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_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()