On May 20, 2019, at 2:27 AM, [email protected] wrote:
Oh, I see.
Even so, If I wanted, for example, not to update anything from the plot, but only to launch some javascript with CustomJS() comand, could it be possible to do it without reuploading the whole plot?
See atached example:
import numpy as np
import pandas as pd
from bokeh.plotting import figure, show, reset_output
from bokeh.models import ColumnDataSource, LinearColorMapper, Range1d, CustomJS
from bokeh.transform import transform
size = 500
#Creating random data to fill heatmap
df = pd.DataFrame(np.random.randint(0,100,size=((size**2), 4)), columns=list('ABCD'))
df['Y'] = list(range(1,size+1))*size
df['X'] = list(np.repeat(np.array(list(range(1,size+1))), size, axis=0))
# Mapper
colors = ['#FF0000','#FF0800','#FF1000','#FF1800','#FF2000','#FF2800','#FF3000','#FF3800','#FF4000','#FF4800','#FF5000','#FF5900','#FF6100','#FF6900','#FF7100','#FF7900','#FF8100','#FF8900','#FF9100','#FF9900','#FFA100','#FFAA00','#FFB200','#FFBA00','#FFC200','#FFCA00','#FFD200','#FFDA00','#FFE200','#FFEA00','#FFF200','#FFFA00','#FAFF00','#F2FF00','#EAFF00','#E2FF00','#DAFF00','#D2FF00','#CAFF00','#C2FF00','#BAFF00','#B2FF00','#AAFF00','#A1FF00','#99FF00','#91FF00','#89FF00','#81FF00','#79FF00','#71FF00','#69FF00','#61FF00','#59FF00','#50FF00','#48FF00','#40FF00','#38FF00','#30FF00','#28FF00','#20FF00','#18FF00','#10FF00','#08FF00','#00FF00']
colors.reverse()
mapper = LinearColorMapper(palette=colors, low=0, high=100)
p = figure(
width = 10000,
height = 10000,
tools=["hover","tap","save","reset","wheel_zoom"],
x_axis_location="above",
active_drag=None,
toolbar_location="right",
toolbar_sticky = False,
)
# Create rectangle for heatmap
mysource = ColumnDataSource(df)
p.rect(
y="Y",
x="X",
width=1,
height=1,
source=mysource,
line_color="white",
fill_color=transform("C", mapper),
fill_alpha=1,
line_alpha=1,
)
mysource.callback = CustomJS(code = """window.alert('Hello world')""")
show(p)
reset_output()
El viernes, 17 de mayo de 2019, 15:57:19 (UTC+2), Bryan Van de Ven escribió:
Hi,
Yes, Bokeh is a bitmapped canvas-based rendering library, so it is absolutely the case the the entire canvas has to be re-rendered to update any part of it (e.g. to highlight one glyph)
Thanks.
Bryan
> On May 17, 2019, at 2:30 AM, alam...@gmail.com wrote:
>
> The previous example was perhaps kind of exaggerated. My largest plot is 2564x16300. That was the limit for my browser apparently: wider plots did not render. This larger plot has about 158k points, which is way less than the example I have published.
>
> The delay thing happens nevertheless in all plots, but is more exaggerated in bigger ones while imperceptible in smaller ones. It seems like the whole plot has to render again every time a point is clicked. In any case, thanks for your help.
>
> El jueves, 16 de mayo de 2019, 17:27:23 (UTC+2), Bryan Van de Ven escribió:
> Hi,
>
> I'm not sure I understand, is your real plot actually 10000x10000? That is *far* beyond standard use cases. I am surprised that even renders at all on most/any browsers. It won't come up at all for me on Safari, e.g. If it works at all I would not be surprised at things being slow in various ways.
>
> 250k points is also on the edge for standard Bokeh. You might try enabling webgl to improve rendering time, but please be advised there is not currently an active maintainer for Bokeh's webgl support, so your mileage may vary. Also it's entirely possible that the slowness is simply in the spatial indexing/hit testing and that Bokeh is just not a good tool for this situation.
>
> Thanks,
>
> Bryan
>
> > On May 16, 2019, at 5:42 AM, alam...@gmail.com wrote:
> >
> > Hi Bryan,
> >
> > Thanks for your quick answer. It is true, indeed, that plot performance is significanctly better when rendered with bokeh 1.1.0. The issue persists, nevertheless. To make it more visible, I have attached a script to generate a huge rect() plot, as big as the ones I'm using on my web.
> >
> > The problem I reffer to is the sligth dealy and plot-freeze when one of the rectangles is clicked. Is there any way to avoid it?
> >
> > Find attached the code to generate the aforementioned plot
> > import numpy as np
> > import pandas as pd
> > from bokeh.plotting import figure, show, reset_output
> > from bokeh.models import ColumnDataSource, LinearColorMapper, Range1d
> > from bokeh.transform import transform
> >
> > size = 500
> >
> > #Creating random data to fill heatmap
> > df = pd.DataFrame(np.random.randint(0,100,size=((size**2), 4)), columns=list('ABCD'))
> > df['Y'] = list(range(1,size+1))*size
> > df['X'] = list(np.repeat(np.array(list(range(1,size+1))), size, axis=0))
> > print(df)
> > # Mapper
> > colors = ['#FF0000','#FF0800','#FF1000','#FF1800','#FF2000','#FF2800','#FF3000','#FF3800','#FF4000','#FF4800','#FF5000','#FF5900','#FF6100','#FF6900','#FF7100','#FF7900','#FF8100','#FF8900','#FF9100','#FF9900','#FFA100','#FFAA00','#FFB200','#FFBA00','#FFC200','#FFCA00','#FFD200','#FFDA00','#FFE200','#FFEA00','#FFF200','#FFFA00','#FAFF00','#F2FF00','#EAFF00','#E2FF00','#DAFF00','#D2FF00','#CAFF00','#C2FF00','#BAFF00','#B2FF00','#AAFF00','#A1FF00','#99FF00','#91FF00','#89FF00','#81FF00','#79FF00','#71FF00','#69FF00','#61FF00','#59FF00','#50FF00','#48FF00','#40FF00','#38FF00','#30FF00','#28FF00','#20FF00','#18FF00','#10FF00','#08FF00','#00FF00']
> > colors.reverse()
> > mapper = LinearColorMapper(palette=colors, low=0, high=100)
> >
> > p = figure(
> > width = 10000,
> > height = 10000,
> > tools=["hover","tap","save","reset","wheel_zoom"],
> > x_axis_location="above",
> > active_drag=None,
> > toolbar_location="right",
> > toolbar_sticky = False,
> > )
> >
> > # Create rectangle for heatmap
> > mysource = ColumnDataSource(df)
> > p.rect(
> > y="Y",
> > x="X",
> > width=1,
> > height=1,
> > source=mysource,
> > line_color="white",
> > fill_color=transform("C", mapper),
> >
> > # set visual properties for selected glyphs
> > selection_line_color="black",
> > selection_fill_color=transform("C", mapper),
> > # set visual properties for non-selected glyphs
> > nonselection_fill_color=transform("C", mapper),
> > nonselection_fill_alpha=1,
> > nonselection_line_alpha=1,
> > nonselection_line_color="white"
> > )
> > show(p)
> > reset_output()
> >
> >
> >
> >
> > El martes, 14 de mayo de 2019, 17:22:09 (UTC+2), Bryan Van de Ven escribió:
> > I can't seem to reproduce any issue with Bokeh 1.1.0 so the first best thing to try is updating your Bokeh version from 0.13.
> >
> > Thanks,
> >
> > Bryan
> >
> > > On May 14, 2019, at 6:30 AM, daran...@gmail.com <[email protected]> wrote:
> > >
> > > I have created a huge heatmap-like plot using the rect() glyph. For this plot, I intend to perform some actions when one of the rectangle elements is clicked. Unfortunately, when clicked, the whole plot freezes for a couple of seconds before performing the desired actions. It may seem meaningless, but on our web it causes the impression that it has freezed
> > >
> > > Is there some way to avoid this small delay in a rec() glyph?
> > >
> > > Please, find an example heatmap-like plot attached to this message, as well as the code used to compute it.
> > > import numpy as np
> > > import pandas as pd
> > > from bokeh.plotting import figure, show, reset_output
> > > from bokeh.models import ColumnDataSource, LinearColorMapper, Range1d
> > > from bokeh.transform import transform
> > >
> > > size = 150
> > >
> > > #Creating random data to fill heatmap
> > > df = pd.DataFrame(np.random.randint(0,size,size=((size**2), 4)), columns=list('ABCD'))
> > > df['Y'] = list(range(1,size+1))*size
> > > df['X'] = list(np.repeat(np.array(list(range(1,size+1))), size, axis=0))
> > >
> > > # Mapper
> > > colors = ['#FF0000','#FF0800','#FF1000','#FF1800','#FF2000','#FF2800','#FF3000','#FF3800','#FF4000','#FF4800','#FF5000','#FF5900','#FF6100','#FF6900','#FF7100','#FF7900','#FF8100','#FF8900','#FF9100','#FF9900','#FFA100','#FFAA00','#FFB200','#FFBA00','#FFC200','#FFCA00','#FFD200','#FFDA00','#FFE200','#FFEA00','#FFF200','#FFFA00','#FAFF00','#F2FF00','#EAFF00','#E2FF00','#DAFF00','#D2FF00','#CAFF00','#C2FF00','#BAFF00','#B2FF00','#AAFF00','#A1FF00','#99FF00','#91FF00','#89FF00','#81FF00','#79FF00','#71FF00','#69FF00','#61FF00','#59FF00','#50FF00','#48FF00','#40FF00','#38FF00','#30FF00','#28FF00','#20FF00','#18FF00','#10FF00','#08FF00','#00FF00']
> > > colors.reverse()
> > > mapper = LinearColorMapper(palette=colors, low=0, high=100)
> > >
> > > p = figure(
> > > width = 1000,
> > > height = 1000,
> > > tools=["hover","tap","save","reset","wheel_zoom"],
> > > x_axis_location="above",
> > > active_drag=None,
> > > toolbar_location="right",
> > > toolbar_sticky = False,
> > > )
> > >
> > > # Create rectangle for heatmap
> > > mysource = ColumnDataSource(df)
> > > p.rect(
> > > y="Y",
> > > x="X",
> > > width=1,
> > > height=1,
> > > source=mysource,
> > > line_color="white",
> > > fill_color=transform("C", mapper),
> > >
> > > # set visual properties for selected glyphs
> > > selection_line_color="black",
> > > selection_fill_color=transform("C", mapper),
> > > # set visual properties for non-selected glyphs
> > > nonselection_fill_color=transform("C", mapper),
> > > nonselection_fill_alpha=1,
> > > nonselection_line_alpha=1,
> > > nonselection_line_color="white"
> > > )
> > > show(p)
> > > reset_output()
> > >
> > >
> > >
> > > --
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> > > <heatmap_plot.html>
> >
> >
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>
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