Commit 967dd40e authored by Mitar's avatar Mitar

Merge branch 'common-primitives' into 'master'

Updating common primitives

See merge request !153
parents 715ae8ed e49ae998
......@@ -17,7 +17,7 @@
},
{
"type": "PIP",
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]6f741202177ce23835b646ccc0189b35e9fef422#egg=common-primitives"
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]e41047e96a4dc17d4259557bc74c733422e07aaf#egg=common-primitives"
}
],
"name": "common_primitives.BayesianLogisticRegression",
......@@ -282,5 +282,5 @@
},
"structural_type": "common_primitives.logistic_regression.BayesianLogisticRegression",
"description": "Example of a primitive wrapping logistic regression using PyMC3 and its\nTheano backend.\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": "86e465b8ccd5c097e2e038962f92e8ce173fe164abb8fdb8979593fddd0d0b8c"
"digest": "be90abfffdc9d4d4f3c51dc2c06d6366ce4fc2c74a3a07c9d65b29932bb7592f"
}
......@@ -18,7 +18,7 @@
"installation": [
{
"type": "PIP",
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]6f741202177ce23835b646ccc0189b35e9fef422#egg=common-primitives"
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]e41047e96a4dc17d4259557bc74c733422e07aaf#egg=common-primitives"
}
],
"algorithm_types": [
......@@ -622,5 +622,5 @@
},
"structural_type": "common_primitives.lgbm_classifier.LightGBMClassifierPrimitive",
"description": "A lightGBM classifier using ``lgbm.LGBMClassifier``.\n\nIt uses semantic types to determine which columns to operate on.\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": "926ccca1bc3a49fd13b33cbe05a5b62cc0223017b689b4ecec587d1d8bb121f7"
"digest": "dcaccedf5a37ee962bc62a5de37b5531703abe713f6d011c5428548f64ddcad7"
}
......@@ -18,7 +18,7 @@
"installation": [
{
"type": "PIP",
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]6f741202177ce23835b646ccc0189b35e9fef422#egg=common-primitives"
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]e41047e96a4dc17d4259557bc74c733422e07aaf#egg=common-primitives"
}
],
"algorithm_types": [
......@@ -648,5 +648,5 @@
},
"structural_type": "common_primitives.random_forest.RandomForestClassifierPrimitive",
"description": "A random forest classifier using ``sklearn.ensemble.forest.RandomForestClassifier``.\n\nIt uses semantic types to determine which columns to operate on.\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": "40a3fc575aa70c25f8c1303f61a9daab402a05c18f3d9ba0a6aeb6f5172706ac"
"digest": "3c0bc9d0fa011d837e3224a1cbb3e7d25b055bb54041e684d625bee6e59209a9"
}
......@@ -18,7 +18,7 @@
"installation": [
{
"type": "PIP",
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]6f741202177ce23835b646ccc0189b35e9fef422#egg=common-primitives"
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]e41047e96a4dc17d4259557bc74c733422e07aaf#egg=common-primitives"
}
],
"algorithm_types": [
......@@ -664,5 +664,5 @@
},
"structural_type": "common_primitives.xgboost_dart.XGBoostDartClassifierPrimitive",
"description": "A XGBoost classifier using ``xgb.XGBoostClassifier`` with Dart Boosting type.\n\nIt uses semantic types to determine which columns to operate on.\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": "5dfabee26735f5d1fc573b492192a380e98edb664d4728c7c813b3c62cf40564"
"digest": "38f8f617b0c738d681ec71d5195caed764cbd2cd79151d96a94ff8080a4be969"
}
......@@ -18,7 +18,7 @@
"installation": [
{
"type": "PIP",
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]6f741202177ce23835b646ccc0189b35e9fef422#egg=common-primitives"
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]e41047e96a4dc17d4259557bc74c733422e07aaf#egg=common-primitives"
}
],
"algorithm_types": [
......@@ -625,5 +625,5 @@
},
"structural_type": "common_primitives.xgboost_gbtree.XGBoostGBTreeClassifierPrimitive",
"description": "A XGBoost classifier using ``xgb.XGBoostClassifier`` with GBTree Boosting type.\n\nIt uses semantic types to determine which columns to operate on.\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": "b4792a67bc8f9eb49ba0cfe7d2e44b8152930019b9a97ade3f3467a9da46e585"
"digest": "43c941760360699625e997e212393928a5d65767ea12b696c8d8b664986b5fa3"
}
......@@ -13,7 +13,7 @@
"installation": [
{
"type": "PIP",
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]6f741202177ce23835b646ccc0189b35e9fef422#egg=common-primitives"
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]e41047e96a4dc17d4259557bc74c733422e07aaf#egg=common-primitives"
}
],
"python_path": "d3m.primitives.clustering.k_means.Common",
......@@ -215,5 +215,5 @@
},
"structural_type": "common_primitives.k_means.KMeans",
"description": "Example of a primitive wrapping an existing sklearn clustering algorithm.\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": "33c2569a8aec94b6f183c7d4d422bc2052447f8c5610fb3dda20f624cb0d8511"
"digest": "a4e1e1b4a919281290af1466907fac4b1160cc1da5a4763d8a657a879246d06b"
}
......@@ -14,7 +14,7 @@
"installation": [
{
"type": "PIP",
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]6f741202177ce23835b646ccc0189b35e9fef422#egg=common-primitives"
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]e41047e96a4dc17d4259557bc74c733422e07aaf#egg=common-primitives"
}
],
"algorithm_types": [
......@@ -211,5 +211,5 @@
},
"structural_type": "common_primitives.tabular_extractor.AnnotatedTabularExtractorPrimitive",
"description": "A primitive wrapping for MIT-LL slacker's ``AnnotatedTabularExtractor``.\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": "0376fec250c1a84fd574893a3e20fe62e94607b2c9eed2efa8f21d297fdfa553"
"digest": "54a8b7fecfa57d9a8dea439e30af70b7a1263a00fb74c4f46742d97f09676b34"
}
......@@ -43,7 +43,7 @@
},
{
"type": "PIP",
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]6f741202177ce23835b646ccc0189b35e9fef422#egg=common_primitives"
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]e41047e96a4dc17d4259557bc74c733422e07aaf#egg=common_primitives"
}
],
"algorithm_types": [
......@@ -261,5 +261,5 @@
},
"structural_type": "common_primitives.audio_reader.AudioReaderPrimitive",
"description": "A primitive which reads columns referencing audio files.\n\nEach column which has ``https://metadata.datadrivendiscovery.org/types/FileName`` semantic type\nand a valid media type (``audio/aiff``, ``audio/flac``, ``audio/ogg``, ``audio/wav``, ``audio/mpeg``)\nhas every filename read into an audio represented as a numpy array. By default the resulting column\nwith read arrays is appended to existing columns.\n\nThe shape of numpy arrays is S x C. S is the number of samples, C is the number of\nchannels in an audio (e.g., C = 1 for mono, C = 2 for stereo). dtype is float32.\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": "2336e381971ae1ffe447257a0409d9fc5a37a0963a5266348fe35f86dd553b21"
"digest": "dbf5dcb8e8c8e005732f895f1a44712a2b651c0dfddada523adad28ee337268a"
}
......@@ -18,7 +18,7 @@
"installation": [
{
"type": "PIP",
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]6f741202177ce23835b646ccc0189b35e9fef422#egg=common_primitives"
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]e41047e96a4dc17d4259557bc74c733422e07aaf#egg=common_primitives"
}
],
"algorithm_types": [
......@@ -232,5 +232,5 @@
},
"structural_type": "common_primitives.csv_reader.CSVReaderPrimitive",
"description": "A primitive which reads columns referencing CSV files.\n\nEach column which has ``https://metadata.datadrivendiscovery.org/types/FileName`` semantic type\nand a valid media type (``text/csv``) has every filename read as a pandas DataFrame. By default\nthe resulting column with read pandas DataFrames is appended to existing columns.\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": "d33cb2c964270bf37184137e9ec169101a10f82310b38b8087330aa10c691cd8"
"digest": "8dad7b68d5eeee869fd1e809bdf5efc1ac6ef2a275874b8d9087017031b1961a"
}
......@@ -19,7 +19,7 @@
"installation": [
{
"type": "PIP",
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]6f741202177ce23835b646ccc0189b35e9fef422#egg=common-primitives"
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]e41047e96a4dc17d4259557bc74c733422e07aaf#egg=common-primitives"
}
],
"python_path": "d3m.primitives.data_preprocessing.image_reader.Common",
......@@ -198,5 +198,5 @@
},
"structural_type": "common_primitives.image_reader.ImageReader",
"description": "Primitive which takes a list of file names to image files and returns a\nsingle Numpy array of shape:\n N x C x H x W\nwhere N is the number of images, C is the number of channels in an image\n(e.g., C = 1 for grayscale, C = 3 for RGB), H is the height, and W is the\nwidth. All images are expected to be of the same shape and channel\ncharacteristics.\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": "2930e833330e64ebd393111578c868243d87886ab51a644356f9159f89f799b8"
"digest": "ccd51d3a0c81bd483677f4fa274be83772e621a57321ba30ba067efa903e2384"
}
......@@ -20,7 +20,7 @@
"installation": [
{
"type": "PIP",
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]6f741202177ce23835b646ccc0189b35e9fef422#egg=common_primitives"
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]e41047e96a4dc17d4259557bc74c733422e07aaf#egg=common_primitives"
}
],
"algorithm_types": [
......@@ -235,5 +235,5 @@
},
"structural_type": "common_primitives.dataframe_image_reader.DataFrameImageReaderPrimitive",
"description": "A primitive which reads columns referencing image files.\n\nEach column which has ``https://metadata.datadrivendiscovery.org/types/FileName`` semantic type\nand a valid media type (``image/jpeg``, ``image/png``) has every filename read into an image\nrepresented as a numpy array. By default the resulting column with read arrays is appended\nto existing columns.\n\nThe shape of numpy arrays is H x W x C. C is the number of channels in an image\n(e.g., C = 1 for greyscale, C = 3 for RGB), H is the height, and W is the width.\ndtype is uint8.\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": "4f607ed80b459254b460fc8d4d0bd805de1c85f7ec17bdcd986cef061bb8a0e3"
"digest": "28b902d52b2bc3c82109c32ea862e6c9acf0e4a9977632634bb1db4a671a4048"
}
......@@ -14,7 +14,7 @@
"installation": [
{
"type": "PIP",
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]6f741202177ce23835b646ccc0189b35e9fef422#egg=common-primitives"
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]e41047e96a4dc17d4259557bc74c733422e07aaf#egg=common-primitives"
}
],
"algorithm_types": [
......@@ -262,5 +262,5 @@
},
"structural_type": "common_primitives.unseen_label_decoder.UnseenLabelDecoderPrimitive",
"description": "A primitive which inverses the label encoding by ``UnseenLabelEncoderPrimitive``.\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": "a8aea6867f6a569a3cbadcf27a0fe86cee519a8bd60e39625786ddc606d0a1e2"
"digest": "cfafdfbef5c003d870fdb2cf0193d2405accffdabb23b1fc7317edb554e01274"
}
......@@ -14,7 +14,7 @@
"installation": [
{
"type": "PIP",
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]6f741202177ce23835b646ccc0189b35e9fef422#egg=common-primitives"
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]e41047e96a4dc17d4259557bc74c733422e07aaf#egg=common-primitives"
}
],
"algorithm_types": [
......@@ -240,5 +240,5 @@
},
"structural_type": "common_primitives.unseen_label_encoder.UnseenLabelEncoderPrimitive",
"description": "Label encoder that can puts any unseen categories into a single category.\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": "943071cbebe517da54fcdf98edfc0464f2534c57de34cb40b1d3c0eb95faf268"
"digest": "6d0ec71de34012b21e98789e06b6fc61443f8b8a4bead00e8da8d1af86f934d7"
}
......@@ -17,7 +17,7 @@
"installation": [
{
"type": "PIP",
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]6f741202177ce23835b646ccc0189b35e9fef422#egg=common-primitives"
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]e41047e96a4dc17d4259557bc74c733422e07aaf#egg=common-primitives"
}
],
"python_path": "d3m.primitives.data_preprocessing.one_hot_encoder.MakerCommon",
......@@ -295,5 +295,5 @@
},
"structural_type": "common_primitives.one_hot_maker.OneHotMakerPrimitive",
"description": "Attempts to detect discrete values in data and convert these to a\none-hot embedding.\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": "c74a4e6a01182d860bff435660d94481880c73d806a5ccfcbf1a6f35fd7c2cff"
"digest": "6072d9a31f64172128b6f855665fee78af36cf204b6eacb6eb60c199ec31a7d3"
}
......@@ -14,7 +14,7 @@
"installation": [
{
"type": "PIP",
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]6f741202177ce23835b646ccc0189b35e9fef422#egg=common-primitives"
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]e41047e96a4dc17d4259557bc74c733422e07aaf#egg=common-primitives"
}
],
"algorithm_types": [
......@@ -257,5 +257,5 @@
},
"structural_type": "common_primitives.pandas_onehot_encoder.PandasOneHotEncoderPrimitive",
"description": "One-hot encoder using Pandas implementation.\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": "b7feedd7c7c668c3e481086b00445d30d33184aa3e2f88572bd601ba09496d0c"
"digest": "d2d61fc99a9547214b23e651a3ae51db0df574932cd3728195f693e32b14e56e"
}
{
"id": "d1b4c4b7-63ba-4ee6-ab30-035157cccf22",
"id": "cf73bb3d-170b-4ba9-9ead-3dd4b4524b61",
"version": "0.1.0",
"name": "Regex dataset filter",
"python_path": "d3m.primitives.data_preprocessing.regex_filter.DatasetCommon",
"python_path": "d3m.primitives.data_preprocessing.regex_filter.DataFrameCommon",
"source": {
"name": "common-primitives",
"contact": "mailto:[email protected]",
"uris": [
"https://gitlab.com/datadrivendiscovery/common-primitives/blob/master/common_primitives/dataset_regex_filter.py",
"https://gitlab.com/datadrivendiscovery/common-primitives/blob/master/common_primitives/regex_filter.py",
"https://gitlab.com/datadrivendiscovery/common-primitives.git"
]
},
"installation": [
{
"type": "PIP",
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]6f741202177ce23835b646ccc0189b35e9fef422#egg=common_primitives"
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]e41047e96a4dc17d4259557bc74c733422e07aaf#egg=common_primitives"
}
],
"algorithm_types": [
......@@ -22,12 +22,12 @@
],
"primitive_family": "DATA_PREPROCESSING",
"schema": "https://metadata.datadrivendiscovery.org/schemas/v0/primitive.json",
"original_python_path": "common_primitives.dataset_regex_filter.RegexFilterPrimitive",
"original_python_path": "common_primitives.regex_filter.RegexFilterPrimitive",
"primitive_code": {
"class_type_arguments": {
"Inputs": "d3m.container.dataset.Dataset",
"Outputs": "d3m.container.dataset.Dataset",
"Hyperparams": "common_primitives.dataset_regex_filter.Hyperparams",
"Inputs": "d3m.container.pandas.DataFrame",
"Outputs": "d3m.container.pandas.DataFrame",
"Hyperparams": "common_primitives.regex_filter.Hyperparams",
"Params": "NoneType"
},
"interfaces_version": "2019.5.8",
......@@ -36,15 +36,6 @@
"base.PrimitiveBase"
],
"hyperparams": {
"resource_id": {
"type": "d3m.metadata.hyperparams.Hyperparameter",
"default": null,
"structural_type": "typing.Union[NoneType, str]",
"semantic_types": [
"https://metadata.datadrivendiscovery.org/types/ControlParameter"
],
"description": "Resource ID of column to filter if there are multiple tabular resources inside a Dataset."
},
"column": {
"type": "d3m.metadata.hyperparams.Hyperparameter",
"default": -1,
......@@ -75,7 +66,7 @@
},
"arguments": {
"hyperparams": {
"type": "common_primitives.dataset_regex_filter.Hyperparams",
"type": "common_primitives.regex_filter.Hyperparams",
"kind": "RUNTIME"
},
"random_seed": {
......@@ -113,7 +104,7 @@
"kind": "RUNTIME"
},
"inputs": {
"type": "d3m.container.dataset.Dataset",
"type": "d3m.container.pandas.DataFrame",
"kind": "PIPELINE"
},
"params": {
......@@ -131,7 +122,7 @@
"type": "typing.Dict[str, typing.Union[d3m.metadata.base.Metadata, type]]"
},
"hyperparams": {
"type": "common_primitives.dataset_regex_filter.Hyperparams"
"type": "common_primitives.regex_filter.Hyperparams"
}
},
"returns": "typing.Union[NoneType, d3m.metadata.base.DataMetadata]",
......@@ -195,7 +186,7 @@
"timeout",
"iterations"
],
"returns": "d3m.primitive_interfaces.base.CallResult[d3m.container.dataset.Dataset]",
"returns": "d3m.primitive_interfaces.base.CallResult[d3m.container.pandas.DataFrame]",
"singleton": false,
"inputs_across_samples": [],
"description": "Produce primitive's best choice of the output for each of the inputs.\n\nThe output value should be wrapped inside ``CallResult`` object before returning.\n\nIn many cases producing an output is a quick operation in comparison with ``fit``, but not\nall cases are like that. For example, a primitive can start a potentially long optimization\nprocess to compute outputs. ``timeout`` and ``iterations`` can serve as a way for a caller\nto guide the length of this process.\n\nIdeally, a primitive should adapt its call to try to produce the best outputs possible\ninside the time allocated. If this is not possible and the primitive reaches the timeout\nbefore producing outputs, it should raise a ``TimeoutError`` exception to signal that the\ncall was unsuccessful in the given time. The state of the primitive after the exception\nshould be as the method call has never happened and primitive should continue to operate\nnormally. The purpose of ``timeout`` is to give opportunity to a primitive to cleanly\nmanage its state instead of interrupting execution from outside. Maintaining stable internal\nstate should have precedence over respecting the ``timeout`` (caller can terminate the\nmisbehaving primitive from outside anyway). If a longer ``timeout`` would produce\ndifferent outputs, then ``CallResult``'s ``has_finished`` should be set to ``False``.\n\nSome primitives have internal iterations (for example, optimization iterations).\nFor those, caller can provide how many of primitive's internal iterations\nshould a primitive do before returning outputs. Primitives should make iterations as\nsmall as reasonable. If ``iterations`` is ``None``, then there is no limit on\nhow many iterations the primitive should do and primitive should choose the best amount\nof iterations on its own (potentially controlled through hyper-parameters).\nIf ``iterations`` is a number, a primitive has to do those number of iterations,\nif possible. ``timeout`` should still be respected and potentially less iterations\ncan be done because of that. Primitives with internal iterations should make\n``CallResult`` contain correct values.\n\nFor primitives which do not have internal iterations, any value of ``iterations``\nmeans that they should run fully, respecting only ``timeout``.\n\nIf primitive should have been fitted before calling this method, but it has not been,\nprimitive should raise a ``PrimitiveNotFittedError`` exception.\n\nParameters\n----------\ninputs : Inputs\n The inputs of shape [num_inputs, ...].\ntimeout : float\n A maximum time this primitive should take to produce outputs during this method call, in seconds.\niterations : int\n How many of internal iterations should the primitive do.\n\nReturns\n-------\nCallResult[Outputs]\n The outputs of shape [num_inputs, ...] wrapped inside ``CallResult``."
......@@ -227,7 +218,7 @@
"temporary_directory": "typing.Union[NoneType, str]"
}
},
"structural_type": "common_primitives.dataset_regex_filter.RegexFilterPrimitive",
"description": "A primitive which filters rows from a dataset based on a regex applied to a given column.\nColumns are identified by index.\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": "9b9006163e9713d90691f9767b79cb8ac1770392272299dddd01a9045261e467"
"structural_type": "common_primitives.regex_filter.RegexFilterPrimitive",
"description": "A primitive which filters rows from a DataFrame based on a regex applied to a given column.\nColumns are identified by index.\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": "88cefdb4f42c48ad7fac63323e89ad9339e82c574e4adc2bf2e473e841832e1c"
}
......@@ -19,7 +19,7 @@
"installation": [
{
"type": "PIP",
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]6f741202177ce23835b646ccc0189b35e9fef422#egg=common_primitives"
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]e41047e96a4dc17d4259557bc74c733422e07aaf#egg=common_primitives"
}
],
"algorithm_types": [
......@@ -233,5 +233,5 @@
},
"structural_type": "common_primitives.text_reader.TextReaderPrimitive",
"description": "A primitive which reads columns referencing plain text files.\n\nEach column which has ``https://metadata.datadrivendiscovery.org/types/FileName`` semantic type\nand a valid media type (``text/plain``) has every filename read as a Python string. By default\nthe resulting column with read strings is appended to existing columns.\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": "96adb885c43315b40d0eb6013a0ab5f25385a165f2fd10bdec49ed72cde58004"
"digest": "a2988986bf352448b4bb6b8e26b7cbbea8f7ee2a12167c053d37fda55bf52c4f"
}
......@@ -20,7 +20,7 @@
"installation": [
{
"type": "PIP",
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]6f741202177ce23835b646ccc0189b35e9fef422#egg=common_primitives"
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]e41047e96a4dc17d4259557bc74c733422e07aaf#egg=common_primitives"
}
],
"algorithm_types": [
......@@ -235,5 +235,5 @@
},
"structural_type": "common_primitives.video_reader.VideoReaderPrimitive",
"description": "A primitive which reads columns referencing video files.\n\nEach column which has ``https://metadata.datadrivendiscovery.org/types/FileName`` semantic type\nand a valid media type (``video/mp4``, ``video/avi``) has every filename read into a video\nrepresented as a numpy array. By default the resulting column with read arrays is appended\nto existing columns.\n\nThe shape of numpy arrays is F x H x W x C. F is the number of frames, C is the number of\nchannels in a video (e.g., C = 1 for greyscale, C = 3 for RGB), H is the height, and W\nis the width. dtype is uint8.\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": "9c16564ec5393ef1380f696b660422d413b5bef7abd5bc67325f97fd38d6b523"
"digest": "4513e651feeb7ab1ea916e86c7e9586969c8e5bb8c9b040b2e2457969d04923f"
}
......@@ -14,7 +14,7 @@
"installation": [
{
"type": "PIP",
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]6f741202177ce23835b646ccc0189b35e9fef422#egg=common_primitives"
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]e41047e96a4dc17d4259557bc74c733422e07aaf#egg=common_primitives"
}
],
"algorithm_types": [
......@@ -227,5 +227,5 @@
},
"structural_type": "common_primitives.add_semantic_types.AddSemanticTypesPrimitive",
"description": "A primitive which adds semantic types for columns in a DataFrame.\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": "80aab44e4055f3bbfd5fe27111184857cc321f39a2413fb2d7c3111d07ca6b6b"
"digest": "2af50de44f464459850ac0d97d61f4f335d630172aea385d5986e1f91a24ce3b"
}
......@@ -14,7 +14,7 @@
"installation": [
{
"type": "PIP",
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]6f741202177ce23835b646ccc0189b35e9fef422#egg=common_primitives"
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]e41047e96a4dc17d4259557bc74c733422e07aaf#egg=common_primitives"
}
],
"algorithm_types": [
......@@ -239,5 +239,5 @@
},
"structural_type": "common_primitives.cast_to_type.CastToTypePrimitive",
"description": "A primitive which casts all columns it can cast (by default, controlled by ``use_columns``,\n``exclude_columns``) of an input DataFrame to a given structural type (dtype).\nIt removes columns which are not cast.\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": "057ced7193e68e18a72676416826c3ade249ffaf18ec3f3460944c768393543a"
"digest": "912014749db4e26642b417baa201b46e2574ae60010b981746967c56f4f3c598"
}
......@@ -14,7 +14,7 @@
"installation": [
{
"type": "PIP",
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]6f741202177ce23835b646ccc0189b35e9fef422#egg=common_primitives"
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]e41047e96a4dc17d4259557bc74c733422e07aaf#egg=common_primitives"
}
],
"algorithm_types": [
......@@ -300,5 +300,5 @@
},
"structural_type": "common_primitives.column_parser.ColumnParserPrimitive",
"description": "A primitive which parses strings into their parsed values.\n\nIt goes over all columns (by default, controlled by ``use_columns``, ``exclude_columns``)\nand checks those with structural type ``str`` if they have a semantic type suggesting\nthat they are a boolean value, categorical, integer, float, or time (by default,\ncontrolled by ``parse_semantic_types``). Categorical values are converted with\nhash encoding.\n\nWhat is returned is controlled by ``return_result`` and ``add_index_columns``.\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": "6deed8e4798fd219f4745c4459ba67036ed25dbb1d3a2459b24416cd4460951e"
"digest": "6938d5c23757c0b92281eb52ed73960443c087013a4e383bc75b63aa0a3e2058"
}
......@@ -14,7 +14,7 @@
"installation": [
{
"type": "PIP",
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]6f741202177ce23835b646ccc0189b35e9fef422#egg=common_primitives"
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]e41047e96a4dc17d4259557bc74c733422e07aaf#egg=common_primitives"
}
],
"algorithm_types": [
......@@ -234,5 +234,5 @@
},
"structural_type": "common_primitives.construct_predictions.ConstructPredictionsPrimitive",
"description": "A primitive which takes as input a DataFrame and outputs a DataFrame in Lincoln Labs predictions\nformat: first column is a d3mIndex column (and other primary index columns, e.g., for object detection\nproblem), and then predicted targets, each in its column, followed by optional confidence column(s).\n\nIt supports both input columns annotated with semantic types (``https://metadata.datadrivendiscovery.org/types/PrimaryKey``,\n``https://metadata.datadrivendiscovery.org/types/PrimaryMultiKey``, ``https://metadata.datadrivendiscovery.org/types/PredictedTarget``,\n``https://metadata.datadrivendiscovery.org/types/Confidence``), or trying to reconstruct metadata.\nThis is why the primitive takes also additional input of a reference DataFrame which should\nhave metadata to help reconstruct missing metadata. If metadata is missing, the primitive\nassumes that all ``inputs`` columns are predicted targets, without confidence column(s).\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": "bc09b1d3e656bbf5ed10a6b13382e8a52ffd18552f5803f28b25b79fbf25ca52"
"digest": "f3a3d19cb609c3c414d853ec895bc73638a361d507f1381470380ba37a7a5761"
}
......@@ -18,7 +18,7 @@
"installation": [
{
"type": "PIP",
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]6f741202177ce23835b646ccc0189b35e9fef422#egg=common_primitives"
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]e41047e96a4dc17d4259557bc74c733422e07aaf#egg=common_primitives"
}
],
"algorithm_types": [
......@@ -255,5 +255,5 @@
},
"structural_type": "common_primitives.cut_audio.CutAudioPrimitive",
"description": "A primitive which uses boundary columns to cut audio columns.\n\nIt uses ``http://schema.org/AudioObject`` and structural type ``container.ndarray` to\nfind columns with audio data.\n\nIt searches for boundary columns referencing them.\nBoundary columns are identified by ``https://metadata.datadrivendiscovery.org/types/Interval``,\n``https://metadata.datadrivendiscovery.org/types/IntervalStart`` and\n``https://metadata.datadrivendiscovery.org/types/IntervalEnd`` semantic types.\n\nIt requires that the audio dimension has ``sample_rate`` metadata set.\n\nBoundaries are rounded down to samples. Cut is done exclusive: not including the last sample.\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": "441a7f028a41908994bd8f55b1f69ea55ec1aa3fdb5431987e1d2abb8ff5c355"
"digest": "8a6e7f3d8af36d28050006ebcae67ec1972f74254b1e0e8d5feee707b04b8e33"
}
......@@ -14,7 +14,7 @@
"installation": [
{
"type": "PIP",
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]6f741202177ce23835b646ccc0189b35e9fef422#egg=common_primitives"
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]e41047e96a4dc17d4259557bc74c733422e07aaf#egg=common_primitives"
}
],
"algorithm_types": [
......@@ -192,5 +192,5 @@
},
"structural_type": "common_primitives.dataframe_to_list.DataFrameToListPrimitive",
"description": "A primitive which converts a pandas dataframe into a list of rows.\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": "f1a3ebf7df5a92467371b3b4dbef7585ff5c6ff81b406ef2146cd337605378b9"
"digest": "c6caf97748c3e0b40372f5368a9f76420105395ae83c1dee6ecedd75600c260b"
}
......@@ -14,7 +14,7 @@
"installation": [
{
"type": "PIP",
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]6f741202177ce23835b646ccc0189b35e9fef422#egg=common_primitives"
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]e41047e96a4dc17d4259557bc74c733422e07aaf#egg=common_primitives"
}
],
"algorithm_types": [
......@@ -192,5 +192,5 @@
},
"structural_type": "common_primitives.dataframe_to_ndarray.DataFrameToNDArrayPrimitive",
"description": "A primitive which converts a pandas dataframe into a numpy array.\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": "e7502a4572c150eff2c45f6f827d2bd12cab03ff8a1dcd74f6205ae2f653a1cb"
"digest": "673ecfe3fdf99a5b214395bc23231d6f2b03e6ce6ee32e2e272a89e7f9552ba8"
}
......@@ -14,7 +14,7 @@
"installation": [
{
"type": "PIP",
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]6f741202177ce23835b646ccc0189b35e9fef422#egg=common_primitives"
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]e41047e96a4dc17d4259557bc74c733422e07aaf#egg=common_primitives"
}
],
"algorithm_types": [
......@@ -202,5 +202,5 @@
},
"structural_type": "common_primitives.dataset_to_dataframe.DatasetToDataFramePrimitive",
"description": "A primitive which extracts a DataFrame out of a Dataset.\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": "748b3f6c9d26a4323a34a6da464c5de3dcab0d784a127819106acef1466e9550"
"digest": "db27f0d242ff948ac1e25aeb18fcf3404be636d82013fa58dee3aac34500f48e"
}
......@@ -14,7 +14,7 @@
"installation": [
{
"type": "PIP",
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]6f741202177ce23835b646ccc0189b35e9fef422#egg=common_primitives"
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]e41047e96a4dc17d4259557bc74c733422e07aaf#egg=common_primitives"
}
],
"algorithm_types": [
......@@ -204,5 +204,5 @@
},
"structural_type": "common_primitives.denormalize.DenormalizePrimitive",
"description": "A primitive which converts a Dataset with multiple tabular resources into a Dataset with only one tabular resource,\nbased on known relations between tabular resources. Any resource which can be joined is joined (thus the resource\nitself is removed), and other resources are by default discarded (controlled by ``discard_resources`` hyper-parameter).\n\nIf hyper-parameter ``recursive`` is set to ``True``, the primitive will join tables recursively. For example,\nif table 1 (main table) has a foreign key that points to table 2, and table 2 has a foreign key that points to table 3,\nthen after table 2 is jointed into table 1, table 1 will have a foreign key that points to table 3. So now the\nprimitive continues to join table 3 into the main table.\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": "3cf3edfbdae9bb9c5ab11dbb6b76eb6c031a061c269d906f88cb232170e0a667"
"digest": "c9b20f7259a8a8066fe19f50e7dfb60a742c4ff6d222ad4b012f292bd44e7716"
}
......@@ -14,7 +14,7 @@
"installation": [
{
"type": "PIP",
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]6f741202177ce23835b646ccc0189b35e9fef422#egg=common_primitives"
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]e41047e96a4dc17d4259557bc74c733422e07aaf#egg=common_primitives"
}
],
"algorithm_types": [
......@@ -210,5 +210,5 @@
},
"structural_type": "common_primitives.extract_columns.ExtractColumnsPrimitive",
"description": "A primitive which extracts a fixed list of columns.\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": "47ace2bf97ccf5c3fe361fddfb6163ae71c200f6e229f80dde4e6af5d8f935c0"
"digest": "8a7842fe25cc4d392a599ecadd935894b756a5b9b16f3c27667a342697c32708"
}
......@@ -14,7 +14,7 @@
"installation": [
{
"type": "PIP",
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]6f741202177ce23835b646ccc0189b35e9fef422#egg=common_primitives"
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]e41047e96a4dc17d4259557bc74c733422e07aaf#egg=common_primitives"
}
],
"algorithm_types": [
......@@ -246,5 +246,5 @@
},
"structural_type": "common_primitives.extract_columns_semantic_types.ExtractColumnsBySemanticTypesPrimitive",
"description": "A primitive which extracts columns from input data based on semantic types provided.\nColumns which match any of the listed semantic types are extracted.\n\nIf you want to extract only attributes, you can use ``https://metadata.datadrivendiscovery.org/types/Attribute``\nsemantic type (also default).\n\nFor real targets (not suggested targets) use ``https://metadata.datadrivendiscovery.org/types/Target``.\nFor this to work, columns have to be are marked as targets by the TA2 in a dataset before passing the dataset\nthrough a pipeline. Or something else has to mark them at some point in a pipeline.\n\nIt uses ``use_columns`` and ``exclude_columns`` to control which columns it considers.\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": "e1ef694b5642f037531be4f9a9c29aef62466b8e61dd8e174ccd673977761abb"
"digest": "60962a5d36beb1e0bb872fbafc3db4cb83b6a5185136e9c2219183a2bef20f87"
}
......@@ -14,7 +14,7 @@
"installation": [
{
"type": "PIP",
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]6f741202177ce23835b646ccc0189b35e9fef422#egg=common_primitives"
"package_uri": "git+https://gitlab.com/datadrivendiscovery/[email protected]e41047e96a4dc17d4259557bc74c733422e07aaf#egg=common_primitives"
}