Updated tests to new function names

aotools/image_processing/centroiders.py

@@ -41,7 +41,7 @@ def correlation_centroid(im, ref, threshold=0., padding=1):
         # Correlate frame with reference image
         corr = cross_correlate(im[frame], ref, padding=padding)
 
-        cx, cy = centreOfGravity(corr, threshold=threshold)
+        cx, cy = centre_of_gravity(corr, threshold=threshold)
 
         cy -= float(ny) / 2. * (float(padding) - 1)
         cx -= float(nx) / 2. * (float(padding) - 1)
@@ -51,7 +51,7 @@ def correlation_centroid(im, ref, threshold=0., padding=1):
     return centroids
 
 
-def centre_of_gravity(img, threshold=0, **kwargs):
+def centre_of_gravity(img, threshold=0, min_threshold=0, **kwargs):
     """
     Centroids an image, or an array of images.
     Centroids over the last 2 dimensions.
@@ -69,10 +69,10 @@ def centre_of_gravity(img, threshold=0, **kwargs):
 
     if threshold != 0:
         if len(img.shape) == 2:
-            thres = numpy.max((threshold*img.max(), minThreshold))
+            thres = numpy.max((threshold*img.max(), min_threshold))
             img = numpy.where(img > thres, img - thres, 0)
         else:
-            thres = numpy.maximum(threshold*img.max(-1).max(-1), [minThreshold]*img.shape[0])
+            thres = numpy.maximum(threshold*img.max(-1).max(-1), [min_threshold]*img.shape[0])
             img_temp = (img.T - thres).T
             zero_coords = numpy.where(img_temp < 0)
             img[zero_coords] = 0

test/test_centroiders.py

@@ -3,33 +3,33 @@
 from nose.tools import raises
 
 
-def test_centreOfGravity_single():
+def test_centre_of_gravity_single():
     img = numpy.random.random((10, 10))
-    com = image_processing.centreOfGravity(img, 0.1)
+    com = image_processing.centre_of_gravity(img, 0.1)
     assert(com.shape[0]) == 2
 
 
-def test_centreOfGravity_many():
+def test_centre_of_gravity_many():
     img = numpy.random.random((5, 10, 10))
-    com = image_processing.centreOfGravity(img, 0.1)
+    com = image_processing.centre_of_gravity(img, 0.1)
     assert(com.shape[0] == 2)
     assert(com.shape[1] == 5)
 
-def test_centreOfGravity_value():
+def test_centre_of_gravity_value():
     img = numpy.zeros((1, 5, 5))
     img[0, 1:3, 2:4] = 1.
-    centroid = image_processing.centreOfGravity(img)
+    centroid = image_processing.centre_of_gravity(img)
     numpy.testing.assert_almost_equal(centroid, numpy.array([[2.5], [1.5]]))
 
-def test_brightestPxl_single():
+def test_brightest_pixel_single():
     img = numpy.random.random((10, 10))
-    com = image_processing.brightestPxl(img, 0.3)
+    com = image_processing.brightest_pixel(img, 0.3)
     assert(com.shape[0] == 2)
 
 
 def test_brightestPxl_many():
     img = numpy.random.random((5, 10, 10))
-    com = image_processing.brightestPxl(img, 0.1)
+    com = image_processing.brightest_pixel(img, 0.1)
     assert(com.shape[0] == 2)
     assert(com.shape[1] == 5)
 

test/test_functions.py

@@ -11,26 +11,3 @@ def test_gaussian2d_2d():
     gaussian = functions.gaussian2d((10, 8), (3, 2), 10., (4, 3))
     print(gaussian.shape)
     assert gaussian.shape == (10, 8)
-
-
-def test_encircledEnergy():
-    data = numpy.random.rand(32, 32)
-    ee50d = functions.encircledEnergy(data)
-    print(ee50d)
-    assert type(ee50d) == float
-
-
-def test_encircledEnergy_func():
-    data = numpy.random.rand(32, 32)
-    x, y = functions.encircledEnergy(data, eeDiameter=False)
-    print(y.min(), y.max())
-    assert len(x) == len(y)
-    assert numpy.max(y) <= 1
-    assert numpy.min(y) >= 0
-
-
-def test_aziAvg():
-    data = numpy.random.rand(32, 32)
-    azi = functions.aziAvg(data)
-    print(azi.shape)
-    assert azi.shape == (16,)

test/test_image_processing.py

@@ -2,22 +2,6 @@
 import numpy
 
 
-def test_r0fromSlopes():
-    slopes = numpy.random.random((2, 100, 2))
-    wavelength = 500e-9
-    subapDiam = 0.5
-    r0 = image_processing.r0fromSlopes(slopes, wavelength, subapDiam)
-    print(type(r0))
-
-
-def test_slopeVarfromR0():
-    r0 = 0.1
-    wavelength = 500e-9
-    subapDiam = 0.5
-    variance = image_processing.slopeVarfromR0(r0, wavelength, subapDiam)
-    assert type(variance) == float
-
-
 def test_image_contrast():
     image = numpy.random.random((20, 20))
     contrast = image_processing.image_contrast(image)
@@ -51,3 +35,26 @@ def test_azimuthal_average():
     azi = image_processing.azimuthal_average(data)
     print(azi.shape)
     assert azi.shape == (16,)
+
+
+def test_encircledEnergy():
+    data = numpy.random.rand(32, 32)
+    ee50d = image_processing.encircled_energy(data)
+    print(ee50d)
+    assert type(ee50d) == float
+
+
+def test_encircledEnergy_func():
+    data = numpy.random.rand(32, 32)
+    x, y = image_processing.encircled_energy(data, eeDiameter=False)
+    print(y.min(), y.max())
+    assert len(x) == len(y)
+    assert numpy.max(y) <= 1
+    assert numpy.min(y) >= 0
+
+
+def test_aziAvg():
+    data = numpy.random.rand(32, 32)
+    azi = image_processing.azimuthal_average(data)
+    print(azi.shape)
+    assert azi.shape == (16,)

test/test_turbulence.py

@@ -0,0 +1,18 @@
+from aotools import turbulence
+import numpy
+
+
+def test_r0fromSlopes():
+    slopes = numpy.random.random((2, 100, 2))
+    wavelength = 500e-9
+    subapDiam = 0.5
+    r0 = turbulence.r0_from_slopes(slopes, wavelength, subapDiam)
+    print(type(r0))
+
+
+def test_slopeVarfromR0():
+    r0 = 0.1
+    wavelength = 500e-9
+    subapDiam = 0.5
+    variance = turbulence.slope_variance_from_r0(r0, wavelength, subapDiam)
+    assert type(variance) == float