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Minor cleanup of hist(). #7481

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Merged
merged 1 commit into from
Nov 19, 2016
Merged

Minor cleanup of hist(). #7481

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23 changes: 9 additions & 14 deletions lib/matplotlib/axes/_axes.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6273,28 +6273,23 @@ def _normalize_input(inp, ename='input'):
totwidth = np.diff(bins)

if rwidth is not None:
dr = min(1.0, max(0.0, rwidth))
dr = np.clip(rwidth, 0, 1)
elif (len(n) > 1 and
((not stacked) or rcParams['_internal.classic_mode'])):
dr = 0.8
else:
dr = 1.0

if histtype == 'bar' and not stacked:
width = dr*totwidth/nx
width = dr * totwidth / nx
dw = width

if nx > 1:
boffset = -0.5*dr*totwidth*(1.0-1.0/nx)
else:
boffset = 0.0
stacked = False
boffset = -0.5 * dr * totwidth * (1 - 1 / nx)
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Doesn't this introduce the possibility of divide-by-zero?

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l.6284 also divides by nx, so if nx is 0, we already to a divide-by-zero.

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Good point.

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if nx is zero, then there is no data so other things are confused as well.

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It seems to me that due to l. 6176-6181 (and above), the case nx == 0 should never occur: the case where the input is empty is preprocessed to have a length of 1.

# Massage 'x' for processing.
if input_empty:
    x = np.array([[]])
else:
    x = _normalize_input(x, 'x')
nx = len(x)  # number of datasets

elif histtype == 'barstacked' or stacked:
width = dr*totwidth
width = dr * totwidth
boffset, dw = 0.0, 0.0

if align == 'mid' or align == 'edge':
boffset += 0.5*totwidth
boffset += 0.5 * totwidth
elif align == 'right':
boffset += totwidth

Expand All @@ -6307,7 +6302,7 @@ def _normalize_input(inp, ename='input'):

for m, c in zip(n, color):
if bottom is None:
bottom = np.zeros(len(m), float)
bottom = np.zeros(len(m))
if stacked:
height = m - bottom
else:
Expand All @@ -6326,14 +6321,14 @@ def _normalize_input(inp, ename='input'):

elif histtype.startswith('step'):
# these define the perimeter of the polygon
x = np.zeros(4 * len(bins) - 3, float)
y = np.zeros(4 * len(bins) - 3, float)
x = np.zeros(4 * len(bins) - 3)
y = np.zeros(4 * len(bins) - 3)

x[0:2*len(bins)-1:2], x[1:2*len(bins)-1:2] = bins, bins[:-1]
x[2*len(bins)-1:] = x[1:2*len(bins)-1][::-1]

if bottom is None:
bottom = np.zeros(len(bins)-1, float)
bottom = np.zeros(len(bins) - 1)

y[1:2*len(bins)-1:2], y[2:2*len(bins):2] = bottom, bottom
y[2*len(bins)-1:] = y[1:2*len(bins)-1][::-1]
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