Commit bcaa8540 authored by David M Johnson's avatar David M Johnson

Michigan bugfixing.

parent d4efadc1
{ {
"id": "e5f15b7b-832f-404c-9d79-511c6c854653", "id": "e71678ce-b182-4f37-8217-df0be3b299e3",
"schema": "https://metadata.datadrivendiscovery.org/schemas/v0/pipeline.json", "schema": "https://metadata.datadrivendiscovery.org/schemas/v0/pipeline.json",
"created": "2019-06-18T15:38:15.578853Z", "created": "2019-06-19T03:18:40.873932Z",
"inputs": [ "inputs": [
{ {
"name": "inputs" "name": "inputs"
...@@ -21,7 +21,7 @@ ...@@ -21,7 +21,7 @@
"version": "0.3.0", "version": "0.3.0",
"python_path": "d3m.primitives.data_transformation.dataset_to_dataframe.Common", "python_path": "d3m.primitives.data_transformation.dataset_to_dataframe.Common",
"name": "Extract a DataFrame from a Dataset", "name": "Extract a DataFrame from a Dataset",
"digest": "4e971e251e548f1188c280c60f4e2f9a460865f21bcfd341114270bdafa4c4dc" "digest": "45f8322097914f9c95c4f9a8224d02db5d79b7166c74115e2eea7b23ccc13510"
}, },
"arguments": { "arguments": {
"inputs": { "inputs": {
...@@ -42,7 +42,7 @@ ...@@ -42,7 +42,7 @@
"version": "0.5.0", "version": "0.5.0",
"python_path": "d3m.primitives.data_transformation.column_parser.DataFrameCommon", "python_path": "d3m.primitives.data_transformation.column_parser.DataFrameCommon",
"name": "Parses strings into their types", "name": "Parses strings into their types",
"digest": "b14b7bcd1a54ee658a7093658eb4b6c9a1b029698f981fec7ad26408a0b5cf64" "digest": "d41ad0c56ef55a233b21f4a4d8df1ac782aca7a78ef98dbfb72215690b3e9850"
}, },
"arguments": { "arguments": {
"inputs": { "inputs": {
...@@ -63,7 +63,7 @@ ...@@ -63,7 +63,7 @@
"version": "0.3.0", "version": "0.3.0",
"python_path": "d3m.primitives.data_transformation.extract_columns_by_semantic_types.DataFrameCommon", "python_path": "d3m.primitives.data_transformation.extract_columns_by_semantic_types.DataFrameCommon",
"name": "Extracts columns by semantic type", "name": "Extracts columns by semantic type",
"digest": "ea473cf02c17ae9d2610be746cb726d91991bc6e39c0c85d1b1550eacd1581be" "digest": "e91e0f7569ad53b6d4b8c01641f80fb0aa764b5dd3ae71dd2fbb433fa62c7f81"
}, },
"arguments": { "arguments": {
"inputs": { "inputs": {
...@@ -92,7 +92,7 @@ ...@@ -92,7 +92,7 @@
"version": "0.1.0", "version": "0.1.0",
"python_path": "d3m.primitives.data_transformation.dataframe_to_ndarray.Common", "python_path": "d3m.primitives.data_transformation.dataframe_to_ndarray.Common",
"name": "DataFrame to ndarray converter", "name": "DataFrame to ndarray converter",
"digest": "766360bfe2af3b5a9f94ff3d5edbafb6ac8a334f56660bdddfdea70c7542c209" "digest": "acd6cfebb0d83da23e3b93034471ca6f04fc2478d2105e13518d6c76c850b676"
}, },
"arguments": { "arguments": {
"inputs": { "inputs": {
...@@ -113,7 +113,7 @@ ...@@ -113,7 +113,7 @@
"version": "0.0.5", "version": "0.0.5",
"python_path": "d3m.primitives.clustering.ekss.Umich", "python_path": "d3m.primitives.clustering.ekss.Umich",
"name": "EKSS", "name": "EKSS",
"digest": "5c30c739d338f3174bb8566efc6baf8395a4186c12e9c72b95afa19f23a76c29" "digest": "dd4b50da6cade6e2835ef617a8edeae39ce0c7209d616f5f501efcdaac7ea73d"
}, },
"arguments": { "arguments": {
"inputs": { "inputs": {
...@@ -140,7 +140,7 @@ ...@@ -140,7 +140,7 @@
"version": "0.1.0", "version": "0.1.0",
"python_path": "d3m.primitives.data_transformation.ndarray_to_dataframe.Common", "python_path": "d3m.primitives.data_transformation.ndarray_to_dataframe.Common",
"name": "ndarray to Dataframe converter", "name": "ndarray to Dataframe converter",
"digest": "ec7afdcc833310158d8f4e7d09ae193655278a1ab4263b2233eb1146dd874ef7" "digest": "7228a01faeab36d201bbe44a87c8b256d91dd03a458c0d589116c8db3f022bb4"
}, },
"arguments": { "arguments": {
"inputs": { "inputs": {
...@@ -161,7 +161,7 @@ ...@@ -161,7 +161,7 @@
"version": "0.3.0", "version": "0.3.0",
"python_path": "d3m.primitives.data_transformation.construct_predictions.DataFrameCommon", "python_path": "d3m.primitives.data_transformation.construct_predictions.DataFrameCommon",
"name": "Construct pipeline predictions output", "name": "Construct pipeline predictions output",
"digest": "0c744dd6ea7eafb9c143f70b40452c6238bc6cab06a070d50868822f904388d3" "digest": "53087aaa6baf0ccc96b6525ca5b79fd4e51b4cce996ab39773a9b0b3e746bf05"
}, },
"arguments": { "arguments": {
"inputs": { "inputs": {
...@@ -180,5 +180,5 @@ ...@@ -180,5 +180,5 @@
] ]
} }
], ],
"digest": "2e0b3109e97d3cbb70e0d6511bedb67c30a523483fe95bdf4e4bdf13ee736d85" "digest": "d18181c1d3942add499a6ee916404877bb4cc5e3853b4cf0e95d482649411c49"
} }
\ No newline at end of file
...@@ -21,7 +21,7 @@ ...@@ -21,7 +21,7 @@
"installation": [ "installation": [
{ {
"type": "PIP", "type": "PIP",
"package_uri": "git+https://github.com/dvdmjohnson/d3m_michigan_primitives.git@1229b579b02a6c84b137f2d72c188da14af563c6#egg=spider" "package_uri": "git+https://github.com/dvdmjohnson/d3m_michigan_primitives.git@98e685e0d16f754caedd1e50afbc1e0d0aa28842#egg=spider"
}, },
{ {
"type": "UBUNTU", "type": "UBUNTU",
...@@ -284,5 +284,5 @@ ...@@ -284,5 +284,5 @@
} }
}, },
"structural_type": "spider.cluster.ekss.ekss.EKSS", "structural_type": "spider.cluster.ekss.ekss.EKSS",
"digest": "5c30c739d338f3174bb8566efc6baf8395a4186c12e9c72b95afa19f23a76c29" "digest": "dd4b50da6cade6e2835ef617a8edeae39ce0c7209d616f5f501efcdaac7ea73d"
} }
{ {
"id": "0f67a73a-9df8-4455-930e-9f5c8b8e4c89", "id": "e91e3130-73f7-4be2-8b2c-164dc7594173",
"schema": "https://metadata.datadrivendiscovery.org/schemas/v0/pipeline.json", "schema": "https://metadata.datadrivendiscovery.org/schemas/v0/pipeline.json",
"created": "2019-06-18T15:38:13.288347Z", "created": "2019-06-19T03:18:38.554743Z",
"inputs": [ "inputs": [
{ {
"name": "inputs" "name": "inputs"
...@@ -21,7 +21,7 @@ ...@@ -21,7 +21,7 @@
"version": "0.3.0", "version": "0.3.0",
"python_path": "d3m.primitives.data_transformation.dataset_to_dataframe.Common", "python_path": "d3m.primitives.data_transformation.dataset_to_dataframe.Common",
"name": "Extract a DataFrame from a Dataset", "name": "Extract a DataFrame from a Dataset",
"digest": "4e971e251e548f1188c280c60f4e2f9a460865f21bcfd341114270bdafa4c4dc" "digest": "45f8322097914f9c95c4f9a8224d02db5d79b7166c74115e2eea7b23ccc13510"
}, },
"arguments": { "arguments": {
"inputs": { "inputs": {
...@@ -42,7 +42,7 @@ ...@@ -42,7 +42,7 @@
"version": "0.5.0", "version": "0.5.0",
"python_path": "d3m.primitives.data_transformation.column_parser.DataFrameCommon", "python_path": "d3m.primitives.data_transformation.column_parser.DataFrameCommon",
"name": "Parses strings into their types", "name": "Parses strings into their types",
"digest": "b14b7bcd1a54ee658a7093658eb4b6c9a1b029698f981fec7ad26408a0b5cf64" "digest": "d41ad0c56ef55a233b21f4a4d8df1ac782aca7a78ef98dbfb72215690b3e9850"
}, },
"arguments": { "arguments": {
"inputs": { "inputs": {
...@@ -63,7 +63,7 @@ ...@@ -63,7 +63,7 @@
"version": "0.3.0", "version": "0.3.0",
"python_path": "d3m.primitives.data_transformation.extract_columns_by_semantic_types.DataFrameCommon", "python_path": "d3m.primitives.data_transformation.extract_columns_by_semantic_types.DataFrameCommon",
"name": "Extracts columns by semantic type", "name": "Extracts columns by semantic type",
"digest": "ea473cf02c17ae9d2610be746cb726d91991bc6e39c0c85d1b1550eacd1581be" "digest": "e91e0f7569ad53b6d4b8c01641f80fb0aa764b5dd3ae71dd2fbb433fa62c7f81"
}, },
"arguments": { "arguments": {
"inputs": { "inputs": {
...@@ -92,7 +92,7 @@ ...@@ -92,7 +92,7 @@
"version": "0.1.0", "version": "0.1.0",
"python_path": "d3m.primitives.data_transformation.dataframe_to_ndarray.Common", "python_path": "d3m.primitives.data_transformation.dataframe_to_ndarray.Common",
"name": "DataFrame to ndarray converter", "name": "DataFrame to ndarray converter",
"digest": "766360bfe2af3b5a9f94ff3d5edbafb6ac8a334f56660bdddfdea70c7542c209" "digest": "acd6cfebb0d83da23e3b93034471ca6f04fc2478d2105e13518d6c76c850b676"
}, },
"arguments": { "arguments": {
"inputs": { "inputs": {
...@@ -113,7 +113,7 @@ ...@@ -113,7 +113,7 @@
"version": "0.0.5", "version": "0.0.5",
"python_path": "d3m.primitives.clustering.kss.Umich", "python_path": "d3m.primitives.clustering.kss.Umich",
"name": "KSS", "name": "KSS",
"digest": "fdf32314fd3a56c5f5176ab10366be421865add54c4044ac10765b6d28aa5845" "digest": "a7dc27c6d7ab54183442b8e3d520777c9fc6ce8ad54c0fb9cb327a3d4361f67d"
}, },
"arguments": { "arguments": {
"inputs": { "inputs": {
...@@ -144,7 +144,7 @@ ...@@ -144,7 +144,7 @@
"version": "0.1.0", "version": "0.1.0",
"python_path": "d3m.primitives.data_transformation.ndarray_to_dataframe.Common", "python_path": "d3m.primitives.data_transformation.ndarray_to_dataframe.Common",
"name": "ndarray to Dataframe converter", "name": "ndarray to Dataframe converter",
"digest": "ec7afdcc833310158d8f4e7d09ae193655278a1ab4263b2233eb1146dd874ef7" "digest": "7228a01faeab36d201bbe44a87c8b256d91dd03a458c0d589116c8db3f022bb4"
}, },
"arguments": { "arguments": {
"inputs": { "inputs": {
...@@ -165,7 +165,7 @@ ...@@ -165,7 +165,7 @@
"version": "0.3.0", "version": "0.3.0",
"python_path": "d3m.primitives.data_transformation.construct_predictions.DataFrameCommon", "python_path": "d3m.primitives.data_transformation.construct_predictions.DataFrameCommon",
"name": "Construct pipeline predictions output", "name": "Construct pipeline predictions output",
"digest": "0c744dd6ea7eafb9c143f70b40452c6238bc6cab06a070d50868822f904388d3" "digest": "53087aaa6baf0ccc96b6525ca5b79fd4e51b4cce996ab39773a9b0b3e746bf05"
}, },
"arguments": { "arguments": {
"inputs": { "inputs": {
...@@ -184,5 +184,5 @@ ...@@ -184,5 +184,5 @@
] ]
} }
], ],
"digest": "64a31a4f6e930ab58f0f9a2e7423b6fd9c41c84a05b81e5d7242d09790050242" "digest": "a53ec1ca05d5089d8faaa42d962d18629c54225fafbffce1bf167c639a8caa6d"
} }
\ No newline at end of file
...@@ -20,7 +20,7 @@ ...@@ -20,7 +20,7 @@
"installation": [ "installation": [
{ {
"type": "PIP", "type": "PIP",
"package_uri": "git+https://github.com/dvdmjohnson/d3m_michigan_primitives.git@1229b579b02a6c84b137f2d72c188da14af563c6#egg=spider" "package_uri": "git+https://github.com/dvdmjohnson/d3m_michigan_primitives.git@98e685e0d16f754caedd1e50afbc1e0d0aa28842#egg=spider"
}, },
{ {
"type": "UBUNTU", "type": "UBUNTU",
...@@ -241,5 +241,5 @@ ...@@ -241,5 +241,5 @@
} }
}, },
"structural_type": "spider.cluster.kss.kss.KSS", "structural_type": "spider.cluster.kss.kss.KSS",
"digest": "fdf32314fd3a56c5f5176ab10366be421865add54c4044ac10765b6d28aa5845" "digest": "a7dc27c6d7ab54183442b8e3d520777c9fc6ce8ad54c0fb9cb327a3d4361f67d"
} }
{ {
"id": "0348e5f1-f0b3-42bb-8921-af26db8cb4d6", "id": "ba6ec74c-1ae5-4059-be4f-ced4f01c8c1a",
"schema": "https://metadata.datadrivendiscovery.org/schemas/v0/pipeline.json", "schema": "https://metadata.datadrivendiscovery.org/schemas/v0/pipeline.json",
"created": "2019-06-18T15:38:17.794620Z", "created": "2019-06-19T03:18:43.166778Z",
"inputs": [ "inputs": [
{ {
"name": "inputs" "name": "inputs"
...@@ -21,7 +21,7 @@ ...@@ -21,7 +21,7 @@
"version": "0.3.0", "version": "0.3.0",
"python_path": "d3m.primitives.data_transformation.dataset_to_dataframe.Common", "python_path": "d3m.primitives.data_transformation.dataset_to_dataframe.Common",
"name": "Extract a DataFrame from a Dataset", "name": "Extract a DataFrame from a Dataset",
"digest": "4e971e251e548f1188c280c60f4e2f9a460865f21bcfd341114270bdafa4c4dc" "digest": "45f8322097914f9c95c4f9a8224d02db5d79b7166c74115e2eea7b23ccc13510"
}, },
"arguments": { "arguments": {
"inputs": { "inputs": {
...@@ -42,7 +42,7 @@ ...@@ -42,7 +42,7 @@
"version": "0.5.0", "version": "0.5.0",
"python_path": "d3m.primitives.data_transformation.column_parser.DataFrameCommon", "python_path": "d3m.primitives.data_transformation.column_parser.DataFrameCommon",
"name": "Parses strings into their types", "name": "Parses strings into their types",
"digest": "b14b7bcd1a54ee658a7093658eb4b6c9a1b029698f981fec7ad26408a0b5cf64" "digest": "d41ad0c56ef55a233b21f4a4d8df1ac782aca7a78ef98dbfb72215690b3e9850"
}, },
"arguments": { "arguments": {
"inputs": { "inputs": {
...@@ -63,7 +63,7 @@ ...@@ -63,7 +63,7 @@
"version": "0.3.0", "version": "0.3.0",
"python_path": "d3m.primitives.data_transformation.extract_columns_by_semantic_types.DataFrameCommon", "python_path": "d3m.primitives.data_transformation.extract_columns_by_semantic_types.DataFrameCommon",
"name": "Extracts columns by semantic type", "name": "Extracts columns by semantic type",
"digest": "ea473cf02c17ae9d2610be746cb726d91991bc6e39c0c85d1b1550eacd1581be" "digest": "e91e0f7569ad53b6d4b8c01641f80fb0aa764b5dd3ae71dd2fbb433fa62c7f81"
}, },
"arguments": { "arguments": {
"inputs": { "inputs": {
...@@ -92,7 +92,7 @@ ...@@ -92,7 +92,7 @@
"version": "0.1.0", "version": "0.1.0",
"python_path": "d3m.primitives.data_transformation.dataframe_to_ndarray.Common", "python_path": "d3m.primitives.data_transformation.dataframe_to_ndarray.Common",
"name": "DataFrame to ndarray converter", "name": "DataFrame to ndarray converter",
"digest": "766360bfe2af3b5a9f94ff3d5edbafb6ac8a334f56660bdddfdea70c7542c209" "digest": "acd6cfebb0d83da23e3b93034471ca6f04fc2478d2105e13518d6c76c850b676"
}, },
"arguments": { "arguments": {
"inputs": { "inputs": {
...@@ -113,7 +113,7 @@ ...@@ -113,7 +113,7 @@
"version": "0.0.5", "version": "0.0.5",
"python_path": "d3m.primitives.clustering.ssc_admm.Umich", "python_path": "d3m.primitives.clustering.ssc_admm.Umich",
"name": "SSC_ADMM", "name": "SSC_ADMM",
"digest": "f7621a0cad0d209adb11404aea6b0c271b40abcbf433003ca4b7a65988c37c0e" "digest": "26d325ba630b7f343d9dc8bbc59d0c1700a64b45e10b85603560c126a01964f5"
}, },
"arguments": { "arguments": {
"inputs": { "inputs": {
...@@ -140,7 +140,7 @@ ...@@ -140,7 +140,7 @@
"version": "0.1.0", "version": "0.1.0",
"python_path": "d3m.primitives.data_transformation.ndarray_to_dataframe.Common", "python_path": "d3m.primitives.data_transformation.ndarray_to_dataframe.Common",
"name": "ndarray to Dataframe converter", "name": "ndarray to Dataframe converter",
"digest": "ec7afdcc833310158d8f4e7d09ae193655278a1ab4263b2233eb1146dd874ef7" "digest": "7228a01faeab36d201bbe44a87c8b256d91dd03a458c0d589116c8db3f022bb4"
}, },
"arguments": { "arguments": {
"inputs": { "inputs": {
...@@ -161,7 +161,7 @@ ...@@ -161,7 +161,7 @@
"version": "0.3.0", "version": "0.3.0",
"python_path": "d3m.primitives.data_transformation.construct_predictions.DataFrameCommon", "python_path": "d3m.primitives.data_transformation.construct_predictions.DataFrameCommon",
"name": "Construct pipeline predictions output", "name": "Construct pipeline predictions output",
"digest": "0c744dd6ea7eafb9c143f70b40452c6238bc6cab06a070d50868822f904388d3" "digest": "53087aaa6baf0ccc96b6525ca5b79fd4e51b4cce996ab39773a9b0b3e746bf05"
}, },
"arguments": { "arguments": {
"inputs": { "inputs": {
...@@ -180,5 +180,5 @@ ...@@ -180,5 +180,5 @@
] ]
} }
], ],
"digest": "65df6f37e781d1d486ba6ab260b2580dec2099060a30ea91273d87148c8aa035" "digest": "29d158947336b07821f53537d6697c5c0e518ca1d0b621c770c08e92efedd875"
} }
\ No newline at end of file
...@@ -21,7 +21,7 @@ ...@@ -21,7 +21,7 @@
"installation": [ "installation": [
{ {
"type": "PIP", "type": "PIP",
"package_uri": "git+https://github.com/dvdmjohnson/d3m_michigan_primitives.git@1229b579b02a6c84b137f2d72c188da14af563c6#egg=spider" "package_uri": "git+https://github.com/dvdmjohnson/d3m_michigan_primitives.git@98e685e0d16f754caedd1e50afbc1e0d0aa28842#egg=spider"
}, },
{ {
"type": "UBUNTU", "type": "UBUNTU",
...@@ -282,5 +282,5 @@ ...@@ -282,5 +282,5 @@
} }
}, },
"structural_type": "spider.cluster.ssc_admm.ssc_admm.SSC_ADMM", "structural_type": "spider.cluster.ssc_admm.ssc_admm.SSC_ADMM",
"digest": "f7621a0cad0d209adb11404aea6b0c271b40abcbf433003ca4b7a65988c37c0e" "digest": "26d325ba630b7f343d9dc8bbc59d0c1700a64b45e10b85603560c126a01964f5"
} }
{ {
"id": "9dd8ae9a-46ea-4974-aaee-9be4be0f8dbb", "id": "ff6cc5a2-a352-4728-8532-99281fc2c2e3",
"schema": "https://metadata.datadrivendiscovery.org/schemas/v0/pipeline.json", "schema": "https://metadata.datadrivendiscovery.org/schemas/v0/pipeline.json",
"created": "2019-06-18T15:38:20.075522Z", "created": "2019-06-19T03:18:45.539386Z",
"inputs": [ "inputs": [
{ {
"name": "inputs" "name": "inputs"
...@@ -21,7 +21,7 @@ ...@@ -21,7 +21,7 @@
"version": "0.3.0", "version": "0.3.0",
"python_path": "d3m.primitives.data_transformation.dataset_to_dataframe.Common", "python_path": "d3m.primitives.data_transformation.dataset_to_dataframe.Common",
"name": "Extract a DataFrame from a Dataset", "name": "Extract a DataFrame from a Dataset",
"digest": "4e971e251e548f1188c280c60f4e2f9a460865f21bcfd341114270bdafa4c4dc" "digest": "45f8322097914f9c95c4f9a8224d02db5d79b7166c74115e2eea7b23ccc13510"
}, },
"arguments": { "arguments": {
"inputs": { "inputs": {
...@@ -42,7 +42,7 @@ ...@@ -42,7 +42,7 @@
"version": "0.5.0", "version": "0.5.0",
"python_path": "d3m.primitives.data_transformation.column_parser.DataFrameCommon", "python_path": "d3m.primitives.data_transformation.column_parser.DataFrameCommon",
"name": "Parses strings into their types", "name": "Parses strings into their types",
"digest": "b14b7bcd1a54ee658a7093658eb4b6c9a1b029698f981fec7ad26408a0b5cf64" "digest": "d41ad0c56ef55a233b21f4a4d8df1ac782aca7a78ef98dbfb72215690b3e9850"
}, },
"arguments": { "arguments": {
"inputs": { "inputs": {
...@@ -63,7 +63,7 @@ ...@@ -63,7 +63,7 @@
"version": "0.3.0", "version": "0.3.0",
"python_path": "d3m.primitives.data_transformation.extract_columns_by_semantic_types.DataFrameCommon", "python_path": "d3m.primitives.data_transformation.extract_columns_by_semantic_types.DataFrameCommon",
"name": "Extracts columns by semantic type", "name": "Extracts columns by semantic type",
"digest": "ea473cf02c17ae9d2610be746cb726d91991bc6e39c0c85d1b1550eacd1581be" "digest": "e91e0f7569ad53b6d4b8c01641f80fb0aa764b5dd3ae71dd2fbb433fa62c7f81"
}, },
"arguments": { "arguments": {
"inputs": { "inputs": {
...@@ -92,7 +92,7 @@ ...@@ -92,7 +92,7 @@
"version": "0.1.0", "version": "0.1.0",
"python_path": "d3m.primitives.data_transformation.dataframe_to_ndarray.Common", "python_path": "d3m.primitives.data_transformation.dataframe_to_ndarray.Common",
"name": "DataFrame to ndarray converter", "name": "DataFrame to ndarray converter",
"digest": "766360bfe2af3b5a9f94ff3d5edbafb6ac8a334f56660bdddfdea70c7542c209" "digest": "acd6cfebb0d83da23e3b93034471ca6f04fc2478d2105e13518d6c76c850b676"
}, },
"arguments": { "arguments": {
"inputs": { "inputs": {
...@@ -113,7 +113,7 @@ ...@@ -113,7 +113,7 @@
"version": "0.0.5", "version": "0.0.5",
"python_path": "d3m.primitives.clustering.ssc_cvx.Umich", "python_path": "d3m.primitives.clustering.ssc_cvx.Umich",
"name": "SSC_CVX", "name": "SSC_CVX",
"digest": "c331c55c1f2901d1159b573984b6a1fa50f74c29d7baf64c4788f3cb314ca671" "digest": "12699548d1360c027e9797c57f6dd778c70574746b604cf4f638fb44ac4466b8"
}, },
"arguments": { "arguments": {
"inputs": { "inputs": {
...@@ -140,7 +140,7 @@ ...@@ -140,7 +140,7 @@
"version": "0.1.0", "version": "0.1.0",
"python_path": "d3m.primitives.data_transformation.ndarray_to_dataframe.Common", "python_path": "d3m.primitives.data_transformation.ndarray_to_dataframe.Common",
"name": "ndarray to Dataframe converter", "name": "ndarray to Dataframe converter",
"digest": "ec7afdcc833310158d8f4e7d09ae193655278a1ab4263b2233eb1146dd874ef7" "digest": "7228a01faeab36d201bbe44a87c8b256d91dd03a458c0d589116c8db3f022bb4"
}, },
"arguments": { "arguments": {
"inputs": { "inputs": {
...@@ -161,7 +161,7 @@ ...@@ -161,7 +161,7 @@
"version": "0.3.0", "version": "0.3.0",
"python_path": "d3m.primitives.data_transformation.construct_predictions.DataFrameCommon", "python_path": "d3m.primitives.data_transformation.construct_predictions.DataFrameCommon",
"name": "Construct pipeline predictions output", "name": "Construct pipeline predictions output",
"digest": "0c744dd6ea7eafb9c143f70b40452c6238bc6cab06a070d50868822f904388d3" "digest": "53087aaa6baf0ccc96b6525ca5b79fd4e51b4cce996ab39773a9b0b3e746bf05"
}, },
"arguments": { "arguments": {
"inputs": { "inputs": {
...@@ -180,5 +180,5 @@ ...@@ -180,5 +180,5 @@
] ]
} }
], ],
"digest": "3db2065c7c6154739f0d44b17200903432178ee049b6fdda8d3eff4021594b39" "digest": "dbf945b4e30e594b896ba8f01de58ac7e874632ab58bf47abed471561d46ec8c"
} }
\ No newline at end of file
...@@ -21,7 +21,7 @@ ...@@ -21,7 +21,7 @@
"installation": [ "installation": [
{ {
"type": "PIP", "type": "PIP",
"package_uri": "git+https://github.com/dvdmjohnson/d3m_michigan_primitives.git@1229b579b02a6c84b137f2d72c188da14af563c6#egg=spider" "package_uri": "git+https://github.com/dvdmjohnson/d3m_michigan_primitives.git@98e685e0d16f754caedd1e50afbc1e0d0aa28842#egg=spider"
}, },
{ {
"type": "UBUNTU", "type": "UBUNTU",
...@@ -295,5 +295,5 @@ ...@@ -295,5 +295,5 @@
} }
}, },
"structural_type": "spider.cluster.ssc_cvx.ssc_cvx.SSC_CVX", "structural_type": "spider.cluster.ssc_cvx.ssc_cvx.SSC_CVX",
"digest": "c331c55c1f2901d1159b573984b6a1fa50f74c29d7baf64c4788f3cb314ca671" "digest": "12699548d1360c027e9797c57f6dd778c70574746b604cf4f638fb44ac4466b8"
} }
{ {
"id": "d64b7dc7-9054-495b-a67e-55db18cad783", "id": "c222168d-7d0d-4d33-b8d1-279828555272",
"schema": "https://metadata.datadrivendiscovery.org/schemas/v0/pipeline.json", "schema": "https://metadata.datadrivendiscovery.org/schemas/v0/pipeline.json",
"created": "2019-06-18T15:38:22.185843Z", "created": "2019-06-19T03:18:47.713539Z",
"inputs": [ "inputs": [
{ {
"name": "inputs" "name": "inputs"
...@@ -21,7 +21,7 @@ ...@@ -21,7 +21,7 @@
"version": "0.3.0", "version": "0.3.0",
"python_path": "d3m.primitives.data_transformation.dataset_to_dataframe.Common", "python_path": "d3m.primitives.data_transformation.dataset_to_dataframe.Common",
"name": "Extract a DataFrame from a Dataset", "name": "Extract a DataFrame from a Dataset",
"digest": "4e971e251e548f1188c280c60f4e2f9a460865f21bcfd341114270bdafa4c4dc" "digest": "45f8322097914f9c95c4f9a8224d02db5d79b7166c74115e2eea7b23ccc13510"
}, },
"arguments": { "arguments": {
"inputs": { "inputs": {
...@@ -42,7 +42,7 @@ ...@@ -42,7 +42,7 @@
"version": "0.5.0", "version": "0.5.0",
"python_path": "d3m.primitives.data_transformation.column_parser.DataFrameCommon", "python_path": "d3m.primitives.data_transformation.column_parser.DataFrameCommon",
"name": "Parses strings into their types", "name": "Parses strings into their types",
"digest": "b14b7bcd1a54ee658a7093658eb4b6c9a1b029698f981fec7ad26408a0b5cf64" "digest": "d41ad0c56ef55a233b21f4a4d8df1ac782aca7a78ef98dbfb72215690b3e9850"
}, },
"arguments": { "arguments": {
"inputs": { "inputs": {
...@@ -63,7 +63,7 @@ ...@@ -63,7 +63,7 @@
"version": "0.3.0", "version": "0.3.0",
"python_path": "d3m.primitives.data_transformation.extract_columns_by_semantic_types.DataFrameCommon", "python_path": "d3m.primitives.data_transformation.extract_columns_by_semantic_types.DataFrameCommon",
"name": "Extracts columns by semantic type", "name": "Extracts columns by semantic type",
"digest": "ea473cf02c17ae9d2610be746cb726d91991bc6e39c0c85d1b1550eacd1581be" "digest": "e91e0f7569ad53b6d4b8c01641f80fb0aa764b5dd3ae71dd2fbb433fa62c7f81"
}, },
"arguments": { "arguments": {
"inputs": { "inputs": {
...@@ -92,7 +92,7 @@ ...@@ -92,7 +92,7 @@
"version": "0.1.0", "version": "0.1.0",
"python_path": "d3m.primitives.data_transformation.dataframe_to_ndarray.Common", "python_path": "d3m.primitives.data_transformation.dataframe_to_ndarray.Common",
"name": "DataFrame to ndarray converter", "name": "DataFrame to ndarray converter",
"digest": "766360bfe2af3b5a9f94ff3d5edbafb6ac8a334f56660bdddfdea70c7542c209" "digest": "acd6cfebb0d83da23e3b93034471ca6f04fc2478d2105e13518d6c76c850b676"
}, },
"arguments": {