I am currently looking for some tools to plot Grotrian diagrams for a particular element given the energy level details.
I have procured the atomic data regarding the energy level changes but am unable to utilize it to plot the respective Grotrian diagrams.
Is there any way using matplotlib to achieve this?
Related
I have plotted a graph using matplotlib.pyplot. I need to integrate specific sections of this graph. All the tutorials I can find online are including drawing a graph from scratch, but what should I use if I already have a graph and just want to integrate a part of it?
Thank you!
I am not familiar enough with Vispy. I did adapt this example for my use case, but I don't know how to modify it further to include the missing features.
I am trying to plot in real-time N-channels of data at the same scale. Using pyqtgraph, the interface looks like this:
And with vispy:
My goal is to match both backends, step by step. The difference for now are:
The order in Vispy is reversed (plot at the top on Vispy is the plot at the bottom on pyqtgraph)
Lack channel names
Lack Y-axis label
Lack X-Axis and X-Axis label
Lack of headroom top/bottom
I do not know how to solve any of those, how to further improve this backend. Any tips, guidance towards the correct, best function to use for this would be very helpful.
I was looking into visual.text, but the positioning seemed difficult. I did not know how to match the label in front of one of the plot.
This figure seems to be generated using python seaborn. But how exactly is each box customized with different shape (star or dot) and background color (size)?
Thanks!
I believe the graph in question was created in the R language 'ggplot2'.
stackoverflow,Correlation Heatmaps in R
The Python seaborn provides the following customization examples.Better Heatmaps and Correlation Matrix Plots in Python
The process I found this answer is to search for the posted image in Google (by right-clicking on it) I'm checking out each of these sites, and I encourage you to take a look at them as well. If you've already searched and posted on our site, you're good to go.
Is there any way in Python to modify the source data by moving data points in the chart?
This is intended to work in streamlit: I'd like to make it convenient for users to edit multiple parameters of the same kind visually changing the curve which represents series of parameters and their corresponding value. As far as I know, streamlit currently supports Matplotlib, Plotly, Altair, Bokeh, Vega Lite, Deck.GL, dagre-d3 charts, but not sure whether any of those libraries provide this functionality.
I would like to use pyplot.contour feature in bokeh. Is there any way I can use it?? I know pyplot.pcolormesh and bokeh.plotting.image. Can I use conotur plot with it?
pyplot.contour is part of Matplotlib, not Bokeh. As of Bokeh 2.3.0 there is no built-in contouring function or capability. Recently a MultiPolygons glyph that can support "polygons with holes" was added. This is a first necessary step to being able to have real contour plots in Bokeh. A next step would be for someone to write a set of functions that can accept array inputs and generate the multi-polygon data necessary to drive Bokeh graphics, but this has not been done by anyone yet.
If image contour plots (similar to pcolormesh) or line (unfilled) contours suit your needs, that you can consider using Holoviews, which can generate Bokeh contour plots for those kinds of cases:
http://holoviews.org/reference/elements/bokeh/Contours.html