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