tabs to space, replace non-ascii [ci skip]

doc/fill_performance.py

@@ -13,55 +13,55 @@ mpl.rcParams.update(mpl.rcParamsDefault)
 
 data = defaultdict(lambda:[])
 for line in open(sys.argv[1]):
-	if line.startswith("baseline"):
-		continue
-	descr, time = [x for x in line.split() if x]
-	dim, label, dist = descr.split("-")
-	data[int(dim[0])].append((label, dist, float(time)))
+    if line.startswith("baseline"):
+        continue
+    descr, time = [x for x in line.split() if x]
+    dim, label, dist = descr.split("-")
+    data[int(dim[0])].append((label, dist, float(time)))
 
 plt.figure()
 if os.path.exists("/proc/cpuinfo"):
-	cpuinfo = open("/proc/cpuinfo").read()
-	m = re.search("model name\s*:\s*(.+)\n", cpuinfo)
-	if m:
-		plt.title(m.group(1))
+    cpuinfo = open("/proc/cpuinfo").read()
+    m = re.search("model name\s*:\s*(.+)\n", cpuinfo)
+    if m:
+        plt.title(m.group(1))
 i = 0
 for dim in sorted(data):
-	v = data[dim]
-	labels = OrderedDict()
-	for label, dist, time in v:
-		if label in labels:
-			labels[label][dist] = time
-		else:
-			labels[label] = {dist: time}
-	j = 0
-	for label, d in labels.items():
-		t1 = d["uniform"]
-		t2 = d["normal"]
-		i -= 1
-		z = float(j) / len(labels)
-		col = ((1.0-z) * np.array((1.0, 0.0, 0.0))
-			   + z * np.array((1.0, 1.0, 0.0)))
-		if label == "root":
-			col = "k"
-		if "numpy" in label:
-			col = "0.6"
-		if "gsl" in label:
-			col = "0.3"
-		r1 = Rectangle((0, i), t1, 0.5, facecolor=col)
-		r2 = Rectangle((0, i+0.5), t2, 0.5, facecolor=col)
-		plt.gca().add_artist(r1)
-		plt.gca().add_artist(r2)
-		tx = Text(-0.1, i+0.5, "%s" % label,
-			      va="center", ha="right", clip_on=False)
-		plt.gca().add_artist(tx)
-		j += 1
-	i -= 1
-	font0 = FontProperties()
-	font0.set_weight("bold")
-	tx = Text(-0.1, i+0.6, "%iD" % dim,
-			  fontproperties=font0, va="center", ha="right", clip_on=False)
-	plt.gca().add_artist(tx)
+    v = data[dim]
+    labels = OrderedDict()
+    for label, dist, time in v:
+        if label in labels:
+            labels[label][dist] = time
+        else:
+            labels[label] = {dist: time}
+    j = 0
+    for label, d in labels.items():
+        t1 = d["uniform"]
+        t2 = d["normal"]
+        i -= 1
+        z = float(j) / len(labels)
+        col = ((1.0-z) * np.array((1.0, 0.0, 0.0))
+               + z * np.array((1.0, 1.0, 0.0)))
+        if label == "root":
+            col = "k"
+        if "numpy" in label:
+            col = "0.6"
+        if "gsl" in label:
+            col = "0.3"
+        r1 = Rectangle((0, i), t1, 0.5, facecolor=col)
+        r2 = Rectangle((0, i+0.5), t2, 0.5, facecolor=col)
+        plt.gca().add_artist(r1)
+        plt.gca().add_artist(r2)
+        tx = Text(-0.1, i+0.5, "%s" % label,
+                  va="center", ha="right", clip_on=False)
+        plt.gca().add_artist(tx)
+        j += 1
+    i -= 1
+    font0 = FontProperties()
+    font0.set_weight("bold")
+    tx = Text(-0.1, i+0.6, "%iD" % dim,
+              fontproperties=font0, va="center", ha="right", clip_on=False)
+    plt.gca().add_artist(tx)
 plt.ylim(0, i)
 plt.xlim(0, 30)
 

doc/iteration_performance.py

@@ -24,10 +24,10 @@ for iline, line in enumerate(open(sys.argv[1])):
 
 fig, ax = plt.subplots(1, 3, figsize=(10, 5), sharex=True, sharey=True)
 if os.path.exists("/proc/cpuinfo"):
-	cpuinfo = open("/proc/cpuinfo").read()
-	m = re.search("model name\s*:\s*(.+)\n", cpuinfo)
-	if m:
-		plt.suptitle(m.group(1))
+    cpuinfo = open("/proc/cpuinfo").read()
+    m = re.search("model name\s*:\s*(.+)\n", cpuinfo)
+    if m:
+        plt.suptitle(m.group(1))
 plt.subplots_adjust(bottom=0.18, wspace=0, top=0.85, right=0.98, left=0.07)
 for iaxis, axis_type in enumerate(("tuple", "vector", "vector_of_variant")):
     plt.sca(ax[iaxis])

include/boost/histogram/accumulators/sum.hpp

@@ -25,7 +25,7 @@ namespace accumulators {
   independent of the number of samples.
 
   A. Neumaier, Zeitschrift fuer Angewandte Mathematik
-  und Mechanik 54 (1974) 39–51.
+  und Mechanik 54 (1974) 39-51.
 */
 template <typename RealType>
 class sum {