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Merged
merged 4 commits into from
Dec 12, 2016
Merged

BUG: fix minpos handling and other log ticker problems #7598

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e3de3be
BUG: fix minpos handling and other log ticker problems
efiring Dec 9, 2016
8bdabcd
refactor LogFormatter classes for consistency, readability
efiring Dec 10, 2016
a8e7575
api_changes: add note about LogFormatter linthresh kwarg.
efiring Dec 10, 2016
aa36ec3
test for shared log axes
efiring Dec 10, 2016
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7 changes: 5 additions & 2 deletions doc/api/api_changes.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -141,8 +141,8 @@ the kwarg is None which internally sets it to the 'auto' string,
triggering a new algorithm for adjusting the maximum according
to the axis length relative to the ticklabel font size.

`matplotlib.ticker.LogFormatter` gains minor_thresholds kwarg
-------------------------------------------------------------
`matplotlib.ticker.LogFormatter`: two new kwargs
------------------------------------------------

Previously, minor ticks on log-scaled axes were not labeled by
default. An algorithm has been added to the
Expand All @@ -151,6 +151,9 @@ ticks between integer powers of the base. The algorithm uses
two parameters supplied in a kwarg tuple named 'minor_thresholds'.
See the docstring for further explanation.

To improve support for axes using `~matplotlib.ticker.SymmetricLogLocator`,
a 'linthresh' kwarg was added.


New defaults for 3D quiver function in mpl_toolkits.mplot3d.axes3d.py
---------------------------------------------------------------------
Expand Down
9 changes: 8 additions & 1 deletion lib/matplotlib/scale.py
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Original file line number Diff line number Diff line change
Expand Up @@ -264,6 +264,10 @@ def limit_range_for_scale(self, vmin, vmax, minpos):
"""
Limit the domain to positive values.
"""
if not np.isfinite(minpos):
minpos = 1e-300 # This value should rarely if ever
# end up with a visible effect.

return (minpos if vmin <= 0 else vmin,
minpos if vmax <= 0 else vmax)

Expand Down Expand Up @@ -499,7 +503,10 @@ def limit_range_for_scale(self, vmin, vmax, minpos):
"""
Limit the domain to values between 0 and 1 (excluded).
"""
return (minpos if vmin <= 0 else minpos,
if not np.isfinite(minpos):
minpos = 1e-7 # This value should rarely if ever
# end up with a visible effect.
return (minpos if vmin <= 0 else vmin,
1 - minpos if vmax >= 1 else vmax)


Expand Down
19 changes: 19 additions & 0 deletions lib/matplotlib/tests/test_axes.py
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Original file line number Diff line number Diff line change
Expand Up @@ -176,6 +176,25 @@ def test_autoscale_tight():
assert_allclose(ax.get_xlim(), (-0.15, 3.15))
assert_allclose(ax.get_ylim(), (1.0, 4.0))


@cleanup(style='default')
def test_autoscale_log_shared():
# related to github #7587
# array starts at zero to trigger _minpos handling
x = np.arange(100, dtype=float)
fig, (ax1, ax2) = plt.subplots(2, 1, sharex=True)
ax1.loglog(x, x)
ax2.semilogx(x, x)
ax1.autoscale(tight=True)
ax2.autoscale(tight=True)
plt.draw()
lims = (x[1], x[-1])
assert_allclose(ax1.get_xlim(), lims)
assert_allclose(ax1.get_ylim(), lims)
assert_allclose(ax2.get_xlim(), lims)
assert_allclose(ax2.get_ylim(), (x[0], x[-1]))


@cleanup(style='default')
def test_use_sticky_edges():
fig, ax = plt.subplots()
Expand Down
193 changes: 93 additions & 100 deletions lib/matplotlib/ticker.py
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Expand Up @@ -902,10 +902,6 @@ def set_locs(self, locs=None):
self._sublabels = None
return

b = self._base

vmin, vmax = self.axis.get_view_interval()

# Handle symlog case:
linthresh = self._linthresh
if linthresh is None:
Expand All @@ -914,6 +910,18 @@ def set_locs(self, locs=None):
except AttributeError:
pass

vmin, vmax = self.axis.get_view_interval()
if vmin > vmax:
vmin, vmax = vmax, vmin

if linthresh is None and vmin <= 0:
# It's probably a colorbar with
# a format kwarg setting a LogFormatter in the manner
# that worked with 1.5.x, but that doesn't work now.
self._sublabels = set((1,)) # label powers of base
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With Python 2.7, can use a set literal {1}.

return

b = self._base
if linthresh is not None: # symlog
# Only compute the number of decades in the logarithmic part of the
# axis
Expand Down Expand Up @@ -943,37 +951,38 @@ def set_locs(self, locs=None):
# Label all integer multiples of base**n.
self._sublabels = set(np.arange(1, b + 1))

def _num_to_string(self, x, vmin, vmax):
if x > 10000:
s = '%1.0e' % x
elif x < 1:
s = '%1.0e' % x
else:
s = self.pprint_val(x, vmax - vmin)

def __call__(self, x, pos=None):
"""
Return the format for tick val `x`.
"""
vmin, vmax = self.axis.get_view_interval()
vmin, vmax = mtransforms.nonsingular(vmin, vmax, expander=0.05)
d = abs(vmax - vmin)
b = self._base
if x == 0.0:
if x == 0.0: # Symlog
return '0'

sign = np.sign(x)
x = abs(x)
b = self._base
# only label the decades
fx = math.log(x) / math.log(b)
is_x_decade = is_close_to_int(fx)
exponent = np.round(fx) if is_x_decade else np.floor(fx)
coeff = np.round(x / b ** exponent)

if self.labelOnlyBase and not is_x_decade:
return ''
if self._sublabels is not None and coeff not in self._sublabels:
return ''

if x > 10000:
s = '%1.0e' % x
elif x < 1:
s = '%1.0e' % x
else:
s = self.pprint_val(x, d)
if sign == -1:
s = '-%s' % s

vmin, vmax = self.axis.get_view_interval()
vmin, vmax = mtransforms.nonsingular(vmin, vmax, expander=0.05)
s = self._num_to_string(x, vmin, vmax)
return self.fix_minus(s)

def format_data(self, value):
Expand Down Expand Up @@ -1026,41 +1035,16 @@ class LogFormatterExponent(LogFormatter):
"""
Format values for log axis using ``exponent = log_base(value)``.
"""
def __call__(self, x, pos=None):
"""
Return the format for tick value `x`.
"""
vmin, vmax = self.axis.get_view_interval()
vmin, vmax = mtransforms.nonsingular(vmin, vmax, expander=0.05)
d = abs(vmax - vmin)
b = self._base
if x == 0:
return '0'
sign = np.sign(x)
x = abs(x)
# only label the decades
fx = math.log(x) / math.log(b)

is_x_decade = is_close_to_int(fx)
exponent = np.round(fx) if is_x_decade else np.floor(fx)
coeff = np.round(x / b ** exponent)

if self.labelOnlyBase and not is_x_decade:
return ''
if self._sublabels is not None and coeff not in self._sublabels:
return ''

def _num_to_string(self, x, vmin, vmax):
fx = math.log(x) / math.log(self._base)
if abs(fx) > 10000:
s = '%1.0g' % fx
elif abs(fx) < 1:
s = '%1.0g' % fx
else:
fd = math.log(abs(d)) / math.log(b)
fd = math.log(vmax - vmin) / math.log(self._base)
s = self.pprint_val(fx, fd)
if sign == -1:
s = '-%s' % s

return self.fix_minus(s)
return s


class LogFormatterMathtext(LogFormatter):
Expand All @@ -1082,35 +1066,34 @@ def __call__(self, x, pos=None):

The position `pos` is ignored.
"""
b = self._base
usetex = rcParams['text.usetex']

# only label the decades
if x == 0:
if x == 0: # Symlog
if usetex:
return '$0$'
else:
return '$%s$' % _mathdefault('0')

sign_string = '-' if x < 0 else ''
x = abs(x)
b = self._base

# only label the decades
fx = math.log(x) / math.log(b)
is_x_decade = is_close_to_int(fx)
exponent = np.round(fx) if is_x_decade else np.floor(fx)
coeff = np.round(x / b ** exponent)

if self.labelOnlyBase and not is_x_decade:
return ''
if self._sublabels is not None and coeff not in self._sublabels:
return ''

# use string formatting of the base if it is not an integer
if b % 1 == 0.0:
base = '%d' % b
else:
base = '%s' % b

if self.labelOnlyBase and not is_x_decade:
return ''
if self._sublabels is not None and coeff not in self._sublabels:
return ''

if not is_x_decade:
return self._non_decade_format(sign_string, base, fx, usetex)
else:
Expand Down Expand Up @@ -2032,36 +2015,41 @@ def view_limits(self, vmin, vmax):
'Try to choose the view limits intelligently'
b = self._base

if vmax < vmin:
vmin, vmax = vmax, vmin
vmin, vmax = self.nonsingular(vmin, vmax)

if self.axis.axes.name == 'polar':
vmax = math.ceil(math.log(vmax) / math.log(b))
vmin = b ** (vmax - self.numdecs)
return vmin, vmax

minpos = self.axis.get_minpos()

if minpos <= 0 or not np.isfinite(minpos):
raise ValueError(
"Data has no positive values, and therefore can not be "
"log-scaled.")

if vmin <= 0:
vmin = minpos

if rcParams['axes.autolimit_mode'] == 'round_numbers':
if not is_decade(vmin, self._base):
vmin = decade_down(vmin, self._base)
if not is_decade(vmax, self._base):
vmax = decade_up(vmax, self._base)

if vmin == vmax:
vmin = decade_down(vmin, self._base)
vmax = decade_up(vmax, self._base)
return vmin, vmax

result = mtransforms.nonsingular(vmin, vmax)
return result
def nonsingular(self, vmin, vmax):
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Don't we already have have a nonsingular?

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Yes, but 'nonsingular' means different things for different transforms--different behaviors are needed.

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can this have a leading underscore? I missread and did not notice that this was a method.

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It could, but there are other nonsingular methods like this that don't, and they are called as locator.nonsingular(x0, x1) in autoscale_view(). So if I were to add an underscore here, I would either have to use two different calls in autoscale_view, or add an underscore to the other locator methods with that name.

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I am sold on consistency of naming.

if not np.isfinite(vmin) or not np.isfinite(vmax):
return 1, 10 # initial range, no data plotted yet

if vmin > vmax:
vmin, vmax = vmax, vmin
if vmax <= 0:
warnings.warn(
"Data has no positive values, and therefore cannot be "
"log-scaled.")
return 1, 10

minpos = self.axis.get_minpos()
if not np.isfinite(minpos):
minpos = 1e-300 # This should never take effect.
if vmin <= 0:
vmin = minpos
if vmin == vmax:
vmin = decade_down(vmin, self._base)
vmax = decade_up(vmax, self._base)
return vmin, vmax


class SymmetricalLogLocator(Locator):
Expand Down Expand Up @@ -2260,32 +2248,7 @@ def tick_values(self, vmin, vmax):
if hasattr(self.axis, 'axes') and self.axis.axes.name == 'polar':
raise NotImplementedError('Polar axis cannot be logit scaled yet')

# what to do if a window beyond ]0, 1[ is chosen
if vmin <= 0.0:
if self.axis is not None:
vmin = self.axis.get_minpos()

if (vmin <= 0.0) or (not np.isfinite(vmin)):
raise ValueError(
"Data has no values in ]0, 1[ and therefore can not be "
"logit-scaled.")

# NOTE: for vmax, we should query a property similar to get_minpos, but
# related to the maximal, less-than-one data point. Unfortunately,
# get_minpos is defined very deep in the BBox and updated with data,
# so for now we use the trick below.
if vmax >= 1.0:
if self.axis is not None:
vmax = 1 - self.axis.get_minpos()

if (vmax >= 1.0) or (not np.isfinite(vmax)):
raise ValueError(
"Data has no values in ]0, 1[ and therefore can not be "
"logit-scaled.")

if vmax < vmin:
vmin, vmax = vmax, vmin

vmin, vmax = self.nonsingular(vmin, vmax)
vmin = np.log10(vmin / (1 - vmin))
vmax = np.log10(vmax / (1 - vmax))

Expand Down Expand Up @@ -2320,6 +2283,36 @@ def tick_values(self, vmin, vmax):

return self.raise_if_exceeds(np.array(ticklocs))

def nonsingular(self, vmin, vmax):
initial_range = (1e-7, 1 - 1e-7)
if not np.isfinite(vmin) or not np.isfinite(vmax):
return initial_range # no data plotted yet

if vmin > vmax:
vmin, vmax = vmax, vmin

# what to do if a window beyond ]0, 1[ is chosen
if self.axis is not None:
minpos = self.axis.get_minpos()
if not np.isfinite(minpos):
return initial_range # again, no data plotted
else:
minpos = 1e-7 # should not occur in normal use

# NOTE: for vmax, we should query a property similar to get_minpos, but
# related to the maximal, less-than-one data point. Unfortunately,
# Bbox._minpos is defined very deep in the BBox and updated with data,
# so for now we use 1 - minpos as a substitute.

if vmin <= 0:
vmin = minpos
if vmax >= 1:
vmax = 1 - minpos
if vmin == vmax:
return 0.1 * vmin, 1 - 0.1 * vmin

return vmin, vmax


class AutoLocator(MaxNLocator):
def __init__(self):
Expand Down
2 changes: 1 addition & 1 deletion lib/matplotlib/transforms.py
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Expand Up @@ -792,7 +792,7 @@ def __init__(self, points, **kwargs):
raise ValueError('Bbox points must be of the form '
'"[[x0, y0], [x1, y1]]".')
self._points = points
self._minpos = np.array([0.0000001, 0.0000001])
self._minpos = np.array([np.inf, np.inf])
self._ignore = True
# it is helpful in some contexts to know if the bbox is a
# default or has been mutated; we store the orig points to
Expand Down