fix see also paths

starfish/_codebook/codebook.py

@@ -514,9 +514,9 @@ def decode_metric(
             norm_order: int, metric: str='euclidean'
     ) -> IntensityTable:
         """
-        Assigns intensity patterns that have been extracted from an :py:class:`ImageStack` and
-        stored in an :py:class:`IntensityTable` by a :py:class:`SpotFinder` to the gene targets that
-        they encode.
+        Assigns intensity patterns that have been extracted from an :py:class:`~starfish.ImageStack`
+        and stored in an :py:class:`~starfish.IntensityTable` by
+        :py:class:`starfish.spots.Decode` to the gene targets that they encode.
 
         This method carries out the assignment by first normalizing both the codes and the
         recovered intensities to be unit magnitude using an L2 norm, and then finds the closest
@@ -539,8 +539,8 @@ def decode_metric(
         metric : str
             the sklearn metric string to pass to NearestNeighbors
 
-        See Also
-        --------
+        Notes
+        -----
         The available norms for this function can be found at the following link:
         https://docs.scipy.org/doc/numpy-1.14.0/reference/generated/numpy.linalg.norm.html
         The available metrics for this function can be found at the following link:
@@ -580,9 +580,9 @@ def decode_metric(
 
     def decode_per_round_max(self, intensities: IntensityTable) -> IntensityTable:
         """
-        Assigns intensity patterns that have been extracted from an :py:class:`ImageStack` and
-        stored in an :py:class:`IntensityTable` by a :py:class:`SpotFinder` to the gene targets that
-        they encode.
+        Assigns intensity patterns that have been extracted from an :py:class:`~starfish.ImageStack`
+        and stored in an :py:class:`~starfish.IntensityTable` by
+        :py:class:`starfish.spots.Decode` to the gene targets that they encode.
 
         This method carries out the assignment by identifying the maximum-intensity channel for each
         round, and assigning each spot to a code if the maximum-intensity pattern exists in the

starfish/_intensity_table/intensity_table.py

@@ -233,8 +233,8 @@ def to_mermaid(self, filename: str) -> pd.DataFrame:
         filename : str
             Name for compressed-gzipped MERMAID data file. Should end in '.csv.gz'.
 
-        See Also
-        --------
+        Notes
+        -----
         https://github.com/JEFworks/MERmaid
 
         """

starfish/spots/_decode/_base.py

@@ -18,7 +18,7 @@ class Decode(PipelineComponent):
     (round, channel) pairs to targets. For coded assays, these codebooks can be much more complex.
 
     Example codebooks are associated with each experiment in :py:mod:`starfish.data` and can
-    be accessed with :py:meth`Experiment.codebook`.
+    be accessed with :py:meth`starfish.Experiment.codebook`.
     """
     @classmethod
     def _cli_run(cls, ctx, instance):

starfish/spots/_detect_spots/blob.py

@@ -48,8 +48,8 @@ class BlobDetector(DetectSpotsAlgorithmBase):
     detector_method: str ['blob_dog', 'blob_doh', 'blob_log']
         name of the type of detection method used from skimage.feature, default: blob_log
 
-    See Also
-    --------
+    Notes
+    -----
     http://scikit-image.org/docs/dev/auto_examples/features_detection/plot_blob.html
 
     """

starfish/spots/_detect_spots/trackpy_local_max_peak_finder.py

@@ -61,8 +61,8 @@ class TrackpyLocalMaxPeakFinder(DetectSpotsAlgorithmBase):
     verbose : bool
         If True, report the percentage completed (default = False) during processing
 
-    See Also
-    --------
+    Notes
+    -----
     trackpy locate: http://soft-matter.github.io/trackpy/dev/generated/trackpy.locate.html
 
     """