WIP: Allow a 2D threshold in StarFinder classes

photutils/detection/core.py

@@ -41,7 +41,7 @@ def _find_stars(convolved_data, kernel, threshold, *, min_separation=0.0,
         kernel : `_StarFinderKernel`
             The convolution kernel.
 
-        threshold : float
+        threshold : float or 2D array-like
             The absolute image value above which to select sources.  This
             threshold should be the threshold input to the star finder class
             multiplied by the kernel relerr.
@@ -96,6 +96,9 @@ def _find_stars(convolved_data, kernel, threshold, *, min_separation=0.0,
             pad_mode = 'constant'
             convolved_data = np.pad(convolved_data, pad, mode=pad_mode,
                                     constant_values=0.0)
+            if not np.isscalar(threshold):
+                threshold = np.pad(threshold, pad, mode=pad_mode,
+                                   constant_values=0.0)
             if mask is not None:
                 mask = np.pad(mask, pad, mode=pad_mode, constant_values=False)
 

photutils/detection/daofinder.py

@@ -57,8 +57,12 @@ class DAOStarFinder(StarFinderBase):
 
     Parameters
     ----------
-    threshold : float
+
+    threshold : float or array-like
         The absolute image value above which to select sources.
+        A non-scalar ``threshold`` must have the same shape
+        as ``data``. See `~photutils.segmentation.detect_threshold` for
+        one way to create a ``threshold`` image.
 
     fwhm : float
         The full-width half-maximum (FWHM) of the major axis of the
@@ -158,9 +162,6 @@ def __init__(self, threshold, fwhm, ratio=1.0, theta=0.0,
                  roundhi=1.0, sky=0.0, exclude_border=False,
                  brightest=None, peakmax=None, xycoords=None):
 
-        if not np.isscalar(threshold):
-            raise TypeError('threshold must be a scalar value.')
-
         if not np.isscalar(fwhm):
             raise TypeError('fwhm must be a scalar value.')
 
@@ -411,6 +412,13 @@ def data_peak(self):
     def convdata_peak(self):
         return self.cutout_convdata[:, self.cutout_center[0],
                                     self.cutout_center[1]]
+    @lazyproperty
+    def threshold_peak(self):
+        if np.isscalar(self.threshold_eff):
+            return np.repeat(self.threshold_eff, len(self.xypos))
+        else:
+            return self.make_cutouts(
+                self.threshold_eff)[:, self.cutout_center[0], self.cutout_center[1]]
 
     @lazyproperty
     def roundness1(self):
@@ -622,7 +630,7 @@ def peak(self):
 
     @lazyproperty
     def flux(self):
-        return ((self.convdata_peak / self.threshold_eff)
+        return ((self.convdata_peak / self.threshold_peak)
                 - (self.sky * self.npix))
 
     @lazyproperty

photutils/detection/irafstarfinder.py

@@ -31,8 +31,12 @@ class IRAFStarFinder(StarFinderBase):
 
     Parameters
     ----------
-    threshold : float
+
+    threshold : float or 2D array-like
         The absolute image value above which to select sources.
+        A non-scalar ``threshold`` must have the same shape
+        as ``data``. See `~photutils.segmentation.detect_threshold` for
+        one way to create a ``threshold`` image.
 
     fwhm : float
         The full-width half-maximum (FWHM) of the 2D circular Gaussian
@@ -132,9 +136,6 @@ def __init__(self, threshold, fwhm, sigma_radius=1.5, minsep_fwhm=2.5,
                  exclude_border=False, brightest=None, peakmax=None,
                  xycoords=None):
 
-        if not np.isscalar(threshold):
-            raise TypeError('threshold must be a scalar value.')
-
         if not np.isscalar(fwhm):
             raise TypeError('fwhm must be a scalar value.')
 

photutils/detection/peakfinder.py

@@ -44,7 +44,7 @@ def find_peaks(data, threshold, box_size=3, footprint=None, mask=None,
     data : array_like
         The 2D array of the image.
 
-    threshold : float or array-like
+    threshold : float or 2D array-like
         The data value or pixel-wise data values to be used for the
         detection threshold. A 2D ``threshold`` must have the same shape
         as ``data``. See `~photutils.segmentation.detect_threshold` for

photutils/detection/starfinder.py

@@ -26,7 +26,7 @@ class StarFinder(StarFinderBase):
 
     Parameters
     ----------
-    threshold : float
+    threshold : float or 2D array-like
         The absolute image value above which to select sources.
 
     kernel : `numpy.ndarray`

photutils/detection/tests/test_daofinder.py

@@ -18,7 +18,7 @@
 
 
 DATA = make_100gaussians_image()
-THRESHOLDS = [8.0, 10.0]
+THRESHOLDS = [8.0, 10.0, 8.*np.ones_like(DATA)]
 FWHMS = [1.0, 1.5, 2.0]
 
 
@@ -29,6 +29,8 @@ class TestDAOStarFinder:
     def test_daofind(self, threshold, fwhm):
         starfinder = DAOStarFinder(threshold, fwhm, sigma_radius=1.5)
         tbl = starfinder(DATA)
+        if not np.isscalar(threshold):
+            threshold = threshold.flatten()[0]
         datafn = f'daofind_test_thresh{threshold:04.1f}_fwhm{fwhm:04.1f}.txt'
         datafn = op.join(op.dirname(op.abspath(__file__)), 'data', datafn)
         tbl_ref = Table.read(datafn, format='ascii')
@@ -37,10 +39,7 @@ def test_daofind(self, threshold, fwhm):
         for col in tbl.colnames:
             assert_allclose(tbl[col], tbl_ref[col])
 
-    def test_daofind_threshold_fwhm_inputs(self):
-        with pytest.raises(TypeError):
-            DAOStarFinder(threshold=np.ones((2, 2)), fwhm=3.)
-
+    def test_daofind_fwhm_input(self):
         with pytest.raises(TypeError):
             DAOStarFinder(threshold=3., fwhm=np.ones((2, 2)))
 

photutils/detection/tests/test_irafstarfinder.py

@@ -18,7 +18,7 @@
 
 
 DATA = make_100gaussians_image()
-THRESHOLDS = [8.0, 10.0]
+THRESHOLDS = [8.0, 10.0, 8.*np.ones_like(DATA)]
 FWHMS = [1.0, 1.5, 2.0]
 
 
@@ -29,6 +29,8 @@ class TestIRAFStarFinder:
     def test_irafstarfind(self, threshold, fwhm):
         starfinder = IRAFStarFinder(threshold, fwhm, sigma_radius=1.5)
         tbl = starfinder(DATA)
+        if not np.isscalar(threshold):
+            threshold = threshold.flatten()[0]
         datafn = (f'irafstarfind_test_thresh{threshold:04.1f}_'
                   f'fwhm{fwhm:04.1f}.txt')
         datafn = op.join(op.dirname(op.abspath(__file__)), 'data', datafn)
@@ -38,10 +40,7 @@ def test_irafstarfind(self, threshold, fwhm):
         for col in tbl.colnames:
             assert_allclose(tbl[col], tbl_ref[col])
 
-    def test_irafstarfind_threshold_fwhm_inputs(self):
-        with pytest.raises(TypeError):
-            IRAFStarFinder(threshold=np.ones((2, 2)), fwhm=3.)
-
+    def test_irafstarfind_fwhm_input(self):
         with pytest.raises(TypeError):
             IRAFStarFinder(threshold=3., fwhm=np.ones((2, 2)))