examples/user_guide/15-Large_Data.ipynb::Cell 0 Notebook cell execution failed Cell 0: Cell execution caused an exception Input: import datashader as ds import numpy as np import holoviews as hv import pandas as pd import numpy as np from holoviews import opts from holoviews.operation.datashader import datashade, rasterize, shade, dynspread, spread from holoviews.operation.resample import ResampleOperation2D from holoviews.operation import decimate hv.extension('bokeh','matplotlib', width=100) # Default values suitable for this notebook decimate.max_samples=1000 dynspread.max_px=20 dynspread.threshold=0.5 ResampleOperation2D.width=500 ResampleOperation2D.height=500 def random_walk(n, f=5000): """Random walk in a 2D space, smoothed with a filter of length f""" xs = np.convolve(np.random.normal(0, 0.1, size=n), np.ones(f)/f).cumsum() ys = np.convolve(np.random.normal(0, 0.1, size=n), np.ones(f)/f).cumsum() xs += 0.1*np.sin(0.1*np.array(range(n-1+f))) # add wobble on x axis xs += np.random.normal(0, 0.005, size=n-1+f) # add measurement noise ys += np.random.normal(0, 0.005, size=n-1+f) return np.column_stack([xs, ys]) def random_cov(): """Random covariance for use in generating 2D Gaussian distributions""" A = np.random.randn(2,2) return np.dot(A, A.T) def time_series(T = 1, N = 100, mu = 0.1, sigma = 0.1, S0 = 20): """Parameterized noisy time series""" dt = float(T)/N t = np.linspace(0, T, N) W = np.random.standard_normal(size = N) W = np.cumsum(W)*np.sqrt(dt) # standard brownian motion X = (mu-0.5*sigma**2)*t + sigma*W S = S0*np.exp(X) # geometric brownian motion return S Traceback: --------------------------------------------------------------------------- NotImplementedError Traceback (most recent call last) Cell In[1], line 1 ----> 1 import datashader as ds 2 import numpy as np 3 import holoviews as hv File ~/work/holoviews/holoviews/.pixi/envs/test-312/lib/python3.12/site-packages/datashader/__init__.py:7 3 from packaging.version import Version 5 from .__version import __version__ # noqa: F401 ----> 7 from .core import Canvas # noqa (API import) 8 from .reductions import * # noqa (API import) 9 from .glyphs import Point # noqa (API import) File ~/work/holoviews/holoviews/.pixi/envs/test-312/lib/python3.12/site-packages/datashader/core.py:13 10 from packaging.version import Version 11 from xarray �[38;

examples/user_guide/15-Large_Data.ipynb::Cell 1 Notebook cell execution failed Cell 1: Cell execution caused an exception Input: np.random.seed(1) points = hv.Points(np.random.multivariate_normal((0,0), [[0.1, 0.1], [0.1, 1.0]], (1000,)),label="Points") paths = hv.Path([random_walk(2000,30)], kdims=["u","v"], label="Paths") points + paths Traceback: --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[1], line 1 ----> 1 np.random.seed(1) 2 points = hv.Points(np.random.multivariate_normal((0,0), [[0.1, 0.1], [0.1, 1.0]], (1000,)),label="Points") 3 paths = hv.Path([random_walk(2000,30)], kdims=["u","v"], label="Paths") NameError: name 'np' is not defined

examples/user_guide/15-Large_Data.ipynb::Cell 2 Notebook cell execution failed Cell 2: Cell execution caused an exception Input: np.random.seed(1) points = hv.Points(np.random.multivariate_normal((0,0), [[0.1, 0.1], [0.1, 1.0]], (1000000,)),label="Points") paths = hv.Path([0.15*random_walk(100000) for i in range(10)], kdims=["u","v"], label="Paths") #points + paths ## Danger! Browsers can't handle 1 million points! Traceback: --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[1], line 1 ----> 1 np.random.seed(1) 2 points = hv.Points(np.random.multivariate_normal((0,0), [[0.1, 0.1], [0.1, 1.0]], (1000000,)),label="Points") 3 paths = hv.Path([0.15*random_walk(100000) for i in range(10)], kdims=["u","v"], label="Paths") NameError: name 'np' is not defined

examples/user_guide/15-Large_Data.ipynb::Cell 3 Notebook cell execution failed Cell 3: Cell execution caused an exception Input: decimate( points).relabel("Decimated Points") + \ rasterize(points).relabel("Rasterized Points").opts(colorbar=True, width=350) + \ rasterize(paths ).relabel("Rasterized Paths") Traceback: --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[1], line 1 ----> 1 decimate( points).relabel("Decimated Points") + \ 2 rasterize(points).relabel("Rasterized Points").opts(colorbar=True, width=350) + \ 3 rasterize(paths ).relabel("Rasterized Paths") NameError: name 'decimate' is not defined

examples/user_guide/15-Large_Data.ipynb::Cell 4 Notebook cell execution failed Cell 4: Cell execution caused an exception Input: ropts = dict(colorbar=True, tools=["hover"], width=350) rasterize( points).opts(cmap="kbc_r", cnorm="linear").relabel('rasterize()').opts(**ropts).hist() + \ shade(rasterize(points), cmap="kbc_r", cnorm="linear").relabel("shade(rasterize())") + \ datashade( points, cmap="kbc_r", cnorm="linear").relabel("datashade()") Traceback: --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[1], line 3 1 ropts = dict(colorbar=True, tools=["hover"], width=350) ----> 3 rasterize( points).opts(cmap="kbc_r", cnorm="linear").relabel('rasterize()').opts(**ropts).hist() + \ 4 shade(rasterize(points), cmap="kbc_r", cnorm="linear").relabel("shade(rasterize())") + \ 5 datashade( points, cmap="kbc_r", cnorm="linear").relabel("datashade()") NameError: name 'rasterize' is not defined

examples/user_guide/15-Large_Data.ipynb::Cell 5 Notebook cell execution failed Cell 5: Cell execution caused an exception Input: points2 = decimate(points, dynamic=False, max_samples=3000) points2.opts(color="green", size=6, marker="s") points2 + rasterize(points2).relabel("Rasterized") + datashade(points2).relabel("Datashaded") Traceback: --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[1], line 1 ----> 1 points2 = decimate(points, dynamic=False, max_samples=3000) 2 points2.opts(color="green", size=6, marker="s") 4 points2 + rasterize(points2).relabel("Rasterized") + datashade(points2).relabel("Datashaded") NameError: name 'decimate' is not defined

examples/user_guide/15-Large_Data.ipynb::Cell 6 Notebook cell execution failed Cell 6: Cell execution caused an exception Input: w=225 points2 + \ spread(rasterize(points2, width=w, height=w), px=4, shape='square').opts(cmap=["green"]).relabel("Rasterized") + \ spread(datashade(points2, width=w, height=w, cmap=["green"]), px=4, shape='square').relabel("Datashaded") Traceback: --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[1], line 3 1 w=225 ----> 3 points2 + \ 4 spread(rasterize(points2, width=w, height=w), px=4, shape='square').opts(cmap=["green"]).relabel("Rasterized") + \ 5 spread(datashade(points2, width=w, height=w, cmap=["green"]), px=4, shape='square').relabel("Datashaded") NameError: name 'points2' is not defined

examples/user_guide/15-Large_Data.ipynb::Cell 8 Notebook cell execution failed Cell 8: Cell execution caused an exception Input: points2 + \ spread(rasterize(points2, width=w, height=w), px=4, shape='square').opts(cmap=greens, cnorm='eq_hist').relabel("Rasterized") +\ spread(datashade(points2, width=w, height=w, cmap="green", cnorm='eq_hist'), px=4, shape='square').relabel("Datashaded") Traceback: --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[1], line 1 ----> 1 points2 + \ 2 spread(rasterize(points2, width=w, height=w), px=4, shape='square').opts(cmap=greens, cnorm='eq_hist').relabel("Rasterized") +\ 3 spread(datashade(points2, width=w, height=w, cmap="green", cnorm='eq_hist'), px=4, shape='square').relabel("Datashaded") NameError: name 'points2' is not defined

examples/user_guide/15-Large_Data.ipynb::Cell 9 Notebook cell execution failed Cell 9: Cell execution caused an exception Input: num=10000 np.random.seed(1) dists = {cat: pd.DataFrame(dict([('x',np.random.normal(x,s,num)), ('y',np.random.normal(y,s,num)), ('val',val), ('cat',cat)])) for x, y, s, val, cat in [( 2, 2, 0.03, 10, "d1"), ( 2, -2, 0.10, 20, "d2"), ( -2, -2, 0.50, 30, "d3"), ( -2, 2, 1.00, 40, "d4"), ( 0, 0, 3.00, 50, "d5")] } df = pd.concat(dists,ignore_index=True) df["cat"]=df["cat"].astype("category") df Traceback: --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[1], line 2 1 num=10000 ----> 2 np.random.seed(1) 4 dists = {cat: pd.DataFrame(dict([('x',np.random.normal(x,s,num)), 5 ('y',np.random.normal(y,s,num)), 6 ('val',val), (...) 12 ( -2, 2, 1.00, 40, "d4"), 13 ( 0, 0, 3.00, 50, "d5")] } 15 df = pd.concat(dists,ignore_index=True) NameError: name 'np' is not defined

examples/user_guide/15-Large_Data.ipynb::Cell 10 Notebook cell execution failed Cell 10: Cell execution caused an exception Input: ropts = dict(tools=["hover"], height=380, width=330, colorbar=True, colorbar_position="bottom") hv.Layout([rasterize(hv.Points(df)).opts(**ropts).opts(cnorm=n).relabel(n) for n in ["linear", "log", "eq_hist"]]) Traceback: --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[1], line 3 1 ropts = dict(tools=["hover"], height=380, width=330, colorbar=True, colorbar_position="bottom") ----> 3 hv.Layout([rasterize(hv.Points(df)).opts(**ropts).opts(cnorm=n).relabel(n) 4 for n in ["linear", "log", "eq_hist"]]) NameError: name 'hv' is not defined

examples/user_guide/15-Large_Data.ipynb::Cell 0 Notebook cell execution failed Cell 0: Cell execution caused an exception Input: import datashader as ds import numpy as np import holoviews as hv import pandas as pd import numpy as np from holoviews import opts from holoviews.operation.datashader import datashade, rasterize, shade, dynspread, spread from holoviews.operation.resample import ResampleOperation2D from holoviews.operation import decimate hv.extension('bokeh','matplotlib', width=100) # Default values suitable for this notebook decimate.max_samples=1000 dynspread.max_px=20 dynspread.threshold=0.5 ResampleOperation2D.width=500 ResampleOperation2D.height=500 def random_walk(n, f=5000): """Random walk in a 2D space, smoothed with a filter of length f""" xs = np.convolve(np.random.normal(0, 0.1, size=n), np.ones(f)/f).cumsum() ys = np.convolve(np.random.normal(0, 0.1, size=n), np.ones(f)/f).cumsum() xs += 0.1*np.sin(0.1*np.array(range(n-1+f))) # add wobble on x axis xs += np.random.normal(0, 0.005, size=n-1+f) # add measurement noise ys += np.random.normal(0, 0.005, size=n-1+f) return np.column_stack([xs, ys]) def random_cov(): """Random covariance for use in generating 2D Gaussian distributions""" A = np.random.randn(2,2) return np.dot(A, A.T) def time_series(T = 1, N = 100, mu = 0.1, sigma = 0.1, S0 = 20): """Parameterized noisy time series""" dt = float(T)/N t = np.linspace(0, T, N) W = np.random.standard_normal(size = N) W = np.cumsum(W)*np.sqrt(dt) # standard brownian motion X = (mu-0.5*sigma**2)*t + sigma*W S = S0*np.exp(X) # geometric brownian motion return S Traceback: --------------------------------------------------------------------------- NotImplementedError Traceback (most recent call last) Cell In[1], line 1 ----> 1 import datashader as ds 2 import numpy as np 3 import holoviews as hv File ~/work/holoviews/holoviews/.pixi/envs/test-312/lib/python3.12/site-packages/datashader/__init__.py:7 3 from packaging.version import Version 5 from .__version import __version__ # noqa: F401 ----> 7 from .core import Canvas # noqa (API import) 8 from .reductions import * # noqa (API import) 9 from .glyphs import Point # noqa (API import) File ~/work/holoviews/holoviews/.pixi/envs/test-312/lib/python3.12/site-packages/datashader/core.py:13 10 from packaging.version import Version 11 from xarray �[38;

examples/user_guide/15-Large_Data.ipynb::Cell 1 Notebook cell execution failed Cell 1: Cell execution caused an exception Input: np.random.seed(1) points = hv.Points(np.random.multivariate_normal((0,0), [[0.1, 0.1], [0.1, 1.0]], (1000,)),label="Points") paths = hv.Path([random_walk(2000,30)], kdims=["u","v"], label="Paths") points + paths Traceback: --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[1], line 1 ----> 1 np.random.seed(1) 2 points = hv.Points(np.random.multivariate_normal((0,0), [[0.1, 0.1], [0.1, 1.0]], (1000,)),label="Points") 3 paths = hv.Path([random_walk(2000,30)], kdims=["u","v"], label="Paths") NameError: name 'np' is not defined

examples/user_guide/15-Large_Data.ipynb::Cell 2 Notebook cell execution failed Cell 2: Cell execution caused an exception Input: np.random.seed(1) points = hv.Points(np.random.multivariate_normal((0,0), [[0.1, 0.1], [0.1, 1.0]], (1000000,)),label="Points") paths = hv.Path([0.15*random_walk(100000) for i in range(10)], kdims=["u","v"], label="Paths") #points + paths ## Danger! Browsers can't handle 1 million points! Traceback: --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[1], line 1 ----> 1 np.random.seed(1) 2 points = hv.Points(np.random.multivariate_normal((0,0), [[0.1, 0.1], [0.1, 1.0]], (1000000,)),label="Points") 3 paths = hv.Path([0.15*random_walk(100000) for i in range(10)], kdims=["u","v"], label="Paths") NameError: name 'np' is not defined

examples/user_guide/15-Large_Data.ipynb::Cell 3 Notebook cell execution failed Cell 3: Cell execution caused an exception Input: decimate( points).relabel("Decimated Points") + \ rasterize(points).relabel("Rasterized Points").opts(colorbar=True, width=350) + \ rasterize(paths ).relabel("Rasterized Paths") Traceback: --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[1], line 1 ----> 1 decimate( points).relabel("Decimated Points") + \ 2 rasterize(points).relabel("Rasterized Points").opts(colorbar=True, width=350) + \ 3 rasterize(paths ).relabel("Rasterized Paths") NameError: name 'decimate' is not defined

examples/user_guide/15-Large_Data.ipynb::Cell 4 Notebook cell execution failed Cell 4: Cell execution caused an exception Input: ropts = dict(colorbar=True, tools=["hover"], width=350) rasterize( points).opts(cmap="kbc_r", cnorm="linear").relabel('rasterize()').opts(**ropts).hist() + \ shade(rasterize(points), cmap="kbc_r", cnorm="linear").relabel("shade(rasterize())") + \ datashade( points, cmap="kbc_r", cnorm="linear").relabel("datashade()") Traceback: --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[1], line 3 1 ropts = dict(colorbar=True, tools=["hover"], width=350) ----> 3 rasterize( points).opts(cmap="kbc_r", cnorm="linear").relabel('rasterize()').opts(**ropts).hist() + \ 4 shade(rasterize(points), cmap="kbc_r", cnorm="linear").relabel("shade(rasterize())") + \ 5 datashade( points, cmap="kbc_r", cnorm="linear").relabel("datashade()") NameError: name 'rasterize' is not defined

examples/user_guide/15-Large_Data.ipynb::Cell 5 Notebook cell execution failed Cell 5: Cell execution caused an exception Input: points2 = decimate(points, dynamic=False, max_samples=3000) points2.opts(color="green", size=6, marker="s") points2 + rasterize(points2).relabel("Rasterized") + datashade(points2).relabel("Datashaded") Traceback: --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[1], line 1 ----> 1 points2 = decimate(points, dynamic=False, max_samples=3000) 2 points2.opts(color="green", size=6, marker="s") 4 points2 + rasterize(points2).relabel("Rasterized") + datashade(points2).relabel("Datashaded") NameError: name 'decimate' is not defined

examples/user_guide/15-Large_Data.ipynb::Cell 6 Notebook cell execution failed Cell 6: Cell execution caused an exception Input: w=225 points2 + \ spread(rasterize(points2, width=w, height=w), px=4, shape='square').opts(cmap=["green"]).relabel("Rasterized") + \ spread(datashade(points2, width=w, height=w, cmap=["green"]), px=4, shape='square').relabel("Datashaded") Traceback: --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[1], line 3 1 w=225 ----> 3 points2 + \ 4 spread(rasterize(points2, width=w, height=w), px=4, shape='square').opts(cmap=["green"]).relabel("Rasterized") + \ 5 spread(datashade(points2, width=w, height=w, cmap=["green"]), px=4, shape='square').relabel("Datashaded") NameError: name 'points2' is not defined

examples/user_guide/15-Large_Data.ipynb::Cell 8 Notebook cell execution failed Cell 8: Cell execution caused an exception Input: points2 + \ spread(rasterize(points2, width=w, height=w), px=4, shape='square').opts(cmap=greens, cnorm='eq_hist').relabel("Rasterized") +\ spread(datashade(points2, width=w, height=w, cmap="green", cnorm='eq_hist'), px=4, shape='square').relabel("Datashaded") Traceback: --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[1], line 1 ----> 1 points2 + \ 2 spread(rasterize(points2, width=w, height=w), px=4, shape='square').opts(cmap=greens, cnorm='eq_hist').relabel("Rasterized") +\ 3 spread(datashade(points2, width=w, height=w, cmap="green", cnorm='eq_hist'), px=4, shape='square').relabel("Datashaded") NameError: name 'points2' is not defined

examples/user_guide/15-Large_Data.ipynb::Cell 9 Notebook cell execution failed Cell 9: Cell execution caused an exception Input: num=10000 np.random.seed(1) dists = {cat: pd.DataFrame(dict([('x',np.random.normal(x,s,num)), ('y',np.random.normal(y,s,num)), ('val',val), ('cat',cat)])) for x, y, s, val, cat in [( 2, 2, 0.03, 10, "d1"), ( 2, -2, 0.10, 20, "d2"), ( -2, -2, 0.50, 30, "d3"), ( -2, 2, 1.00, 40, "d4"), ( 0, 0, 3.00, 50, "d5")] } df = pd.concat(dists,ignore_index=True) df["cat"]=df["cat"].astype("category") df Traceback: --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[1], line 2 1 num=10000 ----> 2 np.random.seed(1) 4 dists = {cat: pd.DataFrame(dict([('x',np.random.normal(x,s,num)), 5 ('y',np.random.normal(y,s,num)), 6 ('val',val), (...) 12 ( -2, 2, 1.00, 40, "d4"), 13 ( 0, 0, 3.00, 50, "d5")] } 15 df = pd.concat(dists,ignore_index=True) NameError: name 'np' is not defined

examples/user_guide/15-Large_Data.ipynb::Cell 10 Notebook cell execution failed Cell 10: Cell execution caused an exception Input: ropts = dict(tools=["hover"], height=380, width=330, colorbar=True, colorbar_position="bottom") hv.Layout([rasterize(hv.Points(df)).opts(**ropts).opts(cnorm=n).relabel(n) for n in ["linear", "log", "eq_hist"]]) Traceback: --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[1], line 3 1 ropts = dict(tools=["hover"], height=380, width=330, colorbar=True, colorbar_position="bottom") ----> 3 hv.Layout([rasterize(hv.Points(df)).opts(**ropts).opts(cnorm=n).relabel(n) 4 for n in ["linear", "log", "eq_hist"]]) NameError: name 'hv' is not defined

examples\user_guide\Linked_Brushing.ipynb::Cell 15 Notebook cell execution failed Cell 15: Cell execution caused an exception Input: import datashader as ds import holoviews.operation.datashader as hd num = 100000 np.random.seed(1) dists = { cat: pd.DataFrame({ 'x': np.random.normal(x, s, num), 'y': np.random.normal(y, s, num), 'val': np.random.normal(val, 1.5, num), 'cat': cat }) for x, y, s, val, cat in [( 2, 2, 0.03, 10, "d1"), ( 2, -2, 0.10, 20, "d2"), ( -2, -2, 0.50, 30, "d3"), ( -2, 2, 1.00, 40, "d4"), ( 0, 0, 3.00, 50, "d5")] } points = hv.Points(pd.concat(dists), ['x', 'y'], ['val', 'cat']) datashaded = hd.datashade(points, aggregator=ds.count_cat('cat')) spreaded = hd.dynspread(datashaded, threshold=0.50, how='over') # Declare dim expression to color by cluster dim_expr = ((0.1+hv.dim('val')/10).round()).categorize(hv.Cycle('Set1').values) histogram = points.hist(num_bins=60, adjoin=False, normed=False).opts(color=dim_expr) link_selections(spreaded + histogram) Traceback: --------------------------------------------------------------------------- NotImplementedError Traceback (most recent call last) Cell In[1], line 1 ----> 1 import datashader as ds 2 import holoviews.operation.datashader as hd 4 num = 100000 File D:\a\holoviews\holoviews\.pixi\envs\test-312\Lib\site-packages\datashader\__init__.py:7 3 from packaging.version import Version 5 from .__version import __version__ # noqa: F401 ----> 7 from .core import Canvas # noqa (API import) 8 from .reductions import * # noqa (API import) 9 from .glyphs import Point # noqa (API import) File D:\a\holoviews\holoviews\.pixi\envs\test-312\Lib\site-packages\datashader\core.py:13 10 from packaging.version import Version 11 from xarray import DataArray, Dataset ---> 13 from .utils import Dispatcher, ngjit, calc_res, calc_bbox, orient_array, \ 14 dshape_from_xarray_dataset 15 from .utils import get_indices, dshape_from_pandas, dshape_from_dask 16 from .utils �[39

examples\user_guide\Linked_Brushing.ipynb::Cell 16 Notebook cell execution failed Cell 16: Cell execution caused an exception Input: colors = hv.Cycle('Category10').values area = autompg_ds.aggregate('yr', function=np.mean).to(hv.Area, 'yr', 'weight') bivariate = hv.Bivariate(autompg_ds, ['mpg', 'accel'], []).opts(show_legend=False) box_whisker = hv.BoxWhisker(autompg_ds, 'cyl', 'accel').sort() curve = autompg_ds.aggregate('yr', function=np.mean).to(hv.Curve, 'yr', 'mpg') spread = autompg_ds.aggregate('yr', function=np.mean, spreadfn=np.std).to(hv.Spread, 'yr', ['mpg', 'mpg_std']) distribution = hv.Distribution(autompg_ds, 'weight') img = hd.rasterize(hv.Points(autompg_ds, ['hp', 'displ']), dynamic=False, width=20, height=20) heatmap = hv.HeatMap(autompg_ds, ['yr', 'origin'], 'accel').aggregate(function=np.mean) hextiles = hv.HexTiles(autompg_ds, ['weight', 'displ'], []).opts(gridsize=20) hist = autompg_ds.hist('displ', adjoin=False, normed=False) scatter = hv.Scatter(autompg_ds, 'mpg', 'hp') violin = hv.Violin(autompg_ds, 'origin', 'mpg').sort() link_selections( area + bivariate + box_whisker + curve + distribution + heatmap + hextiles + hist + img + scatter + spread + violin ).opts( opts.Area(color=colors[0]), opts.Bivariate(cmap='Blues'), opts.BoxWhisker(box_color=colors[1]), opts.Curve(color=colors[2]), opts.Distribution(color=colors[3]), opts.HexTiles(cmap='Purples'), opts.HeatMap(cmap='Greens'), opts.Histogram(color=colors[4]), opts.Image(cmap='Reds'), opts.Scatter(color=colors[5]), opts.Spread(color=colors[6]), opts.Violin(violin_fill_color=colors[7]), ) Traceback: --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[1], line 9 7 spread = autompg_ds.aggregate('yr', function=np.mean, spreadfn=np.std).to(hv.Spread, 'yr', ['mpg', 'mpg_std']) 8 distribution = hv.Distribution(autompg_ds, 'weight') ----> 9 img = hd.rasterize(hv.Points(autompg_ds, ['hp', 'displ']), dynamic=False, width=20, height=20) 10 heatmap = hv.HeatMap(autompg_ds, ['yr', 'origin'], 'accel').aggregate(function=np.mean) 11 hextiles = hv.HexTiles(autompg_ds, ['weight', 'displ'], []).opts(gridsize=20) NameError: name 'hd' is not defined

examples\gallery\demos\bokeh\multichannel_timeseries_viewer.ipynb::Cell 0 Notebook cell execution failed Cell 0: Cell execution caused an exception Input: import pandas as pd import numpy as np import pandas as pd import holoviews as hv from holoviews.operation.normalization import subcoordinate_group_ranges from holoviews.operation.datashader import rasterize from holoviews.plotting.links import RangeToolLink import colorcet as cc from scipy.stats import zscore hv.extension('bokeh') Traceback: --------------------------------------------------------------------------- NotImplementedError Traceback (most recent call last) Cell In[1], line 6 4 import holoviews as hv 5 from holoviews.operation.normalization import subcoordinate_group_ranges ----> 6 from holoviews.operation.datashader import rasterize 7 from holoviews.plotting.links import RangeToolLink 8 import colorcet as cc File D:\a\holoviews\holoviews\holoviews\operation\datashader.py:5 2 from collections.abc import Callable, Iterable 3 from functools import partial ----> 5 import datashader as ds 6 import datashader.reductions as rd 7 import datashader.transfer_functions as tf File D:\a\holoviews\holoviews\.pixi\envs\test-312\Lib\site-packages\datashader\__init__.py:7 3 from packaging.version import Version 5 from .__version import __version__ # noqa: F401 ----> 7 from .core import Canvas # noqa (API import) 8 from .reductions import * # noqa (API import) 9 from .glyphs import Point �

examples\gallery\demos\bokeh\multichannel_timeseries_viewer.ipynb::Cell 2 Notebook cell execution failed Cell 2: Cell execution caused an exception Input: # Create a Curve per data series def df_to_curves(df, kdim, vdim, color='black', group='EEG', ): curves = [] for i, (channel, channel_data) in enumerate(df.items()): ds = hv.Dataset((channel_data.index, channel_data), [kdim, vdim]) curve = hv.Curve(ds, kdim, vdim, group=group, label=str(channel)) curve.opts( subcoordinate_y=True, color=color if isinstance(color, str) else color[i], line_width=1, hover_tooltips=hover_tooltips, tools=['xwheel_zoom'], line_alpha=.8, ) curves.append(curve) return curves hover_tooltips = [("Group", "$group"), ("Channel", "$label"), ("Time"), ("Value")] vdim_EEG = hv.Dimension("Value", unit="µV") vdim_POS = hv.Dimension("Value", unit="cm") time_dim = hv.Dimension("Time", unit="s") eeg_curves = df_to_curves(eeg_df, time_dim, vdim_EEG, color='black', group='EEG') pos_curves = df_to_curves(pos_df, time_dim, vdim_POS, color=cc.glasbey_cool, group='POS') # Combine EEG and POS curves into an Overlay eeg_curves_overlay = hv.Overlay(eeg_curves, "Channel") pos_curves_overlay = hv.Overlay(pos_curves, "Channel") curves_overlay = (eeg_curves_overlay * pos_curves_overlay).opts( xlabel=time_dim.pprint_label, ylabel="Channel", show_legend=False, aspect=3, responsive=True, ) curves_overlay Traceback: --------------------------------------------------------------------------- ValueError Traceback (most recent call last) Cell In[1], line 20 17 vdim_POS = hv.Dimension("Value", unit="cm") 18 time_dim = hv.Dimension("Time", unit="s") ---> 20 eeg_curves = df_to_curves(eeg_df, time_dim, vdim_EEG, color='black', group='EEG') 21 pos_curves = df_to_curves(pos_df, time_dim, vdim_POS, color=cc.glasbey_cool, group='POS') 23 # Combine EEG and POS curves into an Overlay Cell In[1], line 7, in df_to_curves(df, kdim, vdim, color, group) 5 ds = hv.Dataset((channel_data.index, channel_data), [kdim, vdim]) 6 curve = hv.Curve(ds, kdim, vdim, group=group, label=str(channel)) ----> 7 curve.opts( 8 subcoordinate_y=True, color=color if isinstance(color, str) else color[i], line_width=1, 9 hover_tooltips=hover_tooltips, tools=�

examples\gallery\demos\bokeh\multichannel_timeseries_viewer.ipynb::Cell 3 Notebook cell execution failed Cell 3: Cell execution caused an exception Input: # Apply group-wise normalization normalized_overlay = subcoordinate_group_ranges(curves_overlay) normalized_overlay Traceback: --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[1], line 2 1 # Apply group-wise normalization ----> 2 normalized_overlay = subcoordinate_group_ranges(curves_overlay) 3 normalized_overlay NameError: name 'curves_overlay' is not defined

examples\gallery\demos\bokeh\multichannel_timeseries_viewer.ipynb::Cell 4 Notebook cell execution failed Cell 4: Cell execution caused an exception Input: y_positions = range(N_CHANNELS_EEG + N_CHANNELS_POS) # Reindex the lower frequency DataFrame to match the higher frequency index pos_df_interp = pos_df.reindex(eeg_df.index).interpolate(method='index') # concatenate the EEG and interpolated POS data and z-score the full data array z_data = zscore(np.concatenate((eeg_df.values, pos_df_interp.values), axis=1), axis=0).T minimap = rasterize(hv.Image((time_eeg, y_positions , z_data), [time_dim, "Channel"], "Value")) minimap = minimap.opts( cmap="RdBu_r", xlabel='', alpha=.7, yticks=[(y_positions[0], f'EEG {eeg_channels[0]}'), (y_positions[-1], f'POS {pos_channels[-1]}')], height=120, responsive=True, toolbar='disable', cnorm='eq_hist' ) minimap Traceback: --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[1], line 7 4 pos_df_interp = pos_df.reindex(eeg_df.index).interpolate(method='index') 6 # concatenate the EEG and interpolated POS data and z-score the full data array ----> 7 z_data = zscore(np.concatenate((eeg_df.values, pos_df_interp.values), axis=1), axis=0).T 9 minimap = rasterize(hv.Image((time_eeg, y_positions , z_data), [time_dim, "Channel"], "Value")) 10 minimap = minimap.opts( 11 cmap="RdBu_r", xlabel='', alpha=.7, 12 yticks=[(y_positions[0], f'EEG {eeg_channels[0]}'), (y_positions[-1], f'POS {pos_channels[-1]}')], 13 height=120, responsive=True, toolbar='disable', cnorm='eq_hist' 14 ) NameError: name 'zscore' is not defined

examples\gallery\demos\bokeh\multichannel_timeseries_viewer.ipynb::Cell 5 Notebook cell execution failed Cell 5: Cell execution caused an exception Input: RangeToolLink( minimap, normalized_overlay, axes=["x", "y"], boundsx=(.5, 3), boundsy=(1.5, 12.5), intervalsx=(None, 3), ) dashboard = (normalized_overlay + minimap).cols(1) dashboard Traceback: --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[1], line 1 ----> 1 RangeToolLink( 2 minimap, normalized_overlay, axes=["x", "y"], 3 boundsx=(.5, 3), boundsy=(1.5, 12.5), 4 intervalsx=(None, 3), 5 ) 7 dashboard = (normalized_overlay + minimap).cols(1) 8 dashboard NameError: name 'RangeToolLink' is not defined

Process completed with exit code 1.

Canceling since a higher priority waiting request for 'tests-6494' exists

The operation was canceled.

Process completed with exit code 1.

ubuntu-latest pipelines will use ubuntu-24.04 soon. For more details, see https://github.com/actions/runner-images/issues/10636

ubuntu-latest pipelines will use ubuntu-24.04 soon. For more details, see https://github.com/actions/runner-images/issues/10636

ubuntu-latest pipelines will use ubuntu-24.04 soon. For more details, see https://github.com/actions/runner-images/issues/10636

ubuntu-latest pipelines will use ubuntu-24.04 soon. For more details, see https://github.com/actions/runner-images/issues/10636

ubuntu-latest pipelines will use ubuntu-24.04 soon. For more details, see https://github.com/actions/runner-images/issues/10636

ubuntu-latest pipelines will use ubuntu-24.04 soon. For more details, see https://github.com/actions/runner-images/issues/10636

ubuntu-latest pipelines will use ubuntu-24.04 soon. For more details, see https://github.com/actions/runner-images/issues/10636