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Small clean to SymmetricalLogLocator #14308

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Merged
merged 4 commits into from
May 31, 2019
Merged

Small clean to SymmetricalLogLocator #14308

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d11ac6a
Add more descriptive variable names
dstansby May 21, 2019
6b312bf
Add some more comments and use np.abs() to make clear intent
dstansby May 24, 2019
508d3b2
Put back missing +1s
dstansby May 27, 2019
c39f4a6
Fix comment typo
dstansby May 27, 2019
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38 changes: 20 additions & 18 deletions lib/matplotlib/ticker.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2442,8 +2442,8 @@ def __call__(self):
return self.tick_values(vmin, vmax)

def tick_values(self, vmin, vmax):
b = self._base
t = self._linthresh
base = self._base
linthresh = self._linthresh

if vmax < vmin:
vmin, vmax = vmax, vmin
Expand All @@ -2468,22 +2468,23 @@ def tick_values(self, vmin, vmax):
# "simple" mode is when the range falls entirely within (-t,
# t) -- it should just display (vmin, 0, vmax)

# Determine which of the three ranges we have
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I think the whole thing can be simplified to

if -linthresh <= vmin <= vmax <= 0 or 0 <= vmin <= vmax <= linthresh:
    return [vmin, vmax]
has_a = (vmin < -linthresh)
has_b = (-linthresh < vmin < linthresh or -linthresh < vmax < linthresh)
has_c = (linthresh < vmax)

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I think SymLogNorm needs quite a few more tests, which I plan to add in for 3.2 at some point; I think this is a good suggestion, but might save it for after I've written tests that exercise this logic properly.

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sure

has_a = has_b = has_c = False
if vmin < -t:
if vmin < -linthresh:
has_a = True
if vmax > -t:
if vmax > -linthresh:
has_b = True
if vmax > t:
if vmax > linthresh:
has_c = True
elif vmin < 0:
if vmax > 0:
has_b = True
if vmax > t:
if vmax > linthresh:
has_c = True
else:
return [vmin, vmax]
elif vmin < t:
if vmax > t:
elif vmin < linthresh:
if vmax > linthresh:
has_b = True
has_c = True
else:
Expand All @@ -2492,46 +2493,47 @@ def tick_values(self, vmin, vmax):
has_c = True

def get_log_range(lo, hi):
lo = np.floor(np.log(lo) / np.log(b))
hi = np.ceil(np.log(hi) / np.log(b))
lo = np.floor(np.log(lo) / np.log(base))
hi = np.ceil(np.log(hi) / np.log(base))
return lo, hi

# First, calculate all the ranges, so we can determine striding
# Calculate all the ranges, so we can determine striding
if has_a:
if has_b:
a_range = get_log_range(t, -vmin + 1)
a_range = get_log_range(linthresh, np.abs(vmin) + 1)
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can use (builtin) abs() instead of np.abs()

else:
a_range = get_log_range(-vmax, -vmin + 1)
a_range = get_log_range(np.abs(vmax), np.abs(vmin) + 1)
else:
a_range = (0, 0)

if has_c:
if has_b:
c_range = get_log_range(t, vmax + 1)
c_range = get_log_range(linthresh, vmax + 1)
else:
c_range = get_log_range(vmin, vmax + 1)
else:
c_range = (0, 0)

# Calculate the total number of integer exponents in a and c ranges
total_ticks = (a_range[1] - a_range[0]) + (c_range[1] - c_range[0])
if has_b:
total_ticks += 1
stride = max(total_ticks // (self.numticks - 1), 1)

decades = []
if has_a:
decades.extend(-1 * (b ** (np.arange(a_range[0], a_range[1],
stride)[::-1])))
decades.extend(-1 * (base ** (np.arange(a_range[0], a_range[1],
stride)[::-1])))

if has_b:
decades.append(0.0)

if has_c:
decades.extend(b ** (np.arange(c_range[0], c_range[1], stride)))
decades.extend(base ** (np.arange(c_range[0], c_range[1], stride)))

# Add the subticks if requested
if self._subs is None:
subs = np.arange(2.0, b)
subs = np.arange(2.0, base)
else:
subs = np.asarray(self._subs)

Expand Down