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Logit scale nonsingular #14928

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Merged
merged 4 commits into from
Sep 10, 2019
Merged

Logit scale nonsingular #14928

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b676ca1
LogitLocator: allows nonsingular works with no plotted values
jb-leger Jul 30, 2019
787f6b8
TestLogitLocator: append a test on nonsingular to avoid issues as #14743
jb-leger Jul 30, 2019
dfa8367
LogitLocator: merge two warnings in nonsingular method
jb-leger Jul 31, 2019
e14ee84
MNT: remove the swap_vlim dance
tacaswell Sep 4, 2019
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39 changes: 39 additions & 0 deletions lib/matplotlib/tests/test_ticker.py
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Original file line number Diff line number Diff line change
@@ -1,5 +1,6 @@
import warnings
import re
import itertools

import numpy as np
from numpy.testing import assert_almost_equal, assert_array_equal
Expand Down Expand Up @@ -366,6 +367,44 @@ def test_minor_attr(self):
loc.set_params(minor=False)
assert not loc.minor

acceptable_vmin_vmax = [
*(2.5 ** np.arange(-3, 0)),
*(1 - 2.5 ** np.arange(-3, 0)),
]

@pytest.mark.parametrize(
"lims",
[
(a, b)
for (a, b) in itertools.product(acceptable_vmin_vmax, repeat=2)
if a != b
],
)
def test_nonsingular_ok(self, lims):
"""
Create logit locator, and test the nonsingular method for acceptable
value
"""
loc = mticker.LogitLocator()
lims2 = loc.nonsingular(*lims)
assert sorted(lims) == sorted(lims2)

@pytest.mark.parametrize("okval", acceptable_vmin_vmax)
def test_nonsingular_nok(self, okval):
"""
Create logit locator, and test the nonsingular method for non
acceptable value
"""
loc = mticker.LogitLocator()
vmin, vmax = (-1, okval)
vmin2, vmax2 = loc.nonsingular(vmin, vmax)
assert vmax2 == vmax
assert 0 < vmin2 < vmax2
vmin, vmax = (okval, 2)
vmin2, vmax2 = loc.nonsingular(vmin, vmax)
assert vmin2 == vmin
assert vmin2 < vmax2 < 1


class TestFixedLocator:
def test_set_params(self):
Expand Down
52 changes: 29 additions & 23 deletions lib/matplotlib/ticker.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2792,32 +2792,38 @@ def ideal_ticks(x):
return MaxNLocator.tick_values(self, vmin, vmax)

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

standard_minpos = 1e-7
initial_range = (standard_minpos, 1 - standard_minpos)
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
if not np.isfinite(vmin) or not np.isfinite(vmax):
vmin, vmax = initial_range # Initial range, no data plotted yet.
elif vmax <= 0 or vmin >= 1:
# vmax <= 0 occurs when all values are negative
# vmin >= 1 occurs when all values are greater than one
cbook._warn_external(
"Data has no values between 0 and 1, and therefore cannot be "
"logit-scaled."
)
vmin, vmax = initial_range
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
minpos = (
self.axis.get_minpos()
if self.axis is not None
else standard_minpos
)
if not np.isfinite(minpos):
minpos = standard_minpos # This should never take effect.
if vmin <= 0:
vmin = minpos
# 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 vmax >= 1:
vmax = 1 - minpos
if vmin == vmax:
vmin, vmax = 0.1 * vmin, 1 - 0.1 * vmin

return vmin, vmax

Expand Down