Minor updates to py2intround

photutils/centroids/core.py

@@ -11,7 +11,7 @@
 from astropy.utils.exceptions import AstropyUserWarning
 
 from photutils.utils._parameters import as_pair
-from photutils.utils._round import _py2intround
+from photutils.utils._round import py2intround
 
 __all__ = ['centroid_com', 'centroid_quadratic', 'centroid_sources']
 
@@ -189,8 +189,8 @@ def centroid_quadratic(data, xpeak=None, ypeak=None, fit_boxsize=5,
     if xpeak is None or ypeak is None:
         yidx, xidx = np.unravel_index(np.nanargmax(data), data.shape)
     else:
-        xidx = _py2intround(xpeak)
-        yidx = _py2intround(ypeak)
+        xidx = py2intround(xpeak)
+        yidx = py2intround(ypeak)
 
         if search_boxsize is not None:
             search_boxsize = as_pair('search_boxsize', search_boxsize,

photutils/psf/epsf.py

@@ -21,7 +21,7 @@
 from photutils.psf.utils import _interpolate_missing_data
 from photutils.utils._optional_deps import HAS_BOTTLENECK, HAS_TQDM
 from photutils.utils._parameters import as_pair
-from photutils.utils._round import _py2intround
+from photutils.utils._round import py2intround
 
 __all__ = ['EPSFFitter', 'EPSFBuilder']
 
@@ -453,8 +453,8 @@ def _resample_residual(self, star, epsf):
 
         epsf_xcenter, epsf_ycenter = (int((epsf.data.shape[1] - 1) / 2),
                                       int((epsf.data.shape[0] - 1) / 2))
-        xidx = _py2intround(x + epsf_xcenter)
-        yidx = _py2intround(y + epsf_ycenter)
+        xidx = py2intround(x + epsf_xcenter)
+        yidx = py2intround(y + epsf_ycenter)
 
         resampled_img = np.full(epsf.shape, np.nan)
 

photutils/utils/_round.py

@@ -6,17 +6,27 @@
 import numpy as np
 
 
-def _py2intround(a):
+def py2intround(a):
     """
     Round the input to the nearest integer.
 
     If two integers are equally close, rounding is done away from 0.
+
+    Parameters
+    ----------
+    a : float or array-like
+        The input float or array.
+
+    Returns
+    -------
+    result : float or array-like
+        The integer-rounded values.
     """
-    data = np.asanyarray(a)
+    data = np.atleast_1d(a)
     value = np.where(data >= 0, np.floor(data + 0.5),
                      np.ceil(data - 0.5)).astype(int)
 
-    if not hasattr(a, '__iter__'):
-        value = value.item()
+    if np.isscalar(value):
+        value = value[0]
 
     return value