diff --git a/byudml/__init__.py b/byudml/__init__.py index e2f45ae..7c9e66e 100644 --- a/byudml/__init__.py +++ b/byudml/__init__.py @@ -1 +1 @@ -__version__ = '0.6.5' +__version__ = '0.6.6' diff --git a/byudml/metafeature_extraction/metafeature_extraction.py b/byudml/metafeature_extraction/metafeature_extraction.py index e1bac93..2941861 100644 --- a/byudml/metafeature_extraction/metafeature_extraction.py +++ b/byudml/metafeature_extraction/metafeature_extraction.py @@ -14,7 +14,7 @@ from byudml import __version__ as __package_version__ -__primitive_version__ = '0.4.3' +__primitive_version__ = '0.4.4' Inputs = DataFrame Outputs = DataFrame diff --git a/pipelines/metafeature_extractor/3013ad40-7c51-4991-b0fb-dbec65607979.json b/pipelines/metafeature_extractor/3013ad40-7c51-4991-b0fb-dbec65607979.json index 5e952ae..f2d7adc 100755 --- a/pipelines/metafeature_extractor/3013ad40-7c51-4991-b0fb-dbec65607979.json +++ b/pipelines/metafeature_extractor/3013ad40-7c51-4991-b0fb-dbec65607979.json @@ -1,7 +1,7 @@ { "id": "3013ad40-7c51-4991-b0fb-dbec65607979", "schema": "https://metadata.datadrivendiscovery.org/schemas/v0/pipeline.json", - "created": "2019-05-31T22:03:55.635611Z", + "created": "2019-05-31T22:13:47.499466Z", "inputs": [ { "name": "inputs" @@ -58,10 +58,10 @@ "type": "PRIMITIVE", "primitive": { "id": "28d12214-8cb0-4ac0-8946-d31fcbcd4142", - "version": "0.4.3", + "version": "0.4.4", "python_path": "d3m.primitives.metalearning.metafeature_extractor.BYU", "name": "Dataset Metafeature Extraction", - "digest": "b6de54719221d73a68324d88556ed60db38743071b6ea2f5185ce4419c3d512a" + "digest": "0c36cd6f0ac9413969535bb0347487df6634e2e954f58cdb24f62785da9fc091" }, "arguments": { "inputs": { diff --git a/pipelines/metafeature_extractor/b32b9af1-34b4-437b-ad83-650f7df10acb.json b/pipelines/metafeature_extractor/b32b9af1-34b4-437b-ad83-650f7df10acb.json index cab03c2..b62a19c 100755 --- a/pipelines/metafeature_extractor/b32b9af1-34b4-437b-ad83-650f7df10acb.json +++ b/pipelines/metafeature_extractor/b32b9af1-34b4-437b-ad83-650f7df10acb.json @@ -1,7 +1,7 @@ { "id": "b32b9af1-34b4-437b-ad83-650f7df10acb", "schema": "https://metadata.datadrivendiscovery.org/schemas/v0/pipeline.json", - "created": "2019-05-31T22:03:55.404180Z", + "created": "2019-05-31T22:13:47.275545Z", "inputs": [ { "name": "inputs" @@ -58,10 +58,10 @@ "type": "PRIMITIVE", "primitive": { "id": "28d12214-8cb0-4ac0-8946-d31fcbcd4142", - "version": "0.4.3", + "version": "0.4.4", "python_path": "d3m.primitives.metalearning.metafeature_extractor.BYU", "name": "Dataset Metafeature Extraction", - "digest": "b6de54719221d73a68324d88556ed60db38743071b6ea2f5185ce4419c3d512a" + "digest": "0c36cd6f0ac9413969535bb0347487df6634e2e954f58cdb24f62785da9fc091" }, "arguments": { "inputs": { diff --git a/pipelines/random_sampling_imputer/74f5ccb1-053a-46cf-ad7f-005f67a15652.json b/pipelines/random_sampling_imputer/74f5ccb1-053a-46cf-ad7f-005f67a15652.json index 9d3bcca..8582bdc 100755 --- a/pipelines/random_sampling_imputer/74f5ccb1-053a-46cf-ad7f-005f67a15652.json +++ b/pipelines/random_sampling_imputer/74f5ccb1-053a-46cf-ad7f-005f67a15652.json @@ -1,7 +1,7 @@ { "id": "74f5ccb1-053a-46cf-ad7f-005f67a15652", "schema": "https://metadata.datadrivendiscovery.org/schemas/v0/pipeline.json", - "created": "2019-05-31T22:03:55.513808Z", + "created": "2019-05-31T22:13:47.378113Z", "inputs": [ { "name": "inputs" @@ -117,7 +117,7 @@ "version": "0.1.4", "python_path": "d3m.primitives.data_preprocessing.random_sampling_imputer.BYU", "name": "Random Sampling Imputer", - "digest": "231d95afe182c5fea17fcbd446eaa88c2725a0f5cdbcf8a7cd9519600087d5bd" + "digest": "5588dc61d64ae0442b07f51dbe6504bb340aeabe1e8d06b0e85bb95eaf71c041" }, "arguments": { "inputs": { diff --git a/pipelines/random_sampling_imputer/f4fe3fcc-45fe-4c85-8845-549e2f466f21.json b/pipelines/random_sampling_imputer/f4fe3fcc-45fe-4c85-8845-549e2f466f21.json index 831be9a..9465fd2 100755 --- a/pipelines/random_sampling_imputer/f4fe3fcc-45fe-4c85-8845-549e2f466f21.json +++ b/pipelines/random_sampling_imputer/f4fe3fcc-45fe-4c85-8845-549e2f466f21.json @@ -1,7 +1,7 @@ { "id": "f4fe3fcc-45fe-4c85-8845-549e2f466f21", "schema": "https://metadata.datadrivendiscovery.org/schemas/v0/pipeline.json", - "created": "2019-05-31T22:03:54.979333Z", + "created": "2019-05-31T22:13:46.827460Z", "inputs": [ { "name": "inputs" @@ -117,7 +117,7 @@ "version": "0.1.4", "python_path": "d3m.primitives.data_preprocessing.random_sampling_imputer.BYU", "name": "Random Sampling Imputer", - "digest": "231d95afe182c5fea17fcbd446eaa88c2725a0f5cdbcf8a7cd9519600087d5bd" + "digest": "5588dc61d64ae0442b07f51dbe6504bb340aeabe1e8d06b0e85bb95eaf71c041" }, "arguments": { "inputs": { diff --git a/primitive_jsons/imputer/primitive.json b/primitive_jsons/imputer/primitive.json index d971355..20b82ae 100755 --- a/primitive_jsons/imputer/primitive.json +++ b/primitive_jsons/imputer/primitive.json @@ -3,7 +3,7 @@ "IMPUTATION" ], "description": "This imputes missing values in a DataFrame by sampling known values from\neach column independently. If the training data has no known values in a\nparticular column, no values are imputed.\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": "231d95afe182c5fea17fcbd446eaa88c2725a0f5cdbcf8a7cd9519600087d5bd", + "digest": "5588dc61d64ae0442b07f51dbe6504bb340aeabe1e8d06b0e85bb95eaf71c041", "effects": [ "NO_MISSING_VALUES" ], @@ -12,7 +12,7 @@ { "package": "byudml", "type": "PIP", - "version": "0.6.5" + "version": "0.6.6" } ], "location_uris": [ diff --git a/primitive_jsons/metafeature_extractor/primitive.json b/primitive_jsons/metafeature_extractor/primitive.json index fd75844..628e2c2 100755 --- a/primitive_jsons/metafeature_extractor/primitive.json +++ b/primitive_jsons/metafeature_extractor/primitive.json @@ -6,13 +6,13 @@ "STATISTICAL_METAFEATURE_EXTRACTION" ], "description": "A primitive which takes a DataFrame and computes metafeatures on the data.\nTarget column is identified by being labeled with 'https://metadata.datadrivendiscovery.org/types/TrueTarget' in 'semantic_types' metadata.\nOtherwise primitive assumes there is no target column and only metafeatures that do not involve targets are returned.\nIf DataFrame metadata does not include semantic type labels for each column, columns will be classified as CATEGORICAL or NUMERIC according\nto their dtype: int and float are NUMERIC, all others are CATEGORICAL.\nMetafeatures are stored in the metadata object of the DataFrame, and the DataFrame itself is returned unchanged\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": "b6de54719221d73a68324d88556ed60db38743071b6ea2f5185ce4419c3d512a", + "digest": "0c36cd6f0ac9413969535bb0347487df6634e2e954f58cdb24f62785da9fc091", "id": "28d12214-8cb0-4ac0-8946-d31fcbcd4142", "installation": [ { "package": "byudml", "type": "PIP", - "version": "0.6.5" + "version": "0.6.6" } ], "location_uris": [ @@ -210,5 +210,5 @@ ] }, "structural_type": "byudml.metafeature_extraction.metafeature_extraction.MetafeatureExtractor", - "version": "0.4.3" + "version": "0.4.4" } \ No newline at end of file diff --git a/run_tests.sh b/run_tests.sh index a5d6b93..f5bdd16 100755 --- a/run_tests.sh +++ b/run_tests.sh @@ -3,8 +3,8 @@ pip3 install . mv byudml tmp_byudml reset +python3 primitive_jsons/generate_primitive_jsons.py +python3 pipelines/generate_pipelines.py python3 run_tests.py -# python3 pipelines/generate_pipelines.py -# python3 primitive_jsons/generate_primitive_jsons.py mv tmp_byudml byudml pip3 uninstall -y byudml > /dev/null