add new files

ab_lab/__init__.py

@@ -1,5 +1,5 @@
-from cluster_experiments.cupac import EmptyRegressor, TargetAggregation
-from cluster_experiments.experiment_analysis import (
+from ab_lab.cupac import EmptyRegressor, TargetAggregation
+from ab_lab.experiment_analysis import (
     ClusteredOLSAnalysis,
     ExperimentAnalysis,
     GeeExperimentAnalysis,
@@ -9,12 +9,12 @@
     SyntheticControlAnalysis,
     TTestClusteredAnalysis,
 )
-from cluster_experiments.inference.analysis_plan import AnalysisPlan
-from cluster_experiments.inference.dimension import Dimension
-from cluster_experiments.inference.hypothesis_test import HypothesisTest
-from cluster_experiments.inference.metric import Metric, RatioMetric, SimpleMetric
-from cluster_experiments.inference.variant import Variant
-from cluster_experiments.perturbator import (
+from ab_lab.inference.analysis_plan import AnalysisPlan
+from ab_lab.inference.dimension import Dimension
+from ab_lab.inference.hypothesis_test import HypothesisTest
+from ab_lab.inference.metric import Metric, RatioMetric, SimpleMetric
+from ab_lab.inference.variant import Variant
+from ab_lab.perturbator import (
     BetaRelativePerturbator,
     BetaRelativePositivePerturbator,
     BinaryPerturbator,
@@ -26,9 +26,9 @@
     SegmentedBetaRelativePerturbator,
     UniformPerturbator,
 )
-from cluster_experiments.power_analysis import NormalPowerAnalysis, PowerAnalysis
-from cluster_experiments.power_config import PowerConfig
-from cluster_experiments.random_splitter import (
+from ab_lab.power_analysis import NormalPowerAnalysis, PowerAnalysis
+from ab_lab.power_config import PowerConfig
+from ab_lab.random_splitter import (
     BalancedClusteredSplitter,
     BalancedSwitchbackSplitter,
     ClusteredSplitter,
@@ -40,7 +40,7 @@
     StratifiedSwitchbackSplitter,
     SwitchbackSplitter,
 )
-from cluster_experiments.washover import ConstantWashover, EmptyWashover, Washover
+from ab_lab.washover import ConstantWashover, EmptyWashover, Washover
 
 __all__ = [
     "ExperimentAnalysis",

ab_lab/inference/analysis_plan.py

@@ -2,12 +2,13 @@
 from typing import Any, Dict, List, Optional
 
 import pandas as pd
-from cluster_experiments.experiment_analysis import ExperimentAnalysis
-from cluster_experiments.inference.analysis_results import AnalysisPlanResults
-from cluster_experiments.inference.dimension import Dimension
-from cluster_experiments.inference.hypothesis_test import HypothesisTest
-from cluster_experiments.inference.metric import Metric
-from cluster_experiments.inference.variant import Variant
+
+from ab_lab.experiment_analysis import ExperimentAnalysis
+from ab_lab.inference.analysis_results import AnalysisPlanResults
+from ab_lab.inference.dimension import Dimension
+from ab_lab.inference.hypothesis_test import HypothesisTest
+from ab_lab.inference.metric import Metric
+from ab_lab.inference.variant import Variant
 
 logger = logging.getLogger(__name__)
 

ab_lab/inference/hypothesis_test.py

@@ -2,13 +2,14 @@
 from typing import Dict, List, Optional
 
 import pandas as pd
-from cluster_experiments.cupac import CupacHandler
-from cluster_experiments.experiment_analysis import ExperimentAnalysis, InferenceResults
-from cluster_experiments.inference.analysis_results import AnalysisPlanResults
-from cluster_experiments.inference.dimension import DefaultDimension, Dimension
-from cluster_experiments.inference.metric import Metric
-from cluster_experiments.inference.variant import Variant
-from cluster_experiments.power_config import analysis_mapping
+
+from ab_lab.cupac import CupacHandler
+from ab_lab.experiment_analysis import ExperimentAnalysis, InferenceResults
+from ab_lab.inference.analysis_results import AnalysisPlanResults
+from ab_lab.inference.dimension import DefaultDimension, Dimension
+from ab_lab.inference.metric import Metric
+from ab_lab.inference.variant import Variant
+from ab_lab.power_config import analysis_mapping
 
 
 class HypothesisTest:

examples/cupac_example_gbm.py

@@ -4,10 +4,10 @@
 import pandas as pd
 from sklearn.ensemble import HistGradientBoostingRegressor
 
-from cluster_experiments.experiment_analysis import GeeExperimentAnalysis
-from cluster_experiments.perturbator import ConstantPerturbator
-from cluster_experiments.power_analysis import PowerAnalysis
-from cluster_experiments.random_splitter import ClusteredSplitter
+from ab_lab.experiment_analysis import GeeExperimentAnalysis
+from ab_lab.perturbator import ConstantPerturbator
+from ab_lab.power_analysis import PowerAnalysis
+from ab_lab.random_splitter import ClusteredSplitter
 
 
 def generate_random_data(clusters, dates, N):

examples/cupac_example_target_mean.py

@@ -3,11 +3,11 @@
 import numpy as np
 import pandas as pd
 
-from cluster_experiments.cupac import TargetAggregation
-from cluster_experiments.experiment_analysis import GeeExperimentAnalysis
-from cluster_experiments.perturbator import ConstantPerturbator
-from cluster_experiments.power_analysis import PowerAnalysis
-from cluster_experiments.random_splitter import ClusteredSplitter
+from ab_lab.cupac import TargetAggregation
+from ab_lab.experiment_analysis import GeeExperimentAnalysis
+from ab_lab.perturbator import ConstantPerturbator
+from ab_lab.power_analysis import PowerAnalysis
+from ab_lab.random_splitter import ClusteredSplitter
 
 
 def generate_random_data(clusters, dates, N, n_users=1000):

examples/long_example.py

@@ -3,10 +3,10 @@
 import numpy as np
 import pandas as pd
 
-from cluster_experiments.experiment_analysis import GeeExperimentAnalysis
-from cluster_experiments.perturbator import ConstantPerturbator
-from cluster_experiments.power_analysis import PowerAnalysis
-from cluster_experiments.random_splitter import ClusteredSplitter
+from ab_lab.experiment_analysis import GeeExperimentAnalysis
+from ab_lab.perturbator import ConstantPerturbator
+from ab_lab.power_analysis import PowerAnalysis
+from ab_lab.random_splitter import ClusteredSplitter
 
 
 def generate_random_data(clusters, dates, N):

examples/parallel_example.py

@@ -5,10 +5,10 @@
 import numpy as np
 import pandas as pd
 
-from cluster_experiments.experiment_analysis import GeeExperimentAnalysis
-from cluster_experiments.perturbator import ConstantPerturbator
-from cluster_experiments.power_analysis import PowerAnalysis
-from cluster_experiments.random_splitter import ClusteredSplitter
+from ab_lab.experiment_analysis import GeeExperimentAnalysis
+from ab_lab.perturbator import ConstantPerturbator
+from ab_lab.power_analysis import PowerAnalysis
+from ab_lab.random_splitter import ClusteredSplitter
 
 
 def generate_random_data(clusters, dates, N):

examples/short_example.py

@@ -3,10 +3,10 @@
 import numpy as np
 import pandas as pd
 
-from cluster_experiments.experiment_analysis import GeeExperimentAnalysis
-from cluster_experiments.perturbator import ConstantPerturbator
-from cluster_experiments.power_analysis import PowerAnalysis
-from cluster_experiments.random_splitter import ClusteredSplitter
+from ab_lab.experiment_analysis import GeeExperimentAnalysis
+from ab_lab.perturbator import ConstantPerturbator
+from ab_lab.power_analysis import PowerAnalysis
+from ab_lab.random_splitter import ClusteredSplitter
 
 
 def generate_random_data(clusters, dates, N):

examples/short_example_config.py

@@ -3,8 +3,8 @@
 import numpy as np
 import pandas as pd
 
-from cluster_experiments.power_analysis import PowerAnalysis
-from cluster_experiments.power_config import PowerConfig
+from ab_lab.power_analysis import PowerAnalysis
+from ab_lab.power_config import PowerConfig
 
 
 def generate_random_data(clusters, dates, N):

examples/short_example_dict.py

@@ -3,7 +3,7 @@
 import numpy as np
 import pandas as pd
 
-from cluster_experiments.power_analysis import PowerAnalysis
+from ab_lab.power_analysis import PowerAnalysis
 
 
 def generate_random_data(clusters, dates, N):

examples/short_example_paired_ttest.py

@@ -3,10 +3,10 @@
 import numpy as np
 import pandas as pd
 
-from cluster_experiments.experiment_analysis import PairedTTestClusteredAnalysis
-from cluster_experiments.perturbator import ConstantPerturbator
-from cluster_experiments.power_analysis import PowerAnalysis
-from cluster_experiments.random_splitter import StratifiedSwitchbackSplitter
+from ab_lab.experiment_analysis import PairedTTestClusteredAnalysis
+from ab_lab.perturbator import ConstantPerturbator
+from ab_lab.power_analysis import PowerAnalysis
+from ab_lab.random_splitter import StratifiedSwitchbackSplitter
 
 
 def generate_random_data(clusters, dates, N):

examples/short_example_synthetic_control.py

@@ -1,8 +1,8 @@
-from cluster_experiments.experiment_analysis import SyntheticControlAnalysis
-from cluster_experiments.perturbator import ConstantPerturbator
-from cluster_experiments.power_analysis import PowerAnalysisWithPreExperimentData
-from cluster_experiments.random_splitter import FixedSizeClusteredSplitter
-from cluster_experiments.synthetic_control_utils import generate_synthetic_control_data
+from ab_lab.experiment_analysis import SyntheticControlAnalysis
+from ab_lab.perturbator import ConstantPerturbator
+from ab_lab.power_analysis import PowerAnalysisWithPreExperimentData
+from ab_lab.random_splitter import FixedSizeClusteredSplitter
+from ab_lab.synthetic_control_utils import generate_synthetic_control_data
 
 df = generate_synthetic_control_data(10, "2022-01-01", "2022-01-30")
 

tests/analysis/test_analysis.py

@@ -2,7 +2,7 @@
 import pandas as pd
 import pytest
 
-from cluster_experiments.experiment_analysis import (
+from ab_lab.experiment_analysis import (
     ClusteredOLSAnalysis,
     ConfidenceInterval,
     ExperimentAnalysis,

tests/analysis/test_hypothesis.py

@@ -1,15 +1,15 @@
 import pandas as pd
 import pytest
 
-from cluster_experiments.experiment_analysis import (
+from ab_lab.experiment_analysis import (
     ClusteredOLSAnalysis,
     GeeExperimentAnalysis,
     MLMExperimentAnalysis,
     OLSAnalysis,
     SyntheticControlAnalysis,
     TTestClusteredAnalysis,
 )
-from cluster_experiments.synthetic_control_utils import generate_synthetic_control_data
+from ab_lab.synthetic_control_utils import generate_synthetic_control_data
 from tests.utils import generate_clustered_data
 
 

tests/analysis/test_synthetic_analysis.py

@@ -4,8 +4,8 @@
 import pandas as pd
 import pytest
 
-from cluster_experiments.experiment_analysis import SyntheticControlAnalysis
-from cluster_experiments.synthetic_control_utils import get_w
+from ab_lab.experiment_analysis import SyntheticControlAnalysis
+from ab_lab.synthetic_control_utils import get_w
 
 
 def generate_2_clusters_data(N, start_date, end_date):

tests/cupac/test_aggregator.py

@@ -2,7 +2,7 @@
 
 import pandas as pd
 
-from cluster_experiments.cupac import TargetAggregation
+from ab_lab.cupac import TargetAggregation
 
 
 def split_x_y(binary_df_agg: pd.DataFrame) -> Tuple[pd.DataFrame, pd.Series]:

tests/cupac/test_cupac_handler.py

@@ -4,7 +4,7 @@
 import pytest
 from sklearn.ensemble import HistGradientBoostingRegressor
 
-from cluster_experiments.cupac import CupacHandler, TargetAggregation
+from ab_lab.cupac import CupacHandler, TargetAggregation
 from tests.utils import generate_random_data
 
 N = 1_000

tests/inference/test_analysis_plan.py

@@ -2,12 +2,12 @@
 import pandas as pd
 import pytest
 
-from cluster_experiments.inference.analysis_plan import AnalysisPlan
-from cluster_experiments.inference.analysis_results import AnalysisPlanResults
-from cluster_experiments.inference.dimension import Dimension
-from cluster_experiments.inference.hypothesis_test import HypothesisTest
-from cluster_experiments.inference.metric import SimpleMetric
-from cluster_experiments.inference.variant import Variant
+from ab_lab.inference.analysis_plan import AnalysisPlan
+from ab_lab.inference.analysis_results import AnalysisPlanResults
+from ab_lab.inference.dimension import Dimension
+from ab_lab.inference.hypothesis_test import HypothesisTest
+from ab_lab.inference.metric import SimpleMetric
+from ab_lab.inference.variant import Variant
 
 # Set up constants for the data
 NUM_ORDERS = 10000

tests/inference/test_analysis_results.py

@@ -3,7 +3,7 @@
 import pandas as pd
 import pytest
 
-from cluster_experiments.inference.analysis_results import AnalysisPlanResults
+from ab_lab.inference.analysis_results import AnalysisPlanResults
 
 
 def test_analysis_plan_results_initialization():

tests/inference/test_dimension.py

@@ -1,6 +1,6 @@
 import pytest
 
-from cluster_experiments.inference.dimension import DefaultDimension, Dimension
+from ab_lab.inference.dimension import DefaultDimension, Dimension
 
 
 def test_dimension_initialization():

tests/inference/test_hypothesis_test.py

@@ -2,13 +2,13 @@
 import pandas as pd
 import pytest
 
-from cluster_experiments import TargetAggregation
-from cluster_experiments.experiment_analysis import ClusteredOLSAnalysis
-from cluster_experiments.inference.dimension import Dimension
-from cluster_experiments.inference.hypothesis_test import HypothesisTest
-from cluster_experiments.inference.metric import SimpleMetric
-from cluster_experiments.inference.variant import Variant
-from cluster_experiments.power_config import analysis_mapping
+from ab_lab import TargetAggregation
+from ab_lab.experiment_analysis import ClusteredOLSAnalysis
+from ab_lab.inference.dimension import Dimension
+from ab_lab.inference.hypothesis_test import HypothesisTest
+from ab_lab.inference.metric import SimpleMetric
+from ab_lab.inference.variant import Variant
+from ab_lab.power_config import analysis_mapping
 
 # Set up constants for the data
 NUM_ORDERS = 10000

tests/inference/test_metric.py

@@ -1,7 +1,7 @@
 import pandas as pd
 import pytest
 
-from cluster_experiments.inference.metric import Metric, RatioMetric, SimpleMetric
+from ab_lab.inference.metric import Metric, RatioMetric, SimpleMetric
 
 # Sample DataFrame for testing
 sample_data = pd.DataFrame(

tests/inference/test_variant.py

@@ -1,6 +1,6 @@
 import pytest
 
-from cluster_experiments.inference.variant import Variant
+from ab_lab.inference.variant import Variant
 
 
 def test_variant_initialization():

tests/perturbator/test_perturbator.py

@@ -2,7 +2,7 @@
 import pandas as pd
 import pytest
 
-from cluster_experiments.perturbator import (
+from ab_lab.perturbator import (
     BetaRelativePerturbator,
     BetaRelativePositivePerturbator,
     BinaryPerturbator,
@@ -13,7 +13,7 @@
     SegmentedBetaRelativePerturbator,
     UniformPerturbator,
 )
-from cluster_experiments.power_config import PowerConfig
+from ab_lab.power_config import PowerConfig
 
 
 def test_binary_perturbator_from_config():

tests/power_analysis/conftest.py

@@ -4,15 +4,15 @@
 import pandas as pd
 import pytest
 
-from cluster_experiments.cupac import TargetAggregation
-from cluster_experiments.experiment_analysis import (
+from ab_lab.cupac import TargetAggregation
+from ab_lab.experiment_analysis import (
     ClusteredOLSAnalysis,
     GeeExperimentAnalysis,
     MLMExperimentAnalysis,
 )
-from cluster_experiments.perturbator import ConstantPerturbator
-from cluster_experiments.power_analysis import PowerAnalysis
-from cluster_experiments.random_splitter import (
+from ab_lab.perturbator import ConstantPerturbator
+from ab_lab.power_analysis import PowerAnalysis
+from ab_lab.random_splitter import (
     ClusteredSplitter,
     StratifiedSwitchbackSplitter,
 )

tests/power_analysis/test_multivariate.py

@@ -1,6 +1,6 @@
 import pytest
 
-from cluster_experiments import (
+from ab_lab import (
     ConstantPerturbator,
     NonClusteredSplitter,
     OLSAnalysis,