Test Data¶
Utility methods to load sample (test) data that are used in unit tests through this project.
Source code in epstats/toolkit/testing/test_data.py
class TestData:
"""
Utility methods to load sample (test) data that are used in unit tests through this
project.
"""
@classmethod
def load_goals_agg(cls, exp_id: str = None) -> pd.DataFrame:
"""
Load sample of aggregated test data to evaluate metrics. We use this dataset
in unit testing and we are making it available here for other possible use-cases too.
See `load_evaluations` set of functions to load corresponding evaluation results.
Arguments:
exp_id: experiment id
"""
with files(resources) / "goals_agg.csv" as df_file:
df = pd.read_csv(df_file, sep="\t")
return df[df.exp_id == exp_id] if exp_id is not None else df
@classmethod
def load_goals_simple_agg(cls) -> pd.DataFrame:
"""
Load sample of aggregated test data in simple wide format. File `goals_simple_agg.csv` contains only one
experiment, so it is sufficient to just open it.
We use this dataset in unit testing and we are making it available here for other possible use-cases too.
See `load_evaluations` set of functions to load corresponding evaluation results.
"""
with files(resources) / "goals_simple_agg.csv" as df_file:
df = pd.read_csv(df_file, sep="\t")
return df
@classmethod
def load_goals_by_unit(cls, exp_id: str = None) -> pd.DataFrame:
"""
Load sample of test data by unit to evaluate metrics. We use this dataset
in unit testing and we are making it available here for other possible use-cases too.
See `load_evaluations` set of functions to load corresponding evaluation results.
Arguments:
exp_id: experiment id
"""
with files(resources) / "goals_by_unit.csv" as df_file:
df = pd.read_csv(df_file, sep="\t")
return df[df.exp_id == exp_id] if exp_id is not None else df
@classmethod
def load_evaluations_checks(cls, exp_id: str = None) -> pd.DataFrame:
"""
Load checks (SRM) evaluations results. This data can be used to do asserts against
after running evaluation on [pre-aggregated][epstats.toolkit.testing.test_data.TestData.load_goals_agg]
or [by-unit][epstats.toolkit.testing.test_data.TestData.load_goals_by_unit] test data.
Arguments:
exp_id: experiment id
"""
with files(resources) / "evaluations_checks.csv" as df_file:
df = pd.read_csv(df_file, sep="\t")
return df[df.exp_id == exp_id] if exp_id is not None else df
@classmethod
def load_evaluations_exposures(cls, exp_id: str = None) -> pd.DataFrame:
"""
Load exposures evaluations results. This data can be used to do asserts against
after running evaluation on [pre-aggregated][epstats.toolkit.testing.test_data.TestData.load_goals_agg]
or [by-unit][epstats.toolkit.testing.test_data.TestData.load_goals_by_unit] test data.
Arguments:
exp_id: experiment id
"""
with files(resources) / "evaluations_exposures.csv" as df_file:
df = pd.read_csv(df_file, sep="\t")
return df[df.exp_id == exp_id] if exp_id is not None else df
@classmethod
def load_evaluations_metrics(cls, exp_id: str = None) -> pd.DataFrame:
"""
Load metric evaluations results. This data can be used to do asserts against
after running evaluation on [pre-aggregated][epstats.toolkit.testing.test_data.TestData.load_goals_agg]
or [by-unit][epstats.toolkit.testing.test_data.TestData.load_goals_by_unit] test data.
Arguments:
exp_id: experiment id
"""
with files(resources) / "evaluations_metrics.csv" as df_file:
df = pd.read_csv(df_file, sep="\t")
return df[df.exp_id == exp_id] if exp_id is not None else df
load_evaluations_checks(exp_id=None)
classmethod
¶
Load checks (SRM) evaluations results. This data can be used to do asserts against after running evaluation on pre-aggregated or by-unit test data.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
exp_id |
str |
experiment id |
None |
Source code in epstats/toolkit/testing/test_data.py
@classmethod
def load_evaluations_checks(cls, exp_id: str = None) -> pd.DataFrame:
"""
Load checks (SRM) evaluations results. This data can be used to do asserts against
after running evaluation on [pre-aggregated][epstats.toolkit.testing.test_data.TestData.load_goals_agg]
or [by-unit][epstats.toolkit.testing.test_data.TestData.load_goals_by_unit] test data.
Arguments:
exp_id: experiment id
"""
with files(resources) / "evaluations_checks.csv" as df_file:
df = pd.read_csv(df_file, sep="\t")
return df[df.exp_id == exp_id] if exp_id is not None else df
load_evaluations_exposures(exp_id=None)
classmethod
¶
Load exposures evaluations results. This data can be used to do asserts against after running evaluation on pre-aggregated or by-unit test data.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
exp_id |
str |
experiment id |
None |
Source code in epstats/toolkit/testing/test_data.py
@classmethod
def load_evaluations_exposures(cls, exp_id: str = None) -> pd.DataFrame:
"""
Load exposures evaluations results. This data can be used to do asserts against
after running evaluation on [pre-aggregated][epstats.toolkit.testing.test_data.TestData.load_goals_agg]
or [by-unit][epstats.toolkit.testing.test_data.TestData.load_goals_by_unit] test data.
Arguments:
exp_id: experiment id
"""
with files(resources) / "evaluations_exposures.csv" as df_file:
df = pd.read_csv(df_file, sep="\t")
return df[df.exp_id == exp_id] if exp_id is not None else df
load_evaluations_metrics(exp_id=None)
classmethod
¶
Load metric evaluations results. This data can be used to do asserts against after running evaluation on pre-aggregated or by-unit test data.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
exp_id |
str |
experiment id |
None |
Source code in epstats/toolkit/testing/test_data.py
@classmethod
def load_evaluations_metrics(cls, exp_id: str = None) -> pd.DataFrame:
"""
Load metric evaluations results. This data can be used to do asserts against
after running evaluation on [pre-aggregated][epstats.toolkit.testing.test_data.TestData.load_goals_agg]
or [by-unit][epstats.toolkit.testing.test_data.TestData.load_goals_by_unit] test data.
Arguments:
exp_id: experiment id
"""
with files(resources) / "evaluations_metrics.csv" as df_file:
df = pd.read_csv(df_file, sep="\t")
return df[df.exp_id == exp_id] if exp_id is not None else df
load_goals_agg(exp_id=None)
classmethod
¶
Load sample of aggregated test data to evaluate metrics. We use this dataset in unit testing and we are making it available here for other possible use-cases too.
See load_evaluations
set of functions to load corresponding evaluation results.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
exp_id |
str |
experiment id |
None |
Source code in epstats/toolkit/testing/test_data.py
@classmethod
def load_goals_agg(cls, exp_id: str = None) -> pd.DataFrame:
"""
Load sample of aggregated test data to evaluate metrics. We use this dataset
in unit testing and we are making it available here for other possible use-cases too.
See `load_evaluations` set of functions to load corresponding evaluation results.
Arguments:
exp_id: experiment id
"""
with files(resources) / "goals_agg.csv" as df_file:
df = pd.read_csv(df_file, sep="\t")
return df[df.exp_id == exp_id] if exp_id is not None else df
load_goals_by_unit(exp_id=None)
classmethod
¶
Load sample of test data by unit to evaluate metrics. We use this dataset in unit testing and we are making it available here for other possible use-cases too.
See load_evaluations
set of functions to load corresponding evaluation results.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
exp_id |
str |
experiment id |
None |
Source code in epstats/toolkit/testing/test_data.py
@classmethod
def load_goals_by_unit(cls, exp_id: str = None) -> pd.DataFrame:
"""
Load sample of test data by unit to evaluate metrics. We use this dataset
in unit testing and we are making it available here for other possible use-cases too.
See `load_evaluations` set of functions to load corresponding evaluation results.
Arguments:
exp_id: experiment id
"""
with files(resources) / "goals_by_unit.csv" as df_file:
df = pd.read_csv(df_file, sep="\t")
return df[df.exp_id == exp_id] if exp_id is not None else df
load_goals_simple_agg()
classmethod
¶
Load sample of aggregated test data in simple wide format. File goals_simple_agg.csv
contains only one
experiment, so it is sufficient to just open it.
We use this dataset in unit testing and we are making it available here for other possible use-cases too.
See load_evaluations
set of functions to load corresponding evaluation results.
Source code in epstats/toolkit/testing/test_data.py
@classmethod
def load_goals_simple_agg(cls) -> pd.DataFrame:
"""
Load sample of aggregated test data in simple wide format. File `goals_simple_agg.csv` contains only one
experiment, so it is sufficient to just open it.
We use this dataset in unit testing and we are making it available here for other possible use-cases too.
See `load_evaluations` set of functions to load corresponding evaluation results.
"""
with files(resources) / "goals_simple_agg.csv" as df_file:
df = pd.read_csv(df_file, sep="\t")
return df