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FIX: refactor code, fix linewidth calculation

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Josh Warner (Mac)
2013-06-28 17:40:05 -05:00
parent 2b5930ad60
commit e20aa7c381
1 changed files with 38 additions and 39 deletions
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skimage/viewer/plugins/lineprofile.py
+38 -39
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@@ -138,13 +138,29 @@ class LineProfile(PlotPlugin):
scan_data[:, 2], 'b-')
def _calc_horiz(img, x1, x2, y1, y2, linewidth):
# Quick calculation if perfectly horizontal
pixels = img[min(y1, y2): max(y1, y2) + 1,
x1 - linewidth / 2: x1 + linewidth / 2 + 1]
intensities = pixels.mean(axis=1)
return intensities
def _calc_vert(img, x1, x2, y1, y2, linewidth):
# Quick calculation if perfectly vertical
pixels = img[y1 - linewidth / 2: y1 + linewidth / 2 + 1,
min(x1, x2): max(x1, x2) + 1]
intensities = pixels.mean(axis=0)
return intensities
def profile_line(img, end_points, linewidth=1):
"""Return the intensity profile of an image measured along a scan line.
Parameters
----------
img : 2d array
The image.
img : 2d or 3d array
The image, in grayscale (2d) or RGB (3d) format.
end_points: (2, 2) list
End points ((x1, y1), (x2, y2)) of scan line.
linewidth: int
@@ -160,45 +176,28 @@ def profile_line(img, end_points, linewidth=1):
x1, y1 = point1 = np.asarray(point1, dtype=float)
x2, y2 = point2 = np.asarray(point2, dtype=float)
dx, dy = point2 - point1
channels = 1
if img.ndim == 3:
channels = 3
# Quick calculation if perfectly horizontal or vertical
if x1 == x2:
if img.ndim == 2:
pixels = img[min(y1, y2): max(y1, y2) + 1,
x1 - linewidth / 2: x1 + linewidth / 2 + 1]
return pixels.mean(axis=1)[:, np.newaxis]
else:
for i in range(3):
try:
temp = img[min(y1, y2): max(y1, y2) + 1,
x1 - linewidth / 2: x1 + linewidth / 2 + 1, i]
pixels = np.concatenate((pixels, temp[..., np.newaxis]),
axis=2)
del temp
except:
pixels = img[min(y1, y2): max(y1, y2) + 1,
x1 - linewidth / 2: x1 + linewidth / 2 + 1,
i][..., np.newaxis]
return pixels.mean(axis=1)
for i in range(channels):
try:
intensities = np.concatenate(
(intensities,
_calc_horiz(img, x1, x2, y1, y2, linewidth)), axis=1)
except:
intensities = _calc_horiz(img, x1, x2, y1, y2, linewidth)
elif y1 == y2:
if img.ndim == 2:
pixels = img[y1 - linewidth / 2: y1 + linewidth / 2 + 1,
min(x1, x2): max(x1, x2) + 1]
return pixels.mean(axis=1)[..., np.newaxis]
else:
for i in range(3):
try:
temp = img[y1 - linewidth / 2: y1 + linewidth / 2 + 1,
min(x1, x2): max(x1, x2) + 1, i]
pixels = np.concatenate((pixels, temp[..., np.newaxis]),
axis=2)
del temp
except:
pixels = img[y1 - linewidth / 2: y1 + linewidth / 2 + 1,
min(x1, x2): max(x1, x2) + 1,
i][..., np.newaxis]
return pixels.mean(axis=0)
for i in range(channels):
try:
intensities = np.concatenate(
(intensities,
_calc_vert(img, x1, x2, y1, y2, linewidth)), axis=1)
except:
intensities = _calc_vert(img, x1, x2, y1, y2, linewidth)
theta = np.arctan2(dy, dx)
a = dy / dx
@@ -214,9 +213,9 @@ def profile_line(img, end_points, linewidth=1):
perp_lines = np.array([perp_ys, perp_xs])
if img.ndim == 3:
pixels = np.zeros((perp_lines.shape[1], y_width * 2 + 1, 3))
for i in range(3):
pixels[..., i] = ndi.map_coordinates(img[..., i], perp_lines)
pixels = [ndi.map_coordinates(img[..., i], perp_lines)
for i in range(3)]
pixels = np.transpose(np.asarray(pixels), (1, 2, 0))
else:
pixels = ndi.map_coordinates(img, perp_lines)
pixels = pixels[..., np.newaxis]