8000 BUG: improve integer step selection in MaxNLocator by efiring · Pull Request #7770 · matplotlib/matplotlib · GitHub
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BUG: improve integer step selection in MaxNLocator #7770

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Merged
merged 1 commit into from
Jan 9, 2017
Merged

BUG: improve integer step selection in MaxNLocator #7770

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6 changes: 5 additions & 1 deletion lib/matplotlib/tests/test_ticker.py
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Original file line number Diff line number Diff line change
Expand Up @@ -32,9 +32,13 @@ def test_MaxNLocator_integer():
test_value = np.array([-1, 0, 1, 2])
assert_almost_equal(loc.tick_values(-0.1, 1.1), test_value)

test_value = np.array([-0.3, 0, 0.3, 0.6, 0.9, 1.2])
test_value = np.array([-0.25, 0, 0.25, 0.5, 0.75, 1.0])
assert_almost_equal(loc.tick_values(-0.1, 0.95), test_value)

loc = mticker.MaxNLocator(nbins=5, integer=True, steps=[1, 1.5, 5, 6, 10])
test_value = np.array([0, 15, 30, 45, 60])
assert_almost_equal(loc.tick_values(1, 55), test_value)


def test_LinearLocator():
loc = mticker.LinearLocator(numticks=3)
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13 changes: 7 additions & 6 deletions lib/matplotlib/ticker.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1836,6 +1836,8 @@ def set_params(self, **kwargs):
raise ValueError(
"prune must be 'upper', 'lower', 'both', or None")
self._prune = prune
if 'min_n_ticks' in kwargs:
self._min_n_ticks = max(1, kwargs['min_n_ticks'])
if 'steps' in kwargs:
steps = kwargs['steps']
if steps is None:
Expand All @@ -1845,12 +1847,6 @@ def set_params(self, **kwargs):
self._extended_steps = self._staircase(self._steps)
if 'integer' in kwargs:
self._integer = kwargs['integer']
if self._integer:
self._steps = np.array([n for n in self._steps
if _divmod(n, 1)[1] < 0.001])
self._extended_steps = self._staircase(self._steps)
if 'min_n_ticks' in kwargs:
self._min_n_ticks = max(1, kwargs['min_n_ticks'])

def _raw_ticks(self, vmin, vmax):
if self._nbins == 'auto':
Expand All @@ -1867,6 +1863,11 @@ def _raw_ticks(self, vmin, vmax):
_vmax = vmax - offset
raw_step = (vmax - vmin) / nbins
steps = self._extended_steps * scale
if self._integer:
# For steps > 1, keep only integer values.
igood = (steps < 1) | (np.abs(steps - np.round(steps)) < 0.001)
steps = steps[igood]

istep = np.nonzero(steps >= raw_step)[0][0]

# Classic round_numbers mode may require a larger step.
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