def test(a_node, pp): ###################################################################### # Now look for kmeans_prostate_model_name using the one-model API and find_compatible_frames, and check it model = a_node.models(key='kmeans_prostate', find_compatible_frames=True) found_kmeans = False; h2o.H2O.verboseprint('k-means model with find_compatible_frames output: ') h2o.H2O.verboseprint('/Models/', 'kmeans_prostate', '?find_compatible_frames=true: ', repr(model)) h2o_test_utils.assertKeysExist(model['models'][0], '', ['compatible_frames']) assert 'prostate_binomial' in model['models'][0]['compatible_frames'], "FAIL: Failed to find " + 'prostate_binomial' + " in compatible_frames list." ###################################################################### # Now look for 'prostate_binomial' using the one-frame API and find_compatible_models, and check it result = a_node.frames(key='prostate_binomial', find_compatible_models=True, row_count=5) frames = result['frames'] frames_dict = h2o_test_utils.list_to_dict(frames, 'frame_id/name') assert 'prostate_binomial' in frames_dict, "FAIL: Failed to find prostate.hex in Frames list." compatible_models = result['compatible_models'] models_dict = h2o_test_utils.list_to_dict(compatible_models, 'model_id/name') assert 'deeplearning_prostate_binomial' in models_dict, "FAIL: Failed to find " + 'deeplearning_prostate_binomial' + " in compatible models list: " + repr(result) assert 'deeplearning_prostate_binomial' in frames[0]['compatible_models'], "FAIL: failed to find deeplearning_prostate_binomial in compatible_models for prostate." assert 'kmeans_prostate' in frames[0]['compatible_models'], "FAIL: failed to find kmeans_prostate in compatible_models for prostate." h2o.H2O.verboseprint('/Frames/prosate.hex?find_compatible_models=true: ', repr(result))
def test(a_node, pp): ###################################################################### # Now look for kmeans_prostate_model_name using the one-model API and find_compatible_frames, and check it model = a_node.models(key='kmeans_prostate', find_compatible_frames=True) found_kmeans = False h2o.H2O.verboseprint('k-means model with find_compatible_frames output: ') h2o.H2O.verboseprint('/Models/', 'kmeans_prostate', '?find_compatible_frames=true: ', repr(model)) h2o_test_utils.assertKeysExist(model['models'][0], '', ['compatible_frames']) assert 'prostate_binomial' in model['models'][0][ 'compatible_frames'], "FAIL: Failed to find " + 'prostate_binomial' + " in compatible_frames list." ###################################################################### # Now look for 'prostate_binomial' using the one-frame API and find_compatible_models, and check it result = a_node.frames(key='prostate_binomial', find_compatible_models=True, row_count=5) frames = result['frames'] frames_dict = h2o_test_utils.list_to_dict(frames, 'frame_id/name') assert 'prostate_binomial' in frames_dict, "FAIL: Failed to find prostate.hex in Frames list." compatible_models = result['compatible_models'] models_dict = h2o_test_utils.list_to_dict(compatible_models, 'model_id/name') assert 'deeplearning_prostate_binomial' in models_dict, "FAIL: Failed to find " + 'deeplearning_prostate_binomial' + " in compatible models list: " + repr( result) assert 'deeplearning_prostate_binomial' in frames[0][ 'compatible_models'], "FAIL: failed to find deeplearning_prostate_binomial in compatible_models for prostate." assert 'kmeans_prostate' in frames[0][ 'compatible_models'], "FAIL: failed to find kmeans_prostate in compatible_models for prostate." h2o.H2O.verboseprint('/Frames/prosate.hex?find_compatible_models=true: ', repr(result))
def load_and_test(a_node, pp): ################## # Test CreateFrame if h2o_test_utils.isVerbose(): print('Testing CreateFrame. . .') created_job = a_node.create_frame(dest='created') # call with defaults a_node.poll_job( job_key=created_job['key']['name'] ) # wait until done and get CreateFrameV3 instance (aka the Job) frames = a_node.frames(key='created')['frames'] assert len( frames ) == 1, "FAIL: expected to find 1 frame called 'created', found: " + str( len(frames)) assert frames[0]['frame_id'][ 'name'] == 'created', "FAIL: expected to find 1 frame called 'created', found: " + repr( frames) created = frames[0] assert 'rows' in created, "FAIL: failed to find 'rows' field in CreateFrame result." assert created[ 'rows'] == 10000, "FAIL: expected value of 'rows' field in CreateFrame result to be: " + str( 10000) + ", found: " + str(created['rows']) assert 'columns' in created, "FAIL: failed to find 'columns' field in CreateFrame result." assert len( created['columns'] ) == 10, "FAIL: expected value of 'columns' field in CreateFrame result to be: " + str( 10) + ", found: " + str(len(created['columns'])) ######################################################### # Import and test all the datasets we'll need for the subsequent tests: ######################################################### # dest_key, path, expected_rows, model_category, response_column, ignored_columns datasets_to_import = [ DatasetSpec('prostate_clustering', '../../../smalldata/logreg/prostate.csv', 380, 'Clustering', None, ['ID']), DatasetSpec('prostate_binomial', '../../../smalldata/logreg/prostate.csv', 380, 'Binomial', 'CAPSULE', ['ID']), DatasetSpec('prostate_regression', '../../../smalldata/logreg/prostate.csv', 380, 'Regression', 'AGE', ['ID']), DatasetSpec('airlines_binomial', '../../../smalldata/airlines/allyears2k_headers.zip', 43978, 'Binomial', 'IsDepDelayed', [ 'DayofMonth', 'DepTime', 'CRSDepTime', 'ArrTime', 'CRSArrTime', 'TailNum', 'ActualElapsedTime', 'CRSElapsedTime', 'AirTime', 'ArrDelay', 'DepDelay', 'TaxiIn', 'TaxiOut', 'Cancelled', 'CancellationCode', 'Diverted', 'CarrierDelay', 'WeatherDelay', 'NASDelay', 'SecurityDelay', 'LateAircraftDelay', 'IsArrDelayed' ]), DatasetSpec('iris_multinomial', '../../../smalldata/iris/iris_wheader.csv', 150, 'Multinomial', 'class', []), ] datasets = {} # the dataset spec for dataset_spec in datasets_to_import: dataset = dataset_spec.import_and_validate_dataset( a_node) # it's also stored in dataset_spec['dataset'] if dataset_spec['model_category'] == 'Binomial': a_node.as_factor(dataset_spec['dest_key'], dataset_spec['response_column']) datasets[dataset_spec['dest_key']] = dataset_spec ################################################ # Test /Frames for prostate.csv frames = a_node.frames(row_count=5)['frames'] frames_dict = h2o_test_utils.list_to_dict(frames, 'frame_id/name') if h2o_test_utils.isVerboser(): print("frames: ") pp.pprint(frames) if h2o_test_utils.isVerboser(): print("frames_dict: ") pp.pprint(frames_dict) assert 'prostate_binomial' in frames_dict, "FAIL: Failed to find " + 'prostate_binomial' + " in Frames list." assert not frames_dict['prostate_binomial'][ 'is_text'], "FAIL: Parsed Frame is is_text" # Test /Frames/{key} for prostate.csv frames = a_node.frames(key='prostate_binomial', row_count=5)['frames'] frames_dict = h2o_test_utils.list_to_dict(frames, 'frame_id/name') assert 'prostate_binomial' in frames_dict, "FAIL: Failed to find prostate.hex in Frames list." columns_dict = h2o_test_utils.list_to_dict(frames[0]['columns'], 'label') assert 'CAPSULE' in columns_dict, "FAIL: Failed to find CAPSULE in Frames/prostate.hex." assert 'AGE' in columns_dict, "FAIL: Failed to find AGE in Frames/prostate.hex/columns." assert 'histogram_bins' in columns_dict[ 'AGE'], "FAIL: Failed to find bins in Frames/prostate.hex/columns/AGE." h2o.H2O.verboseprint('bins: ' + repr(columns_dict['AGE']['histogram_bins'])) assert None is columns_dict['AGE'][ 'histogram_bins'], "FAIL: Failed to clear bins field." # should be cleared except for /summary # Test /Frames/{key}/columns for prostate.csv frames = a_node.columns(key='prostate_binomial')['frames'] columns_dict = h2o_test_utils.list_to_dict(frames[0]['columns'], 'label') assert 'ID' in columns_dict, "FAIL: Failed to find ID in Frames/prostate.hex/columns." assert 'AGE' in columns_dict, "FAIL: Failed to find AGE in Frames/prostate.hex/columns." assert 'histogram_bins' in columns_dict[ 'AGE'], "FAIL: Failed to find bins in Frames/prostate.hex/columns/AGE." h2o.H2O.verboseprint('bins: ' + repr(columns_dict['AGE']['histogram_bins'])) assert None is columns_dict['AGE'][ 'histogram_bins'], "FAIL: Failed to clear bins field." # should be cleared except for /summary # Test /Frames/{key}/columns/{label} for prostate.csv frames = a_node.column(key='prostate_binomial', column='AGE')['frames'] columns_dict = h2o_test_utils.list_to_dict(frames[0]['columns'], 'label') assert 'AGE' in columns_dict, "FAIL: Failed to find AGE in Frames/prostate.hex/columns." assert 'histogram_bins' in columns_dict[ 'AGE'], "FAIL: Failed to find bins in Frames/prostate.hex/columns/AGE." h2o.H2O.verboseprint('bins: ' + repr(columns_dict['AGE']['histogram_bins'])) assert None is columns_dict['AGE'][ 'histogram_bins'], "FAIL: Failed to clear bins field." # should be cleared except for /summary # Test /Frames/{key}/columns/{label}/summary for prostate.csv frames = a_node.summary(key='prostate_binomial', column='AGE')['frames'] columns_dict = h2o_test_utils.list_to_dict(frames[0]['columns'], 'label') assert 'AGE' in columns_dict, "FAIL: Failed to find AGE in Frames/prostate.hex/columns/AGE/summary." col = columns_dict['AGE'] h2o_test_utils.assertKeysExistAndNonNull(col, '', [ 'label', 'missing_count', 'zero_count', 'positive_infinity_count', 'negative_infinity_count', 'mins', 'maxs', 'mean', 'sigma', 'type', 'data', 'precision', 'histogram_bins', 'histogram_base', 'histogram_stride', 'percentiles' ]) h2o_test_utils.assertKeysExist(col, '', ['domain', 'string_data']) assert col['mins'][ 0] == 43, 'FAIL: Failed to find 43 as the first min for AGE.' assert col['maxs'][ 0] == 79, 'FAIL: Failed to find 79 as the first max for AGE.' assert abs( col['mean'] - 66.03947368421052 ) < 1e-8, 'FAIL: Failed to find 66.03947368421052 as the mean for AGE.' assert abs( col['sigma'] - 6.527071269173308 ) < 1e-8, 'FAIL: Failed to find 6.527071269173308 as the sigma for AGE.' assert col[ 'type'] == 'int', 'FAIL: Failed to find int as the type for AGE.' assert col['data'][ 0] == 65, 'FAIL: Failed to find 65 as the first data for AGE.' assert col[ 'precision'] == -1, 'FAIL: Failed to find -1 as the precision for AGE.' assert col['histogram_bins'][ 0] == 1, 'FAIL: Failed to find 1 as the first bin for AGE.' assert col[ 'histogram_base'] == 43, 'FAIL: Failed to find 43 as the histogram_base for AGE.' assert col[ 'histogram_stride'] == 1, 'FAIL: Failed to find 1 as the histogram_stride for AGE.' assert col['percentiles'][ 0] == 44.516, 'FAIL: Failed to find 43.516 as the 0.1% percentile for AGE. ' + str( col['percentiles'][0]) assert col['percentiles'][ 1] == 50.79, 'FAIL: Failed to find 50.79 as the 1.0% percentile for AGE. ' + str( col['percentiles'][1]) assert col['percentiles'][ 15] == 78, 'FAIL: Failed to find 78 as the 99.0% percentile for AGE. ' + str( col['percentiles'][15]) assert col['percentiles'][ 16] == 79, 'FAIL: Failed to find 79 as the 99.9% percentile for AGE. ' + str( col['percentiles'][16]) # NB: col['percentiles'] corresponds to probs=[0.001,0.01,0.1,0.2,0.25,0.3,1.0/3.0,0.4,0.5,0.6,2.0/3.0,0.7,0.75,0.8,0.9,0.99,0.999] # Test /SplitFrame for prostate.csv if h2o_test_utils.isVerbose(): print('Testing SplitFrame with named destination_frames. . .') splits = a_node.split_frame(dataset='prostate_binomial', ratios=[0.8], destination_frames=['bigger', 'smaller']) frames = a_node.frames()['frames'] h2o_test_utils.validate_frame_exists(a_node, 'bigger', frames) h2o_test_utils.validate_frame_exists(a_node, 'smaller', frames) bigger = a_node.frames(key='bigger')['frames'][0] smaller = a_node.frames(key='smaller')['frames'][0] assert bigger[ 'rows'] == 304, 'FAIL: 80/20 SplitFrame yielded the wrong number of rows. Expected: 304; got: ' + bigger[ 'rows'] assert smaller[ 'rows'] == 76, 'FAIL: 80/20 SplitFrame yielded the wrong number of rows. Expected: 76; got: ' + smaller[ 'rows'] h2o_test_utils.validate_job_exists(a_node, splits['key']['name']) if h2o_test_utils.isVerbose(): print('Testing SplitFrame with generated destination_frames. . .') splits = a_node.split_frame(dataset='prostate_binomial', ratios=[0.5]) frames = a_node.frames()['frames'] h2o_test_utils.validate_frame_exists( a_node, splits['destination_frames'][0]['name'], frames) h2o_test_utils.validate_frame_exists( a_node, splits['destination_frames'][1]['name'], frames) first = a_node.frames( key=splits['destination_frames'][0]['name'])['frames'][0] second = a_node.frames( key=splits['destination_frames'][1]['name'])['frames'][0] assert first[ 'rows'] == 190, 'FAIL: 50/50 SplitFrame yielded the wrong number of rows. Expected: 190; got: ' + first[ 'rows'] assert second[ 'rows'] == 190, 'FAIL: 50/50 SplitFrame yielded the wrong number of rows. Expected: 190; got: ' + second[ 'rows'] h2o_test_utils.validate_job_exists(a_node, splits['key']['name']) return datasets
def load_and_test(a_node, pp): ################## # Test CreateFrame if h2o_test_utils.isVerbose(): print 'Testing CreateFrame. . .' created_job = a_node.create_frame(dest='created') # call with defaults a_node.poll_job(job_key=created_job['key']['name']) # wait until done and get CreateFrameV3 instance (aka the Job) frames = a_node.frames(key='created')['frames'] assert len(frames) == 1, "FAIL: expected to find 1 frame called 'created', found: " + str(len(frames)) assert frames[0]['frame_id']['name'] == 'created', "FAIL: expected to find 1 frame called 'created', found: " + repr(frames) created = frames[0] assert 'rows' in created, "FAIL: failed to find 'rows' field in CreateFrame result." assert created['rows'] == 10000, "FAIL: expected value of 'rows' field in CreateFrame result to be: " + str(10000) + ", found: " + str(created['rows']) assert 'columns' in created, "FAIL: failed to find 'columns' field in CreateFrame result." assert len(created['columns']) == 10, "FAIL: expected value of 'columns' field in CreateFrame result to be: " + str(10) + ", found: " + str(len(created['columns'])) ######################################################### # Import and test all the datasets we'll need for the subsequent tests: ######################################################### # dest_key, path, expected_rows, model_category, response_column, ignored_columns datasets_to_import = [ DatasetSpec('prostate_clustering', '../../smalldata/logreg/prostate.csv', 380, 'Clustering', None, ['ID']), DatasetSpec('prostate_binomial', '../../smalldata/logreg/prostate.csv', 380, 'Binomial', 'CAPSULE', ['ID']), DatasetSpec('prostate_regression', '../../smalldata/logreg/prostate.csv', 380, 'Regression', 'AGE', ['ID']), DatasetSpec('airlines_binomial', '../../smalldata/airlines/allyears2k_headers.zip', 43978, 'Binomial', 'IsDepDelayed', ['IsArrDelayed', 'ArrDelay', 'DepDelay']), # TODO: more ignored? DatasetSpec('iris_multinomial', '../../smalldata/iris/iris_wheader.csv', 150, 'Multinomial', 'class', []), ] datasets = {} # the dataset spec for dataset_spec in datasets_to_import: dataset = dataset_spec.import_and_validate_dataset(a_node) # it's also stored in dataset_spec['dataset'] datasets[dataset_spec['dest_key']] = dataset_spec ################################################ # Test /Frames for prostate.csv frames = a_node.frames(row_count=5)['frames'] frames_dict = h2o_test_utils.list_to_dict(frames, 'frame_id/name') # TODO: remove: if h2o_test_utils.isVerboser(): print "frames: " pp.pprint(frames) if h2o_test_utils.isVerboser(): print "frames_dict: " pp.pprint(frames_dict) assert 'prostate_binomial' in frames_dict, "FAIL: Failed to find " + 'prostate_binomial' + " in Frames list." assert not frames_dict['prostate_binomial']['is_text'], "FAIL: Parsed Frame is is_text" # Test /Frames/{key} for prostate.csv frames = a_node.frames(key='prostate_binomial', row_count=5)['frames'] frames_dict = h2o_test_utils.list_to_dict(frames, 'frame_id/name') assert 'prostate_binomial' in frames_dict, "FAIL: Failed to find prostate.hex in Frames list." columns_dict = h2o_test_utils.list_to_dict(frames[0]['columns'], 'label') assert 'CAPSULE' in columns_dict, "FAIL: Failed to find CAPSULE in Frames/prostate.hex." assert 'AGE' in columns_dict, "FAIL: Failed to find AGE in Frames/prostate.hex/columns." assert 'histogram_bins' in columns_dict['AGE'], "FAIL: Failed to find bins in Frames/prostate.hex/columns/AGE." h2o.H2O.verboseprint('bins: ' + repr(columns_dict['AGE']['histogram_bins'])) assert None is columns_dict['AGE']['histogram_bins'], "FAIL: Failed to clear bins field." # should be cleared except for /summary # Test /Frames/{key}/columns for prostate.csv frames = a_node.columns(key='prostate_binomial')['frames'] columns_dict = h2o_test_utils.list_to_dict(frames[0]['columns'], 'label') assert 'ID' in columns_dict, "FAIL: Failed to find ID in Frames/prostate.hex/columns." assert 'AGE' in columns_dict, "FAIL: Failed to find AGE in Frames/prostate.hex/columns." assert 'histogram_bins' in columns_dict['AGE'], "FAIL: Failed to find bins in Frames/prostate.hex/columns/AGE." h2o.H2O.verboseprint('bins: ' + repr(columns_dict['AGE']['histogram_bins'])) assert None is columns_dict['AGE']['histogram_bins'], "FAIL: Failed to clear bins field." # should be cleared except for /summary # Test /Frames/{key}/columns/{label} for prostate.csv frames = a_node.column(key='prostate_binomial', column='AGE')['frames'] columns_dict = h2o_test_utils.list_to_dict(frames[0]['columns'], 'label') assert 'AGE' in columns_dict, "FAIL: Failed to find AGE in Frames/prostate.hex/columns." assert 'histogram_bins' in columns_dict['AGE'], "FAIL: Failed to find bins in Frames/prostate.hex/columns/AGE." h2o.H2O.verboseprint('bins: ' + repr(columns_dict['AGE']['histogram_bins'])) assert None is columns_dict['AGE']['histogram_bins'], "FAIL: Failed to clear bins field." # should be cleared except for /summary # Test /Frames/{key}/columns/{label}/summary for prostate.csv frames = a_node.summary(key='prostate_binomial', column='AGE')['frames'] columns_dict = h2o_test_utils.list_to_dict(frames[0]['columns'], 'label') assert 'AGE' in columns_dict, "FAIL: Failed to find AGE in Frames/prostate.hex/columns/AGE/summary." col = columns_dict['AGE'] h2o_test_utils.assertKeysExistAndNonNull(col, '', ['label', 'missing_count', 'zero_count', 'positive_infinity_count', 'negative_infinity_count', 'mins', 'maxs', 'mean', 'sigma', 'type', 'data', 'precision', 'histogram_bins', 'histogram_base', 'histogram_stride', 'percentiles']) h2o_test_utils.assertKeysExist(col, '', ['domain', 'string_data']) assert col['mins'][0] == 43, 'FAIL: Failed to find 43 as the first min for AGE.' assert col['maxs'][0] == 79, 'FAIL: Failed to find 79 as the first max for AGE.' assert abs(col['mean'] - 66.03947368421052) < 1e-8, 'FAIL: Failed to find 66.03947368421052 as the mean for AGE.' assert abs(col['sigma'] - 6.527071269173308) < 1e-8, 'FAIL: Failed to find 6.527071269173308 as the sigma for AGE.' assert col['type'] == 'int', 'FAIL: Failed to find int as the type for AGE.' assert col['data'][0] == 65, 'FAIL: Failed to find 65 as the first data for AGE.' assert col['precision'] == -1, 'FAIL: Failed to find -1 as the precision for AGE.' assert col['histogram_bins'][0] == 1, 'FAIL: Failed to find 1 as the first bin for AGE.' assert col['histogram_base'] == 43, 'FAIL: Failed to find 43 as the histogram_base for AGE.' assert col['histogram_stride'] == 1, 'FAIL: Failed to find 1 as the histogram_stride for AGE.' assert col['percentiles'][0] == 44.516, 'FAIL: Failed to find 43.516 as the 0.1% percentile for AGE. '+str(col['percentiles'][0]) assert col['percentiles'][1] == 50.79, 'FAIL: Failed to find 50.79 as the 1.0% percentile for AGE. '+str(col['percentiles'][1]) assert col['percentiles'][15] == 78, 'FAIL: Failed to find 78 as the 99.0% percentile for AGE. '+str(col['percentiles'][15]) assert col['percentiles'][16] == 79, 'FAIL: Failed to find 79 as the 99.9% percentile for AGE. '+str(col['percentiles'][16]) # NB: col['percentiles'] corresponds to probs=[0.001,0.01,0.1,0.2,0.25,0.3,1.0/3.0,0.4,0.5,0.6,2.0/3.0,0.7,0.75,0.8,0.9,0.99,0.999] # Test /SplitFrame for prostate.csv if h2o_test_utils.isVerbose(): print 'Testing SplitFrame with named destination_frames. . .' splits = a_node.split_frame(dataset='prostate_binomial', ratios=[0.8], destination_frames=['bigger', 'smaller']) frames = a_node.frames()['frames'] h2o_test_utils.validate_frame_exists(a_node, 'bigger', frames) h2o_test_utils.validate_frame_exists(a_node, 'smaller', frames) bigger = a_node.frames(key='bigger')['frames'][0] smaller = a_node.frames(key='smaller')['frames'][0] assert bigger['rows'] == 304, 'FAIL: 80/20 SplitFrame yielded the wrong number of rows. Expected: 304; got: ' + bigger['rows'] assert smaller['rows'] == 76, 'FAIL: 80/20 SplitFrame yielded the wrong number of rows. Expected: 76; got: ' + smaller['rows'] # TODO: h2o_test_utils.validate_job_exists(a_node, splits['frame_id']['name']) if h2o_test_utils.isVerbose(): print 'Testing SplitFrame with generated destination_frames. . .' splits = a_node.split_frame(dataset='prostate_binomial', ratios=[0.5]) frames = a_node.frames()['frames'] h2o_test_utils.validate_frame_exists(a_node, splits['destination_frames'][0]['name'], frames) h2o_test_utils.validate_frame_exists(a_node, splits['destination_frames'][1]['name'], frames) first = a_node.frames(key=splits['destination_frames'][0]['name'])['frames'][0] second = a_node.frames(key=splits['destination_frames'][1]['name'])['frames'][0] assert first['rows'] == 190, 'FAIL: 50/50 SplitFrame yielded the wrong number of rows. Expected: 190; got: ' + first['rows'] assert second['rows'] == 190, 'FAIL: 50/50 SplitFrame yielded the wrong number of rows. Expected: 190; got: ' + second['rows'] # TODO: h2o_test_utils.validate_job_exists(a_node, splits['frame_id']['name']) return datasets
def load_and_test(a_node, pp): ################## # Test CreateFrame if h2o_test_utils.isVerbose(): print 'Testing CreateFrame. . .' created_job = a_node.create_frame(dest='created') # call with defaults a_node.poll_job(job_key=created_job['key']['name']) # wait until done and get CreateFrameV3 instance (aka the Job) frames = a_node.frames(key='created')['frames'] assert len(frames) == 1, "FAIL: expected to find 1 frame called 'created', found: " + str(len(frames)) assert frames[0]['frame_id']['name'] == 'created', "FAIL: expected to find 1 frame called 'created', found: " + repr(frames) created = frames[0] assert 'rows' in created, "FAIL: failed to find 'rows' field in CreateFrame result." assert created['rows'] == 10000, "FAIL: expected value of 'rows' field in CreateFrame result to be: " + str(10000) + ", found: " + str(created['rows']) assert 'columns' in created, "FAIL: failed to find 'columns' field in CreateFrame result." assert len(created['columns']) == 10, "FAIL: expected value of 'columns' field in CreateFrame result to be: " + str(10) + ", found: " + str(len(created['columns'])) # Test CreateFrame -- With Wrong parameter param_job = a_node.create_frame(raiseIfNon200=False, dests='created') h2o_test_utils.validate_412_statusCode(param_job) h2o_test_utils.validate_412_InfoMessage(param_job, "Unknown parameter: dests") ######################################################### # Import and test all the datasets we'll need for the subsequent tests: ######################################################### # dest_key, path, expected_rows, model_category, response_column, ignored_columns datasets_to_import = [ DatasetSpec('prostate_clustering', '../../smalldata/logreg/prostate.csv', 380, 'Clustering', None, ['ID']), DatasetSpec('prostate_binomial', '../../smalldata/logreg/prostate.csv', 380, 'Binomial', 'CAPSULE', ['ID']), DatasetSpec('prostate_regression', '../../smalldata/logreg/prostate.csv', 380, 'Regression', 'AGE', ['ID']), DatasetSpec('prostate_delete', '../../smalldata/logreg/prostate.csv', 380, 'Regression', 'AGE', ['ID']), DatasetSpec('prostate_spt_negetive', '../../smalldata/logreg/prostate.csv', 380, 'Regression', 'AGE', ['ID']), DatasetSpec('airlines_binomial', '../../smalldata/airlines/allyears2k_headers.zip', 43978, 'Binomial', 'IsDepDelayed', ['IsArrDelayed', 'ArrDelay', 'DepDelay']), # TODO: more ignored? DatasetSpec('iris_multinomial', '../../smalldata/iris/iris_wheader.csv', 150, 'Multinomial', 'class', []), ] datasets = {} # the dataset spec for dataset_spec in datasets_to_import: dataset = dataset_spec.import_and_validate_dataset(a_node) # it's also stored in dataset_spec['dataset'] datasets[dataset_spec['dest_key']] = dataset_spec ################################################ # Test /Frames for prostate.csv frames = a_node.frames(row_count=5)['frames'] frames_dict = h2o_test_utils.list_to_dict(frames, 'frame_id/name') # TODO: remove: if h2o_test_utils.isVerboser(): print "frames: " pp.pprint(frames) if h2o_test_utils.isVerboser(): print "frames_dict: " pp.pprint(frames_dict) assert 'prostate_binomial' in frames_dict, "FAIL: Failed to find " + 'prostate_binomial' + " in Frames list." assert not frames_dict['prostate_binomial']['is_text'], "FAIL: Parsed Frame is is_text" # Test /Frames/{key} for prostate.csv frames = a_node.frames(key='prostate_binomial', row_count=5)['frames'] frames_dict = h2o_test_utils.list_to_dict(frames, 'frame_id/name') assert 'prostate_binomial' in frames_dict, "FAIL: Failed to find prostate.hex in Frames list." columns_dict = h2o_test_utils.list_to_dict(frames[0]['columns'], 'label') assert 'CAPSULE' in columns_dict, "FAIL: Failed to find CAPSULE in Frames/prostate.hex." assert 'AGE' in columns_dict, "FAIL: Failed to find AGE in Frames/prostate.hex/columns." assert 'histogram_bins' in columns_dict['AGE'], "FAIL: Failed to find bins in Frames/prostate.hex/columns/AGE." h2o.H2O.verboseprint('bins: ' + repr(columns_dict['AGE']['histogram_bins'])) assert None is columns_dict['AGE']['histogram_bins'], "FAIL: Failed to clear bins field." # should be cleared except for /summary # Test /Frames for prostate.csv -- Wrong Parameter print("Testing the Bad Parameters.....") param_frames = a_node.frames_negetive(row_counts=5) h2o_test_utils.validate_412_statusCode(param_frames) h2o_test_utils.validate_412_InfoMessage(param_frames, "Unknown parameter: row_counts") print("DONE Testing the Bad Parameters.....") # Test /Frames/{key}/columns for prostate.csv frames = a_node.columns(key='prostate_binomial')['frames'] columns_dict = h2o_test_utils.list_to_dict(frames[0]['columns'], 'label') assert 'ID' in columns_dict, "FAIL: Failed to find ID in Frames/prostate.hex/columns." assert 'AGE' in columns_dict, "FAIL: Failed to find AGE in Frames/prostate.hex/columns." assert 'histogram_bins' in columns_dict['AGE'], "FAIL: Failed to find bins in Frames/prostate.hex/columns/AGE." h2o.H2O.verboseprint('bins: ' + repr(columns_dict['AGE']['histogram_bins'])) assert None is columns_dict['AGE']['histogram_bins'], "FAIL: Failed to clear bins field." # should be cleared except for /summary # Test /Frames/{key} for prostate.csv ### worong Parameter key_param_frames = a_node.frames_negetive(key='prostate_binomial', row_offsets=10) h2o_test_utils.validate_412_statusCode(key_param_frames) h2o_test_utils.validate_412_InfoMessage(key_param_frames, "Unknown parameter: row_offsets") # Test /Frames/{key}/columns/{label} for prostate.csv frames = a_node.column(key='prostate_binomial', column='AGE')['frames'] columns_dict = h2o_test_utils.list_to_dict(frames[0]['columns'], 'label') assert 'AGE' in columns_dict, "FAIL: Failed to find AGE in Frames/prostate.hex/columns." assert 'histogram_bins' in columns_dict['AGE'], "FAIL: Failed to find bins in Frames/prostate.hex/columns/AGE." h2o.H2O.verboseprint('bins: ' + repr(columns_dict['AGE']['histogram_bins'])) assert None is columns_dict['AGE']['histogram_bins'], "FAIL: Failed to clear bins field." # should be cleared except for /summary # Test /Frames/{key}/columns/{label} for prostate.csv ### Wrong param col_param_frames = a_node.frames_negetive(key='prostate_binomial', column_counts=3) h2o_test_utils.validate_412_statusCode(col_param_frames) h2o_test_utils.validate_412_InfoMessage(col_param_frames, "Unknown parameter: column_counts") # Test /Frames/{key}/columns/{label}/summary for prostate.csv frames = a_node.summary(key='prostate_binomial', column='AGE')['frames'] columns_dict = h2o_test_utils.list_to_dict(frames[0]['columns'], 'label') assert 'AGE' in columns_dict, "FAIL: Failed to find AGE in Frames/prostate.hex/columns/AGE/summary." col = columns_dict['AGE'] h2o_test_utils.assertKeysExistAndNonNull(col, '', ['label', 'missing_count', 'zero_count', 'positive_infinity_count', 'negative_infinity_count', 'mins', 'maxs', 'mean', 'sigma', 'type', 'data', 'precision', 'histogram_bins', 'histogram_base', 'histogram_stride', 'percentiles']) h2o_test_utils.assertKeysExist(col, '', ['domain', 'string_data']) assert col['mins'][0] == 43, 'FAIL: Failed to find 43 as the first min for AGE.' assert col['maxs'][0] == 79, 'FAIL: Failed to find 79 as the first max for AGE.' assert abs(col['mean'] - 66.03947368421052) < 1e-8, 'FAIL: Failed to find 66.03947368421052 as the mean for AGE.' assert abs(col['sigma'] - 6.527071269173308) < 1e-8, 'FAIL: Failed to find 6.527071269173308 as the sigma for AGE.' assert col['type'] == 'int', 'FAIL: Failed to find int as the type for AGE.' assert col['data'][0] == 65, 'FAIL: Failed to find 65 as the first data for AGE.' assert col['precision'] == -1, 'FAIL: Failed to find -1 as the precision for AGE.' assert col['histogram_bins'][0] == 1, 'FAIL: Failed to find 1 as the first bin for AGE.' assert col['histogram_base'] == 43, 'FAIL: Failed to find 43 as the histogram_base for AGE.' assert col['histogram_stride'] == 1, 'FAIL: Failed to find 1 as the histogram_stride for AGE.' assert col['percentiles'][0] == 44.516, 'FAIL: Failed to find 43.516 as the 0.1% percentile for AGE. '+str(col['percentiles'][0]) assert col['percentiles'][1] == 50.79, 'FAIL: Failed to find 50.79 as the 1.0% percentile for AGE. '+str(col['percentiles'][1]) assert col['percentiles'][9] == 78, 'FAIL: Failed to find 78 as the 99.0% percentile for AGE. '+str(col['percentiles'][9]) assert col['percentiles'][10] == 79, 'FAIL: Failed to find 79 as the 99.9% percentile for AGE. '+str(col['percentiles'][10]) # NB: col['percentiles'] corresponds to probs=[0.001, 0.01, 0.1, 0.25, 0.333, 0.5, 0.667, 0.75, 0.9, 0.99, 0.999] # Test /Frames/{key}/columns/{label} for prostate.csv ### Wrong param summary_param_frames = a_node.frames_negetive(key='prostate_binomial', find_compatible_model=0) h2o_test_utils.validate_412_statusCode(summary_param_frames) h2o_test_utils.validate_412_InfoMessage(summary_param_frames, "Unknown parameter: find_compatible_model") #Test /Frames/{key}/export for prostate.csv ### Positive job = a_node.export(key='prostate_binomial', row_count=100, path="/Users/sureshvuyyuru/export", force="true")['job'] assert job['dest']['name'] == '/Users/sureshvuyyuru/export', "FAIL: Export Name is not as Expected" assert job['description'] == 'Export frame', "FAIL: Frame Descrion is NOT Correct" #Test /Frames/{key}/export for prostate.csv ### Wrong param job_negetive = a_node.export(key='prostate_binomial', raiseIfNon200=False, row_count=100, path="/Users/sureshvuyyuru/export", forces="true") h2o_test_utils.validate_412_statusCode(job_negetive) h2o_test_utils.validate_412_InfoMessage(job_negetive, 'Unknown parameter: forces') #Suresh domain ### Positive # Test /Frames/{key}/columns/{label}/domain for created domains = a_node.domain(key='iris_multinomial', raiseIfNon200=False, column='class', row_offset=0, row_count=100) domain = domains['domain'] #pp.pprint(domains) assert 'Iris-setosa' in domain[0], "FAIL: Does not find the domain value" assert 'Iris-virginica' in domain[0], "FAIL: Does not find the domain Value" #Suresh domain ### Negetive domains_negetive = a_node.domain(key='iris_multinomial', column='class', domain='Iris-setosa') h2o_test_utils.validate_412_statusCode(domains_negetive) h2o_test_utils.validate_412_InfoMessage(domains_negetive, 'Attempting to set output field: domain for class: class water.api.FramesV3') # Suresh -- ### delete Frame #Test DELETE /Frames/{key} for prostate.csv resp = a_node.delete_frame(key='prostate_delete') assert resp['row_count'] == 0, "FAIL: Row count is not Zero in delete frame" assert 'rows' not in resp, "FAIL: Row count is not Zero in delete frame" print("prostate_delete Frame has deleted...") # Test /SplitFrame for prostate.csv if h2o_test_utils.isVerbose(): print 'Testing SplitFrame with named destination_frames. . .' splits = a_node.split_frame(dataset='prostate_binomial', ratios=[0.8], destination_frames=['bigger', 'smaller']) frames = a_node.frames()['frames'] h2o_test_utils.validate_frame_exists(a_node, 'bigger', frames) h2o_test_utils.validate_frame_exists(a_node, 'smaller', frames) bigger = a_node.frames(key='bigger')['frames'][0] smaller = a_node.frames(key='smaller')['frames'][0] assert bigger['rows'] == 304, 'FAIL: 80/20 SplitFrame yielded the wrong number of rows. Expected: 304; got: ' + bigger['rows'] assert smaller['rows'] == 76, 'FAIL: 80/20 SplitFrame yielded the wrong number of rows. Expected: 76; got: ' + smaller['rows'] # TODO: h2o_test_utils.validate_job_exists(a_node, splits['frame_id']['name']) if h2o_test_utils.isVerbose(): print 'Testing SplitFrame with generated destination_frames. . .' splits = a_node.split_frame(dataset='prostate_binomial', ratios=[0.5]) frames = a_node.frames()['frames'] h2o_test_utils.validate_frame_exists(a_node, splits['destination_frames'][0]['name'], frames) h2o_test_utils.validate_frame_exists(a_node, splits['destination_frames'][1]['name'], frames) first = a_node.frames(key=splits['destination_frames'][0]['name'])['frames'][0] second = a_node.frames(key=splits['destination_frames'][1]['name'])['frames'][0] assert first['rows'] == 190, 'FAIL: 50/50 SplitFrame yielded the wrong number of rows. Expected: 190; got: ' + first['rows'] assert second['rows'] == 190, 'FAIL: 50/50 SplitFrame yielded the wrong number of rows. Expected: 190; got: ' + second['rows'] # TODO: h2o_test_utils.validate_job_exists(a_node, splits['frame_id']['name']) # Test /SplitFrame for prostate.csv ### Split negetive print 'Testing SplitFrame with Wrong params...' splits_neg = a_node.split_frame( raiseIfNon200=False, dataset='prostate_spt_negetive', ratio=[0.4], destination_frames=['bigger', 'smaller']) h2o_test_utils.validate_412_statusCode(splits_neg) h2o_test_utils.validate_412_InfoMessage(splits_neg, 'Unknown parameter: ratio') #Ratio must be between 0 and 1! return datasets