Fix remaining Sphinx errors.

python/lsst/ip/isr/ampOffset.py

@@ -267,20 +267,23 @@ def getAmpAssociations(self, amps):
             and column index corresponds to the ampIds of a specific pair of
             amplifiers, and the matrix elements indicate their associations as
             follows:
-            0: No association
-            -1: Association exists (direction specified in the ampSides matrix)
-            n >= 1: Diagonal elements indicate the number of neighboring
-                    amplifiers for the corresponding ampId==row==column number.
+
+            * 0: No association
+            * -1: Association exists (direction specified in the ampSides
+              matrix)
+            * n >= 1: Diagonal elements indicate the number of neighboring
+              amplifiers for the corresponding ampId==row==column number.
 
         ampSides : `numpy.ndarray`
             An N x N matrix (N = the number of amplifiers) representing the amp
             side information corresponding to the `ampAssociations`
             matrix. The elements are integers defined as below:
-            -1: No side due to no association or the same amp (diagonals)
-            0: Side on the bottom
-            1: Side on the right
-            2: Side on the top
-            3: Side on the left
+
+            * -1: No side due to no association or the same amp (diagonals)
+            * 0: Side on the bottom
+            * 1: Side on the right
+            * 2: Side on the top
+            * 3: Side on the left
         """
         xCenters = [amp.getBBox().getCenterX() for amp in amps]
         yCenters = [amp.getBBox().getCenterY() for amp in amps]

python/lsst/ip/isr/isrStatistics.py

@@ -338,7 +338,7 @@ def measureCti(self, inputExp, overscans, gains):
 
         Returns
         -------
-        outputStats : `dict` [`str`, [`dict` [`str`,`float]]
+        outputStats : `dict` [`str`, [`dict` [`str`, `float`]]]
             Dictionary of measurements, keyed by amplifier name and
             statistics segment.
         """
@@ -462,7 +462,7 @@ def measureBanding(self, inputExp, overscans):
 
         Returns
         -------
-        outputStats : `dict` [`str`, [`dict` [`str`,`float]]
+        outputStats : `dict` [`str`, [`dict` [`str`, `float`]]]
             Dictionary of measurements, keyed by amplifier name and
             statistics segment.
         """
@@ -515,7 +515,7 @@ def measureProjectionStatistics(self, inputExp, overscans):
 
         Returns
         -------
-        outputStats : `dict` [`str`, [`dict` [`str`,`float]]
+        outputStats : `dict` [`str`, [`dict` [`str`, `float`]]]
             Dictionary of measurements, keyed by amplifier name and
             statistics segment.
         """
@@ -585,7 +585,7 @@ def copyCalibDistributionStatistics(self, inputExp, **kwargs):
 
         Returns
         -------
-        outputStats : `dict` [`str`, [`dict` [`str`,`float]]
+        outputStats : `dict` [`str`, [`dict` [`str`, `float`]]]
             Dictionary of measurements, keyed by amplifier name and
             statistics segment.
         """
@@ -643,7 +643,7 @@ def measureBiasShifts(self, inputExp, overscanResults):
 
         Returns
         -------
-        outputStats : `dict` [`str`, [`dict` [`str`,`float]]
+        outputStats : `dict` [`str`, [`dict` [`str`, `float`]]]
             Dictionary of measurements, keyed by amplifier name and
             statistics segment.
 
@@ -771,7 +771,7 @@ def measureAmpCorrelations(self, inputExp, overscanResults):
 
         Returns
         -------
-        outputStats : `dict` [`str`, [`dict` [`str`,`float`]]
+        outputStats : `dict` [`str`, [`dict` [`str`, `float`]]]
             Dictionary of measurements, keyed by amplifier name and
             statistics segment.
 
@@ -826,20 +826,21 @@ def measureDivisaderoStatistics(self, inputExp, **kwargs):
 
         Returns
         -------
-        outputStats : `dict` [`str`, [`dict` [`str`,`float]]
+        outputStats : `dict` [`str`, [`dict` [`str`, `float`]]]
             Dictionary of measurements, keyed by amplifier name and
             statistics segment.
             Measurements include
+
             - DIVISADERO_PROFILE: Robust mean of rows between
-                divisaderoProjection<Maximum|Minumum> on readout edge of ccd
-                normalized by a linear fit to the same rows.
+              divisaderoProjection<Maximum|Minumum> on readout edge of ccd
+              normalized by a linear fit to the same rows.
             - DIVISADERO_MAX_PAIR: Tuple of maximum of the absolute values of
-                the DIVISADERO_PROFILE, for number of pixels (specified by
-                divisaderoNumImpactPixels on left and right side of amp.
+              the DIVISADERO_PROFILE, for number of pixels (specified by
+              divisaderoNumImpactPixels on left and right side of amp.
             - DIVISADERO_MAX: Maximum of the absolute values of the
-                the DIVISADERO_PROFILE, for the divisaderoNumImpactPixels on
-                boundaries of neighboring amps (including the pixels in those
-                neighborboring amps).
+              the DIVISADERO_PROFILE, for the divisaderoNumImpactPixels on
+              boundaries of neighboring amps (including the pixels in those
+              neighborboring amps).
         """
         outputStats = {}
 

python/lsst/ip/isr/isrTask.py

@@ -1784,7 +1784,7 @@ def defineEffectivePtc(self, ptcDataset, detector, bfGains, overScans, metadata)
         with nominal gains and noise.
 
         Parameters
-        ------
+        ----------
         ptcDataset : `lsst.ip.isr.PhotonTransferCurveDataset`
             Input Photon Transfer Curve dataset.
         detector : `lsst.afw.cameraGeom.Detector`

python/lsst/ip/isr/ptcDataset.py

@@ -59,7 +59,7 @@ class PhotonTransferCurveDataset(IsrCalib):
     covMatrixSide : `int`, optional
         Maximum lag of measured covariances (size of square covariance
         matrices).
-    covMatrixSideFullCovFit : `int, optional
+    covMatrixSideFullCovFit : `int`, optional
         Maximum covariances lag for FULLCOVARIANCE fit. It should be less or
         equal than covMatrixSide.
     kwargs : `dict`, optional