import datetime as dt import numpy as np import pandas as pd import pytest from holoviews.core.options import AbbreviatedException from holoviews.core.overlay import NdOverlay from holoviews.element import Curve from holoviews.util.transform import dim from .test_plot import TestMPLPlot, mpl_renderer class TestCurvePlot(TestMPLPlot): def test_curve_datetime64(self): dates = [np.datetime64(dt.datetime(2016,1,i)) for i in range(1, 11)] curve = Curve((dates, np.random.rand(10))) plot = mpl_renderer.get_plot(curve) self.assertEqual(plot.handles['axis'].get_xlim(), (16801.0, 16810.0)) def test_curve_pandas_timestamps(self): dates = pd.date_range('2016-01-01', '2016-01-10', freq='D') curve = Curve((dates, np.random.rand(10))) plot = mpl_renderer.get_plot(curve) self.assertEqual(plot.handles['axis'].get_xlim(), (16801.0, 16810.0)) def test_curve_dt_datetime(self): dates = [dt.datetime(2016,1,i) for i in range(1, 11)] curve = Curve((dates, np.random.rand(10))) plot = mpl_renderer.get_plot(curve) self.assertEqual(tuple(map(round, plot.handles['axis'].get_xlim())), (16801.0, 16810.0)) def test_curve_heterogeneous_datetime_types_overlay(self): dates64 = [np.datetime64(dt.datetime(2016,1,i)) for i in range(1, 11)] dates = [dt.datetime(2016,1,i) for i in range(2, 12)] curve_dt64 = Curve((dates64, np.random.rand(10))) curve_dt = Curve((dates, np.random.rand(10))) plot = mpl_renderer.get_plot(curve_dt*curve_dt64) self.assertEqual(tuple(map(round, plot.handles['axis'].get_xlim())), (16801.0, 16811.0)) def test_curve_heterogeneous_datetime_types_with_pd_overlay(self): dates_pd = pd.date_range('2016-01-04', '2016-01-13', freq='D') dates64 = [np.datetime64(dt.datetime(2016,1,i)) for i in range(1, 11)] dates = [dt.datetime(2016,1,i) for i in range(2, 12)] curve_dt64 = Curve((dates64, np.random.rand(10))) curve_dt = Curve((dates, np.random.rand(10))) curve_pd = Curve((dates_pd, np.random.rand(10))) plot = mpl_renderer.get_plot(curve_dt*curve_dt64*curve_pd) self.assertEqual(plot.handles['axis'].get_xlim(), (16801.0, 16813.0)) def test_curve_padding_square(self): curve = Curve([1, 2, 3]).opts(padding=0.1) plot = mpl_renderer.get_plot(curve) x_range, y_range = plot.handles['axis'].get_xlim(), plot.handles['axis'].get_ylim() self.assertEqual(x_range[0], -0.2) self.assertEqual(x_range[1], 2.2) self.assertEqual(y_range[0], 0.8) self.assertEqual(y_range[1], 3.2) def test_curve_padding_square_per_axis(self): curve = Curve([1, 2, 3]).opts(padding=((0, 0.1), (0.1, 0.2))) plot = mpl_renderer.get_plot(curve) x_range, y_range = plot.handles['axis'].get_xlim(), plot.handles['axis'].get_ylim() self.assertEqual(x_range[0], 0) self.assertEqual(x_range[1], 2.2) self.assertEqual(y_range[0], 0.8) self.assertEqual(y_range[1], 3.4) def test_curve_padding_hard_xrange(self): curve = Curve([1, 2, 3]).redim.range(x=(0, 3)).opts(padding=0.1) plot = mpl_renderer.get_plot(curve) x_range, y_range = plot.handles['axis'].get_xlim(), plot.handles['axis'].get_ylim() self.assertEqual(x_range[0], 0) self.assertEqual(x_range[1], 3) self.assertEqual(y_range[0], 0.8) self.assertEqual(y_range[1], 3.2) def test_curve_padding_soft_xrange(self): curve = Curve([1, 2, 3]).redim.soft_range(x=(0, 3)).opts(padding=0.1) plot = mpl_renderer.get_plot(curve) x_range, y_range = plot.handles['axis'].get_xlim(), plot.handles['axis'].get_ylim() self.assertEqual(x_range[0], 0) self.assertEqual(x_range[1], 3) self.assertEqual(y_range[0], 0.8) self.assertEqual(y_range[1], 3.2) def test_curve_padding_unequal(self): curve = Curve([1, 2, 3]).opts(padding=(0.05, 0.1)) plot = mpl_renderer.get_plot(curve) x_range, y_range = plot.handles['axis'].get_xlim(), plot.handles['axis'].get_ylim() self.assertEqual(x_range[0], -0.1) self.assertEqual(x_range[1], 2.1) self.assertEqual(y_range[0], 0.8) self.assertEqual(y_range[1], 3.2) def test_curve_padding_nonsquare(self): curve = Curve([1, 2, 3]).opts(padding=0.1, aspect=2) plot = mpl_renderer.get_plot(curve) x_range, y_range = plot.handles['axis'].get_xlim(), plot.handles['axis'].get_ylim() self.assertEqual(x_range[0], -0.1) self.assertEqual(x_range[1], 2.1) self.assertEqual(y_range[0], 0.8) self.assertEqual(y_range[1], 3.2) def test_curve_padding_logx(self): curve = Curve([(1, 1), (2, 2), (3,3)]).opts(padding=0.1, logx=True) plot = mpl_renderer.get_plot(curve) x_range, y_range = plot.handles['axis'].get_xlim(), plot.handles['axis'].get_ylim() self.assertEqual(x_range[0], 0.89595845984076228) self.assertEqual(x_range[1], 3.3483695221017129) self.assertEqual(y_range[0], 0.8) self.assertEqual(y_range[1], 3.2) def test_curve_padding_logy(self): curve = Curve([1, 2, 3]).opts(padding=0.1, logy=True) plot = mpl_renderer.get_plot(curve) x_range, y_range = plot.handles['axis'].get_xlim(), plot.handles['axis'].get_ylim() self.assertEqual(x_range[0], -0.2) self.assertEqual(x_range[1], 2.2) self.assertEqual(y_range[0], 0.89595845984076228) self.assertEqual(y_range[1], 3.3483695221017129) def test_curve_padding_datetime_square(self): curve = Curve([(np.datetime64('2016-04-0%d' % i), i) for i in range(1, 4)]).opts( padding=0.1 ) plot = mpl_renderer.get_plot(curve) x_range, y_range = plot.handles['axis'].get_xlim(), plot.handles['axis'].get_ylim() self.assertEqual(x_range[0], 16891.8) self.assertEqual(x_range[1], 16894.2) self.assertEqual(y_range[0], 0.8) self.assertEqual(y_range[1], 3.2) def test_curve_padding_datetime_nonsquare(self): curve = Curve([(np.datetime64('2016-04-0%d' % i), i) for i in range(1, 4)]).opts( padding=0.1, aspect=2 ) plot = mpl_renderer.get_plot(curve) x_range, y_range = plot.handles['axis'].get_xlim(), plot.handles['axis'].get_ylim() self.assertEqual(x_range[0], 16891.9) self.assertEqual(x_range[1], 16894.1) self.assertEqual(y_range[0], 0.8) self.assertEqual(y_range[1], 3.2) ########################### # Styling mapping # ########################### def test_curve_scalar_color_op(self): curve = Curve([(0, 0, 'red'), (0, 1, 'red'), (0, 2, 'red')], vdims=['y', 'color']).opts(color='color') plot = mpl_renderer.get_plot(curve) artist = plot.handles['artist'] self.assertEqual(artist.get_color(), 'red') def test_op_ndoverlay_color_value(self): colors = ['blue', 'red'] overlay = NdOverlay({color: Curve(np.arange(i)) for i, color in enumerate(colors)}, 'color').opts('Curve', color='color') plot = mpl_renderer.get_plot(overlay) for subplot, color in zip(plot.subplots.values(), colors): style = dict(subplot.style[subplot.cyclic_index]) style = subplot._apply_transforms(subplot.current_frame, {}, style) self.assertEqual(style['color'], color) def test_curve_color_op(self): curve = Curve([(0, 0, 'red'), (0, 1, 'blue'), (0, 2, 'red')], vdims=['y', 'color']).opts(color='color') msg = 'ValueError: Mapping a dimension to the "color" style' with pytest.raises(AbbreviatedException, match=msg): mpl_renderer.get_plot(curve) def test_curve_alpha_op(self): curve = Curve([(0, 0, 0.1), (0, 1, 0.3), (0, 2, 1)], vdims=['y', 'alpha']).opts(alpha='alpha') msg = 'ValueError: Mapping a dimension to the "alpha" style' with pytest.raises(AbbreviatedException, match=msg): mpl_renderer.get_plot(curve) def test_curve_linewidth_op(self): curve = Curve([(0, 0, 0.1), (0, 1, 0.3), (0, 2, 1)], vdims=['y', 'linewidth']).opts(linewidth='linewidth') msg = 'ValueError: Mapping a dimension to the "linewidth" style' with pytest.raises(AbbreviatedException, match=msg): mpl_renderer.get_plot(curve) def test_curve_style_mapping_ndoverlay_dimensions(self): ndoverlay = NdOverlay({ (0, 'A'): Curve([1, 2, 0]), (0, 'B'): Curve([1, 2, 1]), (1, 'A'): Curve([1, 2, 2]), (1, 'B'): Curve([1, 2, 3])}, ['num', 'cat'] ).opts({ 'Curve': dict( color=dim('num').categorize({0: 'red', 1: 'blue'}), linestyle=dim('cat').categorize({'A': '-.', 'B': '-'}) ) }) plot = mpl_renderer.get_plot(ndoverlay) for (num, cat), sp in plot.subplots.items(): artist = sp.handles['artist'] color = artist.get_color() if num == 0: self.assertEqual(color, 'red') else: self.assertEqual(color, 'blue') linestyle = artist.get_linestyle() if cat == 'A': self.assertEqual(linestyle, '-.') else: self.assertEqual(linestyle, '-') def test_curve_style_mapping_constant_value_dimensions(self): vdims = ['y', 'num', 'cat'] ndoverlay = NdOverlay({ 0: Curve([(0, 1, 0, 'A'), (1, 0, 0, 'A')], vdims=vdims), 1: Curve([(0, 1, 0, 'B'), (1, 1, 0, 'B')], vdims=vdims), 2: Curve([(0, 1, 1, 'A'), (1, 2, 1, 'A')], vdims=vdims), 3: Curve([(0, 1, 1, 'B'), (1, 3, 1, 'B')], vdims=vdims)} ).opts({ 'Curve': dict( color=dim('num').categorize({0: 'red', 1: 'blue'}), linestyle=dim('cat').categorize({'A': '-.', 'B': '-'}) ) }) plot = mpl_renderer.get_plot(ndoverlay) for k, sp in plot.subplots.items(): artist = sp.handles['artist'] color = artist.get_color() if ndoverlay[k].iloc[0, 2] == 0: self.assertEqual(color, 'red') else: self.assertEqual(color, 'blue') linestyle = artist.get_linestyle() if ndoverlay[k].iloc[0, 3] == 'A': self.assertEqual(linestyle, '-.') else: self.assertEqual(linestyle, '-')