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made better docstrings #147

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Dec 18, 2022
Merged

made better docstrings #147

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44 changes: 25 additions & 19 deletions mesmerize_core/batch_utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -24,7 +24,7 @@ def set_parent_raw_data_path(path: Union[Path, str]) -> Path:
Parameters
----------
path: Union[Path, str]
path: Path or str
Full parent data path
"""
global PARENT_DATA_PATH
Expand All @@ -41,10 +41,11 @@ def set_parent_raw_data_path(path: Union[Path, str]) -> Path:
def get_parent_raw_data_path() -> Path:
"""
Get the global `PARENT_DATA_PATH`
Returns
-------
Path
global `PARENT_DATA_PATH`
global `PARENT_DATA_PATH` as a Path object
"""
global PARENT_DATA_PATH
Expand All @@ -59,6 +60,14 @@ def set_batch_path(self, path: Union[str, Path]):
self._data.attrs["batch_path"] = Path(path)

def get_batch_path(self) -> Path:
"""
Get the full path to the batch dataframe file
Returns
-------
Path
full path to the batch dataframe file as a Path object
"""
if "batch_path" in self._data.attrs.keys():
if self._data.attrs["batch_path"] is not None:
return self._data.attrs["batch_path"]
Expand All @@ -67,17 +76,18 @@ def get_batch_path(self) -> Path:

def resolve(self, path: Union[str, Path]) -> Path:
"""
Resolve the full path of ``path`` if possible, first tries batch_dir then raw_data_dir
Last resort plain resolve.
Resolve the full path of the passed ``path`` if possible, first tries
"batch_dir" then "raw_data_dir".
Parameters
----------
path: Union[str, Path]
path: str or Path
The relative path to resolve
Returns
-------
Full path with the batch path or raw data path appended
Path
Full path with the batch path or raw data path appended
"""
path = Path(path)
Expand All @@ -95,15 +105,16 @@ def resolve(self, path: Union[str, Path]) -> Path:
def split(self, path: Union[str, Path]):
"""
Split a full path into (batch_dir, relative_path) or (raw_data_dir, relative_path)
Parameters
----------
path: Union[str, Path]
path: str or Path
Full path to split with respect to batch_dir or raw_data_dir
Returns
-------
Tuple[Path, Path]
(<batch_dir or raw_data_dir>, <relative_path>)
(<batch_dir> or <raw_data_dir>, <relative_path>)
"""
path = Path(path)
Expand Down Expand Up @@ -139,11 +150,11 @@ class PathsSeriesExtension(_BasePathExtensions):

def load_batch(path: Union[str, Path]) -> pd.DataFrame:
"""
Load the batch pickle file, also sets the global `CURRENT_BATCH_PATH`
Load the batch dataframe pickle file
Parameters
----------
path: Union[str, Path])
path: str or Path
Returns
-------
Expand All @@ -163,13 +174,11 @@ def load_batch(path: Union[str, Path]) -> pd.DataFrame:
df.head()
"""
# global CURRENT_BATCH_PATH

path = validate_path(path)

df = pd.read_pickle(Path(path))

# CURRENT_BATCH_PATH = pathlib.Path(batch_file)

df.paths.set_batch_path(path)

return df
Expand All @@ -181,11 +190,11 @@ def create_batch(path: Union[str, Path], remove_existing: bool = False) -> pd.Da
Parameters
----------
path: Union[str. Path]
path to save the new batch DataFrame
path: str or Path
path to save the new batch DataFrame as a pickle file
remove_existing: bool
If `True`, remove an existing batch DataFrame file if it exists at the given `path`
If ``True``, remove an existing batch DataFrame file if it exists at the given `path`, default ``False``
Returns
-------
Expand Down Expand Up @@ -220,9 +229,6 @@ def create_batch(path: Union[str, Path], remove_existing: bool = False) -> pd.Da

df.to_pickle(path)

# global CURRENT_BATCH_PATH
# CURRENT_BATCH_PATH = path

return df


Expand Down
42 changes: 21 additions & 21 deletions mesmerize_core/caiman_extensions/cnmf.py
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Expand Up @@ -88,7 +88,8 @@ def __init__(self, s: pd.Series):
@validate("cnmf")
def get_cnmf_memmap(self, mode: str = "r") -> np.ndarray:
"""
Get the CNMF C-order memmap
Get the CNMF C-order memmap. This should NOT be used for viewing the
movie frames use ``caiman.get_input_movie()`` for that purpose.
Parameters
----------
Expand Down Expand Up @@ -189,13 +190,12 @@ def get_masks(
Parameters
----------
component_indices: optional, Union[np.ndarray, str]
component_indices: str or np.ndarray, optional
| indices of the components to include
| if ``np.ndarray``, uses these indices in the provided array
| if ``"good"`` uses good components, i.e. cnmf.estimates.idx_components
| if ``"bad"`` uses bad components, i.e. cnmf.estimates.idx_components_bad
| if not provided, ``None``, or ``"all"`` uses all components
| if ``"good"`` uses good components, i.e. ``Estimates.idx_components``
| if ``"bad"`` uses bad components, i.e. ``Estimates.idx_components_bad``
| if ``np.ndarray``, uses the indices in the provided array
threshold: float
threshold
Expand Down Expand Up @@ -264,12 +264,12 @@ def get_contours(
Parameters
----------
component_indices: optional, Union[np.ndarray, str]
component_indices: str or np.ndarray, optional
| indices of the components to include
| if ``np.ndarray``, uses these indices in the provided array
| if ``"good"`` uses good components, i.e. cnmf.estimates.idx_components
| if ``"bad"`` uses bad components, i.e. cnmf.estimates.idx_components_bad
| if not provided, ``None``, or ``"all"`` uses all components
| if ``"good"`` uses good components, i.e. ``Estimates.idx_components``
| if ``"bad"`` uses bad components, i.e. ``Estimates.idx_components_bad``
| if ``np.ndarray``, uses the indices in the provided array
swap_dim: bool
swap the x and y coordinates, use if the contours don't align with the cells in your image
Expand Down Expand Up @@ -366,12 +366,12 @@ def get_temporal(
Parameters
----------
component_indices: optional, Union[np.ndarray, str]
component_indices: str or np.ndarray, optional
| indices of the components to include
| if ``np.ndarray``, uses these indices in the provided array
| if ``"good"`` uses good components, i.e. cnmf.estimates.idx_components
| if ``"bad"`` uses bad components, i.e. cnmf.estimates.idx_components_bad
| if not provided, ``None``, or ``"all"`` uses all components
| if ``"good"`` uses good components, i.e. ``Estimates.idx_components``
| if ``"bad"`` uses bad components, i.e. ``Estimates.idx_components_bad``
| if ``np.ndarray``, uses the indices in the provided array
add_background: bool
if ``True``, add the temporal background, ``cnmf.estimates.C + cnmf.estimates.f``
Expand Down Expand Up @@ -660,7 +660,7 @@ def run_detrend_dfof(
) -> None:
"""
| Uses caiman's detrend_df_f.
| call ``cnmf.get_detrend_dfof()`` to get the values.
| call ``CNMF.get_detrend_dfof()`` to get the values.
| Sets ``CNMF.estimates.F_dff``
Warnings
Expand Down Expand Up @@ -728,12 +728,12 @@ def get_detrend_dfof(
Parameters
----------
component_indices: optional, Union[np.ndarray, str]
component_indices: str or np.ndarray, optional
| indices of the components to include
| if ``np.ndarray``, uses these indices in the provided array
| if ``"good"`` uses good components, i.e. cnmf.estimates.idx_components
| if ``"bad"`` uses bad components, i.e. cnmf.estimates.idx_components_bad
| if not provided, ``None``, or ``"all"`` uses all components
| if ``"good"`` uses good components, i.e. ``Estimates.idx_components``
| if ``"bad"`` uses bad components, i.e. ``Estimates.idx_components_bad``
| if ``np.ndarray``, uses the indices in the provided array
return_copy: bool
| if ``True`` returns a copy of the cached value in memory.
Expand Down Expand Up @@ -818,7 +818,7 @@ def run_eval(self, params: dict) -> None:
@validate("cnmf")
def get_good_components(self) -> np.ndarray:
"""
get the good component indices, ``CNMF.estimates.idx_components``
get the good component indices, ``Estimates.idx_components``
Returns
-------
Expand All @@ -833,7 +833,7 @@ def get_good_components(self) -> np.ndarray:
@validate("cnmf")
def get_bad_components(self) -> np.ndarray:
"""
get the bad component indices, ``CNMF.estimates.idx_components_bad``
get the bad component indices, ``Estimates.idx_components_bad``
Returns
-------
Expand Down
25 changes: 14 additions & 11 deletions mesmerize_core/caiman_extensions/common.py
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Expand Up @@ -164,8 +164,9 @@ def remove_item(self, index: Union[int, str, UUID], remove_data: bool = True, sa
Parameters
----------
index: Union[int, str, UUID]
The index of the batch item to remove from the DataFrame
index: int, str or UUID
The index of the batch item to remove from the DataFrame as a numerical ``int`` index, ``str`` representing
a UUID, or a UUID object.
remove_data: bool
if ``True`` removes all output data associated to the batch item from disk.
Expand Down Expand Up @@ -270,14 +271,14 @@ def get_children(self, index: Union[int, str, UUID]) -> List[UUID]:
Parameters
----------
index: Union[int, str, UUID]
the index of the mcorr item to get the children of
index: int, str, or UUID
the index of the mcorr item to get the children of, provided as a numerical ``int`` index, str representing
a UUID, or a UUID object
Returns
-------
List[UUID]
List of UUIDs of child CNMF items
"""

if not self._df.iloc[index]["algo"] == "mcorr":
Expand Down Expand Up @@ -311,12 +312,13 @@ def get_parent(self, index: Union[int, str, UUID]) -> Union[UUID, None]:
Parameters
----------
index: Union[int, str, UUID]
the index of the batch item to get the parent of
index: int, str, or UUID
the index of the batch item to get the parent of, provided as a numerical ``int`` index, str representing
a UUID, or a UUID object
Returns
-------
Union[UUID, None]
UUID or None
| if ``UUID``, this is the UUID of the batch item whose output was used for the input of the batch item at
the provided ``index``
Expand Down Expand Up @@ -408,8 +410,9 @@ def run(
Parameters
----------
backend: Optional[str]
One of the available backends, if none default is `COMPUTE_BACKEND_SUBPROCESS`
backend: str, optional
One of the available backends, default on Linux & Mac is ``"subprocess"``. Default on Windows is
``"local"`` since Windows is inconsistent in the way it launches subprocesses
**kwargs
any kwargs to pass to the backend
Expand Down Expand Up @@ -492,7 +495,7 @@ def get_input_movie(self, reader: callable = None) -> Union[np.ndarray, Any]:
Parameters
----------
reader: callable
a function that return an array-like
a function that take the input movie path and return an array-like
Returns
-------
Expand Down