diff --git a/lib/matplotlib/axes/_axes.py b/lib/matplotlib/axes/_axes.py
index 4630a7568818..b63c810d210e 100644
--- a/lib/matplotlib/axes/_axes.py
+++ b/lib/matplotlib/axes/_axes.py
@@ -36,6 +36,30 @@
from matplotlib.axes._base import _AxesBase, _process_plot_format
from matplotlib.axes._secondary_axes import SecondaryAxis
+try:
+ from numpy.lib.histograms import histogram_bin_edges
+except ImportError:
+ # this function is new in np 1.15
+ def histogram_bin_edges(arr, bins, range=None, weights=None):
+ # this in True for 1D arrays, and False for None and str
+ if np.ndim(bins) == 1:
+ return bins
+
+ if isinstance(bins, str):
+ # rather than backporting the internals, just do the full
+ # computation. If this is too slow for users, they can
+ # update numpy, or pick a manual number of bins
+ return np.histogram(arr, bins, range, weights)[1]
+ else:
+ if bins is None:
+ # hard-code numpy's default
+ bins = 10
+ if range is None:
+ range = np.min(arr), np.max(arr)
+
+ return np.linspace(*range, bins + 1)
+
+
_log = logging.getLogger(__name__)
@@ -6611,9 +6635,6 @@ def hist(self, x, bins=None, range=None, density=None, weights=None,
if bin_range is not None:
bin_range = self.convert_xunits(bin_range)
- # Check whether bins or range are given explicitly.
- binsgiven = np.iterable(bins) or bin_range is not None
-
# We need to do to 'weights' what was done to 'x'
if weights is not None:
w = cbook._reshape_2D(weights, 'weights')
@@ -6638,22 +6659,42 @@ def hist(self, x, bins=None, range=None, density=None, weights=None,
"sets and %d colors were provided" % (nx, len(color)))
raise ValueError(error_message)
- # If bins are not specified either explicitly or via range,
- # we need to figure out the range required for all datasets,
- # and supply that to np.histogram.
- if not binsgiven and not input_empty:
+ hist_kwargs = dict()
+
+ # if the bin_range is not given, compute without nan numpy
+ # does not do this for us when guessing the range (but will
+ # happily ignore nans when computing the histogram).
+ if bin_range is None:
xmin = np.inf
xmax = -np.inf
for xi in x:
- if len(xi) > 0:
+ if len(xi):
+ # python's min/max ignore nan,
+ # np.minnan returns nan for all nan input
xmin = min(xmin, np.nanmin(xi))
xmax = max(xmax, np.nanmax(xi))
- bin_range = (xmin, xmax)
+ # make sure we have seen at least one non-nan and finite
+ # value before we reset the bin range
+ if not np.isnan([xmin, xmax]).any() and not (xmin > xmax):
+ bin_range = (xmin, xmax)
+
+ # If bins are not specified either explicitly or via range,
+ # we need to figure out the range required for all datasets,
+ # and supply that to np.histogram.
+ if not input_empty and len(x) > 1:
+ if weights is not None:
+ _w = np.concatenate(w)
+ else:
+ _w = None
+
+ bins = histogram_bin_edges(np.concatenate(x),
+ bins, bin_range, _w)
+ else:
+ hist_kwargs['range'] = bin_range
+
density = bool(density) or bool(normed)
if density and not stacked:
- hist_kwargs = dict(range=bin_range, density=density)
- else:
- hist_kwargs = dict(range=bin_range)
+ hist_kwargs = dict(density=density)
# List to store all the top coordinates of the histograms
tops = []
diff --git a/lib/matplotlib/tests/test_axes.py b/lib/matplotlib/tests/test_axes.py
index 741a9c2b574a..3e5d00b16f06 100644
--- a/lib/matplotlib/tests/test_axes.py
+++ b/lib/matplotlib/tests/test_axes.py
@@ -6346,3 +6346,23 @@ def test_datetime_masked():
ax.plot(x, m)
# these are the default viewlim
assert ax.get_xlim() == (730120.0, 733773.0)
+
+
+def test_hist_auto_bins():
+ _, bins, _ = plt.hist([[1, 2, 3], [3, 4, 5, 6]], bins='auto')
+ assert bins[0] <= 1
+ assert bins[-1] >= 6
+
+
+def test_hist_nan_data():
+ fig, (ax1, ax2) = plt.subplots(2)
+
+ data = [1, 2, 3]
+ nan_data = data + [np.nan]
+
+ bins, edges, _ = ax1.hist(data)
+ with np.errstate(invalid='ignore'):
+ nanbins, nanedges, _ = ax2.hist(nan_data)
+
+ assert np.allclose(bins, nanbins)
+ assert np.allclose(edges, nanedges)
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