Within an angular 9 app. I'm using the ag-grid and I decided to update it from 21.2.2 to 24.0.0 version.
What I realized though is that it stopped render the custom header components properly.
For example I'm attaching two images that show how it looks like before and after.
Before:
After:
As you can see, after update the height of the header doesn't seem to follow the height of the custom components and as a result the plots are getting cropped.
Any ideas on what could cause this issue or what I can look for would be very helpful.
This functionality I need in server side(nodejs)
I have installed canvas 2.2.0 version and in this I m unable to use loadFromJSON function.
But when I am using fabric and its canvas then this working fine.
I have changed from Fabric canvas to canvas because unable to change/set custom font in that
With the canvas 2.2.0 version, I am able to change or set custom fonts. But now I am anable to convert json data to base64image.
Any help would be appreciated.
Thanks in advance
I've a JSON object that defines an image on the canvas like so:
The JSON was created from Fabricjs version 1.7.17 and I'm loading that JSON into a canvas made from Fabricjs versions 2.3.6 & 2.4.1 and this is what the image looks like:
The canvas sizes are the same and the options for the canvas are the same. The JSON loads just fine in the 1.7.17 version. All the other objects from the JSON data load fine, the image box is the right width/height and placement (left & top)...it's just the image isn't scaled to fit.
I've tried setting the scaleX/Y, resize filters to no avail - anyone tackle this issue already?
Fabric 2.0 changed the way that height/width attributes are handled for images in order to support cropping. You'll find an explanation and example code for dealing with this here:
http://fabricjs.com/v2-breaking-changes#image
I recently upgraded bokeh from 0.12.4 to 0.12.10, primarily to enable Plot.output.backend = "svg" for the SaveTool. This feature works pretty well, but I've been experiencing other plotting issues when it is enabled.
I have a layout based plot composed of 2 subplots and a slider panel, but the issue seems to be plot- and glyph-independent. For example, the first plot in the layout is based on:
p1=figure(width=1500, x_range=get_xrange(rawdat), tools="box_zoom,tap,xwheel_zoom,reset,save", y_range=get_yrange(rawdat))
source = ColumnDataSource(data=dict(ps=rawdat.ps, logsp=-log10(rawdat.p_score), radii=rawdat.radii, alpha=rawdat.alpha, color=rawdat.color, mafcolor=rawdat.mafcolor, weightcolor=rawdat.weightcolor, outcol=rawdat.outcolor, outalpha=rawdat.outalpha, alpha_prevsig=rawdat.alpha_prevsig, snpid=rawdat.rs, rs=rawdat.ensembl_rs, maf=rawdat.maf, csq=rawdat.ensembl_consequence))
p1.circle(x='ps', y='logsp', radius='radii', fill_alpha='alpha', fill_color='color', line_color='outcol', line_alpha='outalpha', line_width=6, radius_units='screen', source=source)
When Plot.output.backend = "svg" is enabled, glyphs overflow outside of the plotting region (especially when zooming), so much so that my circles collide with the bokeh toolbar, as below:
This behaviour happens no matter what the glyphs are (on plot 2, segments and rectangles do the same). When the backend is set to the default, the plot does not overflow. This happens on Opera, Vivaldi, Safari and Firefox.
I'd like to see if other people have experienced and/or solved this before I raise an issue on their github page.
I'm looking at the gorgeous and powerful Plotly Python API with the goal of generating a static html dashboard.
This raises two questions:
For generating html, I see the following example. It appears the charts are embedded via a URL. Does this URL embedding implementation still apply since plotly has gone open source? Are there now other methods for sending plotly plots to static html?
How does one control the layout of the plots/dashboard elements? In Bokeh, for example we could do something like:
bar = Bar(<define bar plot>)
line = Line(<define line plot>)
donut = Donut(<define donut chart>)
bar_line_panel = hplot(bar, line)
final_layout = vplot(bar_line_panel, donut)
output_file('foo.html')
show(final_layout)
The rendered html file would contain the line and bar plots next to each other above the donut chart. Is there similar functionality in plotly, or are templates and html/css wrangling required to specify layout for plot elements like in this example?
Thank you for your time, very much looking forward to creating some interactive visualizations in Plotly!