juaml/junifer
Watch
3
0
Fork
You've already forked junifer
 0
Code Issues 14 Pull requests 2 Packages Activity Actions

[ENH]: Add feature_md5 argument to read_transform() #248

Merged
synchon merged 3 commits from update/read_transform_feature_md5 into main 2023-08-03 10:21:37 +00:00
Conversation 2 Commits 3 Files changed 2 +14 -6
2 changed files with 14 additions and 6 deletions
Download patch file Download diff file Expand all files Collapse all files

1
docs/changes/newsfragments/248.change Normal file
View file

@ -0,0 +1 @@
Add ``feature_md5`` argument to :func:`.read_transform()` by `Synchon Mandal`_

19
junifer/onthefly/read_transform.py
View file

@ -17,8 +17,9 @@ if TYPE_CHECKING:
def read_transform( def read_transform(
storage: Type["BaseFeatureStorage"], storage: Type["BaseFeatureStorage"],
feature_name: str,
transform: str, transform: str,
feature_name: Optional[str] = None,
feature_md5: Optional[str] = None,
transform_args: Optional[Tuple] = None, transform_args: Optional[Tuple] = None,
transform_kw_args: Optional[Dict] = None, transform_kw_args: Optional[Dict] = None,
) -> pd.DataFrame: ) -> pd.DataFrame:
@ -28,11 +29,13 @@ def read_transform(
---------- ----------
storage : storage-like storage : storage-like
The storage class, for example, SQLiteFeatureStorage. The storage class, for example, SQLiteFeatureStorage.
feature_name : str
Name of the feature to read.
transform : str transform : str
The kind of transform formatted as ``<package>_<function>``, The kind of transform formatted as ``<package>_<function>``,
for example, ``bctpy_degrees_und``. for example, ``bctpy_degrees_und``.
feature_name : str, optional
Name of the feature to read (default None).
feature_md5 : str, optional
MD5 hash of the feature to read (default None).
transform_args : tuple, optional transform_args : tuple, optional
The positional arguments for the callable of ``transform`` The positional arguments for the callable of ``transform``
(default None). (default None).
@ -62,7 +65,9 @@ def read_transform(
transform_kw_args = transform_kw_args or {} transform_kw_args = transform_kw_args or {}
# Read storage # Read storage
stored_data = storage.read(feature_name=feature_name) # type: ignore stored_data = storage.read(
feature_name=feature_name, feature_md5=feature_md5
) # type: ignore
# Retrieve package and function # Retrieve package and function
package, func_str = transform.split("_", 1) package, func_str = transform.split("_", 1)
# Condition for package # Condition for package
@ -105,7 +110,8 @@ def read_transform(
# Apply function and store subject-wise # Apply function and store subject-wise
output_list = [] output_list = []
logger.debug( logger.debug(
f"Computing '{package}.{func_str}' for feature {feature_name} ..." f"Computing '{package}.{func_str}' for feature "
f"{feature_name or feature_md5} ..."
) )
for subject in range(stored_data["data"].shape[2]): for subject in range(stored_data["data"].shape[2]):
output = func( output = func(
@ -119,7 +125,8 @@ def read_transform(
idx_df = pd.DataFrame(data=stored_data["element"]) idx_df = pd.DataFrame(data=stored_data["element"])
# Create multiindex from dataframe # Create multiindex from dataframe
logger.debug( logger.debug(
f"Generating pandas.MultiIndex for feature {feature_name} ..." "Generating pandas.MultiIndex for feature "
f"{feature_name or feature_md5} ..."
) )
data_idx = pd.MultiIndex.from_frame(df=idx_df) data_idx = pd.MultiIndex.from_frame(df=idx_df)