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Set norm to log if bins=='log' in hexbin #9223

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Merged
merged 1 commit into from
Jul 12, 2018
Merged

Set norm to log if bins=='log' in hexbin #9223

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6 changes: 6 additions & 0 deletions doc/api/api_changes.rst
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Expand Up @@ -451,6 +451,12 @@ Deprecations
`.Legend.draggable()` is drepecated in favor of `.Legend.set_draggable()`.
``Legend.draggable`` may be reintroduced as a property in future releases.

Colorbar for log-scaled hexbin
------------------------------

When using `hexbin` and plotting with a logarithmic color scale, the colorbar
ticks are now correctly log scaled. Previously the tick values were linear
scaled log(number of counts).

API Changes in 2.2.0
====================
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24 changes: 16 additions & 8 deletions lib/matplotlib/axes/_axes.py
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Expand Up @@ -4326,9 +4326,23 @@ def hexbin(self, x, y, C=None, gridsize=100, bins=None,
offset_position="data"
)

# Check for valid norm
if norm is not None and not isinstance(norm, mcolors.Normalize):
msg = "'norm' must be an instance of 'mcolors.Normalize'"
raise ValueError(msg)

# Set normalizer if bins is 'log'
if bins == 'log':
if norm is not None:
warnings.warn("Only one of 'bins' and 'norm' arguments can be "
"supplied, ignoring bins={}".format(bins))
else:
norm = mcolors.LogNorm()
bins = None

if isinstance(norm, mcolors.LogNorm):
if (accum == 0).any():
# make sure we have not zeros
# make sure we have no zeros
accum += 1

# autoscale the norm with curren accum values if it hasn't
Expand All @@ -4337,20 +4351,14 @@ def hexbin(self, x, y, C=None, gridsize=100, bins=None,
if norm.vmin is None and norm.vmax is None:
norm.autoscale(accum)

# Transform accum if needed
if bins == 'log':
accum = np.log10(accum + 1)
elif bins is not None:
if bins is not None:
if not iterable(bins):
minimum, maximum = min(accum), max(accum)
bins -= 1 # one less edge than bins
bins = minimum + (maximum - minimum) * np.arange(bins) / bins
bins = np.sort(bins)
accum = bins.searchsorted(accum)

if norm is not None and not isinstance(norm, mcolors.Normalize):
raise ValueError(
"'norm' must be an instance of 'mcolors.Normalize'")
collection.set_array(accum)
collection.set_cmap(cmap)
collection.set_norm(norm)
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Binary file modified lib/matplotlib/tests/baseline_images/test_axes/hexbin_log.png
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10 changes: 5 additions & 5 deletions lib/matplotlib/tests/test_axes.py
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Expand Up @@ -858,18 +858,18 @@ def __init__(self, x, y):


@image_comparison(baseline_images=['hexbin_log'],
remove_text=True,
extensions=['png'])
extensions=['png'], style='mpl20')
def test_hexbin_log():
# Issue #1636
np.random.seed(0)
# Issue #1636 (and also test log scaled colorbar)
np.random.seed(19680801)
n = 100000
x = np.random.standard_normal(n)
y = 2.0 + 3.0 * x + 4.0 * np.random.standard_normal(n)
y = np.power(2, y * 0.5)

fig, ax = plt.subplots()
ax.hexbin(x, y, yscale='log')
h = ax.hexbin(x, y, yscale='log', bins='log')
plt.colorbar(h)


def test_inverted_limits():
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