Commit 93947947 authored by Jeffrey Gleason's avatar Jeffrey Gleason Committed by Mitar

Jg/v5.8

parent b7cf7a92
......@@ -20,7 +20,7 @@
},
{
"type": "PIP",
"package_uri": "git+https://github.com/NewKnowledge/TimeSeries-D3M-Wrappers.git@b7ba05ae4b3edcbbacddbd0fc138b75f8d4af5be#egg=TimeSeriesD3MWrappers"
"package_uri": "git+https://github.com/NewKnowledge/TimeSeries-D3M-Wrappers.git@e5355acdc8f1b497bf72c25120a03f47fd48ff42#egg=TimeSeriesD3MWrappers"
}
],
"python_path": "d3m.primitives.clustering.hdbscan.Hdbscan",
......@@ -242,5 +242,5 @@
},
"structural_type": "TimeSeriesD3MWrappers.Hdbscan.Hdbscan",
"description": "Produce primitive's best guess for the cluster number of each series using Hierarchical Density-Based\nClustering or Density-Based Clustering.\n\nAttributes\n----------\nmetadata : PrimitiveMetadata\n Primitive's metadata. Available as a class attribute.\nlogger : Logger\n Primitive's logger. Available as a class attribute.\nhyperparams : Hyperparams\n Hyperparams passed to the constructor.\nrandom_seed : int\n Random seed passed to the constructor.\ndocker_containers : Dict[str, DockerContainer]\n A dict mapping Docker image keys from primitive's metadata to (named) tuples containing\n container's address under which the container is accessible by the primitive, and a\n dict mapping exposed ports to ports on that address.\nvolumes : Dict[str, str]\n A dict mapping volume keys from primitive's metadata to file and directory paths\n where downloaded and extracted files are available to the primitive.\ntemporary_directory : str\n An absolute path to a temporary directory a primitive can use to store any files\n for the duration of the current pipeline run phase. Directory is automatically\n cleaned up after the current pipeline run phase finishes.",
"digest": "d5bded48802086b8b3ad25cfe964ab7854bf039af78667370d39e370240f346e"
"digest": "8717c01d00f929384879113d87c88a38212bba0fc9828d1cf3de1e50718378f0"
}
......@@ -21,7 +21,7 @@
},
{
"type": "PIP",
"package_uri": "git+https://github.com/NewKnowledge/TimeSeries-D3M-Wrappers.git@b7ba05ae4b3edcbbacddbd0fc138b75f8d4af5be#egg=TimeSeriesD3MWrappers"
"package_uri": "git+https://github.com/NewKnowledge/TimeSeries-D3M-Wrappers.git@e5355acdc8f1b497bf72c25120a03f47fd48ff42#egg=TimeSeriesD3MWrappers"
}
],
"python_path": "d3m.primitives.clustering.k_means.Sloth",
......@@ -225,5 +225,5 @@
},
"structural_type": "TimeSeriesD3MWrappers.Storc.Storc",
"description": "Produce primitive's best guess for the cluster number of each series.\n\nAttributes\n----------\nmetadata : PrimitiveMetadata\n Primitive's metadata. Available as a class attribute.\nlogger : Logger\n Primitive's logger. Available as a class attribute.\nhyperparams : Hyperparams\n Hyperparams passed to the constructor.\nrandom_seed : int\n Random seed passed to the constructor.\ndocker_containers : Dict[str, DockerContainer]\n A dict mapping Docker image keys from primitive's metadata to (named) tuples containing\n container's address under which the container is accessible by the primitive, and a\n dict mapping exposed ports to ports on that address.\nvolumes : Dict[str, str]\n A dict mapping volume keys from primitive's metadata to file and directory paths\n where downloaded and extracted files are available to the primitive.\ntemporary_directory : str\n An absolute path to a temporary directory a primitive can use to store any files\n for the duration of the current pipeline run phase. Directory is automatically\n cleaned up after the current pipeline run phase finishes.",
"digest": "73915626b10509d7b8d1c774c647232d64db0eafaf6e8ce4dd4ff93285a02966"
"digest": "d12bc3e491b082b5f50f8de5ec62672be9141cfc01c21f7c75eedb67c4bee784"
}
......@@ -20,7 +20,7 @@
},
{
"type": "PIP",
"package_uri": "git+https://github.com/NewKnowledge/TimeSeries-D3M-Wrappers.git@b7ba05ae4b3edcbbacddbd0fc138b75f8d4af5be#egg=TimeSeriesD3MWrappers"
"package_uri": "git+https://github.com/NewKnowledge/TimeSeries-D3M-Wrappers.git@e5355acdc8f1b497bf72c25120a03f47fd48ff42#egg=TimeSeriesD3MWrappers"
}
],
"python_path": "d3m.primitives.time_series_classification.k_neighbors.Kanine",
......@@ -211,5 +211,5 @@
},
"structural_type": "TimeSeriesD3MWrappers.Kanine.Kanine",
"description": "Produce primitive's classifications for new time series data. The input is a numpy ndarray of\nsize (number_of_time_series, time_series_length) containing new time series.\nThe output is a numpy ndarray containing a predicted class for each of the input time series.\n\nAttributes\n----------\nmetadata : PrimitiveMetadata\n Primitive's metadata. Available as a class attribute.\nlogger : Logger\n Primitive's logger. Available as a class attribute.\nhyperparams : Hyperparams\n Hyperparams passed to the constructor.\nrandom_seed : int\n Random seed passed to the constructor.\ndocker_containers : Dict[str, DockerContainer]\n A dict mapping Docker image keys from primitive's metadata to (named) tuples containing\n container's address under which the container is accessible by the primitive, and a\n dict mapping exposed ports to ports on that address.\nvolumes : Dict[str, str]\n A dict mapping volume keys from primitive's metadata to file and directory paths\n where downloaded and extracted files are available to the primitive.\ntemporary_directory : str\n An absolute path to a temporary directory a primitive can use to store any files\n for the duration of the current pipeline run phase. Directory is automatically\n cleaned up after the current pipeline run phase finishes.",
"digest": "2dbc5aa12886ab0a1a97533c6081e4610bbd82f002a7f68dc3723afaab98e276"
"digest": "c9a5c50be81181f5e54593a3f240296341d50a3e54f0e328a4ffb4324988419b"
}
......@@ -21,7 +21,7 @@
},
{
"type": "PIP",
"package_uri": "git+https://github.com/NewKnowledge/TimeSeries-D3M-Wrappers.git@b7ba05ae4b3edcbbacddbd0fc138b75f8d4af5be#egg=TimeSeriesD3MWrappers"
"package_uri": "git+https://github.com/NewKnowledge/TimeSeries-D3M-Wrappers.git@e5355acdc8f1b497bf72c25120a03f47fd48ff42#egg=TimeSeriesD3MWrappers"
}
],
"python_path": "d3m.primitives.time_series_classification.shapelet_learning.Shallot",
......@@ -264,5 +264,5 @@
},
"structural_type": "TimeSeriesD3MWrappers.Shallot.Shallot",
"description": "Produce primitive's classifications for new time series data The input is a numpy ndarray of\nsize (number_of_time_series, time_series_length, dimension) containing new time series.\nThe output is a numpy ndarray containing a predicted class for each of the input time series.\n\nAttributes\n----------\nmetadata : PrimitiveMetadata\n Primitive's metadata. Available as a class attribute.\nlogger : Logger\n Primitive's logger. Available as a class attribute.\nhyperparams : Hyperparams\n Hyperparams passed to the constructor.\nrandom_seed : int\n Random seed passed to the constructor.\ndocker_containers : Dict[str, DockerContainer]\n A dict mapping Docker image keys from primitive's metadata to (named) tuples containing\n container's address under which the container is accessible by the primitive, and a\n dict mapping exposed ports to ports on that address.\nvolumes : Dict[str, str]\n A dict mapping volume keys from primitive's metadata to file and directory paths\n where downloaded and extracted files are available to the primitive.\ntemporary_directory : str\n An absolute path to a temporary directory a primitive can use to store any files\n for the duration of the current pipeline run phase. Directory is automatically\n cleaned up after the current pipeline run phase finishes.",
"digest": "349a6182f05c635e067d455e075bd7de2541aad0a2cf24d9052d3dfee4469e61"
"digest": "76e69522530c33c1d16b771d35e72b963695c431ab3f90417ab3e84e351255a4"
}
......@@ -20,7 +20,7 @@
},
{
"type": "PIP",
"package_uri": "git+https://github.com/NewKnowledge/TimeSeries-D3M-Wrappers.git@f3671ed72ead927cfcb1a387d237f40eadc28b93#egg=TimeSeriesD3MWrappers"
"package_uri": "git+https://github.com/NewKnowledge/TimeSeries-D3M-Wrappers.git@e5355acdc8f1b497bf72c25120a03f47fd48ff42#egg=TimeSeriesD3MWrappers"
}
],
"python_path": "d3m.primitives.time_series_forecasting.arima.Parrot",
......@@ -233,5 +233,5 @@
},
"structural_type": "TimeSeriesD3MWrappers.Parrot.Parrot",
"description": "Produce the primitive's prediction for future time series data. The output\nis a list of length 'n_periods' that contains a prediction for each of 'n_periods'\nfuture time periods. 'n_periods' is a hyperparameter that must be set before making the prediction.\n\nAttributes\n----------\nmetadata : PrimitiveMetadata\n Primitive's metadata. Available as a class attribute.\nlogger : Logger\n Primitive's logger. Available as a class attribute.\nhyperparams : Hyperparams\n Hyperparams passed to the constructor.\nrandom_seed : int\n Random seed passed to the constructor.\ndocker_containers : Dict[str, DockerContainer]\n A dict mapping Docker image keys from primitive's metadata to (named) tuples containing\n container's address under which the container is accessible by the primitive, and a\n dict mapping exposed ports to ports on that address.\nvolumes : Dict[str, str]\n A dict mapping volume keys from primitive's metadata to file and directory paths\n where downloaded and extracted files are available to the primitive.\ntemporary_directory : str\n An absolute path to a temporary directory a primitive can use to store any files\n for the duration of the current pipeline run phase. Directory is automatically\n cleaned up after the current pipeline run phase finishes.",
"digest": "a77b91a4cbd302c84a10d09ebb092169af61c633c5336983debf65c0cd3b255e"
"digest": "14f5afe8bcee2b9f8297e5b9db472afca52bdb38cecd103dfa5abc3ca2bd6776"
}
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