def test_gap_upsample(self):
low = tm.makeTimeSeries()
low[5:25] = np.nan
ax = low.plot()
idxh = date_range(low.index[0], low.index[-1], freq='12h')
s = Series(np.random.randn(len(idxh)), idxh)
s.plot(secondary_y=True)
lines = ax.get_lines()
self.assertEqual(len(lines), 1)
self.assertEqual(len(ax.right_ax.get_lines()), 1)
l = lines[0]
data = l.get_xydata()
tm._skip_if_mpl_1_5()
tm.assertIsInstance(data, np.ma.core.MaskedArray)
mask = data.mask
self.assertTrue(mask[5:25, 1].all())
def test_gaps(self):
ts = tm.makeTimeSeries()
ts[5:25] = np.nan
_, ax = self.plt.subplots()
ts.plot(ax=ax)
lines = ax.get_lines()
tm._skip_if_mpl_1_5()
assert len(lines) == 1
l = lines[0]
data = l.get_xydata()
assert isinstance(data, np.ma.core.MaskedArray)
mask = data.mask
assert mask[5:25, 1].all()
self.plt.close(ax.get_figure())
# irregular
ts = tm.makeTimeSeries()
ts = ts[[0, 1, 2, 5, 7, 9, 12, 15, 20]]
ts[2:5] = np.nan
_, ax = self.plt.subplots()
ax = ts.plot(ax=ax)
lines = ax.get_lines()
assert len(lines) == 1
l = lines[0]
data = l.get_xydata()
assert isinstance(data, np.ma.core.MaskedArray)
mask = data.mask
assert mask[2:5, 1].all()
self.plt.close(ax.get_figure())
# non-ts
idx = [0, 1, 2, 5, 7, 9, 12, 15, 20]
ser = Series(np.random.randn(len(idx)), idx)
ser[2:5] = np.nan
_, ax = self.plt.subplots()
ser.plot(ax=ax)
lines = ax.get_lines()
assert len(lines) == 1
l = lines[0]
data = l.get_xydata()
assert isinstance(data, np.ma.core.MaskedArray)
mask = data.mask
assert mask[2:5, 1].all()
def test_gap_upsample(self):
low = tm.makeTimeSeries()
low[5:25] = np.nan
ax = low.plot()
idxh = date_range(low.index[0], low.index[-1], freq='12h')
s = Series(np.random.randn(len(idxh)), idxh)
s.plot(secondary_y=True)
lines = ax.get_lines()
self.assertEqual(len(lines), 1)
self.assertEqual(len(ax.right_ax.get_lines()), 1)
l = lines[0]
data = l.get_xydata()
tm._skip_if_mpl_1_5()
tm.assertIsInstance(data, np.ma.core.MaskedArray)
mask = data.mask
self.assertTrue(mask[5:25, 1].all())
def test_gaps(self):
import matplotlib.pyplot as plt
ts = tm.makeTimeSeries()
ts[5:25] = np.nan
ax = ts.plot()
lines = ax.get_lines()
tm._skip_if_mpl_1_5()
self.assertEqual(len(lines), 1)
l = lines[0]
data = l.get_xydata()
tm.assertIsInstance(data, np.ma.core.MaskedArray)
mask = data.mask
self.assertTrue(mask[5:25, 1].all())
plt.close(ax.get_figure())
# irregular
ts = tm.makeTimeSeries()
ts = ts[[0, 1, 2, 5, 7, 9, 12, 15, 20]]
ts[2:5] = np.nan
ax = ts.plot()
lines = ax.get_lines()
self.assertEqual(len(lines), 1)
l = lines[0]
data = l.get_xydata()
tm.assertIsInstance(data, np.ma.core.MaskedArray)
mask = data.mask
self.assertTrue(mask[2:5, 1].all())
plt.close(ax.get_figure())
# non-ts
idx = [0, 1, 2, 5, 7, 9, 12, 15, 20]
ser = Series(np.random.randn(len(idx)), idx)
ser[2:5] = np.nan
ax = ser.plot()
lines = ax.get_lines()
self.assertEqual(len(lines), 1)
l = lines[0]
data = l.get_xydata()
tm.assertIsInstance(data, np.ma.core.MaskedArray)
mask = data.mask
self.assertTrue(mask[2:5, 1].all())
def test_gaps(self):
import matplotlib.pyplot as plt
ts = tm.makeTimeSeries()
ts[5:25] = np.nan
ax = ts.plot()
lines = ax.get_lines()
tm._skip_if_mpl_1_5()
self.assertEqual(len(lines), 1)
l = lines[0]
data = l.get_xydata()
tm.assertIsInstance(data, np.ma.core.MaskedArray)
mask = data.mask
self.assertTrue(mask[5:25, 1].all())
plt.close(ax.get_figure())
# irregular
ts = tm.makeTimeSeries()
ts = ts[[0, 1, 2, 5, 7, 9, 12, 15, 20]]
ts[2:5] = np.nan
ax = ts.plot()
lines = ax.get_lines()
self.assertEqual(len(lines), 1)
l = lines[0]
data = l.get_xydata()
tm.assertIsInstance(data, np.ma.core.MaskedArray)
mask = data.mask
self.assertTrue(mask[2:5, 1].all())
plt.close(ax.get_figure())
# non-ts
idx = [0, 1, 2, 5, 7, 9, 12, 15, 20]
ser = Series(np.random.randn(len(idx)), idx)
ser[2:5] = np.nan
ax = ser.plot()
lines = ax.get_lines()
self.assertEqual(len(lines), 1)
l = lines[0]
data = l.get_xydata()
tm.assertIsInstance(data, np.ma.core.MaskedArray)
mask = data.mask
self.assertTrue(mask[2:5, 1].all())
def test_gap_upsample(self):
low = tm.makeTimeSeries()
low[5:25] = np.nan
_, ax = self.plt.subplots()
low.plot(ax=ax)
idxh = date_range(low.index[0], low.index[-1], freq='12h')
s = Series(np.random.randn(len(idxh)), idxh)
s.plot(secondary_y=True)
lines = ax.get_lines()
assert len(lines) == 1
assert len(ax.right_ax.get_lines()) == 1
l = lines[0]
data = l.get_xydata()
tm._skip_if_mpl_1_5()
assert isinstance(data, np.ma.core.MaskedArray)
mask = data.mask
assert mask[5:25, 1].all()
