n    # figure.show()"
       ]
     }
   ],

development/_downloads/f0660e643860808c88e59e2b47bd432b/importances.py

@@ -26,13 +26,13 @@
         budget_ids=budget_ids,
         method="global",
         n_hps=3,
-        n_trees=10
+        n_trees=10,
     )
     # Note: Filter variables are not considered.
     outputs = plugin.generate_outputs(run, inputs)
 
     # Finally, you can load the figure. Here, the filter variables play a role.
     # Alternatively: Use the matplotlib output (`load_mpl_outputs`) if available.
     figure = plugin.load_outputs(run, inputs, outputs)  # plotly.go figure
-    figure.write_image("examples/api/importances.png", scale=2.)
-    # figure.show()
+    figure.write_image("examples/api/importances.png", scale=2.0)
+    # figure.show()