def test_plot_plugin():
    viewer = ImageViewer(data.moon())
    plugin = PlotPlugin(image_filter=lambda x: x)
    viewer += plugin

    assert_equal(viewer.image, data.moon())
    plugin._update_original_image(data.coins())
    assert_equal(viewer.image, data.coins())
    viewer.close()

def test_paint_tool():
    img = data.moon()
    viewer = ImageViewer(img)

    tool = PaintTool(viewer, img.shape)

    tool.radius = 10
    assert_equal(tool.radius, 10)
    tool.label = 2
    assert_equal(tool.label, 2)
    assert_equal(tool.shape, img.shape)

    do_event(viewer, 'mouse_press', xdata=100, ydata=100)
    do_event(viewer, 'move', xdata=110, ydata=110)
    do_event(viewer, 'mouse_release')

    assert_equal(tool.overlay[tool.overlay == 2].size, 761)

    tool.label = 5
    do_event(viewer, 'mouse_press', xdata=20, ydata=20)
    do_event(viewer, 'move', xdata=40, ydata=40)
    do_event(viewer, 'mouse_release')

    assert_equal(tool.overlay[tool.overlay == 5].size, 881)
    assert_equal(tool.overlay[tool.overlay == 2].size, 761)

    do_event(viewer, 'key_press', key='enter')

    tool.overlay = tool.overlay * 0
    assert_equal(tool.overlay.sum(), 0)

def mono_check(plugin, fmt='png'):
    """Check the roundtrip behavior for images that support most types.

    All major input types should be handled.
    """

    img = img_as_ubyte(data.moon())
    r1 = roundtrip(img, plugin, fmt)
    testing.assert_allclose(img, r1)

    img2 = img > 128
    r2 = roundtrip(img2, plugin, fmt)
    testing.assert_allclose(img2.astype(np.uint8), r2)

    img3 = img_as_float(img)
    r3 = roundtrip(img3, plugin, fmt)
    if r3.dtype.kind == 'f':
        testing.assert_allclose(img3, r3)
    else:
        testing.assert_allclose(r3, img_as_uint(img))

    img4 = img_as_int(img)
    if fmt.lower() in (('tif', 'tiff')):
        img4 -= 100
        r4 = roundtrip(img4, plugin, fmt)
        testing.assert_allclose(r4, img4)
    else:
        r4 = roundtrip(img4, plugin, fmt)
        testing.assert_allclose(r4, img_as_uint(img4))

    img5 = img_as_uint(img)
    r5 = roundtrip(img5, plugin, fmt)
    testing.assert_allclose(r5, img5)

def test_paint_tool():
    img = data.moon()
    viewer = ImageViewer(img)

    tool = PaintTool(viewer.ax, img.shape)

    tool.radius = 10
    assert_equal(tool.radius, 10)
    tool.label = 2
    assert_equal(tool.label, 2)
    assert_equal(tool.shape, img.shape)

    start = create_mouse_event(viewer.ax, xdata=100, ydata=100)
    tool.on_mouse_press(start)
    move = create_mouse_event(viewer.ax, xdata=110, ydata=110)
    tool.on_move(move)
    tool.on_mouse_release(move)
    assert_equal(tool.overlay[tool.overlay == 2].size, 761)

    tool.label = 5
    start = create_mouse_event(viewer.ax, xdata=20, ydata=20)
    tool.on_mouse_press(start)
    move = create_mouse_event(viewer.ax, xdata=40, ydata=40)
    tool.on_move(move)
    tool.on_mouse_release(move)
    assert_equal(tool.overlay[tool.overlay == 5].size, 881)
    assert_equal(tool.overlay[tool.overlay == 2].size, 761)

    enter = create_mouse_event(viewer.ax, key='enter')
    tool.on_mouse_press(enter)

    tool.overlay = tool.overlay * 0
    assert_equal(tool.overlay.sum(), 0)

def main():
    """Load image, apply filters and plot the results."""
    img = data.moon()
    util.plot_images_grayscale(
        [img, median(img), morphological_edge(img),
         erosion(img), dilation(img),
         opening(img), closing(img)],
        ["Image", "Median", "Morphological Edge", "Erosion", "Dilation", "Opening", "Closing"]
    )

def test_isodata_moon_image_negative_float():
    moon = skimage.img_as_ubyte(data.moon()).astype(np.float64)
    moon -= 100

    assert -14 < threshold_isodata(moon) < -13

    thresholds = threshold_isodata(moon, return_all=True)
    assert_almost_equal(thresholds,
                        [-13.83789062, -12.84179688, -11.84570312, 22.02148438,
                         23.01757812, 24.01367188, 38.95507812, 39.95117188])

def test_isodata_moon_image():
    moon = skimage.img_as_ubyte(data.moon())

    threshold = threshold_isodata(moon)
    assert np.floor((moon[moon <= threshold].mean() + moon[moon > threshold].mean()) / 2.0) == threshold
    assert threshold == 86

    thresholds = threshold_isodata(moon, return_all=True)
    for threshold in thresholds:
        assert np.floor((moon[moon <= threshold].mean() + moon[moon > threshold].mean()) / 2.0) == threshold
    assert_equal(thresholds, [86, 87, 88, 122, 123, 124, 139, 140])

def test_isodata_moon_image_negative_int():
    moon = skimage.img_as_ubyte(data.moon()).astype(np.int32)
    moon -= 100

    threshold = threshold_isodata(moon)
    assert np.floor((moon[moon <= threshold].mean() + moon[moon > threshold].mean()) / 2.0) == threshold
    assert threshold == -14

    thresholds = threshold_isodata(moon, return_all=True)
    for threshold in thresholds:
        assert np.floor((moon[moon <= threshold].mean() + moon[moon > threshold].mean()) / 2.0) == threshold
    assert_equal(thresholds, [-14, -13, -12, 22, 23, 24, 39, 40])

def test_adapthist_scalar():
    """Test a scalar uint8 image
    """
    img = skimage.img_as_ubyte(data.moon())
    adapted = exposure.equalize_adapthist(img, kernel_size=64, clip_limit=0.02)
    assert adapted.min() == 0.0
    assert adapted.max() == 1.0
    assert img.shape == adapted.shape
    full_scale = skimage.exposure.rescale_intensity(skimage.img_as_float(img))

    assert_almost_equal(peak_snr(full_scale, adapted), 102.066, 3)
    assert_almost_equal(norm_brightness_err(full_scale, adapted),
                        0.038, 3)

def test_adapthist_scalar():
    '''Test a scalar uint8 image
    '''
    img = skimage.img_as_ubyte(data.moon())
    adapted = exposure.equalize_adapthist(img, clip_limit=0.02)
    assert adapted.min() == 0
    assert adapted.max() == (1 << 16) - 1
    assert img.shape == adapted.shape
    full_scale = skimage.exposure.rescale_intensity(skimage.img_as_uint(img))
    assert_almost_equal = np.testing.assert_almost_equal
    assert_almost_equal(peak_snr(full_scale, adapted), 101.231, 3)
    assert_almost_equal(norm_brightness_err(full_scale, adapted),
                        0.041, 3)
    return img, adapted

def test_base_tool():
    img = data.moon()
    viewer = ImageViewer(img)

    tool = CanvasToolBase(viewer)
    tool.set_visible(False)
    tool.set_visible(True)

    do_event(viewer, 'key_press', key='enter')

    tool.redraw()
    tool.remove()

    tool = CanvasToolBase(viewer, useblit=False)
    tool.redraw()

def test_label_painter():
    image = data.camera()
    moon = data.moon()
    viewer = ImageViewer(image)
    lp = LabelPainter()
    viewer += lp

    assert_equal(lp.radius, 5)
    lp.label = 1
    assert_equal(str(lp.label), '1')
    lp.label = 2
    assert_equal(str(lp.paint_tool.label), '2')
    assert_equal(lp.paint_tool.radius, 5)
    lp._on_new_image(moon)
    assert_equal(lp.paint_tool.shape, moon.shape)

def test_base_tool():
    img = data.moon()
    viewer = ImageViewer(img)

    tool = CanvasToolBase(viewer.ax)
    tool.set_visible(False)
    tool.set_visible(True)

    enter = create_mouse_event(viewer.ax, key='enter')
    tool._on_key_press(enter)

    tool.redraw()
    tool.remove()

    tool = CanvasToolBase(viewer.ax, useblit=False)
    tool.redraw()

def test_keypoints_censure_moon_image_octagon():
    """Verify the actual Censure keypoints and their corresponding scale with
    the expected values for Octagon filter."""
    img = moon()
    actual_kp_octagon, actual_scale = keypoints_censure(img, 1, 7, 'Octagon',
                                                        0.15)
    expected_kp_octagon = np.array([[ 21, 496],
                                    [ 35,  46],
                                    [287, 250],
                                    [356, 239],
                                    [463, 116]])

    expected_scale = np.array([3, 4, 2, 2, 2])

    assert_array_equal(expected_kp_octagon, actual_kp_octagon)
    assert_array_equal(expected_scale, actual_scale)

def test_keypoints_censure_moon_image_dob():
    """Verify the actual Censure keypoints and their corresponding scale with
    the expected values for DoB filter."""
    img = moon()
    actual_kp_dob, actual_scale = keypoints_censure(img, 1, 7, 'DoB', 0.15)
    expected_kp_dob = np.array([[ 21, 497],
                                [ 36,  46],
                                [119, 350],
                                [185, 177],
                                [287, 250],
                                [357, 239],
                                [463, 116],
                                [464, 132],
                                [467, 260]])
    expected_scale = np.array([3, 4, 4, 2, 2, 3, 2, 2, 2])

    assert_array_equal(expected_kp_dob, actual_kp_dob)
    assert_array_equal(expected_scale, actual_scale)

def test_keypoints_censure_moon_image_star():
    """Verify the actual Censure keypoints and their corresponding scale with
    the expected values for STAR filter."""
    img = moon()
    actual_kp_star, actual_scale = keypoints_censure(img, 1, 7, 'STAR', 0.15)
    expected_kp_star = np.array([[ 21, 497],
                                 [ 36,  46],
                                 [117, 356],
                                 [185, 177],
                                 [260, 227],
                                 [287, 250],
                                 [357, 239],
                                 [451, 281],
                                 [463, 116],
                                 [467, 260]])

    expected_scale = np.array([3, 3, 6, 2, 3, 2, 3, 5, 2, 2])

    assert_array_equal(expected_kp_star, actual_kp_star)
    assert_array_equal(expected_scale, actual_scale)

def test_plugin():
    img = skimage.img_as_float(data.moon())
    viewer = ImageViewer(img)

    def median_filter(img, radius=3):
        return median(img, selem=disk(radius=radius))

    plugin = Plugin(image_filter=median_filter)
    viewer += plugin

    plugin += Slider('radius', 1, 5)

    assert_almost_equal(np.std(viewer.image), 12.556, 3)

    plugin.filter_image()

    assert_almost_equal(np.std(viewer.image), 12.931, 3)

    plugin.show()
    plugin.close()
    plugin.clean_up()
    img, _ = plugin.output()
    assert_equal(img, viewer.image)

import matplotlib.pyplot as plt

from skimage import data
from skimage.exposure import rescale_intensity

import time

t1 = time.time()
image = data.moon()
# Rescale image intensity so that we can see dim features.
image = rescale_intensity(image, in_range=(50, 200))

t2 = time.time()
print (t2-t1)

# convenience function for plotting images
def imshow(image, **kwargs):
    plt.figure(figsize=(5, 4))
    plt.imshow(image, **kwargs)
    plt.axis('off')

#imshow(image)
#plt.title('original image')

def test_adapthist_ntiles_raises():
    img = skimage.img_as_ubyte(data.moon())
    assert_raises(ValueError, exposure.equalize_adapthist, img, ntiles_x=8)
    assert_raises(ValueError, exposure.equalize_adapthist, img, ntiles_y=8)
    assert_raises(ValueError, exposure.equalize_adapthist, img,
                  ntiles_x=8, ntiles_y=8)

def find_bounding_box(Array):
	a = np.zeros(4).reshape((2,2))
	a[0] = Array[0]
	for x in range(0, array.shape[0]): 
		if(a[0][0] > array[x][0]):
			a[0][0] = array[x][0]

		if(a[0][1] > array[x][1]):
			a[0][1] = array[x][1]

		if(a[1][0] < array[x][0]):
			a[1][0] = array[x][0]

		elif(a[1][1] < array[x][1]):
			a[1][1] = array[x][1]
	return a

def fault_detector(image):
	fault_sercher = image_search()
	bounding_box = find_bounding_box(fault_sercher)
	bound_image = image_cut(image,bounding_box[0][0],bounding_box[0][1],(bounding_box[1][0] - bounding_box[0][0]), (bounding_box[1][1]-bounding_box[0][1]))
	
	return bound_image

#===============================================================================
#MAIN PROGRAM
#test_image = data.load("/home/lapowell/Downloads/asteroids.jpg")
image1 = data.moon()
l = image_search(image1,78)
print l