Started tests for new stuff. Added plotting utils for pupil masks and…

… ImageMapper round trip.

policy/estimation/tie.yaml

@@ -8,6 +8,5 @@ compSequence: [4, 4, 6, 6, 13, 13, 13, 13, 22, 22, 22, 22, 22, 22]
 compGain: 0.6
 centerTol: 10.0e-9
 centerBinary: True
-centerSubPixel: False
 convergeTol: 10.0e-9
 saveHistory: False

policy/instruments/LsstCam.yaml

@@ -7,6 +7,7 @@ obscuration: 0.612 # fractional obscuration
 focalLength: 10.312 # effective focal length in meters
 defocalOffset: 1.5e-3 # defocal offset in meters
 pixelSize: 10.0e-6 # pixel size in meters
+refBand: r # band to use for BandLabel.REF
 wavelength: # effective wavelength per band, in meters
   u: 367.1e-9
   g: 482.7e-9
@@ -15,62 +16,61 @@ wavelength: # effective wavelength per band, in meters
   z: 869.1e-9
   y: 971.0e-9
 batoidModelName: LSST_{band}.yaml # name used to load the Batoid model
-batoidRefBand: r # band to use with Batoid when band == BandLabel.REF
 
 maskParams: # center and radius are in meters, theta in degrees
   M1Outer:
-    thetaMin: 0.00
-    center: [-7.890e-17, 2.013e-16, 1.768e-10, 2.978e-17]
-    radius: [-1.098e-16, -2.652e-15, 5.961e-15, 4.180e+00]
+    thetaMin: 0.0
+    center: [-7.88971e-17, 2.01334e-16, 1.76752e-10, 2.97835e-17]
+    radius: [-1.09847e-16, -2.65166e-15, 5.96051e-15, 4.18000e+00]
   M1Inner:
-    thetaMin: 0.00
-    center: [-1.834e-17, 1.314e-16, -4.792e-03, 8.014e-17]
-    radius: [-1.181e-15, 2.582e-15, -1.030e-15, 2.558e+00]
+    thetaMin: 0.0
+    center: [-1.83436e-17, 1.31384e-16, -4.79254e-03, 8.01445e-17]
+    radius: [-1.18085e-15, 2.58188e-15, -1.02954e-15, 2.55800e+00]
   M2Outer:
     thetaMin: 0.67
-    center: [-2.971e-05, 1.195e-03, -2.902e-01, -2.017e-04]
-    radius: [-1.274e-04, 8.016e-04, -1.107e-03, 4.497e+00]
+    center: [-2.97063e-05, 1.19495e-03, -2.90176e-01, -2.01690e-04]
+    radius: [-1.27356e-04, 8.01567e-04, -1.10665e-03, 4.49700e+00]
   M2Inner:
-    thetaMin: 0.00
-    center: [-1.623e-04, -8.488e-04, -2.909e-01, -2.258e-06]
-    radius: [2.317e-05, 2.541e-04, 1.269e-04, 2.371e+00]
+    thetaMin: 0.0
+    center: [-1.62275e-04, -8.48813e-04, -2.90949e-01, -2.25777e-06]
+    radius: [2.31676e-05, 2.54062e-04, 1.26852e-04, 2.37089e+00]
   M3Outer:
     thetaMin: 1.14
-    center: [-1.030e-03, -6.107e-03, -7.955e-01, 2.908e-05]
-    radius: [1.351e-04, -5.517e-04, 3.607e-03, 5.216e+00]
+    center: [-1.03001e-03, -6.10645e-03, -7.95453e-01, 2.90781e-05]
+    radius: [1.35117e-04, -5.51696e-04, 3.60650e-03, 5.21560e+00]
   M3Inner:
     thetaMin: 1.15
-    center: [-1.798e-03, 3.392e-03, -9.378e-01, 1.100e-03]
-    radius: [-6.097e-04, 5.360e-04, 1.755e-04, 1.222e+00]
+    center: [-1.79773e-03, 3.39167e-03, -9.37836e-01, 1.10023e-03]
+    radius: [-6.09716e-04, 5.36056e-04, 1.75529e-04, 1.22190e+00]
   L1Entrance:
     thetaMin: 1.48
-    center: [-7.045e-02, 8.504e-02, -1.800e+00, 1.875e-01]
-    radius: [6.528e-02, -2.652e-01, 4.832e-01, 6.473e+00]
+    center: [-7.04511e-02, 8.50359e-02, -1.80035e+00, 1.87490e-01]
+    radius: [6.52778e-02, -2.65192e-01, 4.83170e-01, 6.47299e+00]
   L1Exit:
     thetaMin: 1.54
-    center: [-1.096e-01, 2.800e-01, -2.139e+00, 3.921e-01]
-    radius: [1.021e-01, -4.587e-01, 8.313e-01, 6.387e+00]
+    center: [-1.09578e-01, 2.80004e-01, -2.13912e+00, 3.92063e-01]
+    radius: [1.02073e-01, -4.58671e-01, 8.31328e-01, 6.38674e+00]
   L2Entrance:
     thetaMin: 1.59
-    center: [-2.447e-01, 1.346e-01, -2.243e+00, -4.267e-02]
-    radius: [2.696e-01, -8.131e-01, 1.018e+00, 7.909e+00]
+    center: [-2.44731e-01, 1.34591e-01, -2.24336e+00, -4.26719e-02]
+    radius: [2.69553e-01, -8.13070e-01, 1.01816e+00, 7.90902e+00]
   L2Exit:
     thetaMin: 1.77
-    center: [-3.232e-02, -1.602e+00, 1.699e+00, -2.806e+00]
-    radius: [8.600e-03, 1.014e+00, -2.945e+00, 1.130e+01]
-  L3Entrance:
-    thetaMin: 1.81
-    center: [-6.929e+03, 3.837e+04, -7.093e+04, 4.373e+04]
-    radius: [6.991e+03, -3.876e+04, 7.169e+04, -4.421e+04]
-  L3Exit:
-    thetaMin: 1.88
-    center: [-7.625e+04, 4.382e+05, -8.394e+05, 5.361e+05]
-    radius: [7.651e+04, -4.398e+05, 8.428e+05, -5.383e+05]
+    center: [-3.23226e-02, -1.60235e+00, 1.69902e+00, -2.80647e+00]
+    radius: [8.59956e-03, 1.01450e+00, -2.94477e+00, 1.12953e+01]
   filterEntrance:
     thetaMin: 1.68
-    center: [-1.412e+02, 7.083e+02, -1.209e+03, 6.906e+02]
-    radius: [1.468e+02, -7.457e+02, 1.276e+03, -7.200e+02]
+    center: [-1.41191e+02, 7.08362e+02, -1.20873e+03, 6.90596e+02]
+    radius: [1.46814e+02, -7.45712e+02, 1.27571e+03, -7.19975e+02]
   filterExit:
     thetaMin: 1.72
-    center: [-2.332e+02, 1.201e+03, -2.090e+03, 1.218e+03]
-    radius: [2.407e+02, -1.251e+03, 2.184e+03, -1.265e+03]
+    center: [-2.33154e+02, 1.20100e+03, -2.09045e+03, 1.21830e+03]
+    radius: [2.40674e+02, -1.25103e+03, 2.18395e+03, -1.26502e+03]
+  L3Entrance:
+    thetaMin: 1.81
+    center: [-6.92919e+03, 3.83751e+04, -7.09271e+04, 4.37325e+04]
+    radius: [6.99082e+03, -3.87585e+04, 7.16872e+04, -4.42130e+04]
+  L3Exit:
+    thetaMin: 1.88
+    center: [-7.62502e+04, 4.38171e+05, -8.39431e+05, 5.36106e+05]
+    radius: [7.65102e+04, -4.39797e+05, 8.42756e+05, -5.38333e+05]

python/lsst/ts/wep/estimation/tie.py

@@ -70,10 +70,6 @@ class TIEAlgorithm(WfAlgorithm):
     centerBinary : bool, optional
         Whether to use a binary template when centering the image.
         Using a binary template is typically less accurate, but faster.
-    centerSubPixel : bool, optional
-        Whether to center the images with sub-pixel resolution.
-        In good conditions (i.e. low noise and good seeing), using a binary
-        template is typically less accurate, but faster.
     convergeTol : float, optional
         The maximum absolute change in any Zernike amplitude (in meters) between
         subsequent TIE iterations below which convergence is declared and iteration
@@ -94,7 +90,6 @@ def __init__(
         compGain: Optional[float] = None,
         centerTol: Optional[float] = None,
         centerBinary: Optional[bool] = None,
-        centerSubPixel: Optional[bool] = None,
         convergeTol: Optional[float] = None,
         saveHistory: Optional[bool] = None,
     ) -> None:
@@ -107,7 +102,6 @@ def __init__(
             compGain=compGain,
             centerTol=centerTol,
             centerBinary=centerBinary,
-            centerSubPixel=centerSubPixel,
             convergeTol=convergeTol,
             saveHistory=saveHistory,
         )
@@ -306,32 +300,6 @@ def centerBinary(self, value: bool) -> None:
 
         self._centerBinary = value
 
-    @property
-    def centerSubPixel(self) -> bool:
-        """Whether to center the donut with sub-pixel resolution."""
-        return self._centerSubPixel
-
-    @centerSubPixel.setter
-    def centerSubPixel(self, value: bool) -> None:
-        """Set whether to center the donut with sub-pixel resolution.
-
-        Parameters
-        ----------
-        value : bool
-            Whether to center the images with sub-pixel resolution.
-            In good conditions (i.e. low noise and good seeing), using a binary
-            template is typically less accurate, but faster.
-
-        Raises
-        ------
-        TypeError
-            If the value is not a boolean
-        """
-        if not isinstance(value, bool):
-            raise TypeError("centerSubPixel must be a boolean.")
-
-        self._centerSubPixel = value
-
     @property
     def convergeTol(self) -> float:
         """Mean abs. deviation in Zernikes (meters) at which the TIE loop terminates."""
@@ -585,13 +553,11 @@ def estimateWf(
                     intra,
                     zkCenter,
                     binary=self.centerBinary,
-                    subPixel=self.centerSubPixel,
                 )
                 extraCent = imageMapper.centerOnProjection(
                     extra,
                     zkCenter,
                     binary=self.centerBinary,
-                    subPixel=self.centerSubPixel,
                 )
 
             # Compensate images using the Zernikes

python/lsst/ts/wep/image.py

@@ -42,9 +42,10 @@ class Image(object):
     defocalType : DefocalType or str
         Whether the image is intra- or extra-focal.
         Can be specified using a DefocalType Enum or the corresponding string.
-    bandLabel : BandLabel or str
+    bandLabel : BandLabel or str, optional
         Photometric band for the exposure.
         Can be specified using a BandLabel Enum or the corresponding string.
+        (the default is BandLabel.REF)
     planeType : PlaneType or str, optional
         Whether the image is on the image plane or the pupil plane.
         Can be specified using a PlaneType Enum, or the corresponding string.
@@ -64,7 +65,7 @@ def __init__(
         image: np.ndarray,
         fieldAngle: Union[np.ndarray, tuple, list],
         defocalType: Union[DefocalType, str],
-        bandLabel: Union[BandLabel, str],
+        bandLabel: Union[BandLabel, str] = BandLabel.REF,
         planeType: Union[PlaneType, str] = PlaneType.Image,
         blendOffsets: Union[np.ndarray, tuple, list] = np.zeros((2, 0)),
         mask: Optional[np.ndarray] = None,
@@ -250,11 +251,12 @@ def mask(self) -> Union[np.ndarray, None]:
     def mask(self, value: Optional[np.ndarray]) -> None:
         """Set the image mask.
 
+        Note that mask creation is meant to be handled by the ImageMapper class.
+
         Parameters
         ----------
         mask : np.ndarray
-            The mask for the image. Mask creation is meant to be handled by the
-            ImageMapper class.
+            The mask for the image.
 
         Raises
         ------

python/lsst/ts/wep/imageMapper.py

@@ -25,15 +25,10 @@
 import numpy as np
 from lsst.ts.wep.image import Image
 from lsst.ts.wep.instrument import Instrument
-from lsst.ts.wep.utils import (
-    DefocalType,
-    PlaneType,
-    centerWithTemplate,
-    configClass,
-    mergeConfigWithFile,
-    polygonContains,
-    zernikeGradEval,
-)
+from lsst.ts.wep.utils.enumUtils import DefocalType, PlaneType
+from lsst.ts.wep.utils.ioUtils import configClass, mergeConfigWithFile
+from lsst.ts.wep.utils.miscUtils import centerWithTemplate, polygonContains
+from lsst.ts.wep.utils.zernikeUtils import zernikeGradEval
 from scipy.interpolate import interpn
 
 
@@ -858,7 +853,6 @@ def centerOnProjection(
         image: Image,
         zkCoeff: np.ndarray = np.zeros(1),
         binary: bool = True,
-        subPixel: bool = True,
         rMax: float = 10,
     ) -> Image:
         """Center the stamp on a projection of the pupil.
@@ -875,8 +869,6 @@ def centerOnProjection(
             otherwise a forward model of the image is used. The latter will
             likely result in a more accurate center, but takes longer to
             calculate. (the default is True)
-        subPixel : bool, optional
-            Whether to center with sub-pixel resolution. (the default is True)
         rMax : float, optional
             The maximum pixel distance the image can be shifted.
             (the default is 10)
@@ -891,7 +883,7 @@ def centerOnProjection(
             template = self.mapPupilToImage(stamp, zkCoeff).image
 
         # Center the image
-        stamp.image = centerWithTemplate(stamp.image, template, subPixel, rMax)
+        stamp.image = centerWithTemplate(stamp.image, template, rMax)
 
         return stamp