nollIndices configurable from tasks.

python/lsst/ts/wep/task/calcZernikesTask.py

@@ -131,7 +131,7 @@ def __init__(self, **kwargs) -> None:
         # Create subtasks
         self.estimateZernikes = self.config.estimateZernikes
         self.makeSubtask("estimateZernikes")
-        self.maxNollIndex = self.estimateZernikes.config.maxNollIndex
+        self.nollIndices = self.estimateZernikes.config.nollIndices
 
         self.combineZernikes = self.config.combineZernikes
         self.makeSubtask("combineZernikes")
@@ -165,7 +165,7 @@ def initZkTable(self) -> QTable:
             ("intra_frac_bad_pix", "<f4"),
             ("extra_frac_bad_pix", "<f4"),
         ]
-        for j in range(4, self.maxNollIndex + 1):
+        for j in self.nollIndices:
             dtype.append((f"Z{j}", "<f4"))
 
         table = QTable(dtype=dtype)
@@ -175,7 +175,7 @@ def initZkTable(self) -> QTable:
         table["extra_field"].unit = u.deg
         table["intra_centroid"].unit = u.pixel
         table["extra_centroid"].unit = u.pixel
-        for j in range(4, self.maxNollIndex + 1):
+        for j in self.nollIndices:
             table[f"Z{j}"].unit = u.nm
 
         return table
@@ -215,8 +215,8 @@ def createZkTable(
                 "label": "average",
                 "used": True,
                 **{
-                    f"Z{j}": zkCoeffCombined.combinedZernikes[j - 4] * u.micron
-                    for j in range(4, self.maxNollIndex + 1)
+                    f"Z{j}": zkCoeffCombined.combinedZernikes[i] * u.micron
+                    for i, j in enumerate(self.nollIndices)
                 },
                 "intra_field": np.nan,
                 "extra_field": np.nan,
@@ -248,7 +248,7 @@ def createZkTable(
             row["label"] = f"pair{i+1}"
             row["used"] = not flag
             row.update(
-                {f"Z{j}": zk[j - 4] * u.micron for j in range(4, self.maxNollIndex + 1)}
+                {f"Z{j}": zk[i] * u.micron for i, j in enumerate(self.nollIndices)}
             )
             row["intra_field"] = (
                 (np.array(np.nan, dtype=pos2f_dtype) * u.deg)
@@ -357,8 +357,8 @@ def empty(self) -> pipeBase.Struct:
             "DEFOCAL_TYPE",
         ]
         return pipeBase.Struct(
-            outputZernikesRaw=np.atleast_2d(np.full(self.maxNollIndex - 3, np.nan)),
-            outputZernikesAvg=np.atleast_2d(np.full(self.maxNollIndex - 3, np.nan)),
+            outputZernikesRaw=np.atleast_2d(np.full(len(self.nollIndices), np.nan)),
+            outputZernikesAvg=np.atleast_2d(np.full(len(self.nollIndices), np.nan)),
             zernikes=self.initZkTable(),
             donutQualityTable=QTable({name: [] for name in qualityTableCols}),
         )

python/lsst/ts/wep/task/estimateZernikesBase.py

@@ -45,10 +45,11 @@ class EstimateZernikesBaseConfig(pexConfig.Config):
         dtype=str,
         optional=True,
     )
-    maxNollIndex = pexConfig.Field(
+    nollIndices = pexConfig.ListField(
         dtype=int,
-        default=28,
-        doc="The maximum Zernike Noll index estimated.",
+        default=tuple(range(4, 29)),
+        doc="Noll indices for which you wish to estimate Zernike coefficients. "
+        + "Note these values must be unique, ascending, and >= 4.",
     )
     startWithIntrinsic = pexConfig.Field(
         dtype=bool,
@@ -60,15 +61,6 @@ class EstimateZernikesBaseConfig(pexConfig.Config):
         default=False,
         doc="If True, returns wavefront deviation. If False, returns full OPD.",
     )
-    return4Up = pexConfig.Field(
-        dtype=bool,
-        default=True,
-        doc="If True, the returned Zernike coefficients start with Noll index 4. "
-        + "If False, they follow the Galsim convention of starting with index 0 "
-        + "(which is meaningless), so the array index of the output corresponds "
-        + "to the Noll index. In this case, indices 0-3 are always set to zero, "
-        + "because they are not estimated by our pipeline.",
-    )
     binning = pexConfig.Field(
         dtype=int,
         default=1,
@@ -260,10 +252,9 @@ def run(
             algoName=self.wfAlgoName,
             algoConfig=self.wfAlgoConfig,
             instConfig=instrument,
-            jmax=self.config.maxNollIndex,
+            nollIndices=self.config.nollIndices,
             startWithIntrinsic=self.config.startWithIntrinsic,
             returnWfDev=self.config.returnWfDev,
-            return4Up=self.config.return4Up,
             units="um",
             saveHistory=self.config.saveHistory,
         )

tests/task/test_calcZernikesTieTaskCwfs.py

@@ -281,3 +281,32 @@ def testUnevenPairs(self):
 
         # Now estimate Zernikes
         self.task.run(stampsExtra, stampsIntra)
+
+    def testNollIndices(self):
+        # Load the stamps
+        donutStampDir = os.path.join(self.testDataDir, "donutImg", "donutStamps")
+        donutStampsExtra = DonutStamps.readFits(
+            os.path.join(donutStampDir, "R04_SW0_donutStamps.fits")
+        )
+        donutStampsIntra = DonutStamps.readFits(
+            os.path.join(donutStampDir, "R04_SW1_donutStamps.fits")
+        )
+
+        # Estimate Zernikes 4, 5, 6
+        self.task.config.estimateZernikes.nollIndices = [4, 5, 6]
+        zk0 = self.task.estimateZernikes.run(
+            donutStampsExtra, donutStampsIntra
+        ).zernikes[0]
+
+        # Estimate Zernikes 4, 5, 6, 10, 11
+        self.task.config.estimateZernikes.nollIndices = [4, 5, 6, 10, 11]
+        zk1 = self.task.estimateZernikes.run(
+            donutStampsExtra, donutStampsIntra
+        ).zernikes[0]
+
+        # Check lengths
+        self.assertEqual(len(zk0), 3)
+        self.assertEqual(len(zk1), 5)
+
+        # Check that 4, 5, 6 are independent of 10, 11
+        self.assertTrue(np.all(np.abs(zk1[:3] - zk0) < 0.035))