Refactor of utility C code for less duplication

astroscrappy/astroscrappy.pyx

@@ -688,7 +688,7 @@ cdef void clean_idwinterp(float[:, ::1] cleanarr, bool[:, ::1] crmask,
         no good pixels in a 5x5 region.
     """
 
-    # Go through all of the pixels, ignore the borders
+    # Go through all the pixels, ignore the borders
     cdef int i, j, k, l
     cdef float f11, f12, f21, f22 = background_level
     cdef int x1, x2, y1, y2

astroscrappy/tests/test_utils.py

@@ -2,10 +2,10 @@
 import numpy as np
 from numpy.testing import assert_allclose
 
-from ..utils import (median, optmed3, optmed5, optmed7, optmed9, optmed25,
-                     medfilt3, medfilt5, medfilt7, sepmedfilt3, sepmedfilt5,
-                     sepmedfilt7, sepmedfilt9, dilate3, dilate5, subsample,
-                     rebin, laplaceconvolve, convolve)
+from astroscrappy.utils import (median, optmed3, optmed5, optmed7, optmed9, optmed25,
+                                medfilt3, medfilt5, medfilt7, sepmedfilt3, sepmedfilt5,
+                                sepmedfilt7, sepmedfilt9, dilate3, dilate5, subsample,
+                                rebin, laplaceconvolve, convolve)
 
 import scipy.ndimage as ndi
 
@@ -49,7 +49,7 @@ def test_medfilt3():
     npmed3[:, -1:] = a[:, -1:]
 
     med3 = medfilt3(a)
-    assert np.all(med3 == npmed3)
+    np.testing.assert_allclose(med3, npmed3)
 
 
 def test_medfilt5():
@@ -61,7 +61,7 @@ def test_medfilt5():
     npmed5[:, -2:] = a[:, -2:]
 
     med5 = medfilt5(a)
-    assert np.all(med5 == npmed5)
+    np.testing.assert_allclose(med5, npmed5)
 
 
 def test_medfilt7():
@@ -73,7 +73,7 @@ def test_medfilt7():
     npmed7[:, -3:] = a[:, -3:]
 
     med7 = medfilt7(a)
-    assert np.all(med7 == npmed7)
+    np.testing.assert_allclose(med7, npmed7)
 
 
 def test_sepmedfilt3():
@@ -88,7 +88,7 @@ def test_sepmedfilt3():
     npmed3[:, -1:] = a[:, -1:]
 
     med3 = sepmedfilt3(a)
-    assert np.all(med3 == npmed3)
+    np.testing.assert_allclose(med3, npmed3)
 
 
 def test_sepmedfilt5():
@@ -103,7 +103,7 @@ def test_sepmedfilt5():
     npmed5[:, -2:] = a[:, -2:]
 
     med5 = sepmedfilt5(a)
-    assert np.all(med5 == npmed5)
+    np.testing.assert_allclose(med5, npmed5)
 
 
 def test_sepmedfilt7():
@@ -118,7 +118,7 @@ def test_sepmedfilt7():
     npmed7[:, -3:] = a[:, -3:]
 
     med7 = sepmedfilt7(a)
-    assert np.all(med7 == npmed7)
+    np.testing.assert_allclose(med7, npmed7)
 
 
 def test_sepmedfilt9():
@@ -133,35 +133,45 @@ def test_sepmedfilt9():
     npmed9[:, -4:] = a[:, -4:]
 
     med9 = sepmedfilt9(a)
-    assert np.all(med9 == npmed9)
+    np.testing.assert_allclose(med9, npmed9)
 
 
 def test_dilate5():
+    niter = 2
     # Put 5% of the pixels into a mask
     a = np.zeros((1001, 1001), dtype=bool)
+    np.random.seed(12431523)
     a[np.random.random((1001, 1001)) < 0.05] = True
     kernel = np.ones((5, 5))
     kernel[0, 0] = 0
     kernel[0, 4] = 0
     kernel[4, 0] = 0
     kernel[4, 4] = 0
     # Make a zero padded array for the numpy version to operate
-    paddeda = np.zeros((1005, 1005), dtype=bool)
-    paddeda[2:-2, 2:-2] = a[:, :]
-    npdilate = ndi.binary_dilation(np.ascontiguousarray(paddeda),
-                                   structure=kernel, iterations=2)
-    cdilate = dilate5(a, 2)
+    npdilate = ndi.binary_dilation(a, structure=kernel, iterations=1, border_value=0)
 
-    assert np.all(npdilate[2:-2, 2:-2] == cdilate)
+    def reset_edges(dilated, data):
+        for i in range(2):
+            dilated[:, i] = data[:, i]
+            dilated[i, :] = data[i, :]
+        for i in range(-2, 0, 1):
+            dilated[:, i] = data[:, i]
+            dilated[i, :] = data[i, :]
+
+    reset_edges(npdilate, a)
+    npdilate = ndi.binary_dilation(npdilate.copy(), structure=kernel, iterations=1, border_value=0)
+    reset_edges(npdilate, a)
+    cdilate = dilate5(a, niter)
+
+    np.testing.assert_allclose(npdilate, cdilate)
 
 
 def test_dilate3():
     # Put 5% of the pixels into a mask
     a = np.zeros((1001, 1001), dtype=bool)
     a[np.random.random((1001, 1001)) < 0.05] = True
     kernel = np.ones((3, 3))
-    npgrow = ndi.binary_dilation(np.ascontiguousarray(a),
-                                 structure=kernel, iterations=1)
+    npgrow = ndi.binary_dilation(np.ascontiguousarray(a), structure=kernel)
     cgrow = dilate3(a)
     npgrow[:, 0] = a[:, 0]
     npgrow[:, -1] = a[:, -1]

astroscrappy/utils/image_utils.pyx

@@ -209,7 +209,7 @@ def dilate3(np.ndarray[np.uint8_t, ndim=2, mode='c', cast=True] dgrow):
 
     # Allocate the output array here so that Python tracks the memory and will
     # free the memory when we are finished with the output array.
-    output = np.zeros((ny, nx), dtype=np.bool_)
+    output = np.zeros((ny, nx), dtype=bool)
 
     cdef uint8_t * dgrowptr = < uint8_t * > np.PyArray_DATA(dgrow)
     cdef uint8_t * outdgrowptr = < uint8_t * > np.PyArray_DATA(output)