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Reparameterize profile_line to avoid the _calc_vert hack

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Juan Nunez-Iglesias
2014-01-29 14:23:51 +11:00
parent 2a6ec20136
commit ae85e26ee3
1 changed files with 24 additions and 27 deletions
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skimage/measure/profile.py
+24 -27
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@@ -1,12 +1,6 @@
import numpy as np
import scipy.ndimage as ndi
def _calc_vert(img, col, src_row, dst_row, linewidth):
# Quick calculation if perfectly vertical
pixels = img[src_row:dst_row:np.sign(dst_row - src_row),
col - linewidth / 2: col + linewidth / 2 + 1]
return pixels.mean(axis=1)[..., np.newaxis]
def profile_line(img, src, dst, linewidth=1, mode='constant', cval=0.0):
"""Return the intensity profile of an image measured along a scan line.
@@ -49,29 +43,32 @@ def profile_line(img, src, dst, linewidth=1, mode='constant', cval=0.0):
dst_row, dst_col = dst = np.asarray(dst, dtype=float)
d_row, d_col = dst - src
# Quick calculation if perfectly vertical; shortcuts div0 error
if src_col == dst_col:
if img.ndim == 2:
img = img[:, :, np.newaxis]
img = np.rollaxis(img, -1)
intensities = np.hstack([_calc_vert(im, src_col,
src_row, dst_row, linewidth)
for im in img])
return np.squeeze(intensities)
if d_col == 0:
if d_row > 0:
theta = -np.pi / 2
else:
theta = np.pi / 2
else:
theta = np.arctan2(-d_row, d_col)
theta = np.arctan2(d_row, d_col)
a = d_row / d_col
b = src_row - a * src_col
length = np.hypot(d_row, d_col)
length = np.ceil(np.hypot(d_row, d_col))
line_col = np.linspace(src_col, dst_col, length)
line_row = np.linspace(src_row, dst_row, length)
line_x = np.linspace(src_col, dst_col, np.ceil(length))
line_y = line_x * a + b
y_width = abs(linewidth * np.cos(theta) / 2)
perp_ys = np.array([np.linspace(yi - y_width,
yi + y_width, linewidth) for yi in line_y])
perp_xs = - a * perp_ys + (line_x + a * line_y)[:, np.newaxis]
perp_lines = np.array([perp_ys, perp_xs])
# this if clause is necessary to keep the line centered on the true
# source and destination points. Otherwise, the computed line has
# an offset of `linewidth/2`
if linewidth <= 1:
perp_lines = np.array([line_row[:, np.newaxis],
line_col[:, np.newaxis]])
else:
col_width = linewidth * np.sin(theta) / 2
row_width = linewidth * np.cos(theta) / 2
perp_rows = np.array([np.linspace(row_i - row_width, row_i + row_width,
linewidth) for row_i in line_row])
perp_cols = np.array([np.linspace(col_i - col_width, col_i + col_width,
linewidth) for col_i in line_col])
perp_lines = np.array([perp_rows, perp_cols])
if img.ndim == 3:
pixels = [ndi.map_coordinates(img[..., i], perp_lines, mode=mode,
cval=cval) for i in range(img.shape[2])]