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FIX: clean up unit conversion unpacking of data, particularly for dates and pandas series#11664

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6 changes: 3 additions & 3 deletionslib/matplotlib/axes/_axes.py
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Original file line numberDiff line numberDiff line change
Expand Up@@ -3901,10 +3901,10 @@ def dopatch(xs, ys, **kwargs):
N = len(bxpstats)
datashape_message = ("List of boxplot statistics and `{0}` "
"values must have same the length")
# check position
if positions is None:
positions = list(range(1, N + 1))
elif len(positions) != N:
positions = self.convert_xunits(positions)
if len(positions) != N:
raise ValueError(datashape_message.format("positions"))

# width
Expand DownExpand Up@@ -6048,7 +6048,7 @@ def pcolormesh(self, *args, alpha=None, norm=None, cmap=None, vmin=None,

# convert to one dimensional arrays
C = C.ravel()
coords = np.column_stack((X, Y)).astype(float, copy=False)
coords = np.column_stack((X, Y)).astype(float)
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I don't see any point in removing the "copy=False" kwarg. It saves time, and it is logically what is wanted here. A copy was already made via thecolumn_stack call, so nothing done to coords will affect X or Y.

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Not sure. Changed back

collection = mcoll.QuadMesh(Nx - 1, Ny - 1, coords,
antialiased=antialiased, shading=shading,
**kwargs)
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11 changes: 9 additions & 2 deletionslib/matplotlib/axis.py
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Expand Up@@ -4,6 +4,8 @@

import datetime
import logging
import numbers
import warnings

import numpy as np

Expand DownExpand Up@@ -1477,9 +1479,14 @@ def have_units(self):
return self.converter is not None or self.units is not None

def convert_units(self, x):
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This seems to be converting anything numlike, which includes things likepint.Quantity, into an array/masked array before callingconvert. That seems like it would breakpint, though I will note that our unit tests seem to be passing.

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Great, I’ll check vs pint when I look at the other comments above. Thanks for the reminder...

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Ok, I guess I still don't understand how all of this works. 😉 Sois_numlike only returnstrue for things that are basic numbers (or contain them) and don't need converting. I think I'm ok with this code then. Tests passing is always a good thing too. 😄

# If x is already a number, doesn't need converting
# If x is already a number, doesn't need converting, but
# some iterables need to be massaged a bit...
if munits.ConversionInterface.is_numlike(x):
return x
if isinstance(x, list) or isinstance(x, numbers.Number):
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What is the rationale for returning a list as-is instead of running it throughnp.asarray? Just that the latter is unnecessary? Or are there cases where the conversion would be an error?

return x
if issubclass(type(x), np.ma.MaskedArray):
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Why is this usingissubclass(type(x)... instead ofisinstance?

return np.ma.asarray(x)
return np.asarray(x)
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Is the point of this whole addition above to short-circuit some of what would otherwise happen inget_converter? I'm not opposed, just confused.

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it seems worse, because callingnp.asarray can drop information in some cases, making it unavailable in the call toconvert below. Unless I'm missing something...


if self.converter is None:
self.converter = munits.registry.get_converter(x)
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5 changes: 5 additions & 0 deletionslib/matplotlib/dates.py
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Original file line numberDiff line numberDiff line change
Expand Up@@ -419,6 +419,11 @@ def date2num(d):
return _dt64_to_ordinalf(d)
if not d.size:
return d
if hasattr(d, 'dtype'):
if ((isinstance(d, np.ndarray) and
np.issubdtype(d.dtype, np.datetime64)) or
isinstance(d, np.datetime64)):
return _dt64_to_ordinalf(d)
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What case is this whole block covering? Again, I'm confused.

return _to_ordinalf_np_vectorized(d)


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17 changes: 4 additions & 13 deletionslib/matplotlib/testing/conftest.py
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Expand Up@@ -91,17 +91,8 @@ def pd():
pd = pytest.importorskip('pandas')
try:
from pandas.plotting import (
register_matplotlib_converters as register)
deregister_matplotlib_converters as deregister)
deregister()
except ImportError:
from pandas.tseries.converter import register
register()
try:
yield pd
finally:
try:
from pandas.plotting import (
deregister_matplotlib_converters as deregister)
except ImportError:
pass
else:
deregister()
pass
return pd
12 changes: 12 additions & 0 deletionslib/matplotlib/tests/test_axes.py
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Expand Up@@ -5422,6 +5422,18 @@ def test_pandas_bar_align_center(pd):
fig.canvas.draw()


def test_pandas_data_unpack(pd):
# smoke test for all these different calling methods.
dates = [datetime.datetime(2018, 7, i) for i in range(1, 5)]
values = np.cumsum(np.random.rand(len(dates)))
df = pd.DataFrame({"dates": dates, "values": values})
plt.plot(df["dates"].values, df["values"])
plt.scatter(df["dates"], df["values"])
plt.plot("dates", "values", data=df)
plt.scatter(x="dates", y="values", data=df)
plt.draw()


def test_axis_set_tick_params_labelsize_labelcolor():
# Tests fix for issue 4346
axis_1 = plt.subplot()
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10 changes: 10 additions & 0 deletionslib/matplotlib/tests/test_dates.py
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Expand Up@@ -616,6 +616,16 @@ def tz_convert(*args):
_test_date2num_dst(pd.date_range, tz_convert)


def test_dateboxplot_pandas(pd):
# smoke test that this doesn't fail.
data = np.random.rand(5, 2)
years = pd.date_range('1/1/2000',
periods=2, freq=pd.DateOffset(years=1)).year
# Does not work
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Another place I am confused. Is the comment obsolete?

plt.figure()
plt.boxplot(data, positions=years)


def _test_rrulewrapper(attach_tz, get_tz):
SYD = get_tz('Australia/Sydney')

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