Updates for python 3

README.txt

@@ -1,4 +1,6 @@
 PyGuide offers image analysis routines for telescope guiding,
 including a star finder, centroider and star shape fitter.
 
-See doc/PyGuideManual.html for installation and usage instructions.
+See doc/PyGuideManual.html for installation and usage instructions.
+
+Modification of PyGuide code (https://github.com/fmerges/PyGuide and https://github.com/ApachePointObservatory/PyGuide) for python 3. Tested on python 3.12, numpy 1.26.0 and astropy 6.1.2. Need to use python3 version of RO package: https://github.com/pavolgaj/RO3/tree/main.

python/Centroid.py

@@ -579,9 +579,9 @@ def checkSignal(
             xyCtr = xyCtr,
             xySize = (outerRad, outerRad),
         )
-        subMask = subMaskObj.getSubFrame().astype(numpy.bool) # force type and copy
+        subMask = subMaskObj.getSubFrame().astype(numpy.bool_) # force type and copy
     else:
-        subMask = numpy.zeros(subData.shape, dtype=numpy.bool)
+        subMask = numpy.zeros(subData.shape, dtype=numpy.bool_)
 
     # create circleMask; a centered circle of radius rad
     # with 0s in the middle and 1s outside
@@ -656,7 +656,7 @@ def conditionMask(mask):
     """
     if mask is None:
         return None
-    return conditionArr(mask, numpy.bool)
+    return conditionArr(mask, numpy.bool_)
 
 def conditionArr(arr, desType):
     """Convert a sequence to a numpy array of the desired type.

python/FakeData.py

@@ -64,7 +64,7 @@ def addNoise(
     - sky       sky level, in ADU
     - ccdInfo   a PyGuide.CCDInfo object
     """
-    outData = numpy.add(data, sky).astype(numpy.int)
+    outData = numpy.add(data, sky).astype(numpy.int32)
     outData = numpy.random.poisson(lam = outData * ccdInfo.ccdGain) / ccdInfo.ccdGain
     outData += numpy.random.normal(loc = ccdInfo.bias, scale = ccdInfo.readNoise/float(ccdInfo.ccdGain), size = data.shape)
     # truncate data and return as UInt16

src/RadProfModule.c

@@ -1103,12 +1103,41 @@ static PyMethodDef radProfMethods[] = {
     {NULL, NULL, 0, NULL} /* Sentinel */
 };
 
+
+#if PY_MAJOR_VERSION >= 3
+static struct PyModuleDef moduledef = {
+    PyModuleDef_HEAD_INIT,
+    "radProf",     		/* m_name */
+    radProfModule_doc,  /* m_doc */
+    -1,                 /* m_size */
+    radProfMethods,    	/* m_methods */
+    NULL,               /* m_reload */
+    NULL,               /* m_traverse */
+    NULL,               /* m_clear */
+    NULL,               /* m_free */
+};
+#endif
+
 // Module initialization function
-PyMODINIT_FUNC initradProf(void) {
+PyMODINIT_FUNC
+#if PY_MAJOR_VERSION >= 3
+PyInit_radProf(void)
+#else
+initradProf(void)
+#endif
+{
     PyObject *m;
+#if PY_MAJOR_VERSION >= 3
+	m = PyModule_Create(&moduledef);
+#else
     m = Py_InitModule3("radProf", radProfMethods, radProfModule_doc);
+#endif
     if (m == NULL)
-        return;
+        return m;
 
     import_array();
+
+#if PY_MAJOR_VERSION >= 3
+    return m;
+#endif
 }

tests/Stats.py

@@ -1,4 +1,4 @@
-from __future__ import division, absolute_import, print_function
+
 
 import math
 

tests/testCentroid.py

@@ -1,5 +1,5 @@
 #!/usr/bin/env python
-from __future__ import division, absolute_import, print_function
+
 """Test PyGuide.centroid with masked data.
 
 History:
@@ -86,7 +86,7 @@
     nPts = ctrData.pix
     print("meas err   = %6.2f, %6.2f; est err = %.2f, %.2f; nCounts = %.0f; nPts = %d" %
         (measCtr[0] - actCtr[0], measCtr[1] - actCtr[1], ctrData.xyErr[0], ctrData.xyErr[1], nCounts, nPts))
-    mask = numpy.zeros(arrShape, numpy.bool)
+    mask = numpy.zeros(arrShape, numpy.bool_)
     for row in range(maskLim[0], maskLim[1]+1):
         mask[row,:] = 1
     ctrData = PyGuide.centroid(

tests/testCentroidLong.py

@@ -35,7 +35,7 @@
 
 imShape = (ImWidth, ImWidth)
 nomCtr = (ImWidth // 2, ImWidth // 2)
-mask = numpy.zeros(imShape, numpy.bool)
+mask = numpy.zeros(imShape, numpy.bool_)
 NaN = float("NaN")
 
 # settings
@@ -44,36 +44,36 @@
 MaskWidthsPerFWHM = (0.0, 0.5, 1.0, 1.5, 2.0) # fractions of a FWHM
 NumTries = 20
 
-print "Compare centroid actual error vs estimated error"
-print "over a range of fake data"
-print
-print "Settings:"
-print "Thresh      =", Thresh
-print "Sky         =", Sky, "ADU"
-print "Read Noise  =", CCDInfo.readNoise, "e-"
-print "CCD Gain    =", CCDInfo.ccdGain, "e-/ADU"
-print "Bias        =", CCDInfo.bias, "ADU"
-print "Amplitudes  =", AmplValues, "ADU"
-print "FWHMs       =", FWHMValues, "pixels"
-print "Mask Widths =", MaskWidthsPerFWHM, "fractions of a FWHM"
-print "Num Ctrs    =", NumTries, "number of centroids per star shape"
-print "CCD Size    =", ImWidth, "x", ImWidth, "pixels"
-print
-print "the equation being minimized is:"
-print "   sum(var(r) * numPts(r))"
-print "though the final number reported is a normalized version:"
-print "   asymm = sum(var(r) * numPts(r)) / (pixNoise^2 * totPts)"
-print "where"
-print "   pixNoise is the noise/pixel due to read noise and sky"
-print "   totPts = sum(numPts(r))"
-print
-print "The centroids are randomly distributed over"
-print "a range of -FWHM/2, FWHM/2 with respect to the"
-print "center of the CCD = the center of the slit."
-print
-print "The slit is along y so the error along y should be smaller than x."
-print
-print "fwhm ampl    maskWid xErr    yErr    xUncert yUncert asymm   totPix  totCts  rad msgs"
+print("Compare centroid actual error vs estimated error")
+print("over a range of fake data")
+print()
+print("Settings:")
+print("Thresh      =", Thresh)
+print("Sky         =", Sky, "ADU")
+print("Read Noise  =", CCDInfo.readNoise, "e-")
+print("CCD Gain    =", CCDInfo.ccdGain, "e-/ADU")
+print("Bias        =", CCDInfo.bias, "ADU")
+print("Amplitudes  =", AmplValues, "ADU")
+print("FWHMs       =", FWHMValues, "pixels")
+print("Mask Widths =", MaskWidthsPerFWHM, "fractions of a FWHM")
+print("Num Ctrs    =", NumTries, "number of centroids per star shape")
+print("CCD Size    =", ImWidth, "x", ImWidth, "pixels")
+print()
+print("the equation being minimized is:")
+print("   sum(var(r) * numPts(r))")
+print("though the final number reported is a normalized version:")
+print("   asymm = sum(var(r) * numPts(r)) / (pixNoise^2 * totPts)")
+print("where")
+print("   pixNoise is the noise/pixel due to read noise and sky")
+print("   totPts = sum(numPts(r))")
+print()
+print("The centroids are randomly distributed over")
+print("a range of -FWHM/2, FWHM/2 with respect to the")
+print("center of the CCD = the center of the slit.")
+print()
+print("The slit is along y so the error along y should be smaller than x.")
+print()
+print("fwhm ampl    maskWid xErr    yErr    xUncert yUncert asymm   totPix  totCts  rad msgs")
 
 nBad = 0
 ctrXStats = Stats()
@@ -110,29 +110,29 @@
                     doSmooth = DoSmooth,
                 )
                 if not ctrData.isOK:
-                    print "%s   %s  %s  NaN NaN NaN NaN NaN NaN NaN %s  %r" % (
+                    print("%s   %s  %s  NaN NaN NaN NaN NaN NaN NaN %s  %r" % (
                         fwhm, ampl, maskWidth, ctrData.rad, ctrData.msgStr,
-                    )
+                    ))
                     nBad += 1
                     continue
 
                 xyMeasErr = [ctrData.xyCtr[ii] - actCtr[ii] for ii in (0,1)]
-                print "%s   %s  %s  %.3f    %.3f    %.3f    %.3f    %.3f    %s  %s  %s  %r" % (
+                print("%s   %s  %s  %.3f    %.3f    %.3f    %.3f    %.3f    %s  %s  %s  %r" % (
                     fwhm, ampl, maskWidth,
                     xyMeasErr[0], xyMeasErr[1],
                     ctrData.xyErr[0], ctrData.xyErr[1],
                     ctrData.asymm, ctrData.pix, ctrData.counts,
                     ctrData.rad, ctrData.msgStr,
-                )
+                ))
                 ctrXStats.append(xyMeasErr[0])
                 ctrYStats.append(xyMeasErr[1])
 
-print
-print "Error statistics (for %d points)" % ctrXStats.nPoints()
-print "            min      max    mean   stdDev"
-print "xErr  %8.1f %8.1f %8.1f %8.1f" % (ctrXStats.min(), ctrXStats.max(), ctrXStats.mean(), ctrXStats.stdDev())
-print "yErr  %8.1f %8.1f %8.1f %8.1f" % (ctrYStats.min(), ctrYStats.max(), ctrYStats.mean(), ctrYStats.stdDev())
+print()
+print("Error statistics (for %d points)" % ctrXStats.nPoints())
+print("            min      max    mean   stdDev")
+print("xErr  %8.1f %8.1f %8.1f %8.1f" % (ctrXStats.min(), ctrXStats.max(), ctrXStats.mean(), ctrXStats.stdDev()))
+print("yErr  %8.1f %8.1f %8.1f %8.1f" % (ctrYStats.min(), ctrYStats.max(), ctrYStats.mean(), ctrYStats.stdDev()))
 
 if nBad > 0:
-    print
-    print "number of failures =", nBad
+    print()
+    print("number of failures =", nBad)

tests/testStarShape.py

@@ -20,7 +20,7 @@
 import os.path
 import sys
 import PyGuide
-import pyfits
+from astropy.io import fits as pyfits
 
 # these values are probably wrong for the given test image
 CCDInfo = PyGuide.CCDInfo(
@@ -50,7 +50,7 @@
 #mask = data < 0
 #mask[64:101, 78:92] = 1
 
-print "searching for stars"
+print("searching for stars")
 ctrDataList, imStats = PyGuide.findStars(
     data = data,
     mask = mask,
@@ -62,7 +62,7 @@
 for ctrData in ctrDataList:
     xyCtr = ctrData.xyCtr
     rad = ctrData.rad
-    print "star xyCtr=%.2f, %.2f, radius=%s" % (xyCtr[0], xyCtr[1], rad)
+    print("star xyCtr=%.2f, %.2f, radius=%s" % (xyCtr[0], xyCtr[1], rad))
 
     shapeData = PyGuide.starShape(
         data,
@@ -71,8 +71,8 @@
         rad = rad,
     )
     if not shapeData.isOK:
-        print "starShape failed: %s" % (shapeData.msgStr,)
+        print("starShape failed: %s" % (shapeData.msgStr,))
     else:
-        print "star ampl=%.1f, fwhm=%.1f, bkgnd=%.1f, chiSq=%.2f" %\
-            (shapeData.ampl,shapeData.fwhm, shapeData.bkgnd, shapeData.chiSq)
-    print
+        print("star ampl=%.1f, fwhm=%.1f, bkgnd=%.1f, chiSq=%.2f" %\
+            (shapeData.ampl,shapeData.fwhm, shapeData.bkgnd, shapeData.chiSq))
+    print()

tests/testStarShapeLong.py

@@ -48,33 +48,33 @@
 
 imShape = (ImWidth, ImWidth)
 nomCtr = (ImWidth // 2, ImWidth // 2)
-mask = numpy.zeros(imShape, numpy.bool)
+mask = numpy.zeros(imShape, numpy.bool_)
 
-print "Compare star shape fit values to correct values"
-print "over a range of fake data"
-print
-print "Settings:"
-print "Sky         =", Sky, "ADU"
-print "Read Noise  =", CCDInfo.readNoise, "e-"
-print "CCD Gain    =", CCDInfo.ccdGain, "e-/ADU"
-print "Bias        =", CCDInfo.bias, "ADU"
-print "DoCentroid  =", DoCentroid
+print("Compare star shape fit values to correct values")
+print("over a range of fake data")
+print()
+print("Settings:")
+print("Sky         =", Sky, "ADU")
+print("Read Noise  =", CCDInfo.readNoise, "e-")
+print("CCD Gain    =", CCDInfo.ccdGain, "e-/ADU")
+print("Bias        =", CCDInfo.bias, "ADU")
+print("DoCentroid  =", DoCentroid)
 if DoCentroid:
-    print "Thresh      =", Thresh
-print "Amplitudes  =", AmplValues, "ADU"
-print "FWHMs       =", FWHMValues, "pixels"
-print "Mask Widths =", MaskWidthsPerFWHM, "fractions of a FWHM"
-print "Num Tries   =", NumTries, "number of cases per star shape"
-print "CCD Size    =", ImWidth, "x", ImWidth, "pixels"
-print
-print "Each try is a star whose center is randomly distributed over"
-print "a range of -FWHM/2, FWHM/2 with respect to the"
-print "center of the CCD = the center of the slit."
-print
-print "Reported errors and statistics on these errors are in percent:"
-print "reported error (%) = 100 * (meas value - act value) / act value"
-print
-print "The slit is along y."
+    print("Thresh      =", Thresh)
+print("Amplitudes  =", AmplValues, "ADU")
+print("FWHMs       =", FWHMValues, "pixels")
+print("Mask Widths =", MaskWidthsPerFWHM, "fractions of a FWHM")
+print("Num Tries   =", NumTries, "number of cases per star shape")
+print("CCD Size    =", ImWidth, "x", ImWidth, "pixels")
+print()
+print("Each try is a star whose center is randomly distributed over")
+print("a range of -FWHM/2, FWHM/2 with respect to the")
+print("center of the CCD = the center of the slit.")
+print()
+print("Reported errors and statistics on these errors are in percent:")
+print("reported error (%) = 100 * (meas value - act value) / act value")
+print()
+print("The slit is along y.")
 
 def pctErr(meas, act):
     return (meas - act) * 100.0 / float(act)
@@ -85,8 +85,8 @@ def pctErr(meas, act):
 nBadCtr = 0
 nBad = 0
 
-print
-print "fwhm ampl    bg  xCtr    yCtr    maskWid xCtMeas yCtMeas fitFWHM fitAmpl fitBg   chiSq   fwhmErr amplErr bgErr   msgs"
+print()
+print("fwhm ampl    bg  xCtr    yCtr    maskWid xCtMeas yCtMeas fitFWHM fitAmpl fitBg   chiSq   fwhmErr amplErr bgErr   msgs")
 bkgnd = Sky + CCDInfo.bias
 for ampl in AmplValues:
     for fwhm in FWHMValues:
@@ -120,11 +120,11 @@ def pctErr(meas, act):
                         thresh = Thresh,
                     )
                     if not ctrData.isOK:
-                        print "%.1f %.1f    %.1f    %.2f    %.2f    %.2f    NaN NaN NaN NaN NaN NaN NaN NaN NaN %r" % (
+                        print("%.1f %.1f    %.1f    %.2f    %.2f    %.2f    NaN NaN NaN NaN NaN NaN NaN NaN NaN %r" % (
                             fwhm, ampl, bkgnd,
                             xyCtr[0], xyCtr[1], maskWidth,
                             ctrData.msgStr,
-                        )
+                        ))
                         nBadCtr += 1
                         continue
                 else:
@@ -140,37 +140,37 @@ def pctErr(meas, act):
                     rad = fwhm * 3,
                 )
                 if not shapeData.isOK:
-                    print "%.1f %.1f    %.1f    %.2f    %.2f    %.2f    %.2f    %.2f    NaN NaN NaN NaN NaN NaN NaN %r" % (
+                    print("%.1f %.1f    %.1f    %.2f    %.2f    %.2f    %.2f    %.2f    NaN NaN NaN NaN NaN NaN NaN %r" % (
                         fwhm, ampl, bkgnd,
                         xyCtr[0], xyCtr[1], maskWidth, ctrData.xyCtr[0], ctrData.xyCtr[1],
                         shapeData.msgStr,
-                    )
+                    ))
                     nBad += 1
                     continue
 
                 fwhmErr = pctErr(shapeData.fwhm, fwhm)
                 amplErr = pctErr(shapeData.ampl, ampl)
                 bkgndErr = pctErr(shapeData.bkgnd, bkgnd)
-                print "%.1f %.1f    %.1f    %.2f    %.2f    %.2f    %.2f    %.2f    %.1f    %.1f    %.1f    %.2f    %.1f    %.1f    %.1f    %r" % (
+                print("%.1f %.1f    %.1f    %.2f    %.2f    %.2f    %.2f    %.2f    %.1f    %.1f    %.1f    %.2f    %.1f    %.1f    %.1f    %r" % (
                     fwhm, ampl, bkgnd,
                     xyCtr[0], xyCtr[1], maskWidth, ctrData.xyCtr[0], ctrData.xyCtr[1],
                     shapeData.fwhm, shapeData.ampl, shapeData.bkgnd, shapeData.chiSq,
                     fwhmErr, amplErr, bkgndErr,
                     shapeData.msgStr,
-                )
+                ))
                 fwhmStats.append(fwhmErr)
                 amplStats.append(amplErr)
                 bkgndStats.append(bkgndErr)
 
-print
-print "Error statistics (for %d points)" % fwhmStats.nPoints()
-print "            min      max    mean   stdDev"
-print "fwhm  %8.1f %8.1f %8.1f %8.1f" % (fwhmStats.min(), fwhmStats.max(), fwhmStats.mean(), fwhmStats.stdDev())
-print "ampl  %8.1f %8.1f %8.1f %8.1f" % (amplStats.min(), amplStats.max(), amplStats.mean(), amplStats.stdDev())
-print "bkgnd %8.1f %8.1f %8.1f %8.1f" % (bkgndStats.min(), bkgndStats.max(), bkgndStats.mean(), bkgndStats.stdDev())
+print()
+print("Error statistics (for %d points)" % fwhmStats.nPoints())
+print("            min      max    mean   stdDev")
+print("fwhm  %8.1f %8.1f %8.1f %8.1f" % (fwhmStats.min(), fwhmStats.max(), fwhmStats.mean(), fwhmStats.stdDev()))
+print("ampl  %8.1f %8.1f %8.1f %8.1f" % (amplStats.min(), amplStats.max(), amplStats.mean(), amplStats.stdDev()))
+print("bkgnd %8.1f %8.1f %8.1f %8.1f" % (bkgndStats.min(), bkgndStats.max(), bkgndStats.mean(), bkgndStats.stdDev()))
 
 if (nBad > 0) or (nBadCtr > 0):
-    print
-    print "number of shape fit failures =", nBad
+    print()
+    print("number of shape fit failures =", nBad)
     if DoCentroid:
-        print "number of centroid failures  =", nBadCtr
+        print("number of centroid failures  =", nBadCtr)