Convert remaining docstrings to numpydoc style

brainglobe_utils/image/binning.py

@@ -3,11 +3,19 @@
 
 def get_bins(image_size, bin_sizes):
     """
-    Given an image size, and bin size, return a list of the bin boundaries
-    :param image_size: Size of the final image (tuple/list)
-    :param bin_sizes: Bin sizes corresponding to the dimensions of
-    "image_size" (tuple/list)
-    :return: List of arrays of bin boundaries
+    Given an image size, and bin size, return a list of the bin boundaries.
+
+    Parameters
+    ----------
+    image_size : tuple of int or list of int
+        Size of the final image
+    bin_sizes : tuple of int or list of int
+        Bin sizes corresponding to the dimensions of "image_size"
+
+    Returns
+    -------
+    list of np.ndarray
+        List of arrays of bin boundaries
     """
     bins = []
     for dim in range(0, len(image_size)):

brainglobe_utils/image/masking.py

@@ -4,11 +4,21 @@
 def mask_image_threshold(image, masking_image, threshold=0):
     """
     Mask one image, based on the values in another image that are above a
-    threshold
-    :param image: Input image
-    :param masking_image: Image to base the mask on (same shape as image)
-    :param threshold: Threshold to base the mask on
-    :return: Masked image
+    threshold.
+
+    Parameters
+    ----------
+    image : np.ndarray
+        Input image
+    masking_image : np.ndarray
+        Image to base the mask on (same shape as image)
+    threshold : int, optional
+        Threshold to base the mask on
+
+    Returns
+    -------
+    np.ndarray
+        Masked image
     """
     masking_image = make_mask(masking_image, threshold=threshold)
     return image * masking_image
@@ -17,11 +27,20 @@ def mask_image_threshold(image, masking_image, threshold=0):
 def make_mask(masking_image, threshold=0):
     """
     Given an image, and an optional threshold, returns a binary image that can
-    be used as a mask
-    :param masking_image: nD image
-    :param threshold: Optional threshold, default 0. Values above this are
-    included in the mask. Values below this are not.
-    :return: Binary mask
+    be used as a mask.
+
+    Parameters
+    ----------
+    masking_image : np.ndarray
+        nD image
+    threshold : int, optional
+        Optional threshold, default 0. Values above this are
+        included in the mask. Values below this are not.
+
+    Returns
+    -------
+    np.ndarray
+        Binary mask
     """
     mask = np.copy(masking_image)
     mask[masking_image <= threshold] = 0

brainglobe_utils/image/scale.py

@@ -5,9 +5,15 @@ def scale_to_16_bits(img):
     """
     Normalise the input image to the full 0-2^16 bit depth.
 
-    :param np.array img: The input image
-    :return: The normalised image
-    :rtype: np.array
+    Parameters
+    ----------
+    img : np.ndarray
+        The input image
+
+    Returns
+    -------
+    np.ndarray
+        The normalised image
     """
     normalised = img / img.max()
     return normalised * (2**16 - 1)
@@ -18,9 +24,15 @@ def scale_and_convert_to_16_bits(img):
     Normalise the input image to the full 0-2^16 bit depth, and return as
     type: "np.uint16".
 
-    :param np.array img: The input image
-    :return: The normalised, 16 bit image
-    :rtype: np.array
+    Parameters
+    ----------
+    img : np.ndarray
+        The input image
+
+    Returns
+    -------
+    np.ndarray
+        The normalised, 16 bit image
     """
     img = scale_to_16_bits(img)
     return img.astype(np.uint16, copy=False)

brainglobe_utils/pandas/misc.py

@@ -4,18 +4,34 @@
 
 def initialise_df(*column_names):
     """
-    Initialise a pandasdataframe with n column names
-    :param str column_names: N column names
-    :return: Empty pandas dataframe with specified column names
+    Initialise a pandas dataframe with n column names.
+
+    Parameters
+    ----------
+    *column_names : str
+        N column names
+
+    Returns
+    -------
+    pd.DataFrame
+        Empty pandas dataframe with specified column names
     """
     return pd.DataFrame(columns=column_names)
 
 
 def sanitise_df(df):
     """
-    Replaces infinite values in a dataframe with NaN
-    :param df: Any dataframe
-    :return: Dataframe with Inf replaced with NaN
+    Replaces infinite values in a dataframe with NaN.
+
+    Parameters
+    ----------
+    df : pd.DataFrame
+        Any dataframe
+
+    Returns
+    -------
+    pd.DataFrame
+        Dataframe with Inf replaced with NaN.
     """
     df = df.replace(np.inf, np.nan)
     return df
@@ -25,14 +41,25 @@ def safe_pandas_concat(df1: pd.DataFrame, df2: pd.DataFrame) -> pd.DataFrame:
     """
     Concatenate two DataFrames without relying on deprecated functionality
     when one of the DataFrames is empty.
-    If df1 and df2 are non-empty, return the concatenation.
+
+    If df1 and df2 are non-empty, return the concatenation. df2 will extend df1
+    in the resulting DataFrame.
     If df1 is empty and df2 is not, return a copy of df2.
     If df1 is non-empty and df2 is, return a copy of df1.
     If df1 and df2 are empty, return an empty DataFrame with the same column
     names as df1.
-    :param df1: DataFrame to concatenate.
-    :param df2: DataFrame to concatenate.
-    :returns: DataFrame formed from concatenation of df1 and df2.
+
+    Parameters
+    ----------
+    df1 : pd.DataFrame
+        DataFrame to concatenate.
+    df2 : pd.DataFrame
+        DataFrame to concatenate.
+
+    Returns
+    -------
+    pd.DataFrame
+        DataFrame formed from concatenation of df1 and df2.
     """
     if df1.empty and df2.empty:
         return pd.DataFrame(columns=df1.columns)

tests/tests/test_brainreg/test_transform.py

@@ -31,12 +31,11 @@ def test_transform_points_from_downsampled_to_atlas_space(
     * check that deformation field of ones maps to 1,1,1*resolution
     * check that too small deformation field maps points to out-of-bounds
 
-    Args:
-        mocker: The mocker object used to patch the reading of deformation
-                field tiffs.
-
-    Returns:
-        None
+    Parameters
+    ----------
+    mocker : pytest_mock.plugin.MockerFixture
+        The mocker object used to patch the reading of deformation
+        field tiffs.
     """
     mocker.patch(
         "brainglobe_utils.brainreg.transform.tifffile.imread",