From d55135ddbb64dba7b1d1c948bed18719a77430ea Mon Sep 17 00:00:00 2001
From: Tim Sheerman-Chase <tim2009@sheerman-chase.org.uk>
Date: Wed, 19 Jun 2013 09:45:26 +0100
Subject: [PATCH] Fix comments and tab whitespace

---
 skimage/feature/_hog.py           |  1 +
 skimage/feature/_hoghistogram.pyx | 90 +++++++++++++++----------------
 2 files changed, 46 insertions(+), 45 deletions(-)

diff --git a/skimage/feature/_hog.py b/skimage/feature/_hog.py
index b9d62926..64ef3bdf 100644
--- a/skimage/feature/_hog.py
+++ b/skimage/feature/_hog.py
@@ -114,6 +114,7 @@ def hog(image, orientations=9, pixels_per_cell=(8, 8),
     n_cellsx = int(np.floor(sx // cx))  # number of cells in x
     n_cellsy = int(np.floor(sy // cy))  # number of cells in y
 
+    # compute orientations integral images
     orientation_histogram = np.zeros((n_cellsy, n_cellsx, orientations))
 
     _hoghistogram.HogHistograms(gx, gy, cx, cy, sx, sy, n_cellsx, n_cellsy, visualise, orientations, 
diff --git a/skimage/feature/_hoghistogram.pyx b/skimage/feature/_hoghistogram.pyx
index 96112730..df38f945 100644
--- a/skimage/feature/_hoghistogram.pyx
+++ b/skimage/feature/_hoghistogram.pyx
@@ -9,62 +9,62 @@ import numpy as np
 from scipy import pi, arctan2, cos, sin
 
 cdef float CellHog(np.ndarray[np.float64_t, ndim=2] magnitude, 
-	np.ndarray[np.float64_t, ndim=2] orientation,
-	float ori1, float ori2,
-	int cx, int cy, int xi, int yi, int sx, int sy):
-	cdef int cx1, cy1
+    np.ndarray[np.float64_t, ndim=2] orientation,
+    float ori1, float ori2,
+    int cx, int cy, int xi, int yi, int sx, int sy):
+    cdef int cx1, cy1
 
-	cdef float total = 0.
-	for cy1 in range(-cy/2, cy/2):
-		for cx1 in range(-cx/2, cx/2):
-			if yi + cy1 < 0: continue
-			if yi + cy1 >= sy: continue
-			if xi + cx1 < 0: continue
-			if xi + cx1 >= sx: continue
-			if orientation[yi + cy1, xi + cx1] >= ori1: continue
-			if orientation[yi + cy1, xi + cx1] < ori2: continue
+    cdef float total = 0.
+    for cy1 in range(-cy/2, cy/2):
+        for cx1 in range(-cx/2, cx/2):
+            if yi + cy1 < 0: continue
+            if yi + cy1 >= sy: continue
+            if xi + cx1 < 0: continue
+            if xi + cx1 >= sx: continue
+            if orientation[yi + cy1, xi + cx1] >= ori1: continue
+            if orientation[yi + cy1, xi + cx1] < ori2: continue
 
-			total += magnitude[yi + cy1, xi + cx1]
+            total += magnitude[yi + cy1, xi + cx1]
 
-	return total
+    return total
 
 def HogHistograms(np.ndarray[np.float64_t, ndim=2] gx, \
-	np.ndarray[np.float64_t, ndim=2] gy, 
-	int cx, int cy, #Pixels per cell
-	int sx, int sy, #Image size
-	int n_cellsx, int n_cellsy, 
-	int visualise, int orientations, 
-	np.ndarray[np.float64_t, ndim=3] orientation_histogram):
+    np.ndarray[np.float64_t, ndim=2] gy, 
+    int cx, int cy, #Pixels per cell
+    int sx, int sy, #Image size
+    int n_cellsx, int n_cellsy, 
+    int visualise, int orientations, 
+    np.ndarray[np.float64_t, ndim=3] orientation_histogram):
 
-	cdef np.ndarray[np.float64_t, ndim=2] magnitude = np.sqrt(gx**2 + gy**2)
-	cdef np.ndarray[np.float64_t, ndim=2] orientation = arctan2(gy, gx) * (180 / pi) % 180
-	cdef int i, x, y, o, yi, xi, cy1, cy2, cx1, cx2
-	cdef float ori1, ori2
+    cdef np.ndarray[np.float64_t, ndim=2] magnitude = np.sqrt(gx**2 + gy**2)
+    cdef np.ndarray[np.float64_t, ndim=2] orientation = arctan2(gy, gx) * (180 / pi) % 180
+    cdef int i, x, y, o, yi, xi, cy1, cy2, cx1, cx2
+    cdef float ori1, ori2
 
-	# compute orientations integral images
+    # compute orientations integral images
 
-	for i in range(orientations):
-		# isolate orientations in this range
+    for i in range(orientations):
+        # isolate orientations in this range
 
-		ori1 = 180. / orientations * (i + 1)
-		ori2 = 180. / orientations * i
+        ori1 = 180. / orientations * (i + 1)
+        ori2 = 180. / orientations * i
 
-		y = cy / 2
-		cy2 = cy * n_cellsy
-		x = cx / 2
-		cx2 = cx * n_cellsx
-		yi = 0
-		xi = 0
+        y = cy / 2
+        cy2 = cy * n_cellsy
+        x = cx / 2
+        cx2 = cx * n_cellsx
+        yi = 0
+        xi = 0
 
-		while y < cy2:
-			xi = 0
-			x = cx / 2
+        while y < cy2:
+            xi = 0
+            x = cx / 2
 
-			while x < cx2:
-				orientation_histogram[yi, xi, i] = CellHog(magnitude, orientation, ori1, ori2, cx, cy, x, y, sx, sy)
-				xi += 1
-				x += cx
+            while x < cx2:
+                orientation_histogram[yi, xi, i] = CellHog(magnitude, orientation, ori1, ori2, cx, cy, x, y, sx, sy)
+                xi += 1
+                x += cx
 
-			yi += 1
-			y += cy
+            yi += 1
+            y += cy